From 08b2d28d04b823846816fa307e4f17f76771c36a Mon Sep 17 00:00:00 2001 From: andy Date: Sat, 10 Apr 2021 16:56:01 +0100 Subject: [PATCH] added 256 node FCs, confusion matrix notebook --- .../architecture.ipynb | 40 +- .../fc/1-layer/256/caffe_output.log | 4438 +++++++++++++++ .../fc/1-layer/256/conf.csv | 197 + .../fc/1-layer/256/deploy.prototxt | 301 + .../fc/1-layer/256/large.png | Bin 0 -> 283915 bytes .../fc/1-layer/256/original.prototxt | 348 ++ .../fc/1-layer/256/pred.csv | 1619 ++++++ .../fc/1-layer/256/small.png | Bin 0 -> 233504 bytes .../fc/1-layer/256/solver.prototxt | 14 + .../fc/1-layer/256/train_val.prototxt | 342 ++ .../fc/2-layers/256/caffe_output.log | 4566 ++++++++++++++++ .../fc/2-layers/256/conf.csv | 197 + .../fc/2-layers/256/deploy.prototxt | 341 ++ .../fc/2-layers/256/large.png | Bin 0 -> 279478 bytes .../fc/2-layers/256/original.prototxt | 388 ++ .../fc/2-layers/256/pred.csv | 1619 ++++++ .../fc/2-layers/256/small.png | Bin 0 -> 226158 bytes .../fc/2-layers/256/solver.prototxt | 14 + .../fc/2-layers/256/train_val.prototxt | 382 ++ .../fc/3-layers/256/caffe_output.log | 4694 ++++++++++++++++ .../fc/3-layers/256/conf.csv | 197 + .../fc/3-layers/256/deploy.prototxt | 381 ++ .../fc/3-layers/256/large.png | Bin 0 -> 127757 bytes .../fc/3-layers/256/original.prototxt | 428 ++ .../fc/3-layers/256/pred.csv | 1619 ++++++ .../fc/3-layers/256/small.png | Bin 0 -> 133947 bytes .../fc/3-layers/256/solver.prototxt | 14 + .../fc/3-layers/256/train_val.prototxt | 422 ++ .../fc/4-layers/256/caffe_output.log | 4822 +++++++++++++++++ .../fc/4-layers/256/conf.csv | 197 + .../fc/4-layers/256/deploy.prototxt | 421 ++ .../fc/4-layers/256/large.png | Bin 0 -> 127254 bytes .../fc/4-layers/256/original.prototxt | 468 ++ .../fc/4-layers/256/pred.csv | 1619 ++++++ .../fc/4-layers/256/small.png | Bin 0 -> 134855 bytes .../fc/4-layers/256/solver.prototxt | 14 + .../fc/4-layers/256/train_val.prototxt | 462 ++ cars/confusions.ipynb | 682 +++ pyproject.toml | 1 + report/report.lyx | 13 - 40 files changed, 31224 insertions(+), 36 deletions(-) create mode 100644 cars/architecture-investigations/fc/1-layer/256/caffe_output.log create mode 100644 cars/architecture-investigations/fc/1-layer/256/conf.csv create mode 100644 cars/architecture-investigations/fc/1-layer/256/deploy.prototxt create mode 100644 cars/architecture-investigations/fc/1-layer/256/large.png create mode 100644 cars/architecture-investigations/fc/1-layer/256/original.prototxt create mode 100644 cars/architecture-investigations/fc/1-layer/256/pred.csv create mode 100644 cars/architecture-investigations/fc/1-layer/256/small.png create mode 100644 cars/architecture-investigations/fc/1-layer/256/solver.prototxt create mode 100644 cars/architecture-investigations/fc/1-layer/256/train_val.prototxt create mode 100644 cars/architecture-investigations/fc/2-layers/256/caffe_output.log create mode 100644 cars/architecture-investigations/fc/2-layers/256/conf.csv create mode 100644 cars/architecture-investigations/fc/2-layers/256/deploy.prototxt create mode 100644 cars/architecture-investigations/fc/2-layers/256/large.png create mode 100644 cars/architecture-investigations/fc/2-layers/256/original.prototxt create mode 100644 cars/architecture-investigations/fc/2-layers/256/pred.csv create mode 100644 cars/architecture-investigations/fc/2-layers/256/small.png create mode 100644 cars/architecture-investigations/fc/2-layers/256/solver.prototxt create mode 100644 cars/architecture-investigations/fc/2-layers/256/train_val.prototxt create mode 100644 cars/architecture-investigations/fc/3-layers/256/caffe_output.log create mode 100644 cars/architecture-investigations/fc/3-layers/256/conf.csv create mode 100644 cars/architecture-investigations/fc/3-layers/256/deploy.prototxt create mode 100644 cars/architecture-investigations/fc/3-layers/256/large.png create mode 100644 cars/architecture-investigations/fc/3-layers/256/original.prototxt create mode 100644 cars/architecture-investigations/fc/3-layers/256/pred.csv create mode 100644 cars/architecture-investigations/fc/3-layers/256/small.png create mode 100644 cars/architecture-investigations/fc/3-layers/256/solver.prototxt create mode 100644 cars/architecture-investigations/fc/3-layers/256/train_val.prototxt create mode 100644 cars/architecture-investigations/fc/4-layers/256/caffe_output.log create mode 100644 cars/architecture-investigations/fc/4-layers/256/conf.csv create mode 100644 cars/architecture-investigations/fc/4-layers/256/deploy.prototxt create mode 100644 cars/architecture-investigations/fc/4-layers/256/large.png create mode 100644 cars/architecture-investigations/fc/4-layers/256/original.prototxt create mode 100644 cars/architecture-investigations/fc/4-layers/256/pred.csv create mode 100644 cars/architecture-investigations/fc/4-layers/256/small.png create mode 100644 cars/architecture-investigations/fc/4-layers/256/solver.prototxt create mode 100644 cars/architecture-investigations/fc/4-layers/256/train_val.prototxt create mode 100644 cars/confusions.ipynb diff --git a/cars/architecture-investigations/architecture.ipynb b/cars/architecture-investigations/architecture.ipynb index e076ba2..b73bf14 100644 --- a/cars/architecture-investigations/architecture.ipynb +++ b/cars/architecture-investigations/architecture.ipynb @@ -3,7 +3,7 @@ { "cell_type": "code", "execution_count": 1, - "id": "e156c77a", + "id": "b536f89d", "metadata": {}, "outputs": [], "source": [ @@ -14,7 +14,7 @@ }, { "cell_type": "markdown", - "id": "0456f690", + "id": "d63144c7", "metadata": {}, "source": [ "# Dense Layers\n", @@ -35,29 +35,33 @@ { "cell_type": "code", "execution_count": 2, - "id": "da786662", + "id": "d5f166e9", "metadata": {}, "outputs": [], "source": [ "fc_results = np.array([\n", + " [1, 256, 52.44, 79.86, 2.49, 57.66],\n", " [1, 512, 49.29, 73.93, 2.95, 53.25],\n", " [1, 1024, 40.7, 68.38, 3.66, 45.22],\n", " [1, 2048, 32.12, 58.93, 4.66, 35.72],\n", " [1, 4096, 24.03, 46.76, 5.61, 27.94],\n", " [1, 8192, 19.70, 41.01, 6.42, 23.96],\n", " \n", + " [2, 256, 54.48, 81.22, 1.86, 57.11],\n", " [2, 512, 56.64, 82.46, 1.94, 60.23],\n", " [2, 1024, 56.39, 81.53, 2.08, 60.91],\n", " [2, 2048, 51.39, 79.00, 2.38, 56.74],\n", " [2, 4096, 44.41, 71.83, 3.04, 47.61], # DEFAULT ALEXNET\n", " [2, 8192, 37.74, 64.36, 3.60, 42.40],\n", " \n", + " [3, 256, 0.8, 2.1, 5.29, 0.55],\n", " [3, 512, 30.7, 65.16, 2.57, 30.82],\n", " [3, 1024, 48.36, 76.65, 2.30, 49.88],\n", " [3, 2048, 54.11, 80.48, 2.38, 58.21],\n", " [3, 4096, 54.48, 82.09, 2.39, 57.17],\n", " [3, 8192, 50.71, 78.57, 2.55, 55.88],\n", " \n", + " [4, 256, 0.8, 2.29, 5.29, 0.55],\n", " [4, 512, 0.8, 2.1, 5.29, 0.55],\n", " [4, 1024, 0.8, 2.1, 5.29, 0.55],\n", " [4, 2048, 25.45, 60.9, 2.84, 28.55],\n", @@ -68,22 +72,22 @@ "fc_0_results = [0, 196, 28.91, 54.05, 6.52, 33.21]\n", "\n", "layers = [1, 2, 3, 4]\n", - "nodes = [512, 1024, 2048, 4096, 8192]\n", + "nodes = [256, 512, 1024, 2048, 4096, 8192]\n", "\n", - "fc_matrix = np.zeros((4, 5))\n", + "fc_matrix = np.zeros((len(layers), len(nodes)))\n", "for i in fc_results:\n", " fc_matrix[layers.index(i[0]), nodes.index(i[1])] = i[2]" ] }, { "cell_type": "code", - "execution_count": 3, - "id": "c0064d43", + "execution_count": 9, + "id": "7b473793", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -108,7 +112,7 @@ "ax.set_ylabel('Nodes Per Layer')\n", "ax.set_zlabel('Top-1 % Test Accuracy')\n", "\n", - "ax.view_init(50, -150)\n", + "ax.view_init(60, -130)\n", "fig.colorbar(surf, shrink=0.3, aspect=6)\n", "\n", "plt.tight_layout()\n", @@ -117,13 +121,13 @@ }, { "cell_type": "code", - "execution_count": 6, - "id": "72a7412c", + "execution_count": 11, + "id": "6007d5b8", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -145,9 +149,7 @@ " textcoords=\"offset points\",\n", " xytext=(40, 10),\n", " ha='center',\n", - " arrowprops={\n", - " 'arrowstyle': 'simple'\n", - " }\n", + " arrowprops={'arrowstyle': 'simple'}\n", " )\n", " \n", "plt.title('Accuracy for Varied Dense Layers')\n", @@ -158,14 +160,6 @@ "plt.legend()\n", "plt.show()" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6e359c36", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/cars/architecture-investigations/fc/1-layer/256/caffe_output.log b/cars/architecture-investigations/fc/1-layer/256/caffe_output.log new file mode 100644 index 0000000..d9b4ad7 --- /dev/null +++ b/cars/architecture-investigations/fc/1-layer/256/caffe_output.log @@ -0,0 +1,4438 @@ +I0410 13:28:45.599097 18353 upgrade_proto.cpp:1082] Attempting to upgrade input file specified using deprecated 'solver_type' field (enum)': /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210410-132843-8f34/solver.prototxt +I0410 13:28:45.599355 18353 upgrade_proto.cpp:1089] Successfully upgraded file specified using deprecated 'solver_type' field (enum) to 'type' field (string). +W0410 13:28:45.599366 18353 upgrade_proto.cpp:1091] Note that future Caffe releases will only support 'type' field (string) for a solver's type. +I0410 13:28:45.599481 18353 caffe.cpp:218] Using GPUs 0 +I0410 13:28:45.626740 18353 caffe.cpp:223] GPU 0: GeForce GTX 1080 Ti +I0410 13:28:45.921651 18353 solver.cpp:44] Initializing solver from parameters: +test_iter: 51 +test_interval: 102 +base_lr: 0.01 +display: 12 +max_iter: 10200 +lr_policy: "exp" +gamma: 0.99980193 +momentum: 0.9 +weight_decay: 0.0001 +snapshot: 102 +snapshot_prefix: "snapshot" +solver_mode: GPU +device_id: 0 +net: "train_val.prototxt" +train_state { +level: 0 +stage: "" +} +type: "SGD" +I0410 13:28:45.922817 18353 solver.cpp:87] Creating training net from net file: train_val.prototxt +I0410 13:28:45.923482 18353 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer val-data +I0410 13:28:45.923497 18353 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer accuracy +I0410 13:28:45.923630 18353 net.cpp:51] Initializing net from parameters: +state { +phase: TRAIN +level: 0 +stage: "" +} +layer { +name: "train-data" +type: "Data" +top: "data" +top: "label" +include { +phase: TRAIN +} +transform_param { +mirror: true +crop_size: 227 +mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" +} +data_param { +source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db" +batch_size: 128 +backend: LMDB +} +} +layer { +name: "conv1" +type: "Convolution" +bottom: "data" +top: "conv1" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 96 +kernel_size: 11 +stride: 4 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu1" +type: "ReLU" +bottom: "conv1" +top: "conv1" +} +layer { +name: "norm1" +type: "LRN" +bottom: "conv1" +top: "norm1" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool1" +type: "Pooling" +bottom: "norm1" +top: "pool1" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv2" +type: "Convolution" +bottom: "pool1" +top: "conv2" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 2 +kernel_size: 5 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu2" +type: "ReLU" +bottom: "conv2" +top: "conv2" +} +layer { +name: "norm2" +type: "LRN" +bottom: "conv2" +top: "norm2" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool2" +type: "Pooling" +bottom: "norm2" +top: "pool2" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv3" +type: "Convolution" +bottom: "pool2" +top: "conv3" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu3" +type: "ReLU" +bottom: "conv3" +top: "conv3" +} +layer { +name: "conv4" +type: "Convolution" +bottom: "conv3" +top: "conv4" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu4" +type: "ReLU" +bottom: "conv4" +top: "conv4" +} +layer { +name: "conv5" +type: "Convolution" +bottom: "conv4" +top: "conv5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu5" +type: "ReLU" +bottom: "conv5" +top: "conv5" +} +layer { +name: "pool5" +type: "Pooling" +bottom: "conv5" +top: "pool5" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "fc6" +type: "InnerProduct" +bottom: "pool5" +top: "fc6" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu6" +type: "ReLU" +bottom: "fc6" +top: "fc6" +} +layer { +name: "drop6" +type: "Dropout" +bottom: "fc6" +top: "fc6" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc8" +type: "InnerProduct" +bottom: "fc6" +top: "fc8" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 196 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "loss" +type: "SoftmaxWithLoss" +bottom: "fc8" +bottom: "label" +top: "loss" +} +I0410 13:28:45.923720 18353 layer_factory.hpp:77] Creating layer train-data +I0410 13:28:46.007031 18353 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db +I0410 13:28:46.007316 18353 net.cpp:84] Creating Layer train-data +I0410 13:28:46.007344 18353 net.cpp:380] train-data -> data +I0410 13:28:46.007385 18353 net.cpp:380] train-data -> label +I0410 13:28:46.007411 18353 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto +I0410 13:28:46.018450 18353 data_layer.cpp:45] output data size: 128,3,227,227 +I0410 13:28:46.212792 18353 net.cpp:122] Setting up train-data +I0410 13:28:46.212821 18353 net.cpp:129] Top shape: 128 3 227 227 (19787136) +I0410 13:28:46.212828 18353 net.cpp:129] Top shape: 128 (128) +I0410 13:28:46.212831 18353 net.cpp:137] Memory required for data: 79149056 +I0410 13:28:46.212844 18353 layer_factory.hpp:77] Creating layer conv1 +I0410 13:28:46.212869 18353 net.cpp:84] Creating Layer conv1 +I0410 13:28:46.212875 18353 net.cpp:406] conv1 <- data +I0410 13:28:46.212890 18353 net.cpp:380] conv1 -> conv1 +I0410 13:28:46.798507 18353 net.cpp:122] Setting up conv1 +I0410 13:28:46.798530 18353 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:28:46.798535 18353 net.cpp:137] Memory required for data: 227833856 +I0410 13:28:46.798557 18353 layer_factory.hpp:77] Creating layer relu1 +I0410 13:28:46.798568 18353 net.cpp:84] Creating Layer relu1 +I0410 13:28:46.798573 18353 net.cpp:406] relu1 <- conv1 +I0410 13:28:46.798581 18353 net.cpp:367] relu1 -> conv1 (in-place) +I0410 13:28:46.798899 18353 net.cpp:122] Setting up relu1 +I0410 13:28:46.798909 18353 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:28:46.798913 18353 net.cpp:137] Memory required for data: 376518656 +I0410 13:28:46.798918 18353 layer_factory.hpp:77] Creating layer norm1 +I0410 13:28:46.798928 18353 net.cpp:84] Creating Layer norm1 +I0410 13:28:46.798933 18353 net.cpp:406] norm1 <- conv1 +I0410 13:28:46.798938 18353 net.cpp:380] norm1 -> norm1 +I0410 13:28:46.799434 18353 net.cpp:122] Setting up norm1 +I0410 13:28:46.799445 18353 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:28:46.799449 18353 net.cpp:137] Memory required for data: 525203456 +I0410 13:28:46.799454 18353 layer_factory.hpp:77] Creating layer pool1 +I0410 13:28:46.799463 18353 net.cpp:84] Creating Layer pool1 +I0410 13:28:46.799468 18353 net.cpp:406] pool1 <- norm1 +I0410 13:28:46.799472 18353 net.cpp:380] pool1 -> pool1 +I0410 13:28:46.799538 18353 net.cpp:122] Setting up pool1 +I0410 13:28:46.799546 18353 net.cpp:129] Top shape: 128 96 27 27 (8957952) +I0410 13:28:46.799549 18353 net.cpp:137] Memory required for data: 561035264 +I0410 13:28:46.799553 18353 layer_factory.hpp:77] Creating layer conv2 +I0410 13:28:46.799566 18353 net.cpp:84] Creating Layer conv2 +I0410 13:28:46.799569 18353 net.cpp:406] conv2 <- pool1 +I0410 13:28:46.799576 18353 net.cpp:380] conv2 -> conv2 +I0410 13:28:46.807049 18353 net.cpp:122] Setting up conv2 +I0410 13:28:46.807062 18353 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:28:46.807066 18353 net.cpp:137] Memory required for data: 656586752 +I0410 13:28:46.807076 18353 layer_factory.hpp:77] Creating layer relu2 +I0410 13:28:46.807083 18353 net.cpp:84] Creating Layer relu2 +I0410 13:28:46.807087 18353 net.cpp:406] relu2 <- conv2 +I0410 13:28:46.807093 18353 net.cpp:367] relu2 -> conv2 (in-place) +I0410 13:28:46.807570 18353 net.cpp:122] Setting up relu2 +I0410 13:28:46.807580 18353 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:28:46.807585 18353 net.cpp:137] Memory required for data: 752138240 +I0410 13:28:46.807590 18353 layer_factory.hpp:77] Creating layer norm2 +I0410 13:28:46.807596 18353 net.cpp:84] Creating Layer norm2 +I0410 13:28:46.807600 18353 net.cpp:406] norm2 <- conv2 +I0410 13:28:46.807606 18353 net.cpp:380] norm2 -> norm2 +I0410 13:28:46.807969 18353 net.cpp:122] Setting up norm2 +I0410 13:28:46.807978 18353 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:28:46.807982 18353 net.cpp:137] Memory required for data: 847689728 +I0410 13:28:46.807986 18353 layer_factory.hpp:77] Creating layer pool2 +I0410 13:28:46.807996 18353 net.cpp:84] Creating Layer pool2 +I0410 13:28:46.808001 18353 net.cpp:406] pool2 <- norm2 +I0410 13:28:46.808007 18353 net.cpp:380] pool2 -> pool2 +I0410 13:28:46.808039 18353 net.cpp:122] Setting up pool2 +I0410 13:28:46.808046 18353 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:28:46.808049 18353 net.cpp:137] Memory required for data: 869840896 +I0410 13:28:46.808053 18353 layer_factory.hpp:77] Creating layer conv3 +I0410 13:28:46.808064 18353 net.cpp:84] Creating Layer conv3 +I0410 13:28:46.808068 18353 net.cpp:406] conv3 <- pool2 +I0410 13:28:46.808075 18353 net.cpp:380] conv3 -> conv3 +I0410 13:28:46.819180 18353 net.cpp:122] Setting up conv3 +I0410 13:28:46.819192 18353 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:28:46.819196 18353 net.cpp:137] Memory required for data: 903067648 +I0410 13:28:46.819207 18353 layer_factory.hpp:77] Creating layer relu3 +I0410 13:28:46.819214 18353 net.cpp:84] Creating Layer relu3 +I0410 13:28:46.819218 18353 net.cpp:406] relu3 <- conv3 +I0410 13:28:46.819226 18353 net.cpp:367] relu3 -> conv3 (in-place) +I0410 13:28:46.819773 18353 net.cpp:122] Setting up relu3 +I0410 13:28:46.819784 18353 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:28:46.819788 18353 net.cpp:137] Memory required for data: 936294400 +I0410 13:28:46.819792 18353 layer_factory.hpp:77] Creating layer conv4 +I0410 13:28:46.819803 18353 net.cpp:84] Creating Layer conv4 +I0410 13:28:46.819808 18353 net.cpp:406] conv4 <- conv3 +I0410 13:28:46.819815 18353 net.cpp:380] conv4 -> conv4 +I0410 13:28:46.831454 18353 net.cpp:122] Setting up conv4 +I0410 13:28:46.831467 18353 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:28:46.831471 18353 net.cpp:137] Memory required for data: 969521152 +I0410 13:28:46.831480 18353 layer_factory.hpp:77] Creating layer relu4 +I0410 13:28:46.831486 18353 net.cpp:84] Creating Layer relu4 +I0410 13:28:46.831490 18353 net.cpp:406] relu4 <- conv4 +I0410 13:28:46.831497 18353 net.cpp:367] relu4 -> conv4 (in-place) +I0410 13:28:46.831881 18353 net.cpp:122] Setting up relu4 +I0410 13:28:46.831892 18353 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:28:46.831897 18353 net.cpp:137] Memory required for data: 1002747904 +I0410 13:28:46.831900 18353 layer_factory.hpp:77] Creating layer conv5 +I0410 13:28:46.831910 18353 net.cpp:84] Creating Layer conv5 +I0410 13:28:46.831914 18353 net.cpp:406] conv5 <- conv4 +I0410 13:28:46.831943 18353 net.cpp:380] conv5 -> conv5 +I0410 13:28:46.841342 18353 net.cpp:122] Setting up conv5 +I0410 13:28:46.841356 18353 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:28:46.841361 18353 net.cpp:137] Memory required for data: 1024899072 +I0410 13:28:46.841372 18353 layer_factory.hpp:77] Creating layer relu5 +I0410 13:28:46.841378 18353 net.cpp:84] Creating Layer relu5 +I0410 13:28:46.841382 18353 net.cpp:406] relu5 <- conv5 +I0410 13:28:46.841389 18353 net.cpp:367] relu5 -> conv5 (in-place) +I0410 13:28:46.841940 18353 net.cpp:122] Setting up relu5 +I0410 13:28:46.841950 18353 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:28:46.841964 18353 net.cpp:137] Memory required for data: 1047050240 +I0410 13:28:46.841969 18353 layer_factory.hpp:77] Creating layer pool5 +I0410 13:28:46.841979 18353 net.cpp:84] Creating Layer pool5 +I0410 13:28:46.841982 18353 net.cpp:406] pool5 <- conv5 +I0410 13:28:46.841989 18353 net.cpp:380] pool5 -> pool5 +I0410 13:28:46.842033 18353 net.cpp:122] Setting up pool5 +I0410 13:28:46.842041 18353 net.cpp:129] Top shape: 128 256 6 6 (1179648) +I0410 13:28:46.842044 18353 net.cpp:137] Memory required for data: 1051768832 +I0410 13:28:46.842047 18353 layer_factory.hpp:77] Creating layer fc6 +I0410 13:28:46.842058 18353 net.cpp:84] Creating Layer fc6 +I0410 13:28:46.842062 18353 net.cpp:406] fc6 <- pool5 +I0410 13:28:46.842069 18353 net.cpp:380] fc6 -> fc6 +I0410 13:28:46.866420 18353 net.cpp:122] Setting up fc6 +I0410 13:28:46.866436 18353 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:28:46.866441 18353 net.cpp:137] Memory required for data: 1051899904 +I0410 13:28:46.866449 18353 layer_factory.hpp:77] Creating layer relu6 +I0410 13:28:46.866457 18353 net.cpp:84] Creating Layer relu6 +I0410 13:28:46.866462 18353 net.cpp:406] relu6 <- fc6 +I0410 13:28:46.866468 18353 net.cpp:367] relu6 -> fc6 (in-place) +I0410 13:28:46.867090 18353 net.cpp:122] Setting up relu6 +I0410 13:28:46.867100 18353 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:28:46.867105 18353 net.cpp:137] Memory required for data: 1052030976 +I0410 13:28:46.867108 18353 layer_factory.hpp:77] Creating layer drop6 +I0410 13:28:46.867115 18353 net.cpp:84] Creating Layer drop6 +I0410 13:28:46.867120 18353 net.cpp:406] drop6 <- fc6 +I0410 13:28:46.867127 18353 net.cpp:367] drop6 -> fc6 (in-place) +I0410 13:28:46.867157 18353 net.cpp:122] Setting up drop6 +I0410 13:28:46.867164 18353 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:28:46.867168 18353 net.cpp:137] Memory required for data: 1052162048 +I0410 13:28:46.867172 18353 layer_factory.hpp:77] Creating layer fc8 +I0410 13:28:46.867179 18353 net.cpp:84] Creating Layer fc8 +I0410 13:28:46.867183 18353 net.cpp:406] fc8 <- fc6 +I0410 13:28:46.867190 18353 net.cpp:380] fc8 -> fc8 +I0410 13:28:46.867763 18353 net.cpp:122] Setting up fc8 +I0410 13:28:46.867769 18353 net.cpp:129] Top shape: 128 196 (25088) +I0410 13:28:46.867772 18353 net.cpp:137] Memory required for data: 1052262400 +I0410 13:28:46.867779 18353 layer_factory.hpp:77] Creating layer loss +I0410 13:28:46.867787 18353 net.cpp:84] Creating Layer loss +I0410 13:28:46.867791 18353 net.cpp:406] loss <- fc8 +I0410 13:28:46.867795 18353 net.cpp:406] loss <- label +I0410 13:28:46.867802 18353 net.cpp:380] loss -> loss +I0410 13:28:46.867811 18353 layer_factory.hpp:77] Creating layer loss +I0410 13:28:46.868445 18353 net.cpp:122] Setting up loss +I0410 13:28:46.868455 18353 net.cpp:129] Top shape: (1) +I0410 13:28:46.868459 18353 net.cpp:132] with loss weight 1 +I0410 13:28:46.868479 18353 net.cpp:137] Memory required for data: 1052262404 +I0410 13:28:46.868484 18353 net.cpp:198] loss needs backward computation. +I0410 13:28:46.868490 18353 net.cpp:198] fc8 needs backward computation. +I0410 13:28:46.868494 18353 net.cpp:198] drop6 needs backward computation. +I0410 13:28:46.868499 18353 net.cpp:198] relu6 needs backward computation. +I0410 13:28:46.868501 18353 net.cpp:198] fc6 needs backward computation. +I0410 13:28:46.868505 18353 net.cpp:198] pool5 needs backward computation. +I0410 13:28:46.868510 18353 net.cpp:198] relu5 needs backward computation. +I0410 13:28:46.868532 18353 net.cpp:198] conv5 needs backward computation. +I0410 13:28:46.868536 18353 net.cpp:198] relu4 needs backward computation. +I0410 13:28:46.868541 18353 net.cpp:198] conv4 needs backward computation. +I0410 13:28:46.868543 18353 net.cpp:198] relu3 needs backward computation. +I0410 13:28:46.868547 18353 net.cpp:198] conv3 needs backward computation. +I0410 13:28:46.868551 18353 net.cpp:198] pool2 needs backward computation. +I0410 13:28:46.868556 18353 net.cpp:198] norm2 needs backward computation. +I0410 13:28:46.868559 18353 net.cpp:198] relu2 needs backward computation. +I0410 13:28:46.868563 18353 net.cpp:198] conv2 needs backward computation. +I0410 13:28:46.868567 18353 net.cpp:198] pool1 needs backward computation. +I0410 13:28:46.868571 18353 net.cpp:198] norm1 needs backward computation. +I0410 13:28:46.868577 18353 net.cpp:198] relu1 needs backward computation. +I0410 13:28:46.868580 18353 net.cpp:198] conv1 needs backward computation. +I0410 13:28:46.868584 18353 net.cpp:200] train-data does not need backward computation. +I0410 13:28:46.868588 18353 net.cpp:242] This network produces output loss +I0410 13:28:46.868602 18353 net.cpp:255] Network initialization done. +I0410 13:28:46.869153 18353 solver.cpp:172] Creating test net (#0) specified by net file: train_val.prototxt +I0410 13:28:46.869184 18353 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer train-data +I0410 13:28:46.869329 18353 net.cpp:51] Initializing net from parameters: +state { +phase: TEST +} +layer { +name: "val-data" +type: "Data" +top: "data" +top: "label" +include { +phase: TEST +} +transform_param { +crop_size: 227 +mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" +} +data_param { +source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db" +batch_size: 32 +backend: LMDB +} +} +layer { +name: "conv1" +type: "Convolution" +bottom: "data" +top: "conv1" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 96 +kernel_size: 11 +stride: 4 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu1" +type: "ReLU" +bottom: "conv1" +top: "conv1" +} +layer { +name: "norm1" +type: "LRN" +bottom: "conv1" +top: "norm1" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool1" +type: "Pooling" +bottom: "norm1" +top: "pool1" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv2" +type: "Convolution" +bottom: "pool1" +top: "conv2" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 2 +kernel_size: 5 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu2" +type: "ReLU" +bottom: "conv2" +top: "conv2" +} +layer { +name: "norm2" +type: "LRN" +bottom: "conv2" +top: "norm2" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool2" +type: "Pooling" +bottom: "norm2" +top: "pool2" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv3" +type: "Convolution" +bottom: "pool2" +top: "conv3" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu3" +type: "ReLU" +bottom: "conv3" +top: "conv3" +} +layer { +name: "conv4" +type: "Convolution" +bottom: "conv3" +top: "conv4" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu4" +type: "ReLU" +bottom: "conv4" +top: "conv4" +} +layer { +name: "conv5" +type: "Convolution" +bottom: "conv4" +top: "conv5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu5" +type: "ReLU" +bottom: "conv5" +top: "conv5" +} +layer { +name: "pool5" +type: "Pooling" +bottom: "conv5" +top: "pool5" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "fc6" +type: "InnerProduct" +bottom: "pool5" +top: "fc6" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu6" +type: "ReLU" +bottom: "fc6" +top: "fc6" +} +layer { +name: "drop6" +type: "Dropout" +bottom: "fc6" +top: "fc6" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc8" +type: "InnerProduct" +bottom: "fc6" +top: "fc8" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 196 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "accuracy" +type: "Accuracy" +bottom: "fc8" +bottom: "label" +top: "accuracy" +include { +phase: TEST +} +} +layer { +name: "loss" +type: "SoftmaxWithLoss" +bottom: "fc8" +bottom: "label" +top: "loss" +} +I0410 13:28:46.869428 18353 layer_factory.hpp:77] Creating layer val-data +I0410 13:28:46.879921 18353 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db +I0410 13:28:46.880173 18353 net.cpp:84] Creating Layer val-data +I0410 13:28:46.880183 18353 net.cpp:380] val-data -> data +I0410 13:28:46.880195 18353 net.cpp:380] val-data -> label +I0410 13:28:46.880203 18353 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto +I0410 13:28:46.884544 18353 data_layer.cpp:45] output data size: 32,3,227,227 +I0410 13:28:46.918799 18353 net.cpp:122] Setting up val-data +I0410 13:28:46.918821 18353 net.cpp:129] Top shape: 32 3 227 227 (4946784) +I0410 13:28:46.918826 18353 net.cpp:129] Top shape: 32 (32) +I0410 13:28:46.918830 18353 net.cpp:137] Memory required for data: 19787264 +I0410 13:28:46.918838 18353 layer_factory.hpp:77] Creating layer label_val-data_1_split +I0410 13:28:46.918851 18353 net.cpp:84] Creating Layer label_val-data_1_split +I0410 13:28:46.918856 18353 net.cpp:406] label_val-data_1_split <- label +I0410 13:28:46.918864 18353 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_0 +I0410 13:28:46.918874 18353 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_1 +I0410 13:28:46.918977 18353 net.cpp:122] Setting up label_val-data_1_split +I0410 13:28:46.918983 18353 net.cpp:129] Top shape: 32 (32) +I0410 13:28:46.918987 18353 net.cpp:129] Top shape: 32 (32) +I0410 13:28:46.918992 18353 net.cpp:137] Memory required for data: 19787520 +I0410 13:28:46.918994 18353 layer_factory.hpp:77] Creating layer conv1 +I0410 13:28:46.919008 18353 net.cpp:84] Creating Layer conv1 +I0410 13:28:46.919011 18353 net.cpp:406] conv1 <- data +I0410 13:28:46.919018 18353 net.cpp:380] conv1 -> conv1 +I0410 13:28:46.921309 18353 net.cpp:122] Setting up conv1 +I0410 13:28:46.921321 18353 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:28:46.921325 18353 net.cpp:137] Memory required for data: 56958720 +I0410 13:28:46.921336 18353 layer_factory.hpp:77] Creating layer relu1 +I0410 13:28:46.921344 18353 net.cpp:84] Creating Layer relu1 +I0410 13:28:46.921368 18353 net.cpp:406] relu1 <- conv1 +I0410 13:28:46.921375 18353 net.cpp:367] relu1 -> conv1 (in-place) +I0410 13:28:46.921885 18353 net.cpp:122] Setting up relu1 +I0410 13:28:46.921896 18353 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:28:46.921900 18353 net.cpp:137] Memory required for data: 94129920 +I0410 13:28:46.921905 18353 layer_factory.hpp:77] Creating layer norm1 +I0410 13:28:46.921913 18353 net.cpp:84] Creating Layer norm1 +I0410 13:28:46.921918 18353 net.cpp:406] norm1 <- conv1 +I0410 13:28:46.921924 18353 net.cpp:380] norm1 -> norm1 +I0410 13:28:46.922299 18353 net.cpp:122] Setting up norm1 +I0410 13:28:46.922309 18353 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:28:46.922313 18353 net.cpp:137] Memory required for data: 131301120 +I0410 13:28:46.922322 18353 layer_factory.hpp:77] Creating layer pool1 +I0410 13:28:46.922331 18353 net.cpp:84] Creating Layer pool1 +I0410 13:28:46.922335 18353 net.cpp:406] pool1 <- norm1 +I0410 13:28:46.922341 18353 net.cpp:380] pool1 -> pool1 +I0410 13:28:46.922379 18353 net.cpp:122] Setting up pool1 +I0410 13:28:46.922384 18353 net.cpp:129] Top shape: 32 96 27 27 (2239488) +I0410 13:28:46.922389 18353 net.cpp:137] Memory required for data: 140259072 +I0410 13:28:46.922391 18353 layer_factory.hpp:77] Creating layer conv2 +I0410 13:28:46.922400 18353 net.cpp:84] Creating Layer conv2 +I0410 13:28:46.922405 18353 net.cpp:406] conv2 <- pool1 +I0410 13:28:46.922410 18353 net.cpp:380] conv2 -> conv2 +I0410 13:28:46.930526 18353 net.cpp:122] Setting up conv2 +I0410 13:28:46.930541 18353 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:28:46.930546 18353 net.cpp:137] Memory required for data: 164146944 +I0410 13:28:46.930557 18353 layer_factory.hpp:77] Creating layer relu2 +I0410 13:28:46.930565 18353 net.cpp:84] Creating Layer relu2 +I0410 13:28:46.930569 18353 net.cpp:406] relu2 <- conv2 +I0410 13:28:46.930577 18353 net.cpp:367] relu2 -> conv2 (in-place) +I0410 13:28:46.931138 18353 net.cpp:122] Setting up relu2 +I0410 13:28:46.931147 18353 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:28:46.931151 18353 net.cpp:137] Memory required for data: 188034816 +I0410 13:28:46.931155 18353 layer_factory.hpp:77] Creating layer norm2 +I0410 13:28:46.931165 18353 net.cpp:84] Creating Layer norm2 +I0410 13:28:46.931170 18353 net.cpp:406] norm2 <- conv2 +I0410 13:28:46.931176 18353 net.cpp:380] norm2 -> norm2 +I0410 13:28:46.931762 18353 net.cpp:122] Setting up norm2 +I0410 13:28:46.931772 18353 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:28:46.931777 18353 net.cpp:137] Memory required for data: 211922688 +I0410 13:28:46.931780 18353 layer_factory.hpp:77] Creating layer pool2 +I0410 13:28:46.931788 18353 net.cpp:84] Creating Layer pool2 +I0410 13:28:46.931792 18353 net.cpp:406] pool2 <- norm2 +I0410 13:28:46.931799 18353 net.cpp:380] pool2 -> pool2 +I0410 13:28:46.931833 18353 net.cpp:122] Setting up pool2 +I0410 13:28:46.931840 18353 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:28:46.931843 18353 net.cpp:137] Memory required for data: 217460480 +I0410 13:28:46.931847 18353 layer_factory.hpp:77] Creating layer conv3 +I0410 13:28:46.931859 18353 net.cpp:84] Creating Layer conv3 +I0410 13:28:46.931862 18353 net.cpp:406] conv3 <- pool2 +I0410 13:28:46.931869 18353 net.cpp:380] conv3 -> conv3 +I0410 13:28:46.942800 18353 net.cpp:122] Setting up conv3 +I0410 13:28:46.942814 18353 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:28:46.942818 18353 net.cpp:137] Memory required for data: 225767168 +I0410 13:28:46.942828 18353 layer_factory.hpp:77] Creating layer relu3 +I0410 13:28:46.942835 18353 net.cpp:84] Creating Layer relu3 +I0410 13:28:46.942839 18353 net.cpp:406] relu3 <- conv3 +I0410 13:28:46.942848 18353 net.cpp:367] relu3 -> conv3 (in-place) +I0410 13:28:46.944607 18353 net.cpp:122] Setting up relu3 +I0410 13:28:46.944618 18353 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:28:46.944622 18353 net.cpp:137] Memory required for data: 234073856 +I0410 13:28:46.944626 18353 layer_factory.hpp:77] Creating layer conv4 +I0410 13:28:46.944658 18353 net.cpp:84] Creating Layer conv4 +I0410 13:28:46.944664 18353 net.cpp:406] conv4 <- conv3 +I0410 13:28:46.944671 18353 net.cpp:380] conv4 -> conv4 +I0410 13:28:46.955147 18353 net.cpp:122] Setting up conv4 +I0410 13:28:46.955159 18353 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:28:46.955165 18353 net.cpp:137] Memory required for data: 242380544 +I0410 13:28:46.955173 18353 layer_factory.hpp:77] Creating layer relu4 +I0410 13:28:46.955180 18353 net.cpp:84] Creating Layer relu4 +I0410 13:28:46.955184 18353 net.cpp:406] relu4 <- conv4 +I0410 13:28:46.955190 18353 net.cpp:367] relu4 -> conv4 (in-place) +I0410 13:28:46.955739 18353 net.cpp:122] Setting up relu4 +I0410 13:28:46.955749 18353 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:28:46.955754 18353 net.cpp:137] Memory required for data: 250687232 +I0410 13:28:46.955757 18353 layer_factory.hpp:77] Creating layer conv5 +I0410 13:28:46.955768 18353 net.cpp:84] Creating Layer conv5 +I0410 13:28:46.955773 18353 net.cpp:406] conv5 <- conv4 +I0410 13:28:46.955780 18353 net.cpp:380] conv5 -> conv5 +I0410 13:28:46.965056 18353 net.cpp:122] Setting up conv5 +I0410 13:28:46.965070 18353 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:28:46.965075 18353 net.cpp:137] Memory required for data: 256225024 +I0410 13:28:46.965087 18353 layer_factory.hpp:77] Creating layer relu5 +I0410 13:28:46.965095 18353 net.cpp:84] Creating Layer relu5 +I0410 13:28:46.965098 18353 net.cpp:406] relu5 <- conv5 +I0410 13:28:46.965106 18353 net.cpp:367] relu5 -> conv5 (in-place) +I0410 13:28:46.965648 18353 net.cpp:122] Setting up relu5 +I0410 13:28:46.965658 18353 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:28:46.965662 18353 net.cpp:137] Memory required for data: 261762816 +I0410 13:28:46.965667 18353 layer_factory.hpp:77] Creating layer pool5 +I0410 13:28:46.965677 18353 net.cpp:84] Creating Layer pool5 +I0410 13:28:46.965682 18353 net.cpp:406] pool5 <- conv5 +I0410 13:28:46.965687 18353 net.cpp:380] pool5 -> pool5 +I0410 13:28:46.965730 18353 net.cpp:122] Setting up pool5 +I0410 13:28:46.965736 18353 net.cpp:129] Top shape: 32 256 6 6 (294912) +I0410 13:28:46.965740 18353 net.cpp:137] Memory required for data: 262942464 +I0410 13:28:46.965744 18353 layer_factory.hpp:77] Creating layer fc6 +I0410 13:28:46.965754 18353 net.cpp:84] Creating Layer fc6 +I0410 13:28:46.965759 18353 net.cpp:406] fc6 <- pool5 +I0410 13:28:46.965765 18353 net.cpp:380] fc6 -> fc6 +I0410 13:28:46.989315 18353 net.cpp:122] Setting up fc6 +I0410 13:28:46.989332 18353 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:28:46.989336 18353 net.cpp:137] Memory required for data: 262975232 +I0410 13:28:46.989346 18353 layer_factory.hpp:77] Creating layer relu6 +I0410 13:28:46.989354 18353 net.cpp:84] Creating Layer relu6 +I0410 13:28:46.989359 18353 net.cpp:406] relu6 <- fc6 +I0410 13:28:46.989367 18353 net.cpp:367] relu6 -> fc6 (in-place) +I0410 13:28:46.990041 18353 net.cpp:122] Setting up relu6 +I0410 13:28:46.990051 18353 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:28:46.990054 18353 net.cpp:137] Memory required for data: 263008000 +I0410 13:28:46.990058 18353 layer_factory.hpp:77] Creating layer drop6 +I0410 13:28:46.990065 18353 net.cpp:84] Creating Layer drop6 +I0410 13:28:46.990069 18353 net.cpp:406] drop6 <- fc6 +I0410 13:28:46.990077 18353 net.cpp:367] drop6 -> fc6 (in-place) +I0410 13:28:46.990104 18353 net.cpp:122] Setting up drop6 +I0410 13:28:46.990110 18353 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:28:46.990113 18353 net.cpp:137] Memory required for data: 263040768 +I0410 13:28:46.990118 18353 layer_factory.hpp:77] Creating layer fc8 +I0410 13:28:46.990124 18353 net.cpp:84] Creating Layer fc8 +I0410 13:28:46.990128 18353 net.cpp:406] fc8 <- fc6 +I0410 13:28:46.990135 18353 net.cpp:380] fc8 -> fc8 +I0410 13:28:46.990672 18353 net.cpp:122] Setting up fc8 +I0410 13:28:46.990679 18353 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:28:46.990682 18353 net.cpp:137] Memory required for data: 263065856 +I0410 13:28:46.990689 18353 layer_factory.hpp:77] Creating layer fc8_fc8_0_split +I0410 13:28:46.990696 18353 net.cpp:84] Creating Layer fc8_fc8_0_split +I0410 13:28:46.990717 18353 net.cpp:406] fc8_fc8_0_split <- fc8 +I0410 13:28:46.990723 18353 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_0 +I0410 13:28:46.990733 18353 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_1 +I0410 13:28:46.990767 18353 net.cpp:122] Setting up fc8_fc8_0_split +I0410 13:28:46.990773 18353 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:28:46.990777 18353 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:28:46.990780 18353 net.cpp:137] Memory required for data: 263116032 +I0410 13:28:46.990783 18353 layer_factory.hpp:77] Creating layer accuracy +I0410 13:28:46.990790 18353 net.cpp:84] Creating Layer accuracy +I0410 13:28:46.990794 18353 net.cpp:406] accuracy <- fc8_fc8_0_split_0 +I0410 13:28:46.990799 18353 net.cpp:406] accuracy <- label_val-data_1_split_0 +I0410 13:28:46.990805 18353 net.cpp:380] accuracy -> accuracy +I0410 13:28:46.990813 18353 net.cpp:122] Setting up accuracy +I0410 13:28:46.990818 18353 net.cpp:129] Top shape: (1) +I0410 13:28:46.990820 18353 net.cpp:137] Memory required for data: 263116036 +I0410 13:28:46.990823 18353 layer_factory.hpp:77] Creating layer loss +I0410 13:28:46.990829 18353 net.cpp:84] Creating Layer loss +I0410 13:28:46.990833 18353 net.cpp:406] loss <- fc8_fc8_0_split_1 +I0410 13:28:46.990837 18353 net.cpp:406] loss <- label_val-data_1_split_1 +I0410 13:28:46.990842 18353 net.cpp:380] loss -> loss +I0410 13:28:46.990849 18353 layer_factory.hpp:77] Creating layer loss +I0410 13:28:46.991662 18353 net.cpp:122] Setting up loss +I0410 13:28:46.991672 18353 net.cpp:129] Top shape: (1) +I0410 13:28:46.991674 18353 net.cpp:132] with loss weight 1 +I0410 13:28:46.991686 18353 net.cpp:137] Memory required for data: 263116040 +I0410 13:28:46.991690 18353 net.cpp:198] loss needs backward computation. +I0410 13:28:46.991695 18353 net.cpp:200] accuracy does not need backward computation. +I0410 13:28:46.991700 18353 net.cpp:198] fc8_fc8_0_split needs backward computation. +I0410 13:28:46.991703 18353 net.cpp:198] fc8 needs backward computation. +I0410 13:28:46.991708 18353 net.cpp:198] drop6 needs backward computation. +I0410 13:28:46.991710 18353 net.cpp:198] relu6 needs backward computation. +I0410 13:28:46.991714 18353 net.cpp:198] fc6 needs backward computation. +I0410 13:28:46.991717 18353 net.cpp:198] pool5 needs backward computation. +I0410 13:28:46.991722 18353 net.cpp:198] relu5 needs backward computation. +I0410 13:28:46.991725 18353 net.cpp:198] conv5 needs backward computation. +I0410 13:28:46.991729 18353 net.cpp:198] relu4 needs backward computation. +I0410 13:28:46.991732 18353 net.cpp:198] conv4 needs backward computation. +I0410 13:28:46.991736 18353 net.cpp:198] relu3 needs backward computation. +I0410 13:28:46.991739 18353 net.cpp:198] conv3 needs backward computation. +I0410 13:28:46.991744 18353 net.cpp:198] pool2 needs backward computation. +I0410 13:28:46.991747 18353 net.cpp:198] norm2 needs backward computation. +I0410 13:28:46.991750 18353 net.cpp:198] relu2 needs backward computation. +I0410 13:28:46.991755 18353 net.cpp:198] conv2 needs backward computation. +I0410 13:28:46.991757 18353 net.cpp:198] pool1 needs backward computation. +I0410 13:28:46.991761 18353 net.cpp:198] norm1 needs backward computation. +I0410 13:28:46.991765 18353 net.cpp:198] relu1 needs backward computation. +I0410 13:28:46.991768 18353 net.cpp:198] conv1 needs backward computation. +I0410 13:28:46.991772 18353 net.cpp:200] label_val-data_1_split does not need backward computation. +I0410 13:28:46.991776 18353 net.cpp:200] val-data does not need backward computation. +I0410 13:28:46.991780 18353 net.cpp:242] This network produces output accuracy +I0410 13:28:46.991784 18353 net.cpp:242] This network produces output loss +I0410 13:28:46.991799 18353 net.cpp:255] Network initialization done. +I0410 13:28:46.991868 18353 solver.cpp:56] Solver scaffolding done. +I0410 13:28:46.992254 18353 caffe.cpp:248] Starting Optimization +I0410 13:28:46.992264 18353 solver.cpp:272] Solving +I0410 13:28:46.992267 18353 solver.cpp:273] Learning Rate Policy: exp +I0410 13:28:46.993083 18353 solver.cpp:330] Iteration 0, Testing net (#0) +I0410 13:28:46.993103 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:28:46.995333 18353 blocking_queue.cpp:49] Waiting for data +I0410 13:28:51.467716 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:28:51.511610 18353 solver.cpp:397] Test net output #0: accuracy = 0.0067402 +I0410 13:28:51.511653 18353 solver.cpp:397] Test net output #1: loss = 5.27914 (* 1 = 5.27914 loss) +I0410 13:28:51.596724 18353 solver.cpp:218] Iteration 0 (-5.2899e-30 iter/s, 4.60427s/12 iters), loss = 5.27351 +I0410 13:28:51.596762 18353 solver.cpp:237] Train net output #0: loss = 5.27351 (* 1 = 5.27351 loss) +I0410 13:28:51.596786 18353 sgd_solver.cpp:105] Iteration 0, lr = 0.01 +I0410 13:28:55.494565 18353 solver.cpp:218] Iteration 12 (3.07878 iter/s, 3.89765s/12 iters), loss = 5.27118 +I0410 13:28:55.494608 18353 solver.cpp:237] Train net output #0: loss = 5.27118 (* 1 = 5.27118 loss) +I0410 13:28:55.494619 18353 sgd_solver.cpp:105] Iteration 12, lr = 0.00997626 +I0410 13:29:00.241415 18353 solver.cpp:218] Iteration 24 (2.52811 iter/s, 4.74663s/12 iters), loss = 5.28136 +I0410 13:29:00.241461 18353 solver.cpp:237] Train net output #0: loss = 5.28136 (* 1 = 5.28136 loss) +I0410 13:29:00.241472 18353 sgd_solver.cpp:105] Iteration 24, lr = 0.00995257 +I0410 13:29:05.047654 18353 solver.cpp:218] Iteration 36 (2.49687 iter/s, 4.80602s/12 iters), loss = 5.28017 +I0410 13:29:05.047699 18353 solver.cpp:237] Train net output #0: loss = 5.28017 (* 1 = 5.28017 loss) +I0410 13:29:05.047713 18353 sgd_solver.cpp:105] Iteration 36, lr = 0.00992894 +I0410 13:29:09.879206 18353 solver.cpp:218] Iteration 48 (2.48379 iter/s, 4.83133s/12 iters), loss = 5.28742 +I0410 13:29:09.879246 18353 solver.cpp:237] Train net output #0: loss = 5.28742 (* 1 = 5.28742 loss) +I0410 13:29:09.879258 18353 sgd_solver.cpp:105] Iteration 48, lr = 0.00990537 +I0410 13:29:14.691164 18353 solver.cpp:218] Iteration 60 (2.4939 iter/s, 4.81174s/12 iters), loss = 5.28094 +I0410 13:29:14.691207 18353 solver.cpp:237] Train net output #0: loss = 5.28094 (* 1 = 5.28094 loss) +I0410 13:29:14.691217 18353 sgd_solver.cpp:105] Iteration 60, lr = 0.00988185 +I0410 13:29:19.510717 18353 solver.cpp:218] Iteration 72 (2.48997 iter/s, 4.81933s/12 iters), loss = 5.2808 +I0410 13:29:19.510808 18353 solver.cpp:237] Train net output #0: loss = 5.2808 (* 1 = 5.2808 loss) +I0410 13:29:19.510821 18353 sgd_solver.cpp:105] Iteration 72, lr = 0.00985839 +I0410 13:29:24.294188 18353 solver.cpp:218] Iteration 84 (2.50878 iter/s, 4.78321s/12 iters), loss = 5.28572 +I0410 13:29:24.294235 18353 solver.cpp:237] Train net output #0: loss = 5.28572 (* 1 = 5.28572 loss) +I0410 13:29:24.294248 18353 sgd_solver.cpp:105] Iteration 84, lr = 0.00983498 +I0410 13:29:29.128234 18353 solver.cpp:218] Iteration 96 (2.4825 iter/s, 4.83383s/12 iters), loss = 5.28377 +I0410 13:29:29.128278 18353 solver.cpp:237] Train net output #0: loss = 5.28377 (* 1 = 5.28377 loss) +I0410 13:29:29.128288 18353 sgd_solver.cpp:105] Iteration 96, lr = 0.00981163 +I0410 13:29:30.760265 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:29:31.065268 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_102.caffemodel +I0410 13:29:31.652758 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_102.solverstate +I0410 13:29:32.011798 18353 solver.cpp:330] Iteration 102, Testing net (#0) +I0410 13:29:32.011826 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:29:36.362304 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:29:36.438158 18353 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:29:36.438201 18353 solver.cpp:397] Test net output #1: loss = 5.27879 (* 1 = 5.27879 loss) +I0410 13:29:38.203984 18353 solver.cpp:218] Iteration 108 (1.32226 iter/s, 9.07539s/12 iters), loss = 5.27684 +I0410 13:29:38.204031 18353 solver.cpp:237] Train net output #0: loss = 5.27684 (* 1 = 5.27684 loss) +I0410 13:29:38.204043 18353 sgd_solver.cpp:105] Iteration 108, lr = 0.00978834 +I0410 13:29:42.993652 18353 solver.cpp:218] Iteration 120 (2.50551 iter/s, 4.78945s/12 iters), loss = 5.27292 +I0410 13:29:42.993701 18353 solver.cpp:237] Train net output #0: loss = 5.27292 (* 1 = 5.27292 loss) +I0410 13:29:42.993713 18353 sgd_solver.cpp:105] Iteration 120, lr = 0.0097651 +I0410 13:29:47.763233 18353 solver.cpp:218] Iteration 132 (2.51606 iter/s, 4.76936s/12 iters), loss = 5.24752 +I0410 13:29:47.763283 18353 solver.cpp:237] Train net output #0: loss = 5.24752 (* 1 = 5.24752 loss) +I0410 13:29:47.763296 18353 sgd_solver.cpp:105] Iteration 132, lr = 0.00974192 +I0410 13:29:52.570581 18353 solver.cpp:218] Iteration 144 (2.49629 iter/s, 4.80713s/12 iters), loss = 5.29731 +I0410 13:29:52.570744 18353 solver.cpp:237] Train net output #0: loss = 5.29731 (* 1 = 5.29731 loss) +I0410 13:29:52.570758 18353 sgd_solver.cpp:105] Iteration 144, lr = 0.00971879 +I0410 13:29:57.389384 18353 solver.cpp:218] Iteration 156 (2.49042 iter/s, 4.81847s/12 iters), loss = 5.26402 +I0410 13:29:57.389434 18353 solver.cpp:237] Train net output #0: loss = 5.26402 (* 1 = 5.26402 loss) +I0410 13:29:57.389447 18353 sgd_solver.cpp:105] Iteration 156, lr = 0.00969571 +I0410 13:30:02.180932 18353 solver.cpp:218] Iteration 168 (2.50453 iter/s, 4.79133s/12 iters), loss = 5.26406 +I0410 13:30:02.180980 18353 solver.cpp:237] Train net output #0: loss = 5.26406 (* 1 = 5.26406 loss) +I0410 13:30:02.180992 18353 sgd_solver.cpp:105] Iteration 168, lr = 0.00967269 +I0410 13:30:06.979442 18353 solver.cpp:218] Iteration 180 (2.50089 iter/s, 4.79829s/12 iters), loss = 5.25816 +I0410 13:30:06.979494 18353 solver.cpp:237] Train net output #0: loss = 5.25816 (* 1 = 5.25816 loss) +I0410 13:30:06.979504 18353 sgd_solver.cpp:105] Iteration 180, lr = 0.00964973 +I0410 13:30:11.786164 18353 solver.cpp:218] Iteration 192 (2.49662 iter/s, 4.80649s/12 iters), loss = 5.26288 +I0410 13:30:11.786226 18353 solver.cpp:237] Train net output #0: loss = 5.26288 (* 1 = 5.26288 loss) +I0410 13:30:11.786242 18353 sgd_solver.cpp:105] Iteration 192, lr = 0.00962682 +I0410 13:30:15.648447 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:30:16.300645 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_204.caffemodel +I0410 13:30:16.603500 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_204.solverstate +I0410 13:30:16.807330 18353 solver.cpp:330] Iteration 204, Testing net (#0) +I0410 13:30:16.807361 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:30:21.316921 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:30:21.438299 18353 solver.cpp:397] Test net output #0: accuracy = 0.00735294 +I0410 13:30:21.438351 18353 solver.cpp:397] Test net output #1: loss = 5.21164 (* 1 = 5.21164 loss) +I0410 13:30:21.519675 18353 solver.cpp:218] Iteration 204 (1.2329 iter/s, 9.73312s/12 iters), loss = 5.19107 +I0410 13:30:21.519727 18353 solver.cpp:237] Train net output #0: loss = 5.19107 (* 1 = 5.19107 loss) +I0410 13:30:21.519738 18353 sgd_solver.cpp:105] Iteration 204, lr = 0.00960396 +I0410 13:30:25.610288 18353 solver.cpp:218] Iteration 216 (2.93369 iter/s, 4.09041s/12 iters), loss = 5.21252 +I0410 13:30:25.610414 18353 solver.cpp:237] Train net output #0: loss = 5.21252 (* 1 = 5.21252 loss) +I0410 13:30:25.610425 18353 sgd_solver.cpp:105] Iteration 216, lr = 0.00958116 +I0410 13:30:30.402014 18353 solver.cpp:218] Iteration 228 (2.50447 iter/s, 4.79142s/12 iters), loss = 5.22201 +I0410 13:30:30.402065 18353 solver.cpp:237] Train net output #0: loss = 5.22201 (* 1 = 5.22201 loss) +I0410 13:30:30.402076 18353 sgd_solver.cpp:105] Iteration 228, lr = 0.00955841 +I0410 13:30:35.195777 18353 solver.cpp:218] Iteration 240 (2.50337 iter/s, 4.79354s/12 iters), loss = 5.22456 +I0410 13:30:35.195832 18353 solver.cpp:237] Train net output #0: loss = 5.22456 (* 1 = 5.22456 loss) +I0410 13:30:35.195843 18353 sgd_solver.cpp:105] Iteration 240, lr = 0.00953572 +I0410 13:30:40.018483 18353 solver.cpp:218] Iteration 252 (2.48835 iter/s, 4.82247s/12 iters), loss = 5.16041 +I0410 13:30:40.018541 18353 solver.cpp:237] Train net output #0: loss = 5.16041 (* 1 = 5.16041 loss) +I0410 13:30:40.018555 18353 sgd_solver.cpp:105] Iteration 252, lr = 0.00951308 +I0410 13:30:44.863235 18353 solver.cpp:218] Iteration 264 (2.47702 iter/s, 4.84452s/12 iters), loss = 5.29866 +I0410 13:30:44.863277 18353 solver.cpp:237] Train net output #0: loss = 5.29866 (* 1 = 5.29866 loss) +I0410 13:30:44.863287 18353 sgd_solver.cpp:105] Iteration 264, lr = 0.00949049 +I0410 13:30:49.661846 18353 solver.cpp:218] Iteration 276 (2.50084 iter/s, 4.79839s/12 iters), loss = 5.20624 +I0410 13:30:49.661901 18353 solver.cpp:237] Train net output #0: loss = 5.20624 (* 1 = 5.20624 loss) +I0410 13:30:49.661912 18353 sgd_solver.cpp:105] Iteration 276, lr = 0.00946796 +I0410 13:30:54.430438 18353 solver.cpp:218] Iteration 288 (2.51659 iter/s, 4.76836s/12 iters), loss = 5.08793 +I0410 13:30:54.430500 18353 solver.cpp:237] Train net output #0: loss = 5.08793 (* 1 = 5.08793 loss) +I0410 13:30:54.430514 18353 sgd_solver.cpp:105] Iteration 288, lr = 0.00944548 +I0410 13:30:59.202740 18353 solver.cpp:218] Iteration 300 (2.51463 iter/s, 4.77206s/12 iters), loss = 5.17502 +I0410 13:30:59.202906 18353 solver.cpp:237] Train net output #0: loss = 5.17502 (* 1 = 5.17502 loss) +I0410 13:30:59.202919 18353 sgd_solver.cpp:105] Iteration 300, lr = 0.00942305 +I0410 13:31:00.147606 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:01.149010 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_306.caffemodel +I0410 13:31:01.638471 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_306.solverstate +I0410 13:31:02.298786 18353 solver.cpp:330] Iteration 306, Testing net (#0) +I0410 13:31:02.298818 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:31:06.590077 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:06.747010 18353 solver.cpp:397] Test net output #0: accuracy = 0.00735294 +I0410 13:31:06.747061 18353 solver.cpp:397] Test net output #1: loss = 5.14714 (* 1 = 5.14714 loss) +I0410 13:31:08.551136 18353 solver.cpp:218] Iteration 312 (1.28371 iter/s, 9.34791s/12 iters), loss = 5.11782 +I0410 13:31:08.551187 18353 solver.cpp:237] Train net output #0: loss = 5.11782 (* 1 = 5.11782 loss) +I0410 13:31:08.551200 18353 sgd_solver.cpp:105] Iteration 312, lr = 0.00940068 +I0410 13:31:13.352361 18353 solver.cpp:218] Iteration 324 (2.49948 iter/s, 4.801s/12 iters), loss = 5.1685 +I0410 13:31:13.352419 18353 solver.cpp:237] Train net output #0: loss = 5.1685 (* 1 = 5.1685 loss) +I0410 13:31:13.352432 18353 sgd_solver.cpp:105] Iteration 324, lr = 0.00937836 +I0410 13:31:18.135365 18353 solver.cpp:218] Iteration 336 (2.509 iter/s, 4.78278s/12 iters), loss = 5.12779 +I0410 13:31:18.135421 18353 solver.cpp:237] Train net output #0: loss = 5.12779 (* 1 = 5.12779 loss) +I0410 13:31:18.135432 18353 sgd_solver.cpp:105] Iteration 336, lr = 0.0093561 +I0410 13:31:22.922883 18353 solver.cpp:218] Iteration 348 (2.50664 iter/s, 4.78729s/12 iters), loss = 5.12706 +I0410 13:31:22.922940 18353 solver.cpp:237] Train net output #0: loss = 5.12706 (* 1 = 5.12706 loss) +I0410 13:31:22.922953 18353 sgd_solver.cpp:105] Iteration 348, lr = 0.00933388 +I0410 13:31:27.818292 18353 solver.cpp:218] Iteration 360 (2.45139 iter/s, 4.89518s/12 iters), loss = 5.15952 +I0410 13:31:27.818341 18353 solver.cpp:237] Train net output #0: loss = 5.15952 (* 1 = 5.15952 loss) +I0410 13:31:27.818349 18353 sgd_solver.cpp:105] Iteration 360, lr = 0.00931172 +I0410 13:31:32.648501 18353 solver.cpp:218] Iteration 372 (2.48448 iter/s, 4.82999s/12 iters), loss = 5.10923 +I0410 13:31:32.648577 18353 solver.cpp:237] Train net output #0: loss = 5.10923 (* 1 = 5.10923 loss) +I0410 13:31:32.648587 18353 sgd_solver.cpp:105] Iteration 372, lr = 0.00928961 +I0410 13:31:37.440991 18353 solver.cpp:218] Iteration 384 (2.50405 iter/s, 4.79224s/12 iters), loss = 5.09812 +I0410 13:31:37.441048 18353 solver.cpp:237] Train net output #0: loss = 5.09812 (* 1 = 5.09812 loss) +I0410 13:31:37.441061 18353 sgd_solver.cpp:105] Iteration 384, lr = 0.00926756 +I0410 13:31:42.235280 18353 solver.cpp:218] Iteration 396 (2.50309 iter/s, 4.79407s/12 iters), loss = 5.06009 +I0410 13:31:42.235325 18353 solver.cpp:237] Train net output #0: loss = 5.06009 (* 1 = 5.06009 loss) +I0410 13:31:42.235334 18353 sgd_solver.cpp:105] Iteration 396, lr = 0.00924556 +I0410 13:31:45.253728 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:46.600811 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_408.caffemodel +I0410 13:31:47.486912 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_408.solverstate +I0410 13:31:47.904908 18353 solver.cpp:330] Iteration 408, Testing net (#0) +I0410 13:31:47.904937 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:31:52.084388 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:52.286082 18353 solver.cpp:397] Test net output #0: accuracy = 0.0159314 +I0410 13:31:52.286114 18353 solver.cpp:397] Test net output #1: loss = 5.09138 (* 1 = 5.09138 loss) +I0410 13:31:52.367595 18353 solver.cpp:218] Iteration 408 (1.18437 iter/s, 10.1319s/12 iters), loss = 5.17838 +I0410 13:31:52.367662 18353 solver.cpp:237] Train net output #0: loss = 5.17838 (* 1 = 5.17838 loss) +I0410 13:31:52.367676 18353 sgd_solver.cpp:105] Iteration 408, lr = 0.00922361 +I0410 13:31:56.396499 18353 solver.cpp:218] Iteration 420 (2.97863 iter/s, 4.0287s/12 iters), loss = 5.13791 +I0410 13:31:56.396557 18353 solver.cpp:237] Train net output #0: loss = 5.13791 (* 1 = 5.13791 loss) +I0410 13:31:56.396569 18353 sgd_solver.cpp:105] Iteration 420, lr = 0.00920171 +I0410 13:32:01.152849 18353 solver.cpp:218] Iteration 432 (2.52306 iter/s, 4.75613s/12 iters), loss = 5.16788 +I0410 13:32:01.152911 18353 solver.cpp:237] Train net output #0: loss = 5.16788 (* 1 = 5.16788 loss) +I0410 13:32:01.152925 18353 sgd_solver.cpp:105] Iteration 432, lr = 0.00917986 +I0410 13:32:06.051076 18353 solver.cpp:218] Iteration 444 (2.44998 iter/s, 4.898s/12 iters), loss = 5.04653 +I0410 13:32:06.051204 18353 solver.cpp:237] Train net output #0: loss = 5.04653 (* 1 = 5.04653 loss) +I0410 13:32:06.051218 18353 sgd_solver.cpp:105] Iteration 444, lr = 0.00915807 +I0410 13:32:10.883579 18353 solver.cpp:218] Iteration 456 (2.48334 iter/s, 4.83221s/12 iters), loss = 5.0797 +I0410 13:32:10.883632 18353 solver.cpp:237] Train net output #0: loss = 5.0797 (* 1 = 5.0797 loss) +I0410 13:32:10.883643 18353 sgd_solver.cpp:105] Iteration 456, lr = 0.00913632 +I0410 13:32:15.690878 18353 solver.cpp:218] Iteration 468 (2.49631 iter/s, 4.80709s/12 iters), loss = 5.10949 +I0410 13:32:15.690922 18353 solver.cpp:237] Train net output #0: loss = 5.10949 (* 1 = 5.10949 loss) +I0410 13:32:15.690932 18353 sgd_solver.cpp:105] Iteration 468, lr = 0.00911463 +I0410 13:32:20.507534 18353 solver.cpp:218] Iteration 480 (2.49146 iter/s, 4.81645s/12 iters), loss = 5.04724 +I0410 13:32:20.507589 18353 solver.cpp:237] Train net output #0: loss = 5.04724 (* 1 = 5.04724 loss) +I0410 13:32:20.507602 18353 sgd_solver.cpp:105] Iteration 480, lr = 0.00909299 +I0410 13:32:25.362396 18353 solver.cpp:218] Iteration 492 (2.47186 iter/s, 4.85464s/12 iters), loss = 5.11802 +I0410 13:32:25.362447 18353 solver.cpp:237] Train net output #0: loss = 5.11802 (* 1 = 5.11802 loss) +I0410 13:32:25.362459 18353 sgd_solver.cpp:105] Iteration 492, lr = 0.0090714 +I0410 13:32:30.133383 18353 solver.cpp:218] Iteration 504 (2.51531 iter/s, 4.77078s/12 iters), loss = 5.11083 +I0410 13:32:30.133442 18353 solver.cpp:237] Train net output #0: loss = 5.11083 (* 1 = 5.11083 loss) +I0410 13:32:30.133455 18353 sgd_solver.cpp:105] Iteration 504, lr = 0.00904986 +I0410 13:32:30.381103 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:32.116602 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_510.caffemodel +I0410 13:32:32.442308 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_510.solverstate +I0410 13:32:32.644781 18353 solver.cpp:330] Iteration 510, Testing net (#0) +I0410 13:32:32.644809 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:32:36.983175 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:37.219594 18353 solver.cpp:397] Test net output #0: accuracy = 0.0232843 +I0410 13:32:37.219626 18353 solver.cpp:397] Test net output #1: loss = 5.03098 (* 1 = 5.03098 loss) +I0410 13:32:39.060112 18353 solver.cpp:218] Iteration 516 (1.34433 iter/s, 8.92639s/12 iters), loss = 4.96743 +I0410 13:32:39.060158 18353 solver.cpp:237] Train net output #0: loss = 4.96743 (* 1 = 4.96743 loss) +I0410 13:32:39.060169 18353 sgd_solver.cpp:105] Iteration 516, lr = 0.00902838 +I0410 13:32:43.856173 18353 solver.cpp:218] Iteration 528 (2.50216 iter/s, 4.79585s/12 iters), loss = 5.06687 +I0410 13:32:43.856220 18353 solver.cpp:237] Train net output #0: loss = 5.06687 (* 1 = 5.06687 loss) +I0410 13:32:43.856230 18353 sgd_solver.cpp:105] Iteration 528, lr = 0.00900694 +I0410 13:32:48.847501 18353 solver.cpp:218] Iteration 540 (2.40427 iter/s, 4.99111s/12 iters), loss = 4.9997 +I0410 13:32:48.847553 18353 solver.cpp:237] Train net output #0: loss = 4.9997 (* 1 = 4.9997 loss) +I0410 13:32:48.847566 18353 sgd_solver.cpp:105] Iteration 540, lr = 0.00898556 +I0410 13:32:53.647042 18353 solver.cpp:218] Iteration 552 (2.50035 iter/s, 4.79933s/12 iters), loss = 5.08308 +I0410 13:32:53.647094 18353 solver.cpp:237] Train net output #0: loss = 5.08308 (* 1 = 5.08308 loss) +I0410 13:32:53.647106 18353 sgd_solver.cpp:105] Iteration 552, lr = 0.00896423 +I0410 13:32:58.454965 18353 solver.cpp:218] Iteration 564 (2.49599 iter/s, 4.80771s/12 iters), loss = 4.99543 +I0410 13:32:58.455015 18353 solver.cpp:237] Train net output #0: loss = 4.99543 (* 1 = 4.99543 loss) +I0410 13:32:58.455029 18353 sgd_solver.cpp:105] Iteration 564, lr = 0.00894294 +I0410 13:33:03.214296 18353 solver.cpp:218] Iteration 576 (2.52147 iter/s, 4.75912s/12 iters), loss = 5.0517 +I0410 13:33:03.214347 18353 solver.cpp:237] Train net output #0: loss = 5.0517 (* 1 = 5.0517 loss) +I0410 13:33:03.214359 18353 sgd_solver.cpp:105] Iteration 576, lr = 0.00892171 +I0410 13:33:08.054003 18353 solver.cpp:218] Iteration 588 (2.4796 iter/s, 4.83949s/12 iters), loss = 4.96009 +I0410 13:33:08.054117 18353 solver.cpp:237] Train net output #0: loss = 4.96009 (* 1 = 4.96009 loss) +I0410 13:33:08.054131 18353 sgd_solver.cpp:105] Iteration 588, lr = 0.00890053 +I0410 13:33:12.873062 18353 solver.cpp:218] Iteration 600 (2.49025 iter/s, 4.81879s/12 iters), loss = 5.02712 +I0410 13:33:12.873113 18353 solver.cpp:237] Train net output #0: loss = 5.02712 (* 1 = 5.02712 loss) +I0410 13:33:12.873126 18353 sgd_solver.cpp:105] Iteration 600, lr = 0.0088794 +I0410 13:33:15.161584 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:33:17.370432 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_612.caffemodel +I0410 13:33:17.692783 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_612.solverstate +I0410 13:33:17.900879 18353 solver.cpp:330] Iteration 612, Testing net (#0) +I0410 13:33:17.900902 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:33:22.024000 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:33:22.307170 18353 solver.cpp:397] Test net output #0: accuracy = 0.0208333 +I0410 13:33:22.307219 18353 solver.cpp:397] Test net output #1: loss = 4.96715 (* 1 = 4.96715 loss) +I0410 13:33:22.389060 18353 solver.cpp:218] Iteration 612 (1.26108 iter/s, 9.51565s/12 iters), loss = 5.00101 +I0410 13:33:22.389107 18353 solver.cpp:237] Train net output #0: loss = 5.00101 (* 1 = 5.00101 loss) +I0410 13:33:22.389119 18353 sgd_solver.cpp:105] Iteration 612, lr = 0.00885831 +I0410 13:33:26.586331 18353 solver.cpp:218] Iteration 624 (2.85913 iter/s, 4.19708s/12 iters), loss = 4.88992 +I0410 13:33:26.586385 18353 solver.cpp:237] Train net output #0: loss = 4.88992 (* 1 = 4.88992 loss) +I0410 13:33:26.586397 18353 sgd_solver.cpp:105] Iteration 624, lr = 0.00883728 +I0410 13:33:31.612911 18353 solver.cpp:218] Iteration 636 (2.38741 iter/s, 5.02636s/12 iters), loss = 4.9153 +I0410 13:33:31.612969 18353 solver.cpp:237] Train net output #0: loss = 4.9153 (* 1 = 4.9153 loss) +I0410 13:33:31.612982 18353 sgd_solver.cpp:105] Iteration 636, lr = 0.0088163 +I0410 13:33:36.421813 18353 solver.cpp:218] Iteration 648 (2.49548 iter/s, 4.80869s/12 iters), loss = 5.13299 +I0410 13:33:36.421856 18353 solver.cpp:237] Train net output #0: loss = 5.13299 (* 1 = 5.13299 loss) +I0410 13:33:36.421865 18353 sgd_solver.cpp:105] Iteration 648, lr = 0.00879537 +I0410 13:33:41.234724 18353 solver.cpp:218] Iteration 660 (2.4934 iter/s, 4.8127s/12 iters), loss = 5.07361 +I0410 13:33:41.234858 18353 solver.cpp:237] Train net output #0: loss = 5.07361 (* 1 = 5.07361 loss) +I0410 13:33:41.234874 18353 sgd_solver.cpp:105] Iteration 660, lr = 0.00877449 +I0410 13:33:45.991466 18353 solver.cpp:218] Iteration 672 (2.52288 iter/s, 4.75646s/12 iters), loss = 4.90382 +I0410 13:33:45.991503 18353 solver.cpp:237] Train net output #0: loss = 4.90382 (* 1 = 4.90382 loss) +I0410 13:33:45.991515 18353 sgd_solver.cpp:105] Iteration 672, lr = 0.00875366 +I0410 13:33:49.948544 18353 blocking_queue.cpp:49] Waiting for data +I0410 13:33:50.813939 18353 solver.cpp:218] Iteration 684 (2.48845 iter/s, 4.82227s/12 iters), loss = 4.77979 +I0410 13:33:50.814013 18353 solver.cpp:237] Train net output #0: loss = 4.77979 (* 1 = 4.77979 loss) +I0410 13:33:50.814024 18353 sgd_solver.cpp:105] Iteration 684, lr = 0.00873287 +I0410 13:33:55.640511 18353 solver.cpp:218] Iteration 696 (2.48636 iter/s, 4.82634s/12 iters), loss = 4.88568 +I0410 13:33:55.640564 18353 solver.cpp:237] Train net output #0: loss = 4.88568 (* 1 = 4.88568 loss) +I0410 13:33:55.640578 18353 sgd_solver.cpp:105] Iteration 696, lr = 0.00871214 +I0410 13:34:00.095309 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:00.466298 18353 solver.cpp:218] Iteration 708 (2.48675 iter/s, 4.82557s/12 iters), loss = 5.00854 +I0410 13:34:00.466358 18353 solver.cpp:237] Train net output #0: loss = 5.00854 (* 1 = 5.00854 loss) +I0410 13:34:00.466372 18353 sgd_solver.cpp:105] Iteration 708, lr = 0.00869145 +I0410 13:34:02.622711 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_714.caffemodel +I0410 13:34:02.936161 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_714.solverstate +I0410 13:34:03.148313 18353 solver.cpp:330] Iteration 714, Testing net (#0) +I0410 13:34:03.148342 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:34:07.349382 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:07.673627 18353 solver.cpp:397] Test net output #0: accuracy = 0.0300245 +I0410 13:34:07.673676 18353 solver.cpp:397] Test net output #1: loss = 4.93297 (* 1 = 4.93297 loss) +I0410 13:34:09.504738 18353 solver.cpp:218] Iteration 720 (1.32771 iter/s, 9.0381s/12 iters), loss = 5.03595 +I0410 13:34:09.504794 18353 solver.cpp:237] Train net output #0: loss = 5.03595 (* 1 = 5.03595 loss) +I0410 13:34:09.504806 18353 sgd_solver.cpp:105] Iteration 720, lr = 0.00867082 +I0410 13:34:14.545984 18353 solver.cpp:218] Iteration 732 (2.38047 iter/s, 5.04101s/12 iters), loss = 4.84105 +I0410 13:34:14.546103 18353 solver.cpp:237] Train net output #0: loss = 4.84105 (* 1 = 4.84105 loss) +I0410 13:34:14.546118 18353 sgd_solver.cpp:105] Iteration 732, lr = 0.00865023 +I0410 13:34:19.344077 18353 solver.cpp:218] Iteration 744 (2.50113 iter/s, 4.79782s/12 iters), loss = 4.9522 +I0410 13:34:19.344130 18353 solver.cpp:237] Train net output #0: loss = 4.9522 (* 1 = 4.9522 loss) +I0410 13:34:19.344141 18353 sgd_solver.cpp:105] Iteration 744, lr = 0.0086297 +I0410 13:34:24.181560 18353 solver.cpp:218] Iteration 756 (2.48073 iter/s, 4.83728s/12 iters), loss = 4.96332 +I0410 13:34:24.181602 18353 solver.cpp:237] Train net output #0: loss = 4.96332 (* 1 = 4.96332 loss) +I0410 13:34:24.181612 18353 sgd_solver.cpp:105] Iteration 756, lr = 0.00860921 +I0410 13:34:29.019403 18353 solver.cpp:218] Iteration 768 (2.48054 iter/s, 4.83765s/12 iters), loss = 4.87163 +I0410 13:34:29.019444 18353 solver.cpp:237] Train net output #0: loss = 4.87163 (* 1 = 4.87163 loss) +I0410 13:34:29.019452 18353 sgd_solver.cpp:105] Iteration 768, lr = 0.00858877 +I0410 13:34:33.830617 18353 solver.cpp:218] Iteration 780 (2.49428 iter/s, 4.81101s/12 iters), loss = 4.85705 +I0410 13:34:33.830667 18353 solver.cpp:237] Train net output #0: loss = 4.85705 (* 1 = 4.85705 loss) +I0410 13:34:33.830677 18353 sgd_solver.cpp:105] Iteration 780, lr = 0.00856838 +I0410 13:34:38.681201 18353 solver.cpp:218] Iteration 792 (2.47403 iter/s, 4.85038s/12 iters), loss = 4.69125 +I0410 13:34:38.681259 18353 solver.cpp:237] Train net output #0: loss = 4.69125 (* 1 = 4.69125 loss) +I0410 13:34:38.681272 18353 sgd_solver.cpp:105] Iteration 792, lr = 0.00854803 +I0410 13:34:43.579320 18353 solver.cpp:218] Iteration 804 (2.45003 iter/s, 4.89791s/12 iters), loss = 4.98446 +I0410 13:34:43.579371 18353 solver.cpp:237] Train net output #0: loss = 4.98446 (* 1 = 4.98446 loss) +I0410 13:34:43.579383 18353 sgd_solver.cpp:105] Iteration 804, lr = 0.00852774 +I0410 13:34:45.254433 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:47.964468 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_816.caffemodel +I0410 13:34:48.275637 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_816.solverstate +I0410 13:34:48.481784 18353 solver.cpp:330] Iteration 816, Testing net (#0) +I0410 13:34:48.481817 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:34:52.561791 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:52.913844 18353 solver.cpp:397] Test net output #0: accuracy = 0.0343137 +I0410 13:34:52.913885 18353 solver.cpp:397] Test net output #1: loss = 4.85525 (* 1 = 4.85525 loss) +I0410 13:34:52.995776 18353 solver.cpp:218] Iteration 816 (1.27441 iter/s, 9.41611s/12 iters), loss = 4.96716 +I0410 13:34:52.995837 18353 solver.cpp:237] Train net output #0: loss = 4.96716 (* 1 = 4.96716 loss) +I0410 13:34:52.995851 18353 sgd_solver.cpp:105] Iteration 816, lr = 0.00850749 +I0410 13:34:57.119913 18353 solver.cpp:218] Iteration 828 (2.90984 iter/s, 4.12393s/12 iters), loss = 4.88911 +I0410 13:34:57.119980 18353 solver.cpp:237] Train net output #0: loss = 4.88911 (* 1 = 4.88911 loss) +I0410 13:34:57.119997 18353 sgd_solver.cpp:105] Iteration 828, lr = 0.00848729 +I0410 13:35:01.931084 18353 solver.cpp:218] Iteration 840 (2.49431 iter/s, 4.81095s/12 iters), loss = 4.71537 +I0410 13:35:01.931143 18353 solver.cpp:237] Train net output #0: loss = 4.71537 (* 1 = 4.71537 loss) +I0410 13:35:01.931156 18353 sgd_solver.cpp:105] Iteration 840, lr = 0.00846714 +I0410 13:35:06.700747 18353 solver.cpp:218] Iteration 852 (2.51601 iter/s, 4.76945s/12 iters), loss = 4.80388 +I0410 13:35:06.700796 18353 solver.cpp:237] Train net output #0: loss = 4.80388 (* 1 = 4.80388 loss) +I0410 13:35:06.700806 18353 sgd_solver.cpp:105] Iteration 852, lr = 0.00844704 +I0410 13:35:11.491523 18353 solver.cpp:218] Iteration 864 (2.50492 iter/s, 4.79057s/12 iters), loss = 4.85414 +I0410 13:35:11.491564 18353 solver.cpp:237] Train net output #0: loss = 4.85414 (* 1 = 4.85414 loss) +I0410 13:35:11.491572 18353 sgd_solver.cpp:105] Iteration 864, lr = 0.00842698 +I0410 13:35:16.550673 18353 solver.cpp:218] Iteration 876 (2.37203 iter/s, 5.05895s/12 iters), loss = 4.75736 +I0410 13:35:16.550779 18353 solver.cpp:237] Train net output #0: loss = 4.75736 (* 1 = 4.75736 loss) +I0410 13:35:16.550792 18353 sgd_solver.cpp:105] Iteration 876, lr = 0.00840698 +I0410 13:35:21.387084 18353 solver.cpp:218] Iteration 888 (2.48131 iter/s, 4.83615s/12 iters), loss = 4.78754 +I0410 13:35:21.387136 18353 solver.cpp:237] Train net output #0: loss = 4.78754 (* 1 = 4.78754 loss) +I0410 13:35:21.387148 18353 sgd_solver.cpp:105] Iteration 888, lr = 0.00838702 +I0410 13:35:26.289463 18353 solver.cpp:218] Iteration 900 (2.44789 iter/s, 4.90217s/12 iters), loss = 4.81667 +I0410 13:35:26.289520 18353 solver.cpp:237] Train net output #0: loss = 4.81667 (* 1 = 4.81667 loss) +I0410 13:35:26.289533 18353 sgd_solver.cpp:105] Iteration 900, lr = 0.0083671 +I0410 13:35:30.065737 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:31.124670 18353 solver.cpp:218] Iteration 912 (2.48191 iter/s, 4.835s/12 iters), loss = 4.73907 +I0410 13:35:31.124722 18353 solver.cpp:237] Train net output #0: loss = 4.73907 (* 1 = 4.73907 loss) +I0410 13:35:31.124734 18353 sgd_solver.cpp:105] Iteration 912, lr = 0.00834724 +I0410 13:35:33.094696 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_918.caffemodel +I0410 13:35:33.394491 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_918.solverstate +I0410 13:35:33.596521 18353 solver.cpp:330] Iteration 918, Testing net (#0) +I0410 13:35:33.596544 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:35:37.711308 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:38.109664 18353 solver.cpp:397] Test net output #0: accuracy = 0.0373775 +I0410 13:35:38.109706 18353 solver.cpp:397] Test net output #1: loss = 4.82748 (* 1 = 4.82748 loss) +I0410 13:35:39.923985 18353 solver.cpp:218] Iteration 924 (1.36379 iter/s, 8.799s/12 iters), loss = 4.6773 +I0410 13:35:39.924044 18353 solver.cpp:237] Train net output #0: loss = 4.6773 (* 1 = 4.6773 loss) +I0410 13:35:39.924057 18353 sgd_solver.cpp:105] Iteration 924, lr = 0.00832742 +I0410 13:35:44.744292 18353 solver.cpp:218] Iteration 936 (2.48958 iter/s, 4.82009s/12 iters), loss = 4.85176 +I0410 13:35:44.744346 18353 solver.cpp:237] Train net output #0: loss = 4.85176 (* 1 = 4.85176 loss) +I0410 13:35:44.744359 18353 sgd_solver.cpp:105] Iteration 936, lr = 0.00830765 +I0410 13:35:49.588932 18353 solver.cpp:218] Iteration 948 (2.47707 iter/s, 4.84443s/12 iters), loss = 4.65436 +I0410 13:35:49.589080 18353 solver.cpp:237] Train net output #0: loss = 4.65436 (* 1 = 4.65436 loss) +I0410 13:35:49.589095 18353 sgd_solver.cpp:105] Iteration 948, lr = 0.00828793 +I0410 13:35:54.423965 18353 solver.cpp:218] Iteration 960 (2.48204 iter/s, 4.83474s/12 iters), loss = 4.54211 +I0410 13:35:54.424005 18353 solver.cpp:237] Train net output #0: loss = 4.54211 (* 1 = 4.54211 loss) +I0410 13:35:54.424015 18353 sgd_solver.cpp:105] Iteration 960, lr = 0.00826825 +I0410 13:35:59.458235 18353 solver.cpp:218] Iteration 972 (2.38376 iter/s, 5.03407s/12 iters), loss = 4.77122 +I0410 13:35:59.458292 18353 solver.cpp:237] Train net output #0: loss = 4.77122 (* 1 = 4.77122 loss) +I0410 13:35:59.458305 18353 sgd_solver.cpp:105] Iteration 972, lr = 0.00824862 +I0410 13:36:04.366421 18353 solver.cpp:218] Iteration 984 (2.445 iter/s, 4.90798s/12 iters), loss = 4.70817 +I0410 13:36:04.366470 18353 solver.cpp:237] Train net output #0: loss = 4.70817 (* 1 = 4.70817 loss) +I0410 13:36:04.366480 18353 sgd_solver.cpp:105] Iteration 984, lr = 0.00822903 +I0410 13:36:09.243734 18353 solver.cpp:218] Iteration 996 (2.46048 iter/s, 4.87711s/12 iters), loss = 4.64167 +I0410 13:36:09.243793 18353 solver.cpp:237] Train net output #0: loss = 4.64167 (* 1 = 4.64167 loss) +I0410 13:36:09.243805 18353 sgd_solver.cpp:105] Iteration 996, lr = 0.0082095 +I0410 13:36:14.046546 18353 solver.cpp:218] Iteration 1008 (2.49864 iter/s, 4.8026s/12 iters), loss = 4.67439 +I0410 13:36:14.046598 18353 solver.cpp:237] Train net output #0: loss = 4.67439 (* 1 = 4.67439 loss) +I0410 13:36:14.046610 18353 sgd_solver.cpp:105] Iteration 1008, lr = 0.00819001 +I0410 13:36:15.039682 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:36:18.497021 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1020.caffemodel +I0410 13:36:18.807870 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1020.solverstate +I0410 13:36:19.018946 18353 solver.cpp:330] Iteration 1020, Testing net (#0) +I0410 13:36:19.018976 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:36:23.132321 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:36:23.568559 18353 solver.cpp:397] Test net output #0: accuracy = 0.0533088 +I0410 13:36:23.568611 18353 solver.cpp:397] Test net output #1: loss = 4.59366 (* 1 = 4.59366 loss) +I0410 13:36:23.650089 18353 solver.cpp:218] Iteration 1020 (1.24958 iter/s, 9.6032s/12 iters), loss = 4.48172 +I0410 13:36:23.650142 18353 solver.cpp:237] Train net output #0: loss = 4.48172 (* 1 = 4.48172 loss) +I0410 13:36:23.650156 18353 sgd_solver.cpp:105] Iteration 1020, lr = 0.00817056 +I0410 13:36:27.798918 18353 solver.cpp:218] Iteration 1032 (2.89251 iter/s, 4.14864s/12 iters), loss = 4.64712 +I0410 13:36:27.798966 18353 solver.cpp:237] Train net output #0: loss = 4.64712 (* 1 = 4.64712 loss) +I0410 13:36:27.798979 18353 sgd_solver.cpp:105] Iteration 1032, lr = 0.00815116 +I0410 13:36:32.693496 18353 solver.cpp:218] Iteration 1044 (2.45179 iter/s, 4.89438s/12 iters), loss = 4.70108 +I0410 13:36:32.693550 18353 solver.cpp:237] Train net output #0: loss = 4.70108 (* 1 = 4.70108 loss) +I0410 13:36:32.693563 18353 sgd_solver.cpp:105] Iteration 1044, lr = 0.00813181 +I0410 13:36:37.619858 18353 solver.cpp:218] Iteration 1056 (2.43598 iter/s, 4.92615s/12 iters), loss = 4.6028 +I0410 13:36:37.619915 18353 solver.cpp:237] Train net output #0: loss = 4.6028 (* 1 = 4.6028 loss) +I0410 13:36:37.619926 18353 sgd_solver.cpp:105] Iteration 1056, lr = 0.0081125 +I0410 13:36:42.535174 18353 solver.cpp:218] Iteration 1068 (2.44145 iter/s, 4.91511s/12 iters), loss = 4.64417 +I0410 13:36:42.535228 18353 solver.cpp:237] Train net output #0: loss = 4.64417 (* 1 = 4.64417 loss) +I0410 13:36:42.535241 18353 sgd_solver.cpp:105] Iteration 1068, lr = 0.00809324 +I0410 13:36:47.451942 18353 solver.cpp:218] Iteration 1080 (2.44073 iter/s, 4.91656s/12 iters), loss = 4.53593 +I0410 13:36:47.451985 18353 solver.cpp:237] Train net output #0: loss = 4.53593 (* 1 = 4.53593 loss) +I0410 13:36:47.451994 18353 sgd_solver.cpp:105] Iteration 1080, lr = 0.00807403 +I0410 13:36:52.483651 18353 solver.cpp:218] Iteration 1092 (2.38497 iter/s, 5.03151s/12 iters), loss = 4.45602 +I0410 13:36:52.483705 18353 solver.cpp:237] Train net output #0: loss = 4.45602 (* 1 = 4.45602 loss) +I0410 13:36:52.483717 18353 sgd_solver.cpp:105] Iteration 1092, lr = 0.00805486 +I0410 13:36:57.492077 18353 solver.cpp:218] Iteration 1104 (2.39606 iter/s, 5.00822s/12 iters), loss = 4.59711 +I0410 13:36:57.492154 18353 solver.cpp:237] Train net output #0: loss = 4.59711 (* 1 = 4.59711 loss) +I0410 13:36:57.492166 18353 sgd_solver.cpp:105] Iteration 1104, lr = 0.00803573 +I0410 13:37:00.640162 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:02.453686 18353 solver.cpp:218] Iteration 1116 (2.41869 iter/s, 4.96137s/12 iters), loss = 4.62401 +I0410 13:37:02.453737 18353 solver.cpp:237] Train net output #0: loss = 4.62401 (* 1 = 4.62401 loss) +I0410 13:37:02.453748 18353 sgd_solver.cpp:105] Iteration 1116, lr = 0.00801666 +I0410 13:37:04.474838 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1122.caffemodel +I0410 13:37:04.754909 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1122.solverstate +I0410 13:37:04.949824 18353 solver.cpp:330] Iteration 1122, Testing net (#0) +I0410 13:37:04.949854 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:37:08.948029 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:09.423416 18353 solver.cpp:397] Test net output #0: accuracy = 0.0618873 +I0410 13:37:09.423453 18353 solver.cpp:397] Test net output #1: loss = 4.50515 (* 1 = 4.50515 loss) +I0410 13:37:11.176360 18353 solver.cpp:218] Iteration 1128 (1.37577 iter/s, 8.72237s/12 iters), loss = 4.68809 +I0410 13:37:11.176407 18353 solver.cpp:237] Train net output #0: loss = 4.68809 (* 1 = 4.68809 loss) +I0410 13:37:11.176416 18353 sgd_solver.cpp:105] Iteration 1128, lr = 0.00799762 +I0410 13:37:16.089619 18353 solver.cpp:218] Iteration 1140 (2.44247 iter/s, 4.91305s/12 iters), loss = 4.60572 +I0410 13:37:16.089673 18353 solver.cpp:237] Train net output #0: loss = 4.60572 (* 1 = 4.60572 loss) +I0410 13:37:16.089686 18353 sgd_solver.cpp:105] Iteration 1140, lr = 0.00797863 +I0410 13:37:20.911170 18353 solver.cpp:218] Iteration 1152 (2.48893 iter/s, 4.82135s/12 iters), loss = 4.48119 +I0410 13:37:20.911224 18353 solver.cpp:237] Train net output #0: loss = 4.48119 (* 1 = 4.48119 loss) +I0410 13:37:20.911235 18353 sgd_solver.cpp:105] Iteration 1152, lr = 0.00795969 +I0410 13:37:25.809062 18353 solver.cpp:218] Iteration 1164 (2.45014 iter/s, 4.89768s/12 iters), loss = 4.35876 +I0410 13:37:25.809104 18353 solver.cpp:237] Train net output #0: loss = 4.35876 (* 1 = 4.35876 loss) +I0410 13:37:25.809114 18353 sgd_solver.cpp:105] Iteration 1164, lr = 0.00794079 +I0410 13:37:30.644976 18353 solver.cpp:218] Iteration 1176 (2.48154 iter/s, 4.83571s/12 iters), loss = 4.37241 +I0410 13:37:30.645107 18353 solver.cpp:237] Train net output #0: loss = 4.37241 (* 1 = 4.37241 loss) +I0410 13:37:30.645121 18353 sgd_solver.cpp:105] Iteration 1176, lr = 0.00792194 +I0410 13:37:35.573251 18353 solver.cpp:218] Iteration 1188 (2.43507 iter/s, 4.928s/12 iters), loss = 4.40613 +I0410 13:37:35.573300 18353 solver.cpp:237] Train net output #0: loss = 4.40613 (* 1 = 4.40613 loss) +I0410 13:37:35.573312 18353 sgd_solver.cpp:105] Iteration 1188, lr = 0.00790313 +I0410 13:37:40.533994 18353 solver.cpp:218] Iteration 1200 (2.41909 iter/s, 4.96054s/12 iters), loss = 4.58569 +I0410 13:37:40.534050 18353 solver.cpp:237] Train net output #0: loss = 4.58569 (* 1 = 4.58569 loss) +I0410 13:37:40.534062 18353 sgd_solver.cpp:105] Iteration 1200, lr = 0.00788437 +I0410 13:37:45.471169 18353 solver.cpp:218] Iteration 1212 (2.43065 iter/s, 4.93696s/12 iters), loss = 4.41038 +I0410 13:37:45.471222 18353 solver.cpp:237] Train net output #0: loss = 4.41038 (* 1 = 4.41038 loss) +I0410 13:37:45.471232 18353 sgd_solver.cpp:105] Iteration 1212, lr = 0.00786565 +I0410 13:37:45.757951 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:49.949860 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1224.caffemodel +I0410 13:37:50.502624 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1224.solverstate +I0410 13:37:50.986214 18353 solver.cpp:330] Iteration 1224, Testing net (#0) +I0410 13:37:50.986243 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:37:55.041323 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:55.559275 18353 solver.cpp:397] Test net output #0: accuracy = 0.0821078 +I0410 13:37:55.559316 18353 solver.cpp:397] Test net output #1: loss = 4.33798 (* 1 = 4.33798 loss) +I0410 13:37:55.640758 18353 solver.cpp:218] Iteration 1224 (1.18003 iter/s, 10.1692s/12 iters), loss = 4.43361 +I0410 13:37:55.640801 18353 solver.cpp:237] Train net output #0: loss = 4.43361 (* 1 = 4.43361 loss) +I0410 13:37:55.640811 18353 sgd_solver.cpp:105] Iteration 1224, lr = 0.00784697 +I0410 13:37:59.775192 18353 solver.cpp:218] Iteration 1236 (2.90257 iter/s, 4.13426s/12 iters), loss = 4.6099 +I0410 13:37:59.775240 18353 solver.cpp:237] Train net output #0: loss = 4.6099 (* 1 = 4.6099 loss) +I0410 13:37:59.775251 18353 sgd_solver.cpp:105] Iteration 1236, lr = 0.00782834 +I0410 13:38:04.626315 18353 solver.cpp:218] Iteration 1248 (2.47376 iter/s, 4.85092s/12 iters), loss = 4.18499 +I0410 13:38:04.626439 18353 solver.cpp:237] Train net output #0: loss = 4.18499 (* 1 = 4.18499 loss) +I0410 13:38:04.626456 18353 sgd_solver.cpp:105] Iteration 1248, lr = 0.00780976 +I0410 13:38:09.543071 18353 solver.cpp:218] Iteration 1260 (2.44077 iter/s, 4.91648s/12 iters), loss = 4.39298 +I0410 13:38:09.543125 18353 solver.cpp:237] Train net output #0: loss = 4.39298 (* 1 = 4.39298 loss) +I0410 13:38:09.543138 18353 sgd_solver.cpp:105] Iteration 1260, lr = 0.00779122 +I0410 13:38:14.472416 18353 solver.cpp:218] Iteration 1272 (2.4345 iter/s, 4.92914s/12 iters), loss = 4.3046 +I0410 13:38:14.472456 18353 solver.cpp:237] Train net output #0: loss = 4.3046 (* 1 = 4.3046 loss) +I0410 13:38:14.472465 18353 sgd_solver.cpp:105] Iteration 1272, lr = 0.00777272 +I0410 13:38:19.426360 18353 solver.cpp:218] Iteration 1284 (2.42241 iter/s, 4.95375s/12 iters), loss = 4.3607 +I0410 13:38:19.426411 18353 solver.cpp:237] Train net output #0: loss = 4.3607 (* 1 = 4.3607 loss) +I0410 13:38:19.426425 18353 sgd_solver.cpp:105] Iteration 1284, lr = 0.00775426 +I0410 13:38:24.272773 18353 solver.cpp:218] Iteration 1296 (2.47616 iter/s, 4.84621s/12 iters), loss = 4.22866 +I0410 13:38:24.272830 18353 solver.cpp:237] Train net output #0: loss = 4.22866 (* 1 = 4.22866 loss) +I0410 13:38:24.272841 18353 sgd_solver.cpp:105] Iteration 1296, lr = 0.00773585 +I0410 13:38:29.202837 18353 solver.cpp:218] Iteration 1308 (2.43415 iter/s, 4.92985s/12 iters), loss = 4.39708 +I0410 13:38:29.202890 18353 solver.cpp:237] Train net output #0: loss = 4.39708 (* 1 = 4.39708 loss) +I0410 13:38:29.202904 18353 sgd_solver.cpp:105] Iteration 1308, lr = 0.00771749 +I0410 13:38:31.676445 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:38:34.110857 18353 solver.cpp:218] Iteration 1320 (2.44508 iter/s, 4.90781s/12 iters), loss = 4.19353 +I0410 13:38:34.110908 18353 solver.cpp:237] Train net output #0: loss = 4.19353 (* 1 = 4.19353 loss) +I0410 13:38:34.110919 18353 sgd_solver.cpp:105] Iteration 1320, lr = 0.00769916 +I0410 13:38:36.096741 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1326.caffemodel +I0410 13:38:36.396412 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1326.solverstate +I0410 13:38:36.589812 18353 solver.cpp:330] Iteration 1326, Testing net (#0) +I0410 13:38:36.589830 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:38:40.607465 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:38:41.160753 18353 solver.cpp:397] Test net output #0: accuracy = 0.0925245 +I0410 13:38:41.160801 18353 solver.cpp:397] Test net output #1: loss = 4.22254 (* 1 = 4.22254 loss) +I0410 13:38:43.092739 18353 solver.cpp:218] Iteration 1332 (1.33607 iter/s, 8.98156s/12 iters), loss = 4.08108 +I0410 13:38:43.092788 18353 solver.cpp:237] Train net output #0: loss = 4.08108 (* 1 = 4.08108 loss) +I0410 13:38:43.092798 18353 sgd_solver.cpp:105] Iteration 1332, lr = 0.00768088 +I0410 13:38:48.032351 18353 solver.cpp:218] Iteration 1344 (2.42944 iter/s, 4.9394s/12 iters), loss = 4.26138 +I0410 13:38:48.032408 18353 solver.cpp:237] Train net output #0: loss = 4.26138 (* 1 = 4.26138 loss) +I0410 13:38:48.032421 18353 sgd_solver.cpp:105] Iteration 1344, lr = 0.00766265 +I0410 13:38:52.917798 18353 solver.cpp:218] Iteration 1356 (2.45638 iter/s, 4.88524s/12 iters), loss = 4.31353 +I0410 13:38:52.917843 18353 solver.cpp:237] Train net output #0: loss = 4.31353 (* 1 = 4.31353 loss) +I0410 13:38:52.917852 18353 sgd_solver.cpp:105] Iteration 1356, lr = 0.00764446 +I0410 13:38:57.325448 18353 blocking_queue.cpp:49] Waiting for data +I0410 13:38:57.770942 18353 solver.cpp:218] Iteration 1368 (2.47273 iter/s, 4.85294s/12 iters), loss = 4.20193 +I0410 13:38:57.770992 18353 solver.cpp:237] Train net output #0: loss = 4.20193 (* 1 = 4.20193 loss) +I0410 13:38:57.771003 18353 sgd_solver.cpp:105] Iteration 1368, lr = 0.00762631 +I0410 13:39:02.608240 18353 solver.cpp:218] Iteration 1380 (2.48082 iter/s, 4.8371s/12 iters), loss = 4.21117 +I0410 13:39:02.608279 18353 solver.cpp:237] Train net output #0: loss = 4.21117 (* 1 = 4.21117 loss) +I0410 13:39:02.608289 18353 sgd_solver.cpp:105] Iteration 1380, lr = 0.0076082 +I0410 13:39:07.547163 18353 solver.cpp:218] Iteration 1392 (2.42978 iter/s, 4.93873s/12 iters), loss = 4.16942 +I0410 13:39:07.547271 18353 solver.cpp:237] Train net output #0: loss = 4.16942 (* 1 = 4.16942 loss) +I0410 13:39:07.547281 18353 sgd_solver.cpp:105] Iteration 1392, lr = 0.00759014 +I0410 13:39:12.453647 18353 solver.cpp:218] Iteration 1404 (2.44587 iter/s, 4.90622s/12 iters), loss = 4.22309 +I0410 13:39:12.453701 18353 solver.cpp:237] Train net output #0: loss = 4.22309 (* 1 = 4.22309 loss) +I0410 13:39:12.453712 18353 sgd_solver.cpp:105] Iteration 1404, lr = 0.00757212 +I0410 13:39:17.010244 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:17.359277 18353 solver.cpp:218] Iteration 1416 (2.44627 iter/s, 4.90542s/12 iters), loss = 3.94939 +I0410 13:39:17.359330 18353 solver.cpp:237] Train net output #0: loss = 3.94939 (* 1 = 3.94939 loss) +I0410 13:39:17.359344 18353 sgd_solver.cpp:105] Iteration 1416, lr = 0.00755414 +I0410 13:39:21.817418 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1428.caffemodel +I0410 13:39:22.135938 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1428.solverstate +I0410 13:39:22.343071 18353 solver.cpp:330] Iteration 1428, Testing net (#0) +I0410 13:39:22.343102 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:39:26.068014 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:26.656471 18353 solver.cpp:397] Test net output #0: accuracy = 0.113358 +I0410 13:39:26.656498 18353 solver.cpp:397] Test net output #1: loss = 4.07387 (* 1 = 4.07387 loss) +I0410 13:39:26.737921 18353 solver.cpp:218] Iteration 1428 (1.27955 iter/s, 9.37831s/12 iters), loss = 3.9925 +I0410 13:39:26.737987 18353 solver.cpp:237] Train net output #0: loss = 3.9925 (* 1 = 3.9925 loss) +I0410 13:39:26.737998 18353 sgd_solver.cpp:105] Iteration 1428, lr = 0.0075362 +I0410 13:39:30.876267 18353 solver.cpp:218] Iteration 1440 (2.89985 iter/s, 4.13815s/12 iters), loss = 4.00927 +I0410 13:39:30.876308 18353 solver.cpp:237] Train net output #0: loss = 4.00927 (* 1 = 4.00927 loss) +I0410 13:39:30.876318 18353 sgd_solver.cpp:105] Iteration 1440, lr = 0.00751831 +I0410 13:39:35.772658 18353 solver.cpp:218] Iteration 1452 (2.45088 iter/s, 4.8962s/12 iters), loss = 4.25292 +I0410 13:39:35.772702 18353 solver.cpp:237] Train net output #0: loss = 4.25292 (* 1 = 4.25292 loss) +I0410 13:39:35.772711 18353 sgd_solver.cpp:105] Iteration 1452, lr = 0.00750046 +I0410 13:39:40.680783 18353 solver.cpp:218] Iteration 1464 (2.44503 iter/s, 4.90792s/12 iters), loss = 4.13796 +I0410 13:39:40.680928 18353 solver.cpp:237] Train net output #0: loss = 4.13796 (* 1 = 4.13796 loss) +I0410 13:39:40.680941 18353 sgd_solver.cpp:105] Iteration 1464, lr = 0.00748265 +I0410 13:39:45.617790 18353 solver.cpp:218] Iteration 1476 (2.43077 iter/s, 4.93671s/12 iters), loss = 3.93171 +I0410 13:39:45.617837 18353 solver.cpp:237] Train net output #0: loss = 3.93171 (* 1 = 3.93171 loss) +I0410 13:39:45.617847 18353 sgd_solver.cpp:105] Iteration 1476, lr = 0.00746489 +I0410 13:39:50.546298 18353 solver.cpp:218] Iteration 1488 (2.43492 iter/s, 4.9283s/12 iters), loss = 3.89786 +I0410 13:39:50.546350 18353 solver.cpp:237] Train net output #0: loss = 3.89786 (* 1 = 3.89786 loss) +I0410 13:39:50.546362 18353 sgd_solver.cpp:105] Iteration 1488, lr = 0.00744716 +I0410 13:39:55.458495 18353 solver.cpp:218] Iteration 1500 (2.443 iter/s, 4.91199s/12 iters), loss = 3.89558 +I0410 13:39:55.458544 18353 solver.cpp:237] Train net output #0: loss = 3.89558 (* 1 = 3.89558 loss) +I0410 13:39:55.458556 18353 sgd_solver.cpp:105] Iteration 1500, lr = 0.00742948 +I0410 13:40:00.541422 18353 solver.cpp:218] Iteration 1512 (2.36094 iter/s, 5.08272s/12 iters), loss = 4.24201 +I0410 13:40:00.541481 18353 solver.cpp:237] Train net output #0: loss = 4.24201 (* 1 = 4.24201 loss) +I0410 13:40:00.541493 18353 sgd_solver.cpp:105] Iteration 1512, lr = 0.00741184 +I0410 13:40:02.387243 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:05.494568 18353 solver.cpp:218] Iteration 1524 (2.42281 iter/s, 4.95294s/12 iters), loss = 3.88614 +I0410 13:40:05.494621 18353 solver.cpp:237] Train net output #0: loss = 3.88614 (* 1 = 3.88614 loss) +I0410 13:40:05.494635 18353 sgd_solver.cpp:105] Iteration 1524, lr = 0.00739425 +I0410 13:40:07.469264 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1530.caffemodel +I0410 13:40:07.804294 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1530.solverstate +I0410 13:40:08.016763 18353 solver.cpp:330] Iteration 1530, Testing net (#0) +I0410 13:40:08.016788 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:40:11.729600 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:12.464538 18353 solver.cpp:397] Test net output #0: accuracy = 0.137255 +I0410 13:40:12.464588 18353 solver.cpp:397] Test net output #1: loss = 3.90476 (* 1 = 3.90476 loss) +I0410 13:40:14.335297 18353 solver.cpp:218] Iteration 1536 (1.3574 iter/s, 8.84041s/12 iters), loss = 3.96422 +I0410 13:40:14.335341 18353 solver.cpp:237] Train net output #0: loss = 3.96422 (* 1 = 3.96422 loss) +I0410 13:40:14.335351 18353 sgd_solver.cpp:105] Iteration 1536, lr = 0.00737669 +I0410 13:40:19.278291 18353 solver.cpp:218] Iteration 1548 (2.42778 iter/s, 4.94279s/12 iters), loss = 3.58958 +I0410 13:40:19.278337 18353 solver.cpp:237] Train net output #0: loss = 3.58958 (* 1 = 3.58958 loss) +I0410 13:40:19.278347 18353 sgd_solver.cpp:105] Iteration 1548, lr = 0.00735918 +I0410 13:40:24.118413 18353 solver.cpp:218] Iteration 1560 (2.47938 iter/s, 4.83992s/12 iters), loss = 3.97728 +I0410 13:40:24.118463 18353 solver.cpp:237] Train net output #0: loss = 3.97728 (* 1 = 3.97728 loss) +I0410 13:40:24.118472 18353 sgd_solver.cpp:105] Iteration 1560, lr = 0.00734171 +I0410 13:40:29.011102 18353 solver.cpp:218] Iteration 1572 (2.45274 iter/s, 4.89249s/12 iters), loss = 3.94714 +I0410 13:40:29.011143 18353 solver.cpp:237] Train net output #0: loss = 3.94714 (* 1 = 3.94714 loss) +I0410 13:40:29.011153 18353 sgd_solver.cpp:105] Iteration 1572, lr = 0.00732427 +I0410 13:40:33.987452 18353 solver.cpp:218] Iteration 1584 (2.4115 iter/s, 4.97615s/12 iters), loss = 3.82087 +I0410 13:40:33.987505 18353 solver.cpp:237] Train net output #0: loss = 3.82087 (* 1 = 3.82087 loss) +I0410 13:40:33.987517 18353 sgd_solver.cpp:105] Iteration 1584, lr = 0.00730688 +I0410 13:40:38.878487 18353 solver.cpp:218] Iteration 1596 (2.45357 iter/s, 4.89083s/12 iters), loss = 4.012 +I0410 13:40:38.878545 18353 solver.cpp:237] Train net output #0: loss = 4.012 (* 1 = 4.012 loss) +I0410 13:40:38.878556 18353 sgd_solver.cpp:105] Iteration 1596, lr = 0.00728954 +I0410 13:40:43.726186 18353 solver.cpp:218] Iteration 1608 (2.47551 iter/s, 4.84749s/12 iters), loss = 3.94032 +I0410 13:40:43.726284 18353 solver.cpp:237] Train net output #0: loss = 3.94032 (* 1 = 3.94032 loss) +I0410 13:40:43.726296 18353 sgd_solver.cpp:105] Iteration 1608, lr = 0.00727223 +I0410 13:40:47.515481 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:48.551498 18353 solver.cpp:218] Iteration 1620 (2.48702 iter/s, 4.82506s/12 iters), loss = 3.70949 +I0410 13:40:48.551556 18353 solver.cpp:237] Train net output #0: loss = 3.70949 (* 1 = 3.70949 loss) +I0410 13:40:48.551569 18353 sgd_solver.cpp:105] Iteration 1620, lr = 0.00725496 +I0410 13:40:53.048491 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1632.caffemodel +I0410 13:40:53.587656 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1632.solverstate +I0410 13:40:54.727617 18353 solver.cpp:330] Iteration 1632, Testing net (#0) +I0410 13:40:54.727634 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:40:58.506417 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:59.173230 18353 solver.cpp:397] Test net output #0: accuracy = 0.134804 +I0410 13:40:59.173285 18353 solver.cpp:397] Test net output #1: loss = 3.85261 (* 1 = 3.85261 loss) +I0410 13:40:59.254660 18353 solver.cpp:218] Iteration 1632 (1.1212 iter/s, 10.7028s/12 iters), loss = 3.87986 +I0410 13:40:59.254710 18353 solver.cpp:237] Train net output #0: loss = 3.87986 (* 1 = 3.87986 loss) +I0410 13:40:59.254721 18353 sgd_solver.cpp:105] Iteration 1632, lr = 0.00723774 +I0410 13:41:03.418031 18353 solver.cpp:218] Iteration 1644 (2.88241 iter/s, 4.16318s/12 iters), loss = 3.79865 +I0410 13:41:03.418089 18353 solver.cpp:237] Train net output #0: loss = 3.79865 (* 1 = 3.79865 loss) +I0410 13:41:03.418102 18353 sgd_solver.cpp:105] Iteration 1644, lr = 0.00722056 +I0410 13:41:08.300027 18353 solver.cpp:218] Iteration 1656 (2.45811 iter/s, 4.88179s/12 iters), loss = 3.72162 +I0410 13:41:08.300071 18353 solver.cpp:237] Train net output #0: loss = 3.72162 (* 1 = 3.72162 loss) +I0410 13:41:08.300081 18353 sgd_solver.cpp:105] Iteration 1656, lr = 0.00720341 +I0410 13:41:13.156759 18353 solver.cpp:218] Iteration 1668 (2.4709 iter/s, 4.85653s/12 iters), loss = 3.82464 +I0410 13:41:13.156822 18353 solver.cpp:237] Train net output #0: loss = 3.82464 (* 1 = 3.82464 loss) +I0410 13:41:13.156836 18353 sgd_solver.cpp:105] Iteration 1668, lr = 0.00718631 +I0410 13:41:17.953485 18353 solver.cpp:218] Iteration 1680 (2.50182 iter/s, 4.79651s/12 iters), loss = 3.6154 +I0410 13:41:17.953616 18353 solver.cpp:237] Train net output #0: loss = 3.6154 (* 1 = 3.6154 loss) +I0410 13:41:17.953629 18353 sgd_solver.cpp:105] Iteration 1680, lr = 0.00716925 +I0410 13:41:22.817329 18353 solver.cpp:218] Iteration 1692 (2.46733 iter/s, 4.86356s/12 iters), loss = 3.70805 +I0410 13:41:22.817382 18353 solver.cpp:237] Train net output #0: loss = 3.70805 (* 1 = 3.70805 loss) +I0410 13:41:22.817394 18353 sgd_solver.cpp:105] Iteration 1692, lr = 0.00715223 +I0410 13:41:28.040139 18353 solver.cpp:218] Iteration 1704 (2.29771 iter/s, 5.2226s/12 iters), loss = 3.63719 +I0410 13:41:28.040184 18353 solver.cpp:237] Train net output #0: loss = 3.63719 (* 1 = 3.63719 loss) +I0410 13:41:28.040195 18353 sgd_solver.cpp:105] Iteration 1704, lr = 0.00713525 +I0410 13:41:32.973126 18353 solver.cpp:218] Iteration 1716 (2.4327 iter/s, 4.93279s/12 iters), loss = 3.76967 +I0410 13:41:32.973171 18353 solver.cpp:237] Train net output #0: loss = 3.76967 (* 1 = 3.76967 loss) +I0410 13:41:32.973183 18353 sgd_solver.cpp:105] Iteration 1716, lr = 0.00711831 +I0410 13:41:34.024582 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:41:37.854669 18353 solver.cpp:218] Iteration 1728 (2.45834 iter/s, 4.88134s/12 iters), loss = 3.58911 +I0410 13:41:37.854710 18353 solver.cpp:237] Train net output #0: loss = 3.58911 (* 1 = 3.58911 loss) +I0410 13:41:37.854719 18353 sgd_solver.cpp:105] Iteration 1728, lr = 0.00710141 +I0410 13:41:39.882814 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1734.caffemodel +I0410 13:41:40.201253 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1734.solverstate +I0410 13:41:40.414444 18353 solver.cpp:330] Iteration 1734, Testing net (#0) +I0410 13:41:40.414474 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:41:44.277782 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:41:44.980921 18353 solver.cpp:397] Test net output #0: accuracy = 0.14277 +I0410 13:41:44.980959 18353 solver.cpp:397] Test net output #1: loss = 3.87625 (* 1 = 3.87625 loss) +I0410 13:41:46.837123 18353 solver.cpp:218] Iteration 1740 (1.33598 iter/s, 8.98214s/12 iters), loss = 3.84722 +I0410 13:41:46.837177 18353 solver.cpp:237] Train net output #0: loss = 3.84722 (* 1 = 3.84722 loss) +I0410 13:41:46.837188 18353 sgd_solver.cpp:105] Iteration 1740, lr = 0.00708455 +I0410 13:41:51.844434 18353 solver.cpp:218] Iteration 1752 (2.3966 iter/s, 5.0071s/12 iters), loss = 3.40985 +I0410 13:41:51.844528 18353 solver.cpp:237] Train net output #0: loss = 3.40985 (* 1 = 3.40985 loss) +I0410 13:41:51.844542 18353 sgd_solver.cpp:105] Iteration 1752, lr = 0.00706773 +I0410 13:41:56.829865 18353 solver.cpp:218] Iteration 1764 (2.40713 iter/s, 4.98519s/12 iters), loss = 3.97024 +I0410 13:41:56.829910 18353 solver.cpp:237] Train net output #0: loss = 3.97024 (* 1 = 3.97024 loss) +I0410 13:41:56.829921 18353 sgd_solver.cpp:105] Iteration 1764, lr = 0.00705094 +I0410 13:42:02.075752 18353 solver.cpp:218] Iteration 1776 (2.2876 iter/s, 5.24567s/12 iters), loss = 3.77286 +I0410 13:42:02.075809 18353 solver.cpp:237] Train net output #0: loss = 3.77286 (* 1 = 3.77286 loss) +I0410 13:42:02.075822 18353 sgd_solver.cpp:105] Iteration 1776, lr = 0.0070342 +I0410 13:42:06.938032 18353 solver.cpp:218] Iteration 1788 (2.46808 iter/s, 4.86208s/12 iters), loss = 3.76638 +I0410 13:42:06.938074 18353 solver.cpp:237] Train net output #0: loss = 3.76638 (* 1 = 3.76638 loss) +I0410 13:42:06.938084 18353 sgd_solver.cpp:105] Iteration 1788, lr = 0.0070175 +I0410 13:42:11.837436 18353 solver.cpp:218] Iteration 1800 (2.44938 iter/s, 4.89921s/12 iters), loss = 3.57106 +I0410 13:42:11.837489 18353 solver.cpp:237] Train net output #0: loss = 3.57106 (* 1 = 3.57106 loss) +I0410 13:42:11.837500 18353 sgd_solver.cpp:105] Iteration 1800, lr = 0.00700084 +I0410 13:42:16.718386 18353 solver.cpp:218] Iteration 1812 (2.45864 iter/s, 4.88075s/12 iters), loss = 3.52729 +I0410 13:42:16.718434 18353 solver.cpp:237] Train net output #0: loss = 3.52729 (* 1 = 3.52729 loss) +I0410 13:42:16.718444 18353 sgd_solver.cpp:105] Iteration 1812, lr = 0.00698422 +I0410 13:42:19.894408 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:42:21.687791 18353 solver.cpp:218] Iteration 1824 (2.41488 iter/s, 4.9692s/12 iters), loss = 3.67844 +I0410 13:42:21.687844 18353 solver.cpp:237] Train net output #0: loss = 3.67844 (* 1 = 3.67844 loss) +I0410 13:42:21.687856 18353 sgd_solver.cpp:105] Iteration 1824, lr = 0.00696764 +I0410 13:42:26.144304 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1836.caffemodel +I0410 13:42:26.472425 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1836.solverstate +I0410 13:42:26.679661 18353 solver.cpp:330] Iteration 1836, Testing net (#0) +I0410 13:42:26.679682 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:42:30.356231 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:42:31.101539 18353 solver.cpp:397] Test net output #0: accuracy = 0.181985 +I0410 13:42:31.101572 18353 solver.cpp:397] Test net output #1: loss = 3.57133 (* 1 = 3.57133 loss) +I0410 13:42:31.182651 18353 solver.cpp:218] Iteration 1836 (1.26389 iter/s, 9.49453s/12 iters), loss = 3.61837 +I0410 13:42:31.182695 18353 solver.cpp:237] Train net output #0: loss = 3.61837 (* 1 = 3.61837 loss) +I0410 13:42:31.182705 18353 sgd_solver.cpp:105] Iteration 1836, lr = 0.0069511 +I0410 13:42:35.476176 18353 solver.cpp:218] Iteration 1848 (2.79502 iter/s, 4.29334s/12 iters), loss = 3.5673 +I0410 13:42:35.476222 18353 solver.cpp:237] Train net output #0: loss = 3.5673 (* 1 = 3.5673 loss) +I0410 13:42:35.476231 18353 sgd_solver.cpp:105] Iteration 1848, lr = 0.00693459 +I0410 13:42:40.317862 18353 solver.cpp:218] Iteration 1860 (2.47858 iter/s, 4.84148s/12 iters), loss = 3.50609 +I0410 13:42:40.317921 18353 solver.cpp:237] Train net output #0: loss = 3.50609 (* 1 = 3.50609 loss) +I0410 13:42:40.317936 18353 sgd_solver.cpp:105] Iteration 1860, lr = 0.00691813 +I0410 13:42:45.256816 18353 solver.cpp:218] Iteration 1872 (2.42977 iter/s, 4.93875s/12 iters), loss = 3.50338 +I0410 13:42:45.256868 18353 solver.cpp:237] Train net output #0: loss = 3.50338 (* 1 = 3.50338 loss) +I0410 13:42:45.256880 18353 sgd_solver.cpp:105] Iteration 1872, lr = 0.0069017 +I0410 13:42:50.117719 18353 solver.cpp:218] Iteration 1884 (2.46878 iter/s, 4.8607s/12 iters), loss = 3.72516 +I0410 13:42:50.117775 18353 solver.cpp:237] Train net output #0: loss = 3.72516 (* 1 = 3.72516 loss) +I0410 13:42:50.117789 18353 sgd_solver.cpp:105] Iteration 1884, lr = 0.00688532 +I0410 13:42:55.027396 18353 solver.cpp:218] Iteration 1896 (2.44425 iter/s, 4.90948s/12 iters), loss = 3.54669 +I0410 13:42:55.027437 18353 solver.cpp:237] Train net output #0: loss = 3.54669 (* 1 = 3.54669 loss) +I0410 13:42:55.027446 18353 sgd_solver.cpp:105] Iteration 1896, lr = 0.00686897 +I0410 13:42:59.966117 18353 solver.cpp:218] Iteration 1908 (2.42988 iter/s, 4.93852s/12 iters), loss = 3.47008 +I0410 13:42:59.966264 18353 solver.cpp:237] Train net output #0: loss = 3.47008 (* 1 = 3.47008 loss) +I0410 13:42:59.966279 18353 sgd_solver.cpp:105] Iteration 1908, lr = 0.00685266 +I0410 13:43:04.878981 18353 solver.cpp:218] Iteration 1920 (2.44271 iter/s, 4.91257s/12 iters), loss = 3.47177 +I0410 13:43:04.879034 18353 solver.cpp:237] Train net output #0: loss = 3.47177 (* 1 = 3.47177 loss) +I0410 13:43:04.879047 18353 sgd_solver.cpp:105] Iteration 1920, lr = 0.00683639 +I0410 13:43:05.200683 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:43:09.914070 18353 solver.cpp:218] Iteration 1932 (2.38337 iter/s, 5.03488s/12 iters), loss = 3.45598 +I0410 13:43:09.914124 18353 solver.cpp:237] Train net output #0: loss = 3.45598 (* 1 = 3.45598 loss) +I0410 13:43:09.914136 18353 sgd_solver.cpp:105] Iteration 1932, lr = 0.00682016 +I0410 13:43:11.965885 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1938.caffemodel +I0410 13:43:12.583484 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1938.solverstate +I0410 13:43:12.794668 18353 solver.cpp:330] Iteration 1938, Testing net (#0) +I0410 13:43:12.794689 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:43:16.462787 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:43:17.245687 18353 solver.cpp:397] Test net output #0: accuracy = 0.205882 +I0410 13:43:17.245723 18353 solver.cpp:397] Test net output #1: loss = 3.39654 (* 1 = 3.39654 loss) +I0410 13:43:19.125082 18353 solver.cpp:218] Iteration 1944 (1.30283 iter/s, 9.21069s/12 iters), loss = 3.3937 +I0410 13:43:19.125131 18353 solver.cpp:237] Train net output #0: loss = 3.3937 (* 1 = 3.3937 loss) +I0410 13:43:19.125142 18353 sgd_solver.cpp:105] Iteration 1944, lr = 0.00680397 +I0410 13:43:24.038681 18353 solver.cpp:218] Iteration 1956 (2.4423 iter/s, 4.91339s/12 iters), loss = 3.51245 +I0410 13:43:24.038736 18353 solver.cpp:237] Train net output #0: loss = 3.51245 (* 1 = 3.51245 loss) +I0410 13:43:24.038748 18353 sgd_solver.cpp:105] Iteration 1956, lr = 0.00678782 +I0410 13:43:28.933876 18353 solver.cpp:218] Iteration 1968 (2.45149 iter/s, 4.89498s/12 iters), loss = 3.3223 +I0410 13:43:28.933933 18353 solver.cpp:237] Train net output #0: loss = 3.3223 (* 1 = 3.3223 loss) +I0410 13:43:28.933944 18353 sgd_solver.cpp:105] Iteration 1968, lr = 0.0067717 +I0410 13:43:33.843350 18353 solver.cpp:218] Iteration 1980 (2.44435 iter/s, 4.90927s/12 iters), loss = 3.47218 +I0410 13:43:33.843729 18353 solver.cpp:237] Train net output #0: loss = 3.47218 (* 1 = 3.47218 loss) +I0410 13:43:33.843742 18353 sgd_solver.cpp:105] Iteration 1980, lr = 0.00675562 +I0410 13:43:38.981032 18353 solver.cpp:218] Iteration 1992 (2.33593 iter/s, 5.13715s/12 iters), loss = 3.44798 +I0410 13:43:38.981092 18353 solver.cpp:237] Train net output #0: loss = 3.44798 (* 1 = 3.44798 loss) +I0410 13:43:38.981106 18353 sgd_solver.cpp:105] Iteration 1992, lr = 0.00673958 +I0410 13:43:43.805471 18353 solver.cpp:218] Iteration 2004 (2.48744 iter/s, 4.82423s/12 iters), loss = 3.23588 +I0410 13:43:43.805527 18353 solver.cpp:237] Train net output #0: loss = 3.23588 (* 1 = 3.23588 loss) +I0410 13:43:43.805541 18353 sgd_solver.cpp:105] Iteration 2004, lr = 0.00672358 +I0410 13:43:48.728796 18353 solver.cpp:218] Iteration 2016 (2.43748 iter/s, 4.92312s/12 iters), loss = 3.44223 +I0410 13:43:48.728847 18353 solver.cpp:237] Train net output #0: loss = 3.44223 (* 1 = 3.44223 loss) +I0410 13:43:48.728861 18353 sgd_solver.cpp:105] Iteration 2016, lr = 0.00670762 +I0410 13:43:51.216867 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:43:53.614385 18353 solver.cpp:218] Iteration 2028 (2.4563 iter/s, 4.88539s/12 iters), loss = 2.93948 +I0410 13:43:53.614442 18353 solver.cpp:237] Train net output #0: loss = 2.93948 (* 1 = 2.93948 loss) +I0410 13:43:53.614454 18353 sgd_solver.cpp:105] Iteration 2028, lr = 0.00669169 +I0410 13:43:58.062755 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2040.caffemodel +I0410 13:43:58.346411 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2040.solverstate +I0410 13:43:58.540051 18353 solver.cpp:330] Iteration 2040, Testing net (#0) +I0410 13:43:58.540076 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:44:02.197772 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:03.036087 18353 solver.cpp:397] Test net output #0: accuracy = 0.224265 +I0410 13:44:03.036150 18353 solver.cpp:397] Test net output #1: loss = 3.28762 (* 1 = 3.28762 loss) +I0410 13:44:03.117566 18353 solver.cpp:218] Iteration 2040 (1.26278 iter/s, 9.50285s/12 iters), loss = 3.17692 +I0410 13:44:03.117614 18353 solver.cpp:237] Train net output #0: loss = 3.17692 (* 1 = 3.17692 loss) +I0410 13:44:03.117627 18353 sgd_solver.cpp:105] Iteration 2040, lr = 0.00667581 +I0410 13:44:07.486397 18353 solver.cpp:218] Iteration 2052 (2.74684 iter/s, 4.36865s/12 iters), loss = 3.36455 +I0410 13:44:07.486559 18353 solver.cpp:237] Train net output #0: loss = 3.36455 (* 1 = 3.36455 loss) +I0410 13:44:07.486572 18353 sgd_solver.cpp:105] Iteration 2052, lr = 0.00665996 +I0410 13:44:07.486806 18353 blocking_queue.cpp:49] Waiting for data +I0410 13:44:12.308060 18353 solver.cpp:218] Iteration 2064 (2.48893 iter/s, 4.82136s/12 iters), loss = 3.27496 +I0410 13:44:12.308107 18353 solver.cpp:237] Train net output #0: loss = 3.27496 (* 1 = 3.27496 loss) +I0410 13:44:12.308117 18353 sgd_solver.cpp:105] Iteration 2064, lr = 0.00664414 +I0410 13:44:17.437088 18353 solver.cpp:218] Iteration 2076 (2.33972 iter/s, 5.12882s/12 iters), loss = 3.28948 +I0410 13:44:17.437134 18353 solver.cpp:237] Train net output #0: loss = 3.28948 (* 1 = 3.28948 loss) +I0410 13:44:17.437145 18353 sgd_solver.cpp:105] Iteration 2076, lr = 0.00662837 +I0410 13:44:22.360395 18353 solver.cpp:218] Iteration 2088 (2.43749 iter/s, 4.9231s/12 iters), loss = 3.16393 +I0410 13:44:22.360450 18353 solver.cpp:237] Train net output #0: loss = 3.16393 (* 1 = 3.16393 loss) +I0410 13:44:22.360462 18353 sgd_solver.cpp:105] Iteration 2088, lr = 0.00661263 +I0410 13:44:27.189093 18353 solver.cpp:218] Iteration 2100 (2.48525 iter/s, 4.82849s/12 iters), loss = 3.349 +I0410 13:44:27.189141 18353 solver.cpp:237] Train net output #0: loss = 3.349 (* 1 = 3.349 loss) +I0410 13:44:27.189149 18353 sgd_solver.cpp:105] Iteration 2100, lr = 0.00659693 +I0410 13:44:32.079792 18353 solver.cpp:218] Iteration 2112 (2.45374 iter/s, 4.8905s/12 iters), loss = 3.25057 +I0410 13:44:32.079834 18353 solver.cpp:237] Train net output #0: loss = 3.25057 (* 1 = 3.25057 loss) +I0410 13:44:32.079843 18353 sgd_solver.cpp:105] Iteration 2112, lr = 0.00658127 +I0410 13:44:36.593744 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:36.906211 18353 solver.cpp:218] Iteration 2124 (2.48642 iter/s, 4.82622s/12 iters), loss = 3.05907 +I0410 13:44:36.906261 18353 solver.cpp:237] Train net output #0: loss = 3.05907 (* 1 = 3.05907 loss) +I0410 13:44:36.906272 18353 sgd_solver.cpp:105] Iteration 2124, lr = 0.00656564 +I0410 13:44:41.836755 18353 solver.cpp:218] Iteration 2136 (2.43391 iter/s, 4.93034s/12 iters), loss = 3.15181 +I0410 13:44:41.836851 18353 solver.cpp:237] Train net output #0: loss = 3.15181 (* 1 = 3.15181 loss) +I0410 13:44:41.836861 18353 sgd_solver.cpp:105] Iteration 2136, lr = 0.00655006 +I0410 13:44:43.828114 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2142.caffemodel +I0410 13:44:44.131263 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2142.solverstate +I0410 13:44:44.325698 18353 solver.cpp:330] Iteration 2142, Testing net (#0) +I0410 13:44:44.325721 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:44:47.943614 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:48.830090 18353 solver.cpp:397] Test net output #0: accuracy = 0.253676 +I0410 13:44:48.830140 18353 solver.cpp:397] Test net output #1: loss = 3.22863 (* 1 = 3.22863 loss) +I0410 13:44:50.762620 18353 solver.cpp:218] Iteration 2148 (1.34446 iter/s, 8.9255s/12 iters), loss = 3.216 +I0410 13:44:50.762666 18353 solver.cpp:237] Train net output #0: loss = 3.216 (* 1 = 3.216 loss) +I0410 13:44:50.762678 18353 sgd_solver.cpp:105] Iteration 2148, lr = 0.00653451 +I0410 13:44:55.708389 18353 solver.cpp:218] Iteration 2160 (2.42642 iter/s, 4.94557s/12 iters), loss = 3.47914 +I0410 13:44:55.708444 18353 solver.cpp:237] Train net output #0: loss = 3.47914 (* 1 = 3.47914 loss) +I0410 13:44:55.708458 18353 sgd_solver.cpp:105] Iteration 2160, lr = 0.00651899 +I0410 13:45:00.649972 18353 solver.cpp:218] Iteration 2172 (2.42848 iter/s, 4.94136s/12 iters), loss = 3.01132 +I0410 13:45:00.650030 18353 solver.cpp:237] Train net output #0: loss = 3.01132 (* 1 = 3.01132 loss) +I0410 13:45:00.650043 18353 sgd_solver.cpp:105] Iteration 2172, lr = 0.00650351 +I0410 13:45:05.515100 18353 solver.cpp:218] Iteration 2184 (2.46664 iter/s, 4.86492s/12 iters), loss = 2.95343 +I0410 13:45:05.515154 18353 solver.cpp:237] Train net output #0: loss = 2.95343 (* 1 = 2.95343 loss) +I0410 13:45:05.515166 18353 sgd_solver.cpp:105] Iteration 2184, lr = 0.00648807 +I0410 13:45:10.449338 18353 solver.cpp:218] Iteration 2196 (2.43209 iter/s, 4.93403s/12 iters), loss = 2.96801 +I0410 13:45:10.449391 18353 solver.cpp:237] Train net output #0: loss = 2.96801 (* 1 = 2.96801 loss) +I0410 13:45:10.449404 18353 sgd_solver.cpp:105] Iteration 2196, lr = 0.00647267 +I0410 13:45:15.373298 18353 solver.cpp:218] Iteration 2208 (2.43718 iter/s, 4.92373s/12 iters), loss = 2.91968 +I0410 13:45:15.373440 18353 solver.cpp:237] Train net output #0: loss = 2.91968 (* 1 = 2.91968 loss) +I0410 13:45:15.373454 18353 sgd_solver.cpp:105] Iteration 2208, lr = 0.0064573 +I0410 13:45:20.264772 18353 solver.cpp:218] Iteration 2220 (2.45339 iter/s, 4.89119s/12 iters), loss = 2.85161 +I0410 13:45:20.264813 18353 solver.cpp:237] Train net output #0: loss = 2.85161 (* 1 = 2.85161 loss) +I0410 13:45:20.264823 18353 sgd_solver.cpp:105] Iteration 2220, lr = 0.00644197 +I0410 13:45:22.042301 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:25.180999 18353 solver.cpp:218] Iteration 2232 (2.44099 iter/s, 4.91604s/12 iters), loss = 2.79306 +I0410 13:45:25.181052 18353 solver.cpp:237] Train net output #0: loss = 2.79306 (* 1 = 2.79306 loss) +I0410 13:45:25.181066 18353 sgd_solver.cpp:105] Iteration 2232, lr = 0.00642668 +I0410 13:45:29.647581 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2244.caffemodel +I0410 13:45:29.967653 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2244.solverstate +I0410 13:45:30.175951 18353 solver.cpp:330] Iteration 2244, Testing net (#0) +I0410 13:45:30.175974 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:45:33.837415 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:34.765846 18353 solver.cpp:397] Test net output #0: accuracy = 0.266544 +I0410 13:45:34.765890 18353 solver.cpp:397] Test net output #1: loss = 3.08475 (* 1 = 3.08475 loss) +I0410 13:45:34.847196 18353 solver.cpp:218] Iteration 2244 (1.24148 iter/s, 9.66586s/12 iters), loss = 3.07465 +I0410 13:45:34.847245 18353 solver.cpp:237] Train net output #0: loss = 3.07465 (* 1 = 3.07465 loss) +I0410 13:45:34.847255 18353 sgd_solver.cpp:105] Iteration 2244, lr = 0.00641142 +I0410 13:45:39.102602 18353 solver.cpp:218] Iteration 2256 (2.82007 iter/s, 4.25522s/12 iters), loss = 2.99262 +I0410 13:45:39.102654 18353 solver.cpp:237] Train net output #0: loss = 2.99262 (* 1 = 2.99262 loss) +I0410 13:45:39.102666 18353 sgd_solver.cpp:105] Iteration 2256, lr = 0.0063962 +I0410 13:45:44.015529 18353 solver.cpp:218] Iteration 2268 (2.44264 iter/s, 4.91272s/12 iters), loss = 3.19675 +I0410 13:45:44.015578 18353 solver.cpp:237] Train net output #0: loss = 3.19675 (* 1 = 3.19675 loss) +I0410 13:45:44.015589 18353 sgd_solver.cpp:105] Iteration 2268, lr = 0.00638101 +I0410 13:45:48.911358 18353 solver.cpp:218] Iteration 2280 (2.45117 iter/s, 4.89563s/12 iters), loss = 2.86009 +I0410 13:45:48.911422 18353 solver.cpp:237] Train net output #0: loss = 2.86009 (* 1 = 2.86009 loss) +I0410 13:45:48.911432 18353 sgd_solver.cpp:105] Iteration 2280, lr = 0.00636586 +I0410 13:45:53.847028 18353 solver.cpp:218] Iteration 2292 (2.43139 iter/s, 4.93545s/12 iters), loss = 2.92611 +I0410 13:45:53.847075 18353 solver.cpp:237] Train net output #0: loss = 2.92611 (* 1 = 2.92611 loss) +I0410 13:45:53.847086 18353 sgd_solver.cpp:105] Iteration 2292, lr = 0.00635075 +I0410 13:45:58.773135 18353 solver.cpp:218] Iteration 2304 (2.4361 iter/s, 4.9259s/12 iters), loss = 2.84746 +I0410 13:45:58.773195 18353 solver.cpp:237] Train net output #0: loss = 2.84746 (* 1 = 2.84746 loss) +I0410 13:45:58.773206 18353 sgd_solver.cpp:105] Iteration 2304, lr = 0.00633567 +I0410 13:46:03.703402 18353 solver.cpp:218] Iteration 2316 (2.43405 iter/s, 4.93005s/12 iters), loss = 2.95571 +I0410 13:46:03.703456 18353 solver.cpp:237] Train net output #0: loss = 2.95571 (* 1 = 2.95571 loss) +I0410 13:46:03.703469 18353 sgd_solver.cpp:105] Iteration 2316, lr = 0.00632063 +I0410 13:46:07.520294 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:46:08.556756 18353 solver.cpp:218] Iteration 2328 (2.47262 iter/s, 4.85315s/12 iters), loss = 2.97204 +I0410 13:46:08.556798 18353 solver.cpp:237] Train net output #0: loss = 2.97204 (* 1 = 2.97204 loss) +I0410 13:46:08.556807 18353 sgd_solver.cpp:105] Iteration 2328, lr = 0.00630562 +I0410 13:46:13.498801 18353 solver.cpp:218] Iteration 2340 (2.42824 iter/s, 4.94185s/12 iters), loss = 2.68723 +I0410 13:46:13.498847 18353 solver.cpp:237] Train net output #0: loss = 2.68723 (* 1 = 2.68723 loss) +I0410 13:46:13.498860 18353 sgd_solver.cpp:105] Iteration 2340, lr = 0.00629065 +I0410 13:46:15.509204 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2346.caffemodel +I0410 13:46:15.916226 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2346.solverstate +I0410 13:46:16.279402 18353 solver.cpp:330] Iteration 2346, Testing net (#0) +I0410 13:46:16.279431 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:46:19.828017 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:46:20.790210 18353 solver.cpp:397] Test net output #0: accuracy = 0.290441 +I0410 13:46:20.790267 18353 solver.cpp:397] Test net output #1: loss = 2.96096 (* 1 = 2.96096 loss) +I0410 13:46:22.695128 18353 solver.cpp:218] Iteration 2352 (1.30491 iter/s, 9.19601s/12 iters), loss = 2.67998 +I0410 13:46:22.695179 18353 solver.cpp:237] Train net output #0: loss = 2.67998 (* 1 = 2.67998 loss) +I0410 13:46:22.695189 18353 sgd_solver.cpp:105] Iteration 2352, lr = 0.00627571 +I0410 13:46:27.556747 18353 solver.cpp:218] Iteration 2364 (2.46842 iter/s, 4.86141s/12 iters), loss = 2.76407 +I0410 13:46:27.556802 18353 solver.cpp:237] Train net output #0: loss = 2.76407 (* 1 = 2.76407 loss) +I0410 13:46:27.556815 18353 sgd_solver.cpp:105] Iteration 2364, lr = 0.00626081 +I0410 13:46:32.363173 18353 solver.cpp:218] Iteration 2376 (2.49677 iter/s, 4.80622s/12 iters), loss = 2.76061 +I0410 13:46:32.363231 18353 solver.cpp:237] Train net output #0: loss = 2.76061 (* 1 = 2.76061 loss) +I0410 13:46:32.363242 18353 sgd_solver.cpp:105] Iteration 2376, lr = 0.00624595 +I0410 13:46:37.229712 18353 solver.cpp:218] Iteration 2388 (2.46593 iter/s, 4.86633s/12 iters), loss = 2.80992 +I0410 13:46:37.229773 18353 solver.cpp:237] Train net output #0: loss = 2.80992 (* 1 = 2.80992 loss) +I0410 13:46:37.229785 18353 sgd_solver.cpp:105] Iteration 2388, lr = 0.00623112 +I0410 13:46:42.184217 18353 solver.cpp:218] Iteration 2400 (2.42214 iter/s, 4.9543s/12 iters), loss = 2.61507 +I0410 13:46:42.184260 18353 solver.cpp:237] Train net output #0: loss = 2.61507 (* 1 = 2.61507 loss) +I0410 13:46:42.184270 18353 sgd_solver.cpp:105] Iteration 2400, lr = 0.00621633 +I0410 13:46:47.351087 18353 solver.cpp:218] Iteration 2412 (2.32258 iter/s, 5.16667s/12 iters), loss = 2.5541 +I0410 13:46:47.351135 18353 solver.cpp:237] Train net output #0: loss = 2.5541 (* 1 = 2.5541 loss) +I0410 13:46:47.351145 18353 sgd_solver.cpp:105] Iteration 2412, lr = 0.00620157 +I0410 13:46:52.294188 18353 solver.cpp:218] Iteration 2424 (2.42772 iter/s, 4.9429s/12 iters), loss = 2.89204 +I0410 13:46:52.294365 18353 solver.cpp:237] Train net output #0: loss = 2.89204 (* 1 = 2.89204 loss) +I0410 13:46:52.294381 18353 sgd_solver.cpp:105] Iteration 2424, lr = 0.00618684 +I0410 13:46:53.339831 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:46:57.144178 18353 solver.cpp:218] Iteration 2436 (2.4744 iter/s, 4.84967s/12 iters), loss = 2.55621 +I0410 13:46:57.144228 18353 solver.cpp:237] Train net output #0: loss = 2.55621 (* 1 = 2.55621 loss) +I0410 13:46:57.144239 18353 sgd_solver.cpp:105] Iteration 2436, lr = 0.00617215 +I0410 13:47:01.594825 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2448.caffemodel +I0410 13:47:01.907812 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2448.solverstate +I0410 13:47:02.113054 18353 solver.cpp:330] Iteration 2448, Testing net (#0) +I0410 13:47:02.113085 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:47:05.662081 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:06.640868 18353 solver.cpp:397] Test net output #0: accuracy = 0.310049 +I0410 13:47:06.640920 18353 solver.cpp:397] Test net output #1: loss = 2.84895 (* 1 = 2.84895 loss) +I0410 13:47:06.722532 18353 solver.cpp:218] Iteration 2448 (1.25287 iter/s, 9.57802s/12 iters), loss = 2.48788 +I0410 13:47:06.722584 18353 solver.cpp:237] Train net output #0: loss = 2.48788 (* 1 = 2.48788 loss) +I0410 13:47:06.722596 18353 sgd_solver.cpp:105] Iteration 2448, lr = 0.0061575 +I0410 13:47:10.848481 18353 solver.cpp:218] Iteration 2460 (2.90855 iter/s, 4.12577s/12 iters), loss = 2.25917 +I0410 13:47:10.848520 18353 solver.cpp:237] Train net output #0: loss = 2.25917 (* 1 = 2.25917 loss) +I0410 13:47:10.848529 18353 sgd_solver.cpp:105] Iteration 2460, lr = 0.00614288 +I0410 13:47:15.772990 18353 solver.cpp:218] Iteration 2472 (2.43689 iter/s, 4.92431s/12 iters), loss = 2.79266 +I0410 13:47:15.773051 18353 solver.cpp:237] Train net output #0: loss = 2.79266 (* 1 = 2.79266 loss) +I0410 13:47:15.773063 18353 sgd_solver.cpp:105] Iteration 2472, lr = 0.0061283 +I0410 13:47:20.874701 18353 solver.cpp:218] Iteration 2484 (2.35225 iter/s, 5.10149s/12 iters), loss = 2.94248 +I0410 13:47:20.874752 18353 solver.cpp:237] Train net output #0: loss = 2.94248 (* 1 = 2.94248 loss) +I0410 13:47:20.874763 18353 sgd_solver.cpp:105] Iteration 2484, lr = 0.00611375 +I0410 13:47:25.965553 18353 solver.cpp:218] Iteration 2496 (2.35727 iter/s, 5.09064s/12 iters), loss = 2.91343 +I0410 13:47:25.965658 18353 solver.cpp:237] Train net output #0: loss = 2.91343 (* 1 = 2.91343 loss) +I0410 13:47:25.965672 18353 sgd_solver.cpp:105] Iteration 2496, lr = 0.00609923 +I0410 13:47:30.886927 18353 solver.cpp:218] Iteration 2508 (2.43847 iter/s, 4.92112s/12 iters), loss = 3.05394 +I0410 13:47:30.886978 18353 solver.cpp:237] Train net output #0: loss = 3.05394 (* 1 = 3.05394 loss) +I0410 13:47:30.886991 18353 sgd_solver.cpp:105] Iteration 2508, lr = 0.00608475 +I0410 13:47:35.834262 18353 solver.cpp:218] Iteration 2520 (2.42565 iter/s, 4.94713s/12 iters), loss = 2.31371 +I0410 13:47:35.834304 18353 solver.cpp:237] Train net output #0: loss = 2.31371 (* 1 = 2.31371 loss) +I0410 13:47:35.834313 18353 sgd_solver.cpp:105] Iteration 2520, lr = 0.0060703 +I0410 13:47:39.019659 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:40.786224 18353 solver.cpp:218] Iteration 2532 (2.42338 iter/s, 4.95177s/12 iters), loss = 2.70147 +I0410 13:47:40.786268 18353 solver.cpp:237] Train net output #0: loss = 2.70147 (* 1 = 2.70147 loss) +I0410 13:47:40.786278 18353 sgd_solver.cpp:105] Iteration 2532, lr = 0.00605589 +I0410 13:47:45.714474 18353 solver.cpp:218] Iteration 2544 (2.43504 iter/s, 4.92805s/12 iters), loss = 2.56679 +I0410 13:47:45.714519 18353 solver.cpp:237] Train net output #0: loss = 2.56679 (* 1 = 2.56679 loss) +I0410 13:47:45.714529 18353 sgd_solver.cpp:105] Iteration 2544, lr = 0.00604151 +I0410 13:47:47.657984 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2550.caffemodel +I0410 13:47:47.942725 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2550.solverstate +I0410 13:47:48.142531 18353 solver.cpp:330] Iteration 2550, Testing net (#0) +I0410 13:47:48.142551 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:47:51.571621 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:52.589107 18353 solver.cpp:397] Test net output #0: accuracy = 0.298407 +I0410 13:47:52.589149 18353 solver.cpp:397] Test net output #1: loss = 2.89551 (* 1 = 2.89551 loss) +I0410 13:47:54.536147 18353 solver.cpp:218] Iteration 2556 (1.36033 iter/s, 8.82136s/12 iters), loss = 2.67895 +I0410 13:47:54.536198 18353 solver.cpp:237] Train net output #0: loss = 2.67895 (* 1 = 2.67895 loss) +I0410 13:47:54.536211 18353 sgd_solver.cpp:105] Iteration 2556, lr = 0.00602717 +I0410 13:47:59.568100 18353 solver.cpp:218] Iteration 2568 (2.38486 iter/s, 5.03175s/12 iters), loss = 2.54045 +I0410 13:47:59.568255 18353 solver.cpp:237] Train net output #0: loss = 2.54045 (* 1 = 2.54045 loss) +I0410 13:47:59.568269 18353 sgd_solver.cpp:105] Iteration 2568, lr = 0.00601286 +I0410 13:48:04.441026 18353 solver.cpp:218] Iteration 2580 (2.46274 iter/s, 4.87262s/12 iters), loss = 2.31302 +I0410 13:48:04.441087 18353 solver.cpp:237] Train net output #0: loss = 2.31302 (* 1 = 2.31302 loss) +I0410 13:48:04.441099 18353 sgd_solver.cpp:105] Iteration 2580, lr = 0.00599858 +I0410 13:48:09.240120 18353 solver.cpp:218] Iteration 2592 (2.50058 iter/s, 4.79888s/12 iters), loss = 2.77194 +I0410 13:48:09.240180 18353 solver.cpp:237] Train net output #0: loss = 2.77194 (* 1 = 2.77194 loss) +I0410 13:48:09.240192 18353 sgd_solver.cpp:105] Iteration 2592, lr = 0.00598434 +I0410 13:48:14.091184 18353 solver.cpp:218] Iteration 2604 (2.47379 iter/s, 4.85085s/12 iters), loss = 2.83817 +I0410 13:48:14.091241 18353 solver.cpp:237] Train net output #0: loss = 2.83817 (* 1 = 2.83817 loss) +I0410 13:48:14.091254 18353 sgd_solver.cpp:105] Iteration 2604, lr = 0.00597013 +I0410 13:48:18.946583 18353 solver.cpp:218] Iteration 2616 (2.47158 iter/s, 4.85519s/12 iters), loss = 2.83714 +I0410 13:48:18.946645 18353 solver.cpp:237] Train net output #0: loss = 2.83714 (* 1 = 2.83714 loss) +I0410 13:48:18.946656 18353 sgd_solver.cpp:105] Iteration 2616, lr = 0.00595596 +I0410 13:48:23.746433 18353 solver.cpp:218] Iteration 2628 (2.50019 iter/s, 4.79964s/12 iters), loss = 2.34667 +I0410 13:48:23.746491 18353 solver.cpp:237] Train net output #0: loss = 2.34667 (* 1 = 2.34667 loss) +I0410 13:48:23.746503 18353 sgd_solver.cpp:105] Iteration 2628, lr = 0.00594182 +I0410 13:48:24.170904 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:48:28.613706 18353 solver.cpp:218] Iteration 2640 (2.46555 iter/s, 4.86706s/12 iters), loss = 2.43352 +I0410 13:48:28.613770 18353 solver.cpp:237] Train net output #0: loss = 2.43352 (* 1 = 2.43352 loss) +I0410 13:48:28.613783 18353 sgd_solver.cpp:105] Iteration 2640, lr = 0.00592771 +I0410 13:48:32.988857 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2652.caffemodel +I0410 13:48:33.295639 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2652.solverstate +I0410 13:48:33.594156 18353 solver.cpp:330] Iteration 2652, Testing net (#0) +I0410 13:48:33.594184 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:48:37.117542 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:48:38.170817 18353 solver.cpp:397] Test net output #0: accuracy = 0.343137 +I0410 13:48:38.170872 18353 solver.cpp:397] Test net output #1: loss = 2.71235 (* 1 = 2.71235 loss) +I0410 13:48:38.252375 18353 solver.cpp:218] Iteration 2652 (1.24503 iter/s, 9.63832s/12 iters), loss = 2.44637 +I0410 13:48:38.252424 18353 solver.cpp:237] Train net output #0: loss = 2.44637 (* 1 = 2.44637 loss) +I0410 13:48:38.252436 18353 sgd_solver.cpp:105] Iteration 2652, lr = 0.00591364 +I0410 13:48:42.436259 18353 solver.cpp:218] Iteration 2664 (2.86828 iter/s, 4.1837s/12 iters), loss = 2.51245 +I0410 13:48:42.436314 18353 solver.cpp:237] Train net output #0: loss = 2.51245 (* 1 = 2.51245 loss) +I0410 13:48:42.436331 18353 sgd_solver.cpp:105] Iteration 2664, lr = 0.0058996 +I0410 13:48:47.315321 18353 solver.cpp:218] Iteration 2676 (2.45959 iter/s, 4.87886s/12 iters), loss = 2.49234 +I0410 13:48:47.315374 18353 solver.cpp:237] Train net output #0: loss = 2.49234 (* 1 = 2.49234 loss) +I0410 13:48:47.315385 18353 sgd_solver.cpp:105] Iteration 2676, lr = 0.00588559 +I0410 13:48:52.233330 18353 solver.cpp:218] Iteration 2688 (2.44011 iter/s, 4.91781s/12 iters), loss = 2.73496 +I0410 13:48:52.233376 18353 solver.cpp:237] Train net output #0: loss = 2.73496 (* 1 = 2.73496 loss) +I0410 13:48:52.233386 18353 sgd_solver.cpp:105] Iteration 2688, lr = 0.00587162 +I0410 13:48:57.113040 18353 solver.cpp:218] Iteration 2700 (2.45926 iter/s, 4.87951s/12 iters), loss = 2.3454 +I0410 13:48:57.113092 18353 solver.cpp:237] Train net output #0: loss = 2.3454 (* 1 = 2.3454 loss) +I0410 13:48:57.113104 18353 sgd_solver.cpp:105] Iteration 2700, lr = 0.00585768 +I0410 13:49:02.045753 18353 solver.cpp:218] Iteration 2712 (2.43284 iter/s, 4.93251s/12 iters), loss = 2.48152 +I0410 13:49:02.045807 18353 solver.cpp:237] Train net output #0: loss = 2.48152 (* 1 = 2.48152 loss) +I0410 13:49:02.045819 18353 sgd_solver.cpp:105] Iteration 2712, lr = 0.00584377 +I0410 13:49:06.977442 18353 solver.cpp:218] Iteration 2724 (2.43335 iter/s, 4.93148s/12 iters), loss = 2.35516 +I0410 13:49:06.977607 18353 solver.cpp:237] Train net output #0: loss = 2.35516 (* 1 = 2.35516 loss) +I0410 13:49:06.977622 18353 sgd_solver.cpp:105] Iteration 2724, lr = 0.0058299 +I0410 13:49:09.560894 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:11.911739 18353 solver.cpp:218] Iteration 2736 (2.43211 iter/s, 4.93399s/12 iters), loss = 2.42899 +I0410 13:49:11.911792 18353 solver.cpp:237] Train net output #0: loss = 2.42899 (* 1 = 2.42899 loss) +I0410 13:49:11.911805 18353 sgd_solver.cpp:105] Iteration 2736, lr = 0.00581605 +I0410 13:49:16.800308 18353 solver.cpp:218] Iteration 2748 (2.45481 iter/s, 4.88837s/12 iters), loss = 2.46431 +I0410 13:49:16.800359 18353 solver.cpp:237] Train net output #0: loss = 2.46431 (* 1 = 2.46431 loss) +I0410 13:49:16.800370 18353 sgd_solver.cpp:105] Iteration 2748, lr = 0.00580225 +I0410 13:49:18.785130 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2754.caffemodel +I0410 13:49:19.079620 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2754.solverstate +I0410 13:49:19.272706 18353 solver.cpp:330] Iteration 2754, Testing net (#0) +I0410 13:49:19.272732 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:49:21.944546 18353 blocking_queue.cpp:49] Waiting for data +I0410 13:49:22.541194 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:23.684855 18353 solver.cpp:397] Test net output #0: accuracy = 0.337623 +I0410 13:49:23.684897 18353 solver.cpp:397] Test net output #1: loss = 2.74954 (* 1 = 2.74954 loss) +I0410 13:49:25.606098 18353 solver.cpp:218] Iteration 2760 (1.36279 iter/s, 8.80548s/12 iters), loss = 2.18205 +I0410 13:49:25.606155 18353 solver.cpp:237] Train net output #0: loss = 2.18205 (* 1 = 2.18205 loss) +I0410 13:49:25.606169 18353 sgd_solver.cpp:105] Iteration 2760, lr = 0.00578847 +I0410 13:49:30.556263 18353 solver.cpp:218] Iteration 2772 (2.42426 iter/s, 4.94996s/12 iters), loss = 2.6785 +I0410 13:49:30.556321 18353 solver.cpp:237] Train net output #0: loss = 2.6785 (* 1 = 2.6785 loss) +I0410 13:49:30.556335 18353 sgd_solver.cpp:105] Iteration 2772, lr = 0.00577473 +I0410 13:49:35.814471 18353 solver.cpp:218] Iteration 2784 (2.28224 iter/s, 5.25799s/12 iters), loss = 2.60569 +I0410 13:49:35.814530 18353 solver.cpp:237] Train net output #0: loss = 2.60569 (* 1 = 2.60569 loss) +I0410 13:49:35.814543 18353 sgd_solver.cpp:105] Iteration 2784, lr = 0.00576102 +I0410 13:49:40.761415 18353 solver.cpp:218] Iteration 2796 (2.42584 iter/s, 4.94673s/12 iters), loss = 2.38172 +I0410 13:49:40.761518 18353 solver.cpp:237] Train net output #0: loss = 2.38172 (* 1 = 2.38172 loss) +I0410 13:49:40.761529 18353 sgd_solver.cpp:105] Iteration 2796, lr = 0.00574734 +I0410 13:49:45.690212 18353 solver.cpp:218] Iteration 2808 (2.4348 iter/s, 4.92854s/12 iters), loss = 2.18728 +I0410 13:49:45.690259 18353 solver.cpp:237] Train net output #0: loss = 2.18728 (* 1 = 2.18728 loss) +I0410 13:49:45.690269 18353 sgd_solver.cpp:105] Iteration 2808, lr = 0.00573369 +I0410 13:49:50.616744 18353 solver.cpp:218] Iteration 2820 (2.43589 iter/s, 4.92633s/12 iters), loss = 2.41611 +I0410 13:49:50.616793 18353 solver.cpp:237] Train net output #0: loss = 2.41611 (* 1 = 2.41611 loss) +I0410 13:49:50.616803 18353 sgd_solver.cpp:105] Iteration 2820, lr = 0.00572008 +I0410 13:49:55.260185 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:55.544586 18353 solver.cpp:218] Iteration 2832 (2.43524 iter/s, 4.92764s/12 iters), loss = 2.41694 +I0410 13:49:55.544631 18353 solver.cpp:237] Train net output #0: loss = 2.41694 (* 1 = 2.41694 loss) +I0410 13:49:55.544641 18353 sgd_solver.cpp:105] Iteration 2832, lr = 0.0057065 +I0410 13:50:00.759503 18353 solver.cpp:218] Iteration 2844 (2.30119 iter/s, 5.2147s/12 iters), loss = 2.38468 +I0410 13:50:00.759562 18353 solver.cpp:237] Train net output #0: loss = 2.38468 (* 1 = 2.38468 loss) +I0410 13:50:00.759575 18353 sgd_solver.cpp:105] Iteration 2844, lr = 0.00569295 +I0410 13:50:06.360571 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2856.caffemodel +I0410 13:50:06.669847 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2856.solverstate +I0410 13:50:06.883953 18353 solver.cpp:330] Iteration 2856, Testing net (#0) +I0410 13:50:06.883972 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:50:10.161761 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:11.308306 18353 solver.cpp:397] Test net output #0: accuracy = 0.342524 +I0410 13:50:11.308468 18353 solver.cpp:397] Test net output #1: loss = 2.68798 (* 1 = 2.68798 loss) +I0410 13:50:11.389681 18353 solver.cpp:218] Iteration 2856 (1.1289 iter/s, 10.6298s/12 iters), loss = 2.29058 +I0410 13:50:11.389734 18353 solver.cpp:237] Train net output #0: loss = 2.29058 (* 1 = 2.29058 loss) +I0410 13:50:11.389744 18353 sgd_solver.cpp:105] Iteration 2856, lr = 0.00567944 +I0410 13:50:15.558637 18353 solver.cpp:218] Iteration 2868 (2.87855 iter/s, 4.16877s/12 iters), loss = 2.34681 +I0410 13:50:15.558686 18353 solver.cpp:237] Train net output #0: loss = 2.34681 (* 1 = 2.34681 loss) +I0410 13:50:15.558696 18353 sgd_solver.cpp:105] Iteration 2868, lr = 0.00566595 +I0410 13:50:20.501816 18353 solver.cpp:218] Iteration 2880 (2.42769 iter/s, 4.94297s/12 iters), loss = 2.01662 +I0410 13:50:20.501869 18353 solver.cpp:237] Train net output #0: loss = 2.01662 (* 1 = 2.01662 loss) +I0410 13:50:20.501883 18353 sgd_solver.cpp:105] Iteration 2880, lr = 0.0056525 +I0410 13:50:25.443928 18353 solver.cpp:218] Iteration 2892 (2.42821 iter/s, 4.9419s/12 iters), loss = 2.27543 +I0410 13:50:25.443987 18353 solver.cpp:237] Train net output #0: loss = 2.27543 (* 1 = 2.27543 loss) +I0410 13:50:25.444000 18353 sgd_solver.cpp:105] Iteration 2892, lr = 0.00563908 +I0410 13:50:30.356631 18353 solver.cpp:218] Iteration 2904 (2.44275 iter/s, 4.91249s/12 iters), loss = 2.11401 +I0410 13:50:30.356681 18353 solver.cpp:237] Train net output #0: loss = 2.11401 (* 1 = 2.11401 loss) +I0410 13:50:30.356693 18353 sgd_solver.cpp:105] Iteration 2904, lr = 0.00562569 +I0410 13:50:35.254042 18353 solver.cpp:218] Iteration 2916 (2.45038 iter/s, 4.89721s/12 iters), loss = 2.25554 +I0410 13:50:35.254094 18353 solver.cpp:237] Train net output #0: loss = 2.25554 (* 1 = 2.25554 loss) +I0410 13:50:35.254106 18353 sgd_solver.cpp:105] Iteration 2916, lr = 0.00561233 +I0410 13:50:40.144529 18353 solver.cpp:218] Iteration 2928 (2.45383 iter/s, 4.89031s/12 iters), loss = 2.07217 +I0410 13:50:40.144588 18353 solver.cpp:237] Train net output #0: loss = 2.07217 (* 1 = 2.07217 loss) +I0410 13:50:40.144599 18353 sgd_solver.cpp:105] Iteration 2928, lr = 0.00559901 +I0410 13:50:41.961776 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:45.095649 18353 solver.cpp:218] Iteration 2940 (2.42377 iter/s, 4.95095s/12 iters), loss = 2.37838 +I0410 13:50:45.095701 18353 solver.cpp:237] Train net output #0: loss = 2.37838 (* 1 = 2.37838 loss) +I0410 13:50:45.095712 18353 sgd_solver.cpp:105] Iteration 2940, lr = 0.00558572 +I0410 13:50:50.091406 18353 solver.cpp:218] Iteration 2952 (2.40211 iter/s, 4.9956s/12 iters), loss = 2.23771 +I0410 13:50:50.091457 18353 solver.cpp:237] Train net output #0: loss = 2.23771 (* 1 = 2.23771 loss) +I0410 13:50:50.091468 18353 sgd_solver.cpp:105] Iteration 2952, lr = 0.00557245 +I0410 13:50:52.095760 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2958.caffemodel +I0410 13:50:52.778113 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2958.solverstate +I0410 13:50:52.985327 18353 solver.cpp:330] Iteration 2958, Testing net (#0) +I0410 13:50:52.985353 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:50:56.255712 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:57.432770 18353 solver.cpp:397] Test net output #0: accuracy = 0.343137 +I0410 13:50:57.432822 18353 solver.cpp:397] Test net output #1: loss = 2.7177 (* 1 = 2.7177 loss) +I0410 13:50:59.406410 18353 solver.cpp:218] Iteration 2964 (1.28828 iter/s, 9.31477s/12 iters), loss = 2.3574 +I0410 13:50:59.406458 18353 solver.cpp:237] Train net output #0: loss = 2.3574 (* 1 = 2.3574 loss) +I0410 13:50:59.406467 18353 sgd_solver.cpp:105] Iteration 2964, lr = 0.00555922 +I0410 13:51:04.379737 18353 solver.cpp:218] Iteration 2976 (2.41295 iter/s, 4.97317s/12 iters), loss = 2.07225 +I0410 13:51:04.379784 18353 solver.cpp:237] Train net output #0: loss = 2.07225 (* 1 = 2.07225 loss) +I0410 13:51:04.379796 18353 sgd_solver.cpp:105] Iteration 2976, lr = 0.00554603 +I0410 13:51:09.267414 18353 solver.cpp:218] Iteration 2988 (2.45523 iter/s, 4.88753s/12 iters), loss = 2.18195 +I0410 13:51:09.267460 18353 solver.cpp:237] Train net output #0: loss = 2.18195 (* 1 = 2.18195 loss) +I0410 13:51:09.267472 18353 sgd_solver.cpp:105] Iteration 2988, lr = 0.00553286 +I0410 13:51:14.215021 18353 solver.cpp:218] Iteration 3000 (2.42549 iter/s, 4.94746s/12 iters), loss = 2.469 +I0410 13:51:14.215113 18353 solver.cpp:237] Train net output #0: loss = 2.469 (* 1 = 2.469 loss) +I0410 13:51:14.215126 18353 sgd_solver.cpp:105] Iteration 3000, lr = 0.00551972 +I0410 13:51:19.091048 18353 solver.cpp:218] Iteration 3012 (2.46112 iter/s, 4.87583s/12 iters), loss = 2.20564 +I0410 13:51:19.091104 18353 solver.cpp:237] Train net output #0: loss = 2.20564 (* 1 = 2.20564 loss) +I0410 13:51:19.091117 18353 sgd_solver.cpp:105] Iteration 3012, lr = 0.00550662 +I0410 13:51:24.201122 18353 solver.cpp:218] Iteration 3024 (2.34838 iter/s, 5.1099s/12 iters), loss = 2.10652 +I0410 13:51:24.201181 18353 solver.cpp:237] Train net output #0: loss = 2.10652 (* 1 = 2.10652 loss) +I0410 13:51:24.201195 18353 sgd_solver.cpp:105] Iteration 3024, lr = 0.00549354 +I0410 13:51:28.093194 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:51:29.106462 18353 solver.cpp:218] Iteration 3036 (2.44639 iter/s, 4.90518s/12 iters), loss = 1.85562 +I0410 13:51:29.106510 18353 solver.cpp:237] Train net output #0: loss = 1.85562 (* 1 = 1.85562 loss) +I0410 13:51:29.106520 18353 sgd_solver.cpp:105] Iteration 3036, lr = 0.0054805 +I0410 13:51:34.059108 18353 solver.cpp:218] Iteration 3048 (2.42303 iter/s, 4.95249s/12 iters), loss = 2.22064 +I0410 13:51:34.059160 18353 solver.cpp:237] Train net output #0: loss = 2.22064 (* 1 = 2.22064 loss) +I0410 13:51:34.059170 18353 sgd_solver.cpp:105] Iteration 3048, lr = 0.00546749 +I0410 13:51:38.504328 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3060.caffemodel +I0410 13:51:38.809418 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3060.solverstate +I0410 13:51:39.007701 18353 solver.cpp:330] Iteration 3060, Testing net (#0) +I0410 13:51:39.007719 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:51:42.407663 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:51:43.624295 18353 solver.cpp:397] Test net output #0: accuracy = 0.363971 +I0410 13:51:43.624346 18353 solver.cpp:397] Test net output #1: loss = 2.66376 (* 1 = 2.66376 loss) +I0410 13:51:43.705695 18353 solver.cpp:218] Iteration 3060 (1.24399 iter/s, 9.64634s/12 iters), loss = 2.17616 +I0410 13:51:43.705742 18353 solver.cpp:237] Train net output #0: loss = 2.17616 (* 1 = 2.17616 loss) +I0410 13:51:43.705754 18353 sgd_solver.cpp:105] Iteration 3060, lr = 0.00545451 +I0410 13:51:47.852028 18353 solver.cpp:218] Iteration 3072 (2.89422 iter/s, 4.14619s/12 iters), loss = 2.25789 +I0410 13:51:47.852171 18353 solver.cpp:237] Train net output #0: loss = 2.25789 (* 1 = 2.25789 loss) +I0410 13:51:47.852183 18353 sgd_solver.cpp:105] Iteration 3072, lr = 0.00544156 +I0410 13:51:52.764294 18353 solver.cpp:218] Iteration 3084 (2.44299 iter/s, 4.91201s/12 iters), loss = 2.22512 +I0410 13:51:52.764350 18353 solver.cpp:237] Train net output #0: loss = 2.22512 (* 1 = 2.22512 loss) +I0410 13:51:52.764364 18353 sgd_solver.cpp:105] Iteration 3084, lr = 0.00542864 +I0410 13:51:57.550388 18353 solver.cpp:218] Iteration 3096 (2.50735 iter/s, 4.78593s/12 iters), loss = 2.21929 +I0410 13:51:57.550441 18353 solver.cpp:237] Train net output #0: loss = 2.21929 (* 1 = 2.21929 loss) +I0410 13:51:57.550453 18353 sgd_solver.cpp:105] Iteration 3096, lr = 0.00541575 +I0410 13:52:02.533702 18353 solver.cpp:218] Iteration 3108 (2.40811 iter/s, 4.98315s/12 iters), loss = 1.79954 +I0410 13:52:02.533751 18353 solver.cpp:237] Train net output #0: loss = 1.79954 (* 1 = 1.79954 loss) +I0410 13:52:02.533763 18353 sgd_solver.cpp:105] Iteration 3108, lr = 0.00540289 +I0410 13:52:07.485780 18353 solver.cpp:218] Iteration 3120 (2.42331 iter/s, 4.95191s/12 iters), loss = 1.85196 +I0410 13:52:07.485839 18353 solver.cpp:237] Train net output #0: loss = 1.85196 (* 1 = 1.85196 loss) +I0410 13:52:07.485853 18353 sgd_solver.cpp:105] Iteration 3120, lr = 0.00539006 +I0410 13:52:12.368455 18353 solver.cpp:218] Iteration 3132 (2.45775 iter/s, 4.88251s/12 iters), loss = 2.52653 +I0410 13:52:12.368516 18353 solver.cpp:237] Train net output #0: loss = 2.52653 (* 1 = 2.52653 loss) +I0410 13:52:12.368530 18353 sgd_solver.cpp:105] Iteration 3132, lr = 0.00537727 +I0410 13:52:13.482409 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:52:17.305106 18353 solver.cpp:218] Iteration 3144 (2.43088 iter/s, 4.93648s/12 iters), loss = 1.9413 +I0410 13:52:17.305160 18353 solver.cpp:237] Train net output #0: loss = 1.9413 (* 1 = 1.9413 loss) +I0410 13:52:17.305174 18353 sgd_solver.cpp:105] Iteration 3144, lr = 0.0053645 +I0410 13:52:22.390087 18353 solver.cpp:218] Iteration 3156 (2.35997 iter/s, 5.08481s/12 iters), loss = 2.11867 +I0410 13:52:22.390170 18353 solver.cpp:237] Train net output #0: loss = 2.11867 (* 1 = 2.11867 loss) +I0410 13:52:22.390182 18353 sgd_solver.cpp:105] Iteration 3156, lr = 0.00535176 +I0410 13:52:24.386270 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3162.caffemodel +I0410 13:52:24.845896 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3162.solverstate +I0410 13:52:25.054814 18353 solver.cpp:330] Iteration 3162, Testing net (#0) +I0410 13:52:25.054836 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:52:28.301630 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:52:29.677714 18353 solver.cpp:397] Test net output #0: accuracy = 0.373774 +I0410 13:52:29.677762 18353 solver.cpp:397] Test net output #1: loss = 2.57004 (* 1 = 2.57004 loss) +I0410 13:52:31.425832 18353 solver.cpp:218] Iteration 3168 (1.3281 iter/s, 9.03547s/12 iters), loss = 1.68413 +I0410 13:52:31.425894 18353 solver.cpp:237] Train net output #0: loss = 1.68413 (* 1 = 1.68413 loss) +I0410 13:52:31.425907 18353 sgd_solver.cpp:105] Iteration 3168, lr = 0.00533906 +I0410 13:52:36.322515 18353 solver.cpp:218] Iteration 3180 (2.45072 iter/s, 4.89651s/12 iters), loss = 2.2834 +I0410 13:52:36.322571 18353 solver.cpp:237] Train net output #0: loss = 2.2834 (* 1 = 2.2834 loss) +I0410 13:52:36.322583 18353 sgd_solver.cpp:105] Iteration 3180, lr = 0.00532638 +I0410 13:52:41.203194 18353 solver.cpp:218] Iteration 3192 (2.45876 iter/s, 4.88052s/12 iters), loss = 2.0547 +I0410 13:52:41.203248 18353 solver.cpp:237] Train net output #0: loss = 2.0547 (* 1 = 2.0547 loss) +I0410 13:52:41.203258 18353 sgd_solver.cpp:105] Iteration 3192, lr = 0.00531374 +I0410 13:52:46.118225 18353 solver.cpp:218] Iteration 3204 (2.44157 iter/s, 4.91487s/12 iters), loss = 1.89946 +I0410 13:52:46.118273 18353 solver.cpp:237] Train net output #0: loss = 1.89946 (* 1 = 1.89946 loss) +I0410 13:52:46.118286 18353 sgd_solver.cpp:105] Iteration 3204, lr = 0.00530112 +I0410 13:52:51.016945 18353 solver.cpp:218] Iteration 3216 (2.4497 iter/s, 4.89856s/12 iters), loss = 2.08793 +I0410 13:52:51.017007 18353 solver.cpp:237] Train net output #0: loss = 2.08793 (* 1 = 2.08793 loss) +I0410 13:52:51.017021 18353 sgd_solver.cpp:105] Iteration 3216, lr = 0.00528853 +I0410 13:52:55.935194 18353 solver.cpp:218] Iteration 3228 (2.43998 iter/s, 4.91808s/12 iters), loss = 2.23101 +I0410 13:52:55.935322 18353 solver.cpp:237] Train net output #0: loss = 2.23101 (* 1 = 2.23101 loss) +I0410 13:52:55.935333 18353 sgd_solver.cpp:105] Iteration 3228, lr = 0.00527598 +I0410 13:52:59.150748 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:00.890262 18353 solver.cpp:218] Iteration 3240 (2.42188 iter/s, 4.95482s/12 iters), loss = 1.91822 +I0410 13:53:00.890316 18353 solver.cpp:237] Train net output #0: loss = 1.91822 (* 1 = 1.91822 loss) +I0410 13:53:00.890326 18353 sgd_solver.cpp:105] Iteration 3240, lr = 0.00526345 +I0410 13:53:05.824908 18353 solver.cpp:218] Iteration 3252 (2.43187 iter/s, 4.93448s/12 iters), loss = 2.00403 +I0410 13:53:05.824966 18353 solver.cpp:237] Train net output #0: loss = 2.00403 (* 1 = 2.00403 loss) +I0410 13:53:05.824980 18353 sgd_solver.cpp:105] Iteration 3252, lr = 0.00525095 +I0410 13:53:10.252840 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3264.caffemodel +I0410 13:53:10.534040 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3264.solverstate +I0410 13:53:10.725033 18353 solver.cpp:330] Iteration 3264, Testing net (#0) +I0410 13:53:10.725059 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:53:13.790335 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:15.118892 18353 solver.cpp:397] Test net output #0: accuracy = 0.393382 +I0410 13:53:15.118928 18353 solver.cpp:397] Test net output #1: loss = 2.54084 (* 1 = 2.54084 loss) +I0410 13:53:15.200150 18353 solver.cpp:218] Iteration 3264 (1.28 iter/s, 9.37498s/12 iters), loss = 2.09418 +I0410 13:53:15.200201 18353 solver.cpp:237] Train net output #0: loss = 2.09418 (* 1 = 2.09418 loss) +I0410 13:53:15.200210 18353 sgd_solver.cpp:105] Iteration 3264, lr = 0.00523849 +I0410 13:53:19.330528 18353 solver.cpp:218] Iteration 3276 (2.90541 iter/s, 4.13023s/12 iters), loss = 1.91352 +I0410 13:53:19.330585 18353 solver.cpp:237] Train net output #0: loss = 1.91352 (* 1 = 1.91352 loss) +I0410 13:53:19.330598 18353 sgd_solver.cpp:105] Iteration 3276, lr = 0.00522605 +I0410 13:53:24.216610 18353 solver.cpp:218] Iteration 3288 (2.45604 iter/s, 4.8859s/12 iters), loss = 1.989 +I0410 13:53:24.216675 18353 solver.cpp:237] Train net output #0: loss = 1.989 (* 1 = 1.989 loss) +I0410 13:53:24.216689 18353 sgd_solver.cpp:105] Iteration 3288, lr = 0.00521364 +I0410 13:53:29.127517 18353 solver.cpp:218] Iteration 3300 (2.44363 iter/s, 4.91073s/12 iters), loss = 2.23016 +I0410 13:53:29.127601 18353 solver.cpp:237] Train net output #0: loss = 2.23016 (* 1 = 2.23016 loss) +I0410 13:53:29.127614 18353 sgd_solver.cpp:105] Iteration 3300, lr = 0.00520126 +I0410 13:53:34.111251 18353 solver.cpp:218] Iteration 3312 (2.40793 iter/s, 4.98354s/12 iters), loss = 1.89274 +I0410 13:53:34.111292 18353 solver.cpp:237] Train net output #0: loss = 1.89274 (* 1 = 1.89274 loss) +I0410 13:53:34.111302 18353 sgd_solver.cpp:105] Iteration 3312, lr = 0.00518892 +I0410 13:53:39.045847 18353 solver.cpp:218] Iteration 3324 (2.43189 iter/s, 4.93444s/12 iters), loss = 1.87024 +I0410 13:53:39.045898 18353 solver.cpp:237] Train net output #0: loss = 1.87024 (* 1 = 1.87024 loss) +I0410 13:53:39.045909 18353 sgd_solver.cpp:105] Iteration 3324, lr = 0.0051766 +I0410 13:53:43.934546 18353 solver.cpp:218] Iteration 3336 (2.45472 iter/s, 4.88853s/12 iters), loss = 1.85678 +I0410 13:53:43.934603 18353 solver.cpp:237] Train net output #0: loss = 1.85678 (* 1 = 1.85678 loss) +I0410 13:53:43.934617 18353 sgd_solver.cpp:105] Iteration 3336, lr = 0.00516431 +I0410 13:53:44.397042 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:48.860785 18353 solver.cpp:218] Iteration 3348 (2.43602 iter/s, 4.92607s/12 iters), loss = 1.69983 +I0410 13:53:48.860841 18353 solver.cpp:237] Train net output #0: loss = 1.69983 (* 1 = 1.69983 loss) +I0410 13:53:48.860854 18353 sgd_solver.cpp:105] Iteration 3348, lr = 0.00515204 +I0410 13:53:53.766647 18353 solver.cpp:218] Iteration 3360 (2.44614 iter/s, 4.9057s/12 iters), loss = 1.6535 +I0410 13:53:53.766696 18353 solver.cpp:237] Train net output #0: loss = 1.6535 (* 1 = 1.6535 loss) +I0410 13:53:53.766707 18353 sgd_solver.cpp:105] Iteration 3360, lr = 0.00513981 +I0410 13:53:55.775666 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3366.caffemodel +I0410 13:53:56.073750 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3366.solverstate +I0410 13:53:56.272873 18353 solver.cpp:330] Iteration 3366, Testing net (#0) +I0410 13:53:56.272895 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:53:59.420053 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:54:00.779429 18353 solver.cpp:397] Test net output #0: accuracy = 0.412377 +I0410 13:54:00.779466 18353 solver.cpp:397] Test net output #1: loss = 2.40072 (* 1 = 2.40072 loss) +I0410 13:54:02.531808 18353 solver.cpp:218] Iteration 3372 (1.3691 iter/s, 8.76491s/12 iters), loss = 2.01821 +I0410 13:54:02.531865 18353 solver.cpp:237] Train net output #0: loss = 2.01821 (* 1 = 2.01821 loss) +I0410 13:54:02.531877 18353 sgd_solver.cpp:105] Iteration 3372, lr = 0.00512761 +I0410 13:54:07.417285 18353 solver.cpp:218] Iteration 3384 (2.45635 iter/s, 4.8853s/12 iters), loss = 1.61832 +I0410 13:54:07.417346 18353 solver.cpp:237] Train net output #0: loss = 1.61832 (* 1 = 1.61832 loss) +I0410 13:54:07.417359 18353 sgd_solver.cpp:105] Iteration 3384, lr = 0.00511544 +I0410 13:54:12.370230 18353 solver.cpp:218] Iteration 3396 (2.42288 iter/s, 4.95277s/12 iters), loss = 2.01214 +I0410 13:54:12.370275 18353 solver.cpp:237] Train net output #0: loss = 2.01214 (* 1 = 2.01214 loss) +I0410 13:54:12.370285 18353 sgd_solver.cpp:105] Iteration 3396, lr = 0.00510329 +I0410 13:54:17.276569 18353 solver.cpp:218] Iteration 3408 (2.4459 iter/s, 4.90617s/12 iters), loss = 2.1487 +I0410 13:54:17.276628 18353 solver.cpp:237] Train net output #0: loss = 2.1487 (* 1 = 2.1487 loss) +I0410 13:54:17.276641 18353 sgd_solver.cpp:105] Iteration 3408, lr = 0.00509117 +I0410 13:54:22.184651 18353 solver.cpp:218] Iteration 3420 (2.44503 iter/s, 4.90791s/12 iters), loss = 1.68488 +I0410 13:54:22.184701 18353 solver.cpp:237] Train net output #0: loss = 1.68488 (* 1 = 1.68488 loss) +I0410 13:54:22.184711 18353 sgd_solver.cpp:105] Iteration 3420, lr = 0.00507909 +I0410 13:54:27.112494 18353 solver.cpp:218] Iteration 3432 (2.43523 iter/s, 4.92768s/12 iters), loss = 1.76902 +I0410 13:54:27.112547 18353 solver.cpp:237] Train net output #0: loss = 1.76902 (* 1 = 1.76902 loss) +I0410 13:54:27.112560 18353 sgd_solver.cpp:105] Iteration 3432, lr = 0.00506703 +I0410 13:54:29.699939 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:54:32.011375 18353 solver.cpp:218] Iteration 3444 (2.44962 iter/s, 4.89871s/12 iters), loss = 1.58958 +I0410 13:54:32.011426 18353 solver.cpp:237] Train net output #0: loss = 1.58958 (* 1 = 1.58958 loss) +I0410 13:54:32.011438 18353 sgd_solver.cpp:105] Iteration 3444, lr = 0.005055 +I0410 13:54:36.981011 18353 solver.cpp:218] Iteration 3456 (2.41475 iter/s, 4.96946s/12 iters), loss = 1.92716 +I0410 13:54:36.981061 18353 solver.cpp:237] Train net output #0: loss = 1.92716 (* 1 = 1.92716 loss) +I0410 13:54:36.981073 18353 sgd_solver.cpp:105] Iteration 3456, lr = 0.005043 +I0410 13:54:41.391474 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3468.caffemodel +I0410 13:54:42.255647 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3468.solverstate +I0410 13:54:42.476663 18353 solver.cpp:330] Iteration 3468, Testing net (#0) +I0410 13:54:42.476692 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:54:42.499825 18353 blocking_queue.cpp:49] Waiting for data +I0410 13:54:45.580359 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:54:46.987639 18353 solver.cpp:397] Test net output #0: accuracy = 0.40625 +I0410 13:54:46.987687 18353 solver.cpp:397] Test net output #1: loss = 2.41752 (* 1 = 2.41752 loss) +I0410 13:54:47.068944 18353 solver.cpp:218] Iteration 3468 (1.18957 iter/s, 10.0877s/12 iters), loss = 1.85254 +I0410 13:54:47.068997 18353 solver.cpp:237] Train net output #0: loss = 1.85254 (* 1 = 1.85254 loss) +I0410 13:54:47.069010 18353 sgd_solver.cpp:105] Iteration 3468, lr = 0.00503102 +I0410 13:54:51.150470 18353 solver.cpp:218] Iteration 3480 (2.94019 iter/s, 4.08137s/12 iters), loss = 1.86459 +I0410 13:54:51.150511 18353 solver.cpp:237] Train net output #0: loss = 1.86459 (* 1 = 1.86459 loss) +I0410 13:54:51.150521 18353 sgd_solver.cpp:105] Iteration 3480, lr = 0.00501908 +I0410 13:54:55.967957 18353 solver.cpp:218] Iteration 3492 (2.49101 iter/s, 4.81733s/12 iters), loss = 1.83596 +I0410 13:54:55.968011 18353 solver.cpp:237] Train net output #0: loss = 1.83596 (* 1 = 1.83596 loss) +I0410 13:54:55.968024 18353 sgd_solver.cpp:105] Iteration 3492, lr = 0.00500716 +I0410 13:55:00.860098 18353 solver.cpp:218] Iteration 3504 (2.453 iter/s, 4.89197s/12 iters), loss = 1.84695 +I0410 13:55:00.860224 18353 solver.cpp:237] Train net output #0: loss = 1.84695 (* 1 = 1.84695 loss) +I0410 13:55:00.860234 18353 sgd_solver.cpp:105] Iteration 3504, lr = 0.00499527 +I0410 13:55:05.782624 18353 solver.cpp:218] Iteration 3516 (2.43789 iter/s, 4.92228s/12 iters), loss = 1.5922 +I0410 13:55:05.782680 18353 solver.cpp:237] Train net output #0: loss = 1.5922 (* 1 = 1.5922 loss) +I0410 13:55:05.782693 18353 sgd_solver.cpp:105] Iteration 3516, lr = 0.00498341 +I0410 13:55:10.745411 18353 solver.cpp:218] Iteration 3528 (2.41808 iter/s, 4.96261s/12 iters), loss = 1.6908 +I0410 13:55:10.745452 18353 solver.cpp:237] Train net output #0: loss = 1.6908 (* 1 = 1.6908 loss) +I0410 13:55:10.745461 18353 sgd_solver.cpp:105] Iteration 3528, lr = 0.00497158 +I0410 13:55:15.355926 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:55:15.612751 18353 solver.cpp:218] Iteration 3540 (2.4655 iter/s, 4.86717s/12 iters), loss = 1.6195 +I0410 13:55:15.612808 18353 solver.cpp:237] Train net output #0: loss = 1.6195 (* 1 = 1.6195 loss) +I0410 13:55:15.612820 18353 sgd_solver.cpp:105] Iteration 3540, lr = 0.00495978 +I0410 13:55:20.524966 18353 solver.cpp:218] Iteration 3552 (2.44298 iter/s, 4.91204s/12 iters), loss = 1.7352 +I0410 13:55:20.525017 18353 solver.cpp:237] Train net output #0: loss = 1.7352 (* 1 = 1.7352 loss) +I0410 13:55:20.525030 18353 sgd_solver.cpp:105] Iteration 3552, lr = 0.004948 +I0410 13:55:25.498132 18353 solver.cpp:218] Iteration 3564 (2.41304 iter/s, 4.97298s/12 iters), loss = 1.50465 +I0410 13:55:25.498184 18353 solver.cpp:237] Train net output #0: loss = 1.50465 (* 1 = 1.50465 loss) +I0410 13:55:25.498195 18353 sgd_solver.cpp:105] Iteration 3564, lr = 0.00493626 +I0410 13:55:27.530716 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3570.caffemodel +I0410 13:55:27.835461 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3570.solverstate +I0410 13:55:28.031257 18353 solver.cpp:330] Iteration 3570, Testing net (#0) +I0410 13:55:28.031289 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:55:31.207485 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:55:32.614687 18353 solver.cpp:397] Test net output #0: accuracy = 0.409314 +I0410 13:55:32.614737 18353 solver.cpp:397] Test net output #1: loss = 2.48611 (* 1 = 2.48611 loss) +I0410 13:55:34.432185 18353 solver.cpp:218] Iteration 3576 (1.34321 iter/s, 8.93379s/12 iters), loss = 1.88175 +I0410 13:55:34.432238 18353 solver.cpp:237] Train net output #0: loss = 1.88175 (* 1 = 1.88175 loss) +I0410 13:55:34.432250 18353 sgd_solver.cpp:105] Iteration 3576, lr = 0.00492454 +I0410 13:55:39.376101 18353 solver.cpp:218] Iteration 3588 (2.42731 iter/s, 4.94374s/12 iters), loss = 1.56805 +I0410 13:55:39.376155 18353 solver.cpp:237] Train net output #0: loss = 1.56805 (* 1 = 1.56805 loss) +I0410 13:55:39.376168 18353 sgd_solver.cpp:105] Iteration 3588, lr = 0.00491284 +I0410 13:55:44.306408 18353 solver.cpp:218] Iteration 3600 (2.43401 iter/s, 4.93013s/12 iters), loss = 1.85162 +I0410 13:55:44.306466 18353 solver.cpp:237] Train net output #0: loss = 1.85162 (* 1 = 1.85162 loss) +I0410 13:55:44.306479 18353 sgd_solver.cpp:105] Iteration 3600, lr = 0.00490118 +I0410 13:55:49.227891 18353 solver.cpp:218] Iteration 3612 (2.43838 iter/s, 4.9213s/12 iters), loss = 1.7518 +I0410 13:55:49.227950 18353 solver.cpp:237] Train net output #0: loss = 1.7518 (* 1 = 1.7518 loss) +I0410 13:55:49.227964 18353 sgd_solver.cpp:105] Iteration 3612, lr = 0.00488954 +I0410 13:55:54.148192 18353 solver.cpp:218] Iteration 3624 (2.43896 iter/s, 4.92012s/12 iters), loss = 1.99102 +I0410 13:55:54.148245 18353 solver.cpp:237] Train net output #0: loss = 1.99102 (* 1 = 1.99102 loss) +I0410 13:55:54.148258 18353 sgd_solver.cpp:105] Iteration 3624, lr = 0.00487793 +I0410 13:55:59.075017 18353 solver.cpp:218] Iteration 3636 (2.43573 iter/s, 4.92665s/12 iters), loss = 1.64064 +I0410 13:55:59.075067 18353 solver.cpp:237] Train net output #0: loss = 1.64064 (* 1 = 1.64064 loss) +I0410 13:55:59.075079 18353 sgd_solver.cpp:105] Iteration 3636, lr = 0.00486635 +I0410 13:56:00.960935 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:04.060689 18353 solver.cpp:218] Iteration 3648 (2.40698 iter/s, 4.9855s/12 iters), loss = 1.48346 +I0410 13:56:04.060797 18353 solver.cpp:237] Train net output #0: loss = 1.48346 (* 1 = 1.48346 loss) +I0410 13:56:04.060811 18353 sgd_solver.cpp:105] Iteration 3648, lr = 0.0048548 +I0410 13:56:08.946457 18353 solver.cpp:218] Iteration 3660 (2.45623 iter/s, 4.88554s/12 iters), loss = 1.68004 +I0410 13:56:08.946514 18353 solver.cpp:237] Train net output #0: loss = 1.68004 (* 1 = 1.68004 loss) +I0410 13:56:08.946527 18353 sgd_solver.cpp:105] Iteration 3660, lr = 0.00484327 +I0410 13:56:13.347187 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3672.caffemodel +I0410 13:56:13.679590 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3672.solverstate +I0410 13:56:13.883628 18353 solver.cpp:330] Iteration 3672, Testing net (#0) +I0410 13:56:13.883657 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:56:16.840193 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:18.293134 18353 solver.cpp:397] Test net output #0: accuracy = 0.411152 +I0410 13:56:18.293182 18353 solver.cpp:397] Test net output #1: loss = 2.42925 (* 1 = 2.42925 loss) +I0410 13:56:18.374298 18353 solver.cpp:218] Iteration 3672 (1.27286 iter/s, 9.42756s/12 iters), loss = 1.614 +I0410 13:56:18.374352 18353 solver.cpp:237] Train net output #0: loss = 1.614 (* 1 = 1.614 loss) +I0410 13:56:18.374364 18353 sgd_solver.cpp:105] Iteration 3672, lr = 0.00483177 +I0410 13:56:22.634196 18353 solver.cpp:218] Iteration 3684 (2.81707 iter/s, 4.25974s/12 iters), loss = 1.79051 +I0410 13:56:22.634235 18353 solver.cpp:237] Train net output #0: loss = 1.79051 (* 1 = 1.79051 loss) +I0410 13:56:22.634244 18353 sgd_solver.cpp:105] Iteration 3684, lr = 0.0048203 +I0410 13:56:27.507311 18353 solver.cpp:218] Iteration 3696 (2.46257 iter/s, 4.87295s/12 iters), loss = 1.58496 +I0410 13:56:27.507366 18353 solver.cpp:237] Train net output #0: loss = 1.58496 (* 1 = 1.58496 loss) +I0410 13:56:27.507377 18353 sgd_solver.cpp:105] Iteration 3696, lr = 0.00480886 +I0410 13:56:32.436619 18353 solver.cpp:218] Iteration 3708 (2.43451 iter/s, 4.92913s/12 iters), loss = 1.81088 +I0410 13:56:32.436667 18353 solver.cpp:237] Train net output #0: loss = 1.81088 (* 1 = 1.81088 loss) +I0410 13:56:32.436679 18353 sgd_solver.cpp:105] Iteration 3708, lr = 0.00479744 +I0410 13:56:37.354802 18353 solver.cpp:218] Iteration 3720 (2.44001 iter/s, 4.91801s/12 iters), loss = 1.87532 +I0410 13:56:37.354956 18353 solver.cpp:237] Train net output #0: loss = 1.87532 (* 1 = 1.87532 loss) +I0410 13:56:37.354969 18353 sgd_solver.cpp:105] Iteration 3720, lr = 0.00478605 +I0410 13:56:42.326727 18353 solver.cpp:218] Iteration 3732 (2.41369 iter/s, 4.97165s/12 iters), loss = 1.50534 +I0410 13:56:42.326781 18353 solver.cpp:237] Train net output #0: loss = 1.50534 (* 1 = 1.50534 loss) +I0410 13:56:42.326794 18353 sgd_solver.cpp:105] Iteration 3732, lr = 0.00477469 +I0410 13:56:46.374681 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:47.372406 18353 solver.cpp:218] Iteration 3744 (2.37836 iter/s, 5.04549s/12 iters), loss = 1.57691 +I0410 13:56:47.372457 18353 solver.cpp:237] Train net output #0: loss = 1.57691 (* 1 = 1.57691 loss) +I0410 13:56:47.372467 18353 sgd_solver.cpp:105] Iteration 3744, lr = 0.00476335 +I0410 13:56:52.314335 18353 solver.cpp:218] Iteration 3756 (2.42829 iter/s, 4.94175s/12 iters), loss = 1.75745 +I0410 13:56:52.314376 18353 solver.cpp:237] Train net output #0: loss = 1.75745 (* 1 = 1.75745 loss) +I0410 13:56:52.314385 18353 sgd_solver.cpp:105] Iteration 3756, lr = 0.00475204 +I0410 13:56:57.231103 18353 solver.cpp:218] Iteration 3768 (2.44071 iter/s, 4.9166s/12 iters), loss = 1.90461 +I0410 13:56:57.231166 18353 solver.cpp:237] Train net output #0: loss = 1.90461 (* 1 = 1.90461 loss) +I0410 13:56:57.231179 18353 sgd_solver.cpp:105] Iteration 3768, lr = 0.00474076 +I0410 13:56:59.190728 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3774.caffemodel +I0410 13:56:59.848824 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3774.solverstate +I0410 13:57:00.058601 18353 solver.cpp:330] Iteration 3774, Testing net (#0) +I0410 13:57:00.058629 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:57:03.063194 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:04.579468 18353 solver.cpp:397] Test net output #0: accuracy = 0.448529 +I0410 13:57:04.579521 18353 solver.cpp:397] Test net output #1: loss = 2.34371 (* 1 = 2.34371 loss) +I0410 13:57:06.401641 18353 solver.cpp:218] Iteration 3780 (1.30858 iter/s, 9.17025s/12 iters), loss = 1.28139 +I0410 13:57:06.401700 18353 solver.cpp:237] Train net output #0: loss = 1.28139 (* 1 = 1.28139 loss) +I0410 13:57:06.401712 18353 sgd_solver.cpp:105] Iteration 3780, lr = 0.00472951 +I0410 13:57:11.357578 18353 solver.cpp:218] Iteration 3792 (2.42143 iter/s, 4.95576s/12 iters), loss = 1.6356 +I0410 13:57:11.357677 18353 solver.cpp:237] Train net output #0: loss = 1.6356 (* 1 = 1.6356 loss) +I0410 13:57:11.357689 18353 sgd_solver.cpp:105] Iteration 3792, lr = 0.00471828 +I0410 13:57:16.341289 18353 solver.cpp:218] Iteration 3804 (2.40796 iter/s, 4.98348s/12 iters), loss = 1.6767 +I0410 13:57:16.341347 18353 solver.cpp:237] Train net output #0: loss = 1.6767 (* 1 = 1.6767 loss) +I0410 13:57:16.341361 18353 sgd_solver.cpp:105] Iteration 3804, lr = 0.00470707 +I0410 13:57:21.255390 18353 solver.cpp:218] Iteration 3816 (2.44204 iter/s, 4.91392s/12 iters), loss = 1.29898 +I0410 13:57:21.255437 18353 solver.cpp:237] Train net output #0: loss = 1.29898 (* 1 = 1.29898 loss) +I0410 13:57:21.255447 18353 sgd_solver.cpp:105] Iteration 3816, lr = 0.0046959 +I0410 13:57:26.183518 18353 solver.cpp:218] Iteration 3828 (2.43509 iter/s, 4.92795s/12 iters), loss = 1.66493 +I0410 13:57:26.183570 18353 solver.cpp:237] Train net output #0: loss = 1.66493 (* 1 = 1.66493 loss) +I0410 13:57:26.183579 18353 sgd_solver.cpp:105] Iteration 3828, lr = 0.00468475 +I0410 13:57:31.167183 18353 solver.cpp:218] Iteration 3840 (2.40796 iter/s, 4.98348s/12 iters), loss = 1.42886 +I0410 13:57:31.167254 18353 solver.cpp:237] Train net output #0: loss = 1.42886 (* 1 = 1.42886 loss) +I0410 13:57:31.167271 18353 sgd_solver.cpp:105] Iteration 3840, lr = 0.00467363 +I0410 13:57:32.300902 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:36.142433 18353 solver.cpp:218] Iteration 3852 (2.41203 iter/s, 4.97506s/12 iters), loss = 1.49186 +I0410 13:57:36.142482 18353 solver.cpp:237] Train net output #0: loss = 1.49186 (* 1 = 1.49186 loss) +I0410 13:57:36.142491 18353 sgd_solver.cpp:105] Iteration 3852, lr = 0.00466253 +I0410 13:57:41.096594 18353 solver.cpp:218] Iteration 3864 (2.42229 iter/s, 4.95399s/12 iters), loss = 1.36063 +I0410 13:57:41.096639 18353 solver.cpp:237] Train net output #0: loss = 1.36063 (* 1 = 1.36063 loss) +I0410 13:57:41.096649 18353 sgd_solver.cpp:105] Iteration 3864, lr = 0.00465146 +I0410 13:57:45.531167 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3876.caffemodel +I0410 13:57:45.849758 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3876.solverstate +I0410 13:57:46.059979 18353 solver.cpp:330] Iteration 3876, Testing net (#0) +I0410 13:57:46.060007 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:57:48.934324 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:50.474426 18353 solver.cpp:397] Test net output #0: accuracy = 0.406863 +I0410 13:57:50.474465 18353 solver.cpp:397] Test net output #1: loss = 2.56164 (* 1 = 2.56164 loss) +I0410 13:57:50.555913 18353 solver.cpp:218] Iteration 3876 (1.26863 iter/s, 9.45904s/12 iters), loss = 1.44307 +I0410 13:57:50.555967 18353 solver.cpp:237] Train net output #0: loss = 1.44307 (* 1 = 1.44307 loss) +I0410 13:57:50.555977 18353 sgd_solver.cpp:105] Iteration 3876, lr = 0.00464042 +I0410 13:57:54.755039 18353 solver.cpp:218] Iteration 3888 (2.85785 iter/s, 4.19896s/12 iters), loss = 1.67879 +I0410 13:57:54.755089 18353 solver.cpp:237] Train net output #0: loss = 1.67879 (* 1 = 1.67879 loss) +I0410 13:57:54.755100 18353 sgd_solver.cpp:105] Iteration 3888, lr = 0.0046294 +I0410 13:57:59.678004 18353 solver.cpp:218] Iteration 3900 (2.43765 iter/s, 4.92278s/12 iters), loss = 1.50739 +I0410 13:57:59.678053 18353 solver.cpp:237] Train net output #0: loss = 1.50739 (* 1 = 1.50739 loss) +I0410 13:57:59.678063 18353 sgd_solver.cpp:105] Iteration 3900, lr = 0.00461841 +I0410 13:58:04.604776 18353 solver.cpp:218] Iteration 3912 (2.43576 iter/s, 4.92659s/12 iters), loss = 1.50933 +I0410 13:58:04.604821 18353 solver.cpp:237] Train net output #0: loss = 1.50933 (* 1 = 1.50933 loss) +I0410 13:58:04.604832 18353 sgd_solver.cpp:105] Iteration 3912, lr = 0.00460744 +I0410 13:58:09.518885 18353 solver.cpp:218] Iteration 3924 (2.44203 iter/s, 4.91394s/12 iters), loss = 1.58535 +I0410 13:58:09.518927 18353 solver.cpp:237] Train net output #0: loss = 1.58535 (* 1 = 1.58535 loss) +I0410 13:58:09.518937 18353 sgd_solver.cpp:105] Iteration 3924, lr = 0.0045965 +I0410 13:58:14.403676 18353 solver.cpp:218] Iteration 3936 (2.45669 iter/s, 4.88462s/12 iters), loss = 1.35585 +I0410 13:58:14.403717 18353 solver.cpp:237] Train net output #0: loss = 1.35585 (* 1 = 1.35585 loss) +I0410 13:58:14.403725 18353 sgd_solver.cpp:105] Iteration 3936, lr = 0.00458559 +I0410 13:58:17.756521 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:58:19.393201 18353 solver.cpp:218] Iteration 3948 (2.40512 iter/s, 4.98935s/12 iters), loss = 1.36038 +I0410 13:58:19.393255 18353 solver.cpp:237] Train net output #0: loss = 1.36038 (* 1 = 1.36038 loss) +I0410 13:58:19.393270 18353 sgd_solver.cpp:105] Iteration 3948, lr = 0.0045747 +I0410 13:58:24.301466 18353 solver.cpp:218] Iteration 3960 (2.44495 iter/s, 4.90808s/12 iters), loss = 1.20048 +I0410 13:58:24.301517 18353 solver.cpp:237] Train net output #0: loss = 1.20048 (* 1 = 1.20048 loss) +I0410 13:58:24.301527 18353 sgd_solver.cpp:105] Iteration 3960, lr = 0.00456384 +I0410 13:58:29.203214 18353 solver.cpp:218] Iteration 3972 (2.4482 iter/s, 4.90157s/12 iters), loss = 1.30836 +I0410 13:58:29.203271 18353 solver.cpp:237] Train net output #0: loss = 1.30836 (* 1 = 1.30836 loss) +I0410 13:58:29.203284 18353 sgd_solver.cpp:105] Iteration 3972, lr = 0.00455301 +I0410 13:58:31.166640 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3978.caffemodel +I0410 13:58:31.473456 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3978.solverstate +I0410 13:58:31.682641 18353 solver.cpp:330] Iteration 3978, Testing net (#0) +I0410 13:58:31.682668 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:58:34.520434 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:58:36.110832 18353 solver.cpp:397] Test net output #0: accuracy = 0.418505 +I0410 13:58:36.110883 18353 solver.cpp:397] Test net output #1: loss = 2.59685 (* 1 = 2.59685 loss) +I0410 13:58:37.946161 18353 solver.cpp:218] Iteration 3984 (1.37258 iter/s, 8.74267s/12 iters), loss = 1.35089 +I0410 13:58:37.946220 18353 solver.cpp:237] Train net output #0: loss = 1.35089 (* 1 = 1.35089 loss) +I0410 13:58:37.946233 18353 sgd_solver.cpp:105] Iteration 3984, lr = 0.0045422 +I0410 13:58:42.942209 18353 solver.cpp:218] Iteration 3996 (2.40199 iter/s, 4.99585s/12 iters), loss = 1.5281 +I0410 13:58:42.942260 18353 solver.cpp:237] Train net output #0: loss = 1.5281 (* 1 = 1.5281 loss) +I0410 13:58:42.942272 18353 sgd_solver.cpp:105] Iteration 3996, lr = 0.00453141 +I0410 13:58:47.826309 18353 solver.cpp:218] Iteration 4008 (2.45704 iter/s, 4.88392s/12 iters), loss = 1.54976 +I0410 13:58:47.826426 18353 solver.cpp:237] Train net output #0: loss = 1.54976 (* 1 = 1.54976 loss) +I0410 13:58:47.826437 18353 sgd_solver.cpp:105] Iteration 4008, lr = 0.00452066 +I0410 13:58:52.756757 18353 solver.cpp:218] Iteration 4020 (2.43398 iter/s, 4.9302s/12 iters), loss = 1.55771 +I0410 13:58:52.756804 18353 solver.cpp:237] Train net output #0: loss = 1.55771 (* 1 = 1.55771 loss) +I0410 13:58:52.756814 18353 sgd_solver.cpp:105] Iteration 4020, lr = 0.00450992 +I0410 13:58:57.678865 18353 solver.cpp:218] Iteration 4032 (2.43807 iter/s, 4.92193s/12 iters), loss = 1.75936 +I0410 13:58:57.678916 18353 solver.cpp:237] Train net output #0: loss = 1.75936 (* 1 = 1.75936 loss) +I0410 13:58:57.678928 18353 sgd_solver.cpp:105] Iteration 4032, lr = 0.00449921 +I0410 13:59:02.567752 18353 solver.cpp:218] Iteration 4044 (2.45464 iter/s, 4.8887s/12 iters), loss = 1.46169 +I0410 13:59:02.567806 18353 solver.cpp:237] Train net output #0: loss = 1.46169 (* 1 = 1.46169 loss) +I0410 13:59:02.567817 18353 sgd_solver.cpp:105] Iteration 4044, lr = 0.00448853 +I0410 13:59:03.060986 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:07.497151 18353 solver.cpp:218] Iteration 4056 (2.43447 iter/s, 4.92921s/12 iters), loss = 1.44946 +I0410 13:59:07.497254 18353 solver.cpp:237] Train net output #0: loss = 1.44946 (* 1 = 1.44946 loss) +I0410 13:59:07.497269 18353 sgd_solver.cpp:105] Iteration 4056, lr = 0.00447788 +I0410 13:59:12.344678 18353 solver.cpp:218] Iteration 4068 (2.4756 iter/s, 4.8473s/12 iters), loss = 1.49567 +I0410 13:59:12.344731 18353 solver.cpp:237] Train net output #0: loss = 1.49567 (* 1 = 1.49567 loss) +I0410 13:59:12.344744 18353 sgd_solver.cpp:105] Iteration 4068, lr = 0.00446724 +I0410 13:59:16.905570 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4080.caffemodel +I0410 13:59:17.223898 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4080.solverstate +I0410 13:59:17.431499 18353 solver.cpp:330] Iteration 4080, Testing net (#0) +I0410 13:59:17.431525 18353 net.cpp:676] Ignoring source layer train-data +I0410 13:59:20.236210 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:21.981973 18353 solver.cpp:397] Test net output #0: accuracy = 0.426471 +I0410 13:59:21.982024 18353 solver.cpp:397] Test net output #1: loss = 2.44497 (* 1 = 2.44497 loss) +I0410 13:59:22.064462 18353 solver.cpp:218] Iteration 4080 (1.23463 iter/s, 9.71949s/12 iters), loss = 1.45275 +I0410 13:59:22.064512 18353 solver.cpp:237] Train net output #0: loss = 1.45275 (* 1 = 1.45275 loss) +I0410 13:59:22.064522 18353 sgd_solver.cpp:105] Iteration 4080, lr = 0.00445664 +I0410 13:59:26.223518 18353 solver.cpp:218] Iteration 4092 (2.88538 iter/s, 4.1589s/12 iters), loss = 1.49643 +I0410 13:59:26.223572 18353 solver.cpp:237] Train net output #0: loss = 1.49643 (* 1 = 1.49643 loss) +I0410 13:59:26.223585 18353 sgd_solver.cpp:105] Iteration 4092, lr = 0.00444606 +I0410 13:59:31.279194 18353 solver.cpp:218] Iteration 4104 (2.37366 iter/s, 5.05549s/12 iters), loss = 1.36383 +I0410 13:59:31.279244 18353 solver.cpp:237] Train net output #0: loss = 1.36383 (* 1 = 1.36383 loss) +I0410 13:59:31.279256 18353 sgd_solver.cpp:105] Iteration 4104, lr = 0.0044355 +I0410 13:59:36.147090 18353 solver.cpp:218] Iteration 4116 (2.46522 iter/s, 4.86772s/12 iters), loss = 1.6937 +I0410 13:59:36.147138 18353 solver.cpp:237] Train net output #0: loss = 1.6937 (* 1 = 1.6937 loss) +I0410 13:59:36.147147 18353 sgd_solver.cpp:105] Iteration 4116, lr = 0.00442497 +I0410 13:59:41.048689 18353 solver.cpp:218] Iteration 4128 (2.44827 iter/s, 4.90142s/12 iters), loss = 1.28422 +I0410 13:59:41.048734 18353 solver.cpp:237] Train net output #0: loss = 1.28422 (* 1 = 1.28422 loss) +I0410 13:59:41.048744 18353 sgd_solver.cpp:105] Iteration 4128, lr = 0.00441447 +I0410 13:59:46.039047 18353 solver.cpp:218] Iteration 4140 (2.40473 iter/s, 4.99017s/12 iters), loss = 1.37031 +I0410 13:59:46.039096 18353 solver.cpp:237] Train net output #0: loss = 1.37031 (* 1 = 1.37031 loss) +I0410 13:59:46.039108 18353 sgd_solver.cpp:105] Iteration 4140, lr = 0.00440398 +I0410 13:59:48.612550 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:50.927711 18353 solver.cpp:218] Iteration 4152 (2.45475 iter/s, 4.88849s/12 iters), loss = 1.30111 +I0410 13:59:50.927805 18353 solver.cpp:237] Train net output #0: loss = 1.30111 (* 1 = 1.30111 loss) +I0410 13:59:50.927816 18353 sgd_solver.cpp:105] Iteration 4152, lr = 0.00439353 +I0410 13:59:50.927991 18353 blocking_queue.cpp:49] Waiting for data +I0410 13:59:55.949334 18353 solver.cpp:218] Iteration 4164 (2.38977 iter/s, 5.0214s/12 iters), loss = 1.51898 +I0410 13:59:55.949381 18353 solver.cpp:237] Train net output #0: loss = 1.51898 (* 1 = 1.51898 loss) +I0410 13:59:55.949391 18353 sgd_solver.cpp:105] Iteration 4164, lr = 0.0043831 +I0410 14:00:01.312629 18353 solver.cpp:218] Iteration 4176 (2.23751 iter/s, 5.3631s/12 iters), loss = 1.35523 +I0410 14:00:01.312678 18353 solver.cpp:237] Train net output #0: loss = 1.35523 (* 1 = 1.35523 loss) +I0410 14:00:01.312688 18353 sgd_solver.cpp:105] Iteration 4176, lr = 0.00437269 +I0410 14:00:03.327309 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4182.caffemodel +I0410 14:00:04.197429 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4182.solverstate +I0410 14:00:04.541380 18353 solver.cpp:330] Iteration 4182, Testing net (#0) +I0410 14:00:04.541406 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:00:07.505839 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:09.160324 18353 solver.cpp:397] Test net output #0: accuracy = 0.426471 +I0410 14:00:09.160356 18353 solver.cpp:397] Test net output #1: loss = 2.54183 (* 1 = 2.54183 loss) +I0410 14:00:11.015223 18353 solver.cpp:218] Iteration 4188 (1.23682 iter/s, 9.7023s/12 iters), loss = 1.16912 +I0410 14:00:11.015265 18353 solver.cpp:237] Train net output #0: loss = 1.16912 (* 1 = 1.16912 loss) +I0410 14:00:11.015275 18353 sgd_solver.cpp:105] Iteration 4188, lr = 0.00436231 +I0410 14:00:15.968037 18353 solver.cpp:218] Iteration 4200 (2.42295 iter/s, 4.95264s/12 iters), loss = 1.55696 +I0410 14:00:15.968091 18353 solver.cpp:237] Train net output #0: loss = 1.55696 (* 1 = 1.55696 loss) +I0410 14:00:15.968102 18353 sgd_solver.cpp:105] Iteration 4200, lr = 0.00435195 +I0410 14:00:20.809840 18353 solver.cpp:218] Iteration 4212 (2.47851 iter/s, 4.84162s/12 iters), loss = 1.26365 +I0410 14:00:20.809885 18353 solver.cpp:237] Train net output #0: loss = 1.26365 (* 1 = 1.26365 loss) +I0410 14:00:20.809895 18353 sgd_solver.cpp:105] Iteration 4212, lr = 0.00434162 +I0410 14:00:25.698807 18353 solver.cpp:218] Iteration 4224 (2.45459 iter/s, 4.88879s/12 iters), loss = 1.31941 +I0410 14:00:25.698931 18353 solver.cpp:237] Train net output #0: loss = 1.31941 (* 1 = 1.31941 loss) +I0410 14:00:25.698943 18353 sgd_solver.cpp:105] Iteration 4224, lr = 0.00433131 +I0410 14:00:30.642099 18353 solver.cpp:218] Iteration 4236 (2.42766 iter/s, 4.94303s/12 iters), loss = 1.40409 +I0410 14:00:30.642158 18353 solver.cpp:237] Train net output #0: loss = 1.40409 (* 1 = 1.40409 loss) +I0410 14:00:30.642170 18353 sgd_solver.cpp:105] Iteration 4236, lr = 0.00432103 +I0410 14:00:35.275243 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:35.501474 18353 solver.cpp:218] Iteration 4248 (2.46955 iter/s, 4.85919s/12 iters), loss = 1.36637 +I0410 14:00:35.501535 18353 solver.cpp:237] Train net output #0: loss = 1.36637 (* 1 = 1.36637 loss) +I0410 14:00:35.501549 18353 sgd_solver.cpp:105] Iteration 4248, lr = 0.00431077 +I0410 14:00:40.464879 18353 solver.cpp:218] Iteration 4260 (2.41779 iter/s, 4.96321s/12 iters), loss = 1.36796 +I0410 14:00:40.464934 18353 solver.cpp:237] Train net output #0: loss = 1.36796 (* 1 = 1.36796 loss) +I0410 14:00:40.464948 18353 sgd_solver.cpp:105] Iteration 4260, lr = 0.00430053 +I0410 14:00:45.368072 18353 solver.cpp:218] Iteration 4272 (2.44748 iter/s, 4.903s/12 iters), loss = 1.1717 +I0410 14:00:45.368124 18353 solver.cpp:237] Train net output #0: loss = 1.1717 (* 1 = 1.1717 loss) +I0410 14:00:45.368135 18353 sgd_solver.cpp:105] Iteration 4272, lr = 0.00429032 +I0410 14:00:49.853034 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4284.caffemodel +I0410 14:00:50.170987 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4284.solverstate +I0410 14:00:50.381084 18353 solver.cpp:330] Iteration 4284, Testing net (#0) +I0410 14:00:50.381114 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:00:53.216172 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:54.904783 18353 solver.cpp:397] Test net output #0: accuracy = 0.430147 +I0410 14:00:54.904835 18353 solver.cpp:397] Test net output #1: loss = 2.39067 (* 1 = 2.39067 loss) +I0410 14:00:54.986205 18353 solver.cpp:218] Iteration 4284 (1.24768 iter/s, 9.61784s/12 iters), loss = 1.4687 +I0410 14:00:54.986254 18353 solver.cpp:237] Train net output #0: loss = 1.4687 (* 1 = 1.4687 loss) +I0410 14:00:54.986268 18353 sgd_solver.cpp:105] Iteration 4284, lr = 0.00428014 +I0410 14:00:59.266633 18353 solver.cpp:218] Iteration 4296 (2.80357 iter/s, 4.28026s/12 iters), loss = 1.66026 +I0410 14:00:59.266717 18353 solver.cpp:237] Train net output #0: loss = 1.66026 (* 1 = 1.66026 loss) +I0410 14:00:59.266731 18353 sgd_solver.cpp:105] Iteration 4296, lr = 0.00426998 +I0410 14:01:04.187674 18353 solver.cpp:218] Iteration 4308 (2.43862 iter/s, 4.92083s/12 iters), loss = 1.37067 +I0410 14:01:04.187721 18353 solver.cpp:237] Train net output #0: loss = 1.37067 (* 1 = 1.37067 loss) +I0410 14:01:04.187731 18353 sgd_solver.cpp:105] Iteration 4308, lr = 0.00425984 +I0410 14:01:09.142001 18353 solver.cpp:218] Iteration 4320 (2.42221 iter/s, 4.95415s/12 iters), loss = 1.41673 +I0410 14:01:09.142048 18353 solver.cpp:237] Train net output #0: loss = 1.41673 (* 1 = 1.41673 loss) +I0410 14:01:09.142058 18353 sgd_solver.cpp:105] Iteration 4320, lr = 0.00424972 +I0410 14:01:14.021447 18353 solver.cpp:218] Iteration 4332 (2.45939 iter/s, 4.87926s/12 iters), loss = 1.48246 +I0410 14:01:14.021507 18353 solver.cpp:237] Train net output #0: loss = 1.48246 (* 1 = 1.48246 loss) +I0410 14:01:14.021519 18353 sgd_solver.cpp:105] Iteration 4332, lr = 0.00423964 +I0410 14:01:19.020776 18353 solver.cpp:218] Iteration 4344 (2.40042 iter/s, 4.99913s/12 iters), loss = 1.25341 +I0410 14:01:19.020834 18353 solver.cpp:237] Train net output #0: loss = 1.25341 (* 1 = 1.25341 loss) +I0410 14:01:19.020848 18353 sgd_solver.cpp:105] Iteration 4344, lr = 0.00422957 +I0410 14:01:20.851737 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:01:23.894788 18353 solver.cpp:218] Iteration 4356 (2.46213 iter/s, 4.87383s/12 iters), loss = 1.38645 +I0410 14:01:23.894840 18353 solver.cpp:237] Train net output #0: loss = 1.38645 (* 1 = 1.38645 loss) +I0410 14:01:23.894851 18353 sgd_solver.cpp:105] Iteration 4356, lr = 0.00421953 +I0410 14:01:28.794024 18353 solver.cpp:218] Iteration 4368 (2.44946 iter/s, 4.89905s/12 iters), loss = 1.18445 +I0410 14:01:28.794078 18353 solver.cpp:237] Train net output #0: loss = 1.18445 (* 1 = 1.18445 loss) +I0410 14:01:28.794091 18353 sgd_solver.cpp:105] Iteration 4368, lr = 0.00420951 +I0410 14:01:34.146457 18353 solver.cpp:218] Iteration 4380 (2.24205 iter/s, 5.35224s/12 iters), loss = 1.42162 +I0410 14:01:34.157761 18353 solver.cpp:237] Train net output #0: loss = 1.42162 (* 1 = 1.42162 loss) +I0410 14:01:34.157774 18353 sgd_solver.cpp:105] Iteration 4380, lr = 0.00419952 +I0410 14:01:36.129391 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4386.caffemodel +I0410 14:01:36.461992 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4386.solverstate +I0410 14:01:36.671322 18353 solver.cpp:330] Iteration 4386, Testing net (#0) +I0410 14:01:36.671345 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:01:39.407163 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:01:41.223201 18353 solver.cpp:397] Test net output #0: accuracy = 0.463848 +I0410 14:01:41.223235 18353 solver.cpp:397] Test net output #1: loss = 2.31559 (* 1 = 2.31559 loss) +I0410 14:01:43.116909 18353 solver.cpp:218] Iteration 4392 (1.33945 iter/s, 8.95892s/12 iters), loss = 1.15617 +I0410 14:01:43.116966 18353 solver.cpp:237] Train net output #0: loss = 1.15617 (* 1 = 1.15617 loss) +I0410 14:01:43.116978 18353 sgd_solver.cpp:105] Iteration 4392, lr = 0.00418954 +I0410 14:01:48.070022 18353 solver.cpp:218] Iteration 4404 (2.42281 iter/s, 4.95292s/12 iters), loss = 1.40094 +I0410 14:01:48.070076 18353 solver.cpp:237] Train net output #0: loss = 1.40094 (* 1 = 1.40094 loss) +I0410 14:01:48.070088 18353 sgd_solver.cpp:105] Iteration 4404, lr = 0.0041796 +I0410 14:01:52.962445 18353 solver.cpp:218] Iteration 4416 (2.45287 iter/s, 4.89223s/12 iters), loss = 1.1402 +I0410 14:01:52.962500 18353 solver.cpp:237] Train net output #0: loss = 1.1402 (* 1 = 1.1402 loss) +I0410 14:01:52.962512 18353 sgd_solver.cpp:105] Iteration 4416, lr = 0.00416967 +I0410 14:01:57.905905 18353 solver.cpp:218] Iteration 4428 (2.42754 iter/s, 4.94327s/12 iters), loss = 1.15563 +I0410 14:01:57.905968 18353 solver.cpp:237] Train net output #0: loss = 1.15563 (* 1 = 1.15563 loss) +I0410 14:01:57.905978 18353 sgd_solver.cpp:105] Iteration 4428, lr = 0.00415977 +I0410 14:02:02.911180 18353 solver.cpp:218] Iteration 4440 (2.39756 iter/s, 5.00509s/12 iters), loss = 1.26739 +I0410 14:02:02.911234 18353 solver.cpp:237] Train net output #0: loss = 1.26739 (* 1 = 1.26739 loss) +I0410 14:02:02.911247 18353 sgd_solver.cpp:105] Iteration 4440, lr = 0.0041499 +I0410 14:02:06.895454 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:07.842903 18353 solver.cpp:218] Iteration 4452 (2.43332 iter/s, 4.93153s/12 iters), loss = 1.07145 +I0410 14:02:07.842962 18353 solver.cpp:237] Train net output #0: loss = 1.07145 (* 1 = 1.07145 loss) +I0410 14:02:07.842975 18353 sgd_solver.cpp:105] Iteration 4452, lr = 0.00414005 +I0410 14:02:12.805490 18353 solver.cpp:218] Iteration 4464 (2.41819 iter/s, 4.96239s/12 iters), loss = 1.42448 +I0410 14:02:12.805548 18353 solver.cpp:237] Train net output #0: loss = 1.42448 (* 1 = 1.42448 loss) +I0410 14:02:12.805562 18353 sgd_solver.cpp:105] Iteration 4464, lr = 0.00413022 +I0410 14:02:17.730872 18353 solver.cpp:218] Iteration 4476 (2.43645 iter/s, 4.92519s/12 iters), loss = 1.12103 +I0410 14:02:17.730918 18353 solver.cpp:237] Train net output #0: loss = 1.12103 (* 1 = 1.12103 loss) +I0410 14:02:17.730927 18353 sgd_solver.cpp:105] Iteration 4476, lr = 0.00412041 +I0410 14:02:22.153439 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4488.caffemodel +I0410 14:02:22.511227 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4488.solverstate +I0410 14:02:22.716478 18353 solver.cpp:330] Iteration 4488, Testing net (#0) +I0410 14:02:22.716501 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:02:25.503085 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:27.305495 18353 solver.cpp:397] Test net output #0: accuracy = 0.45098 +I0410 14:02:27.305538 18353 solver.cpp:397] Test net output #1: loss = 2.4038 (* 1 = 2.4038 loss) +I0410 14:02:27.387152 18353 solver.cpp:218] Iteration 4488 (1.24275 iter/s, 9.65598s/12 iters), loss = 1.08103 +I0410 14:02:27.387203 18353 solver.cpp:237] Train net output #0: loss = 1.08103 (* 1 = 1.08103 loss) +I0410 14:02:27.387214 18353 sgd_solver.cpp:105] Iteration 4488, lr = 0.00411063 +I0410 14:02:31.719975 18353 solver.cpp:218] Iteration 4500 (2.76967 iter/s, 4.33265s/12 iters), loss = 1.08215 +I0410 14:02:31.720031 18353 solver.cpp:237] Train net output #0: loss = 1.08215 (* 1 = 1.08215 loss) +I0410 14:02:31.720041 18353 sgd_solver.cpp:105] Iteration 4500, lr = 0.00410087 +I0410 14:02:36.633400 18353 solver.cpp:218] Iteration 4512 (2.44238 iter/s, 4.91323s/12 iters), loss = 1.22718 +I0410 14:02:36.633452 18353 solver.cpp:237] Train net output #0: loss = 1.22718 (* 1 = 1.22718 loss) +I0410 14:02:36.633466 18353 sgd_solver.cpp:105] Iteration 4512, lr = 0.00409113 +I0410 14:02:41.555280 18353 solver.cpp:218] Iteration 4524 (2.43819 iter/s, 4.92169s/12 iters), loss = 1.15856 +I0410 14:02:41.555425 18353 solver.cpp:237] Train net output #0: loss = 1.15856 (* 1 = 1.15856 loss) +I0410 14:02:41.555438 18353 sgd_solver.cpp:105] Iteration 4524, lr = 0.00408142 +I0410 14:02:46.421232 18353 solver.cpp:218] Iteration 4536 (2.46626 iter/s, 4.86567s/12 iters), loss = 0.911608 +I0410 14:02:46.421283 18353 solver.cpp:237] Train net output #0: loss = 0.911608 (* 1 = 0.911608 loss) +I0410 14:02:46.421293 18353 sgd_solver.cpp:105] Iteration 4536, lr = 0.00407173 +I0410 14:02:51.401795 18353 solver.cpp:218] Iteration 4548 (2.40946 iter/s, 4.98037s/12 iters), loss = 0.927532 +I0410 14:02:51.401850 18353 solver.cpp:237] Train net output #0: loss = 0.927532 (* 1 = 0.927532 loss) +I0410 14:02:51.401861 18353 sgd_solver.cpp:105] Iteration 4548, lr = 0.00406206 +I0410 14:02:52.620151 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:56.246757 18353 solver.cpp:218] Iteration 4560 (2.4769 iter/s, 4.84477s/12 iters), loss = 1.13474 +I0410 14:02:56.246799 18353 solver.cpp:237] Train net output #0: loss = 1.13474 (* 1 = 1.13474 loss) +I0410 14:02:56.246809 18353 sgd_solver.cpp:105] Iteration 4560, lr = 0.00405242 +I0410 14:03:01.207598 18353 solver.cpp:218] Iteration 4572 (2.41903 iter/s, 4.96066s/12 iters), loss = 1.15158 +I0410 14:03:01.207650 18353 solver.cpp:237] Train net output #0: loss = 1.15158 (* 1 = 1.15158 loss) +I0410 14:03:01.207661 18353 sgd_solver.cpp:105] Iteration 4572, lr = 0.0040428 +I0410 14:03:06.064555 18353 solver.cpp:218] Iteration 4584 (2.47078 iter/s, 4.85677s/12 iters), loss = 1.40769 +I0410 14:03:06.064604 18353 solver.cpp:237] Train net output #0: loss = 1.40769 (* 1 = 1.40769 loss) +I0410 14:03:06.064615 18353 sgd_solver.cpp:105] Iteration 4584, lr = 0.0040332 +I0410 14:03:08.181063 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4590.caffemodel +I0410 14:03:08.903422 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4590.solverstate +I0410 14:03:09.106135 18353 solver.cpp:330] Iteration 4590, Testing net (#0) +I0410 14:03:09.106156 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:03:11.678071 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:13.489878 18353 solver.cpp:397] Test net output #0: accuracy = 0.452206 +I0410 14:03:13.489923 18353 solver.cpp:397] Test net output #1: loss = 2.36515 (* 1 = 2.36515 loss) +I0410 14:03:15.362236 18353 solver.cpp:218] Iteration 4596 (1.29069 iter/s, 9.29739s/12 iters), loss = 1.24643 +I0410 14:03:15.362287 18353 solver.cpp:237] Train net output #0: loss = 1.24643 (* 1 = 1.24643 loss) +I0410 14:03:15.362298 18353 sgd_solver.cpp:105] Iteration 4596, lr = 0.00402362 +I0410 14:03:20.241621 18353 solver.cpp:218] Iteration 4608 (2.45942 iter/s, 4.8792s/12 iters), loss = 1.01562 +I0410 14:03:20.241662 18353 solver.cpp:237] Train net output #0: loss = 1.01562 (* 1 = 1.01562 loss) +I0410 14:03:20.241670 18353 sgd_solver.cpp:105] Iteration 4608, lr = 0.00401407 +I0410 14:03:25.085870 18353 solver.cpp:218] Iteration 4620 (2.47726 iter/s, 4.84407s/12 iters), loss = 0.904701 +I0410 14:03:25.085923 18353 solver.cpp:237] Train net output #0: loss = 0.904701 (* 1 = 0.904701 loss) +I0410 14:03:25.085935 18353 sgd_solver.cpp:105] Iteration 4620, lr = 0.00400454 +I0410 14:03:29.976976 18353 solver.cpp:218] Iteration 4632 (2.45353 iter/s, 4.89091s/12 iters), loss = 1.254 +I0410 14:03:29.977035 18353 solver.cpp:237] Train net output #0: loss = 1.254 (* 1 = 1.254 loss) +I0410 14:03:29.977047 18353 sgd_solver.cpp:105] Iteration 4632, lr = 0.00399503 +I0410 14:03:34.946321 18353 solver.cpp:218] Iteration 4644 (2.4149 iter/s, 4.96915s/12 iters), loss = 1.26888 +I0410 14:03:34.946374 18353 solver.cpp:237] Train net output #0: loss = 1.26888 (* 1 = 1.26888 loss) +I0410 14:03:34.946384 18353 sgd_solver.cpp:105] Iteration 4644, lr = 0.00398555 +I0410 14:03:38.316803 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:39.879413 18353 solver.cpp:218] Iteration 4656 (2.43265 iter/s, 4.9329s/12 iters), loss = 1.00222 +I0410 14:03:39.879464 18353 solver.cpp:237] Train net output #0: loss = 1.00222 (* 1 = 1.00222 loss) +I0410 14:03:39.879477 18353 sgd_solver.cpp:105] Iteration 4656, lr = 0.00397608 +I0410 14:03:44.789042 18353 solver.cpp:218] Iteration 4668 (2.44427 iter/s, 4.90944s/12 iters), loss = 1.165 +I0410 14:03:44.789157 18353 solver.cpp:237] Train net output #0: loss = 1.165 (* 1 = 1.165 loss) +I0410 14:03:44.789170 18353 sgd_solver.cpp:105] Iteration 4668, lr = 0.00396664 +I0410 14:03:50.016512 18353 solver.cpp:218] Iteration 4680 (2.29568 iter/s, 5.22721s/12 iters), loss = 1.05062 +I0410 14:03:50.016557 18353 solver.cpp:237] Train net output #0: loss = 1.05062 (* 1 = 1.05062 loss) +I0410 14:03:50.016567 18353 sgd_solver.cpp:105] Iteration 4680, lr = 0.00395723 +I0410 14:03:54.453541 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4692.caffemodel +I0410 14:03:54.753439 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4692.solverstate +I0410 14:03:54.945390 18353 solver.cpp:330] Iteration 4692, Testing net (#0) +I0410 14:03:54.945410 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:03:57.424165 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:59.271379 18353 solver.cpp:397] Test net output #0: accuracy = 0.455882 +I0410 14:03:59.271418 18353 solver.cpp:397] Test net output #1: loss = 2.4423 (* 1 = 2.4423 loss) +I0410 14:03:59.352795 18353 solver.cpp:218] Iteration 4692 (1.28535 iter/s, 9.33599s/12 iters), loss = 1.06474 +I0410 14:03:59.352859 18353 solver.cpp:237] Train net output #0: loss = 1.06474 (* 1 = 1.06474 loss) +I0410 14:03:59.352874 18353 sgd_solver.cpp:105] Iteration 4692, lr = 0.00394783 +I0410 14:04:03.622735 18353 solver.cpp:218] Iteration 4704 (2.81046 iter/s, 4.26976s/12 iters), loss = 1.38137 +I0410 14:04:03.622773 18353 solver.cpp:237] Train net output #0: loss = 1.38137 (* 1 = 1.38137 loss) +I0410 14:04:03.622782 18353 sgd_solver.cpp:105] Iteration 4704, lr = 0.00393846 +I0410 14:04:08.541153 18353 solver.cpp:218] Iteration 4716 (2.4399 iter/s, 4.91824s/12 iters), loss = 1.15609 +I0410 14:04:08.541209 18353 solver.cpp:237] Train net output #0: loss = 1.15609 (* 1 = 1.15609 loss) +I0410 14:04:08.541222 18353 sgd_solver.cpp:105] Iteration 4716, lr = 0.00392911 +I0410 14:04:13.462571 18353 solver.cpp:218] Iteration 4728 (2.43842 iter/s, 4.92123s/12 iters), loss = 1.14382 +I0410 14:04:13.462615 18353 solver.cpp:237] Train net output #0: loss = 1.14382 (* 1 = 1.14382 loss) +I0410 14:04:13.462623 18353 sgd_solver.cpp:105] Iteration 4728, lr = 0.00391978 +I0410 14:04:18.374457 18353 solver.cpp:218] Iteration 4740 (2.44315 iter/s, 4.9117s/12 iters), loss = 1.03227 +I0410 14:04:18.374598 18353 solver.cpp:237] Train net output #0: loss = 1.03227 (* 1 = 1.03227 loss) +I0410 14:04:18.374608 18353 sgd_solver.cpp:105] Iteration 4740, lr = 0.00391047 +I0410 14:04:23.292039 18353 solver.cpp:218] Iteration 4752 (2.44036 iter/s, 4.91731s/12 iters), loss = 1.09029 +I0410 14:04:23.292088 18353 solver.cpp:237] Train net output #0: loss = 1.09029 (* 1 = 1.09029 loss) +I0410 14:04:23.292100 18353 sgd_solver.cpp:105] Iteration 4752, lr = 0.00390119 +I0410 14:04:23.813587 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:04:28.201828 18353 solver.cpp:218] Iteration 4764 (2.44419 iter/s, 4.9096s/12 iters), loss = 1.05631 +I0410 14:04:28.201884 18353 solver.cpp:237] Train net output #0: loss = 1.05631 (* 1 = 1.05631 loss) +I0410 14:04:28.201896 18353 sgd_solver.cpp:105] Iteration 4764, lr = 0.00389193 +I0410 14:04:33.077327 18353 solver.cpp:218] Iteration 4776 (2.46138 iter/s, 4.87531s/12 iters), loss = 0.932104 +I0410 14:04:33.077379 18353 solver.cpp:237] Train net output #0: loss = 0.932104 (* 1 = 0.932104 loss) +I0410 14:04:33.077392 18353 sgd_solver.cpp:105] Iteration 4776, lr = 0.00388269 +I0410 14:04:37.994797 18353 solver.cpp:218] Iteration 4788 (2.44037 iter/s, 4.91728s/12 iters), loss = 1.08139 +I0410 14:04:37.994853 18353 solver.cpp:237] Train net output #0: loss = 1.08139 (* 1 = 1.08139 loss) +I0410 14:04:37.994865 18353 sgd_solver.cpp:105] Iteration 4788, lr = 0.00387347 +I0410 14:04:39.996443 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4794.caffemodel +I0410 14:04:40.337741 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4794.solverstate +I0410 14:04:40.568343 18353 solver.cpp:330] Iteration 4794, Testing net (#0) +I0410 14:04:40.568374 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:04:43.169656 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:04:45.168460 18353 solver.cpp:397] Test net output #0: accuracy = 0.471814 +I0410 14:04:45.168509 18353 solver.cpp:397] Test net output #1: loss = 2.3401 (* 1 = 2.3401 loss) +I0410 14:04:46.931562 18353 solver.cpp:218] Iteration 4800 (1.34281 iter/s, 8.93647s/12 iters), loss = 1.10191 +I0410 14:04:46.931609 18353 solver.cpp:237] Train net output #0: loss = 1.10191 (* 1 = 1.10191 loss) +I0410 14:04:46.931620 18353 sgd_solver.cpp:105] Iteration 4800, lr = 0.00386427 +I0410 14:04:51.918498 18353 solver.cpp:218] Iteration 4812 (2.40637 iter/s, 4.98675s/12 iters), loss = 1.08118 +I0410 14:04:51.918601 18353 solver.cpp:237] Train net output #0: loss = 1.08118 (* 1 = 1.08118 loss) +I0410 14:04:51.918613 18353 sgd_solver.cpp:105] Iteration 4812, lr = 0.0038551 +I0410 14:04:56.863299 18353 solver.cpp:218] Iteration 4824 (2.42691 iter/s, 4.94456s/12 iters), loss = 1.20497 +I0410 14:04:56.863353 18353 solver.cpp:237] Train net output #0: loss = 1.20497 (* 1 = 1.20497 loss) +I0410 14:04:56.863365 18353 sgd_solver.cpp:105] Iteration 4824, lr = 0.00384594 +I0410 14:05:01.915419 18353 solver.cpp:218] Iteration 4836 (2.37533 iter/s, 5.05193s/12 iters), loss = 0.941107 +I0410 14:05:01.915475 18353 solver.cpp:237] Train net output #0: loss = 0.941107 (* 1 = 0.941107 loss) +I0410 14:05:01.915488 18353 sgd_solver.cpp:105] Iteration 4836, lr = 0.00383681 +I0410 14:05:02.296501 18353 blocking_queue.cpp:49] Waiting for data +I0410 14:05:06.918074 18353 solver.cpp:218] Iteration 4848 (2.39883 iter/s, 5.00244s/12 iters), loss = 1.17652 +I0410 14:05:06.918131 18353 solver.cpp:237] Train net output #0: loss = 1.17652 (* 1 = 1.17652 loss) +I0410 14:05:06.918146 18353 sgd_solver.cpp:105] Iteration 4848, lr = 0.0038277 +I0410 14:05:09.515722 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:11.836706 18353 solver.cpp:218] Iteration 4860 (2.4398 iter/s, 4.91844s/12 iters), loss = 0.993077 +I0410 14:05:11.836747 18353 solver.cpp:237] Train net output #0: loss = 0.993077 (* 1 = 0.993077 loss) +I0410 14:05:11.836755 18353 sgd_solver.cpp:105] Iteration 4860, lr = 0.00381862 +I0410 14:05:16.763666 18353 solver.cpp:218] Iteration 4872 (2.43567 iter/s, 4.92678s/12 iters), loss = 1.07611 +I0410 14:05:16.763718 18353 solver.cpp:237] Train net output #0: loss = 1.07611 (* 1 = 1.07611 loss) +I0410 14:05:16.763729 18353 sgd_solver.cpp:105] Iteration 4872, lr = 0.00380955 +I0410 14:05:21.707432 18353 solver.cpp:218] Iteration 4884 (2.4274 iter/s, 4.94357s/12 iters), loss = 1.11437 +I0410 14:05:21.707485 18353 solver.cpp:237] Train net output #0: loss = 1.11437 (* 1 = 1.11437 loss) +I0410 14:05:21.707499 18353 sgd_solver.cpp:105] Iteration 4884, lr = 0.0038005 +I0410 14:05:26.124266 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4896.caffemodel +I0410 14:05:26.588547 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4896.solverstate +I0410 14:05:26.834033 18353 solver.cpp:330] Iteration 4896, Testing net (#0) +I0410 14:05:26.834053 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:05:29.303061 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:31.230383 18353 solver.cpp:397] Test net output #0: accuracy = 0.492647 +I0410 14:05:31.230418 18353 solver.cpp:397] Test net output #1: loss = 2.18453 (* 1 = 2.18453 loss) +I0410 14:05:31.311601 18353 solver.cpp:218] Iteration 4896 (1.2495 iter/s, 9.60386s/12 iters), loss = 0.927349 +I0410 14:05:31.311642 18353 solver.cpp:237] Train net output #0: loss = 0.927349 (* 1 = 0.927349 loss) +I0410 14:05:31.311650 18353 sgd_solver.cpp:105] Iteration 4896, lr = 0.00379148 +I0410 14:05:35.416991 18353 solver.cpp:218] Iteration 4908 (2.9231 iter/s, 4.10523s/12 iters), loss = 1.17862 +I0410 14:05:35.417038 18353 solver.cpp:237] Train net output #0: loss = 1.17862 (* 1 = 1.17862 loss) +I0410 14:05:35.417048 18353 sgd_solver.cpp:105] Iteration 4908, lr = 0.00378248 +I0410 14:05:40.404382 18353 solver.cpp:218] Iteration 4920 (2.40616 iter/s, 4.9872s/12 iters), loss = 1.14615 +I0410 14:05:40.404430 18353 solver.cpp:237] Train net output #0: loss = 1.14615 (* 1 = 1.14615 loss) +I0410 14:05:40.404439 18353 sgd_solver.cpp:105] Iteration 4920, lr = 0.0037735 +I0410 14:05:45.308162 18353 solver.cpp:218] Iteration 4932 (2.44719 iter/s, 4.90359s/12 iters), loss = 1.13513 +I0410 14:05:45.308210 18353 solver.cpp:237] Train net output #0: loss = 1.13513 (* 1 = 1.13513 loss) +I0410 14:05:45.308219 18353 sgd_solver.cpp:105] Iteration 4932, lr = 0.00376454 +I0410 14:05:50.207789 18353 solver.cpp:218] Iteration 4944 (2.44926 iter/s, 4.89944s/12 iters), loss = 0.981502 +I0410 14:05:50.207829 18353 solver.cpp:237] Train net output #0: loss = 0.981502 (* 1 = 0.981502 loss) +I0410 14:05:50.207839 18353 sgd_solver.cpp:105] Iteration 4944, lr = 0.0037556 +I0410 14:05:54.847867 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:55.039412 18353 solver.cpp:218] Iteration 4956 (2.48373 iter/s, 4.83144s/12 iters), loss = 0.846399 +I0410 14:05:55.039458 18353 solver.cpp:237] Train net output #0: loss = 0.846399 (* 1 = 0.846399 loss) +I0410 14:05:55.039467 18353 sgd_solver.cpp:105] Iteration 4956, lr = 0.00374669 +I0410 14:06:00.061573 18353 solver.cpp:218] Iteration 4968 (2.3895 iter/s, 5.02197s/12 iters), loss = 1.08995 +I0410 14:06:00.061650 18353 solver.cpp:237] Train net output #0: loss = 1.08995 (* 1 = 1.08995 loss) +I0410 14:06:00.061662 18353 sgd_solver.cpp:105] Iteration 4968, lr = 0.00373779 +I0410 14:06:04.944831 18353 solver.cpp:218] Iteration 4980 (2.45748 iter/s, 4.88305s/12 iters), loss = 0.930892 +I0410 14:06:04.944873 18353 solver.cpp:237] Train net output #0: loss = 0.930892 (* 1 = 0.930892 loss) +I0410 14:06:04.944883 18353 sgd_solver.cpp:105] Iteration 4980, lr = 0.00372892 +I0410 14:06:09.757166 18353 solver.cpp:218] Iteration 4992 (2.49369 iter/s, 4.81215s/12 iters), loss = 1.16513 +I0410 14:06:09.757223 18353 solver.cpp:237] Train net output #0: loss = 1.16513 (* 1 = 1.16513 loss) +I0410 14:06:09.757236 18353 sgd_solver.cpp:105] Iteration 4992, lr = 0.00372006 +I0410 14:06:11.759436 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4998.caffemodel +I0410 14:06:12.056474 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4998.solverstate +I0410 14:06:12.249815 18353 solver.cpp:330] Iteration 4998, Testing net (#0) +I0410 14:06:12.249840 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:06:14.722052 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:06:16.682961 18353 solver.cpp:397] Test net output #0: accuracy = 0.500613 +I0410 14:06:16.683013 18353 solver.cpp:397] Test net output #1: loss = 2.25058 (* 1 = 2.25058 loss) +I0410 14:06:18.546725 18353 solver.cpp:218] Iteration 5004 (1.3653 iter/s, 8.78926s/12 iters), loss = 0.969264 +I0410 14:06:18.546778 18353 solver.cpp:237] Train net output #0: loss = 0.969264 (* 1 = 0.969264 loss) +I0410 14:06:18.546792 18353 sgd_solver.cpp:105] Iteration 5004, lr = 0.00371123 +I0410 14:06:23.490792 18353 solver.cpp:218] Iteration 5016 (2.42725 iter/s, 4.94387s/12 iters), loss = 0.743767 +I0410 14:06:23.490849 18353 solver.cpp:237] Train net output #0: loss = 0.743767 (* 1 = 0.743767 loss) +I0410 14:06:23.490861 18353 sgd_solver.cpp:105] Iteration 5016, lr = 0.00370242 +I0410 14:06:28.436518 18353 solver.cpp:218] Iteration 5028 (2.42643 iter/s, 4.94553s/12 iters), loss = 1.0275 +I0410 14:06:28.436573 18353 solver.cpp:237] Train net output #0: loss = 1.0275 (* 1 = 1.0275 loss) +I0410 14:06:28.436585 18353 sgd_solver.cpp:105] Iteration 5028, lr = 0.00369363 +I0410 14:06:33.353547 18353 solver.cpp:218] Iteration 5040 (2.44059 iter/s, 4.91684s/12 iters), loss = 1.05361 +I0410 14:06:33.353711 18353 solver.cpp:237] Train net output #0: loss = 1.05361 (* 1 = 1.05361 loss) +I0410 14:06:33.353726 18353 sgd_solver.cpp:105] Iteration 5040, lr = 0.00368486 +I0410 14:06:38.280802 18353 solver.cpp:218] Iteration 5052 (2.43558 iter/s, 4.92695s/12 iters), loss = 1.08544 +I0410 14:06:38.280855 18353 solver.cpp:237] Train net output #0: loss = 1.08544 (* 1 = 1.08544 loss) +I0410 14:06:38.280869 18353 sgd_solver.cpp:105] Iteration 5052, lr = 0.00367611 +I0410 14:06:40.171129 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:06:43.203887 18353 solver.cpp:218] Iteration 5064 (2.43759 iter/s, 4.92289s/12 iters), loss = 1.04984 +I0410 14:06:43.203946 18353 solver.cpp:237] Train net output #0: loss = 1.04984 (* 1 = 1.04984 loss) +I0410 14:06:43.203958 18353 sgd_solver.cpp:105] Iteration 5064, lr = 0.00366738 +I0410 14:06:48.124760 18353 solver.cpp:218] Iteration 5076 (2.43869 iter/s, 4.92068s/12 iters), loss = 0.851784 +I0410 14:06:48.124807 18353 solver.cpp:237] Train net output #0: loss = 0.851784 (* 1 = 0.851784 loss) +I0410 14:06:48.124819 18353 sgd_solver.cpp:105] Iteration 5076, lr = 0.00365868 +I0410 14:06:53.141297 18353 solver.cpp:218] Iteration 5088 (2.39218 iter/s, 5.01635s/12 iters), loss = 0.918238 +I0410 14:06:53.141342 18353 solver.cpp:237] Train net output #0: loss = 0.918238 (* 1 = 0.918238 loss) +I0410 14:06:53.141356 18353 sgd_solver.cpp:105] Iteration 5088, lr = 0.00364999 +I0410 14:06:57.715163 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5100.caffemodel +I0410 14:06:58.016777 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5100.solverstate +I0410 14:06:58.209563 18353 solver.cpp:330] Iteration 5100, Testing net (#0) +I0410 14:06:58.209581 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:07:00.555544 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:07:02.559027 18353 solver.cpp:397] Test net output #0: accuracy = 0.476103 +I0410 14:07:02.559065 18353 solver.cpp:397] Test net output #1: loss = 2.295 (* 1 = 2.295 loss) +I0410 14:07:02.640404 18353 solver.cpp:218] Iteration 5100 (1.26332 iter/s, 9.4988s/12 iters), loss = 1.1357 +I0410 14:07:02.640455 18353 solver.cpp:237] Train net output #0: loss = 1.1357 (* 1 = 1.1357 loss) +I0410 14:07:02.640465 18353 sgd_solver.cpp:105] Iteration 5100, lr = 0.00364132 +I0410 14:07:06.747450 18353 solver.cpp:218] Iteration 5112 (2.92192 iter/s, 4.10688s/12 iters), loss = 0.892774 +I0410 14:07:06.747589 18353 solver.cpp:237] Train net output #0: loss = 0.892774 (* 1 = 0.892774 loss) +I0410 14:07:06.747602 18353 sgd_solver.cpp:105] Iteration 5112, lr = 0.00363268 +I0410 14:07:11.726480 18353 solver.cpp:218] Iteration 5124 (2.41024 iter/s, 4.97875s/12 iters), loss = 1.14238 +I0410 14:07:11.726542 18353 solver.cpp:237] Train net output #0: loss = 1.14238 (* 1 = 1.14238 loss) +I0410 14:07:11.726555 18353 sgd_solver.cpp:105] Iteration 5124, lr = 0.00362405 +I0410 14:07:16.567629 18353 solver.cpp:218] Iteration 5136 (2.47885 iter/s, 4.84095s/12 iters), loss = 0.952066 +I0410 14:07:16.567687 18353 solver.cpp:237] Train net output #0: loss = 0.952066 (* 1 = 0.952066 loss) +I0410 14:07:16.567699 18353 sgd_solver.cpp:105] Iteration 5136, lr = 0.00361545 +I0410 14:07:21.642412 18353 solver.cpp:218] Iteration 5148 (2.36473 iter/s, 5.07458s/12 iters), loss = 0.867987 +I0410 14:07:21.642472 18353 solver.cpp:237] Train net output #0: loss = 0.867987 (* 1 = 0.867987 loss) +I0410 14:07:21.642485 18353 sgd_solver.cpp:105] Iteration 5148, lr = 0.00360687 +I0410 14:07:25.668248 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:07:26.589309 18353 solver.cpp:218] Iteration 5160 (2.42586 iter/s, 4.94669s/12 iters), loss = 0.906246 +I0410 14:07:26.589354 18353 solver.cpp:237] Train net output #0: loss = 0.906246 (* 1 = 0.906246 loss) +I0410 14:07:26.589365 18353 sgd_solver.cpp:105] Iteration 5160, lr = 0.0035983 +I0410 14:07:31.521200 18353 solver.cpp:218] Iteration 5172 (2.43324 iter/s, 4.9317s/12 iters), loss = 1.0638 +I0410 14:07:31.521260 18353 solver.cpp:237] Train net output #0: loss = 1.0638 (* 1 = 1.0638 loss) +I0410 14:07:31.521272 18353 sgd_solver.cpp:105] Iteration 5172, lr = 0.00358976 +I0410 14:07:36.415705 18353 solver.cpp:218] Iteration 5184 (2.45183 iter/s, 4.8943s/12 iters), loss = 1.0089 +I0410 14:07:36.415762 18353 solver.cpp:237] Train net output #0: loss = 1.0089 (* 1 = 1.0089 loss) +I0410 14:07:36.415776 18353 sgd_solver.cpp:105] Iteration 5184, lr = 0.00358124 +I0410 14:07:41.302879 18353 solver.cpp:218] Iteration 5196 (2.45551 iter/s, 4.88698s/12 iters), loss = 1.16452 +I0410 14:07:41.303005 18353 solver.cpp:237] Train net output #0: loss = 1.16452 (* 1 = 1.16452 loss) +I0410 14:07:41.303020 18353 sgd_solver.cpp:105] Iteration 5196, lr = 0.00357273 +I0410 14:07:43.296200 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5202.caffemodel +I0410 14:07:43.637859 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5202.solverstate +I0410 14:07:43.848836 18353 solver.cpp:330] Iteration 5202, Testing net (#0) +I0410 14:07:43.848866 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:07:46.391675 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:07:48.435194 18353 solver.cpp:397] Test net output #0: accuracy = 0.485294 +I0410 14:07:48.435233 18353 solver.cpp:397] Test net output #1: loss = 2.30226 (* 1 = 2.30226 loss) +I0410 14:07:50.272680 18353 solver.cpp:218] Iteration 5208 (1.33788 iter/s, 8.96943s/12 iters), loss = 0.730962 +I0410 14:07:50.272733 18353 solver.cpp:237] Train net output #0: loss = 0.730962 (* 1 = 0.730962 loss) +I0410 14:07:50.272745 18353 sgd_solver.cpp:105] Iteration 5208, lr = 0.00356425 +I0410 14:07:55.372608 18353 solver.cpp:218] Iteration 5220 (2.35306 iter/s, 5.09973s/12 iters), loss = 0.739734 +I0410 14:07:55.372665 18353 solver.cpp:237] Train net output #0: loss = 0.739734 (* 1 = 0.739734 loss) +I0410 14:07:55.372678 18353 sgd_solver.cpp:105] Iteration 5220, lr = 0.00355579 +I0410 14:08:00.289011 18353 solver.cpp:218] Iteration 5232 (2.44091 iter/s, 4.91621s/12 iters), loss = 0.91464 +I0410 14:08:00.289067 18353 solver.cpp:237] Train net output #0: loss = 0.91464 (* 1 = 0.91464 loss) +I0410 14:08:00.289079 18353 sgd_solver.cpp:105] Iteration 5232, lr = 0.00354735 +I0410 14:08:05.112500 18353 solver.cpp:218] Iteration 5244 (2.48793 iter/s, 4.82329s/12 iters), loss = 0.874483 +I0410 14:08:05.112555 18353 solver.cpp:237] Train net output #0: loss = 0.874483 (* 1 = 0.874483 loss) +I0410 14:08:05.112566 18353 sgd_solver.cpp:105] Iteration 5244, lr = 0.00353892 +I0410 14:08:10.047274 18353 solver.cpp:218] Iteration 5256 (2.43182 iter/s, 4.93458s/12 iters), loss = 0.807583 +I0410 14:08:10.047319 18353 solver.cpp:237] Train net output #0: loss = 0.807583 (* 1 = 0.807583 loss) +I0410 14:08:10.047329 18353 sgd_solver.cpp:105] Iteration 5256, lr = 0.00353052 +I0410 14:08:11.281033 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:14.927904 18353 solver.cpp:218] Iteration 5268 (2.45879 iter/s, 4.88045s/12 iters), loss = 0.734387 +I0410 14:08:14.928041 18353 solver.cpp:237] Train net output #0: loss = 0.734387 (* 1 = 0.734387 loss) +I0410 14:08:14.928052 18353 sgd_solver.cpp:105] Iteration 5268, lr = 0.00352214 +I0410 14:08:19.857867 18353 solver.cpp:218] Iteration 5280 (2.43423 iter/s, 4.92968s/12 iters), loss = 0.82683 +I0410 14:08:19.857924 18353 solver.cpp:237] Train net output #0: loss = 0.82683 (* 1 = 0.82683 loss) +I0410 14:08:19.857937 18353 sgd_solver.cpp:105] Iteration 5280, lr = 0.00351378 +I0410 14:08:24.745258 18353 solver.cpp:218] Iteration 5292 (2.4554 iter/s, 4.88719s/12 iters), loss = 1.20893 +I0410 14:08:24.745316 18353 solver.cpp:237] Train net output #0: loss = 1.20893 (* 1 = 1.20893 loss) +I0410 14:08:24.745329 18353 sgd_solver.cpp:105] Iteration 5292, lr = 0.00350544 +I0410 14:08:29.172103 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5304.caffemodel +I0410 14:08:30.766839 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5304.solverstate +I0410 14:08:31.373553 18353 solver.cpp:330] Iteration 5304, Testing net (#0) +I0410 14:08:31.373584 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:08:33.766425 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:35.873558 18353 solver.cpp:397] Test net output #0: accuracy = 0.492034 +I0410 14:08:35.873610 18353 solver.cpp:397] Test net output #1: loss = 2.33675 (* 1 = 2.33675 loss) +I0410 14:08:35.954913 18353 solver.cpp:218] Iteration 5304 (1.07054 iter/s, 11.2093s/12 iters), loss = 0.75875 +I0410 14:08:35.954972 18353 solver.cpp:237] Train net output #0: loss = 0.75875 (* 1 = 0.75875 loss) +I0410 14:08:35.954986 18353 sgd_solver.cpp:105] Iteration 5304, lr = 0.00349711 +I0410 14:08:40.149448 18353 solver.cpp:218] Iteration 5316 (2.86099 iter/s, 4.19435s/12 iters), loss = 0.772529 +I0410 14:08:40.149497 18353 solver.cpp:237] Train net output #0: loss = 0.772529 (* 1 = 0.772529 loss) +I0410 14:08:40.149508 18353 sgd_solver.cpp:105] Iteration 5316, lr = 0.00348881 +I0410 14:08:45.111250 18353 solver.cpp:218] Iteration 5328 (2.41857 iter/s, 4.96161s/12 iters), loss = 0.959453 +I0410 14:08:45.111363 18353 solver.cpp:237] Train net output #0: loss = 0.959453 (* 1 = 0.959453 loss) +I0410 14:08:45.111377 18353 sgd_solver.cpp:105] Iteration 5328, lr = 0.00348053 +I0410 14:08:49.985132 18353 solver.cpp:218] Iteration 5340 (2.46223 iter/s, 4.87363s/12 iters), loss = 1.02819 +I0410 14:08:49.985189 18353 solver.cpp:237] Train net output #0: loss = 1.02819 (* 1 = 1.02819 loss) +I0410 14:08:49.985203 18353 sgd_solver.cpp:105] Iteration 5340, lr = 0.00347226 +I0410 14:08:54.874246 18353 solver.cpp:218] Iteration 5352 (2.45453 iter/s, 4.88891s/12 iters), loss = 0.989113 +I0410 14:08:54.874308 18353 solver.cpp:237] Train net output #0: loss = 0.989113 (* 1 = 0.989113 loss) +I0410 14:08:54.874321 18353 sgd_solver.cpp:105] Iteration 5352, lr = 0.00346402 +I0410 14:08:58.183200 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:59.716583 18353 solver.cpp:218] Iteration 5364 (2.47825 iter/s, 4.84214s/12 iters), loss = 0.729132 +I0410 14:08:59.716634 18353 solver.cpp:237] Train net output #0: loss = 0.729132 (* 1 = 0.729132 loss) +I0410 14:08:59.716646 18353 sgd_solver.cpp:105] Iteration 5364, lr = 0.0034558 +I0410 14:09:04.547833 18353 solver.cpp:218] Iteration 5376 (2.48393 iter/s, 4.83106s/12 iters), loss = 0.942957 +I0410 14:09:04.547892 18353 solver.cpp:237] Train net output #0: loss = 0.942957 (* 1 = 0.942957 loss) +I0410 14:09:04.547904 18353 sgd_solver.cpp:105] Iteration 5376, lr = 0.00344759 +I0410 14:09:09.354701 18353 solver.cpp:218] Iteration 5388 (2.49653 iter/s, 4.80667s/12 iters), loss = 0.729248 +I0410 14:09:09.354769 18353 solver.cpp:237] Train net output #0: loss = 0.729248 (* 1 = 0.729248 loss) +I0410 14:09:09.354781 18353 sgd_solver.cpp:105] Iteration 5388, lr = 0.00343941 +I0410 14:09:14.189153 18353 solver.cpp:218] Iteration 5400 (2.48229 iter/s, 4.83425s/12 iters), loss = 0.942244 +I0410 14:09:14.189218 18353 solver.cpp:237] Train net output #0: loss = 0.942244 (* 1 = 0.942244 loss) +I0410 14:09:14.189229 18353 sgd_solver.cpp:105] Iteration 5400, lr = 0.00343124 +I0410 14:09:16.159343 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5406.caffemodel +I0410 14:09:16.461465 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5406.solverstate +I0410 14:09:16.656494 18353 solver.cpp:330] Iteration 5406, Testing net (#0) +I0410 14:09:16.656522 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:09:18.961336 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:09:21.084326 18353 solver.cpp:397] Test net output #0: accuracy = 0.48652 +I0410 14:09:21.084384 18353 solver.cpp:397] Test net output #1: loss = 2.34564 (* 1 = 2.34564 loss) +I0410 14:09:22.980984 18353 solver.cpp:218] Iteration 5412 (1.36495 iter/s, 8.79153s/12 iters), loss = 0.814675 +I0410 14:09:22.981040 18353 solver.cpp:237] Train net output #0: loss = 0.814675 (* 1 = 0.814675 loss) +I0410 14:09:22.981051 18353 sgd_solver.cpp:105] Iteration 5412, lr = 0.00342309 +I0410 14:09:27.884358 18353 solver.cpp:218] Iteration 5424 (2.44739 iter/s, 4.90318s/12 iters), loss = 0.747278 +I0410 14:09:27.884421 18353 solver.cpp:237] Train net output #0: loss = 0.747278 (* 1 = 0.747278 loss) +I0410 14:09:27.884435 18353 sgd_solver.cpp:105] Iteration 5424, lr = 0.00341497 +I0410 14:09:32.762265 18353 solver.cpp:218] Iteration 5436 (2.46017 iter/s, 4.87771s/12 iters), loss = 0.853731 +I0410 14:09:32.762310 18353 solver.cpp:237] Train net output #0: loss = 0.853731 (* 1 = 0.853731 loss) +I0410 14:09:32.762320 18353 sgd_solver.cpp:105] Iteration 5436, lr = 0.00340686 +I0410 14:09:37.678890 18353 solver.cpp:218] Iteration 5448 (2.44079 iter/s, 4.91644s/12 iters), loss = 0.733606 +I0410 14:09:37.678942 18353 solver.cpp:237] Train net output #0: loss = 0.733606 (* 1 = 0.733606 loss) +I0410 14:09:37.678954 18353 sgd_solver.cpp:105] Iteration 5448, lr = 0.00339877 +I0410 14:09:42.592376 18353 solver.cpp:218] Iteration 5460 (2.44235 iter/s, 4.9133s/12 iters), loss = 0.880428 +I0410 14:09:42.592434 18353 solver.cpp:237] Train net output #0: loss = 0.880428 (* 1 = 0.880428 loss) +I0410 14:09:42.592447 18353 sgd_solver.cpp:105] Iteration 5460, lr = 0.0033907 +I0410 14:09:43.135032 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:09:47.451612 18353 solver.cpp:218] Iteration 5472 (2.46962 iter/s, 4.85904s/12 iters), loss = 0.680865 +I0410 14:09:47.451711 18353 solver.cpp:237] Train net output #0: loss = 0.680865 (* 1 = 0.680865 loss) +I0410 14:09:47.451722 18353 sgd_solver.cpp:105] Iteration 5472, lr = 0.00338265 +I0410 14:09:52.338194 18353 solver.cpp:218] Iteration 5484 (2.45582 iter/s, 4.88634s/12 iters), loss = 0.718375 +I0410 14:09:52.338235 18353 solver.cpp:237] Train net output #0: loss = 0.718375 (* 1 = 0.718375 loss) +I0410 14:09:52.338244 18353 sgd_solver.cpp:105] Iteration 5484, lr = 0.00337462 +I0410 14:09:57.357069 18353 solver.cpp:218] Iteration 5496 (2.39106 iter/s, 5.01869s/12 iters), loss = 0.786509 +I0410 14:09:57.357118 18353 solver.cpp:237] Train net output #0: loss = 0.786509 (* 1 = 0.786509 loss) +I0410 14:09:57.357129 18353 sgd_solver.cpp:105] Iteration 5496, lr = 0.00336661 +I0410 14:10:01.968523 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5508.caffemodel +I0410 14:10:02.594524 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5508.solverstate +I0410 14:10:02.802541 18353 solver.cpp:330] Iteration 5508, Testing net (#0) +I0410 14:10:02.802568 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:10:05.044905 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:10:07.219151 18353 solver.cpp:397] Test net output #0: accuracy = 0.496324 +I0410 14:10:07.219180 18353 solver.cpp:397] Test net output #1: loss = 2.32296 (* 1 = 2.32296 loss) +I0410 14:10:07.300184 18353 solver.cpp:218] Iteration 5508 (1.2069 iter/s, 9.9428s/12 iters), loss = 1.06439 +I0410 14:10:07.300221 18353 solver.cpp:237] Train net output #0: loss = 1.06439 (* 1 = 1.06439 loss) +I0410 14:10:07.300230 18353 sgd_solver.cpp:105] Iteration 5508, lr = 0.00335861 +I0410 14:10:11.647392 18353 solver.cpp:218] Iteration 5520 (2.7605 iter/s, 4.34704s/12 iters), loss = 0.965831 +I0410 14:10:11.647454 18353 solver.cpp:237] Train net output #0: loss = 0.965831 (* 1 = 0.965831 loss) +I0410 14:10:11.647467 18353 sgd_solver.cpp:105] Iteration 5520, lr = 0.00335064 +I0410 14:10:12.423095 18353 blocking_queue.cpp:49] Waiting for data +I0410 14:10:16.610991 18353 solver.cpp:218] Iteration 5532 (2.4177 iter/s, 4.9634s/12 iters), loss = 0.932608 +I0410 14:10:16.611043 18353 solver.cpp:237] Train net output #0: loss = 0.932608 (* 1 = 0.932608 loss) +I0410 14:10:16.611055 18353 sgd_solver.cpp:105] Iteration 5532, lr = 0.00334268 +I0410 14:10:21.536157 18353 solver.cpp:218] Iteration 5544 (2.43656 iter/s, 4.92497s/12 iters), loss = 0.749615 +I0410 14:10:21.536309 18353 solver.cpp:237] Train net output #0: loss = 0.749615 (* 1 = 0.749615 loss) +I0410 14:10:21.536324 18353 sgd_solver.cpp:105] Iteration 5544, lr = 0.00333475 +I0410 14:10:26.471607 18353 solver.cpp:218] Iteration 5556 (2.43153 iter/s, 4.93516s/12 iters), loss = 0.509865 +I0410 14:10:26.471654 18353 solver.cpp:237] Train net output #0: loss = 0.509865 (* 1 = 0.509865 loss) +I0410 14:10:26.471665 18353 sgd_solver.cpp:105] Iteration 5556, lr = 0.00332683 +I0410 14:10:29.080044 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:10:31.348310 18353 solver.cpp:218] Iteration 5568 (2.46077 iter/s, 4.87651s/12 iters), loss = 0.734006 +I0410 14:10:31.348371 18353 solver.cpp:237] Train net output #0: loss = 0.734006 (* 1 = 0.734006 loss) +I0410 14:10:31.348383 18353 sgd_solver.cpp:105] Iteration 5568, lr = 0.00331893 +I0410 14:10:36.311226 18353 solver.cpp:218] Iteration 5580 (2.41803 iter/s, 4.96272s/12 iters), loss = 0.653475 +I0410 14:10:36.311272 18353 solver.cpp:237] Train net output #0: loss = 0.653475 (* 1 = 0.653475 loss) +I0410 14:10:36.311282 18353 sgd_solver.cpp:105] Iteration 5580, lr = 0.00331105 +I0410 14:10:41.227285 18353 solver.cpp:218] Iteration 5592 (2.44108 iter/s, 4.91587s/12 iters), loss = 0.881881 +I0410 14:10:41.227345 18353 solver.cpp:237] Train net output #0: loss = 0.881881 (* 1 = 0.881881 loss) +I0410 14:10:41.227357 18353 sgd_solver.cpp:105] Iteration 5592, lr = 0.00330319 +I0410 14:10:46.200119 18353 solver.cpp:218] Iteration 5604 (2.41321 iter/s, 4.97263s/12 iters), loss = 0.874188 +I0410 14:10:46.200178 18353 solver.cpp:237] Train net output #0: loss = 0.874188 (* 1 = 0.874188 loss) +I0410 14:10:46.200191 18353 sgd_solver.cpp:105] Iteration 5604, lr = 0.00329535 +I0410 14:10:48.233809 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5610.caffemodel +I0410 14:10:48.561676 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5610.solverstate +I0410 14:10:48.764101 18353 solver.cpp:330] Iteration 5610, Testing net (#0) +I0410 14:10:48.764130 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:10:51.075510 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:10:53.332931 18353 solver.cpp:397] Test net output #0: accuracy = 0.511642 +I0410 14:10:53.333132 18353 solver.cpp:397] Test net output #1: loss = 2.19515 (* 1 = 2.19515 loss) +I0410 14:10:55.276001 18353 solver.cpp:218] Iteration 5616 (1.32223 iter/s, 9.07557s/12 iters), loss = 0.788042 +I0410 14:10:55.276055 18353 solver.cpp:237] Train net output #0: loss = 0.788042 (* 1 = 0.788042 loss) +I0410 14:10:55.276067 18353 sgd_solver.cpp:105] Iteration 5616, lr = 0.00328752 +I0410 14:11:00.304826 18353 solver.cpp:218] Iteration 5628 (2.38634 iter/s, 5.02862s/12 iters), loss = 0.831445 +I0410 14:11:00.304879 18353 solver.cpp:237] Train net output #0: loss = 0.831445 (* 1 = 0.831445 loss) +I0410 14:11:00.304889 18353 sgd_solver.cpp:105] Iteration 5628, lr = 0.00327972 +I0410 14:11:05.329720 18353 solver.cpp:218] Iteration 5640 (2.38821 iter/s, 5.02469s/12 iters), loss = 0.738849 +I0410 14:11:05.329777 18353 solver.cpp:237] Train net output #0: loss = 0.738849 (* 1 = 0.738849 loss) +I0410 14:11:05.329788 18353 sgd_solver.cpp:105] Iteration 5640, lr = 0.00327193 +I0410 14:11:10.273906 18353 solver.cpp:218] Iteration 5652 (2.42719 iter/s, 4.94398s/12 iters), loss = 0.735652 +I0410 14:11:10.273980 18353 solver.cpp:237] Train net output #0: loss = 0.735652 (* 1 = 0.735652 loss) +I0410 14:11:10.273993 18353 sgd_solver.cpp:105] Iteration 5652, lr = 0.00326416 +I0410 14:11:15.030660 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:11:15.195209 18353 solver.cpp:218] Iteration 5664 (2.43847 iter/s, 4.92111s/12 iters), loss = 0.632614 +I0410 14:11:15.195256 18353 solver.cpp:237] Train net output #0: loss = 0.632614 (* 1 = 0.632614 loss) +I0410 14:11:15.195267 18353 sgd_solver.cpp:105] Iteration 5664, lr = 0.00325641 +I0410 14:11:20.092293 18353 solver.cpp:218] Iteration 5676 (2.45054 iter/s, 4.89689s/12 iters), loss = 0.771162 +I0410 14:11:20.092353 18353 solver.cpp:237] Train net output #0: loss = 0.771162 (* 1 = 0.771162 loss) +I0410 14:11:20.092367 18353 sgd_solver.cpp:105] Iteration 5676, lr = 0.00324868 +I0410 14:11:25.202016 18353 solver.cpp:218] Iteration 5688 (2.34856 iter/s, 5.10951s/12 iters), loss = 0.661734 +I0410 14:11:25.202148 18353 solver.cpp:237] Train net output #0: loss = 0.661734 (* 1 = 0.661734 loss) +I0410 14:11:25.202162 18353 sgd_solver.cpp:105] Iteration 5688, lr = 0.00324097 +I0410 14:11:30.074534 18353 solver.cpp:218] Iteration 5700 (2.46293 iter/s, 4.87224s/12 iters), loss = 0.735425 +I0410 14:11:30.074592 18353 solver.cpp:237] Train net output #0: loss = 0.735425 (* 1 = 0.735425 loss) +I0410 14:11:30.074604 18353 sgd_solver.cpp:105] Iteration 5700, lr = 0.00323328 +I0410 14:11:34.476070 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5712.caffemodel +I0410 14:11:34.763168 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5712.solverstate +I0410 14:11:35.399518 18353 solver.cpp:330] Iteration 5712, Testing net (#0) +I0410 14:11:35.399540 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:11:37.544523 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:11:39.782631 18353 solver.cpp:397] Test net output #0: accuracy = 0.509804 +I0410 14:11:39.782683 18353 solver.cpp:397] Test net output #1: loss = 2.27155 (* 1 = 2.27155 loss) +I0410 14:11:39.864259 18353 solver.cpp:218] Iteration 5712 (1.22582 iter/s, 9.78939s/12 iters), loss = 1.00892 +I0410 14:11:39.864336 18353 solver.cpp:237] Train net output #0: loss = 1.00892 (* 1 = 1.00892 loss) +I0410 14:11:39.864353 18353 sgd_solver.cpp:105] Iteration 5712, lr = 0.0032256 +I0410 14:11:43.993985 18353 solver.cpp:218] Iteration 5724 (2.90591 iter/s, 4.12952s/12 iters), loss = 0.742137 +I0410 14:11:43.994040 18353 solver.cpp:237] Train net output #0: loss = 0.742137 (* 1 = 0.742137 loss) +I0410 14:11:43.994053 18353 sgd_solver.cpp:105] Iteration 5724, lr = 0.00321794 +I0410 14:11:48.828318 18353 solver.cpp:218] Iteration 5736 (2.48235 iter/s, 4.83413s/12 iters), loss = 0.76919 +I0410 14:11:48.828382 18353 solver.cpp:237] Train net output #0: loss = 0.76919 (* 1 = 0.76919 loss) +I0410 14:11:48.828395 18353 sgd_solver.cpp:105] Iteration 5736, lr = 0.0032103 +I0410 14:11:53.620748 18353 solver.cpp:218] Iteration 5748 (2.50406 iter/s, 4.79222s/12 iters), loss = 0.805564 +I0410 14:11:53.620816 18353 solver.cpp:237] Train net output #0: loss = 0.805564 (* 1 = 0.805564 loss) +I0410 14:11:53.620829 18353 sgd_solver.cpp:105] Iteration 5748, lr = 0.00320268 +I0410 14:11:58.493387 18353 solver.cpp:218] Iteration 5760 (2.46284 iter/s, 4.87243s/12 iters), loss = 0.574332 +I0410 14:11:58.493547 18353 solver.cpp:237] Train net output #0: loss = 0.574332 (* 1 = 0.574332 loss) +I0410 14:11:58.493561 18353 sgd_solver.cpp:105] Iteration 5760, lr = 0.00319508 +I0410 14:12:00.406102 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:03.317028 18353 solver.cpp:218] Iteration 5772 (2.4879 iter/s, 4.82334s/12 iters), loss = 0.794722 +I0410 14:12:03.317083 18353 solver.cpp:237] Train net output #0: loss = 0.794722 (* 1 = 0.794722 loss) +I0410 14:12:03.317096 18353 sgd_solver.cpp:105] Iteration 5772, lr = 0.00318749 +I0410 14:12:08.159518 18353 solver.cpp:218] Iteration 5784 (2.47816 iter/s, 4.8423s/12 iters), loss = 0.692924 +I0410 14:12:08.159572 18353 solver.cpp:237] Train net output #0: loss = 0.692924 (* 1 = 0.692924 loss) +I0410 14:12:08.159585 18353 sgd_solver.cpp:105] Iteration 5784, lr = 0.00317992 +I0410 14:12:13.007699 18353 solver.cpp:218] Iteration 5796 (2.47526 iter/s, 4.84798s/12 iters), loss = 0.784665 +I0410 14:12:13.007762 18353 solver.cpp:237] Train net output #0: loss = 0.784665 (* 1 = 0.784665 loss) +I0410 14:12:13.007776 18353 sgd_solver.cpp:105] Iteration 5796, lr = 0.00317237 +I0410 14:12:17.806195 18353 solver.cpp:218] Iteration 5808 (2.50089 iter/s, 4.79829s/12 iters), loss = 0.750609 +I0410 14:12:17.806258 18353 solver.cpp:237] Train net output #0: loss = 0.750609 (* 1 = 0.750609 loss) +I0410 14:12:17.806270 18353 sgd_solver.cpp:105] Iteration 5808, lr = 0.00316484 +I0410 14:12:19.774613 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5814.caffemodel +I0410 14:12:20.084256 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5814.solverstate +I0410 14:12:20.280352 18353 solver.cpp:330] Iteration 5814, Testing net (#0) +I0410 14:12:20.280380 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:12:22.744614 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:25.025694 18353 solver.cpp:397] Test net output #0: accuracy = 0.515319 +I0410 14:12:25.025728 18353 solver.cpp:397] Test net output #1: loss = 2.29007 (* 1 = 2.29007 loss) +I0410 14:12:26.971669 18353 solver.cpp:218] Iteration 5820 (1.30931 iter/s, 9.16516s/12 iters), loss = 0.643536 +I0410 14:12:26.971724 18353 solver.cpp:237] Train net output #0: loss = 0.643536 (* 1 = 0.643536 loss) +I0410 14:12:26.971737 18353 sgd_solver.cpp:105] Iteration 5820, lr = 0.00315733 +I0410 14:12:31.996568 18353 solver.cpp:218] Iteration 5832 (2.3882 iter/s, 5.0247s/12 iters), loss = 0.590614 +I0410 14:12:31.996675 18353 solver.cpp:237] Train net output #0: loss = 0.590614 (* 1 = 0.590614 loss) +I0410 14:12:31.996685 18353 sgd_solver.cpp:105] Iteration 5832, lr = 0.00314983 +I0410 14:12:36.852124 18353 solver.cpp:218] Iteration 5844 (2.47152 iter/s, 4.85531s/12 iters), loss = 0.744024 +I0410 14:12:36.852166 18353 solver.cpp:237] Train net output #0: loss = 0.744024 (* 1 = 0.744024 loss) +I0410 14:12:36.852176 18353 sgd_solver.cpp:105] Iteration 5844, lr = 0.00314235 +I0410 14:12:41.739073 18353 solver.cpp:218] Iteration 5856 (2.45561 iter/s, 4.88677s/12 iters), loss = 0.828271 +I0410 14:12:41.739114 18353 solver.cpp:237] Train net output #0: loss = 0.828271 (* 1 = 0.828271 loss) +I0410 14:12:41.739123 18353 sgd_solver.cpp:105] Iteration 5856, lr = 0.00313489 +I0410 14:12:45.889986 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:46.694523 18353 solver.cpp:218] Iteration 5868 (2.42167 iter/s, 4.95527s/12 iters), loss = 0.687506 +I0410 14:12:46.694558 18353 solver.cpp:237] Train net output #0: loss = 0.687506 (* 1 = 0.687506 loss) +I0410 14:12:46.694568 18353 sgd_solver.cpp:105] Iteration 5868, lr = 0.00312745 +I0410 14:12:51.629735 18353 solver.cpp:218] Iteration 5880 (2.43159 iter/s, 4.93504s/12 iters), loss = 0.576345 +I0410 14:12:51.629776 18353 solver.cpp:237] Train net output #0: loss = 0.576345 (* 1 = 0.576345 loss) +I0410 14:12:51.629784 18353 sgd_solver.cpp:105] Iteration 5880, lr = 0.00312002 +I0410 14:12:56.500676 18353 solver.cpp:218] Iteration 5892 (2.46369 iter/s, 4.87075s/12 iters), loss = 0.693972 +I0410 14:12:56.500733 18353 solver.cpp:237] Train net output #0: loss = 0.693972 (* 1 = 0.693972 loss) +I0410 14:12:56.500744 18353 sgd_solver.cpp:105] Iteration 5892, lr = 0.00311262 +I0410 14:13:01.454926 18353 solver.cpp:218] Iteration 5904 (2.42226 iter/s, 4.95405s/12 iters), loss = 0.669614 +I0410 14:13:01.454973 18353 solver.cpp:237] Train net output #0: loss = 0.669614 (* 1 = 0.669614 loss) +I0410 14:13:01.454983 18353 sgd_solver.cpp:105] Iteration 5904, lr = 0.00310523 +I0410 14:13:05.903183 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5916.caffemodel +I0410 14:13:06.221999 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5916.solverstate +I0410 14:13:06.429867 18353 solver.cpp:330] Iteration 5916, Testing net (#0) +I0410 14:13:06.429888 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:13:08.565433 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:10.883311 18353 solver.cpp:397] Test net output #0: accuracy = 0.502451 +I0410 14:13:10.883361 18353 solver.cpp:397] Test net output #1: loss = 2.28403 (* 1 = 2.28403 loss) +I0410 14:13:10.964967 18353 solver.cpp:218] Iteration 5916 (1.26187 iter/s, 9.50973s/12 iters), loss = 0.797538 +I0410 14:13:10.965020 18353 solver.cpp:237] Train net output #0: loss = 0.797538 (* 1 = 0.797538 loss) +I0410 14:13:10.965032 18353 sgd_solver.cpp:105] Iteration 5916, lr = 0.00309785 +I0410 14:13:15.178560 18353 solver.cpp:218] Iteration 5928 (2.84805 iter/s, 4.21341s/12 iters), loss = 0.654663 +I0410 14:13:15.178618 18353 solver.cpp:237] Train net output #0: loss = 0.654663 (* 1 = 0.654663 loss) +I0410 14:13:15.178632 18353 sgd_solver.cpp:105] Iteration 5928, lr = 0.0030905 +I0410 14:13:20.062857 18353 solver.cpp:218] Iteration 5940 (2.45695 iter/s, 4.88409s/12 iters), loss = 0.665314 +I0410 14:13:20.062911 18353 solver.cpp:237] Train net output #0: loss = 0.665314 (* 1 = 0.665314 loss) +I0410 14:13:20.062925 18353 sgd_solver.cpp:105] Iteration 5940, lr = 0.00308316 +I0410 14:13:24.999192 18353 solver.cpp:218] Iteration 5952 (2.43105 iter/s, 4.93614s/12 iters), loss = 0.789209 +I0410 14:13:24.999246 18353 solver.cpp:237] Train net output #0: loss = 0.789209 (* 1 = 0.789209 loss) +I0410 14:13:24.999259 18353 sgd_solver.cpp:105] Iteration 5952, lr = 0.00307584 +I0410 14:13:29.913111 18353 solver.cpp:218] Iteration 5964 (2.44214 iter/s, 4.91372s/12 iters), loss = 0.696207 +I0410 14:13:29.913156 18353 solver.cpp:237] Train net output #0: loss = 0.696207 (* 1 = 0.696207 loss) +I0410 14:13:29.913166 18353 sgd_solver.cpp:105] Iteration 5964, lr = 0.00306854 +I0410 14:13:31.228168 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:34.888600 18353 solver.cpp:218] Iteration 5976 (2.41192 iter/s, 4.9753s/12 iters), loss = 0.762595 +I0410 14:13:34.888646 18353 solver.cpp:237] Train net output #0: loss = 0.762595 (* 1 = 0.762595 loss) +I0410 14:13:34.888656 18353 sgd_solver.cpp:105] Iteration 5976, lr = 0.00306125 +I0410 14:13:39.729584 18353 solver.cpp:218] Iteration 5988 (2.47893 iter/s, 4.8408s/12 iters), loss = 0.543626 +I0410 14:13:39.729683 18353 solver.cpp:237] Train net output #0: loss = 0.543626 (* 1 = 0.543626 loss) +I0410 14:13:39.729694 18353 sgd_solver.cpp:105] Iteration 5988, lr = 0.00305398 +I0410 14:13:44.644070 18353 solver.cpp:218] Iteration 6000 (2.44188 iter/s, 4.91424s/12 iters), loss = 0.736389 +I0410 14:13:44.644115 18353 solver.cpp:237] Train net output #0: loss = 0.736389 (* 1 = 0.736389 loss) +I0410 14:13:44.644125 18353 sgd_solver.cpp:105] Iteration 6000, lr = 0.00304673 +I0410 14:13:49.726470 18353 solver.cpp:218] Iteration 6012 (2.36118 iter/s, 5.08221s/12 iters), loss = 0.817832 +I0410 14:13:49.726511 18353 solver.cpp:237] Train net output #0: loss = 0.817832 (* 1 = 0.817832 loss) +I0410 14:13:49.726521 18353 sgd_solver.cpp:105] Iteration 6012, lr = 0.0030395 +I0410 14:13:51.759835 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6018.caffemodel +I0410 14:13:52.061887 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6018.solverstate +I0410 14:13:52.254604 18353 solver.cpp:330] Iteration 6018, Testing net (#0) +I0410 14:13:52.254628 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:13:54.358570 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:56.894659 18353 solver.cpp:397] Test net output #0: accuracy = 0.521446 +I0410 14:13:56.894717 18353 solver.cpp:397] Test net output #1: loss = 2.15105 (* 1 = 2.15105 loss) +I0410 14:13:58.818353 18353 solver.cpp:218] Iteration 6024 (1.3199 iter/s, 9.09159s/12 iters), loss = 0.710735 +I0410 14:13:58.818408 18353 solver.cpp:237] Train net output #0: loss = 0.710735 (* 1 = 0.710735 loss) +I0410 14:13:58.818419 18353 sgd_solver.cpp:105] Iteration 6024, lr = 0.00303228 +I0410 14:14:03.704183 18353 solver.cpp:218] Iteration 6036 (2.45618 iter/s, 4.88563s/12 iters), loss = 0.912934 +I0410 14:14:03.704241 18353 solver.cpp:237] Train net output #0: loss = 0.912934 (* 1 = 0.912934 loss) +I0410 14:14:03.704252 18353 sgd_solver.cpp:105] Iteration 6036, lr = 0.00302508 +I0410 14:14:08.662220 18353 solver.cpp:218] Iteration 6048 (2.42041 iter/s, 4.95784s/12 iters), loss = 0.7883 +I0410 14:14:08.662276 18353 solver.cpp:237] Train net output #0: loss = 0.7883 (* 1 = 0.7883 loss) +I0410 14:14:08.662287 18353 sgd_solver.cpp:105] Iteration 6048, lr = 0.0030179 +I0410 14:14:13.515789 18353 solver.cpp:218] Iteration 6060 (2.47251 iter/s, 4.85337s/12 iters), loss = 0.636425 +I0410 14:14:13.523874 18353 solver.cpp:237] Train net output #0: loss = 0.636425 (* 1 = 0.636425 loss) +I0410 14:14:13.523890 18353 sgd_solver.cpp:105] Iteration 6060, lr = 0.00301074 +I0410 14:14:16.935297 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:14:18.456315 18353 solver.cpp:218] Iteration 6072 (2.43294 iter/s, 4.9323s/12 iters), loss = 0.670976 +I0410 14:14:18.456359 18353 solver.cpp:237] Train net output #0: loss = 0.670976 (* 1 = 0.670976 loss) +I0410 14:14:18.456368 18353 sgd_solver.cpp:105] Iteration 6072, lr = 0.00300359 +I0410 14:14:23.365787 18353 solver.cpp:218] Iteration 6084 (2.44435 iter/s, 4.90927s/12 iters), loss = 0.722059 +I0410 14:14:23.365841 18353 solver.cpp:237] Train net output #0: loss = 0.722059 (* 1 = 0.722059 loss) +I0410 14:14:23.365854 18353 sgd_solver.cpp:105] Iteration 6084, lr = 0.00299646 +I0410 14:14:28.240967 18353 solver.cpp:218] Iteration 6096 (2.46155 iter/s, 4.87498s/12 iters), loss = 0.770837 +I0410 14:14:28.241019 18353 solver.cpp:237] Train net output #0: loss = 0.770837 (* 1 = 0.770837 loss) +I0410 14:14:28.241031 18353 sgd_solver.cpp:105] Iteration 6096, lr = 0.00298934 +I0410 14:14:33.153525 18353 solver.cpp:218] Iteration 6108 (2.44282 iter/s, 4.91237s/12 iters), loss = 0.697178 +I0410 14:14:33.153575 18353 solver.cpp:237] Train net output #0: loss = 0.697178 (* 1 = 0.697178 loss) +I0410 14:14:33.153586 18353 sgd_solver.cpp:105] Iteration 6108, lr = 0.00298225 +I0410 14:14:37.614692 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6120.caffemodel +I0410 14:14:39.098008 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6120.solverstate +I0410 14:14:39.305007 18353 solver.cpp:330] Iteration 6120, Testing net (#0) +I0410 14:14:39.305027 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:14:41.429913 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:14:43.823109 18353 solver.cpp:397] Test net output #0: accuracy = 0.51348 +I0410 14:14:43.823321 18353 solver.cpp:397] Test net output #1: loss = 2.22052 (* 1 = 2.22052 loss) +I0410 14:14:43.904706 18353 solver.cpp:218] Iteration 6120 (1.11619 iter/s, 10.7508s/12 iters), loss = 0.521173 +I0410 14:14:43.904759 18353 solver.cpp:237] Train net output #0: loss = 0.521173 (* 1 = 0.521173 loss) +I0410 14:14:43.904772 18353 sgd_solver.cpp:105] Iteration 6120, lr = 0.00297517 +I0410 14:14:48.134862 18353 solver.cpp:218] Iteration 6132 (2.8369 iter/s, 4.22997s/12 iters), loss = 0.531146 +I0410 14:14:48.134914 18353 solver.cpp:237] Train net output #0: loss = 0.531146 (* 1 = 0.531146 loss) +I0410 14:14:48.134927 18353 sgd_solver.cpp:105] Iteration 6132, lr = 0.0029681 +I0410 14:14:53.252141 18353 solver.cpp:218] Iteration 6144 (2.34509 iter/s, 5.11708s/12 iters), loss = 0.973454 +I0410 14:14:53.252185 18353 solver.cpp:237] Train net output #0: loss = 0.973454 (* 1 = 0.973454 loss) +I0410 14:14:53.252195 18353 sgd_solver.cpp:105] Iteration 6144, lr = 0.00296105 +I0410 14:14:58.177613 18353 solver.cpp:218] Iteration 6156 (2.43641 iter/s, 4.92528s/12 iters), loss = 0.662244 +I0410 14:14:58.177662 18353 solver.cpp:237] Train net output #0: loss = 0.662244 (* 1 = 0.662244 loss) +I0410 14:14:58.177672 18353 sgd_solver.cpp:105] Iteration 6156, lr = 0.00295402 +I0410 14:15:03.130434 18353 solver.cpp:218] Iteration 6168 (2.42296 iter/s, 4.95262s/12 iters), loss = 0.717742 +I0410 14:15:03.130483 18353 solver.cpp:237] Train net output #0: loss = 0.717742 (* 1 = 0.717742 loss) +I0410 14:15:03.130496 18353 sgd_solver.cpp:105] Iteration 6168, lr = 0.00294701 +I0410 14:15:03.700232 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:08.033159 18353 solver.cpp:218] Iteration 6180 (2.44772 iter/s, 4.90253s/12 iters), loss = 0.627013 +I0410 14:15:08.033202 18353 solver.cpp:237] Train net output #0: loss = 0.627013 (* 1 = 0.627013 loss) +I0410 14:15:08.033212 18353 sgd_solver.cpp:105] Iteration 6180, lr = 0.00294001 +I0410 14:15:12.938045 18353 solver.cpp:218] Iteration 6192 (2.44664 iter/s, 4.90469s/12 iters), loss = 0.455912 +I0410 14:15:12.938097 18353 solver.cpp:237] Train net output #0: loss = 0.455912 (* 1 = 0.455912 loss) +I0410 14:15:12.938109 18353 sgd_solver.cpp:105] Iteration 6192, lr = 0.00293303 +I0410 14:15:17.844672 18353 solver.cpp:218] Iteration 6204 (2.44577 iter/s, 4.90643s/12 iters), loss = 0.567118 +I0410 14:15:17.844766 18353 solver.cpp:237] Train net output #0: loss = 0.567118 (* 1 = 0.567118 loss) +I0410 14:15:17.844776 18353 sgd_solver.cpp:105] Iteration 6204, lr = 0.00292607 +I0410 14:15:22.728669 18353 solver.cpp:218] Iteration 6216 (2.45712 iter/s, 4.88376s/12 iters), loss = 0.606701 +I0410 14:15:22.728718 18353 solver.cpp:237] Train net output #0: loss = 0.606701 (* 1 = 0.606701 loss) +I0410 14:15:22.728729 18353 sgd_solver.cpp:105] Iteration 6216, lr = 0.00291912 +I0410 14:15:24.728497 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6222.caffemodel +I0410 14:15:25.060364 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6222.solverstate +I0410 14:15:25.267180 18353 solver.cpp:330] Iteration 6222, Testing net (#0) +I0410 14:15:25.267204 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:15:27.276801 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:28.193138 18353 blocking_queue.cpp:49] Waiting for data +I0410 14:15:29.745867 18353 solver.cpp:397] Test net output #0: accuracy = 0.518995 +I0410 14:15:29.745916 18353 solver.cpp:397] Test net output #1: loss = 2.19724 (* 1 = 2.19724 loss) +I0410 14:15:31.503708 18353 solver.cpp:218] Iteration 6228 (1.36756 iter/s, 8.77474s/12 iters), loss = 0.683243 +I0410 14:15:31.503755 18353 solver.cpp:237] Train net output #0: loss = 0.683243 (* 1 = 0.683243 loss) +I0410 14:15:31.503765 18353 sgd_solver.cpp:105] Iteration 6228, lr = 0.00291219 +I0410 14:15:36.444991 18353 solver.cpp:218] Iteration 6240 (2.42861 iter/s, 4.94109s/12 iters), loss = 0.650123 +I0410 14:15:36.445051 18353 solver.cpp:237] Train net output #0: loss = 0.650123 (* 1 = 0.650123 loss) +I0410 14:15:36.445065 18353 sgd_solver.cpp:105] Iteration 6240, lr = 0.00290528 +I0410 14:15:41.386240 18353 solver.cpp:218] Iteration 6252 (2.42864 iter/s, 4.94105s/12 iters), loss = 0.597079 +I0410 14:15:41.386287 18353 solver.cpp:237] Train net output #0: loss = 0.597079 (* 1 = 0.597079 loss) +I0410 14:15:41.386298 18353 sgd_solver.cpp:105] Iteration 6252, lr = 0.00289838 +I0410 14:15:46.334187 18353 solver.cpp:218] Iteration 6264 (2.42534 iter/s, 4.94775s/12 iters), loss = 0.648929 +I0410 14:15:46.334239 18353 solver.cpp:237] Train net output #0: loss = 0.648929 (* 1 = 0.648929 loss) +I0410 14:15:46.334251 18353 sgd_solver.cpp:105] Iteration 6264, lr = 0.0028915 +I0410 14:15:49.062376 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:51.232539 18353 solver.cpp:218] Iteration 6276 (2.4499 iter/s, 4.89815s/12 iters), loss = 0.680992 +I0410 14:15:51.232592 18353 solver.cpp:237] Train net output #0: loss = 0.680992 (* 1 = 0.680992 loss) +I0410 14:15:51.232605 18353 sgd_solver.cpp:105] Iteration 6276, lr = 0.00288463 +I0410 14:15:56.159600 18353 solver.cpp:218] Iteration 6288 (2.43563 iter/s, 4.92686s/12 iters), loss = 0.561973 +I0410 14:15:56.159658 18353 solver.cpp:237] Train net output #0: loss = 0.561973 (* 1 = 0.561973 loss) +I0410 14:15:56.159670 18353 sgd_solver.cpp:105] Iteration 6288, lr = 0.00287779 +I0410 14:16:01.089377 18353 solver.cpp:218] Iteration 6300 (2.43429 iter/s, 4.92957s/12 iters), loss = 0.840369 +I0410 14:16:01.089435 18353 solver.cpp:237] Train net output #0: loss = 0.840369 (* 1 = 0.840369 loss) +I0410 14:16:01.089447 18353 sgd_solver.cpp:105] Iteration 6300, lr = 0.00287095 +I0410 14:16:06.014642 18353 solver.cpp:218] Iteration 6312 (2.43652 iter/s, 4.92506s/12 iters), loss = 0.693389 +I0410 14:16:06.014694 18353 solver.cpp:237] Train net output #0: loss = 0.693389 (* 1 = 0.693389 loss) +I0410 14:16:06.014706 18353 sgd_solver.cpp:105] Iteration 6312, lr = 0.00286414 +I0410 14:16:10.469365 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6324.caffemodel +I0410 14:16:10.789842 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6324.solverstate +I0410 14:16:11.054728 18353 solver.cpp:330] Iteration 6324, Testing net (#0) +I0410 14:16:11.054754 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:16:13.128293 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:16:15.681551 18353 solver.cpp:397] Test net output #0: accuracy = 0.507353 +I0410 14:16:15.681622 18353 solver.cpp:397] Test net output #1: loss = 2.29632 (* 1 = 2.29632 loss) +I0410 14:16:15.762956 18353 solver.cpp:218] Iteration 6324 (1.23102 iter/s, 9.74799s/12 iters), loss = 0.742045 +I0410 14:16:15.763005 18353 solver.cpp:237] Train net output #0: loss = 0.742045 (* 1 = 0.742045 loss) +I0410 14:16:15.763018 18353 sgd_solver.cpp:105] Iteration 6324, lr = 0.00285734 +I0410 14:16:19.785337 18353 solver.cpp:218] Iteration 6336 (2.98343 iter/s, 4.02221s/12 iters), loss = 0.780067 +I0410 14:16:19.785436 18353 solver.cpp:237] Train net output #0: loss = 0.780067 (* 1 = 0.780067 loss) +I0410 14:16:19.785446 18353 sgd_solver.cpp:105] Iteration 6336, lr = 0.00285055 +I0410 14:16:24.629740 18353 solver.cpp:218] Iteration 6348 (2.47721 iter/s, 4.84416s/12 iters), loss = 0.732231 +I0410 14:16:24.629792 18353 solver.cpp:237] Train net output #0: loss = 0.732231 (* 1 = 0.732231 loss) +I0410 14:16:24.629802 18353 sgd_solver.cpp:105] Iteration 6348, lr = 0.00284379 +I0410 14:16:29.532035 18353 solver.cpp:218] Iteration 6360 (2.44793 iter/s, 4.9021s/12 iters), loss = 0.632658 +I0410 14:16:29.532079 18353 solver.cpp:237] Train net output #0: loss = 0.632658 (* 1 = 0.632658 loss) +I0410 14:16:29.532089 18353 sgd_solver.cpp:105] Iteration 6360, lr = 0.00283703 +I0410 14:16:34.314391 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:16:34.451148 18353 solver.cpp:218] Iteration 6372 (2.43956 iter/s, 4.91892s/12 iters), loss = 0.526726 +I0410 14:16:34.451198 18353 solver.cpp:237] Train net output #0: loss = 0.526726 (* 1 = 0.526726 loss) +I0410 14:16:34.451210 18353 sgd_solver.cpp:105] Iteration 6372, lr = 0.0028303 +I0410 14:16:39.296636 18353 solver.cpp:218] Iteration 6384 (2.47663 iter/s, 4.84529s/12 iters), loss = 0.688702 +I0410 14:16:39.296686 18353 solver.cpp:237] Train net output #0: loss = 0.688702 (* 1 = 0.688702 loss) +I0410 14:16:39.296698 18353 sgd_solver.cpp:105] Iteration 6384, lr = 0.00282358 +I0410 14:16:44.156250 18353 solver.cpp:218] Iteration 6396 (2.46943 iter/s, 4.85942s/12 iters), loss = 0.566177 +I0410 14:16:44.156293 18353 solver.cpp:237] Train net output #0: loss = 0.566177 (* 1 = 0.566177 loss) +I0410 14:16:44.156302 18353 sgd_solver.cpp:105] Iteration 6396, lr = 0.00281687 +I0410 14:16:48.989298 18353 solver.cpp:218] Iteration 6408 (2.483 iter/s, 4.83287s/12 iters), loss = 0.656679 +I0410 14:16:48.989347 18353 solver.cpp:237] Train net output #0: loss = 0.656679 (* 1 = 0.656679 loss) +I0410 14:16:48.989356 18353 sgd_solver.cpp:105] Iteration 6408, lr = 0.00281019 +I0410 14:16:53.882079 18353 solver.cpp:218] Iteration 6420 (2.45269 iter/s, 4.89258s/12 iters), loss = 0.65559 +I0410 14:16:53.882236 18353 solver.cpp:237] Train net output #0: loss = 0.65559 (* 1 = 0.65559 loss) +I0410 14:16:53.882251 18353 sgd_solver.cpp:105] Iteration 6420, lr = 0.00280351 +I0410 14:16:55.871907 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6426.caffemodel +I0410 14:16:56.181867 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6426.solverstate +I0410 14:16:56.381321 18353 solver.cpp:330] Iteration 6426, Testing net (#0) +I0410 14:16:56.381342 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:16:58.540225 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:17:01.125926 18353 solver.cpp:397] Test net output #0: accuracy = 0.511642 +I0410 14:17:01.125977 18353 solver.cpp:397] Test net output #1: loss = 2.31938 (* 1 = 2.31938 loss) +I0410 14:17:02.868880 18353 solver.cpp:218] Iteration 6432 (1.33535 iter/s, 8.9864s/12 iters), loss = 0.720779 +I0410 14:17:02.868932 18353 solver.cpp:237] Train net output #0: loss = 0.720779 (* 1 = 0.720779 loss) +I0410 14:17:02.868942 18353 sgd_solver.cpp:105] Iteration 6432, lr = 0.00279686 +I0410 14:17:07.781014 18353 solver.cpp:218] Iteration 6444 (2.44303 iter/s, 4.91194s/12 iters), loss = 0.534056 +I0410 14:17:07.781071 18353 solver.cpp:237] Train net output #0: loss = 0.534056 (* 1 = 0.534056 loss) +I0410 14:17:07.781083 18353 sgd_solver.cpp:105] Iteration 6444, lr = 0.00279022 +I0410 14:17:12.683377 18353 solver.cpp:218] Iteration 6456 (2.4479 iter/s, 4.90216s/12 iters), loss = 0.540262 +I0410 14:17:12.683434 18353 solver.cpp:237] Train net output #0: loss = 0.540262 (* 1 = 0.540262 loss) +I0410 14:17:12.683446 18353 sgd_solver.cpp:105] Iteration 6456, lr = 0.00278359 +I0410 14:17:17.614414 18353 solver.cpp:218] Iteration 6468 (2.43366 iter/s, 4.93084s/12 iters), loss = 0.455039 +I0410 14:17:17.614466 18353 solver.cpp:237] Train net output #0: loss = 0.455039 (* 1 = 0.455039 loss) +I0410 14:17:17.614477 18353 sgd_solver.cpp:105] Iteration 6468, lr = 0.00277698 +I0410 14:17:19.647624 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:17:22.593626 18353 solver.cpp:218] Iteration 6480 (2.41012 iter/s, 4.97901s/12 iters), loss = 0.627442 +I0410 14:17:22.593681 18353 solver.cpp:237] Train net output #0: loss = 0.627442 (* 1 = 0.627442 loss) +I0410 14:17:22.593693 18353 sgd_solver.cpp:105] Iteration 6480, lr = 0.00277039 +I0410 14:17:27.485996 18353 solver.cpp:218] Iteration 6492 (2.45291 iter/s, 4.89216s/12 iters), loss = 0.527949 +I0410 14:17:27.486090 18353 solver.cpp:237] Train net output #0: loss = 0.527949 (* 1 = 0.527949 loss) +I0410 14:17:27.486105 18353 sgd_solver.cpp:105] Iteration 6492, lr = 0.00276381 +I0410 14:17:32.394727 18353 solver.cpp:218] Iteration 6504 (2.44474 iter/s, 4.90849s/12 iters), loss = 0.748762 +I0410 14:17:32.394780 18353 solver.cpp:237] Train net output #0: loss = 0.748762 (* 1 = 0.748762 loss) +I0410 14:17:32.394793 18353 sgd_solver.cpp:105] Iteration 6504, lr = 0.00275725 +I0410 14:17:37.289431 18353 solver.cpp:218] Iteration 6516 (2.45173 iter/s, 4.89451s/12 iters), loss = 0.590916 +I0410 14:17:37.289479 18353 solver.cpp:237] Train net output #0: loss = 0.590916 (* 1 = 0.590916 loss) +I0410 14:17:37.289489 18353 sgd_solver.cpp:105] Iteration 6516, lr = 0.00275071 +I0410 14:17:41.789191 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6528.caffemodel +I0410 14:17:43.386485 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6528.solverstate +I0410 14:17:43.943349 18353 solver.cpp:330] Iteration 6528, Testing net (#0) +I0410 14:17:43.943379 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:17:45.839660 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:17:48.389947 18353 solver.cpp:397] Test net output #0: accuracy = 0.529412 +I0410 14:17:48.390027 18353 solver.cpp:397] Test net output #1: loss = 2.24723 (* 1 = 2.24723 loss) +I0410 14:17:48.471159 18353 solver.cpp:218] Iteration 6528 (1.07321 iter/s, 11.1814s/12 iters), loss = 0.615411 +I0410 14:17:48.471215 18353 solver.cpp:237] Train net output #0: loss = 0.615411 (* 1 = 0.615411 loss) +I0410 14:17:48.471226 18353 sgd_solver.cpp:105] Iteration 6528, lr = 0.00274418 +I0410 14:17:52.590828 18353 solver.cpp:218] Iteration 6540 (2.91298 iter/s, 4.11949s/12 iters), loss = 0.500604 +I0410 14:17:52.590883 18353 solver.cpp:237] Train net output #0: loss = 0.500604 (* 1 = 0.500604 loss) +I0410 14:17:52.590893 18353 sgd_solver.cpp:105] Iteration 6540, lr = 0.00273766 +I0410 14:17:57.550961 18353 solver.cpp:218] Iteration 6552 (2.41939 iter/s, 4.95993s/12 iters), loss = 0.59679 +I0410 14:17:57.551095 18353 solver.cpp:237] Train net output #0: loss = 0.59679 (* 1 = 0.59679 loss) +I0410 14:17:57.551107 18353 sgd_solver.cpp:105] Iteration 6552, lr = 0.00273116 +I0410 14:18:02.536068 18353 solver.cpp:218] Iteration 6564 (2.4073 iter/s, 4.98483s/12 iters), loss = 0.498057 +I0410 14:18:02.536120 18353 solver.cpp:237] Train net output #0: loss = 0.498057 (* 1 = 0.498057 loss) +I0410 14:18:02.536132 18353 sgd_solver.cpp:105] Iteration 6564, lr = 0.00272468 +I0410 14:18:06.680294 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:07.453735 18353 solver.cpp:218] Iteration 6576 (2.44028 iter/s, 4.91747s/12 iters), loss = 0.579873 +I0410 14:18:07.453790 18353 solver.cpp:237] Train net output #0: loss = 0.579873 (* 1 = 0.579873 loss) +I0410 14:18:07.453804 18353 sgd_solver.cpp:105] Iteration 6576, lr = 0.00271821 +I0410 14:18:12.460707 18353 solver.cpp:218] Iteration 6588 (2.39675 iter/s, 5.00677s/12 iters), loss = 0.416741 +I0410 14:18:12.460762 18353 solver.cpp:237] Train net output #0: loss = 0.416741 (* 1 = 0.416741 loss) +I0410 14:18:12.460774 18353 sgd_solver.cpp:105] Iteration 6588, lr = 0.00271175 +I0410 14:18:17.412199 18353 solver.cpp:218] Iteration 6600 (2.42361 iter/s, 4.95129s/12 iters), loss = 0.66588 +I0410 14:18:17.412253 18353 solver.cpp:237] Train net output #0: loss = 0.66588 (* 1 = 0.66588 loss) +I0410 14:18:17.412266 18353 sgd_solver.cpp:105] Iteration 6600, lr = 0.00270532 +I0410 14:18:22.370187 18353 solver.cpp:218] Iteration 6612 (2.42044 iter/s, 4.95778s/12 iters), loss = 0.56734 +I0410 14:18:22.370240 18353 solver.cpp:237] Train net output #0: loss = 0.56734 (* 1 = 0.56734 loss) +I0410 14:18:22.370254 18353 sgd_solver.cpp:105] Iteration 6612, lr = 0.00269889 +I0410 14:18:27.514252 18353 solver.cpp:218] Iteration 6624 (2.33288 iter/s, 5.14386s/12 iters), loss = 0.46341 +I0410 14:18:27.514312 18353 solver.cpp:237] Train net output #0: loss = 0.46341 (* 1 = 0.46341 loss) +I0410 14:18:27.514324 18353 sgd_solver.cpp:105] Iteration 6624, lr = 0.00269248 +I0410 14:18:29.592909 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6630.caffemodel +I0410 14:18:30.175792 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6630.solverstate +I0410 14:18:30.395292 18353 solver.cpp:330] Iteration 6630, Testing net (#0) +I0410 14:18:30.395324 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:18:32.304487 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:34.889278 18353 solver.cpp:397] Test net output #0: accuracy = 0.541667 +I0410 14:18:34.889333 18353 solver.cpp:397] Test net output #1: loss = 2.19279 (* 1 = 2.19279 loss) +I0410 14:18:36.711316 18353 solver.cpp:218] Iteration 6636 (1.30481 iter/s, 9.19674s/12 iters), loss = 0.439095 +I0410 14:18:36.711371 18353 solver.cpp:237] Train net output #0: loss = 0.439095 (* 1 = 0.439095 loss) +I0410 14:18:36.711383 18353 sgd_solver.cpp:105] Iteration 6636, lr = 0.00268609 +I0410 14:18:41.654682 18353 solver.cpp:218] Iteration 6648 (2.42759 iter/s, 4.94317s/12 iters), loss = 0.302347 +I0410 14:18:41.654728 18353 solver.cpp:237] Train net output #0: loss = 0.302347 (* 1 = 0.302347 loss) +I0410 14:18:41.654738 18353 sgd_solver.cpp:105] Iteration 6648, lr = 0.00267971 +I0410 14:18:46.578032 18353 solver.cpp:218] Iteration 6660 (2.43746 iter/s, 4.92316s/12 iters), loss = 0.69557 +I0410 14:18:46.578090 18353 solver.cpp:237] Train net output #0: loss = 0.69557 (* 1 = 0.69557 loss) +I0410 14:18:46.578104 18353 sgd_solver.cpp:105] Iteration 6660, lr = 0.00267335 +I0410 14:18:51.481019 18353 solver.cpp:218] Iteration 6672 (2.44759 iter/s, 4.90279s/12 iters), loss = 0.524651 +I0410 14:18:51.481072 18353 solver.cpp:237] Train net output #0: loss = 0.524651 (* 1 = 0.524651 loss) +I0410 14:18:51.481087 18353 sgd_solver.cpp:105] Iteration 6672, lr = 0.00266701 +I0410 14:18:52.819705 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:56.575670 18353 solver.cpp:218] Iteration 6684 (2.3555 iter/s, 5.09445s/12 iters), loss = 0.376114 +I0410 14:18:56.575721 18353 solver.cpp:237] Train net output #0: loss = 0.376114 (* 1 = 0.376114 loss) +I0410 14:18:56.575733 18353 sgd_solver.cpp:105] Iteration 6684, lr = 0.00266067 +I0410 14:19:01.498241 18353 solver.cpp:218] Iteration 6696 (2.43785 iter/s, 4.92238s/12 iters), loss = 0.654246 +I0410 14:19:01.498327 18353 solver.cpp:237] Train net output #0: loss = 0.654246 (* 1 = 0.654246 loss) +I0410 14:19:01.498337 18353 sgd_solver.cpp:105] Iteration 6696, lr = 0.00265436 +I0410 14:19:06.413019 18353 solver.cpp:218] Iteration 6708 (2.44173 iter/s, 4.91455s/12 iters), loss = 0.413601 +I0410 14:19:06.413077 18353 solver.cpp:237] Train net output #0: loss = 0.413601 (* 1 = 0.413601 loss) +I0410 14:19:06.413090 18353 sgd_solver.cpp:105] Iteration 6708, lr = 0.00264805 +I0410 14:19:11.297039 18353 solver.cpp:218] Iteration 6720 (2.4571 iter/s, 4.88381s/12 iters), loss = 0.636433 +I0410 14:19:11.297098 18353 solver.cpp:237] Train net output #0: loss = 0.636433 (* 1 = 0.636433 loss) +I0410 14:19:11.297112 18353 sgd_solver.cpp:105] Iteration 6720, lr = 0.00264177 +I0410 14:19:16.254699 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6732.caffemodel +I0410 14:19:16.563588 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6732.solverstate +I0410 14:19:16.771816 18353 solver.cpp:330] Iteration 6732, Testing net (#0) +I0410 14:19:16.771845 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:19:18.587491 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:19:21.315678 18353 solver.cpp:397] Test net output #0: accuracy = 0.530025 +I0410 14:19:21.315730 18353 solver.cpp:397] Test net output #1: loss = 2.28978 (* 1 = 2.28978 loss) +I0410 14:19:21.397089 18353 solver.cpp:218] Iteration 6732 (1.18815 iter/s, 10.0997s/12 iters), loss = 0.561599 +I0410 14:19:21.397140 18353 solver.cpp:237] Train net output #0: loss = 0.561599 (* 1 = 0.561599 loss) +I0410 14:19:21.397153 18353 sgd_solver.cpp:105] Iteration 6732, lr = 0.0026355 +I0410 14:19:25.674952 18353 solver.cpp:218] Iteration 6744 (2.80526 iter/s, 4.27768s/12 iters), loss = 0.467465 +I0410 14:19:25.675011 18353 solver.cpp:237] Train net output #0: loss = 0.467465 (* 1 = 0.467465 loss) +I0410 14:19:25.675024 18353 sgd_solver.cpp:105] Iteration 6744, lr = 0.00262924 +I0410 14:19:30.553550 18353 solver.cpp:218] Iteration 6756 (2.45982 iter/s, 4.8784s/12 iters), loss = 0.532863 +I0410 14:19:30.553599 18353 solver.cpp:237] Train net output #0: loss = 0.532863 (* 1 = 0.532863 loss) +I0410 14:19:30.553609 18353 sgd_solver.cpp:105] Iteration 6756, lr = 0.002623 +I0410 14:19:35.520421 18353 solver.cpp:218] Iteration 6768 (2.4161 iter/s, 4.96667s/12 iters), loss = 0.591368 +I0410 14:19:35.520539 18353 solver.cpp:237] Train net output #0: loss = 0.591368 (* 1 = 0.591368 loss) +I0410 14:19:35.520550 18353 sgd_solver.cpp:105] Iteration 6768, lr = 0.00261677 +I0410 14:19:38.935684 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:19:40.417479 18353 solver.cpp:218] Iteration 6780 (2.45058 iter/s, 4.89679s/12 iters), loss = 0.666838 +I0410 14:19:40.417536 18353 solver.cpp:237] Train net output #0: loss = 0.666838 (* 1 = 0.666838 loss) +I0410 14:19:40.417548 18353 sgd_solver.cpp:105] Iteration 6780, lr = 0.00261056 +I0410 14:19:45.285915 18353 solver.cpp:218] Iteration 6792 (2.46496 iter/s, 4.86823s/12 iters), loss = 0.286074 +I0410 14:19:45.285995 18353 solver.cpp:237] Train net output #0: loss = 0.286074 (* 1 = 0.286074 loss) +I0410 14:19:45.286010 18353 sgd_solver.cpp:105] Iteration 6792, lr = 0.00260436 +I0410 14:19:50.122663 18353 solver.cpp:218] Iteration 6804 (2.48112 iter/s, 4.83653s/12 iters), loss = 0.694836 +I0410 14:19:50.122706 18353 solver.cpp:237] Train net output #0: loss = 0.694836 (* 1 = 0.694836 loss) +I0410 14:19:50.122716 18353 sgd_solver.cpp:105] Iteration 6804, lr = 0.00259817 +I0410 14:19:54.941778 18353 solver.cpp:218] Iteration 6816 (2.49018 iter/s, 4.81892s/12 iters), loss = 0.556946 +I0410 14:19:54.941838 18353 solver.cpp:237] Train net output #0: loss = 0.556946 (* 1 = 0.556946 loss) +I0410 14:19:54.941851 18353 sgd_solver.cpp:105] Iteration 6816, lr = 0.00259201 +I0410 14:19:59.877501 18353 solver.cpp:218] Iteration 6828 (2.43136 iter/s, 4.93552s/12 iters), loss = 0.412786 +I0410 14:19:59.877549 18353 solver.cpp:237] Train net output #0: loss = 0.412786 (* 1 = 0.412786 loss) +I0410 14:19:59.877560 18353 sgd_solver.cpp:105] Iteration 6828, lr = 0.00258585 +I0410 14:20:01.874425 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6834.caffemodel +I0410 14:20:02.177280 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6834.solverstate +I0410 14:20:02.384155 18353 solver.cpp:330] Iteration 6834, Testing net (#0) +I0410 14:20:02.384182 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:20:04.145292 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:06.805377 18353 solver.cpp:397] Test net output #0: accuracy = 0.532475 +I0410 14:20:06.805480 18353 solver.cpp:397] Test net output #1: loss = 2.32753 (* 1 = 2.32753 loss) +I0410 14:20:08.716609 18353 solver.cpp:218] Iteration 6840 (1.35765 iter/s, 8.8388s/12 iters), loss = 0.485697 +I0410 14:20:08.716667 18353 solver.cpp:237] Train net output #0: loss = 0.485697 (* 1 = 0.485697 loss) +I0410 14:20:08.716681 18353 sgd_solver.cpp:105] Iteration 6840, lr = 0.00257971 +I0410 14:20:13.577514 18353 solver.cpp:218] Iteration 6852 (2.46878 iter/s, 4.86071s/12 iters), loss = 0.577252 +I0410 14:20:13.577558 18353 solver.cpp:237] Train net output #0: loss = 0.577252 (* 1 = 0.577252 loss) +I0410 14:20:13.577567 18353 sgd_solver.cpp:105] Iteration 6852, lr = 0.00257359 +I0410 14:20:18.499302 18353 solver.cpp:218] Iteration 6864 (2.43823 iter/s, 4.9216s/12 iters), loss = 0.433717 +I0410 14:20:18.499351 18353 solver.cpp:237] Train net output #0: loss = 0.433717 (* 1 = 0.433717 loss) +I0410 14:20:18.499361 18353 sgd_solver.cpp:105] Iteration 6864, lr = 0.00256748 +I0410 14:20:23.405505 18353 solver.cpp:218] Iteration 6876 (2.44598 iter/s, 4.90601s/12 iters), loss = 0.581418 +I0410 14:20:23.405550 18353 solver.cpp:237] Train net output #0: loss = 0.581418 (* 1 = 0.581418 loss) +I0410 14:20:23.405560 18353 sgd_solver.cpp:105] Iteration 6876, lr = 0.00256138 +I0410 14:20:24.019603 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:28.318297 18353 solver.cpp:218] Iteration 6888 (2.4427 iter/s, 4.9126s/12 iters), loss = 0.432214 +I0410 14:20:28.318352 18353 solver.cpp:237] Train net output #0: loss = 0.432214 (* 1 = 0.432214 loss) +I0410 14:20:28.318365 18353 sgd_solver.cpp:105] Iteration 6888, lr = 0.0025553 +I0410 14:20:33.272722 18353 solver.cpp:218] Iteration 6900 (2.42217 iter/s, 4.95423s/12 iters), loss = 0.569574 +I0410 14:20:33.272768 18353 solver.cpp:237] Train net output #0: loss = 0.569574 (* 1 = 0.569574 loss) +I0410 14:20:33.272778 18353 sgd_solver.cpp:105] Iteration 6900, lr = 0.00254923 +I0410 14:20:38.123504 18353 solver.cpp:218] Iteration 6912 (2.47392 iter/s, 4.8506s/12 iters), loss = 0.375758 +I0410 14:20:38.125365 18353 solver.cpp:237] Train net output #0: loss = 0.375758 (* 1 = 0.375758 loss) +I0410 14:20:38.125377 18353 sgd_solver.cpp:105] Iteration 6912, lr = 0.00254318 +I0410 14:20:42.967500 18353 solver.cpp:218] Iteration 6924 (2.47832 iter/s, 4.84199s/12 iters), loss = 0.591047 +I0410 14:20:42.967545 18353 solver.cpp:237] Train net output #0: loss = 0.591047 (* 1 = 0.591047 loss) +I0410 14:20:42.967554 18353 sgd_solver.cpp:105] Iteration 6924, lr = 0.00253714 +I0410 14:20:47.394068 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6936.caffemodel +I0410 14:20:47.681661 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6936.solverstate +I0410 14:20:47.875120 18353 solver.cpp:330] Iteration 6936, Testing net (#0) +I0410 14:20:47.875138 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:20:48.092234 18353 blocking_queue.cpp:49] Waiting for data +I0410 14:20:49.506413 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:52.241219 18353 solver.cpp:397] Test net output #0: accuracy = 0.535539 +I0410 14:20:52.241263 18353 solver.cpp:397] Test net output #1: loss = 2.26357 (* 1 = 2.26357 loss) +I0410 14:20:52.322482 18353 solver.cpp:218] Iteration 6936 (1.28278 iter/s, 9.35467s/12 iters), loss = 0.467544 +I0410 14:20:52.322532 18353 solver.cpp:237] Train net output #0: loss = 0.467544 (* 1 = 0.467544 loss) +I0410 14:20:52.322543 18353 sgd_solver.cpp:105] Iteration 6936, lr = 0.00253112 +I0410 14:20:56.558121 18353 solver.cpp:218] Iteration 6948 (2.83322 iter/s, 4.23546s/12 iters), loss = 0.450545 +I0410 14:20:56.558178 18353 solver.cpp:237] Train net output #0: loss = 0.450545 (* 1 = 0.450545 loss) +I0410 14:20:56.558189 18353 sgd_solver.cpp:105] Iteration 6948, lr = 0.00252511 +I0410 14:21:01.491282 18353 solver.cpp:218] Iteration 6960 (2.43262 iter/s, 4.93296s/12 iters), loss = 0.440145 +I0410 14:21:01.491334 18353 solver.cpp:237] Train net output #0: loss = 0.440145 (* 1 = 0.440145 loss) +I0410 14:21:01.491345 18353 sgd_solver.cpp:105] Iteration 6960, lr = 0.00251911 +I0410 14:21:06.427083 18353 solver.cpp:218] Iteration 6972 (2.43132 iter/s, 4.9356s/12 iters), loss = 0.503401 +I0410 14:21:06.427132 18353 solver.cpp:237] Train net output #0: loss = 0.503401 (* 1 = 0.503401 loss) +I0410 14:21:06.427142 18353 sgd_solver.cpp:105] Iteration 6972, lr = 0.00251313 +I0410 14:21:09.099288 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:11.304221 18353 solver.cpp:218] Iteration 6984 (2.46056 iter/s, 4.87694s/12 iters), loss = 0.470529 +I0410 14:21:11.304270 18353 solver.cpp:237] Train net output #0: loss = 0.470529 (* 1 = 0.470529 loss) +I0410 14:21:11.304280 18353 sgd_solver.cpp:105] Iteration 6984, lr = 0.00250717 +I0410 14:21:16.266705 18353 solver.cpp:218] Iteration 6996 (2.41824 iter/s, 4.96229s/12 iters), loss = 0.344354 +I0410 14:21:16.266757 18353 solver.cpp:237] Train net output #0: loss = 0.344354 (* 1 = 0.344354 loss) +I0410 14:21:16.266770 18353 sgd_solver.cpp:105] Iteration 6996, lr = 0.00250121 +I0410 14:21:21.193593 18353 solver.cpp:218] Iteration 7008 (2.43571 iter/s, 4.92669s/12 iters), loss = 0.693073 +I0410 14:21:21.193634 18353 solver.cpp:237] Train net output #0: loss = 0.693073 (* 1 = 0.693073 loss) +I0410 14:21:21.193642 18353 sgd_solver.cpp:105] Iteration 7008, lr = 0.00249528 +I0410 14:21:26.087723 18353 solver.cpp:218] Iteration 7020 (2.45201 iter/s, 4.89394s/12 iters), loss = 0.336238 +I0410 14:21:26.087782 18353 solver.cpp:237] Train net output #0: loss = 0.336238 (* 1 = 0.336238 loss) +I0410 14:21:26.087795 18353 sgd_solver.cpp:105] Iteration 7020, lr = 0.00248935 +I0410 14:21:31.005491 18353 solver.cpp:218] Iteration 7032 (2.44023 iter/s, 4.91756s/12 iters), loss = 0.317085 +I0410 14:21:31.005546 18353 solver.cpp:237] Train net output #0: loss = 0.317085 (* 1 = 0.317085 loss) +I0410 14:21:31.005560 18353 sgd_solver.cpp:105] Iteration 7032, lr = 0.00248344 +I0410 14:21:32.996740 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7038.caffemodel +I0410 14:21:33.290553 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7038.solverstate +I0410 14:21:33.497277 18353 solver.cpp:330] Iteration 7038, Testing net (#0) +I0410 14:21:33.497295 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:21:35.095932 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:37.837136 18353 solver.cpp:397] Test net output #0: accuracy = 0.533701 +I0410 14:21:37.837172 18353 solver.cpp:397] Test net output #1: loss = 2.32735 (* 1 = 2.32735 loss) +I0410 14:21:39.716154 18353 solver.cpp:218] Iteration 7044 (1.37767 iter/s, 8.71036s/12 iters), loss = 0.323803 +I0410 14:21:39.716277 18353 solver.cpp:237] Train net output #0: loss = 0.323803 (* 1 = 0.323803 loss) +I0410 14:21:39.716287 18353 sgd_solver.cpp:105] Iteration 7044, lr = 0.00247755 +I0410 14:21:44.618693 18353 solver.cpp:218] Iteration 7056 (2.44785 iter/s, 4.90227s/12 iters), loss = 0.554409 +I0410 14:21:44.618736 18353 solver.cpp:237] Train net output #0: loss = 0.554409 (* 1 = 0.554409 loss) +I0410 14:21:44.618746 18353 sgd_solver.cpp:105] Iteration 7056, lr = 0.00247166 +I0410 14:21:49.696239 18353 solver.cpp:218] Iteration 7068 (2.36343 iter/s, 5.07736s/12 iters), loss = 0.497578 +I0410 14:21:49.696280 18353 solver.cpp:237] Train net output #0: loss = 0.497578 (* 1 = 0.497578 loss) +I0410 14:21:49.696290 18353 sgd_solver.cpp:105] Iteration 7068, lr = 0.0024658 +I0410 14:21:54.492274 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:54.591624 18353 solver.cpp:218] Iteration 7080 (2.45138 iter/s, 4.8952s/12 iters), loss = 0.454659 +I0410 14:21:54.591665 18353 solver.cpp:237] Train net output #0: loss = 0.454659 (* 1 = 0.454659 loss) +I0410 14:21:54.591672 18353 sgd_solver.cpp:105] Iteration 7080, lr = 0.00245994 +I0410 14:21:59.487835 18353 solver.cpp:218] Iteration 7092 (2.45097 iter/s, 4.89603s/12 iters), loss = 0.427035 +I0410 14:21:59.487879 18353 solver.cpp:237] Train net output #0: loss = 0.427035 (* 1 = 0.427035 loss) +I0410 14:21:59.487890 18353 sgd_solver.cpp:105] Iteration 7092, lr = 0.0024541 +I0410 14:22:04.357770 18353 solver.cpp:218] Iteration 7104 (2.46419 iter/s, 4.86975s/12 iters), loss = 0.426499 +I0410 14:22:04.357815 18353 solver.cpp:237] Train net output #0: loss = 0.426499 (* 1 = 0.426499 loss) +I0410 14:22:04.357825 18353 sgd_solver.cpp:105] Iteration 7104, lr = 0.00244827 +I0410 14:22:09.297428 18353 solver.cpp:218] Iteration 7116 (2.42941 iter/s, 4.93947s/12 iters), loss = 0.365494 +I0410 14:22:09.297468 18353 solver.cpp:237] Train net output #0: loss = 0.365494 (* 1 = 0.365494 loss) +I0410 14:22:09.297478 18353 sgd_solver.cpp:105] Iteration 7116, lr = 0.00244246 +I0410 14:22:14.193352 18353 solver.cpp:218] Iteration 7128 (2.45111 iter/s, 4.89573s/12 iters), loss = 0.449697 +I0410 14:22:14.193465 18353 solver.cpp:237] Train net output #0: loss = 0.449697 (* 1 = 0.449697 loss) +I0410 14:22:14.193478 18353 sgd_solver.cpp:105] Iteration 7128, lr = 0.00243666 +I0410 14:22:18.700829 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7140.caffemodel +I0410 14:22:18.993100 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7140.solverstate +I0410 14:22:19.196791 18353 solver.cpp:330] Iteration 7140, Testing net (#0) +I0410 14:22:19.196820 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:22:20.848943 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:22:23.643405 18353 solver.cpp:397] Test net output #0: accuracy = 0.531863 +I0410 14:22:23.643450 18353 solver.cpp:397] Test net output #1: loss = 2.38475 (* 1 = 2.38475 loss) +I0410 14:22:23.724684 18353 solver.cpp:218] Iteration 7140 (1.25906 iter/s, 9.53095s/12 iters), loss = 0.471034 +I0410 14:22:23.724735 18353 solver.cpp:237] Train net output #0: loss = 0.471034 (* 1 = 0.471034 loss) +I0410 14:22:23.724747 18353 sgd_solver.cpp:105] Iteration 7140, lr = 0.00243088 +I0410 14:22:28.073588 18353 solver.cpp:218] Iteration 7152 (2.75943 iter/s, 4.34872s/12 iters), loss = 0.408697 +I0410 14:22:28.073642 18353 solver.cpp:237] Train net output #0: loss = 0.408697 (* 1 = 0.408697 loss) +I0410 14:22:28.073652 18353 sgd_solver.cpp:105] Iteration 7152, lr = 0.00242511 +I0410 14:22:33.042829 18353 solver.cpp:218] Iteration 7164 (2.41496 iter/s, 4.96903s/12 iters), loss = 0.264834 +I0410 14:22:33.042888 18353 solver.cpp:237] Train net output #0: loss = 0.264834 (* 1 = 0.264834 loss) +I0410 14:22:33.042901 18353 sgd_solver.cpp:105] Iteration 7164, lr = 0.00241935 +I0410 14:22:38.022423 18353 solver.cpp:218] Iteration 7176 (2.40994 iter/s, 4.97938s/12 iters), loss = 0.390787 +I0410 14:22:38.022481 18353 solver.cpp:237] Train net output #0: loss = 0.390787 (* 1 = 0.390787 loss) +I0410 14:22:38.022495 18353 sgd_solver.cpp:105] Iteration 7176, lr = 0.0024136 +I0410 14:22:40.236450 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:22:43.145560 18353 solver.cpp:218] Iteration 7188 (2.34241 iter/s, 5.12293s/12 iters), loss = 0.462879 +I0410 14:22:43.145609 18353 solver.cpp:237] Train net output #0: loss = 0.462879 (* 1 = 0.462879 loss) +I0410 14:22:43.145623 18353 sgd_solver.cpp:105] Iteration 7188, lr = 0.00240787 +I0410 14:22:48.017293 18353 solver.cpp:218] Iteration 7200 (2.46329 iter/s, 4.87154s/12 iters), loss = 0.411483 +I0410 14:22:48.017419 18353 solver.cpp:237] Train net output #0: loss = 0.411483 (* 1 = 0.411483 loss) +I0410 14:22:48.017429 18353 sgd_solver.cpp:105] Iteration 7200, lr = 0.00240216 +I0410 14:22:52.927667 18353 solver.cpp:218] Iteration 7212 (2.44394 iter/s, 4.9101s/12 iters), loss = 0.225682 +I0410 14:22:52.927721 18353 solver.cpp:237] Train net output #0: loss = 0.225682 (* 1 = 0.225682 loss) +I0410 14:22:52.927732 18353 sgd_solver.cpp:105] Iteration 7212, lr = 0.00239645 +I0410 14:22:57.987843 18353 solver.cpp:218] Iteration 7224 (2.37155 iter/s, 5.05998s/12 iters), loss = 0.410161 +I0410 14:22:57.987891 18353 solver.cpp:237] Train net output #0: loss = 0.410161 (* 1 = 0.410161 loss) +I0410 14:22:57.987901 18353 sgd_solver.cpp:105] Iteration 7224, lr = 0.00239076 +I0410 14:23:02.962646 18353 solver.cpp:218] Iteration 7236 (2.41225 iter/s, 4.9746s/12 iters), loss = 0.439174 +I0410 14:23:02.962702 18353 solver.cpp:237] Train net output #0: loss = 0.439174 (* 1 = 0.439174 loss) +I0410 14:23:02.962713 18353 sgd_solver.cpp:105] Iteration 7236, lr = 0.00238509 +I0410 14:23:05.011018 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7242.caffemodel +I0410 14:23:05.308598 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7242.solverstate +I0410 14:23:05.515314 18353 solver.cpp:330] Iteration 7242, Testing net (#0) +I0410 14:23:05.515347 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:23:07.146154 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:09.997645 18353 solver.cpp:397] Test net output #0: accuracy = 0.537377 +I0410 14:23:09.997695 18353 solver.cpp:397] Test net output #1: loss = 2.34597 (* 1 = 2.34597 loss) +I0410 14:23:11.767606 18353 solver.cpp:218] Iteration 7248 (1.36292 iter/s, 8.80466s/12 iters), loss = 0.446899 +I0410 14:23:11.767663 18353 solver.cpp:237] Train net output #0: loss = 0.446899 (* 1 = 0.446899 loss) +I0410 14:23:11.767675 18353 sgd_solver.cpp:105] Iteration 7248, lr = 0.00237942 +I0410 14:23:16.694267 18353 solver.cpp:218] Iteration 7260 (2.43583 iter/s, 4.92646s/12 iters), loss = 0.288486 +I0410 14:23:16.694325 18353 solver.cpp:237] Train net output #0: loss = 0.288486 (* 1 = 0.288486 loss) +I0410 14:23:16.694339 18353 sgd_solver.cpp:105] Iteration 7260, lr = 0.00237378 +I0410 14:23:21.641233 18353 solver.cpp:218] Iteration 7272 (2.42583 iter/s, 4.94676s/12 iters), loss = 0.366645 +I0410 14:23:21.641387 18353 solver.cpp:237] Train net output #0: loss = 0.366645 (* 1 = 0.366645 loss) +I0410 14:23:21.641403 18353 sgd_solver.cpp:105] Iteration 7272, lr = 0.00236814 +I0410 14:23:25.799857 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:26.538076 18353 solver.cpp:218] Iteration 7284 (2.45071 iter/s, 4.89655s/12 iters), loss = 0.452616 +I0410 14:23:26.538130 18353 solver.cpp:237] Train net output #0: loss = 0.452616 (* 1 = 0.452616 loss) +I0410 14:23:26.538143 18353 sgd_solver.cpp:105] Iteration 7284, lr = 0.00236252 +I0410 14:23:31.472009 18353 solver.cpp:218] Iteration 7296 (2.43223 iter/s, 4.93374s/12 iters), loss = 0.686861 +I0410 14:23:31.472060 18353 solver.cpp:237] Train net output #0: loss = 0.686861 (* 1 = 0.686861 loss) +I0410 14:23:31.472072 18353 sgd_solver.cpp:105] Iteration 7296, lr = 0.00235691 +I0410 14:23:36.342562 18353 solver.cpp:218] Iteration 7308 (2.46388 iter/s, 4.87036s/12 iters), loss = 0.480239 +I0410 14:23:36.342605 18353 solver.cpp:237] Train net output #0: loss = 0.480239 (* 1 = 0.480239 loss) +I0410 14:23:36.342615 18353 sgd_solver.cpp:105] Iteration 7308, lr = 0.00235131 +I0410 14:23:41.259428 18353 solver.cpp:218] Iteration 7320 (2.44067 iter/s, 4.91667s/12 iters), loss = 0.557563 +I0410 14:23:41.259477 18353 solver.cpp:237] Train net output #0: loss = 0.557563 (* 1 = 0.557563 loss) +I0410 14:23:41.259490 18353 sgd_solver.cpp:105] Iteration 7320, lr = 0.00234573 +I0410 14:23:46.185106 18353 solver.cpp:218] Iteration 7332 (2.43631 iter/s, 4.92548s/12 iters), loss = 0.501118 +I0410 14:23:46.185161 18353 solver.cpp:237] Train net output #0: loss = 0.501118 (* 1 = 0.501118 loss) +I0410 14:23:46.185173 18353 sgd_solver.cpp:105] Iteration 7332, lr = 0.00234016 +I0410 14:23:50.873056 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7344.caffemodel +I0410 14:23:51.431845 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7344.solverstate +I0410 14:23:52.242501 18353 solver.cpp:330] Iteration 7344, Testing net (#0) +I0410 14:23:52.242563 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:23:53.731781 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:56.592808 18353 solver.cpp:397] Test net output #0: accuracy = 0.548407 +I0410 14:23:56.592857 18353 solver.cpp:397] Test net output #1: loss = 2.28191 (* 1 = 2.28191 loss) +I0410 14:23:56.674088 18353 solver.cpp:218] Iteration 7344 (1.1441 iter/s, 10.4886s/12 iters), loss = 0.267234 +I0410 14:23:56.674139 18353 solver.cpp:237] Train net output #0: loss = 0.267234 (* 1 = 0.267234 loss) +I0410 14:23:56.674150 18353 sgd_solver.cpp:105] Iteration 7344, lr = 0.0023346 +I0410 14:24:00.775830 18353 solver.cpp:218] Iteration 7356 (2.92571 iter/s, 4.10157s/12 iters), loss = 0.209648 +I0410 14:24:00.775885 18353 solver.cpp:237] Train net output #0: loss = 0.209648 (* 1 = 0.209648 loss) +I0410 14:24:00.775898 18353 sgd_solver.cpp:105] Iteration 7356, lr = 0.00232906 +I0410 14:24:05.670747 18353 solver.cpp:218] Iteration 7368 (2.45162 iter/s, 4.89471s/12 iters), loss = 0.333602 +I0410 14:24:05.670807 18353 solver.cpp:237] Train net output #0: loss = 0.333602 (* 1 = 0.333602 loss) +I0410 14:24:05.670820 18353 sgd_solver.cpp:105] Iteration 7368, lr = 0.00232353 +I0410 14:24:10.577785 18353 solver.cpp:218] Iteration 7380 (2.44557 iter/s, 4.90683s/12 iters), loss = 0.342976 +I0410 14:24:10.577849 18353 solver.cpp:237] Train net output #0: loss = 0.342976 (* 1 = 0.342976 loss) +I0410 14:24:10.577865 18353 sgd_solver.cpp:105] Iteration 7380, lr = 0.00231802 +I0410 14:24:11.934064 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:15.491094 18353 solver.cpp:218] Iteration 7392 (2.44245 iter/s, 4.9131s/12 iters), loss = 0.519873 +I0410 14:24:15.491148 18353 solver.cpp:237] Train net output #0: loss = 0.519873 (* 1 = 0.519873 loss) +I0410 14:24:15.491159 18353 sgd_solver.cpp:105] Iteration 7392, lr = 0.00231251 +I0410 14:24:20.379324 18353 solver.cpp:218] Iteration 7404 (2.45498 iter/s, 4.88803s/12 iters), loss = 0.239125 +I0410 14:24:20.379379 18353 solver.cpp:237] Train net output #0: loss = 0.239125 (* 1 = 0.239125 loss) +I0410 14:24:20.379390 18353 sgd_solver.cpp:105] Iteration 7404, lr = 0.00230702 +I0410 14:24:25.317571 18353 solver.cpp:218] Iteration 7416 (2.43011 iter/s, 4.93805s/12 iters), loss = 0.27665 +I0410 14:24:25.317716 18353 solver.cpp:237] Train net output #0: loss = 0.27665 (* 1 = 0.27665 loss) +I0410 14:24:25.317729 18353 sgd_solver.cpp:105] Iteration 7416, lr = 0.00230154 +I0410 14:24:30.211930 18353 solver.cpp:218] Iteration 7428 (2.45195 iter/s, 4.89407s/12 iters), loss = 0.274236 +I0410 14:24:30.211982 18353 solver.cpp:237] Train net output #0: loss = 0.274236 (* 1 = 0.274236 loss) +I0410 14:24:30.211993 18353 sgd_solver.cpp:105] Iteration 7428, lr = 0.00229608 +I0410 14:24:35.138453 18353 solver.cpp:218] Iteration 7440 (2.43589 iter/s, 4.92632s/12 iters), loss = 0.453611 +I0410 14:24:35.138509 18353 solver.cpp:237] Train net output #0: loss = 0.453611 (* 1 = 0.453611 loss) +I0410 14:24:35.138520 18353 sgd_solver.cpp:105] Iteration 7440, lr = 0.00229063 +I0410 14:24:37.114804 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7446.caffemodel +I0410 14:24:37.421856 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7446.solverstate +I0410 14:24:37.627766 18353 solver.cpp:330] Iteration 7446, Testing net (#0) +I0410 14:24:37.627800 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:24:39.177572 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:42.263938 18353 solver.cpp:397] Test net output #0: accuracy = 0.542892 +I0410 14:24:42.263990 18353 solver.cpp:397] Test net output #1: loss = 2.33987 (* 1 = 2.33987 loss) +I0410 14:24:44.111340 18353 solver.cpp:218] Iteration 7452 (1.33741 iter/s, 8.97258s/12 iters), loss = 0.437316 +I0410 14:24:44.111397 18353 solver.cpp:237] Train net output #0: loss = 0.437316 (* 1 = 0.437316 loss) +I0410 14:24:44.111409 18353 sgd_solver.cpp:105] Iteration 7452, lr = 0.00228519 +I0410 14:24:49.080281 18353 solver.cpp:218] Iteration 7464 (2.41508 iter/s, 4.96879s/12 iters), loss = 0.357817 +I0410 14:24:49.080339 18353 solver.cpp:237] Train net output #0: loss = 0.357817 (* 1 = 0.357817 loss) +I0410 14:24:49.080353 18353 sgd_solver.cpp:105] Iteration 7464, lr = 0.00227976 +I0410 14:24:53.983656 18353 solver.cpp:218] Iteration 7476 (2.44737 iter/s, 4.90323s/12 iters), loss = 0.460165 +I0410 14:24:53.983711 18353 solver.cpp:237] Train net output #0: loss = 0.460165 (* 1 = 0.460165 loss) +I0410 14:24:53.983726 18353 sgd_solver.cpp:105] Iteration 7476, lr = 0.00227435 +I0410 14:24:57.473981 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:58.944938 18353 solver.cpp:218] Iteration 7488 (2.4188 iter/s, 4.96114s/12 iters), loss = 0.628991 +I0410 14:24:58.944988 18353 solver.cpp:237] Train net output #0: loss = 0.628991 (* 1 = 0.628991 loss) +I0410 14:24:58.944998 18353 sgd_solver.cpp:105] Iteration 7488, lr = 0.00226895 +I0410 14:25:03.788949 18353 solver.cpp:218] Iteration 7500 (2.47735 iter/s, 4.84388s/12 iters), loss = 0.34601 +I0410 14:25:03.788987 18353 solver.cpp:237] Train net output #0: loss = 0.34601 (* 1 = 0.34601 loss) +I0410 14:25:03.788996 18353 sgd_solver.cpp:105] Iteration 7500, lr = 0.00226357 +I0410 14:25:08.711354 18353 solver.cpp:218] Iteration 7512 (2.4379 iter/s, 4.92228s/12 iters), loss = 0.243745 +I0410 14:25:08.711395 18353 solver.cpp:237] Train net output #0: loss = 0.243745 (* 1 = 0.243745 loss) +I0410 14:25:08.711405 18353 sgd_solver.cpp:105] Iteration 7512, lr = 0.00225819 +I0410 14:25:13.653805 18353 solver.cpp:218] Iteration 7524 (2.42801 iter/s, 4.94232s/12 iters), loss = 0.243297 +I0410 14:25:13.653862 18353 solver.cpp:237] Train net output #0: loss = 0.243297 (* 1 = 0.243297 loss) +I0410 14:25:13.653877 18353 sgd_solver.cpp:105] Iteration 7524, lr = 0.00225283 +I0410 14:25:18.594547 18353 solver.cpp:218] Iteration 7536 (2.42886 iter/s, 4.9406s/12 iters), loss = 0.296403 +I0410 14:25:18.594606 18353 solver.cpp:237] Train net output #0: loss = 0.296403 (* 1 = 0.296403 loss) +I0410 14:25:18.594619 18353 sgd_solver.cpp:105] Iteration 7536, lr = 0.00224748 +I0410 14:25:23.016207 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7548.caffemodel +I0410 14:25:23.342218 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7548.solverstate +I0410 14:25:23.548983 18353 solver.cpp:330] Iteration 7548, Testing net (#0) +I0410 14:25:23.549005 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:25:24.938483 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:25:27.875013 18353 solver.cpp:397] Test net output #0: accuracy = 0.551471 +I0410 14:25:27.875126 18353 solver.cpp:397] Test net output #1: loss = 2.39349 (* 1 = 2.39349 loss) +I0410 14:25:27.957713 18353 solver.cpp:218] Iteration 7548 (1.28165 iter/s, 9.36295s/12 iters), loss = 0.238834 +I0410 14:25:27.957757 18353 solver.cpp:237] Train net output #0: loss = 0.238834 (* 1 = 0.238834 loss) +I0410 14:25:27.957767 18353 sgd_solver.cpp:105] Iteration 7548, lr = 0.00224215 +I0410 14:25:32.069738 18353 solver.cpp:218] Iteration 7560 (2.91836 iter/s, 4.1119s/12 iters), loss = 0.379549 +I0410 14:25:32.069787 18353 solver.cpp:237] Train net output #0: loss = 0.379549 (* 1 = 0.379549 loss) +I0410 14:25:32.069797 18353 sgd_solver.cpp:105] Iteration 7560, lr = 0.00223682 +I0410 14:25:36.958432 18353 solver.cpp:218] Iteration 7572 (2.45471 iter/s, 4.88856s/12 iters), loss = 0.405818 +I0410 14:25:36.958473 18353 solver.cpp:237] Train net output #0: loss = 0.405818 (* 1 = 0.405818 loss) +I0410 14:25:36.958482 18353 sgd_solver.cpp:105] Iteration 7572, lr = 0.00223151 +I0410 14:25:42.049321 18353 solver.cpp:218] Iteration 7584 (2.35721 iter/s, 5.09075s/12 iters), loss = 0.399859 +I0410 14:25:42.049367 18353 solver.cpp:237] Train net output #0: loss = 0.399859 (* 1 = 0.399859 loss) +I0410 14:25:42.049377 18353 sgd_solver.cpp:105] Iteration 7584, lr = 0.00222621 +I0410 14:25:42.682785 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:25:46.988426 18353 solver.cpp:218] Iteration 7596 (2.42966 iter/s, 4.93897s/12 iters), loss = 0.320253 +I0410 14:25:46.988482 18353 solver.cpp:237] Train net output #0: loss = 0.320253 (* 1 = 0.320253 loss) +I0410 14:25:46.988495 18353 sgd_solver.cpp:105] Iteration 7596, lr = 0.00222093 +I0410 14:25:51.906843 18353 solver.cpp:218] Iteration 7608 (2.43988 iter/s, 4.91828s/12 iters), loss = 0.213703 +I0410 14:25:51.906881 18353 solver.cpp:237] Train net output #0: loss = 0.213703 (* 1 = 0.213703 loss) +I0410 14:25:51.906891 18353 sgd_solver.cpp:105] Iteration 7608, lr = 0.00221565 +I0410 14:25:56.984663 18353 solver.cpp:218] Iteration 7620 (2.36328 iter/s, 5.07769s/12 iters), loss = 0.363002 +I0410 14:25:56.984716 18353 solver.cpp:237] Train net output #0: loss = 0.363002 (* 1 = 0.363002 loss) +I0410 14:25:56.984730 18353 sgd_solver.cpp:105] Iteration 7620, lr = 0.00221039 +I0410 14:25:57.759373 18353 blocking_queue.cpp:49] Waiting for data +I0410 14:26:01.951365 18353 solver.cpp:218] Iteration 7632 (2.41616 iter/s, 4.96656s/12 iters), loss = 0.482575 +I0410 14:26:01.951457 18353 solver.cpp:237] Train net output #0: loss = 0.482575 (* 1 = 0.482575 loss) +I0410 14:26:01.951472 18353 sgd_solver.cpp:105] Iteration 7632, lr = 0.00220515 +I0410 14:26:06.885231 18353 solver.cpp:218] Iteration 7644 (2.43226 iter/s, 4.93369s/12 iters), loss = 0.273094 +I0410 14:26:06.885277 18353 solver.cpp:237] Train net output #0: loss = 0.273094 (* 1 = 0.273094 loss) +I0410 14:26:06.885286 18353 sgd_solver.cpp:105] Iteration 7644, lr = 0.00219991 +I0410 14:26:08.881283 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7650.caffemodel +I0410 14:26:09.193208 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7650.solverstate +I0410 14:26:09.399282 18353 solver.cpp:330] Iteration 7650, Testing net (#0) +I0410 14:26:09.399308 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:26:10.854840 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:13.855095 18353 solver.cpp:397] Test net output #0: accuracy = 0.547794 +I0410 14:26:13.855126 18353 solver.cpp:397] Test net output #1: loss = 2.37706 (* 1 = 2.37706 loss) +I0410 14:26:15.805285 18353 solver.cpp:218] Iteration 7656 (1.34531 iter/s, 8.91985s/12 iters), loss = 0.408765 +I0410 14:26:15.805335 18353 solver.cpp:237] Train net output #0: loss = 0.408765 (* 1 = 0.408765 loss) +I0410 14:26:15.805344 18353 sgd_solver.cpp:105] Iteration 7656, lr = 0.00219469 +I0410 14:26:20.728349 18353 solver.cpp:218] Iteration 7668 (2.43758 iter/s, 4.92292s/12 iters), loss = 0.288223 +I0410 14:26:20.728397 18353 solver.cpp:237] Train net output #0: loss = 0.288223 (* 1 = 0.288223 loss) +I0410 14:26:20.728406 18353 sgd_solver.cpp:105] Iteration 7668, lr = 0.00218948 +I0410 14:26:25.663763 18353 solver.cpp:218] Iteration 7680 (2.43148 iter/s, 4.93526s/12 iters), loss = 0.425493 +I0410 14:26:25.663812 18353 solver.cpp:237] Train net output #0: loss = 0.425493 (* 1 = 0.425493 loss) +I0410 14:26:25.663822 18353 sgd_solver.cpp:105] Iteration 7680, lr = 0.00218428 +I0410 14:26:28.425352 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:30.627898 18353 solver.cpp:218] Iteration 7692 (2.41741 iter/s, 4.96399s/12 iters), loss = 0.327503 +I0410 14:26:30.627951 18353 solver.cpp:237] Train net output #0: loss = 0.327503 (* 1 = 0.327503 loss) +I0410 14:26:30.627962 18353 sgd_solver.cpp:105] Iteration 7692, lr = 0.00217909 +I0410 14:26:35.506058 18353 solver.cpp:218] Iteration 7704 (2.46002 iter/s, 4.87801s/12 iters), loss = 0.375226 +I0410 14:26:35.506201 18353 solver.cpp:237] Train net output #0: loss = 0.375226 (* 1 = 0.375226 loss) +I0410 14:26:35.506222 18353 sgd_solver.cpp:105] Iteration 7704, lr = 0.00217392 +I0410 14:26:40.388186 18353 solver.cpp:218] Iteration 7716 (2.45806 iter/s, 4.88189s/12 iters), loss = 0.367266 +I0410 14:26:40.388236 18353 solver.cpp:237] Train net output #0: loss = 0.367266 (* 1 = 0.367266 loss) +I0410 14:26:40.388245 18353 sgd_solver.cpp:105] Iteration 7716, lr = 0.00216876 +I0410 14:26:45.293215 18353 solver.cpp:218] Iteration 7728 (2.44654 iter/s, 4.90488s/12 iters), loss = 0.374394 +I0410 14:26:45.293273 18353 solver.cpp:237] Train net output #0: loss = 0.374394 (* 1 = 0.374394 loss) +I0410 14:26:45.293287 18353 sgd_solver.cpp:105] Iteration 7728, lr = 0.00216361 +I0410 14:26:50.314680 18353 solver.cpp:218] Iteration 7740 (2.38982 iter/s, 5.02131s/12 iters), loss = 0.434383 +I0410 14:26:50.314741 18353 solver.cpp:237] Train net output #0: loss = 0.434383 (* 1 = 0.434383 loss) +I0410 14:26:50.314755 18353 sgd_solver.cpp:105] Iteration 7740, lr = 0.00215847 +I0410 14:26:54.816440 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7752.caffemodel +I0410 14:26:55.114588 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7752.solverstate +I0410 14:26:55.315079 18353 solver.cpp:330] Iteration 7752, Testing net (#0) +I0410 14:26:55.315102 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:26:56.720266 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:59.737787 18353 solver.cpp:397] Test net output #0: accuracy = 0.548407 +I0410 14:26:59.737835 18353 solver.cpp:397] Test net output #1: loss = 2.40263 (* 1 = 2.40263 loss) +I0410 14:26:59.819334 18353 solver.cpp:218] Iteration 7752 (1.26257 iter/s, 9.50442s/12 iters), loss = 0.289652 +I0410 14:26:59.819386 18353 solver.cpp:237] Train net output #0: loss = 0.289652 (* 1 = 0.289652 loss) +I0410 14:26:59.819398 18353 sgd_solver.cpp:105] Iteration 7752, lr = 0.00215335 +I0410 14:27:04.016626 18353 solver.cpp:218] Iteration 7764 (2.85908 iter/s, 4.19715s/12 iters), loss = 0.25654 +I0410 14:27:04.016680 18353 solver.cpp:237] Train net output #0: loss = 0.25654 (* 1 = 0.25654 loss) +I0410 14:27:04.016690 18353 sgd_solver.cpp:105] Iteration 7764, lr = 0.00214823 +I0410 14:27:08.920397 18353 solver.cpp:218] Iteration 7776 (2.44718 iter/s, 4.90361s/12 iters), loss = 0.411403 +I0410 14:27:08.920547 18353 solver.cpp:237] Train net output #0: loss = 0.411403 (* 1 = 0.411403 loss) +I0410 14:27:08.920562 18353 sgd_solver.cpp:105] Iteration 7776, lr = 0.00214313 +I0410 14:27:13.823060 18353 solver.cpp:218] Iteration 7788 (2.44777 iter/s, 4.90242s/12 iters), loss = 0.216058 +I0410 14:27:13.823120 18353 solver.cpp:237] Train net output #0: loss = 0.216058 (* 1 = 0.216058 loss) +I0410 14:27:13.823134 18353 sgd_solver.cpp:105] Iteration 7788, lr = 0.00213805 +I0410 14:27:13.831174 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:27:18.984700 18353 solver.cpp:218] Iteration 7800 (2.32492 iter/s, 5.16148s/12 iters), loss = 0.367202 +I0410 14:27:18.984750 18353 solver.cpp:237] Train net output #0: loss = 0.367202 (* 1 = 0.367202 loss) +I0410 14:27:18.984762 18353 sgd_solver.cpp:105] Iteration 7800, lr = 0.00213297 +I0410 14:27:23.937992 18353 solver.cpp:218] Iteration 7812 (2.42271 iter/s, 4.95312s/12 iters), loss = 0.403354 +I0410 14:27:23.938052 18353 solver.cpp:237] Train net output #0: loss = 0.403354 (* 1 = 0.403354 loss) +I0410 14:27:23.938067 18353 sgd_solver.cpp:105] Iteration 7812, lr = 0.00212791 +I0410 14:27:28.816071 18353 solver.cpp:218] Iteration 7824 (2.46006 iter/s, 4.87792s/12 iters), loss = 0.284613 +I0410 14:27:28.816126 18353 solver.cpp:237] Train net output #0: loss = 0.284613 (* 1 = 0.284613 loss) +I0410 14:27:28.816138 18353 sgd_solver.cpp:105] Iteration 7824, lr = 0.00212285 +I0410 14:27:33.652515 18353 solver.cpp:218] Iteration 7836 (2.48124 iter/s, 4.83629s/12 iters), loss = 0.217343 +I0410 14:27:33.652575 18353 solver.cpp:237] Train net output #0: loss = 0.217343 (* 1 = 0.217343 loss) +I0410 14:27:33.652588 18353 sgd_solver.cpp:105] Iteration 7836, lr = 0.00211781 +I0410 14:27:38.575361 18353 solver.cpp:218] Iteration 7848 (2.4377 iter/s, 4.92268s/12 iters), loss = 0.567162 +I0410 14:27:38.575413 18353 solver.cpp:237] Train net output #0: loss = 0.567162 (* 1 = 0.567162 loss) +I0410 14:27:38.575425 18353 sgd_solver.cpp:105] Iteration 7848, lr = 0.00211279 +I0410 14:27:40.544589 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7854.caffemodel +I0410 14:27:40.880473 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7854.solverstate +I0410 14:27:41.092520 18353 solver.cpp:330] Iteration 7854, Testing net (#0) +I0410 14:27:41.092545 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:27:42.423786 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:27:45.489166 18353 solver.cpp:397] Test net output #0: accuracy = 0.553309 +I0410 14:27:45.489198 18353 solver.cpp:397] Test net output #1: loss = 2.34634 (* 1 = 2.34634 loss) +I0410 14:27:47.322710 18353 solver.cpp:218] Iteration 7860 (1.37188 iter/s, 8.74713s/12 iters), loss = 0.353139 +I0410 14:27:47.322762 18353 solver.cpp:237] Train net output #0: loss = 0.353139 (* 1 = 0.353139 loss) +I0410 14:27:47.322774 18353 sgd_solver.cpp:105] Iteration 7860, lr = 0.00210777 +I0410 14:27:52.169790 18353 solver.cpp:218] Iteration 7872 (2.4758 iter/s, 4.84692s/12 iters), loss = 0.374548 +I0410 14:27:52.169848 18353 solver.cpp:237] Train net output #0: loss = 0.374548 (* 1 = 0.374548 loss) +I0410 14:27:52.169860 18353 sgd_solver.cpp:105] Iteration 7872, lr = 0.00210277 +I0410 14:27:57.051791 18353 solver.cpp:218] Iteration 7884 (2.45809 iter/s, 4.88184s/12 iters), loss = 0.307182 +I0410 14:27:57.051848 18353 solver.cpp:237] Train net output #0: loss = 0.307182 (* 1 = 0.307182 loss) +I0410 14:27:57.051862 18353 sgd_solver.cpp:105] Iteration 7884, lr = 0.00209777 +I0410 14:27:59.149827 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:02.072031 18353 solver.cpp:218] Iteration 7896 (2.3904 iter/s, 5.02008s/12 iters), loss = 0.305245 +I0410 14:28:02.072094 18353 solver.cpp:237] Train net output #0: loss = 0.305245 (* 1 = 0.305245 loss) +I0410 14:28:02.072108 18353 sgd_solver.cpp:105] Iteration 7896, lr = 0.00209279 +I0410 14:28:06.935024 18353 solver.cpp:218] Iteration 7908 (2.4677 iter/s, 4.86283s/12 iters), loss = 0.392762 +I0410 14:28:06.935082 18353 solver.cpp:237] Train net output #0: loss = 0.392762 (* 1 = 0.392762 loss) +I0410 14:28:06.935096 18353 sgd_solver.cpp:105] Iteration 7908, lr = 0.00208782 +I0410 14:28:11.835238 18353 solver.cpp:218] Iteration 7920 (2.44895 iter/s, 4.90006s/12 iters), loss = 0.394749 +I0410 14:28:11.835392 18353 solver.cpp:237] Train net output #0: loss = 0.394749 (* 1 = 0.394749 loss) +I0410 14:28:11.835407 18353 sgd_solver.cpp:105] Iteration 7920, lr = 0.00208287 +I0410 14:28:16.741601 18353 solver.cpp:218] Iteration 7932 (2.44593 iter/s, 4.90611s/12 iters), loss = 0.479549 +I0410 14:28:16.741655 18353 solver.cpp:237] Train net output #0: loss = 0.479549 (* 1 = 0.479549 loss) +I0410 14:28:16.741669 18353 sgd_solver.cpp:105] Iteration 7932, lr = 0.00207792 +I0410 14:28:21.628052 18353 solver.cpp:218] Iteration 7944 (2.45585 iter/s, 4.88629s/12 iters), loss = 0.247805 +I0410 14:28:21.628105 18353 solver.cpp:237] Train net output #0: loss = 0.247805 (* 1 = 0.247805 loss) +I0410 14:28:21.628118 18353 sgd_solver.cpp:105] Iteration 7944, lr = 0.00207299 +I0410 14:28:26.100972 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7956.caffemodel +I0410 14:28:26.411490 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7956.solverstate +I0410 14:28:26.607393 18353 solver.cpp:330] Iteration 7956, Testing net (#0) +I0410 14:28:26.607414 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:28:27.944399 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:31.042133 18353 solver.cpp:397] Test net output #0: accuracy = 0.54902 +I0410 14:28:31.042179 18353 solver.cpp:397] Test net output #1: loss = 2.37796 (* 1 = 2.37796 loss) +I0410 14:28:31.123400 18353 solver.cpp:218] Iteration 7956 (1.26381 iter/s, 9.49511s/12 iters), loss = 0.341276 +I0410 14:28:31.123457 18353 solver.cpp:237] Train net output #0: loss = 0.341276 (* 1 = 0.341276 loss) +I0410 14:28:31.123469 18353 sgd_solver.cpp:105] Iteration 7956, lr = 0.00206807 +I0410 14:28:35.166353 18353 solver.cpp:218] Iteration 7968 (2.96823 iter/s, 4.04281s/12 iters), loss = 0.317345 +I0410 14:28:35.166401 18353 solver.cpp:237] Train net output #0: loss = 0.317345 (* 1 = 0.317345 loss) +I0410 14:28:35.166409 18353 sgd_solver.cpp:105] Iteration 7968, lr = 0.00206316 +I0410 14:28:40.059130 18353 solver.cpp:218] Iteration 7980 (2.45267 iter/s, 4.89262s/12 iters), loss = 0.198083 +I0410 14:28:40.059177 18353 solver.cpp:237] Train net output #0: loss = 0.198083 (* 1 = 0.198083 loss) +I0410 14:28:40.059188 18353 sgd_solver.cpp:105] Iteration 7980, lr = 0.00205826 +I0410 14:28:44.395006 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:45.108878 18353 solver.cpp:218] Iteration 7992 (2.37643 iter/s, 5.0496s/12 iters), loss = 0.291573 +I0410 14:28:45.108922 18353 solver.cpp:237] Train net output #0: loss = 0.291573 (* 1 = 0.291573 loss) +I0410 14:28:45.108932 18353 sgd_solver.cpp:105] Iteration 7992, lr = 0.00205337 +I0410 14:28:50.052569 18353 solver.cpp:218] Iteration 8004 (2.42741 iter/s, 4.94354s/12 iters), loss = 0.341455 +I0410 14:28:50.052623 18353 solver.cpp:237] Train net output #0: loss = 0.341455 (* 1 = 0.341455 loss) +I0410 14:28:50.052635 18353 sgd_solver.cpp:105] Iteration 8004, lr = 0.0020485 +I0410 14:28:55.008193 18353 solver.cpp:218] Iteration 8016 (2.42157 iter/s, 4.95546s/12 iters), loss = 0.389072 +I0410 14:28:55.008241 18353 solver.cpp:237] Train net output #0: loss = 0.389072 (* 1 = 0.389072 loss) +I0410 14:28:55.008251 18353 sgd_solver.cpp:105] Iteration 8016, lr = 0.00204363 +I0410 14:28:59.923367 18353 solver.cpp:218] Iteration 8028 (2.4415 iter/s, 4.91501s/12 iters), loss = 0.377484 +I0410 14:28:59.923426 18353 solver.cpp:237] Train net output #0: loss = 0.377484 (* 1 = 0.377484 loss) +I0410 14:28:59.923439 18353 sgd_solver.cpp:105] Iteration 8028, lr = 0.00203878 +I0410 14:29:04.853814 18353 solver.cpp:218] Iteration 8040 (2.43394 iter/s, 4.93028s/12 iters), loss = 0.380077 +I0410 14:29:04.853865 18353 solver.cpp:237] Train net output #0: loss = 0.380077 (* 1 = 0.380077 loss) +I0410 14:29:04.853878 18353 sgd_solver.cpp:105] Iteration 8040, lr = 0.00203394 +I0410 14:29:09.737445 18353 solver.cpp:218] Iteration 8052 (2.45727 iter/s, 4.88348s/12 iters), loss = 0.420411 +I0410 14:29:09.737501 18353 solver.cpp:237] Train net output #0: loss = 0.420411 (* 1 = 0.420411 loss) +I0410 14:29:09.737514 18353 sgd_solver.cpp:105] Iteration 8052, lr = 0.00202911 +I0410 14:29:11.765049 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8058.caffemodel +I0410 14:29:12.086783 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8058.solverstate +I0410 14:29:12.297161 18353 solver.cpp:330] Iteration 8058, Testing net (#0) +I0410 14:29:12.297191 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:29:13.495993 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:29:16.641419 18353 solver.cpp:397] Test net output #0: accuracy = 0.561275 +I0410 14:29:16.641598 18353 solver.cpp:397] Test net output #1: loss = 2.3362 (* 1 = 2.3362 loss) +I0410 14:29:18.501336 18353 solver.cpp:218] Iteration 8064 (1.36929 iter/s, 8.76366s/12 iters), loss = 0.236726 +I0410 14:29:18.501389 18353 solver.cpp:237] Train net output #0: loss = 0.236726 (* 1 = 0.236726 loss) +I0410 14:29:18.501400 18353 sgd_solver.cpp:105] Iteration 8064, lr = 0.00202429 +I0410 14:29:23.442833 18353 solver.cpp:218] Iteration 8076 (2.42849 iter/s, 4.94134s/12 iters), loss = 0.291229 +I0410 14:29:23.442883 18353 solver.cpp:237] Train net output #0: loss = 0.291229 (* 1 = 0.291229 loss) +I0410 14:29:23.442895 18353 sgd_solver.cpp:105] Iteration 8076, lr = 0.00201949 +I0410 14:29:28.426789 18353 solver.cpp:218] Iteration 8088 (2.4078 iter/s, 4.9838s/12 iters), loss = 0.232112 +I0410 14:29:28.426843 18353 solver.cpp:237] Train net output #0: loss = 0.232112 (* 1 = 0.232112 loss) +I0410 14:29:28.426858 18353 sgd_solver.cpp:105] Iteration 8088, lr = 0.00201469 +I0410 14:29:29.789894 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:29:33.322602 18353 solver.cpp:218] Iteration 8100 (2.45116 iter/s, 4.89564s/12 iters), loss = 0.265101 +I0410 14:29:33.322669 18353 solver.cpp:237] Train net output #0: loss = 0.265101 (* 1 = 0.265101 loss) +I0410 14:29:33.322685 18353 sgd_solver.cpp:105] Iteration 8100, lr = 0.00200991 +I0410 14:29:38.230742 18353 solver.cpp:218] Iteration 8112 (2.44501 iter/s, 4.90796s/12 iters), loss = 0.337756 +I0410 14:29:38.230799 18353 solver.cpp:237] Train net output #0: loss = 0.337756 (* 1 = 0.337756 loss) +I0410 14:29:38.230811 18353 sgd_solver.cpp:105] Iteration 8112, lr = 0.00200514 +I0410 14:29:43.164695 18353 solver.cpp:218] Iteration 8124 (2.43221 iter/s, 4.93378s/12 iters), loss = 0.230637 +I0410 14:29:43.164750 18353 solver.cpp:237] Train net output #0: loss = 0.230637 (* 1 = 0.230637 loss) +I0410 14:29:43.164762 18353 sgd_solver.cpp:105] Iteration 8124, lr = 0.00200038 +I0410 14:29:48.046355 18353 solver.cpp:218] Iteration 8136 (2.45826 iter/s, 4.88149s/12 iters), loss = 0.264065 +I0410 14:29:48.046458 18353 solver.cpp:237] Train net output #0: loss = 0.264065 (* 1 = 0.264065 loss) +I0410 14:29:48.046471 18353 sgd_solver.cpp:105] Iteration 8136, lr = 0.00199563 +I0410 14:29:53.277913 18353 solver.cpp:218] Iteration 8148 (2.29387 iter/s, 5.23134s/12 iters), loss = 0.36992 +I0410 14:29:53.277990 18353 solver.cpp:237] Train net output #0: loss = 0.36992 (* 1 = 0.36992 loss) +I0410 14:29:53.278004 18353 sgd_solver.cpp:105] Iteration 8148, lr = 0.00199089 +I0410 14:29:57.830231 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8160.caffemodel +I0410 14:29:58.127279 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8160.solverstate +I0410 14:29:58.332096 18353 solver.cpp:330] Iteration 8160, Testing net (#0) +I0410 14:29:58.332129 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:29:59.629873 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:30:03.178757 18353 solver.cpp:397] Test net output #0: accuracy = 0.54902 +I0410 14:30:03.178804 18353 solver.cpp:397] Test net output #1: loss = 2.39821 (* 1 = 2.39821 loss) +I0410 14:30:03.260154 18353 solver.cpp:218] Iteration 8160 (1.20217 iter/s, 9.98196s/12 iters), loss = 0.329622 +I0410 14:30:03.260202 18353 solver.cpp:237] Train net output #0: loss = 0.329622 (* 1 = 0.329622 loss) +I0410 14:30:03.260215 18353 sgd_solver.cpp:105] Iteration 8160, lr = 0.00198616 +I0410 14:30:07.502768 18353 solver.cpp:218] Iteration 8172 (2.82855 iter/s, 4.24246s/12 iters), loss = 0.160831 +I0410 14:30:07.502828 18353 solver.cpp:237] Train net output #0: loss = 0.160831 (* 1 = 0.160831 loss) +I0410 14:30:07.502841 18353 sgd_solver.cpp:105] Iteration 8172, lr = 0.00198145 +I0410 14:30:12.435073 18353 solver.cpp:218] Iteration 8184 (2.43303 iter/s, 4.93213s/12 iters), loss = 0.305543 +I0410 14:30:12.435139 18353 solver.cpp:237] Train net output #0: loss = 0.305543 (* 1 = 0.305543 loss) +I0410 14:30:12.435153 18353 sgd_solver.cpp:105] Iteration 8184, lr = 0.00197674 +I0410 14:30:15.882968 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:30:17.310302 18353 solver.cpp:218] Iteration 8196 (2.46151 iter/s, 4.87505s/12 iters), loss = 0.209504 +I0410 14:30:17.310350 18353 solver.cpp:237] Train net output #0: loss = 0.209504 (* 1 = 0.209504 loss) +I0410 14:30:17.310361 18353 sgd_solver.cpp:105] Iteration 8196, lr = 0.00197205 +I0410 14:30:22.243680 18353 solver.cpp:218] Iteration 8208 (2.43249 iter/s, 4.93322s/12 iters), loss = 0.383752 +I0410 14:30:22.243818 18353 solver.cpp:237] Train net output #0: loss = 0.383752 (* 1 = 0.383752 loss) +I0410 14:30:22.243830 18353 sgd_solver.cpp:105] Iteration 8208, lr = 0.00196737 +I0410 14:30:27.290490 18353 solver.cpp:218] Iteration 8220 (2.37786 iter/s, 5.04656s/12 iters), loss = 0.305497 +I0410 14:30:27.290542 18353 solver.cpp:237] Train net output #0: loss = 0.305497 (* 1 = 0.305497 loss) +I0410 14:30:27.290555 18353 sgd_solver.cpp:105] Iteration 8220, lr = 0.0019627 +I0410 14:30:32.269920 18353 solver.cpp:218] Iteration 8232 (2.41 iter/s, 4.97926s/12 iters), loss = 0.328397 +I0410 14:30:32.269990 18353 solver.cpp:237] Train net output #0: loss = 0.328397 (* 1 = 0.328397 loss) +I0410 14:30:32.270004 18353 sgd_solver.cpp:105] Iteration 8232, lr = 0.00195804 +I0410 14:30:37.209275 18353 solver.cpp:218] Iteration 8244 (2.42955 iter/s, 4.93918s/12 iters), loss = 0.26712 +I0410 14:30:37.209321 18353 solver.cpp:237] Train net output #0: loss = 0.26712 (* 1 = 0.26712 loss) +I0410 14:30:37.209331 18353 sgd_solver.cpp:105] Iteration 8244, lr = 0.00195339 +I0410 14:30:42.114804 18353 solver.cpp:218] Iteration 8256 (2.4463 iter/s, 4.90537s/12 iters), loss = 0.268471 +I0410 14:30:42.114861 18353 solver.cpp:237] Train net output #0: loss = 0.268471 (* 1 = 0.268471 loss) +I0410 14:30:42.114873 18353 sgd_solver.cpp:105] Iteration 8256, lr = 0.00194875 +I0410 14:30:44.116461 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8262.caffemodel +I0410 14:30:44.412611 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8262.solverstate +I0410 14:30:44.616968 18353 solver.cpp:330] Iteration 8262, Testing net (#0) +I0410 14:30:44.617002 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:30:45.817574 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:30:49.187706 18353 solver.cpp:397] Test net output #0: accuracy = 0.567402 +I0410 14:30:49.187757 18353 solver.cpp:397] Test net output #1: loss = 2.3375 (* 1 = 2.3375 loss) +I0410 14:30:51.006175 18353 solver.cpp:218] Iteration 8268 (1.34966 iter/s, 8.89112s/12 iters), loss = 0.352603 +I0410 14:30:51.006233 18353 solver.cpp:237] Train net output #0: loss = 0.352603 (* 1 = 0.352603 loss) +I0410 14:30:51.006245 18353 sgd_solver.cpp:105] Iteration 8268, lr = 0.00194412 +I0410 14:30:55.851364 18353 solver.cpp:218] Iteration 8280 (2.47677 iter/s, 4.84502s/12 iters), loss = 0.205603 +I0410 14:30:55.851521 18353 solver.cpp:237] Train net output #0: loss = 0.205603 (* 1 = 0.205603 loss) +I0410 14:30:55.851536 18353 sgd_solver.cpp:105] Iteration 8280, lr = 0.00193951 +I0410 14:31:00.779754 18353 solver.cpp:218] Iteration 8292 (2.43501 iter/s, 4.92812s/12 iters), loss = 0.24311 +I0410 14:31:00.779798 18353 solver.cpp:237] Train net output #0: loss = 0.24311 (* 1 = 0.24311 loss) +I0410 14:31:00.779808 18353 sgd_solver.cpp:105] Iteration 8292, lr = 0.0019349 +I0410 14:31:01.450857 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:05.809840 18353 solver.cpp:218] Iteration 8304 (2.38572 iter/s, 5.02992s/12 iters), loss = 0.199807 +I0410 14:31:05.809886 18353 solver.cpp:237] Train net output #0: loss = 0.199807 (* 1 = 0.199807 loss) +I0410 14:31:05.809896 18353 sgd_solver.cpp:105] Iteration 8304, lr = 0.00193031 +I0410 14:31:06.986207 18353 blocking_queue.cpp:49] Waiting for data +I0410 14:31:10.771862 18353 solver.cpp:218] Iteration 8316 (2.41845 iter/s, 4.96186s/12 iters), loss = 0.328271 +I0410 14:31:10.771909 18353 solver.cpp:237] Train net output #0: loss = 0.328271 (* 1 = 0.328271 loss) +I0410 14:31:10.771919 18353 sgd_solver.cpp:105] Iteration 8316, lr = 0.00192573 +I0410 14:31:15.886297 18353 solver.cpp:218] Iteration 8328 (2.34638 iter/s, 5.11426s/12 iters), loss = 0.201862 +I0410 14:31:15.886358 18353 solver.cpp:237] Train net output #0: loss = 0.201862 (* 1 = 0.201862 loss) +I0410 14:31:15.886370 18353 sgd_solver.cpp:105] Iteration 8328, lr = 0.00192115 +I0410 14:31:20.858796 18353 solver.cpp:218] Iteration 8340 (2.41336 iter/s, 4.97232s/12 iters), loss = 0.336924 +I0410 14:31:20.858850 18353 solver.cpp:237] Train net output #0: loss = 0.336924 (* 1 = 0.336924 loss) +I0410 14:31:20.858860 18353 sgd_solver.cpp:105] Iteration 8340, lr = 0.00191659 +I0410 14:31:25.750823 18353 solver.cpp:218] Iteration 8352 (2.45305 iter/s, 4.89186s/12 iters), loss = 0.217553 +I0410 14:31:25.750865 18353 solver.cpp:237] Train net output #0: loss = 0.217553 (* 1 = 0.217553 loss) +I0410 14:31:25.750874 18353 sgd_solver.cpp:105] Iteration 8352, lr = 0.00191204 +I0410 14:31:30.185088 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8364.caffemodel +I0410 14:31:31.956107 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8364.solverstate +I0410 14:31:33.250620 18353 solver.cpp:330] Iteration 8364, Testing net (#0) +I0410 14:31:33.250650 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:31:34.443787 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:37.702507 18353 solver.cpp:397] Test net output #0: accuracy = 0.566789 +I0410 14:31:37.702556 18353 solver.cpp:397] Test net output #1: loss = 2.43773 (* 1 = 2.43773 loss) +I0410 14:31:37.784090 18353 solver.cpp:218] Iteration 8364 (0.997261 iter/s, 12.033s/12 iters), loss = 0.400595 +I0410 14:31:37.784144 18353 solver.cpp:237] Train net output #0: loss = 0.400595 (* 1 = 0.400595 loss) +I0410 14:31:37.784157 18353 sgd_solver.cpp:105] Iteration 8364, lr = 0.0019075 +I0410 14:31:41.987370 18353 solver.cpp:218] Iteration 8376 (2.85502 iter/s, 4.20312s/12 iters), loss = 0.233826 +I0410 14:31:41.987426 18353 solver.cpp:237] Train net output #0: loss = 0.233826 (* 1 = 0.233826 loss) +I0410 14:31:41.987439 18353 sgd_solver.cpp:105] Iteration 8376, lr = 0.00190297 +I0410 14:31:46.826704 18353 solver.cpp:218] Iteration 8388 (2.47977 iter/s, 4.83916s/12 iters), loss = 0.427233 +I0410 14:31:46.826762 18353 solver.cpp:237] Train net output #0: loss = 0.427233 (* 1 = 0.427233 loss) +I0410 14:31:46.826776 18353 sgd_solver.cpp:105] Iteration 8388, lr = 0.00189846 +I0410 14:31:49.644484 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:51.754027 18353 solver.cpp:218] Iteration 8400 (2.43549 iter/s, 4.92715s/12 iters), loss = 0.279025 +I0410 14:31:51.754079 18353 solver.cpp:237] Train net output #0: loss = 0.279025 (* 1 = 0.279025 loss) +I0410 14:31:51.754091 18353 sgd_solver.cpp:105] Iteration 8400, lr = 0.00189395 +I0410 14:31:56.610452 18353 solver.cpp:218] Iteration 8412 (2.47104 iter/s, 4.85626s/12 iters), loss = 0.195502 +I0410 14:31:56.610507 18353 solver.cpp:237] Train net output #0: loss = 0.195502 (* 1 = 0.195502 loss) +I0410 14:31:56.610520 18353 sgd_solver.cpp:105] Iteration 8412, lr = 0.00188945 +I0410 14:32:01.440502 18353 solver.cpp:218] Iteration 8424 (2.48453 iter/s, 4.82988s/12 iters), loss = 0.371617 +I0410 14:32:01.440661 18353 solver.cpp:237] Train net output #0: loss = 0.371617 (* 1 = 0.371617 loss) +I0410 14:32:01.440676 18353 sgd_solver.cpp:105] Iteration 8424, lr = 0.00188497 +I0410 14:32:06.267702 18353 solver.cpp:218] Iteration 8436 (2.48606 iter/s, 4.82692s/12 iters), loss = 0.224545 +I0410 14:32:06.267756 18353 solver.cpp:237] Train net output #0: loss = 0.224545 (* 1 = 0.224545 loss) +I0410 14:32:06.267767 18353 sgd_solver.cpp:105] Iteration 8436, lr = 0.00188049 +I0410 14:32:11.231158 18353 solver.cpp:218] Iteration 8448 (2.41776 iter/s, 4.96328s/12 iters), loss = 0.257283 +I0410 14:32:11.231209 18353 solver.cpp:237] Train net output #0: loss = 0.257283 (* 1 = 0.257283 loss) +I0410 14:32:11.231220 18353 sgd_solver.cpp:105] Iteration 8448, lr = 0.00187603 +I0410 14:32:16.124188 18353 solver.cpp:218] Iteration 8460 (2.45256 iter/s, 4.89286s/12 iters), loss = 0.216957 +I0410 14:32:16.124240 18353 solver.cpp:237] Train net output #0: loss = 0.216957 (* 1 = 0.216957 loss) +I0410 14:32:16.124253 18353 sgd_solver.cpp:105] Iteration 8460, lr = 0.00187157 +I0410 14:32:18.117771 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8466.caffemodel +I0410 14:32:18.400900 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8466.solverstate +I0410 14:32:18.595048 18353 solver.cpp:330] Iteration 8466, Testing net (#0) +I0410 14:32:18.595082 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:32:19.629070 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:32:23.023052 18353 solver.cpp:397] Test net output #0: accuracy = 0.548407 +I0410 14:32:23.023104 18353 solver.cpp:397] Test net output #1: loss = 2.44418 (* 1 = 2.44418 loss) +I0410 14:32:24.961500 18353 solver.cpp:218] Iteration 8472 (1.35792 iter/s, 8.83706s/12 iters), loss = 0.164592 +I0410 14:32:24.961555 18353 solver.cpp:237] Train net output #0: loss = 0.164592 (* 1 = 0.164592 loss) +I0410 14:32:24.961567 18353 sgd_solver.cpp:105] Iteration 8472, lr = 0.00186713 +I0410 14:32:29.898959 18353 solver.cpp:218] Iteration 8484 (2.43048 iter/s, 4.93729s/12 iters), loss = 0.319812 +I0410 14:32:29.899014 18353 solver.cpp:237] Train net output #0: loss = 0.319812 (* 1 = 0.319812 loss) +I0410 14:32:29.899027 18353 sgd_solver.cpp:105] Iteration 8484, lr = 0.0018627 +I0410 14:32:34.841655 18353 solver.cpp:218] Iteration 8496 (2.42791 iter/s, 4.94252s/12 iters), loss = 0.248408 +I0410 14:32:34.841776 18353 solver.cpp:237] Train net output #0: loss = 0.248408 (* 1 = 0.248408 loss) +I0410 14:32:34.841792 18353 sgd_solver.cpp:105] Iteration 8496, lr = 0.00185827 +I0410 14:32:34.880514 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:32:39.675909 18353 solver.cpp:218] Iteration 8508 (2.48241 iter/s, 4.83402s/12 iters), loss = 0.247901 +I0410 14:32:39.675967 18353 solver.cpp:237] Train net output #0: loss = 0.247901 (* 1 = 0.247901 loss) +I0410 14:32:39.675979 18353 sgd_solver.cpp:105] Iteration 8508, lr = 0.00185386 +I0410 14:32:44.529790 18353 solver.cpp:218] Iteration 8520 (2.47234 iter/s, 4.8537s/12 iters), loss = 0.207359 +I0410 14:32:44.529850 18353 solver.cpp:237] Train net output #0: loss = 0.207359 (* 1 = 0.207359 loss) +I0410 14:32:44.529860 18353 sgd_solver.cpp:105] Iteration 8520, lr = 0.00184946 +I0410 14:32:49.365579 18353 solver.cpp:218] Iteration 8532 (2.48159 iter/s, 4.83561s/12 iters), loss = 0.171135 +I0410 14:32:49.365638 18353 solver.cpp:237] Train net output #0: loss = 0.171135 (* 1 = 0.171135 loss) +I0410 14:32:49.365651 18353 sgd_solver.cpp:105] Iteration 8532, lr = 0.00184507 +I0410 14:32:54.200006 18353 solver.cpp:218] Iteration 8544 (2.48229 iter/s, 4.83425s/12 iters), loss = 0.341448 +I0410 14:32:54.200069 18353 solver.cpp:237] Train net output #0: loss = 0.341448 (* 1 = 0.341448 loss) +I0410 14:32:54.200083 18353 sgd_solver.cpp:105] Iteration 8544, lr = 0.00184069 +I0410 14:32:59.061676 18353 solver.cpp:218] Iteration 8556 (2.46838 iter/s, 4.86148s/12 iters), loss = 0.221535 +I0410 14:32:59.061739 18353 solver.cpp:237] Train net output #0: loss = 0.221535 (* 1 = 0.221535 loss) +I0410 14:32:59.061753 18353 sgd_solver.cpp:105] Iteration 8556, lr = 0.00183632 +I0410 14:33:03.454402 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8568.caffemodel +I0410 14:33:03.785652 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8568.solverstate +I0410 14:33:03.993767 18353 solver.cpp:330] Iteration 8568, Testing net (#0) +I0410 14:33:03.993793 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:33:05.122313 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:33:08.502822 18353 solver.cpp:397] Test net output #0: accuracy = 0.549632 +I0410 14:33:08.502873 18353 solver.cpp:397] Test net output #1: loss = 2.41547 (* 1 = 2.41547 loss) +I0410 14:33:08.584102 18353 solver.cpp:218] Iteration 8568 (1.26022 iter/s, 9.52215s/12 iters), loss = 0.233711 +I0410 14:33:08.584153 18353 solver.cpp:237] Train net output #0: loss = 0.233711 (* 1 = 0.233711 loss) +I0410 14:33:08.584165 18353 sgd_solver.cpp:105] Iteration 8568, lr = 0.00183196 +I0410 14:33:12.640694 18353 solver.cpp:218] Iteration 8580 (2.95826 iter/s, 4.05644s/12 iters), loss = 0.184957 +I0410 14:33:12.640745 18353 solver.cpp:237] Train net output #0: loss = 0.184957 (* 1 = 0.184957 loss) +I0410 14:33:12.640756 18353 sgd_solver.cpp:105] Iteration 8580, lr = 0.00182761 +I0410 14:33:17.615176 18353 solver.cpp:218] Iteration 8592 (2.4124 iter/s, 4.97431s/12 iters), loss = 0.242305 +I0410 14:33:17.615236 18353 solver.cpp:237] Train net output #0: loss = 0.242305 (* 1 = 0.242305 loss) +I0410 14:33:17.615248 18353 sgd_solver.cpp:105] Iteration 8592, lr = 0.00182327 +I0410 14:33:19.700482 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:33:22.469069 18353 solver.cpp:218] Iteration 8604 (2.47233 iter/s, 4.85371s/12 iters), loss = 0.234007 +I0410 14:33:22.469128 18353 solver.cpp:237] Train net output #0: loss = 0.234007 (* 1 = 0.234007 loss) +I0410 14:33:22.469142 18353 sgd_solver.cpp:105] Iteration 8604, lr = 0.00181894 +I0410 14:33:27.547739 18353 solver.cpp:218] Iteration 8616 (2.36291 iter/s, 5.07849s/12 iters), loss = 0.218544 +I0410 14:33:27.547793 18353 solver.cpp:237] Train net output #0: loss = 0.218544 (* 1 = 0.218544 loss) +I0410 14:33:27.547804 18353 sgd_solver.cpp:105] Iteration 8616, lr = 0.00181462 +I0410 14:33:32.396983 18353 solver.cpp:218] Iteration 8628 (2.4747 iter/s, 4.84907s/12 iters), loss = 0.252311 +I0410 14:33:32.397045 18353 solver.cpp:237] Train net output #0: loss = 0.252311 (* 1 = 0.252311 loss) +I0410 14:33:32.397059 18353 sgd_solver.cpp:105] Iteration 8628, lr = 0.00181031 +I0410 14:33:37.202036 18353 solver.cpp:218] Iteration 8640 (2.49746 iter/s, 4.80488s/12 iters), loss = 0.25067 +I0410 14:33:37.205322 18353 solver.cpp:237] Train net output #0: loss = 0.25067 (* 1 = 0.25067 loss) +I0410 14:33:37.205332 18353 sgd_solver.cpp:105] Iteration 8640, lr = 0.00180602 +I0410 14:33:42.204701 18353 solver.cpp:218] Iteration 8652 (2.40036 iter/s, 4.99926s/12 iters), loss = 0.133641 +I0410 14:33:42.204747 18353 solver.cpp:237] Train net output #0: loss = 0.133641 (* 1 = 0.133641 loss) +I0410 14:33:42.204756 18353 sgd_solver.cpp:105] Iteration 8652, lr = 0.00180173 +I0410 14:33:47.089359 18353 solver.cpp:218] Iteration 8664 (2.45675 iter/s, 4.88449s/12 iters), loss = 0.349766 +I0410 14:33:47.089406 18353 solver.cpp:237] Train net output #0: loss = 0.349766 (* 1 = 0.349766 loss) +I0410 14:33:47.089416 18353 sgd_solver.cpp:105] Iteration 8664, lr = 0.00179745 +I0410 14:33:49.351301 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8670.caffemodel +I0410 14:33:50.105013 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8670.solverstate +I0410 14:33:50.349575 18353 solver.cpp:330] Iteration 8670, Testing net (#0) +I0410 14:33:50.349603 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:33:51.437636 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:33:55.029505 18353 solver.cpp:397] Test net output #0: accuracy = 0.566789 +I0410 14:33:55.029539 18353 solver.cpp:397] Test net output #1: loss = 2.41216 (* 1 = 2.41216 loss) +I0410 14:33:56.869036 18353 solver.cpp:218] Iteration 8676 (1.22707 iter/s, 9.7794s/12 iters), loss = 0.134833 +I0410 14:33:56.869084 18353 solver.cpp:237] Train net output #0: loss = 0.134833 (* 1 = 0.134833 loss) +I0410 14:33:56.869094 18353 sgd_solver.cpp:105] Iteration 8676, lr = 0.00179318 +I0410 14:34:01.846196 18353 solver.cpp:218] Iteration 8688 (2.4111 iter/s, 4.97699s/12 iters), loss = 0.206649 +I0410 14:34:01.846252 18353 solver.cpp:237] Train net output #0: loss = 0.206649 (* 1 = 0.206649 loss) +I0410 14:34:01.846266 18353 sgd_solver.cpp:105] Iteration 8688, lr = 0.00178893 +I0410 14:34:06.110931 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:06.785404 18353 solver.cpp:218] Iteration 8700 (2.42963 iter/s, 4.93903s/12 iters), loss = 0.203242 +I0410 14:34:06.785460 18353 solver.cpp:237] Train net output #0: loss = 0.203242 (* 1 = 0.203242 loss) +I0410 14:34:06.785472 18353 sgd_solver.cpp:105] Iteration 8700, lr = 0.00178468 +I0410 14:34:11.874472 18353 solver.cpp:218] Iteration 8712 (2.35808 iter/s, 5.08889s/12 iters), loss = 0.182803 +I0410 14:34:11.874590 18353 solver.cpp:237] Train net output #0: loss = 0.182803 (* 1 = 0.182803 loss) +I0410 14:34:11.874600 18353 sgd_solver.cpp:105] Iteration 8712, lr = 0.00178044 +I0410 14:34:16.775470 18353 solver.cpp:218] Iteration 8724 (2.4486 iter/s, 4.90076s/12 iters), loss = 0.260401 +I0410 14:34:16.775516 18353 solver.cpp:237] Train net output #0: loss = 0.260401 (* 1 = 0.260401 loss) +I0410 14:34:16.775527 18353 sgd_solver.cpp:105] Iteration 8724, lr = 0.00177621 +I0410 14:34:21.652289 18353 solver.cpp:218] Iteration 8736 (2.4607 iter/s, 4.87665s/12 iters), loss = 0.231608 +I0410 14:34:21.652338 18353 solver.cpp:237] Train net output #0: loss = 0.231608 (* 1 = 0.231608 loss) +I0410 14:34:21.652348 18353 sgd_solver.cpp:105] Iteration 8736, lr = 0.001772 +I0410 14:34:26.598891 18353 solver.cpp:218] Iteration 8748 (2.42599 iter/s, 4.94643s/12 iters), loss = 0.335587 +I0410 14:34:26.598935 18353 solver.cpp:237] Train net output #0: loss = 0.335587 (* 1 = 0.335587 loss) +I0410 14:34:26.598944 18353 sgd_solver.cpp:105] Iteration 8748, lr = 0.00176779 +I0410 14:34:31.556612 18353 solver.cpp:218] Iteration 8760 (2.42055 iter/s, 4.95755s/12 iters), loss = 0.151108 +I0410 14:34:31.556668 18353 solver.cpp:237] Train net output #0: loss = 0.151108 (* 1 = 0.151108 loss) +I0410 14:34:31.556680 18353 sgd_solver.cpp:105] Iteration 8760, lr = 0.00176359 +I0410 14:34:36.030589 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8772.caffemodel +I0410 14:34:36.342351 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8772.solverstate +I0410 14:34:36.549528 18353 solver.cpp:330] Iteration 8772, Testing net (#0) +I0410 14:34:36.549561 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:34:37.565647 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:40.989535 18353 solver.cpp:397] Test net output #0: accuracy = 0.570466 +I0410 14:34:40.989573 18353 solver.cpp:397] Test net output #1: loss = 2.42441 (* 1 = 2.42441 loss) +I0410 14:34:41.070848 18353 solver.cpp:218] Iteration 8772 (1.2613 iter/s, 9.51396s/12 iters), loss = 0.277366 +I0410 14:34:41.070906 18353 solver.cpp:237] Train net output #0: loss = 0.277366 (* 1 = 0.277366 loss) +I0410 14:34:41.070919 18353 sgd_solver.cpp:105] Iteration 8772, lr = 0.00175941 +I0410 14:34:45.314833 18353 solver.cpp:218] Iteration 8784 (2.82764 iter/s, 4.24382s/12 iters), loss = 0.151882 +I0410 14:34:45.314981 18353 solver.cpp:237] Train net output #0: loss = 0.151882 (* 1 = 0.151882 loss) +I0410 14:34:45.314992 18353 sgd_solver.cpp:105] Iteration 8784, lr = 0.00175523 +I0410 14:34:50.140313 18353 solver.cpp:218] Iteration 8796 (2.48694 iter/s, 4.82521s/12 iters), loss = 0.201846 +I0410 14:34:50.140368 18353 solver.cpp:237] Train net output #0: loss = 0.201846 (* 1 = 0.201846 loss) +I0410 14:34:50.140383 18353 sgd_solver.cpp:105] Iteration 8796, lr = 0.00175106 +I0410 14:34:51.541460 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:55.062031 18353 solver.cpp:218] Iteration 8808 (2.43826 iter/s, 4.92154s/12 iters), loss = 0.38256 +I0410 14:34:55.062085 18353 solver.cpp:237] Train net output #0: loss = 0.38256 (* 1 = 0.38256 loss) +I0410 14:34:55.062099 18353 sgd_solver.cpp:105] Iteration 8808, lr = 0.0017469 +I0410 14:34:59.951509 18353 solver.cpp:218] Iteration 8820 (2.45434 iter/s, 4.8893s/12 iters), loss = 0.189713 +I0410 14:34:59.951563 18353 solver.cpp:237] Train net output #0: loss = 0.189713 (* 1 = 0.189713 loss) +I0410 14:34:59.951576 18353 sgd_solver.cpp:105] Iteration 8820, lr = 0.00174276 +I0410 14:35:04.886657 18353 solver.cpp:218] Iteration 8832 (2.43163 iter/s, 4.93497s/12 iters), loss = 0.132332 +I0410 14:35:04.886705 18353 solver.cpp:237] Train net output #0: loss = 0.132332 (* 1 = 0.132332 loss) +I0410 14:35:04.886714 18353 sgd_solver.cpp:105] Iteration 8832, lr = 0.00173862 +I0410 14:35:09.795842 18353 solver.cpp:218] Iteration 8844 (2.44448 iter/s, 4.90901s/12 iters), loss = 0.20236 +I0410 14:35:09.795886 18353 solver.cpp:237] Train net output #0: loss = 0.20236 (* 1 = 0.20236 loss) +I0410 14:35:09.795895 18353 sgd_solver.cpp:105] Iteration 8844, lr = 0.00173449 +I0410 14:35:14.738719 18353 solver.cpp:218] Iteration 8856 (2.42782 iter/s, 4.94271s/12 iters), loss = 0.230461 +I0410 14:35:14.738759 18353 solver.cpp:237] Train net output #0: loss = 0.230461 (* 1 = 0.230461 loss) +I0410 14:35:14.738767 18353 sgd_solver.cpp:105] Iteration 8856, lr = 0.00173037 +I0410 14:35:19.636201 18353 solver.cpp:218] Iteration 8868 (2.45032 iter/s, 4.89732s/12 iters), loss = 0.295618 +I0410 14:35:19.636334 18353 solver.cpp:237] Train net output #0: loss = 0.295618 (* 1 = 0.295618 loss) +I0410 14:35:19.636344 18353 sgd_solver.cpp:105] Iteration 8868, lr = 0.00172626 +I0410 14:35:21.627316 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8874.caffemodel +I0410 14:35:21.928701 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8874.solverstate +I0410 14:35:22.144127 18353 solver.cpp:330] Iteration 8874, Testing net (#0) +I0410 14:35:22.144157 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:35:23.103143 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:35:26.738929 18353 solver.cpp:397] Test net output #0: accuracy = 0.5625 +I0410 14:35:26.738973 18353 solver.cpp:397] Test net output #1: loss = 2.42246 (* 1 = 2.42246 loss) +I0410 14:35:28.732332 18353 solver.cpp:218] Iteration 8880 (1.31929 iter/s, 9.09578s/12 iters), loss = 0.213152 +I0410 14:35:28.732383 18353 solver.cpp:237] Train net output #0: loss = 0.213152 (* 1 = 0.213152 loss) +I0410 14:35:28.732396 18353 sgd_solver.cpp:105] Iteration 8880, lr = 0.00172217 +I0410 14:35:33.801215 18353 solver.cpp:218] Iteration 8892 (2.36747 iter/s, 5.06871s/12 iters), loss = 0.249368 +I0410 14:35:33.801265 18353 solver.cpp:237] Train net output #0: loss = 0.249368 (* 1 = 0.249368 loss) +I0410 14:35:33.801276 18353 sgd_solver.cpp:105] Iteration 8892, lr = 0.00171808 +I0410 14:35:37.283007 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:35:38.701995 18353 solver.cpp:218] Iteration 8904 (2.44868 iter/s, 4.9006s/12 iters), loss = 0.150592 +I0410 14:35:38.702051 18353 solver.cpp:237] Train net output #0: loss = 0.150592 (* 1 = 0.150592 loss) +I0410 14:35:38.702064 18353 sgd_solver.cpp:105] Iteration 8904, lr = 0.001714 +I0410 14:35:43.618988 18353 solver.cpp:218] Iteration 8916 (2.44061 iter/s, 4.91681s/12 iters), loss = 0.195952 +I0410 14:35:43.619047 18353 solver.cpp:237] Train net output #0: loss = 0.195952 (* 1 = 0.195952 loss) +I0410 14:35:43.619061 18353 sgd_solver.cpp:105] Iteration 8916, lr = 0.00170993 +I0410 14:35:48.503921 18353 solver.cpp:218] Iteration 8928 (2.45662 iter/s, 4.88475s/12 iters), loss = 0.270088 +I0410 14:35:48.503978 18353 solver.cpp:237] Train net output #0: loss = 0.270088 (* 1 = 0.270088 loss) +I0410 14:35:48.503989 18353 sgd_solver.cpp:105] Iteration 8928, lr = 0.00170587 +I0410 14:35:53.334822 18353 solver.cpp:218] Iteration 8940 (2.4841 iter/s, 4.83072s/12 iters), loss = 0.209815 +I0410 14:35:53.334978 18353 solver.cpp:237] Train net output #0: loss = 0.209815 (* 1 = 0.209815 loss) +I0410 14:35:53.334991 18353 sgd_solver.cpp:105] Iteration 8940, lr = 0.00170182 +I0410 14:35:58.196499 18353 solver.cpp:218] Iteration 8952 (2.46842 iter/s, 4.8614s/12 iters), loss = 0.32383 +I0410 14:35:58.196547 18353 solver.cpp:237] Train net output #0: loss = 0.32383 (* 1 = 0.32383 loss) +I0410 14:35:58.196555 18353 sgd_solver.cpp:105] Iteration 8952, lr = 0.00169778 +I0410 14:36:03.073809 18353 solver.cpp:218] Iteration 8964 (2.46046 iter/s, 4.87714s/12 iters), loss = 0.220448 +I0410 14:36:03.073860 18353 solver.cpp:237] Train net output #0: loss = 0.220448 (* 1 = 0.220448 loss) +I0410 14:36:03.073871 18353 sgd_solver.cpp:105] Iteration 8964, lr = 0.00169375 +I0410 14:36:07.505633 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8976.caffemodel +I0410 14:36:07.848467 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8976.solverstate +I0410 14:36:08.052081 18353 solver.cpp:330] Iteration 8976, Testing net (#0) +I0410 14:36:08.052109 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:36:09.015918 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:36:12.542117 18353 solver.cpp:397] Test net output #0: accuracy = 0.560662 +I0410 14:36:12.542150 18353 solver.cpp:397] Test net output #1: loss = 2.48925 (* 1 = 2.48925 loss) +I0410 14:36:12.623476 18353 solver.cpp:218] Iteration 8976 (1.25663 iter/s, 9.54939s/12 iters), loss = 0.222873 +I0410 14:36:12.623520 18353 solver.cpp:237] Train net output #0: loss = 0.222873 (* 1 = 0.222873 loss) +I0410 14:36:12.623530 18353 sgd_solver.cpp:105] Iteration 8976, lr = 0.00168973 +I0410 14:36:16.798837 18353 solver.cpp:218] Iteration 8988 (2.87412 iter/s, 4.1752s/12 iters), loss = 0.153636 +I0410 14:36:16.798902 18353 solver.cpp:237] Train net output #0: loss = 0.153636 (* 1 = 0.153636 loss) +I0410 14:36:16.798915 18353 sgd_solver.cpp:105] Iteration 8988, lr = 0.00168571 +I0410 14:36:18.380266 18353 blocking_queue.cpp:49] Waiting for data +I0410 14:36:21.669431 18353 solver.cpp:218] Iteration 9000 (2.46386 iter/s, 4.87041s/12 iters), loss = 0.282873 +I0410 14:36:21.669487 18353 solver.cpp:237] Train net output #0: loss = 0.282873 (* 1 = 0.282873 loss) +I0410 14:36:21.669498 18353 sgd_solver.cpp:105] Iteration 9000, lr = 0.00168171 +I0410 14:36:22.372877 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:36:26.637550 18353 solver.cpp:218] Iteration 9012 (2.41549 iter/s, 4.96794s/12 iters), loss = 0.222454 +I0410 14:36:26.637639 18353 solver.cpp:237] Train net output #0: loss = 0.222454 (* 1 = 0.222454 loss) +I0410 14:36:26.637652 18353 sgd_solver.cpp:105] Iteration 9012, lr = 0.00167772 +I0410 14:36:31.522013 18353 solver.cpp:218] Iteration 9024 (2.45688 iter/s, 4.88425s/12 iters), loss = 0.141025 +I0410 14:36:31.522076 18353 solver.cpp:237] Train net output #0: loss = 0.141025 (* 1 = 0.141025 loss) +I0410 14:36:31.522089 18353 sgd_solver.cpp:105] Iteration 9024, lr = 0.00167374 +I0410 14:36:36.440255 18353 solver.cpp:218] Iteration 9036 (2.43999 iter/s, 4.91805s/12 iters), loss = 0.160364 +I0410 14:36:36.440317 18353 solver.cpp:237] Train net output #0: loss = 0.160364 (* 1 = 0.160364 loss) +I0410 14:36:36.440330 18353 sgd_solver.cpp:105] Iteration 9036, lr = 0.00166976 +I0410 14:36:41.350888 18353 solver.cpp:218] Iteration 9048 (2.44377 iter/s, 4.91044s/12 iters), loss = 0.324145 +I0410 14:36:41.350944 18353 solver.cpp:237] Train net output #0: loss = 0.324145 (* 1 = 0.324145 loss) +I0410 14:36:41.350955 18353 sgd_solver.cpp:105] Iteration 9048, lr = 0.0016658 +I0410 14:36:46.374720 18353 solver.cpp:218] Iteration 9060 (2.3887 iter/s, 5.02364s/12 iters), loss = 0.227145 +I0410 14:36:46.374774 18353 solver.cpp:237] Train net output #0: loss = 0.227144 (* 1 = 0.227144 loss) +I0410 14:36:46.374786 18353 sgd_solver.cpp:105] Iteration 9060, lr = 0.00166184 +I0410 14:36:51.193707 18353 solver.cpp:218] Iteration 9072 (2.49024 iter/s, 4.81881s/12 iters), loss = 0.17629 +I0410 14:36:51.193750 18353 solver.cpp:237] Train net output #0: loss = 0.17629 (* 1 = 0.17629 loss) +I0410 14:36:51.193758 18353 sgd_solver.cpp:105] Iteration 9072, lr = 0.0016579 +I0410 14:36:53.189146 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9078.caffemodel +I0410 14:36:53.542078 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9078.solverstate +I0410 14:36:53.752290 18353 solver.cpp:330] Iteration 9078, Testing net (#0) +I0410 14:36:53.752313 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:36:54.636091 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:36:58.179864 18353 solver.cpp:397] Test net output #0: accuracy = 0.569853 +I0410 14:36:58.180008 18353 solver.cpp:397] Test net output #1: loss = 2.46042 (* 1 = 2.46042 loss) +I0410 14:37:00.108847 18353 solver.cpp:218] Iteration 9084 (1.34606 iter/s, 8.91488s/12 iters), loss = 0.226079 +I0410 14:37:00.108893 18353 solver.cpp:237] Train net output #0: loss = 0.226079 (* 1 = 0.226079 loss) +I0410 14:37:00.108902 18353 sgd_solver.cpp:105] Iteration 9084, lr = 0.00165396 +I0410 14:37:04.978091 18353 solver.cpp:218] Iteration 9096 (2.46453 iter/s, 4.86907s/12 iters), loss = 0.404843 +I0410 14:37:04.978137 18353 solver.cpp:237] Train net output #0: loss = 0.404843 (* 1 = 0.404843 loss) +I0410 14:37:04.978145 18353 sgd_solver.cpp:105] Iteration 9096, lr = 0.00165003 +I0410 14:37:07.814417 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:09.831142 18353 solver.cpp:218] Iteration 9108 (2.47276 iter/s, 4.85288s/12 iters), loss = 0.239005 +I0410 14:37:09.831190 18353 solver.cpp:237] Train net output #0: loss = 0.239005 (* 1 = 0.239005 loss) +I0410 14:37:09.831199 18353 sgd_solver.cpp:105] Iteration 9108, lr = 0.00164612 +I0410 14:37:14.742961 18353 solver.cpp:218] Iteration 9120 (2.44317 iter/s, 4.91164s/12 iters), loss = 0.230034 +I0410 14:37:14.743007 18353 solver.cpp:237] Train net output #0: loss = 0.230034 (* 1 = 0.230034 loss) +I0410 14:37:14.743018 18353 sgd_solver.cpp:105] Iteration 9120, lr = 0.00164221 +I0410 14:37:19.706104 18353 solver.cpp:218] Iteration 9132 (2.41791 iter/s, 4.96297s/12 iters), loss = 0.249215 +I0410 14:37:19.706151 18353 solver.cpp:237] Train net output #0: loss = 0.249215 (* 1 = 0.249215 loss) +I0410 14:37:19.706161 18353 sgd_solver.cpp:105] Iteration 9132, lr = 0.00163831 +I0410 14:37:24.919384 18353 solver.cpp:218] Iteration 9144 (2.30189 iter/s, 5.2131s/12 iters), loss = 0.213244 +I0410 14:37:24.919433 18353 solver.cpp:237] Train net output #0: loss = 0.213244 (* 1 = 0.213244 loss) +I0410 14:37:24.919445 18353 sgd_solver.cpp:105] Iteration 9144, lr = 0.00163442 +I0410 14:37:29.882719 18353 solver.cpp:218] Iteration 9156 (2.41782 iter/s, 4.96316s/12 iters), loss = 0.253894 +I0410 14:37:29.882807 18353 solver.cpp:237] Train net output #0: loss = 0.253894 (* 1 = 0.253894 loss) +I0410 14:37:29.882817 18353 sgd_solver.cpp:105] Iteration 9156, lr = 0.00163054 +I0410 14:37:34.817373 18353 solver.cpp:218] Iteration 9168 (2.43189 iter/s, 4.93444s/12 iters), loss = 0.182433 +I0410 14:37:34.817416 18353 solver.cpp:237] Train net output #0: loss = 0.182433 (* 1 = 0.182433 loss) +I0410 14:37:34.817425 18353 sgd_solver.cpp:105] Iteration 9168, lr = 0.00162667 +I0410 14:37:39.256000 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9180.caffemodel +I0410 14:37:39.564245 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9180.solverstate +I0410 14:37:39.771158 18353 solver.cpp:330] Iteration 9180, Testing net (#0) +I0410 14:37:39.771191 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:37:40.581583 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:44.161528 18353 solver.cpp:397] Test net output #0: accuracy = 0.567402 +I0410 14:37:44.161577 18353 solver.cpp:397] Test net output #1: loss = 2.43285 (* 1 = 2.43285 loss) +I0410 14:37:44.242144 18353 solver.cpp:218] Iteration 9180 (1.27328 iter/s, 9.42449s/12 iters), loss = 0.220207 +I0410 14:37:44.242197 18353 solver.cpp:237] Train net output #0: loss = 0.220207 (* 1 = 0.220207 loss) +I0410 14:37:44.242209 18353 sgd_solver.cpp:105] Iteration 9180, lr = 0.00162281 +I0410 14:37:48.512907 18353 solver.cpp:218] Iteration 9192 (2.80991 iter/s, 4.2706s/12 iters), loss = 0.1856 +I0410 14:37:48.512953 18353 solver.cpp:237] Train net output #0: loss = 0.1856 (* 1 = 0.1856 loss) +I0410 14:37:48.512964 18353 sgd_solver.cpp:105] Iteration 9192, lr = 0.00161895 +I0410 14:37:53.441063 18353 solver.cpp:218] Iteration 9204 (2.43507 iter/s, 4.92798s/12 iters), loss = 0.257251 +I0410 14:37:53.441113 18353 solver.cpp:237] Train net output #0: loss = 0.257251 (* 1 = 0.257251 loss) +I0410 14:37:53.441123 18353 sgd_solver.cpp:105] Iteration 9204, lr = 0.00161511 +I0410 14:37:53.508723 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:58.380167 18353 solver.cpp:218] Iteration 9216 (2.42968 iter/s, 4.93893s/12 iters), loss = 0.096656 +I0410 14:37:58.380210 18353 solver.cpp:237] Train net output #0: loss = 0.096656 (* 1 = 0.096656 loss) +I0410 14:37:58.380220 18353 sgd_solver.cpp:105] Iteration 9216, lr = 0.00161128 +I0410 14:38:03.278777 18353 solver.cpp:218] Iteration 9228 (2.44976 iter/s, 4.89844s/12 iters), loss = 0.220446 +I0410 14:38:03.278895 18353 solver.cpp:237] Train net output #0: loss = 0.220446 (* 1 = 0.220446 loss) +I0410 14:38:03.278906 18353 sgd_solver.cpp:105] Iteration 9228, lr = 0.00160745 +I0410 14:38:08.211591 18353 solver.cpp:218] Iteration 9240 (2.43281 iter/s, 4.93258s/12 iters), loss = 0.21657 +I0410 14:38:08.211628 18353 solver.cpp:237] Train net output #0: loss = 0.21657 (* 1 = 0.21657 loss) +I0410 14:38:08.211637 18353 sgd_solver.cpp:105] Iteration 9240, lr = 0.00160363 +I0410 14:38:13.197633 18353 solver.cpp:218] Iteration 9252 (2.4068 iter/s, 4.98587s/12 iters), loss = 0.224744 +I0410 14:38:13.197687 18353 solver.cpp:237] Train net output #0: loss = 0.224744 (* 1 = 0.224744 loss) +I0410 14:38:13.197700 18353 sgd_solver.cpp:105] Iteration 9252, lr = 0.00159983 +I0410 14:38:18.079635 18353 solver.cpp:218] Iteration 9264 (2.4581 iter/s, 4.88182s/12 iters), loss = 0.257278 +I0410 14:38:18.079694 18353 solver.cpp:237] Train net output #0: loss = 0.257278 (* 1 = 0.257278 loss) +I0410 14:38:18.079707 18353 sgd_solver.cpp:105] Iteration 9264, lr = 0.00159603 +I0410 14:38:22.955104 18353 solver.cpp:218] Iteration 9276 (2.4614 iter/s, 4.87528s/12 iters), loss = 0.195508 +I0410 14:38:22.955164 18353 solver.cpp:237] Train net output #0: loss = 0.195508 (* 1 = 0.195508 loss) +I0410 14:38:22.955178 18353 sgd_solver.cpp:105] Iteration 9276, lr = 0.00159224 +I0410 14:38:24.929638 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9282.caffemodel +I0410 14:38:25.252574 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9282.solverstate +I0410 14:38:25.462672 18353 solver.cpp:330] Iteration 9282, Testing net (#0) +I0410 14:38:25.462703 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:38:26.415925 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:38:30.467905 18353 solver.cpp:397] Test net output #0: accuracy = 0.558824 +I0410 14:38:30.467936 18353 solver.cpp:397] Test net output #1: loss = 2.53961 (* 1 = 2.53961 loss) +I0410 14:38:32.272337 18353 solver.cpp:218] Iteration 9288 (1.28798 iter/s, 9.31694s/12 iters), loss = 0.250262 +I0410 14:38:32.272387 18353 solver.cpp:237] Train net output #0: loss = 0.250262 (* 1 = 0.250262 loss) +I0410 14:38:32.272397 18353 sgd_solver.cpp:105] Iteration 9288, lr = 0.00158846 +I0410 14:38:37.449395 18353 solver.cpp:218] Iteration 9300 (2.318 iter/s, 5.17687s/12 iters), loss = 0.199941 +I0410 14:38:37.450652 18353 solver.cpp:237] Train net output #0: loss = 0.199941 (* 1 = 0.199941 loss) +I0410 14:38:37.450665 18353 sgd_solver.cpp:105] Iteration 9300, lr = 0.00158469 +I0410 14:38:39.661242 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:38:42.416648 18353 solver.cpp:218] Iteration 9312 (2.4165 iter/s, 4.96587s/12 iters), loss = 0.312211 +I0410 14:38:42.416707 18353 solver.cpp:237] Train net output #0: loss = 0.312211 (* 1 = 0.312211 loss) +I0410 14:38:42.416719 18353 sgd_solver.cpp:105] Iteration 9312, lr = 0.00158092 +I0410 14:38:47.331915 18353 solver.cpp:218] Iteration 9324 (2.44147 iter/s, 4.91508s/12 iters), loss = 0.185038 +I0410 14:38:47.331976 18353 solver.cpp:237] Train net output #0: loss = 0.185038 (* 1 = 0.185038 loss) +I0410 14:38:47.331990 18353 sgd_solver.cpp:105] Iteration 9324, lr = 0.00157717 +I0410 14:38:52.210268 18353 solver.cpp:218] Iteration 9336 (2.45994 iter/s, 4.87816s/12 iters), loss = 0.169188 +I0410 14:38:52.210327 18353 solver.cpp:237] Train net output #0: loss = 0.169188 (* 1 = 0.169188 loss) +I0410 14:38:52.210340 18353 sgd_solver.cpp:105] Iteration 9336, lr = 0.00157343 +I0410 14:38:57.089310 18353 solver.cpp:218] Iteration 9348 (2.45959 iter/s, 4.87885s/12 iters), loss = 0.207522 +I0410 14:38:57.089371 18353 solver.cpp:237] Train net output #0: loss = 0.207522 (* 1 = 0.207522 loss) +I0410 14:38:57.089385 18353 sgd_solver.cpp:105] Iteration 9348, lr = 0.00156969 +I0410 14:39:02.031010 18353 solver.cpp:218] Iteration 9360 (2.42841 iter/s, 4.9415s/12 iters), loss = 0.142523 +I0410 14:39:02.031075 18353 solver.cpp:237] Train net output #0: loss = 0.142523 (* 1 = 0.142523 loss) +I0410 14:39:02.031087 18353 sgd_solver.cpp:105] Iteration 9360, lr = 0.00156596 +I0410 14:39:06.909809 18353 solver.cpp:218] Iteration 9372 (2.45972 iter/s, 4.87861s/12 iters), loss = 0.205736 +I0410 14:39:06.909860 18353 solver.cpp:237] Train net output #0: loss = 0.205736 (* 1 = 0.205736 loss) +I0410 14:39:06.909873 18353 sgd_solver.cpp:105] Iteration 9372, lr = 0.00156225 +I0410 14:39:11.439465 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9384.caffemodel +I0410 14:39:11.750174 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9384.solverstate +I0410 14:39:11.950016 18353 solver.cpp:330] Iteration 9384, Testing net (#0) +I0410 14:39:11.950034 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:39:12.702491 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:39:16.507683 18353 solver.cpp:397] Test net output #0: accuracy = 0.561275 +I0410 14:39:16.507732 18353 solver.cpp:397] Test net output #1: loss = 2.502 (* 1 = 2.502 loss) +I0410 14:39:16.588929 18353 solver.cpp:218] Iteration 9384 (1.23982 iter/s, 9.67883s/12 iters), loss = 0.194883 +I0410 14:39:16.588992 18353 solver.cpp:237] Train net output #0: loss = 0.194883 (* 1 = 0.194883 loss) +I0410 14:39:16.589006 18353 sgd_solver.cpp:105] Iteration 9384, lr = 0.00155854 +I0410 14:39:20.694499 18353 solver.cpp:218] Iteration 9396 (2.92298 iter/s, 4.10539s/12 iters), loss = 0.26062 +I0410 14:39:20.694545 18353 solver.cpp:237] Train net output #0: loss = 0.26062 (* 1 = 0.26062 loss) +I0410 14:39:20.694555 18353 sgd_solver.cpp:105] Iteration 9396, lr = 0.00155484 +I0410 14:39:24.914744 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:39:25.570451 18353 solver.cpp:218] Iteration 9408 (2.46115 iter/s, 4.87578s/12 iters), loss = 0.158863 +I0410 14:39:25.570495 18353 solver.cpp:237] Train net output #0: loss = 0.158863 (* 1 = 0.158863 loss) +I0410 14:39:25.570505 18353 sgd_solver.cpp:105] Iteration 9408, lr = 0.00155114 +I0410 14:39:30.740375 18353 solver.cpp:218] Iteration 9420 (2.3212 iter/s, 5.16975s/12 iters), loss = 0.233335 +I0410 14:39:30.740419 18353 solver.cpp:237] Train net output #0: loss = 0.233335 (* 1 = 0.233335 loss) +I0410 14:39:30.740428 18353 sgd_solver.cpp:105] Iteration 9420, lr = 0.00154746 +I0410 14:39:35.633522 18353 solver.cpp:218] Iteration 9432 (2.4525 iter/s, 4.89296s/12 iters), loss = 0.212536 +I0410 14:39:35.633579 18353 solver.cpp:237] Train net output #0: loss = 0.212536 (* 1 = 0.212536 loss) +I0410 14:39:35.633594 18353 sgd_solver.cpp:105] Iteration 9432, lr = 0.00154379 +I0410 14:39:40.639696 18353 solver.cpp:218] Iteration 9444 (2.39713 iter/s, 5.00599s/12 iters), loss = 0.136083 +I0410 14:39:40.639739 18353 solver.cpp:237] Train net output #0: loss = 0.136083 (* 1 = 0.136083 loss) +I0410 14:39:40.639748 18353 sgd_solver.cpp:105] Iteration 9444, lr = 0.00154012 +I0410 14:39:45.494421 18353 solver.cpp:218] Iteration 9456 (2.47191 iter/s, 4.85455s/12 iters), loss = 0.29401 +I0410 14:39:45.494556 18353 solver.cpp:237] Train net output #0: loss = 0.29401 (* 1 = 0.29401 loss) +I0410 14:39:45.494572 18353 sgd_solver.cpp:105] Iteration 9456, lr = 0.00153647 +I0410 14:39:50.390158 18353 solver.cpp:218] Iteration 9468 (2.45124 iter/s, 4.89547s/12 iters), loss = 0.231563 +I0410 14:39:50.390208 18353 solver.cpp:237] Train net output #0: loss = 0.231563 (* 1 = 0.231563 loss) +I0410 14:39:50.390220 18353 sgd_solver.cpp:105] Iteration 9468, lr = 0.00153282 +I0410 14:39:55.332906 18353 solver.cpp:218] Iteration 9480 (2.42789 iter/s, 4.94256s/12 iters), loss = 0.236992 +I0410 14:39:55.332958 18353 solver.cpp:237] Train net output #0: loss = 0.236992 (* 1 = 0.236992 loss) +I0410 14:39:55.332970 18353 sgd_solver.cpp:105] Iteration 9480, lr = 0.00152918 +I0410 14:39:57.339954 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9486.caffemodel +I0410 14:39:57.645627 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9486.solverstate +I0410 14:39:57.857519 18353 solver.cpp:330] Iteration 9486, Testing net (#0) +I0410 14:39:57.857539 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:39:58.527278 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:02.361070 18353 solver.cpp:397] Test net output #0: accuracy = 0.575368 +I0410 14:40:02.361124 18353 solver.cpp:397] Test net output #1: loss = 2.46542 (* 1 = 2.46542 loss) +I0410 14:40:04.189177 18353 solver.cpp:218] Iteration 9492 (1.35501 iter/s, 8.85599s/12 iters), loss = 0.209818 +I0410 14:40:04.189240 18353 solver.cpp:237] Train net output #0: loss = 0.209818 (* 1 = 0.209818 loss) +I0410 14:40:04.189254 18353 sgd_solver.cpp:105] Iteration 9492, lr = 0.00152555 +I0410 14:40:09.099334 18353 solver.cpp:218] Iteration 9504 (2.44401 iter/s, 4.90996s/12 iters), loss = 0.150755 +I0410 14:40:09.099398 18353 solver.cpp:237] Train net output #0: loss = 0.150755 (* 1 = 0.150755 loss) +I0410 14:40:09.099412 18353 sgd_solver.cpp:105] Iteration 9504, lr = 0.00152193 +I0410 14:40:10.545635 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:14.011312 18353 solver.cpp:218] Iteration 9516 (2.4431 iter/s, 4.91179s/12 iters), loss = 0.303428 +I0410 14:40:14.011361 18353 solver.cpp:237] Train net output #0: loss = 0.303428 (* 1 = 0.303428 loss) +I0410 14:40:14.011370 18353 sgd_solver.cpp:105] Iteration 9516, lr = 0.00151831 +I0410 14:40:18.888329 18353 solver.cpp:218] Iteration 9528 (2.46061 iter/s, 4.87683s/12 iters), loss = 0.216133 +I0410 14:40:18.888453 18353 solver.cpp:237] Train net output #0: loss = 0.216133 (* 1 = 0.216133 loss) +I0410 14:40:18.888468 18353 sgd_solver.cpp:105] Iteration 9528, lr = 0.00151471 +I0410 14:40:23.739980 18353 solver.cpp:218] Iteration 9540 (2.47351 iter/s, 4.8514s/12 iters), loss = 0.115403 +I0410 14:40:23.740038 18353 solver.cpp:237] Train net output #0: loss = 0.115403 (* 1 = 0.115403 loss) +I0410 14:40:23.740052 18353 sgd_solver.cpp:105] Iteration 9540, lr = 0.00151111 +I0410 14:40:28.627835 18353 solver.cpp:218] Iteration 9552 (2.45516 iter/s, 4.88767s/12 iters), loss = 0.0946793 +I0410 14:40:28.627885 18353 solver.cpp:237] Train net output #0: loss = 0.0946793 (* 1 = 0.0946793 loss) +I0410 14:40:28.627898 18353 sgd_solver.cpp:105] Iteration 9552, lr = 0.00150752 +I0410 14:40:33.575628 18353 solver.cpp:218] Iteration 9564 (2.42541 iter/s, 4.94761s/12 iters), loss = 0.227629 +I0410 14:40:33.575678 18353 solver.cpp:237] Train net output #0: loss = 0.227629 (* 1 = 0.227629 loss) +I0410 14:40:33.575690 18353 sgd_solver.cpp:105] Iteration 9564, lr = 0.00150395 +I0410 14:40:38.493116 18353 solver.cpp:218] Iteration 9576 (2.44036 iter/s, 4.91731s/12 iters), loss = 0.166091 +I0410 14:40:38.493171 18353 solver.cpp:237] Train net output #0: loss = 0.166091 (* 1 = 0.166091 loss) +I0410 14:40:38.493186 18353 sgd_solver.cpp:105] Iteration 9576, lr = 0.00150037 +I0410 14:40:42.998380 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9588.caffemodel +I0410 14:40:43.549921 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9588.solverstate +I0410 14:40:43.956768 18353 solver.cpp:330] Iteration 9588, Testing net (#0) +I0410 14:40:43.956790 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:40:44.646225 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:48.408604 18353 solver.cpp:397] Test net output #0: accuracy = 0.567402 +I0410 14:40:48.408655 18353 solver.cpp:397] Test net output #1: loss = 2.52206 (* 1 = 2.52206 loss) +I0410 14:40:48.490751 18353 solver.cpp:218] Iteration 9588 (1.20032 iter/s, 9.99733s/12 iters), loss = 0.237975 +I0410 14:40:48.490798 18353 solver.cpp:237] Train net output #0: loss = 0.237975 (* 1 = 0.237975 loss) +I0410 14:40:48.490811 18353 sgd_solver.cpp:105] Iteration 9588, lr = 0.00149681 +I0410 14:40:52.762014 18353 solver.cpp:218] Iteration 9600 (2.80958 iter/s, 4.2711s/12 iters), loss = 0.249677 +I0410 14:40:52.762166 18353 solver.cpp:237] Train net output #0: loss = 0.249677 (* 1 = 0.249677 loss) +I0410 14:40:52.762177 18353 sgd_solver.cpp:105] Iteration 9600, lr = 0.00149326 +I0410 14:40:56.398937 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:57.769876 18353 solver.cpp:218] Iteration 9612 (2.39637 iter/s, 5.00758s/12 iters), loss = 0.147398 +I0410 14:40:57.769922 18353 solver.cpp:237] Train net output #0: loss = 0.147398 (* 1 = 0.147398 loss) +I0410 14:40:57.769932 18353 sgd_solver.cpp:105] Iteration 9612, lr = 0.00148971 +I0410 14:41:02.708220 18353 solver.cpp:218] Iteration 9624 (2.43006 iter/s, 4.93816s/12 iters), loss = 0.243233 +I0410 14:41:02.708272 18353 solver.cpp:237] Train net output #0: loss = 0.243233 (* 1 = 0.243233 loss) +I0410 14:41:02.708282 18353 sgd_solver.cpp:105] Iteration 9624, lr = 0.00148618 +I0410 14:41:07.602622 18353 solver.cpp:218] Iteration 9636 (2.45187 iter/s, 4.89422s/12 iters), loss = 0.158165 +I0410 14:41:07.602680 18353 solver.cpp:237] Train net output #0: loss = 0.158165 (* 1 = 0.158165 loss) +I0410 14:41:07.602694 18353 sgd_solver.cpp:105] Iteration 9636, lr = 0.00148265 +I0410 14:41:12.509347 18353 solver.cpp:218] Iteration 9648 (2.44572 iter/s, 4.90653s/12 iters), loss = 0.123908 +I0410 14:41:12.509409 18353 solver.cpp:237] Train net output #0: loss = 0.123908 (* 1 = 0.123908 loss) +I0410 14:41:12.509423 18353 sgd_solver.cpp:105] Iteration 9648, lr = 0.00147913 +I0410 14:41:17.444718 18353 solver.cpp:218] Iteration 9660 (2.43152 iter/s, 4.93518s/12 iters), loss = 0.309192 +I0410 14:41:17.444767 18353 solver.cpp:237] Train net output #0: loss = 0.309192 (* 1 = 0.309192 loss) +I0410 14:41:17.444777 18353 sgd_solver.cpp:105] Iteration 9660, lr = 0.00147562 +I0410 14:41:22.437513 18353 solver.cpp:218] Iteration 9672 (2.40355 iter/s, 4.99261s/12 iters), loss = 0.239987 +I0410 14:41:22.437564 18353 solver.cpp:237] Train net output #0: loss = 0.239987 (* 1 = 0.239987 loss) +I0410 14:41:22.437575 18353 sgd_solver.cpp:105] Iteration 9672, lr = 0.00147211 +I0410 14:41:27.348919 18353 solver.cpp:218] Iteration 9684 (2.44338 iter/s, 4.91122s/12 iters), loss = 0.214072 +I0410 14:41:27.349099 18353 solver.cpp:237] Train net output #0: loss = 0.214072 (* 1 = 0.214072 loss) +I0410 14:41:27.349114 18353 sgd_solver.cpp:105] Iteration 9684, lr = 0.00146862 +I0410 14:41:29.415582 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9690.caffemodel +I0410 14:41:29.697649 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9690.solverstate +I0410 14:41:29.893741 18353 solver.cpp:330] Iteration 9690, Testing net (#0) +I0410 14:41:29.893774 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:41:30.664129 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:33.499447 18353 blocking_queue.cpp:49] Waiting for data +I0410 14:41:34.874099 18353 solver.cpp:397] Test net output #0: accuracy = 0.561275 +I0410 14:41:34.874150 18353 solver.cpp:397] Test net output #1: loss = 2.504 (* 1 = 2.504 loss) +I0410 14:41:36.772971 18353 solver.cpp:218] Iteration 9696 (1.27339 iter/s, 9.42364s/12 iters), loss = 0.184445 +I0410 14:41:36.773020 18353 solver.cpp:237] Train net output #0: loss = 0.184445 (* 1 = 0.184445 loss) +I0410 14:41:36.773031 18353 sgd_solver.cpp:105] Iteration 9696, lr = 0.00146513 +I0410 14:41:41.762070 18353 solver.cpp:218] Iteration 9708 (2.40534 iter/s, 4.98891s/12 iters), loss = 0.182564 +I0410 14:41:41.762142 18353 solver.cpp:237] Train net output #0: loss = 0.182564 (* 1 = 0.182564 loss) +I0410 14:41:41.762156 18353 sgd_solver.cpp:105] Iteration 9708, lr = 0.00146165 +I0410 14:41:42.490715 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:46.773536 18353 solver.cpp:218] Iteration 9720 (2.39461 iter/s, 5.01126s/12 iters), loss = 0.14053 +I0410 14:41:46.773582 18353 solver.cpp:237] Train net output #0: loss = 0.14053 (* 1 = 0.14053 loss) +I0410 14:41:46.773593 18353 sgd_solver.cpp:105] Iteration 9720, lr = 0.00145818 +I0410 14:41:51.831698 18353 solver.cpp:218] Iteration 9732 (2.37249 iter/s, 5.05798s/12 iters), loss = 0.247079 +I0410 14:41:51.831756 18353 solver.cpp:237] Train net output #0: loss = 0.247079 (* 1 = 0.247079 loss) +I0410 14:41:51.831768 18353 sgd_solver.cpp:105] Iteration 9732, lr = 0.00145472 +I0410 14:41:56.748929 18353 solver.cpp:218] Iteration 9744 (2.44049 iter/s, 4.91704s/12 iters), loss = 0.16689 +I0410 14:41:56.748987 18353 solver.cpp:237] Train net output #0: loss = 0.16689 (* 1 = 0.16689 loss) +I0410 14:41:56.748998 18353 sgd_solver.cpp:105] Iteration 9744, lr = 0.00145127 +I0410 14:42:01.675180 18353 solver.cpp:218] Iteration 9756 (2.43603 iter/s, 4.92606s/12 iters), loss = 0.195629 +I0410 14:42:01.675348 18353 solver.cpp:237] Train net output #0: loss = 0.195629 (* 1 = 0.195629 loss) +I0410 14:42:01.675361 18353 sgd_solver.cpp:105] Iteration 9756, lr = 0.00144782 +I0410 14:42:06.582463 18353 solver.cpp:218] Iteration 9768 (2.44549 iter/s, 4.90699s/12 iters), loss = 0.158777 +I0410 14:42:06.582518 18353 solver.cpp:237] Train net output #0: loss = 0.158777 (* 1 = 0.158777 loss) +I0410 14:42:06.582531 18353 sgd_solver.cpp:105] Iteration 9768, lr = 0.00144438 +I0410 14:42:11.535090 18353 solver.cpp:218] Iteration 9780 (2.42305 iter/s, 4.95244s/12 iters), loss = 0.195333 +I0410 14:42:11.535133 18353 solver.cpp:237] Train net output #0: loss = 0.195334 (* 1 = 0.195334 loss) +I0410 14:42:11.535142 18353 sgd_solver.cpp:105] Iteration 9780, lr = 0.00144095 +I0410 14:42:15.887224 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9792.caffemodel +I0410 14:42:16.218623 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9792.solverstate +I0410 14:42:16.416877 18353 solver.cpp:330] Iteration 9792, Testing net (#0) +I0410 14:42:16.416898 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:42:17.031771 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:42:20.933519 18353 solver.cpp:397] Test net output #0: accuracy = 0.579044 +I0410 14:42:20.933555 18353 solver.cpp:397] Test net output #1: loss = 2.37845 (* 1 = 2.37845 loss) +I0410 14:42:21.015034 18353 solver.cpp:218] Iteration 9792 (1.26587 iter/s, 9.47965s/12 iters), loss = 0.198765 +I0410 14:42:21.015090 18353 solver.cpp:237] Train net output #0: loss = 0.198765 (* 1 = 0.198765 loss) +I0410 14:42:21.015102 18353 sgd_solver.cpp:105] Iteration 9792, lr = 0.00143753 +I0410 14:42:25.479322 18353 solver.cpp:218] Iteration 9804 (2.6881 iter/s, 4.46411s/12 iters), loss = 0.133107 +I0410 14:42:25.479365 18353 solver.cpp:237] Train net output #0: loss = 0.133108 (* 1 = 0.133108 loss) +I0410 14:42:25.479374 18353 sgd_solver.cpp:105] Iteration 9804, lr = 0.00143412 +I0410 14:42:28.635205 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:42:30.593412 18353 solver.cpp:218] Iteration 9816 (2.34654 iter/s, 5.1139s/12 iters), loss = 0.337727 +I0410 14:42:30.593467 18353 solver.cpp:237] Train net output #0: loss = 0.337728 (* 1 = 0.337728 loss) +I0410 14:42:30.593482 18353 sgd_solver.cpp:105] Iteration 9816, lr = 0.00143072 +I0410 14:42:35.510040 18353 solver.cpp:218] Iteration 9828 (2.44079 iter/s, 4.91644s/12 iters), loss = 0.245532 +I0410 14:42:35.510167 18353 solver.cpp:237] Train net output #0: loss = 0.245532 (* 1 = 0.245532 loss) +I0410 14:42:35.510177 18353 sgd_solver.cpp:105] Iteration 9828, lr = 0.00142732 +I0410 14:42:40.390113 18353 solver.cpp:218] Iteration 9840 (2.45912 iter/s, 4.8798s/12 iters), loss = 0.126397 +I0410 14:42:40.390188 18353 solver.cpp:237] Train net output #0: loss = 0.126397 (* 1 = 0.126397 loss) +I0410 14:42:40.390202 18353 sgd_solver.cpp:105] Iteration 9840, lr = 0.00142393 +I0410 14:42:45.275735 18353 solver.cpp:218] Iteration 9852 (2.45628 iter/s, 4.88543s/12 iters), loss = 0.185942 +I0410 14:42:45.275786 18353 solver.cpp:237] Train net output #0: loss = 0.185942 (* 1 = 0.185942 loss) +I0410 14:42:45.275799 18353 sgd_solver.cpp:105] Iteration 9852, lr = 0.00142055 +I0410 14:42:50.214323 18353 solver.cpp:218] Iteration 9864 (2.42993 iter/s, 4.93841s/12 iters), loss = 0.158418 +I0410 14:42:50.214365 18353 solver.cpp:237] Train net output #0: loss = 0.158418 (* 1 = 0.158418 loss) +I0410 14:42:50.214373 18353 sgd_solver.cpp:105] Iteration 9864, lr = 0.00141718 +I0410 14:42:55.104404 18353 solver.cpp:218] Iteration 9876 (2.45404 iter/s, 4.8899s/12 iters), loss = 0.255006 +I0410 14:42:55.104452 18353 solver.cpp:237] Train net output #0: loss = 0.255006 (* 1 = 0.255006 loss) +I0410 14:42:55.104462 18353 sgd_solver.cpp:105] Iteration 9876, lr = 0.00141381 +I0410 14:43:00.034459 18353 solver.cpp:218] Iteration 9888 (2.43414 iter/s, 4.92987s/12 iters), loss = 0.186781 +I0410 14:43:00.034512 18353 solver.cpp:237] Train net output #0: loss = 0.186781 (* 1 = 0.186781 loss) +I0410 14:43:00.034523 18353 sgd_solver.cpp:105] Iteration 9888, lr = 0.00141045 +I0410 14:43:02.052062 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9894.caffemodel +I0410 14:43:02.355147 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9894.solverstate +I0410 14:43:02.549393 18353 solver.cpp:330] Iteration 9894, Testing net (#0) +I0410 14:43:02.549412 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:43:03.019343 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:43:06.852264 18353 solver.cpp:397] Test net output #0: accuracy = 0.572917 +I0410 14:43:06.852387 18353 solver.cpp:397] Test net output #1: loss = 2.44568 (* 1 = 2.44568 loss) +I0410 14:43:08.824234 18353 solver.cpp:218] Iteration 9900 (1.36527 iter/s, 8.7895s/12 iters), loss = 0.151593 +I0410 14:43:08.824286 18353 solver.cpp:237] Train net output #0: loss = 0.151593 (* 1 = 0.151593 loss) +I0410 14:43:08.824298 18353 sgd_solver.cpp:105] Iteration 9900, lr = 0.00140711 +I0410 14:43:13.762876 18353 solver.cpp:218] Iteration 9912 (2.42991 iter/s, 4.93846s/12 iters), loss = 0.151792 +I0410 14:43:13.762931 18353 solver.cpp:237] Train net output #0: loss = 0.151793 (* 1 = 0.151793 loss) +I0410 14:43:13.762944 18353 sgd_solver.cpp:105] Iteration 9912, lr = 0.00140377 +I0410 14:43:13.872913 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:43:18.871026 18353 solver.cpp:218] Iteration 9924 (2.34928 iter/s, 5.10796s/12 iters), loss = 0.148947 +I0410 14:43:18.871080 18353 solver.cpp:237] Train net output #0: loss = 0.148947 (* 1 = 0.148947 loss) +I0410 14:43:18.871093 18353 sgd_solver.cpp:105] Iteration 9924, lr = 0.00140043 +I0410 14:43:23.963198 18353 solver.cpp:218] Iteration 9936 (2.35665 iter/s, 5.09198s/12 iters), loss = 0.158432 +I0410 14:43:23.963248 18353 solver.cpp:237] Train net output #0: loss = 0.158432 (* 1 = 0.158432 loss) +I0410 14:43:23.963258 18353 sgd_solver.cpp:105] Iteration 9936, lr = 0.00139711 +I0410 14:43:28.974037 18353 solver.cpp:218] Iteration 9948 (2.3949 iter/s, 5.01065s/12 iters), loss = 0.221105 +I0410 14:43:28.974088 18353 solver.cpp:237] Train net output #0: loss = 0.221105 (* 1 = 0.221105 loss) +I0410 14:43:28.974102 18353 sgd_solver.cpp:105] Iteration 9948, lr = 0.00139379 +I0410 14:43:33.869300 18353 solver.cpp:218] Iteration 9960 (2.45144 iter/s, 4.89508s/12 iters), loss = 0.329547 +I0410 14:43:33.869354 18353 solver.cpp:237] Train net output #0: loss = 0.329547 (* 1 = 0.329547 loss) +I0410 14:43:33.869366 18353 sgd_solver.cpp:105] Iteration 9960, lr = 0.00139048 +I0410 14:43:38.764585 18353 solver.cpp:218] Iteration 9972 (2.45144 iter/s, 4.89509s/12 iters), loss = 0.208258 +I0410 14:43:38.764758 18353 solver.cpp:237] Train net output #0: loss = 0.208258 (* 1 = 0.208258 loss) +I0410 14:43:38.764775 18353 sgd_solver.cpp:105] Iteration 9972, lr = 0.00138718 +I0410 14:43:43.735884 18353 solver.cpp:218] Iteration 9984 (2.41401 iter/s, 4.97099s/12 iters), loss = 0.219894 +I0410 14:43:43.735946 18353 solver.cpp:237] Train net output #0: loss = 0.219894 (* 1 = 0.219894 loss) +I0410 14:43:43.735960 18353 sgd_solver.cpp:105] Iteration 9984, lr = 0.00138389 +I0410 14:43:48.102035 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9996.caffemodel +I0410 14:43:48.554915 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9996.solverstate +I0410 14:43:49.502020 18353 solver.cpp:330] Iteration 9996, Testing net (#0) +I0410 14:43:49.502048 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:43:50.019614 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:43:54.244901 18353 solver.cpp:397] Test net output #0: accuracy = 0.585172 +I0410 14:43:54.244952 18353 solver.cpp:397] Test net output #1: loss = 2.45077 (* 1 = 2.45077 loss) +I0410 14:43:54.326189 18353 solver.cpp:218] Iteration 9996 (1.13315 iter/s, 10.59s/12 iters), loss = 0.14048 +I0410 14:43:54.326243 18353 solver.cpp:237] Train net output #0: loss = 0.14048 (* 1 = 0.14048 loss) +I0410 14:43:54.326256 18353 sgd_solver.cpp:105] Iteration 9996, lr = 0.0013806 +I0410 14:43:58.552924 18353 solver.cpp:218] Iteration 10008 (2.83919 iter/s, 4.22656s/12 iters), loss = 0.24623 +I0410 14:43:58.552978 18353 solver.cpp:237] Train net output #0: loss = 0.24623 (* 1 = 0.24623 loss) +I0410 14:43:58.552991 18353 sgd_solver.cpp:105] Iteration 10008, lr = 0.00137732 +I0410 14:44:00.771916 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:03.500396 18353 solver.cpp:218] Iteration 10020 (2.42557 iter/s, 4.94729s/12 iters), loss = 0.115294 +I0410 14:44:03.500452 18353 solver.cpp:237] Train net output #0: loss = 0.115294 (* 1 = 0.115294 loss) +I0410 14:44:03.500464 18353 sgd_solver.cpp:105] Iteration 10020, lr = 0.00137405 +I0410 14:44:08.447297 18353 solver.cpp:218] Iteration 10032 (2.42585 iter/s, 4.94671s/12 iters), loss = 0.149437 +I0410 14:44:08.447352 18353 solver.cpp:237] Train net output #0: loss = 0.149437 (* 1 = 0.149437 loss) +I0410 14:44:08.447366 18353 sgd_solver.cpp:105] Iteration 10032, lr = 0.00137079 +I0410 14:44:13.289423 18353 solver.cpp:218] Iteration 10044 (2.47835 iter/s, 4.84194s/12 iters), loss = 0.165375 +I0410 14:44:13.289572 18353 solver.cpp:237] Train net output #0: loss = 0.165375 (* 1 = 0.165375 loss) +I0410 14:44:13.289587 18353 sgd_solver.cpp:105] Iteration 10044, lr = 0.00136754 +I0410 14:44:18.081051 18353 solver.cpp:218] Iteration 10056 (2.50451 iter/s, 4.79135s/12 iters), loss = 0.102136 +I0410 14:44:18.081095 18353 solver.cpp:237] Train net output #0: loss = 0.102136 (* 1 = 0.102136 loss) +I0410 14:44:18.081104 18353 sgd_solver.cpp:105] Iteration 10056, lr = 0.00136429 +I0410 14:44:22.994966 18353 solver.cpp:218] Iteration 10068 (2.44213 iter/s, 4.91374s/12 iters), loss = 0.137657 +I0410 14:44:22.995013 18353 solver.cpp:237] Train net output #0: loss = 0.137658 (* 1 = 0.137658 loss) +I0410 14:44:22.995023 18353 sgd_solver.cpp:105] Iteration 10068, lr = 0.00136105 +I0410 14:44:27.875278 18353 solver.cpp:218] Iteration 10080 (2.45895 iter/s, 4.88013s/12 iters), loss = 0.0803564 +I0410 14:44:27.875335 18353 solver.cpp:237] Train net output #0: loss = 0.0803565 (* 1 = 0.0803565 loss) +I0410 14:44:27.875349 18353 sgd_solver.cpp:105] Iteration 10080, lr = 0.00135782 +I0410 14:44:32.799690 18353 solver.cpp:218] Iteration 10092 (2.43694 iter/s, 4.92422s/12 iters), loss = 0.204733 +I0410 14:44:32.799747 18353 solver.cpp:237] Train net output #0: loss = 0.204733 (* 1 = 0.204733 loss) +I0410 14:44:32.799762 18353 sgd_solver.cpp:105] Iteration 10092, lr = 0.0013546 +I0410 14:44:34.807947 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10098.caffemodel +I0410 14:44:35.112897 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10098.solverstate +I0410 14:44:35.320705 18353 solver.cpp:330] Iteration 10098, Testing net (#0) +I0410 14:44:35.320735 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:44:35.798521 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:39.769268 18353 solver.cpp:397] Test net output #0: accuracy = 0.574755 +I0410 14:44:39.769312 18353 solver.cpp:397] Test net output #1: loss = 2.41586 (* 1 = 2.41586 loss) +I0410 14:44:41.557220 18353 solver.cpp:218] Iteration 10104 (1.37029 iter/s, 8.75724s/12 iters), loss = 0.0673311 +I0410 14:44:41.557289 18353 solver.cpp:237] Train net output #0: loss = 0.0673311 (* 1 = 0.0673311 loss) +I0410 14:44:41.557302 18353 sgd_solver.cpp:105] Iteration 10104, lr = 0.00135138 +I0410 14:44:45.793998 18357 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:46.420656 18353 solver.cpp:218] Iteration 10116 (2.46749 iter/s, 4.86323s/12 iters), loss = 0.150756 +I0410 14:44:46.420707 18353 solver.cpp:237] Train net output #0: loss = 0.150756 (* 1 = 0.150756 loss) +I0410 14:44:46.420717 18353 sgd_solver.cpp:105] Iteration 10116, lr = 0.00134817 +I0410 14:44:51.800137 18353 solver.cpp:218] Iteration 10128 (2.23078 iter/s, 5.37928s/12 iters), loss = 0.151478 +I0410 14:44:51.800191 18353 solver.cpp:237] Train net output #0: loss = 0.151478 (* 1 = 0.151478 loss) +I0410 14:44:51.800205 18353 sgd_solver.cpp:105] Iteration 10128, lr = 0.00134497 +I0410 14:44:56.886482 18353 solver.cpp:218] Iteration 10140 (2.35935 iter/s, 5.08615s/12 iters), loss = 0.100837 +I0410 14:44:56.886536 18353 solver.cpp:237] Train net output #0: loss = 0.100837 (* 1 = 0.100837 loss) +I0410 14:44:56.886549 18353 sgd_solver.cpp:105] Iteration 10140, lr = 0.00134178 +I0410 14:45:01.694110 18353 solver.cpp:218] Iteration 10152 (2.49613 iter/s, 4.80745s/12 iters), loss = 0.171949 +I0410 14:45:01.694154 18353 solver.cpp:237] Train net output #0: loss = 0.171949 (* 1 = 0.171949 loss) +I0410 14:45:01.694164 18353 sgd_solver.cpp:105] Iteration 10152, lr = 0.00133859 +I0410 14:45:06.600464 18353 solver.cpp:218] Iteration 10164 (2.44589 iter/s, 4.90618s/12 iters), loss = 0.22351 +I0410 14:45:06.600507 18353 solver.cpp:237] Train net output #0: loss = 0.22351 (* 1 = 0.22351 loss) +I0410 14:45:06.600515 18353 sgd_solver.cpp:105] Iteration 10164, lr = 0.00133541 +I0410 14:45:11.500793 18353 solver.cpp:218] Iteration 10176 (2.44891 iter/s, 4.90015s/12 iters), loss = 0.107566 +I0410 14:45:11.500850 18353 solver.cpp:237] Train net output #0: loss = 0.107566 (* 1 = 0.107566 loss) +I0410 14:45:11.500864 18353 sgd_solver.cpp:105] Iteration 10176, lr = 0.00133224 +I0410 14:45:16.397441 18353 solver.cpp:218] Iteration 10188 (2.45075 iter/s, 4.89646s/12 iters), loss = 0.21583 +I0410 14:45:16.397604 18353 solver.cpp:237] Train net output #0: loss = 0.21583 (* 1 = 0.21583 loss) +I0410 14:45:16.397619 18353 sgd_solver.cpp:105] Iteration 10188, lr = 0.00132908 +I0410 14:45:20.889103 18353 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10200.caffemodel +I0410 14:45:21.179427 18353 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10200.solverstate +I0410 14:45:21.416931 18353 solver.cpp:310] Iteration 10200, loss = 0.178516 +I0410 14:45:21.416970 18353 solver.cpp:330] Iteration 10200, Testing net (#0) +I0410 14:45:21.416980 18353 net.cpp:676] Ignoring source layer train-data +I0410 14:45:21.945623 18358 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:45:25.985695 18353 solver.cpp:397] Test net output #0: accuracy = 0.576593 +I0410 14:45:25.985738 18353 solver.cpp:397] Test net output #1: loss = 2.49071 (* 1 = 2.49071 loss) +I0410 14:45:25.985749 18353 solver.cpp:315] Optimization Done. +I0410 14:45:25.985756 18353 caffe.cpp:259] Optimization Done. diff --git a/cars/architecture-investigations/fc/1-layer/256/conf.csv b/cars/architecture-investigations/fc/1-layer/256/conf.csv new file mode 100644 index 0000000..f423b90 --- /dev/null +++ b/cars/architecture-investigations/fc/1-layer/256/conf.csv @@ -0,0 +1,197 @@ +,AM General Hummer SUV 2000,Acura RL Sedan 2012,Acura TL Sedan 2012,Acura TL Type-S 2008,Acura TSX Sedan 2012,Acura Integra Type R 2001,Acura ZDX Hatchback 2012,Aston Martin V8 Vantage Convertible 2012,Aston Martin V8 Vantage Coupe 2012,Aston Martin Virage Convertible 2012,Aston Martin Virage Coupe 2012,Audi RS 4 Convertible 2008,Audi A5 Coupe 2012,Audi TTS Coupe 2012,Audi R8 Coupe 2012,Audi V8 Sedan 1994,Audi 100 Sedan 1994,Audi 100 Wagon 1994,Audi TT Hatchback 2011,Audi S6 Sedan 2011,Audi S5 Convertible 2012,Audi S5 Coupe 2012,Audi S4 Sedan 2012,Audi S4 Sedan 2007,Audi TT RS Coupe 2012,BMW ActiveHybrid 5 Sedan 2012,BMW 1 Series Convertible 2012,BMW 1 Series Coupe 2012,BMW 3 Series Sedan 2012,BMW 3 Series Wagon 2012,BMW 6 Series Convertible 2007,BMW X5 SUV 2007,BMW X6 SUV 2012,BMW M3 Coupe 2012,BMW M5 Sedan 2010,BMW M6 Convertible 2010,BMW X3 SUV 2012,BMW Z4 Convertible 2012,Bentley Continental Supersports Conv. Convertible 2012,Bentley Arnage Sedan 2009,Bentley Mulsanne Sedan 2011,Bentley Continental GT Coupe 2012,Bentley Continental GT Coupe 2007,Bentley Continental Flying Spur Sedan 2007,Bugatti Veyron 16.4 Convertible 2009,Bugatti Veyron 16.4 Coupe 2009,Buick Regal GS 2012,Buick Rainier SUV 2007,Buick Verano Sedan 2012,Buick Enclave SUV 2012,Cadillac CTS-V Sedan 2012,Cadillac SRX SUV 2012,Cadillac Escalade EXT Crew Cab 2007,Chevrolet Silverado 1500 Hybrid Crew Cab 2012,Chevrolet Corvette Convertible 2012,Chevrolet Corvette ZR1 2012,Chevrolet Corvette Ron Fellows Edition Z06 2007,Chevrolet Traverse SUV 2012,Chevrolet Camaro Convertible 2012,Chevrolet HHR SS 2010,Chevrolet Impala Sedan 2007,Chevrolet Tahoe Hybrid SUV 2012,Chevrolet Sonic Sedan 2012,Chevrolet Express Cargo Van 2007,Chevrolet Avalanche Crew Cab 2012,Chevrolet Cobalt SS 2010,Chevrolet Malibu Hybrid Sedan 2010,Chevrolet TrailBlazer SS 2009,Chevrolet Silverado 2500HD Regular Cab 2012,Chevrolet Silverado 1500 Classic Extended Cab 2007,Chevrolet Express Van 2007,Chevrolet Monte Carlo Coupe 2007,Chevrolet Malibu Sedan 2007,Chevrolet Silverado 1500 Extended Cab 2012,Chevrolet Silverado 1500 Regular Cab 2012,Chrysler Aspen SUV 2009,Chrysler Sebring Convertible 2010,Chrysler Town and Country Minivan 2012,Chrysler 300 SRT-8 2010,Chrysler Crossfire Convertible 2008,Chrysler PT Cruiser Convertible 2008,Daewoo Nubira Wagon 2002,Dodge Caliber Wagon 2012,Dodge Caliber Wagon 2007,Dodge Caravan Minivan 1997,Dodge Ram Pickup 3500 Crew Cab 2010,Dodge Ram Pickup 3500 Quad Cab 2009,Dodge Sprinter Cargo Van 2009,Dodge Journey SUV 2012,Dodge Dakota Crew Cab 2010,Dodge Dakota Club Cab 2007,Dodge Magnum Wagon 2008,Dodge Challenger SRT8 2011,Dodge Durango SUV 2012,Dodge Durango SUV 2007,Dodge Charger Sedan 2012,Dodge Charger SRT-8 2009,Eagle Talon Hatchback 1998,FIAT 500 Abarth 2012,FIAT 500 Convertible 2012,Ferrari FF Coupe 2012,Ferrari California Convertible 2012,Ferrari 458 Italia Convertible 2012,Ferrari 458 Italia Coupe 2012,Fisker Karma Sedan 2012,Ford F-450 Super Duty Crew Cab 2012,Ford Mustang Convertible 2007,Ford Freestar Minivan 2007,Ford Expedition EL SUV 2009,Ford Edge SUV 2012,Ford Ranger SuperCab 2011,Ford GT Coupe 2006,Ford F-150 Regular Cab 2012,Ford F-150 Regular Cab 2007,Ford Focus Sedan 2007,Ford E-Series Wagon Van 2012,Ford Fiesta Sedan 2012,GMC Terrain SUV 2012,GMC Savana Van 2012,GMC Yukon Hybrid SUV 2012,GMC Acadia SUV 2012,GMC Canyon Extended Cab 2012,Geo Metro Convertible 1993,HUMMER H3T Crew Cab 2010,HUMMER H2 SUT Crew Cab 2009,Honda Odyssey Minivan 2012,Honda Odyssey Minivan 2007,Honda Accord Coupe 2012,Honda Accord Sedan 2012,Hyundai Veloster Hatchback 2012,Hyundai Santa Fe SUV 2012,Hyundai Tucson SUV 2012,Hyundai Veracruz SUV 2012,Hyundai Sonata Hybrid Sedan 2012,Hyundai Elantra Sedan 2007,Hyundai Accent Sedan 2012,Hyundai Genesis Sedan 2012,Hyundai Sonata Sedan 2012,Hyundai Elantra Touring Hatchback 2012,Hyundai Azera Sedan 2012,Infiniti G Coupe IPL 2012,Infiniti QX56 SUV 2011,Isuzu Ascender SUV 2008,Jaguar XK XKR 2012,Jeep Patriot SUV 2012,Jeep Wrangler SUV 2012,Jeep Liberty SUV 2012,Jeep Grand Cherokee SUV 2012,Jeep Compass SUV 2012,Lamborghini Reventon Coupe 2008,Lamborghini Aventador Coupe 2012,Lamborghini Gallardo LP 570-4 Superleggera 2012,Lamborghini Diablo Coupe 2001,Land Rover Range Rover SUV 2012,Land Rover LR2 SUV 2012,Lincoln Town Car Sedan 2011,MINI Cooper Roadster Convertible 2012,Maybach Landaulet Convertible 2012,Mazda Tribute SUV 2011,McLaren MP4-12C Coupe 2012,Mercedes-Benz 300-Class Convertible 1993,Mercedes-Benz C-Class Sedan 2012,Mercedes-Benz SL-Class Coupe 2009,Mercedes-Benz E-Class Sedan 2012,Mercedes-Benz S-Class Sedan 2012,Mercedes-Benz Sprinter Van 2012,Mitsubishi Lancer Sedan 2012,Nissan Leaf Hatchback 2012,Nissan NV Passenger Van 2012,Nissan Juke Hatchback 2012,Nissan 240SX Coupe 1998,Plymouth Neon Coupe 1999,Porsche Panamera Sedan 2012,Ram C/V Cargo Van Minivan 2012,Rolls-Royce Phantom Drophead Coupe Convertible 2012,Rolls-Royce Ghost Sedan 2012,Rolls-Royce Phantom Sedan 2012,Scion xD Hatchback 2012,Spyker C8 Convertible 2009,Spyker C8 Coupe 2009,Suzuki Aerio Sedan 2007,Suzuki Kizashi Sedan 2012,Suzuki SX4 Hatchback 2012,Suzuki SX4 Sedan 2012,Tesla Model S Sedan 2012,Toyota Sequoia SUV 2012,Toyota Camry Sedan 2012,Toyota Corolla Sedan 2012,Toyota 4Runner SUV 2012,Volkswagen Golf Hatchback 2012,Volkswagen Golf Hatchback 1991,Volkswagen Beetle Hatchback 2012,Volvo C30 Hatchback 2012,Volvo 240 Sedan 1993,Volvo XC90 SUV 2007,smart fortwo Convertible 2012,Per-class accuracy +AM General Hummer SUV 2000,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,83.33% +Acura RL Sedan 2012,0,3,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.5% +Acura TL Sedan 2012,0,0,6,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Acura TL Type-S 2008,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Acura TSX Sedan 2012,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,85.71% +Acura Integra Type R 2001,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Acura ZDX Hatchback 2012,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Aston Martin V8 Vantage Convertible 2012,0,0,0,0,0,0,0,2,3,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,18.18% +Aston Martin V8 Vantage Coupe 2012,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,83.33% +Aston Martin Virage Convertible 2012,0,0,0,0,0,0,0,1,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Aston Martin Virage Coupe 2012,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +Audi RS 4 Convertible 2008,0,0,0,0,0,0,0,0,0,0,0,3,1,0,0,0,0,0,0,0,2,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Audi A5 Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,7,1,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,70.0% +Audi TTS Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,1,1,3,1,0,0,0,1,0,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,25.0% +Audi R8 Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,1,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45.45% +Audi V8 Sedan 1994,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,62.5% +Audi 100 Sedan 1994,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,3,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Audi 100 Wagon 1994,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,36.36% +Audi TT Hatchback 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,14.29% +Audi S6 Sedan 2011,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Audi S5 Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,4,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Audi S5 Coupe 2012,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,25.0% +Audi S4 Sedan 2012,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,1,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Audi S4 Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,1,2,1,0,0,0,0,0,2,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11.11% +Audi TT RS Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +BMW ActiveHybrid 5 Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,4,0,0,2,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +BMW 1 Series Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +BMW 1 Series Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,71.43% +BMW 3 Series Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +BMW 3 Series Wagon 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,50.0% +BMW 6 Series Convertible 2007,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,2,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,25.0% +BMW X5 SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,33.33% +BMW X6 SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,46.15% +BMW M3 Coupe 2012,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,20.0% +BMW M5 Sedan 2010,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +BMW M6 Convertible 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,2,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,22.22% +BMW X3 SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +BMW Z4 Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Bentley Continental Supersports Conv. Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,1,3,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Bentley Arnage Sedan 2009,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,50.0% +Bentley Mulsanne Sedan 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Bentley Continental GT Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Bentley Continental GT Coupe 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,5,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Bentley Continental Flying Spur Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,2,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Bugatti Veyron 16.4 Convertible 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,3,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Bugatti Veyron 16.4 Coupe 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Buick Regal GS 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,54.55% +Buick Rainier SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,1,1,0,30.0% +Buick Verano Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Buick Enclave SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,42.86% +Cadillac CTS-V Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Cadillac SRX SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Cadillac Escalade EXT Crew Cab 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Chevrolet Silverado 1500 Hybrid Crew Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,22.22% +Chevrolet Corvette Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,38.46% +Chevrolet Corvette ZR1 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,42.86% +Chevrolet Corvette Ron Fellows Edition Z06 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,70.0% +Chevrolet Traverse SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,2,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Chevrolet Camaro Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,20.0% +Chevrolet HHR SS 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Chevrolet Impala Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,2,2,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,12.5% +Chevrolet Tahoe Hybrid SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Chevrolet Sonic Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Chevrolet Express Cargo Van 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Chevrolet Avalanche Crew Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Chevrolet Cobalt SS 2010,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,25.0% +Chevrolet Malibu Hybrid Sedan 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,33.33% +Chevrolet TrailBlazer SS 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Chevrolet Silverado 2500HD Regular Cab 2012,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,5,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45.45% +Chevrolet Silverado 1500 Classic Extended Cab 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Chevrolet Express Van 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,22.22% +Chevrolet Monte Carlo Coupe 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Chevrolet Malibu Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,30.0% +Chevrolet Silverado 1500 Extended Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Chevrolet Silverado 1500 Regular Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.5% +Chrysler Aspen SUV 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,71.43% +Chrysler Sebring Convertible 2010,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.5% +Chrysler Town and Country Minivan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Chrysler 300 SRT-8 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2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Daewoo Nubira Wagon 2002,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Dodge Caliber Wagon 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,57.14% +Dodge Dakota Crew Cab 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80.0% +Dodge Dakota Club Cab 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2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Dodge Durango SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,7,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,70.0% +Dodge Durango SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,53.85% +Dodge Charger Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Dodge Charger SRT-8 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,83.33% +FIAT 500 Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Ferrari FF Coupe 2012,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Ferrari California Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,88.89% +Ferrari 458 Italia Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Ferrari 458 Italia Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,1,3,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,23.08% +Fisker Karma Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,1,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,28.57% +Ford F-450 Super Duty Crew Cab 2012,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80.0% +Ford Mustang Convertible 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Ford Freestar Minivan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,90.0% +Ford Expedition EL SUV 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,72.73% +Ford Edge SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80.0% +Ford Ranger SuperCab 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Ford GT Coupe 2006,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Ford F-150 Regular Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,9,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,64.29% +Ford F-150 Regular Cab 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,7,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,53.85% +Ford Focus Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,46.15% +Ford E-Series Wagon Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +Ford Fiesta Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,77.78% +GMC Terrain SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,81.82% +GMC Savana Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,92.31% +GMC Yukon Hybrid SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.14% +GMC Acadia SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +GMC Canyon Extended Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Geo Metro Convertible 1993,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,69.23% +HUMMER H3T Crew Cab 2010,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,3,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,42.86% +HUMMER H2 SUT Crew Cab 2009,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Honda Odyssey Minivan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,1,0,0,2,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Honda Odyssey Minivan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Honda Accord Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Honda Accord Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80.0% +Hyundai Veloster Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Hyundai Santa Fe SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,85.71% +Hyundai Tucson SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Hyundai Veracruz SUV 2012,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,33.33% +Hyundai Sonata Hybrid Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,71.43% +Hyundai Elantra Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,5,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Hyundai Accent Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,20.0% +Hyundai Genesis Sedan 2012,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Hyundai Sonata Sedan 2012,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,37.5% +Hyundai Elantra Touring Hatchback 2012,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Hyundai Azera Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,22.22% +Infiniti G Coupe IPL 2012,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,20.0% +Infiniti QX56 SUV 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +Isuzu Ascender SUV 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Jaguar XK XKR 2012,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,28.57% +Jeep Patriot SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80.0% +Jeep Wrangler SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Jeep Liberty SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,63.64% +Jeep Grand Cherokee SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,54.55% +Jeep Compass SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Lamborghini Reventon Coupe 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.14% +Lamborghini Aventador Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,3,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Lamborghini Gallardo LP 570-4 Superleggera 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Lamborghini Diablo Coupe 2001,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Land Rover Range Rover SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,33.33% +Land Rover LR2 SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,2,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,28.57% +Lincoln Town Car Sedan 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,71.43% +MINI Cooper Roadster Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,88.89% +Maybach Landaulet Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +Mazda Tribute SUV 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +McLaren MP4-12C Coupe 2012,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,70.0% +Mercedes-Benz 300-Class Convertible 1993,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Mercedes-Benz C-Class Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Mercedes-Benz SL-Class Coupe 2009,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Mercedes-Benz E-Class Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,14.29% +Mercedes-Benz S-Class Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,42.86% +Mercedes-Benz Sprinter Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,87.5% +Mitsubishi Lancer Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12.5% +Nissan Leaf Hatchback 2012,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Nissan NV Passenger Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,54.55% +Nissan Juke Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,37.5% +Nissan 240SX Coupe 1998,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,7.14% +Plymouth Neon Coupe 1999,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,50.0% +Porsche Panamera Sedan 2012,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,33.33% +Ram C/V Cargo Van Minivan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Rolls-Royce Phantom Drophead Coupe Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Rolls-Royce Ghost Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,3,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Rolls-Royce Phantom Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,71.43% +Scion xD Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.14% +Spyker C8 Convertible 2009,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,41.67% +Spyker C8 Coupe 2009,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Suzuki Aerio Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,50.0% +Suzuki Kizashi Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,6,0,0,0,0,0,1,0,0,0,0,0,0,0,0,60.0% +Suzuki SX4 Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,6,1,0,0,0,0,0,0,1,0,0,0,2,0,46.15% +Suzuki SX4 Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Tesla Model S Sedan 2012,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,37.5% +Toyota Sequoia SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,81.82% +Toyota Camry Sedan 2012,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,1,0,0,0,0,0,0,0,0,57.14% +Toyota Corolla Sedan 2012,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,3,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,4,0,0,0,0,0,0,0,0,30.77% +Toyota 4Runner SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,6,0,0,0,0,0,0,0,50.0% +Volkswagen Golf Hatchback 2012,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,7,0,0,0,0,0,0,53.85% +Volkswagen Golf Hatchback 1991,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,28.57% +Volkswagen Beetle Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,4,0,0,0,0,36.36% +Volvo C30 Hatchback 2012,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,66.67% +Volvo 240 Sedan 1993,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,75.0% +Volvo XC90 SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,87.5% +smart fortwo Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,9,69.23% diff --git a/cars/architecture-investigations/fc/1-layer/256/deploy.prototxt b/cars/architecture-investigations/fc/1-layer/256/deploy.prototxt new file mode 100644 index 0000000..3fb78c4 --- /dev/null +++ b/cars/architecture-investigations/fc/1-layer/256/deploy.prototxt @@ -0,0 +1,301 @@ +input: "data" +input_shape { + dim: 1 + dim: 3 + dim: 227 + dim: 227 +} +layer { + name: "conv1" + type: "Convolution" + bottom: "data" + top: "conv1" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu1" + type: "ReLU" + bottom: "conv1" + top: "conv1" +} +layer { + name: "norm1" + type: "LRN" + bottom: "conv1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool1" + type: "Pooling" + bottom: "norm1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv2" + type: "Convolution" + bottom: "pool1" + top: "conv2" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu2" + type: "ReLU" + bottom: "conv2" + top: "conv2" +} +layer { + name: "norm2" + type: "LRN" + bottom: "conv2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool2" + type: "Pooling" + bottom: "norm2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv3" + type: "Convolution" + bottom: "pool2" + top: "conv3" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu3" + type: "ReLU" + bottom: "conv3" + top: "conv3" +} +layer { + name: "conv4" + type: "Convolution" + bottom: "conv3" + top: "conv4" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu4" + type: "ReLU" + bottom: "conv4" + top: "conv4" +} +layer { + name: "conv5" + type: "Convolution" + bottom: "conv4" + top: "conv5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu5" + type: "ReLU" + bottom: "conv5" + top: "conv5" +} +layer { + name: "pool5" + type: "Pooling" + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "fc6" + type: "InnerProduct" + bottom: "pool5" + top: "fc6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu6" + type: "ReLU" + bottom: "fc6" + top: "fc6" +} +layer { + name: "drop6" + type: "Dropout" + bottom: "fc6" + top: "fc6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc8" + type: "InnerProduct" + bottom: "fc6" + top: "fc8" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 196 + weight_filler { + type: "gaussian" + std: 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zxrDe;fS2=F5p>|5ccwKt_IV*)mpADr6lz-N)rJYtC5SY4W7*=+n0|4%hjSw6LZB$+Mn7LP@M2|!ZM zCSZl;l2j5vEA)3~jP|bHlhETxB8=JJ9&eZG7{G8{0N1 zJ*7M(_LEKl*)J&escZ0Q`+v!SeX9HQc>f?l|5Kv9k%_97_4|{CeZC9(kHCsPed=EV z^S4KTJ)HqnAN5zh>-{JFbl&tIfz{xzQ-A0~kPubHZsfXN|EDf^0H}oNTJfn<|C{08 zUq3TZRcy0skrTfapx+4lH?Xc{p=uvH`ln9)UK+m>Kv#B>frB6{mYRX!VQIE`D|2O*&JK6vM literal 0 HcmV?d00001 diff --git a/cars/architecture-investigations/fc/1-layer/256/original.prototxt b/cars/architecture-investigations/fc/1-layer/256/original.prototxt new file mode 100644 index 0000000..df763ea --- /dev/null +++ b/cars/architecture-investigations/fc/1-layer/256/original.prototxt @@ -0,0 +1,348 @@ +name: "AlexNet" +layer { + name: "train-data" + type: "Data" + top: "data" + top: "label" + include { + stage: "train" + } + transform_param { + mirror: true + crop_size: 227 + } + data_param { + batch_size: 128 + } +} +layer { + name: "val-data" + type: "Data" + top: "data" + top: "label" + include { + stage: "val" + } + transform_param { + crop_size: 227 + } + data_param { + batch_size: 32 + } +} +layer { + name: "conv1" + type: "Convolution" + bottom: "data" + top: "conv1" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu1" + type: "ReLU" + bottom: "conv1" + top: "conv1" +} +layer { + name: "norm1" + type: "LRN" + bottom: "conv1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool1" + type: "Pooling" + bottom: "norm1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv2" + type: "Convolution" + bottom: "pool1" + top: "conv2" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu2" + type: "ReLU" + bottom: "conv2" + top: "conv2" +} +layer { + name: "norm2" + type: "LRN" + bottom: "conv2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool2" + type: "Pooling" + bottom: "norm2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv3" + type: "Convolution" + bottom: "pool2" + top: "conv3" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu3" + type: "ReLU" + bottom: "conv3" + top: "conv3" +} +layer { + name: "conv4" + type: "Convolution" + bottom: "conv3" + top: "conv4" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu4" + type: "ReLU" + bottom: "conv4" + top: "conv4" +} +layer { + name: "conv5" + type: "Convolution" + bottom: "conv4" + top: "conv5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu5" + type: "ReLU" + bottom: "conv5" + top: "conv5" +} +layer { + name: "pool5" + type: "Pooling" + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "fc6" + type: "InnerProduct" + bottom: "pool5" + top: "fc6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu6" + type: "ReLU" + bottom: "fc6" + top: "fc6" +} +layer { + name: "drop6" + type: "Dropout" + bottom: "fc6" + top: "fc6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc8" + type: "InnerProduct" + bottom: "fc6" + top: "fc8" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "accuracy" + type: "Accuracy" + bottom: "fc8" + bottom: "label" + top: "accuracy" + include { + stage: "val" + } +} +layer { + name: "loss" + type: "SoftmaxWithLoss" + bottom: "fc8" + bottom: "label" + top: "loss" + exclude { + stage: "deploy" + } +} +layer { + name: "softmax" + type: "Softmax" + bottom: "fc8" + top: "softmax" + include { + stage: "deploy" + } +} diff --git a/cars/architecture-investigations/fc/1-layer/256/pred.csv b/cars/architecture-investigations/fc/1-layer/256/pred.csv new file mode 100644 index 0000000..b23ae9a --- /dev/null +++ b/cars/architecture-investigations/fc/1-layer/256/pred.csv @@ -0,0 +1,1619 @@ +1 /scratch/Teaching/cars/car_ims/012117.jpg Jeep Grand Cherokee SUV 2012 Jeep Compass SUV 2012 57.89% Jeep Grand Cherokee SUV 2012 35.51% BMW X3 SUV 2012 6.07% Mazda Tribute SUV 2011 0.32% BMW X6 SUV 2012 0.09% +2 /scratch/Teaching/cars/car_ims/008738.jpg Ford Mustang Convertible 2007 Eagle Talon Hatchback 1998 47.01% Chevrolet Malibu Hybrid Sedan 2010 10.36% Chevrolet Monte Carlo Coupe 2007 9.8% Acura Integra Type R 2001 6.4% Audi V8 Sedan 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25.62% Audi S4 Sedan 2012 6.77% Audi A5 Coupe 2012 0.34% Audi RS 4 Convertible 2008 0.02% +12 /scratch/Teaching/cars/car_ims/004557.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Spyker C8 Coupe 2009 60.68% Chevrolet Corvette Ron Fellows Edition Z06 2007 31.4% Nissan 240SX Coupe 1998 1.74% Ferrari 458 Italia Coupe 2012 1.17% Chevrolet Camaro Convertible 2012 0.82% +13 /scratch/Teaching/cars/car_ims/004311.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 72.55% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 12.39% HUMMER H3T Crew Cab 2010 5.71% Chevrolet Silverado 1500 Extended Cab 2012 5.2% Chevrolet Silverado 2500HD Regular Cab 2012 2.96% +14 /scratch/Teaching/cars/car_ims/006145.jpg Chrysler Aspen SUV 2009 Chrysler Aspen SUV 2009 99.7% Jeep Liberty SUV 2012 0.13% Dodge Durango SUV 2007 0.11% Isuzu Ascender SUV 2008 0.03% Jeep Patriot SUV 2012 0.01% +15 /scratch/Teaching/cars/car_ims/012832.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 45.92% Daewoo Nubira Wagon 2002 17.75% Chevrolet Malibu Sedan 2007 15.92% Ford Focus Sedan 2007 12.18% Chrysler Sebring Convertible 2010 4.9% +16 /scratch/Teaching/cars/car_ims/006057.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 65.14% Dodge Dakota Club Cab 2007 34.28% Chevrolet Silverado 1500 Extended Cab 2012 0.29% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.23% Chevrolet Silverado 2500HD Regular Cab 2012 0.02% +17 /scratch/Teaching/cars/car_ims/005195.jpg Chevrolet Avalanche Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 97.97% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.74% Chevrolet Silverado 2500HD Regular Cab 2012 0.52% Volvo C30 Hatchback 2012 0.35% GMC Canyon Extended Cab 2012 0.2% +18 /scratch/Teaching/cars/car_ims/013970.jpg Nissan Juke Hatchback 2012 Mazda Tribute SUV 2011 88.09% Nissan Juke Hatchback 2012 11.45% smart fortwo Convertible 2012 0.17% Hyundai Veracruz SUV 2012 0.12% Suzuki SX4 Hatchback 2012 0.05% +19 /scratch/Teaching/cars/car_ims/000910.jpg Audi RS 4 Convertible 2008 Audi S4 Sedan 2007 53.25% Audi S5 Convertible 2012 43.84% Porsche Panamera Sedan 2012 1.38% BMW 3 Series Wagon 2012 0.34% BMW M5 Sedan 2010 0.33% +20 /scratch/Teaching/cars/car_ims/008161.jpg FIAT 500 Convertible 2012 FIAT 500 Convertible 2012 99.86% Bentley Continental Supersports Conv. Convertible 2012 0.13% MINI Cooper Roadster Convertible 2012 0.02% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.0% Maybach Landaulet Convertible 2012 0.0% +21 /scratch/Teaching/cars/car_ims/001019.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 99.59% Audi S5 Coupe 2012 0.38% Audi S4 Sedan 2012 0.02% Audi TTS Coupe 2012 0.01% Audi S5 Convertible 2012 0.0% +22 /scratch/Teaching/cars/car_ims/002588.jpg BMW X5 SUV 2007 Volvo XC90 SUV 2007 31.29% Mazda Tribute SUV 2011 27.24% Hyundai Veracruz SUV 2012 14.96% Buick Enclave SUV 2012 7.26% BMW X5 SUV 2007 2.87% +23 /scratch/Teaching/cars/car_ims/004884.jpg Chevrolet Impala Sedan 2007 Dodge Caravan Minivan 1997 77.67% Chevrolet Impala Sedan 2007 19.53% Chevrolet Monte Carlo Coupe 2007 2.7% Geo Metro Convertible 1993 0.06% Lincoln Town Car Sedan 2011 0.02% +24 /scratch/Teaching/cars/car_ims/001972.jpg Audi S4 Sedan 2007 Suzuki Aerio Sedan 2007 55.1% Audi S4 Sedan 2007 34.0% BMW 1 Series Convertible 2012 4.47% Mitsubishi Lancer Sedan 2012 1.63% BMW 3 Series Wagon 2012 1.1% +25 /scratch/Teaching/cars/car_ims/001030.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 88.17% Audi S5 Convertible 2012 11.43% Audi S5 Coupe 2012 0.36% Audi RS 4 Convertible 2008 0.02% Audi TT Hatchback 2011 0.02% +26 /scratch/Teaching/cars/car_ims/002376.jpg BMW 3 Series Wagon 2012 BMW 3 Series Wagon 2012 99.14% Bentley Arnage Sedan 2009 0.28% Bentley Mulsanne Sedan 2011 0.21% Volvo XC90 SUV 2007 0.09% Land Rover Range Rover SUV 2012 0.07% +27 /scratch/Teaching/cars/car_ims/009940.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 77.85% Mazda Tribute SUV 2011 21.26% Land Rover LR2 SUV 2012 0.65% BMW X3 SUV 2012 0.12% Infiniti QX56 SUV 2011 0.04% +28 /scratch/Teaching/cars/car_ims/012396.jpg Lamborghini Aventador Coupe 2012 Lamborghini Aventador Coupe 2012 99.98% Ferrari FF Coupe 2012 0.02% McLaren MP4-12C Coupe 2012 0.0% Ferrari California Convertible 2012 0.0% Ford GT Coupe 2006 0.0% +29 /scratch/Teaching/cars/car_ims/006287.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 98.16% Cadillac Escalade EXT Crew Cab 2007 1.14% Dodge Caliber Wagon 2012 0.2% Chrysler PT Cruiser Convertible 2008 0.17% GMC Yukon Hybrid SUV 2012 0.14% +30 /scratch/Teaching/cars/car_ims/006286.jpg Chrysler Town and Country Minivan 2012 Ram C/V Cargo Van Minivan 2012 86.34% Chrysler Town and Country Minivan 2012 13.65% Honda Odyssey Minivan 2007 0.01% Suzuki SX4 Sedan 2012 0.0% Daewoo Nubira Wagon 2002 0.0% +31 /scratch/Teaching/cars/car_ims/001090.jpg Audi TTS Coupe 2012 Audi S5 Convertible 2012 86.34% Audi A5 Coupe 2012 8.95% Audi TTS Coupe 2012 3.56% Audi S4 Sedan 2012 0.52% Audi RS 4 Convertible 2008 0.27% +32 /scratch/Teaching/cars/car_ims/003162.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental Supersports Conv. Convertible 2012 99.99% Maybach Landaulet Convertible 2012 0.0% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Acura Integra Type R 2001 0.0% Bentley Continental Flying Spur Sedan 2007 0.0% +33 /scratch/Teaching/cars/car_ims/009978.jpg GMC Canyon Extended Cab 2012 GMC Canyon Extended Cab 2012 94.92% Chevrolet Silverado 1500 Regular Cab 2012 4.21% Dodge Ram Pickup 3500 Quad Cab 2009 0.4% Chevrolet Silverado 1500 Extended Cab 2012 0.23% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.09% +34 /scratch/Teaching/cars/car_ims/013824.jpg Nissan Leaf Hatchback 2012 Geo Metro Convertible 1993 37.05% Chevrolet Malibu Sedan 2007 26.25% Nissan Leaf Hatchback 2012 11.1% Ford Fiesta Sedan 2012 10.01% smart fortwo Convertible 2012 8.52% +35 /scratch/Teaching/cars/car_ims/003698.jpg Bugatti Veyron 16.4 Coupe 2009 Bugatti Veyron 16.4 Coupe 2009 62.27% Lamborghini Aventador Coupe 2012 34.35% Audi R8 Coupe 2012 1.07% Aston Martin V8 Vantage Coupe 2012 0.83% McLaren MP4-12C Coupe 2012 0.73% +36 /scratch/Teaching/cars/car_ims/007674.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 96.88% Hyundai Santa Fe SUV 2012 2.16% Toyota 4Runner SUV 2012 0.56% Chevrolet Traverse SUV 2012 0.29% Toyota Camry Sedan 2012 0.07% +37 /scratch/Teaching/cars/car_ims/012705.jpg Land Rover LR2 SUV 2012 GMC Terrain SUV 2012 76.61% Land Rover LR2 SUV 2012 22.7% Land Rover Range Rover SUV 2012 0.23% Chevrolet Silverado 1500 Regular Cab 2012 0.15% MINI Cooper Roadster Convertible 2012 0.1% +38 /scratch/Teaching/cars/car_ims/007644.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 99.99% Dodge Journey SUV 2012 0.01% Dodge Dakota Crew Cab 2010 0.0% Hyundai Santa Fe SUV 2012 0.0% Toyota Sequoia SUV 2012 0.0% +39 /scratch/Teaching/cars/car_ims/007457.jpg Dodge Dakota Club Cab 2007 Dodge Dakota Club Cab 2007 99.98% Ford Ranger SuperCab 2011 0.01% Ford F-150 Regular Cab 2007 0.01% Dodge Dakota Crew Cab 2010 0.0% Chevrolet Silverado 1500 Extended Cab 2012 0.0% +40 /scratch/Teaching/cars/car_ims/005424.jpg Chevrolet Malibu Hybrid Sedan 2010 BMW 3 Series Sedan 2012 48.49% BMW X6 SUV 2012 34.09% Volvo C30 Hatchback 2012 5.15% Dodge Caliber Wagon 2007 4.01% Mitsubishi Lancer Sedan 2012 3.42% +41 /scratch/Teaching/cars/car_ims/003712.jpg Bugatti Veyron 16.4 Coupe 2009 Chrysler 300 SRT-8 2010 47.48% Bugatti Veyron 16.4 Coupe 2009 15.95% Lamborghini Reventon Coupe 2008 14.87% Ferrari FF Coupe 2012 11.36% Porsche Panamera Sedan 2012 2.26% +42 /scratch/Teaching/cars/car_ims/007814.jpg Dodge Charger Sedan 2012 Dodge Charger Sedan 2012 89.27% Dodge Charger SRT-8 2009 7.52% Cadillac CTS-V Sedan 2012 0.86% Dodge Magnum Wagon 2008 0.69% Chevrolet Sonic Sedan 2012 0.62% +43 /scratch/Teaching/cars/car_ims/015765.jpg Volkswagen Beetle Hatchback 2012 Spyker C8 Convertible 2009 23.81% Cadillac CTS-V Sedan 2012 17.99% Bentley Continental Flying Spur Sedan 2007 13.67% Suzuki Kizashi Sedan 2012 12.83% Bentley Continental GT Coupe 2012 10.17% +44 /scratch/Teaching/cars/car_ims/012091.jpg Jeep Liberty SUV 2012 Isuzu Ascender SUV 2008 55.87% Cadillac Escalade EXT Crew Cab 2007 22.86% GMC Yukon Hybrid SUV 2012 11.34% Chrysler Aspen SUV 2009 2.29% Chevrolet Avalanche Crew Cab 2012 1.86% +45 /scratch/Teaching/cars/car_ims/015546.jpg Toyota 4Runner SUV 2012 Land Rover LR2 SUV 2012 95.66% Infiniti QX56 SUV 2011 1.4% Toyota 4Runner SUV 2012 1.03% Ford Edge SUV 2012 1.03% Ford Expedition EL SUV 2009 0.19% +46 /scratch/Teaching/cars/car_ims/012984.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 30.64% smart fortwo Convertible 2012 26.07% FIAT 500 Convertible 2012 11.89% Bugatti Veyron 16.4 Convertible 2009 6.1% Rolls-Royce Phantom Drophead Coupe Convertible 2012 5.76% +47 /scratch/Teaching/cars/car_ims/007744.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 82.24% Dodge Caliber Wagon 2012 17.68% Dodge Durango SUV 2012 0.04% Chrysler PT Cruiser Convertible 2008 0.02% Dodge Caliber Wagon 2007 0.01% +48 /scratch/Teaching/cars/car_ims/001459.jpg Audi 100 Wagon 1994 Audi 100 Wagon 1994 62.95% Daewoo Nubira Wagon 2002 34.73% Audi 100 Sedan 1994 2.21% Audi V8 Sedan 1994 0.09% Dodge Caravan Minivan 1997 0.01% +49 /scratch/Teaching/cars/car_ims/004803.jpg Chevrolet Camaro Convertible 2012 Dodge Charger Sedan 2012 65.75% Dodge Charger SRT-8 2009 34.05% Chevrolet Camaro Convertible 2012 0.18% Dodge Challenger SRT8 2011 0.01% Dodge Magnum Wagon 2008 0.0% +50 /scratch/Teaching/cars/car_ims/013803.jpg Nissan Leaf Hatchback 2012 Nissan Leaf Hatchback 2012 99.98% Ford Fiesta Sedan 2012 0.01% Acura ZDX Hatchback 2012 0.01% Hyundai Sonata Sedan 2012 0.0% Toyota Camry Sedan 2012 0.0% +51 /scratch/Teaching/cars/car_ims/009797.jpg GMC Yukon Hybrid SUV 2012 Chevrolet Avalanche Crew Cab 2012 63.23% Dodge Dakota Club Cab 2007 26.27% Chrysler Aspen SUV 2009 8.34% Ford Freestar Minivan 2007 0.58% Chevrolet Silverado 1500 Extended Cab 2012 0.54% +52 /scratch/Teaching/cars/car_ims/014728.jpg Spyker C8 Convertible 2009 Bugatti Veyron 16.4 Coupe 2009 93.3% Lamborghini Aventador Coupe 2012 3.99% Lamborghini Reventon Coupe 2008 1.09% Chevrolet Corvette ZR1 2012 0.77% Audi R8 Coupe 2012 0.46% +53 /scratch/Teaching/cars/car_ims/007389.jpg Dodge Dakota Club Cab 2007 Dodge Ram Pickup 3500 Quad Cab 2009 47.44% Dodge Dakota Club Cab 2007 39.99% Chevrolet Silverado 1500 Classic Extended Cab 2007 6.08% Chevrolet Silverado 1500 Extended Cab 2012 5.34% Ford Ranger SuperCab 2011 0.53% +54 /scratch/Teaching/cars/car_ims/011599.jpg Infiniti G Coupe IPL 2012 Mitsubishi Lancer Sedan 2012 41.4% Chevrolet Malibu Hybrid Sedan 2010 34.66% BMW 6 Series Convertible 2007 17.38% Infiniti G Coupe IPL 2012 3.5% Acura TL Type-S 2008 1.19% +55 /scratch/Teaching/cars/car_ims/006305.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 99.68% Buick Verano Sedan 2012 0.12% Chevrolet Malibu Hybrid Sedan 2010 0.08% Dodge Magnum Wagon 2008 0.05% Ford Freestar Minivan 2007 0.03% +56 /scratch/Teaching/cars/car_ims/010055.jpg GMC Savana Van 2012 GMC Savana Van 2012 99.5% Chevrolet Express Cargo Van 2007 0.27% Chevrolet Express Van 2007 0.23% Volkswagen Golf Hatchback 1991 0.0% Audi V8 Sedan 1994 0.0% +57 /scratch/Teaching/cars/car_ims/014172.jpg Plymouth Neon Coupe 1999 Audi 100 Wagon 1994 37.53% Audi V8 Sedan 1994 16.1% Volkswagen Golf Hatchback 1991 16.01% Volvo 240 Sedan 1993 15.37% Volvo XC90 SUV 2007 8.68% +58 /scratch/Teaching/cars/car_ims/004832.jpg Chevrolet HHR SS 2010 Chevrolet HHR SS 2010 99.99% Dodge Magnum Wagon 2008 0.01% Dodge Journey SUV 2012 0.0% Dodge Charger SRT-8 2009 0.0% Volkswagen Beetle Hatchback 2012 0.0% +59 /scratch/Teaching/cars/car_ims/001935.jpg Audi S4 Sedan 2007 Audi S4 Sedan 2007 72.85% Suzuki Kizashi Sedan 2012 13.27% Mitsubishi Lancer Sedan 2012 9.92% Volvo C30 Hatchback 2012 2.45% Audi A5 Coupe 2012 1.15% +60 /scratch/Teaching/cars/car_ims/014928.jpg Suzuki Kizashi Sedan 2012 Mitsubishi Lancer Sedan 2012 55.55% Suzuki SX4 Sedan 2012 20.12% Suzuki Aerio Sedan 2007 15.82% Suzuki Kizashi Sedan 2012 7.33% BMW 1 Series Convertible 2012 0.72% +61 /scratch/Teaching/cars/car_ims/008224.jpg Ferrari FF Coupe 2012 Aston Martin V8 Vantage Convertible 2012 30.31% Aston Martin V8 Vantage Coupe 2012 21.32% Jaguar XK XKR 2012 20.58% Chevrolet Corvette Convertible 2012 6.63% BMW M5 Sedan 2010 3.66% +62 /scratch/Teaching/cars/car_ims/005419.jpg Chevrolet Malibu Hybrid Sedan 2010 Chevrolet Malibu Hybrid Sedan 2010 74.91% Chevrolet Cobalt SS 2010 24.81% Jaguar XK XKR 2012 0.15% Audi S4 Sedan 2007 0.07% Chevrolet HHR SS 2010 0.03% +63 /scratch/Teaching/cars/car_ims/000617.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin Virage Convertible 2012 48.97% Fisker Karma Sedan 2012 21.94% Aston Martin V8 Vantage Coupe 2012 13.05% Aston Martin V8 Vantage Convertible 2012 11.01% Lamborghini Reventon Coupe 2008 2.48% +64 /scratch/Teaching/cars/car_ims/004587.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 99.77% Chevrolet Corvette ZR1 2012 0.12% Chevrolet Camaro Convertible 2012 0.09% Chevrolet Corvette Convertible 2012 0.02% Jaguar XK XKR 2012 0.0% +65 /scratch/Teaching/cars/car_ims/014717.jpg Spyker C8 Convertible 2009 Hyundai Veloster Hatchback 2012 82.51% Spyker C8 Coupe 2009 15.18% Volvo C30 Hatchback 2012 0.72% Spyker C8 Convertible 2009 0.72% Audi TTS Coupe 2012 0.47% +66 /scratch/Teaching/cars/car_ims/014933.jpg Suzuki Kizashi Sedan 2012 Suzuki Aerio Sedan 2007 18.8% Hyundai Sonata Hybrid Sedan 2012 16.69% Toyota Camry Sedan 2012 14.03% Chevrolet Malibu Hybrid Sedan 2010 10.85% Scion xD Hatchback 2012 9.92% +67 /scratch/Teaching/cars/car_ims/015065.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Sedan 2012 31.36% Honda Accord Sedan 2012 18.44% Suzuki SX4 Hatchback 2012 15.85% Scion xD Hatchback 2012 15.55% Acura ZDX Hatchback 2012 9.01% +68 /scratch/Teaching/cars/car_ims/002362.jpg BMW 3 Series Wagon 2012 Mercedes-Benz C-Class Sedan 2012 15.97% BMW 3 Series Wagon 2012 11.72% Audi S6 Sedan 2011 10.22% Hyundai Veracruz SUV 2012 9.25% Audi RS 4 Convertible 2008 7.02% +69 /scratch/Teaching/cars/car_ims/001718.jpg Audi S5 Convertible 2012 Audi S6 Sedan 2011 66.45% Audi S5 Convertible 2012 16.99% Audi RS 4 Convertible 2008 12.33% Audi S5 Coupe 2012 3.9% Audi S4 Sedan 2012 0.22% +70 /scratch/Teaching/cars/car_ims/007698.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 99.4% Dodge Dakota Crew Cab 2010 0.56% Dodge Journey SUV 2012 0.02% Dodge Magnum Wagon 2008 0.01% Dodge Charger SRT-8 2009 0.01% +71 /scratch/Teaching/cars/car_ims/006352.jpg Chrysler 300 SRT-8 2010 Chrysler 300 SRT-8 2010 100.0% Ford Mustang Convertible 2007 0.0% Chevrolet Corvette ZR1 2012 0.0% Rolls-Royce Phantom Sedan 2012 0.0% Dodge Charger SRT-8 2009 0.0% +72 /scratch/Teaching/cars/car_ims/008545.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 42.48% Spyker C8 Convertible 2009 37.36% Aston Martin V8 Vantage Convertible 2012 10.16% Aston Martin V8 Vantage Coupe 2012 2.14% Dodge Charger SRT-8 2009 1.93% +73 /scratch/Teaching/cars/car_ims/000555.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 95.71% Hyundai Veracruz SUV 2012 3.09% Chevrolet Traverse SUV 2012 0.98% Chevrolet Malibu Sedan 2007 0.1% Chevrolet Malibu Hybrid Sedan 2010 0.04% +74 /scratch/Teaching/cars/car_ims/010155.jpg Geo Metro Convertible 1993 Volvo 240 Sedan 1993 97.99% Volkswagen Golf Hatchback 1991 0.71% Chrysler Aspen SUV 2009 0.58% Audi 100 Wagon 1994 0.52% Mercedes-Benz 300-Class Convertible 1993 0.14% +75 /scratch/Teaching/cars/car_ims/006070.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 98.34% Chevrolet Silverado 1500 Extended Cab 2012 1.48% Chevrolet Silverado 1500 Regular Cab 2012 0.13% Chevrolet Silverado 2500HD Regular Cab 2012 0.02% Chevrolet Avalanche Crew Cab 2012 0.02% +76 /scratch/Teaching/cars/car_ims/010758.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 92.29% Hyundai Genesis Sedan 2012 6.69% Honda Accord Sedan 2012 0.6% Hyundai Sonata Sedan 2012 0.13% Mercedes-Benz C-Class Sedan 2012 0.12% +77 /scratch/Teaching/cars/car_ims/014203.jpg Porsche Panamera Sedan 2012 Spyker C8 Convertible 2009 51.2% Infiniti G Coupe IPL 2012 24.81% Chrysler 300 SRT-8 2010 7.0% Dodge Charger SRT-8 2009 3.24% Cadillac CTS-V Sedan 2012 3.2% +78 /scratch/Teaching/cars/car_ims/006788.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2012 84.22% Dodge Caliber Wagon 2007 13.81% BMW X3 SUV 2012 1.71% Jeep Compass SUV 2012 0.24% Dodge Journey SUV 2012 0.01% +79 /scratch/Teaching/cars/car_ims/005775.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Monte Carlo Coupe 2007 98.55% Chevrolet Cobalt SS 2010 1.0% Geo Metro Convertible 1993 0.15% Chevrolet Impala Sedan 2007 0.14% Chevrolet Malibu Sedan 2007 0.07% +80 /scratch/Teaching/cars/car_ims/013231.jpg Mercedes-Benz 300-Class Convertible 1993 Mercedes-Benz 300-Class Convertible 1993 100.0% Audi 100 Wagon 1994 0.0% Audi 100 Sedan 1994 0.0% BMW 6 Series Convertible 2007 0.0% BMW M6 Convertible 2010 0.0% +81 /scratch/Teaching/cars/car_ims/006212.jpg Chrysler Sebring Convertible 2010 Chrysler Crossfire Convertible 2008 89.33% Chrysler Sebring Convertible 2010 10.67% Chrysler PT Cruiser Convertible 2008 0.0% Mercedes-Benz S-Class Sedan 2012 0.0% Hyundai Genesis Sedan 2012 0.0% +82 /scratch/Teaching/cars/car_ims/003269.jpg Bentley Mulsanne Sedan 2011 Bentley Mulsanne Sedan 2011 99.92% Bentley Continental Supersports Conv. Convertible 2012 0.06% Rolls-Royce Phantom Sedan 2012 0.01% Bentley Arnage Sedan 2009 0.0% Bentley Continental GT Coupe 2012 0.0% +83 /scratch/Teaching/cars/car_ims/000569.jpg Acura ZDX Hatchback 2012 Hyundai Veracruz SUV 2012 98.73% Hyundai Tucson SUV 2012 0.93% Chevrolet Traverse SUV 2012 0.28% BMW X6 SUV 2012 0.05% Hyundai Santa Fe SUV 2012 0.01% +84 /scratch/Teaching/cars/car_ims/013843.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 100.0% Ford F-150 Regular Cab 2012 0.0% Ford F-150 Regular Cab 2007 0.0% Volvo XC90 SUV 2007 0.0% Ford E-Series Wagon Van 2012 0.0% +85 /scratch/Teaching/cars/car_ims/002828.jpg BMW M5 Sedan 2010 BMW M5 Sedan 2010 71.16% BMW M3 Coupe 2012 24.81% BMW 3 Series Wagon 2012 2.37% Infiniti G Coupe IPL 2012 0.59% BMW 1 Series Coupe 2012 0.32% +86 /scratch/Teaching/cars/car_ims/015020.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 99.98% Chevrolet Traverse SUV 2012 0.01% Hyundai Tucson SUV 2012 0.0% Suzuki SX4 Sedan 2012 0.0% Dodge Journey SUV 2012 0.0% +87 /scratch/Teaching/cars/car_ims/007528.jpg Dodge Magnum Wagon 2008 Dodge Magnum Wagon 2008 99.74% Chrysler 300 SRT-8 2010 0.07% Chevrolet HHR SS 2010 0.07% Chevrolet Monte Carlo Coupe 2007 0.05% Chevrolet Cobalt SS 2010 0.02% +88 /scratch/Teaching/cars/car_ims/001985.jpg Audi TT RS Coupe 2012 Audi S5 Convertible 2012 61.2% Audi TT Hatchback 2011 20.06% Audi TT RS Coupe 2012 6.0% Audi TTS Coupe 2012 3.28% BMW 1 Series Convertible 2012 3.23% +89 /scratch/Teaching/cars/car_ims/002403.jpg BMW 3 Series Wagon 2012 Bugatti Veyron 16.4 Coupe 2009 52.34% Ferrari 458 Italia Coupe 2012 31.05% Chevrolet Corvette ZR1 2012 4.67% Jaguar XK XKR 2012 4.24% Spyker C8 Convertible 2009 2.03% +90 /scratch/Teaching/cars/car_ims/014148.jpg Plymouth Neon Coupe 1999 Mercedes-Benz 300-Class Convertible 1993 66.17% Ford Mustang Convertible 2007 16.44% Audi V8 Sedan 1994 14.67% Audi RS 4 Convertible 2008 1.02% Eagle Talon Hatchback 1998 0.53% +91 /scratch/Teaching/cars/car_ims/004645.jpg Chevrolet Traverse SUV 2012 Ford GT Coupe 2006 73.43% Lamborghini Gallardo LP 570-4 Superleggera 2012 14.25% Lamborghini Diablo Coupe 2001 9.32% Spyker C8 Convertible 2009 2.05% Lamborghini Reventon Coupe 2008 0.31% +92 /scratch/Teaching/cars/car_ims/007318.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 29.98% GMC Canyon Extended Cab 2012 29.17% Dodge Durango SUV 2007 11.4% Chevrolet TrailBlazer SS 2009 8.34% Chevrolet Silverado 1500 Classic Extended Cab 2007 6.01% +93 /scratch/Teaching/cars/car_ims/001070.jpg Audi TTS Coupe 2012 Audi S5 Coupe 2012 77.21% Audi A5 Coupe 2012 14.95% Audi S4 Sedan 2007 5.35% Audi TTS Coupe 2012 1.56% Audi S5 Convertible 2012 0.49% +94 /scratch/Teaching/cars/car_ims/004489.jpg Chevrolet Corvette ZR1 2012 Chevrolet Corvette ZR1 2012 83.37% Ford GT Coupe 2006 8.47% Bugatti Veyron 16.4 Coupe 2009 2.94% Spyker C8 Convertible 2009 2.21% FIAT 500 Abarth 2012 0.94% +95 /scratch/Teaching/cars/car_ims/013414.jpg Mercedes-Benz E-Class Sedan 2012 BMW M6 Convertible 2010 57.33% BMW 6 Series Convertible 2007 16.2% Mercedes-Benz 300-Class Convertible 1993 13.51% Audi RS 4 Convertible 2008 6.41% Dodge Charger Sedan 2012 1.84% +96 /scratch/Teaching/cars/car_ims/008628.jpg Ford F-450 Super Duty Crew Cab 2012 AM General Hummer SUV 2000 48.6% Ford F-450 Super Duty Crew Cab 2012 16.59% HUMMER H2 SUT Crew Cab 2009 15.35% Ford F-150 Regular Cab 2007 6.5% Chevrolet Corvette ZR1 2012 4.44% +97 /scratch/Teaching/cars/car_ims/012921.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 100.0% Cadillac CTS-V Sedan 2012 0.0% Porsche Panamera Sedan 2012 0.0% Bentley Mulsanne Sedan 2011 0.0% Chevrolet Camaro Convertible 2012 0.0% +98 /scratch/Teaching/cars/car_ims/005304.jpg Chevrolet Cobalt SS 2010 Acura Integra Type R 2001 82.44% Chevrolet Corvette Convertible 2012 14.24% Lamborghini Diablo Coupe 2001 2.31% Geo Metro Convertible 1993 0.92% Ferrari 458 Italia Convertible 2012 0.05% +99 /scratch/Teaching/cars/car_ims/000951.jpg Audi RS 4 Convertible 2008 Audi RS 4 Convertible 2008 48.38% Audi S5 Convertible 2012 46.94% BMW M6 Convertible 2010 3.85% BMW 1 Series Convertible 2012 0.62% Mercedes-Benz 300-Class Convertible 1993 0.18% +100 /scratch/Teaching/cars/car_ims/006517.jpg Chrysler Crossfire Convertible 2008 Chrysler Sebring Convertible 2010 75.17% Chrysler Crossfire Convertible 2008 21.99% Chevrolet Camaro Convertible 2012 1.52% Chrysler PT Cruiser Convertible 2008 1.04% Mercedes-Benz S-Class Sedan 2012 0.2% +101 /scratch/Teaching/cars/car_ims/007067.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 99.96% Dodge Dakota Club Cab 2007 0.02% Dodge Ram Pickup 3500 Crew Cab 2010 0.01% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% Ford F-150 Regular Cab 2012 0.0% +102 /scratch/Teaching/cars/car_ims/013445.jpg Mercedes-Benz E-Class Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 52.35% BMW M3 Coupe 2012 43.93% BMW M5 Sedan 2010 2.78% BMW 3 Series Wagon 2012 0.41% Audi S6 Sedan 2011 0.37% +103 /scratch/Teaching/cars/car_ims/005331.jpg Chevrolet Cobalt SS 2010 Porsche Panamera Sedan 2012 24.4% Chevrolet Corvette ZR1 2012 19.33% Audi TTS Coupe 2012 13.52% Infiniti G Coupe IPL 2012 8.33% Audi S5 Convertible 2012 5.06% +104 /scratch/Teaching/cars/car_ims/005569.jpg Chevrolet Silverado 2500HD Regular Cab 2012 AM General Hummer SUV 2000 39.53% HUMMER H2 SUT Crew Cab 2009 25.55% Chevrolet Silverado 1500 Extended Cab 2012 22.56% HUMMER H3T Crew Cab 2010 5.02% Chevrolet Silverado 1500 Regular Cab 2012 2.3% +105 /scratch/Teaching/cars/car_ims/011571.jpg Infiniti G Coupe IPL 2012 Infiniti G Coupe IPL 2012 100.0% Acura TL Type-S 2008 0.0% Suzuki Kizashi Sedan 2012 0.0% Toyota Camry Sedan 2012 0.0% Mercedes-Benz S-Class Sedan 2012 0.0% +106 /scratch/Teaching/cars/car_ims/015756.jpg Volkswagen Golf Hatchback 1991 Mercedes-Benz 300-Class Convertible 1993 57.2% Chrysler Crossfire Convertible 2008 18.22% Dodge Dakota Crew Cab 2010 7.86% Dodge Magnum Wagon 2008 3.75% Volkswagen Golf Hatchback 1991 2.84% +107 /scratch/Teaching/cars/car_ims/001231.jpg Audi V8 Sedan 1994 Audi V8 Sedan 1994 99.98% Audi 100 Sedan 1994 0.02% Volkswagen Golf Hatchback 1991 0.0% Audi 100 Wagon 1994 0.0% Nissan 240SX Coupe 1998 0.0% +108 /scratch/Teaching/cars/car_ims/004435.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Ron Fellows Edition Z06 2007 87.24% Bugatti Veyron 16.4 Convertible 2009 3.03% Bentley Continental Supersports Conv. Convertible 2012 3.0% Ferrari 458 Italia Convertible 2012 2.79% MINI Cooper Roadster Convertible 2012 0.92% +109 /scratch/Teaching/cars/car_ims/006110.jpg Chrysler Aspen SUV 2009 Chrysler Aspen SUV 2009 100.0% Dodge Durango SUV 2007 0.0% Dodge Dakota Crew Cab 2010 0.0% Ford Freestar Minivan 2007 0.0% GMC Canyon Extended Cab 2012 0.0% +110 /scratch/Teaching/cars/car_ims/012879.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 100.0% Bugatti Veyron 16.4 Convertible 2009 0.0% Bentley Continental Supersports Conv. Convertible 2012 0.0% Spyker C8 Convertible 2009 0.0% Spyker C8 Coupe 2009 0.0% +111 /scratch/Teaching/cars/car_ims/015062.jpg Suzuki SX4 Hatchback 2012 Volvo XC90 SUV 2007 38.02% Jeep Compass SUV 2012 28.16% Jeep Patriot SUV 2012 4.72% Jeep Grand Cherokee SUV 2012 4.46% Chevrolet Traverse SUV 2012 4.23% +112 /scratch/Teaching/cars/car_ims/009405.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 100.0% Plymouth Neon Coupe 1999 0.0% Suzuki Aerio Sedan 2007 0.0% Daewoo Nubira Wagon 2002 0.0% Hyundai Elantra Touring Hatchback 2012 0.0% +113 /scratch/Teaching/cars/car_ims/012882.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 100.0% Bentley Mulsanne Sedan 2011 0.0% FIAT 500 Convertible 2012 0.0% Bentley Continental Supersports Conv. Convertible 2012 0.0% smart fortwo Convertible 2012 0.0% +114 /scratch/Teaching/cars/car_ims/010887.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 42.06% Hyundai Veracruz SUV 2012 29.08% Chevrolet Traverse SUV 2012 16.93% Buick Enclave SUV 2012 10.49% Hyundai Elantra Touring Hatchback 2012 0.54% +115 /scratch/Teaching/cars/car_ims/000441.jpg Acura Integra Type R 2001 Chevrolet Cobalt SS 2010 43.91% Lamborghini Diablo Coupe 2001 19.42% Chevrolet Corvette Convertible 2012 17.21% Acura Integra Type R 2001 15.92% Chevrolet Corvette ZR1 2012 1.1% +116 /scratch/Teaching/cars/car_ims/010536.jpg Honda Accord Coupe 2012 Honda Accord Sedan 2012 77.15% Honda Accord Coupe 2012 17.21% Acura RL Sedan 2012 2.91% Hyundai Genesis Sedan 2012 2.61% Acura TSX Sedan 2012 0.11% +117 /scratch/Teaching/cars/car_ims/013656.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 48.02% Dodge Sprinter Cargo Van 2009 40.88% Ram C/V Cargo Van Minivan 2012 9.47% Mercedes-Benz SL-Class Coupe 2009 0.56% Nissan NV Passenger Van 2012 0.24% +118 /scratch/Teaching/cars/car_ims/009218.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 50.9% Ford F-450 Super Duty Crew Cab 2012 49.1% Ford E-Series Wagon Van 2012 0.0% Ford Ranger SuperCab 2011 0.0% Ford F-150 Regular Cab 2007 0.0% +119 /scratch/Teaching/cars/car_ims/015198.jpg Tesla Model S Sedan 2012 Bugatti Veyron 16.4 Convertible 2009 78.46% Bugatti Veyron 16.4 Coupe 2009 10.28% smart fortwo Convertible 2012 3.73% Spyker C8 Convertible 2009 2.52% Spyker C8 Coupe 2009 1.81% +120 /scratch/Teaching/cars/car_ims/008421.jpg Ferrari 458 Italia Coupe 2012 FIAT 500 Abarth 2012 99.97% Lamborghini Aventador Coupe 2012 0.01% Bugatti Veyron 16.4 Coupe 2009 0.01% Chevrolet Corvette ZR1 2012 0.01% Spyker C8 Convertible 2009 0.0% +121 /scratch/Teaching/cars/car_ims/013496.jpg Mercedes-Benz S-Class Sedan 2012 Mercedes-Benz E-Class Sedan 2012 86.1% Mercedes-Benz S-Class Sedan 2012 13.11% Audi RS 4 Convertible 2008 0.2% Suzuki Kizashi Sedan 2012 0.16% Chrysler Crossfire Convertible 2008 0.11% +122 /scratch/Teaching/cars/car_ims/009437.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 96.73% Plymouth Neon Coupe 1999 3.27% Hyundai Elantra Touring Hatchback 2012 0.0% Suzuki Aerio Sedan 2007 0.0% Chrysler Sebring Convertible 2010 0.0% +123 /scratch/Teaching/cars/car_ims/012516.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 Lamborghini Gallardo LP 570-4 Superleggera 2012 100.0% Hyundai Veloster Hatchback 2012 0.0% smart fortwo Convertible 2012 0.0% Bentley Continental Supersports Conv. Convertible 2012 0.0% Spyker C8 Coupe 2009 0.0% +124 /scratch/Teaching/cars/car_ims/015679.jpg Volkswagen Golf Hatchback 1991 BMW X5 SUV 2007 52.36% BMW M5 Sedan 2010 29.62% BMW M6 Convertible 2010 14.57% Audi 100 Wagon 1994 3.01% BMW Z4 Convertible 2012 0.12% +125 /scratch/Teaching/cars/car_ims/002639.jpg BMW X6 SUV 2012 Nissan Juke Hatchback 2012 63.07% Spyker C8 Coupe 2009 28.55% Bugatti Veyron 16.4 Coupe 2009 4.66% Mitsubishi Lancer Sedan 2012 1.53% Chevrolet Corvette ZR1 2012 0.49% +126 /scratch/Teaching/cars/car_ims/008918.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 87.57% Land Rover LR2 SUV 2012 11.72% Land Rover Range Rover SUV 2012 0.7% Ford Edge SUV 2012 0.01% Toyota 4Runner SUV 2012 0.0% +127 /scratch/Teaching/cars/car_ims/004135.jpg Cadillac SRX SUV 2012 Ram C/V Cargo Van Minivan 2012 34.84% Chevrolet Traverse SUV 2012 33.7% GMC Acadia SUV 2012 11.13% Chevrolet Malibu Sedan 2007 10.29% Cadillac SRX SUV 2012 4.19% +128 /scratch/Teaching/cars/car_ims/008676.jpg Ford Mustang Convertible 2007 Spyker C8 Convertible 2009 60.96% Ford GT Coupe 2006 9.66% Chevrolet Corvette ZR1 2012 6.03% Bugatti Veyron 16.4 Coupe 2009 5.67% Ford Mustang Convertible 2007 4.74% +129 /scratch/Teaching/cars/car_ims/014637.jpg Scion xD Hatchback 2012 Scion xD Hatchback 2012 100.0% Ford Fiesta Sedan 2012 0.0% Suzuki SX4 Hatchback 2012 0.0% Toyota Corolla Sedan 2012 0.0% Hyundai Tucson SUV 2012 0.0% +130 /scratch/Teaching/cars/car_ims/005759.jpg Chevrolet Monte Carlo Coupe 2007 Suzuki SX4 Sedan 2012 83.81% Chevrolet Monte Carlo Coupe 2007 9.91% Chevrolet Impala Sedan 2007 5.13% Dodge Caliber Wagon 2012 0.71% Suzuki Kizashi Sedan 2012 0.2% +131 /scratch/Teaching/cars/car_ims/001181.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 99.97% Bentley Continental Supersports Conv. Convertible 2012 0.02% Lamborghini Aventador Coupe 2012 0.0% Mercedes-Benz SL-Class Coupe 2009 0.0% Jaguar XK XKR 2012 0.0% +132 /scratch/Teaching/cars/car_ims/016126.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 100.0% FIAT 500 Convertible 2012 0.0% Suzuki SX4 Hatchback 2012 0.0% Hyundai Veloster Hatchback 2012 0.0% Ford Fiesta Sedan 2012 0.0% +133 /scratch/Teaching/cars/car_ims/016061.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 90.61% Jeep Patriot SUV 2012 9.14% Jeep Compass SUV 2012 0.13% Dodge Durango SUV 2007 0.04% GMC Yukon Hybrid SUV 2012 0.03% +134 /scratch/Teaching/cars/car_ims/004335.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Isuzu Ascender SUV 2008 38.5% Ford Ranger SuperCab 2011 27.91% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 18.9% Chevrolet Silverado 1500 Extended Cab 2012 4.44% Chevrolet Silverado 1500 Regular Cab 2012 3.26% +135 /scratch/Teaching/cars/car_ims/006750.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2012 79.68% Dodge Caliber Wagon 2007 19.77% Dodge Durango SUV 2007 0.55% Dodge Durango SUV 2012 0.0% Dodge Magnum Wagon 2008 0.0% +136 /scratch/Teaching/cars/car_ims/000446.jpg Acura Integra Type R 2001 Acura Integra Type R 2001 99.6% Dodge Charger Sedan 2012 0.19% Ford Mustang Convertible 2007 0.11% Chevrolet Corvette Convertible 2012 0.08% Lamborghini Diablo Coupe 2001 0.02% +137 /scratch/Teaching/cars/car_ims/010470.jpg Honda Odyssey Minivan 2007 Honda Odyssey Minivan 2007 100.0% Honda Odyssey Minivan 2012 0.0% Hyundai Sonata Sedan 2012 0.0% Honda Accord Sedan 2012 0.0% Chrysler Town and Country Minivan 2012 0.0% +138 /scratch/Teaching/cars/car_ims/002896.jpg BMW M6 Convertible 2010 BMW 6 Series Convertible 2007 97.13% BMW M6 Convertible 2010 1.8% BMW Z4 Convertible 2012 0.51% Jaguar XK XKR 2012 0.3% Chevrolet Corvette Convertible 2012 0.08% +139 /scratch/Teaching/cars/car_ims/002910.jpg BMW M6 Convertible 2010 BMW Z4 Convertible 2012 35.25% BMW 6 Series Convertible 2007 21.38% Chevrolet Monte Carlo Coupe 2007 8.87% BMW M6 Convertible 2010 8.31% Chevrolet Impala Sedan 2007 4.53% +140 /scratch/Teaching/cars/car_ims/014739.jpg Spyker C8 Convertible 2009 Bugatti Veyron 16.4 Coupe 2009 92.28% Chevrolet Corvette ZR1 2012 2.9% Spyker C8 Convertible 2009 2.49% Spyker C8 Coupe 2009 0.73% Aston Martin V8 Vantage Convertible 2012 0.49% +141 /scratch/Teaching/cars/car_ims/011972.jpg Jeep Wrangler SUV 2012 Jeep Liberty SUV 2012 95.8% AM General Hummer SUV 2000 2.27% Jeep Patriot SUV 2012 0.96% Jeep Wrangler SUV 2012 0.5% Chevrolet TrailBlazer SS 2009 0.17% +142 /scratch/Teaching/cars/car_ims/015837.jpg Volkswagen Beetle Hatchback 2012 Volkswagen Beetle Hatchback 2012 64.62% Ford GT Coupe 2006 31.63% Suzuki Kizashi Sedan 2012 3.4% Chevrolet Monte Carlo Coupe 2007 0.13% Chevrolet Cobalt SS 2010 0.1% +143 /scratch/Teaching/cars/car_ims/012094.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 97.75% BMW X5 SUV 2007 2.24% Jeep Grand Cherokee SUV 2012 0.01% Buick Enclave SUV 2012 0.0% Jeep Patriot SUV 2012 0.0% +144 /scratch/Teaching/cars/car_ims/007379.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 99.99% Dodge Charger SRT-8 2009 0.0% Dodge Charger Sedan 2012 0.0% Dodge Journey SUV 2012 0.0% Dodge Durango SUV 2012 0.0% +145 /scratch/Teaching/cars/car_ims/012130.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 72.66% Toyota Sequoia SUV 2012 19.56% Chevrolet Traverse SUV 2012 2.51% Dodge Durango SUV 2012 2.36% Buick Enclave SUV 2012 2.28% +146 /scratch/Teaching/cars/car_ims/003988.jpg Buick Enclave SUV 2012 Nissan Juke Hatchback 2012 27.89% Dodge Durango SUV 2012 4.66% Chrysler 300 SRT-8 2010 4.07% BMW X6 SUV 2012 3.9% HUMMER H2 SUT Crew Cab 2009 3.54% +147 /scratch/Teaching/cars/car_ims/009771.jpg GMC Savana Van 2012 GMC Savana Van 2012 82.05% Chevrolet Express Cargo Van 2007 17.55% Chevrolet Express Van 2007 0.4% Volkswagen Golf Hatchback 1991 0.0% Jeep Patriot SUV 2012 0.0% +148 /scratch/Teaching/cars/car_ims/007198.jpg Dodge Sprinter Cargo Van 2009 Nissan Juke Hatchback 2012 35.92% Dodge Sprinter Cargo Van 2009 33.44% Hyundai Elantra Sedan 2007 9.73% Audi 100 Wagon 1994 6.14% Dodge Durango SUV 2007 2.68% +149 /scratch/Teaching/cars/car_ims/015552.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 99.82% GMC Terrain SUV 2012 0.06% Jeep Liberty SUV 2012 0.03% Toyota Sequoia SUV 2012 0.02% Cadillac Escalade EXT Crew Cab 2007 0.02% +150 /scratch/Teaching/cars/car_ims/010126.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 99.98% Plymouth Neon Coupe 1999 0.02% Eagle Talon Hatchback 1998 0.0% Daewoo Nubira Wagon 2002 0.0% Acura Integra Type R 2001 0.0% +151 /scratch/Teaching/cars/car_ims/006590.jpg Chrysler PT Cruiser Convertible 2008 Mercedes-Benz 300-Class Convertible 1993 50.69% Ford Mustang Convertible 2007 22.56% Chrysler Crossfire Convertible 2008 19.33% BMW 6 Series Convertible 2007 5.99% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.46% +152 /scratch/Teaching/cars/car_ims/001275.jpg Audi V8 Sedan 1994 Audi 100 Wagon 1994 90.43% Chevrolet Malibu Sedan 2007 7.35% Mercedes-Benz 300-Class Convertible 1993 2.2% Audi 100 Sedan 1994 0.0% Lincoln Town Car Sedan 2011 0.0% +153 /scratch/Teaching/cars/car_ims/006732.jpg Dodge Caliber Wagon 2012 Cadillac SRX SUV 2012 26.09% Chrysler PT Cruiser Convertible 2008 13.04% Toyota Camry Sedan 2012 9.4% Dodge Caliber Wagon 2012 6.1% Ford Edge SUV 2012 5.03% +154 /scratch/Teaching/cars/car_ims/006313.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 99.44% Ram C/V Cargo Van Minivan 2012 0.27% Honda Odyssey Minivan 2007 0.25% Daewoo Nubira Wagon 2002 0.04% Suzuki Aerio Sedan 2007 0.0% +155 /scratch/Teaching/cars/car_ims/006413.jpg Chrysler 300 SRT-8 2010 Rolls-Royce Phantom Sedan 2012 56.56% Rolls-Royce Phantom Drophead Coupe Convertible 2012 25.75% Bentley Continental Supersports Conv. Convertible 2012 10.34% Maybach Landaulet Convertible 2012 4.78% Rolls-Royce Ghost Sedan 2012 1.48% +156 /scratch/Teaching/cars/car_ims/002546.jpg BMW X5 SUV 2007 BMW X5 SUV 2007 95.42% Hyundai Elantra Touring Hatchback 2012 1.07% Ford Mustang Convertible 2007 0.96% Buick Enclave SUV 2012 0.69% Toyota Sequoia SUV 2012 0.33% +157 /scratch/Teaching/cars/car_ims/003794.jpg Buick Regal GS 2012 Buick Regal GS 2012 62.33% Buick Verano Sedan 2012 27.39% Infiniti G Coupe IPL 2012 9.95% BMW M5 Sedan 2010 0.16% Acura RL Sedan 2012 0.09% +158 /scratch/Teaching/cars/car_ims/004370.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 47.61% Chevrolet Avalanche Crew Cab 2012 41.74% Chevrolet Silverado 1500 Regular Cab 2012 4.44% Chevrolet Silverado 1500 Extended Cab 2012 1.74% GMC Canyon Extended Cab 2012 1.58% +159 /scratch/Teaching/cars/car_ims/012547.jpg Lamborghini Diablo Coupe 2001 Aston Martin Virage Coupe 2012 65.11% Lamborghini Diablo Coupe 2001 28.79% McLaren MP4-12C Coupe 2012 2.38% Aston Martin V8 Vantage Coupe 2012 1.96% Spyker C8 Coupe 2009 0.92% +160 /scratch/Teaching/cars/car_ims/003093.jpg BMW Z4 Convertible 2012 BMW Z4 Convertible 2012 96.21% Audi S5 Convertible 2012 1.69% BMW 3 Series Sedan 2012 1.13% BMW 3 Series Wagon 2012 0.3% Jaguar XK XKR 2012 0.19% +161 /scratch/Teaching/cars/car_ims/011134.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 100.0% Chrysler Town and Country Minivan 2012 0.0% Acura TL Type-S 2008 0.0% Hyundai Sonata Sedan 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% +162 /scratch/Teaching/cars/car_ims/000466.jpg Acura Integra Type R 2001 Acura Integra Type R 2001 66.27% BMW Z4 Convertible 2012 19.15% Chevrolet Monte Carlo Coupe 2007 11.06% Chevrolet Malibu Sedan 2007 1.07% BMW M3 Coupe 2012 0.7% +163 /scratch/Teaching/cars/car_ims/004251.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 98.26% Cadillac SRX SUV 2012 1.62% Dodge Durango SUV 2012 0.05% GMC Acadia SUV 2012 0.04% Dodge Magnum Wagon 2008 0.01% +164 /scratch/Teaching/cars/car_ims/012043.jpg Jeep Liberty SUV 2012 Mercedes-Benz 300-Class Convertible 1993 67.35% Volvo 240 Sedan 1993 17.14% Audi 100 Sedan 1994 5.0% Audi V8 Sedan 1994 2.62% Volkswagen Golf Hatchback 1991 2.23% +165 /scratch/Teaching/cars/car_ims/013956.jpg Nissan Juke Hatchback 2012 MINI Cooper Roadster Convertible 2012 60.37% Mercedes-Benz Sprinter Van 2012 16.76% Ford F-450 Super Duty Crew Cab 2012 4.16% Audi R8 Coupe 2012 3.1% Dodge Ram Pickup 3500 Crew Cab 2010 2.86% +166 /scratch/Teaching/cars/car_ims/011227.jpg Hyundai Genesis Sedan 2012 Hyundai Genesis Sedan 2012 100.0% Mercedes-Benz C-Class Sedan 2012 0.0% Hyundai Sonata Sedan 2012 0.0% Hyundai Azera Sedan 2012 0.0% Toyota Corolla Sedan 2012 0.0% +167 /scratch/Teaching/cars/car_ims/009636.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 99.9% Jeep Compass SUV 2012 0.09% Jeep Patriot SUV 2012 0.0% Dodge Durango SUV 2007 0.0% Dodge Caliber Wagon 2012 0.0% +168 /scratch/Teaching/cars/car_ims/001345.jpg Audi 100 Sedan 1994 Ford F-150 Regular Cab 2007 76.96% Ford Ranger SuperCab 2011 17.34% Volvo XC90 SUV 2007 4.56% Volvo 240 Sedan 1993 0.77% Dodge Dakota Club Cab 2007 0.17% +169 /scratch/Teaching/cars/car_ims/006159.jpg Chrysler Aspen SUV 2009 Chrysler Aspen SUV 2009 99.99% Volvo XC90 SUV 2007 0.0% Dodge Durango SUV 2007 0.0% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.0% Land Rover Range Rover SUV 2012 0.0% +170 /scratch/Teaching/cars/car_ims/014729.jpg Spyker C8 Convertible 2009 Bugatti Veyron 16.4 Coupe 2009 95.73% Spyker C8 Coupe 2009 2.35% Spyker C8 Convertible 2009 1.59% Audi S5 Convertible 2012 0.19% Bugatti Veyron 16.4 Convertible 2009 0.07% +171 /scratch/Teaching/cars/car_ims/003356.jpg Bentley Continental GT Coupe 2012 Bentley Continental GT Coupe 2007 99.84% Bentley Continental GT Coupe 2012 0.15% BMW 1 Series Coupe 2012 0.0% Bentley Continental Flying Spur Sedan 2007 0.0% Suzuki Kizashi Sedan 2012 0.0% +172 /scratch/Teaching/cars/car_ims/000255.jpg Acura TL Type-S 2008 Acura TL Type-S 2008 91.28% Honda Odyssey Minivan 2012 3.21% Toyota Camry Sedan 2012 2.04% Honda Accord Sedan 2012 1.73% Acura RL Sedan 2012 1.48% +173 /scratch/Teaching/cars/car_ims/001575.jpg Audi S6 Sedan 2011 Acura TSX Sedan 2012 44.16% BMW ActiveHybrid 5 Sedan 2012 39.36% BMW 1 Series Convertible 2012 5.76% Audi S4 Sedan 2012 3.02% Audi S5 Coupe 2012 2.53% +174 /scratch/Teaching/cars/car_ims/003495.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 91.68% Bentley Continental GT Coupe 2007 2.34% Rolls-Royce Phantom Drophead Coupe Convertible 2012 1.65% Rolls-Royce Ghost Sedan 2012 1.38% Rolls-Royce Phantom Sedan 2012 1.16% +175 /scratch/Teaching/cars/car_ims/015738.jpg Volkswagen Golf Hatchback 1991 Volkswagen Golf Hatchback 1991 95.81% Volvo 240 Sedan 1993 4.02% Ford Mustang Convertible 2007 0.14% Bentley Arnage Sedan 2009 0.03% Audi 100 Wagon 1994 0.0% +176 /scratch/Teaching/cars/car_ims/011241.jpg Hyundai Genesis Sedan 2012 Acura RL Sedan 2012 79.66% Honda Accord Sedan 2012 7.18% Chevrolet Sonic Sedan 2012 3.56% Acura TL Type-S 2008 1.76% Honda Odyssey Minivan 2012 1.74% +177 /scratch/Teaching/cars/car_ims/007077.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Jeep Compass SUV 2012 61.57% Dodge Ram Pickup 3500 Quad Cab 2009 14.98% Volvo XC90 SUV 2007 7.05% BMW X6 SUV 2012 4.14% BMW X3 SUV 2012 2.94% +178 /scratch/Teaching/cars/car_ims/008495.jpg Ferrari 458 Italia Coupe 2012 Ferrari 458 Italia Convertible 2012 44.15% Lamborghini Diablo Coupe 2001 34.71% Chevrolet Corvette Convertible 2012 20.75% Acura Integra Type R 2001 0.16% Ferrari 458 Italia Coupe 2012 0.16% +179 /scratch/Teaching/cars/car_ims/010613.jpg Honda Accord Sedan 2012 Honda Accord Sedan 2012 98.19% Toyota Camry Sedan 2012 1.72% Toyota Corolla Sedan 2012 0.04% Hyundai Veracruz SUV 2012 0.02% Acura TL Type-S 2008 0.02% +180 /scratch/Teaching/cars/car_ims/006821.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2012 99.1% Dodge Caliber Wagon 2007 0.9% BMW X3 SUV 2012 0.0% Jeep Compass SUV 2012 0.0% BMW X6 SUV 2012 0.0% +181 /scratch/Teaching/cars/car_ims/003406.jpg Bentley Continental GT Coupe 2007 Bentley Continental GT Coupe 2007 67.81% Bentley Continental GT Coupe 2012 15.0% Fisker Karma Sedan 2012 6.09% Bentley Continental Flying Spur Sedan 2007 3.34% Bentley Mulsanne Sedan 2011 2.18% +182 /scratch/Teaching/cars/car_ims/000523.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 91.3% BMW X3 SUV 2012 8.66% Cadillac SRX SUV 2012 0.03% Hyundai Tucson SUV 2012 0.01% BMW X5 SUV 2007 0.0% +183 /scratch/Teaching/cars/car_ims/010431.jpg Honda Odyssey Minivan 2012 Honda Odyssey Minivan 2012 95.18% Honda Accord Sedan 2012 2.09% Toyota Camry Sedan 2012 1.2% Hyundai Sonata Sedan 2012 0.74% Scion xD Hatchback 2012 0.24% +184 /scratch/Teaching/cars/car_ims/002193.jpg BMW 1 Series Convertible 2012 BMW 1 Series Convertible 2012 67.95% Chevrolet Camaro Convertible 2012 30.72% BMW Z4 Convertible 2012 0.87% Audi S5 Convertible 2012 0.44% BMW 6 Series Convertible 2007 0.02% +185 /scratch/Teaching/cars/car_ims/002106.jpg BMW ActiveHybrid 5 Sedan 2012 Audi S6 Sedan 2011 28.83% BMW ActiveHybrid 5 Sedan 2012 21.04% Aston Martin Virage Convertible 2012 9.27% Volkswagen Beetle Hatchback 2012 3.93% Nissan Juke Hatchback 2012 3.68% +186 /scratch/Teaching/cars/car_ims/009326.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 83.19% Ford F-150 Regular Cab 2012 16.1% GMC Yukon Hybrid SUV 2012 0.68% Nissan NV Passenger Van 2012 0.02% Ford Ranger SuperCab 2011 0.0% +187 /scratch/Teaching/cars/car_ims/004448.jpg Chevrolet Corvette Convertible 2012 McLaren MP4-12C Coupe 2012 63.23% Chevrolet Corvette Convertible 2012 23.54% Aston Martin Virage Coupe 2012 7.71% Lamborghini Diablo Coupe 2001 2.5% BMW Z4 Convertible 2012 1.49% +188 /scratch/Teaching/cars/car_ims/013876.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 100.0% Ford F-150 Regular Cab 2007 0.0% Ford F-150 Regular Cab 2012 0.0% Ford Ranger SuperCab 2011 0.0% Ford E-Series Wagon Van 2012 0.0% +189 /scratch/Teaching/cars/car_ims/009358.jpg Ford F-150 Regular Cab 2007 Lincoln Town Car Sedan 2011 72.79% Geo Metro Convertible 1993 14.21% Dodge Caravan Minivan 1997 7.04% Ford F-150 Regular Cab 2007 1.26% Chevrolet Silverado 1500 Extended Cab 2012 0.98% +190 /scratch/Teaching/cars/car_ims/014404.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Sedan 2012 86.1% Rolls-Royce Phantom Drophead Coupe Convertible 2012 13.78% Rolls-Royce Ghost Sedan 2012 0.12% Bentley Mulsanne Sedan 2011 0.0% Maybach Landaulet Convertible 2012 0.0% +191 /scratch/Teaching/cars/car_ims/009561.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 98.08% Toyota Corolla Sedan 2012 1.74% Dodge Journey SUV 2012 0.1% Hyundai Accent Sedan 2012 0.07% Toyota Camry Sedan 2012 0.0% +192 /scratch/Teaching/cars/car_ims/011623.jpg Infiniti QX56 SUV 2011 Infiniti QX56 SUV 2011 98.55% Chevrolet Sonic Sedan 2012 1.3% Buick Verano Sedan 2012 0.09% Volkswagen Golf Hatchback 2012 0.02% Hyundai Santa Fe SUV 2012 0.02% +193 /scratch/Teaching/cars/car_ims/009392.jpg Ford Focus Sedan 2007 Suzuki Aerio Sedan 2007 95.36% Ford Focus Sedan 2007 1.82% Suzuki SX4 Hatchback 2012 1.75% Hyundai Elantra Touring Hatchback 2012 0.99% Daewoo Nubira Wagon 2002 0.06% +194 /scratch/Teaching/cars/car_ims/008462.jpg Ferrari 458 Italia Coupe 2012 Lamborghini Aventador Coupe 2012 53.12% McLaren MP4-12C Coupe 2012 29.35% Ferrari 458 Italia Coupe 2012 10.49% Ferrari 458 Italia Convertible 2012 4.62% Ferrari California Convertible 2012 1.99% +195 /scratch/Teaching/cars/car_ims/005643.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 38.33% Chevrolet Silverado 1500 Regular Cab 2012 32.6% Chevrolet Silverado 1500 Extended Cab 2012 27.07% Chevrolet Avalanche Crew Cab 2012 1.16% Chevrolet Silverado 2500HD Regular Cab 2012 0.28% +196 /scratch/Teaching/cars/car_ims/016142.jpg smart fortwo Convertible 2012 FIAT 500 Convertible 2012 63.69% smart fortwo Convertible 2012 36.31% MINI Cooper Roadster Convertible 2012 0.0% Bentley Continental Supersports Conv. Convertible 2012 0.0% Maybach Landaulet Convertible 2012 0.0% +197 /scratch/Teaching/cars/car_ims/013939.jpg Nissan Juke Hatchback 2012 Nissan Juke Hatchback 2012 54.47% Suzuki SX4 Hatchback 2012 43.98% Chevrolet Traverse SUV 2012 0.56% Hyundai Tucson SUV 2012 0.29% Dodge Journey SUV 2012 0.25% +198 /scratch/Teaching/cars/car_ims/010662.jpg Honda Accord Sedan 2012 Honda Accord Sedan 2012 33.73% Toyota Corolla Sedan 2012 25.16% Honda Accord Coupe 2012 18.46% Land Rover LR2 SUV 2012 17.9% Hyundai Genesis Sedan 2012 2.55% +199 /scratch/Teaching/cars/car_ims/011023.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 99.99% Hyundai Sonata Sedan 2012 0.01% Hyundai Azera Sedan 2012 0.0% Hyundai Accent Sedan 2012 0.0% Hyundai Veloster Hatchback 2012 0.0% +200 /scratch/Teaching/cars/car_ims/005575.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 83.31% Chevrolet Silverado 1500 Regular Cab 2012 15.74% Chevrolet Tahoe Hybrid SUV 2012 0.42% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.37% Chevrolet Silverado 2500HD Regular Cab 2012 0.07% +201 /scratch/Teaching/cars/car_ims/002201.jpg BMW 1 Series Coupe 2012 Nissan Juke Hatchback 2012 70.76% BMW 3 Series Sedan 2012 12.44% BMW X6 SUV 2012 8.53% Volvo C30 Hatchback 2012 8.08% BMW 1 Series Coupe 2012 0.08% +202 /scratch/Teaching/cars/car_ims/004506.jpg Chevrolet Corvette ZR1 2012 Chevrolet Corvette ZR1 2012 99.44% AM General Hummer SUV 2000 0.29% Porsche Panamera Sedan 2012 0.14% Ford GT Coupe 2006 0.09% Bentley Continental GT Coupe 2007 0.02% +203 /scratch/Teaching/cars/car_ims/010099.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 62.03% Jeep Patriot SUV 2012 22.65% Daewoo Nubira Wagon 2002 7.8% Nissan NV Passenger Van 2012 3.99% Dodge Durango SUV 2007 1.24% +204 /scratch/Teaching/cars/car_ims/014813.jpg Spyker C8 Coupe 2009 Lamborghini Diablo Coupe 2001 87.89% McLaren MP4-12C Coupe 2012 11.85% Spyker C8 Coupe 2009 0.1% Lamborghini Aventador Coupe 2012 0.05% Aston Martin Virage Coupe 2012 0.04% +205 /scratch/Teaching/cars/car_ims/005180.jpg Chevrolet Express Cargo Van 2007 GMC Savana Van 2012 96.5% Chevrolet Express Cargo Van 2007 3.06% Chevrolet Express Van 2007 0.45% Volkswagen Golf Hatchback 1991 0.0% Audi V8 Sedan 1994 0.0% +206 /scratch/Teaching/cars/car_ims/015822.jpg Volkswagen Beetle Hatchback 2012 Tesla Model S Sedan 2012 30.06% Mitsubishi Lancer Sedan 2012 19.87% BMW Z4 Convertible 2012 15.58% Aston Martin Virage Coupe 2012 9.4% Volkswagen Beetle Hatchback 2012 8.62% +207 /scratch/Teaching/cars/car_ims/008501.jpg Ferrari 458 Italia Coupe 2012 Ferrari 458 Italia Coupe 2012 46.79% Ferrari 458 Italia Convertible 2012 30.48% Lamborghini Aventador Coupe 2012 14.63% Ford GT Coupe 2006 6.04% Volvo C30 Hatchback 2012 0.58% +208 /scratch/Teaching/cars/car_ims/003132.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental GT Coupe 2012 52.63% Ford GT Coupe 2006 23.95% Bentley Continental Supersports Conv. Convertible 2012 21.19% Lamborghini Aventador Coupe 2012 0.66% Spyker C8 Coupe 2009 0.43% +209 /scratch/Teaching/cars/car_ims/004268.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 99.92% GMC Yukon Hybrid SUV 2012 0.08% Chevrolet Tahoe Hybrid SUV 2012 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% Dodge Durango SUV 2012 0.0% +210 /scratch/Teaching/cars/car_ims/014799.jpg Spyker C8 Coupe 2009 Spyker C8 Coupe 2009 69.11% Aston Martin Virage Coupe 2012 30.84% Spyker C8 Convertible 2009 0.02% Dodge Challenger SRT8 2011 0.01% Ford GT Coupe 2006 0.01% +211 /scratch/Teaching/cars/car_ims/009257.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 99.29% Nissan NV Passenger Van 2012 0.67% Ford F-150 Regular Cab 2007 0.03% Ford E-Series Wagon Van 2012 0.01% Ford Ranger SuperCab 2011 0.0% +212 /scratch/Teaching/cars/car_ims/005514.jpg Chevrolet TrailBlazer SS 2009 Chevrolet TrailBlazer SS 2009 66.68% Chevrolet Avalanche Crew Cab 2012 32.48% BMW X6 SUV 2012 0.16% Dodge Charger SRT-8 2009 0.1% Chevrolet Tahoe Hybrid SUV 2012 0.06% +213 /scratch/Teaching/cars/car_ims/000813.jpg Aston Martin Virage Coupe 2012 Aston Martin Virage Coupe 2012 99.71% McLaren MP4-12C Coupe 2012 0.29% Aston Martin V8 Vantage Coupe 2012 0.0% Spyker C8 Coupe 2009 0.0% Lamborghini Diablo Coupe 2001 0.0% +214 /scratch/Teaching/cars/car_ims/015343.jpg Toyota Camry Sedan 2012 Toyota Camry Sedan 2012 82.85% Hyundai Accent Sedan 2012 14.06% Hyundai Sonata Hybrid Sedan 2012 3.06% Hyundai Sonata Sedan 2012 0.01% Honda Accord Coupe 2012 0.01% +215 /scratch/Teaching/cars/car_ims/014452.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Ghost Sedan 2012 64.85% Rolls-Royce Phantom Drophead Coupe Convertible 2012 27.26% Rolls-Royce Phantom Sedan 2012 6.19% BMW M6 Convertible 2010 0.81% BMW 6 Series Convertible 2007 0.33% +216 /scratch/Teaching/cars/car_ims/005861.jpg Chevrolet Malibu Sedan 2007 Chevrolet Impala Sedan 2007 53.34% Chevrolet Monte Carlo Coupe 2007 41.05% Buick Verano Sedan 2012 3.0% Hyundai Elantra Sedan 2007 0.82% Acura TL Sedan 2012 0.57% +217 /scratch/Teaching/cars/car_ims/003121.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental GT Coupe 2007 99.91% Dodge Challenger SRT8 2011 0.09% Bentley Continental Flying Spur Sedan 2007 0.0% Bentley Continental GT Coupe 2012 0.0% BMW M5 Sedan 2010 0.0% +218 /scratch/Teaching/cars/car_ims/003017.jpg BMW X3 SUV 2012 BMW X5 SUV 2007 89.68% BMW X3 SUV 2012 8.23% BMW X6 SUV 2012 1.63% Ford Mustang Convertible 2007 0.42% Jeep Grand Cherokee SUV 2012 0.02% +219 /scratch/Teaching/cars/car_ims/014597.jpg Scion xD Hatchback 2012 Scion xD Hatchback 2012 99.84% Ford Fiesta Sedan 2012 0.16% Hyundai Tucson SUV 2012 0.0% Nissan Leaf Hatchback 2012 0.0% Suzuki SX4 Hatchback 2012 0.0% +220 /scratch/Teaching/cars/car_ims/011717.jpg Isuzu Ascender SUV 2008 Isuzu Ascender SUV 2008 99.96% Ford Ranger SuperCab 2011 0.04% Dodge Dakota Crew Cab 2010 0.0% Jeep Compass SUV 2012 0.0% HUMMER H3T Crew Cab 2010 0.0% +221 /scratch/Teaching/cars/car_ims/009772.jpg GMC Savana Van 2012 GMC Savana Van 2012 99.94% Chevrolet Express Van 2007 0.05% Chevrolet Express Cargo Van 2007 0.01% Volvo XC90 SUV 2007 0.0% Dodge Sprinter Cargo Van 2009 0.0% +222 /scratch/Teaching/cars/car_ims/003355.jpg Bentley Continental GT Coupe 2012 Mitsubishi Lancer Sedan 2012 82.92% Volvo C30 Hatchback 2012 11.15% Hyundai Veloster Hatchback 2012 2.17% BMW 1 Series Coupe 2012 0.92% Buick Regal GS 2012 0.6% +223 /scratch/Teaching/cars/car_ims/008636.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 100.0% Ford F-150 Regular Cab 2012 0.0% Ford Expedition EL SUV 2009 0.0% MINI Cooper Roadster Convertible 2012 0.0% Toyota Sequoia SUV 2012 0.0% +224 /scratch/Teaching/cars/car_ims/016134.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 82.93% FIAT 500 Convertible 2012 17.07% MINI Cooper Roadster Convertible 2012 0.0% Chrysler PT Cruiser Convertible 2008 0.0% Suzuki SX4 Hatchback 2012 0.0% +225 /scratch/Teaching/cars/car_ims/006048.jpg Chevrolet Silverado 1500 Regular Cab 2012 Dodge Dakota Club Cab 2007 71.03% Ford F-150 Regular Cab 2007 15.9% GMC Canyon Extended Cab 2012 11.23% Ford F-150 Regular Cab 2012 0.55% Dodge Dakota Crew Cab 2010 0.44% +226 /scratch/Teaching/cars/car_ims/001833.jpg Audi S4 Sedan 2012 Audi S6 Sedan 2011 54.96% Audi S5 Convertible 2012 29.12% Audi A5 Coupe 2012 4.64% Audi S4 Sedan 2012 4.56% Audi TT Hatchback 2011 3.57% +227 /scratch/Teaching/cars/car_ims/007571.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 100.0% Rolls-Royce Phantom Sedan 2012 0.0% Dodge Charger SRT-8 2009 0.0% Rolls-Royce Ghost Sedan 2012 0.0% Audi S4 Sedan 2007 0.0% +228 /scratch/Teaching/cars/car_ims/001141.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 49.28% Lamborghini Aventador Coupe 2012 26.37% Lamborghini Reventon Coupe 2008 13.3% Bugatti Veyron 16.4 Convertible 2009 6.11% Bugatti Veyron 16.4 Coupe 2009 1.74% +229 /scratch/Teaching/cars/car_ims/006985.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 99.94% Dodge Ram Pickup 3500 Quad Cab 2009 0.05% Ford F-450 Super Duty Crew Cab 2012 0.0% Ford F-150 Regular Cab 2012 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% +230 /scratch/Teaching/cars/car_ims/001795.jpg Audi S5 Coupe 2012 Audi RS 4 Convertible 2008 79.39% Audi A5 Coupe 2012 6.56% Audi TTS Coupe 2012 5.18% Audi S5 Coupe 2012 4.36% Audi S4 Sedan 2007 3.55% +231 /scratch/Teaching/cars/car_ims/013009.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 100.0% GMC Acadia SUV 2012 0.0% Dodge Durango SUV 2007 0.0% Jeep Grand Cherokee SUV 2012 0.0% Toyota 4Runner SUV 2012 0.0% +232 /scratch/Teaching/cars/car_ims/001230.jpg Audi V8 Sedan 1994 Audi V8 Sedan 1994 98.92% Audi 100 Sedan 1994 0.99% BMW 3 Series Sedan 2012 0.05% BMW 1 Series Convertible 2012 0.01% Ford Mustang Convertible 2007 0.01% +233 /scratch/Teaching/cars/car_ims/014300.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 99.85% Chrysler Sebring Convertible 2010 0.11% Mercedes-Benz S-Class Sedan 2012 0.01% Chrysler Town and Country Minivan 2012 0.01% Chevrolet Malibu Sedan 2007 0.0% +234 /scratch/Teaching/cars/car_ims/014169.jpg Plymouth Neon Coupe 1999 Plymouth Neon Coupe 1999 99.99% Eagle Talon Hatchback 1998 0.01% Nissan 240SX Coupe 1998 0.0% Ford Focus Sedan 2007 0.0% Audi 100 Wagon 1994 0.0% +235 /scratch/Teaching/cars/car_ims/013258.jpg Mercedes-Benz C-Class Sedan 2012 Hyundai Genesis Sedan 2012 99.95% Mercedes-Benz C-Class Sedan 2012 0.03% Dodge Durango SUV 2012 0.01% Mercedes-Benz SL-Class Coupe 2009 0.0% Mercedes-Benz E-Class Sedan 2012 0.0% +236 /scratch/Teaching/cars/car_ims/015661.jpg Volkswagen Golf Hatchback 2012 Chevrolet Impala Sedan 2007 67.4% Chevrolet Malibu Sedan 2007 32.46% Chevrolet Malibu Hybrid Sedan 2010 0.1% Honda Accord Sedan 2012 0.02% Chevrolet Monte Carlo Coupe 2007 0.01% +237 /scratch/Teaching/cars/car_ims/011790.jpg Jaguar XK XKR 2012 Jaguar XK XKR 2012 99.42% Buick Verano Sedan 2012 0.47% BMW M6 Convertible 2010 0.04% BMW 1 Series Convertible 2012 0.02% BMW 6 Series Convertible 2007 0.02% +238 /scratch/Teaching/cars/car_ims/007625.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2007 99.93% Dodge Dakota Crew Cab 2010 0.03% Dodge Durango SUV 2012 0.03% Infiniti QX56 SUV 2011 0.0% Land Rover Range Rover SUV 2012 0.0% +239 /scratch/Teaching/cars/car_ims/000226.jpg Acura TL Sedan 2012 Buick Regal GS 2012 74.29% Acura TL Sedan 2012 20.43% Buick Verano Sedan 2012 2.14% Hyundai Sonata Hybrid Sedan 2012 0.83% Chevrolet Sonic Sedan 2012 0.7% +240 /scratch/Teaching/cars/car_ims/011515.jpg Hyundai Azera Sedan 2012 Infiniti G Coupe IPL 2012 79.78% Hyundai Azera Sedan 2012 18.86% Hyundai Genesis Sedan 2012 1.35% Hyundai Sonata Sedan 2012 0.0% BMW M6 Convertible 2010 0.0% +241 /scratch/Teaching/cars/car_ims/002699.jpg BMW M3 Coupe 2012 BMW M5 Sedan 2010 76.91% BMW Z4 Convertible 2012 15.08% BMW M3 Coupe 2012 6.11% BMW M6 Convertible 2010 1.61% Chevrolet Cobalt SS 2010 0.09% +242 /scratch/Teaching/cars/car_ims/012239.jpg Jeep Compass SUV 2012 HUMMER H3T Crew Cab 2010 99.06% Jeep Wrangler SUV 2012 0.51% Jeep Patriot SUV 2012 0.24% Jeep Compass SUV 2012 0.18% AM General Hummer SUV 2000 0.01% +243 /scratch/Teaching/cars/car_ims/010522.jpg Honda Accord Coupe 2012 Honda Accord Coupe 2012 99.97% Jaguar XK XKR 2012 0.01% Nissan 240SX Coupe 1998 0.01% Acura TSX Sedan 2012 0.01% BMW 3 Series Sedan 2012 0.0% +244 /scratch/Teaching/cars/car_ims/007178.jpg Dodge Sprinter Cargo Van 2009 Mercedes-Benz Sprinter Van 2012 94.87% Honda Odyssey Minivan 2012 1.29% Honda Accord Sedan 2012 0.99% Dodge Sprinter Cargo Van 2009 0.61% Land Rover LR2 SUV 2012 0.57% +245 /scratch/Teaching/cars/car_ims/016121.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 99.99% FIAT 500 Convertible 2012 0.01% Chrysler PT Cruiser Convertible 2008 0.0% MINI Cooper Roadster Convertible 2012 0.0% Chevrolet Sonic Sedan 2012 0.0% +246 /scratch/Teaching/cars/car_ims/014422.jpg Rolls-Royce Ghost Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 51.77% Volvo C30 Hatchback 2012 13.67% Rolls-Royce Phantom Sedan 2012 11.93% BMW X3 SUV 2012 6.41% BMW 3 Series Sedan 2012 3.54% +247 /scratch/Teaching/cars/car_ims/005261.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 76.57% Chevrolet Tahoe Hybrid SUV 2012 16.37% Isuzu Ascender SUV 2008 2.69% Dodge Dakota Crew Cab 2010 2.43% Chevrolet Silverado 1500 Extended Cab 2012 0.78% +248 /scratch/Teaching/cars/car_ims/000853.jpg Aston Martin Virage Coupe 2012 Aston Martin Virage Coupe 2012 99.33% Aston Martin V8 Vantage Coupe 2012 0.66% McLaren MP4-12C Coupe 2012 0.01% Spyker C8 Coupe 2009 0.0% Aston Martin Virage Convertible 2012 0.0% +249 /scratch/Teaching/cars/car_ims/001391.jpg Audi 100 Wagon 1994 Mercedes-Benz 300-Class Convertible 1993 86.2% Audi 100 Wagon 1994 9.87% Audi 100 Sedan 1994 3.86% Geo Metro Convertible 1993 0.04% Volkswagen Golf Hatchback 1991 0.01% +250 /scratch/Teaching/cars/car_ims/009933.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 100.0% Land Rover LR2 SUV 2012 0.0% Mazda Tribute SUV 2011 0.0% Chevrolet Tahoe Hybrid SUV 2012 0.0% Infiniti QX56 SUV 2011 0.0% +251 /scratch/Teaching/cars/car_ims/015495.jpg Toyota Corolla Sedan 2012 Chevrolet Sonic Sedan 2012 56.57% Toyota Corolla Sedan 2012 36.56% Hyundai Accent Sedan 2012 2.31% Toyota Camry Sedan 2012 1.3% Honda Accord Coupe 2012 1.29% +252 /scratch/Teaching/cars/car_ims/002817.jpg BMW M5 Sedan 2010 BMW M5 Sedan 2010 99.97% Buick Verano Sedan 2012 0.02% Acura TL Type-S 2008 0.0% Suzuki SX4 Sedan 2012 0.0% BMW 6 Series Convertible 2007 0.0% +253 /scratch/Teaching/cars/car_ims/012192.jpg Jeep Grand Cherokee SUV 2012 Ram C/V Cargo Van Minivan 2012 50.14% Suzuki SX4 Hatchback 2012 15.21% Toyota Sequoia SUV 2012 12.54% Mazda Tribute SUV 2011 10.17% GMC Acadia SUV 2012 3.58% +254 /scratch/Teaching/cars/car_ims/014214.jpg Porsche Panamera Sedan 2012 Porsche Panamera Sedan 2012 99.73% Chevrolet Corvette ZR1 2012 0.15% Audi S5 Convertible 2012 0.05% Aston Martin Virage Convertible 2012 0.01% Mercedes-Benz C-Class Sedan 2012 0.01% +255 /scratch/Teaching/cars/car_ims/008646.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 100.0% Ford F-150 Regular Cab 2012 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% Ford Expedition EL SUV 2009 0.0% Toyota 4Runner SUV 2012 0.0% +256 /scratch/Teaching/cars/car_ims/012906.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 99.68% Bugatti Veyron 16.4 Convertible 2009 0.27% Bugatti Veyron 16.4 Coupe 2009 0.02% Hyundai Azera Sedan 2012 0.01% Audi S5 Convertible 2012 0.0% +257 /scratch/Teaching/cars/car_ims/009128.jpg Ford GT Coupe 2006 Ford GT Coupe 2006 98.16% Lamborghini Aventador Coupe 2012 0.77% Volvo C30 Hatchback 2012 0.52% Chevrolet Corvette ZR1 2012 0.32% Bugatti Veyron 16.4 Coupe 2009 0.12% +258 /scratch/Teaching/cars/car_ims/007474.jpg Dodge Magnum Wagon 2008 Audi S5 Coupe 2012 65.33% Dodge Magnum Wagon 2008 8.23% Chrysler 300 SRT-8 2010 4.16% Audi 100 Wagon 1994 3.07% Cadillac Escalade EXT Crew Cab 2007 1.88% +259 /scratch/Teaching/cars/car_ims/014815.jpg Spyker C8 Coupe 2009 Bugatti Veyron 16.4 Convertible 2009 56.94% Spyker C8 Convertible 2009 16.51% Bugatti Veyron 16.4 Coupe 2009 16.39% Mercedes-Benz SL-Class Coupe 2009 4.53% Spyker C8 Coupe 2009 2.48% +260 /scratch/Teaching/cars/car_ims/011980.jpg Jeep Wrangler SUV 2012 Jeep Wrangler SUV 2012 99.99% GMC Canyon Extended Cab 2012 0.01% Chevrolet Silverado 1500 Extended Cab 2012 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% AM General Hummer SUV 2000 0.0% +261 /scratch/Teaching/cars/car_ims/003373.jpg Bentley Continental GT Coupe 2012 Bentley Continental GT Coupe 2012 99.63% Bentley Continental GT Coupe 2007 0.37% Bentley Continental Flying Spur Sedan 2007 0.0% Cadillac CTS-V Sedan 2012 0.0% Suzuki Kizashi Sedan 2012 0.0% +262 /scratch/Teaching/cars/car_ims/006316.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 99.95% Dodge Magnum Wagon 2008 0.02% Suzuki Aerio Sedan 2007 0.02% Dodge Caliber Wagon 2012 0.01% Mercedes-Benz 300-Class Convertible 1993 0.0% +263 /scratch/Teaching/cars/car_ims/014191.jpg Porsche Panamera Sedan 2012 Porsche Panamera Sedan 2012 79.9% Chrysler 300 SRT-8 2010 7.59% Bentley Continental GT Coupe 2007 3.76% Volkswagen Golf Hatchback 1991 1.79% Chevrolet Corvette ZR1 2012 1.35% +264 /scratch/Teaching/cars/car_ims/015602.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 99.51% Dodge Journey SUV 2012 0.18% Honda Accord Sedan 2012 0.09% Hyundai Tucson SUV 2012 0.08% Ford Fiesta Sedan 2012 0.04% +265 /scratch/Teaching/cars/car_ims/009702.jpg GMC Terrain SUV 2012 Toyota 4Runner SUV 2012 45.92% Dodge Durango SUV 2012 15.84% Suzuki SX4 Sedan 2012 11.21% BMW X3 SUV 2012 6.12% Honda Odyssey Minivan 2012 4.9% +266 /scratch/Teaching/cars/car_ims/007788.jpg Dodge Durango SUV 2007 Dodge Dakota Crew Cab 2010 86.5% Dodge Dakota Club Cab 2007 9.94% Dodge Durango SUV 2007 3.06% Chrysler Aspen SUV 2009 0.5% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% +267 /scratch/Teaching/cars/car_ims/011684.jpg Isuzu Ascender SUV 2008 Isuzu Ascender SUV 2008 99.84% Dodge Dakota Crew Cab 2010 0.16% Ford Ranger SuperCab 2011 0.0% Jeep Compass SUV 2012 0.0% Jeep Grand Cherokee SUV 2012 0.0% +268 /scratch/Teaching/cars/car_ims/014740.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 95.69% Spyker C8 Coupe 2009 4.29% Ford GT Coupe 2006 0.01% Bugatti Veyron 16.4 Coupe 2009 0.01% Fisker Karma Sedan 2012 0.0% +269 /scratch/Teaching/cars/car_ims/003392.jpg Bentley Continental GT Coupe 2012 Bentley Continental GT Coupe 2012 50.93% Bentley Continental GT Coupe 2007 49.07% Bentley Continental Flying Spur Sedan 2007 0.0% Buick Verano Sedan 2012 0.0% Suzuki Kizashi Sedan 2012 0.0% +270 /scratch/Teaching/cars/car_ims/002205.jpg BMW 1 Series Coupe 2012 Ford GT Coupe 2006 94.39% BMW 1 Series Coupe 2012 5.11% Spyker C8 Convertible 2009 0.21% Bentley Continental GT Coupe 2007 0.12% Chevrolet Corvette Convertible 2012 0.04% +271 /scratch/Teaching/cars/car_ims/012049.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 92.93% Jeep Patriot SUV 2012 6.82% Jeep Grand Cherokee SUV 2012 0.15% Jeep Wrangler SUV 2012 0.08% Jeep Compass SUV 2012 0.01% +272 /scratch/Teaching/cars/car_ims/008724.jpg Ford Mustang Convertible 2007 Ford Mustang Convertible 2007 100.0% Audi V8 Sedan 1994 0.0% Volkswagen Golf Hatchback 1991 0.0% Nissan 240SX Coupe 1998 0.0% Chrysler 300 SRT-8 2010 0.0% +273 /scratch/Teaching/cars/car_ims/008524.jpg Fisker Karma Sedan 2012 BMW Z4 Convertible 2012 46.75% BMW 6 Series Convertible 2007 30.44% Chrysler Crossfire Convertible 2008 5.81% BMW M6 Convertible 2010 5.04% Chevrolet Corvette Convertible 2012 2.03% +274 /scratch/Teaching/cars/car_ims/015516.jpg Toyota 4Runner SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 99.58% Isuzu Ascender SUV 2008 0.19% GMC Yukon Hybrid SUV 2012 0.08% Toyota 4Runner SUV 2012 0.08% GMC Acadia SUV 2012 0.02% +275 /scratch/Teaching/cars/car_ims/004373.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 70.15% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 29.32% Chevrolet Silverado 1500 Regular Cab 2012 0.3% Chevrolet Silverado 2500HD Regular Cab 2012 0.23% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.01% +276 /scratch/Teaching/cars/car_ims/008948.jpg Ford Edge SUV 2012 Chevrolet Sonic Sedan 2012 44.04% Buick Verano Sedan 2012 20.35% Mitsubishi Lancer Sedan 2012 20.09% Dodge Journey SUV 2012 8.09% Volvo C30 Hatchback 2012 2.55% +277 /scratch/Teaching/cars/car_ims/011319.jpg Hyundai Sonata Sedan 2012 Hyundai Sonata Sedan 2012 99.94% Hyundai Azera Sedan 2012 0.06% Honda Odyssey Minivan 2012 0.0% Honda Accord Sedan 2012 0.0% Hyundai Genesis Sedan 2012 0.0% +278 /scratch/Teaching/cars/car_ims/016185.jpg smart fortwo Convertible 2012 Hyundai Tucson SUV 2012 54.38% smart fortwo Convertible 2012 44.89% Ford Fiesta Sedan 2012 0.67% Nissan Leaf Hatchback 2012 0.05% Scion xD Hatchback 2012 0.0% +279 /scratch/Teaching/cars/car_ims/009506.jpg Ford E-Series Wagon Van 2012 Ford E-Series Wagon Van 2012 100.0% Ford Ranger SuperCab 2011 0.0% Ford F-150 Regular Cab 2012 0.0% Isuzu Ascender SUV 2008 0.0% Ford F-150 Regular Cab 2007 0.0% +280 /scratch/Teaching/cars/car_ims/010110.jpg Geo Metro Convertible 1993 Chevrolet Express Van 2007 91.7% Acura Integra Type R 2001 4.23% GMC Savana Van 2012 1.8% Ford Mustang Convertible 2007 0.46% Volkswagen Golf Hatchback 1991 0.35% +281 /scratch/Teaching/cars/car_ims/015510.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 37.94% Land Rover LR2 SUV 2012 36.84% Ford Expedition EL SUV 2009 18.26% Ford Edge SUV 2012 4.94% Infiniti QX56 SUV 2011 1.08% +282 /scratch/Teaching/cars/car_ims/008054.jpg Eagle Talon Hatchback 1998 Eagle Talon Hatchback 1998 99.53% Nissan 240SX Coupe 1998 0.31% Plymouth Neon Coupe 1999 0.12% Toyota Camry Sedan 2012 0.03% Toyota Corolla Sedan 2012 0.0% +283 /scratch/Teaching/cars/car_ims/005535.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 76.86% Chevrolet Silverado 1500 Regular Cab 2012 18.59% Chevrolet Silverado 1500 Extended Cab 2012 2.72% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.59% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.54% +284 /scratch/Teaching/cars/car_ims/009341.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 99.65% Ford F-150 Regular Cab 2012 0.27% Ford Ranger SuperCab 2011 0.06% Nissan NV Passenger Van 2012 0.01% GMC Canyon Extended Cab 2012 0.0% +285 /scratch/Teaching/cars/car_ims/014486.jpg Rolls-Royce Ghost Sedan 2012 BMW Z4 Convertible 2012 81.14% Rolls-Royce Phantom Drophead Coupe Convertible 2012 7.66% Chevrolet Corvette Convertible 2012 5.27% Aston Martin V8 Vantage Convertible 2012 3.08% Bentley Continental GT Coupe 2007 0.82% +286 /scratch/Teaching/cars/car_ims/007525.jpg Dodge Magnum Wagon 2008 Dodge Magnum Wagon 2008 35.76% Chevrolet Impala Sedan 2007 16.62% Chevrolet Malibu Sedan 2007 13.83% Chevrolet Silverado 1500 Regular Cab 2012 9.26% Mercedes-Benz 300-Class Convertible 1993 8.89% +287 /scratch/Teaching/cars/car_ims/004555.jpg Chevrolet Corvette ZR1 2012 Audi S5 Convertible 2012 42.55% Bugatti Veyron 16.4 Coupe 2009 17.89% Chevrolet Corvette ZR1 2012 14.81% Spyker C8 Convertible 2009 13.21% Porsche Panamera Sedan 2012 7.78% +288 /scratch/Teaching/cars/car_ims/012913.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 99.51% Ford F-450 Super Duty Crew Cab 2012 0.49% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% Dodge Charger Sedan 2012 0.0% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.0% +289 /scratch/Teaching/cars/car_ims/009843.jpg GMC Yukon Hybrid SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 70.03% GMC Yukon Hybrid SUV 2012 27.75% Isuzu Ascender SUV 2008 1.1% Chevrolet Avalanche Crew Cab 2012 0.83% Cadillac Escalade EXT Crew Cab 2007 0.09% +290 /scratch/Teaching/cars/car_ims/008907.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 44.19% GMC Yukon Hybrid SUV 2012 34.55% Ford F-150 Regular Cab 2012 11.79% Ford F-150 Regular Cab 2007 4.47% Ford Ranger SuperCab 2011 2.44% +291 /scratch/Teaching/cars/car_ims/001105.jpg Audi TTS Coupe 2012 Audi RS 4 Convertible 2008 38.1% Audi TTS Coupe 2012 30.83% Audi TT Hatchback 2011 26.08% Audi R8 Coupe 2012 1.52% Audi S5 Coupe 2012 1.35% +292 /scratch/Teaching/cars/car_ims/013839.jpg Nissan Leaf Hatchback 2012 Nissan Leaf Hatchback 2012 71.36% Acura ZDX Hatchback 2012 19.57% Suzuki SX4 Sedan 2012 4.22% FIAT 500 Convertible 2012 1.93% Chevrolet Corvette Ron Fellows Edition Z06 2007 1.38% +293 /scratch/Teaching/cars/car_ims/005266.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 95.52% Chevrolet Tahoe Hybrid SUV 2012 2.87% GMC Yukon Hybrid SUV 2012 1.36% Ford Expedition EL SUV 2009 0.12% Chevrolet TrailBlazer SS 2009 0.04% +294 /scratch/Teaching/cars/car_ims/007367.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 99.85% Chevrolet Avalanche Crew Cab 2012 0.08% Chrysler Aspen SUV 2009 0.02% Isuzu Ascender SUV 2008 0.01% Dodge Journey SUV 2012 0.01% +295 /scratch/Teaching/cars/car_ims/011359.jpg Hyundai Sonata Sedan 2012 Hyundai Azera Sedan 2012 34.48% Tesla Model S Sedan 2012 15.7% Buick Verano Sedan 2012 12.13% Hyundai Sonata Hybrid Sedan 2012 9.25% Hyundai Sonata Sedan 2012 5.77% +296 /scratch/Teaching/cars/car_ims/014464.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Phantom Sedan 2012 100.0% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Rolls-Royce Ghost Sedan 2012 0.0% Volvo 240 Sedan 1993 0.0% Maybach Landaulet Convertible 2012 0.0% +297 /scratch/Teaching/cars/car_ims/006729.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2007 70.89% Volvo C30 Hatchback 2012 25.19% Dodge Caliber Wagon 2012 3.84% Chrysler PT Cruiser Convertible 2008 0.02% Mercedes-Benz E-Class Sedan 2012 0.02% +298 /scratch/Teaching/cars/car_ims/006580.jpg Chrysler PT Cruiser Convertible 2008 Chrysler PT Cruiser Convertible 2008 53.94% Dodge Caliber Wagon 2012 45.32% Mazda Tribute SUV 2011 0.39% Dodge Caliber Wagon 2007 0.17% Dodge Journey SUV 2012 0.04% +299 /scratch/Teaching/cars/car_ims/006265.jpg Chrysler Sebring Convertible 2010 Chrysler Crossfire Convertible 2008 99.99% Chrysler Sebring Convertible 2010 0.01% Cadillac CTS-V Sedan 2012 0.0% Dodge Journey SUV 2012 0.0% Chevrolet Camaro Convertible 2012 0.0% +300 /scratch/Teaching/cars/car_ims/015297.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.88% Dodge Durango SUV 2012 0.07% Hyundai Santa Fe SUV 2012 0.04% Cadillac SRX SUV 2012 0.0% Dodge Journey SUV 2012 0.0% +301 /scratch/Teaching/cars/car_ims/011484.jpg Hyundai Azera Sedan 2012 Dodge Charger Sedan 2012 30.94% Spyker C8 Coupe 2009 26.81% Mercedes-Benz SL-Class Coupe 2009 10.04% Chevrolet Corvette ZR1 2012 5.9% Hyundai Azera Sedan 2012 4.65% +302 /scratch/Teaching/cars/car_ims/003613.jpg Bugatti Veyron 16.4 Convertible 2009 Bugatti Veyron 16.4 Convertible 2009 43.34% Maybach Landaulet Convertible 2012 17.17% Acura Integra Type R 2001 11.36% smart fortwo Convertible 2012 7.03% Lamborghini Diablo Coupe 2001 3.65% +303 /scratch/Teaching/cars/car_ims/002787.jpg BMW M3 Coupe 2012 BMW M3 Coupe 2012 99.39% BMW M5 Sedan 2010 0.61% Nissan 240SX Coupe 1998 0.0% BMW Z4 Convertible 2012 0.0% BMW M6 Convertible 2010 0.0% +304 /scratch/Teaching/cars/car_ims/000912.jpg Audi RS 4 Convertible 2008 Audi RS 4 Convertible 2008 98.42% BMW Z4 Convertible 2012 1.46% Dodge Charger Sedan 2012 0.08% Chevrolet Corvette Convertible 2012 0.02% Ford Mustang Convertible 2007 0.01% +305 /scratch/Teaching/cars/car_ims/013209.jpg Mercedes-Benz 300-Class Convertible 1993 Mercedes-Benz 300-Class Convertible 1993 99.91% Audi 100 Wagon 1994 0.07% Ford Freestar Minivan 2007 0.0% Ford Mustang Convertible 2007 0.0% Chrysler Sebring Convertible 2010 0.0% +306 /scratch/Teaching/cars/car_ims/006547.jpg Chrysler PT Cruiser Convertible 2008 Chrysler PT Cruiser Convertible 2008 100.0% Chrysler Crossfire Convertible 2008 0.0% Dodge Caliber Wagon 2012 0.0% Ford F-150 Regular Cab 2012 0.0% Chrysler Aspen SUV 2009 0.0% +307 /scratch/Teaching/cars/car_ims/002290.jpg BMW 3 Series Sedan 2012 BMW Z4 Convertible 2012 47.21% BMW 3 Series Wagon 2012 24.0% BMW 3 Series Sedan 2012 17.18% BMW 1 Series Convertible 2012 8.31% BMW 1 Series Coupe 2012 1.72% +308 /scratch/Teaching/cars/car_ims/013562.jpg Mercedes-Benz S-Class Sedan 2012 Mercedes-Benz E-Class Sedan 2012 99.39% Mercedes-Benz S-Class Sedan 2012 0.55% Mercedes-Benz C-Class Sedan 2012 0.04% Suzuki Kizashi Sedan 2012 0.02% Audi S4 Sedan 2007 0.0% +309 /scratch/Teaching/cars/car_ims/016027.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 100.0% Dodge Durango SUV 2007 0.0% Volkswagen Golf Hatchback 1991 0.0% Dodge Magnum Wagon 2008 0.0% Volvo 240 Sedan 1993 0.0% +310 /scratch/Teaching/cars/car_ims/008859.jpg Ford Expedition EL SUV 2009 Mazda Tribute SUV 2011 70.04% Ram C/V Cargo Van Minivan 2012 9.8% Dodge Durango SUV 2007 4.26% Chevrolet Tahoe Hybrid SUV 2012 3.01% Chevrolet Malibu Sedan 2007 2.74% +311 /scratch/Teaching/cars/car_ims/003480.jpg Bentley Continental GT Coupe 2007 Bentley Continental GT Coupe 2007 98.03% Bentley Continental GT Coupe 2012 1.78% Bentley Continental Flying Spur Sedan 2007 0.17% BMW Z4 Convertible 2012 0.01% Aston Martin V8 Vantage Coupe 2012 0.01% +312 /scratch/Teaching/cars/car_ims/005221.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 99.43% Cadillac Escalade EXT Crew Cab 2007 0.3% Chevrolet Tahoe Hybrid SUV 2012 0.13% Dodge Dakota Crew Cab 2010 0.07% GMC Canyon Extended Cab 2012 0.01% +313 /scratch/Teaching/cars/car_ims/001094.jpg Audi TTS Coupe 2012 Audi TTS Coupe 2012 99.94% Audi S5 Coupe 2012 0.04% Audi A5 Coupe 2012 0.01% Audi TT Hatchback 2011 0.01% Audi TT RS Coupe 2012 0.0% +314 /scratch/Teaching/cars/car_ims/005591.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 99.81% Chevrolet Silverado 1500 Regular Cab 2012 0.18% Chevrolet Silverado 1500 Extended Cab 2012 0.01% Chrysler 300 SRT-8 2010 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% +315 /scratch/Teaching/cars/car_ims/013904.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 99.56% Ford E-Series Wagon Van 2012 0.41% Ford F-150 Regular Cab 2007 0.01% Ford F-450 Super Duty Crew Cab 2012 0.01% Ford F-150 Regular Cab 2012 0.0% +316 /scratch/Teaching/cars/car_ims/006434.jpg Chrysler 300 SRT-8 2010 Rolls-Royce Phantom Sedan 2012 83.72% Chrysler 300 SRT-8 2010 14.12% Bentley Mulsanne Sedan 2011 1.36% Bentley Arnage Sedan 2009 0.55% Bentley Continental GT Coupe 2012 0.08% +317 /scratch/Teaching/cars/car_ims/003946.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 99.99% Buick Regal GS 2012 0.01% Chevrolet Malibu Hybrid Sedan 2010 0.0% Suzuki Kizashi Sedan 2012 0.0% Volkswagen Golf Hatchback 2012 0.0% +318 /scratch/Teaching/cars/car_ims/005945.jpg Chevrolet Silverado 1500 Extended Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 47.69% Chevrolet Tahoe Hybrid SUV 2012 32.32% Chevrolet Avalanche Crew Cab 2012 19.61% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.23% Chevrolet Silverado 1500 Regular Cab 2012 0.16% +319 /scratch/Teaching/cars/car_ims/006819.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2012 99.94% Dodge Caliber Wagon 2007 0.06% Dodge Magnum Wagon 2008 0.0% Dodge Durango SUV 2012 0.0% Dodge Durango SUV 2007 0.0% +320 /scratch/Teaching/cars/car_ims/010120.jpg Geo Metro Convertible 1993 McLaren MP4-12C Coupe 2012 98.19% Aston Martin Virage Coupe 2012 1.59% Aston Martin V8 Vantage Coupe 2012 0.12% Spyker C8 Coupe 2009 0.04% Lamborghini Diablo Coupe 2001 0.03% +321 /scratch/Teaching/cars/car_ims/004932.jpg Chevrolet Impala Sedan 2007 Maybach Landaulet Convertible 2012 82.86% Ford GT Coupe 2006 5.31% Mercedes-Benz SL-Class Coupe 2009 4.93% Bugatti Veyron 16.4 Convertible 2009 2.57% Spyker C8 Coupe 2009 1.34% +322 /scratch/Teaching/cars/car_ims/000277.jpg Acura TL Type-S 2008 Acura TL Type-S 2008 99.97% Acura RL Sedan 2012 0.02% Mitsubishi Lancer Sedan 2012 0.0% Chevrolet Impala Sedan 2007 0.0% Honda Accord Sedan 2012 0.0% +323 /scratch/Teaching/cars/car_ims/007678.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 99.99% Dodge Caliber Wagon 2012 0.0% Dodge Durango SUV 2007 0.0% Dodge Charger Sedan 2012 0.0% Infiniti QX56 SUV 2011 0.0% +324 /scratch/Teaching/cars/car_ims/008349.jpg Ferrari 458 Italia Convertible 2012 Ferrari California Convertible 2012 41.36% Ferrari 458 Italia Coupe 2012 36.75% Ferrari 458 Italia Convertible 2012 6.39% Dodge Charger Sedan 2012 5.15% Audi TT RS Coupe 2012 1.38% +325 /scratch/Teaching/cars/car_ims/003694.jpg Bugatti Veyron 16.4 Coupe 2009 Audi S5 Convertible 2012 71.55% Bugatti Veyron 16.4 Convertible 2009 17.66% Audi RS 4 Convertible 2008 8.87% Audi TTS Coupe 2012 1.57% Chevrolet Sonic Sedan 2012 0.12% +326 /scratch/Teaching/cars/car_ims/010035.jpg GMC Savana Van 2012 Chevrolet Express Van 2007 37.49% GMC Savana Van 2012 35.94% Chevrolet Express Cargo Van 2007 13.61% Volkswagen Golf Hatchback 1991 12.79% Audi V8 Sedan 1994 0.11% +327 /scratch/Teaching/cars/car_ims/015965.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 100.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Volkswagen Golf Hatchback 1991 0.0% Volvo XC90 SUV 2007 0.0% Ford Ranger SuperCab 2011 0.0% +328 /scratch/Teaching/cars/car_ims/002291.jpg BMW 3 Series Sedan 2012 Ferrari FF Coupe 2012 32.25% Ferrari 458 Italia Convertible 2012 26.15% Ferrari 458 Italia Coupe 2012 25.83% Bugatti Veyron 16.4 Coupe 2009 9.52% Spyker C8 Coupe 2009 2.61% +329 /scratch/Teaching/cars/car_ims/014383.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 71.42% Maybach Landaulet Convertible 2012 28.44% Bugatti Veyron 16.4 Convertible 2009 0.06% Bentley Continental Flying Spur Sedan 2007 0.03% MINI Cooper Roadster Convertible 2012 0.02% +330 /scratch/Teaching/cars/car_ims/001160.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 81.84% Audi TT Hatchback 2011 16.9% Mercedes-Benz SL-Class Coupe 2009 0.38% Mitsubishi Lancer Sedan 2012 0.31% Audi TT RS Coupe 2012 0.22% +331 /scratch/Teaching/cars/car_ims/000145.jpg Acura RL Sedan 2012 Acura TSX Sedan 2012 99.93% Acura RL Sedan 2012 0.06% Acura TL Sedan 2012 0.02% Acura ZDX Hatchback 2012 0.0% Honda Accord Coupe 2012 0.0% +332 /scratch/Teaching/cars/car_ims/012308.jpg Lamborghini Reventon Coupe 2008 Lamborghini Reventon Coupe 2008 99.99% Lamborghini Aventador Coupe 2012 0.01% Mercedes-Benz SL-Class Coupe 2009 0.0% Bugatti Veyron 16.4 Coupe 2009 0.0% Bugatti Veyron 16.4 Convertible 2009 0.0% +333 /scratch/Teaching/cars/car_ims/012830.jpg Lincoln Town Car Sedan 2011 Audi 100 Wagon 1994 62.74% Audi V8 Sedan 1994 31.76% Mercedes-Benz 300-Class Convertible 1993 1.33% Bentley Arnage Sedan 2009 1.12% Volkswagen Golf Hatchback 1991 0.72% +334 /scratch/Teaching/cars/car_ims/014310.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 100.0% Chrysler Town and Country Minivan 2012 0.0% Chevrolet Impala Sedan 2007 0.0% Suzuki SX4 Sedan 2012 0.0% Ford Freestar Minivan 2007 0.0% +335 /scratch/Teaching/cars/car_ims/008263.jpg Ferrari California Convertible 2012 Chevrolet Corvette Convertible 2012 80.66% Ferrari California Convertible 2012 15.22% Ferrari 458 Italia Convertible 2012 3.6% Chevrolet Camaro Convertible 2012 0.29% BMW Z4 Convertible 2012 0.15% +336 /scratch/Teaching/cars/car_ims/005342.jpg Chevrolet Cobalt SS 2010 Chevrolet Cobalt SS 2010 99.99% Suzuki Kizashi Sedan 2012 0.0% Hyundai Elantra Sedan 2007 0.0% Toyota Corolla Sedan 2012 0.0% Buick Verano Sedan 2012 0.0% +337 /scratch/Teaching/cars/car_ims/008726.jpg Ford Mustang Convertible 2007 Ford Mustang Convertible 2007 100.0% Audi 100 Sedan 1994 0.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Audi V8 Sedan 1994 0.0% Dodge Charger Sedan 2012 0.0% +338 /scratch/Teaching/cars/car_ims/008665.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 100.0% Ford F-150 Regular Cab 2012 0.0% Ford Expedition EL SUV 2009 0.0% HUMMER H2 SUT Crew Cab 2009 0.0% Toyota Sequoia SUV 2012 0.0% +339 /scratch/Teaching/cars/car_ims/002664.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 52.47% BMW 1 Series Coupe 2012 40.66% Volvo C30 Hatchback 2012 3.78% Nissan Juke Hatchback 2012 1.03% BMW 3 Series Sedan 2012 1.02% +340 /scratch/Teaching/cars/car_ims/000024.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 78.07% HUMMER H2 SUT Crew Cab 2009 21.75% HUMMER H3T Crew Cab 2010 0.16% Lamborghini Aventador Coupe 2012 0.01% McLaren MP4-12C Coupe 2012 0.0% +341 /scratch/Teaching/cars/car_ims/015973.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 99.84% Volvo XC90 SUV 2007 0.15% Mercedes-Benz 300-Class Convertible 1993 0.0% Jeep Patriot SUV 2012 0.0% Audi 100 Wagon 1994 0.0% +342 /scratch/Teaching/cars/car_ims/014127.jpg Plymouth Neon Coupe 1999 Plymouth Neon Coupe 1999 99.8% Ford Focus Sedan 2007 0.2% Hyundai Elantra Touring Hatchback 2012 0.0% Suzuki Aerio Sedan 2007 0.0% Eagle Talon Hatchback 1998 0.0% +343 /scratch/Teaching/cars/car_ims/007476.jpg Dodge Magnum Wagon 2008 Dodge Magnum Wagon 2008 100.0% Dodge Charger SRT-8 2009 0.0% Chevrolet HHR SS 2010 0.0% Dodge Charger Sedan 2012 0.0% Chevrolet Camaro Convertible 2012 0.0% +344 /scratch/Teaching/cars/car_ims/015381.jpg Toyota Camry Sedan 2012 Toyota Corolla Sedan 2012 96.81% Scion xD Hatchback 2012 2.58% Toyota Camry Sedan 2012 0.26% Suzuki SX4 Sedan 2012 0.13% Chevrolet Cobalt SS 2010 0.07% +345 /scratch/Teaching/cars/car_ims/007769.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 67.12% Chrysler Aspen SUV 2009 27.21% GMC Yukon Hybrid SUV 2012 2.77% Dodge Caliber Wagon 2012 0.52% Mazda Tribute SUV 2011 0.43% +346 /scratch/Teaching/cars/car_ims/009388.jpg Ford Focus Sedan 2007 Lincoln Town Car Sedan 2011 29.84% Ford Focus Sedan 2007 20.45% Mercedes-Benz 300-Class Convertible 1993 13.38% Audi 100 Wagon 1994 11.57% Geo Metro Convertible 1993 7.61% +347 /scratch/Teaching/cars/car_ims/014738.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 99.37% Spyker C8 Coupe 2009 0.6% Hyundai Veloster Hatchback 2012 0.02% Volvo C30 Hatchback 2012 0.0% Aston Martin Virage Coupe 2012 0.0% +348 /scratch/Teaching/cars/car_ims/006310.jpg Chrysler Town and Country Minivan 2012 Dodge Caliber Wagon 2012 76.04% Chrysler Town and Country Minivan 2012 23.72% Chrysler PT Cruiser Convertible 2008 0.23% Chevrolet Malibu Sedan 2007 0.0% Dodge Magnum Wagon 2008 0.0% +349 /scratch/Teaching/cars/car_ims/016167.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 98.91% FIAT 500 Convertible 2012 0.74% MINI Cooper Roadster Convertible 2012 0.34% Scion xD Hatchback 2012 0.01% Chrysler PT Cruiser Convertible 2008 0.0% +350 /scratch/Teaching/cars/car_ims/015279.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.84% Infiniti QX56 SUV 2011 0.12% Ford Expedition EL SUV 2009 0.02% Toyota 4Runner SUV 2012 0.01% Ford F-450 Super Duty Crew Cab 2012 0.01% +351 /scratch/Teaching/cars/car_ims/015944.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 99.94% Volkswagen Golf Hatchback 1991 0.06% Buick Rainier SUV 2007 0.0% Audi V8 Sedan 1994 0.0% Bentley Arnage Sedan 2009 0.0% +352 /scratch/Teaching/cars/car_ims/015578.jpg Toyota 4Runner SUV 2012 Toyota Sequoia SUV 2012 99.7% Jeep Compass SUV 2012 0.06% BMW X3 SUV 2012 0.05% Dodge Durango SUV 2012 0.04% Toyota 4Runner SUV 2012 0.03% +353 /scratch/Teaching/cars/car_ims/009330.jpg Ford F-150 Regular Cab 2007 Ford Mustang Convertible 2007 80.67% Chrysler 300 SRT-8 2010 10.64% Chevrolet TrailBlazer SS 2009 3.07% Mercedes-Benz 300-Class Convertible 1993 1.24% Dodge Charger SRT-8 2009 1.14% +354 /scratch/Teaching/cars/car_ims/003812.jpg Buick Rainier SUV 2007 Jeep Patriot SUV 2012 80.57% Jeep Liberty SUV 2012 6.4% Rolls-Royce Phantom Sedan 2012 5.34% Chevrolet TrailBlazer SS 2009 2.88% Dodge Durango SUV 2007 2.69% +355 /scratch/Teaching/cars/car_ims/003823.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 99.21% Volkswagen Golf Hatchback 1991 0.78% Ford Mustang Convertible 2007 0.01% Ford Focus Sedan 2007 0.0% Audi 100 Wagon 1994 0.0% +356 /scratch/Teaching/cars/car_ims/003564.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 99.97% Bentley Mulsanne Sedan 2011 0.03% Bentley Continental GT Coupe 2007 0.0% Bentley Continental GT Coupe 2012 0.0% Mercedes-Benz S-Class Sedan 2012 0.0% +357 /scratch/Teaching/cars/car_ims/012659.jpg Land Rover Range Rover SUV 2012 Land Rover Range Rover SUV 2012 99.89% Ford Expedition EL SUV 2009 0.06% Land Rover LR2 SUV 2012 0.03% Infiniti QX56 SUV 2011 0.01% Chrysler Aspen SUV 2009 0.01% +358 /scratch/Teaching/cars/car_ims/015287.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.99% Toyota 4Runner SUV 2012 0.01% Mazda Tribute SUV 2011 0.0% Dodge Durango SUV 2012 0.0% BMW X3 SUV 2012 0.0% +359 /scratch/Teaching/cars/car_ims/009173.jpg Ford GT Coupe 2006 Lamborghini Diablo Coupe 2001 99.88% McLaren MP4-12C Coupe 2012 0.11% Ferrari 458 Italia Convertible 2012 0.01% BMW Z4 Convertible 2012 0.0% Audi RS 4 Convertible 2008 0.0% +360 /scratch/Teaching/cars/car_ims/013266.jpg Mercedes-Benz C-Class Sedan 2012 Hyundai Genesis Sedan 2012 59.0% Hyundai Sonata Sedan 2012 34.5% Honda Accord Sedan 2012 4.15% Mercedes-Benz E-Class Sedan 2012 1.01% Mercedes-Benz C-Class Sedan 2012 0.68% +361 /scratch/Teaching/cars/car_ims/004553.jpg Chevrolet Corvette ZR1 2012 Chevrolet Corvette ZR1 2012 99.99% Porsche Panamera Sedan 2012 0.01% Audi S5 Convertible 2012 0.0% Suzuki SX4 Sedan 2012 0.0% Audi S4 Sedan 2007 0.0% +362 /scratch/Teaching/cars/car_ims/009374.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 89.09% Ford F-150 Regular Cab 2012 10.83% Nissan NV Passenger Van 2012 0.04% Ford Ranger SuperCab 2011 0.02% Ford E-Series Wagon Van 2012 0.02% +363 /scratch/Teaching/cars/car_ims/015096.jpg Suzuki SX4 Sedan 2012 Hyundai Veracruz SUV 2012 80.49% Chevrolet Traverse SUV 2012 17.27% Suzuki SX4 Hatchback 2012 1.22% Mazda Tribute SUV 2011 0.4% GMC Acadia SUV 2012 0.36% +364 /scratch/Teaching/cars/car_ims/008828.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 53.41% Ram C/V Cargo Van Minivan 2012 14.05% Dodge Caravan Minivan 1997 13.05% Mercedes-Benz Sprinter Van 2012 11.58% Buick Rainier SUV 2007 2.54% +365 /scratch/Teaching/cars/car_ims/013404.jpg Mercedes-Benz SL-Class Coupe 2009 Mercedes-Benz SL-Class Coupe 2009 100.0% Hyundai Genesis Sedan 2012 0.0% Hyundai Sonata Hybrid Sedan 2012 0.0% Aston Martin Virage Convertible 2012 0.0% Mercedes-Benz C-Class Sedan 2012 0.0% +366 /scratch/Teaching/cars/car_ims/010800.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 96.69% Ford Edge SUV 2012 0.75% Hyundai Veracruz SUV 2012 0.64% Toyota Sequoia SUV 2012 0.58% Jeep Compass SUV 2012 0.32% +367 /scratch/Teaching/cars/car_ims/014414.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 99.98% Mercedes-Benz 300-Class Convertible 1993 0.02% Maybach Landaulet Convertible 2012 0.0% Bentley Continental Supersports Conv. Convertible 2012 0.0% BMW 1 Series Convertible 2012 0.0% +368 /scratch/Teaching/cars/car_ims/002266.jpg BMW 1 Series Coupe 2012 BMW 1 Series Coupe 2012 93.48% BMW X6 SUV 2012 4.37% BMW 3 Series Sedan 2012 1.12% Audi S4 Sedan 2012 0.64% Buick Verano Sedan 2012 0.13% +369 /scratch/Teaching/cars/car_ims/009733.jpg GMC Savana Van 2012 GMC Savana Van 2012 99.84% Chevrolet Express Cargo Van 2007 0.14% Chevrolet Express Van 2007 0.01% Audi V8 Sedan 1994 0.0% Volvo XC90 SUV 2007 0.0% +370 /scratch/Teaching/cars/car_ims/003846.jpg Buick Rainier SUV 2007 Volvo XC90 SUV 2007 62.0% Ford F-150 Regular Cab 2007 26.05% Mazda Tribute SUV 2011 6.35% Dodge Durango SUV 2007 0.97% Chevrolet TrailBlazer SS 2009 0.93% +371 /scratch/Teaching/cars/car_ims/014244.jpg Porsche Panamera Sedan 2012 Acura TL Type-S 2008 56.62% Acura TL Sedan 2012 10.54% Acura RL Sedan 2012 7.96% Infiniti G Coupe IPL 2012 5.72% Aston Martin Virage Convertible 2012 4.38% +372 /scratch/Teaching/cars/car_ims/005903.jpg Chevrolet Malibu Sedan 2007 Dodge Durango SUV 2007 41.3% Suzuki SX4 Hatchback 2012 15.44% Jeep Patriot SUV 2012 7.65% Dodge Caliber Wagon 2012 7.35% Scion xD Hatchback 2012 6.69% +373 /scratch/Teaching/cars/car_ims/000029.jpg AM General Hummer SUV 2000 Chevrolet Silverado 2500HD Regular Cab 2012 27.35% Ford F-150 Regular Cab 2012 14.84% Ford Ranger SuperCab 2011 12.99% Ford F-150 Regular Cab 2007 12.62% GMC Savana Van 2012 8.56% +374 /scratch/Teaching/cars/car_ims/014423.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Phantom Sedan 2012 39.55% Bentley Arnage Sedan 2009 32.79% Jeep Liberty SUV 2012 19.93% Jeep Compass SUV 2012 2.64% Jeep Grand Cherokee SUV 2012 1.88% +375 /scratch/Teaching/cars/car_ims/011224.jpg Hyundai Genesis Sedan 2012 Audi S5 Convertible 2012 63.05% Infiniti G Coupe IPL 2012 13.16% Audi S5 Coupe 2012 6.71% Audi S4 Sedan 2012 5.77% Audi TTS Coupe 2012 4.58% +376 /scratch/Teaching/cars/car_ims/001451.jpg Audi 100 Wagon 1994 Chevrolet Monte Carlo Coupe 2007 25.82% Hyundai Elantra Sedan 2007 13.48% Chevrolet Malibu Sedan 2007 12.24% Chevrolet Impala Sedan 2007 10.08% Ford F-150 Regular Cab 2007 6.61% +377 /scratch/Teaching/cars/car_ims/011438.jpg Hyundai Elantra Touring Hatchback 2012 Hyundai Elantra Touring Hatchback 2012 100.0% Volvo C30 Hatchback 2012 0.0% Volkswagen Golf Hatchback 2012 0.0% Suzuki SX4 Hatchback 2012 0.0% Daewoo Nubira Wagon 2002 0.0% +378 /scratch/Teaching/cars/car_ims/001650.jpg Audi S5 Convertible 2012 BMW 1 Series Convertible 2012 61.95% Chevrolet Sonic Sedan 2012 17.52% Jaguar XK XKR 2012 15.9% BMW M6 Convertible 2010 1.27% Ford Fiesta Sedan 2012 0.87% +379 /scratch/Teaching/cars/car_ims/007592.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 97.83% Audi S5 Coupe 2012 0.36% BMW ActiveHybrid 5 Sedan 2012 0.32% Jaguar XK XKR 2012 0.28% Buick Regal GS 2012 0.21% +380 /scratch/Teaching/cars/car_ims/002115.jpg BMW ActiveHybrid 5 Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 99.92% BMW Z4 Convertible 2012 0.08% BMW 3 Series Wagon 2012 0.0% BMW M5 Sedan 2010 0.0% BMW 6 Series Convertible 2007 0.0% +381 /scratch/Teaching/cars/car_ims/011727.jpg Isuzu Ascender SUV 2008 Isuzu Ascender SUV 2008 99.73% Jeep Compass SUV 2012 0.27% Volvo XC90 SUV 2007 0.0% Jeep Grand Cherokee SUV 2012 0.0% HUMMER H3T Crew Cab 2010 0.0% +382 /scratch/Teaching/cars/car_ims/013469.jpg Mercedes-Benz E-Class Sedan 2012 Mercedes-Benz E-Class Sedan 2012 75.1% Mercedes-Benz C-Class Sedan 2012 20.86% Mercedes-Benz S-Class Sedan 2012 3.77% Hyundai Genesis Sedan 2012 0.26% Audi S6 Sedan 2011 0.0% +383 /scratch/Teaching/cars/car_ims/001052.jpg Audi TTS Coupe 2012 Audi S5 Convertible 2012 52.12% BMW 1 Series Convertible 2012 26.88% Audi RS 4 Convertible 2008 5.17% BMW M6 Convertible 2010 4.0% Audi R8 Coupe 2012 3.69% +384 /scratch/Teaching/cars/car_ims/009676.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 99.99% Jeep Compass SUV 2012 0.01% Jeep Grand Cherokee SUV 2012 0.0% Dodge Caliber Wagon 2012 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% +385 /scratch/Teaching/cars/car_ims/011540.jpg Hyundai Azera Sedan 2012 Jaguar XK XKR 2012 37.75% Dodge Charger Sedan 2012 16.01% Chevrolet Corvette ZR1 2012 15.34% Ferrari California Convertible 2012 9.91% Aston Martin V8 Vantage Convertible 2012 6.31% +386 /scratch/Teaching/cars/car_ims/004615.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 93.85% Chevrolet Corvette Convertible 2012 3.97% Jaguar XK XKR 2012 1.2% Chevrolet Corvette ZR1 2012 0.71% Spyker C8 Convertible 2009 0.15% +387 /scratch/Teaching/cars/car_ims/009898.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 100.0% Buick Enclave SUV 2012 0.0% Ford Ranger SuperCab 2011 0.0% Cadillac SRX SUV 2012 0.0% Jeep Grand Cherokee SUV 2012 0.0% +388 /scratch/Teaching/cars/car_ims/001026.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 74.8% Audi S4 Sedan 2007 25.2% Audi S5 Coupe 2012 0.0% Audi S4 Sedan 2012 0.0% Mitsubishi Lancer Sedan 2012 0.0% +389 /scratch/Teaching/cars/car_ims/012162.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 94.45% Jeep Compass SUV 2012 5.55% GMC Terrain SUV 2012 0.0% Dodge Durango SUV 2007 0.0% Dodge Durango SUV 2012 0.0% +390 /scratch/Teaching/cars/car_ims/011125.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 96.93% Acura TSX Sedan 2012 1.28% Chevrolet Sonic Sedan 2012 0.64% Suzuki SX4 Hatchback 2012 0.38% Mitsubishi Lancer Sedan 2012 0.27% +391 /scratch/Teaching/cars/car_ims/015324.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.99% Ford Expedition EL SUV 2009 0.01% Hyundai Santa Fe SUV 2012 0.0% Infiniti QX56 SUV 2011 0.0% Land Rover LR2 SUV 2012 0.0% +392 /scratch/Teaching/cars/car_ims/004953.jpg Chevrolet Impala Sedan 2007 Volkswagen Golf Hatchback 2012 50.81% Chrysler Crossfire Convertible 2008 12.8% BMW 6 Series Convertible 2007 5.98% BMW 1 Series Convertible 2012 4.48% Honda Accord Sedan 2012 4.14% +393 /scratch/Teaching/cars/car_ims/011876.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 95.16% Jeep Compass SUV 2012 3.66% Chevrolet TrailBlazer SS 2009 0.93% Jeep Liberty SUV 2012 0.24% Land Rover Range Rover SUV 2012 0.01% +394 /scratch/Teaching/cars/car_ims/007754.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 52.54% Chrysler Aspen SUV 2009 34.45% Jeep Liberty SUV 2012 8.45% Jeep Patriot SUV 2012 2.17% Cadillac Escalade EXT Crew Cab 2007 2.01% +395 /scratch/Teaching/cars/car_ims/008589.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 98.83% Audi TTS Coupe 2012 0.64% Aston Martin V8 Vantage Coupe 2012 0.18% Tesla Model S Sedan 2012 0.16% Aston Martin Virage Coupe 2012 0.11% +396 /scratch/Teaching/cars/car_ims/008551.jpg Fisker Karma Sedan 2012 Spyker C8 Coupe 2009 55.87% Spyker C8 Convertible 2009 42.48% Hyundai Veloster Hatchback 2012 1.13% Ford GT Coupe 2006 0.17% Bugatti Veyron 16.4 Convertible 2009 0.09% +397 /scratch/Teaching/cars/car_ims/010555.jpg Honda Accord Coupe 2012 Honda Accord Coupe 2012 62.02% Jaguar XK XKR 2012 7.33% Chevrolet Camaro Convertible 2012 6.53% Chevrolet Corvette Convertible 2012 3.85% Hyundai Veloster Hatchback 2012 1.83% +398 /scratch/Teaching/cars/car_ims/009647.jpg GMC Terrain SUV 2012 Hyundai Veracruz SUV 2012 40.54% Volvo XC90 SUV 2007 13.78% Chevrolet Traverse SUV 2012 8.1% Mazda Tribute SUV 2011 7.66% Hyundai Tucson SUV 2012 3.96% +399 /scratch/Teaching/cars/car_ims/012971.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 99.94% Nissan Leaf Hatchback 2012 0.02% Rolls-Royce Phantom Sedan 2012 0.01% Chevrolet Sonic Sedan 2012 0.01% Chevrolet Malibu Sedan 2007 0.01% +400 /scratch/Teaching/cars/car_ims/013113.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 99.99% Lamborghini Aventador Coupe 2012 0.01% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.0% Aston Martin Virage Coupe 2012 0.0% Ferrari 458 Italia Coupe 2012 0.0% +401 /scratch/Teaching/cars/car_ims/006956.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 99.97% Plymouth Neon Coupe 1999 0.02% Lincoln Town Car Sedan 2011 0.0% Chrysler Aspen SUV 2009 0.0% Hyundai Santa Fe SUV 2012 0.0% +402 /scratch/Teaching/cars/car_ims/010404.jpg Honda Odyssey Minivan 2012 BMW X6 SUV 2012 35.97% Hyundai Veracruz SUV 2012 32.52% BMW X3 SUV 2012 9.77% Chevrolet Sonic Sedan 2012 4.59% Acura ZDX Hatchback 2012 3.67% +403 /scratch/Teaching/cars/car_ims/013135.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 99.99% Lamborghini Aventador Coupe 2012 0.0% Spyker C8 Coupe 2009 0.0% Bugatti Veyron 16.4 Coupe 2009 0.0% Spyker C8 Convertible 2009 0.0% +404 /scratch/Teaching/cars/car_ims/011991.jpg Jeep Wrangler SUV 2012 Jeep Wrangler SUV 2012 99.99% HUMMER H3T Crew Cab 2010 0.01% GMC Canyon Extended Cab 2012 0.0% AM General Hummer SUV 2000 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% +405 /scratch/Teaching/cars/car_ims/002250.jpg BMW 1 Series Coupe 2012 BMW 1 Series Coupe 2012 78.98% BMW 1 Series Convertible 2012 11.55% BMW X6 SUV 2012 9.29% BMW Z4 Convertible 2012 0.07% Dodge Caliber Wagon 2007 0.05% +406 /scratch/Teaching/cars/car_ims/013497.jpg Mercedes-Benz S-Class Sedan 2012 Mercedes-Benz S-Class Sedan 2012 99.96% Suzuki Kizashi Sedan 2012 0.04% Chrysler 300 SRT-8 2010 0.0% Ford Focus Sedan 2007 0.0% Chrysler Sebring Convertible 2010 0.0% +407 /scratch/Teaching/cars/car_ims/011077.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 42.9% Chevrolet Malibu Hybrid Sedan 2010 23.29% Acura RL Sedan 2012 13.28% Acura TSX Sedan 2012 9.32% Buick Verano Sedan 2012 8.38% +408 /scratch/Teaching/cars/car_ims/015949.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 99.95% Audi 100 Wagon 1994 0.05% Mercedes-Benz 300-Class Convertible 1993 0.0% BMW 3 Series Wagon 2012 0.0% Volkswagen Golf Hatchback 1991 0.0% +409 /scratch/Teaching/cars/car_ims/003900.jpg Buick Verano Sedan 2012 Hyundai Accent Sedan 2012 47.15% Hyundai Sonata Sedan 2012 18.37% Dodge Journey SUV 2012 15.55% Chevrolet Sonic Sedan 2012 7.51% Toyota Corolla Sedan 2012 2.63% +410 /scratch/Teaching/cars/car_ims/009294.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2012 57.11% Ford F-150 Regular Cab 2007 19.15% Ford Ranger SuperCab 2011 6.23% Toyota 4Runner SUV 2012 4.63% Dodge Ram Pickup 3500 Crew Cab 2010 2.41% +411 /scratch/Teaching/cars/car_ims/013363.jpg Mercedes-Benz SL-Class Coupe 2009 Audi R8 Coupe 2012 67.97% Porsche Panamera Sedan 2012 11.79% BMW ActiveHybrid 5 Sedan 2012 11.64% Audi S5 Coupe 2012 4.79% Mercedes-Benz SL-Class Coupe 2009 1.03% +412 /scratch/Teaching/cars/car_ims/005909.jpg Chevrolet Malibu Sedan 2007 Fisker Karma Sedan 2012 91.56% Hyundai Sonata Sedan 2012 4.04% Hyundai Genesis Sedan 2012 1.89% Chevrolet Corvette ZR1 2012 1.12% Infiniti G Coupe IPL 2012 0.28% +413 /scratch/Teaching/cars/car_ims/012223.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 100.0% Jeep Grand Cherokee SUV 2012 0.0% BMW X5 SUV 2007 0.0% BMW X3 SUV 2012 0.0% Volvo XC90 SUV 2007 0.0% +414 /scratch/Teaching/cars/car_ims/001412.jpg Audi 100 Wagon 1994 Audi 100 Sedan 1994 97.04% Volkswagen Golf Hatchback 1991 2.6% Audi V8 Sedan 1994 0.32% Audi 100 Wagon 1994 0.03% Mercedes-Benz 300-Class Convertible 1993 0.01% +415 /scratch/Teaching/cars/car_ims/012399.jpg Lamborghini Aventador Coupe 2012 Lamborghini Aventador Coupe 2012 95.84% Ferrari 458 Italia Convertible 2012 3.11% McLaren MP4-12C Coupe 2012 1.03% Mercedes-Benz SL-Class Coupe 2009 0.01% Spyker C8 Coupe 2009 0.01% +416 /scratch/Teaching/cars/car_ims/007952.jpg Dodge Charger SRT-8 2009 Dodge Charger SRT-8 2009 99.95% Dodge Magnum Wagon 2008 0.04% Chevrolet Camaro Convertible 2012 0.0% Dodge Charger Sedan 2012 0.0% Audi A5 Coupe 2012 0.0% +417 /scratch/Teaching/cars/car_ims/009266.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 98.82% Dodge Ram Pickup 3500 Crew Cab 2010 0.53% Ford E-Series Wagon Van 2012 0.31% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.25% Chevrolet Silverado 1500 Regular Cab 2012 0.03% +418 /scratch/Teaching/cars/car_ims/009440.jpg Ford Focus Sedan 2007 BMW 1 Series Convertible 2012 99.6% BMW Z4 Convertible 2012 0.36% Maybach Landaulet Convertible 2012 0.01% Mercedes-Benz S-Class Sedan 2012 0.01% Audi S5 Convertible 2012 0.01% +419 /scratch/Teaching/cars/car_ims/013751.jpg Mitsubishi Lancer Sedan 2012 Land Rover LR2 SUV 2012 80.46% Hyundai Veracruz SUV 2012 11.48% Toyota 4Runner SUV 2012 2.46% Acura TL Type-S 2008 0.93% Honda Odyssey Minivan 2012 0.76% +420 /scratch/Teaching/cars/car_ims/013403.jpg Mercedes-Benz SL-Class Coupe 2009 Mercedes-Benz SL-Class Coupe 2009 99.16% Audi TTS Coupe 2012 0.32% Hyundai Elantra Touring Hatchback 2012 0.24% Ford Fiesta Sedan 2012 0.06% Volkswagen Golf Hatchback 2012 0.06% +421 /scratch/Teaching/cars/car_ims/005810.jpg Chevrolet Monte Carlo Coupe 2007 Suzuki Kizashi Sedan 2012 49.86% Chevrolet Malibu Hybrid Sedan 2010 12.19% BMW M5 Sedan 2010 7.35% Chevrolet Cobalt SS 2010 6.1% Jaguar XK XKR 2012 4.95% +422 /scratch/Teaching/cars/car_ims/000698.jpg Aston Martin V8 Vantage Coupe 2012 Aston Martin V8 Vantage Coupe 2012 82.16% Aston Martin V8 Vantage Convertible 2012 17.84% Aston Martin Virage Convertible 2012 0.0% Lamborghini Reventon Coupe 2008 0.0% Jaguar XK XKR 2012 0.0% +423 /scratch/Teaching/cars/car_ims/002327.jpg BMW 3 Series Sedan 2012 BMW 3 Series Sedan 2012 97.74% BMW 1 Series Coupe 2012 1.01% BMW Z4 Convertible 2012 0.48% BMW 3 Series Wagon 2012 0.3% Chevrolet Sonic Sedan 2012 0.15% +424 /scratch/Teaching/cars/car_ims/005186.jpg Chevrolet Express Cargo Van 2007 GMC Savana Van 2012 49.3% Chevrolet Express Cargo Van 2007 27.33% Chevrolet Express Van 2007 23.21% AM General Hummer SUV 2000 0.08% Jeep Wrangler SUV 2012 0.03% +425 /scratch/Teaching/cars/car_ims/002812.jpg BMW M5 Sedan 2010 BMW M5 Sedan 2010 98.55% BMW M6 Convertible 2010 1.3% BMW M3 Coupe 2012 0.11% BMW 6 Series Convertible 2007 0.01% Jaguar XK XKR 2012 0.01% +426 /scratch/Teaching/cars/car_ims/014385.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Sedan 2012 99.62% Rolls-Royce Ghost Sedan 2012 0.38% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Maybach Landaulet Convertible 2012 0.0% Bentley Mulsanne Sedan 2011 0.0% +427 /scratch/Teaching/cars/car_ims/009864.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 100.0% Ford Ranger SuperCab 2011 0.0% Buick Enclave SUV 2012 0.0% Chevrolet Traverse SUV 2012 0.0% GMC Yukon Hybrid SUV 2012 0.0% +428 /scratch/Teaching/cars/car_ims/005652.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chevrolet Silverado 1500 Classic Extended Cab 2007 99.83% Ford Ranger SuperCab 2011 0.16% Chrysler Aspen SUV 2009 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% Chevrolet Silverado 1500 Extended Cab 2012 0.0% +429 /scratch/Teaching/cars/car_ims/009984.jpg GMC Canyon Extended Cab 2012 Dodge Ram Pickup 3500 Quad Cab 2009 26.02% Dodge Dakota Club Cab 2007 17.41% Dodge Dakota Crew Cab 2010 15.71% Isuzu Ascender SUV 2008 12.89% Jeep Compass SUV 2012 7.43% +430 /scratch/Teaching/cars/car_ims/014469.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Ghost Sedan 2012 77.94% Rolls-Royce Phantom Sedan 2012 9.81% BMW 6 Series Convertible 2007 3.99% Fisker Karma Sedan 2012 3.58% Tesla Model S Sedan 2012 2.18% +431 /scratch/Teaching/cars/car_ims/005406.jpg Chevrolet Malibu Hybrid Sedan 2010 Toyota Camry Sedan 2012 84.56% Acura TSX Sedan 2012 10.77% Acura TL Sedan 2012 4.15% Chevrolet Monte Carlo Coupe 2007 0.17% Suzuki SX4 Sedan 2012 0.09% +432 /scratch/Teaching/cars/car_ims/003969.jpg Buick Enclave SUV 2012 Buick Enclave SUV 2012 100.0% Suzuki Kizashi Sedan 2012 0.0% Hyundai Elantra Touring Hatchback 2012 0.0% Nissan Juke Hatchback 2012 0.0% Ford Focus Sedan 2007 0.0% +433 /scratch/Teaching/cars/car_ims/012313.jpg Lamborghini Reventon Coupe 2008 Lamborghini Reventon Coupe 2008 99.99% Aston Martin V8 Vantage Convertible 2012 0.01% Fisker Karma Sedan 2012 0.0% BMW 6 Series Convertible 2007 0.0% Bugatti Veyron 16.4 Coupe 2009 0.0% +434 /scratch/Teaching/cars/car_ims/014768.jpg Spyker C8 Coupe 2009 Ford GT Coupe 2006 53.1% Spyker C8 Coupe 2009 35.73% Spyker C8 Convertible 2009 10.11% Ford F-150 Regular Cab 2007 0.44% Nissan NV Passenger Van 2012 0.11% +435 /scratch/Teaching/cars/car_ims/002802.jpg BMW M5 Sedan 2010 Chevrolet Corvette Ron Fellows Edition Z06 2007 48.07% Jaguar XK XKR 2012 18.21% Chevrolet Corvette ZR1 2012 12.63% BMW ActiveHybrid 5 Sedan 2012 3.31% Mercedes-Benz SL-Class Coupe 2009 3.09% +436 /scratch/Teaching/cars/car_ims/013139.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 60.2% Lamborghini Diablo Coupe 2001 28.41% Ferrari 458 Italia Convertible 2012 4.31% Ferrari 458 Italia Coupe 2012 2.64% Lamborghini Aventador Coupe 2012 2.33% +437 /scratch/Teaching/cars/car_ims/004653.jpg Chevrolet Traverse SUV 2012 Hyundai Tucson SUV 2012 32.5% Hyundai Veracruz SUV 2012 29.33% Hyundai Santa Fe SUV 2012 18.96% Chevrolet Traverse SUV 2012 16.11% smart fortwo Convertible 2012 1.44% +438 /scratch/Teaching/cars/car_ims/004806.jpg Chevrolet Camaro Convertible 2012 Chevrolet Sonic Sedan 2012 26.61% Toyota Corolla Sedan 2012 18.1% Chevrolet Cobalt SS 2010 15.83% Chevrolet Camaro Convertible 2012 9.97% Dodge Journey SUV 2012 8.12% +439 /scratch/Teaching/cars/car_ims/007292.jpg Dodge Journey SUV 2012 Volkswagen Golf Hatchback 2012 96.06% Dodge Journey SUV 2012 2.21% Hyundai Genesis Sedan 2012 1.48% Toyota Corolla Sedan 2012 0.23% Nissan 240SX Coupe 1998 0.0% +440 /scratch/Teaching/cars/car_ims/003526.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Mulsanne Sedan 2011 99.03% Bentley Continental Flying Spur Sedan 2007 0.64% Bentley Continental GT Coupe 2007 0.32% Bentley Continental GT Coupe 2012 0.01% Bentley Arnage Sedan 2009 0.0% +441 /scratch/Teaching/cars/car_ims/012011.jpg Jeep Wrangler SUV 2012 Spyker C8 Coupe 2009 50.54% Spyker C8 Convertible 2009 46.21% Aston Martin Virage Coupe 2012 0.92% Aston Martin Virage Convertible 2012 0.6% Hyundai Veloster Hatchback 2012 0.38% +442 /scratch/Teaching/cars/car_ims/012291.jpg Lamborghini Reventon Coupe 2008 Lamborghini Reventon Coupe 2008 99.64% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.33% Lamborghini Aventador Coupe 2012 0.03% McLaren MP4-12C Coupe 2012 0.0% Mercedes-Benz SL-Class Coupe 2009 0.0% +443 /scratch/Teaching/cars/car_ims/013933.jpg Nissan Juke Hatchback 2012 Nissan Juke Hatchback 2012 88.16% Volkswagen Golf Hatchback 2012 11.31% Chevrolet Traverse SUV 2012 0.15% Acura ZDX Hatchback 2012 0.09% Hyundai Tucson SUV 2012 0.08% +444 /scratch/Teaching/cars/car_ims/007158.jpg Dodge Sprinter Cargo Van 2009 Honda Odyssey Minivan 2007 71.46% Honda Accord Sedan 2012 12.8% Hyundai Elantra Sedan 2007 5.19% Dodge Sprinter Cargo Van 2009 4.43% Daewoo Nubira Wagon 2002 1.74% +445 /scratch/Teaching/cars/car_ims/010652.jpg Honda Accord Sedan 2012 Hyundai Genesis Sedan 2012 47.91% Hyundai Azera Sedan 2012 45.23% Honda Accord Sedan 2012 6.11% Hyundai Sonata Sedan 2012 0.47% Mercedes-Benz C-Class Sedan 2012 0.19% +446 /scratch/Teaching/cars/car_ims/000416.jpg Acura Integra Type R 2001 Acura Integra Type R 2001 100.0% Lamborghini Diablo Coupe 2001 0.0% Chevrolet Corvette Convertible 2012 0.0% Chevrolet Cobalt SS 2010 0.0% Ford Mustang Convertible 2007 0.0% +447 /scratch/Teaching/cars/car_ims/014945.jpg Suzuki Kizashi Sedan 2012 Chevrolet HHR SS 2010 41.05% Suzuki Kizashi Sedan 2012 29.28% Volvo C30 Hatchback 2012 29.13% Dodge Journey SUV 2012 0.16% Suzuki SX4 Hatchback 2012 0.14% +448 /scratch/Teaching/cars/car_ims/005530.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 82.1% Ford F-150 Regular Cab 2012 9.63% Chevrolet Silverado 1500 Regular Cab 2012 5.28% Chevrolet Silverado 2500HD Regular Cab 2012 1.48% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.47% +449 /scratch/Teaching/cars/car_ims/001845.jpg Audi S4 Sedan 2012 Audi S5 Convertible 2012 42.51% Audi S4 Sedan 2012 27.95% Audi TT RS Coupe 2012 17.25% Audi A5 Coupe 2012 4.63% Audi TTS Coupe 2012 2.36% +450 /scratch/Teaching/cars/car_ims/004226.jpg Cadillac Escalade EXT Crew Cab 2007 GMC Acadia SUV 2012 44.07% Volvo XC90 SUV 2007 21.8% GMC Yukon Hybrid SUV 2012 17.02% Cadillac Escalade EXT Crew Cab 2007 13.46% Jeep Compass SUV 2012 1.04% +451 /scratch/Teaching/cars/car_ims/002516.jpg BMW 6 Series Convertible 2007 BMW M6 Convertible 2010 88.54% BMW 1 Series Convertible 2012 4.95% BMW Z4 Convertible 2012 2.69% Audi RS 4 Convertible 2008 2.5% Chevrolet Camaro Convertible 2012 0.41% +452 /scratch/Teaching/cars/car_ims/011648.jpg Infiniti QX56 SUV 2011 Infiniti QX56 SUV 2011 46.48% Volvo XC90 SUV 2007 23.21% BMW X3 SUV 2012 11.34% Buick Enclave SUV 2012 9.19% Buick Verano Sedan 2012 5.0% +453 /scratch/Teaching/cars/car_ims/005093.jpg Chevrolet Sonic Sedan 2012 Chevrolet Sonic Sedan 2012 98.02% Volvo C30 Hatchback 2012 1.4% Dodge Journey SUV 2012 0.3% BMW X6 SUV 2012 0.15% Toyota Corolla Sedan 2012 0.07% +454 /scratch/Teaching/cars/car_ims/008321.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 72.24% Ferrari 458 Italia Convertible 2012 27.38% Chevrolet Corvette Convertible 2012 0.37% Ferrari 458 Italia Coupe 2012 0.0% Chevrolet Camaro Convertible 2012 0.0% +455 /scratch/Teaching/cars/car_ims/014458.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Ghost Sedan 2012 99.85% Rolls-Royce Phantom Sedan 2012 0.15% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Audi S6 Sedan 2011 0.0% Buick Regal GS 2012 0.0% +456 /scratch/Teaching/cars/car_ims/011027.jpg Hyundai Sonata Hybrid Sedan 2012 Ferrari FF Coupe 2012 28.46% Bugatti Veyron 16.4 Coupe 2009 16.82% Aston Martin V8 Vantage Convertible 2012 14.78% Chevrolet Corvette ZR1 2012 6.04% Lamborghini Reventon Coupe 2008 5.27% +457 /scratch/Teaching/cars/car_ims/010038.jpg GMC Savana Van 2012 GMC Savana Van 2012 79.2% Chevrolet Express Cargo Van 2007 20.42% Chevrolet Express Van 2007 0.38% Volkswagen Golf Hatchback 1991 0.0% Audi 100 Sedan 1994 0.0% +458 /scratch/Teaching/cars/car_ims/009238.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 74.71% Ford Expedition EL SUV 2009 19.58% Chrysler Aspen SUV 2009 1.93% GMC Acadia SUV 2012 1.37% GMC Canyon Extended Cab 2012 0.64% +459 /scratch/Teaching/cars/car_ims/002093.jpg BMW ActiveHybrid 5 Sedan 2012 Suzuki Kizashi Sedan 2012 50.49% Mitsubishi Lancer Sedan 2012 6.33% Infiniti G Coupe IPL 2012 6.24% Chevrolet Cobalt SS 2010 3.66% Toyota Camry Sedan 2012 3.36% +460 /scratch/Teaching/cars/car_ims/007336.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 99.84% Isuzu Ascender SUV 2008 0.1% Dodge Dakota Club Cab 2007 0.05% Dodge Ram Pickup 3500 Quad Cab 2009 0.01% Jeep Compass SUV 2012 0.0% +461 /scratch/Teaching/cars/car_ims/011947.jpg Jeep Wrangler SUV 2012 Jeep Wrangler SUV 2012 99.55% HUMMER H3T Crew Cab 2010 0.38% AM General Hummer SUV 2000 0.06% HUMMER H2 SUT Crew Cab 2009 0.01% Jeep Patriot SUV 2012 0.0% +462 /scratch/Teaching/cars/car_ims/003886.jpg Buick Rainier SUV 2007 Volkswagen Golf Hatchback 1991 44.81% Buick Rainier SUV 2007 44.6% Volvo 240 Sedan 1993 7.03% GMC Canyon Extended Cab 2012 1.08% GMC Acadia SUV 2012 0.81% +463 /scratch/Teaching/cars/car_ims/013212.jpg Mercedes-Benz 300-Class Convertible 1993 Mercedes-Benz 300-Class Convertible 1993 72.24% Nissan 240SX Coupe 1998 12.68% Audi 100 Wagon 1994 10.0% Volvo 240 Sedan 1993 3.27% Audi V8 Sedan 1994 0.97% +464 /scratch/Teaching/cars/car_ims/006447.jpg Chrysler Crossfire Convertible 2008 Dodge Journey SUV 2012 33.68% Hyundai Genesis Sedan 2012 31.09% Mercedes-Benz C-Class Sedan 2012 13.93% Hyundai Azera Sedan 2012 8.35% Honda Accord Sedan 2012 4.3% +465 /scratch/Teaching/cars/car_ims/014069.jpg Nissan 240SX Coupe 1998 BMW M6 Convertible 2010 64.32% Nissan 240SX Coupe 1998 19.95% Eagle Talon Hatchback 1998 11.19% Audi RS 4 Convertible 2008 3.24% BMW 6 Series Convertible 2007 0.44% +466 /scratch/Teaching/cars/car_ims/001355.jpg Audi 100 Sedan 1994 Audi 100 Sedan 1994 98.06% Plymouth Neon Coupe 1999 0.72% Audi 100 Wagon 1994 0.61% Geo Metro Convertible 1993 0.4% Audi V8 Sedan 1994 0.2% +467 /scratch/Teaching/cars/car_ims/012077.jpg Jeep Liberty SUV 2012 Buick Rainier SUV 2007 55.95% BMW X5 SUV 2007 22.67% Mazda Tribute SUV 2011 12.53% Volkswagen Golf Hatchback 1991 3.32% Chrysler 300 SRT-8 2010 2.11% +468 /scratch/Teaching/cars/car_ims/005632.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Ford F-450 Super Duty Crew Cab 2012 72.89% Mercedes-Benz E-Class Sedan 2012 22.05% Hyundai Genesis Sedan 2012 1.1% Mercedes-Benz C-Class Sedan 2012 1.05% Ford F-150 Regular Cab 2007 1.01% +469 /scratch/Teaching/cars/car_ims/000453.jpg Acura Integra Type R 2001 Mitsubishi Lancer Sedan 2012 34.23% Chevrolet Corvette ZR1 2012 25.54% Chevrolet Corvette Convertible 2012 7.87% Bugatti Veyron 16.4 Coupe 2009 7.13% Porsche Panamera Sedan 2012 3.87% +470 /scratch/Teaching/cars/car_ims/015438.jpg Toyota Corolla Sedan 2012 Chevrolet Traverse SUV 2012 39.97% Jaguar XK XKR 2012 26.99% BMW X6 SUV 2012 10.58% Ford Edge SUV 2012 8.19% Scion xD Hatchback 2012 7.37% +471 /scratch/Teaching/cars/car_ims/011934.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 100.0% Jeep Wrangler SUV 2012 0.0% Jeep Liberty SUV 2012 0.0% Jeep Compass SUV 2012 0.0% GMC Yukon Hybrid SUV 2012 0.0% +472 /scratch/Teaching/cars/car_ims/007109.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 99.87% Dodge Ram Pickup 3500 Crew Cab 2010 0.13% Dodge Dakota Club Cab 2007 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% Dodge Dakota Crew Cab 2010 0.0% +473 /scratch/Teaching/cars/car_ims/001523.jpg Audi TT Hatchback 2011 Jaguar XK XKR 2012 58.93% Porsche Panamera Sedan 2012 36.43% Audi R8 Coupe 2012 2.06% Audi TT RS Coupe 2012 1.01% Chevrolet Corvette ZR1 2012 0.4% +474 /scratch/Teaching/cars/car_ims/012994.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 99.9% Suzuki SX4 Hatchback 2012 0.07% Dodge Caliber Wagon 2012 0.01% BMW X3 SUV 2012 0.01% Jeep Grand Cherokee SUV 2012 0.01% +475 /scratch/Teaching/cars/car_ims/005420.jpg Chevrolet Malibu Hybrid Sedan 2010 Chevrolet Cobalt SS 2010 61.27% Chevrolet Malibu Hybrid Sedan 2010 26.01% Chrysler Sebring Convertible 2010 8.43% Honda Odyssey Minivan 2007 0.99% Honda Accord Sedan 2012 0.8% +476 /scratch/Teaching/cars/car_ims/003607.jpg Bugatti Veyron 16.4 Convertible 2009 Bugatti Veyron 16.4 Convertible 2009 87.79% Bugatti Veyron 16.4 Coupe 2009 5.37% Spyker C8 Coupe 2009 2.1% Chevrolet Corvette Ron Fellows Edition Z06 2007 1.88% Suzuki Aerio Sedan 2007 1.07% +477 /scratch/Teaching/cars/car_ims/014653.jpg Scion xD Hatchback 2012 Scion xD Hatchback 2012 96.91% Ford Fiesta Sedan 2012 2.97% Nissan Leaf Hatchback 2012 0.04% Hyundai Tucson SUV 2012 0.04% Suzuki Aerio Sedan 2007 0.01% +478 /scratch/Teaching/cars/car_ims/002912.jpg BMW M6 Convertible 2010 BMW M6 Convertible 2010 51.12% BMW 1 Series Convertible 2012 33.08% Jaguar XK XKR 2012 7.38% BMW 6 Series Convertible 2007 6.3% BMW Z4 Convertible 2012 1.72% +479 /scratch/Teaching/cars/car_ims/011037.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 90.36% Hyundai Accent Sedan 2012 6.45% Toyota Camry Sedan 2012 1.81% Toyota Corolla Sedan 2012 0.7% Hyundai Elantra Sedan 2007 0.17% +480 /scratch/Teaching/cars/car_ims/013104.jpg McLaren MP4-12C Coupe 2012 Aston Martin V8 Vantage Coupe 2012 41.41% Aston Martin V8 Vantage Convertible 2012 31.25% McLaren MP4-12C Coupe 2012 13.2% Lamborghini Reventon Coupe 2008 3.81% Mercedes-Benz SL-Class Coupe 2009 2.84% +481 /scratch/Teaching/cars/car_ims/003769.jpg Buick Regal GS 2012 BMW Z4 Convertible 2012 85.11% Dodge Charger Sedan 2012 13.56% Bentley Continental GT Coupe 2012 0.67% Audi TTS Coupe 2012 0.21% BMW 1 Series Convertible 2012 0.13% +482 /scratch/Teaching/cars/car_ims/006031.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 44.62% Chevrolet Silverado 2500HD Regular Cab 2012 17.06% Dodge Ram Pickup 3500 Crew Cab 2010 15.31% Chevrolet Silverado 1500 Regular Cab 2012 13.22% Ford F-450 Super Duty Crew Cab 2012 5.01% +483 /scratch/Teaching/cars/car_ims/002655.jpg BMW X6 SUV 2012 Buick Verano Sedan 2012 97.52% Acura ZDX Hatchback 2012 1.45% Chevrolet Malibu Hybrid Sedan 2010 0.52% Acura RL Sedan 2012 0.39% Mitsubishi Lancer Sedan 2012 0.08% +484 /scratch/Teaching/cars/car_ims/014170.jpg Plymouth Neon Coupe 1999 Plymouth Neon Coupe 1999 99.77% Ford Focus Sedan 2007 0.19% Hyundai Elantra Touring Hatchback 2012 0.03% Daewoo Nubira Wagon 2002 0.0% Eagle Talon Hatchback 1998 0.0% +485 /scratch/Teaching/cars/car_ims/006724.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2012 59.9% Suzuki SX4 Hatchback 2012 39.2% Ram C/V Cargo Van Minivan 2012 0.58% Dodge Caliber Wagon 2007 0.28% Dodge Durango SUV 2007 0.02% +486 /scratch/Teaching/cars/car_ims/002363.jpg BMW 3 Series Wagon 2012 BMW 3 Series Sedan 2012 100.0% BMW ActiveHybrid 5 Sedan 2012 0.0% BMW 3 Series Wagon 2012 0.0% Audi S6 Sedan 2011 0.0% BMW Z4 Convertible 2012 0.0% +487 /scratch/Teaching/cars/car_ims/000128.jpg Acura RL Sedan 2012 Acura RL Sedan 2012 98.55% Acura TSX Sedan 2012 1.19% Acura TL Sedan 2012 0.15% Acura ZDX Hatchback 2012 0.06% Chevrolet Impala Sedan 2007 0.02% +488 /scratch/Teaching/cars/car_ims/000984.jpg Audi A5 Coupe 2012 Audi TTS Coupe 2012 93.02% Audi A5 Coupe 2012 3.29% Audi S4 Sedan 2012 1.86% Audi S5 Coupe 2012 1.13% Audi S4 Sedan 2007 0.36% +489 /scratch/Teaching/cars/car_ims/007998.jpg Eagle Talon Hatchback 1998 Plymouth Neon Coupe 1999 56.14% Dodge Caravan Minivan 1997 9.14% Daewoo Nubira Wagon 2002 8.8% Eagle Talon Hatchback 1998 8.32% Porsche Panamera Sedan 2012 2.81% +490 /scratch/Teaching/cars/car_ims/013245.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 97.79% Hyundai Genesis Sedan 2012 1.47% Audi S6 Sedan 2011 0.44% Mercedes-Benz E-Class Sedan 2012 0.08% Volkswagen Golf Hatchback 2012 0.07% +491 /scratch/Teaching/cars/car_ims/009214.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 100.0% Ford Ranger SuperCab 2011 0.0% Ford F-450 Super Duty Crew Cab 2012 0.0% GMC Terrain SUV 2012 0.0% Ford F-150 Regular Cab 2007 0.0% +492 /scratch/Teaching/cars/car_ims/013574.jpg Mercedes-Benz S-Class Sedan 2012 Mercedes-Benz S-Class Sedan 2012 99.53% Mercedes-Benz E-Class Sedan 2012 0.45% Mercedes-Benz C-Class Sedan 2012 0.02% Chrysler Crossfire Convertible 2008 0.0% Chrysler Sebring Convertible 2010 0.0% +493 /scratch/Teaching/cars/car_ims/015307.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.91% Hyundai Santa Fe SUV 2012 0.08% Ford Expedition EL SUV 2009 0.01% Infiniti QX56 SUV 2011 0.0% Mazda Tribute SUV 2011 0.0% +494 /scratch/Teaching/cars/car_ims/015848.jpg Volvo C30 Hatchback 2012 Volvo C30 Hatchback 2012 54.67% BMW 1 Series Coupe 2012 39.05% Mitsubishi Lancer Sedan 2012 5.69% Chevrolet Sonic Sedan 2012 0.35% Dodge Charger Sedan 2012 0.19% +495 /scratch/Teaching/cars/car_ims/010136.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 92.51% Mercedes-Benz 300-Class Convertible 1993 6.94% Audi 100 Sedan 1994 0.18% Plymouth Neon Coupe 1999 0.13% Dodge Caravan Minivan 1997 0.1% +496 /scratch/Teaching/cars/car_ims/003459.jpg Bentley Continental GT Coupe 2007 BMW M6 Convertible 2010 38.77% Bentley Continental Supersports Conv. Convertible 2012 16.77% Dodge Charger Sedan 2012 10.93% Mercedes-Benz 300-Class Convertible 1993 10.85% BMW 6 Series Convertible 2007 3.75% +497 /scratch/Teaching/cars/car_ims/015818.jpg Volkswagen Beetle Hatchback 2012 Chevrolet Cobalt SS 2010 46.06% Volkswagen Beetle Hatchback 2012 34.61% Chevrolet HHR SS 2010 14.64% Volvo C30 Hatchback 2012 2.22% Dodge Journey SUV 2012 1.04% +498 /scratch/Teaching/cars/car_ims/007766.jpg Dodge Durango SUV 2007 Dodge Ram Pickup 3500 Crew Cab 2010 95.05% Dodge Durango SUV 2007 4.13% Dodge Ram Pickup 3500 Quad Cab 2009 0.82% Dodge Dakota Club Cab 2007 0.0% Dodge Dakota Crew Cab 2010 0.0% +499 /scratch/Teaching/cars/car_ims/003391.jpg Bentley Continental GT Coupe 2012 Chevrolet Corvette Ron Fellows Edition Z06 2007 46.11% Maybach Landaulet Convertible 2012 23.2% Spyker C8 Convertible 2009 14.45% Spyker C8 Coupe 2009 4.96% BMW M5 Sedan 2010 3.5% +500 /scratch/Teaching/cars/car_ims/007805.jpg Dodge Charger Sedan 2012 Dodge Charger Sedan 2012 67.12% Mitsubishi Lancer Sedan 2012 29.61% Audi R8 Coupe 2012 1.79% Dodge Charger SRT-8 2009 0.45% Dodge Magnum Wagon 2008 0.18% +501 /scratch/Teaching/cars/car_ims/002965.jpg BMW X3 SUV 2012 BMW X3 SUV 2012 70.39% Suzuki SX4 Hatchback 2012 17.86% Chevrolet Traverse SUV 2012 3.04% Ford Edge SUV 2012 2.61% Mazda Tribute SUV 2011 2.49% +502 /scratch/Teaching/cars/car_ims/007262.jpg Dodge Journey SUV 2012 Dodge Journey SUV 2012 99.93% Chevrolet HHR SS 2010 0.02% Mitsubishi Lancer Sedan 2012 0.02% Chevrolet Sonic Sedan 2012 0.01% Land Rover Range Rover SUV 2012 0.01% +503 /scratch/Teaching/cars/car_ims/005585.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 59.86% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 28.83% Chevrolet Silverado 1500 Extended Cab 2012 6.29% GMC Canyon Extended Cab 2012 4.36% Chevrolet Silverado 1500 Regular Cab 2012 0.53% +504 /scratch/Teaching/cars/car_ims/015036.jpg Suzuki SX4 Hatchback 2012 Volvo XC90 SUV 2007 63.51% Suzuki SX4 Hatchback 2012 20.77% Chevrolet Traverse SUV 2012 11.5% Mazda Tribute SUV 2011 2.45% Buick Enclave SUV 2012 1.35% +505 /scratch/Teaching/cars/car_ims/000892.jpg Audi RS 4 Convertible 2008 Dodge Charger SRT-8 2009 52.98% BMW M6 Convertible 2010 19.85% Jaguar XK XKR 2012 10.59% Mercedes-Benz 300-Class Convertible 1993 3.74% BMW 6 Series Convertible 2007 1.39% +506 /scratch/Teaching/cars/car_ims/002195.jpg BMW 1 Series Coupe 2012 BMW 1 Series Coupe 2012 99.22% BMW M3 Coupe 2012 0.78% Volvo C30 Hatchback 2012 0.0% BMW M5 Sedan 2010 0.0% BMW Z4 Convertible 2012 0.0% +507 /scratch/Teaching/cars/car_ims/000546.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 99.03% Hyundai Veracruz SUV 2012 0.67% Infiniti QX56 SUV 2011 0.1% Hyundai Tucson SUV 2012 0.09% Buick Verano Sedan 2012 0.03% +508 /scratch/Teaching/cars/car_ims/001117.jpg Audi TTS Coupe 2012 Audi TT Hatchback 2011 98.37% Audi A5 Coupe 2012 1.34% Audi TTS Coupe 2012 0.24% Audi TT RS Coupe 2012 0.05% Audi S5 Coupe 2012 0.01% +509 /scratch/Teaching/cars/car_ims/014807.jpg Spyker C8 Coupe 2009 Spyker C8 Coupe 2009 93.22% Spyker C8 Convertible 2009 6.73% Aston Martin V8 Vantage Convertible 2012 0.01% Aston Martin Virage Coupe 2012 0.01% Mercedes-Benz SL-Class Coupe 2009 0.01% +510 /scratch/Teaching/cars/car_ims/012191.jpg Jeep Grand Cherokee SUV 2012 Volvo XC90 SUV 2007 57.1% BMW X6 SUV 2012 28.39% Buick Rainier SUV 2007 2.93% Dodge Durango SUV 2007 2.87% Jeep Compass SUV 2012 2.72% +511 /scratch/Teaching/cars/car_ims/007101.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Lincoln Town Car Sedan 2011 56.09% Chevrolet Silverado 1500 Extended Cab 2012 18.19% GMC Canyon Extended Cab 2012 9.25% Ford F-150 Regular Cab 2007 7.62% Dodge Dakota Club Cab 2007 1.64% +512 /scratch/Teaching/cars/car_ims/011872.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 98.63% Mazda Tribute SUV 2011 1.1% Volvo XC90 SUV 2007 0.19% Jeep Liberty SUV 2012 0.08% GMC Acadia SUV 2012 0.01% +513 /scratch/Teaching/cars/car_ims/015234.jpg Tesla Model S Sedan 2012 Tesla Model S Sedan 2012 81.34% Fisker Karma Sedan 2012 18.6% BMW 6 Series Convertible 2007 0.02% Audi S4 Sedan 2012 0.01% Audi A5 Coupe 2012 0.01% +514 /scratch/Teaching/cars/car_ims/014883.jpg Suzuki Aerio Sedan 2007 Toyota Corolla Sedan 2012 62.3% Chevrolet Sonic Sedan 2012 29.82% Suzuki Aerio Sedan 2007 2.15% Acura TSX Sedan 2012 2.1% Mitsubishi Lancer Sedan 2012 1.87% +515 /scratch/Teaching/cars/car_ims/009194.jpg Ford GT Coupe 2006 Ford GT Coupe 2006 91.16% Spyker C8 Convertible 2009 6.46% Bugatti Veyron 16.4 Coupe 2009 2.16% Bentley Continental GT Coupe 2007 0.1% Lamborghini Aventador Coupe 2012 0.05% +516 /scratch/Teaching/cars/car_ims/016080.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 98.28% GMC Canyon Extended Cab 2012 0.65% Dodge Durango SUV 2007 0.56% Jeep Patriot SUV 2012 0.23% Mazda Tribute SUV 2011 0.07% +517 /scratch/Teaching/cars/car_ims/008820.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 99.99% Lincoln Town Car Sedan 2011 0.0% Daewoo Nubira Wagon 2002 0.0% Chevrolet Malibu Sedan 2007 0.0% Dodge Magnum Wagon 2008 0.0% +518 /scratch/Teaching/cars/car_ims/008045.jpg Eagle Talon Hatchback 1998 Spyker C8 Convertible 2009 38.16% Eagle Talon Hatchback 1998 10.34% Aston Martin Virage Coupe 2012 6.74% BMW Z4 Convertible 2012 6.23% Chevrolet Corvette ZR1 2012 5.64% +519 /scratch/Teaching/cars/car_ims/003819.jpg Buick Rainier SUV 2007 Volkswagen Golf Hatchback 1991 49.19% Buick Rainier SUV 2007 46.22% Jeep Patriot SUV 2012 2.54% Chrysler Aspen SUV 2009 1.27% Volvo 240 Sedan 1993 0.32% +520 /scratch/Teaching/cars/car_ims/001680.jpg Audi S5 Convertible 2012 Audi S5 Convertible 2012 55.03% Audi RS 4 Convertible 2008 31.02% Jeep Compass SUV 2012 8.83% Audi R8 Coupe 2012 1.47% Audi S5 Coupe 2012 1.44% +521 /scratch/Teaching/cars/car_ims/012267.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 99.39% Jeep Grand Cherokee SUV 2012 0.61% Isuzu Ascender SUV 2008 0.0% BMW X3 SUV 2012 0.0% Dodge Dakota Crew Cab 2010 0.0% +522 /scratch/Teaching/cars/car_ims/008598.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 100.0% Ford F-150 Regular Cab 2012 0.0% HUMMER H2 SUT Crew Cab 2009 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% +523 /scratch/Teaching/cars/car_ims/000229.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 99.71% Acura RL Sedan 2012 0.22% Acura ZDX Hatchback 2012 0.03% Acura TSX Sedan 2012 0.01% Buick Verano Sedan 2012 0.01% +524 /scratch/Teaching/cars/car_ims/012148.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 95.27% Jeep Compass SUV 2012 4.73% Jeep Liberty SUV 2012 0.0% BMW X5 SUV 2007 0.0% Jeep Patriot SUV 2012 0.0% +525 /scratch/Teaching/cars/car_ims/000342.jpg Acura TSX Sedan 2012 Hyundai Elantra Sedan 2007 87.15% Acura RL Sedan 2012 5.86% Toyota Camry Sedan 2012 1.87% Honda Odyssey Minivan 2012 1.65% Hyundai Sonata Hybrid Sedan 2012 1.24% +526 /scratch/Teaching/cars/car_ims/001909.jpg Audi S4 Sedan 2007 Audi S6 Sedan 2011 98.87% Audi A5 Coupe 2012 0.53% Audi S4 Sedan 2007 0.35% Audi S5 Coupe 2012 0.19% Audi S5 Convertible 2012 0.03% +527 /scratch/Teaching/cars/car_ims/012118.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 99.97% Nissan Juke Hatchback 2012 0.01% BMW X6 SUV 2012 0.01% Jeep Compass SUV 2012 0.0% GMC Acadia SUV 2012 0.0% +528 /scratch/Teaching/cars/car_ims/007485.jpg Dodge Magnum Wagon 2008 Dodge Magnum Wagon 2008 89.22% Chrysler 300 SRT-8 2010 7.79% Chrysler Sebring Convertible 2010 1.31% Chevrolet Impala Sedan 2007 0.42% Cadillac CTS-V Sedan 2012 0.27% +529 /scratch/Teaching/cars/car_ims/009914.jpg GMC Acadia SUV 2012 Ram C/V Cargo Van Minivan 2012 94.01% GMC Acadia SUV 2012 5.39% Mazda Tribute SUV 2011 0.18% Daewoo Nubira Wagon 2002 0.08% Volvo XC90 SUV 2007 0.08% +530 /scratch/Teaching/cars/car_ims/015487.jpg Toyota Corolla Sedan 2012 Toyota Corolla Sedan 2012 99.79% Toyota Camry Sedan 2012 0.2% Scion xD Hatchback 2012 0.0% Mitsubishi Lancer Sedan 2012 0.0% Chevrolet Sonic Sedan 2012 0.0% +531 /scratch/Teaching/cars/car_ims/015946.jpg Volvo 240 Sedan 1993 Rolls-Royce Phantom Drophead Coupe Convertible 2012 97.12% Volvo 240 Sedan 1993 2.26% Mercedes-Benz 300-Class Convertible 1993 0.59% Rolls-Royce Phantom Sedan 2012 0.02% Chrysler Crossfire Convertible 2008 0.0% +532 /scratch/Teaching/cars/car_ims/008766.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 100.0% Chevrolet Malibu Sedan 2007 0.0% Ram C/V Cargo Van Minivan 2012 0.0% Chrysler Aspen SUV 2009 0.0% Dodge Caravan Minivan 1997 0.0% +533 /scratch/Teaching/cars/car_ims/012625.jpg Land Rover Range Rover SUV 2012 Land Rover LR2 SUV 2012 41.52% Mazda Tribute SUV 2011 34.86% Dodge Journey SUV 2012 10.28% Suzuki SX4 Hatchback 2012 7.63% Land Rover Range Rover SUV 2012 3.34% +534 /scratch/Teaching/cars/car_ims/013688.jpg Mitsubishi Lancer Sedan 2012 Mitsubishi Lancer Sedan 2012 100.0% Chevrolet Sonic Sedan 2012 0.0% Audi S5 Convertible 2012 0.0% Audi A5 Coupe 2012 0.0% Acura TSX Sedan 2012 0.0% +535 /scratch/Teaching/cars/car_ims/013807.jpg Nissan Leaf Hatchback 2012 Nissan Leaf Hatchback 2012 99.98% Porsche Panamera Sedan 2012 0.01% Buick Verano Sedan 2012 0.01% Suzuki Kizashi Sedan 2012 0.0% Nissan Juke Hatchback 2012 0.0% +536 /scratch/Teaching/cars/car_ims/013924.jpg Nissan Juke Hatchback 2012 Nissan Juke Hatchback 2012 99.59% BMW X3 SUV 2012 0.12% Hyundai Tucson SUV 2012 0.08% Dodge Journey SUV 2012 0.05% Chevrolet Traverse SUV 2012 0.04% +537 /scratch/Teaching/cars/car_ims/008198.jpg Ferrari FF Coupe 2012 Ferrari FF Coupe 2012 45.43% Fisker Karma Sedan 2012 44.86% Acura TL Sedan 2012 3.77% Aston Martin V8 Vantage Convertible 2012 3.46% Ferrari 458 Italia Coupe 2012 1.03% +538 /scratch/Teaching/cars/car_ims/006493.jpg Chrysler Crossfire Convertible 2008 Bentley Continental GT Coupe 2007 46.68% BMW M6 Convertible 2010 19.41% Ford Mustang Convertible 2007 13.4% Bentley Arnage Sedan 2009 4.68% Mercedes-Benz 300-Class Convertible 1993 3.85% +539 /scratch/Teaching/cars/car_ims/003322.jpg Bentley Mulsanne Sedan 2011 Ford GT Coupe 2006 49.33% Chrysler 300 SRT-8 2010 8.17% AM General Hummer SUV 2000 7.14% Spyker C8 Coupe 2009 6.14% Ford Ranger SuperCab 2011 4.56% +540 /scratch/Teaching/cars/car_ims/015298.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.78% Infiniti QX56 SUV 2011 0.22% Toyota 4Runner SUV 2012 0.0% Cadillac SRX SUV 2012 0.0% Land Rover Range Rover SUV 2012 0.0% +541 /scratch/Teaching/cars/car_ims/004771.jpg Chevrolet Camaro Convertible 2012 Volvo C30 Hatchback 2012 50.23% Spyker C8 Coupe 2009 18.41% BMW M3 Coupe 2012 6.98% Chevrolet Cobalt SS 2010 6.26% Chevrolet Sonic Sedan 2012 5.91% +542 /scratch/Teaching/cars/car_ims/011062.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 84.43% Ford Edge SUV 2012 6.52% Mitsubishi Lancer Sedan 2012 5.17% Hyundai Sonata Sedan 2012 2.3% Hyundai Accent Sedan 2012 0.96% +543 /scratch/Teaching/cars/car_ims/012742.jpg Land Rover LR2 SUV 2012 Land Rover LR2 SUV 2012 95.68% GMC Terrain SUV 2012 2.49% Toyota 4Runner SUV 2012 0.52% Ford Edge SUV 2012 0.43% Chevrolet Silverado 1500 Regular Cab 2012 0.33% +544 /scratch/Teaching/cars/car_ims/015518.jpg Toyota 4Runner SUV 2012 Ford Edge SUV 2012 79.14% Toyota 4Runner SUV 2012 11.59% Land Rover LR2 SUV 2012 3.79% Chevrolet Traverse SUV 2012 3.25% GMC Terrain SUV 2012 0.81% +545 /scratch/Teaching/cars/car_ims/013472.jpg Mercedes-Benz E-Class Sedan 2012 Bentley Arnage Sedan 2009 79.23% Jeep Liberty SUV 2012 5.97% FIAT 500 Abarth 2012 2.82% Nissan Juke Hatchback 2012 2.36% MINI Cooper Roadster Convertible 2012 2.21% +546 /scratch/Teaching/cars/car_ims/003839.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 69.4% Mazda Tribute SUV 2011 24.39% Toyota Sequoia SUV 2012 4.25% Dodge Durango SUV 2007 0.75% Ford Expedition EL SUV 2009 0.24% +547 /scratch/Teaching/cars/car_ims/007108.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Crew Cab 2010 90.02% Dodge Ram Pickup 3500 Quad Cab 2009 9.98% Dodge Durango SUV 2007 0.0% Dodge Dakota Club Cab 2007 0.0% Dodge Dakota Crew Cab 2010 0.0% +548 /scratch/Teaching/cars/car_ims/007273.jpg Dodge Journey SUV 2012 Mercedes-Benz E-Class Sedan 2012 91.71% Hyundai Azera Sedan 2012 3.14% Infiniti G Coupe IPL 2012 2.98% Suzuki Kizashi Sedan 2012 0.97% Hyundai Genesis Sedan 2012 0.63% +549 /scratch/Teaching/cars/car_ims/004666.jpg Chevrolet Traverse SUV 2012 Hyundai Veracruz SUV 2012 45.98% Hyundai Santa Fe SUV 2012 33.89% Chevrolet Traverse SUV 2012 13.75% Suzuki SX4 Hatchback 2012 3.09% Hyundai Tucson SUV 2012 2.08% +550 /scratch/Teaching/cars/car_ims/010722.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 46.56% Mitsubishi Lancer Sedan 2012 46.5% Spyker C8 Coupe 2009 2.33% Dodge Charger Sedan 2012 1.32% Chevrolet Sonic Sedan 2012 1.27% +551 /scratch/Teaching/cars/car_ims/000919.jpg Audi RS 4 Convertible 2008 Audi A5 Coupe 2012 48.79% Audi RS 4 Convertible 2008 21.23% Audi S4 Sedan 2007 9.57% Audi S5 Convertible 2012 9.37% Audi S5 Coupe 2012 7.61% +552 /scratch/Teaching/cars/car_ims/003108.jpg BMW Z4 Convertible 2012 BMW Z4 Convertible 2012 100.0% BMW M3 Coupe 2012 0.0% Ford Mustang Convertible 2007 0.0% Audi RS 4 Convertible 2008 0.0% Acura Integra Type R 2001 0.0% +553 /scratch/Teaching/cars/car_ims/006228.jpg Chrysler Sebring Convertible 2010 Chrysler Crossfire Convertible 2008 80.74% Mercedes-Benz 300-Class Convertible 1993 9.34% BMW 6 Series Convertible 2007 6.07% Chrysler Sebring Convertible 2010 1.72% Jaguar XK XKR 2012 0.43% +554 /scratch/Teaching/cars/car_ims/015713.jpg Volkswagen Golf Hatchback 1991 Audi 100 Wagon 1994 88.96% Chevrolet Express Van 2007 4.65% Volkswagen Golf Hatchback 1991 2.09% Volvo 240 Sedan 1993 1.99% Buick Rainier SUV 2007 0.9% +555 /scratch/Teaching/cars/car_ims/003552.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 85.17% Bentley Continental GT Coupe 2007 14.77% Bentley Continental GT Coupe 2012 0.04% Spyker C8 Convertible 2009 0.01% Volkswagen Beetle Hatchback 2012 0.0% +556 /scratch/Teaching/cars/car_ims/005717.jpg Chevrolet Express Van 2007 Chevrolet Express Cargo Van 2007 99.62% GMC Savana Van 2012 0.34% Chevrolet Express Van 2007 0.04% Volkswagen Golf Hatchback 1991 0.0% Nissan NV Passenger Van 2012 0.0% +557 /scratch/Teaching/cars/car_ims/009534.jpg Ford E-Series Wagon Van 2012 Ford E-Series Wagon Van 2012 100.0% Ford Ranger SuperCab 2011 0.0% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.0% GMC Savana Van 2012 0.0% Chrysler Aspen SUV 2009 0.0% +558 /scratch/Teaching/cars/car_ims/003906.jpg Buick Verano Sedan 2012 Ferrari FF Coupe 2012 33.06% Aston Martin V8 Vantage Coupe 2012 17.6% Porsche Panamera Sedan 2012 14.75% Fisker Karma Sedan 2012 13.86% Infiniti G Coupe IPL 2012 3.98% +559 /scratch/Teaching/cars/car_ims/015003.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 95.68% Hyundai Veloster Hatchback 2012 2.0% Mitsubishi Lancer Sedan 2012 0.98% FIAT 500 Convertible 2012 0.42% Chevrolet Cobalt SS 2010 0.13% +560 /scratch/Teaching/cars/car_ims/002850.jpg BMW M5 Sedan 2010 BMW ActiveHybrid 5 Sedan 2012 70.62% BMW M5 Sedan 2010 21.77% Acura TL Type-S 2008 1.88% Fisker Karma Sedan 2012 1.37% BMW 3 Series Wagon 2012 1.3% +561 /scratch/Teaching/cars/car_ims/003100.jpg BMW Z4 Convertible 2012 BMW Z4 Convertible 2012 99.57% Audi TTS Coupe 2012 0.24% BMW M6 Convertible 2010 0.15% BMW 6 Series Convertible 2007 0.01% BMW M3 Coupe 2012 0.01% +562 /scratch/Teaching/cars/car_ims/014344.jpg Ram C/V Cargo Van Minivan 2012 Ford Freestar Minivan 2007 51.62% Dodge Dakota Crew Cab 2010 19.39% Chrysler Aspen SUV 2009 14.94% Ford Ranger SuperCab 2011 9.57% Ford E-Series Wagon Van 2012 1.38% +563 /scratch/Teaching/cars/car_ims/004836.jpg Chevrolet HHR SS 2010 Mercedes-Benz S-Class Sedan 2012 45.06% Chevrolet HHR SS 2010 31.82% Bentley Continental Flying Spur Sedan 2007 21.35% Suzuki Kizashi Sedan 2012 1.44% Mercedes-Benz C-Class Sedan 2012 0.16% +564 /scratch/Teaching/cars/car_ims/016180.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 100.0% Ford Fiesta Sedan 2012 0.0% FIAT 500 Convertible 2012 0.0% MINI Cooper Roadster Convertible 2012 0.0% Chrysler PT Cruiser Convertible 2008 0.0% +565 /scratch/Teaching/cars/car_ims/009217.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 99.88% Ford F-150 Regular Cab 2007 0.12% GMC Yukon Hybrid SUV 2012 0.0% Ford Ranger SuperCab 2011 0.0% Nissan NV Passenger Van 2012 0.0% +566 /scratch/Teaching/cars/car_ims/008334.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 88.72% Ferrari 458 Italia Coupe 2012 11.19% Ferrari 458 Italia Convertible 2012 0.04% Volkswagen Beetle Hatchback 2012 0.02% Scion xD Hatchback 2012 0.01% +567 /scratch/Teaching/cars/car_ims/015474.jpg Toyota Corolla Sedan 2012 Chevrolet Sonic Sedan 2012 64.93% Toyota Corolla Sedan 2012 17.18% Toyota Camry Sedan 2012 11.8% Hyundai Accent Sedan 2012 3.41% Buick Regal GS 2012 1.88% +568 /scratch/Teaching/cars/car_ims/016106.jpg smart fortwo Convertible 2012 Nissan Leaf Hatchback 2012 69.18% smart fortwo Convertible 2012 7.69% Suzuki SX4 Hatchback 2012 6.88% Nissan Juke Hatchback 2012 5.3% Ford Fiesta Sedan 2012 2.89% +569 /scratch/Teaching/cars/car_ims/004993.jpg Chevrolet Tahoe Hybrid SUV 2012 Chevrolet Avalanche Crew Cab 2012 99.99% Chevrolet Malibu Hybrid Sedan 2010 0.0% Chevrolet Tahoe Hybrid SUV 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% GMC Acadia SUV 2012 0.0% +570 /scratch/Teaching/cars/car_ims/000765.jpg Aston Martin Virage Convertible 2012 Aston Martin V8 Vantage Convertible 2012 87.53% Aston Martin Virage Convertible 2012 7.44% Aston Martin V8 Vantage Coupe 2012 4.56% BMW M6 Convertible 2010 0.35% Spyker C8 Coupe 2009 0.04% +571 /scratch/Teaching/cars/car_ims/009609.jpg Ford Fiesta Sedan 2012 Buick Verano Sedan 2012 95.6% Volkswagen Golf Hatchback 2012 1.65% Chevrolet Sonic Sedan 2012 0.7% Ford Fiesta Sedan 2012 0.69% BMW X6 SUV 2012 0.4% +572 /scratch/Teaching/cars/car_ims/006166.jpg Chrysler Aspen SUV 2009 Chrysler Aspen SUV 2009 77.64% Dodge Durango SUV 2007 13.27% Chrysler Town and Country Minivan 2012 5.02% Ram C/V Cargo Van Minivan 2012 1.66% Dodge Caliber Wagon 2012 1.42% +573 /scratch/Teaching/cars/car_ims/009438.jpg Ford Focus Sedan 2007 Suzuki Aerio Sedan 2007 55.34% Hyundai Elantra Touring Hatchback 2012 13.89% Ford Focus Sedan 2007 5.88% Mercedes-Benz C-Class Sedan 2012 4.84% FIAT 500 Convertible 2012 4.33% +574 /scratch/Teaching/cars/car_ims/008504.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 94.0% Porsche Panamera Sedan 2012 2.48% Aston Martin V8 Vantage Coupe 2012 2.05% Chevrolet Corvette ZR1 2012 0.58% Ferrari 458 Italia Coupe 2012 0.48% +575 /scratch/Teaching/cars/car_ims/002457.jpg BMW 6 Series Convertible 2007 Chrysler Crossfire Convertible 2008 37.43% Chevrolet Camaro Convertible 2012 30.75% BMW 6 Series Convertible 2007 12.75% BMW 3 Series Sedan 2012 7.28% Mercedes-Benz 300-Class Convertible 1993 4.99% +576 /scratch/Teaching/cars/car_ims/013755.jpg Mitsubishi Lancer Sedan 2012 Hyundai Veloster Hatchback 2012 65.67% Mitsubishi Lancer Sedan 2012 14.73% Volvo C30 Hatchback 2012 11.37% Spyker C8 Coupe 2009 5.23% Dodge Charger Sedan 2012 1.93% +577 /scratch/Teaching/cars/car_ims/001706.jpg Audi S5 Convertible 2012 Audi S5 Convertible 2012 92.73% BMW 1 Series Convertible 2012 4.16% Jaguar XK XKR 2012 2.79% BMW X6 SUV 2012 0.14% Hyundai Sonata Hybrid Sedan 2012 0.07% +578 /scratch/Teaching/cars/car_ims/000395.jpg Acura TSX Sedan 2012 Acura TSX Sedan 2012 40.99% Mitsubishi Lancer Sedan 2012 14.35% Suzuki SX4 Sedan 2012 11.25% Acura Integra Type R 2001 5.63% Toyota Camry Sedan 2012 5.38% +579 /scratch/Teaching/cars/car_ims/014349.jpg Ram C/V Cargo Van Minivan 2012 Dodge Caliber Wagon 2012 95.47% Suzuki SX4 Sedan 2012 2.18% Suzuki SX4 Hatchback 2012 1.0% Dodge Caliber Wagon 2007 0.38% GMC Terrain SUV 2012 0.38% +580 /scratch/Teaching/cars/car_ims/004627.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 McLaren MP4-12C Coupe 2012 96.14% Lamborghini Aventador Coupe 2012 1.13% Bugatti Veyron 16.4 Coupe 2009 0.95% Ford GT Coupe 2006 0.92% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.82% +581 /scratch/Teaching/cars/car_ims/008247.jpg Ferrari FF Coupe 2012 HUMMER H2 SUT Crew Cab 2009 35.27% HUMMER H3T Crew Cab 2010 31.17% Jeep Grand Cherokee SUV 2012 8.54% Nissan Juke Hatchback 2012 6.53% AM General Hummer SUV 2000 4.99% +582 /scratch/Teaching/cars/car_ims/013470.jpg Mercedes-Benz E-Class Sedan 2012 Mercedes-Benz S-Class Sedan 2012 88.55% Mercedes-Benz E-Class Sedan 2012 10.1% Chrysler Crossfire Convertible 2008 1.04% Mercedes-Benz C-Class Sedan 2012 0.15% Audi RS 4 Convertible 2008 0.11% +583 /scratch/Teaching/cars/car_ims/015022.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 73.16% Chevrolet Sonic Sedan 2012 9.6% Volvo C30 Hatchback 2012 4.72% Buick Regal GS 2012 3.78% Hyundai Tucson SUV 2012 1.65% +584 /scratch/Teaching/cars/car_ims/008559.jpg Fisker Karma Sedan 2012 Dodge Charger SRT-8 2009 59.67% Rolls-Royce Ghost Sedan 2012 23.34% Chevrolet Camaro Convertible 2012 11.43% Chrysler Crossfire Convertible 2008 2.03% Chevrolet TrailBlazer SS 2009 0.58% +585 /scratch/Teaching/cars/car_ims/003568.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 72.76% Bentley Continental GT Coupe 2007 24.67% Bentley Continental GT Coupe 2012 2.0% Spyker C8 Convertible 2009 0.31% Aston Martin Virage Convertible 2012 0.08% +586 /scratch/Teaching/cars/car_ims/002865.jpg BMW M5 Sedan 2010 BMW M6 Convertible 2010 70.32% Jaguar XK XKR 2012 9.92% Nissan Juke Hatchback 2012 5.38% Audi S6 Sedan 2011 3.56% BMW M5 Sedan 2010 3.25% +587 /scratch/Teaching/cars/car_ims/005797.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Monte Carlo Coupe 2007 95.65% Chevrolet Malibu Sedan 2007 2.38% Chevrolet Impala Sedan 2007 1.24% Chevrolet Cobalt SS 2010 0.67% Chrysler Sebring Convertible 2010 0.01% +588 /scratch/Teaching/cars/car_ims/015378.jpg Toyota Camry Sedan 2012 Toyota Camry Sedan 2012 87.31% Toyota Corolla Sedan 2012 12.65% Hyundai Accent Sedan 2012 0.04% Hyundai Sonata Hybrid Sedan 2012 0.01% Ford Fiesta Sedan 2012 0.0% +589 /scratch/Teaching/cars/car_ims/004432.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Convertible 2012 99.7% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.19% Chevrolet Camaro Convertible 2012 0.04% Eagle Talon Hatchback 1998 0.03% Audi S5 Convertible 2012 0.01% +590 /scratch/Teaching/cars/car_ims/001529.jpg Audi TT Hatchback 2011 Audi TT RS Coupe 2012 99.6% Audi R8 Coupe 2012 0.28% Audi TT Hatchback 2011 0.1% Audi TTS Coupe 2012 0.01% Audi S5 Convertible 2012 0.0% +591 /scratch/Teaching/cars/car_ims/008896.jpg Ford Expedition EL SUV 2009 Rolls-Royce Phantom Sedan 2012 31.63% Jeep Liberty SUV 2012 26.34% Buick Rainier SUV 2007 8.72% Jeep Patriot SUV 2012 8.0% Volvo 240 Sedan 1993 5.47% +592 /scratch/Teaching/cars/car_ims/014448.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Phantom Sedan 2012 60.16% Rolls-Royce Ghost Sedan 2012 39.84% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Chrysler 300 SRT-8 2010 0.0% Volvo 240 Sedan 1993 0.0% +593 /scratch/Teaching/cars/car_ims/004929.jpg Chevrolet Impala Sedan 2007 Chevrolet Malibu Sedan 2007 84.77% Chevrolet Impala Sedan 2007 7.63% Chevrolet Sonic Sedan 2012 4.47% Suzuki SX4 Sedan 2012 0.69% Honda Odyssey Minivan 2012 0.4% +594 /scratch/Teaching/cars/car_ims/005217.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 74.92% Chevrolet Tahoe Hybrid SUV 2012 25.07% GMC Yukon Hybrid SUV 2012 0.0% Chevrolet Silverado 1500 Extended Cab 2012 0.0% Chevrolet TrailBlazer SS 2009 0.0% +595 /scratch/Teaching/cars/car_ims/015873.jpg Volvo C30 Hatchback 2012 Volvo C30 Hatchback 2012 99.52% Chevrolet HHR SS 2010 0.22% Volkswagen Beetle Hatchback 2012 0.19% Hyundai Elantra Touring Hatchback 2012 0.03% Chevrolet Express Van 2007 0.03% +596 /scratch/Teaching/cars/car_ims/000758.jpg Aston Martin Virage Convertible 2012 Aston Martin Virage Convertible 2012 53.38% Lamborghini Reventon Coupe 2008 15.91% smart fortwo Convertible 2012 6.86% Spyker C8 Coupe 2009 4.27% Land Rover Range Rover SUV 2012 2.77% +597 /scratch/Teaching/cars/car_ims/002913.jpg BMW M6 Convertible 2010 BMW 6 Series Convertible 2007 24.09% BMW M6 Convertible 2010 20.98% Lamborghini Reventon Coupe 2008 17.74% Volvo 240 Sedan 1993 17.11% Bentley Arnage Sedan 2009 6.28% +598 /scratch/Teaching/cars/car_ims/012741.jpg Land Rover LR2 SUV 2012 Mazda Tribute SUV 2011 35.22% Land Rover LR2 SUV 2012 20.64% GMC Acadia SUV 2012 18.18% Chevrolet Tahoe Hybrid SUV 2012 13.49% Chevrolet Avalanche Crew Cab 2012 7.91% +599 /scratch/Teaching/cars/car_ims/002523.jpg BMW 6 Series Convertible 2007 Chevrolet Camaro Convertible 2012 28.62% Mercedes-Benz 300-Class Convertible 1993 24.17% BMW M6 Convertible 2010 14.24% Audi RS 4 Convertible 2008 10.02% Eagle Talon Hatchback 1998 5.3% +600 /scratch/Teaching/cars/car_ims/007048.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 64.44% Dodge Ram Pickup 3500 Crew Cab 2010 35.56% Dodge Dakota Crew Cab 2010 0.0% Dodge Durango SUV 2007 0.0% Dodge Dakota Club Cab 2007 0.0% +601 /scratch/Teaching/cars/car_ims/006641.jpg Daewoo Nubira Wagon 2002 Ford Focus Sedan 2007 97.27% Daewoo Nubira Wagon 2002 2.69% Plymouth Neon Coupe 1999 0.03% Hyundai Elantra Touring Hatchback 2012 0.01% Suzuki Aerio Sedan 2007 0.0% +602 /scratch/Teaching/cars/car_ims/015522.jpg Toyota 4Runner SUV 2012 Ford Edge SUV 2012 94.8% Land Rover LR2 SUV 2012 4.31% GMC Terrain SUV 2012 0.28% Ford Expedition EL SUV 2009 0.25% Land Rover Range Rover SUV 2012 0.1% +603 /scratch/Teaching/cars/car_ims/004214.jpg Cadillac SRX SUV 2012 Hyundai Veracruz SUV 2012 69.5% Suzuki SX4 Sedan 2012 4.55% Chevrolet Traverse SUV 2012 3.53% Volkswagen Golf Hatchback 2012 2.96% Hyundai Tucson SUV 2012 2.1% +604 /scratch/Teaching/cars/car_ims/016144.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 68.38% Spyker C8 Convertible 2009 15.51% Spyker C8 Coupe 2009 8.47% HUMMER H2 SUT Crew Cab 2009 2.64% Suzuki Kizashi Sedan 2012 2.03% +605 /scratch/Teaching/cars/car_ims/001971.jpg Audi S4 Sedan 2007 Audi TTS Coupe 2012 42.87% Audi RS 4 Convertible 2008 19.3% Audi S4 Sedan 2012 16.62% Audi R8 Coupe 2012 11.69% Audi S5 Coupe 2012 4.31% +606 /scratch/Teaching/cars/car_ims/009309.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 39.01% Ford F-150 Regular Cab 2012 28.26% Dodge Ram Pickup 3500 Quad Cab 2009 27.69% Ford Ranger SuperCab 2011 4.32% Dodge Dakota Club Cab 2007 0.68% +607 /scratch/Teaching/cars/car_ims/000893.jpg Audi RS 4 Convertible 2008 Audi S5 Convertible 2012 99.49% Audi RS 4 Convertible 2008 0.46% Audi S5 Coupe 2012 0.04% Audi S6 Sedan 2011 0.0% Audi S4 Sedan 2007 0.0% +608 /scratch/Teaching/cars/car_ims/005124.jpg Chevrolet Sonic Sedan 2012 Chevrolet Sonic Sedan 2012 46.42% Mitsubishi Lancer Sedan 2012 12.25% Buick Regal GS 2012 8.17% Buick Verano Sedan 2012 7.06% BMW 1 Series Coupe 2012 5.07% +609 /scratch/Teaching/cars/car_ims/006393.jpg Chrysler 300 SRT-8 2010 Bentley Arnage Sedan 2009 40.74% Volkswagen Golf Hatchback 1991 29.96% Volvo 240 Sedan 1993 7.4% Ford F-150 Regular Cab 2007 2.61% Dodge Charger Sedan 2012 2.55% +610 /scratch/Teaching/cars/car_ims/000591.jpg Aston Martin V8 Vantage Convertible 2012 Jaguar XK XKR 2012 89.12% Aston Martin V8 Vantage Convertible 2012 8.71% Dodge Charger Sedan 2012 0.36% Ferrari 458 Italia Convertible 2012 0.33% Chevrolet Corvette Convertible 2012 0.33% +611 /scratch/Teaching/cars/car_ims/010263.jpg HUMMER H3T Crew Cab 2010 AM General Hummer SUV 2000 53.13% HUMMER H3T Crew Cab 2010 18.06% Jeep Wrangler SUV 2012 15.58% HUMMER H2 SUT Crew Cab 2009 12.87% Jeep Patriot SUV 2012 0.35% +612 /scratch/Teaching/cars/car_ims/006805.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2007 70.18% Dodge Dakota Crew Cab 2010 27.61% Dodge Caliber Wagon 2012 2.21% Dodge Magnum Wagon 2008 0.0% Dodge Durango SUV 2012 0.0% +613 /scratch/Teaching/cars/car_ims/013816.jpg Nissan Leaf Hatchback 2012 Nissan Leaf Hatchback 2012 100.0% Nissan Juke Hatchback 2012 0.0% Daewoo Nubira Wagon 2002 0.0% Buick Enclave SUV 2012 0.0% Buick Verano Sedan 2012 0.0% +614 /scratch/Teaching/cars/car_ims/000652.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin V8 Vantage Coupe 2012 68.05% Aston Martin V8 Vantage Convertible 2012 29.73% Fisker Karma Sedan 2012 1.31% Aston Martin Virage Convertible 2012 0.7% Ferrari 458 Italia Coupe 2012 0.05% +615 /scratch/Teaching/cars/car_ims/005034.jpg Chevrolet Tahoe Hybrid SUV 2012 GMC Yukon Hybrid SUV 2012 84.66% Chevrolet Tahoe Hybrid SUV 2012 12.14% Land Rover Range Rover SUV 2012 1.66% Chevrolet Avalanche Crew Cab 2012 0.7% Cadillac Escalade EXT Crew Cab 2007 0.51% +616 /scratch/Teaching/cars/car_ims/004339.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Isuzu Ascender SUV 2008 84.3% Chevrolet Avalanche Crew Cab 2012 3.71% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 3.68% Chevrolet Silverado 1500 Extended Cab 2012 3.07% Chevrolet Silverado 1500 Regular Cab 2012 2.02% +617 /scratch/Teaching/cars/car_ims/013997.jpg Nissan Juke Hatchback 2012 Nissan Juke Hatchback 2012 65.94% Hyundai Tucson SUV 2012 18.14% Hyundai Veracruz SUV 2012 7.68% Suzuki SX4 Hatchback 2012 4.81% Chevrolet Traverse SUV 2012 0.88% +618 /scratch/Teaching/cars/car_ims/004603.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 99.73% Chevrolet Corvette ZR1 2012 0.23% Ford GT Coupe 2006 0.03% Chevrolet Corvette Convertible 2012 0.01% Spyker C8 Convertible 2009 0.0% +619 /scratch/Teaching/cars/car_ims/010145.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 85.44% Plymouth Neon Coupe 1999 11.97% Ford Focus Sedan 2007 1.86% Dodge Caravan Minivan 1997 0.5% Audi 100 Wagon 1994 0.22% +620 /scratch/Teaching/cars/car_ims/002622.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 97.13% BMW X3 SUV 2012 2.77% BMW X5 SUV 2007 0.07% Jeep Compass SUV 2012 0.02% BMW 1 Series Convertible 2012 0.01% +621 /scratch/Teaching/cars/car_ims/006477.jpg Chrysler Crossfire Convertible 2008 Hyundai Genesis Sedan 2012 71.76% Chrysler Crossfire Convertible 2008 25.05% Chevrolet Cobalt SS 2010 1.1% Mercedes-Benz C-Class Sedan 2012 1.0% Chrysler Sebring Convertible 2010 0.63% +622 /scratch/Teaching/cars/car_ims/011090.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 99.53% Honda Accord Sedan 2012 0.44% Honda Odyssey Minivan 2007 0.01% Hyundai Veracruz SUV 2012 0.01% Suzuki SX4 Sedan 2012 0.0% +623 /scratch/Teaching/cars/car_ims/007581.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 100.0% Dodge Charger SRT-8 2009 0.0% Volkswagen Golf Hatchback 1991 0.0% Chevrolet Camaro Convertible 2012 0.0% Dodge Charger Sedan 2012 0.0% +624 /scratch/Teaching/cars/car_ims/009268.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 58.14% Ford F-450 Super Duty Crew Cab 2012 41.86% Ford F-150 Regular Cab 2007 0.0% Nissan NV Passenger Van 2012 0.0% Ford E-Series Wagon Van 2012 0.0% +625 /scratch/Teaching/cars/car_ims/006895.jpg Dodge Caravan Minivan 1997 Plymouth Neon Coupe 1999 99.99% Dodge Caravan Minivan 1997 0.0% Ford Focus Sedan 2007 0.0% Geo Metro Convertible 1993 0.0% Daewoo Nubira Wagon 2002 0.0% +626 /scratch/Teaching/cars/car_ims/010704.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 96.08% Hyundai Sonata Hybrid Sedan 2012 3.91% Ford Edge SUV 2012 0.01% Spyker C8 Coupe 2009 0.0% Hyundai Accent Sedan 2012 0.0% +627 /scratch/Teaching/cars/car_ims/006608.jpg Chrysler PT Cruiser Convertible 2008 Chrysler PT Cruiser Convertible 2008 99.27% Dodge Caravan Minivan 1997 0.38% Chevrolet Malibu Sedan 2007 0.27% Ford Freestar Minivan 2007 0.06% Dodge Caliber Wagon 2012 0.01% +628 /scratch/Teaching/cars/car_ims/004696.jpg Chevrolet Traverse SUV 2012 HUMMER H2 SUT Crew Cab 2009 8.37% Chevrolet Corvette Ron Fellows Edition Z06 2007 6.7% Chrysler Crossfire Convertible 2008 4.85% GMC Yukon Hybrid SUV 2012 4.4% Toyota 4Runner SUV 2012 3.79% +629 /scratch/Teaching/cars/car_ims/009757.jpg GMC Savana Van 2012 GMC Savana Van 2012 55.3% Chevrolet Express Van 2007 30.62% Audi V8 Sedan 1994 6.87% Plymouth Neon Coupe 1999 3.89% Ford Mustang Convertible 2007 1.69% +630 /scratch/Teaching/cars/car_ims/003003.jpg BMW X3 SUV 2012 BMW X3 SUV 2012 91.67% Jeep Compass SUV 2012 2.35% BMW 1 Series Coupe 2012 2.32% BMW X6 SUV 2012 2.32% Dodge Journey SUV 2012 0.68% +631 /scratch/Teaching/cars/car_ims/014395.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 75.28% BMW 1 Series Convertible 2012 8.3% BMW Z4 Convertible 2012 7.71% Rolls-Royce Ghost Sedan 2012 2.13% Jaguar XK XKR 2012 1.18% +632 /scratch/Teaching/cars/car_ims/002554.jpg BMW X5 SUV 2007 BMW 3 Series Wagon 2012 92.43% Mercedes-Benz E-Class Sedan 2012 2.73% BMW M5 Sedan 2010 1.37% Mercedes-Benz C-Class Sedan 2012 0.88% Hyundai Genesis Sedan 2012 0.7% +633 /scratch/Teaching/cars/car_ims/013908.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 65.22% Ford F-150 Regular Cab 2007 22.06% Ford E-Series Wagon Van 2012 4.94% Ford Ranger SuperCab 2011 4.6% Ford F-150 Regular Cab 2012 2.83% +634 /scratch/Teaching/cars/car_ims/014579.jpg Rolls-Royce Phantom Sedan 2012 Rolls-Royce Phantom Sedan 2012 62.91% Rolls-Royce Ghost Sedan 2012 37.08% Fisker Karma Sedan 2012 0.0% Chrysler 300 SRT-8 2010 0.0% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% +635 /scratch/Teaching/cars/car_ims/014999.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 21.0% Ford Mustang Convertible 2007 19.48% Chevrolet Sonic Sedan 2012 10.48% BMW 6 Series Convertible 2007 10.21% Mitsubishi Lancer Sedan 2012 5.86% +636 /scratch/Teaching/cars/car_ims/008716.jpg Ford Mustang Convertible 2007 Ford Mustang Convertible 2007 100.0% Dodge Charger Sedan 2012 0.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Dodge Charger SRT-8 2009 0.0% Chevrolet Camaro Convertible 2012 0.0% +637 /scratch/Teaching/cars/car_ims/004416.jpg Chevrolet Corvette Convertible 2012 Lamborghini Diablo Coupe 2001 97.37% Chevrolet Corvette Convertible 2012 1.1% Ford GT Coupe 2006 0.93% Dodge Charger Sedan 2012 0.34% Ferrari 458 Italia Convertible 2012 0.17% +638 /scratch/Teaching/cars/car_ims/002442.jpg BMW 3 Series Wagon 2012 BMW 3 Series Wagon 2012 68.42% Daewoo Nubira Wagon 2002 21.88% Ford Focus Sedan 2007 7.69% Suzuki Aerio Sedan 2007 1.56% Acura TL Type-S 2008 0.15% +639 /scratch/Teaching/cars/car_ims/003992.jpg Buick Enclave SUV 2012 Buick Enclave SUV 2012 49.19% Chevrolet Traverse SUV 2012 22.36% Jeep Grand Cherokee SUV 2012 15.51% Hyundai Veracruz SUV 2012 5.59% Dodge Durango SUV 2007 3.07% +640 /scratch/Teaching/cars/car_ims/006082.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 98.64% Chevrolet Silverado 1500 Extended Cab 2012 0.81% Chevrolet Silverado 2500HD Regular Cab 2012 0.33% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.21% Chevrolet Avalanche Crew Cab 2012 0.01% +641 /scratch/Teaching/cars/car_ims/011625.jpg Infiniti QX56 SUV 2011 Infiniti QX56 SUV 2011 100.0% Dodge Durango SUV 2012 0.0% Mazda Tribute SUV 2011 0.0% GMC Acadia SUV 2012 0.0% Land Rover Range Rover SUV 2012 0.0% +642 /scratch/Teaching/cars/car_ims/006980.jpg Dodge Ram Pickup 3500 Crew Cab 2010 AM General Hummer SUV 2000 95.9% HUMMER H2 SUT Crew Cab 2009 2.28% HUMMER H3T Crew Cab 2010 1.64% Ford F-450 Super Duty Crew Cab 2012 0.11% Ford Ranger SuperCab 2011 0.01% +643 /scratch/Teaching/cars/car_ims/008322.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 100.0% Ferrari 458 Italia Coupe 2012 0.0% Chevrolet Corvette Convertible 2012 0.0% Ferrari FF Coupe 2012 0.0% Chevrolet Camaro Convertible 2012 0.0% +644 /scratch/Teaching/cars/car_ims/009348.jpg Ford F-150 Regular Cab 2007 HUMMER H3T Crew Cab 2010 73.93% Ford F-150 Regular Cab 2007 16.38% Ford Ranger SuperCab 2011 8.66% Dodge Ram Pickup 3500 Crew Cab 2010 0.46% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.23% +645 /scratch/Teaching/cars/car_ims/011815.jpg Jaguar XK XKR 2012 Aston Martin V8 Vantage Coupe 2012 85.53% Jaguar XK XKR 2012 14.47% Porsche Panamera Sedan 2012 0.0% Aston Martin V8 Vantage Convertible 2012 0.0% Ferrari 458 Italia Coupe 2012 0.0% +646 /scratch/Teaching/cars/car_ims/004434.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Convertible 2012 99.83% Geo Metro Convertible 1993 0.11% Ford Mustang Convertible 2007 0.04% Chevrolet Camaro Convertible 2012 0.02% Ferrari California Convertible 2012 0.0% +647 /scratch/Teaching/cars/car_ims/010411.jpg Honda Odyssey Minivan 2012 Jeep Grand Cherokee SUV 2012 61.06% Jeep Liberty SUV 2012 12.38% Suzuki SX4 Sedan 2012 7.06% Daewoo Nubira Wagon 2002 4.4% Jeep Compass SUV 2012 2.19% +648 /scratch/Teaching/cars/car_ims/003908.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 95.46% Acura RL Sedan 2012 3.35% Buick Regal GS 2012 0.75% Hyundai Veracruz SUV 2012 0.11% Mitsubishi Lancer Sedan 2012 0.05% +649 /scratch/Teaching/cars/car_ims/015223.jpg Tesla Model S Sedan 2012 BMW 1 Series Convertible 2012 59.09% BMW X6 SUV 2012 25.82% BMW 3 Series Wagon 2012 6.99% Hyundai Accent Sedan 2012 2.57% Hyundai Sonata Hybrid Sedan 2012 1.66% +650 /scratch/Teaching/cars/car_ims/011392.jpg Hyundai Elantra Touring Hatchback 2012 Eagle Talon Hatchback 1998 39.84% Hyundai Elantra Touring Hatchback 2012 13.63% Ford Focus Sedan 2007 5.67% Audi RS 4 Convertible 2008 5.56% Ford Mustang Convertible 2007 4.92% +651 /scratch/Teaching/cars/car_ims/015246.jpg Tesla Model S Sedan 2012 Aston Martin V8 Vantage Convertible 2012 86.37% Aston Martin V8 Vantage Coupe 2012 4.3% Aston Martin Virage Convertible 2012 3.59% BMW 6 Series Convertible 2007 1.03% Ferrari California Convertible 2012 0.7% +652 /scratch/Teaching/cars/car_ims/000143.jpg Acura RL Sedan 2012 Audi S4 Sedan 2007 35.47% Rolls-Royce Ghost Sedan 2012 18.4% Rolls-Royce Phantom Sedan 2012 6.25% Aston Martin V8 Vantage Convertible 2012 6.18% Audi TTS Coupe 2012 4.73% +653 /scratch/Teaching/cars/car_ims/009657.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 100.0% Jeep Compass SUV 2012 0.0% GMC Yukon Hybrid SUV 2012 0.0% Chrysler 300 SRT-8 2010 0.0% Chevrolet Tahoe Hybrid SUV 2012 0.0% +654 /scratch/Teaching/cars/car_ims/009563.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 99.75% Scion xD Hatchback 2012 0.22% Toyota Corolla Sedan 2012 0.02% Hyundai Tucson SUV 2012 0.01% Suzuki SX4 Hatchback 2012 0.0% +655 /scratch/Teaching/cars/car_ims/004966.jpg Chevrolet Impala Sedan 2007 Chevrolet Malibu Sedan 2007 43.82% Chrysler Sebring Convertible 2010 23.32% Hyundai Elantra Sedan 2007 18.52% Chevrolet Monte Carlo Coupe 2007 5.75% Rolls-Royce Phantom Drophead Coupe Convertible 2012 3.67% +656 /scratch/Teaching/cars/car_ims/014411.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 97.6% Dodge Charger Sedan 2012 0.88% Audi S4 Sedan 2007 0.81% Ford Mustang Convertible 2007 0.23% Dodge Challenger SRT8 2011 0.08% +657 /scratch/Teaching/cars/car_ims/004441.jpg Chevrolet Corvette Convertible 2012 Ferrari 458 Italia Coupe 2012 78.58% Lamborghini Diablo Coupe 2001 16.66% Chevrolet Corvette Convertible 2012 2.26% Spyker C8 Coupe 2009 1.13% Aston Martin V8 Vantage Coupe 2012 0.68% +658 /scratch/Teaching/cars/car_ims/011300.jpg Hyundai Sonata Sedan 2012 Hyundai Sonata Sedan 2012 99.79% Toyota Corolla Sedan 2012 0.09% Hyundai Azera Sedan 2012 0.05% Hyundai Sonata Hybrid Sedan 2012 0.04% Hyundai Elantra Sedan 2007 0.01% +659 /scratch/Teaching/cars/car_ims/002102.jpg BMW ActiveHybrid 5 Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 98.54% BMW 3 Series Wagon 2012 1.34% Audi S6 Sedan 2011 0.09% Acura TL Type-S 2008 0.01% Acura TL Sedan 2012 0.0% +660 /scratch/Teaching/cars/car_ims/008892.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 100.0% Hyundai Santa Fe SUV 2012 0.0% Toyota 4Runner SUV 2012 0.0% Land Rover LR2 SUV 2012 0.0% Dodge Durango SUV 2007 0.0% +661 /scratch/Teaching/cars/car_ims/000600.jpg Aston Martin V8 Vantage Convertible 2012 BMW M6 Convertible 2010 64.69% Aston Martin Virage Convertible 2012 18.36% Chevrolet Camaro Convertible 2012 6.81% Aston Martin V8 Vantage Coupe 2012 3.83% Jaguar XK XKR 2012 2.09% +662 /scratch/Teaching/cars/car_ims/004782.jpg Chevrolet Camaro Convertible 2012 Ferrari FF Coupe 2012 80.67% Mitsubishi Lancer Sedan 2012 4.76% McLaren MP4-12C Coupe 2012 4.2% Hyundai Veloster Hatchback 2012 2.65% Chevrolet Corvette Convertible 2012 1.78% +663 /scratch/Teaching/cars/car_ims/012429.jpg Lamborghini Aventador Coupe 2012 Spyker C8 Convertible 2009 52.43% Bugatti Veyron 16.4 Coupe 2009 44.0% Mercedes-Benz SL-Class Coupe 2009 2.69% Lamborghini Reventon Coupe 2008 0.23% Aston Martin V8 Vantage Convertible 2012 0.19% +664 /scratch/Teaching/cars/car_ims/007575.jpg Dodge Challenger SRT8 2011 Rolls-Royce Phantom Sedan 2012 71.66% Bentley Arnage Sedan 2009 18.76% Chevrolet TrailBlazer SS 2009 9.03% Land Rover Range Rover SUV 2012 0.13% Cadillac CTS-V Sedan 2012 0.07% +665 /scratch/Teaching/cars/car_ims/006747.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2007 70.18% Dodge Dakota Crew Cab 2010 27.61% Dodge Caliber Wagon 2012 2.21% Dodge Magnum Wagon 2008 0.0% Dodge Durango SUV 2012 0.0% +666 /scratch/Teaching/cars/car_ims/011650.jpg Infiniti QX56 SUV 2011 Infiniti QX56 SUV 2011 99.97% Bentley Mulsanne Sedan 2011 0.02% Buick Verano Sedan 2012 0.0% Maybach Landaulet Convertible 2012 0.0% Chevrolet Malibu Hybrid Sedan 2010 0.0% +667 /scratch/Teaching/cars/car_ims/010408.jpg Honda Odyssey Minivan 2012 Honda Odyssey Minivan 2012 99.72% Ford Edge SUV 2012 0.28% Honda Accord Sedan 2012 0.0% Land Rover LR2 SUV 2012 0.0% Honda Odyssey Minivan 2007 0.0% +668 /scratch/Teaching/cars/car_ims/002225.jpg BMW 1 Series Coupe 2012 BMW 1 Series Coupe 2012 98.2% Dodge Caliber Wagon 2007 0.96% Suzuki SX4 Hatchback 2012 0.19% Volvo C30 Hatchback 2012 0.16% HUMMER H3T Crew Cab 2010 0.13% +669 /scratch/Teaching/cars/car_ims/012883.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 99.95% Bentley Continental Supersports Conv. Convertible 2012 0.04% Ford GT Coupe 2006 0.0% Mercedes-Benz SL-Class Coupe 2009 0.0% Spyker C8 Coupe 2009 0.0% +670 /scratch/Teaching/cars/car_ims/013917.jpg Nissan NV Passenger Van 2012 Jeep Patriot SUV 2012 47.43% Chevrolet Tahoe Hybrid SUV 2012 17.37% Jeep Wrangler SUV 2012 12.64% Nissan NV Passenger Van 2012 7.7% Jeep Liberty SUV 2012 5.34% +671 /scratch/Teaching/cars/car_ims/009827.jpg GMC Yukon Hybrid SUV 2012 GMC Yukon Hybrid SUV 2012 99.9% HUMMER H3T Crew Cab 2010 0.09% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.01% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% Ford F-150 Regular Cab 2012 0.0% +672 /scratch/Teaching/cars/car_ims/014721.jpg Spyker C8 Convertible 2009 Spyker C8 Coupe 2009 43.64% Mitsubishi Lancer Sedan 2012 41.7% McLaren MP4-12C Coupe 2012 8.12% Hyundai Veloster Hatchback 2012 4.89% HUMMER H3T Crew Cab 2010 0.77% +673 /scratch/Teaching/cars/car_ims/001746.jpg Audi S5 Coupe 2012 Audi S5 Coupe 2012 31.56% Audi A5 Coupe 2012 21.96% Acura RL Sedan 2012 11.93% Audi S4 Sedan 2007 10.15% Acura TSX Sedan 2012 6.64% +674 /scratch/Teaching/cars/car_ims/015475.jpg Toyota Corolla Sedan 2012 Aston Martin Virage Convertible 2012 48.27% Acura TL Type-S 2008 24.38% Hyundai Genesis Sedan 2012 15.78% Honda Accord Sedan 2012 6.32% Chevrolet Monte Carlo Coupe 2007 0.97% +675 /scratch/Teaching/cars/car_ims/013396.jpg Mercedes-Benz SL-Class Coupe 2009 Mercedes-Benz SL-Class Coupe 2009 98.3% BMW M6 Convertible 2010 0.83% Aston Martin Virage Convertible 2012 0.33% Audi R8 Coupe 2012 0.16% Lamborghini Reventon Coupe 2008 0.11% +676 /scratch/Teaching/cars/car_ims/004427.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Convertible 2012 57.48% BMW Z4 Convertible 2012 41.93% Aston Martin V8 Vantage Convertible 2012 0.19% Ferrari California Convertible 2012 0.12% BMW M6 Convertible 2010 0.11% +677 /scratch/Teaching/cars/car_ims/010890.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 60.2% Ford Fiesta Sedan 2012 39.4% Scion xD Hatchback 2012 0.37% Suzuki SX4 Hatchback 2012 0.02% Hyundai Veloster Hatchback 2012 0.01% +678 /scratch/Teaching/cars/car_ims/013957.jpg Nissan Juke Hatchback 2012 HUMMER H2 SUT Crew Cab 2009 77.02% HUMMER H3T Crew Cab 2010 13.07% Nissan Juke Hatchback 2012 3.08% Suzuki Kizashi Sedan 2012 1.14% Jeep Grand Cherokee SUV 2012 0.56% +679 /scratch/Teaching/cars/car_ims/012211.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 82.0% Jeep Grand Cherokee SUV 2012 12.06% Isuzu Ascender SUV 2008 5.25% GMC Acadia SUV 2012 0.24% Volvo XC90 SUV 2007 0.16% +680 /scratch/Teaching/cars/car_ims/014328.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 99.06% Dodge Caravan Minivan 1997 0.77% Chrysler Town and Country Minivan 2012 0.07% Audi 100 Wagon 1994 0.05% Ford Freestar Minivan 2007 0.04% +681 /scratch/Teaching/cars/car_ims/001464.jpg Audi 100 Wagon 1994 Audi 100 Sedan 1994 76.97% Audi V8 Sedan 1994 15.08% Mercedes-Benz 300-Class Convertible 1993 6.11% Volkswagen Golf Hatchback 1991 0.6% Volvo 240 Sedan 1993 0.52% +682 /scratch/Teaching/cars/car_ims/010220.jpg HUMMER H3T Crew Cab 2010 GMC Canyon Extended Cab 2012 99.02% Chevrolet Silverado 1500 Extended Cab 2012 0.79% HUMMER H3T Crew Cab 2010 0.09% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.02% Dodge Dakota Club Cab 2007 0.02% +683 /scratch/Teaching/cars/car_ims/009050.jpg Ford Ranger SuperCab 2011 Ford Ranger SuperCab 2011 97.25% Chevrolet Silverado 1500 Extended Cab 2012 1.41% Dodge Dakota Club Cab 2007 0.83% Volvo 240 Sedan 1993 0.22% Dodge Dakota Crew Cab 2010 0.11% +684 /scratch/Teaching/cars/car_ims/008465.jpg Ferrari 458 Italia Coupe 2012 Audi S5 Convertible 2012 59.51% Hyundai Genesis Sedan 2012 10.84% Porsche Panamera Sedan 2012 10.32% Mercedes-Benz E-Class Sedan 2012 7.77% Infiniti G Coupe IPL 2012 3.62% +685 /scratch/Teaching/cars/car_ims/010568.jpg Honda Accord Coupe 2012 Honda Accord Coupe 2012 93.0% Acura TL Type-S 2008 3.04% Eagle Talon Hatchback 1998 2.18% BMW M6 Convertible 2010 0.84% Nissan 240SX Coupe 1998 0.33% +686 /scratch/Teaching/cars/car_ims/002226.jpg BMW 1 Series Coupe 2012 BMW 1 Series Coupe 2012 59.22% BMW 3 Series Wagon 2012 13.58% Mitsubishi Lancer Sedan 2012 12.72% BMW 1 Series Convertible 2012 5.84% BMW 3 Series Sedan 2012 2.0% +687 /scratch/Teaching/cars/car_ims/005122.jpg Chevrolet Sonic Sedan 2012 BMW X6 SUV 2012 36.34% Chevrolet Sonic Sedan 2012 27.45% Hyundai Accent Sedan 2012 11.69% Suzuki SX4 Hatchback 2012 7.0% Dodge Journey SUV 2012 5.71% +688 /scratch/Teaching/cars/car_ims/007993.jpg Eagle Talon Hatchback 1998 Eagle Talon Hatchback 1998 83.19% Scion xD Hatchback 2012 16.35% Mitsubishi Lancer Sedan 2012 0.23% Toyota Corolla Sedan 2012 0.12% Chevrolet Monte Carlo Coupe 2007 0.08% +689 /scratch/Teaching/cars/car_ims/016051.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 56.8% BMW X5 SUV 2007 13.91% Mazda Tribute SUV 2011 11.2% Land Rover Range Rover SUV 2012 6.02% Suzuki SX4 Hatchback 2012 4.51% +690 /scratch/Teaching/cars/car_ims/000033.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 98.93% HUMMER H3T Crew Cab 2010 0.91% HUMMER H2 SUT Crew Cab 2009 0.16% Jeep Patriot SUV 2012 0.0% Rolls-Royce Phantom Sedan 2012 0.0% +691 /scratch/Teaching/cars/car_ims/015077.jpg Suzuki SX4 Hatchback 2012 Suzuki Kizashi Sedan 2012 60.32% Volvo C30 Hatchback 2012 16.97% Chevrolet Sonic Sedan 2012 12.76% BMW 1 Series Coupe 2012 4.2% BMW 3 Series Sedan 2012 2.6% +692 /scratch/Teaching/cars/car_ims/011526.jpg Hyundai Azera Sedan 2012 Buick Verano Sedan 2012 76.32% Mitsubishi Lancer Sedan 2012 11.26% Infiniti G Coupe IPL 2012 5.35% Suzuki Kizashi Sedan 2012 2.25% Hyundai Azera Sedan 2012 1.06% +693 /scratch/Teaching/cars/car_ims/015147.jpg Suzuki SX4 Sedan 2012 BMW 3 Series Sedan 2012 32.91% Audi S5 Convertible 2012 24.42% Chevrolet Sonic Sedan 2012 15.63% Suzuki Kizashi Sedan 2012 4.18% Fisker Karma Sedan 2012 2.64% +694 /scratch/Teaching/cars/car_ims/014145.jpg Plymouth Neon Coupe 1999 Mitsubishi Lancer Sedan 2012 19.14% Hyundai Sonata Hybrid Sedan 2012 15.23% Hyundai Elantra Touring Hatchback 2012 12.67% Spyker C8 Coupe 2009 11.57% Scion xD Hatchback 2012 6.95% +695 /scratch/Teaching/cars/car_ims/007728.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 100.0% Chrysler Aspen SUV 2009 0.0% Dodge Caliber Wagon 2012 0.0% Dodge Caliber Wagon 2007 0.0% Volvo XC90 SUV 2007 0.0% +696 /scratch/Teaching/cars/car_ims/014074.jpg Nissan 240SX Coupe 1998 Dodge Charger Sedan 2012 61.3% Nissan 240SX Coupe 1998 12.92% Mercedes-Benz 300-Class Convertible 1993 6.34% Geo Metro Convertible 1993 5.85% Dodge Charger SRT-8 2009 4.8% +697 /scratch/Teaching/cars/car_ims/015644.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 100.0% Nissan 240SX Coupe 1998 0.0% Ford Focus Sedan 2007 0.0% Hyundai Elantra Touring Hatchback 2012 0.0% Suzuki Aerio Sedan 2007 0.0% +698 /scratch/Teaching/cars/car_ims/014953.jpg Suzuki Kizashi Sedan 2012 Toyota Corolla Sedan 2012 96.41% Acura TSX Sedan 2012 1.42% Hyundai Elantra Sedan 2007 0.9% Suzuki SX4 Sedan 2012 0.26% Toyota Camry Sedan 2012 0.21% +699 /scratch/Teaching/cars/car_ims/000732.jpg Aston Martin V8 Vantage Coupe 2012 Aston Martin V8 Vantage Coupe 2012 88.59% Fisker Karma Sedan 2012 8.22% Jaguar XK XKR 2012 2.19% Aston Martin V8 Vantage Convertible 2012 0.62% Lamborghini Reventon Coupe 2008 0.07% +700 /scratch/Teaching/cars/car_ims/012590.jpg Lamborghini Diablo Coupe 2001 Lamborghini Diablo Coupe 2001 99.92% Acura Integra Type R 2001 0.05% Ferrari 458 Italia Convertible 2012 0.03% Aston Martin V8 Vantage Convertible 2012 0.0% Ford GT Coupe 2006 0.0% +701 /scratch/Teaching/cars/car_ims/008074.jpg FIAT 500 Abarth 2012 FIAT 500 Abarth 2012 78.44% Hyundai Genesis Sedan 2012 8.59% Audi R8 Coupe 2012 6.94% Lamborghini Gallardo LP 570-4 Superleggera 2012 1.41% Chevrolet Corvette ZR1 2012 0.98% +702 /scratch/Teaching/cars/car_ims/014033.jpg Nissan 240SX Coupe 1998 Nissan 240SX Coupe 1998 95.42% Plymouth Neon Coupe 1999 2.35% Eagle Talon Hatchback 1998 2.16% BMW 3 Series Sedan 2012 0.03% Chevrolet Camaro Convertible 2012 0.02% +703 /scratch/Teaching/cars/car_ims/014859.jpg Suzuki Aerio Sedan 2007 Suzuki Aerio Sedan 2007 51.15% Ford Focus Sedan 2007 43.63% Audi S4 Sedan 2007 2.49% Daewoo Nubira Wagon 2002 1.25% BMW M5 Sedan 2010 0.27% +704 /scratch/Teaching/cars/car_ims/008489.jpg Ferrari 458 Italia Coupe 2012 Ferrari California Convertible 2012 80.27% Ferrari 458 Italia Coupe 2012 13.1% Ferrari 458 Italia Convertible 2012 2.0% Lamborghini Aventador Coupe 2012 1.94% Lamborghini Reventon Coupe 2008 1.9% +705 /scratch/Teaching/cars/car_ims/002980.jpg BMW X3 SUV 2012 Land Rover LR2 SUV 2012 47.52% Ford Edge SUV 2012 47.36% Toyota 4Runner SUV 2012 3.45% GMC Terrain SUV 2012 1.22% BMW X3 SUV 2012 0.19% +706 /scratch/Teaching/cars/car_ims/010980.jpg Hyundai Veracruz SUV 2012 Volvo XC90 SUV 2007 38.73% Acura ZDX Hatchback 2012 25.55% Land Rover Range Rover SUV 2012 8.19% Buick Enclave SUV 2012 4.67% Nissan Juke Hatchback 2012 2.91% +707 /scratch/Teaching/cars/car_ims/011681.jpg Isuzu Ascender SUV 2008 Ford Ranger SuperCab 2011 65.31% Isuzu Ascender SUV 2008 32.98% HUMMER H3T Crew Cab 2010 0.47% Mazda Tribute SUV 2011 0.44% Ford F-150 Regular Cab 2007 0.37% +708 /scratch/Teaching/cars/car_ims/014655.jpg Scion xD Hatchback 2012 BMW X6 SUV 2012 46.68% Dodge Journey SUV 2012 18.44% Chevrolet Sonic Sedan 2012 18.08% Suzuki SX4 Hatchback 2012 3.71% Ferrari FF Coupe 2012 1.69% +709 /scratch/Teaching/cars/car_ims/014848.jpg Suzuki Aerio Sedan 2007 Suzuki Kizashi Sedan 2012 44.32% Chrysler PT Cruiser Convertible 2008 13.72% Chevrolet Sonic Sedan 2012 11.63% smart fortwo Convertible 2012 6.96% Land Rover LR2 SUV 2012 5.65% +710 /scratch/Teaching/cars/car_ims/001427.jpg Audi 100 Wagon 1994 Audi 100 Wagon 1994 45.92% Audi 100 Sedan 1994 44.13% Audi V8 Sedan 1994 7.54% Mercedes-Benz 300-Class Convertible 1993 1.57% Lincoln Town Car Sedan 2011 0.67% +711 /scratch/Teaching/cars/car_ims/011775.jpg Jaguar XK XKR 2012 Jaguar XK XKR 2012 100.0% Aston Martin V8 Vantage Coupe 2012 0.0% Porsche Panamera Sedan 2012 0.0% Buick Regal GS 2012 0.0% BMW M3 Coupe 2012 0.0% +712 /scratch/Teaching/cars/car_ims/000818.jpg Aston Martin Virage Coupe 2012 Aston Martin Virage Coupe 2012 100.0% McLaren MP4-12C Coupe 2012 0.0% Aston Martin V8 Vantage Coupe 2012 0.0% Spyker C8 Coupe 2009 0.0% BMW M3 Coupe 2012 0.0% +713 /scratch/Teaching/cars/car_ims/000009.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 99.94% Jeep Wrangler SUV 2012 0.06% HUMMER H3T Crew Cab 2010 0.0% Lamborghini Diablo Coupe 2001 0.0% HUMMER H2 SUT Crew Cab 2009 0.0% +714 /scratch/Teaching/cars/car_ims/013636.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 100.0% Dodge Sprinter Cargo Van 2009 0.0% Volkswagen Golf Hatchback 1991 0.0% Ford E-Series Wagon Van 2012 0.0% Audi 100 Sedan 1994 0.0% +715 /scratch/Teaching/cars/car_ims/008656.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 99.89% Dodge Ram Pickup 3500 Quad Cab 2009 0.05% HUMMER H2 SUT Crew Cab 2009 0.04% AM General Hummer SUV 2000 0.02% Jeep Liberty SUV 2012 0.01% +716 /scratch/Teaching/cars/car_ims/011167.jpg Hyundai Accent Sedan 2012 BMW 3 Series Sedan 2012 34.32% Toyota Camry Sedan 2012 33.66% BMW M3 Coupe 2012 15.97% Audi TT Hatchback 2011 3.25% Ferrari FF Coupe 2012 2.06% +717 /scratch/Teaching/cars/car_ims/012951.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 96.97% FIAT 500 Convertible 2012 1.17% Bugatti Veyron 16.4 Convertible 2009 1.17% smart fortwo Convertible 2012 0.52% Audi RS 4 Convertible 2008 0.03% +718 /scratch/Teaching/cars/car_ims/010140.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 100.0% Plymouth Neon Coupe 1999 0.0% Audi 100 Wagon 1994 0.0% Dodge Caravan Minivan 1997 0.0% Mercedes-Benz 300-Class Convertible 1993 0.0% +719 /scratch/Teaching/cars/car_ims/013084.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 43.25% Spyker C8 Coupe 2009 31.67% Spyker C8 Convertible 2009 16.75% Lamborghini Aventador Coupe 2012 5.0% Aston Martin Virage Coupe 2012 1.71% +720 /scratch/Teaching/cars/car_ims/007168.jpg Dodge Sprinter Cargo Van 2009 Dodge Sprinter Cargo Van 2009 91.24% Mercedes-Benz Sprinter Van 2012 8.7% Audi 100 Sedan 1994 0.05% Ram C/V Cargo Van Minivan 2012 0.01% BMW M6 Convertible 2010 0.0% +721 /scratch/Teaching/cars/car_ims/013590.jpg Mercedes-Benz Sprinter Van 2012 Dodge Sprinter Cargo Van 2009 78.34% Mercedes-Benz Sprinter Van 2012 20.56% Nissan NV Passenger Van 2012 0.39% Ram C/V Cargo Van Minivan 2012 0.2% Maybach Landaulet Convertible 2012 0.08% +722 /scratch/Teaching/cars/car_ims/015424.jpg Toyota Corolla Sedan 2012 Toyota Corolla Sedan 2012 49.79% Toyota Camry Sedan 2012 48.07% Hyundai Accent Sedan 2012 1.07% Ford Fiesta Sedan 2012 0.51% Volkswagen Golf Hatchback 2012 0.28% +723 /scratch/Teaching/cars/car_ims/012976.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 99.79% GMC Acadia SUV 2012 0.05% Rolls-Royce Phantom Sedan 2012 0.03% Dodge Challenger SRT8 2011 0.03% Daewoo Nubira Wagon 2002 0.02% +724 /scratch/Teaching/cars/car_ims/006812.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2007 57.57% Dodge Caliber Wagon 2012 42.37% Dodge Magnum Wagon 2008 0.05% Dodge Charger Sedan 2012 0.0% Suzuki SX4 Hatchback 2012 0.0% +725 /scratch/Teaching/cars/car_ims/000349.jpg Acura TSX Sedan 2012 Acura TSX Sedan 2012 99.56% Acura RL Sedan 2012 0.34% Hyundai Sonata Sedan 2012 0.07% Acura TL Sedan 2012 0.02% BMW Z4 Convertible 2012 0.0% +726 /scratch/Teaching/cars/car_ims/013355.jpg Mercedes-Benz SL-Class Coupe 2009 Mercedes-Benz SL-Class Coupe 2009 41.39% Audi TT RS Coupe 2012 28.17% Chevrolet Camaro Convertible 2012 14.06% Jaguar XK XKR 2012 5.32% Bugatti Veyron 16.4 Convertible 2009 4.28% +727 /scratch/Teaching/cars/car_ims/001618.jpg Audi S6 Sedan 2011 Audi S6 Sedan 2011 99.97% Audi S4 Sedan 2012 0.03% Audi S5 Convertible 2012 0.0% Audi S5 Coupe 2012 0.0% Audi RS 4 Convertible 2008 0.0% +728 /scratch/Teaching/cars/car_ims/001863.jpg Audi S4 Sedan 2012 Audi A5 Coupe 2012 49.2% Audi S5 Convertible 2012 36.32% Audi S4 Sedan 2012 7.91% Audi S5 Coupe 2012 4.53% Audi S6 Sedan 2011 0.88% +729 /scratch/Teaching/cars/car_ims/015511.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 67.76% Chevrolet Malibu Sedan 2007 19.84% Ford F-150 Regular Cab 2007 8.9% Dodge Caliber Wagon 2012 2.51% Dodge Durango SUV 2007 0.36% +730 /scratch/Teaching/cars/car_ims/008480.jpg Ferrari 458 Italia Coupe 2012 Spyker C8 Convertible 2009 45.19% Ford GT Coupe 2006 43.83% Dodge Challenger SRT8 2011 6.67% Chevrolet Corvette ZR1 2012 3.2% Bugatti Veyron 16.4 Coupe 2009 0.52% +731 /scratch/Teaching/cars/car_ims/002609.jpg BMW X5 SUV 2007 BMW X5 SUV 2007 99.96% BMW X3 SUV 2012 0.02% BMW X6 SUV 2012 0.01% Buick Rainier SUV 2007 0.01% GMC Acadia SUV 2012 0.0% +732 /scratch/Teaching/cars/car_ims/003279.jpg Bentley Mulsanne Sedan 2011 Spyker C8 Convertible 2009 54.56% Chevrolet Corvette ZR1 2012 10.55% Bugatti Veyron 16.4 Coupe 2009 9.69% Audi R8 Coupe 2012 9.14% Mercedes-Benz SL-Class Coupe 2009 5.39% +733 /scratch/Teaching/cars/car_ims/010913.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 71.74% Hyundai Veracruz SUV 2012 21.73% Acura ZDX Hatchback 2012 2.04% Nissan Juke Hatchback 2012 1.63% Scion xD Hatchback 2012 1.03% +734 /scratch/Teaching/cars/car_ims/004762.jpg Chevrolet Camaro Convertible 2012 Chevrolet Camaro Convertible 2012 94.52% Chrysler Crossfire Convertible 2008 4.18% Audi A5 Coupe 2012 0.97% Audi S5 Coupe 2012 0.17% Spyker C8 Convertible 2009 0.03% +735 /scratch/Teaching/cars/car_ims/009327.jpg Ford F-150 Regular Cab 2007 HUMMER H3T Crew Cab 2010 43.41% AM General Hummer SUV 2000 21.42% HUMMER H2 SUT Crew Cab 2009 7.53% Ford Ranger SuperCab 2011 5.31% Ford F-150 Regular Cab 2012 4.28% +736 /scratch/Teaching/cars/car_ims/003600.jpg Bugatti Veyron 16.4 Convertible 2009 Bugatti Veyron 16.4 Coupe 2009 99.76% Ford GT Coupe 2006 0.21% Spyker C8 Convertible 2009 0.02% Bugatti Veyron 16.4 Convertible 2009 0.02% Spyker C8 Coupe 2009 0.0% +737 /scratch/Teaching/cars/car_ims/003857.jpg Buick Rainier SUV 2007 Volvo 240 Sedan 1993 39.32% Lincoln Town Car Sedan 2011 30.91% Buick Rainier SUV 2007 26.57% Audi 100 Wagon 1994 2.63% Isuzu Ascender SUV 2008 0.37% +738 /scratch/Teaching/cars/car_ims/014370.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 BMW 1 Series Convertible 2012 38.98% Bentley Continental Supersports Conv. Convertible 2012 21.56% Chevrolet Corvette Convertible 2012 15.76% Rolls-Royce Phantom Drophead Coupe Convertible 2012 12.7% MINI Cooper Roadster Convertible 2012 8.53% +739 /scratch/Teaching/cars/car_ims/002307.jpg BMW 3 Series Sedan 2012 BMW 1 Series Coupe 2012 35.77% Volvo C30 Hatchback 2012 33.99% BMW Z4 Convertible 2012 5.82% Chevrolet Camaro Convertible 2012 4.82% BMW 1 Series Convertible 2012 4.35% +740 /scratch/Teaching/cars/car_ims/015777.jpg Volkswagen Beetle Hatchback 2012 Volkswagen Beetle Hatchback 2012 92.92% Nissan Leaf Hatchback 2012 2.99% Maybach Landaulet Convertible 2012 2.44% Bentley Continental Flying Spur Sedan 2007 0.81% Bentley Continental Supersports Conv. Convertible 2012 0.47% +741 /scratch/Teaching/cars/car_ims/001337.jpg Audi 100 Sedan 1994 Audi 100 Wagon 1994 95.75% Mercedes-Benz 300-Class Convertible 1993 4.24% Audi 100 Sedan 1994 0.01% Volkswagen Golf Hatchback 1991 0.0% BMW M6 Convertible 2010 0.0% +742 /scratch/Teaching/cars/car_ims/007051.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 98.45% Dodge Ram Pickup 3500 Crew Cab 2010 1.55% HUMMER H3T Crew Cab 2010 0.0% GMC Canyon Extended Cab 2012 0.0% HUMMER H2 SUT Crew Cab 2009 0.0% +743 /scratch/Teaching/cars/car_ims/013230.jpg Mercedes-Benz 300-Class Convertible 1993 Mercedes-Benz 300-Class Convertible 1993 94.91% Dodge Charger SRT-8 2009 3.6% Dodge Charger Sedan 2012 1.48% Ford Mustang Convertible 2007 0.0% Dodge Magnum Wagon 2008 0.0% +744 /scratch/Teaching/cars/car_ims/007872.jpg Dodge Charger Sedan 2012 Dodge Charger Sedan 2012 44.11% Buick Verano Sedan 2012 18.52% Honda Accord Coupe 2012 9.06% Buick Regal GS 2012 8.87% Audi S4 Sedan 2012 6.06% +745 /scratch/Teaching/cars/car_ims/006685.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 54.05% Dodge Caravan Minivan 1997 11.65% Chevrolet Monte Carlo Coupe 2007 8.71% Chevrolet Malibu Sedan 2007 7.17% Lincoln Town Car Sedan 2011 6.58% +746 /scratch/Teaching/cars/car_ims/015192.jpg Tesla Model S Sedan 2012 Tesla Model S Sedan 2012 68.73% Audi R8 Coupe 2012 23.36% BMW 3 Series Sedan 2012 3.58% Buick Regal GS 2012 1.34% BMW Z4 Convertible 2012 0.92% +747 /scratch/Teaching/cars/car_ims/013967.jpg Nissan Juke Hatchback 2012 Nissan Juke Hatchback 2012 99.62% BMW X3 SUV 2012 0.19% Hyundai Tucson SUV 2012 0.13% Hyundai Veracruz SUV 2012 0.02% Hyundai Santa Fe SUV 2012 0.01% +748 /scratch/Teaching/cars/car_ims/002079.jpg BMW ActiveHybrid 5 Sedan 2012 BMW 3 Series Sedan 2012 54.53% BMW ActiveHybrid 5 Sedan 2012 27.9% BMW 1 Series Convertible 2012 11.33% BMW Z4 Convertible 2012 4.95% BMW 1 Series Coupe 2012 0.6% +749 /scratch/Teaching/cars/car_ims/016002.jpg Volvo 240 Sedan 1993 Buick Rainier SUV 2007 86.42% Volvo 240 Sedan 1993 7.86% Ford Ranger SuperCab 2011 1.3% Ford F-150 Regular Cab 2007 0.87% GMC Canyon Extended Cab 2012 0.69% +750 /scratch/Teaching/cars/car_ims/007936.jpg Dodge Charger SRT-8 2009 Rolls-Royce Phantom Sedan 2012 54.73% Chevrolet TrailBlazer SS 2009 14.99% Dodge Charger SRT-8 2009 8.15% Aston Martin V8 Vantage Coupe 2012 6.69% Chevrolet Cobalt SS 2010 6.44% +751 /scratch/Teaching/cars/car_ims/010130.jpg Geo Metro Convertible 1993 Chevrolet Corvette Convertible 2012 60.85% Mercedes-Benz 300-Class Convertible 1993 31.48% Ford Mustang Convertible 2007 4.43% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.61% Geo Metro Convertible 1993 0.5% +752 /scratch/Teaching/cars/car_ims/003523.jpg Bentley Continental Flying Spur Sedan 2007 Mercedes-Benz C-Class Sedan 2012 69.58% Bentley Arnage Sedan 2009 16.9% Audi V8 Sedan 1994 9.14% Nissan 240SX Coupe 1998 1.27% Volvo 240 Sedan 1993 0.81% +753 /scratch/Teaching/cars/car_ims/015824.jpg Volkswagen Beetle Hatchback 2012 Infiniti G Coupe IPL 2012 74.57% Hyundai Veloster Hatchback 2012 12.45% Mitsubishi Lancer Sedan 2012 7.08% BMW M5 Sedan 2010 2.32% Volkswagen Beetle Hatchback 2012 1.74% +754 /scratch/Teaching/cars/car_ims/008826.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 99.97% Dodge Caravan Minivan 1997 0.01% Ford Ranger SuperCab 2011 0.01% Buick Rainier SUV 2007 0.0% Audi 100 Wagon 1994 0.0% +755 /scratch/Teaching/cars/car_ims/001420.jpg Audi 100 Wagon 1994 Audi 100 Wagon 1994 57.52% Audi 100 Sedan 1994 22.69% Mercedes-Benz 300-Class Convertible 1993 14.56% Volvo 240 Sedan 1993 1.45% Volkswagen Golf Hatchback 1991 1.2% +756 /scratch/Teaching/cars/car_ims/013730.jpg Mitsubishi Lancer Sedan 2012 Bentley Continental GT Coupe 2012 72.31% BMW Z4 Convertible 2012 13.64% Chevrolet Cobalt SS 2010 2.62% BMW M5 Sedan 2010 1.35% Ford Mustang Convertible 2007 1.21% +757 /scratch/Teaching/cars/car_ims/004698.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 84.7% Dodge Journey SUV 2012 5.42% BMW X6 SUV 2012 3.52% Mazda Tribute SUV 2011 2.5% Ford Expedition EL SUV 2009 0.7% +758 /scratch/Teaching/cars/car_ims/003921.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 77.75% BMW X6 SUV 2012 19.57% Chevrolet Sonic Sedan 2012 1.54% Suzuki SX4 Hatchback 2012 0.8% BMW X3 SUV 2012 0.16% +759 /scratch/Teaching/cars/car_ims/002297.jpg BMW 3 Series Sedan 2012 Rolls-Royce Phantom Sedan 2012 51.73% Bentley Continental Flying Spur Sedan 2007 14.59% BMW 3 Series Sedan 2012 7.04% Porsche Panamera Sedan 2012 4.74% Bentley Continental GT Coupe 2007 3.93% +760 /scratch/Teaching/cars/car_ims/008484.jpg Ferrari 458 Italia Coupe 2012 Ferrari 458 Italia Coupe 2012 77.95% Ferrari 458 Italia Convertible 2012 15.34% Chevrolet Corvette Convertible 2012 5.5% Ferrari California Convertible 2012 1.14% McLaren MP4-12C Coupe 2012 0.03% +761 /scratch/Teaching/cars/car_ims/014198.jpg Porsche Panamera Sedan 2012 Porsche Panamera Sedan 2012 51.13% Buick Rainier SUV 2007 13.4% Audi 100 Wagon 1994 12.44% Volkswagen Golf Hatchback 1991 8.82% Volvo 240 Sedan 1993 5.16% +762 /scratch/Teaching/cars/car_ims/010816.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 47.79% Dodge Durango SUV 2012 35.19% Chrysler PT Cruiser Convertible 2008 4.43% Infiniti QX56 SUV 2011 3.64% Hyundai Genesis Sedan 2012 3.02% +763 /scratch/Teaching/cars/car_ims/007710.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 90.05% Chrysler Aspen SUV 2009 5.08% Dodge Dakota Club Cab 2007 2.78% Dodge Dakota Crew Cab 2010 0.95% Dodge Caliber Wagon 2012 0.8% +764 /scratch/Teaching/cars/car_ims/006589.jpg Chrysler PT Cruiser Convertible 2008 Chrysler PT Cruiser Convertible 2008 100.0% Dodge Caliber Wagon 2012 0.0% Chrysler Town and Country Minivan 2012 0.0% Audi S4 Sedan 2007 0.0% Suzuki SX4 Sedan 2012 0.0% +765 /scratch/Teaching/cars/car_ims/008316.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 89.76% Tesla Model S Sedan 2012 10.14% Cadillac CTS-V Sedan 2012 0.05% Ferrari 458 Italia Coupe 2012 0.02% Lamborghini Reventon Coupe 2008 0.01% +766 /scratch/Teaching/cars/car_ims/006133.jpg Chrysler Aspen SUV 2009 Dodge Durango SUV 2007 66.34% Jeep Compass SUV 2012 25.79% Jeep Liberty SUV 2012 5.41% Chrysler Aspen SUV 2009 1.78% Dodge Dakota Crew Cab 2010 0.48% +767 /scratch/Teaching/cars/car_ims/002056.jpg BMW ActiveHybrid 5 Sedan 2012 BMW Z4 Convertible 2012 99.55% BMW ActiveHybrid 5 Sedan 2012 0.44% BMW 3 Series Sedan 2012 0.01% Fisker Karma Sedan 2012 0.0% Aston Martin Virage Convertible 2012 0.0% +768 /scratch/Teaching/cars/car_ims/012823.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 100.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Chevrolet Malibu Sedan 2007 0.0% Audi 100 Wagon 1994 0.0% Volvo 240 Sedan 1993 0.0% +769 /scratch/Teaching/cars/car_ims/001121.jpg Audi TTS Coupe 2012 Audi R8 Coupe 2012 76.56% Audi TT RS Coupe 2012 7.87% Audi S4 Sedan 2012 6.58% Audi TTS Coupe 2012 4.03% Volvo C30 Hatchback 2012 2.6% +770 /scratch/Teaching/cars/car_ims/013075.jpg McLaren MP4-12C Coupe 2012 Spyker C8 Convertible 2009 49.46% McLaren MP4-12C Coupe 2012 21.65% Lamborghini Aventador Coupe 2012 13.78% Spyker C8 Coupe 2009 7.46% Ford GT Coupe 2006 7.28% +771 /scratch/Teaching/cars/car_ims/012908.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 100.0% Cadillac CTS-V Sedan 2012 0.0% Bentley Continental Supersports Conv. Convertible 2012 0.0% FIAT 500 Convertible 2012 0.0% smart fortwo Convertible 2012 0.0% +772 /scratch/Teaching/cars/car_ims/005847.jpg Chevrolet Malibu Sedan 2007 BMW 6 Series Convertible 2007 34.6% Ford F-150 Regular Cab 2007 14.22% Volvo XC90 SUV 2007 14.14% Dodge Ram Pickup 3500 Crew Cab 2010 7.68% Hyundai Genesis Sedan 2012 4.66% +773 /scratch/Teaching/cars/car_ims/012960.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 100.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Acura Integra Type R 2001 0.0% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Chevrolet Camaro Convertible 2012 0.0% +774 /scratch/Teaching/cars/car_ims/000627.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin V8 Vantage Coupe 2012 56.55% Aston Martin Virage Convertible 2012 32.51% BMW M6 Convertible 2010 9.51% Aston Martin V8 Vantage Convertible 2012 1.37% Jaguar XK XKR 2012 0.05% +775 /scratch/Teaching/cars/car_ims/005723.jpg Chevrolet Express Van 2007 Chevrolet Express Cargo Van 2007 56.04% GMC Savana Van 2012 43.92% Chevrolet Express Van 2007 0.04% Volkswagen Golf Hatchback 1991 0.0% Audi 100 Wagon 1994 0.0% +776 /scratch/Teaching/cars/car_ims/011465.jpg Hyundai Azera Sedan 2012 Honda Odyssey Minivan 2012 28.41% Honda Accord Sedan 2012 25.47% Porsche Panamera Sedan 2012 24.3% Acura RL Sedan 2012 4.36% Chevrolet Cobalt SS 2010 4.28% +777 /scratch/Teaching/cars/car_ims/004650.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 86.41% Hyundai Tucson SUV 2012 12.98% Ford Edge SUV 2012 0.23% Suzuki SX4 Hatchback 2012 0.2% BMW X6 SUV 2012 0.04% +778 /scratch/Teaching/cars/car_ims/014580.jpg Rolls-Royce Phantom Sedan 2012 Nissan NV Passenger Van 2012 47.1% Chrysler PT Cruiser Convertible 2008 15.91% Rolls-Royce Phantom Sedan 2012 7.28% Honda Odyssey Minivan 2012 5.71% Dodge Durango SUV 2012 4.72% +779 /scratch/Teaching/cars/car_ims/006959.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 75.16% Plymouth Neon Coupe 1999 24.31% Chevrolet Traverse SUV 2012 0.32% Hyundai Tucson SUV 2012 0.19% Hyundai Elantra Touring Hatchback 2012 0.01% +780 /scratch/Teaching/cars/car_ims/000632.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin V8 Vantage Coupe 2012 56.48% Aston Martin V8 Vantage Convertible 2012 42.87% Aston Martin Virage Convertible 2012 0.39% Fisker Karma Sedan 2012 0.13% Jaguar XK XKR 2012 0.12% +781 /scratch/Teaching/cars/car_ims/003032.jpg BMW Z4 Convertible 2012 BMW Z4 Convertible 2012 81.91% BMW 1 Series Convertible 2012 13.46% Jaguar XK XKR 2012 1.95% Hyundai Elantra Sedan 2007 0.92% Dodge Charger Sedan 2012 0.82% +782 /scratch/Teaching/cars/car_ims/006364.jpg Chrysler 300 SRT-8 2010 Dodge Charger SRT-8 2009 79.83% Chevrolet Monte Carlo Coupe 2007 13.39% Rolls-Royce Phantom Drophead Coupe Convertible 2012 5.0% Nissan Leaf Hatchback 2012 0.81% Chevrolet Corvette Convertible 2012 0.5% +783 /scratch/Teaching/cars/car_ims/007496.jpg Dodge Magnum Wagon 2008 Dodge Magnum Wagon 2008 90.4% Dodge Charger SRT-8 2009 9.53% Chevrolet HHR SS 2010 0.06% Dodge Charger Sedan 2012 0.01% Dodge Journey SUV 2012 0.0% +784 /scratch/Teaching/cars/car_ims/008279.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 99.87% Chevrolet Camaro Convertible 2012 0.07% Ferrari 458 Italia Convertible 2012 0.04% Ferrari 458 Italia Coupe 2012 0.01% Chevrolet Corvette Convertible 2012 0.01% +785 /scratch/Teaching/cars/car_ims/008861.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 99.46% Ford F-150 Regular Cab 2012 0.42% Ford F-450 Super Duty Crew Cab 2012 0.05% Chrysler Aspen SUV 2009 0.04% Dodge Ram Pickup 3500 Crew Cab 2010 0.02% +786 /scratch/Teaching/cars/car_ims/010412.jpg Honda Odyssey Minivan 2012 Hyundai Sonata Sedan 2012 76.8% Honda Odyssey Minivan 2012 16.54% Hyundai Genesis Sedan 2012 3.74% Mercedes-Benz E-Class Sedan 2012 0.96% Hyundai Elantra Sedan 2007 0.64% +787 /scratch/Teaching/cars/car_ims/001203.jpg Audi R8 Coupe 2012 Dodge Charger Sedan 2012 35.9% Audi R8 Coupe 2012 26.91% Chrysler 300 SRT-8 2010 19.26% Volvo C30 Hatchback 2012 7.1% Jaguar XK XKR 2012 2.39% +788 /scratch/Teaching/cars/car_ims/003807.jpg Buick Rainier SUV 2007 Ford Mustang Convertible 2007 74.68% Plymouth Neon Coupe 1999 12.4% Audi V8 Sedan 1994 6.04% Volkswagen Golf Hatchback 1991 3.32% Buick Rainier SUV 2007 1.61% +789 /scratch/Teaching/cars/car_ims/008503.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 99.92% Aston Martin V8 Vantage Coupe 2012 0.05% Dodge Challenger SRT8 2011 0.03% Tesla Model S Sedan 2012 0.0% BMW Z4 Convertible 2012 0.0% +790 /scratch/Teaching/cars/car_ims/012426.jpg Lamborghini Aventador Coupe 2012 Lamborghini Reventon Coupe 2008 63.1% Spyker C8 Coupe 2009 26.23% BMW 6 Series Convertible 2007 4.83% Aston Martin Virage Convertible 2012 2.37% Spyker C8 Convertible 2009 1.6% +791 /scratch/Teaching/cars/car_ims/001176.jpg Audi R8 Coupe 2012 BMW M6 Convertible 2010 80.67% BMW 6 Series Convertible 2007 7.73% Audi TTS Coupe 2012 5.52% Audi S5 Convertible 2012 2.14% Bugatti Veyron 16.4 Coupe 2009 1.36% +792 /scratch/Teaching/cars/car_ims/002185.jpg BMW 1 Series Convertible 2012 BMW 1 Series Convertible 2012 98.29% Chevrolet Sonic Sedan 2012 0.5% BMW M6 Convertible 2010 0.27% Acura RL Sedan 2012 0.19% Jeep Compass SUV 2012 0.14% +793 /scratch/Teaching/cars/car_ims/003826.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 100.0% Buick Enclave SUV 2012 0.0% Mazda Tribute SUV 2011 0.0% BMW X5 SUV 2007 0.0% Jeep Liberty SUV 2012 0.0% +794 /scratch/Teaching/cars/car_ims/010670.jpg Honda Accord Sedan 2012 Honda Accord Sedan 2012 99.71% Honda Accord Coupe 2012 0.27% Toyota Camry Sedan 2012 0.01% Hyundai Genesis Sedan 2012 0.0% Acura RL Sedan 2012 0.0% +795 /scratch/Teaching/cars/car_ims/007448.jpg Dodge Dakota Club Cab 2007 Dodge Dakota Club Cab 2007 98.89% Dodge Dakota Crew Cab 2010 0.5% Dodge Ram Pickup 3500 Quad Cab 2009 0.39% Mercedes-Benz 300-Class Convertible 1993 0.12% Dodge Magnum Wagon 2008 0.07% +796 /scratch/Teaching/cars/car_ims/000723.jpg Aston Martin V8 Vantage Coupe 2012 Aston Martin V8 Vantage Coupe 2012 99.52% Ferrari 458 Italia Coupe 2012 0.2% Aston Martin V8 Vantage Convertible 2012 0.15% Ferrari California Convertible 2012 0.06% McLaren MP4-12C Coupe 2012 0.04% +797 /scratch/Teaching/cars/car_ims/009184.jpg Ford GT Coupe 2006 Ford GT Coupe 2006 100.0% Bugatti Veyron 16.4 Convertible 2009 0.0% Spyker C8 Coupe 2009 0.0% Lamborghini Aventador Coupe 2012 0.0% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.0% +798 /scratch/Teaching/cars/car_ims/000066.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 98.36% HUMMER H2 SUT Crew Cab 2009 1.59% HUMMER H3T Crew Cab 2010 0.03% Jeep Wrangler SUV 2012 0.01% Maybach Landaulet Convertible 2012 0.0% +799 /scratch/Teaching/cars/car_ims/012992.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 98.77% Land Rover LR2 SUV 2012 0.43% Ford Edge SUV 2012 0.31% Chrysler PT Cruiser Convertible 2008 0.11% Dodge Durango SUV 2007 0.1% +800 /scratch/Teaching/cars/car_ims/013728.jpg Mitsubishi Lancer Sedan 2012 Audi S4 Sedan 2012 77.2% Dodge Charger Sedan 2012 17.79% Chevrolet Cobalt SS 2010 1.59% Audi S4 Sedan 2007 0.96% Audi S5 Coupe 2012 0.79% +801 /scratch/Teaching/cars/car_ims/009624.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 99.34% Hyundai Tucson SUV 2012 0.61% Hyundai Veloster Hatchback 2012 0.02% Ford Edge SUV 2012 0.01% Dodge Journey SUV 2012 0.01% +802 /scratch/Teaching/cars/car_ims/008594.jpg Ford F-450 Super Duty Crew Cab 2012 Dodge Ram Pickup 3500 Crew Cab 2010 92.79% Ford E-Series Wagon Van 2012 6.53% Ford Ranger SuperCab 2011 0.21% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.15% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.1% +803 /scratch/Teaching/cars/car_ims/005287.jpg Chevrolet Cobalt SS 2010 Dodge Charger Sedan 2012 78.8% Lamborghini Diablo Coupe 2001 15.17% Hyundai Veloster Hatchback 2012 2.6% Chevrolet Cobalt SS 2010 1.61% Spyker C8 Coupe 2009 0.81% +804 /scratch/Teaching/cars/car_ims/000508.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 97.16% Honda Accord Sedan 2012 2.26% Acura RL Sedan 2012 0.42% BMW X3 SUV 2012 0.11% Hyundai Veracruz SUV 2012 0.02% +805 /scratch/Teaching/cars/car_ims/005798.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Monte Carlo Coupe 2007 98.41% Chevrolet Malibu Sedan 2007 0.77% Chevrolet Impala Sedan 2007 0.36% Eagle Talon Hatchback 1998 0.21% Plymouth Neon Coupe 1999 0.13% +806 /scratch/Teaching/cars/car_ims/013129.jpg McLaren MP4-12C Coupe 2012 Lamborghini Aventador Coupe 2012 46.19% Ford GT Coupe 2006 35.93% McLaren MP4-12C Coupe 2012 13.49% Ferrari 458 Italia Convertible 2012 2.07% Ferrari FF Coupe 2012 1.09% +807 /scratch/Teaching/cars/car_ims/008759.jpg Ford Mustang Convertible 2007 Ford Mustang Convertible 2007 99.96% Buick Enclave SUV 2012 0.02% BMW X5 SUV 2007 0.01% Audi V8 Sedan 1994 0.0% Buick Rainier SUV 2007 0.0% +808 /scratch/Teaching/cars/car_ims/010445.jpg Honda Odyssey Minivan 2007 Maybach Landaulet Convertible 2012 14.26% Bentley Continental Supersports Conv. Convertible 2012 14.08% Bentley Continental Flying Spur Sedan 2007 12.41% Rolls-Royce Phantom Sedan 2012 12.38% GMC Acadia SUV 2012 6.46% +809 /scratch/Teaching/cars/car_ims/005005.jpg Chevrolet Tahoe Hybrid SUV 2012 Mazda Tribute SUV 2011 80.81% Jeep Compass SUV 2012 5.59% BMW X5 SUV 2007 4.9% Jeep Liberty SUV 2012 2.15% Volvo XC90 SUV 2007 1.39% +810 /scratch/Teaching/cars/car_ims/015755.jpg Volkswagen Golf Hatchback 1991 Ford Mustang Convertible 2007 88.08% Volkswagen Golf Hatchback 1991 4.88% Mercedes-Benz 300-Class Convertible 1993 3.33% Audi 100 Sedan 1994 1.13% Audi 100 Wagon 1994 1.05% +811 /scratch/Teaching/cars/car_ims/005182.jpg Chevrolet Express Cargo Van 2007 Chevrolet Express Cargo Van 2007 75.58% GMC Savana Van 2012 24.39% Chevrolet Express Van 2007 0.02% Nissan NV Passenger Van 2012 0.0% Audi 100 Sedan 1994 0.0% +812 /scratch/Teaching/cars/car_ims/003909.jpg Buick Verano Sedan 2012 Buick Regal GS 2012 48.67% Jaguar XK XKR 2012 13.92% Buick Verano Sedan 2012 11.95% Honda Accord Coupe 2012 8.22% Mitsubishi Lancer Sedan 2012 1.97% +813 /scratch/Teaching/cars/car_ims/004818.jpg Chevrolet HHR SS 2010 Chevrolet HHR SS 2010 57.59% Cadillac CTS-V Sedan 2012 12.31% Acura TL Type-S 2008 6.11% Toyota Camry Sedan 2012 2.84% Volkswagen Beetle Hatchback 2012 2.79% +814 /scratch/Teaching/cars/car_ims/005640.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chevrolet Silverado 1500 Classic Extended Cab 2007 100.0% Ford Ranger SuperCab 2011 0.0% Chrysler Aspen SUV 2009 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% GMC Canyon Extended Cab 2012 0.0% +815 /scratch/Teaching/cars/car_ims/011143.jpg Hyundai Elantra Sedan 2007 Hyundai Genesis Sedan 2012 57.03% Chevrolet Sonic Sedan 2012 29.92% Hyundai Sonata Sedan 2012 2.24% Acura TSX Sedan 2012 1.65% Honda Accord Coupe 2012 1.2% +816 /scratch/Teaching/cars/car_ims/009085.jpg Ford Ranger SuperCab 2011 Ford Ranger SuperCab 2011 99.99% Ford F-150 Regular Cab 2012 0.0% Ford F-150 Regular Cab 2007 0.0% Chrysler Aspen SUV 2009 0.0% Dodge Dakota Club Cab 2007 0.0% +817 /scratch/Teaching/cars/car_ims/011897.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 100.0% Jeep Wrangler SUV 2012 0.0% Jeep Liberty SUV 2012 0.0% GMC Yukon Hybrid SUV 2012 0.0% Nissan NV Passenger Van 2012 0.0% +818 /scratch/Teaching/cars/car_ims/013878.jpg Nissan NV Passenger Van 2012 BMW X5 SUV 2007 94.43% BMW X3 SUV 2012 3.58% Jeep Compass SUV 2012 1.07% Volvo XC90 SUV 2007 0.34% Bentley Arnage Sedan 2009 0.28% +819 /scratch/Teaching/cars/car_ims/008951.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 100.0% Honda Odyssey Minivan 2012 0.0% Hyundai Santa Fe SUV 2012 0.0% Hyundai Veracruz SUV 2012 0.0% Toyota Camry Sedan 2012 0.0% +820 /scratch/Teaching/cars/car_ims/005235.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 40.79% Chevrolet Silverado 1500 Classic Extended Cab 2007 18.0% GMC Canyon Extended Cab 2012 16.76% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 10.99% Chevrolet Avalanche Crew Cab 2012 3.02% +821 /scratch/Teaching/cars/car_ims/009642.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 100.0% Ford Edge SUV 2012 0.0% Toyota 4Runner SUV 2012 0.0% Land Rover LR2 SUV 2012 0.0% Rolls-Royce Ghost Sedan 2012 0.0% +822 /scratch/Teaching/cars/car_ims/015583.jpg Volkswagen Golf Hatchback 2012 Chrysler PT Cruiser Convertible 2008 24.77% Maybach Landaulet Convertible 2012 15.32% Chevrolet Monte Carlo Coupe 2007 9.65% Aston Martin Virage Convertible 2012 6.95% FIAT 500 Convertible 2012 5.78% +823 /scratch/Teaching/cars/car_ims/007324.jpg Dodge Dakota Crew Cab 2010 Dodge Caliber Wagon 2007 90.15% Volvo C30 Hatchback 2012 7.04% Dodge Dakota Crew Cab 2010 1.84% Jeep Compass SUV 2012 0.35% HUMMER H3T Crew Cab 2010 0.15% +824 /scratch/Teaching/cars/car_ims/004568.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 99.16% Aston Martin Virage Convertible 2012 0.78% Chevrolet Corvette ZR1 2012 0.05% Maybach Landaulet Convertible 2012 0.01% Aston Martin V8 Vantage Coupe 2012 0.0% +825 /scratch/Teaching/cars/car_ims/009680.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 99.39% Jeep Compass SUV 2012 0.54% HUMMER H3T Crew Cab 2010 0.07% Jeep Grand Cherokee SUV 2012 0.0% Toyota 4Runner SUV 2012 0.0% +826 /scratch/Teaching/cars/car_ims/002483.jpg BMW 6 Series Convertible 2007 BMW M6 Convertible 2010 59.64% BMW M5 Sedan 2010 24.16% BMW M3 Coupe 2012 6.61% Infiniti G Coupe IPL 2012 5.15% BMW 1 Series Convertible 2012 1.15% +827 /scratch/Teaching/cars/car_ims/012401.jpg Lamborghini Aventador Coupe 2012 Bugatti Veyron 16.4 Coupe 2009 84.37% Bugatti Veyron 16.4 Convertible 2009 15.62% Ford GT Coupe 2006 0.01% Mercedes-Benz SL-Class Coupe 2009 0.0% Mitsubishi Lancer Sedan 2012 0.0% +828 /scratch/Teaching/cars/car_ims/015111.jpg Suzuki SX4 Sedan 2012 Suzuki SX4 Hatchback 2012 34.41% Nissan Juke Hatchback 2012 25.03% Buick Enclave SUV 2012 21.04% Daewoo Nubira Wagon 2002 15.23% Chevrolet Traverse SUV 2012 2.46% +829 /scratch/Teaching/cars/car_ims/006490.jpg Chrysler Crossfire Convertible 2008 Chrysler Crossfire Convertible 2008 42.43% Chevrolet Camaro Convertible 2012 32.83% Chevrolet Corvette ZR1 2012 10.19% Chevrolet Corvette Ron Fellows Edition Z06 2007 6.49% Spyker C8 Convertible 2009 4.06% +830 /scratch/Teaching/cars/car_ims/009972.jpg GMC Canyon Extended Cab 2012 Lincoln Town Car Sedan 2011 89.04% Chevrolet Silverado 1500 Extended Cab 2012 5.31% Chevrolet Silverado 2500HD Regular Cab 2012 2.97% Dodge Dakota Club Cab 2007 0.99% Ford F-150 Regular Cab 2007 0.85% +831 /scratch/Teaching/cars/car_ims/015504.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 99.35% Ford Edge SUV 2012 0.61% GMC Terrain SUV 2012 0.02% Jeep Grand Cherokee SUV 2012 0.01% Dodge Caliber Wagon 2012 0.0% +832 /scratch/Teaching/cars/car_ims/000020.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 89.17% HUMMER H2 SUT Crew Cab 2009 10.74% HUMMER H3T Crew Cab 2010 0.09% Jeep Wrangler SUV 2012 0.0% Ford F-450 Super Duty Crew Cab 2012 0.0% +833 /scratch/Teaching/cars/car_ims/013888.jpg Nissan NV Passenger Van 2012 Jeep Compass SUV 2012 33.84% AM General Hummer SUV 2000 22.3% Nissan NV Passenger Van 2012 18.55% HUMMER H2 SUT Crew Cab 2009 7.34% HUMMER H3T Crew Cab 2010 6.76% +834 /scratch/Teaching/cars/car_ims/014080.jpg Nissan 240SX Coupe 1998 Mercedes-Benz C-Class Sedan 2012 35.87% Chevrolet Corvette ZR1 2012 25.77% Mercedes-Benz SL-Class Coupe 2009 11.57% Eagle Talon Hatchback 1998 10.52% Hyundai Elantra Touring Hatchback 2012 7.95% +835 /scratch/Teaching/cars/car_ims/006105.jpg Chrysler Aspen SUV 2009 Jeep Grand Cherokee SUV 2012 71.15% Chevrolet Tahoe Hybrid SUV 2012 14.17% Chrysler Aspen SUV 2009 4.95% Dodge Durango SUV 2007 3.51% Jeep Compass SUV 2012 0.99% +836 /scratch/Teaching/cars/car_ims/000567.jpg Acura ZDX Hatchback 2012 Hyundai Veloster Hatchback 2012 35.01% Chevrolet Sonic Sedan 2012 17.65% Acura TSX Sedan 2012 16.08% Mitsubishi Lancer Sedan 2012 5.85% Hyundai Veracruz SUV 2012 4.32% +837 /scratch/Teaching/cars/car_ims/004196.jpg Cadillac SRX SUV 2012 Hyundai Veracruz SUV 2012 31.69% Chevrolet Traverse SUV 2012 23.89% Volvo XC90 SUV 2007 23.34% Dodge Durango SUV 2012 11.47% Hyundai Santa Fe SUV 2012 2.45% +838 /scratch/Teaching/cars/car_ims/009663.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 100.0% Dodge Durango SUV 2007 0.0% Jeep Compass SUV 2012 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% Ford Edge SUV 2012 0.0% +839 /scratch/Teaching/cars/car_ims/001143.jpg Audi R8 Coupe 2012 Bugatti Veyron 16.4 Coupe 2009 36.21% Hyundai Veloster Hatchback 2012 32.0% FIAT 500 Abarth 2012 15.35% Spyker C8 Coupe 2009 5.44% Spyker C8 Convertible 2009 4.65% +840 /scratch/Teaching/cars/car_ims/009447.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 99.79% Plymouth Neon Coupe 1999 0.17% Daewoo Nubira Wagon 2002 0.04% Suzuki Aerio Sedan 2007 0.0% Hyundai Elantra Touring Hatchback 2012 0.0% +841 /scratch/Teaching/cars/car_ims/015480.jpg Toyota Corolla Sedan 2012 Toyota Camry Sedan 2012 95.49% Toyota Corolla Sedan 2012 1.83% Chevrolet Sonic Sedan 2012 0.53% Suzuki Kizashi Sedan 2012 0.43% Hyundai Sonata Hybrid Sedan 2012 0.4% +842 /scratch/Teaching/cars/car_ims/010121.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 100.0% Daewoo Nubira Wagon 2002 0.0% Dodge Sprinter Cargo Van 2009 0.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Chrysler PT Cruiser Convertible 2008 0.0% +843 /scratch/Teaching/cars/car_ims/007070.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 99.71% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.16% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.08% Chevrolet Silverado 1500 Extended Cab 2012 0.04% GMC Canyon Extended Cab 2012 0.0% +844 /scratch/Teaching/cars/car_ims/004134.jpg Cadillac SRX SUV 2012 Cadillac SRX SUV 2012 98.74% GMC Acadia SUV 2012 0.87% Cadillac CTS-V Sedan 2012 0.26% Nissan Juke Hatchback 2012 0.07% Buick Enclave SUV 2012 0.04% +845 /scratch/Teaching/cars/car_ims/013374.jpg Mercedes-Benz SL-Class Coupe 2009 Audi RS 4 Convertible 2008 62.7% Bugatti Veyron 16.4 Coupe 2009 15.38% Fisker Karma Sedan 2012 4.64% Acura ZDX Hatchback 2012 2.61% Ford GT Coupe 2006 2.31% +846 /scratch/Teaching/cars/car_ims/001167.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 99.99% Bugatti Veyron 16.4 Coupe 2009 0.01% Mercedes-Benz SL-Class Coupe 2009 0.0% Bugatti Veyron 16.4 Convertible 2009 0.0% Mitsubishi Lancer Sedan 2012 0.0% +847 /scratch/Teaching/cars/car_ims/006421.jpg Chrysler 300 SRT-8 2010 Chevrolet Monte Carlo Coupe 2007 64.01% Chevrolet Impala Sedan 2007 22.73% Chevrolet Malibu Sedan 2007 12.96% Lincoln Town Car Sedan 2011 0.15% Dodge Magnum Wagon 2008 0.1% +848 /scratch/Teaching/cars/car_ims/002925.jpg BMW M6 Convertible 2010 Chevrolet Malibu Sedan 2007 98.5% Chevrolet Monte Carlo Coupe 2007 1.34% BMW 6 Series Convertible 2007 0.13% Mercedes-Benz 300-Class Convertible 1993 0.02% Lincoln Town Car Sedan 2011 0.01% +849 /scratch/Teaching/cars/car_ims/009373.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 99.98% Dodge Dakota Club Cab 2007 0.02% Ford Ranger SuperCab 2011 0.0% Ford F-150 Regular Cab 2012 0.0% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% +850 /scratch/Teaching/cars/car_ims/003176.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental GT Coupe 2007 74.15% Bentley Continental Supersports Conv. Convertible 2012 6.55% Ford GT Coupe 2006 5.89% Acura Integra Type R 2001 5.63% Bentley Continental GT Coupe 2012 4.94% +851 /scratch/Teaching/cars/car_ims/007264.jpg Dodge Journey SUV 2012 Dodge Journey SUV 2012 100.0% Chevrolet Sonic Sedan 2012 0.0% Cadillac CTS-V Sedan 2012 0.0% Toyota Corolla Sedan 2012 0.0% Chevrolet HHR SS 2010 0.0% +852 /scratch/Teaching/cars/car_ims/015908.jpg Volvo C30 Hatchback 2012 Nissan Juke Hatchback 2012 61.4% Spyker C8 Coupe 2009 19.59% Volvo C30 Hatchback 2012 10.08% Dodge Challenger SRT8 2011 3.41% Audi R8 Coupe 2012 1.9% +853 /scratch/Teaching/cars/car_ims/014023.jpg Nissan 240SX Coupe 1998 Ford Mustang Convertible 2007 64.43% Nissan 240SX Coupe 1998 24.85% Chevrolet Silverado 1500 Classic Extended Cab 2007 2.29% Jeep Grand Cherokee SUV 2012 1.61% Buick Rainier SUV 2007 1.47% +854 /scratch/Teaching/cars/car_ims/015655.jpg Volkswagen Golf Hatchback 2012 Acura ZDX Hatchback 2012 25.81% Volkswagen Golf Hatchback 2012 17.96% Plymouth Neon Coupe 1999 13.97% Acura TL Sedan 2012 12.82% Nissan 240SX Coupe 1998 9.35% +855 /scratch/Teaching/cars/car_ims/007139.jpg Dodge Sprinter Cargo Van 2009 Dodge Sprinter Cargo Van 2009 62.69% Dodge Caliber Wagon 2012 7.15% Nissan NV Passenger Van 2012 6.42% Ram C/V Cargo Van Minivan 2012 2.02% Dodge Caliber Wagon 2007 1.86% +856 /scratch/Teaching/cars/car_ims/006712.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2012 99.62% Dodge Caliber Wagon 2007 0.18% Suzuki SX4 Sedan 2012 0.11% FIAT 500 Convertible 2012 0.06% Suzuki SX4 Hatchback 2012 0.02% +857 /scratch/Teaching/cars/car_ims/006965.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 99.95% Dodge Durango SUV 2007 0.05% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% Dodge Dakota Club Cab 2007 0.0% Dodge Dakota Crew Cab 2010 0.0% +858 /scratch/Teaching/cars/car_ims/008228.jpg Ferrari FF Coupe 2012 Ferrari FF Coupe 2012 100.0% Ferrari California Convertible 2012 0.0% BMW 3 Series Sedan 2012 0.0% Ferrari 458 Italia Coupe 2012 0.0% Dodge Charger Sedan 2012 0.0% +859 /scratch/Teaching/cars/car_ims/001966.jpg Audi S4 Sedan 2007 Audi RS 4 Convertible 2008 36.11% Spyker C8 Convertible 2009 32.72% Audi S4 Sedan 2007 8.12% Aston Martin Virage Coupe 2012 7.78% Dodge Challenger SRT8 2011 6.01% +860 /scratch/Teaching/cars/car_ims/000398.jpg Acura TSX Sedan 2012 Acura TSX Sedan 2012 74.62% Acura RL Sedan 2012 15.16% Toyota Corolla Sedan 2012 4.35% Honda Accord Sedan 2012 3.45% Toyota Camry Sedan 2012 1.03% +861 /scratch/Teaching/cars/car_ims/010351.jpg HUMMER H2 SUT Crew Cab 2009 AM General Hummer SUV 2000 61.6% Jeep Wrangler SUV 2012 23.54% HUMMER H2 SUT Crew Cab 2009 14.84% HUMMER H3T Crew Cab 2010 0.02% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% +862 /scratch/Teaching/cars/car_ims/012458.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 Lamborghini Gallardo LP 570-4 Superleggera 2012 99.66% Lamborghini Diablo Coupe 2001 0.2% Hyundai Veloster Hatchback 2012 0.09% Acura Integra Type R 2001 0.04% Ford GT Coupe 2006 0.01% +863 /scratch/Teaching/cars/car_ims/011103.jpg Hyundai Elantra Sedan 2007 Honda Odyssey Minivan 2012 45.54% Hyundai Elantra Sedan 2007 19.85% Toyota Corolla Sedan 2012 11.73% Hyundai Veracruz SUV 2012 9.19% Chevrolet Malibu Sedan 2007 5.89% +864 /scratch/Teaching/cars/car_ims/004419.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Ron Fellows Edition Z06 2007 100.0% Chevrolet Corvette ZR1 2012 0.0% MINI Cooper Roadster Convertible 2012 0.0% Chevrolet Corvette Convertible 2012 0.0% Bugatti Veyron 16.4 Convertible 2009 0.0% +865 /scratch/Teaching/cars/car_ims/006967.jpg Dodge Ram Pickup 3500 Crew Cab 2010 HUMMER H3T Crew Cab 2010 64.52% HUMMER H2 SUT Crew Cab 2009 33.08% Dodge Ram Pickup 3500 Crew Cab 2010 0.83% Nissan NV Passenger Van 2012 0.48% Rolls-Royce Phantom Sedan 2012 0.34% +866 /scratch/Teaching/cars/car_ims/004018.jpg Buick Enclave SUV 2012 Suzuki SX4 Hatchback 2012 57.67% Volvo XC90 SUV 2007 24.97% Mazda Tribute SUV 2011 12.69% Buick Enclave SUV 2012 2.02% Chevrolet Traverse SUV 2012 1.07% +867 /scratch/Teaching/cars/car_ims/012576.jpg Lamborghini Diablo Coupe 2001 Rolls-Royce Phantom Drophead Coupe Convertible 2012 41.94% Mazda Tribute SUV 2011 24.89% Lamborghini Diablo Coupe 2001 9.11% Dodge Charger Sedan 2012 7.61% Rolls-Royce Ghost Sedan 2012 4.42% +868 /scratch/Teaching/cars/car_ims/013596.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 99.86% Dodge Sprinter Cargo Van 2009 0.14% Volkswagen Golf Hatchback 1991 0.0% GMC Savana Van 2012 0.0% Chevrolet Express Van 2007 0.0% +869 /scratch/Teaching/cars/car_ims/011106.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 100.0% Dodge Caliber Wagon 2012 0.0% Hyundai Sonata Sedan 2012 0.0% Honda Accord Coupe 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% +870 /scratch/Teaching/cars/car_ims/002486.jpg BMW 6 Series Convertible 2007 Aston Martin V8 Vantage Convertible 2012 63.17% BMW Z4 Convertible 2012 15.48% Bugatti Veyron 16.4 Convertible 2009 6.9% BMW M6 Convertible 2010 6.17% BMW 6 Series Convertible 2007 2.41% +871 /scratch/Teaching/cars/car_ims/011343.jpg Hyundai Sonata Sedan 2012 Acura TSX Sedan 2012 45.15% Honda Accord Sedan 2012 38.19% Toyota Camry Sedan 2012 7.65% Hyundai Sonata Sedan 2012 4.32% Acura RL Sedan 2012 1.86% +872 /scratch/Teaching/cars/car_ims/011861.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 99.91% Rolls-Royce Phantom Sedan 2012 0.06% Jeep Compass SUV 2012 0.02% Jeep Liberty SUV 2012 0.0% BMW X3 SUV 2012 0.0% +873 /scratch/Teaching/cars/car_ims/012238.jpg Jeep Compass SUV 2012 Nissan Juke Hatchback 2012 62.96% Jeep Grand Cherokee SUV 2012 13.11% BMW M6 Convertible 2010 9.83% Acura RL Sedan 2012 9.47% Jeep Compass SUV 2012 4.1% +874 /scratch/Teaching/cars/car_ims/005355.jpg Chevrolet Cobalt SS 2010 Acura Integra Type R 2001 98.63% Chevrolet Cobalt SS 2010 0.35% Ford Mustang Convertible 2007 0.25% Bentley Mulsanne Sedan 2011 0.21% Chrysler Crossfire Convertible 2008 0.17% +875 /scratch/Teaching/cars/car_ims/003970.jpg Buick Enclave SUV 2012 Chevrolet Traverse SUV 2012 83.89% Chrysler Aspen SUV 2009 5.9% Buick Enclave SUV 2012 5.07% Jeep Grand Cherokee SUV 2012 1.42% GMC Acadia SUV 2012 1.02% +876 /scratch/Teaching/cars/car_ims/003067.jpg BMW Z4 Convertible 2012 BMW Z4 Convertible 2012 94.69% Audi RS 4 Convertible 2008 5.08% Dodge Charger Sedan 2012 0.11% Acura Integra Type R 2001 0.09% Ford Mustang Convertible 2007 0.01% +877 /scratch/Teaching/cars/car_ims/009449.jpg Ford Focus Sedan 2007 Volvo C30 Hatchback 2012 38.04% Volvo 240 Sedan 1993 21.54% Audi 100 Wagon 1994 7.34% Volkswagen Golf Hatchback 1991 6.61% Ford Ranger SuperCab 2011 5.2% +878 /scratch/Teaching/cars/car_ims/004934.jpg Chevrolet Impala Sedan 2007 Chevrolet Monte Carlo Coupe 2007 94.82% Chevrolet Impala Sedan 2007 5.16% Daewoo Nubira Wagon 2002 0.01% Plymouth Neon Coupe 1999 0.01% Ford Focus Sedan 2007 0.0% +879 /scratch/Teaching/cars/car_ims/004901.jpg Chevrolet Impala Sedan 2007 Chevrolet Monte Carlo Coupe 2007 33.53% Lincoln Town Car Sedan 2011 31.24% BMW 3 Series Sedan 2012 10.16% Chevrolet Impala Sedan 2007 5.73% Eagle Talon Hatchback 1998 5.62% +880 /scratch/Teaching/cars/car_ims/001385.jpg Audi 100 Wagon 1994 Audi 100 Wagon 1994 79.77% Audi 100 Sedan 1994 18.84% Daewoo Nubira Wagon 2002 0.95% Volkswagen Golf Hatchback 1991 0.17% Audi V8 Sedan 1994 0.14% +881 /scratch/Teaching/cars/car_ims/005731.jpg Chevrolet Express Van 2007 Chevrolet Express Van 2007 99.18% GMC Savana Van 2012 0.61% Chevrolet Express Cargo Van 2007 0.21% Nissan NV Passenger Van 2012 0.0% Ford E-Series Wagon Van 2012 0.0% +882 /scratch/Teaching/cars/car_ims/014791.jpg Spyker C8 Coupe 2009 BMW M6 Convertible 2010 36.59% Lamborghini Diablo Coupe 2001 6.08% Audi RS 4 Convertible 2008 4.82% Bugatti Veyron 16.4 Convertible 2009 4.3% MINI Cooper Roadster Convertible 2012 3.85% +883 /scratch/Teaching/cars/car_ims/006018.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 56.17% Chevrolet Silverado 1500 Extended Cab 2012 42.27% Chevrolet Silverado 1500 Regular Cab 2012 1.39% Chevrolet Avalanche Crew Cab 2012 0.09% Chevrolet Silverado 2500HD Regular Cab 2012 0.04% +884 /scratch/Teaching/cars/car_ims/000789.jpg Aston Martin Virage Convertible 2012 Aston Martin Virage Convertible 2012 89.49% Spyker C8 Coupe 2009 5.2% Bentley Continental GT Coupe 2012 2.58% Aston Martin Virage Coupe 2012 0.72% Tesla Model S Sedan 2012 0.49% +885 /scratch/Teaching/cars/car_ims/001233.jpg Audi V8 Sedan 1994 Audi V8 Sedan 1994 83.83% Audi 100 Sedan 1994 16.1% Audi 100 Wagon 1994 0.06% Volkswagen Golf Hatchback 1991 0.02% Volvo 240 Sedan 1993 0.0% +886 /scratch/Teaching/cars/car_ims/014230.jpg Porsche Panamera Sedan 2012 BMW Z4 Convertible 2012 91.6% Mercedes-Benz E-Class Sedan 2012 3.97% Bentley Continental GT Coupe 2012 2.74% Acura Integra Type R 2001 0.25% Mitsubishi Lancer Sedan 2012 0.25% +887 /scratch/Teaching/cars/car_ims/007378.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 79.02% Dodge Durango SUV 2007 20.5% Dodge Dakota Club Cab 2007 0.3% Chrysler Aspen SUV 2009 0.09% Dodge Durango SUV 2012 0.08% +888 /scratch/Teaching/cars/car_ims/007154.jpg Dodge Sprinter Cargo Van 2009 Mercedes-Benz Sprinter Van 2012 70.68% Dodge Sprinter Cargo Van 2009 29.31% Ram C/V Cargo Van Minivan 2012 0.0% Audi 100 Sedan 1994 0.0% Nissan NV Passenger Van 2012 0.0% +889 /scratch/Teaching/cars/car_ims/009739.jpg GMC Savana Van 2012 GMC Savana Van 2012 99.47% Chevrolet Express Van 2007 0.32% Jeep Patriot SUV 2012 0.06% Chevrolet Tahoe Hybrid SUV 2012 0.04% Ford E-Series Wagon Van 2012 0.03% +890 /scratch/Teaching/cars/car_ims/014264.jpg Porsche Panamera Sedan 2012 BMW 3 Series Sedan 2012 87.56% Audi S5 Convertible 2012 10.28% BMW Z4 Convertible 2012 1.47% BMW 3 Series Wagon 2012 0.49% Tesla Model S Sedan 2012 0.11% +891 /scratch/Teaching/cars/car_ims/012998.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 97.71% Dodge Durango SUV 2007 1.69% Volvo XC90 SUV 2007 0.35% Jeep Patriot SUV 2012 0.18% Jeep Compass SUV 2012 0.05% +892 /scratch/Teaching/cars/car_ims/015916.jpg Volvo C30 Hatchback 2012 Volvo C30 Hatchback 2012 98.99% HUMMER H3T Crew Cab 2010 0.93% Nissan Juke Hatchback 2012 0.05% Spyker C8 Coupe 2009 0.01% HUMMER H2 SUT Crew Cab 2009 0.01% +893 /scratch/Teaching/cars/car_ims/001148.jpg Audi R8 Coupe 2012 Spyker C8 Convertible 2009 96.7% Bugatti Veyron 16.4 Coupe 2009 2.7% Audi TTS Coupe 2012 0.17% Aston Martin Virage Convertible 2012 0.11% Audi S5 Convertible 2012 0.08% +894 /scratch/Teaching/cars/car_ims/007607.jpg Dodge Challenger SRT8 2011 Dodge Charger SRT-8 2009 99.9% Dodge Challenger SRT8 2011 0.09% Chrysler 300 SRT-8 2010 0.02% Chevrolet TrailBlazer SS 2009 0.0% Rolls-Royce Phantom Sedan 2012 0.0% +895 /scratch/Teaching/cars/car_ims/009813.jpg GMC Yukon Hybrid SUV 2012 GMC Yukon Hybrid SUV 2012 100.0% Cadillac Escalade EXT Crew Cab 2007 0.0% GMC Terrain SUV 2012 0.0% Chevrolet Tahoe Hybrid SUV 2012 0.0% Ford F-150 Regular Cab 2007 0.0% +896 /scratch/Teaching/cars/car_ims/004076.jpg Cadillac CTS-V Sedan 2012 Cadillac CTS-V Sedan 2012 95.25% Mercedes-Benz E-Class Sedan 2012 1.79% Infiniti G Coupe IPL 2012 0.98% Audi S4 Sedan 2007 0.81% Mercedes-Benz C-Class Sedan 2012 0.34% +897 /scratch/Teaching/cars/car_ims/003788.jpg Buick Regal GS 2012 Chevrolet Sonic Sedan 2012 73.75% Buick Regal GS 2012 7.29% Buick Verano Sedan 2012 4.74% Dodge Charger SRT-8 2009 3.72% GMC Terrain SUV 2012 3.64% +898 /scratch/Teaching/cars/car_ims/014521.jpg Rolls-Royce Phantom Sedan 2012 Dodge Charger SRT-8 2009 57.65% BMW M5 Sedan 2010 6.76% Rolls-Royce Phantom Sedan 2012 5.89% Maybach Landaulet Convertible 2012 3.79% Dodge Challenger SRT8 2011 3.02% +899 /scratch/Teaching/cars/car_ims/009619.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 100.0% Scion xD Hatchback 2012 0.0% Hyundai Accent Sedan 2012 0.0% Toyota Corolla Sedan 2012 0.0% Hyundai Tucson SUV 2012 0.0% +900 /scratch/Teaching/cars/car_ims/009020.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 100.0% Hyundai Santa Fe SUV 2012 0.0% Land Rover LR2 SUV 2012 0.0% Honda Odyssey Minivan 2012 0.0% Toyota 4Runner SUV 2012 0.0% +901 /scratch/Teaching/cars/car_ims/005526.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Dodge Dakota Crew Cab 2010 39.75% Dodge Dakota Club Cab 2007 28.25% Isuzu Ascender SUV 2008 11.45% Dodge Ram Pickup 3500 Quad Cab 2009 6.75% Dodge Ram Pickup 3500 Crew Cab 2010 4.84% +902 /scratch/Teaching/cars/car_ims/008575.jpg Fisker Karma Sedan 2012 Jaguar XK XKR 2012 23.88% Spyker C8 Convertible 2009 18.31% Spyker C8 Coupe 2009 12.24% Acura ZDX Hatchback 2012 7.72% Nissan Juke Hatchback 2012 6.6% +903 /scratch/Teaching/cars/car_ims/007366.jpg Dodge Dakota Crew Cab 2010 Chevrolet Silverado 1500 Extended Cab 2012 84.96% Dodge Dakota Club Cab 2007 10.81% Dodge Ram Pickup 3500 Quad Cab 2009 1.86% GMC Canyon Extended Cab 2012 0.63% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.59% +904 /scratch/Teaching/cars/car_ims/006213.jpg Chrysler Sebring Convertible 2010 Acura RL Sedan 2012 28.06% Honda Accord Sedan 2012 24.0% Acura TSX Sedan 2012 19.56% Toyota Corolla Sedan 2012 7.62% Hyundai Elantra Sedan 2007 5.3% +905 /scratch/Teaching/cars/car_ims/010402.jpg Honda Odyssey Minivan 2012 Honda Odyssey Minivan 2012 63.44% Acura RL Sedan 2012 19.59% Hyundai Veracruz SUV 2012 6.98% Honda Odyssey Minivan 2007 5.97% Honda Accord Sedan 2012 1.83% +906 /scratch/Teaching/cars/car_ims/015604.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 97.47% Ford Fiesta Sedan 2012 2.05% Hyundai Tucson SUV 2012 0.33% Toyota Corolla Sedan 2012 0.07% Hyundai Elantra Touring Hatchback 2012 0.05% +907 /scratch/Teaching/cars/car_ims/007699.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 93.17% Dodge Dakota Crew Cab 2010 4.09% Dodge Durango SUV 2007 2.6% Dodge Caliber Wagon 2012 0.14% Jeep Grand Cherokee SUV 2012 0.0% +908 /scratch/Teaching/cars/car_ims/009072.jpg Ford Ranger SuperCab 2011 Ford F-150 Regular Cab 2012 89.34% Dodge Dakota Club Cab 2007 5.7% GMC Canyon Extended Cab 2012 2.47% Ford F-150 Regular Cab 2007 1.78% Ford Ranger SuperCab 2011 0.25% +909 /scratch/Teaching/cars/car_ims/008015.jpg Eagle Talon Hatchback 1998 Mitsubishi Lancer Sedan 2012 44.54% Ford Fiesta Sedan 2012 33.5% Suzuki Aerio Sedan 2007 7.86% Eagle Talon Hatchback 1998 5.56% Scion xD Hatchback 2012 3.81% +910 /scratch/Teaching/cars/car_ims/009026.jpg Ford Ranger SuperCab 2011 Mazda Tribute SUV 2011 98.17% Volvo XC90 SUV 2007 0.71% Ford F-150 Regular Cab 2007 0.42% Ford F-150 Regular Cab 2012 0.28% Ford Ranger SuperCab 2011 0.14% +911 /scratch/Teaching/cars/car_ims/004421.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette ZR1 2012 98.51% Chevrolet Corvette Convertible 2012 0.91% Porsche Panamera Sedan 2012 0.58% Jaguar XK XKR 2012 0.01% Fisker Karma Sedan 2012 0.0% +912 /scratch/Teaching/cars/car_ims/008106.jpg FIAT 500 Abarth 2012 Spyker C8 Convertible 2009 95.16% FIAT 500 Abarth 2012 3.29% Bugatti Veyron 16.4 Coupe 2009 1.54% Audi TTS Coupe 2012 0.0% Lamborghini Aventador Coupe 2012 0.0% +913 /scratch/Teaching/cars/car_ims/003418.jpg Bentley Continental GT Coupe 2007 Bentley Continental Flying Spur Sedan 2007 90.43% Bentley Continental GT Coupe 2007 8.83% Chevrolet Malibu Hybrid Sedan 2010 0.33% Bentley Mulsanne Sedan 2011 0.31% BMW 3 Series Wagon 2012 0.02% +914 /scratch/Teaching/cars/car_ims/005333.jpg Chevrolet Cobalt SS 2010 Chevrolet Cobalt SS 2010 99.99% Dodge Charger SRT-8 2009 0.01% Chevrolet Malibu Hybrid Sedan 2010 0.0% Chevrolet Monte Carlo Coupe 2007 0.0% Aston Martin V8 Vantage Coupe 2012 0.0% +915 /scratch/Teaching/cars/car_ims/000917.jpg Audi RS 4 Convertible 2008 Chevrolet Corvette Convertible 2012 64.64% Audi RS 4 Convertible 2008 22.48% Dodge Charger Sedan 2012 9.94% Acura Integra Type R 2001 2.31% Audi S4 Sedan 2012 0.32% +916 /scratch/Teaching/cars/car_ims/004408.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette ZR1 2012 69.78% Porsche Panamera Sedan 2012 10.58% Fisker Karma Sedan 2012 9.25% Chevrolet Corvette Convertible 2012 7.24% Nissan Leaf Hatchback 2012 0.97% +917 /scratch/Teaching/cars/car_ims/012045.jpg Jeep Liberty SUV 2012 Dodge Durango SUV 2007 54.01% Jeep Liberty SUV 2012 15.4% Ford E-Series Wagon Van 2012 7.39% Volvo XC90 SUV 2007 6.75% Ford Expedition EL SUV 2009 3.75% +918 /scratch/Teaching/cars/car_ims/009074.jpg Ford Ranger SuperCab 2011 Ford Ranger SuperCab 2011 100.0% Isuzu Ascender SUV 2008 0.0% Ford F-150 Regular Cab 2007 0.0% Audi 100 Sedan 1994 0.0% Audi 100 Wagon 1994 0.0% +919 /scratch/Teaching/cars/car_ims/006203.jpg Chrysler Sebring Convertible 2010 Chrysler Sebring Convertible 2010 85.24% Chrysler Crossfire Convertible 2008 10.51% Chevrolet Cobalt SS 2010 3.21% BMW 6 Series Convertible 2007 0.46% Chevrolet Malibu Hybrid Sedan 2010 0.38% +920 /scratch/Teaching/cars/car_ims/011446.jpg Hyundai Elantra Touring Hatchback 2012 Acura Integra Type R 2001 99.47% Hyundai Elantra Touring Hatchback 2012 0.19% Chevrolet Sonic Sedan 2012 0.08% Nissan 240SX Coupe 1998 0.07% Eagle Talon Hatchback 1998 0.04% +921 /scratch/Teaching/cars/car_ims/009880.jpg GMC Acadia SUV 2012 Hyundai Veracruz SUV 2012 32.57% Jeep Grand Cherokee SUV 2012 24.2% Buick Enclave SUV 2012 13.29% Dodge Durango SUV 2007 10.15% Chevrolet Traverse SUV 2012 8.19% +922 /scratch/Teaching/cars/car_ims/013039.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 100.0% Land Rover LR2 SUV 2012 0.0% Hyundai Veracruz SUV 2012 0.0% Suzuki SX4 Hatchback 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% +923 /scratch/Teaching/cars/car_ims/008658.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 43.76% Ford Expedition EL SUV 2009 42.35% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 8.08% Ford F-150 Regular Cab 2012 4.28% Ford Ranger SuperCab 2011 0.53% +924 /scratch/Teaching/cars/car_ims/009235.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 99.98% Ford F-150 Regular Cab 2007 0.02% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% GMC Canyon Extended Cab 2012 0.0% Toyota 4Runner SUV 2012 0.0% +925 /scratch/Teaching/cars/car_ims/007739.jpg Dodge Durango SUV 2007 Dodge Dakota Club Cab 2007 91.65% Dodge Durango SUV 2007 4.05% Dodge Dakota Crew Cab 2010 3.76% Rolls-Royce Ghost Sedan 2012 0.4% Dodge Magnum Wagon 2008 0.08% +926 /scratch/Teaching/cars/car_ims/002147.jpg BMW 1 Series Convertible 2012 BMW 3 Series Sedan 2012 27.14% Ford Mustang Convertible 2007 21.59% BMW X6 SUV 2012 16.11% Chevrolet Sonic Sedan 2012 8.01% Dodge Charger Sedan 2012 7.81% +927 /scratch/Teaching/cars/car_ims/016030.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 99.99% Dodge Durango SUV 2007 0.0% Jeep Patriot SUV 2012 0.0% GMC Acadia SUV 2012 0.0% Buick Enclave SUV 2012 0.0% +928 /scratch/Teaching/cars/car_ims/003296.jpg Bentley Mulsanne Sedan 2011 Bentley Mulsanne Sedan 2011 99.59% Bentley Continental GT Coupe 2012 0.22% Bentley Continental Flying Spur Sedan 2007 0.15% Cadillac CTS-V Sedan 2012 0.03% Bentley Continental GT Coupe 2007 0.01% +929 /scratch/Teaching/cars/car_ims/010208.jpg HUMMER H3T Crew Cab 2010 HUMMER H3T Crew Cab 2010 91.37% Dodge Ram Pickup 3500 Quad Cab 2009 7.19% Dodge Ram Pickup 3500 Crew Cab 2010 0.82% Dodge Dakota Crew Cab 2010 0.41% Dodge Dakota Club Cab 2007 0.1% +930 /scratch/Teaching/cars/car_ims/005686.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 98.57% Chevrolet Express Cargo Van 2007 0.73% Chevrolet Express Van 2007 0.7% Volkswagen Golf Hatchback 1991 0.0% Buick Rainier SUV 2007 0.0% +931 /scratch/Teaching/cars/car_ims/001115.jpg Audi TTS Coupe 2012 Audi TTS Coupe 2012 91.84% Mitsubishi Lancer Sedan 2012 6.23% BMW 6 Series Convertible 2007 0.79% Audi S4 Sedan 2012 0.51% Jaguar XK XKR 2012 0.13% +932 /scratch/Teaching/cars/car_ims/012283.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 47.7% Dodge Caliber Wagon 2012 42.04% BMW X3 SUV 2012 3.56% Jeep Grand Cherokee SUV 2012 3.35% Dodge Journey SUV 2012 1.01% +933 /scratch/Teaching/cars/car_ims/012179.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 99.95% Jeep Compass SUV 2012 0.05% BMW X3 SUV 2012 0.0% Dodge Dakota Crew Cab 2010 0.0% BMW X6 SUV 2012 0.0% +934 /scratch/Teaching/cars/car_ims/012403.jpg Lamborghini Aventador Coupe 2012 BMW M3 Coupe 2012 40.38% Audi TT RS Coupe 2012 36.09% Chevrolet Camaro Convertible 2012 22.07% Ford GT Coupe 2006 0.5% Lamborghini Aventador Coupe 2012 0.32% +935 /scratch/Teaching/cars/car_ims/003556.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 42.97% Bentley Mulsanne Sedan 2011 18.19% Mercedes-Benz E-Class Sedan 2012 5.4% Infiniti QX56 SUV 2011 5.01% Honda Accord Sedan 2012 3.79% +936 /scratch/Teaching/cars/car_ims/000637.jpg Aston Martin V8 Vantage Convertible 2012 Dodge Charger SRT-8 2009 35.01% Ford F-450 Super Duty Crew Cab 2012 10.93% Audi S5 Convertible 2012 7.5% Ferrari California Convertible 2012 5.88% Chrysler 300 SRT-8 2010 5.12% +937 /scratch/Teaching/cars/car_ims/008797.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 57.23% Chrysler Town and Country Minivan 2012 32.64% Ram C/V Cargo Van Minivan 2012 10.01% Chevrolet Malibu Sedan 2007 0.12% Chevrolet Impala Sedan 2007 0.0% +938 /scratch/Teaching/cars/car_ims/007510.jpg Dodge Magnum Wagon 2008 Chevrolet Impala Sedan 2007 60.63% Dodge Magnum Wagon 2008 28.49% BMW 3 Series Wagon 2012 4.94% Chevrolet Malibu Sedan 2007 3.31% Lincoln Town Car Sedan 2011 0.57% +939 /scratch/Teaching/cars/car_ims/011048.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 99.99% Buick Regal GS 2012 0.0% Scion xD Hatchback 2012 0.0% Hyundai Azera Sedan 2012 0.0% Hyundai Tucson SUV 2012 0.0% +940 /scratch/Teaching/cars/car_ims/000228.jpg Acura TL Sedan 2012 Dodge Sprinter Cargo Van 2009 60.54% Audi 100 Wagon 1994 12.3% Acura ZDX Hatchback 2012 8.13% Nissan Leaf Hatchback 2012 4.46% Chevrolet Corvette ZR1 2012 1.69% +941 /scratch/Teaching/cars/car_ims/007213.jpg Dodge Sprinter Cargo Van 2009 Mercedes-Benz Sprinter Van 2012 56.63% Dodge Sprinter Cargo Van 2009 25.97% Geo Metro Convertible 1993 2.08% Ram C/V Cargo Van Minivan 2012 1.92% Mercedes-Benz 300-Class Convertible 1993 1.22% +942 /scratch/Teaching/cars/car_ims/006041.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 62.12% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 22.13% Chevrolet Silverado 1500 Extended Cab 2012 10.68% Chevrolet Silverado 2500HD Regular Cab 2012 5.04% HUMMER H3T Crew Cab 2010 0.02% +943 /scratch/Teaching/cars/car_ims/010693.jpg Hyundai Veloster Hatchback 2012 BMW 3 Series Sedan 2012 94.73% Ferrari FF Coupe 2012 1.82% Ferrari 458 Italia Convertible 2012 1.27% Ford GT Coupe 2006 0.45% Daewoo Nubira Wagon 2002 0.33% +944 /scratch/Teaching/cars/car_ims/013371.jpg Mercedes-Benz SL-Class Coupe 2009 Mercedes-Benz SL-Class Coupe 2009 99.93% Audi R8 Coupe 2012 0.03% Bugatti Veyron 16.4 Convertible 2009 0.02% Bugatti Veyron 16.4 Coupe 2009 0.01% Lamborghini Reventon Coupe 2008 0.0% +945 /scratch/Teaching/cars/car_ims/002175.jpg BMW 1 Series Convertible 2012 BMW 1 Series Coupe 2012 68.04% BMW 1 Series Convertible 2012 28.89% Chevrolet Sonic Sedan 2012 1.27% Dodge Caliber Wagon 2012 0.37% BMW 3 Series Wagon 2012 0.31% +946 /scratch/Teaching/cars/car_ims/013290.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 87.69% Hyundai Sonata Sedan 2012 9.54% Hyundai Genesis Sedan 2012 2.01% Hyundai Azera Sedan 2012 0.76% Toyota Corolla Sedan 2012 0.0% +947 /scratch/Teaching/cars/car_ims/003560.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental GT Coupe 2007 92.12% Bentley Continental Flying Spur Sedan 2007 7.56% Bentley Continental GT Coupe 2012 0.26% Bentley Mulsanne Sedan 2011 0.06% Volkswagen Beetle Hatchback 2012 0.0% +948 /scratch/Teaching/cars/car_ims/010817.jpg Hyundai Santa Fe SUV 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 98.55% Ford Edge SUV 2012 1.03% Chevrolet Silverado 1500 Regular Cab 2012 0.33% Chevrolet TrailBlazer SS 2009 0.05% Chevrolet Avalanche Crew Cab 2012 0.01% +949 /scratch/Teaching/cars/car_ims/004769.jpg Chevrolet Camaro Convertible 2012 McLaren MP4-12C Coupe 2012 23.15% Jaguar XK XKR 2012 19.88% Aston Martin V8 Vantage Coupe 2012 8.17% BMW M6 Convertible 2010 6.45% Maybach Landaulet Convertible 2012 5.69% +950 /scratch/Teaching/cars/car_ims/014713.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 100.0% Chevrolet Corvette ZR1 2012 0.0% FIAT 500 Abarth 2012 0.0% Spyker C8 Coupe 2009 0.0% Ford GT Coupe 2006 0.0% +951 /scratch/Teaching/cars/car_ims/001087.jpg Audi TTS Coupe 2012 Audi TTS Coupe 2012 78.23% Audi TT Hatchback 2011 10.66% Audi S5 Coupe 2012 10.39% Audi A5 Coupe 2012 0.48% Audi R8 Coupe 2012 0.15% +952 /scratch/Teaching/cars/car_ims/008190.jpg Ferrari FF Coupe 2012 Ferrari 458 Italia Coupe 2012 57.06% Ferrari FF Coupe 2012 23.16% Ferrari 458 Italia Convertible 2012 8.53% Chevrolet Corvette Ron Fellows Edition Z06 2007 4.55% Spyker C8 Convertible 2009 1.87% +953 /scratch/Teaching/cars/car_ims/002508.jpg BMW 6 Series Convertible 2007 Audi S4 Sedan 2007 38.97% BMW M5 Sedan 2010 28.57% BMW M6 Convertible 2010 12.32% BMW 6 Series Convertible 2007 8.04% Bentley Continental GT Coupe 2007 5.7% +954 /scratch/Teaching/cars/car_ims/006276.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 51.66% BMW 3 Series Wagon 2012 23.87% Dodge Magnum Wagon 2008 8.67% Chevrolet Impala Sedan 2007 8.58% Daewoo Nubira Wagon 2002 1.77% +955 /scratch/Teaching/cars/car_ims/008633.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 100.0% Dodge Ram Pickup 3500 Crew Cab 2010 0.0% Ford F-150 Regular Cab 2012 0.0% Ford E-Series Wagon Van 2012 0.0% Ford Expedition EL SUV 2009 0.0% +956 /scratch/Teaching/cars/car_ims/009557.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 92.67% Nissan Leaf Hatchback 2012 6.33% Scion xD Hatchback 2012 0.69% Suzuki SX4 Hatchback 2012 0.27% Hyundai Accent Sedan 2012 0.02% +957 /scratch/Teaching/cars/car_ims/006446.jpg Chrysler Crossfire Convertible 2008 Audi S5 Convertible 2012 91.51% BMW M6 Convertible 2010 4.33% Audi RS 4 Convertible 2008 2.32% BMW 1 Series Convertible 2012 1.54% Spyker C8 Convertible 2009 0.25% +958 /scratch/Teaching/cars/car_ims/010714.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 94.39% Chevrolet Cobalt SS 2010 3.47% Lamborghini Diablo Coupe 2001 1.18% Audi RS 4 Convertible 2008 0.43% Audi S4 Sedan 2007 0.28% +959 /scratch/Teaching/cars/car_ims/013880.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 100.0% Ford F-150 Regular Cab 2007 0.0% Jeep Patriot SUV 2012 0.0% Ford F-150 Regular Cab 2012 0.0% Volvo XC90 SUV 2007 0.0% +960 /scratch/Teaching/cars/car_ims/016170.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 99.95% FIAT 500 Convertible 2012 0.05% Suzuki SX4 Hatchback 2012 0.0% Nissan Leaf Hatchback 2012 0.0% Scion xD Hatchback 2012 0.0% +961 /scratch/Teaching/cars/car_ims/004672.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 99.95% Toyota 4Runner SUV 2012 0.03% Hyundai Veracruz SUV 2012 0.02% Chevrolet Malibu Sedan 2007 0.0% Hyundai Santa Fe SUV 2012 0.0% +962 /scratch/Teaching/cars/car_ims/001197.jpg Audi R8 Coupe 2012 Lamborghini Reventon Coupe 2008 45.19% Spyker C8 Convertible 2009 15.08% Lamborghini Aventador Coupe 2012 8.69% Spyker C8 Coupe 2009 4.74% Cadillac CTS-V Sedan 2012 3.83% +963 /scratch/Teaching/cars/car_ims/012142.jpg Jeep Grand Cherokee SUV 2012 Cadillac SRX SUV 2012 29.38% Cadillac Escalade EXT Crew Cab 2007 12.99% Hyundai Veracruz SUV 2012 8.66% Chevrolet Traverse SUV 2012 3.8% Buick Verano Sedan 2012 3.4% +964 /scratch/Teaching/cars/car_ims/001506.jpg Audi TT Hatchback 2011 Audi S4 Sedan 2012 47.14% Audi A5 Coupe 2012 41.81% Audi TT RS Coupe 2012 2.45% Audi S5 Coupe 2012 2.21% Audi TT Hatchback 2011 1.8% +965 /scratch/Teaching/cars/car_ims/007421.jpg Dodge Dakota Club Cab 2007 Dodge Dakota Crew Cab 2010 99.98% Dodge Dakota Club Cab 2007 0.02% Dodge Durango SUV 2007 0.0% Chrysler Aspen SUV 2009 0.0% Dodge Magnum Wagon 2008 0.0% +966 /scratch/Teaching/cars/car_ims/012202.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 96.91% Jeep Compass SUV 2012 3.09% BMW X3 SUV 2012 0.0% Jeep Liberty SUV 2012 0.0% Dodge Dakota Crew Cab 2010 0.0% +967 /scratch/Teaching/cars/car_ims/002656.jpg BMW X6 SUV 2012 Dodge Journey SUV 2012 73.51% Nissan Juke Hatchback 2012 18.16% Suzuki SX4 Hatchback 2012 3.48% Chevrolet Traverse SUV 2012 3.06% Jeep Grand Cherokee SUV 2012 1.62% +968 /scratch/Teaching/cars/car_ims/013926.jpg Nissan Juke Hatchback 2012 Nissan Juke Hatchback 2012 90.03% Hyundai Tucson SUV 2012 6.43% Ford Fiesta Sedan 2012 3.3% Hyundai Veracruz SUV 2012 0.13% Suzuki SX4 Hatchback 2012 0.04% +969 /scratch/Teaching/cars/car_ims/013382.jpg Mercedes-Benz SL-Class Coupe 2009 Chevrolet Corvette ZR1 2012 91.37% Mercedes-Benz SL-Class Coupe 2009 7.86% Aston Martin Virage Convertible 2012 0.36% Porsche Panamera Sedan 2012 0.2% Spyker C8 Convertible 2009 0.07% +970 /scratch/Teaching/cars/car_ims/003445.jpg Bentley Continental GT Coupe 2007 Bentley Continental GT Coupe 2007 89.05% Bentley Continental GT Coupe 2012 10.36% Suzuki Kizashi Sedan 2012 0.55% Bentley Continental Flying Spur Sedan 2007 0.02% Buick Verano Sedan 2012 0.01% +971 /scratch/Teaching/cars/car_ims/003412.jpg Bentley Continental GT Coupe 2007 Bentley Continental GT Coupe 2007 99.76% Bentley Continental Flying Spur Sedan 2007 0.19% Cadillac CTS-V Sedan 2012 0.05% Bentley Continental GT Coupe 2012 0.0% Bentley Mulsanne Sedan 2011 0.0% +972 /scratch/Teaching/cars/car_ims/009981.jpg GMC Canyon Extended Cab 2012 GMC Canyon Extended Cab 2012 93.8% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 3.46% Ford F-150 Regular Cab 2012 1.64% Chevrolet Silverado 2500HD Regular Cab 2012 0.93% Chevrolet Silverado 1500 Extended Cab 2012 0.12% +973 /scratch/Teaching/cars/car_ims/000490.jpg Acura Integra Type R 2001 Acura Integra Type R 2001 33.26% Ford Mustang Convertible 2007 25.84% Audi S5 Convertible 2012 11.98% Mercedes-Benz 300-Class Convertible 1993 10.45% Bentley Continental Supersports Conv. Convertible 2012 5.45% +974 /scratch/Teaching/cars/car_ims/004062.jpg Cadillac CTS-V Sedan 2012 Cadillac CTS-V Sedan 2012 100.0% Cadillac SRX SUV 2012 0.0% GMC Acadia SUV 2012 0.0% Dodge Journey SUV 2012 0.0% Chrysler Sebring Convertible 2010 0.0% +975 /scratch/Teaching/cars/car_ims/007422.jpg Dodge Dakota Club Cab 2007 Dodge Dakota Club Cab 2007 99.81% HUMMER H3T Crew Cab 2010 0.08% Dodge Dakota Crew Cab 2010 0.08% Dodge Ram Pickup 3500 Quad Cab 2009 0.03% Isuzu Ascender SUV 2008 0.0% +976 /scratch/Teaching/cars/car_ims/002178.jpg BMW 1 Series Convertible 2012 Chrysler PT Cruiser Convertible 2008 67.44% Ford Mustang Convertible 2007 23.03% Chevrolet Camaro Convertible 2012 7.43% Audi S5 Convertible 2012 0.79% BMW 1 Series Convertible 2012 0.68% +977 /scratch/Teaching/cars/car_ims/004266.jpg Cadillac Escalade EXT Crew Cab 2007 Dodge Dakota Crew Cab 2010 60.91% Cadillac Escalade EXT Crew Cab 2007 33.15% Isuzu Ascender SUV 2008 3.63% Chevrolet Tahoe Hybrid SUV 2012 1.92% Dodge Dakota Club Cab 2007 0.34% +978 /scratch/Teaching/cars/car_ims/015188.jpg Tesla Model S Sedan 2012 Aston Martin Virage Convertible 2012 30.39% Aston Martin V8 Vantage Convertible 2012 20.09% BMW M6 Convertible 2010 17.1% Chevrolet Corvette ZR1 2012 5.8% Fisker Karma Sedan 2012 3.94% +979 /scratch/Teaching/cars/car_ims/002002.jpg Audi TT RS Coupe 2012 Audi TT RS Coupe 2012 99.87% Audi TT Hatchback 2011 0.08% Audi TTS Coupe 2012 0.04% Mitsubishi Lancer Sedan 2012 0.01% BMW M3 Coupe 2012 0.01% +980 /scratch/Teaching/cars/car_ims/008840.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 98.55% Dodge Caravan Minivan 1997 1.08% Buick Rainier SUV 2007 0.19% Honda Odyssey Minivan 2007 0.06% Chrysler Aspen SUV 2009 0.03% +981 /scratch/Teaching/cars/car_ims/004274.jpg Cadillac Escalade EXT Crew Cab 2007 Chevrolet Tahoe Hybrid SUV 2012 94.98% Cadillac Escalade EXT Crew Cab 2007 4.23% GMC Yukon Hybrid SUV 2012 0.77% Chevrolet Avalanche Crew Cab 2012 0.01% Dodge Magnum Wagon 2008 0.0% +982 /scratch/Teaching/cars/car_ims/008583.jpg Fisker Karma Sedan 2012 Ferrari FF Coupe 2012 37.04% Jaguar XK XKR 2012 21.81% BMW 3 Series Sedan 2012 13.3% Tesla Model S Sedan 2012 12.95% Hyundai Sonata Sedan 2012 5.11% +983 /scratch/Teaching/cars/car_ims/012221.jpg Jeep Compass SUV 2012 Dodge Durango SUV 2007 75.28% Dodge Durango SUV 2012 7.72% Jeep Liberty SUV 2012 6.37% Jeep Grand Cherokee SUV 2012 2.8% Jeep Compass SUV 2012 2.52% +984 /scratch/Teaching/cars/car_ims/015598.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 39.82% Suzuki SX4 Hatchback 2012 24.66% Hyundai Elantra Touring Hatchback 2012 10.64% Ford Focus Sedan 2007 9.47% Daewoo Nubira Wagon 2002 2.23% +985 /scratch/Teaching/cars/car_ims/002822.jpg BMW M5 Sedan 2010 BMW M5 Sedan 2010 99.14% BMW M6 Convertible 2010 0.86% BMW 6 Series Convertible 2007 0.0% BMW M3 Coupe 2012 0.0% BMW Z4 Convertible 2012 0.0% +986 /scratch/Teaching/cars/car_ims/006494.jpg Chrysler Crossfire Convertible 2008 Jeep Compass SUV 2012 35.86% Dodge Caliber Wagon 2012 17.51% Eagle Talon Hatchback 1998 14.96% Dodge Magnum Wagon 2008 9.98% Daewoo Nubira Wagon 2002 5.63% +987 /scratch/Teaching/cars/car_ims/014565.jpg Rolls-Royce Phantom Sedan 2012 Rolls-Royce Phantom Sedan 2012 99.73% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.2% Rolls-Royce Ghost Sedan 2012 0.07% Bentley Mulsanne Sedan 2011 0.0% Volvo 240 Sedan 1993 0.0% +988 /scratch/Teaching/cars/car_ims/002923.jpg BMW M6 Convertible 2010 BMW 6 Series Convertible 2007 56.11% BMW M6 Convertible 2010 39.14% Dodge Charger Sedan 2012 1.13% Audi S5 Convertible 2012 0.94% BMW Z4 Convertible 2012 0.92% +989 /scratch/Teaching/cars/car_ims/003244.jpg Bentley Arnage Sedan 2009 Bentley Arnage Sedan 2009 100.0% Rolls-Royce Phantom Sedan 2012 0.0% Cadillac CTS-V Sedan 2012 0.0% Volkswagen Golf Hatchback 1991 0.0% Bentley Continental Flying Spur Sedan 2007 0.0% +990 /scratch/Teaching/cars/car_ims/006647.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 99.19% Plymouth Neon Coupe 1999 0.56% Audi 100 Wagon 1994 0.07% Maybach Landaulet Convertible 2012 0.06% Acura Integra Type R 2001 0.04% +991 /scratch/Teaching/cars/car_ims/001498.jpg Audi TT Hatchback 2011 Audi TTS Coupe 2012 53.16% Audi TT Hatchback 2011 43.56% Audi S4 Sedan 2012 1.71% Audi S5 Convertible 2012 1.12% Audi S5 Coupe 2012 0.35% +992 /scratch/Teaching/cars/car_ims/000974.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 99.97% Audi S4 Sedan 2012 0.02% Audi S5 Coupe 2012 0.01% Audi S5 Convertible 2012 0.0% Audi S4 Sedan 2007 0.0% +993 /scratch/Teaching/cars/car_ims/009660.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 100.0% Chevrolet Tahoe Hybrid SUV 2012 0.0% Land Rover LR2 SUV 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% Chevrolet Silverado 1500 Regular Cab 2012 0.0% +994 /scratch/Teaching/cars/car_ims/010604.jpg Honda Accord Sedan 2012 Honda Accord Sedan 2012 99.33% Acura RL Sedan 2012 0.48% Honda Accord Coupe 2012 0.06% Audi A5 Coupe 2012 0.04% Mitsubishi Lancer Sedan 2012 0.02% +995 /scratch/Teaching/cars/car_ims/007023.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 99.39% Ford F-450 Super Duty Crew Cab 2012 0.58% Dodge Ram Pickup 3500 Quad Cab 2009 0.02% Ford F-150 Regular Cab 2012 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% +996 /scratch/Teaching/cars/car_ims/014533.jpg Rolls-Royce Phantom Sedan 2012 Rolls-Royce Phantom Sedan 2012 84.19% Rolls-Royce Ghost Sedan 2012 7.12% Rolls-Royce Phantom Drophead Coupe Convertible 2012 2.62% Volvo 240 Sedan 1993 1.44% Jeep Patriot SUV 2012 1.28% +997 /scratch/Teaching/cars/car_ims/016011.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 100.0% Volvo XC90 SUV 2007 0.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Buick Rainier SUV 2007 0.0% Audi 100 Wagon 1994 0.0% +998 /scratch/Teaching/cars/car_ims/007080.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 99.96% GMC Canyon Extended Cab 2012 0.04% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.0% Dodge Dakota Club Cab 2007 0.0% Dodge Dakota Crew Cab 2010 0.0% +999 /scratch/Teaching/cars/car_ims/011700.jpg Isuzu Ascender SUV 2008 Cadillac Escalade EXT Crew Cab 2007 72.92% Land Rover LR2 SUV 2012 7.19% Ford Ranger SuperCab 2011 5.25% Ford Expedition EL SUV 2009 4.59% Cadillac SRX SUV 2012 3.04% +1000 /scratch/Teaching/cars/car_ims/005453.jpg Chevrolet TrailBlazer SS 2009 Chevrolet TrailBlazer SS 2009 100.0% Land Rover Range Rover SUV 2012 0.0% Chevrolet Tahoe Hybrid SUV 2012 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% Buick Rainier SUV 2007 0.0% +1001 /scratch/Teaching/cars/car_ims/004598.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 54.0% Aston Martin V8 Vantage Convertible 2012 36.66% Aston Martin Virage Convertible 2012 4.38% Spyker C8 Coupe 2009 1.21% Dodge Challenger SRT8 2011 0.63% +1002 /scratch/Teaching/cars/car_ims/008155.jpg FIAT 500 Convertible 2012 FIAT 500 Convertible 2012 99.51% smart fortwo Convertible 2012 0.48% Chrysler PT Cruiser Convertible 2008 0.01% Suzuki SX4 Sedan 2012 0.0% Scion xD Hatchback 2012 0.0% +1003 /scratch/Teaching/cars/car_ims/012847.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 100.0% Chevrolet Monte Carlo Coupe 2007 0.0% Dodge Caravan Minivan 1997 0.0% Chevrolet Impala Sedan 2007 0.0% Volvo 240 Sedan 1993 0.0% +1004 /scratch/Teaching/cars/car_ims/012355.jpg Lamborghini Reventon Coupe 2008 Lamborghini Aventador Coupe 2012 96.94% Lamborghini Reventon Coupe 2008 3.02% McLaren MP4-12C Coupe 2012 0.03% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.0% Tesla Model S Sedan 2012 0.0% +1005 /scratch/Teaching/cars/car_ims/000141.jpg Acura RL Sedan 2012 Acura TSX Sedan 2012 99.97% Acura TL Sedan 2012 0.02% Honda Accord Coupe 2012 0.01% Toyota Camry Sedan 2012 0.0% Acura RL Sedan 2012 0.0% +1006 /scratch/Teaching/cars/car_ims/014822.jpg Spyker C8 Coupe 2009 Aston Martin Virage Coupe 2012 89.55% Spyker C8 Coupe 2009 6.08% McLaren MP4-12C Coupe 2012 2.5% Hyundai Veloster Hatchback 2012 0.79% Aston Martin V8 Vantage Coupe 2012 0.7% +1007 /scratch/Teaching/cars/car_ims/007071.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 93.58% Ford F-150 Regular Cab 2007 5.06% Chevrolet Silverado 2500HD Regular Cab 2012 0.81% Ford F-150 Regular Cab 2012 0.41% Dodge Ram Pickup 3500 Crew Cab 2010 0.08% +1008 /scratch/Teaching/cars/car_ims/005872.jpg Chevrolet Malibu Sedan 2007 Maybach Landaulet Convertible 2012 24.09% Mercedes-Benz Sprinter Van 2012 16.73% Daewoo Nubira Wagon 2002 12.03% Suzuki SX4 Sedan 2012 7.6% Chrysler PT Cruiser Convertible 2008 6.8% +1009 /scratch/Teaching/cars/car_ims/008052.jpg Eagle Talon Hatchback 1998 BMW X6 SUV 2012 36.14% Audi 100 Wagon 1994 26.97% Jeep Patriot SUV 2012 7.56% Hyundai Veracruz SUV 2012 5.47% Jeep Compass SUV 2012 5.47% +1010 /scratch/Teaching/cars/car_ims/010944.jpg Hyundai Veracruz SUV 2012 Hyundai Veracruz SUV 2012 99.99% Honda Odyssey Minivan 2012 0.01% Chevrolet Traverse SUV 2012 0.0% Nissan Juke Hatchback 2012 0.0% Scion xD Hatchback 2012 0.0% +1011 /scratch/Teaching/cars/car_ims/000392.jpg Acura TSX Sedan 2012 Acura TSX Sedan 2012 98.71% Toyota Camry Sedan 2012 1.05% Acura RL Sedan 2012 0.08% Chevrolet Malibu Sedan 2007 0.06% Chevrolet Monte Carlo Coupe 2007 0.06% +1012 /scratch/Teaching/cars/car_ims/002633.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 63.63% BMW 1 Series Coupe 2012 34.85% BMW 1 Series Convertible 2012 0.59% Volvo C30 Hatchback 2012 0.47% Dodge Caliber Wagon 2007 0.15% +1013 /scratch/Teaching/cars/car_ims/003169.jpg Bentley Continental Supersports Conv. Convertible 2012 Buick Regal GS 2012 69.43% Rolls-Royce Phantom Sedan 2012 7.34% Bentley Continental Supersports Conv. Convertible 2012 6.73% Rolls-Royce Ghost Sedan 2012 5.04% Bentley Continental GT Coupe 2012 3.78% +1014 /scratch/Teaching/cars/car_ims/004231.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 99.96% GMC Yukon Hybrid SUV 2012 0.03% Cadillac SRX SUV 2012 0.01% Chrysler Town and Country Minivan 2012 0.0% Dodge Magnum Wagon 2008 0.0% +1015 /scratch/Teaching/cars/car_ims/005814.jpg Chevrolet Monte Carlo Coupe 2007 Ford Focus Sedan 2007 27.25% Daewoo Nubira Wagon 2002 25.37% Chevrolet Impala Sedan 2007 22.86% Chevrolet Monte Carlo Coupe 2007 4.97% Mercedes-Benz 300-Class Convertible 1993 4.03% +1016 /scratch/Teaching/cars/car_ims/002179.jpg BMW 1 Series Convertible 2012 BMW 1 Series Convertible 2012 86.59% Audi S5 Convertible 2012 10.46% Audi RS 4 Convertible 2008 1.48% Chrysler Crossfire Convertible 2008 0.48% BMW Z4 Convertible 2012 0.28% +1017 /scratch/Teaching/cars/car_ims/002834.jpg BMW M5 Sedan 2010 Acura RL Sedan 2012 68.48% Acura TSX Sedan 2012 7.58% Audi S4 Sedan 2007 5.6% BMW M5 Sedan 2010 5.38% Acura TL Type-S 2008 5.19% +1018 /scratch/Teaching/cars/car_ims/015390.jpg Toyota Camry Sedan 2012 Buick Verano Sedan 2012 59.47% Honda Accord Coupe 2012 12.53% Ford Fiesta Sedan 2012 6.83% Toyota Camry Sedan 2012 5.34% Hyundai Accent Sedan 2012 3.5% +1019 /scratch/Teaching/cars/car_ims/009812.jpg GMC Yukon Hybrid SUV 2012 GMC Yukon Hybrid SUV 2012 81.49% Cadillac Escalade EXT Crew Cab 2007 12.89% Rolls-Royce Phantom Sedan 2012 5.36% Bentley Arnage Sedan 2009 0.09% GMC Terrain SUV 2012 0.05% +1020 /scratch/Teaching/cars/car_ims/003228.jpg Bentley Arnage Sedan 2009 AM General Hummer SUV 2000 45.96% Bugatti Veyron 16.4 Coupe 2009 30.31% Audi R8 Coupe 2012 9.21% Bentley Arnage Sedan 2009 6.55% Ford GT Coupe 2006 2.58% +1021 /scratch/Teaching/cars/car_ims/011527.jpg Hyundai Azera Sedan 2012 Suzuki Kizashi Sedan 2012 30.12% Suzuki SX4 Sedan 2012 18.51% Chevrolet Sonic Sedan 2012 13.77% Hyundai Azera Sedan 2012 9.9% Volkswagen Beetle Hatchback 2012 3.92% +1022 /scratch/Teaching/cars/car_ims/015630.jpg Volkswagen Golf Hatchback 2012 Suzuki SX4 Hatchback 2012 52.31% Volkswagen Golf Hatchback 2012 11.03% Jeep Grand Cherokee SUV 2012 10.41% Hyundai Santa Fe SUV 2012 7.26% Hyundai Veracruz SUV 2012 6.74% +1023 /scratch/Teaching/cars/car_ims/010264.jpg HUMMER H3T Crew Cab 2010 HUMMER H3T Crew Cab 2010 99.79% Volvo XC90 SUV 2007 0.15% Jeep Compass SUV 2012 0.04% Jeep Patriot SUV 2012 0.01% Dodge Caliber Wagon 2012 0.01% +1024 /scratch/Teaching/cars/car_ims/009295.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 46.87% Chevrolet Silverado 1500 Extended Cab 2012 21.68% Chevrolet Silverado 1500 Regular Cab 2012 12.37% GMC Canyon Extended Cab 2012 7.46% Chevrolet Avalanche Crew Cab 2012 7.44% +1025 /scratch/Teaching/cars/car_ims/013922.jpg Nissan Juke Hatchback 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 14.53% Dodge Caliber Wagon 2012 10.45% Buick Rainier SUV 2007 10.33% Ford Ranger SuperCab 2011 8.87% Ford Expedition EL SUV 2009 8.5% +1026 /scratch/Teaching/cars/car_ims/013465.jpg Mercedes-Benz E-Class Sedan 2012 Audi S5 Convertible 2012 46.19% Mercedes-Benz E-Class Sedan 2012 31.26% Audi RS 4 Convertible 2008 11.88% Audi S5 Coupe 2012 5.3% BMW 6 Series Convertible 2007 1.88% +1027 /scratch/Teaching/cars/car_ims/009411.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 93.6% Chevrolet Impala Sedan 2007 3.53% Chrysler Sebring Convertible 2010 2.06% Chevrolet Corvette ZR1 2012 0.34% Chevrolet Corvette Convertible 2012 0.12% +1028 /scratch/Teaching/cars/car_ims/007733.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 99.99% Dodge Dakota Club Cab 2007 0.01% Dodge Dakota Crew Cab 2010 0.0% Dodge Caliber Wagon 2012 0.0% Chrysler Aspen SUV 2009 0.0% +1029 /scratch/Teaching/cars/car_ims/011307.jpg Hyundai Sonata Sedan 2012 Hyundai Sonata Sedan 2012 99.99% Hyundai Sonata Hybrid Sedan 2012 0.01% Hyundai Azera Sedan 2012 0.0% Toyota Camry Sedan 2012 0.0% Hyundai Accent Sedan 2012 0.0% +1030 /scratch/Teaching/cars/car_ims/004403.jpg Chevrolet Corvette Convertible 2012 Audi RS 4 Convertible 2008 18.49% Audi S5 Convertible 2012 16.62% Mercedes-Benz 300-Class Convertible 1993 11.92% Maybach Landaulet Convertible 2012 9.26% Chrysler 300 SRT-8 2010 6.85% +1031 /scratch/Teaching/cars/car_ims/000219.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 47.77% Acura TSX Sedan 2012 32.88% Acura RL Sedan 2012 15.77% Acura TL Type-S 2008 3.34% Honda Accord Coupe 2012 0.09% +1032 /scratch/Teaching/cars/car_ims/010368.jpg Honda Odyssey Minivan 2012 Honda Odyssey Minivan 2012 99.82% Infiniti QX56 SUV 2011 0.05% Acura TL Sedan 2012 0.04% Porsche Panamera Sedan 2012 0.03% Buick Verano Sedan 2012 0.03% +1033 /scratch/Teaching/cars/car_ims/011290.jpg Hyundai Genesis Sedan 2012 Hyundai Genesis Sedan 2012 98.13% Hyundai Azera Sedan 2012 1.53% Hyundai Sonata Sedan 2012 0.33% Infiniti G Coupe IPL 2012 0.0% Toyota Corolla Sedan 2012 0.0% +1034 /scratch/Teaching/cars/car_ims/003115.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental GT Coupe 2007 99.37% Bentley Continental Flying Spur Sedan 2007 0.43% Ford GT Coupe 2006 0.11% Spyker C8 Convertible 2009 0.1% Bentley Continental GT Coupe 2012 0.0% +1035 /scratch/Teaching/cars/car_ims/000002.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 99.86% HUMMER H2 SUT Crew Cab 2009 0.11% HUMMER H3T Crew Cab 2010 0.01% Jeep Wrangler SUV 2012 0.01% Nissan NV Passenger Van 2012 0.0% +1036 /scratch/Teaching/cars/car_ims/009463.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 99.36% Plymouth Neon Coupe 1999 0.62% Suzuki Aerio Sedan 2007 0.02% Daewoo Nubira Wagon 2002 0.0% Chevrolet Impala Sedan 2007 0.0% +1037 /scratch/Teaching/cars/car_ims/008366.jpg Ferrari 458 Italia Convertible 2012 Ferrari 458 Italia Coupe 2012 99.74% Ferrari 458 Italia Convertible 2012 0.26% Ferrari California Convertible 2012 0.0% Ford GT Coupe 2006 0.0% Ferrari FF Coupe 2012 0.0% +1038 /scratch/Teaching/cars/car_ims/007368.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 63.77% Dodge Ram Pickup 3500 Quad Cab 2009 7.84% Jeep Liberty SUV 2012 6.22% Dodge Durango SUV 2007 5.23% Chevrolet Silverado 1500 Classic Extended Cab 2007 4.81% +1039 /scratch/Teaching/cars/car_ims/014075.jpg Nissan 240SX Coupe 1998 Chevrolet Monte Carlo Coupe 2007 46.78% Eagle Talon Hatchback 1998 30.79% Nissan 240SX Coupe 1998 18.12% Geo Metro Convertible 1993 1.95% Acura Integra Type R 2001 1.02% +1040 /scratch/Teaching/cars/car_ims/015807.jpg Volkswagen Beetle Hatchback 2012 Cadillac CTS-V Sedan 2012 58.51% Volkswagen Beetle Hatchback 2012 33.27% Porsche Panamera Sedan 2012 1.28% Chevrolet Cobalt SS 2010 1.08% Chevrolet Malibu Hybrid Sedan 2010 0.76% +1041 /scratch/Teaching/cars/car_ims/012874.jpg MINI Cooper Roadster Convertible 2012 BMW 6 Series Convertible 2007 31.61% Chrysler Sebring Convertible 2010 24.84% Chrysler Crossfire Convertible 2008 16.71% Jaguar XK XKR 2012 6.4% Chevrolet Monte Carlo Coupe 2007 5.8% +1042 /scratch/Teaching/cars/car_ims/005741.jpg Chevrolet Express Van 2007 Chevrolet Express Cargo Van 2007 90.7% GMC Savana Van 2012 9.25% Chevrolet Express Van 2007 0.06% Volvo XC90 SUV 2007 0.0% Nissan NV Passenger Van 2012 0.0% +1043 /scratch/Teaching/cars/car_ims/006241.jpg Chrysler Sebring Convertible 2010 Chrysler Sebring Convertible 2010 27.12% Chevrolet Impala Sedan 2007 18.8% Acura RL Sedan 2012 16.63% Chevrolet Malibu Hybrid Sedan 2010 10.11% Ford Focus Sedan 2007 4.32% +1044 /scratch/Teaching/cars/car_ims/016097.jpg Volvo XC90 SUV 2007 Isuzu Ascender SUV 2008 97.99% Volvo XC90 SUV 2007 1.17% Ford Freestar Minivan 2007 0.7% Cadillac Escalade EXT Crew Cab 2007 0.06% Chrysler Aspen SUV 2009 0.04% +1045 /scratch/Teaching/cars/car_ims/006340.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 99.99% Suzuki SX4 Sedan 2012 0.01% Dodge Caliber Wagon 2012 0.0% Ram C/V Cargo Van Minivan 2012 0.0% Suzuki Aerio Sedan 2007 0.0% +1046 /scratch/Teaching/cars/car_ims/014079.jpg Nissan 240SX Coupe 1998 Plymouth Neon Coupe 1999 94.08% Daewoo Nubira Wagon 2002 2.29% Nissan 240SX Coupe 1998 0.89% Eagle Talon Hatchback 1998 0.66% Dodge Challenger SRT8 2011 0.4% +1047 /scratch/Teaching/cars/car_ims/009567.jpg Ford Fiesta Sedan 2012 Chevrolet Corvette ZR1 2012 68.52% Ford Fiesta Sedan 2012 25.87% Audi S4 Sedan 2007 3.39% Bentley Continental GT Coupe 2007 0.45% Suzuki Kizashi Sedan 2012 0.42% +1048 /scratch/Teaching/cars/car_ims/015538.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 95.4% Jeep Compass SUV 2012 3.87% BMW X3 SUV 2012 0.29% Dodge Caliber Wagon 2012 0.23% Jeep Grand Cherokee SUV 2012 0.1% +1049 /scratch/Teaching/cars/car_ims/013973.jpg Nissan Juke Hatchback 2012 Ferrari FF Coupe 2012 66.46% BMW M6 Convertible 2010 6.48% BMW 3 Series Sedan 2012 3.76% Porsche Panamera Sedan 2012 3.35% BMW M5 Sedan 2010 3.26% +1050 /scratch/Teaching/cars/car_ims/012102.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 100.0% Jeep Patriot SUV 2012 0.0% Jeep Grand Cherokee SUV 2012 0.0% BMW X5 SUV 2007 0.0% Jeep Compass SUV 2012 0.0% +1051 /scratch/Teaching/cars/car_ims/008870.jpg Ford Expedition EL SUV 2009 Chrysler Aspen SUV 2009 86.74% Dodge Durango SUV 2007 7.74% Ford Expedition EL SUV 2009 2.28% Chrysler PT Cruiser Convertible 2008 2.17% Dodge Durango SUV 2012 0.34% +1052 /scratch/Teaching/cars/car_ims/004459.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Convertible 2012 96.01% Chrysler Crossfire Convertible 2008 3.49% Audi S5 Convertible 2012 0.47% Chevrolet Corvette ZR1 2012 0.03% Chevrolet Camaro Convertible 2012 0.0% +1053 /scratch/Teaching/cars/car_ims/005611.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chevrolet Silverado 1500 Classic Extended Cab 2007 100.0% Ford Ranger SuperCab 2011 0.0% Chevrolet Silverado 2500HD Regular Cab 2012 0.0% GMC Canyon Extended Cab 2012 0.0% Ford F-150 Regular Cab 2012 0.0% +1054 /scratch/Teaching/cars/car_ims/016149.jpg smart fortwo Convertible 2012 Suzuki Kizashi Sedan 2012 59.71% Nissan Juke Hatchback 2012 35.43% Hyundai Veloster Hatchback 2012 2.12% Toyota 4Runner SUV 2012 1.26% smart fortwo Convertible 2012 0.61% +1055 /scratch/Teaching/cars/car_ims/012076.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 99.99% Jeep Patriot SUV 2012 0.01% Jeep Compass SUV 2012 0.0% Bentley Arnage Sedan 2009 0.0% Jeep Wrangler SUV 2012 0.0% +1056 /scratch/Teaching/cars/car_ims/012761.jpg Land Rover LR2 SUV 2012 Hyundai Santa Fe SUV 2012 72.78% Ford Expedition EL SUV 2009 13.43% Ford Edge SUV 2012 5.29% Hyundai Veracruz SUV 2012 3.0% Infiniti QX56 SUV 2011 2.94% +1057 /scratch/Teaching/cars/car_ims/003792.jpg Buick Regal GS 2012 Buick Regal GS 2012 100.0% Buick Verano Sedan 2012 0.0% Chevrolet Sonic Sedan 2012 0.0% Suzuki Kizashi Sedan 2012 0.0% Suzuki SX4 Sedan 2012 0.0% +1058 /scratch/Teaching/cars/car_ims/014273.jpg Porsche Panamera Sedan 2012 Fisker Karma Sedan 2012 53.36% Porsche Panamera Sedan 2012 18.63% Chevrolet Corvette Convertible 2012 5.98% Buick Verano Sedan 2012 5.2% Bentley Mulsanne Sedan 2011 3.48% +1059 /scratch/Teaching/cars/car_ims/007323.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 99.89% Dodge Dakota Club Cab 2007 0.08% Ford Freestar Minivan 2007 0.01% Chrysler Aspen SUV 2009 0.01% Ford Ranger SuperCab 2011 0.01% +1060 /scratch/Teaching/cars/car_ims/004675.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 100.0% Ford F-150 Regular Cab 2012 0.0% GMC Acadia SUV 2012 0.0% Ford Expedition EL SUV 2009 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% +1061 /scratch/Teaching/cars/car_ims/008262.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 99.97% Chevrolet Corvette Convertible 2012 0.03% Ferrari 458 Italia Convertible 2012 0.0% Chevrolet Camaro Convertible 2012 0.0% Ferrari 458 Italia Coupe 2012 0.0% +1062 /scratch/Teaching/cars/car_ims/006998.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 100.0% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% Dodge Durango SUV 2007 0.0% Dodge Dakota Crew Cab 2010 0.0% Chrysler Aspen SUV 2009 0.0% +1063 /scratch/Teaching/cars/car_ims/008120.jpg FIAT 500 Convertible 2012 Nissan NV Passenger Van 2012 92.0% Ford F-150 Regular Cab 2007 2.82% Jeep Compass SUV 2012 2.66% Volvo C30 Hatchback 2012 1.06% Suzuki SX4 Hatchback 2012 0.56% +1064 /scratch/Teaching/cars/car_ims/009140.jpg Ford GT Coupe 2006 Audi R8 Coupe 2012 86.4% McLaren MP4-12C Coupe 2012 8.89% Lamborghini Aventador Coupe 2012 1.2% Chevrolet Corvette ZR1 2012 0.93% BMW M6 Convertible 2010 0.66% +1065 /scratch/Teaching/cars/car_ims/007690.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 99.67% Land Rover LR2 SUV 2012 0.11% Honda Accord Coupe 2012 0.08% Chevrolet Malibu Sedan 2007 0.03% Honda Odyssey Minivan 2012 0.03% +1066 /scratch/Teaching/cars/car_ims/001313.jpg Audi 100 Sedan 1994 Audi 100 Sedan 1994 31.56% Ford Ranger SuperCab 2011 31.46% Ford F-150 Regular Cab 2007 13.96% Chevrolet Silverado 1500 Classic Extended Cab 2007 11.58% Audi V8 Sedan 1994 4.68% +1067 /scratch/Teaching/cars/car_ims/008110.jpg FIAT 500 Convertible 2012 FIAT 500 Convertible 2012 99.88% MINI Cooper Roadster Convertible 2012 0.12% smart fortwo Convertible 2012 0.0% Bugatti Veyron 16.4 Convertible 2009 0.0% Nissan Leaf Hatchback 2012 0.0% +1068 /scratch/Teaching/cars/car_ims/000989.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 58.72% Audi S5 Coupe 2012 30.36% Audi S5 Convertible 2012 7.16% Audi S4 Sedan 2012 2.28% Audi TTS Coupe 2012 0.75% +1069 /scratch/Teaching/cars/car_ims/007554.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 74.5% Chevrolet Malibu Hybrid Sedan 2010 14.1% Mitsubishi Lancer Sedan 2012 4.29% Chevrolet Cobalt SS 2010 2.74% Buick Verano Sedan 2012 2.04% +1070 /scratch/Teaching/cars/car_ims/013859.jpg Nissan NV Passenger Van 2012 Mitsubishi Lancer Sedan 2012 51.9% Chevrolet Sonic Sedan 2012 10.1% Audi RS 4 Convertible 2008 7.85% Chrysler PT Cruiser Convertible 2008 7.21% Ford F-150 Regular Cab 2007 6.32% +1071 /scratch/Teaching/cars/car_ims/011773.jpg Jaguar XK XKR 2012 Chevrolet Corvette ZR1 2012 79.49% Jaguar XK XKR 2012 19.43% Chevrolet Corvette Convertible 2012 0.97% Dodge Challenger SRT8 2011 0.04% Porsche Panamera Sedan 2012 0.03% +1072 /scratch/Teaching/cars/car_ims/015588.jpg Volkswagen Golf Hatchback 2012 Buick Verano Sedan 2012 50.32% Chevrolet Sonic Sedan 2012 25.17% Acura ZDX Hatchback 2012 19.51% Audi S5 Coupe 2012 1.21% Volkswagen Beetle Hatchback 2012 0.74% +1073 /scratch/Teaching/cars/car_ims/000592.jpg Aston Martin V8 Vantage Convertible 2012 Chevrolet Corvette Ron Fellows Edition Z06 2007 62.46% Acura Integra Type R 2001 20.08% Bentley Continental Supersports Conv. Convertible 2012 3.05% MINI Cooper Roadster Convertible 2012 1.9% Ford GT Coupe 2006 1.41% +1074 /scratch/Teaching/cars/car_ims/014017.jpg Nissan 240SX Coupe 1998 Volvo 240 Sedan 1993 64.8% Aston Martin V8 Vantage Convertible 2012 13.07% Mercedes-Benz 300-Class Convertible 1993 9.7% Volkswagen Golf Hatchback 1991 7.97% Jaguar XK XKR 2012 1.82% +1075 /scratch/Teaching/cars/car_ims/007508.jpg Dodge Magnum Wagon 2008 Nissan 240SX Coupe 1998 39.78% BMW 3 Series Sedan 2012 33.22% Volkswagen Golf Hatchback 1991 18.62% Dodge Magnum Wagon 2008 2.19% Chevrolet HHR SS 2010 1.39% +1076 /scratch/Teaching/cars/car_ims/014750.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 100.0% Spyker C8 Coupe 2009 0.0% Aston Martin Virage Convertible 2012 0.0% Bugatti Veyron 16.4 Coupe 2009 0.0% Mercedes-Benz SL-Class Coupe 2009 0.0% +1077 /scratch/Teaching/cars/car_ims/009180.jpg Ford GT Coupe 2006 Ford GT Coupe 2006 68.78% Bentley Arnage Sedan 2009 15.53% Nissan NV Passenger Van 2012 6.63% Rolls-Royce Phantom Sedan 2012 6.54% Bugatti Veyron 16.4 Coupe 2009 1.28% +1078 /scratch/Teaching/cars/car_ims/000686.jpg Aston Martin V8 Vantage Coupe 2012 Aston Martin V8 Vantage Coupe 2012 87.23% Aston Martin V8 Vantage Convertible 2012 10.81% Ferrari California Convertible 2012 1.45% Ferrari 458 Italia Convertible 2012 0.21% Aston Martin Virage Convertible 2012 0.1% +1079 /scratch/Teaching/cars/car_ims/004701.jpg Chevrolet Traverse SUV 2012 Hyundai Tucson SUV 2012 93.62% Chevrolet Traverse SUV 2012 4.16% Ford Fiesta Sedan 2012 1.02% Hyundai Veracruz SUV 2012 0.55% smart fortwo Convertible 2012 0.19% +1080 /scratch/Teaching/cars/car_ims/011950.jpg Jeep Wrangler SUV 2012 Mercedes-Benz 300-Class Convertible 1993 56.4% Ford Mustang Convertible 2007 22.59% BMW 3 Series Sedan 2012 5.53% Volvo 240 Sedan 1993 4.72% BMW 1 Series Convertible 2012 4.02% +1081 /scratch/Teaching/cars/car_ims/015611.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 99.98% Toyota Camry Sedan 2012 0.01% Toyota Corolla Sedan 2012 0.01% Ford Fiesta Sedan 2012 0.0% Dodge Journey SUV 2012 0.0% +1082 /scratch/Teaching/cars/car_ims/004995.jpg Chevrolet Tahoe Hybrid SUV 2012 Land Rover Range Rover SUV 2012 75.89% Chevrolet TrailBlazer SS 2009 19.81% Chevrolet Tahoe Hybrid SUV 2012 1.49% Chevrolet Avalanche Crew Cab 2012 0.85% Jeep Patriot SUV 2012 0.55% +1083 /scratch/Teaching/cars/car_ims/003748.jpg Buick Regal GS 2012 Volkswagen Golf Hatchback 2012 96.45% Honda Odyssey Minivan 2007 2.4% Suzuki SX4 Sedan 2012 0.62% Toyota Camry Sedan 2012 0.22% Acura TSX Sedan 2012 0.05% +1084 /scratch/Teaching/cars/car_ims/015992.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 100.0% Bentley Arnage Sedan 2009 0.0% Rolls-Royce Phantom Sedan 2012 0.0% Volkswagen Golf Hatchback 1991 0.0% Mercedes-Benz 300-Class Convertible 1993 0.0% +1085 /scratch/Teaching/cars/car_ims/008030.jpg Eagle Talon Hatchback 1998 Eagle Talon Hatchback 1998 91.15% Nissan 240SX Coupe 1998 7.91% Honda Accord Coupe 2012 0.23% Audi R8 Coupe 2012 0.17% Plymouth Neon Coupe 1999 0.09% +1086 /scratch/Teaching/cars/car_ims/002055.jpg BMW ActiveHybrid 5 Sedan 2012 BMW 3 Series Sedan 2012 69.49% BMW 3 Series Wagon 2012 12.83% Audi 100 Wagon 1994 5.6% Rolls-Royce Phantom Sedan 2012 5.03% Volkswagen Golf Hatchback 1991 1.78% +1087 /scratch/Teaching/cars/car_ims/015999.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 96.81% Volkswagen Golf Hatchback 1991 2.45% Audi 100 Wagon 1994 0.64% Audi 100 Sedan 1994 0.09% Mercedes-Benz 300-Class Convertible 1993 0.0% +1088 /scratch/Teaching/cars/car_ims/009576.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 95.85% Hyundai Accent Sedan 2012 3.96% Hyundai Tucson SUV 2012 0.17% Chevrolet Sonic Sedan 2012 0.01% Hyundai Veloster Hatchback 2012 0.01% +1089 /scratch/Teaching/cars/car_ims/015026.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 98.75% Volvo C30 Hatchback 2012 0.91% Suzuki SX4 Sedan 2012 0.31% Chevrolet Sonic Sedan 2012 0.02% Scion xD Hatchback 2012 0.01% +1090 /scratch/Teaching/cars/car_ims/001039.jpg Audi A5 Coupe 2012 Audi S5 Coupe 2012 84.1% Audi A5 Coupe 2012 15.55% Audi RS 4 Convertible 2008 0.19% Audi S5 Convertible 2012 0.13% Audi S4 Sedan 2012 0.02% +1091 /scratch/Teaching/cars/car_ims/013301.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz S-Class Sedan 2012 61.34% Mercedes-Benz E-Class Sedan 2012 18.16% Mercedes-Benz C-Class Sedan 2012 13.32% Hyundai Genesis Sedan 2012 4.0% Chrysler Crossfire Convertible 2008 3.16% +1092 /scratch/Teaching/cars/car_ims/008407.jpg Ferrari 458 Italia Convertible 2012 Ferrari 458 Italia Convertible 2012 93.52% Ferrari 458 Italia Coupe 2012 6.08% Spyker C8 Convertible 2009 0.21% Spyker C8 Coupe 2009 0.08% McLaren MP4-12C Coupe 2012 0.05% +1093 /scratch/Teaching/cars/car_ims/000568.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 82.94% Daewoo Nubira Wagon 2002 8.92% Acura RL Sedan 2012 3.53% Chevrolet Malibu Hybrid Sedan 2010 1.52% Chevrolet Impala Sedan 2007 0.87% +1094 /scratch/Teaching/cars/car_ims/010012.jpg GMC Canyon Extended Cab 2012 Dodge Ram Pickup 3500 Quad Cab 2009 97.0% Ford F-450 Super Duty Crew Cab 2012 0.97% HUMMER H3T Crew Cab 2010 0.72% Ford Ranger SuperCab 2011 0.35% Ford F-150 Regular Cab 2012 0.34% +1095 /scratch/Teaching/cars/car_ims/013059.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 99.22% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.72% Ferrari 458 Italia Convertible 2012 0.03% Aston Martin Virage Coupe 2012 0.01% Aston Martin V8 Vantage Coupe 2012 0.01% +1096 /scratch/Teaching/cars/car_ims/009753.jpg GMC Savana Van 2012 GMC Savana Van 2012 90.75% Volvo 240 Sedan 1993 8.12% Chevrolet Express Cargo Van 2007 0.59% Volkswagen Golf Hatchback 1991 0.3% Chevrolet Express Van 2007 0.12% +1097 /scratch/Teaching/cars/car_ims/010563.jpg Honda Accord Coupe 2012 Honda Accord Coupe 2012 93.96% BMW 3 Series Sedan 2012 5.29% BMW X6 SUV 2012 0.49% Chevrolet Cobalt SS 2010 0.18% BMW 1 Series Coupe 2012 0.02% +1098 /scratch/Teaching/cars/car_ims/004714.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 93.25% Hyundai Veracruz SUV 2012 6.69% Hyundai Tucson SUV 2012 0.05% Acura ZDX Hatchback 2012 0.0% Suzuki SX4 Hatchback 2012 0.0% +1099 /scratch/Teaching/cars/car_ims/002407.jpg BMW 3 Series Wagon 2012 Volvo 240 Sedan 1993 60.59% Chrysler 300 SRT-8 2010 19.01% Rolls-Royce Phantom Sedan 2012 10.7% Dodge Charger SRT-8 2009 3.78% Nissan 240SX Coupe 1998 1.27% +1100 /scratch/Teaching/cars/car_ims/015130.jpg Suzuki SX4 Sedan 2012 Suzuki SX4 Sedan 2012 99.22% Chevrolet Malibu Sedan 2007 0.72% Suzuki SX4 Hatchback 2012 0.03% Buick Verano Sedan 2012 0.03% Hyundai Elantra Sedan 2007 0.0% +1101 /scratch/Teaching/cars/car_ims/008515.jpg Fisker Karma Sedan 2012 Spyker C8 Convertible 2009 87.52% smart fortwo Convertible 2012 5.66% Jeep Liberty SUV 2012 3.96% Fisker Karma Sedan 2012 1.21% Spyker C8 Coupe 2009 1.15% +1102 /scratch/Teaching/cars/car_ims/012610.jpg Land Rover Range Rover SUV 2012 Chevrolet Avalanche Crew Cab 2012 60.67% Dodge Durango SUV 2012 36.37% Land Rover Range Rover SUV 2012 1.35% Dodge Magnum Wagon 2008 0.69% Chevrolet TrailBlazer SS 2009 0.66% +1103 /scratch/Teaching/cars/car_ims/004795.jpg Chevrolet Camaro Convertible 2012 Audi S5 Coupe 2012 75.12% Fisker Karma Sedan 2012 6.77% Bentley Continental GT Coupe 2012 6.6% Bentley Continental GT Coupe 2007 2.62% BMW Z4 Convertible 2012 1.85% +1104 /scratch/Teaching/cars/car_ims/006544.jpg Chrysler PT Cruiser Convertible 2008 Chrysler PT Cruiser Convertible 2008 99.98% Mercedes-Benz E-Class Sedan 2012 0.01% Hyundai Genesis Sedan 2012 0.0% Hyundai Azera Sedan 2012 0.0% Chrysler Town and Country Minivan 2012 0.0% +1105 /scratch/Teaching/cars/car_ims/001975.jpg Audi S4 Sedan 2007 Audi S6 Sedan 2011 49.95% Audi S5 Coupe 2012 48.08% Audi S5 Convertible 2012 0.55% Audi RS 4 Convertible 2008 0.42% Audi A5 Coupe 2012 0.37% +1106 /scratch/Teaching/cars/car_ims/000017.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 69.03% Daewoo Nubira Wagon 2002 24.61% Volkswagen Golf Hatchback 1991 1.54% Jeep Patriot SUV 2012 1.27% Land Rover Range Rover SUV 2012 1.1% +1107 /scratch/Teaching/cars/car_ims/012250.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 99.98% Jeep Grand Cherokee SUV 2012 0.02% BMW X3 SUV 2012 0.0% Dodge Durango SUV 2007 0.0% GMC Terrain SUV 2012 0.0% +1108 /scratch/Teaching/cars/car_ims/009230.jpg Ford F-150 Regular Cab 2012 Dodge Durango SUV 2007 58.62% Chrysler Aspen SUV 2009 33.21% Ford F-150 Regular Cab 2012 4.78% Ford F-150 Regular Cab 2007 1.8% Nissan NV Passenger Van 2012 1.43% +1109 /scratch/Teaching/cars/car_ims/009058.jpg Ford Ranger SuperCab 2011 Dodge Ram Pickup 3500 Crew Cab 2010 15.93% Volvo 240 Sedan 1993 12.22% HUMMER H3T Crew Cab 2010 11.56% Dodge Ram Pickup 3500 Quad Cab 2009 10.21% Ford Ranger SuperCab 2011 8.77% +1110 /scratch/Teaching/cars/car_ims/015778.jpg Volkswagen Beetle Hatchback 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 37.56% BMW Z4 Convertible 2012 17.5% BMW 6 Series Convertible 2007 16.5% Dodge Challenger SRT8 2011 8.43% Bugatti Veyron 16.4 Convertible 2009 3.99% +1111 /scratch/Teaching/cars/car_ims/005742.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 47.92% Chevrolet Express Cargo Van 2007 42.49% Chevrolet Express Van 2007 9.46% Nissan NV Passenger Van 2012 0.1% Ford E-Series Wagon Van 2012 0.03% +1112 /scratch/Teaching/cars/car_ims/005803.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Monte Carlo Coupe 2007 98.6% Chevrolet Malibu Sedan 2007 1.17% Chevrolet Impala Sedan 2007 0.17% Chevrolet Cobalt SS 2010 0.01% Mitsubishi Lancer Sedan 2012 0.01% +1113 /scratch/Teaching/cars/car_ims/004059.jpg Cadillac CTS-V Sedan 2012 BMW 6 Series Convertible 2007 32.13% Toyota Camry Sedan 2012 29.52% Infiniti G Coupe IPL 2012 7.23% Mercedes-Benz E-Class Sedan 2012 5.99% Acura TL Type-S 2008 3.85% +1114 /scratch/Teaching/cars/car_ims/010921.jpg Hyundai Tucson SUV 2012 Chevrolet Traverse SUV 2012 48.26% Eagle Talon Hatchback 1998 13.57% Chevrolet Malibu Hybrid Sedan 2010 12.36% Chevrolet Malibu Sedan 2007 7.24% Chevrolet Impala Sedan 2007 5.07% +1115 /scratch/Teaching/cars/car_ims/001738.jpg Audi S5 Coupe 2012 Audi S5 Convertible 2012 84.38% BMW 3 Series Sedan 2012 9.04% Audi A5 Coupe 2012 3.16% Audi S4 Sedan 2012 1.21% Nissan 240SX Coupe 1998 0.37% +1116 /scratch/Teaching/cars/car_ims/015727.jpg Volkswagen Golf Hatchback 1991 Volkswagen Golf Hatchback 1991 33.49% Volvo C30 Hatchback 2012 30.31% Nissan Juke Hatchback 2012 17.28% Hyundai Elantra Touring Hatchback 2012 8.52% Hyundai Veloster Hatchback 2012 2.52% +1117 /scratch/Teaching/cars/car_ims/011005.jpg Hyundai Veracruz SUV 2012 Nissan Leaf Hatchback 2012 84.52% FIAT 500 Convertible 2012 5.72% Suzuki Aerio Sedan 2007 3.86% Scion xD Hatchback 2012 1.55% Suzuki SX4 Hatchback 2012 0.68% +1118 /scratch/Teaching/cars/car_ims/012806.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 100.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Chevrolet Malibu Sedan 2007 0.0% Chevrolet Monte Carlo Coupe 2007 0.0% Audi 100 Sedan 1994 0.0% +1119 /scratch/Teaching/cars/car_ims/011874.jpg Jeep Patriot SUV 2012 Bentley Arnage Sedan 2009 84.99% BMW M6 Convertible 2010 3.65% BMW X5 SUV 2007 2.53% Jeep Grand Cherokee SUV 2012 2.39% Jeep Liberty SUV 2012 2.15% +1120 /scratch/Teaching/cars/car_ims/013938.jpg Nissan Juke Hatchback 2012 smart fortwo Convertible 2012 83.28% Nissan Juke Hatchback 2012 15.42% Audi S5 Convertible 2012 1.07% Suzuki SX4 Sedan 2012 0.08% Mitsubishi Lancer Sedan 2012 0.04% +1121 /scratch/Teaching/cars/car_ims/001564.jpg Audi S6 Sedan 2011 Audi S4 Sedan 2007 65.82% BMW M6 Convertible 2010 10.23% Audi S6 Sedan 2011 9.37% BMW M5 Sedan 2010 6.52% Audi A5 Coupe 2012 3.15% +1122 /scratch/Teaching/cars/car_ims/008698.jpg Ford Mustang Convertible 2007 Ford Mustang Convertible 2007 99.05% Mercedes-Benz 300-Class Convertible 1993 0.73% BMW Z4 Convertible 2012 0.11% BMW M6 Convertible 2010 0.05% BMW M3 Coupe 2012 0.04% +1123 /scratch/Teaching/cars/car_ims/005863.jpg Chevrolet Malibu Sedan 2007 Chevrolet Malibu Sedan 2007 99.97% Chevrolet Impala Sedan 2007 0.03% Suzuki SX4 Hatchback 2012 0.0% Suzuki SX4 Sedan 2012 0.0% Chevrolet Monte Carlo Coupe 2007 0.0% +1124 /scratch/Teaching/cars/car_ims/000378.jpg Acura TSX Sedan 2012 Acura TSX Sedan 2012 71.39% Acura RL Sedan 2012 25.08% Acura TL Sedan 2012 2.88% Honda Accord Sedan 2012 0.61% Acura TL Type-S 2008 0.01% +1125 /scratch/Teaching/cars/car_ims/006093.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 84.5% Chevrolet Silverado 1500 Regular Cab 2012 15.19% Chevrolet Silverado 1500 Extended Cab 2012 0.28% GMC Terrain SUV 2012 0.01% GMC Canyon Extended Cab 2012 0.01% +1126 /scratch/Teaching/cars/car_ims/015490.jpg Toyota Corolla Sedan 2012 Chevrolet Malibu Sedan 2007 51.78% Toyota Corolla Sedan 2012 43.45% Hyundai Elantra Sedan 2007 2.14% Toyota Camry Sedan 2012 1.31% Chevrolet Monte Carlo Coupe 2007 0.52% +1127 /scratch/Teaching/cars/car_ims/015847.jpg Volvo C30 Hatchback 2012 Aston Martin Virage Coupe 2012 42.5% Volvo C30 Hatchback 2012 35.13% Dodge Charger SRT-8 2009 18.76% Chevrolet HHR SS 2010 1.19% Spyker C8 Convertible 2009 1.07% +1128 /scratch/Teaching/cars/car_ims/005267.jpg Chevrolet Avalanche Crew Cab 2012 Audi 100 Wagon 1994 57.02% Dodge Dakota Club Cab 2007 9.95% Dodge Dakota Crew Cab 2010 5.45% BMW 1 Series Coupe 2012 5.03% Volkswagen Golf Hatchback 1991 4.73% +1129 /scratch/Teaching/cars/car_ims/014061.jpg Nissan 240SX Coupe 1998 Audi S5 Convertible 2012 43.78% Eagle Talon Hatchback 1998 18.94% Nissan 240SX Coupe 1998 11.69% Spyker C8 Convertible 2009 6.05% Mercedes-Benz 300-Class Convertible 1993 4.57% +1130 /scratch/Teaching/cars/car_ims/003691.jpg Bugatti Veyron 16.4 Coupe 2009 Bugatti Veyron 16.4 Coupe 2009 52.92% Eagle Talon Hatchback 1998 36.32% Spyker C8 Convertible 2009 10.27% Chevrolet Corvette ZR1 2012 0.34% Bugatti Veyron 16.4 Convertible 2009 0.05% +1131 /scratch/Teaching/cars/car_ims/009509.jpg Ford E-Series Wagon Van 2012 Ford E-Series Wagon Van 2012 100.0% Ford F-150 Regular Cab 2007 0.0% Nissan NV Passenger Van 2012 0.0% Ford Ranger SuperCab 2011 0.0% Dodge Ram Pickup 3500 Crew Cab 2010 0.0% +1132 /scratch/Teaching/cars/car_ims/006354.jpg Chrysler 300 SRT-8 2010 Buick Regal GS 2012 76.35% BMW 3 Series Sedan 2012 6.7% Chevrolet Sonic Sedan 2012 3.48% Volvo C30 Hatchback 2012 2.81% Buick Verano Sedan 2012 1.81% +1133 /scratch/Teaching/cars/car_ims/007736.jpg Dodge Durango SUV 2007 BMW X5 SUV 2007 31.88% Buick Enclave SUV 2012 26.33% GMC Acadia SUV 2012 25.74% Jeep Liberty SUV 2012 10.83% Land Rover Range Rover SUV 2012 2.53% +1134 /scratch/Teaching/cars/car_ims/010883.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 99.91% Chevrolet Traverse SUV 2012 0.09% Hyundai Veracruz SUV 2012 0.0% Hyundai Sonata Sedan 2012 0.0% Dodge Journey SUV 2012 0.0% +1135 /scratch/Teaching/cars/car_ims/014271.jpg Porsche Panamera Sedan 2012 BMW 6 Series Convertible 2007 31.38% Acura Integra Type R 2001 20.31% Aston Martin Virage Convertible 2012 8.45% Rolls-Royce Phantom Drophead Coupe Convertible 2012 8.2% Chevrolet Corvette Convertible 2012 5.19% +1136 /scratch/Teaching/cars/car_ims/002762.jpg BMW M3 Coupe 2012 BMW M5 Sedan 2010 81.1% BMW M3 Coupe 2012 17.27% BMW 1 Series Convertible 2012 0.78% BMW 1 Series Coupe 2012 0.39% BMW Z4 Convertible 2012 0.17% +1137 /scratch/Teaching/cars/car_ims/011888.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 99.95% Volvo XC90 SUV 2007 0.04% Jeep Compass SUV 2012 0.01% HUMMER H3T Crew Cab 2010 0.0% Ford Ranger SuperCab 2011 0.0% +1138 /scratch/Teaching/cars/car_ims/000751.jpg Aston Martin Virage Convertible 2012 Jaguar XK XKR 2012 50.63% Aston Martin V8 Vantage Coupe 2012 26.94% Aston Martin V8 Vantage Convertible 2012 12.55% BMW M6 Convertible 2010 5.39% Aston Martin Virage Convertible 2012 3.68% +1139 /scratch/Teaching/cars/car_ims/007403.jpg Dodge Dakota Club Cab 2007 Jeep Compass SUV 2012 54.39% Dodge Durango SUV 2007 17.46% Volvo XC90 SUV 2007 12.89% Jeep Patriot SUV 2012 4.13% Jeep Grand Cherokee SUV 2012 2.47% +1140 /scratch/Teaching/cars/car_ims/009025.jpg Ford Ranger SuperCab 2011 Dodge Dakota Club Cab 2007 93.1% Ford Ranger SuperCab 2011 3.44% Lincoln Town Car Sedan 2011 1.3% Volvo 240 Sedan 1993 0.85% Mercedes-Benz 300-Class Convertible 1993 0.61% +1141 /scratch/Teaching/cars/car_ims/013509.jpg Mercedes-Benz S-Class Sedan 2012 Chrysler 300 SRT-8 2010 94.33% Ford Mustang Convertible 2007 2.22% Mercedes-Benz S-Class Sedan 2012 1.89% Buick Enclave SUV 2012 0.77% Ford Focus Sedan 2007 0.2% +1142 /scratch/Teaching/cars/car_ims/001054.jpg Audi TTS Coupe 2012 Audi S5 Coupe 2012 66.02% Audi A5 Coupe 2012 26.76% Audi TTS Coupe 2012 2.27% Audi S4 Sedan 2007 1.25% Audi S4 Sedan 2012 0.87% +1143 /scratch/Teaching/cars/car_ims/014942.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 96.05% Buick Verano Sedan 2012 1.88% Cadillac CTS-V Sedan 2012 1.58% Suzuki SX4 Sedan 2012 0.21% BMW M5 Sedan 2010 0.14% +1144 /scratch/Teaching/cars/car_ims/008194.jpg Ferrari FF Coupe 2012 Lamborghini Aventador Coupe 2012 72.49% FIAT 500 Abarth 2012 5.36% Ford GT Coupe 2006 5.23% Nissan Juke Hatchback 2012 3.08% Volvo C30 Hatchback 2012 2.21% +1145 /scratch/Teaching/cars/car_ims/006466.jpg Chrysler Crossfire Convertible 2008 Chrysler Crossfire Convertible 2008 96.99% Chevrolet Camaro Convertible 2012 1.44% Eagle Talon Hatchback 1998 0.84% Nissan 240SX Coupe 1998 0.7% Mercedes-Benz 300-Class Convertible 1993 0.02% +1146 /scratch/Teaching/cars/car_ims/013641.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 90.47% Dodge Sprinter Cargo Van 2009 9.53% Ram C/V Cargo Van Minivan 2012 0.0% Ford E-Series Wagon Van 2012 0.0% Chrysler Town and Country Minivan 2012 0.0% +1147 /scratch/Teaching/cars/car_ims/013204.jpg Mercedes-Benz 300-Class Convertible 1993 Mercedes-Benz 300-Class Convertible 1993 99.92% BMW 3 Series Sedan 2012 0.03% Audi 100 Wagon 1994 0.02% Volvo 240 Sedan 1993 0.02% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% +1148 /scratch/Teaching/cars/car_ims/000208.jpg Acura TL Sedan 2012 Acura TSX Sedan 2012 84.19% Acura TL Sedan 2012 15.56% Acura RL Sedan 2012 0.26% Acura ZDX Hatchback 2012 0.0% Toyota Camry Sedan 2012 0.0% +1149 /scratch/Teaching/cars/car_ims/015286.jpg Toyota Sequoia SUV 2012 Mazda Tribute SUV 2011 93.11% Suzuki SX4 Hatchback 2012 5.09% Land Rover LR2 SUV 2012 0.58% Hyundai Santa Fe SUV 2012 0.45% Toyota Sequoia SUV 2012 0.28% +1150 /scratch/Teaching/cars/car_ims/009923.jpg GMC Acadia SUV 2012 Dodge Charger Sedan 2012 94.43% Chevrolet Camaro Convertible 2012 1.83% Spyker C8 Coupe 2009 1.1% Volvo C30 Hatchback 2012 0.76% Audi RS 4 Convertible 2008 0.42% +1151 /scratch/Teaching/cars/car_ims/003545.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 81.65% Bentley Continental GT Coupe 2007 17.53% Bentley Mulsanne Sedan 2011 0.28% Bentley Continental GT Coupe 2012 0.16% Buick Verano Sedan 2012 0.16% +1152 /scratch/Teaching/cars/car_ims/009202.jpg Ford F-150 Regular Cab 2012 Ford F-450 Super Duty Crew Cab 2012 50.09% Ford F-150 Regular Cab 2012 42.76% Dodge Ram Pickup 3500 Quad Cab 2009 1.83% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 1.79% Ford F-150 Regular Cab 2007 1.78% +1153 /scratch/Teaching/cars/car_ims/009857.jpg GMC Yukon Hybrid SUV 2012 GMC Yukon Hybrid SUV 2012 99.99% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.01% Ford F-150 Regular Cab 2007 0.0% HUMMER H3T Crew Cab 2010 0.0% Ford F-150 Regular Cab 2012 0.0% +1154 /scratch/Teaching/cars/car_ims/015306.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.97% Infiniti QX56 SUV 2011 0.03% Chevrolet Traverse SUV 2012 0.0% Hyundai Santa Fe SUV 2012 0.0% Dodge Durango SUV 2012 0.0% +1155 /scratch/Teaching/cars/car_ims/010908.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 99.87% Hyundai Santa Fe SUV 2012 0.1% Hyundai Veracruz SUV 2012 0.02% Chevrolet Traverse SUV 2012 0.01% Honda Accord Sedan 2012 0.0% +1156 /scratch/Teaching/cars/car_ims/011179.jpg Hyundai Accent Sedan 2012 Suzuki SX4 Hatchback 2012 17.67% Volvo C30 Hatchback 2012 16.73% BMW 3 Series Sedan 2012 15.25% Nissan Juke Hatchback 2012 10.17% Dodge Journey SUV 2012 8.11% +1157 /scratch/Teaching/cars/car_ims/003435.jpg Bentley Continental GT Coupe 2007 Bentley Continental Supersports Conv. Convertible 2012 90.96% Maybach Landaulet Convertible 2012 2.79% Buick Regal GS 2012 1.44% Audi R8 Coupe 2012 1.03% MINI Cooper Roadster Convertible 2012 0.9% +1158 /scratch/Teaching/cars/car_ims/009602.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 85.7% Hyundai Accent Sedan 2012 11.35% Hyundai Sonata Hybrid Sedan 2012 1.87% Hyundai Tucson SUV 2012 0.93% Chevrolet Traverse SUV 2012 0.08% +1159 /scratch/Teaching/cars/car_ims/013038.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 99.67% Volvo XC90 SUV 2007 0.24% Toyota 4Runner SUV 2012 0.04% Land Rover LR2 SUV 2012 0.03% Suzuki SX4 Hatchback 2012 0.01% +1160 /scratch/Teaching/cars/car_ims/005572.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 81.36% Chevrolet Silverado 1500 Regular Cab 2012 18.57% Chevrolet Silverado 1500 Extended Cab 2012 0.04% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.03% GMC Canyon Extended Cab 2012 0.0% +1161 /scratch/Teaching/cars/car_ims/000093.jpg Acura RL Sedan 2012 Acura RL Sedan 2012 99.94% Chevrolet Impala Sedan 2007 0.06% Chrysler Town and Country Minivan 2012 0.0% Acura TSX Sedan 2012 0.0% Suzuki SX4 Sedan 2012 0.0% +1162 /scratch/Teaching/cars/car_ims/006588.jpg Chrysler PT Cruiser Convertible 2008 Jeep Compass SUV 2012 52.66% Chrysler PT Cruiser Convertible 2008 17.15% Dodge Caliber Wagon 2012 8.59% BMW X3 SUV 2012 6.76% Dodge Caliber Wagon 2007 4.22% +1163 /scratch/Teaching/cars/car_ims/004105.jpg Cadillac CTS-V Sedan 2012 Cadillac CTS-V Sedan 2012 96.2% MINI Cooper Roadster Convertible 2012 3.23% Suzuki Aerio Sedan 2007 0.19% Chevrolet Camaro Convertible 2012 0.12% Scion xD Hatchback 2012 0.12% +1164 /scratch/Teaching/cars/car_ims/015664.jpg Volkswagen Golf Hatchback 2012 Chevrolet Malibu Sedan 2007 31.62% Chevrolet Monte Carlo Coupe 2007 22.95% Chevrolet Impala Sedan 2007 14.73% Ford Focus Sedan 2007 12.63% Lincoln Town Car Sedan 2011 4.07% +1165 /scratch/Teaching/cars/car_ims/013306.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 99.95% Hyundai Genesis Sedan 2012 0.04% Mercedes-Benz E-Class Sedan 2012 0.0% Mercedes-Benz S-Class Sedan 2012 0.0% Chrysler Crossfire Convertible 2008 0.0% +1166 /scratch/Teaching/cars/car_ims/002824.jpg BMW M5 Sedan 2010 BMW M5 Sedan 2010 47.16% BMW M3 Coupe 2012 22.33% BMW Z4 Convertible 2012 8.54% Aston Martin Virage Coupe 2012 8.09% BMW 1 Series Coupe 2012 4.63% +1167 /scratch/Teaching/cars/car_ims/004726.jpg Chevrolet Camaro Convertible 2012 Ford Mustang Convertible 2007 98.92% BMW 1 Series Convertible 2012 0.75% BMW M6 Convertible 2010 0.18% Audi S5 Convertible 2012 0.06% Mercedes-Benz 300-Class Convertible 1993 0.05% +1168 /scratch/Teaching/cars/car_ims/007118.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Chevrolet Silverado 1500 Extended Cab 2012 64.83% Dodge Dakota Club Cab 2007 18.29% Dodge Ram Pickup 3500 Quad Cab 2009 10.33% Dodge Dakota Crew Cab 2010 6.31% GMC Canyon Extended Cab 2012 0.19% +1169 /scratch/Teaching/cars/car_ims/014786.jpg Spyker C8 Coupe 2009 Spyker C8 Coupe 2009 60.29% Spyker C8 Convertible 2009 39.36% Audi S5 Convertible 2012 0.2% Bugatti Veyron 16.4 Convertible 2009 0.04% Hyundai Azera Sedan 2012 0.03% +1170 /scratch/Teaching/cars/car_ims/013280.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 53.47% Mercedes-Benz E-Class Sedan 2012 29.32% Audi V8 Sedan 1994 4.74% Mercedes-Benz S-Class Sedan 2012 3.75% Hyundai Genesis Sedan 2012 2.84% +1171 /scratch/Teaching/cars/car_ims/010762.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 99.99% Hyundai Tucson SUV 2012 0.0% Scion xD Hatchback 2012 0.0% Jeep Grand Cherokee SUV 2012 0.0% Hyundai Veracruz SUV 2012 0.0% +1172 /scratch/Teaching/cars/car_ims/015885.jpg Volvo C30 Hatchback 2012 Volvo C30 Hatchback 2012 86.35% BMW 1 Series Coupe 2012 11.77% BMW 3 Series Sedan 2012 0.65% BMW X6 SUV 2012 0.33% Bentley Continental GT Coupe 2012 0.3% +1173 /scratch/Teaching/cars/car_ims/010409.jpg Honda Odyssey Minivan 2012 Hyundai Elantra Sedan 2007 57.96% Honda Odyssey Minivan 2012 41.99% Toyota Corolla Sedan 2012 0.03% Hyundai Sonata Sedan 2012 0.01% Hyundai Veracruz SUV 2012 0.0% +1174 /scratch/Teaching/cars/car_ims/012344.jpg Lamborghini Reventon Coupe 2008 Lamborghini Reventon Coupe 2008 99.92% Lamborghini Aventador Coupe 2012 0.08% McLaren MP4-12C Coupe 2012 0.0% Aston Martin V8 Vantage Coupe 2012 0.0% Mercedes-Benz SL-Class Coupe 2009 0.0% +1175 /scratch/Teaching/cars/car_ims/001648.jpg Audi S5 Convertible 2012 Audi S5 Convertible 2012 77.0% Audi RS 4 Convertible 2008 13.08% BMW 1 Series Convertible 2012 7.29% Audi A5 Coupe 2012 1.9% Audi S5 Coupe 2012 0.68% +1176 /scratch/Teaching/cars/car_ims/005555.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Avalanche Crew Cab 2012 52.2% HUMMER H3T Crew Cab 2010 13.26% Ford Ranger SuperCab 2011 10.35% Mazda Tribute SUV 2011 8.8% Dodge Durango SUV 2007 4.24% +1177 /scratch/Teaching/cars/car_ims/006375.jpg Chrysler 300 SRT-8 2010 Chrysler 300 SRT-8 2010 99.98% Dodge Magnum Wagon 2008 0.02% GMC Yukon Hybrid SUV 2012 0.0% Chevrolet Corvette ZR1 2012 0.0% Dodge Charger SRT-8 2009 0.0% +1178 /scratch/Teaching/cars/car_ims/015238.jpg Tesla Model S Sedan 2012 Tesla Model S Sedan 2012 83.9% Mitsubishi Lancer Sedan 2012 6.62% Hyundai Sonata Hybrid Sedan 2012 5.34% Chevrolet Sonic Sedan 2012 3.94% Hyundai Accent Sedan 2012 0.09% +1179 /scratch/Teaching/cars/car_ims/004215.jpg Cadillac SRX SUV 2012 Cadillac SRX SUV 2012 100.0% GMC Acadia SUV 2012 0.0% Cadillac Escalade EXT Crew Cab 2007 0.0% MINI Cooper Roadster Convertible 2012 0.0% Cadillac CTS-V Sedan 2012 0.0% +1180 /scratch/Teaching/cars/car_ims/001301.jpg Audi 100 Sedan 1994 Audi V8 Sedan 1994 82.59% Audi 100 Sedan 1994 17.4% Mercedes-Benz Sprinter Van 2012 0.01% Volkswagen Golf Hatchback 1991 0.0% Audi 100 Wagon 1994 0.0% +1181 /scratch/Teaching/cars/car_ims/012479.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 Lamborghini Diablo Coupe 2001 99.56% Ford GT Coupe 2006 0.27% Aston Martin Virage Coupe 2012 0.04% McLaren MP4-12C Coupe 2012 0.03% BMW Z4 Convertible 2012 0.02% +1182 /scratch/Teaching/cars/car_ims/011568.jpg Infiniti G Coupe IPL 2012 Jaguar XK XKR 2012 45.43% Acura TSX Sedan 2012 26.93% Acura RL Sedan 2012 13.96% Acura TL Type-S 2008 5.49% Toyota Corolla Sedan 2012 3.74% +1183 /scratch/Teaching/cars/car_ims/010848.jpg Hyundai Tucson SUV 2012 Scion xD Hatchback 2012 99.76% Hyundai Tucson SUV 2012 0.17% Suzuki SX4 Hatchback 2012 0.06% Ford Fiesta Sedan 2012 0.0% Suzuki SX4 Sedan 2012 0.0% +1184 /scratch/Teaching/cars/car_ims/014995.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 100.0% BMW M5 Sedan 2010 0.0% Audi S6 Sedan 2011 0.0% Audi S4 Sedan 2007 0.0% Infiniti G Coupe IPL 2012 0.0% +1185 /scratch/Teaching/cars/car_ims/011881.jpg Jeep Patriot SUV 2012 Jeep Compass SUV 2012 34.34% Jeep Patriot SUV 2012 34.02% Chevrolet TrailBlazer SS 2009 10.78% Dodge Durango SUV 2007 7.5% GMC Yukon Hybrid SUV 2012 4.94% +1186 /scratch/Teaching/cars/car_ims/011410.jpg Hyundai Elantra Touring Hatchback 2012 Hyundai Elantra Touring Hatchback 2012 100.0% Ford Focus Sedan 2007 0.0% Plymouth Neon Coupe 1999 0.0% Chrysler Sebring Convertible 2010 0.0% Mercedes-Benz C-Class Sedan 2012 0.0% +1187 /scratch/Teaching/cars/car_ims/010039.jpg GMC Savana Van 2012 GMC Savana Van 2012 94.88% Chevrolet Express Cargo Van 2007 4.96% Chevrolet Express Van 2007 0.15% Volkswagen Golf Hatchback 1991 0.01% Ford Mustang Convertible 2007 0.0% +1188 /scratch/Teaching/cars/car_ims/013224.jpg Mercedes-Benz 300-Class Convertible 1993 Mercedes-Benz 300-Class Convertible 1993 84.28% Bentley Continental Supersports Conv. Convertible 2012 7.84% BMW M6 Convertible 2010 5.42% Rolls-Royce Phantom Drophead Coupe Convertible 2012 1.96% Audi RS 4 Convertible 2008 0.18% +1189 /scratch/Teaching/cars/car_ims/003997.jpg Buick Enclave SUV 2012 Suzuki Kizashi Sedan 2012 76.67% Chrysler Sebring Convertible 2010 15.48% Buick Enclave SUV 2012 3.98% Ford Focus Sedan 2007 2.87% Volkswagen Golf Hatchback 2012 0.69% +1190 /scratch/Teaching/cars/car_ims/015619.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 86.03% Suzuki Kizashi Sedan 2012 13.03% Audi S6 Sedan 2011 0.46% Hyundai Elantra Touring Hatchback 2012 0.18% BMW M5 Sedan 2010 0.16% +1191 /scratch/Teaching/cars/car_ims/004153.jpg Cadillac SRX SUV 2012 Cadillac SRX SUV 2012 100.0% GMC Acadia SUV 2012 0.0% Buick Enclave SUV 2012 0.0% Toyota Sequoia SUV 2012 0.0% Cadillac Escalade EXT Crew Cab 2007 0.0% +1192 /scratch/Teaching/cars/car_ims/010746.jpg Hyundai Veloster Hatchback 2012 Spyker C8 Coupe 2009 44.37% Hyundai Veloster Hatchback 2012 38.66% Aston Martin Virage Coupe 2012 5.99% HUMMER H3T Crew Cab 2010 4.28% smart fortwo Convertible 2012 2.37% +1193 /scratch/Teaching/cars/car_ims/001152.jpg Audi R8 Coupe 2012 Audi TTS Coupe 2012 75.55% Audi R8 Coupe 2012 19.92% Aston Martin Virage Convertible 2012 2.65% Aston Martin V8 Vantage Convertible 2012 0.74% BMW M6 Convertible 2010 0.46% +1194 /scratch/Teaching/cars/car_ims/013711.jpg Mitsubishi Lancer Sedan 2012 BMW 3 Series Sedan 2012 30.98% Chevrolet Sonic Sedan 2012 16.96% Mercedes-Benz 300-Class Convertible 1993 6.69% BMW Z4 Convertible 2012 5.67% Suzuki Aerio Sedan 2007 5.53% +1195 /scratch/Teaching/cars/car_ims/012074.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 81.75% Jeep Grand Cherokee SUV 2012 9.05% Bentley Arnage Sedan 2009 5.8% Jeep Wrangler SUV 2012 2.37% Rolls-Royce Phantom Sedan 2012 0.72% +1196 /scratch/Teaching/cars/car_ims/006280.jpg Chrysler Town and Country Minivan 2012 Dodge Caliber Wagon 2012 65.93% Dodge Durango SUV 2007 14.87% Dodge Magnum Wagon 2008 13.06% Rolls-Royce Ghost Sedan 2012 2.69% Chevrolet Malibu Sedan 2007 1.35% +1197 /scratch/Teaching/cars/car_ims/005720.jpg Chevrolet Express Van 2007 Chevrolet Express Cargo Van 2007 55.44% GMC Savana Van 2012 28.59% Chevrolet Express Van 2007 15.97% Volkswagen Golf Hatchback 1991 0.0% Audi V8 Sedan 1994 0.0% +1198 /scratch/Teaching/cars/car_ims/012588.jpg Lamborghini Diablo Coupe 2001 Lamborghini Diablo Coupe 2001 98.26% McLaren MP4-12C Coupe 2012 1.31% Hyundai Veloster Hatchback 2012 0.14% Acura Integra Type R 2001 0.1% Spyker C8 Coupe 2009 0.08% +1199 /scratch/Teaching/cars/car_ims/005327.jpg Chevrolet Cobalt SS 2010 Suzuki Kizashi Sedan 2012 92.21% Volkswagen Beetle Hatchback 2012 5.14% Chevrolet Sonic Sedan 2012 1.73% Chevrolet Cobalt SS 2010 0.19% Buick Verano Sedan 2012 0.12% +1200 /scratch/Teaching/cars/car_ims/014640.jpg Scion xD Hatchback 2012 Chevrolet Sonic Sedan 2012 93.37% Volvo C30 Hatchback 2012 1.37% MINI Cooper Roadster Convertible 2012 1.17% Bentley Mulsanne Sedan 2011 0.92% Suzuki Kizashi Sedan 2012 0.64% +1201 /scratch/Teaching/cars/car_ims/004163.jpg Cadillac SRX SUV 2012 Nissan Leaf Hatchback 2012 44.83% Hyundai Tucson SUV 2012 19.05% Nissan Juke Hatchback 2012 14.86% Ford Fiesta Sedan 2012 13.8% Suzuki SX4 Hatchback 2012 2.66% +1202 /scratch/Teaching/cars/car_ims/000148.jpg Acura RL Sedan 2012 Acura TSX Sedan 2012 55.32% Acura TL Sedan 2012 41.07% Acura RL Sedan 2012 3.42% Acura ZDX Hatchback 2012 0.08% BMW Z4 Convertible 2012 0.04% +1203 /scratch/Teaching/cars/car_ims/006869.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2012 83.71% Dodge Caliber Wagon 2007 16.28% Dodge Durango SUV 2012 0.01% BMW 1 Series Convertible 2012 0.0% Ford Mustang Convertible 2007 0.0% +1204 /scratch/Teaching/cars/car_ims/001861.jpg Audi S4 Sedan 2012 Audi S4 Sedan 2012 95.06% Audi A5 Coupe 2012 2.47% Audi S5 Coupe 2012 2.02% Dodge Charger Sedan 2012 0.09% Audi TTS Coupe 2012 0.09% +1205 /scratch/Teaching/cars/car_ims/008282.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 99.75% Ferrari 458 Italia Coupe 2012 0.21% Ferrari FF Coupe 2012 0.03% Chevrolet Corvette Convertible 2012 0.01% Ferrari 458 Italia Convertible 2012 0.0% +1206 /scratch/Teaching/cars/car_ims/000155.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 99.78% Acura TSX Sedan 2012 0.22% Acura RL Sedan 2012 0.01% Toyota Camry Sedan 2012 0.0% Acura TL Type-S 2008 0.0% +1207 /scratch/Teaching/cars/car_ims/004388.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Convertible 2012 99.8% Acura Integra Type R 2001 0.15% BMW Z4 Convertible 2012 0.05% Chevrolet Camaro Convertible 2012 0.0% Dodge Charger Sedan 2012 0.0% +1208 /scratch/Teaching/cars/car_ims/006706.jpg Daewoo Nubira Wagon 2002 Chevrolet Impala Sedan 2007 95.25% Ford Focus Sedan 2007 3.61% Lincoln Town Car Sedan 2011 0.9% Chevrolet Malibu Sedan 2007 0.19% Daewoo Nubira Wagon 2002 0.02% +1209 /scratch/Teaching/cars/car_ims/005698.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 81.43% Chevrolet Express Van 2007 10.88% Chevrolet Express Cargo Van 2007 7.69% Volkswagen Golf Hatchback 1991 0.0% Nissan NV Passenger Van 2012 0.0% +1210 /scratch/Teaching/cars/car_ims/005502.jpg Chevrolet TrailBlazer SS 2009 Dodge Durango SUV 2007 24.93% BMW X6 SUV 2012 12.52% Chrysler Town and Country Minivan 2012 11.93% Chevrolet TrailBlazer SS 2009 10.89% GMC Acadia SUV 2012 6.51% +1211 /scratch/Teaching/cars/car_ims/002873.jpg BMW M6 Convertible 2010 BMW M6 Convertible 2010 59.2% Audi S5 Convertible 2012 40.26% Audi RS 4 Convertible 2008 0.31% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.14% BMW 1 Series Convertible 2012 0.04% +1212 /scratch/Teaching/cars/car_ims/000206.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 99.98% Acura RL Sedan 2012 0.01% Acura TSX Sedan 2012 0.0% Chevrolet Monte Carlo Coupe 2007 0.0% Chevrolet Impala Sedan 2007 0.0% +1213 /scratch/Teaching/cars/car_ims/000956.jpg Audi RS 4 Convertible 2008 Audi RS 4 Convertible 2008 49.13% Dodge Charger Sedan 2012 36.99% BMW Z4 Convertible 2012 7.57% Dodge Challenger SRT8 2011 2.89% Aston Martin Virage Coupe 2012 1.07% +1214 /scratch/Teaching/cars/car_ims/005301.jpg Chevrolet Cobalt SS 2010 Lamborghini Diablo Coupe 2001 98.36% Acura Integra Type R 2001 1.63% Dodge Charger Sedan 2012 0.01% Chevrolet Corvette Convertible 2012 0.0% Ford Mustang Convertible 2007 0.0% +1215 /scratch/Teaching/cars/car_ims/009658.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 63.48% Rolls-Royce Ghost Sedan 2012 18.77% Rolls-Royce Phantom Sedan 2012 17.51% Land Rover Range Rover SUV 2012 0.15% Chrysler 300 SRT-8 2010 0.03% +1216 /scratch/Teaching/cars/car_ims/001969.jpg Audi S4 Sedan 2007 Audi A5 Coupe 2012 90.3% Mitsubishi Lancer Sedan 2012 9.49% Audi S4 Sedan 2007 0.1% Audi TT Hatchback 2011 0.08% Audi R8 Coupe 2012 0.01% +1217 /scratch/Teaching/cars/car_ims/003042.jpg BMW Z4 Convertible 2012 Lamborghini Diablo Coupe 2001 95.78% Spyker C8 Coupe 2009 2.3% Audi RS 4 Convertible 2008 1.28% Dodge Charger Sedan 2012 0.32% Spyker C8 Convertible 2009 0.11% +1218 /scratch/Teaching/cars/car_ims/014243.jpg Porsche Panamera Sedan 2012 Jaguar XK XKR 2012 93.25% Rolls-Royce Ghost Sedan 2012 3.05% Fisker Karma Sedan 2012 3.02% Audi R8 Coupe 2012 0.23% Porsche Panamera Sedan 2012 0.14% +1219 /scratch/Teaching/cars/car_ims/005431.jpg Chevrolet Malibu Hybrid Sedan 2010 Chevrolet Malibu Sedan 2007 99.39% Hyundai Elantra Sedan 2007 0.38% Chevrolet Impala Sedan 2007 0.2% Chevrolet Monte Carlo Coupe 2007 0.03% Chevrolet Malibu Hybrid Sedan 2010 0.0% +1220 /scratch/Teaching/cars/car_ims/002433.jpg BMW 3 Series Wagon 2012 BMW 3 Series Wagon 2012 97.39% BMW 1 Series Coupe 2012 1.22% FIAT 500 Convertible 2012 0.63% Hyundai Veloster Hatchback 2012 0.17% BMW M3 Coupe 2012 0.15% +1221 /scratch/Teaching/cars/car_ims/006663.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 99.2% Volkswagen Golf Hatchback 1991 0.45% Audi 100 Wagon 1994 0.35% Chevrolet Express Van 2007 0.0% BMW X5 SUV 2007 0.0% +1222 /scratch/Teaching/cars/car_ims/007433.jpg Dodge Dakota Club Cab 2007 Dodge Dakota Club Cab 2007 99.07% Dodge Dakota Crew Cab 2010 0.93% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% Isuzu Ascender SUV 2008 0.0% Dodge Durango SUV 2007 0.0% +1223 /scratch/Teaching/cars/car_ims/011964.jpg Jeep Wrangler SUV 2012 HUMMER H2 SUT Crew Cab 2009 34.78% HUMMER H3T Crew Cab 2010 29.62% AM General Hummer SUV 2000 23.72% GMC Canyon Extended Cab 2012 10.78% Ford F-150 Regular Cab 2012 0.39% +1224 /scratch/Teaching/cars/car_ims/012047.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 99.35% Jeep Patriot SUV 2012 0.64% Jeep Compass SUV 2012 0.01% BMW X5 SUV 2007 0.0% Jeep Wrangler SUV 2012 0.0% +1225 /scratch/Teaching/cars/car_ims/008226.jpg Ferrari FF Coupe 2012 Ferrari FF Coupe 2012 86.67% BMW ActiveHybrid 5 Sedan 2012 4.47% BMW M3 Coupe 2012 1.95% Maybach Landaulet Convertible 2012 1.91% BMW M5 Sedan 2010 1.08% +1226 /scratch/Teaching/cars/car_ims/001270.jpg Audi V8 Sedan 1994 Dodge Charger SRT-8 2009 90.37% Dodge Magnum Wagon 2008 4.3% Chevrolet Monte Carlo Coupe 2007 2.66% Chrysler 300 SRT-8 2010 1.15% Mercedes-Benz 300-Class Convertible 1993 0.43% +1227 /scratch/Teaching/cars/car_ims/004621.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 99.83% BMW 3 Series Sedan 2012 0.06% Chevrolet Corvette ZR1 2012 0.04% Acura Integra Type R 2001 0.02% Porsche Panamera Sedan 2012 0.02% +1228 /scratch/Teaching/cars/car_ims/000674.jpg Aston Martin V8 Vantage Coupe 2012 Aston Martin V8 Vantage Coupe 2012 96.94% Aston Martin V8 Vantage Convertible 2012 3.04% Chevrolet Corvette ZR1 2012 0.02% Aston Martin Virage Convertible 2012 0.0% Jaguar XK XKR 2012 0.0% +1229 /scratch/Teaching/cars/car_ims/000047.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 99.97% Jeep Wrangler SUV 2012 0.03% Lamborghini Diablo Coupe 2001 0.0% HUMMER H2 SUT Crew Cab 2009 0.0% Jeep Patriot SUV 2012 0.0% +1230 /scratch/Teaching/cars/car_ims/007641.jpg Dodge Durango SUV 2012 Dodge Charger Sedan 2012 76.6% Dodge Magnum Wagon 2008 14.81% Dodge Charger SRT-8 2009 4.18% Dodge Durango SUV 2012 3.71% Audi A5 Coupe 2012 0.18% +1231 /scratch/Teaching/cars/car_ims/004064.jpg Cadillac CTS-V Sedan 2012 Rolls-Royce Phantom Sedan 2012 99.41% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.31% Volvo 240 Sedan 1993 0.23% Chrysler 300 SRT-8 2010 0.02% Ford GT Coupe 2006 0.02% +1232 /scratch/Teaching/cars/car_ims/011299.jpg Hyundai Sonata Sedan 2012 Chevrolet Malibu Hybrid Sedan 2010 57.45% Hyundai Sonata Sedan 2012 30.72% Acura RL Sedan 2012 10.62% Acura ZDX Hatchback 2012 0.59% Buick Verano Sedan 2012 0.21% +1233 /scratch/Teaching/cars/car_ims/006658.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 68.65% Plymouth Neon Coupe 1999 26.97% Ford Focus Sedan 2007 2.55% Chevrolet Monte Carlo Coupe 2007 0.91% Suzuki Aerio Sedan 2007 0.66% +1234 /scratch/Teaching/cars/car_ims/002584.jpg BMW X5 SUV 2007 Audi R8 Coupe 2012 55.56% Mercedes-Benz SL-Class Coupe 2009 34.43% Porsche Panamera Sedan 2012 3.29% BMW M6 Convertible 2010 1.87% Hyundai Genesis Sedan 2012 1.66% +1235 /scratch/Teaching/cars/car_ims/003177.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental Supersports Conv. Convertible 2012 94.59% Chevrolet Corvette Ron Fellows Edition Z06 2007 3.98% Lamborghini Aventador Coupe 2012 1.13% FIAT 500 Convertible 2012 0.04% Ford GT Coupe 2006 0.04% +1236 /scratch/Teaching/cars/car_ims/011552.jpg Infiniti G Coupe IPL 2012 Hyundai Genesis Sedan 2012 80.58% Infiniti G Coupe IPL 2012 19.26% Hyundai Azera Sedan 2012 0.13% Mercedes-Benz E-Class Sedan 2012 0.01% Suzuki Kizashi Sedan 2012 0.01% +1237 /scratch/Teaching/cars/car_ims/003529.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental GT Coupe 2007 49.33% Bentley Continental Flying Spur Sedan 2007 32.53% Suzuki Aerio Sedan 2007 9.59% Bentley Continental GT Coupe 2012 4.98% Chrysler 300 SRT-8 2010 2.64% +1238 /scratch/Teaching/cars/car_ims/016015.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 97.59% Audi 100 Sedan 1994 1.9% Volkswagen Golf Hatchback 1991 0.35% Ford Ranger SuperCab 2011 0.08% Mercedes-Benz 300-Class Convertible 1993 0.03% +1239 /scratch/Teaching/cars/car_ims/009160.jpg Ford GT Coupe 2006 Chevrolet Corvette ZR1 2012 63.27% AM General Hummer SUV 2000 17.73% Spyker C8 Coupe 2009 13.67% Spyker C8 Convertible 2009 2.88% Ford GT Coupe 2006 0.67% +1240 /scratch/Teaching/cars/car_ims/007978.jpg Eagle Talon Hatchback 1998 Nissan 240SX Coupe 1998 61.88% Eagle Talon Hatchback 1998 28.55% Ford Focus Sedan 2007 7.43% Plymouth Neon Coupe 1999 1.15% Ford Mustang Convertible 2007 0.37% +1241 /scratch/Teaching/cars/car_ims/004731.jpg Chevrolet Camaro Convertible 2012 Chrysler Crossfire Convertible 2008 34.63% Chevrolet Camaro Convertible 2012 29.2% Dodge Charger SRT-8 2009 25.63% Eagle Talon Hatchback 1998 6.29% Mercedes-Benz 300-Class Convertible 1993 1.1% +1242 /scratch/Teaching/cars/car_ims/004773.jpg Chevrolet Camaro Convertible 2012 Chevrolet Camaro Convertible 2012 98.53% Chrysler Crossfire Convertible 2008 0.28% Ferrari 458 Italia Convertible 2012 0.26% Jaguar XK XKR 2012 0.19% Aston Martin Virage Convertible 2012 0.19% +1243 /scratch/Teaching/cars/car_ims/008087.jpg FIAT 500 Abarth 2012 FIAT 500 Abarth 2012 100.0% Spyker C8 Convertible 2009 0.0% HUMMER H3T Crew Cab 2010 0.0% Chevrolet Corvette ZR1 2012 0.0% HUMMER H2 SUT Crew Cab 2009 0.0% +1244 /scratch/Teaching/cars/car_ims/004574.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 93.71% Chevrolet Corvette ZR1 2012 5.1% Chevrolet Corvette Convertible 2012 0.67% Jaguar XK XKR 2012 0.31% Acura Integra Type R 2001 0.12% +1245 /scratch/Teaching/cars/car_ims/008917.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 97.76% Ford F-150 Regular Cab 2012 1.13% GMC Yukon Hybrid SUV 2012 1.07% Chrysler Town and Country Minivan 2012 0.03% Ford F-150 Regular Cab 2007 0.0% +1246 /scratch/Teaching/cars/car_ims/010032.jpg GMC Savana Van 2012 GMC Savana Van 2012 97.99% Chevrolet Express Cargo Van 2007 1.53% Chevrolet Express Van 2007 0.48% Volkswagen Golf Hatchback 1991 0.0% Jeep Patriot SUV 2012 0.0% +1247 /scratch/Teaching/cars/car_ims/009014.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 99.9% Hyundai Santa Fe SUV 2012 0.1% Honda Odyssey Minivan 2012 0.0% Land Rover LR2 SUV 2012 0.0% Toyota 4Runner SUV 2012 0.0% +1248 /scratch/Teaching/cars/car_ims/002645.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 99.96% BMW X3 SUV 2012 0.03% Jeep Compass SUV 2012 0.0% Dodge Caliber Wagon 2007 0.0% Jeep Grand Cherokee SUV 2012 0.0% +1249 /scratch/Teaching/cars/car_ims/008094.jpg FIAT 500 Abarth 2012 FIAT 500 Abarth 2012 99.96% Spyker C8 Convertible 2009 0.02% Hyundai Genesis Sedan 2012 0.01% Audi S5 Convertible 2012 0.0% Audi R8 Coupe 2012 0.0% +1250 /scratch/Teaching/cars/car_ims/009876.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 99.11% BMW X5 SUV 2007 0.38% Jeep Grand Cherokee SUV 2012 0.34% Dodge Journey SUV 2012 0.14% BMW X6 SUV 2012 0.03% +1251 /scratch/Teaching/cars/car_ims/003933.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 76.38% Bentley Continental GT Coupe 2007 7.52% BMW M5 Sedan 2010 6.22% Bentley Continental GT Coupe 2012 3.15% Suzuki Kizashi Sedan 2012 2.14% +1252 /scratch/Teaching/cars/car_ims/001216.jpg Audi V8 Sedan 1994 Audi V8 Sedan 1994 94.49% Audi 100 Sedan 1994 2.42% Audi 100 Wagon 1994 1.67% Volvo 240 Sedan 1993 0.81% Volkswagen Golf Hatchback 1991 0.44% +1253 /scratch/Teaching/cars/car_ims/006426.jpg Chrysler 300 SRT-8 2010 Chevrolet Monte Carlo Coupe 2007 62.74% Chevrolet Impala Sedan 2007 29.78% Chrysler 300 SRT-8 2010 2.3% Chevrolet Malibu Hybrid Sedan 2010 1.98% Chevrolet Malibu Sedan 2007 1.37% +1254 /scratch/Teaching/cars/car_ims/003740.jpg Buick Regal GS 2012 Buick Regal GS 2012 100.0% BMW X3 SUV 2012 0.0% GMC Terrain SUV 2012 0.0% Chevrolet Sonic Sedan 2012 0.0% Buick Verano Sedan 2012 0.0% +1255 /scratch/Teaching/cars/car_ims/000430.jpg Acura Integra Type R 2001 Lamborghini Diablo Coupe 2001 99.3% Chevrolet Corvette Convertible 2012 0.66% Acura Integra Type R 2001 0.03% Ferrari 458 Italia Convertible 2012 0.0% Geo Metro Convertible 1993 0.0% +1256 /scratch/Teaching/cars/car_ims/014909.jpg Suzuki Aerio Sedan 2007 Suzuki Aerio Sedan 2007 99.88% Audi 100 Wagon 1994 0.06% Daewoo Nubira Wagon 2002 0.05% Chrysler PT Cruiser Convertible 2008 0.0% Bentley Continental Flying Spur Sedan 2007 0.0% +1257 /scratch/Teaching/cars/car_ims/014372.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Sedan 2012 95.1% Rolls-Royce Ghost Sedan 2012 4.13% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.57% Maybach Landaulet Convertible 2012 0.21% Volvo 240 Sedan 1993 0.0% +1258 /scratch/Teaching/cars/car_ims/001836.jpg Audi S4 Sedan 2012 Audi S4 Sedan 2012 99.73% Audi S5 Coupe 2012 0.05% BMW M5 Sedan 2010 0.04% BMW 1 Series Coupe 2012 0.04% Acura TSX Sedan 2012 0.03% +1259 /scratch/Teaching/cars/car_ims/010997.jpg Hyundai Veracruz SUV 2012 Jeep Grand Cherokee SUV 2012 42.59% HUMMER H3T Crew Cab 2010 11.39% Mazda Tribute SUV 2011 9.38% BMW X6 SUV 2012 7.73% Chevrolet Traverse SUV 2012 4.99% +1260 /scratch/Teaching/cars/car_ims/004286.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 95.76% Cadillac SRX SUV 2012 2.35% GMC Yukon Hybrid SUV 2012 1.86% Chevrolet Tahoe Hybrid SUV 2012 0.01% GMC Acadia SUV 2012 0.01% +1261 /scratch/Teaching/cars/car_ims/007124.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 99.77% Dodge Ram Pickup 3500 Crew Cab 2010 0.16% Dodge Charger Sedan 2012 0.02% Dodge Dakota Club Cab 2007 0.01% Dodge Durango SUV 2007 0.01% +1262 /scratch/Teaching/cars/car_ims/007215.jpg Dodge Journey SUV 2012 Dodge Journey SUV 2012 86.24% Dodge Caliber Wagon 2007 8.6% Dodge Durango SUV 2012 3.4% Dodge Dakota Crew Cab 2010 1.52% Honda Accord Coupe 2012 0.18% +1263 /scratch/Teaching/cars/car_ims/010212.jpg HUMMER H3T Crew Cab 2010 HUMMER H3T Crew Cab 2010 98.89% HUMMER H2 SUT Crew Cab 2009 1.11% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% Jeep Wrangler SUV 2012 0.0% Jeep Compass SUV 2012 0.0% +1264 /scratch/Teaching/cars/car_ims/001513.jpg Audi TT Hatchback 2011 Hyundai Veloster Hatchback 2012 25.84% Audi R8 Coupe 2012 25.73% Audi TT Hatchback 2011 14.82% Buick Regal GS 2012 9.55% Audi S4 Sedan 2012 5.94% +1265 /scratch/Teaching/cars/car_ims/001712.jpg Audi S5 Convertible 2012 Audi S5 Convertible 2012 99.96% BMW M6 Convertible 2010 0.03% Audi RS 4 Convertible 2008 0.01% BMW 1 Series Convertible 2012 0.0% BMW Z4 Convertible 2012 0.0% +1266 /scratch/Teaching/cars/car_ims/002494.jpg BMW 6 Series Convertible 2007 BMW 6 Series Convertible 2007 72.4% BMW M6 Convertible 2010 22.02% Dodge Charger Sedan 2012 2.61% Audi A5 Coupe 2012 1.9% Jaguar XK XKR 2012 0.51% +1267 /scratch/Teaching/cars/car_ims/008811.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 65.87% Ram C/V Cargo Van Minivan 2012 34.05% Chevrolet Malibu Sedan 2007 0.08% Chrysler Town and Country Minivan 2012 0.0% Chevrolet Impala Sedan 2007 0.0% +1268 /scratch/Teaching/cars/car_ims/010732.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 99.0% Lamborghini Diablo Coupe 2001 0.53% smart fortwo Convertible 2012 0.45% McLaren MP4-12C Coupe 2012 0.0% Spyker C8 Coupe 2009 0.0% +1269 /scratch/Teaching/cars/car_ims/012382.jpg Lamborghini Aventador Coupe 2012 McLaren MP4-12C Coupe 2012 57.9% Chevrolet Corvette Ron Fellows Edition Z06 2007 34.0% Lamborghini Aventador Coupe 2012 7.95% Lamborghini Reventon Coupe 2008 0.14% Aston Martin V8 Vantage Coupe 2012 0.0% +1270 /scratch/Teaching/cars/car_ims/010739.jpg Hyundai Veloster Hatchback 2012 Mitsubishi Lancer Sedan 2012 68.49% Chevrolet Sonic Sedan 2012 21.29% Hyundai Veloster Hatchback 2012 7.5% Suzuki SX4 Sedan 2012 0.7% Toyota Camry Sedan 2012 0.62% +1271 /scratch/Teaching/cars/car_ims/008547.jpg Fisker Karma Sedan 2012 BMW 3 Series Sedan 2012 57.09% BMW Z4 Convertible 2012 25.06% Hyundai Sonata Hybrid Sedan 2012 11.09% Acura RL Sedan 2012 2.0% Jaguar XK XKR 2012 1.2% +1272 /scratch/Teaching/cars/car_ims/003323.jpg Bentley Mulsanne Sedan 2011 Bentley Arnage Sedan 2009 36.54% Bentley Mulsanne Sedan 2011 33.55% Rolls-Royce Phantom Sedan 2012 20.21% BMW ActiveHybrid 5 Sedan 2012 4.55% Bentley Continental Flying Spur Sedan 2007 3.04% +1273 /scratch/Teaching/cars/car_ims/016077.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 59.35% Bentley Arnage Sedan 2009 10.79% BMW 1 Series Coupe 2012 8.93% smart fortwo Convertible 2012 7.23% HUMMER H2 SUT Crew Cab 2009 3.21% +1274 /scratch/Teaching/cars/car_ims/000085.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 100.0% Jeep Wrangler SUV 2012 0.0% HUMMER H2 SUT Crew Cab 2009 0.0% Jeep Patriot SUV 2012 0.0% Lamborghini Diablo Coupe 2001 0.0% +1275 /scratch/Teaching/cars/car_ims/005924.jpg Chevrolet Malibu Sedan 2007 Chevrolet Monte Carlo Coupe 2007 98.16% Chevrolet Impala Sedan 2007 1.14% Chevrolet Malibu Sedan 2007 0.63% Lincoln Town Car Sedan 2011 0.08% Dodge Magnum Wagon 2008 0.0% +1276 /scratch/Teaching/cars/car_ims/003140.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental Supersports Conv. Convertible 2012 100.0% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Bentley Continental GT Coupe 2012 0.0% Bentley Mulsanne Sedan 2011 0.0% Maybach Landaulet Convertible 2012 0.0% +1277 /scratch/Teaching/cars/car_ims/002722.jpg BMW M3 Coupe 2012 Porsche Panamera Sedan 2012 96.35% Audi S6 Sedan 2011 1.3% Jaguar XK XKR 2012 0.81% BMW M5 Sedan 2010 0.49% Audi S5 Convertible 2012 0.4% +1278 /scratch/Teaching/cars/car_ims/013259.jpg Mercedes-Benz C-Class Sedan 2012 Hyundai Genesis Sedan 2012 83.65% Mercedes-Benz C-Class Sedan 2012 10.6% Mercedes-Benz S-Class Sedan 2012 4.14% Chrysler Aspen SUV 2009 0.7% Mercedes-Benz E-Class Sedan 2012 0.4% +1279 /scratch/Teaching/cars/car_ims/011274.jpg Hyundai Genesis Sedan 2012 Hyundai Genesis Sedan 2012 99.99% Honda Odyssey Minivan 2007 0.0% Honda Accord Sedan 2012 0.0% Hyundai Sonata Sedan 2012 0.0% Honda Odyssey Minivan 2012 0.0% +1280 /scratch/Teaching/cars/car_ims/008990.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 97.93% Infiniti QX56 SUV 2011 1.5% Nissan Juke Hatchback 2012 0.24% Mazda Tribute SUV 2011 0.13% Land Rover LR2 SUV 2012 0.04% +1281 /scratch/Teaching/cars/car_ims/003079.jpg BMW Z4 Convertible 2012 BMW 6 Series Convertible 2007 76.64% Acura ZDX Hatchback 2012 10.54% Jaguar XK XKR 2012 4.74% BMW M5 Sedan 2010 2.25% Bugatti Veyron 16.4 Coupe 2009 1.33% +1282 /scratch/Teaching/cars/car_ims/006904.jpg Dodge Caravan Minivan 1997 Plymouth Neon Coupe 1999 90.99% Ford Focus Sedan 2007 5.8% Chevrolet Impala Sedan 2007 1.72% Chevrolet Monte Carlo Coupe 2007 0.65% Dodge Caravan Minivan 1997 0.44% +1283 /scratch/Teaching/cars/car_ims/012720.jpg Land Rover LR2 SUV 2012 Jeep Wrangler SUV 2012 96.56% HUMMER H3T Crew Cab 2010 1.16% HUMMER H2 SUT Crew Cab 2009 0.67% Jeep Compass SUV 2012 0.44% Ford F-150 Regular Cab 2007 0.33% +1284 /scratch/Teaching/cars/car_ims/012469.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 Lamborghini Gallardo LP 570-4 Superleggera 2012 100.0% Hyundai Veloster Hatchback 2012 0.0% Acura Integra Type R 2001 0.0% Bentley Continental Supersports Conv. Convertible 2012 0.0% BMW 6 Series Convertible 2007 0.0% +1285 /scratch/Teaching/cars/car_ims/006501.jpg Chrysler Crossfire Convertible 2008 Chevrolet TrailBlazer SS 2009 93.08% Chrysler Crossfire Convertible 2008 3.32% Dodge Charger SRT-8 2009 1.36% Ford Mustang Convertible 2007 0.81% Audi S5 Convertible 2012 0.8% +1286 /scratch/Teaching/cars/car_ims/009232.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 99.99% Ford F-150 Regular Cab 2007 0.01% Ford Ranger SuperCab 2011 0.0% Volvo XC90 SUV 2007 0.0% GMC Yukon Hybrid SUV 2012 0.0% +1287 /scratch/Teaching/cars/car_ims/001116.jpg Audi TTS Coupe 2012 Dodge Charger Sedan 2012 59.96% Chevrolet Sonic Sedan 2012 29.79% Audi TTS Coupe 2012 4.19% Mitsubishi Lancer Sedan 2012 1.69% Chevrolet TrailBlazer SS 2009 0.76% +1288 /scratch/Teaching/cars/car_ims/012692.jpg Land Rover LR2 SUV 2012 Land Rover LR2 SUV 2012 99.9% Land Rover Range Rover SUV 2012 0.1% Ford Edge SUV 2012 0.0% Ford Expedition EL SUV 2009 0.0% Mazda Tribute SUV 2011 0.0% +1289 /scratch/Teaching/cars/car_ims/002661.jpg BMW X6 SUV 2012 Nissan Juke Hatchback 2012 41.76% Hyundai Veloster Hatchback 2012 22.78% Jeep Grand Cherokee SUV 2012 8.34% Mitsubishi Lancer Sedan 2012 8.08% BMW X6 SUV 2012 4.45% +1290 /scratch/Teaching/cars/car_ims/014596.jpg Scion xD Hatchback 2012 Chevrolet Sonic Sedan 2012 96.71% Scion xD Hatchback 2012 0.91% Suzuki SX4 Hatchback 2012 0.83% Suzuki SX4 Sedan 2012 0.81% Dodge Caliber Wagon 2012 0.44% +1291 /scratch/Teaching/cars/car_ims/008508.jpg Fisker Karma Sedan 2012 Bugatti Veyron 16.4 Coupe 2009 30.33% Audi RS 4 Convertible 2008 14.54% BMW 3 Series Sedan 2012 10.19% Mercedes-Benz 300-Class Convertible 1993 8.94% Fisker Karma Sedan 2012 7.92% +1292 /scratch/Teaching/cars/car_ims/004323.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 94.01% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 5.67% Chevrolet Silverado 1500 Extended Cab 2012 0.17% Chevrolet Silverado 2500HD Regular Cab 2012 0.15% Chevrolet Avalanche Crew Cab 2012 0.0% +1293 /scratch/Teaching/cars/car_ims/014085.jpg Nissan 240SX Coupe 1998 Plymouth Neon Coupe 1999 93.26% Nissan 240SX Coupe 1998 5.44% Eagle Talon Hatchback 1998 0.65% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.17% Acura Integra Type R 2001 0.08% +1294 /scratch/Teaching/cars/car_ims/010191.jpg HUMMER H3T Crew Cab 2010 HUMMER H2 SUT Crew Cab 2009 68.07% HUMMER H3T Crew Cab 2010 22.0% Jeep Compass SUV 2012 6.08% Jeep Liberty SUV 2012 3.0% Jeep Wrangler SUV 2012 0.3% +1295 /scratch/Teaching/cars/car_ims/009119.jpg Ford GT Coupe 2006 Scion xD Hatchback 2012 87.22% Suzuki SX4 Hatchback 2012 5.14% Ford GT Coupe 2006 3.08% Spyker C8 Coupe 2009 3.07% Lamborghini Aventador Coupe 2012 0.62% +1296 /scratch/Teaching/cars/car_ims/002119.jpg BMW ActiveHybrid 5 Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 94.72% Mercedes-Benz S-Class Sedan 2012 4.14% BMW Z4 Convertible 2012 0.45% BMW 6 Series Convertible 2007 0.28% BMW 3 Series Wagon 2012 0.22% +1297 /scratch/Teaching/cars/car_ims/001378.jpg Audi 100 Sedan 1994 Audi 100 Sedan 1994 45.32% Audi 100 Wagon 1994 27.59% BMW 3 Series Sedan 2012 17.62% Mercedes-Benz 300-Class Convertible 1993 7.69% Audi V8 Sedan 1994 1.51% +1298 /scratch/Teaching/cars/car_ims/014277.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 100.0% Chevrolet Malibu Sedan 2007 0.0% Chevrolet Impala Sedan 2007 0.0% Chrysler Town and Country Minivan 2012 0.0% Ford Freestar Minivan 2007 0.0% +1299 /scratch/Teaching/cars/car_ims/001048.jpg Audi TTS Coupe 2012 Audi A5 Coupe 2012 60.69% Audi TTS Coupe 2012 30.02% Acura RL Sedan 2012 4.17% BMW Z4 Convertible 2012 2.84% Audi S5 Coupe 2012 1.82% +1300 /scratch/Teaching/cars/car_ims/011379.jpg Hyundai Elantra Touring Hatchback 2012 Hyundai Elantra Touring Hatchback 2012 100.0% Volkswagen Golf Hatchback 2012 0.0% Ford Fiesta Sedan 2012 0.0% Hyundai Accent Sedan 2012 0.0% Ford Focus Sedan 2007 0.0% +1301 /scratch/Teaching/cars/car_ims/000289.jpg Acura TL Type-S 2008 Jaguar XK XKR 2012 81.25% Honda Accord Coupe 2012 6.52% Nissan 240SX Coupe 1998 5.97% BMW M3 Coupe 2012 1.4% BMW M5 Sedan 2010 1.3% +1302 /scratch/Teaching/cars/car_ims/008798.jpg Ford Freestar Minivan 2007 Audi 100 Wagon 1994 67.98% Volvo 240 Sedan 1993 7.47% Volvo XC90 SUV 2007 5.37% Isuzu Ascender SUV 2008 4.93% Ford Freestar Minivan 2007 4.1% +1303 /scratch/Teaching/cars/car_ims/012540.jpg Lamborghini Diablo Coupe 2001 Lamborghini Diablo Coupe 2001 99.49% Acura Integra Type R 2001 0.4% Ferrari 458 Italia Convertible 2012 0.1% McLaren MP4-12C Coupe 2012 0.01% Chevrolet Corvette Convertible 2012 0.0% +1304 /scratch/Teaching/cars/car_ims/007703.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 99.77% Honda Accord Coupe 2012 0.09% Toyota Camry Sedan 2012 0.06% Jeep Grand Cherokee SUV 2012 0.04% Chevrolet Malibu Sedan 2007 0.02% +1305 /scratch/Teaching/cars/car_ims/012505.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 McLaren MP4-12C Coupe 2012 99.68% Lamborghini Diablo Coupe 2001 0.31% Aston Martin Virage Coupe 2012 0.0% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.0% Lamborghini Aventador Coupe 2012 0.0% +1306 /scratch/Teaching/cars/car_ims/015699.jpg Volkswagen Golf Hatchback 1991 Hyundai Veloster Hatchback 2012 47.86% Ford Fiesta Sedan 2012 35.5% Buick Enclave SUV 2012 6.04% Hyundai Santa Fe SUV 2012 5.09% Hyundai Tucson SUV 2012 1.53% +1307 /scratch/Teaching/cars/car_ims/001763.jpg Audi S5 Coupe 2012 Aston Martin V8 Vantage Coupe 2012 24.44% Audi S4 Sedan 2012 17.13% Honda Accord Coupe 2012 12.2% Audi A5 Coupe 2012 9.38% Audi TTS Coupe 2012 6.35% +1308 /scratch/Teaching/cars/car_ims/013750.jpg Mitsubishi Lancer Sedan 2012 Chevrolet Sonic Sedan 2012 38.25% Mitsubishi Lancer Sedan 2012 31.71% Toyota Corolla Sedan 2012 21.78% Volvo C30 Hatchback 2012 3.84% Hyundai Veloster Hatchback 2012 2.62% +1309 /scratch/Teaching/cars/car_ims/002060.jpg BMW ActiveHybrid 5 Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 80.92% Audi S6 Sedan 2011 7.33% BMW 3 Series Sedan 2012 2.58% Audi S4 Sedan 2007 1.98% Acura RL Sedan 2012 1.22% +1310 /scratch/Teaching/cars/car_ims/008410.jpg Ferrari 458 Italia Convertible 2012 Ferrari 458 Italia Convertible 2012 99.69% Ferrari 458 Italia Coupe 2012 0.31% Ferrari California Convertible 2012 0.0% Chevrolet Corvette Convertible 2012 0.0% Lamborghini Aventador Coupe 2012 0.0% +1311 /scratch/Teaching/cars/car_ims/009147.jpg Ford GT Coupe 2006 Spyker C8 Coupe 2009 42.95% McLaren MP4-12C Coupe 2012 17.87% HUMMER H3T Crew Cab 2010 12.66% Hyundai Veloster Hatchback 2012 9.32% Dodge Charger Sedan 2012 6.3% +1312 /scratch/Teaching/cars/car_ims/011104.jpg Hyundai Elantra Sedan 2007 Hyundai Genesis Sedan 2012 78.2% Infiniti G Coupe IPL 2012 12.34% Hyundai Sonata Sedan 2012 5.54% Honda Accord Sedan 2012 3.04% Toyota Corolla Sedan 2012 0.44% +1313 /scratch/Teaching/cars/car_ims/000769.jpg Aston Martin Virage Convertible 2012 BMW 6 Series Convertible 2007 65.57% BMW M6 Convertible 2010 19.65% Aston Martin Virage Convertible 2012 8.64% Aston Martin V8 Vantage Convertible 2012 5.27% Aston Martin V8 Vantage Coupe 2012 0.31% +1314 /scratch/Teaching/cars/car_ims/014094.jpg Nissan 240SX Coupe 1998 Plymouth Neon Coupe 1999 99.96% Eagle Talon Hatchback 1998 0.02% Audi V8 Sedan 1994 0.01% Ford Mustang Convertible 2007 0.0% Acura Integra Type R 2001 0.0% +1315 /scratch/Teaching/cars/car_ims/011535.jpg Hyundai Azera Sedan 2012 Scion xD Hatchback 2012 33.3% Hyundai Tucson SUV 2012 21.01% Hyundai Sonata Hybrid Sedan 2012 8.42% Hyundai Sonata Sedan 2012 7.05% Ford Edge SUV 2012 6.57% +1316 /scratch/Teaching/cars/car_ims/015564.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 85.46% Infiniti QX56 SUV 2011 9.45% Mazda Tribute SUV 2011 4.22% Dodge Durango SUV 2012 0.34% Toyota Sequoia SUV 2012 0.31% +1317 /scratch/Teaching/cars/car_ims/014217.jpg Porsche Panamera Sedan 2012 Porsche Panamera Sedan 2012 76.59% Audi TTS Coupe 2012 9.22% Audi TT Hatchback 2011 5.39% Audi R8 Coupe 2012 2.56% Tesla Model S Sedan 2012 1.59% +1318 /scratch/Teaching/cars/car_ims/008660.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 90.02% Ford F-150 Regular Cab 2012 9.9% Dodge Ram Pickup 3500 Crew Cab 2010 0.08% Ford E-Series Wagon Van 2012 0.0% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% +1319 /scratch/Teaching/cars/car_ims/011270.jpg Hyundai Genesis Sedan 2012 Hyundai Genesis Sedan 2012 99.94% Hyundai Sonata Sedan 2012 0.06% Hyundai Azera Sedan 2012 0.0% Honda Accord Sedan 2012 0.0% Toyota Corolla Sedan 2012 0.0% +1320 /scratch/Teaching/cars/car_ims/013974.jpg Nissan Juke Hatchback 2012 BMW X6 SUV 2012 76.34% Ford Edge SUV 2012 9.3% Dodge Journey SUV 2012 4.07% Chevrolet Sonic Sedan 2012 2.22% Hyundai Veracruz SUV 2012 1.63% +1321 /scratch/Teaching/cars/car_ims/007285.jpg Dodge Journey SUV 2012 Dodge Journey SUV 2012 100.0% Suzuki SX4 Hatchback 2012 0.0% Dodge Durango SUV 2012 0.0% Suzuki Kizashi Sedan 2012 0.0% BMW M6 Convertible 2010 0.0% +1322 /scratch/Teaching/cars/car_ims/005881.jpg Chevrolet Malibu Sedan 2007 Chevrolet Malibu Sedan 2007 99.33% Chevrolet Monte Carlo Coupe 2007 0.56% Chevrolet Impala Sedan 2007 0.12% Acura TL Type-S 2008 0.0% Hyundai Elantra Sedan 2007 0.0% +1323 /scratch/Teaching/cars/car_ims/002050.jpg Audi TT RS Coupe 2012 Jaguar XK XKR 2012 50.15% Porsche Panamera Sedan 2012 44.23% Acura TL Type-S 2008 1.62% Buick Regal GS 2012 1.19% Audi S4 Sedan 2007 1.0% +1324 /scratch/Teaching/cars/car_ims/000887.jpg Audi RS 4 Convertible 2008 Audi S5 Convertible 2012 56.11% Audi RS 4 Convertible 2008 32.95% BMW M6 Convertible 2010 9.52% Mercedes-Benz 300-Class Convertible 1993 1.36% BMW 1 Series Convertible 2012 0.03% +1325 /scratch/Teaching/cars/car_ims/014762.jpg Spyker C8 Coupe 2009 Spyker C8 Coupe 2009 26.56% Volvo C30 Hatchback 2012 19.87% Chevrolet Camaro Convertible 2012 12.77% BMW Z4 Convertible 2012 12.46% Dodge Charger SRT-8 2009 4.64% +1326 /scratch/Teaching/cars/car_ims/000494.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 76.02% Hyundai Tucson SUV 2012 17.7% Hyundai Veracruz SUV 2012 4.22% Nissan Juke Hatchback 2012 0.68% Hyundai Veloster Hatchback 2012 0.59% +1327 /scratch/Teaching/cars/car_ims/006450.jpg Chrysler Crossfire Convertible 2008 Rolls-Royce Phantom Drophead Coupe Convertible 2012 39.98% Dodge Charger Sedan 2012 37.31% Chevrolet Cobalt SS 2010 5.3% Chrysler Crossfire Convertible 2008 5.25% Chevrolet Tahoe Hybrid SUV 2012 3.17% +1328 /scratch/Teaching/cars/car_ims/010301.jpg HUMMER H2 SUT Crew Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 59.77% HUMMER H2 SUT Crew Cab 2009 22.93% HUMMER H3T Crew Cab 2010 17.13% Jeep Wrangler SUV 2012 0.11% AM General Hummer SUV 2000 0.05% +1329 /scratch/Teaching/cars/car_ims/013990.jpg Nissan Juke Hatchback 2012 BMW 3 Series Sedan 2012 88.92% BMW 1 Series Convertible 2012 5.33% Nissan Juke Hatchback 2012 1.83% BMW 1 Series Coupe 2012 1.17% BMW M6 Convertible 2010 1.02% +1330 /scratch/Teaching/cars/car_ims/004935.jpg Chevrolet Impala Sedan 2007 Chevrolet Impala Sedan 2007 33.11% Acura TSX Sedan 2012 24.81% Acura RL Sedan 2012 9.03% BMW X6 SUV 2012 7.41% Acura ZDX Hatchback 2012 3.65% +1331 /scratch/Teaching/cars/car_ims/013528.jpg Mercedes-Benz S-Class Sedan 2012 Mercedes-Benz S-Class Sedan 2012 99.95% Mercedes-Benz E-Class Sedan 2012 0.04% Mercedes-Benz C-Class Sedan 2012 0.01% Suzuki Kizashi Sedan 2012 0.0% Chrysler Crossfire Convertible 2008 0.0% +1332 /scratch/Teaching/cars/car_ims/007439.jpg Dodge Dakota Club Cab 2007 HUMMER H3T Crew Cab 2010 69.71% Dodge Dakota Club Cab 2007 13.86% Dodge Ram Pickup 3500 Quad Cab 2009 11.43% Ford Ranger SuperCab 2011 2.25% Dodge Ram Pickup 3500 Crew Cab 2010 2.23% +1333 /scratch/Teaching/cars/car_ims/008494.jpg Ferrari 458 Italia Coupe 2012 Chevrolet Corvette Convertible 2012 49.89% Ferrari California Convertible 2012 36.06% Ferrari 458 Italia Coupe 2012 6.45% Ferrari 458 Italia Convertible 2012 5.05% Chevrolet Corvette ZR1 2012 1.6% +1334 /scratch/Teaching/cars/car_ims/008964.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 99.7% Honda Odyssey Minivan 2012 0.24% Hyundai Santa Fe SUV 2012 0.05% Land Rover LR2 SUV 2012 0.0% Hyundai Veracruz SUV 2012 0.0% +1335 /scratch/Teaching/cars/car_ims/000062.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 76.88% HUMMER H2 SUT Crew Cab 2009 21.13% HUMMER H3T Crew Cab 2010 2.0% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% Jeep Wrangler SUV 2012 0.0% +1336 /scratch/Teaching/cars/car_ims/003985.jpg Buick Enclave SUV 2012 Buick Enclave SUV 2012 91.74% Nissan Juke Hatchback 2012 4.83% Buick Verano Sedan 2012 1.68% Acura ZDX Hatchback 2012 0.7% Infiniti QX56 SUV 2011 0.39% +1337 /scratch/Teaching/cars/car_ims/009512.jpg Ford E-Series Wagon Van 2012 Ford E-Series Wagon Van 2012 95.77% GMC Savana Van 2012 4.04% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.15% Ford Ranger SuperCab 2011 0.03% Ford F-150 Regular Cab 2012 0.01% +1338 /scratch/Teaching/cars/car_ims/015320.jpg Toyota Sequoia SUV 2012 Dodge Durango SUV 2012 83.58% Toyota Sequoia SUV 2012 15.26% Hyundai Santa Fe SUV 2012 0.65% Dodge Journey SUV 2012 0.36% Toyota 4Runner SUV 2012 0.09% +1339 /scratch/Teaching/cars/car_ims/002971.jpg BMW X3 SUV 2012 BMW X3 SUV 2012 99.94% BMW X6 SUV 2012 0.05% Suzuki SX4 Hatchback 2012 0.01% Nissan Juke Hatchback 2012 0.0% BMW X5 SUV 2007 0.0% +1340 /scratch/Teaching/cars/car_ims/003780.jpg Buick Regal GS 2012 Buick Regal GS 2012 99.05% Buick Verano Sedan 2012 0.46% Volvo C30 Hatchback 2012 0.33% Ford Edge SUV 2012 0.06% GMC Terrain SUV 2012 0.04% +1341 /scratch/Teaching/cars/car_ims/011908.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 100.0% GMC Yukon Hybrid SUV 2012 0.0% Jeep Compass SUV 2012 0.0% Isuzu Ascender SUV 2008 0.0% Dodge Durango SUV 2007 0.0% +1342 /scratch/Teaching/cars/car_ims/009296.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 99.71% Ford F-150 Regular Cab 2012 0.17% Nissan NV Passenger Van 2012 0.03% GMC Canyon Extended Cab 2012 0.02% Mercedes-Benz 300-Class Convertible 1993 0.02% +1343 /scratch/Teaching/cars/car_ims/014367.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Sedan 2012 59.86% Volvo 240 Sedan 1993 16.97% Bentley Arnage Sedan 2009 13.1% Maybach Landaulet Convertible 2012 3.86% Bentley Mulsanne Sedan 2011 2.99% +1344 /scratch/Teaching/cars/car_ims/012525.jpg Lamborghini Diablo Coupe 2001 Lamborghini Diablo Coupe 2001 99.87% Acura Integra Type R 2001 0.12% Dodge Charger Sedan 2012 0.02% Audi RS 4 Convertible 2008 0.0% Ford GT Coupe 2006 0.0% +1345 /scratch/Teaching/cars/car_ims/003869.jpg Buick Rainier SUV 2007 Chevrolet Tahoe Hybrid SUV 2012 77.66% Volvo XC90 SUV 2007 6.32% Jeep Liberty SUV 2012 3.75% Chrysler Aspen SUV 2009 3.38% Dodge Durango SUV 2007 3.06% +1346 /scratch/Teaching/cars/car_ims/012241.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 100.0% Chevrolet Sonic Sedan 2012 0.0% BMW 1 Series Coupe 2012 0.0% Dodge Charger SRT-8 2009 0.0% Audi A5 Coupe 2012 0.0% +1347 /scratch/Teaching/cars/car_ims/003232.jpg Bentley Arnage Sedan 2009 Bentley Arnage Sedan 2009 96.47% Jeep Compass SUV 2012 1.48% Rolls-Royce Phantom Sedan 2012 1.07% GMC Yukon Hybrid SUV 2012 0.53% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.14% +1348 /scratch/Teaching/cars/car_ims/006218.jpg Chrysler Sebring Convertible 2010 Honda Accord Sedan 2012 85.42% BMW 3 Series Wagon 2012 8.33% Chrysler Sebring Convertible 2010 3.1% Acura TL Type-S 2008 1.02% BMW 6 Series Convertible 2007 0.68% +1349 /scratch/Teaching/cars/car_ims/011792.jpg Jaguar XK XKR 2012 McLaren MP4-12C Coupe 2012 29.75% Spyker C8 Coupe 2009 26.24% Ferrari 458 Italia Convertible 2012 14.19% Ferrari 458 Italia Coupe 2012 9.46% Jaguar XK XKR 2012 9.26% +1350 /scratch/Teaching/cars/car_ims/004319.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 56.87% Chevrolet Avalanche Crew Cab 2012 21.37% Chevrolet Malibu Sedan 2007 8.29% Chevrolet Tahoe Hybrid SUV 2012 6.41% Chrysler Crossfire Convertible 2008 2.49% +1351 /scratch/Teaching/cars/car_ims/012092.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 99.93% Jeep Patriot SUV 2012 0.07% Jeep Wrangler SUV 2012 0.01% BMW X5 SUV 2007 0.0% Jeep Compass SUV 2012 0.0% +1352 /scratch/Teaching/cars/car_ims/015334.jpg Toyota Camry Sedan 2012 Toyota Camry Sedan 2012 98.39% Toyota Corolla Sedan 2012 1.61% Ford Fiesta Sedan 2012 0.0% Hyundai Accent Sedan 2012 0.0% Mitsubishi Lancer Sedan 2012 0.0% +1353 /scratch/Teaching/cars/car_ims/010831.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 100.0% Dodge Durango SUV 2012 0.0% Toyota Sequoia SUV 2012 0.0% Ford Edge SUV 2012 0.0% Chevrolet Traverse SUV 2012 0.0% +1354 /scratch/Teaching/cars/car_ims/009879.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 99.97% Ford F-150 Regular Cab 2007 0.01% Volvo 240 Sedan 1993 0.0% Ford Freestar Minivan 2007 0.0% Volkswagen Golf Hatchback 1991 0.0% +1355 /scratch/Teaching/cars/car_ims/014688.jpg Spyker C8 Convertible 2009 Audi R8 Coupe 2012 83.73% Audi TTS Coupe 2012 11.41% Mercedes-Benz SL-Class Coupe 2009 1.74% Audi TT RS Coupe 2012 0.54% Audi TT Hatchback 2011 0.5% +1356 /scratch/Teaching/cars/car_ims/008883.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 72.97% Cadillac Escalade EXT Crew Cab 2007 11.01% GMC Acadia SUV 2012 10.21% Land Rover LR2 SUV 2012 3.1% Cadillac SRX SUV 2012 1.27% +1357 /scratch/Teaching/cars/car_ims/003755.jpg Buick Regal GS 2012 Buick Regal GS 2012 85.97% Chevrolet Sonic Sedan 2012 9.25% Hyundai Accent Sedan 2012 2.8% Buick Verano Sedan 2012 1.91% Mitsubishi Lancer Sedan 2012 0.07% +1358 /scratch/Teaching/cars/car_ims/013132.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 27.7% Hyundai Veloster Hatchback 2012 11.26% Aston Martin V8 Vantage Coupe 2012 7.31% Maybach Landaulet Convertible 2012 6.52% Land Rover LR2 SUV 2012 5.29% +1359 /scratch/Teaching/cars/car_ims/005564.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 97.72% Chevrolet Silverado 1500 Regular Cab 2012 1.78% Chevrolet Silverado 1500 Extended Cab 2012 0.37% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.1% Chevrolet Avalanche Crew Cab 2012 0.01% +1360 /scratch/Teaching/cars/car_ims/015454.jpg Toyota Corolla Sedan 2012 Toyota Camry Sedan 2012 39.86% Hyundai Azera Sedan 2012 33.19% Hyundai Sonata Sedan 2012 17.24% Honda Accord Sedan 2012 4.64% Ford Fiesta Sedan 2012 1.8% +1361 /scratch/Teaching/cars/car_ims/006504.jpg Chrysler Crossfire Convertible 2008 Rolls-Royce Phantom Drophead Coupe Convertible 2012 90.22% Chrysler Crossfire Convertible 2008 5.87% Rolls-Royce Ghost Sedan 2012 0.95% Mercedes-Benz 300-Class Convertible 1993 0.67% BMW 6 Series Convertible 2007 0.67% +1362 /scratch/Teaching/cars/car_ims/004983.jpg Chevrolet Tahoe Hybrid SUV 2012 HUMMER H3T Crew Cab 2010 62.64% HUMMER H2 SUT Crew Cab 2009 33.37% AM General Hummer SUV 2000 1.22% Dodge Ram Pickup 3500 Quad Cab 2009 0.64% Toyota 4Runner SUV 2012 0.62% +1363 /scratch/Teaching/cars/car_ims/012376.jpg Lamborghini Aventador Coupe 2012 Lamborghini Aventador Coupe 2012 100.0% Spyker C8 Coupe 2009 0.0% McLaren MP4-12C Coupe 2012 0.0% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.0% Hyundai Veloster Hatchback 2012 0.0% +1364 /scratch/Teaching/cars/car_ims/014072.jpg Nissan 240SX Coupe 1998 Hyundai Azera Sedan 2012 18.87% Hyundai Genesis Sedan 2012 13.3% Mercedes-Benz SL-Class Coupe 2009 10.1% Aston Martin Virage Convertible 2012 9.66% Hyundai Sonata Hybrid Sedan 2012 7.14% +1365 /scratch/Teaching/cars/car_ims/014702.jpg Spyker C8 Convertible 2009 Acura ZDX Hatchback 2012 13.16% Jeep Compass SUV 2012 11.72% Ford Mustang Convertible 2007 10.05% BMW X3 SUV 2012 8.7% Audi S5 Convertible 2012 5.21% +1366 /scratch/Teaching/cars/car_ims/002465.jpg BMW 6 Series Convertible 2007 BMW 6 Series Convertible 2007 97.42% BMW M6 Convertible 2010 2.56% Chevrolet Camaro Convertible 2012 0.02% Audi TTS Coupe 2012 0.0% Audi RS 4 Convertible 2008 0.0% +1367 /scratch/Teaching/cars/car_ims/003962.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 99.97% Chevrolet Impala Sedan 2007 0.01% Chevrolet Malibu Sedan 2007 0.01% Suzuki SX4 Sedan 2012 0.0% Acura RL Sedan 2012 0.0% +1368 /scratch/Teaching/cars/car_ims/009088.jpg Ford Ranger SuperCab 2011 Ford Ranger SuperCab 2011 97.59% Volvo 240 Sedan 1993 1.16% Dodge Dakota Club Cab 2007 0.66% Dodge Ram Pickup 3500 Crew Cab 2010 0.5% Ford F-150 Regular Cab 2012 0.03% +1369 /scratch/Teaching/cars/car_ims/011008.jpg Hyundai Veracruz SUV 2012 Hyundai Veracruz SUV 2012 99.94% Suzuki SX4 Sedan 2012 0.03% Scion xD Hatchback 2012 0.03% Chevrolet Traverse SUV 2012 0.01% Honda Odyssey Minivan 2012 0.0% +1370 /scratch/Teaching/cars/car_ims/000220.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 94.61% Acura RL Sedan 2012 1.91% Hyundai Veracruz SUV 2012 0.75% Acura ZDX Hatchback 2012 0.65% Buick Verano Sedan 2012 0.56% +1371 /scratch/Teaching/cars/car_ims/002755.jpg BMW M3 Coupe 2012 Acura TL Type-S 2008 77.73% BMW M3 Coupe 2012 9.74% Audi S4 Sedan 2007 5.9% BMW M5 Sedan 2010 3.38% BMW ActiveHybrid 5 Sedan 2012 2.04% +1372 /scratch/Teaching/cars/car_ims/008438.jpg Ferrari 458 Italia Coupe 2012 Ford GT Coupe 2006 48.07% Bentley Continental GT Coupe 2007 31.06% Ferrari California Convertible 2012 7.68% Ferrari 458 Italia Convertible 2012 1.79% Chevrolet Cobalt SS 2010 1.69% +1373 /scratch/Teaching/cars/car_ims/014284.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 99.96% Suzuki Aerio Sedan 2007 0.03% Chrysler Town and Country Minivan 2012 0.01% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.0% Chevrolet Impala Sedan 2007 0.0% +1374 /scratch/Teaching/cars/car_ims/015029.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 99.78% Suzuki SX4 Sedan 2012 0.21% Dodge Caliber Wagon 2012 0.0% Scion xD Hatchback 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% +1375 /scratch/Teaching/cars/car_ims/002875.jpg BMW M6 Convertible 2010 Spyker C8 Convertible 2009 90.85% AM General Hummer SUV 2000 7.57% Bentley Arnage Sedan 2009 0.66% Lamborghini Diablo Coupe 2001 0.35% Bugatti Veyron 16.4 Coupe 2009 0.14% +1376 /scratch/Teaching/cars/car_ims/010491.jpg Honda Odyssey Minivan 2007 Honda Odyssey Minivan 2007 99.97% Honda Odyssey Minivan 2012 0.01% Toyota Corolla Sedan 2012 0.01% Chevrolet Malibu Sedan 2007 0.0% Honda Accord Sedan 2012 0.0% +1377 /scratch/Teaching/cars/car_ims/001402.jpg Audi 100 Wagon 1994 Ford Mustang Convertible 2007 21.57% Chevrolet Cobalt SS 2010 15.93% Chevrolet Malibu Hybrid Sedan 2010 11.15% Dodge Charger Sedan 2012 9.42% Dodge Journey SUV 2012 6.38% +1378 /scratch/Teaching/cars/car_ims/012673.jpg Land Rover Range Rover SUV 2012 Volvo XC90 SUV 2007 86.47% Land Rover Range Rover SUV 2012 11.28% Land Rover LR2 SUV 2012 0.83% HUMMER H3T Crew Cab 2010 0.81% Dodge Ram Pickup 3500 Crew Cab 2010 0.22% +1379 /scratch/Teaching/cars/car_ims/009875.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 94.05% Buick Enclave SUV 2012 4.96% Mazda Tribute SUV 2011 0.87% Cadillac SRX SUV 2012 0.02% Maybach Landaulet Convertible 2012 0.02% +1380 /scratch/Teaching/cars/car_ims/001290.jpg Audi V8 Sedan 1994 Audi V8 Sedan 1994 99.87% Audi 100 Sedan 1994 0.13% Ford Mustang Convertible 2007 0.0% Volkswagen Golf Hatchback 1991 0.0% Plymouth Neon Coupe 1999 0.0% +1381 /scratch/Teaching/cars/car_ims/002698.jpg BMW X6 SUV 2012 Nissan Juke Hatchback 2012 71.18% FIAT 500 Abarth 2012 12.61% BMW X6 SUV 2012 10.87% Spyker C8 Coupe 2009 1.6% BMW 1 Series Coupe 2012 0.92% +1382 /scratch/Teaching/cars/car_ims/000107.jpg Acura RL Sedan 2012 Acura RL Sedan 2012 96.16% Acura TSX Sedan 2012 2.23% Acura TL Sedan 2012 0.73% Honda Odyssey Minivan 2012 0.34% Audi S4 Sedan 2007 0.06% +1383 /scratch/Teaching/cars/car_ims/002390.jpg BMW 3 Series Wagon 2012 BMW 3 Series Wagon 2012 96.8% BMW ActiveHybrid 5 Sedan 2012 2.48% Acura TL Type-S 2008 0.47% Mercedes-Benz C-Class Sedan 2012 0.2% BMW M5 Sedan 2010 0.02% +1384 /scratch/Teaching/cars/car_ims/009104.jpg Ford Ranger SuperCab 2011 Ford Ranger SuperCab 2011 99.96% Ford Expedition EL SUV 2009 0.04% Ford F-150 Regular Cab 2012 0.0% Ford F-150 Regular Cab 2007 0.0% Isuzu Ascender SUV 2008 0.0% +1385 /scratch/Teaching/cars/car_ims/015276.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 100.0% Toyota 4Runner SUV 2012 0.0% Hyundai Santa Fe SUV 2012 0.0% Ford Expedition EL SUV 2009 0.0% Cadillac SRX SUV 2012 0.0% +1386 /scratch/Teaching/cars/car_ims/005523.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Ford Ranger SuperCab 2011 89.91% Chevrolet Silverado 2500HD Regular Cab 2012 3.35% HUMMER H2 SUT Crew Cab 2009 2.83% Volvo XC90 SUV 2007 0.79% HUMMER H3T Crew Cab 2010 0.69% +1387 /scratch/Teaching/cars/car_ims/011279.jpg Hyundai Genesis Sedan 2012 Hyundai Genesis Sedan 2012 57.02% Infiniti G Coupe IPL 2012 36.03% Dodge Journey SUV 2012 2.62% Chrysler Crossfire Convertible 2008 1.57% BMW M6 Convertible 2010 0.91% +1388 /scratch/Teaching/cars/car_ims/004537.jpg Chevrolet Corvette ZR1 2012 Nissan Leaf Hatchback 2012 95.95% Chevrolet Corvette ZR1 2012 2.24% Jaguar XK XKR 2012 1.11% Porsche Panamera Sedan 2012 0.28% Suzuki Kizashi Sedan 2012 0.27% +1389 /scratch/Teaching/cars/car_ims/003789.jpg Buick Regal GS 2012 Buick Regal GS 2012 66.0% Ford Edge SUV 2012 31.02% Audi TTS Coupe 2012 1.21% Jaguar XK XKR 2012 0.47% GMC Terrain SUV 2012 0.47% +1390 /scratch/Teaching/cars/car_ims/014512.jpg Rolls-Royce Phantom Sedan 2012 Rolls-Royce Phantom Sedan 2012 97.13% Land Rover Range Rover SUV 2012 2.19% Rolls-Royce Ghost Sedan 2012 0.21% Honda Odyssey Minivan 2012 0.2% Bentley Arnage Sedan 2009 0.16% +1391 /scratch/Teaching/cars/car_ims/015459.jpg Toyota Corolla Sedan 2012 Hyundai Elantra Sedan 2007 65.77% Toyota Corolla Sedan 2012 30.12% Chrysler Sebring Convertible 2010 2.13% Honda Accord Sedan 2012 0.57% Honda Odyssey Minivan 2012 0.47% +1392 /scratch/Teaching/cars/car_ims/008952.jpg Ford Edge SUV 2012 Hyundai Sonata Hybrid Sedan 2012 98.2% Buick Regal GS 2012 1.75% Hyundai Azera Sedan 2012 0.03% Infiniti G Coupe IPL 2012 0.01% Toyota Camry Sedan 2012 0.0% +1393 /scratch/Teaching/cars/car_ims/011166.jpg Hyundai Accent Sedan 2012 Maybach Landaulet Convertible 2012 60.98% Dodge Caliber Wagon 2012 17.13% BMW M5 Sedan 2010 6.34% Bentley Continental Flying Spur Sedan 2007 6.29% Chevrolet Sonic Sedan 2012 4.14% +1394 /scratch/Teaching/cars/car_ims/007727.jpg Dodge Durango SUV 2007 Jeep Patriot SUV 2012 98.34% Jeep Liberty SUV 2012 1.15% Chrysler Aspen SUV 2009 0.33% Dodge Durango SUV 2007 0.08% Isuzu Ascender SUV 2008 0.06% +1395 /scratch/Teaching/cars/car_ims/005110.jpg Chevrolet Sonic Sedan 2012 Chevrolet Sonic Sedan 2012 84.97% Dodge Caliber Wagon 2012 5.43% Daewoo Nubira Wagon 2002 3.35% Scion xD Hatchback 2012 2.47% Ford Focus Sedan 2007 0.93% +1396 /scratch/Teaching/cars/car_ims/012339.jpg Lamborghini Reventon Coupe 2008 Lamborghini Aventador Coupe 2012 52.91% Audi R8 Coupe 2012 21.79% Spyker C8 Convertible 2009 11.07% Bugatti Veyron 16.4 Coupe 2009 4.62% Bugatti Veyron 16.4 Convertible 2009 4.62% +1397 /scratch/Teaching/cars/car_ims/006699.jpg Daewoo Nubira Wagon 2002 BMW Z4 Convertible 2012 34.47% BMW M6 Convertible 2010 16.05% Audi RS 4 Convertible 2008 8.15% Acura TL Sedan 2012 7.9% Aston Martin V8 Vantage Coupe 2012 6.14% +1398 /scratch/Teaching/cars/car_ims/008420.jpg Ferrari 458 Italia Coupe 2012 Ferrari 458 Italia Coupe 2012 47.77% Ford GT Coupe 2006 36.43% Aston Martin V8 Vantage Coupe 2012 13.45% Spyker C8 Coupe 2009 1.43% Ferrari FF Coupe 2012 0.58% +1399 /scratch/Teaching/cars/car_ims/010390.jpg Honda Odyssey Minivan 2012 Hyundai Sonata Sedan 2012 71.98% Honda Odyssey Minivan 2012 24.11% Hyundai Azera Sedan 2012 3.85% Hyundai Sonata Hybrid Sedan 2012 0.02% Hyundai Elantra Sedan 2007 0.02% +1400 /scratch/Teaching/cars/car_ims/014792.jpg Spyker C8 Coupe 2009 Spyker C8 Coupe 2009 99.33% Lamborghini Aventador Coupe 2012 0.46% Spyker C8 Convertible 2009 0.21% Bugatti Veyron 16.4 Coupe 2009 0.0% Bugatti Veyron 16.4 Convertible 2009 0.0% +1401 /scratch/Teaching/cars/car_ims/000454.jpg Acura Integra Type R 2001 Acura Integra Type R 2001 99.98% BMW 3 Series Sedan 2012 0.01% Nissan 240SX Coupe 1998 0.0% Audi 100 Sedan 1994 0.0% Daewoo Nubira Wagon 2002 0.0% +1402 /scratch/Teaching/cars/car_ims/010181.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 100.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Chevrolet Corvette Convertible 2012 0.0% Chrysler PT Cruiser Convertible 2008 0.0% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% +1403 /scratch/Teaching/cars/car_ims/005233.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 97.18% Chevrolet Tahoe Hybrid SUV 2012 2.81% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% Isuzu Ascender SUV 2008 0.0% Chevrolet Silverado 1500 Extended Cab 2012 0.0% +1404 /scratch/Teaching/cars/car_ims/015663.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 99.97% Acura Integra Type R 2001 0.03% Suzuki SX4 Hatchback 2012 0.0% FIAT 500 Convertible 2012 0.0% Suzuki Aerio Sedan 2007 0.0% +1405 /scratch/Teaching/cars/car_ims/008991.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 100.0% Hyundai Santa Fe SUV 2012 0.0% Hyundai Accent Sedan 2012 0.0% Honda Odyssey Minivan 2012 0.0% Hyundai Tucson SUV 2012 0.0% +1406 /scratch/Teaching/cars/car_ims/001612.jpg Audi S6 Sedan 2011 Audi S6 Sedan 2011 99.95% Audi S4 Sedan 2007 0.05% Audi RS 4 Convertible 2008 0.0% Audi S5 Convertible 2012 0.0% Audi S4 Sedan 2012 0.0% +1407 /scratch/Teaching/cars/car_ims/001454.jpg Audi 100 Wagon 1994 Dodge Magnum Wagon 2008 99.94% Chevrolet Malibu Sedan 2007 0.04% Mercedes-Benz 300-Class Convertible 1993 0.02% Dodge Caliber Wagon 2012 0.0% Chrysler Sebring Convertible 2010 0.0% +1408 /scratch/Teaching/cars/car_ims/010958.jpg Hyundai Veracruz SUV 2012 Acura ZDX Hatchback 2012 40.33% Hyundai Tucson SUV 2012 27.05% Acura TL Sedan 2012 15.2% Hyundai Veracruz SUV 2012 8.37% Nissan Juke Hatchback 2012 4.42% +1409 /scratch/Teaching/cars/car_ims/001015.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 99.49% Audi S5 Coupe 2012 0.29% Audi S5 Convertible 2012 0.22% Audi S4 Sedan 2012 0.0% Audi TT Hatchback 2011 0.0% +1410 /scratch/Teaching/cars/car_ims/007609.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 99.3% Bugatti Veyron 16.4 Coupe 2009 0.41% Jaguar XK XKR 2012 0.21% Audi S4 Sedan 2007 0.04% Dodge Charger Sedan 2012 0.01% +1411 /scratch/Teaching/cars/car_ims/014554.jpg Rolls-Royce Phantom Sedan 2012 Rolls-Royce Phantom Sedan 2012 95.86% Rolls-Royce Ghost Sedan 2012 3.81% Dodge Charger SRT-8 2009 0.29% Bentley Arnage Sedan 2009 0.02% Chevrolet Sonic Sedan 2012 0.01% +1412 /scratch/Teaching/cars/car_ims/015356.jpg Toyota Camry Sedan 2012 Acura TSX Sedan 2012 32.43% Honda Odyssey Minivan 2007 17.61% Toyota Corolla Sedan 2012 10.26% Toyota Camry Sedan 2012 9.16% Honda Accord Sedan 2012 7.72% +1413 /scratch/Teaching/cars/car_ims/011019.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 98.89% Chevrolet Sonic Sedan 2012 0.26% Toyota Camry Sedan 2012 0.25% Honda Accord Sedan 2012 0.13% Hyundai Accent Sedan 2012 0.13% +1414 /scratch/Teaching/cars/car_ims/012852.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 99.99% Mercedes-Benz 300-Class Convertible 1993 0.01% Audi 100 Sedan 1994 0.0% Chevrolet Malibu Sedan 2007 0.0% Audi 100 Wagon 1994 0.0% +1415 /scratch/Teaching/cars/car_ims/005882.jpg Chevrolet Malibu Sedan 2007 Chevrolet Malibu Sedan 2007 99.68% Chevrolet Monte Carlo Coupe 2007 0.27% Chevrolet Impala Sedan 2007 0.03% Lincoln Town Car Sedan 2011 0.02% Hyundai Elantra Sedan 2007 0.0% +1416 /scratch/Teaching/cars/car_ims/002331.jpg BMW 3 Series Sedan 2012 BMW 3 Series Sedan 2012 40.46% Fisker Karma Sedan 2012 29.32% Dodge Charger SRT-8 2009 6.04% Audi S5 Convertible 2012 5.41% Audi S4 Sedan 2012 2.34% +1417 /scratch/Teaching/cars/car_ims/008134.jpg FIAT 500 Convertible 2012 Chrysler PT Cruiser Convertible 2008 98.46% smart fortwo Convertible 2012 0.86% MINI Cooper Roadster Convertible 2012 0.5% Land Rover LR2 SUV 2012 0.09% Land Rover Range Rover SUV 2012 0.06% +1418 /scratch/Teaching/cars/car_ims/012487.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 Lamborghini Gallardo LP 570-4 Superleggera 2012 99.74% Lamborghini Diablo Coupe 2001 0.24% Chevrolet Corvette Convertible 2012 0.0% Hyundai Veloster Hatchback 2012 0.0% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% +1419 /scratch/Teaching/cars/car_ims/005011.jpg Chevrolet Tahoe Hybrid SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 57.48% Chevrolet Avalanche Crew Cab 2012 42.52% Isuzu Ascender SUV 2008 0.01% Dodge Dakota Crew Cab 2010 0.0% Chevrolet Silverado 1500 Extended Cab 2012 0.0% +1420 /scratch/Teaching/cars/car_ims/004372.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 84.92% Chevrolet Silverado 1500 Regular Cab 2012 11.65% Chevrolet Silverado 1500 Extended Cab 2012 3.35% Dodge Dakota Club Cab 2007 0.03% Chevrolet Avalanche Crew Cab 2012 0.02% +1421 /scratch/Teaching/cars/car_ims/000857.jpg Aston Martin Virage Coupe 2012 Aston Martin Virage Coupe 2012 99.98% Hyundai Veloster Hatchback 2012 0.01% Lamborghini Diablo Coupe 2001 0.01% Spyker C8 Coupe 2009 0.0% McLaren MP4-12C Coupe 2012 0.0% +1422 /scratch/Teaching/cars/car_ims/001844.jpg Audi S4 Sedan 2012 Acura RL Sedan 2012 79.78% Acura TSX Sedan 2012 16.22% BMW ActiveHybrid 5 Sedan 2012 1.93% Mercedes-Benz E-Class Sedan 2012 0.88% Honda Accord Sedan 2012 0.59% +1423 /scratch/Teaching/cars/car_ims/009420.jpg Ford Focus Sedan 2007 Audi S4 Sedan 2007 54.31% Suzuki SX4 Sedan 2012 21.79% Chevrolet Cobalt SS 2010 13.54% Chevrolet Monte Carlo Coupe 2007 9.46% Dodge Caravan Minivan 1997 0.3% +1424 /scratch/Teaching/cars/car_ims/003218.jpg Bentley Arnage Sedan 2009 Volvo 240 Sedan 1993 52.88% BMW 3 Series Sedan 2012 28.88% Bentley Arnage Sedan 2009 8.33% Volkswagen Golf Hatchback 1991 5.79% Audi 100 Wagon 1994 2.09% +1425 /scratch/Teaching/cars/car_ims/009866.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 98.99% Buick Enclave SUV 2012 0.97% Mazda Tribute SUV 2011 0.02% BMW X3 SUV 2012 0.01% BMW X5 SUV 2007 0.0% +1426 /scratch/Teaching/cars/car_ims/009886.jpg GMC Acadia SUV 2012 BMW X6 SUV 2012 53.26% Dodge Durango SUV 2012 31.72% Dodge Journey SUV 2012 9.33% Jeep Compass SUV 2012 1.2% Dodge Caliber Wagon 2007 1.06% +1427 /scratch/Teaching/cars/car_ims/003624.jpg Bugatti Veyron 16.4 Convertible 2009 Bentley Continental GT Coupe 2007 43.44% Hyundai Veloster Hatchback 2012 11.59% Fisker Karma Sedan 2012 6.13% Ford GT Coupe 2006 6.02% Chevrolet Corvette Ron Fellows Edition Z06 2007 5.17% +1428 /scratch/Teaching/cars/car_ims/008311.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 99.0% Ferrari 458 Italia Convertible 2012 0.78% Ferrari 458 Italia Coupe 2012 0.14% Aston Martin V8 Vantage Convertible 2012 0.06% Ferrari FF Coupe 2012 0.02% +1429 /scratch/Teaching/cars/car_ims/014188.jpg Porsche Panamera Sedan 2012 Tesla Model S Sedan 2012 41.64% Porsche Panamera Sedan 2012 17.77% Audi TTS Coupe 2012 15.53% Fisker Karma Sedan 2012 11.95% Aston Martin Virage Convertible 2012 3.32% +1430 /scratch/Teaching/cars/car_ims/008213.jpg Ferrari FF Coupe 2012 BMW M5 Sedan 2010 68.49% Mercedes-Benz SL-Class Coupe 2009 9.07% Chrysler 300 SRT-8 2010 7.49% Porsche Panamera Sedan 2012 4.04% BMW M3 Coupe 2012 1.65% +1431 /scratch/Teaching/cars/car_ims/011930.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 100.0% Volvo XC90 SUV 2007 0.0% GMC Yukon Hybrid SUV 2012 0.0% Jeep Liberty SUV 2012 0.0% Jeep Compass SUV 2012 0.0% +1432 /scratch/Teaching/cars/car_ims/006592.jpg Chrysler PT Cruiser Convertible 2008 Chevrolet Camaro Convertible 2012 43.32% Chrysler Crossfire Convertible 2008 36.09% Audi S5 Convertible 2012 16.31% Chevrolet Corvette Convertible 2012 2.01% Audi RS 4 Convertible 2008 0.78% +1433 /scratch/Teaching/cars/car_ims/002670.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 97.9% Jeep Compass SUV 2012 1.24% BMW X3 SUV 2012 0.26% BMW X5 SUV 2007 0.13% Dodge Caliber Wagon 2007 0.13% +1434 /scratch/Teaching/cars/car_ims/012748.jpg Land Rover LR2 SUV 2012 Land Rover Range Rover SUV 2012 59.23% Land Rover LR2 SUV 2012 25.21% Toyota 4Runner SUV 2012 7.78% GMC Terrain SUV 2012 2.63% GMC Canyon Extended Cab 2012 2.26% +1435 /scratch/Teaching/cars/car_ims/014923.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 92.69% Suzuki SX4 Sedan 2012 6.94% Buick Verano Sedan 2012 0.18% Acura ZDX Hatchback 2012 0.07% Mitsubishi Lancer Sedan 2012 0.06% +1436 /scratch/Teaching/cars/car_ims/004479.jpg Chevrolet Corvette ZR1 2012 Chevrolet Corvette Convertible 2012 99.66% Chevrolet Monte Carlo Coupe 2007 0.2% Dodge Charger SRT-8 2009 0.07% Chevrolet Corvette ZR1 2012 0.03% Ford GT Coupe 2006 0.02% +1437 /scratch/Teaching/cars/car_ims/011339.jpg Hyundai Sonata Sedan 2012 Suzuki SX4 Hatchback 2012 72.83% Dodge Caliber Wagon 2012 20.01% Dodge Journey SUV 2012 6.54% Acura RL Sedan 2012 0.16% Volvo C30 Hatchback 2012 0.15% +1438 /scratch/Teaching/cars/car_ims/012004.jpg Jeep Wrangler SUV 2012 Jeep Wrangler SUV 2012 99.88% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.09% Chevrolet Silverado 1500 Extended Cab 2012 0.01% AM General Hummer SUV 2000 0.01% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.0% +1439 /scratch/Teaching/cars/car_ims/015148.jpg Suzuki SX4 Sedan 2012 Suzuki Aerio Sedan 2007 66.35% Suzuki SX4 Sedan 2012 25.03% Suzuki SX4 Hatchback 2012 8.6% Honda Odyssey Minivan 2007 0.01% Chevrolet Malibu Sedan 2007 0.01% +1440 /scratch/Teaching/cars/car_ims/002682.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 99.98% BMW X5 SUV 2007 0.02% BMW 1 Series Convertible 2012 0.0% BMW X3 SUV 2012 0.0% BMW 1 Series Coupe 2012 0.0% +1441 /scratch/Teaching/cars/car_ims/012905.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 95.99% Rolls-Royce Phantom Drophead Coupe Convertible 2012 1.42% BMW M6 Convertible 2010 0.93% BMW 6 Series Convertible 2007 0.64% Jaguar XK XKR 2012 0.38% +1442 /scratch/Teaching/cars/car_ims/009970.jpg GMC Canyon Extended Cab 2012 GMC Canyon Extended Cab 2012 96.87% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 2.74% Chevrolet Avalanche Crew Cab 2012 0.16% HUMMER H3T Crew Cab 2010 0.13% Chevrolet Silverado 1500 Extended Cab 2012 0.06% +1443 /scratch/Teaching/cars/car_ims/006480.jpg Chrysler Crossfire Convertible 2008 Chrysler Crossfire Convertible 2008 99.11% Chrysler Sebring Convertible 2010 0.88% Hyundai Genesis Sedan 2012 0.0% Chevrolet Cobalt SS 2010 0.0% Mercedes-Benz C-Class Sedan 2012 0.0% +1444 /scratch/Teaching/cars/car_ims/000325.jpg Acura TSX Sedan 2012 Acura TSX Sedan 2012 99.87% Toyota Camry Sedan 2012 0.09% Honda Accord Coupe 2012 0.04% Toyota Corolla Sedan 2012 0.0% Mitsubishi Lancer Sedan 2012 0.0% +1445 /scratch/Teaching/cars/car_ims/000405.jpg Acura Integra Type R 2001 Chevrolet Corvette Convertible 2012 37.04% Acura Integra Type R 2001 30.38% Dodge Charger Sedan 2012 15.62% Lamborghini Diablo Coupe 2001 13.91% Audi RS 4 Convertible 2008 1.43% +1446 /scratch/Teaching/cars/car_ims/014665.jpg Scion xD Hatchback 2012 Scion xD Hatchback 2012 64.63% Chevrolet Sonic Sedan 2012 16.88% Buick Verano Sedan 2012 6.28% Dodge Journey SUV 2012 3.38% Ford Edge SUV 2012 3.17% +1447 /scratch/Teaching/cars/car_ims/006913.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 96.49% Lincoln Town Car Sedan 2011 3.07% Audi 100 Wagon 1994 0.35% Ford Freestar Minivan 2007 0.06% Ford Ranger SuperCab 2011 0.01% +1448 /scratch/Teaching/cars/car_ims/013848.jpg Nissan NV Passenger Van 2012 Volvo 240 Sedan 1993 86.66% Nissan NV Passenger Van 2012 8.91% Volkswagen Golf Hatchback 1991 2.07% Ford F-150 Regular Cab 2007 0.77% Jeep Patriot SUV 2012 0.66% +1449 /scratch/Teaching/cars/car_ims/012668.jpg Land Rover Range Rover SUV 2012 Chevrolet TrailBlazer SS 2009 60.51% Land Rover Range Rover SUV 2012 37.67% Land Rover LR2 SUV 2012 1.76% Chevrolet Tahoe Hybrid SUV 2012 0.02% Volvo XC90 SUV 2007 0.01% +1450 /scratch/Teaching/cars/car_ims/015840.jpg Volkswagen Beetle Hatchback 2012 Volkswagen Beetle Hatchback 2012 99.87% Ford GT Coupe 2006 0.13% Bentley Continental GT Coupe 2007 0.0% Chevrolet Corvette ZR1 2012 0.0% Volvo C30 Hatchback 2012 0.0% +1451 /scratch/Teaching/cars/car_ims/008207.jpg Ferrari FF Coupe 2012 Ferrari FF Coupe 2012 96.67% BMW 3 Series Sedan 2012 3.23% Chevrolet Sonic Sedan 2012 0.04% Ford Mustang Convertible 2007 0.03% Dodge Charger Sedan 2012 0.02% +1452 /scratch/Teaching/cars/car_ims/009360.jpg Ford F-150 Regular Cab 2007 Jeep Grand Cherokee SUV 2012 64.55% Cadillac Escalade EXT Crew Cab 2007 26.28% Chevrolet Tahoe Hybrid SUV 2012 2.52% Isuzu Ascender SUV 2008 2.34% Jeep Compass SUV 2012 1.08% +1453 /scratch/Teaching/cars/car_ims/003473.jpg Bentley Continental GT Coupe 2007 Bentley Continental GT Coupe 2007 100.0% Bentley Continental GT Coupe 2012 0.0% BMW 1 Series Coupe 2012 0.0% Buick Verano Sedan 2012 0.0% Bentley Continental Flying Spur Sedan 2007 0.0% +1454 /scratch/Teaching/cars/car_ims/003444.jpg Bentley Continental GT Coupe 2007 Bentley Continental Flying Spur Sedan 2007 95.69% Chevrolet Monte Carlo Coupe 2007 3.05% Bentley Continental GT Coupe 2007 0.48% Dodge Challenger SRT8 2011 0.33% Bentley Continental GT Coupe 2012 0.17% +1455 /scratch/Teaching/cars/car_ims/004542.jpg Chevrolet Corvette ZR1 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 48.42% Chevrolet Corvette Convertible 2012 18.12% Bentley Continental Supersports Conv. Convertible 2012 12.28% Chevrolet Corvette Ron Fellows Edition Z06 2007 5.98% Jaguar XK XKR 2012 2.94% +1456 /scratch/Teaching/cars/car_ims/013201.jpg Mercedes-Benz 300-Class Convertible 1993 Dodge Caliber Wagon 2007 46.59% Dodge Caliber Wagon 2012 21.83% Dodge Charger SRT-8 2009 14.85% Volvo C30 Hatchback 2012 8.38% Hyundai Elantra Sedan 2007 3.19% +1457 /scratch/Teaching/cars/car_ims/014143.jpg Plymouth Neon Coupe 1999 Plymouth Neon Coupe 1999 48.31% Dodge Journey SUV 2012 32.94% Buick Rainier SUV 2007 9.72% Ford Focus Sedan 2007 3.54% Hyundai Elantra Touring Hatchback 2012 2.45% +1458 /scratch/Teaching/cars/car_ims/016125.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 52.99% Hyundai Veloster Hatchback 2012 37.62% Ford Fiesta Sedan 2012 1.57% Spyker C8 Convertible 2009 1.52% Volkswagen Golf Hatchback 2012 1.26% +1459 /scratch/Teaching/cars/car_ims/015945.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 99.81% Volkswagen Golf Hatchback 1991 0.14% Rolls-Royce Phantom Sedan 2012 0.03% Audi V8 Sedan 1994 0.01% Volvo XC90 SUV 2007 0.01% +1460 /scratch/Teaching/cars/car_ims/011783.jpg Jaguar XK XKR 2012 Bugatti Veyron 16.4 Coupe 2009 91.5% Dodge Challenger SRT8 2011 3.09% Jaguar XK XKR 2012 2.34% Mercedes-Benz SL-Class Coupe 2009 1.35% Dodge Charger Sedan 2012 0.72% +1461 /scratch/Teaching/cars/car_ims/007800.jpg Dodge Charger Sedan 2012 Lamborghini Diablo Coupe 2001 53.89% Dodge Charger Sedan 2012 24.76% Chevrolet Cobalt SS 2010 10.95% Hyundai Veloster Hatchback 2012 4.46% Lamborghini Gallardo LP 570-4 Superleggera 2012 1.77% +1462 /scratch/Teaching/cars/car_ims/002900.jpg BMW M6 Convertible 2010 Jaguar XK XKR 2012 71.23% BMW M6 Convertible 2010 15.41% BMW Z4 Convertible 2012 6.2% BMW 6 Series Convertible 2007 5.48% Aston Martin V8 Vantage Convertible 2012 0.46% +1463 /scratch/Teaching/cars/car_ims/007606.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 97.23% Dodge Charger SRT-8 2009 2.77% Chrysler 300 SRT-8 2010 0.0% Nissan 240SX Coupe 1998 0.0% Aston Martin V8 Vantage Convertible 2012 0.0% +1464 /scratch/Teaching/cars/car_ims/012979.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 99.5% Rolls-Royce Phantom Sedan 2012 0.47% Mercedes-Benz S-Class Sedan 2012 0.02% FIAT 500 Convertible 2012 0.0% Chrysler Sebring Convertible 2010 0.0% +1465 /scratch/Teaching/cars/car_ims/009732.jpg GMC Savana Van 2012 GMC Savana Van 2012 96.68% Nissan NV Passenger Van 2012 1.67% Chevrolet Express Van 2007 0.7% Buick Rainier SUV 2007 0.64% Jeep Patriot SUV 2012 0.21% +1466 /scratch/Teaching/cars/car_ims/011633.jpg Infiniti QX56 SUV 2011 Infiniti QX56 SUV 2011 96.98% Dodge Durango SUV 2012 2.95% Land Rover LR2 SUV 2012 0.02% Ford Edge SUV 2012 0.02% BMW X3 SUV 2012 0.01% +1467 /scratch/Teaching/cars/car_ims/013761.jpg Nissan Leaf Hatchback 2012 Acura Integra Type R 2001 36.86% Bentley Mulsanne Sedan 2011 34.44% Rolls-Royce Phantom Drophead Coupe Convertible 2012 14.79% Dodge Challenger SRT8 2011 3.29% Nissan Leaf Hatchback 2012 2.0% +1468 /scratch/Teaching/cars/car_ims/004228.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 99.92% Chevrolet Tahoe Hybrid SUV 2012 0.07% GMC Yukon Hybrid SUV 2012 0.0% Cadillac SRX SUV 2012 0.0% Ford Freestar Minivan 2007 0.0% +1469 /scratch/Teaching/cars/car_ims/011529.jpg Hyundai Azera Sedan 2012 Hyundai Azera Sedan 2012 99.63% Hyundai Genesis Sedan 2012 0.27% Hyundai Sonata Sedan 2012 0.08% Infiniti G Coupe IPL 2012 0.01% Chrysler Crossfire Convertible 2008 0.0% +1470 /scratch/Teaching/cars/car_ims/011960.jpg Jeep Wrangler SUV 2012 Jeep Wrangler SUV 2012 100.0% HUMMER H3T Crew Cab 2010 0.0% Jeep Patriot SUV 2012 0.0% AM General Hummer SUV 2000 0.0% Jeep Compass SUV 2012 0.0% +1471 /scratch/Teaching/cars/car_ims/015080.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 99.96% Suzuki SX4 Sedan 2012 0.03% Scion xD Hatchback 2012 0.0% Toyota Corolla Sedan 2012 0.0% Dodge Caliber Wagon 2012 0.0% +1472 /scratch/Teaching/cars/car_ims/015270.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 97.67% Infiniti QX56 SUV 2011 1.06% Chrysler Aspen SUV 2009 0.6% Dodge Durango SUV 2007 0.51% Mazda Tribute SUV 2011 0.07% +1473 /scratch/Teaching/cars/car_ims/006000.jpg Chevrolet Silverado 1500 Extended Cab 2012 Dodge Dakota Club Cab 2007 75.53% Volvo XC90 SUV 2007 7.95% Dodge Ram Pickup 3500 Quad Cab 2009 5.6% Ford F-150 Regular Cab 2012 2.4% Chevrolet Silverado 1500 Extended Cab 2012 2.16% +1474 /scratch/Teaching/cars/car_ims/006961.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 99.99% Lincoln Town Car Sedan 2011 0.01% Geo Metro Convertible 1993 0.01% Daewoo Nubira Wagon 2002 0.0% Audi 100 Wagon 1994 0.0% +1475 /scratch/Teaching/cars/car_ims/013612.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 99.91% Dodge Sprinter Cargo Van 2009 0.09% Volkswagen Golf Hatchback 1991 0.0% Ram C/V Cargo Van Minivan 2012 0.0% Audi 100 Sedan 1994 0.0% +1476 /scratch/Teaching/cars/car_ims/010690.jpg Hyundai Veloster Hatchback 2012 BMW M6 Convertible 2010 54.78% Dodge Charger SRT-8 2009 27.84% Fisker Karma Sedan 2012 3.03% Chevrolet Malibu Sedan 2007 2.75% BMW 6 Series Convertible 2007 2.37% +1477 /scratch/Teaching/cars/car_ims/009412.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 85.85% Chrysler Sebring Convertible 2010 13.62% Chrysler Crossfire Convertible 2008 0.33% Plymouth Neon Coupe 1999 0.09% Chrysler 300 SRT-8 2010 0.07% +1478 /scratch/Teaching/cars/car_ims/015218.jpg Tesla Model S Sedan 2012 Chevrolet Corvette ZR1 2012 58.62% Fisker Karma Sedan 2012 35.55% Porsche Panamera Sedan 2012 3.53% Ford GT Coupe 2006 1.16% Bugatti Veyron 16.4 Coupe 2009 0.12% +1479 /scratch/Teaching/cars/car_ims/008775.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 46.14% Buick Rainier SUV 2007 26.74% Mercedes-Benz 300-Class Convertible 1993 10.06% Hyundai Elantra Sedan 2007 9.0% Ford Focus Sedan 2007 4.4% +1480 /scratch/Teaching/cars/car_ims/015101.jpg Suzuki SX4 Sedan 2012 Suzuki SX4 Sedan 2012 100.0% Suzuki SX4 Hatchback 2012 0.0% Scion xD Hatchback 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% Suzuki Aerio Sedan 2007 0.0% +1481 /scratch/Teaching/cars/car_ims/000576.jpg Aston Martin V8 Vantage Convertible 2012 Geo Metro Convertible 1993 85.6% Chevrolet Corvette Convertible 2012 7.59% Rolls-Royce Phantom Drophead Coupe Convertible 2012 5.53% Ferrari California Convertible 2012 0.54% Mercedes-Benz 300-Class Convertible 1993 0.29% +1482 /scratch/Teaching/cars/car_ims/012289.jpg Lamborghini Reventon Coupe 2008 Plymouth Neon Coupe 1999 98.25% Geo Metro Convertible 1993 1.03% Dodge Caravan Minivan 1997 0.2% Volkswagen Golf Hatchback 1991 0.13% Daewoo Nubira Wagon 2002 0.12% +1483 /scratch/Teaching/cars/car_ims/009430.jpg Ford Focus Sedan 2007 Audi 100 Wagon 1994 68.1% Volkswagen Golf Hatchback 1991 21.44% Chevrolet Malibu Sedan 2007 3.94% Lincoln Town Car Sedan 2011 2.84% Daewoo Nubira Wagon 2002 1.64% +1484 /scratch/Teaching/cars/car_ims/016136.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 99.95% MINI Cooper Roadster Convertible 2012 0.02% Maybach Landaulet Convertible 2012 0.01% Mitsubishi Lancer Sedan 2012 0.01% Hyundai Veloster Hatchback 2012 0.0% +1485 /scratch/Teaching/cars/car_ims/011715.jpg Isuzu Ascender SUV 2008 Jeep Grand Cherokee SUV 2012 63.95% Rolls-Royce Phantom Sedan 2012 10.32% Jeep Compass SUV 2012 8.69% Jeep Liberty SUV 2012 5.63% Dodge Dakota Crew Cab 2010 3.02% +1486 /scratch/Teaching/cars/car_ims/014341.jpg Ram C/V Cargo Van Minivan 2012 Suzuki SX4 Sedan 2012 38.86% Ram C/V Cargo Van Minivan 2012 25.61% Audi S4 Sedan 2007 8.91% Dodge Durango SUV 2012 5.57% Chevrolet Impala Sedan 2007 3.99% +1487 /scratch/Teaching/cars/car_ims/011329.jpg Hyundai Sonata Sedan 2012 Hyundai Azera Sedan 2012 94.43% Hyundai Sonata Sedan 2012 3.5% Hyundai Genesis Sedan 2012 1.36% Infiniti G Coupe IPL 2012 0.43% Honda Odyssey Minivan 2012 0.2% +1488 /scratch/Teaching/cars/car_ims/001727.jpg Audi S5 Coupe 2012 Suzuki Kizashi Sedan 2012 92.54% Chevrolet Cobalt SS 2010 5.62% BMW X6 SUV 2012 0.68% Bentley Continental GT Coupe 2007 0.41% Buick Verano Sedan 2012 0.33% +1489 /scratch/Teaching/cars/car_ims/009223.jpg Ford F-150 Regular Cab 2012 Hyundai Veracruz SUV 2012 48.42% Chevrolet Avalanche Crew Cab 2012 14.31% Lamborghini Aventador Coupe 2012 5.52% Ford Ranger SuperCab 2011 5.36% Chevrolet Traverse SUV 2012 5.04% +1490 /scratch/Teaching/cars/car_ims/011174.jpg Hyundai Accent Sedan 2012 BMW 3 Series Sedan 2012 69.17% Ferrari FF Coupe 2012 24.94% Ferrari 458 Italia Convertible 2012 3.19% Suzuki SX4 Hatchback 2012 0.58% BMW M3 Coupe 2012 0.44% +1491 /scratch/Teaching/cars/car_ims/006627.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 96.72% Audi 100 Wagon 1994 3.16% Suzuki Aerio Sedan 2007 0.12% Audi V8 Sedan 1994 0.0% Ford Focus Sedan 2007 0.0% +1492 /scratch/Teaching/cars/car_ims/013292.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 98.63% Audi S6 Sedan 2011 1.23% Hyundai Genesis Sedan 2012 0.06% Audi S4 Sedan 2007 0.03% Mercedes-Benz S-Class Sedan 2012 0.02% +1493 /scratch/Teaching/cars/car_ims/008722.jpg Ford Mustang Convertible 2007 Chevrolet Camaro Convertible 2012 59.29% BMW Z4 Convertible 2012 27.03% Ford Mustang Convertible 2007 5.0% BMW M6 Convertible 2010 3.54% BMW 3 Series Sedan 2012 2.43% +1494 /scratch/Teaching/cars/car_ims/004986.jpg Chevrolet Tahoe Hybrid SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 34.02% Ram C/V Cargo Van Minivan 2012 16.53% Suzuki Aerio Sedan 2007 12.97% Chrysler PT Cruiser Convertible 2008 8.03% GMC Yukon Hybrid SUV 2012 5.37% +1495 /scratch/Teaching/cars/car_ims/007960.jpg Dodge Charger SRT-8 2009 Dodge Charger SRT-8 2009 93.23% Dodge Charger Sedan 2012 6.77% Dodge Magnum Wagon 2008 0.01% Chevrolet Camaro Convertible 2012 0.0% Dodge Challenger SRT8 2011 0.0% +1496 /scratch/Teaching/cars/car_ims/016023.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 99.99% Audi 100 Wagon 1994 0.01% Dodge Caliber Wagon 2012 0.0% Jeep Compass SUV 2012 0.0% Volvo 240 Sedan 1993 0.0% +1497 /scratch/Teaching/cars/car_ims/011732.jpg Isuzu Ascender SUV 2008 Jeep Patriot SUV 2012 62.92% Chevrolet Tahoe Hybrid SUV 2012 22.27% Isuzu Ascender SUV 2008 6.23% GMC Yukon Hybrid SUV 2012 5.45% Mazda Tribute SUV 2011 1.17% +1498 /scratch/Teaching/cars/car_ims/006880.jpg Dodge Caravan Minivan 1997 Audi V8 Sedan 1994 51.78% Plymouth Neon Coupe 1999 10.23% Eagle Talon Hatchback 1998 9.75% Audi 100 Sedan 1994 8.38% Chevrolet Corvette ZR1 2012 7.14% +1499 /scratch/Teaching/cars/car_ims/010117.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 99.83% Mercedes-Benz 300-Class Convertible 1993 0.13% Daewoo Nubira Wagon 2002 0.03% Audi 100 Wagon 1994 0.01% Ford F-150 Regular Cab 2007 0.0% +1500 /scratch/Teaching/cars/car_ims/015476.jpg Toyota Corolla Sedan 2012 Chevrolet Sonic Sedan 2012 67.06% Scion xD Hatchback 2012 14.71% Buick Verano Sedan 2012 5.46% Honda Odyssey Minivan 2012 5.26% Toyota Corolla Sedan 2012 2.68% +1501 /scratch/Teaching/cars/car_ims/000812.jpg Aston Martin Virage Coupe 2012 Aston Martin Virage Coupe 2012 86.35% McLaren MP4-12C Coupe 2012 13.61% Aston Martin V8 Vantage Coupe 2012 0.03% Audi TTS Coupe 2012 0.0% Spyker C8 Coupe 2009 0.0% +1502 /scratch/Teaching/cars/car_ims/006900.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 69.02% Ford Freestar Minivan 2007 13.57% Ram C/V Cargo Van Minivan 2012 10.36% Dodge Caliber Wagon 2007 4.53% Daewoo Nubira Wagon 2002 1.1% +1503 /scratch/Teaching/cars/car_ims/003161.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental Supersports Conv. Convertible 2012 94.26% Rolls-Royce Phantom Drophead Coupe Convertible 2012 2.47% Maybach Landaulet Convertible 2012 0.7% MINI Cooper Roadster Convertible 2012 0.47% Buick Regal GS 2012 0.35% +1504 /scratch/Teaching/cars/car_ims/006498.jpg Chrysler Crossfire Convertible 2008 Chrysler Crossfire Convertible 2008 99.98% Chrysler Sebring Convertible 2010 0.01% Mercedes-Benz S-Class Sedan 2012 0.01% Infiniti G Coupe IPL 2012 0.0% BMW 6 Series Convertible 2007 0.0% +1505 /scratch/Teaching/cars/car_ims/013583.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 100.0% Dodge Sprinter Cargo Van 2009 0.0% Mercedes-Benz S-Class Sedan 2012 0.0% Nissan Juke Hatchback 2012 0.0% Audi V8 Sedan 1994 0.0% +1506 /scratch/Teaching/cars/car_ims/009838.jpg GMC Yukon Hybrid SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 99.8% Chevrolet Avalanche Crew Cab 2012 0.18% GMC Yukon Hybrid SUV 2012 0.02% Cadillac Escalade EXT Crew Cab 2007 0.0% Isuzu Ascender SUV 2008 0.0% +1507 /scratch/Teaching/cars/car_ims/015092.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 62.81% BMW X3 SUV 2012 36.85% Chevrolet Sonic Sedan 2012 0.09% Nissan Juke Hatchback 2012 0.07% Suzuki SX4 Sedan 2012 0.05% +1508 /scratch/Teaching/cars/car_ims/007177.jpg Dodge Sprinter Cargo Van 2009 Dodge Sprinter Cargo Van 2009 98.42% Mercedes-Benz Sprinter Van 2012 1.58% Ram C/V Cargo Van Minivan 2012 0.0% Chrysler Aspen SUV 2009 0.0% Volkswagen Golf Hatchback 1991 0.0% +1509 /scratch/Teaching/cars/car_ims/007289.jpg Dodge Journey SUV 2012 Buick Verano Sedan 2012 55.79% Cadillac SRX SUV 2012 21.86% Dodge Journey SUV 2012 19.82% Suzuki SX4 Sedan 2012 2.12% Nissan Juke Hatchback 2012 0.15% +1510 /scratch/Teaching/cars/car_ims/007647.jpg Dodge Durango SUV 2012 Chrysler PT Cruiser Convertible 2008 63.23% Dodge Durango SUV 2012 36.72% Chevrolet Avalanche Crew Cab 2012 0.02% Dodge Caliber Wagon 2012 0.01% Ford Expedition EL SUV 2009 0.01% +1511 /scratch/Teaching/cars/car_ims/015449.jpg Toyota Corolla Sedan 2012 Toyota Corolla Sedan 2012 99.73% Toyota Camry Sedan 2012 0.27% Hyundai Accent Sedan 2012 0.0% Scion xD Hatchback 2012 0.0% Acura TSX Sedan 2012 0.0% +1512 /scratch/Teaching/cars/car_ims/004145.jpg Cadillac SRX SUV 2012 Buick Enclave SUV 2012 38.8% Volvo XC90 SUV 2007 29.63% Cadillac SRX SUV 2012 9.74% Hyundai Veracruz SUV 2012 6.61% BMW X6 SUV 2012 3.83% +1513 /scratch/Teaching/cars/car_ims/015083.jpg Suzuki SX4 Hatchback 2012 Volkswagen Golf Hatchback 1991 49.8% Ford Ranger SuperCab 2011 39.78% Ford F-150 Regular Cab 2007 4.9% Chevrolet Silverado 1500 Classic Extended Cab 2007 1.55% Audi 100 Sedan 1994 1.16% +1514 /scratch/Teaching/cars/car_ims/001774.jpg Audi S5 Coupe 2012 Audi S5 Convertible 2012 86.6% Audi S6 Sedan 2011 12.73% Audi RS 4 Convertible 2008 0.41% Audi S5 Coupe 2012 0.15% BMW 1 Series Convertible 2012 0.05% +1515 /scratch/Teaching/cars/car_ims/010206.jpg HUMMER H3T Crew Cab 2010 HUMMER H2 SUT Crew Cab 2009 99.98% HUMMER H3T Crew Cab 2010 0.02% AM General Hummer SUV 2000 0.0% Jeep Grand Cherokee SUV 2012 0.0% Jeep Compass SUV 2012 0.0% +1516 /scratch/Teaching/cars/car_ims/008923.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 98.86% Suzuki SX4 Hatchback 2012 0.25% Dodge Durango SUV 2007 0.22% Ford Edge SUV 2012 0.15% Dodge Durango SUV 2012 0.13% +1517 /scratch/Teaching/cars/car_ims/002014.jpg Audi TT RS Coupe 2012 Audi TT RS Coupe 2012 99.57% Lamborghini Aventador Coupe 2012 0.35% BMW M3 Coupe 2012 0.07% Ferrari 458 Italia Coupe 2012 0.0% Audi R8 Coupe 2012 0.0% +1518 /scratch/Teaching/cars/car_ims/011188.jpg Hyundai Accent Sedan 2012 Hyundai Accent Sedan 2012 84.46% Toyota Corolla Sedan 2012 10.81% Ford Fiesta Sedan 2012 2.56% Hyundai Sonata Hybrid Sedan 2012 1.44% Hyundai Veloster Hatchback 2012 0.36% +1519 /scratch/Teaching/cars/car_ims/015046.jpg Suzuki SX4 Hatchback 2012 Hyundai Santa Fe SUV 2012 46.95% Scion xD Hatchback 2012 29.14% Hyundai Veracruz SUV 2012 4.39% Chevrolet Malibu Sedan 2007 3.83% Suzuki SX4 Sedan 2012 3.29% +1520 /scratch/Teaching/cars/car_ims/008104.jpg FIAT 500 Abarth 2012 FIAT 500 Abarth 2012 100.0% Bugatti Veyron 16.4 Coupe 2009 0.0% McLaren MP4-12C Coupe 2012 0.0% Audi R8 Coupe 2012 0.0% Nissan Juke Hatchback 2012 0.0% +1521 /scratch/Teaching/cars/car_ims/010880.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 95.92% Chevrolet Traverse SUV 2012 1.78% Hyundai Sonata Sedan 2012 1.45% Hyundai Veracruz SUV 2012 0.36% Ford Fiesta Sedan 2012 0.34% +1522 /scratch/Teaching/cars/car_ims/014073.jpg Nissan 240SX Coupe 1998 Chevrolet TrailBlazer SS 2009 61.75% Nissan 240SX Coupe 1998 14.58% Bentley Arnage Sedan 2009 9.02% Chrysler 300 SRT-8 2010 5.37% Bentley Continental Flying Spur Sedan 2007 1.25% +1523 /scratch/Teaching/cars/car_ims/000739.jpg Aston Martin V8 Vantage Coupe 2012 Jaguar XK XKR 2012 78.62% Aston Martin V8 Vantage Convertible 2012 8.95% Aston Martin V8 Vantage Coupe 2012 4.39% Porsche Panamera Sedan 2012 4.16% Chevrolet Corvette Convertible 2012 2.6% +1524 /scratch/Teaching/cars/car_ims/007972.jpg Eagle Talon Hatchback 1998 BMW 3 Series Sedan 2012 65.23% Ferrari FF Coupe 2012 22.33% Ferrari 458 Italia Coupe 2012 3.23% BMW M6 Convertible 2010 1.12% Buick Regal GS 2012 1.1% +1525 /scratch/Teaching/cars/car_ims/001931.jpg Audi S4 Sedan 2007 Audi A5 Coupe 2012 74.58% Audi S4 Sedan 2007 22.64% Audi S5 Coupe 2012 1.66% Audi RS 4 Convertible 2008 0.53% Audi S4 Sedan 2012 0.27% +1526 /scratch/Teaching/cars/car_ims/011269.jpg Hyundai Genesis Sedan 2012 Chrysler Crossfire Convertible 2008 40.22% Hyundai Azera Sedan 2012 12.09% Aston Martin Virage Convertible 2012 11.57% Volkswagen Golf Hatchback 2012 6.17% Infiniti G Coupe IPL 2012 6.11% +1527 /scratch/Teaching/cars/car_ims/014691.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 92.84% Chevrolet Corvette ZR1 2012 7.15% Bugatti Veyron 16.4 Coupe 2009 0.01% Porsche Panamera Sedan 2012 0.0% Aston Martin Virage Convertible 2012 0.0% +1528 /scratch/Teaching/cars/car_ims/008526.jpg Fisker Karma Sedan 2012 Audi R8 Coupe 2012 48.48% Nissan Juke Hatchback 2012 8.27% McLaren MP4-12C Coupe 2012 7.92% Lamborghini Aventador Coupe 2012 6.19% Fisker Karma Sedan 2012 4.28% +1529 /scratch/Teaching/cars/car_ims/014456.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 77.98% BMW 6 Series Convertible 2007 4.4% Mitsubishi Lancer Sedan 2012 3.62% Honda Odyssey Minivan 2012 3.52% MINI Cooper Roadster Convertible 2012 2.95% +1530 /scratch/Teaching/cars/car_ims/001760.jpg Audi S5 Coupe 2012 Daewoo Nubira Wagon 2002 48.31% Maybach Landaulet Convertible 2012 12.6% Acura RL Sedan 2012 10.46% BMW 3 Series Wagon 2012 10.18% Volkswagen Golf Hatchback 2012 4.41% +1531 /scratch/Teaching/cars/car_ims/011603.jpg Infiniti G Coupe IPL 2012 Acura RL Sedan 2012 39.18% BMW ActiveHybrid 5 Sedan 2012 36.86% Acura TL Type-S 2008 8.13% BMW M3 Coupe 2012 3.2% Audi S4 Sedan 2007 1.79% +1532 /scratch/Teaching/cars/car_ims/000210.jpg Acura TL Sedan 2012 Hyundai Veracruz SUV 2012 49.31% BMW X6 SUV 2012 16.06% Acura ZDX Hatchback 2012 14.19% Acura RL Sedan 2012 9.37% Honda Odyssey Minivan 2012 4.07% +1533 /scratch/Teaching/cars/car_ims/015090.jpg Suzuki SX4 Hatchback 2012 Dodge Caliber Wagon 2007 55.44% Dodge Caliber Wagon 2012 28.09% Jeep Wrangler SUV 2012 8.08% Jeep Patriot SUV 2012 2.92% Suzuki SX4 Hatchback 2012 2.09% +1534 /scratch/Teaching/cars/car_ims/005019.jpg Chevrolet Tahoe Hybrid SUV 2012 Dodge Durango SUV 2007 99.51% Dodge Magnum Wagon 2008 0.2% Dodge Dakota Crew Cab 2010 0.14% Dodge Dakota Club Cab 2007 0.09% Chevrolet Avalanche Crew Cab 2012 0.02% +1535 /scratch/Teaching/cars/car_ims/007715.jpg Dodge Durango SUV 2007 Rolls-Royce Phantom Sedan 2012 34.26% Chrysler 300 SRT-8 2010 30.26% GMC Savana Van 2012 6.78% Audi 100 Wagon 1994 6.69% Acura TL Type-S 2008 3.98% +1536 /scratch/Teaching/cars/car_ims/005418.jpg Chevrolet Malibu Hybrid Sedan 2010 Chevrolet Malibu Hybrid Sedan 2010 100.0% Buick Verano Sedan 2012 0.0% Honda Accord Sedan 2012 0.0% Chevrolet Impala Sedan 2007 0.0% Acura RL Sedan 2012 0.0% +1537 /scratch/Teaching/cars/car_ims/012690.jpg Land Rover Range Rover SUV 2012 Land Rover Range Rover SUV 2012 97.5% Land Rover LR2 SUV 2012 2.49% GMC Terrain SUV 2012 0.0% Ford Edge SUV 2012 0.0% Ford Expedition EL SUV 2009 0.0% +1538 /scratch/Teaching/cars/car_ims/007134.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 99.97% Dodge Ram Pickup 3500 Crew Cab 2010 0.02% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% Dodge Dakota Crew Cab 2010 0.0% Ford F-450 Super Duty Crew Cab 2012 0.0% +1539 /scratch/Teaching/cars/car_ims/013235.jpg Mercedes-Benz 300-Class Convertible 1993 Audi V8 Sedan 1994 50.84% Ford Mustang Convertible 2007 43.01% Mercedes-Benz 300-Class Convertible 1993 2.17% Volkswagen Golf Hatchback 1991 1.03% Audi 100 Sedan 1994 0.86% +1540 /scratch/Teaching/cars/car_ims/008464.jpg Ferrari 458 Italia Coupe 2012 McLaren MP4-12C Coupe 2012 46.53% Lamborghini Aventador Coupe 2012 30.63% Ferrari 458 Italia Convertible 2012 21.65% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.38% Lamborghini Diablo Coupe 2001 0.15% +1541 /scratch/Teaching/cars/car_ims/012425.jpg Lamborghini Aventador Coupe 2012 Bentley Continental Supersports Conv. Convertible 2012 99.78% Bentley Mulsanne Sedan 2011 0.06% BMW M3 Coupe 2012 0.04% Lamborghini Aventador Coupe 2012 0.04% Mercedes-Benz SL-Class Coupe 2009 0.01% +1542 /scratch/Teaching/cars/car_ims/006779.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2007 99.85% Dodge Caliber Wagon 2012 0.15% Dodge Charger Sedan 2012 0.0% BMW 3 Series Sedan 2012 0.0% Hyundai Elantra Sedan 2007 0.0% +1543 /scratch/Teaching/cars/car_ims/009242.jpg Ford F-150 Regular Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 48.09% Chevrolet Silverado 2500HD Regular Cab 2012 20.44% Ford Ranger SuperCab 2011 13.99% Chevrolet Silverado 1500 Classic Extended Cab 2007 7.27% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 4.11% +1544 /scratch/Teaching/cars/car_ims/000614.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin V8 Vantage Convertible 2012 79.28% Aston Martin V8 Vantage Coupe 2012 20.47% Ferrari 458 Italia Coupe 2012 0.12% Ferrari California Convertible 2012 0.12% Chevrolet Corvette Convertible 2012 0.0% +1545 /scratch/Teaching/cars/car_ims/010172.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 99.99% Acura Integra Type R 2001 0.01% Ford Mustang Convertible 2007 0.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Chevrolet Corvette Convertible 2012 0.0% +1546 /scratch/Teaching/cars/car_ims/002685.jpg BMW X6 SUV 2012 Chevrolet Sonic Sedan 2012 32.27% Infiniti QX56 SUV 2011 19.56% Buick Verano Sedan 2012 16.32% BMW X6 SUV 2012 6.91% Mitsubishi Lancer Sedan 2012 6.58% +1547 /scratch/Teaching/cars/car_ims/006255.jpg Chrysler Sebring Convertible 2010 Chrysler Sebring Convertible 2010 64.63% Maybach Landaulet Convertible 2012 10.29% Chevrolet Malibu Sedan 2007 7.57% Ram C/V Cargo Van Minivan 2012 6.01% Dodge Magnum Wagon 2008 5.39% +1548 /scratch/Teaching/cars/car_ims/010701.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 94.71% Spyker C8 Coupe 2009 3.58% Mitsubishi Lancer Sedan 2012 1.39% Chevrolet Sonic Sedan 2012 0.28% Volvo C30 Hatchback 2012 0.03% +1549 /scratch/Teaching/cars/car_ims/008937.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 93.63% Ford F-150 Regular Cab 2012 4.07% Land Rover Range Rover SUV 2012 0.84% Ford Ranger SuperCab 2011 0.56% Land Rover LR2 SUV 2012 0.33% +1550 /scratch/Teaching/cars/car_ims/011221.jpg Hyundai Genesis Sedan 2012 Acura TL Type-S 2008 52.3% Acura RL Sedan 2012 35.79% Hyundai Genesis Sedan 2012 6.13% Mitsubishi Lancer Sedan 2012 4.49% BMW M6 Convertible 2010 0.9% +1551 /scratch/Teaching/cars/car_ims/000611.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin V8 Vantage Convertible 2012 98.12% Aston Martin V8 Vantage Coupe 2012 1.61% Aston Martin Virage Convertible 2012 0.25% Ferrari California Convertible 2012 0.01% McLaren MP4-12C Coupe 2012 0.0% +1552 /scratch/Teaching/cars/car_ims/009229.jpg Ford F-150 Regular Cab 2012 Ford E-Series Wagon Van 2012 92.71% Ford Ranger SuperCab 2011 2.83% Chevrolet Express Cargo Van 2007 2.06% Ford F-150 Regular Cab 2012 1.11% Nissan NV Passenger Van 2012 0.74% +1553 /scratch/Teaching/cars/car_ims/013895.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 100.0% Jeep Patriot SUV 2012 0.0% Ford F-150 Regular Cab 2012 0.0% Ford F-150 Regular Cab 2007 0.0% Ford E-Series Wagon Van 2012 0.0% +1554 /scratch/Teaching/cars/car_ims/001569.jpg Audi S6 Sedan 2011 Audi S4 Sedan 2007 92.88% Audi A5 Coupe 2012 7.03% Audi S6 Sedan 2011 0.1% Audi S4 Sedan 2012 0.0% Audi S5 Coupe 2012 0.0% +1555 /scratch/Teaching/cars/car_ims/006173.jpg Chrysler Aspen SUV 2009 Chrysler Aspen SUV 2009 99.15% Chrysler PT Cruiser Convertible 2008 0.41% Ford F-150 Regular Cab 2012 0.4% Ford Expedition EL SUV 2009 0.03% Toyota Sequoia SUV 2012 0.0% +1556 /scratch/Teaching/cars/car_ims/001960.jpg Audi S4 Sedan 2007 Audi S5 Coupe 2012 81.33% Audi RS 4 Convertible 2008 10.06% Audi A5 Coupe 2012 7.95% Audi S5 Convertible 2012 0.22% Audi S4 Sedan 2007 0.19% +1557 /scratch/Teaching/cars/car_ims/013514.jpg Mercedes-Benz S-Class Sedan 2012 Dodge Challenger SRT8 2011 23.95% Maybach Landaulet Convertible 2012 21.86% Mercedes-Benz S-Class Sedan 2012 11.47% Acura Integra Type R 2001 10.87% BMW 3 Series Sedan 2012 8.0% +1558 /scratch/Teaching/cars/car_ims/003636.jpg Bugatti Veyron 16.4 Convertible 2009 Bugatti Veyron 16.4 Convertible 2009 85.88% Bugatti Veyron 16.4 Coupe 2009 13.84% Ford GT Coupe 2006 0.25% Spyker C8 Convertible 2009 0.02% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% +1559 /scratch/Teaching/cars/car_ims/013698.jpg Mitsubishi Lancer Sedan 2012 Bentley Continental Supersports Conv. Convertible 2012 36.94% Chevrolet Corvette Ron Fellows Edition Z06 2007 23.94% Lamborghini Aventador Coupe 2012 6.45% MINI Cooper Roadster Convertible 2012 6.24% Buick Regal GS 2012 5.82% +1560 /scratch/Teaching/cars/car_ims/009760.jpg GMC Savana Van 2012 GMC Savana Van 2012 87.15% Audi V8 Sedan 1994 5.69% Chevrolet Express Cargo Van 2007 3.46% Audi 100 Wagon 1994 1.3% Chevrolet Express Van 2007 1.12% +1561 /scratch/Teaching/cars/car_ims/008162.jpg FIAT 500 Convertible 2012 FIAT 500 Convertible 2012 100.0% Maybach Landaulet Convertible 2012 0.0% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.0% Suzuki Kizashi Sedan 2012 0.0% Volkswagen Beetle Hatchback 2012 0.0% +1562 /scratch/Teaching/cars/car_ims/014001.jpg Nissan Juke Hatchback 2012 Bugatti Veyron 16.4 Coupe 2009 98.34% Bugatti Veyron 16.4 Convertible 2009 0.88% Ford GT Coupe 2006 0.48% Spyker C8 Convertible 2009 0.15% Cadillac CTS-V Sedan 2012 0.04% +1563 /scratch/Teaching/cars/car_ims/011483.jpg Hyundai Azera Sedan 2012 Hyundai Azera Sedan 2012 96.09% Hyundai Sonata Sedan 2012 3.83% Hyundai Genesis Sedan 2012 0.07% Mercedes-Benz C-Class Sedan 2012 0.0% Toyota Corolla Sedan 2012 0.0% +1564 /scratch/Teaching/cars/car_ims/011017.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Genesis Sedan 2012 31.66% BMW ActiveHybrid 5 Sedan 2012 26.17% Acura ZDX Hatchback 2012 8.22% Volkswagen Beetle Hatchback 2012 5.69% Acura RL Sedan 2012 3.8% +1565 /scratch/Teaching/cars/car_ims/012165.jpg Jeep Grand Cherokee SUV 2012 Volvo XC90 SUV 2007 69.72% Chevrolet Traverse SUV 2012 15.88% GMC Acadia SUV 2012 6.92% Buick Enclave SUV 2012 3.04% Jeep Grand Cherokee SUV 2012 1.17% +1566 /scratch/Teaching/cars/car_ims/001027.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 52.67% Audi S5 Coupe 2012 47.25% Audi S4 Sedan 2012 0.06% Rolls-Royce Ghost Sedan 2012 0.01% Audi S4 Sedan 2007 0.0% +1567 /scratch/Teaching/cars/car_ims/001665.jpg Audi S5 Convertible 2012 Porsche Panamera Sedan 2012 57.84% Audi TT Hatchback 2011 11.98% Audi S5 Convertible 2012 9.13% Audi S5 Coupe 2012 6.46% Fisker Karma Sedan 2012 4.37% +1568 /scratch/Teaching/cars/car_ims/005675.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chrysler Aspen SUV 2009 40.86% Chevrolet Silverado 1500 Classic Extended Cab 2007 36.06% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 5.1% Chevrolet Avalanche Crew Cab 2012 4.96% GMC Canyon Extended Cab 2012 4.66% +1569 /scratch/Teaching/cars/car_ims/015576.jpg Toyota 4Runner SUV 2012 Infiniti QX56 SUV 2011 93.43% Land Rover Range Rover SUV 2012 2.74% Land Rover LR2 SUV 2012 2.62% Hyundai Veracruz SUV 2012 0.19% Ford Expedition EL SUV 2009 0.18% +1570 /scratch/Teaching/cars/car_ims/013128.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 99.83% Spyker C8 Coupe 2009 0.08% Lamborghini Aventador Coupe 2012 0.03% Spyker C8 Convertible 2009 0.03% Bugatti Veyron 16.4 Coupe 2009 0.02% +1571 /scratch/Teaching/cars/car_ims/007383.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 99.08% Dodge Dakota Club Cab 2007 0.91% Dodge Durango SUV 2007 0.01% Dodge Magnum Wagon 2008 0.0% Dodge Charger SRT-8 2009 0.0% +1572 /scratch/Teaching/cars/car_ims/006760.jpg Dodge Caliber Wagon 2012 Chrysler PT Cruiser Convertible 2008 84.48% Dodge Caliber Wagon 2012 15.08% Ford Expedition EL SUV 2009 0.13% Ram C/V Cargo Van Minivan 2012 0.06% Hyundai Genesis Sedan 2012 0.06% +1573 /scratch/Teaching/cars/car_ims/005733.jpg Chevrolet Express Van 2007 Chevrolet Express Van 2007 54.03% Plymouth Neon Coupe 1999 43.0% Chevrolet Express Cargo Van 2007 1.06% Audi V8 Sedan 1994 0.95% Volkswagen Golf Hatchback 1991 0.66% +1574 /scratch/Teaching/cars/car_ims/003803.jpg Buick Regal GS 2012 Audi S5 Coupe 2012 49.12% Audi S4 Sedan 2012 23.74% Audi TT Hatchback 2011 6.58% Audi S6 Sedan 2011 5.56% Buick Regal GS 2012 2.7% +1575 /scratch/Teaching/cars/car_ims/008956.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 100.0% Honda Odyssey Minivan 2012 0.0% Land Rover LR2 SUV 2012 0.0% Hyundai Santa Fe SUV 2012 0.0% Toyota 4Runner SUV 2012 0.0% +1576 /scratch/Teaching/cars/car_ims/014087.jpg Nissan 240SX Coupe 1998 BMW 6 Series Convertible 2007 71.65% BMW M6 Convertible 2010 23.14% Nissan 240SX Coupe 1998 3.25% Jaguar XK XKR 2012 1.39% BMW M3 Coupe 2012 0.12% +1577 /scratch/Teaching/cars/car_ims/008802.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 88.53% Chevrolet Malibu Sedan 2007 5.13% Geo Metro Convertible 1993 4.37% Lincoln Town Car Sedan 2011 0.98% Chevrolet Monte Carlo Coupe 2007 0.31% +1578 /scratch/Teaching/cars/car_ims/013409.jpg Mercedes-Benz E-Class Sedan 2012 Land Rover Range Rover SUV 2012 23.27% Chrysler Crossfire Convertible 2008 17.42% Mercedes-Benz C-Class Sedan 2012 12.57% Cadillac SRX SUV 2012 10.84% Bentley Mulsanne Sedan 2011 7.24% +1579 /scratch/Teaching/cars/car_ims/004847.jpg Chevrolet HHR SS 2010 Chevrolet Sonic Sedan 2012 91.77% Chevrolet HHR SS 2010 6.22% Scion xD Hatchback 2012 1.08% BMW 1 Series Coupe 2012 0.28% Volvo C30 Hatchback 2012 0.19% +1580 /scratch/Teaching/cars/car_ims/003903.jpg Buick Verano Sedan 2012 Porsche Panamera Sedan 2012 55.29% Buick Regal GS 2012 22.53% Buick Verano Sedan 2012 13.65% Nissan Juke Hatchback 2012 6.34% Jaguar XK XKR 2012 1.03% +1581 /scratch/Teaching/cars/car_ims/009008.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 57.23% Toyota 4Runner SUV 2012 37.51% HUMMER H3T Crew Cab 2010 2.83% HUMMER H2 SUT Crew Cab 2009 0.94% GMC Canyon Extended Cab 2012 0.54% +1582 /scratch/Teaching/cars/car_ims/001253.jpg Audi V8 Sedan 1994 Volkswagen Golf Hatchback 1991 34.21% Mercedes-Benz 300-Class Convertible 1993 24.04% Chrysler 300 SRT-8 2010 20.72% Chevrolet TrailBlazer SS 2009 7.98% Volvo 240 Sedan 1993 4.2% +1583 /scratch/Teaching/cars/car_ims/008715.jpg Ford Mustang Convertible 2007 Chrysler PT Cruiser Convertible 2008 31.04% Nissan Juke Hatchback 2012 17.04% Suzuki Kizashi Sedan 2012 15.33% Dodge Caliber Wagon 2012 5.16% Dodge Caliber Wagon 2007 4.36% +1584 /scratch/Teaching/cars/car_ims/004985.jpg Chevrolet Tahoe Hybrid SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 84.87% Chevrolet Avalanche Crew Cab 2012 14.23% Dodge Durango SUV 2007 0.53% Jeep Patriot SUV 2012 0.16% GMC Yukon Hybrid SUV 2012 0.08% +1585 /scratch/Teaching/cars/car_ims/015428.jpg Toyota Corolla Sedan 2012 Toyota Corolla Sedan 2012 99.99% Toyota Camry Sedan 2012 0.01% Hyundai Accent Sedan 2012 0.0% Scion xD Hatchback 2012 0.0% Mitsubishi Lancer Sedan 2012 0.0% +1586 /scratch/Teaching/cars/car_ims/001193.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 95.12% Spyker C8 Coupe 2009 0.66% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.64% Aston Martin V8 Vantage Coupe 2012 0.61% Lamborghini Aventador Coupe 2012 0.47% +1587 /scratch/Teaching/cars/car_ims/007763.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 97.87% Dodge Dakota Crew Cab 2010 1.51% Dodge Dakota Club Cab 2007 0.5% Dodge Durango SUV 2012 0.03% Dodge Ram Pickup 3500 Crew Cab 2010 0.03% +1588 /scratch/Teaching/cars/car_ims/010777.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 100.0% Honda Odyssey Minivan 2012 0.0% Ford Edge SUV 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% Land Rover LR2 SUV 2012 0.0% +1589 /scratch/Teaching/cars/car_ims/001538.jpg Audi TT Hatchback 2011 Hyundai Azera Sedan 2012 34.71% Suzuki Kizashi Sedan 2012 32.8% Acura ZDX Hatchback 2012 16.04% Hyundai Genesis Sedan 2012 2.45% Jaguar XK XKR 2012 2.31% +1590 /scratch/Teaching/cars/car_ims/013652.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 100.0% Chevrolet Traverse SUV 2012 0.0% Chevrolet Express Cargo Van 2007 0.0% Dodge Sprinter Cargo Van 2009 0.0% Audi 100 Wagon 1994 0.0% +1591 /scratch/Teaching/cars/car_ims/008561.jpg Fisker Karma Sedan 2012 Dodge Charger SRT-8 2009 18.8% Chrysler Crossfire Convertible 2008 15.48% BMW Z4 Convertible 2012 13.23% Aston Martin V8 Vantage Coupe 2012 12.31% Aston Martin Virage Convertible 2012 9.36% +1592 /scratch/Teaching/cars/car_ims/014119.jpg Plymouth Neon Coupe 1999 Volkswagen Golf Hatchback 1991 98.47% Volvo 240 Sedan 1993 1.15% Audi 100 Wagon 1994 0.17% GMC Canyon Extended Cab 2012 0.1% Mazda Tribute SUV 2011 0.02% +1593 /scratch/Teaching/cars/car_ims/009661.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 99.99% Dodge Caliber Wagon 2012 0.01% Toyota 4Runner SUV 2012 0.0% Chevrolet Traverse SUV 2012 0.0% Ford Edge SUV 2012 0.0% +1594 /scratch/Teaching/cars/car_ims/003797.jpg Buick Regal GS 2012 Chevrolet Sonic Sedan 2012 59.96% Buick Verano Sedan 2012 21.7% Buick Regal GS 2012 7.84% Chevrolet Malibu Hybrid Sedan 2010 3.15% Mitsubishi Lancer Sedan 2012 2.06% +1595 /scratch/Teaching/cars/car_ims/004624.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Rolls-Royce Phantom Drophead Coupe Convertible 2012 83.91% Mercedes-Benz 300-Class Convertible 1993 7.37% Bentley Continental Supersports Conv. Convertible 2012 3.59% Chevrolet Corvette Convertible 2012 2.46% BMW M6 Convertible 2010 2.12% +1596 /scratch/Teaching/cars/car_ims/012206.jpg Jeep Compass SUV 2012 BMW X5 SUV 2007 92.23% Jeep Compass SUV 2012 5.39% Bentley Arnage Sedan 2009 2.2% BMW 3 Series Sedan 2012 0.06% Rolls-Royce Ghost Sedan 2012 0.02% +1597 /scratch/Teaching/cars/car_ims/000959.jpg Audi A5 Coupe 2012 Audi S5 Coupe 2012 60.26% Audi S6 Sedan 2011 15.5% Audi A5 Coupe 2012 14.05% Audi RS 4 Convertible 2008 6.19% Audi TTS Coupe 2012 1.33% +1598 /scratch/Teaching/cars/car_ims/001742.jpg Audi S5 Coupe 2012 Audi S5 Coupe 2012 94.07% Audi A5 Coupe 2012 3.0% Audi S5 Convertible 2012 1.72% BMW 3 Series Sedan 2012 0.5% BMW 3 Series Wagon 2012 0.17% +1599 /scratch/Teaching/cars/car_ims/010453.jpg Honda Odyssey Minivan 2007 Honda Odyssey Minivan 2012 99.94% Honda Odyssey Minivan 2007 0.05% Chevrolet Impala Sedan 2007 0.0% Chevrolet Malibu Sedan 2007 0.0% Acura RL Sedan 2012 0.0% +1600 /scratch/Teaching/cars/car_ims/014991.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 44.06% Toyota Corolla Sedan 2012 30.15% Audi S4 Sedan 2007 17.53% Chevrolet Cobalt SS 2010 2.27% Chrysler Sebring Convertible 2010 1.52% +1601 /scratch/Teaching/cars/car_ims/006866.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2007 53.08% Dodge Caliber Wagon 2012 46.92% Chrysler PT Cruiser Convertible 2008 0.0% Dodge Journey SUV 2012 0.0% Dodge Magnum Wagon 2008 0.0% +1602 /scratch/Teaching/cars/car_ims/002615.jpg BMW X6 SUV 2012 BMW X5 SUV 2007 87.66% BMW X3 SUV 2012 6.28% Volvo XC90 SUV 2007 4.78% BMW 1 Series Convertible 2012 0.47% BMW X6 SUV 2012 0.44% +1603 /scratch/Teaching/cars/car_ims/014002.jpg Nissan Juke Hatchback 2012 Chevrolet Corvette Convertible 2012 75.02% Ferrari 458 Italia Convertible 2012 7.61% Ford GT Coupe 2006 6.13% Chevrolet Corvette ZR1 2012 2.27% Ferrari California Convertible 2012 1.51% +1604 /scratch/Teaching/cars/car_ims/010528.jpg Honda Accord Coupe 2012 Mitsubishi Lancer Sedan 2012 95.37% Audi A5 Coupe 2012 2.19% BMW 1 Series Convertible 2012 1.0% Acura RL Sedan 2012 0.67% Honda Accord Coupe 2012 0.23% +1605 /scratch/Teaching/cars/car_ims/015780.jpg Volkswagen Beetle Hatchback 2012 Volkswagen Beetle Hatchback 2012 64.75% Volvo C30 Hatchback 2012 30.38% Suzuki Kizashi Sedan 2012 4.26% BMW 1 Series Coupe 2012 0.47% Chevrolet Cobalt SS 2010 0.06% +1606 /scratch/Teaching/cars/car_ims/000119.jpg Acura RL Sedan 2012 Chevrolet Impala Sedan 2007 68.88% Chevrolet Monte Carlo Coupe 2007 8.96% BMW 6 Series Convertible 2007 5.86% Daewoo Nubira Wagon 2002 3.02% Dodge Magnum Wagon 2008 2.15% +1607 /scratch/Teaching/cars/car_ims/000214.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 99.75% Acura RL Sedan 2012 0.25% Acura TSX Sedan 2012 0.0% Acura ZDX Hatchback 2012 0.0% Acura TL Type-S 2008 0.0% +1608 /scratch/Teaching/cars/car_ims/005466.jpg Chevrolet TrailBlazer SS 2009 Chevrolet TrailBlazer SS 2009 100.0% Chevrolet Avalanche Crew Cab 2012 0.0% Dodge Charger SRT-8 2009 0.0% Land Rover Range Rover SUV 2012 0.0% Chevrolet Traverse SUV 2012 0.0% +1609 /scratch/Teaching/cars/car_ims/011729.jpg Isuzu Ascender SUV 2008 Isuzu Ascender SUV 2008 100.0% Chevrolet Tahoe Hybrid SUV 2012 0.0% Ford Freestar Minivan 2007 0.0% Cadillac Escalade EXT Crew Cab 2007 0.0% Dodge Dakota Crew Cab 2010 0.0% +1610 /scratch/Teaching/cars/car_ims/015370.jpg Toyota Camry Sedan 2012 Toyota Camry Sedan 2012 94.98% Toyota Corolla Sedan 2012 4.2% Mitsubishi Lancer Sedan 2012 0.37% Chevrolet Sonic Sedan 2012 0.26% Suzuki Kizashi Sedan 2012 0.1% +1611 /scratch/Teaching/cars/car_ims/011835.jpg Jaguar XK XKR 2012 Infiniti G Coupe IPL 2012 45.49% Suzuki Kizashi Sedan 2012 30.09% BMW M5 Sedan 2010 7.55% BMW M3 Coupe 2012 6.66% Toyota Corolla Sedan 2012 1.71% +1612 /scratch/Teaching/cars/car_ims/003714.jpg Bugatti Veyron 16.4 Coupe 2009 Bugatti Veyron 16.4 Coupe 2009 78.84% Audi R8 Coupe 2012 19.54% Chrysler 300 SRT-8 2010 1.34% Lamborghini Aventador Coupe 2012 0.11% Lamborghini Reventon Coupe 2008 0.1% +1613 /scratch/Teaching/cars/car_ims/008459.jpg Ferrari 458 Italia Coupe 2012 McLaren MP4-12C Coupe 2012 56.16% Hyundai Veloster Hatchback 2012 32.05% Ferrari 458 Italia Convertible 2012 8.48% Aston Martin Virage Coupe 2012 1.41% Lamborghini Aventador Coupe 2012 0.7% +1614 /scratch/Teaching/cars/car_ims/015939.jpg Volvo 240 Sedan 1993 Rolls-Royce Phantom Drophead Coupe Convertible 2012 43.72% Volvo 240 Sedan 1993 36.13% Mercedes-Benz 300-Class Convertible 1993 19.56% Rolls-Royce Phantom Sedan 2012 0.37% Rolls-Royce Ghost Sedan 2012 0.17% +1615 /scratch/Teaching/cars/car_ims/007031.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 99.68% Dodge Durango SUV 2007 0.2% Dodge Ram Pickup 3500 Quad Cab 2009 0.11% Dodge Charger Sedan 2012 0.0% Dodge Dakota Club Cab 2007 0.0% +1616 /scratch/Teaching/cars/car_ims/005796.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Impala Sedan 2007 44.92% Lincoln Town Car Sedan 2011 25.26% Chevrolet Monte Carlo Coupe 2007 20.08% Chevrolet Malibu Sedan 2007 9.58% Audi S4 Sedan 2007 0.07% +1617 /scratch/Teaching/cars/car_ims/012842.jpg Lincoln Town Car Sedan 2011 Chevrolet Impala Sedan 2007 42.08% Audi 100 Wagon 1994 20.29% Dodge Magnum Wagon 2008 8.91% Volvo XC90 SUV 2007 7.47% Lincoln Town Car Sedan 2011 5.61% +1618 /scratch/Teaching/cars/car_ims/004377.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Malibu Hybrid Sedan 2010 36.12% Chevrolet Sonic Sedan 2012 21.37% Ford Edge SUV 2012 10.57% Dodge Charger Sedan 2012 4.63% Hyundai Tucson SUV 2012 3.58% +1619 /scratch/Teaching/cars/car_ims/003059.jpg BMW Z4 Convertible 2012 Rolls-Royce Ghost Sedan 2012 57.31% Fisker Karma Sedan 2012 23.79% Rolls-Royce Phantom Sedan 2012 14.87% Rolls-Royce Phantom Drophead Coupe Convertible 2012 2.21% BMW M6 Convertible 2010 0.98% \ No newline at end of file diff --git a/cars/architecture-investigations/fc/1-layer/256/small.png b/cars/architecture-investigations/fc/1-layer/256/small.png 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literal 0 HcmV?d00001 diff --git a/cars/architecture-investigations/fc/1-layer/256/solver.prototxt b/cars/architecture-investigations/fc/1-layer/256/solver.prototxt new file mode 100644 index 0000000..803ddda --- /dev/null +++ b/cars/architecture-investigations/fc/1-layer/256/solver.prototxt @@ -0,0 +1,14 @@ +test_iter: 51 +test_interval: 102 +base_lr: 0.00999999977648 +display: 12 +max_iter: 10200 +lr_policy: "exp" +gamma: 0.999801933765 +momentum: 0.899999976158 +weight_decay: 9.99999974738e-05 +snapshot: 102 +snapshot_prefix: "snapshot" +solver_mode: GPU +net: "train_val.prototxt" +solver_type: SGD diff --git a/cars/architecture-investigations/fc/1-layer/256/train_val.prototxt b/cars/architecture-investigations/fc/1-layer/256/train_val.prototxt new file mode 100644 index 0000000..86d1a9c --- /dev/null +++ b/cars/architecture-investigations/fc/1-layer/256/train_val.prototxt @@ -0,0 +1,342 @@ +layer { + name: "train-data" + type: "Data" + top: "data" + top: "label" + include { + phase: TRAIN + } + transform_param { + mirror: true + crop_size: 227 + mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" + } + data_param { + source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db" + batch_size: 128 + backend: LMDB + } +} +layer { + name: "val-data" + type: "Data" + top: "data" + top: "label" + include { + phase: TEST + } + transform_param { + crop_size: 227 + mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" + } + data_param { + source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db" + batch_size: 32 + backend: LMDB + } +} +layer { + name: "conv1" + type: "Convolution" + bottom: "data" + top: "conv1" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu1" + type: "ReLU" + bottom: "conv1" + top: "conv1" +} +layer { + name: "norm1" + type: "LRN" + bottom: "conv1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool1" + type: "Pooling" + bottom: "norm1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv2" + type: "Convolution" + bottom: "pool1" + top: "conv2" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu2" + type: "ReLU" + bottom: "conv2" + top: "conv2" +} +layer { + name: "norm2" + type: "LRN" + bottom: "conv2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool2" + type: "Pooling" + bottom: "norm2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv3" + type: "Convolution" + bottom: "pool2" + top: "conv3" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu3" + type: "ReLU" + bottom: "conv3" + top: "conv3" +} +layer { + name: "conv4" + type: "Convolution" + bottom: "conv3" + top: "conv4" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu4" + type: "ReLU" + bottom: "conv4" + top: "conv4" +} +layer { + name: "conv5" + type: "Convolution" + bottom: "conv4" + top: "conv5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu5" + type: "ReLU" + bottom: "conv5" + top: "conv5" +} +layer { + name: "pool5" + type: "Pooling" + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "fc6" + type: "InnerProduct" + bottom: "pool5" + top: "fc6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu6" + type: "ReLU" + bottom: "fc6" + top: "fc6" +} +layer { + name: "drop6" + type: "Dropout" + bottom: "fc6" + top: "fc6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc8" + type: "InnerProduct" + bottom: "fc6" + top: "fc8" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 196 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "accuracy" + type: "Accuracy" + bottom: "fc8" + bottom: "label" + top: "accuracy" + include { + phase: TEST + } +} +layer { + name: "loss" + type: "SoftmaxWithLoss" + bottom: "fc8" + bottom: "label" + top: "loss" +} diff --git a/cars/architecture-investigations/fc/2-layers/256/caffe_output.log b/cars/architecture-investigations/fc/2-layers/256/caffe_output.log new file mode 100644 index 0000000..795a532 --- /dev/null +++ b/cars/architecture-investigations/fc/2-layers/256/caffe_output.log @@ -0,0 +1,4566 @@ +I0410 13:29:11.132328 18414 upgrade_proto.cpp:1082] Attempting to upgrade input file specified using deprecated 'solver_type' field (enum)': /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210410-132909-6e23/solver.prototxt +I0410 13:29:11.132555 18414 upgrade_proto.cpp:1089] Successfully upgraded file specified using deprecated 'solver_type' field (enum) to 'type' field (string). +W0410 13:29:11.132565 18414 upgrade_proto.cpp:1091] Note that future Caffe releases will only support 'type' field (string) for a solver's type. +I0410 13:29:11.132664 18414 caffe.cpp:218] Using GPUs 1 +I0410 13:29:11.160727 18414 caffe.cpp:223] GPU 1: GeForce GTX 1080 Ti +I0410 13:29:11.455583 18414 solver.cpp:44] Initializing solver from parameters: +test_iter: 51 +test_interval: 102 +base_lr: 0.01 +display: 12 +max_iter: 10200 +lr_policy: "exp" +gamma: 0.99980193 +momentum: 0.9 +weight_decay: 0.0001 +snapshot: 102 +snapshot_prefix: "snapshot" +solver_mode: GPU +device_id: 1 +net: "train_val.prototxt" +train_state { +level: 0 +stage: "" +} +type: "SGD" +I0410 13:29:11.456357 18414 solver.cpp:87] Creating training net from net file: train_val.prototxt +I0410 13:29:11.456928 18414 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer val-data +I0410 13:29:11.456944 18414 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer accuracy +I0410 13:29:11.457085 18414 net.cpp:51] Initializing net from parameters: +state { +phase: TRAIN +level: 0 +stage: "" +} +layer { +name: "train-data" +type: "Data" +top: "data" +top: "label" +include { +phase: TRAIN +} +transform_param { +mirror: true +crop_size: 227 +mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" +} +data_param { +source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db" +batch_size: 128 +backend: LMDB +} +} +layer { +name: "conv1" +type: "Convolution" +bottom: "data" +top: "conv1" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 96 +kernel_size: 11 +stride: 4 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu1" +type: "ReLU" +bottom: "conv1" +top: "conv1" +} +layer { +name: "norm1" +type: "LRN" +bottom: "conv1" +top: "norm1" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool1" +type: "Pooling" +bottom: "norm1" +top: "pool1" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv2" +type: "Convolution" +bottom: "pool1" +top: "conv2" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 2 +kernel_size: 5 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu2" +type: "ReLU" +bottom: "conv2" +top: "conv2" +} +layer { +name: "norm2" +type: "LRN" +bottom: "conv2" +top: "norm2" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool2" +type: "Pooling" +bottom: "norm2" +top: "pool2" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv3" +type: "Convolution" +bottom: "pool2" +top: "conv3" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu3" +type: "ReLU" +bottom: "conv3" +top: "conv3" +} +layer { +name: "conv4" +type: "Convolution" +bottom: "conv3" +top: "conv4" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu4" +type: "ReLU" +bottom: "conv4" +top: "conv4" +} +layer { +name: "conv5" +type: "Convolution" +bottom: "conv4" +top: "conv5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu5" +type: "ReLU" +bottom: "conv5" +top: "conv5" +} +layer { +name: "pool5" +type: "Pooling" +bottom: "conv5" +top: "pool5" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "fc6" +type: "InnerProduct" +bottom: "pool5" +top: "fc6" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu6" +type: "ReLU" +bottom: "fc6" +top: "fc6" +} +layer { +name: "drop6" +type: "Dropout" +bottom: "fc6" +top: "fc6" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7" +type: "InnerProduct" +bottom: "fc6" +top: "fc7" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7" +type: "ReLU" +bottom: "fc7" +top: "fc7" +} +layer { +name: "drop7" +type: "Dropout" +bottom: "fc7" +top: "fc7" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc8" +type: "InnerProduct" +bottom: "fc7" +top: "fc8" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 196 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "loss" +type: "SoftmaxWithLoss" +bottom: "fc8" +bottom: "label" +top: "loss" +} +I0410 13:29:11.457176 18414 layer_factory.hpp:77] Creating layer train-data +I0410 13:29:11.458528 18414 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db +I0410 13:29:11.458734 18414 net.cpp:84] Creating Layer train-data +I0410 13:29:11.458745 18414 net.cpp:380] train-data -> data +I0410 13:29:11.458765 18414 net.cpp:380] train-data -> label +I0410 13:29:11.458776 18414 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto +I0410 13:29:11.463439 18414 data_layer.cpp:45] output data size: 128,3,227,227 +I0410 13:29:11.602185 18414 net.cpp:122] Setting up train-data +I0410 13:29:11.602208 18414 net.cpp:129] Top shape: 128 3 227 227 (19787136) +I0410 13:29:11.602214 18414 net.cpp:129] Top shape: 128 (128) +I0410 13:29:11.602217 18414 net.cpp:137] Memory required for data: 79149056 +I0410 13:29:11.602226 18414 layer_factory.hpp:77] Creating layer conv1 +I0410 13:29:11.602248 18414 net.cpp:84] Creating Layer conv1 +I0410 13:29:11.602254 18414 net.cpp:406] conv1 <- data +I0410 13:29:11.602267 18414 net.cpp:380] conv1 -> conv1 +I0410 13:29:12.171809 18414 net.cpp:122] Setting up conv1 +I0410 13:29:12.171830 18414 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:29:12.171834 18414 net.cpp:137] Memory required for data: 227833856 +I0410 13:29:12.171854 18414 layer_factory.hpp:77] Creating layer relu1 +I0410 13:29:12.171864 18414 net.cpp:84] Creating Layer relu1 +I0410 13:29:12.171869 18414 net.cpp:406] relu1 <- conv1 +I0410 13:29:12.171875 18414 net.cpp:367] relu1 -> conv1 (in-place) +I0410 13:29:12.172163 18414 net.cpp:122] Setting up relu1 +I0410 13:29:12.172171 18414 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:29:12.172175 18414 net.cpp:137] Memory required for data: 376518656 +I0410 13:29:12.172179 18414 layer_factory.hpp:77] Creating layer norm1 +I0410 13:29:12.172188 18414 net.cpp:84] Creating Layer norm1 +I0410 13:29:12.172191 18414 net.cpp:406] norm1 <- conv1 +I0410 13:29:12.172216 18414 net.cpp:380] norm1 -> norm1 +I0410 13:29:12.172655 18414 net.cpp:122] Setting up norm1 +I0410 13:29:12.172665 18414 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:29:12.172669 18414 net.cpp:137] Memory required for data: 525203456 +I0410 13:29:12.172673 18414 layer_factory.hpp:77] Creating layer pool1 +I0410 13:29:12.172681 18414 net.cpp:84] Creating Layer pool1 +I0410 13:29:12.172684 18414 net.cpp:406] pool1 <- norm1 +I0410 13:29:12.172690 18414 net.cpp:380] pool1 -> pool1 +I0410 13:29:12.172725 18414 net.cpp:122] Setting up pool1 +I0410 13:29:12.172732 18414 net.cpp:129] Top shape: 128 96 27 27 (8957952) +I0410 13:29:12.172735 18414 net.cpp:137] Memory required for data: 561035264 +I0410 13:29:12.172739 18414 layer_factory.hpp:77] Creating layer conv2 +I0410 13:29:12.172749 18414 net.cpp:84] Creating Layer conv2 +I0410 13:29:12.172752 18414 net.cpp:406] conv2 <- pool1 +I0410 13:29:12.172758 18414 net.cpp:380] conv2 -> conv2 +I0410 13:29:12.180650 18414 net.cpp:122] Setting up conv2 +I0410 13:29:12.180666 18414 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:29:12.180670 18414 net.cpp:137] Memory required for data: 656586752 +I0410 13:29:12.180680 18414 layer_factory.hpp:77] Creating layer relu2 +I0410 13:29:12.180688 18414 net.cpp:84] Creating Layer relu2 +I0410 13:29:12.180691 18414 net.cpp:406] relu2 <- conv2 +I0410 13:29:12.180697 18414 net.cpp:367] relu2 -> conv2 (in-place) +I0410 13:29:12.181121 18414 net.cpp:122] Setting up relu2 +I0410 13:29:12.181130 18414 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:29:12.181134 18414 net.cpp:137] Memory required for data: 752138240 +I0410 13:29:12.181138 18414 layer_factory.hpp:77] Creating layer norm2 +I0410 13:29:12.181145 18414 net.cpp:84] Creating Layer norm2 +I0410 13:29:12.181149 18414 net.cpp:406] norm2 <- conv2 +I0410 13:29:12.181154 18414 net.cpp:380] norm2 -> norm2 +I0410 13:29:12.181437 18414 net.cpp:122] Setting up norm2 +I0410 13:29:12.181445 18414 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:29:12.181448 18414 net.cpp:137] Memory required for data: 847689728 +I0410 13:29:12.181452 18414 layer_factory.hpp:77] Creating layer pool2 +I0410 13:29:12.181459 18414 net.cpp:84] Creating Layer pool2 +I0410 13:29:12.181463 18414 net.cpp:406] pool2 <- norm2 +I0410 13:29:12.181468 18414 net.cpp:380] pool2 -> pool2 +I0410 13:29:12.181494 18414 net.cpp:122] Setting up pool2 +I0410 13:29:12.181499 18414 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:29:12.181502 18414 net.cpp:137] Memory required for data: 869840896 +I0410 13:29:12.181505 18414 layer_factory.hpp:77] Creating layer conv3 +I0410 13:29:12.181514 18414 net.cpp:84] Creating Layer conv3 +I0410 13:29:12.181517 18414 net.cpp:406] conv3 <- pool2 +I0410 13:29:12.181522 18414 net.cpp:380] conv3 -> conv3 +I0410 13:29:12.191294 18414 net.cpp:122] Setting up conv3 +I0410 13:29:12.191306 18414 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:29:12.191309 18414 net.cpp:137] Memory required for data: 903067648 +I0410 13:29:12.191319 18414 layer_factory.hpp:77] Creating layer relu3 +I0410 13:29:12.191326 18414 net.cpp:84] Creating Layer relu3 +I0410 13:29:12.191330 18414 net.cpp:406] relu3 <- conv3 +I0410 13:29:12.191335 18414 net.cpp:367] relu3 -> conv3 (in-place) +I0410 13:29:12.191756 18414 net.cpp:122] Setting up relu3 +I0410 13:29:12.191766 18414 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:29:12.191769 18414 net.cpp:137] Memory required for data: 936294400 +I0410 13:29:12.191772 18414 layer_factory.hpp:77] Creating layer conv4 +I0410 13:29:12.191782 18414 net.cpp:84] Creating Layer conv4 +I0410 13:29:12.191787 18414 net.cpp:406] conv4 <- conv3 +I0410 13:29:12.191792 18414 net.cpp:380] conv4 -> conv4 +I0410 13:29:12.202033 18414 net.cpp:122] Setting up conv4 +I0410 13:29:12.202045 18414 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:29:12.202049 18414 net.cpp:137] Memory required for data: 969521152 +I0410 13:29:12.202056 18414 layer_factory.hpp:77] Creating layer relu4 +I0410 13:29:12.202064 18414 net.cpp:84] Creating Layer relu4 +I0410 13:29:12.202086 18414 net.cpp:406] relu4 <- conv4 +I0410 13:29:12.202092 18414 net.cpp:367] relu4 -> conv4 (in-place) +I0410 13:29:12.202430 18414 net.cpp:122] Setting up relu4 +I0410 13:29:12.202437 18414 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:29:12.202440 18414 net.cpp:137] Memory required for data: 1002747904 +I0410 13:29:12.202445 18414 layer_factory.hpp:77] Creating layer conv5 +I0410 13:29:12.202455 18414 net.cpp:84] Creating Layer conv5 +I0410 13:29:12.202458 18414 net.cpp:406] conv5 <- conv4 +I0410 13:29:12.202466 18414 net.cpp:380] conv5 -> conv5 +I0410 13:29:12.210791 18414 net.cpp:122] Setting up conv5 +I0410 13:29:12.210804 18414 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:29:12.210808 18414 net.cpp:137] Memory required for data: 1024899072 +I0410 13:29:12.210819 18414 layer_factory.hpp:77] Creating layer relu5 +I0410 13:29:12.210827 18414 net.cpp:84] Creating Layer relu5 +I0410 13:29:12.210830 18414 net.cpp:406] relu5 <- conv5 +I0410 13:29:12.210836 18414 net.cpp:367] relu5 -> conv5 (in-place) +I0410 13:29:12.211318 18414 net.cpp:122] Setting up relu5 +I0410 13:29:12.211329 18414 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:29:12.211333 18414 net.cpp:137] Memory required for data: 1047050240 +I0410 13:29:12.211336 18414 layer_factory.hpp:77] Creating layer pool5 +I0410 13:29:12.211344 18414 net.cpp:84] Creating Layer pool5 +I0410 13:29:12.211346 18414 net.cpp:406] pool5 <- conv5 +I0410 13:29:12.211352 18414 net.cpp:380] pool5 -> pool5 +I0410 13:29:12.211390 18414 net.cpp:122] Setting up pool5 +I0410 13:29:12.211396 18414 net.cpp:129] Top shape: 128 256 6 6 (1179648) +I0410 13:29:12.211400 18414 net.cpp:137] Memory required for data: 1051768832 +I0410 13:29:12.211402 18414 layer_factory.hpp:77] Creating layer fc6 +I0410 13:29:12.211411 18414 net.cpp:84] Creating Layer fc6 +I0410 13:29:12.211416 18414 net.cpp:406] fc6 <- pool5 +I0410 13:29:12.211421 18414 net.cpp:380] fc6 -> fc6 +I0410 13:29:12.233635 18414 net.cpp:122] Setting up fc6 +I0410 13:29:12.233650 18414 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:12.233654 18414 net.cpp:137] Memory required for data: 1051899904 +I0410 13:29:12.233662 18414 layer_factory.hpp:77] Creating layer relu6 +I0410 13:29:12.233670 18414 net.cpp:84] Creating Layer relu6 +I0410 13:29:12.233675 18414 net.cpp:406] relu6 <- fc6 +I0410 13:29:12.233680 18414 net.cpp:367] relu6 -> fc6 (in-place) +I0410 13:29:12.234284 18414 net.cpp:122] Setting up relu6 +I0410 13:29:12.234294 18414 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:12.234297 18414 net.cpp:137] Memory required for data: 1052030976 +I0410 13:29:12.234302 18414 layer_factory.hpp:77] Creating layer drop6 +I0410 13:29:12.234308 18414 net.cpp:84] Creating Layer drop6 +I0410 13:29:12.234313 18414 net.cpp:406] drop6 <- fc6 +I0410 13:29:12.234318 18414 net.cpp:367] drop6 -> fc6 (in-place) +I0410 13:29:12.234347 18414 net.cpp:122] Setting up drop6 +I0410 13:29:12.234352 18414 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:12.234356 18414 net.cpp:137] Memory required for data: 1052162048 +I0410 13:29:12.234360 18414 layer_factory.hpp:77] Creating layer fc7 +I0410 13:29:12.234369 18414 net.cpp:84] Creating Layer fc7 +I0410 13:29:12.234371 18414 net.cpp:406] fc7 <- fc6 +I0410 13:29:12.234377 18414 net.cpp:380] fc7 -> fc7 +I0410 13:29:12.235016 18414 net.cpp:122] Setting up fc7 +I0410 13:29:12.235023 18414 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:12.235026 18414 net.cpp:137] Memory required for data: 1052293120 +I0410 13:29:12.235033 18414 layer_factory.hpp:77] Creating layer relu7 +I0410 13:29:12.235038 18414 net.cpp:84] Creating Layer relu7 +I0410 13:29:12.235041 18414 net.cpp:406] relu7 <- fc7 +I0410 13:29:12.235046 18414 net.cpp:367] relu7 -> fc7 (in-place) +I0410 13:29:12.235522 18414 net.cpp:122] Setting up relu7 +I0410 13:29:12.235532 18414 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:12.235534 18414 net.cpp:137] Memory required for data: 1052424192 +I0410 13:29:12.235539 18414 layer_factory.hpp:77] Creating layer drop7 +I0410 13:29:12.235545 18414 net.cpp:84] Creating Layer drop7 +I0410 13:29:12.235549 18414 net.cpp:406] drop7 <- fc7 +I0410 13:29:12.235571 18414 net.cpp:367] drop7 -> fc7 (in-place) +I0410 13:29:12.235597 18414 net.cpp:122] Setting up drop7 +I0410 13:29:12.235602 18414 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:12.235606 18414 net.cpp:137] Memory required for data: 1052555264 +I0410 13:29:12.235610 18414 layer_factory.hpp:77] Creating layer fc8 +I0410 13:29:12.235616 18414 net.cpp:84] Creating Layer fc8 +I0410 13:29:12.235620 18414 net.cpp:406] fc8 <- fc7 +I0410 13:29:12.235626 18414 net.cpp:380] fc8 -> fc8 +I0410 13:29:12.236143 18414 net.cpp:122] Setting up fc8 +I0410 13:29:12.236150 18414 net.cpp:129] Top shape: 128 196 (25088) +I0410 13:29:12.236152 18414 net.cpp:137] Memory required for data: 1052655616 +I0410 13:29:12.236158 18414 layer_factory.hpp:77] Creating layer loss +I0410 13:29:12.236166 18414 net.cpp:84] Creating Layer loss +I0410 13:29:12.236168 18414 net.cpp:406] loss <- fc8 +I0410 13:29:12.236172 18414 net.cpp:406] loss <- label +I0410 13:29:12.236179 18414 net.cpp:380] loss -> loss +I0410 13:29:12.236188 18414 layer_factory.hpp:77] Creating layer loss +I0410 13:29:12.236773 18414 net.cpp:122] Setting up loss +I0410 13:29:12.236781 18414 net.cpp:129] Top shape: (1) +I0410 13:29:12.236785 18414 net.cpp:132] with loss weight 1 +I0410 13:29:12.236802 18414 net.cpp:137] Memory required for data: 1052655620 +I0410 13:29:12.236806 18414 net.cpp:198] loss needs backward computation. +I0410 13:29:12.236814 18414 net.cpp:198] fc8 needs backward computation. +I0410 13:29:12.236817 18414 net.cpp:198] drop7 needs backward computation. +I0410 13:29:12.236821 18414 net.cpp:198] relu7 needs backward computation. +I0410 13:29:12.236825 18414 net.cpp:198] fc7 needs backward computation. +I0410 13:29:12.236829 18414 net.cpp:198] drop6 needs backward computation. +I0410 13:29:12.236832 18414 net.cpp:198] relu6 needs backward computation. +I0410 13:29:12.236836 18414 net.cpp:198] fc6 needs backward computation. +I0410 13:29:12.236841 18414 net.cpp:198] pool5 needs backward computation. +I0410 13:29:12.236845 18414 net.cpp:198] relu5 needs backward computation. +I0410 13:29:12.236848 18414 net.cpp:198] conv5 needs backward computation. +I0410 13:29:12.236851 18414 net.cpp:198] relu4 needs backward computation. +I0410 13:29:12.236855 18414 net.cpp:198] conv4 needs backward computation. +I0410 13:29:12.236860 18414 net.cpp:198] relu3 needs backward computation. +I0410 13:29:12.236863 18414 net.cpp:198] conv3 needs backward computation. +I0410 13:29:12.236867 18414 net.cpp:198] pool2 needs backward computation. +I0410 13:29:12.236871 18414 net.cpp:198] norm2 needs backward computation. +I0410 13:29:12.236874 18414 net.cpp:198] relu2 needs backward computation. +I0410 13:29:12.236878 18414 net.cpp:198] conv2 needs backward computation. +I0410 13:29:12.236882 18414 net.cpp:198] pool1 needs backward computation. +I0410 13:29:12.236886 18414 net.cpp:198] norm1 needs backward computation. +I0410 13:29:12.236891 18414 net.cpp:198] relu1 needs backward computation. +I0410 13:29:12.236893 18414 net.cpp:198] conv1 needs backward computation. +I0410 13:29:12.236898 18414 net.cpp:200] train-data does not need backward computation. +I0410 13:29:12.236901 18414 net.cpp:242] This network produces output loss +I0410 13:29:12.236915 18414 net.cpp:255] Network initialization done. +I0410 13:29:12.237438 18414 solver.cpp:172] Creating test net (#0) specified by net file: train_val.prototxt +I0410 13:29:12.237470 18414 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer train-data +I0410 13:29:12.237617 18414 net.cpp:51] Initializing net from parameters: +state { +phase: TEST +} +layer { +name: "val-data" +type: "Data" +top: "data" +top: "label" +include { +phase: TEST +} +transform_param { +crop_size: 227 +mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" +} +data_param { +source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db" +batch_size: 32 +backend: LMDB +} +} +layer { +name: "conv1" +type: "Convolution" +bottom: "data" +top: "conv1" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 96 +kernel_size: 11 +stride: 4 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu1" +type: "ReLU" +bottom: "conv1" +top: "conv1" +} +layer { +name: "norm1" +type: "LRN" +bottom: "conv1" +top: "norm1" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool1" +type: "Pooling" +bottom: "norm1" +top: "pool1" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv2" +type: "Convolution" +bottom: "pool1" +top: "conv2" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 2 +kernel_size: 5 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu2" +type: "ReLU" +bottom: "conv2" +top: "conv2" +} +layer { +name: "norm2" +type: "LRN" +bottom: "conv2" +top: "norm2" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool2" +type: "Pooling" +bottom: "norm2" +top: "pool2" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv3" +type: "Convolution" +bottom: "pool2" +top: "conv3" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu3" +type: "ReLU" +bottom: "conv3" +top: "conv3" +} +layer { +name: "conv4" +type: "Convolution" +bottom: "conv3" +top: "conv4" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu4" +type: "ReLU" +bottom: "conv4" +top: "conv4" +} +layer { +name: "conv5" +type: "Convolution" +bottom: "conv4" +top: "conv5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu5" +type: "ReLU" +bottom: "conv5" +top: "conv5" +} +layer { +name: "pool5" +type: "Pooling" +bottom: "conv5" +top: "pool5" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "fc6" +type: "InnerProduct" +bottom: "pool5" +top: "fc6" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu6" +type: "ReLU" +bottom: "fc6" +top: "fc6" +} +layer { +name: "drop6" +type: "Dropout" +bottom: "fc6" +top: "fc6" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7" +type: "InnerProduct" +bottom: "fc6" +top: "fc7" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7" +type: "ReLU" +bottom: "fc7" +top: "fc7" +} +layer { +name: "drop7" +type: "Dropout" +bottom: "fc7" +top: "fc7" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc8" +type: "InnerProduct" +bottom: "fc7" +top: "fc8" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 196 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "accuracy" +type: "Accuracy" +bottom: "fc8" +bottom: "label" +top: "accuracy" +include { +phase: TEST +} +} +layer { +name: "loss" +type: "SoftmaxWithLoss" +bottom: "fc8" +bottom: "label" +top: "loss" +} +I0410 13:29:12.237707 18414 layer_factory.hpp:77] Creating layer val-data +I0410 13:29:12.239034 18414 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db +I0410 13:29:12.239235 18414 net.cpp:84] Creating Layer val-data +I0410 13:29:12.239246 18414 net.cpp:380] val-data -> data +I0410 13:29:12.239254 18414 net.cpp:380] val-data -> label +I0410 13:29:12.239262 18414 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto +I0410 13:29:12.243901 18414 data_layer.cpp:45] output data size: 32,3,227,227 +I0410 13:29:12.276731 18414 net.cpp:122] Setting up val-data +I0410 13:29:12.276749 18414 net.cpp:129] Top shape: 32 3 227 227 (4946784) +I0410 13:29:12.276754 18414 net.cpp:129] Top shape: 32 (32) +I0410 13:29:12.276758 18414 net.cpp:137] Memory required for data: 19787264 +I0410 13:29:12.276764 18414 layer_factory.hpp:77] Creating layer label_val-data_1_split +I0410 13:29:12.276777 18414 net.cpp:84] Creating Layer label_val-data_1_split +I0410 13:29:12.276782 18414 net.cpp:406] label_val-data_1_split <- label +I0410 13:29:12.276789 18414 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_0 +I0410 13:29:12.276798 18414 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_1 +I0410 13:29:12.276841 18414 net.cpp:122] Setting up label_val-data_1_split +I0410 13:29:12.276847 18414 net.cpp:129] Top shape: 32 (32) +I0410 13:29:12.276851 18414 net.cpp:129] Top shape: 32 (32) +I0410 13:29:12.276854 18414 net.cpp:137] Memory required for data: 19787520 +I0410 13:29:12.276857 18414 layer_factory.hpp:77] Creating layer conv1 +I0410 13:29:12.276868 18414 net.cpp:84] Creating Layer conv1 +I0410 13:29:12.276872 18414 net.cpp:406] conv1 <- data +I0410 13:29:12.276878 18414 net.cpp:380] conv1 -> conv1 +I0410 13:29:12.279009 18414 net.cpp:122] Setting up conv1 +I0410 13:29:12.279021 18414 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:29:12.279024 18414 net.cpp:137] Memory required for data: 56958720 +I0410 13:29:12.279034 18414 layer_factory.hpp:77] Creating layer relu1 +I0410 13:29:12.279042 18414 net.cpp:84] Creating Layer relu1 +I0410 13:29:12.279047 18414 net.cpp:406] relu1 <- conv1 +I0410 13:29:12.279052 18414 net.cpp:367] relu1 -> conv1 (in-place) +I0410 13:29:12.279341 18414 net.cpp:122] Setting up relu1 +I0410 13:29:12.279350 18414 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:29:12.279354 18414 net.cpp:137] Memory required for data: 94129920 +I0410 13:29:12.279358 18414 layer_factory.hpp:77] Creating layer norm1 +I0410 13:29:12.279366 18414 net.cpp:84] Creating Layer norm1 +I0410 13:29:12.279371 18414 net.cpp:406] norm1 <- conv1 +I0410 13:29:12.279376 18414 net.cpp:380] norm1 -> norm1 +I0410 13:29:12.279829 18414 net.cpp:122] Setting up norm1 +I0410 13:29:12.279839 18414 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:29:12.279844 18414 net.cpp:137] Memory required for data: 131301120 +I0410 13:29:12.279846 18414 layer_factory.hpp:77] Creating layer pool1 +I0410 13:29:12.279853 18414 net.cpp:84] Creating Layer pool1 +I0410 13:29:12.279857 18414 net.cpp:406] pool1 <- norm1 +I0410 13:29:12.279862 18414 net.cpp:380] pool1 -> pool1 +I0410 13:29:12.279891 18414 net.cpp:122] Setting up pool1 +I0410 13:29:12.279896 18414 net.cpp:129] Top shape: 32 96 27 27 (2239488) +I0410 13:29:12.279899 18414 net.cpp:137] Memory required for data: 140259072 +I0410 13:29:12.279903 18414 layer_factory.hpp:77] Creating layer conv2 +I0410 13:29:12.279911 18414 net.cpp:84] Creating Layer conv2 +I0410 13:29:12.279914 18414 net.cpp:406] conv2 <- pool1 +I0410 13:29:12.279937 18414 net.cpp:380] conv2 -> conv2 +I0410 13:29:12.291481 18414 net.cpp:122] Setting up conv2 +I0410 13:29:12.291496 18414 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:29:12.291499 18414 net.cpp:137] Memory required for data: 164146944 +I0410 13:29:12.291509 18414 layer_factory.hpp:77] Creating layer relu2 +I0410 13:29:12.291517 18414 net.cpp:84] Creating Layer relu2 +I0410 13:29:12.291522 18414 net.cpp:406] relu2 <- conv2 +I0410 13:29:12.291528 18414 net.cpp:367] relu2 -> conv2 (in-place) +I0410 13:29:12.292035 18414 net.cpp:122] Setting up relu2 +I0410 13:29:12.292047 18414 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:29:12.292050 18414 net.cpp:137] Memory required for data: 188034816 +I0410 13:29:12.292054 18414 layer_factory.hpp:77] Creating layer norm2 +I0410 13:29:12.292064 18414 net.cpp:84] Creating Layer norm2 +I0410 13:29:12.292068 18414 net.cpp:406] norm2 <- conv2 +I0410 13:29:12.292074 18414 net.cpp:380] norm2 -> norm2 +I0410 13:29:12.292591 18414 net.cpp:122] Setting up norm2 +I0410 13:29:12.292601 18414 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:29:12.292606 18414 net.cpp:137] Memory required for data: 211922688 +I0410 13:29:12.292610 18414 layer_factory.hpp:77] Creating layer pool2 +I0410 13:29:12.292618 18414 net.cpp:84] Creating Layer pool2 +I0410 13:29:12.292620 18414 net.cpp:406] pool2 <- norm2 +I0410 13:29:12.292626 18414 net.cpp:380] pool2 -> pool2 +I0410 13:29:12.292659 18414 net.cpp:122] Setting up pool2 +I0410 13:29:12.292665 18414 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:29:12.292668 18414 net.cpp:137] Memory required for data: 217460480 +I0410 13:29:12.292672 18414 layer_factory.hpp:77] Creating layer conv3 +I0410 13:29:12.292681 18414 net.cpp:84] Creating Layer conv3 +I0410 13:29:12.292685 18414 net.cpp:406] conv3 <- pool2 +I0410 13:29:12.292692 18414 net.cpp:380] conv3 -> conv3 +I0410 13:29:12.303673 18414 net.cpp:122] Setting up conv3 +I0410 13:29:12.303689 18414 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:29:12.303692 18414 net.cpp:137] Memory required for data: 225767168 +I0410 13:29:12.303704 18414 layer_factory.hpp:77] Creating layer relu3 +I0410 13:29:12.303712 18414 net.cpp:84] Creating Layer relu3 +I0410 13:29:12.303717 18414 net.cpp:406] relu3 <- conv3 +I0410 13:29:12.303723 18414 net.cpp:367] relu3 -> conv3 (in-place) +I0410 13:29:12.304247 18414 net.cpp:122] Setting up relu3 +I0410 13:29:12.304256 18414 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:29:12.304260 18414 net.cpp:137] Memory required for data: 234073856 +I0410 13:29:12.304263 18414 layer_factory.hpp:77] Creating layer conv4 +I0410 13:29:12.304275 18414 net.cpp:84] Creating Layer conv4 +I0410 13:29:12.304278 18414 net.cpp:406] conv4 <- conv3 +I0410 13:29:12.304286 18414 net.cpp:380] conv4 -> conv4 +I0410 13:29:12.313686 18414 net.cpp:122] Setting up conv4 +I0410 13:29:12.313700 18414 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:29:12.313704 18414 net.cpp:137] Memory required for data: 242380544 +I0410 13:29:12.313711 18414 layer_factory.hpp:77] Creating layer relu4 +I0410 13:29:12.313717 18414 net.cpp:84] Creating Layer relu4 +I0410 13:29:12.313721 18414 net.cpp:406] relu4 <- conv4 +I0410 13:29:12.313727 18414 net.cpp:367] relu4 -> conv4 (in-place) +I0410 13:29:12.314086 18414 net.cpp:122] Setting up relu4 +I0410 13:29:12.314095 18414 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:29:12.314098 18414 net.cpp:137] Memory required for data: 250687232 +I0410 13:29:12.314101 18414 layer_factory.hpp:77] Creating layer conv5 +I0410 13:29:12.314112 18414 net.cpp:84] Creating Layer conv5 +I0410 13:29:12.314116 18414 net.cpp:406] conv5 <- conv4 +I0410 13:29:12.314122 18414 net.cpp:380] conv5 -> conv5 +I0410 13:29:12.324683 18414 net.cpp:122] Setting up conv5 +I0410 13:29:12.324699 18414 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:29:12.324703 18414 net.cpp:137] Memory required for data: 256225024 +I0410 13:29:12.324715 18414 layer_factory.hpp:77] Creating layer relu5 +I0410 13:29:12.324723 18414 net.cpp:84] Creating Layer relu5 +I0410 13:29:12.324728 18414 net.cpp:406] relu5 <- conv5 +I0410 13:29:12.324751 18414 net.cpp:367] relu5 -> conv5 (in-place) +I0410 13:29:12.325245 18414 net.cpp:122] Setting up relu5 +I0410 13:29:12.325256 18414 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:29:12.325259 18414 net.cpp:137] Memory required for data: 261762816 +I0410 13:29:12.325263 18414 layer_factory.hpp:77] Creating layer pool5 +I0410 13:29:12.325273 18414 net.cpp:84] Creating Layer pool5 +I0410 13:29:12.325278 18414 net.cpp:406] pool5 <- conv5 +I0410 13:29:12.325284 18414 net.cpp:380] pool5 -> pool5 +I0410 13:29:12.325321 18414 net.cpp:122] Setting up pool5 +I0410 13:29:12.325328 18414 net.cpp:129] Top shape: 32 256 6 6 (294912) +I0410 13:29:12.325331 18414 net.cpp:137] Memory required for data: 262942464 +I0410 13:29:12.325335 18414 layer_factory.hpp:77] Creating layer fc6 +I0410 13:29:12.325341 18414 net.cpp:84] Creating Layer fc6 +I0410 13:29:12.325345 18414 net.cpp:406] fc6 <- pool5 +I0410 13:29:12.325350 18414 net.cpp:380] fc6 -> fc6 +I0410 13:29:12.348320 18414 net.cpp:122] Setting up fc6 +I0410 13:29:12.348340 18414 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:12.348342 18414 net.cpp:137] Memory required for data: 262975232 +I0410 13:29:12.348352 18414 layer_factory.hpp:77] Creating layer relu6 +I0410 13:29:12.348361 18414 net.cpp:84] Creating Layer relu6 +I0410 13:29:12.348366 18414 net.cpp:406] relu6 <- fc6 +I0410 13:29:12.348371 18414 net.cpp:367] relu6 -> fc6 (in-place) +I0410 13:29:12.349212 18414 net.cpp:122] Setting up relu6 +I0410 13:29:12.349221 18414 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:12.349225 18414 net.cpp:137] Memory required for data: 263008000 +I0410 13:29:12.349228 18414 layer_factory.hpp:77] Creating layer drop6 +I0410 13:29:12.349234 18414 net.cpp:84] Creating Layer drop6 +I0410 13:29:12.349238 18414 net.cpp:406] drop6 <- fc6 +I0410 13:29:12.349246 18414 net.cpp:367] drop6 -> fc6 (in-place) +I0410 13:29:12.349272 18414 net.cpp:122] Setting up drop6 +I0410 13:29:12.349277 18414 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:12.349282 18414 net.cpp:137] Memory required for data: 263040768 +I0410 13:29:12.349284 18414 layer_factory.hpp:77] Creating layer fc7 +I0410 13:29:12.349292 18414 net.cpp:84] Creating Layer fc7 +I0410 13:29:12.349294 18414 net.cpp:406] fc7 <- fc6 +I0410 13:29:12.349300 18414 net.cpp:380] fc7 -> fc7 +I0410 13:29:12.349946 18414 net.cpp:122] Setting up fc7 +I0410 13:29:12.349952 18414 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:12.349968 18414 net.cpp:137] Memory required for data: 263073536 +I0410 13:29:12.349974 18414 layer_factory.hpp:77] Creating layer relu7 +I0410 13:29:12.349980 18414 net.cpp:84] Creating Layer relu7 +I0410 13:29:12.349983 18414 net.cpp:406] relu7 <- fc7 +I0410 13:29:12.349988 18414 net.cpp:367] relu7 -> fc7 (in-place) +I0410 13:29:12.350343 18414 net.cpp:122] Setting up relu7 +I0410 13:29:12.350351 18414 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:12.350354 18414 net.cpp:137] Memory required for data: 263106304 +I0410 13:29:12.350358 18414 layer_factory.hpp:77] Creating layer drop7 +I0410 13:29:12.350364 18414 net.cpp:84] Creating Layer drop7 +I0410 13:29:12.350368 18414 net.cpp:406] drop7 <- fc7 +I0410 13:29:12.350373 18414 net.cpp:367] drop7 -> fc7 (in-place) +I0410 13:29:12.350395 18414 net.cpp:122] Setting up drop7 +I0410 13:29:12.350400 18414 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:12.350404 18414 net.cpp:137] Memory required for data: 263139072 +I0410 13:29:12.350406 18414 layer_factory.hpp:77] Creating layer fc8 +I0410 13:29:12.350412 18414 net.cpp:84] Creating Layer fc8 +I0410 13:29:12.350416 18414 net.cpp:406] fc8 <- fc7 +I0410 13:29:12.350421 18414 net.cpp:380] fc8 -> fc8 +I0410 13:29:12.350946 18414 net.cpp:122] Setting up fc8 +I0410 13:29:12.350953 18414 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:29:12.350956 18414 net.cpp:137] Memory required for data: 263164160 +I0410 13:29:12.350962 18414 layer_factory.hpp:77] Creating layer fc8_fc8_0_split +I0410 13:29:12.350967 18414 net.cpp:84] Creating Layer fc8_fc8_0_split +I0410 13:29:12.350971 18414 net.cpp:406] fc8_fc8_0_split <- fc8 +I0410 13:29:12.350977 18414 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_0 +I0410 13:29:12.351001 18414 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_1 +I0410 13:29:12.351033 18414 net.cpp:122] Setting up fc8_fc8_0_split +I0410 13:29:12.351039 18414 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:29:12.351042 18414 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:29:12.351045 18414 net.cpp:137] Memory required for data: 263214336 +I0410 13:29:12.351048 18414 layer_factory.hpp:77] Creating layer accuracy +I0410 13:29:12.351055 18414 net.cpp:84] Creating Layer accuracy +I0410 13:29:12.351058 18414 net.cpp:406] accuracy <- fc8_fc8_0_split_0 +I0410 13:29:12.351063 18414 net.cpp:406] accuracy <- label_val-data_1_split_0 +I0410 13:29:12.351069 18414 net.cpp:380] accuracy -> accuracy +I0410 13:29:12.351076 18414 net.cpp:122] Setting up accuracy +I0410 13:29:12.351080 18414 net.cpp:129] Top shape: (1) +I0410 13:29:12.351083 18414 net.cpp:137] Memory required for data: 263214340 +I0410 13:29:12.351086 18414 layer_factory.hpp:77] Creating layer loss +I0410 13:29:12.351092 18414 net.cpp:84] Creating Layer loss +I0410 13:29:12.351095 18414 net.cpp:406] loss <- fc8_fc8_0_split_1 +I0410 13:29:12.351099 18414 net.cpp:406] loss <- label_val-data_1_split_1 +I0410 13:29:12.351104 18414 net.cpp:380] loss -> loss +I0410 13:29:12.351111 18414 layer_factory.hpp:77] Creating layer loss +I0410 13:29:12.351688 18414 net.cpp:122] Setting up loss +I0410 13:29:12.351697 18414 net.cpp:129] Top shape: (1) +I0410 13:29:12.351701 18414 net.cpp:132] with loss weight 1 +I0410 13:29:12.351711 18414 net.cpp:137] Memory required for data: 263214344 +I0410 13:29:12.351714 18414 net.cpp:198] loss needs backward computation. +I0410 13:29:12.351719 18414 net.cpp:200] accuracy does not need backward computation. +I0410 13:29:12.351723 18414 net.cpp:198] fc8_fc8_0_split needs backward computation. +I0410 13:29:12.351727 18414 net.cpp:198] fc8 needs backward computation. +I0410 13:29:12.351729 18414 net.cpp:198] drop7 needs backward computation. +I0410 13:29:12.351732 18414 net.cpp:198] relu7 needs backward computation. +I0410 13:29:12.351737 18414 net.cpp:198] fc7 needs backward computation. +I0410 13:29:12.351739 18414 net.cpp:198] drop6 needs backward computation. +I0410 13:29:12.351742 18414 net.cpp:198] relu6 needs backward computation. +I0410 13:29:12.351745 18414 net.cpp:198] fc6 needs backward computation. +I0410 13:29:12.351748 18414 net.cpp:198] pool5 needs backward computation. +I0410 13:29:12.351752 18414 net.cpp:198] relu5 needs backward computation. +I0410 13:29:12.351755 18414 net.cpp:198] conv5 needs backward computation. +I0410 13:29:12.351759 18414 net.cpp:198] relu4 needs backward computation. +I0410 13:29:12.351763 18414 net.cpp:198] conv4 needs backward computation. +I0410 13:29:12.351765 18414 net.cpp:198] relu3 needs backward computation. +I0410 13:29:12.351768 18414 net.cpp:198] conv3 needs backward computation. +I0410 13:29:12.351773 18414 net.cpp:198] pool2 needs backward computation. +I0410 13:29:12.351775 18414 net.cpp:198] norm2 needs backward computation. +I0410 13:29:12.351779 18414 net.cpp:198] relu2 needs backward computation. +I0410 13:29:12.351783 18414 net.cpp:198] conv2 needs backward computation. +I0410 13:29:12.351785 18414 net.cpp:198] pool1 needs backward computation. +I0410 13:29:12.351789 18414 net.cpp:198] norm1 needs backward computation. +I0410 13:29:12.351792 18414 net.cpp:198] relu1 needs backward computation. +I0410 13:29:12.351795 18414 net.cpp:198] conv1 needs backward computation. +I0410 13:29:12.351799 18414 net.cpp:200] label_val-data_1_split does not need backward computation. +I0410 13:29:12.351804 18414 net.cpp:200] val-data does not need backward computation. +I0410 13:29:12.351809 18414 net.cpp:242] This network produces output accuracy +I0410 13:29:12.351811 18414 net.cpp:242] This network produces output loss +I0410 13:29:12.351828 18414 net.cpp:255] Network initialization done. +I0410 13:29:12.351910 18414 solver.cpp:56] Solver scaffolding done. +I0410 13:29:12.352341 18414 caffe.cpp:248] Starting Optimization +I0410 13:29:12.352350 18414 solver.cpp:272] Solving +I0410 13:29:12.352355 18414 solver.cpp:273] Learning Rate Policy: exp +I0410 13:29:12.353152 18414 solver.cpp:330] Iteration 0, Testing net (#0) +I0410 13:29:12.353163 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:29:12.355518 18414 blocking_queue.cpp:49] Waiting for data +I0410 13:29:16.928656 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:29:16.972996 18414 solver.cpp:397] Test net output #0: accuracy = 0.00796569 +I0410 13:29:16.973042 18414 solver.cpp:397] Test net output #1: loss = 5.27825 (* 1 = 5.27825 loss) +I0410 13:29:17.060310 18414 solver.cpp:218] Iteration 0 (9.03957e+36 iter/s, 4.70775s/12 iters), loss = 5.27781 +I0410 13:29:17.061883 18414 solver.cpp:237] Train net output #0: loss = 5.27781 (* 1 = 5.27781 loss) +I0410 13:29:17.061901 18414 sgd_solver.cpp:105] Iteration 0, lr = 0.01 +I0410 13:29:20.970299 18414 solver.cpp:218] Iteration 12 (3.07041 iter/s, 3.90828s/12 iters), loss = 5.27916 +I0410 13:29:20.970337 18414 solver.cpp:237] Train net output #0: loss = 5.27916 (* 1 = 5.27916 loss) +I0410 13:29:20.970346 18414 sgd_solver.cpp:105] Iteration 12, lr = 0.00997626 +I0410 13:29:25.779376 18414 solver.cpp:218] Iteration 24 (2.49539 iter/s, 4.80887s/12 iters), loss = 5.28016 +I0410 13:29:25.779422 18414 solver.cpp:237] Train net output #0: loss = 5.28016 (* 1 = 5.28016 loss) +I0410 13:29:25.779433 18414 sgd_solver.cpp:105] Iteration 24, lr = 0.00995257 +I0410 13:29:30.566710 18414 solver.cpp:218] Iteration 36 (2.50673 iter/s, 4.78712s/12 iters), loss = 5.27703 +I0410 13:29:30.566757 18414 solver.cpp:237] Train net output #0: loss = 5.27703 (* 1 = 5.27703 loss) +I0410 13:29:30.566769 18414 sgd_solver.cpp:105] Iteration 36, lr = 0.00992894 +I0410 13:29:35.390864 18414 solver.cpp:218] Iteration 48 (2.48759 iter/s, 4.82394s/12 iters), loss = 5.27829 +I0410 13:29:35.390905 18414 solver.cpp:237] Train net output #0: loss = 5.27829 (* 1 = 5.27829 loss) +I0410 13:29:35.390916 18414 sgd_solver.cpp:105] Iteration 48, lr = 0.00990537 +I0410 13:29:40.202005 18414 solver.cpp:218] Iteration 60 (2.49432 iter/s, 4.81093s/12 iters), loss = 5.2779 +I0410 13:29:40.202051 18414 solver.cpp:237] Train net output #0: loss = 5.2779 (* 1 = 5.2779 loss) +I0410 13:29:40.202064 18414 sgd_solver.cpp:105] Iteration 60, lr = 0.00988185 +I0410 13:29:45.040838 18414 solver.cpp:218] Iteration 72 (2.48005 iter/s, 4.83861s/12 iters), loss = 5.27761 +I0410 13:29:45.040966 18414 solver.cpp:237] Train net output #0: loss = 5.27761 (* 1 = 5.27761 loss) +I0410 13:29:45.040983 18414 sgd_solver.cpp:105] Iteration 72, lr = 0.00985839 +I0410 13:29:49.860772 18414 solver.cpp:218] Iteration 84 (2.48981 iter/s, 4.81965s/12 iters), loss = 5.27931 +I0410 13:29:49.860810 18414 solver.cpp:237] Train net output #0: loss = 5.27931 (* 1 = 5.27931 loss) +I0410 13:29:49.860818 18414 sgd_solver.cpp:105] Iteration 84, lr = 0.00983498 +I0410 13:29:54.713986 18414 solver.cpp:218] Iteration 96 (2.4727 iter/s, 4.85299s/12 iters), loss = 5.28099 +I0410 13:29:54.714032 18414 solver.cpp:237] Train net output #0: loss = 5.28099 (* 1 = 5.28099 loss) +I0410 13:29:54.714046 18414 sgd_solver.cpp:105] Iteration 96, lr = 0.00981163 +I0410 13:29:56.364625 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:29:56.668895 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_102.caffemodel +I0410 13:29:57.002784 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_102.solverstate +I0410 13:29:57.210002 18414 solver.cpp:330] Iteration 102, Testing net (#0) +I0410 13:29:57.210033 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:30:01.706233 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:30:01.782299 18414 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:30:01.782347 18414 solver.cpp:397] Test net output #1: loss = 5.27891 (* 1 = 5.27891 loss) +I0410 13:30:03.687377 18414 solver.cpp:218] Iteration 108 (1.33734 iter/s, 8.97303s/12 iters), loss = 5.27768 +I0410 13:30:03.687427 18414 solver.cpp:237] Train net output #0: loss = 5.27768 (* 1 = 5.27768 loss) +I0410 13:30:03.687438 18414 sgd_solver.cpp:105] Iteration 108, lr = 0.00978834 +I0410 13:30:08.481166 18414 solver.cpp:218] Iteration 120 (2.50336 iter/s, 4.79356s/12 iters), loss = 5.27537 +I0410 13:30:08.481222 18414 solver.cpp:237] Train net output #0: loss = 5.27537 (* 1 = 5.27537 loss) +I0410 13:30:08.481236 18414 sgd_solver.cpp:105] Iteration 120, lr = 0.0097651 +I0410 13:30:13.265877 18414 solver.cpp:218] Iteration 132 (2.50811 iter/s, 4.78448s/12 iters), loss = 5.26061 +I0410 13:30:13.265926 18414 solver.cpp:237] Train net output #0: loss = 5.26061 (* 1 = 5.26061 loss) +I0410 13:30:13.265939 18414 sgd_solver.cpp:105] Iteration 132, lr = 0.00974192 +I0410 13:30:18.070266 18414 solver.cpp:218] Iteration 144 (2.49783 iter/s, 4.80417s/12 iters), loss = 5.28169 +I0410 13:30:18.070437 18414 solver.cpp:237] Train net output #0: loss = 5.28169 (* 1 = 5.28169 loss) +I0410 13:30:18.070451 18414 sgd_solver.cpp:105] Iteration 144, lr = 0.00971879 +I0410 13:30:22.921808 18414 solver.cpp:218] Iteration 156 (2.47362 iter/s, 4.8512s/12 iters), loss = 5.26972 +I0410 13:30:22.921851 18414 solver.cpp:237] Train net output #0: loss = 5.26972 (* 1 = 5.26972 loss) +I0410 13:30:22.921860 18414 sgd_solver.cpp:105] Iteration 156, lr = 0.00969571 +I0410 13:30:27.726739 18414 solver.cpp:218] Iteration 168 (2.49755 iter/s, 4.80471s/12 iters), loss = 5.27281 +I0410 13:30:27.726794 18414 solver.cpp:237] Train net output #0: loss = 5.27281 (* 1 = 5.27281 loss) +I0410 13:30:27.726805 18414 sgd_solver.cpp:105] Iteration 168, lr = 0.00967269 +I0410 13:30:32.571811 18414 solver.cpp:218] Iteration 180 (2.47686 iter/s, 4.84484s/12 iters), loss = 5.27197 +I0410 13:30:32.571871 18414 solver.cpp:237] Train net output #0: loss = 5.27197 (* 1 = 5.27197 loss) +I0410 13:30:32.571883 18414 sgd_solver.cpp:105] Iteration 180, lr = 0.00964973 +I0410 13:30:37.399507 18414 solver.cpp:218] Iteration 192 (2.48578 iter/s, 4.82747s/12 iters), loss = 5.27435 +I0410 13:30:37.399555 18414 solver.cpp:237] Train net output #0: loss = 5.27435 (* 1 = 5.27435 loss) +I0410 13:30:37.399564 18414 sgd_solver.cpp:105] Iteration 192, lr = 0.00962682 +I0410 13:30:41.140643 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:30:41.845474 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_204.caffemodel +I0410 13:30:42.155871 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_204.solverstate +I0410 13:30:42.379150 18414 solver.cpp:330] Iteration 204, Testing net (#0) +I0410 13:30:42.379171 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:30:46.826395 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:30:46.950076 18414 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:30:46.950122 18414 solver.cpp:397] Test net output #1: loss = 5.28007 (* 1 = 5.28007 loss) +I0410 13:30:47.032701 18414 solver.cpp:218] Iteration 204 (1.24574 iter/s, 9.63281s/12 iters), loss = 5.27689 +I0410 13:30:47.032761 18414 solver.cpp:237] Train net output #0: loss = 5.27689 (* 1 = 5.27689 loss) +I0410 13:30:47.032773 18414 sgd_solver.cpp:105] Iteration 204, lr = 0.00960396 +I0410 13:30:51.115669 18414 solver.cpp:218] Iteration 216 (2.93919 iter/s, 4.08276s/12 iters), loss = 5.27862 +I0410 13:30:51.115793 18414 solver.cpp:237] Train net output #0: loss = 5.27862 (* 1 = 5.27862 loss) +I0410 13:30:51.115806 18414 sgd_solver.cpp:105] Iteration 216, lr = 0.00958116 +I0410 13:30:55.959874 18414 solver.cpp:218] Iteration 228 (2.47734 iter/s, 4.84391s/12 iters), loss = 5.26686 +I0410 13:30:55.959928 18414 solver.cpp:237] Train net output #0: loss = 5.26686 (* 1 = 5.26686 loss) +I0410 13:30:55.959939 18414 sgd_solver.cpp:105] Iteration 228, lr = 0.00955841 +I0410 13:31:00.761535 18414 solver.cpp:218] Iteration 240 (2.49925 iter/s, 4.80144s/12 iters), loss = 5.28253 +I0410 13:31:00.761586 18414 solver.cpp:237] Train net output #0: loss = 5.28253 (* 1 = 5.28253 loss) +I0410 13:31:00.761600 18414 sgd_solver.cpp:105] Iteration 240, lr = 0.00953572 +I0410 13:31:05.583853 18414 solver.cpp:218] Iteration 252 (2.48855 iter/s, 4.82209s/12 iters), loss = 5.27331 +I0410 13:31:05.583895 18414 solver.cpp:237] Train net output #0: loss = 5.27331 (* 1 = 5.27331 loss) +I0410 13:31:05.583906 18414 sgd_solver.cpp:105] Iteration 252, lr = 0.00951308 +I0410 13:31:10.379379 18414 solver.cpp:218] Iteration 264 (2.50245 iter/s, 4.79531s/12 iters), loss = 5.27661 +I0410 13:31:10.379431 18414 solver.cpp:237] Train net output #0: loss = 5.27661 (* 1 = 5.27661 loss) +I0410 13:31:10.379443 18414 sgd_solver.cpp:105] Iteration 264, lr = 0.00949049 +I0410 13:31:15.191030 18414 solver.cpp:218] Iteration 276 (2.49406 iter/s, 4.81143s/12 iters), loss = 5.28686 +I0410 13:31:15.191078 18414 solver.cpp:237] Train net output #0: loss = 5.28686 (* 1 = 5.28686 loss) +I0410 13:31:15.191088 18414 sgd_solver.cpp:105] Iteration 276, lr = 0.00946796 +I0410 13:31:19.979941 18414 solver.cpp:218] Iteration 288 (2.50591 iter/s, 4.78868s/12 iters), loss = 5.27789 +I0410 13:31:19.980008 18414 solver.cpp:237] Train net output #0: loss = 5.27789 (* 1 = 5.27789 loss) +I0410 13:31:19.980020 18414 sgd_solver.cpp:105] Iteration 288, lr = 0.00944548 +I0410 13:31:24.865764 18414 solver.cpp:218] Iteration 300 (2.45621 iter/s, 4.88558s/12 iters), loss = 5.2833 +I0410 13:31:24.865900 18414 solver.cpp:237] Train net output #0: loss = 5.2833 (* 1 = 5.2833 loss) +I0410 13:31:24.865911 18414 sgd_solver.cpp:105] Iteration 300, lr = 0.00942305 +I0410 13:31:25.813176 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:26.827906 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_306.caffemodel +I0410 13:31:27.108428 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_306.solverstate +I0410 13:31:27.302245 18414 solver.cpp:330] Iteration 306, Testing net (#0) +I0410 13:31:27.302265 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:31:31.440220 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:31.596529 18414 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:31:31.596571 18414 solver.cpp:397] Test net output #1: loss = 5.28129 (* 1 = 5.28129 loss) +I0410 13:31:33.351917 18414 solver.cpp:218] Iteration 312 (1.41414 iter/s, 8.48572s/12 iters), loss = 5.28109 +I0410 13:31:33.351974 18414 solver.cpp:237] Train net output #0: loss = 5.28109 (* 1 = 5.28109 loss) +I0410 13:31:33.351984 18414 sgd_solver.cpp:105] Iteration 312, lr = 0.00940068 +I0410 13:31:38.130451 18414 solver.cpp:218] Iteration 324 (2.51135 iter/s, 4.77831s/12 iters), loss = 5.25853 +I0410 13:31:38.130508 18414 solver.cpp:237] Train net output #0: loss = 5.25853 (* 1 = 5.25853 loss) +I0410 13:31:38.130522 18414 sgd_solver.cpp:105] Iteration 324, lr = 0.00937836 +I0410 13:31:42.913368 18414 solver.cpp:218] Iteration 336 (2.50905 iter/s, 4.78269s/12 iters), loss = 5.26553 +I0410 13:31:42.913429 18414 solver.cpp:237] Train net output #0: loss = 5.26553 (* 1 = 5.26553 loss) +I0410 13:31:42.913444 18414 sgd_solver.cpp:105] Iteration 336, lr = 0.0093561 +I0410 13:31:47.690304 18414 solver.cpp:218] Iteration 348 (2.51219 iter/s, 4.7767s/12 iters), loss = 5.26952 +I0410 13:31:47.690361 18414 solver.cpp:237] Train net output #0: loss = 5.26952 (* 1 = 5.26952 loss) +I0410 13:31:47.690380 18414 sgd_solver.cpp:105] Iteration 348, lr = 0.00933388 +I0410 13:31:52.485208 18414 solver.cpp:218] Iteration 360 (2.50278 iter/s, 4.79467s/12 iters), loss = 5.28552 +I0410 13:31:52.485265 18414 solver.cpp:237] Train net output #0: loss = 5.28552 (* 1 = 5.28552 loss) +I0410 13:31:52.485275 18414 sgd_solver.cpp:105] Iteration 360, lr = 0.00931172 +I0410 13:31:57.272385 18414 solver.cpp:218] Iteration 372 (2.50682 iter/s, 4.78695s/12 iters), loss = 5.27111 +I0410 13:31:57.272539 18414 solver.cpp:237] Train net output #0: loss = 5.27111 (* 1 = 5.27111 loss) +I0410 13:31:57.272552 18414 sgd_solver.cpp:105] Iteration 372, lr = 0.00928961 +I0410 13:32:02.067373 18414 solver.cpp:218] Iteration 384 (2.50278 iter/s, 4.79466s/12 iters), loss = 5.27791 +I0410 13:32:02.067437 18414 solver.cpp:237] Train net output #0: loss = 5.27791 (* 1 = 5.27791 loss) +I0410 13:32:02.067451 18414 sgd_solver.cpp:105] Iteration 384, lr = 0.00926756 +I0410 13:32:06.874275 18414 solver.cpp:218] Iteration 396 (2.49653 iter/s, 4.80667s/12 iters), loss = 5.27045 +I0410 13:32:06.874331 18414 solver.cpp:237] Train net output #0: loss = 5.27045 (* 1 = 5.27045 loss) +I0410 13:32:06.874343 18414 sgd_solver.cpp:105] Iteration 396, lr = 0.00924556 +I0410 13:32:09.868899 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:11.244029 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_408.caffemodel +I0410 13:32:11.567994 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_408.solverstate +I0410 13:32:11.779083 18414 solver.cpp:330] Iteration 408, Testing net (#0) +I0410 13:32:11.779109 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:32:15.929858 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:16.130236 18414 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:32:16.130270 18414 solver.cpp:397] Test net output #1: loss = 5.28308 (* 1 = 5.28308 loss) +I0410 13:32:16.204085 18414 solver.cpp:218] Iteration 408 (1.28625 iter/s, 9.32943s/12 iters), loss = 5.27665 +I0410 13:32:16.204131 18414 solver.cpp:237] Train net output #0: loss = 5.27665 (* 1 = 5.27665 loss) +I0410 13:32:16.204139 18414 sgd_solver.cpp:105] Iteration 408, lr = 0.00922361 +I0410 13:32:20.363898 18414 solver.cpp:218] Iteration 420 (2.88489 iter/s, 4.15961s/12 iters), loss = 5.27662 +I0410 13:32:20.363955 18414 solver.cpp:237] Train net output #0: loss = 5.27662 (* 1 = 5.27662 loss) +I0410 13:32:20.363968 18414 sgd_solver.cpp:105] Iteration 420, lr = 0.00920171 +I0410 13:32:25.366330 18414 solver.cpp:218] Iteration 432 (2.39894 iter/s, 5.00221s/12 iters), loss = 5.27123 +I0410 13:32:25.366360 18414 solver.cpp:237] Train net output #0: loss = 5.27123 (* 1 = 5.27123 loss) +I0410 13:32:25.366369 18414 sgd_solver.cpp:105] Iteration 432, lr = 0.00917986 +I0410 13:32:30.235595 18414 solver.cpp:218] Iteration 444 (2.46454 iter/s, 4.86906s/12 iters), loss = 5.2826 +I0410 13:32:30.235695 18414 solver.cpp:237] Train net output #0: loss = 5.2826 (* 1 = 5.2826 loss) +I0410 13:32:30.235705 18414 sgd_solver.cpp:105] Iteration 444, lr = 0.00915807 +I0410 13:32:35.206437 18414 solver.cpp:218] Iteration 456 (2.41421 iter/s, 4.97056s/12 iters), loss = 5.27899 +I0410 13:32:35.206487 18414 solver.cpp:237] Train net output #0: loss = 5.27899 (* 1 = 5.27899 loss) +I0410 13:32:35.206498 18414 sgd_solver.cpp:105] Iteration 456, lr = 0.00913632 +I0410 13:32:40.016019 18414 solver.cpp:218] Iteration 468 (2.49513 iter/s, 4.80936s/12 iters), loss = 5.2865 +I0410 13:32:40.016073 18414 solver.cpp:237] Train net output #0: loss = 5.2865 (* 1 = 5.2865 loss) +I0410 13:32:40.016085 18414 sgd_solver.cpp:105] Iteration 468, lr = 0.00911463 +I0410 13:32:44.960484 18414 solver.cpp:218] Iteration 480 (2.42707 iter/s, 4.94424s/12 iters), loss = 5.26674 +I0410 13:32:44.960530 18414 solver.cpp:237] Train net output #0: loss = 5.26674 (* 1 = 5.26674 loss) +I0410 13:32:44.960539 18414 sgd_solver.cpp:105] Iteration 480, lr = 0.00909299 +I0410 13:32:49.800788 18414 solver.cpp:218] Iteration 492 (2.4793 iter/s, 4.84008s/12 iters), loss = 5.28935 +I0410 13:32:49.800844 18414 solver.cpp:237] Train net output #0: loss = 5.28935 (* 1 = 5.28935 loss) +I0410 13:32:49.800858 18414 sgd_solver.cpp:105] Iteration 492, lr = 0.0090714 +I0410 13:32:54.639428 18414 solver.cpp:218] Iteration 504 (2.48015 iter/s, 4.83841s/12 iters), loss = 5.26999 +I0410 13:32:54.639482 18414 solver.cpp:237] Train net output #0: loss = 5.26999 (* 1 = 5.26999 loss) +I0410 13:32:54.639492 18414 sgd_solver.cpp:105] Iteration 504, lr = 0.00904986 +I0410 13:32:54.899322 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:56.627377 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_510.caffemodel +I0410 13:32:56.943753 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_510.solverstate +I0410 13:32:57.157532 18414 solver.cpp:330] Iteration 510, Testing net (#0) +I0410 13:32:57.157560 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:33:01.405076 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:33:01.642314 18414 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:33:01.642357 18414 solver.cpp:397] Test net output #1: loss = 5.28317 (* 1 = 5.28317 loss) +I0410 13:33:03.380848 18414 solver.cpp:218] Iteration 516 (1.37283 iter/s, 8.74107s/12 iters), loss = 5.27861 +I0410 13:33:03.380897 18414 solver.cpp:237] Train net output #0: loss = 5.27861 (* 1 = 5.27861 loss) +I0410 13:33:03.380908 18414 sgd_solver.cpp:105] Iteration 516, lr = 0.00902838 +I0410 13:33:08.243428 18414 solver.cpp:218] Iteration 528 (2.46794 iter/s, 4.86235s/12 iters), loss = 5.27168 +I0410 13:33:08.243489 18414 solver.cpp:237] Train net output #0: loss = 5.27168 (* 1 = 5.27168 loss) +I0410 13:33:08.243502 18414 sgd_solver.cpp:105] Iteration 528, lr = 0.00900694 +I0410 13:33:13.099728 18414 solver.cpp:218] Iteration 540 (2.47113 iter/s, 4.85607s/12 iters), loss = 5.27509 +I0410 13:33:13.099784 18414 solver.cpp:237] Train net output #0: loss = 5.27509 (* 1 = 5.27509 loss) +I0410 13:33:13.099798 18414 sgd_solver.cpp:105] Iteration 540, lr = 0.00898556 +I0410 13:33:18.011384 18414 solver.cpp:218] Iteration 552 (2.44328 iter/s, 4.91142s/12 iters), loss = 5.27305 +I0410 13:33:18.011445 18414 solver.cpp:237] Train net output #0: loss = 5.27305 (* 1 = 5.27305 loss) +I0410 13:33:18.011458 18414 sgd_solver.cpp:105] Iteration 552, lr = 0.00896423 +I0410 13:33:22.850450 18414 solver.cpp:218] Iteration 564 (2.47994 iter/s, 4.83884s/12 iters), loss = 5.26045 +I0410 13:33:22.850507 18414 solver.cpp:237] Train net output #0: loss = 5.26045 (* 1 = 5.26045 loss) +I0410 13:33:22.850520 18414 sgd_solver.cpp:105] Iteration 564, lr = 0.00894294 +I0410 13:33:27.735179 18414 solver.cpp:218] Iteration 576 (2.45675 iter/s, 4.8845s/12 iters), loss = 5.2767 +I0410 13:33:27.735231 18414 solver.cpp:237] Train net output #0: loss = 5.2767 (* 1 = 5.2767 loss) +I0410 13:33:27.735244 18414 sgd_solver.cpp:105] Iteration 576, lr = 0.00892171 +I0410 13:33:32.560617 18414 solver.cpp:218] Iteration 588 (2.48694 iter/s, 4.82522s/12 iters), loss = 5.26867 +I0410 13:33:32.560745 18414 solver.cpp:237] Train net output #0: loss = 5.26867 (* 1 = 5.26867 loss) +I0410 13:33:32.560760 18414 sgd_solver.cpp:105] Iteration 588, lr = 0.00890053 +I0410 13:33:37.397773 18414 solver.cpp:218] Iteration 600 (2.48095 iter/s, 4.83686s/12 iters), loss = 5.25873 +I0410 13:33:37.397823 18414 solver.cpp:237] Train net output #0: loss = 5.25873 (* 1 = 5.25873 loss) +I0410 13:33:37.397835 18414 sgd_solver.cpp:105] Iteration 600, lr = 0.0088794 +I0410 13:33:39.845280 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:33:41.906404 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_612.caffemodel +I0410 13:33:42.673825 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_612.solverstate +I0410 13:33:42.869518 18414 solver.cpp:330] Iteration 612, Testing net (#0) +I0410 13:33:42.869535 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:33:47.100347 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:33:47.384822 18414 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:33:47.384873 18414 solver.cpp:397] Test net output #1: loss = 5.2833 (* 1 = 5.2833 loss) +I0410 13:33:47.467782 18414 solver.cpp:218] Iteration 612 (1.1917 iter/s, 10.0696s/12 iters), loss = 5.27269 +I0410 13:33:47.467840 18414 solver.cpp:237] Train net output #0: loss = 5.27269 (* 1 = 5.27269 loss) +I0410 13:33:47.467852 18414 sgd_solver.cpp:105] Iteration 612, lr = 0.00885831 +I0410 13:33:51.631808 18414 solver.cpp:218] Iteration 624 (2.88197 iter/s, 4.16382s/12 iters), loss = 5.2868 +I0410 13:33:51.631853 18414 solver.cpp:237] Train net output #0: loss = 5.2868 (* 1 = 5.2868 loss) +I0410 13:33:51.631861 18414 sgd_solver.cpp:105] Iteration 624, lr = 0.00883728 +I0410 13:33:56.509260 18414 solver.cpp:218] Iteration 636 (2.46041 iter/s, 4.87723s/12 iters), loss = 5.28431 +I0410 13:33:56.509326 18414 solver.cpp:237] Train net output #0: loss = 5.28431 (* 1 = 5.28431 loss) +I0410 13:33:56.509344 18414 sgd_solver.cpp:105] Iteration 636, lr = 0.0088163 +I0410 13:34:01.268994 18414 solver.cpp:218] Iteration 648 (2.52127 iter/s, 4.7595s/12 iters), loss = 5.27278 +I0410 13:34:01.269047 18414 solver.cpp:237] Train net output #0: loss = 5.27278 (* 1 = 5.27278 loss) +I0410 13:34:01.269060 18414 sgd_solver.cpp:105] Iteration 648, lr = 0.00879537 +I0410 13:34:06.096830 18414 solver.cpp:218] Iteration 660 (2.4857 iter/s, 4.82761s/12 iters), loss = 5.26942 +I0410 13:34:06.097004 18414 solver.cpp:237] Train net output #0: loss = 5.26942 (* 1 = 5.26942 loss) +I0410 13:34:06.097018 18414 sgd_solver.cpp:105] Iteration 660, lr = 0.00877449 +I0410 13:34:10.931980 18414 solver.cpp:218] Iteration 672 (2.482 iter/s, 4.83481s/12 iters), loss = 5.27223 +I0410 13:34:10.932036 18414 solver.cpp:237] Train net output #0: loss = 5.27223 (* 1 = 5.27223 loss) +I0410 13:34:10.932049 18414 sgd_solver.cpp:105] Iteration 672, lr = 0.00875366 +I0410 13:34:14.973541 18414 blocking_queue.cpp:49] Waiting for data +I0410 13:34:15.823873 18414 solver.cpp:218] Iteration 684 (2.45315 iter/s, 4.89167s/12 iters), loss = 5.2743 +I0410 13:34:15.823920 18414 solver.cpp:237] Train net output #0: loss = 5.2743 (* 1 = 5.2743 loss) +I0410 13:34:15.823931 18414 sgd_solver.cpp:105] Iteration 684, lr = 0.00873287 +I0410 13:34:20.701836 18414 solver.cpp:218] Iteration 696 (2.46016 iter/s, 4.87774s/12 iters), loss = 5.2648 +I0410 13:34:20.701894 18414 solver.cpp:237] Train net output #0: loss = 5.2648 (* 1 = 5.2648 loss) +I0410 13:34:20.701907 18414 sgd_solver.cpp:105] Iteration 696, lr = 0.00871214 +I0410 13:34:25.183463 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:25.556548 18414 solver.cpp:218] Iteration 708 (2.47194 iter/s, 4.85448s/12 iters), loss = 5.25816 +I0410 13:34:25.556610 18414 solver.cpp:237] Train net output #0: loss = 5.25816 (* 1 = 5.25816 loss) +I0410 13:34:25.556624 18414 sgd_solver.cpp:105] Iteration 708, lr = 0.00869145 +I0410 13:34:27.573058 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_714.caffemodel +I0410 13:34:27.882889 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_714.solverstate +I0410 13:34:28.095609 18414 solver.cpp:330] Iteration 714, Testing net (#0) +I0410 13:34:28.095638 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:34:32.205555 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:32.529147 18414 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:34:32.529198 18414 solver.cpp:397] Test net output #1: loss = 5.28343 (* 1 = 5.28343 loss) +I0410 13:34:34.409166 18414 solver.cpp:218] Iteration 720 (1.35559 iter/s, 8.85226s/12 iters), loss = 5.27277 +I0410 13:34:34.409209 18414 solver.cpp:237] Train net output #0: loss = 5.27277 (* 1 = 5.27277 loss) +I0410 13:34:34.409219 18414 sgd_solver.cpp:105] Iteration 720, lr = 0.00867082 +I0410 13:34:39.207520 18414 solver.cpp:218] Iteration 732 (2.50097 iter/s, 4.79813s/12 iters), loss = 5.277 +I0410 13:34:39.207655 18414 solver.cpp:237] Train net output #0: loss = 5.277 (* 1 = 5.277 loss) +I0410 13:34:39.207670 18414 sgd_solver.cpp:105] Iteration 732, lr = 0.00865023 +I0410 13:34:44.035487 18414 solver.cpp:218] Iteration 744 (2.48567 iter/s, 4.82766s/12 iters), loss = 5.27333 +I0410 13:34:44.035545 18414 solver.cpp:237] Train net output #0: loss = 5.27333 (* 1 = 5.27333 loss) +I0410 13:34:44.035559 18414 sgd_solver.cpp:105] Iteration 744, lr = 0.0086297 +I0410 13:34:48.964545 18414 solver.cpp:218] Iteration 756 (2.43466 iter/s, 4.92883s/12 iters), loss = 5.27173 +I0410 13:34:48.964592 18414 solver.cpp:237] Train net output #0: loss = 5.27173 (* 1 = 5.27173 loss) +I0410 13:34:48.964602 18414 sgd_solver.cpp:105] Iteration 756, lr = 0.00860921 +I0410 13:34:53.827921 18414 solver.cpp:218] Iteration 768 (2.46753 iter/s, 4.86316s/12 iters), loss = 5.27053 +I0410 13:34:53.827966 18414 solver.cpp:237] Train net output #0: loss = 5.27053 (* 1 = 5.27053 loss) +I0410 13:34:53.827978 18414 sgd_solver.cpp:105] Iteration 768, lr = 0.00858877 +I0410 13:34:58.755915 18414 solver.cpp:218] Iteration 780 (2.43518 iter/s, 4.92778s/12 iters), loss = 5.25003 +I0410 13:34:58.755970 18414 solver.cpp:237] Train net output #0: loss = 5.25003 (* 1 = 5.25003 loss) +I0410 13:34:58.755983 18414 sgd_solver.cpp:105] Iteration 780, lr = 0.00856838 +I0410 13:35:03.647716 18414 solver.cpp:218] Iteration 792 (2.4532 iter/s, 4.89158s/12 iters), loss = 5.23546 +I0410 13:35:03.647768 18414 solver.cpp:237] Train net output #0: loss = 5.23546 (* 1 = 5.23546 loss) +I0410 13:35:03.647778 18414 sgd_solver.cpp:105] Iteration 792, lr = 0.00854803 +I0410 13:35:08.542412 18414 solver.cpp:218] Iteration 804 (2.45174 iter/s, 4.89447s/12 iters), loss = 5.24207 +I0410 13:35:08.542464 18414 solver.cpp:237] Train net output #0: loss = 5.24207 (* 1 = 5.24207 loss) +I0410 13:35:08.542475 18414 sgd_solver.cpp:105] Iteration 804, lr = 0.00852774 +I0410 13:35:10.254098 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:13.000504 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_816.caffemodel +I0410 13:35:13.297406 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_816.solverstate +I0410 13:35:13.501272 18414 solver.cpp:330] Iteration 816, Testing net (#0) +I0410 13:35:13.501307 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:35:17.812043 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:18.188352 18414 solver.cpp:397] Test net output #0: accuracy = 0.00857843 +I0410 13:35:18.188401 18414 solver.cpp:397] Test net output #1: loss = 5.23191 (* 1 = 5.23191 loss) +I0410 13:35:18.271304 18414 solver.cpp:218] Iteration 816 (1.23349 iter/s, 9.72852s/12 iters), loss = 5.24341 +I0410 13:35:18.271358 18414 solver.cpp:237] Train net output #0: loss = 5.24341 (* 1 = 5.24341 loss) +I0410 13:35:18.271369 18414 sgd_solver.cpp:105] Iteration 816, lr = 0.00850749 +I0410 13:35:22.440999 18414 solver.cpp:218] Iteration 828 (2.87805 iter/s, 4.16949s/12 iters), loss = 5.21934 +I0410 13:35:22.441053 18414 solver.cpp:237] Train net output #0: loss = 5.21934 (* 1 = 5.21934 loss) +I0410 13:35:22.441066 18414 sgd_solver.cpp:105] Iteration 828, lr = 0.00848729 +I0410 13:35:27.316193 18414 solver.cpp:218] Iteration 840 (2.46155 iter/s, 4.87497s/12 iters), loss = 5.16046 +I0410 13:35:27.316237 18414 solver.cpp:237] Train net output #0: loss = 5.16046 (* 1 = 5.16046 loss) +I0410 13:35:27.316246 18414 sgd_solver.cpp:105] Iteration 840, lr = 0.00846714 +I0410 13:35:32.136536 18414 solver.cpp:218] Iteration 852 (2.48956 iter/s, 4.82012s/12 iters), loss = 5.20175 +I0410 13:35:32.136592 18414 solver.cpp:237] Train net output #0: loss = 5.20175 (* 1 = 5.20175 loss) +I0410 13:35:32.136605 18414 sgd_solver.cpp:105] Iteration 852, lr = 0.00844704 +I0410 13:35:37.038434 18414 solver.cpp:218] Iteration 864 (2.44815 iter/s, 4.90167s/12 iters), loss = 5.13432 +I0410 13:35:37.038484 18414 solver.cpp:237] Train net output #0: loss = 5.13432 (* 1 = 5.13432 loss) +I0410 13:35:37.038497 18414 sgd_solver.cpp:105] Iteration 864, lr = 0.00842698 +I0410 13:35:41.933192 18414 solver.cpp:218] Iteration 876 (2.45171 iter/s, 4.89453s/12 iters), loss = 5.1922 +I0410 13:35:41.933305 18414 solver.cpp:237] Train net output #0: loss = 5.1922 (* 1 = 5.1922 loss) +I0410 13:35:41.933315 18414 sgd_solver.cpp:105] Iteration 876, lr = 0.00840698 +I0410 13:35:46.860473 18414 solver.cpp:218] Iteration 888 (2.43556 iter/s, 4.927s/12 iters), loss = 5.07627 +I0410 13:35:46.860527 18414 solver.cpp:237] Train net output #0: loss = 5.07627 (* 1 = 5.07627 loss) +I0410 13:35:46.860538 18414 sgd_solver.cpp:105] Iteration 888, lr = 0.00838702 +I0410 13:35:51.720036 18414 solver.cpp:218] Iteration 900 (2.46947 iter/s, 4.85934s/12 iters), loss = 5.25271 +I0410 13:35:51.720093 18414 solver.cpp:237] Train net output #0: loss = 5.25271 (* 1 = 5.25271 loss) +I0410 13:35:51.720104 18414 sgd_solver.cpp:105] Iteration 900, lr = 0.0083671 +I0410 13:35:55.543215 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:56.646065 18414 solver.cpp:218] Iteration 912 (2.43615 iter/s, 4.9258s/12 iters), loss = 5.07518 +I0410 13:35:56.646113 18414 solver.cpp:237] Train net output #0: loss = 5.07518 (* 1 = 5.07518 loss) +I0410 13:35:56.646122 18414 sgd_solver.cpp:105] Iteration 912, lr = 0.00834724 +I0410 13:35:58.675138 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_918.caffemodel +I0410 13:35:59.000520 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_918.solverstate +I0410 13:35:59.214232 18414 solver.cpp:330] Iteration 918, Testing net (#0) +I0410 13:35:59.214260 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:36:03.193490 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:36:03.592269 18414 solver.cpp:397] Test net output #0: accuracy = 0.00919118 +I0410 13:36:03.592301 18414 solver.cpp:397] Test net output #1: loss = 5.14877 (* 1 = 5.14877 loss) +I0410 13:36:05.423198 18414 solver.cpp:218] Iteration 924 (1.36724 iter/s, 8.77678s/12 iters), loss = 5.15584 +I0410 13:36:05.423259 18414 solver.cpp:237] Train net output #0: loss = 5.15584 (* 1 = 5.15584 loss) +I0410 13:36:05.423270 18414 sgd_solver.cpp:105] Iteration 924, lr = 0.00832742 +I0410 13:36:10.415086 18414 solver.cpp:218] Iteration 936 (2.40401 iter/s, 4.99165s/12 iters), loss = 5.20976 +I0410 13:36:10.415135 18414 solver.cpp:237] Train net output #0: loss = 5.20976 (* 1 = 5.20976 loss) +I0410 13:36:10.415148 18414 sgd_solver.cpp:105] Iteration 936, lr = 0.00830765 +I0410 13:36:15.361109 18414 solver.cpp:218] Iteration 948 (2.4263 iter/s, 4.9458s/12 iters), loss = 5.15877 +I0410 13:36:15.361255 18414 solver.cpp:237] Train net output #0: loss = 5.15877 (* 1 = 5.15877 loss) +I0410 13:36:15.361268 18414 sgd_solver.cpp:105] Iteration 948, lr = 0.00828793 +I0410 13:36:20.320794 18414 solver.cpp:218] Iteration 960 (2.41966 iter/s, 4.95937s/12 iters), loss = 5.11153 +I0410 13:36:20.320848 18414 solver.cpp:237] Train net output #0: loss = 5.11153 (* 1 = 5.11153 loss) +I0410 13:36:20.320860 18414 sgd_solver.cpp:105] Iteration 960, lr = 0.00826825 +I0410 13:36:25.214808 18414 solver.cpp:218] Iteration 972 (2.45209 iter/s, 4.89379s/12 iters), loss = 5.16652 +I0410 13:36:25.214856 18414 solver.cpp:237] Train net output #0: loss = 5.16652 (* 1 = 5.16652 loss) +I0410 13:36:25.214865 18414 sgd_solver.cpp:105] Iteration 972, lr = 0.00824862 +I0410 13:36:30.167196 18414 solver.cpp:218] Iteration 984 (2.42318 iter/s, 4.95216s/12 iters), loss = 5.15878 +I0410 13:36:30.167248 18414 solver.cpp:237] Train net output #0: loss = 5.15878 (* 1 = 5.15878 loss) +I0410 13:36:30.167260 18414 sgd_solver.cpp:105] Iteration 984, lr = 0.00822903 +I0410 13:36:34.984027 18414 solver.cpp:218] Iteration 996 (2.49138 iter/s, 4.81662s/12 iters), loss = 5.04231 +I0410 13:36:34.984073 18414 solver.cpp:237] Train net output #0: loss = 5.04231 (* 1 = 5.04231 loss) +I0410 13:36:34.984083 18414 sgd_solver.cpp:105] Iteration 996, lr = 0.0082095 +I0410 13:36:39.974649 18414 solver.cpp:218] Iteration 1008 (2.40462 iter/s, 4.9904s/12 iters), loss = 5.15956 +I0410 13:36:39.974704 18414 solver.cpp:237] Train net output #0: loss = 5.15956 (* 1 = 5.15956 loss) +I0410 13:36:39.974717 18414 sgd_solver.cpp:105] Iteration 1008, lr = 0.00819001 +I0410 13:36:40.963227 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:36:44.353693 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1020.caffemodel +I0410 13:36:45.472123 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1020.solverstate +I0410 13:36:46.419459 18414 solver.cpp:330] Iteration 1020, Testing net (#0) +I0410 13:36:46.419487 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:36:50.435389 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:36:50.865402 18414 solver.cpp:397] Test net output #0: accuracy = 0.00980392 +I0410 13:36:50.865458 18414 solver.cpp:397] Test net output #1: loss = 5.11962 (* 1 = 5.11962 loss) +I0410 13:36:50.948312 18414 solver.cpp:218] Iteration 1020 (1.09357 iter/s, 10.9732s/12 iters), loss = 5.09065 +I0410 13:36:50.948369 18414 solver.cpp:237] Train net output #0: loss = 5.09065 (* 1 = 5.09065 loss) +I0410 13:36:50.948381 18414 sgd_solver.cpp:105] Iteration 1020, lr = 0.00817056 +I0410 13:36:55.331732 18414 solver.cpp:218] Iteration 1032 (2.73772 iter/s, 4.38321s/12 iters), loss = 5.12848 +I0410 13:36:55.331776 18414 solver.cpp:237] Train net output #0: loss = 5.12848 (* 1 = 5.12848 loss) +I0410 13:36:55.331786 18414 sgd_solver.cpp:105] Iteration 1032, lr = 0.00815116 +I0410 13:37:00.161909 18414 solver.cpp:218] Iteration 1044 (2.48449 iter/s, 4.82996s/12 iters), loss = 5.14631 +I0410 13:37:00.161986 18414 solver.cpp:237] Train net output #0: loss = 5.14631 (* 1 = 5.14631 loss) +I0410 13:37:00.162000 18414 sgd_solver.cpp:105] Iteration 1044, lr = 0.00813181 +I0410 13:37:05.099752 18414 solver.cpp:218] Iteration 1056 (2.43033 iter/s, 4.93759s/12 iters), loss = 5.11856 +I0410 13:37:05.099804 18414 solver.cpp:237] Train net output #0: loss = 5.11856 (* 1 = 5.11856 loss) +I0410 13:37:05.099815 18414 sgd_solver.cpp:105] Iteration 1056, lr = 0.0081125 +I0410 13:37:10.067718 18414 solver.cpp:218] Iteration 1068 (2.41559 iter/s, 4.96774s/12 iters), loss = 5.15348 +I0410 13:37:10.067771 18414 solver.cpp:237] Train net output #0: loss = 5.15348 (* 1 = 5.15348 loss) +I0410 13:37:10.067783 18414 sgd_solver.cpp:105] Iteration 1068, lr = 0.00809324 +I0410 13:37:14.947788 18414 solver.cpp:218] Iteration 1080 (2.4591 iter/s, 4.87984s/12 iters), loss = 5.11424 +I0410 13:37:14.947849 18414 solver.cpp:237] Train net output #0: loss = 5.11424 (* 1 = 5.11424 loss) +I0410 13:37:14.947863 18414 sgd_solver.cpp:105] Iteration 1080, lr = 0.00807403 +I0410 13:37:19.874876 18414 solver.cpp:218] Iteration 1092 (2.43563 iter/s, 4.92686s/12 iters), loss = 5.05678 +I0410 13:37:19.875000 18414 solver.cpp:237] Train net output #0: loss = 5.05678 (* 1 = 5.05678 loss) +I0410 13:37:19.875013 18414 sgd_solver.cpp:105] Iteration 1092, lr = 0.00805486 +I0410 13:37:24.777276 18414 solver.cpp:218] Iteration 1104 (2.44793 iter/s, 4.90211s/12 iters), loss = 5.06221 +I0410 13:37:24.777318 18414 solver.cpp:237] Train net output #0: loss = 5.06221 (* 1 = 5.06221 loss) +I0410 13:37:24.777328 18414 sgd_solver.cpp:105] Iteration 1104, lr = 0.00803573 +I0410 13:37:27.871193 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:29.698330 18414 solver.cpp:218] Iteration 1116 (2.43861 iter/s, 4.92084s/12 iters), loss = 5.13468 +I0410 13:37:29.698390 18414 solver.cpp:237] Train net output #0: loss = 5.13468 (* 1 = 5.13468 loss) +I0410 13:37:29.698400 18414 sgd_solver.cpp:105] Iteration 1116, lr = 0.00801666 +I0410 13:37:31.720798 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1122.caffemodel +I0410 13:37:32.041496 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1122.solverstate +I0410 13:37:32.252424 18414 solver.cpp:330] Iteration 1122, Testing net (#0) +I0410 13:37:32.252454 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:37:36.189384 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:36.663794 18414 solver.cpp:397] Test net output #0: accuracy = 0.0116422 +I0410 13:37:36.663844 18414 solver.cpp:397] Test net output #1: loss = 5.07439 (* 1 = 5.07439 loss) +I0410 13:37:38.437510 18414 solver.cpp:218] Iteration 1128 (1.37318 iter/s, 8.73882s/12 iters), loss = 5.19451 +I0410 13:37:38.437568 18414 solver.cpp:237] Train net output #0: loss = 5.19451 (* 1 = 5.19451 loss) +I0410 13:37:38.437582 18414 sgd_solver.cpp:105] Iteration 1128, lr = 0.00799762 +I0410 13:37:43.374339 18414 solver.cpp:218] Iteration 1140 (2.43082 iter/s, 4.9366s/12 iters), loss = 5.14523 +I0410 13:37:43.374399 18414 solver.cpp:237] Train net output #0: loss = 5.14523 (* 1 = 5.14523 loss) +I0410 13:37:43.374414 18414 sgd_solver.cpp:105] Iteration 1140, lr = 0.00797863 +I0410 13:37:48.282910 18414 solver.cpp:218] Iteration 1152 (2.44482 iter/s, 4.90834s/12 iters), loss = 5.07681 +I0410 13:37:48.282960 18414 solver.cpp:237] Train net output #0: loss = 5.07681 (* 1 = 5.07681 loss) +I0410 13:37:48.282974 18414 sgd_solver.cpp:105] Iteration 1152, lr = 0.00795969 +I0410 13:37:53.226547 18414 solver.cpp:218] Iteration 1164 (2.42747 iter/s, 4.94342s/12 iters), loss = 5.09931 +I0410 13:37:53.226671 18414 solver.cpp:237] Train net output #0: loss = 5.09931 (* 1 = 5.09931 loss) +I0410 13:37:53.226683 18414 sgd_solver.cpp:105] Iteration 1164, lr = 0.00794079 +I0410 13:37:58.188537 18414 solver.cpp:218] Iteration 1176 (2.41853 iter/s, 4.9617s/12 iters), loss = 5.06658 +I0410 13:37:58.188585 18414 solver.cpp:237] Train net output #0: loss = 5.06658 (* 1 = 5.06658 loss) +I0410 13:37:58.188593 18414 sgd_solver.cpp:105] Iteration 1176, lr = 0.00792194 +I0410 13:38:03.237505 18414 solver.cpp:218] Iteration 1188 (2.37683 iter/s, 5.04875s/12 iters), loss = 5.09439 +I0410 13:38:03.237546 18414 solver.cpp:237] Train net output #0: loss = 5.09439 (* 1 = 5.09439 loss) +I0410 13:38:03.237555 18414 sgd_solver.cpp:105] Iteration 1188, lr = 0.00790313 +I0410 13:38:08.278012 18414 solver.cpp:218] Iteration 1200 (2.38082 iter/s, 5.04029s/12 iters), loss = 5.13578 +I0410 13:38:08.278060 18414 solver.cpp:237] Train net output #0: loss = 5.13578 (* 1 = 5.13578 loss) +I0410 13:38:08.278071 18414 sgd_solver.cpp:105] Iteration 1200, lr = 0.00788437 +I0410 13:38:13.282841 18414 solver.cpp:218] Iteration 1212 (2.39779 iter/s, 5.0046s/12 iters), loss = 5.10662 +I0410 13:38:13.282899 18414 solver.cpp:237] Train net output #0: loss = 5.10662 (* 1 = 5.10662 loss) +I0410 13:38:13.282913 18414 sgd_solver.cpp:105] Iteration 1212, lr = 0.00786565 +I0410 13:38:13.570884 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:38:17.793365 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1224.caffemodel +I0410 13:38:18.113535 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1224.solverstate +I0410 13:38:18.325714 18414 solver.cpp:330] Iteration 1224, Testing net (#0) +I0410 13:38:18.325747 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:38:22.268731 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:38:22.777717 18414 solver.cpp:397] Test net output #0: accuracy = 0.0110294 +I0410 13:38:22.777770 18414 solver.cpp:397] Test net output #1: loss = 5.07459 (* 1 = 5.07459 loss) +I0410 13:38:22.861155 18414 solver.cpp:218] Iteration 1224 (1.25288 iter/s, 9.57793s/12 iters), loss = 5.05978 +I0410 13:38:22.861232 18414 solver.cpp:237] Train net output #0: loss = 5.05978 (* 1 = 5.05978 loss) +I0410 13:38:22.861249 18414 sgd_solver.cpp:105] Iteration 1224, lr = 0.00784697 +I0410 13:38:27.044953 18414 solver.cpp:218] Iteration 1236 (2.86836 iter/s, 4.18357s/12 iters), loss = 5.16312 +I0410 13:38:27.045087 18414 solver.cpp:237] Train net output #0: loss = 5.16312 (* 1 = 5.16312 loss) +I0410 13:38:27.045099 18414 sgd_solver.cpp:105] Iteration 1236, lr = 0.00782834 +I0410 13:38:31.934890 18414 solver.cpp:218] Iteration 1248 (2.45417 iter/s, 4.88963s/12 iters), loss = 4.99644 +I0410 13:38:31.934948 18414 solver.cpp:237] Train net output #0: loss = 4.99644 (* 1 = 4.99644 loss) +I0410 13:38:31.934962 18414 sgd_solver.cpp:105] Iteration 1248, lr = 0.00780976 +I0410 13:38:36.853236 18414 solver.cpp:218] Iteration 1260 (2.43996 iter/s, 4.91811s/12 iters), loss = 5.08416 +I0410 13:38:36.853299 18414 solver.cpp:237] Train net output #0: loss = 5.08416 (* 1 = 5.08416 loss) +I0410 13:38:36.853312 18414 sgd_solver.cpp:105] Iteration 1260, lr = 0.00779122 +I0410 13:38:41.794574 18414 solver.cpp:218] Iteration 1272 (2.42861 iter/s, 4.9411s/12 iters), loss = 5.01848 +I0410 13:38:41.794629 18414 solver.cpp:237] Train net output #0: loss = 5.01848 (* 1 = 5.01848 loss) +I0410 13:38:41.794643 18414 sgd_solver.cpp:105] Iteration 1272, lr = 0.00777272 +I0410 13:38:46.779919 18414 solver.cpp:218] Iteration 1284 (2.40717 iter/s, 4.98511s/12 iters), loss = 5.00842 +I0410 13:38:46.779971 18414 solver.cpp:237] Train net output #0: loss = 5.00842 (* 1 = 5.00842 loss) +I0410 13:38:46.779984 18414 sgd_solver.cpp:105] Iteration 1284, lr = 0.00775426 +I0410 13:38:51.867154 18414 solver.cpp:218] Iteration 1296 (2.35895 iter/s, 5.087s/12 iters), loss = 4.97769 +I0410 13:38:51.867210 18414 solver.cpp:237] Train net output #0: loss = 4.97769 (* 1 = 4.97769 loss) +I0410 13:38:51.867224 18414 sgd_solver.cpp:105] Iteration 1296, lr = 0.00773585 +I0410 13:38:56.720449 18414 solver.cpp:218] Iteration 1308 (2.47266 iter/s, 4.85307s/12 iters), loss = 5.00322 +I0410 13:38:56.720499 18414 solver.cpp:237] Train net output #0: loss = 5.00322 (* 1 = 5.00322 loss) +I0410 13:38:56.720510 18414 sgd_solver.cpp:105] Iteration 1308, lr = 0.00771749 +I0410 13:38:59.174463 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:01.612107 18414 solver.cpp:218] Iteration 1320 (2.45327 iter/s, 4.89143s/12 iters), loss = 5.0406 +I0410 13:39:01.612154 18414 solver.cpp:237] Train net output #0: loss = 5.0406 (* 1 = 5.0406 loss) +I0410 13:39:01.612165 18414 sgd_solver.cpp:105] Iteration 1320, lr = 0.00769916 +I0410 13:39:03.617300 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1326.caffemodel +I0410 13:39:03.939131 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1326.solverstate +I0410 13:39:04.152679 18414 solver.cpp:330] Iteration 1326, Testing net (#0) +I0410 13:39:04.152712 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:39:07.982985 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:08.537451 18414 solver.cpp:397] Test net output #0: accuracy = 0.0171569 +I0410 13:39:08.537501 18414 solver.cpp:397] Test net output #1: loss = 5.03808 (* 1 = 5.03808 loss) +I0410 13:39:10.763094 18414 solver.cpp:218] Iteration 1332 (1.31138 iter/s, 9.15064s/12 iters), loss = 5.0067 +I0410 13:39:10.763135 18414 solver.cpp:237] Train net output #0: loss = 5.0067 (* 1 = 5.0067 loss) +I0410 13:39:10.763144 18414 sgd_solver.cpp:105] Iteration 1332, lr = 0.00768088 +I0410 13:39:15.817493 18414 solver.cpp:218] Iteration 1344 (2.37427 iter/s, 5.05418s/12 iters), loss = 4.96974 +I0410 13:39:15.817546 18414 solver.cpp:237] Train net output #0: loss = 4.96974 (* 1 = 4.96974 loss) +I0410 13:39:15.817560 18414 sgd_solver.cpp:105] Iteration 1344, lr = 0.00766265 +I0410 13:39:20.690896 18414 solver.cpp:218] Iteration 1356 (2.46246 iter/s, 4.87318s/12 iters), loss = 5.05981 +I0410 13:39:20.690945 18414 solver.cpp:237] Train net output #0: loss = 5.05981 (* 1 = 5.05981 loss) +I0410 13:39:20.690956 18414 sgd_solver.cpp:105] Iteration 1356, lr = 0.00764446 +I0410 13:39:25.272742 18414 blocking_queue.cpp:49] Waiting for data +I0410 13:39:25.745815 18414 solver.cpp:218] Iteration 1368 (2.37403 iter/s, 5.05469s/12 iters), loss = 5.06717 +I0410 13:39:25.745859 18414 solver.cpp:237] Train net output #0: loss = 5.06717 (* 1 = 5.06717 loss) +I0410 13:39:25.745868 18414 sgd_solver.cpp:105] Iteration 1368, lr = 0.00762631 +I0410 13:39:30.724884 18414 solver.cpp:218] Iteration 1380 (2.4102 iter/s, 4.97884s/12 iters), loss = 4.94453 +I0410 13:39:30.725064 18414 solver.cpp:237] Train net output #0: loss = 4.94453 (* 1 = 4.94453 loss) +I0410 13:39:30.725082 18414 sgd_solver.cpp:105] Iteration 1380, lr = 0.0076082 +I0410 13:39:35.693132 18414 solver.cpp:218] Iteration 1392 (2.41551 iter/s, 4.9679s/12 iters), loss = 4.87116 +I0410 13:39:35.693188 18414 solver.cpp:237] Train net output #0: loss = 4.87116 (* 1 = 4.87116 loss) +I0410 13:39:35.693203 18414 sgd_solver.cpp:105] Iteration 1392, lr = 0.00759014 +I0410 13:39:40.557808 18414 solver.cpp:218] Iteration 1404 (2.46688 iter/s, 4.86445s/12 iters), loss = 4.99481 +I0410 13:39:40.557865 18414 solver.cpp:237] Train net output #0: loss = 4.99481 (* 1 = 4.99481 loss) +I0410 13:39:40.557878 18414 sgd_solver.cpp:105] Iteration 1404, lr = 0.00757212 +I0410 13:39:45.183990 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:45.536074 18414 solver.cpp:218] Iteration 1416 (2.41059 iter/s, 4.97804s/12 iters), loss = 5.06835 +I0410 13:39:45.536124 18414 solver.cpp:237] Train net output #0: loss = 5.06835 (* 1 = 5.06835 loss) +I0410 13:39:45.536135 18414 sgd_solver.cpp:105] Iteration 1416, lr = 0.00755414 +I0410 13:39:50.096536 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1428.caffemodel +I0410 13:39:50.984773 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1428.solverstate +I0410 13:39:51.799734 18414 solver.cpp:330] Iteration 1428, Testing net (#0) +I0410 13:39:51.799754 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:39:55.665325 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:56.253597 18414 solver.cpp:397] Test net output #0: accuracy = 0.0147059 +I0410 13:39:56.253643 18414 solver.cpp:397] Test net output #1: loss = 5.00002 (* 1 = 5.00002 loss) +I0410 13:39:56.336794 18414 solver.cpp:218] Iteration 1428 (1.11108 iter/s, 10.8003s/12 iters), loss = 5.11335 +I0410 13:39:56.336840 18414 solver.cpp:237] Train net output #0: loss = 5.11335 (* 1 = 5.11335 loss) +I0410 13:39:56.336851 18414 sgd_solver.cpp:105] Iteration 1428, lr = 0.0075362 +I0410 13:40:00.626067 18414 solver.cpp:218] Iteration 1440 (2.79781 iter/s, 4.28907s/12 iters), loss = 4.94122 +I0410 13:40:00.626127 18414 solver.cpp:237] Train net output #0: loss = 4.94122 (* 1 = 4.94122 loss) +I0410 13:40:00.626138 18414 sgd_solver.cpp:105] Iteration 1440, lr = 0.00751831 +I0410 13:40:05.680697 18414 solver.cpp:218] Iteration 1452 (2.37417 iter/s, 5.0544s/12 iters), loss = 4.97424 +I0410 13:40:05.680856 18414 solver.cpp:237] Train net output #0: loss = 4.97424 (* 1 = 4.97424 loss) +I0410 13:40:05.680871 18414 sgd_solver.cpp:105] Iteration 1452, lr = 0.00750046 +I0410 13:40:10.697561 18414 solver.cpp:218] Iteration 1464 (2.39209 iter/s, 5.01653s/12 iters), loss = 4.9814 +I0410 13:40:10.697619 18414 solver.cpp:237] Train net output #0: loss = 4.9814 (* 1 = 4.9814 loss) +I0410 13:40:10.697633 18414 sgd_solver.cpp:105] Iteration 1464, lr = 0.00748265 +I0410 13:40:15.780824 18414 solver.cpp:218] Iteration 1476 (2.3608 iter/s, 5.08303s/12 iters), loss = 4.97256 +I0410 13:40:15.780871 18414 solver.cpp:237] Train net output #0: loss = 4.97256 (* 1 = 4.97256 loss) +I0410 13:40:15.780881 18414 sgd_solver.cpp:105] Iteration 1476, lr = 0.00746489 +I0410 13:40:20.852403 18414 solver.cpp:218] Iteration 1488 (2.36623 iter/s, 5.07135s/12 iters), loss = 4.93309 +I0410 13:40:20.852456 18414 solver.cpp:237] Train net output #0: loss = 4.93309 (* 1 = 4.93309 loss) +I0410 13:40:20.852469 18414 sgd_solver.cpp:105] Iteration 1488, lr = 0.00744716 +I0410 13:40:25.847476 18414 solver.cpp:218] Iteration 1500 (2.40248 iter/s, 4.99485s/12 iters), loss = 4.8382 +I0410 13:40:25.847519 18414 solver.cpp:237] Train net output #0: loss = 4.8382 (* 1 = 4.8382 loss) +I0410 13:40:25.847529 18414 sgd_solver.cpp:105] Iteration 1500, lr = 0.00742948 +I0410 13:40:30.720330 18414 solver.cpp:218] Iteration 1512 (2.46273 iter/s, 4.87264s/12 iters), loss = 4.98873 +I0410 13:40:30.720383 18414 solver.cpp:237] Train net output #0: loss = 4.98873 (* 1 = 4.98873 loss) +I0410 13:40:30.720396 18414 sgd_solver.cpp:105] Iteration 1512, lr = 0.00741184 +I0410 13:40:32.499296 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:35.648749 18414 solver.cpp:218] Iteration 1524 (2.43497 iter/s, 4.92819s/12 iters), loss = 5.00206 +I0410 13:40:35.648792 18414 solver.cpp:237] Train net output #0: loss = 5.00206 (* 1 = 5.00206 loss) +I0410 13:40:35.648800 18414 sgd_solver.cpp:105] Iteration 1524, lr = 0.00739425 +I0410 13:40:37.619890 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1530.caffemodel +I0410 13:40:37.938519 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1530.solverstate +I0410 13:40:38.154229 18414 solver.cpp:330] Iteration 1530, Testing net (#0) +I0410 13:40:38.154251 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:40:41.955472 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:42.589799 18414 solver.cpp:397] Test net output #0: accuracy = 0.0269608 +I0410 13:40:42.589843 18414 solver.cpp:397] Test net output #1: loss = 4.88975 (* 1 = 4.88975 loss) +I0410 13:40:44.476305 18414 solver.cpp:218] Iteration 1536 (1.35943 iter/s, 8.82721s/12 iters), loss = 4.92441 +I0410 13:40:44.476359 18414 solver.cpp:237] Train net output #0: loss = 4.92441 (* 1 = 4.92441 loss) +I0410 13:40:44.476370 18414 sgd_solver.cpp:105] Iteration 1536, lr = 0.00737669 +I0410 13:40:49.364060 18414 solver.cpp:218] Iteration 1548 (2.45523 iter/s, 4.88753s/12 iters), loss = 4.86293 +I0410 13:40:49.364116 18414 solver.cpp:237] Train net output #0: loss = 4.86293 (* 1 = 4.86293 loss) +I0410 13:40:49.364130 18414 sgd_solver.cpp:105] Iteration 1548, lr = 0.00735918 +I0410 13:40:54.475062 18414 solver.cpp:218] Iteration 1560 (2.34798 iter/s, 5.11077s/12 iters), loss = 4.96922 +I0410 13:40:54.475109 18414 solver.cpp:237] Train net output #0: loss = 4.96922 (* 1 = 4.96922 loss) +I0410 13:40:54.475122 18414 sgd_solver.cpp:105] Iteration 1560, lr = 0.00734171 +I0410 13:40:59.455812 18414 solver.cpp:218] Iteration 1572 (2.40938 iter/s, 4.98053s/12 iters), loss = 4.85737 +I0410 13:40:59.455866 18414 solver.cpp:237] Train net output #0: loss = 4.85737 (* 1 = 4.85737 loss) +I0410 13:40:59.455878 18414 sgd_solver.cpp:105] Iteration 1572, lr = 0.00732427 +I0410 13:41:04.354627 18414 solver.cpp:218] Iteration 1584 (2.44968 iter/s, 4.89859s/12 iters), loss = 4.89667 +I0410 13:41:04.354681 18414 solver.cpp:237] Train net output #0: loss = 4.89667 (* 1 = 4.89667 loss) +I0410 13:41:04.354692 18414 sgd_solver.cpp:105] Iteration 1584, lr = 0.00730688 +I0410 13:41:09.247287 18414 solver.cpp:218] Iteration 1596 (2.45277 iter/s, 4.89244s/12 iters), loss = 4.76169 +I0410 13:41:09.247396 18414 solver.cpp:237] Train net output #0: loss = 4.76169 (* 1 = 4.76169 loss) +I0410 13:41:09.247409 18414 sgd_solver.cpp:105] Iteration 1596, lr = 0.00728954 +I0410 13:41:14.152238 18414 solver.cpp:218] Iteration 1608 (2.44665 iter/s, 4.90467s/12 iters), loss = 4.84343 +I0410 13:41:14.152297 18414 solver.cpp:237] Train net output #0: loss = 4.84343 (* 1 = 4.84343 loss) +I0410 13:41:14.152309 18414 sgd_solver.cpp:105] Iteration 1608, lr = 0.00727223 +I0410 13:41:18.008484 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:41:19.085561 18414 solver.cpp:218] Iteration 1620 (2.43255 iter/s, 4.9331s/12 iters), loss = 4.79993 +I0410 13:41:19.085604 18414 solver.cpp:237] Train net output #0: loss = 4.79993 (* 1 = 4.79993 loss) +I0410 13:41:19.085613 18414 sgd_solver.cpp:105] Iteration 1620, lr = 0.00725496 +I0410 13:41:23.625901 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1632.caffemodel +I0410 13:41:23.963229 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1632.solverstate +I0410 13:41:24.178838 18414 solver.cpp:330] Iteration 1632, Testing net (#0) +I0410 13:41:24.178867 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:41:28.003849 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:41:28.672793 18414 solver.cpp:397] Test net output #0: accuracy = 0.0226716 +I0410 13:41:28.672839 18414 solver.cpp:397] Test net output #1: loss = 4.87081 (* 1 = 4.87081 loss) +I0410 13:41:28.755868 18414 solver.cpp:218] Iteration 1632 (1.24096 iter/s, 9.66993s/12 iters), loss = 4.91069 +I0410 13:41:28.755926 18414 solver.cpp:237] Train net output #0: loss = 4.91069 (* 1 = 4.91069 loss) +I0410 13:41:28.755941 18414 sgd_solver.cpp:105] Iteration 1632, lr = 0.00723774 +I0410 13:41:32.987231 18414 solver.cpp:218] Iteration 1644 (2.8361 iter/s, 4.23116s/12 iters), loss = 4.92342 +I0410 13:41:32.987277 18414 solver.cpp:237] Train net output #0: loss = 4.92342 (* 1 = 4.92342 loss) +I0410 13:41:32.987290 18414 sgd_solver.cpp:105] Iteration 1644, lr = 0.00722056 +I0410 13:41:37.923141 18414 solver.cpp:218] Iteration 1656 (2.43127 iter/s, 4.93569s/12 iters), loss = 4.83072 +I0410 13:41:37.923198 18414 solver.cpp:237] Train net output #0: loss = 4.83072 (* 1 = 4.83072 loss) +I0410 13:41:37.923211 18414 sgd_solver.cpp:105] Iteration 1656, lr = 0.00720341 +I0410 13:41:42.810792 18414 solver.cpp:218] Iteration 1668 (2.45528 iter/s, 4.88742s/12 iters), loss = 4.66138 +I0410 13:41:42.810951 18414 solver.cpp:237] Train net output #0: loss = 4.66138 (* 1 = 4.66138 loss) +I0410 13:41:42.810966 18414 sgd_solver.cpp:105] Iteration 1668, lr = 0.00718631 +I0410 13:41:47.710206 18414 solver.cpp:218] Iteration 1680 (2.44943 iter/s, 4.89909s/12 iters), loss = 4.82562 +I0410 13:41:47.710247 18414 solver.cpp:237] Train net output #0: loss = 4.82562 (* 1 = 4.82562 loss) +I0410 13:41:47.710258 18414 sgd_solver.cpp:105] Iteration 1680, lr = 0.00716925 +I0410 13:41:52.622938 18414 solver.cpp:218] Iteration 1692 (2.44274 iter/s, 4.91251s/12 iters), loss = 4.83826 +I0410 13:41:52.623004 18414 solver.cpp:237] Train net output #0: loss = 4.83826 (* 1 = 4.83826 loss) +I0410 13:41:52.623023 18414 sgd_solver.cpp:105] Iteration 1692, lr = 0.00715223 +I0410 13:41:57.545172 18414 solver.cpp:218] Iteration 1704 (2.43803 iter/s, 4.922s/12 iters), loss = 4.61118 +I0410 13:41:57.545220 18414 solver.cpp:237] Train net output #0: loss = 4.61118 (* 1 = 4.61118 loss) +I0410 13:41:57.545230 18414 sgd_solver.cpp:105] Iteration 1704, lr = 0.00713525 +I0410 13:42:02.465366 18414 solver.cpp:218] Iteration 1716 (2.43904 iter/s, 4.91998s/12 iters), loss = 4.77231 +I0410 13:42:02.465415 18414 solver.cpp:237] Train net output #0: loss = 4.77231 (* 1 = 4.77231 loss) +I0410 13:42:02.465427 18414 sgd_solver.cpp:105] Iteration 1716, lr = 0.00711831 +I0410 13:42:03.495221 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:42:07.408921 18414 solver.cpp:218] Iteration 1728 (2.42751 iter/s, 4.94333s/12 iters), loss = 4.78694 +I0410 13:42:07.408982 18414 solver.cpp:237] Train net output #0: loss = 4.78694 (* 1 = 4.78694 loss) +I0410 13:42:07.408995 18414 sgd_solver.cpp:105] Iteration 1728, lr = 0.00710141 +I0410 13:42:09.394531 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1734.caffemodel +I0410 13:42:10.254133 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1734.solverstate +I0410 13:42:10.553369 18414 solver.cpp:330] Iteration 1734, Testing net (#0) +I0410 13:42:10.553390 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:42:14.299103 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:42:15.003398 18414 solver.cpp:397] Test net output #0: accuracy = 0.0324755 +I0410 13:42:15.003449 18414 solver.cpp:397] Test net output #1: loss = 4.78457 (* 1 = 4.78457 loss) +I0410 13:42:16.882753 18414 solver.cpp:218] Iteration 1740 (1.2667 iter/s, 9.47345s/12 iters), loss = 4.7619 +I0410 13:42:16.882812 18414 solver.cpp:237] Train net output #0: loss = 4.7619 (* 1 = 4.7619 loss) +I0410 13:42:16.882824 18414 sgd_solver.cpp:105] Iteration 1740, lr = 0.00708455 +I0410 13:42:21.768186 18414 solver.cpp:218] Iteration 1752 (2.4564 iter/s, 4.88521s/12 iters), loss = 4.78071 +I0410 13:42:21.768234 18414 solver.cpp:237] Train net output #0: loss = 4.78071 (* 1 = 4.78071 loss) +I0410 13:42:21.768244 18414 sgd_solver.cpp:105] Iteration 1752, lr = 0.00706773 +I0410 13:42:26.859372 18414 solver.cpp:218] Iteration 1764 (2.35712 iter/s, 5.09096s/12 iters), loss = 4.71936 +I0410 13:42:26.859416 18414 solver.cpp:237] Train net output #0: loss = 4.71936 (* 1 = 4.71936 loss) +I0410 13:42:26.859426 18414 sgd_solver.cpp:105] Iteration 1764, lr = 0.00705094 +I0410 13:42:31.782546 18414 solver.cpp:218] Iteration 1776 (2.43756 iter/s, 4.92295s/12 iters), loss = 4.80977 +I0410 13:42:31.782603 18414 solver.cpp:237] Train net output #0: loss = 4.80977 (* 1 = 4.80977 loss) +I0410 13:42:31.782614 18414 sgd_solver.cpp:105] Iteration 1776, lr = 0.0070342 +I0410 13:42:36.699331 18414 solver.cpp:218] Iteration 1788 (2.44073 iter/s, 4.91656s/12 iters), loss = 4.74778 +I0410 13:42:36.699379 18414 solver.cpp:237] Train net output #0: loss = 4.74778 (* 1 = 4.74778 loss) +I0410 13:42:36.699391 18414 sgd_solver.cpp:105] Iteration 1788, lr = 0.0070175 +I0410 13:42:41.605751 18414 solver.cpp:218] Iteration 1800 (2.44589 iter/s, 4.9062s/12 iters), loss = 4.5991 +I0410 13:42:41.605798 18414 solver.cpp:237] Train net output #0: loss = 4.5991 (* 1 = 4.5991 loss) +I0410 13:42:41.605809 18414 sgd_solver.cpp:105] Iteration 1800, lr = 0.00700084 +I0410 13:42:46.550184 18414 solver.cpp:218] Iteration 1812 (2.42708 iter/s, 4.94421s/12 iters), loss = 4.78978 +I0410 13:42:46.550308 18414 solver.cpp:237] Train net output #0: loss = 4.78978 (* 1 = 4.78978 loss) +I0410 13:42:46.550318 18414 sgd_solver.cpp:105] Iteration 1812, lr = 0.00698422 +I0410 13:42:49.668670 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:42:51.453701 18414 solver.cpp:218] Iteration 1824 (2.44737 iter/s, 4.90322s/12 iters), loss = 4.60533 +I0410 13:42:51.453760 18414 solver.cpp:237] Train net output #0: loss = 4.60533 (* 1 = 4.60533 loss) +I0410 13:42:51.453773 18414 sgd_solver.cpp:105] Iteration 1824, lr = 0.00696764 +I0410 13:42:55.932952 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1836.caffemodel +I0410 13:42:56.244904 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1836.solverstate +I0410 13:42:56.464938 18414 solver.cpp:330] Iteration 1836, Testing net (#0) +I0410 13:42:56.464956 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:43:00.234799 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:43:00.982280 18414 solver.cpp:397] Test net output #0: accuracy = 0.0373775 +I0410 13:43:00.982324 18414 solver.cpp:397] Test net output #1: loss = 4.63891 (* 1 = 4.63891 loss) +I0410 13:43:01.065310 18414 solver.cpp:218] Iteration 1836 (1.24854 iter/s, 9.61123s/12 iters), loss = 4.79966 +I0410 13:43:01.065361 18414 solver.cpp:237] Train net output #0: loss = 4.79966 (* 1 = 4.79966 loss) +I0410 13:43:01.065372 18414 sgd_solver.cpp:105] Iteration 1836, lr = 0.0069511 +I0410 13:43:05.138000 18414 solver.cpp:218] Iteration 1848 (2.9466 iter/s, 4.07249s/12 iters), loss = 4.77414 +I0410 13:43:05.138052 18414 solver.cpp:237] Train net output #0: loss = 4.77414 (* 1 = 4.77414 loss) +I0410 13:43:05.138065 18414 sgd_solver.cpp:105] Iteration 1848, lr = 0.00693459 +I0410 13:43:10.057704 18414 solver.cpp:218] Iteration 1860 (2.43928 iter/s, 4.91948s/12 iters), loss = 4.66096 +I0410 13:43:10.057754 18414 solver.cpp:237] Train net output #0: loss = 4.66096 (* 1 = 4.66096 loss) +I0410 13:43:10.057765 18414 sgd_solver.cpp:105] Iteration 1860, lr = 0.00691813 +I0410 13:43:15.008285 18414 solver.cpp:218] Iteration 1872 (2.42407 iter/s, 4.95036s/12 iters), loss = 4.64144 +I0410 13:43:15.008330 18414 solver.cpp:237] Train net output #0: loss = 4.64144 (* 1 = 4.64144 loss) +I0410 13:43:15.008342 18414 sgd_solver.cpp:105] Iteration 1872, lr = 0.0069017 +I0410 13:43:20.224874 18414 solver.cpp:218] Iteration 1884 (2.30046 iter/s, 5.21636s/12 iters), loss = 4.68019 +I0410 13:43:20.224961 18414 solver.cpp:237] Train net output #0: loss = 4.68019 (* 1 = 4.68019 loss) +I0410 13:43:20.224973 18414 sgd_solver.cpp:105] Iteration 1884, lr = 0.00688532 +I0410 13:43:25.203523 18414 solver.cpp:218] Iteration 1896 (2.41042 iter/s, 4.97839s/12 iters), loss = 4.67905 +I0410 13:43:25.203579 18414 solver.cpp:237] Train net output #0: loss = 4.67905 (* 1 = 4.67905 loss) +I0410 13:43:25.203591 18414 sgd_solver.cpp:105] Iteration 1896, lr = 0.00686897 +I0410 13:43:30.132406 18414 solver.cpp:218] Iteration 1908 (2.43474 iter/s, 4.92866s/12 iters), loss = 4.62178 +I0410 13:43:30.132450 18414 solver.cpp:237] Train net output #0: loss = 4.62178 (* 1 = 4.62178 loss) +I0410 13:43:30.132459 18414 sgd_solver.cpp:105] Iteration 1908, lr = 0.00685266 +I0410 13:43:35.060539 18414 solver.cpp:218] Iteration 1920 (2.43511 iter/s, 4.92791s/12 iters), loss = 4.70867 +I0410 13:43:35.060591 18414 solver.cpp:237] Train net output #0: loss = 4.70867 (* 1 = 4.70867 loss) +I0410 13:43:35.060601 18414 sgd_solver.cpp:105] Iteration 1920, lr = 0.00683639 +I0410 13:43:35.486928 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:43:40.111781 18414 solver.cpp:218] Iteration 1932 (2.37576 iter/s, 5.05101s/12 iters), loss = 4.61917 +I0410 13:43:40.111833 18414 solver.cpp:237] Train net output #0: loss = 4.61917 (* 1 = 4.61917 loss) +I0410 13:43:40.111845 18414 sgd_solver.cpp:105] Iteration 1932, lr = 0.00682016 +I0410 13:43:42.113250 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1938.caffemodel +I0410 13:43:42.438810 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1938.solverstate +I0410 13:43:42.651198 18414 solver.cpp:330] Iteration 1938, Testing net (#0) +I0410 13:43:42.651217 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:43:46.248142 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:43:47.031141 18414 solver.cpp:397] Test net output #0: accuracy = 0.0496324 +I0410 13:43:47.031177 18414 solver.cpp:397] Test net output #1: loss = 4.52498 (* 1 = 4.52498 loss) +I0410 13:43:48.798861 18414 solver.cpp:218] Iteration 1944 (1.38142 iter/s, 8.68673s/12 iters), loss = 4.64515 +I0410 13:43:48.798908 18414 solver.cpp:237] Train net output #0: loss = 4.64515 (* 1 = 4.64515 loss) +I0410 13:43:48.798918 18414 sgd_solver.cpp:105] Iteration 1944, lr = 0.00680397 +I0410 13:43:53.707008 18414 solver.cpp:218] Iteration 1956 (2.44503 iter/s, 4.90792s/12 iters), loss = 4.5065 +I0410 13:43:53.707159 18414 solver.cpp:237] Train net output #0: loss = 4.5065 (* 1 = 4.5065 loss) +I0410 13:43:53.707171 18414 sgd_solver.cpp:105] Iteration 1956, lr = 0.00678782 +I0410 13:43:58.673869 18414 solver.cpp:218] Iteration 1968 (2.41617 iter/s, 4.96654s/12 iters), loss = 4.45062 +I0410 13:43:58.673918 18414 solver.cpp:237] Train net output #0: loss = 4.45062 (* 1 = 4.45062 loss) +I0410 13:43:58.673930 18414 sgd_solver.cpp:105] Iteration 1968, lr = 0.0067717 +I0410 13:44:03.538074 18414 solver.cpp:218] Iteration 1980 (2.46711 iter/s, 4.86399s/12 iters), loss = 4.5621 +I0410 13:44:03.538127 18414 solver.cpp:237] Train net output #0: loss = 4.5621 (* 1 = 4.5621 loss) +I0410 13:44:03.538139 18414 sgd_solver.cpp:105] Iteration 1980, lr = 0.00675562 +I0410 13:44:08.412128 18414 solver.cpp:218] Iteration 1992 (2.46213 iter/s, 4.87383s/12 iters), loss = 4.62087 +I0410 13:44:08.412189 18414 solver.cpp:237] Train net output #0: loss = 4.62087 (* 1 = 4.62087 loss) +I0410 13:44:08.412202 18414 sgd_solver.cpp:105] Iteration 1992, lr = 0.00673958 +I0410 13:44:13.508309 18414 solver.cpp:218] Iteration 2004 (2.35482 iter/s, 5.09594s/12 iters), loss = 4.47741 +I0410 13:44:13.508363 18414 solver.cpp:237] Train net output #0: loss = 4.47741 (* 1 = 4.47741 loss) +I0410 13:44:13.508375 18414 sgd_solver.cpp:105] Iteration 2004, lr = 0.00672358 +I0410 13:44:18.480022 18414 solver.cpp:218] Iteration 2016 (2.41377 iter/s, 4.97148s/12 iters), loss = 4.54577 +I0410 13:44:18.480077 18414 solver.cpp:237] Train net output #0: loss = 4.54577 (* 1 = 4.54577 loss) +I0410 13:44:18.480088 18414 sgd_solver.cpp:105] Iteration 2016, lr = 0.00670762 +I0410 13:44:21.103185 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:23.597563 18414 solver.cpp:218] Iteration 2028 (2.34498 iter/s, 5.1173s/12 iters), loss = 4.32547 +I0410 13:44:23.597617 18414 solver.cpp:237] Train net output #0: loss = 4.32547 (* 1 = 4.32547 loss) +I0410 13:44:23.597631 18414 sgd_solver.cpp:105] Iteration 2028, lr = 0.00669169 +I0410 13:44:28.030637 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2040.caffemodel +I0410 13:44:28.349472 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2040.solverstate +I0410 13:44:28.561725 18414 solver.cpp:330] Iteration 2040, Testing net (#0) +I0410 13:44:28.561751 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:44:32.157577 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:32.983654 18414 solver.cpp:397] Test net output #0: accuracy = 0.0545343 +I0410 13:44:32.983707 18414 solver.cpp:397] Test net output #1: loss = 4.42935 (* 1 = 4.42935 loss) +I0410 13:44:33.066874 18414 solver.cpp:218] Iteration 2040 (1.2673 iter/s, 9.46894s/12 iters), loss = 4.37663 +I0410 13:44:33.066928 18414 solver.cpp:237] Train net output #0: loss = 4.37663 (* 1 = 4.37663 loss) +I0410 13:44:33.066941 18414 sgd_solver.cpp:105] Iteration 2040, lr = 0.00667581 +I0410 13:44:37.381688 18414 solver.cpp:218] Iteration 2052 (2.78125 iter/s, 4.31461s/12 iters), loss = 4.38097 +I0410 13:44:37.381744 18414 solver.cpp:237] Train net output #0: loss = 4.38097 (* 1 = 4.38097 loss) +I0410 13:44:37.381757 18414 sgd_solver.cpp:105] Iteration 2052, lr = 0.00665996 +I0410 13:44:37.382052 18414 blocking_queue.cpp:49] Waiting for data +I0410 13:44:42.272420 18414 solver.cpp:218] Iteration 2064 (2.45373 iter/s, 4.89051s/12 iters), loss = 4.52869 +I0410 13:44:42.272464 18414 solver.cpp:237] Train net output #0: loss = 4.52869 (* 1 = 4.52869 loss) +I0410 13:44:42.272475 18414 sgd_solver.cpp:105] Iteration 2064, lr = 0.00664414 +I0410 13:44:47.217397 18414 solver.cpp:218] Iteration 2076 (2.42681 iter/s, 4.94475s/12 iters), loss = 4.67386 +I0410 13:44:47.217453 18414 solver.cpp:237] Train net output #0: loss = 4.67386 (* 1 = 4.67386 loss) +I0410 13:44:47.217464 18414 sgd_solver.cpp:105] Iteration 2076, lr = 0.00662837 +I0410 13:44:52.225270 18414 solver.cpp:218] Iteration 2088 (2.39634 iter/s, 5.00764s/12 iters), loss = 4.42582 +I0410 13:44:52.225320 18414 solver.cpp:237] Train net output #0: loss = 4.42582 (* 1 = 4.42582 loss) +I0410 13:44:52.225332 18414 sgd_solver.cpp:105] Iteration 2088, lr = 0.00661263 +I0410 13:44:57.231570 18414 solver.cpp:218] Iteration 2100 (2.39709 iter/s, 5.00607s/12 iters), loss = 4.38782 +I0410 13:44:57.231616 18414 solver.cpp:237] Train net output #0: loss = 4.38782 (* 1 = 4.38782 loss) +I0410 13:44:57.231626 18414 sgd_solver.cpp:105] Iteration 2100, lr = 0.00659693 +I0410 13:45:02.159150 18414 solver.cpp:218] Iteration 2112 (2.43538 iter/s, 4.92736s/12 iters), loss = 4.41396 +I0410 13:45:02.159265 18414 solver.cpp:237] Train net output #0: loss = 4.41396 (* 1 = 4.41396 loss) +I0410 13:45:02.159279 18414 sgd_solver.cpp:105] Iteration 2112, lr = 0.00658127 +I0410 13:45:07.005097 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:07.434115 18414 solver.cpp:218] Iteration 2124 (2.27502 iter/s, 5.27467s/12 iters), loss = 4.2531 +I0410 13:45:07.434168 18414 solver.cpp:237] Train net output #0: loss = 4.2531 (* 1 = 4.2531 loss) +I0410 13:45:07.434180 18414 sgd_solver.cpp:105] Iteration 2124, lr = 0.00656564 +I0410 13:45:12.429741 18414 solver.cpp:218] Iteration 2136 (2.40221 iter/s, 4.9954s/12 iters), loss = 4.32118 +I0410 13:45:12.429788 18414 solver.cpp:237] Train net output #0: loss = 4.32118 (* 1 = 4.32118 loss) +I0410 13:45:12.429800 18414 sgd_solver.cpp:105] Iteration 2136, lr = 0.00655006 +I0410 13:45:14.480376 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2142.caffemodel +I0410 13:45:15.462234 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2142.solverstate +I0410 13:45:16.503474 18414 solver.cpp:330] Iteration 2142, Testing net (#0) +I0410 13:45:16.503506 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:45:20.162389 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:21.036149 18414 solver.cpp:397] Test net output #0: accuracy = 0.057598 +I0410 13:45:21.036196 18414 solver.cpp:397] Test net output #1: loss = 4.42432 (* 1 = 4.42432 loss) +I0410 13:45:22.951026 18414 solver.cpp:218] Iteration 2148 (1.14059 iter/s, 10.5209s/12 iters), loss = 4.3511 +I0410 13:45:22.951078 18414 solver.cpp:237] Train net output #0: loss = 4.3511 (* 1 = 4.3511 loss) +I0410 13:45:22.951089 18414 sgd_solver.cpp:105] Iteration 2148, lr = 0.00653451 +I0410 13:45:27.896766 18414 solver.cpp:218] Iteration 2160 (2.42644 iter/s, 4.94552s/12 iters), loss = 4.47949 +I0410 13:45:27.896814 18414 solver.cpp:237] Train net output #0: loss = 4.47949 (* 1 = 4.47949 loss) +I0410 13:45:27.896824 18414 sgd_solver.cpp:105] Iteration 2160, lr = 0.00651899 +I0410 13:45:32.867326 18414 solver.cpp:218] Iteration 2172 (2.41432 iter/s, 4.97034s/12 iters), loss = 4.32458 +I0410 13:45:32.867513 18414 solver.cpp:237] Train net output #0: loss = 4.32458 (* 1 = 4.32458 loss) +I0410 13:45:32.867528 18414 sgd_solver.cpp:105] Iteration 2172, lr = 0.00650351 +I0410 13:45:37.889499 18414 solver.cpp:218] Iteration 2184 (2.38957 iter/s, 5.02182s/12 iters), loss = 4.43832 +I0410 13:45:37.889554 18414 solver.cpp:237] Train net output #0: loss = 4.43832 (* 1 = 4.43832 loss) +I0410 13:45:37.889565 18414 sgd_solver.cpp:105] Iteration 2184, lr = 0.00648807 +I0410 13:45:42.897665 18414 solver.cpp:218] Iteration 2196 (2.3962 iter/s, 5.00794s/12 iters), loss = 4.51654 +I0410 13:45:42.897722 18414 solver.cpp:237] Train net output #0: loss = 4.51654 (* 1 = 4.51654 loss) +I0410 13:45:42.897735 18414 sgd_solver.cpp:105] Iteration 2196, lr = 0.00647267 +I0410 13:45:47.812731 18414 solver.cpp:218] Iteration 2208 (2.44159 iter/s, 4.91484s/12 iters), loss = 4.27511 +I0410 13:45:47.812789 18414 solver.cpp:237] Train net output #0: loss = 4.27511 (* 1 = 4.27511 loss) +I0410 13:45:47.812803 18414 sgd_solver.cpp:105] Iteration 2208, lr = 0.0064573 +I0410 13:45:52.777060 18414 solver.cpp:218] Iteration 2220 (2.41736 iter/s, 4.96409s/12 iters), loss = 4.43864 +I0410 13:45:52.777110 18414 solver.cpp:237] Train net output #0: loss = 4.43864 (* 1 = 4.43864 loss) +I0410 13:45:52.777120 18414 sgd_solver.cpp:105] Iteration 2220, lr = 0.00644197 +I0410 13:45:54.535348 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:57.663246 18414 solver.cpp:218] Iteration 2232 (2.45601 iter/s, 4.88596s/12 iters), loss = 4.37391 +I0410 13:45:57.663293 18414 solver.cpp:237] Train net output #0: loss = 4.37391 (* 1 = 4.37391 loss) +I0410 13:45:57.663302 18414 sgd_solver.cpp:105] Iteration 2232, lr = 0.00642668 +I0410 13:46:02.173698 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2244.caffemodel +I0410 13:46:02.473256 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2244.solverstate +I0410 13:46:02.670337 18414 solver.cpp:330] Iteration 2244, Testing net (#0) +I0410 13:46:02.670357 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:46:06.203639 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:46:07.109249 18414 solver.cpp:397] Test net output #0: accuracy = 0.0643382 +I0410 13:46:07.109300 18414 solver.cpp:397] Test net output #1: loss = 4.26176 (* 1 = 4.26176 loss) +I0410 13:46:07.192387 18414 solver.cpp:218] Iteration 2244 (1.25934 iter/s, 9.52877s/12 iters), loss = 4.40179 +I0410 13:46:07.192440 18414 solver.cpp:237] Train net output #0: loss = 4.40179 (* 1 = 4.40179 loss) +I0410 13:46:07.192451 18414 sgd_solver.cpp:105] Iteration 2244, lr = 0.00641142 +I0410 13:46:11.318854 18414 solver.cpp:218] Iteration 2256 (2.9082 iter/s, 4.12627s/12 iters), loss = 4.16425 +I0410 13:46:11.318900 18414 solver.cpp:237] Train net output #0: loss = 4.16425 (* 1 = 4.16425 loss) +I0410 13:46:11.318909 18414 sgd_solver.cpp:105] Iteration 2256, lr = 0.0063962 +I0410 13:46:16.196516 18414 solver.cpp:218] Iteration 2268 (2.46031 iter/s, 4.87744s/12 iters), loss = 4.33489 +I0410 13:46:16.196561 18414 solver.cpp:237] Train net output #0: loss = 4.33489 (* 1 = 4.33489 loss) +I0410 13:46:16.196570 18414 sgd_solver.cpp:105] Iteration 2268, lr = 0.00638101 +I0410 13:46:21.154881 18414 solver.cpp:218] Iteration 2280 (2.42026 iter/s, 4.95814s/12 iters), loss = 4.36555 +I0410 13:46:21.154925 18414 solver.cpp:237] Train net output #0: loss = 4.36555 (* 1 = 4.36555 loss) +I0410 13:46:21.154934 18414 sgd_solver.cpp:105] Iteration 2280, lr = 0.00636586 +I0410 13:46:26.164386 18414 solver.cpp:218] Iteration 2292 (2.39555 iter/s, 5.00928s/12 iters), loss = 4.24164 +I0410 13:46:26.164438 18414 solver.cpp:237] Train net output #0: loss = 4.24164 (* 1 = 4.24164 loss) +I0410 13:46:26.164448 18414 sgd_solver.cpp:105] Iteration 2292, lr = 0.00635075 +I0410 13:46:31.249780 18414 solver.cpp:218] Iteration 2304 (2.35981 iter/s, 5.08517s/12 iters), loss = 4.40367 +I0410 13:46:31.249828 18414 solver.cpp:237] Train net output #0: loss = 4.40367 (* 1 = 4.40367 loss) +I0410 13:46:31.249838 18414 sgd_solver.cpp:105] Iteration 2304, lr = 0.00633567 +I0410 13:46:36.202759 18414 solver.cpp:218] Iteration 2316 (2.42289 iter/s, 4.95276s/12 iters), loss = 4.33381 +I0410 13:46:36.202816 18414 solver.cpp:237] Train net output #0: loss = 4.33381 (* 1 = 4.33381 loss) +I0410 13:46:36.202829 18414 sgd_solver.cpp:105] Iteration 2316, lr = 0.00632063 +I0410 13:46:40.108769 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:46:41.153715 18414 solver.cpp:218] Iteration 2328 (2.42389 iter/s, 4.95073s/12 iters), loss = 4.20526 +I0410 13:46:41.153775 18414 solver.cpp:237] Train net output #0: loss = 4.20526 (* 1 = 4.20526 loss) +I0410 13:46:41.153789 18414 sgd_solver.cpp:105] Iteration 2328, lr = 0.00630562 +I0410 13:46:46.125656 18414 solver.cpp:218] Iteration 2340 (2.41366 iter/s, 4.97171s/12 iters), loss = 4.09605 +I0410 13:46:46.125708 18414 solver.cpp:237] Train net output #0: loss = 4.09605 (* 1 = 4.09605 loss) +I0410 13:46:46.125720 18414 sgd_solver.cpp:105] Iteration 2340, lr = 0.00629065 +I0410 13:46:48.164641 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2346.caffemodel +I0410 13:46:48.456393 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2346.solverstate +I0410 13:46:48.662020 18414 solver.cpp:330] Iteration 2346, Testing net (#0) +I0410 13:46:48.662043 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:46:52.159699 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:46:53.099689 18414 solver.cpp:397] Test net output #0: accuracy = 0.0827206 +I0410 13:46:53.099740 18414 solver.cpp:397] Test net output #1: loss = 4.12775 (* 1 = 4.12775 loss) +I0410 13:46:55.068559 18414 solver.cpp:218] Iteration 2352 (1.3419 iter/s, 8.94255s/12 iters), loss = 4.17091 +I0410 13:46:55.068608 18414 solver.cpp:237] Train net output #0: loss = 4.17091 (* 1 = 4.17091 loss) +I0410 13:46:55.068619 18414 sgd_solver.cpp:105] Iteration 2352, lr = 0.00627571 +I0410 13:47:00.101277 18414 solver.cpp:218] Iteration 2364 (2.38451 iter/s, 5.03249s/12 iters), loss = 4.17065 +I0410 13:47:00.101330 18414 solver.cpp:237] Train net output #0: loss = 4.17065 (* 1 = 4.17065 loss) +I0410 13:47:00.101341 18414 sgd_solver.cpp:105] Iteration 2364, lr = 0.00626081 +I0410 13:47:05.114555 18414 solver.cpp:218] Iteration 2376 (2.39375 iter/s, 5.01305s/12 iters), loss = 4.12378 +I0410 13:47:05.114606 18414 solver.cpp:237] Train net output #0: loss = 4.12378 (* 1 = 4.12378 loss) +I0410 13:47:05.114620 18414 sgd_solver.cpp:105] Iteration 2376, lr = 0.00624595 +I0410 13:47:10.107283 18414 solver.cpp:218] Iteration 2388 (2.40361 iter/s, 4.9925s/12 iters), loss = 4.17782 +I0410 13:47:10.107331 18414 solver.cpp:237] Train net output #0: loss = 4.17782 (* 1 = 4.17782 loss) +I0410 13:47:10.107340 18414 sgd_solver.cpp:105] Iteration 2388, lr = 0.00623112 +I0410 13:47:15.085644 18414 solver.cpp:218] Iteration 2400 (2.41054 iter/s, 4.97813s/12 iters), loss = 4.14265 +I0410 13:47:15.085774 18414 solver.cpp:237] Train net output #0: loss = 4.14265 (* 1 = 4.14265 loss) +I0410 13:47:15.085789 18414 sgd_solver.cpp:105] Iteration 2400, lr = 0.00621633 +I0410 13:47:19.941720 18414 solver.cpp:218] Iteration 2412 (2.47128 iter/s, 4.85578s/12 iters), loss = 3.9827 +I0410 13:47:19.941761 18414 solver.cpp:237] Train net output #0: loss = 3.9827 (* 1 = 3.9827 loss) +I0410 13:47:19.941771 18414 sgd_solver.cpp:105] Iteration 2412, lr = 0.00620157 +I0410 13:47:24.905184 18414 solver.cpp:218] Iteration 2424 (2.41777 iter/s, 4.96325s/12 iters), loss = 4.23445 +I0410 13:47:24.905233 18414 solver.cpp:237] Train net output #0: loss = 4.23445 (* 1 = 4.23445 loss) +I0410 13:47:24.905246 18414 sgd_solver.cpp:105] Iteration 2424, lr = 0.00618684 +I0410 13:47:25.940922 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:29.914173 18414 solver.cpp:218] Iteration 2436 (2.3958 iter/s, 5.00876s/12 iters), loss = 3.963 +I0410 13:47:29.914232 18414 solver.cpp:237] Train net output #0: loss = 3.963 (* 1 = 3.963 loss) +I0410 13:47:29.914244 18414 sgd_solver.cpp:105] Iteration 2436, lr = 0.00617215 +I0410 13:47:34.603446 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2448.caffemodel +I0410 13:47:35.163326 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2448.solverstate +I0410 13:47:35.377991 18414 solver.cpp:330] Iteration 2448, Testing net (#0) +I0410 13:47:35.378028 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:47:38.784369 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:39.809201 18414 solver.cpp:397] Test net output #0: accuracy = 0.0863971 +I0410 13:47:39.809253 18414 solver.cpp:397] Test net output #1: loss = 4.02927 (* 1 = 4.02927 loss) +I0410 13:47:39.892274 18414 solver.cpp:218] Iteration 2448 (1.20268 iter/s, 9.97771s/12 iters), loss = 3.98828 +I0410 13:47:39.892323 18414 solver.cpp:237] Train net output #0: loss = 3.98828 (* 1 = 3.98828 loss) +I0410 13:47:39.892333 18414 sgd_solver.cpp:105] Iteration 2448, lr = 0.0061575 +I0410 13:47:44.013083 18414 solver.cpp:218] Iteration 2460 (2.91219 iter/s, 4.12061s/12 iters), loss = 4.13796 +I0410 13:47:44.013131 18414 solver.cpp:237] Train net output #0: loss = 4.13796 (* 1 = 4.13796 loss) +I0410 13:47:44.013144 18414 sgd_solver.cpp:105] Iteration 2460, lr = 0.00614288 +I0410 13:47:48.871409 18414 solver.cpp:218] Iteration 2472 (2.4701 iter/s, 4.8581s/12 iters), loss = 4.05721 +I0410 13:47:48.871553 18414 solver.cpp:237] Train net output #0: loss = 4.05721 (* 1 = 4.05721 loss) +I0410 13:47:48.871565 18414 sgd_solver.cpp:105] Iteration 2472, lr = 0.0061283 +I0410 13:47:53.833326 18414 solver.cpp:218] Iteration 2484 (2.41857 iter/s, 4.9616s/12 iters), loss = 4.14055 +I0410 13:47:53.833366 18414 solver.cpp:237] Train net output #0: loss = 4.14055 (* 1 = 4.14055 loss) +I0410 13:47:53.833375 18414 sgd_solver.cpp:105] Iteration 2484, lr = 0.00611375 +I0410 13:47:58.803802 18414 solver.cpp:218] Iteration 2496 (2.41436 iter/s, 4.97026s/12 iters), loss = 4.23468 +I0410 13:47:58.803855 18414 solver.cpp:237] Train net output #0: loss = 4.23468 (* 1 = 4.23468 loss) +I0410 13:47:58.803866 18414 sgd_solver.cpp:105] Iteration 2496, lr = 0.00609923 +I0410 13:48:03.754518 18414 solver.cpp:218] Iteration 2508 (2.424 iter/s, 4.95049s/12 iters), loss = 4.15612 +I0410 13:48:03.754575 18414 solver.cpp:237] Train net output #0: loss = 4.15612 (* 1 = 4.15612 loss) +I0410 13:48:03.754590 18414 sgd_solver.cpp:105] Iteration 2508, lr = 0.00608475 +I0410 13:48:08.726279 18414 solver.cpp:218] Iteration 2520 (2.41374 iter/s, 4.97153s/12 iters), loss = 4.20219 +I0410 13:48:08.726326 18414 solver.cpp:237] Train net output #0: loss = 4.20219 (* 1 = 4.20219 loss) +I0410 13:48:08.726336 18414 sgd_solver.cpp:105] Iteration 2520, lr = 0.0060703 +I0410 13:48:11.860965 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:48:13.585193 18414 solver.cpp:218] Iteration 2532 (2.4698 iter/s, 4.85869s/12 iters), loss = 4.10859 +I0410 13:48:13.585249 18414 solver.cpp:237] Train net output #0: loss = 4.10859 (* 1 = 4.10859 loss) +I0410 13:48:13.585263 18414 sgd_solver.cpp:105] Iteration 2532, lr = 0.00605589 +I0410 13:48:18.490806 18414 solver.cpp:218] Iteration 2544 (2.44629 iter/s, 4.90539s/12 iters), loss = 3.9133 +I0410 13:48:18.490847 18414 solver.cpp:237] Train net output #0: loss = 3.9133 (* 1 = 3.9133 loss) +I0410 13:48:18.490856 18414 sgd_solver.cpp:105] Iteration 2544, lr = 0.00604151 +I0410 13:48:20.506240 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2550.caffemodel +I0410 13:48:21.324074 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2550.solverstate +I0410 13:48:21.526445 18414 solver.cpp:330] Iteration 2550, Testing net (#0) +I0410 13:48:21.526464 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:48:24.938338 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:48:25.968605 18414 solver.cpp:397] Test net output #0: accuracy = 0.0949755 +I0410 13:48:25.968664 18414 solver.cpp:397] Test net output #1: loss = 3.97405 (* 1 = 3.97405 loss) +I0410 13:48:27.928553 18414 solver.cpp:218] Iteration 2556 (1.27154 iter/s, 9.43739s/12 iters), loss = 4.10569 +I0410 13:48:27.928601 18414 solver.cpp:237] Train net output #0: loss = 4.10569 (* 1 = 4.10569 loss) +I0410 13:48:27.928611 18414 sgd_solver.cpp:105] Iteration 2556, lr = 0.00602717 +I0410 13:48:32.883217 18414 solver.cpp:218] Iteration 2568 (2.42207 iter/s, 4.95444s/12 iters), loss = 3.96756 +I0410 13:48:32.883267 18414 solver.cpp:237] Train net output #0: loss = 3.96756 (* 1 = 3.96756 loss) +I0410 13:48:32.883276 18414 sgd_solver.cpp:105] Iteration 2568, lr = 0.00601286 +I0410 13:48:37.810613 18414 solver.cpp:218] Iteration 2580 (2.43548 iter/s, 4.92717s/12 iters), loss = 3.9357 +I0410 13:48:37.810664 18414 solver.cpp:237] Train net output #0: loss = 3.9357 (* 1 = 3.9357 loss) +I0410 13:48:37.810678 18414 sgd_solver.cpp:105] Iteration 2580, lr = 0.00599858 +I0410 13:48:42.691910 18414 solver.cpp:218] Iteration 2592 (2.45848 iter/s, 4.88107s/12 iters), loss = 4.15716 +I0410 13:48:42.691970 18414 solver.cpp:237] Train net output #0: loss = 4.15716 (* 1 = 4.15716 loss) +I0410 13:48:42.691982 18414 sgd_solver.cpp:105] Iteration 2592, lr = 0.00598434 +I0410 13:48:47.614104 18414 solver.cpp:218] Iteration 2604 (2.43805 iter/s, 4.92196s/12 iters), loss = 4.04234 +I0410 13:48:47.614161 18414 solver.cpp:237] Train net output #0: loss = 4.04234 (* 1 = 4.04234 loss) +I0410 13:48:47.614173 18414 sgd_solver.cpp:105] Iteration 2604, lr = 0.00597013 +I0410 13:48:52.855720 18414 solver.cpp:218] Iteration 2616 (2.28948 iter/s, 5.24137s/12 iters), loss = 4.04193 +I0410 13:48:52.855826 18414 solver.cpp:237] Train net output #0: loss = 4.04193 (* 1 = 4.04193 loss) +I0410 13:48:52.855837 18414 sgd_solver.cpp:105] Iteration 2616, lr = 0.00595596 +I0410 13:48:57.791118 18414 solver.cpp:218] Iteration 2628 (2.43155 iter/s, 4.93512s/12 iters), loss = 4.17375 +I0410 13:48:57.791172 18414 solver.cpp:237] Train net output #0: loss = 4.17375 (* 1 = 4.17375 loss) +I0410 13:48:57.791184 18414 sgd_solver.cpp:105] Iteration 2628, lr = 0.00594182 +I0410 13:48:58.217216 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:02.785001 18414 solver.cpp:218] Iteration 2640 (2.40305 iter/s, 4.99366s/12 iters), loss = 3.93077 +I0410 13:49:02.785053 18414 solver.cpp:237] Train net output #0: loss = 3.93077 (* 1 = 3.93077 loss) +I0410 13:49:02.785064 18414 sgd_solver.cpp:105] Iteration 2640, lr = 0.00592771 +I0410 13:49:07.333087 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2652.caffemodel +I0410 13:49:07.663471 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2652.solverstate +I0410 13:49:07.875030 18414 solver.cpp:330] Iteration 2652, Testing net (#0) +I0410 13:49:07.875052 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:49:11.378588 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:12.440490 18414 solver.cpp:397] Test net output #0: accuracy = 0.11152 +I0410 13:49:12.440537 18414 solver.cpp:397] Test net output #1: loss = 3.81984 (* 1 = 3.81984 loss) +I0410 13:49:12.523479 18414 solver.cpp:218] Iteration 2652 (1.23227 iter/s, 9.7381s/12 iters), loss = 3.79404 +I0410 13:49:12.523531 18414 solver.cpp:237] Train net output #0: loss = 3.79404 (* 1 = 3.79404 loss) +I0410 13:49:12.523542 18414 sgd_solver.cpp:105] Iteration 2652, lr = 0.00591364 +I0410 13:49:16.828434 18414 solver.cpp:218] Iteration 2664 (2.78762 iter/s, 4.30475s/12 iters), loss = 3.87898 +I0410 13:49:16.828483 18414 solver.cpp:237] Train net output #0: loss = 3.87898 (* 1 = 3.87898 loss) +I0410 13:49:16.828495 18414 sgd_solver.cpp:105] Iteration 2664, lr = 0.0058996 +I0410 13:49:21.773969 18414 solver.cpp:218] Iteration 2676 (2.42655 iter/s, 4.9453s/12 iters), loss = 3.94354 +I0410 13:49:21.774016 18414 solver.cpp:237] Train net output #0: loss = 3.94354 (* 1 = 3.94354 loss) +I0410 13:49:21.774026 18414 sgd_solver.cpp:105] Iteration 2676, lr = 0.00588559 +I0410 13:49:27.082185 18414 solver.cpp:218] Iteration 2688 (2.26075 iter/s, 5.30798s/12 iters), loss = 3.9881 +I0410 13:49:27.082345 18414 solver.cpp:237] Train net output #0: loss = 3.9881 (* 1 = 3.9881 loss) +I0410 13:49:27.082358 18414 sgd_solver.cpp:105] Iteration 2688, lr = 0.00587162 +I0410 13:49:32.049407 18414 solver.cpp:218] Iteration 2700 (2.416 iter/s, 4.96689s/12 iters), loss = 3.8019 +I0410 13:49:32.049463 18414 solver.cpp:237] Train net output #0: loss = 3.8019 (* 1 = 3.8019 loss) +I0410 13:49:32.049475 18414 sgd_solver.cpp:105] Iteration 2700, lr = 0.00585768 +I0410 13:49:37.004009 18414 solver.cpp:218] Iteration 2712 (2.4221 iter/s, 4.95437s/12 iters), loss = 3.86684 +I0410 13:49:37.004050 18414 solver.cpp:237] Train net output #0: loss = 3.86684 (* 1 = 3.86684 loss) +I0410 13:49:37.004058 18414 sgd_solver.cpp:105] Iteration 2712, lr = 0.00584377 +I0410 13:49:41.874984 18414 solver.cpp:218] Iteration 2724 (2.46368 iter/s, 4.87076s/12 iters), loss = 4.03465 +I0410 13:49:41.875032 18414 solver.cpp:237] Train net output #0: loss = 4.03465 (* 1 = 4.03465 loss) +I0410 13:49:41.875041 18414 sgd_solver.cpp:105] Iteration 2724, lr = 0.0058299 +I0410 13:49:44.416754 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:46.799170 18414 solver.cpp:218] Iteration 2736 (2.43706 iter/s, 4.92396s/12 iters), loss = 3.73403 +I0410 13:49:46.799219 18414 solver.cpp:237] Train net output #0: loss = 3.73403 (* 1 = 3.73403 loss) +I0410 13:49:46.799232 18414 sgd_solver.cpp:105] Iteration 2736, lr = 0.00581605 +I0410 13:49:51.909889 18414 solver.cpp:218] Iteration 2748 (2.34811 iter/s, 5.11049s/12 iters), loss = 3.88427 +I0410 13:49:51.909943 18414 solver.cpp:237] Train net output #0: loss = 3.88427 (* 1 = 3.88427 loss) +I0410 13:49:51.909971 18414 sgd_solver.cpp:105] Iteration 2748, lr = 0.00580225 +I0410 13:49:54.110026 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2754.caffemodel +I0410 13:49:54.401068 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2754.solverstate +I0410 13:49:54.597044 18414 solver.cpp:330] Iteration 2754, Testing net (#0) +I0410 13:49:54.597070 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:49:57.503176 18414 blocking_queue.cpp:49] Waiting for data +I0410 13:49:58.144167 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:59.321875 18414 solver.cpp:397] Test net output #0: accuracy = 0.115196 +I0410 13:49:59.321904 18414 solver.cpp:397] Test net output #1: loss = 3.78614 (* 1 = 3.78614 loss) +I0410 13:50:01.644927 18414 solver.cpp:218] Iteration 2760 (1.23271 iter/s, 9.73466s/12 iters), loss = 3.77909 +I0410 13:50:01.644975 18414 solver.cpp:237] Train net output #0: loss = 3.77909 (* 1 = 3.77909 loss) +I0410 13:50:01.644984 18414 sgd_solver.cpp:105] Iteration 2760, lr = 0.00578847 +I0410 13:50:07.340348 18414 solver.cpp:218] Iteration 2772 (2.10705 iter/s, 5.69517s/12 iters), loss = 3.70015 +I0410 13:50:07.340404 18414 solver.cpp:237] Train net output #0: loss = 3.70015 (* 1 = 3.70015 loss) +I0410 13:50:07.340416 18414 sgd_solver.cpp:105] Iteration 2772, lr = 0.00577473 +I0410 13:50:12.330922 18414 solver.cpp:218] Iteration 2784 (2.40464 iter/s, 4.99034s/12 iters), loss = 3.91902 +I0410 13:50:12.330983 18414 solver.cpp:237] Train net output #0: loss = 3.91902 (* 1 = 3.91902 loss) +I0410 13:50:12.330996 18414 sgd_solver.cpp:105] Iteration 2784, lr = 0.00576102 +I0410 13:50:17.314252 18414 solver.cpp:218] Iteration 2796 (2.40814 iter/s, 4.98309s/12 iters), loss = 3.64917 +I0410 13:50:17.314314 18414 solver.cpp:237] Train net output #0: loss = 3.64917 (* 1 = 3.64917 loss) +I0410 13:50:17.314327 18414 sgd_solver.cpp:105] Iteration 2796, lr = 0.00574734 +I0410 13:50:22.293895 18414 solver.cpp:218] Iteration 2808 (2.40992 iter/s, 4.97941s/12 iters), loss = 3.63892 +I0410 13:50:22.293946 18414 solver.cpp:237] Train net output #0: loss = 3.63892 (* 1 = 3.63892 loss) +I0410 13:50:22.293974 18414 sgd_solver.cpp:105] Iteration 2808, lr = 0.00573369 +I0410 13:50:27.337122 18414 solver.cpp:218] Iteration 2820 (2.37954 iter/s, 5.04299s/12 iters), loss = 3.73945 +I0410 13:50:27.337183 18414 solver.cpp:237] Train net output #0: loss = 3.73945 (* 1 = 3.73945 loss) +I0410 13:50:27.337196 18414 sgd_solver.cpp:105] Iteration 2820, lr = 0.00572008 +I0410 13:50:32.026021 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:32.307150 18414 solver.cpp:218] Iteration 2832 (2.41459 iter/s, 4.96979s/12 iters), loss = 3.47928 +I0410 13:50:32.307206 18414 solver.cpp:237] Train net output #0: loss = 3.47928 (* 1 = 3.47928 loss) +I0410 13:50:32.307227 18414 sgd_solver.cpp:105] Iteration 2832, lr = 0.0057065 +I0410 13:50:37.189402 18414 solver.cpp:218] Iteration 2844 (2.458 iter/s, 4.88202s/12 iters), loss = 3.81042 +I0410 13:50:37.189472 18414 solver.cpp:237] Train net output #0: loss = 3.81042 (* 1 = 3.81042 loss) +I0410 13:50:37.189487 18414 sgd_solver.cpp:105] Iteration 2844, lr = 0.00569295 +I0410 13:50:41.593636 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2856.caffemodel +I0410 13:50:41.888159 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2856.solverstate +I0410 13:50:42.082072 18414 solver.cpp:330] Iteration 2856, Testing net (#0) +I0410 13:50:42.082091 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:50:45.402696 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:46.688247 18414 solver.cpp:397] Test net output #0: accuracy = 0.110907 +I0410 13:50:46.688298 18414 solver.cpp:397] Test net output #1: loss = 3.71302 (* 1 = 3.71302 loss) +I0410 13:50:46.774282 18414 solver.cpp:218] Iteration 2856 (1.25201 iter/s, 9.5846s/12 iters), loss = 3.59756 +I0410 13:50:46.774322 18414 solver.cpp:237] Train net output #0: loss = 3.59756 (* 1 = 3.59756 loss) +I0410 13:50:46.774333 18414 sgd_solver.cpp:105] Iteration 2856, lr = 0.00567944 +I0410 13:50:50.906733 18414 solver.cpp:218] Iteration 2868 (2.90395 iter/s, 4.1323s/12 iters), loss = 3.96012 +I0410 13:50:50.906790 18414 solver.cpp:237] Train net output #0: loss = 3.96012 (* 1 = 3.96012 loss) +I0410 13:50:50.906803 18414 sgd_solver.cpp:105] Iteration 2868, lr = 0.00566595 +I0410 13:50:55.825377 18414 solver.cpp:218] Iteration 2880 (2.43979 iter/s, 4.91846s/12 iters), loss = 3.78693 +I0410 13:50:55.825443 18414 solver.cpp:237] Train net output #0: loss = 3.78693 (* 1 = 3.78693 loss) +I0410 13:50:55.825459 18414 sgd_solver.cpp:105] Iteration 2880, lr = 0.0056525 +I0410 13:51:00.775544 18414 solver.cpp:218] Iteration 2892 (2.42425 iter/s, 4.94998s/12 iters), loss = 3.67015 +I0410 13:51:00.775604 18414 solver.cpp:237] Train net output #0: loss = 3.67015 (* 1 = 3.67015 loss) +I0410 13:51:00.775617 18414 sgd_solver.cpp:105] Iteration 2892, lr = 0.00563908 +I0410 13:51:05.678243 18414 solver.cpp:218] Iteration 2904 (2.44772 iter/s, 4.90252s/12 iters), loss = 3.69001 +I0410 13:51:05.678319 18414 solver.cpp:237] Train net output #0: loss = 3.69001 (* 1 = 3.69001 loss) +I0410 13:51:05.678329 18414 sgd_solver.cpp:105] Iteration 2904, lr = 0.00562569 +I0410 13:51:10.566437 18414 solver.cpp:218] Iteration 2916 (2.455 iter/s, 4.88799s/12 iters), loss = 3.71568 +I0410 13:51:10.566494 18414 solver.cpp:237] Train net output #0: loss = 3.71568 (* 1 = 3.71568 loss) +I0410 13:51:10.566506 18414 sgd_solver.cpp:105] Iteration 2916, lr = 0.00561233 +I0410 13:51:15.436333 18414 solver.cpp:218] Iteration 2928 (2.46421 iter/s, 4.86971s/12 iters), loss = 3.76573 +I0410 13:51:15.436383 18414 solver.cpp:237] Train net output #0: loss = 3.76573 (* 1 = 3.76573 loss) +I0410 13:51:15.436394 18414 sgd_solver.cpp:105] Iteration 2928, lr = 0.00559901 +I0410 13:51:17.263586 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:51:20.352831 18414 solver.cpp:218] Iteration 2940 (2.44085 iter/s, 4.91632s/12 iters), loss = 3.54438 +I0410 13:51:20.352888 18414 solver.cpp:237] Train net output #0: loss = 3.54438 (* 1 = 3.54438 loss) +I0410 13:51:20.352900 18414 sgd_solver.cpp:105] Iteration 2940, lr = 0.00558572 +I0410 13:51:25.314632 18414 solver.cpp:218] Iteration 2952 (2.41857 iter/s, 4.96161s/12 iters), loss = 3.69539 +I0410 13:51:25.314679 18414 solver.cpp:237] Train net output #0: loss = 3.69539 (* 1 = 3.69539 loss) +I0410 13:51:25.314688 18414 sgd_solver.cpp:105] Iteration 2952, lr = 0.00557245 +I0410 13:51:27.299798 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2958.caffemodel +I0410 13:51:27.596752 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2958.solverstate +I0410 13:51:27.807029 18414 solver.cpp:330] Iteration 2958, Testing net (#0) +I0410 13:51:27.807050 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:51:31.070546 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:51:32.249120 18414 solver.cpp:397] Test net output #0: accuracy = 0.171569 +I0410 13:51:32.249174 18414 solver.cpp:397] Test net output #1: loss = 3.47051 (* 1 = 3.47051 loss) +I0410 13:51:33.950291 18414 solver.cpp:218] Iteration 2964 (1.38963 iter/s, 8.6354s/12 iters), loss = 3.32671 +I0410 13:51:33.950342 18414 solver.cpp:237] Train net output #0: loss = 3.32671 (* 1 = 3.32671 loss) +I0410 13:51:33.950354 18414 sgd_solver.cpp:105] Iteration 2964, lr = 0.00555922 +I0410 13:51:38.821691 18414 solver.cpp:218] Iteration 2976 (2.46345 iter/s, 4.87122s/12 iters), loss = 3.63552 +I0410 13:51:38.821848 18414 solver.cpp:237] Train net output #0: loss = 3.63552 (* 1 = 3.63552 loss) +I0410 13:51:38.821861 18414 sgd_solver.cpp:105] Iteration 2976, lr = 0.00554603 +I0410 13:51:43.743206 18414 solver.cpp:218] Iteration 2988 (2.43841 iter/s, 4.92124s/12 iters), loss = 3.52068 +I0410 13:51:43.743257 18414 solver.cpp:237] Train net output #0: loss = 3.52068 (* 1 = 3.52068 loss) +I0410 13:51:43.743268 18414 sgd_solver.cpp:105] Iteration 2988, lr = 0.00553286 +I0410 13:51:48.692811 18414 solver.cpp:218] Iteration 3000 (2.42452 iter/s, 4.94942s/12 iters), loss = 3.77422 +I0410 13:51:48.692867 18414 solver.cpp:237] Train net output #0: loss = 3.77422 (* 1 = 3.77422 loss) +I0410 13:51:48.692880 18414 sgd_solver.cpp:105] Iteration 3000, lr = 0.00551972 +I0410 13:51:53.586128 18414 solver.cpp:218] Iteration 3012 (2.45242 iter/s, 4.89314s/12 iters), loss = 3.70725 +I0410 13:51:53.586176 18414 solver.cpp:237] Train net output #0: loss = 3.70725 (* 1 = 3.70725 loss) +I0410 13:51:53.586185 18414 sgd_solver.cpp:105] Iteration 3012, lr = 0.00550662 +I0410 13:51:58.669782 18414 solver.cpp:218] Iteration 3024 (2.36059 iter/s, 5.08347s/12 iters), loss = 3.48861 +I0410 13:51:58.669842 18414 solver.cpp:237] Train net output #0: loss = 3.48861 (* 1 = 3.48861 loss) +I0410 13:51:58.669855 18414 sgd_solver.cpp:105] Iteration 3024, lr = 0.00549354 +I0410 13:52:02.708534 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:52:03.712018 18414 solver.cpp:218] Iteration 3036 (2.37999 iter/s, 5.04204s/12 iters), loss = 3.56953 +I0410 13:52:03.712074 18414 solver.cpp:237] Train net output #0: loss = 3.56953 (* 1 = 3.56953 loss) +I0410 13:52:03.712088 18414 sgd_solver.cpp:105] Iteration 3036, lr = 0.0054805 +I0410 13:52:08.602952 18414 solver.cpp:218] Iteration 3048 (2.45361 iter/s, 4.89075s/12 iters), loss = 3.65539 +I0410 13:52:08.603008 18414 solver.cpp:237] Train net output #0: loss = 3.65539 (* 1 = 3.65539 loss) +I0410 13:52:08.603020 18414 sgd_solver.cpp:105] Iteration 3048, lr = 0.00546749 +I0410 13:52:13.026718 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3060.caffemodel +I0410 13:52:13.335188 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3060.solverstate +I0410 13:52:13.545740 18414 solver.cpp:330] Iteration 3060, Testing net (#0) +I0410 13:52:13.545763 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:52:16.786015 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:52:17.998577 18414 solver.cpp:397] Test net output #0: accuracy = 0.146446 +I0410 13:52:17.998615 18414 solver.cpp:397] Test net output #1: loss = 3.51531 (* 1 = 3.51531 loss) +I0410 13:52:18.081508 18414 solver.cpp:218] Iteration 3060 (1.26605 iter/s, 9.47826s/12 iters), loss = 3.64994 +I0410 13:52:18.081547 18414 solver.cpp:237] Train net output #0: loss = 3.64994 (* 1 = 3.64994 loss) +I0410 13:52:18.081555 18414 sgd_solver.cpp:105] Iteration 3060, lr = 0.00545451 +I0410 13:52:22.235957 18414 solver.cpp:218] Iteration 3072 (2.88857 iter/s, 4.1543s/12 iters), loss = 3.33306 +I0410 13:52:22.235998 18414 solver.cpp:237] Train net output #0: loss = 3.33306 (* 1 = 3.33306 loss) +I0410 13:52:22.236006 18414 sgd_solver.cpp:105] Iteration 3072, lr = 0.00544156 +I0410 13:52:27.193996 18414 solver.cpp:218] Iteration 3084 (2.4204 iter/s, 4.95786s/12 iters), loss = 3.60152 +I0410 13:52:27.194058 18414 solver.cpp:237] Train net output #0: loss = 3.60152 (* 1 = 3.60152 loss) +I0410 13:52:27.194072 18414 sgd_solver.cpp:105] Iteration 3084, lr = 0.00542864 +I0410 13:52:32.099275 18414 solver.cpp:218] Iteration 3096 (2.44644 iter/s, 4.90509s/12 iters), loss = 3.59683 +I0410 13:52:32.099330 18414 solver.cpp:237] Train net output #0: loss = 3.59683 (* 1 = 3.59683 loss) +I0410 13:52:32.099342 18414 sgd_solver.cpp:105] Iteration 3096, lr = 0.00541575 +I0410 13:52:37.028882 18414 solver.cpp:218] Iteration 3108 (2.43437 iter/s, 4.92942s/12 iters), loss = 3.38059 +I0410 13:52:37.028942 18414 solver.cpp:237] Train net output #0: loss = 3.38059 (* 1 = 3.38059 loss) +I0410 13:52:37.028954 18414 sgd_solver.cpp:105] Iteration 3108, lr = 0.00540289 +I0410 13:52:41.871585 18414 solver.cpp:218] Iteration 3120 (2.47805 iter/s, 4.84251s/12 iters), loss = 3.21714 +I0410 13:52:41.871644 18414 solver.cpp:237] Train net output #0: loss = 3.21714 (* 1 = 3.21714 loss) +I0410 13:52:41.871655 18414 sgd_solver.cpp:105] Iteration 3120, lr = 0.00539006 +I0410 13:52:46.746475 18414 solver.cpp:218] Iteration 3132 (2.46169 iter/s, 4.8747s/12 iters), loss = 3.69685 +I0410 13:52:46.746605 18414 solver.cpp:237] Train net output #0: loss = 3.69685 (* 1 = 3.69685 loss) +I0410 13:52:46.746618 18414 sgd_solver.cpp:105] Iteration 3132, lr = 0.00537727 +I0410 13:52:47.827234 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:52:51.636044 18414 solver.cpp:218] Iteration 3144 (2.45434 iter/s, 4.8893s/12 iters), loss = 3.42414 +I0410 13:52:51.636099 18414 solver.cpp:237] Train net output #0: loss = 3.42414 (* 1 = 3.42414 loss) +I0410 13:52:51.636111 18414 sgd_solver.cpp:105] Iteration 3144, lr = 0.0053645 +I0410 13:52:56.492864 18414 solver.cpp:218] Iteration 3156 (2.47085 iter/s, 4.85663s/12 iters), loss = 3.30308 +I0410 13:52:56.492929 18414 solver.cpp:237] Train net output #0: loss = 3.30308 (* 1 = 3.30308 loss) +I0410 13:52:56.492942 18414 sgd_solver.cpp:105] Iteration 3156, lr = 0.00535176 +I0410 13:52:58.449638 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3162.caffemodel +I0410 13:52:58.771698 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3162.solverstate +I0410 13:52:58.966497 18414 solver.cpp:330] Iteration 3162, Testing net (#0) +I0410 13:52:58.966521 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:53:02.217779 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:03.478456 18414 solver.cpp:397] Test net output #0: accuracy = 0.17402 +I0410 13:53:03.478507 18414 solver.cpp:397] Test net output #1: loss = 3.37063 (* 1 = 3.37063 loss) +I0410 13:53:05.266052 18414 solver.cpp:218] Iteration 3168 (1.36785 iter/s, 8.77289s/12 iters), loss = 3.27858 +I0410 13:53:05.266117 18414 solver.cpp:237] Train net output #0: loss = 3.27858 (* 1 = 3.27858 loss) +I0410 13:53:05.266129 18414 sgd_solver.cpp:105] Iteration 3168, lr = 0.00533906 +I0410 13:53:10.185015 18414 solver.cpp:218] Iteration 3180 (2.43964 iter/s, 4.91876s/12 iters), loss = 3.37539 +I0410 13:53:10.185072 18414 solver.cpp:237] Train net output #0: loss = 3.37539 (* 1 = 3.37539 loss) +I0410 13:53:10.185086 18414 sgd_solver.cpp:105] Iteration 3180, lr = 0.00532638 +I0410 13:53:15.113373 18414 solver.cpp:218] Iteration 3192 (2.43499 iter/s, 4.92816s/12 iters), loss = 3.44837 +I0410 13:53:15.113431 18414 solver.cpp:237] Train net output #0: loss = 3.44837 (* 1 = 3.44837 loss) +I0410 13:53:15.113446 18414 sgd_solver.cpp:105] Iteration 3192, lr = 0.00531374 +I0410 13:53:20.022343 18414 solver.cpp:218] Iteration 3204 (2.4446 iter/s, 4.90878s/12 iters), loss = 3.67105 +I0410 13:53:20.022505 18414 solver.cpp:237] Train net output #0: loss = 3.67105 (* 1 = 3.67105 loss) +I0410 13:53:20.022518 18414 sgd_solver.cpp:105] Iteration 3204, lr = 0.00530112 +I0410 13:53:24.906257 18414 solver.cpp:218] Iteration 3216 (2.45719 iter/s, 4.88362s/12 iters), loss = 3.55829 +I0410 13:53:24.906312 18414 solver.cpp:237] Train net output #0: loss = 3.55829 (* 1 = 3.55829 loss) +I0410 13:53:24.906324 18414 sgd_solver.cpp:105] Iteration 3216, lr = 0.00528853 +I0410 13:53:29.871451 18414 solver.cpp:218] Iteration 3228 (2.41692 iter/s, 4.965s/12 iters), loss = 3.40999 +I0410 13:53:29.871505 18414 solver.cpp:237] Train net output #0: loss = 3.40999 (* 1 = 3.40999 loss) +I0410 13:53:29.871518 18414 sgd_solver.cpp:105] Iteration 3228, lr = 0.00527598 +I0410 13:53:33.086696 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:34.783105 18414 solver.cpp:218] Iteration 3240 (2.44326 iter/s, 4.91147s/12 iters), loss = 3.70686 +I0410 13:53:34.783149 18414 solver.cpp:237] Train net output #0: loss = 3.70686 (* 1 = 3.70686 loss) +I0410 13:53:34.783159 18414 sgd_solver.cpp:105] Iteration 3240, lr = 0.00526345 +I0410 13:53:39.706470 18414 solver.cpp:218] Iteration 3252 (2.43745 iter/s, 4.92318s/12 iters), loss = 3.43318 +I0410 13:53:39.706524 18414 solver.cpp:237] Train net output #0: loss = 3.43318 (* 1 = 3.43318 loss) +I0410 13:53:39.706535 18414 sgd_solver.cpp:105] Iteration 3252, lr = 0.00525095 +I0410 13:53:44.154359 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3264.caffemodel +I0410 13:53:44.475097 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3264.solverstate +I0410 13:53:44.899706 18414 solver.cpp:330] Iteration 3264, Testing net (#0) +I0410 13:53:44.899739 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:53:47.982921 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:49.280207 18414 solver.cpp:397] Test net output #0: accuracy = 0.20098 +I0410 13:53:49.280249 18414 solver.cpp:397] Test net output #1: loss = 3.23878 (* 1 = 3.23878 loss) +I0410 13:53:49.363109 18414 solver.cpp:218] Iteration 3264 (1.24271 iter/s, 9.65633s/12 iters), loss = 3.41443 +I0410 13:53:49.363159 18414 solver.cpp:237] Train net output #0: loss = 3.41443 (* 1 = 3.41443 loss) +I0410 13:53:49.363171 18414 sgd_solver.cpp:105] Iteration 3264, lr = 0.00523849 +I0410 13:53:53.587370 18414 solver.cpp:218] Iteration 3276 (2.84085 iter/s, 4.22409s/12 iters), loss = 3.29945 +I0410 13:53:53.587460 18414 solver.cpp:237] Train net output #0: loss = 3.29945 (* 1 = 3.29945 loss) +I0410 13:53:53.587473 18414 sgd_solver.cpp:105] Iteration 3276, lr = 0.00522605 +I0410 13:53:58.598001 18414 solver.cpp:218] Iteration 3288 (2.39502 iter/s, 5.01041s/12 iters), loss = 3.46563 +I0410 13:53:58.598063 18414 solver.cpp:237] Train net output #0: loss = 3.46563 (* 1 = 3.46563 loss) +I0410 13:53:58.598076 18414 sgd_solver.cpp:105] Iteration 3288, lr = 0.00521364 +I0410 13:54:03.555496 18414 solver.cpp:218] Iteration 3300 (2.42067 iter/s, 4.95731s/12 iters), loss = 3.60111 +I0410 13:54:03.555555 18414 solver.cpp:237] Train net output #0: loss = 3.60111 (* 1 = 3.60111 loss) +I0410 13:54:03.555568 18414 sgd_solver.cpp:105] Iteration 3300, lr = 0.00520126 +I0410 13:54:08.515661 18414 solver.cpp:218] Iteration 3312 (2.41937 iter/s, 4.95997s/12 iters), loss = 3.40017 +I0410 13:54:08.515707 18414 solver.cpp:237] Train net output #0: loss = 3.40017 (* 1 = 3.40017 loss) +I0410 13:54:08.515718 18414 sgd_solver.cpp:105] Iteration 3312, lr = 0.00518892 +I0410 13:54:13.529778 18414 solver.cpp:218] Iteration 3324 (2.39333 iter/s, 5.01393s/12 iters), loss = 3.21156 +I0410 13:54:13.529829 18414 solver.cpp:237] Train net output #0: loss = 3.21156 (* 1 = 3.21156 loss) +I0410 13:54:13.529840 18414 sgd_solver.cpp:105] Iteration 3324, lr = 0.0051766 +I0410 13:54:18.490012 18414 solver.cpp:218] Iteration 3336 (2.41933 iter/s, 4.96004s/12 iters), loss = 3.28743 +I0410 13:54:18.490065 18414 solver.cpp:237] Train net output #0: loss = 3.28743 (* 1 = 3.28743 loss) +I0410 13:54:18.490080 18414 sgd_solver.cpp:105] Iteration 3336, lr = 0.00516431 +I0410 13:54:19.000916 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:54:23.835016 18414 solver.cpp:218] Iteration 3348 (2.24517 iter/s, 5.3448s/12 iters), loss = 3.04482 +I0410 13:54:23.835178 18414 solver.cpp:237] Train net output #0: loss = 3.04482 (* 1 = 3.04482 loss) +I0410 13:54:23.835193 18414 sgd_solver.cpp:105] Iteration 3348, lr = 0.00515204 +I0410 13:54:28.814024 18414 solver.cpp:218] Iteration 3360 (2.41026 iter/s, 4.97871s/12 iters), loss = 3.2114 +I0410 13:54:28.814071 18414 solver.cpp:237] Train net output #0: loss = 3.2114 (* 1 = 3.2114 loss) +I0410 13:54:28.814080 18414 sgd_solver.cpp:105] Iteration 3360, lr = 0.00513981 +I0410 13:54:30.819401 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3366.caffemodel +I0410 13:54:31.098374 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3366.solverstate +I0410 13:54:31.292048 18414 solver.cpp:330] Iteration 3366, Testing net (#0) +I0410 13:54:31.292069 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:54:34.370232 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:54:35.701139 18414 solver.cpp:397] Test net output #0: accuracy = 0.220588 +I0410 13:54:35.701190 18414 solver.cpp:397] Test net output #1: loss = 3.13798 (* 1 = 3.13798 loss) +I0410 13:54:37.602406 18414 solver.cpp:218] Iteration 3372 (1.36548 iter/s, 8.7881s/12 iters), loss = 3.17512 +I0410 13:54:37.602452 18414 solver.cpp:237] Train net output #0: loss = 3.17512 (* 1 = 3.17512 loss) +I0410 13:54:37.602460 18414 sgd_solver.cpp:105] Iteration 3372, lr = 0.00512761 +I0410 13:54:42.732477 18414 solver.cpp:218] Iteration 3384 (2.33924 iter/s, 5.12987s/12 iters), loss = 3.08541 +I0410 13:54:42.732532 18414 solver.cpp:237] Train net output #0: loss = 3.08541 (* 1 = 3.08541 loss) +I0410 13:54:42.732542 18414 sgd_solver.cpp:105] Iteration 3384, lr = 0.00511544 +I0410 13:54:47.719519 18414 solver.cpp:218] Iteration 3396 (2.40633 iter/s, 4.98684s/12 iters), loss = 3.36047 +I0410 13:54:47.719578 18414 solver.cpp:237] Train net output #0: loss = 3.36047 (* 1 = 3.36047 loss) +I0410 13:54:47.719590 18414 sgd_solver.cpp:105] Iteration 3396, lr = 0.00510329 +I0410 13:54:52.788141 18414 solver.cpp:218] Iteration 3408 (2.3676 iter/s, 5.06842s/12 iters), loss = 3.32197 +I0410 13:54:52.788187 18414 solver.cpp:237] Train net output #0: loss = 3.32197 (* 1 = 3.32197 loss) +I0410 13:54:52.788197 18414 sgd_solver.cpp:105] Iteration 3408, lr = 0.00509117 +I0410 13:54:57.708122 18414 solver.cpp:218] Iteration 3420 (2.43913 iter/s, 4.91979s/12 iters), loss = 3.03265 +I0410 13:54:57.708232 18414 solver.cpp:237] Train net output #0: loss = 3.03265 (* 1 = 3.03265 loss) +I0410 13:54:57.708246 18414 sgd_solver.cpp:105] Iteration 3420, lr = 0.00507909 +I0410 13:55:02.617564 18414 solver.cpp:218] Iteration 3432 (2.44439 iter/s, 4.90919s/12 iters), loss = 3.3957 +I0410 13:55:02.617616 18414 solver.cpp:237] Train net output #0: loss = 3.3957 (* 1 = 3.3957 loss) +I0410 13:55:02.617630 18414 sgd_solver.cpp:105] Iteration 3432, lr = 0.00506703 +I0410 13:55:05.189458 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:55:07.544013 18414 solver.cpp:218] Iteration 3444 (2.43593 iter/s, 4.92625s/12 iters), loss = 2.92423 +I0410 13:55:07.544067 18414 solver.cpp:237] Train net output #0: loss = 2.92423 (* 1 = 2.92423 loss) +I0410 13:55:07.544081 18414 sgd_solver.cpp:105] Iteration 3444, lr = 0.005055 +I0410 13:55:12.448598 18414 solver.cpp:218] Iteration 3456 (2.44679 iter/s, 4.90439s/12 iters), loss = 2.98268 +I0410 13:55:12.448649 18414 solver.cpp:237] Train net output #0: loss = 2.98268 (* 1 = 2.98268 loss) +I0410 13:55:12.448662 18414 sgd_solver.cpp:105] Iteration 3456, lr = 0.005043 +I0410 13:55:16.908411 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3468.caffemodel +I0410 13:55:17.215858 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3468.solverstate +I0410 13:55:17.428023 18414 solver.cpp:330] Iteration 3468, Testing net (#0) +I0410 13:55:17.428057 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:55:17.450659 18414 blocking_queue.cpp:49] Waiting for data +I0410 13:55:20.530405 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:55:21.943506 18414 solver.cpp:397] Test net output #0: accuracy = 0.210172 +I0410 13:55:21.943557 18414 solver.cpp:397] Test net output #1: loss = 3.10701 (* 1 = 3.10701 loss) +I0410 13:55:22.025673 18414 solver.cpp:218] Iteration 3468 (1.25303 iter/s, 9.57676s/12 iters), loss = 3.0695 +I0410 13:55:22.025727 18414 solver.cpp:237] Train net output #0: loss = 3.0695 (* 1 = 3.0695 loss) +I0410 13:55:22.025740 18414 sgd_solver.cpp:105] Iteration 3468, lr = 0.00503102 +I0410 13:55:26.315555 18414 solver.cpp:218] Iteration 3480 (2.7974 iter/s, 4.2897s/12 iters), loss = 3.27457 +I0410 13:55:26.315606 18414 solver.cpp:237] Train net output #0: loss = 3.27457 (* 1 = 3.27457 loss) +I0410 13:55:26.315618 18414 sgd_solver.cpp:105] Iteration 3480, lr = 0.00501908 +I0410 13:55:31.414228 18414 solver.cpp:218] Iteration 3492 (2.35364 iter/s, 5.09848s/12 iters), loss = 3.32446 +I0410 13:55:31.414352 18414 solver.cpp:237] Train net output #0: loss = 3.32446 (* 1 = 3.32446 loss) +I0410 13:55:31.414362 18414 sgd_solver.cpp:105] Iteration 3492, lr = 0.00500716 +I0410 13:55:36.376430 18414 solver.cpp:218] Iteration 3504 (2.41841 iter/s, 4.96194s/12 iters), loss = 3.05821 +I0410 13:55:36.376472 18414 solver.cpp:237] Train net output #0: loss = 3.05821 (* 1 = 3.05821 loss) +I0410 13:55:36.376482 18414 sgd_solver.cpp:105] Iteration 3504, lr = 0.00499527 +I0410 13:55:41.322083 18414 solver.cpp:218] Iteration 3516 (2.42647 iter/s, 4.94546s/12 iters), loss = 2.98277 +I0410 13:55:41.322144 18414 solver.cpp:237] Train net output #0: loss = 2.98277 (* 1 = 2.98277 loss) +I0410 13:55:41.322155 18414 sgd_solver.cpp:105] Iteration 3516, lr = 0.00498341 +I0410 13:55:46.300992 18414 solver.cpp:218] Iteration 3528 (2.41027 iter/s, 4.9787s/12 iters), loss = 3.16743 +I0410 13:55:46.301049 18414 solver.cpp:237] Train net output #0: loss = 3.16743 (* 1 = 3.16743 loss) +I0410 13:55:46.301064 18414 sgd_solver.cpp:105] Iteration 3528, lr = 0.00497158 +I0410 13:55:50.967958 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:55:51.234496 18414 solver.cpp:218] Iteration 3540 (2.43245 iter/s, 4.9333s/12 iters), loss = 2.97683 +I0410 13:55:51.234549 18414 solver.cpp:237] Train net output #0: loss = 2.97683 (* 1 = 2.97683 loss) +I0410 13:55:51.234561 18414 sgd_solver.cpp:105] Iteration 3540, lr = 0.00495978 +I0410 13:55:56.257071 18414 solver.cpp:218] Iteration 3552 (2.38931 iter/s, 5.02238s/12 iters), loss = 3.00463 +I0410 13:55:56.257115 18414 solver.cpp:237] Train net output #0: loss = 3.00463 (* 1 = 3.00463 loss) +I0410 13:55:56.257126 18414 sgd_solver.cpp:105] Iteration 3552, lr = 0.004948 +I0410 13:56:01.165144 18414 solver.cpp:218] Iteration 3564 (2.44504 iter/s, 4.90789s/12 iters), loss = 2.86452 +I0410 13:56:01.165189 18414 solver.cpp:237] Train net output #0: loss = 2.86452 (* 1 = 2.86452 loss) +I0410 13:56:01.165197 18414 sgd_solver.cpp:105] Iteration 3564, lr = 0.00493626 +I0410 13:56:03.212183 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3570.caffemodel +I0410 13:56:03.513849 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3570.solverstate +I0410 13:56:03.711982 18414 solver.cpp:330] Iteration 3570, Testing net (#0) +I0410 13:56:03.712011 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:56:06.879987 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:08.442607 18414 solver.cpp:397] Test net output #0: accuracy = 0.217525 +I0410 13:56:08.442652 18414 solver.cpp:397] Test net output #1: loss = 3.01251 (* 1 = 3.01251 loss) +I0410 13:56:10.326153 18414 solver.cpp:218] Iteration 3576 (1.30994 iter/s, 9.16071s/12 iters), loss = 3.16498 +I0410 13:56:10.326206 18414 solver.cpp:237] Train net output #0: loss = 3.16498 (* 1 = 3.16498 loss) +I0410 13:56:10.326215 18414 sgd_solver.cpp:105] Iteration 3576, lr = 0.00492454 +I0410 13:56:15.275367 18414 solver.cpp:218] Iteration 3588 (2.42473 iter/s, 4.94901s/12 iters), loss = 2.93402 +I0410 13:56:15.275424 18414 solver.cpp:237] Train net output #0: loss = 2.93402 (* 1 = 2.93402 loss) +I0410 13:56:15.275439 18414 sgd_solver.cpp:105] Iteration 3588, lr = 0.00491284 +I0410 13:56:20.207276 18414 solver.cpp:218] Iteration 3600 (2.43323 iter/s, 4.93171s/12 iters), loss = 3.03669 +I0410 13:56:20.207334 18414 solver.cpp:237] Train net output #0: loss = 3.03669 (* 1 = 3.03669 loss) +I0410 13:56:20.207348 18414 sgd_solver.cpp:105] Iteration 3600, lr = 0.00490118 +I0410 13:56:25.160887 18414 solver.cpp:218] Iteration 3612 (2.42257 iter/s, 4.95341s/12 iters), loss = 3.07548 +I0410 13:56:25.160933 18414 solver.cpp:237] Train net output #0: loss = 3.07548 (* 1 = 3.07548 loss) +I0410 13:56:25.160943 18414 sgd_solver.cpp:105] Iteration 3612, lr = 0.00488954 +I0410 13:56:30.068615 18414 solver.cpp:218] Iteration 3624 (2.44522 iter/s, 4.90753s/12 iters), loss = 3.20084 +I0410 13:56:30.068662 18414 solver.cpp:237] Train net output #0: loss = 3.20084 (* 1 = 3.20084 loss) +I0410 13:56:30.068671 18414 sgd_solver.cpp:105] Iteration 3624, lr = 0.00487793 +I0410 13:56:34.967572 18414 solver.cpp:218] Iteration 3636 (2.4496 iter/s, 4.89877s/12 iters), loss = 3.22739 +I0410 13:56:34.967679 18414 solver.cpp:237] Train net output #0: loss = 3.22739 (* 1 = 3.22739 loss) +I0410 13:56:34.967689 18414 sgd_solver.cpp:105] Iteration 3636, lr = 0.00486635 +I0410 13:56:36.822014 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:39.894299 18414 solver.cpp:218] Iteration 3648 (2.43582 iter/s, 4.92648s/12 iters), loss = 3.01096 +I0410 13:56:39.894345 18414 solver.cpp:237] Train net output #0: loss = 3.01096 (* 1 = 3.01096 loss) +I0410 13:56:39.894354 18414 sgd_solver.cpp:105] Iteration 3648, lr = 0.0048548 +I0410 13:56:44.830453 18414 solver.cpp:218] Iteration 3660 (2.43114 iter/s, 4.93596s/12 iters), loss = 2.79562 +I0410 13:56:44.830497 18414 solver.cpp:237] Train net output #0: loss = 2.79562 (* 1 = 2.79562 loss) +I0410 13:56:44.830505 18414 sgd_solver.cpp:105] Iteration 3660, lr = 0.00484327 +I0410 13:56:49.248656 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3672.caffemodel +I0410 13:56:49.891188 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3672.solverstate +I0410 13:56:50.175750 18414 solver.cpp:330] Iteration 3672, Testing net (#0) +I0410 13:56:50.175781 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:56:53.095834 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:54.552925 18414 solver.cpp:397] Test net output #0: accuracy = 0.26348 +I0410 13:56:54.552956 18414 solver.cpp:397] Test net output #1: loss = 2.85146 (* 1 = 2.85146 loss) +I0410 13:56:54.635833 18414 solver.cpp:218] Iteration 3672 (1.22386 iter/s, 9.80506s/12 iters), loss = 2.91754 +I0410 13:56:54.635874 18414 solver.cpp:237] Train net output #0: loss = 2.91754 (* 1 = 2.91754 loss) +I0410 13:56:54.635882 18414 sgd_solver.cpp:105] Iteration 3672, lr = 0.00483177 +I0410 13:56:58.704449 18414 solver.cpp:218] Iteration 3684 (2.94953 iter/s, 4.06845s/12 iters), loss = 3.03404 +I0410 13:56:58.704507 18414 solver.cpp:237] Train net output #0: loss = 3.03404 (* 1 = 3.03404 loss) +I0410 13:56:58.704520 18414 sgd_solver.cpp:105] Iteration 3684, lr = 0.0048203 +I0410 13:57:03.900980 18414 solver.cpp:218] Iteration 3696 (2.30933 iter/s, 5.19632s/12 iters), loss = 2.84856 +I0410 13:57:03.901048 18414 solver.cpp:237] Train net output #0: loss = 2.84856 (* 1 = 2.84856 loss) +I0410 13:57:03.901062 18414 sgd_solver.cpp:105] Iteration 3696, lr = 0.00480886 +I0410 13:57:08.770165 18414 solver.cpp:218] Iteration 3708 (2.46458 iter/s, 4.86898s/12 iters), loss = 3.04494 +I0410 13:57:08.770310 18414 solver.cpp:237] Train net output #0: loss = 3.04494 (* 1 = 3.04494 loss) +I0410 13:57:08.770320 18414 sgd_solver.cpp:105] Iteration 3708, lr = 0.00479744 +I0410 13:57:13.795089 18414 solver.cpp:218] Iteration 3720 (2.38824 iter/s, 5.02463s/12 iters), loss = 2.99097 +I0410 13:57:13.795131 18414 solver.cpp:237] Train net output #0: loss = 2.99097 (* 1 = 2.99097 loss) +I0410 13:57:13.795141 18414 sgd_solver.cpp:105] Iteration 3720, lr = 0.00478605 +I0410 13:57:18.770179 18414 solver.cpp:218] Iteration 3732 (2.41211 iter/s, 4.9749s/12 iters), loss = 2.94415 +I0410 13:57:18.770220 18414 solver.cpp:237] Train net output #0: loss = 2.94415 (* 1 = 2.94415 loss) +I0410 13:57:18.770228 18414 sgd_solver.cpp:105] Iteration 3732, lr = 0.00477469 +I0410 13:57:22.732805 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:23.735224 18414 solver.cpp:218] Iteration 3744 (2.41699 iter/s, 4.96485s/12 iters), loss = 2.93997 +I0410 13:57:23.735281 18414 solver.cpp:237] Train net output #0: loss = 2.93997 (* 1 = 2.93997 loss) +I0410 13:57:23.735293 18414 sgd_solver.cpp:105] Iteration 3744, lr = 0.00476335 +I0410 13:57:28.650617 18414 solver.cpp:218] Iteration 3756 (2.44141 iter/s, 4.91519s/12 iters), loss = 3.03087 +I0410 13:57:28.650667 18414 solver.cpp:237] Train net output #0: loss = 3.03087 (* 1 = 3.03087 loss) +I0410 13:57:28.650679 18414 sgd_solver.cpp:105] Iteration 3756, lr = 0.00475204 +I0410 13:57:33.538763 18414 solver.cpp:218] Iteration 3768 (2.45502 iter/s, 4.88795s/12 iters), loss = 2.94635 +I0410 13:57:33.538806 18414 solver.cpp:237] Train net output #0: loss = 2.94635 (* 1 = 2.94635 loss) +I0410 13:57:33.538816 18414 sgd_solver.cpp:105] Iteration 3768, lr = 0.00474076 +I0410 13:57:35.540868 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3774.caffemodel +I0410 13:57:35.880388 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3774.solverstate +I0410 13:57:36.092072 18414 solver.cpp:330] Iteration 3774, Testing net (#0) +I0410 13:57:36.092103 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:57:38.973953 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:40.477241 18414 solver.cpp:397] Test net output #0: accuracy = 0.265319 +I0410 13:57:40.477290 18414 solver.cpp:397] Test net output #1: loss = 2.78307 (* 1 = 2.78307 loss) +I0410 13:57:42.341066 18414 solver.cpp:218] Iteration 3780 (1.36333 iter/s, 8.802s/12 iters), loss = 2.95994 +I0410 13:57:42.341121 18414 solver.cpp:237] Train net output #0: loss = 2.95994 (* 1 = 2.95994 loss) +I0410 13:57:42.341133 18414 sgd_solver.cpp:105] Iteration 3780, lr = 0.00472951 +I0410 13:57:47.283696 18414 solver.cpp:218] Iteration 3792 (2.42795 iter/s, 4.94243s/12 iters), loss = 2.77478 +I0410 13:57:47.283743 18414 solver.cpp:237] Train net output #0: loss = 2.77478 (* 1 = 2.77478 loss) +I0410 13:57:47.283756 18414 sgd_solver.cpp:105] Iteration 3792, lr = 0.00471828 +I0410 13:57:52.229271 18414 solver.cpp:218] Iteration 3804 (2.42651 iter/s, 4.94538s/12 iters), loss = 2.90176 +I0410 13:57:52.229317 18414 solver.cpp:237] Train net output #0: loss = 2.90176 (* 1 = 2.90176 loss) +I0410 13:57:52.229329 18414 sgd_solver.cpp:105] Iteration 3804, lr = 0.00470707 +I0410 13:57:57.294710 18414 solver.cpp:218] Iteration 3816 (2.36909 iter/s, 5.06524s/12 iters), loss = 2.85068 +I0410 13:57:57.294770 18414 solver.cpp:237] Train net output #0: loss = 2.85068 (* 1 = 2.85068 loss) +I0410 13:57:57.294781 18414 sgd_solver.cpp:105] Iteration 3816, lr = 0.0046959 +I0410 13:58:02.221580 18414 solver.cpp:218] Iteration 3828 (2.43573 iter/s, 4.92666s/12 iters), loss = 3.07162 +I0410 13:58:02.221632 18414 solver.cpp:237] Train net output #0: loss = 3.07162 (* 1 = 3.07162 loss) +I0410 13:58:02.221643 18414 sgd_solver.cpp:105] Iteration 3828, lr = 0.00468475 +I0410 13:58:07.127607 18414 solver.cpp:218] Iteration 3840 (2.44607 iter/s, 4.90583s/12 iters), loss = 2.9526 +I0410 13:58:07.127661 18414 solver.cpp:237] Train net output #0: loss = 2.9526 (* 1 = 2.9526 loss) +I0410 13:58:07.127673 18414 sgd_solver.cpp:105] Iteration 3840, lr = 0.00467363 +I0410 13:58:08.269623 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:58:12.080744 18414 solver.cpp:218] Iteration 3852 (2.42281 iter/s, 4.95293s/12 iters), loss = 2.69912 +I0410 13:58:12.080926 18414 solver.cpp:237] Train net output #0: loss = 2.69912 (* 1 = 2.69912 loss) +I0410 13:58:12.080948 18414 sgd_solver.cpp:105] Iteration 3852, lr = 0.00466253 +I0410 13:58:16.985276 18414 solver.cpp:218] Iteration 3864 (2.44687 iter/s, 4.90422s/12 iters), loss = 2.95602 +I0410 13:58:16.985321 18414 solver.cpp:237] Train net output #0: loss = 2.95602 (* 1 = 2.95602 loss) +I0410 13:58:16.985330 18414 sgd_solver.cpp:105] Iteration 3864, lr = 0.00465146 +I0410 13:58:21.461838 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3876.caffemodel +I0410 13:58:21.771426 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3876.solverstate +I0410 13:58:21.982115 18414 solver.cpp:330] Iteration 3876, Testing net (#0) +I0410 13:58:21.982139 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:58:24.906162 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:58:26.492285 18414 solver.cpp:397] Test net output #0: accuracy = 0.261642 +I0410 13:58:26.492331 18414 solver.cpp:397] Test net output #1: loss = 2.8455 (* 1 = 2.8455 loss) +I0410 13:58:26.574719 18414 solver.cpp:218] Iteration 3876 (1.25142 iter/s, 9.58912s/12 iters), loss = 2.81109 +I0410 13:58:26.574776 18414 solver.cpp:237] Train net output #0: loss = 2.81109 (* 1 = 2.81109 loss) +I0410 13:58:26.574787 18414 sgd_solver.cpp:105] Iteration 3876, lr = 0.00464042 +I0410 13:58:30.712575 18414 solver.cpp:218] Iteration 3888 (2.90018 iter/s, 4.13767s/12 iters), loss = 2.6814 +I0410 13:58:30.712620 18414 solver.cpp:237] Train net output #0: loss = 2.6814 (* 1 = 2.6814 loss) +I0410 13:58:30.712630 18414 sgd_solver.cpp:105] Iteration 3888, lr = 0.0046294 +I0410 13:58:35.570740 18414 solver.cpp:218] Iteration 3900 (2.47017 iter/s, 4.85797s/12 iters), loss = 2.67094 +I0410 13:58:35.570789 18414 solver.cpp:237] Train net output #0: loss = 2.67094 (* 1 = 2.67094 loss) +I0410 13:58:35.570801 18414 sgd_solver.cpp:105] Iteration 3900, lr = 0.00461841 +I0410 13:58:40.521500 18414 solver.cpp:218] Iteration 3912 (2.42397 iter/s, 4.95056s/12 iters), loss = 2.93082 +I0410 13:58:40.521556 18414 solver.cpp:237] Train net output #0: loss = 2.93082 (* 1 = 2.93082 loss) +I0410 13:58:40.521569 18414 sgd_solver.cpp:105] Iteration 3912, lr = 0.00460744 +I0410 13:58:45.613479 18414 solver.cpp:218] Iteration 3924 (2.35674 iter/s, 5.09177s/12 iters), loss = 2.93666 +I0410 13:58:45.613598 18414 solver.cpp:237] Train net output #0: loss = 2.93666 (* 1 = 2.93666 loss) +I0410 13:58:45.613615 18414 sgd_solver.cpp:105] Iteration 3924, lr = 0.0045965 +I0410 13:58:50.543184 18414 solver.cpp:218] Iteration 3936 (2.43436 iter/s, 4.92944s/12 iters), loss = 2.54878 +I0410 13:58:50.543242 18414 solver.cpp:237] Train net output #0: loss = 2.54878 (* 1 = 2.54878 loss) +I0410 13:58:50.543256 18414 sgd_solver.cpp:105] Iteration 3936, lr = 0.00458559 +I0410 13:58:53.886200 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:58:55.478505 18414 solver.cpp:218] Iteration 3948 (2.43155 iter/s, 4.93512s/12 iters), loss = 2.63647 +I0410 13:58:55.478552 18414 solver.cpp:237] Train net output #0: loss = 2.63647 (* 1 = 2.63647 loss) +I0410 13:58:55.478562 18414 sgd_solver.cpp:105] Iteration 3948, lr = 0.0045747 +I0410 13:59:00.376485 18414 solver.cpp:218] Iteration 3960 (2.45009 iter/s, 4.89778s/12 iters), loss = 2.62746 +I0410 13:59:00.376546 18414 solver.cpp:237] Train net output #0: loss = 2.62746 (* 1 = 2.62746 loss) +I0410 13:59:00.376560 18414 sgd_solver.cpp:105] Iteration 3960, lr = 0.00456384 +I0410 13:59:05.298736 18414 solver.cpp:218] Iteration 3972 (2.43801 iter/s, 4.92204s/12 iters), loss = 2.89322 +I0410 13:59:05.298790 18414 solver.cpp:237] Train net output #0: loss = 2.89322 (* 1 = 2.89322 loss) +I0410 13:59:05.298801 18414 sgd_solver.cpp:105] Iteration 3972, lr = 0.00455301 +I0410 13:59:07.284513 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3978.caffemodel +I0410 13:59:08.108355 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3978.solverstate +I0410 13:59:08.343611 18414 solver.cpp:330] Iteration 3978, Testing net (#0) +I0410 13:59:08.343637 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:59:11.151216 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:12.728888 18414 solver.cpp:397] Test net output #0: accuracy = 0.287377 +I0410 13:59:12.728935 18414 solver.cpp:397] Test net output #1: loss = 2.70535 (* 1 = 2.70535 loss) +I0410 13:59:14.525759 18414 solver.cpp:218] Iteration 3984 (1.30057 iter/s, 9.2267s/12 iters), loss = 2.92262 +I0410 13:59:14.525804 18414 solver.cpp:237] Train net output #0: loss = 2.92262 (* 1 = 2.92262 loss) +I0410 13:59:14.525812 18414 sgd_solver.cpp:105] Iteration 3984, lr = 0.0045422 +I0410 13:59:19.572402 18414 solver.cpp:218] Iteration 3996 (2.37791 iter/s, 5.04644s/12 iters), loss = 2.58188 +I0410 13:59:19.572527 18414 solver.cpp:237] Train net output #0: loss = 2.58188 (* 1 = 2.58188 loss) +I0410 13:59:19.572543 18414 sgd_solver.cpp:105] Iteration 3996, lr = 0.00453141 +I0410 13:59:24.598122 18414 solver.cpp:218] Iteration 4008 (2.38785 iter/s, 5.02544s/12 iters), loss = 2.74006 +I0410 13:59:24.598186 18414 solver.cpp:237] Train net output #0: loss = 2.74006 (* 1 = 2.74006 loss) +I0410 13:59:24.598197 18414 sgd_solver.cpp:105] Iteration 4008, lr = 0.00452066 +I0410 13:59:29.607030 18414 solver.cpp:218] Iteration 4020 (2.39583 iter/s, 5.0087s/12 iters), loss = 2.95298 +I0410 13:59:29.607086 18414 solver.cpp:237] Train net output #0: loss = 2.95298 (* 1 = 2.95298 loss) +I0410 13:59:29.607098 18414 sgd_solver.cpp:105] Iteration 4020, lr = 0.00450992 +I0410 13:59:34.565754 18414 solver.cpp:218] Iteration 4032 (2.42008 iter/s, 4.95851s/12 iters), loss = 2.69841 +I0410 13:59:34.565809 18414 solver.cpp:237] Train net output #0: loss = 2.69841 (* 1 = 2.69841 loss) +I0410 13:59:34.565819 18414 sgd_solver.cpp:105] Iteration 4032, lr = 0.00449921 +I0410 13:59:39.496455 18414 solver.cpp:218] Iteration 4044 (2.43383 iter/s, 4.9305s/12 iters), loss = 2.78749 +I0410 13:59:39.496503 18414 solver.cpp:237] Train net output #0: loss = 2.78749 (* 1 = 2.78749 loss) +I0410 13:59:39.496513 18414 sgd_solver.cpp:105] Iteration 4044, lr = 0.00448853 +I0410 13:59:39.992655 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:44.445119 18414 solver.cpp:218] Iteration 4056 (2.425 iter/s, 4.94846s/12 iters), loss = 2.67322 +I0410 13:59:44.445171 18414 solver.cpp:237] Train net output #0: loss = 2.67322 (* 1 = 2.67322 loss) +I0410 13:59:44.445184 18414 sgd_solver.cpp:105] Iteration 4056, lr = 0.00447788 +I0410 13:59:49.350200 18414 solver.cpp:218] Iteration 4068 (2.44655 iter/s, 4.90487s/12 iters), loss = 2.66436 +I0410 13:59:49.350260 18414 solver.cpp:237] Train net output #0: loss = 2.66436 (* 1 = 2.66436 loss) +I0410 13:59:49.350273 18414 sgd_solver.cpp:105] Iteration 4068, lr = 0.00446724 +I0410 13:59:53.831138 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4080.caffemodel +I0410 13:59:54.123172 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4080.solverstate +I0410 13:59:54.324872 18414 solver.cpp:330] Iteration 4080, Testing net (#0) +I0410 13:59:54.324899 18414 net.cpp:676] Ignoring source layer train-data +I0410 13:59:57.130178 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:58.742940 18414 solver.cpp:397] Test net output #0: accuracy = 0.303309 +I0410 13:59:58.742988 18414 solver.cpp:397] Test net output #1: loss = 2.70645 (* 1 = 2.70645 loss) +I0410 13:59:58.826071 18414 solver.cpp:218] Iteration 4080 (1.26642 iter/s, 9.47553s/12 iters), loss = 2.72842 +I0410 13:59:58.826128 18414 solver.cpp:237] Train net output #0: loss = 2.72842 (* 1 = 2.72842 loss) +I0410 13:59:58.826138 18414 sgd_solver.cpp:105] Iteration 4080, lr = 0.00445664 +I0410 14:00:03.000277 18414 solver.cpp:218] Iteration 4092 (2.87493 iter/s, 4.17401s/12 iters), loss = 2.64337 +I0410 14:00:03.000336 18414 solver.cpp:237] Train net output #0: loss = 2.64337 (* 1 = 2.64337 loss) +I0410 14:00:03.000349 18414 sgd_solver.cpp:105] Iteration 4092, lr = 0.00444606 +I0410 14:00:07.951275 18414 solver.cpp:218] Iteration 4104 (2.42386 iter/s, 4.95078s/12 iters), loss = 2.91753 +I0410 14:00:07.951328 18414 solver.cpp:237] Train net output #0: loss = 2.91753 (* 1 = 2.91753 loss) +I0410 14:00:07.951340 18414 sgd_solver.cpp:105] Iteration 4104, lr = 0.0044355 +I0410 14:00:12.857589 18414 solver.cpp:218] Iteration 4116 (2.44593 iter/s, 4.90611s/12 iters), loss = 2.51763 +I0410 14:00:12.857636 18414 solver.cpp:237] Train net output #0: loss = 2.51763 (* 1 = 2.51763 loss) +I0410 14:00:12.857645 18414 sgd_solver.cpp:105] Iteration 4116, lr = 0.00442497 +I0410 14:00:17.831074 18414 solver.cpp:218] Iteration 4128 (2.41289 iter/s, 4.97328s/12 iters), loss = 2.45217 +I0410 14:00:17.831126 18414 solver.cpp:237] Train net output #0: loss = 2.45217 (* 1 = 2.45217 loss) +I0410 14:00:17.831138 18414 sgd_solver.cpp:105] Iteration 4128, lr = 0.00441447 +I0410 14:00:22.720276 18414 solver.cpp:218] Iteration 4140 (2.45449 iter/s, 4.889s/12 iters), loss = 2.788 +I0410 14:00:22.720330 18414 solver.cpp:237] Train net output #0: loss = 2.788 (* 1 = 2.788 loss) +I0410 14:00:22.720341 18414 sgd_solver.cpp:105] Iteration 4140, lr = 0.00440398 +I0410 14:00:25.333513 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:27.672665 18414 solver.cpp:218] Iteration 4152 (2.42317 iter/s, 4.95218s/12 iters), loss = 2.49024 +I0410 14:00:27.672715 18414 solver.cpp:237] Train net output #0: loss = 2.49024 (* 1 = 2.49024 loss) +I0410 14:00:27.672725 18414 sgd_solver.cpp:105] Iteration 4152, lr = 0.00439353 +I0410 14:00:27.673000 18414 blocking_queue.cpp:49] Waiting for data +I0410 14:00:32.558754 18414 solver.cpp:218] Iteration 4164 (2.45605 iter/s, 4.88589s/12 iters), loss = 2.32443 +I0410 14:00:32.558801 18414 solver.cpp:237] Train net output #0: loss = 2.32443 (* 1 = 2.32443 loss) +I0410 14:00:32.558811 18414 sgd_solver.cpp:105] Iteration 4164, lr = 0.0043831 +I0410 14:00:37.454324 18414 solver.cpp:218] Iteration 4176 (2.45129 iter/s, 4.89537s/12 iters), loss = 2.44923 +I0410 14:00:37.454375 18414 solver.cpp:237] Train net output #0: loss = 2.44923 (* 1 = 2.44923 loss) +I0410 14:00:37.454387 18414 sgd_solver.cpp:105] Iteration 4176, lr = 0.00437269 +I0410 14:00:39.494097 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4182.caffemodel +I0410 14:00:39.819110 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4182.solverstate +I0410 14:00:40.028364 18414 solver.cpp:330] Iteration 4182, Testing net (#0) +I0410 14:00:40.028388 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:00:42.903447 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:44.561077 18414 solver.cpp:397] Test net output #0: accuracy = 0.337623 +I0410 14:00:44.561138 18414 solver.cpp:397] Test net output #1: loss = 2.53815 (* 1 = 2.53815 loss) +I0410 14:00:46.490641 18414 solver.cpp:218] Iteration 4188 (1.32802 iter/s, 9.036s/12 iters), loss = 2.35225 +I0410 14:00:46.490690 18414 solver.cpp:237] Train net output #0: loss = 2.35225 (* 1 = 2.35225 loss) +I0410 14:00:46.490700 18414 sgd_solver.cpp:105] Iteration 4188, lr = 0.00436231 +I0410 14:00:51.417002 18414 solver.cpp:218] Iteration 4200 (2.43598 iter/s, 4.92616s/12 iters), loss = 2.58267 +I0410 14:00:51.417057 18414 solver.cpp:237] Train net output #0: loss = 2.58267 (* 1 = 2.58267 loss) +I0410 14:00:51.417070 18414 sgd_solver.cpp:105] Iteration 4200, lr = 0.00435195 +I0410 14:00:56.316273 18414 solver.cpp:218] Iteration 4212 (2.44945 iter/s, 4.89907s/12 iters), loss = 2.34055 +I0410 14:00:56.316447 18414 solver.cpp:237] Train net output #0: loss = 2.34055 (* 1 = 2.34055 loss) +I0410 14:00:56.316464 18414 sgd_solver.cpp:105] Iteration 4212, lr = 0.00434162 +I0410 14:01:01.307729 18414 solver.cpp:218] Iteration 4224 (2.40426 iter/s, 4.99113s/12 iters), loss = 2.617 +I0410 14:01:01.307780 18414 solver.cpp:237] Train net output #0: loss = 2.617 (* 1 = 2.617 loss) +I0410 14:01:01.307793 18414 sgd_solver.cpp:105] Iteration 4224, lr = 0.00433131 +I0410 14:01:06.290788 18414 solver.cpp:218] Iteration 4236 (2.40826 iter/s, 4.98285s/12 iters), loss = 2.48291 +I0410 14:01:06.290840 18414 solver.cpp:237] Train net output #0: loss = 2.48291 (* 1 = 2.48291 loss) +I0410 14:01:06.290853 18414 sgd_solver.cpp:105] Iteration 4236, lr = 0.00432103 +I0410 14:01:11.057847 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:01:11.288161 18414 solver.cpp:218] Iteration 4248 (2.40136 iter/s, 4.99717s/12 iters), loss = 2.83814 +I0410 14:01:11.288209 18414 solver.cpp:237] Train net output #0: loss = 2.83814 (* 1 = 2.83814 loss) +I0410 14:01:11.288219 18414 sgd_solver.cpp:105] Iteration 4248, lr = 0.00431077 +I0410 14:01:16.241717 18414 solver.cpp:218] Iteration 4260 (2.4226 iter/s, 4.95335s/12 iters), loss = 2.49977 +I0410 14:01:16.241777 18414 solver.cpp:237] Train net output #0: loss = 2.49977 (* 1 = 2.49977 loss) +I0410 14:01:16.241791 18414 sgd_solver.cpp:105] Iteration 4260, lr = 0.00430053 +I0410 14:01:21.263298 18414 solver.cpp:218] Iteration 4272 (2.38979 iter/s, 5.02137s/12 iters), loss = 2.56613 +I0410 14:01:21.263351 18414 solver.cpp:237] Train net output #0: loss = 2.56613 (* 1 = 2.56613 loss) +I0410 14:01:21.263365 18414 sgd_solver.cpp:105] Iteration 4272, lr = 0.00429032 +I0410 14:01:25.847436 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4284.caffemodel +I0410 14:01:26.170532 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4284.solverstate +I0410 14:01:26.424517 18414 solver.cpp:330] Iteration 4284, Testing net (#0) +I0410 14:01:26.424603 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:01:29.363044 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:01:31.100821 18414 solver.cpp:397] Test net output #0: accuracy = 0.348652 +I0410 14:01:31.100872 18414 solver.cpp:397] Test net output #1: loss = 2.47666 (* 1 = 2.47666 loss) +I0410 14:01:31.183770 18414 solver.cpp:218] Iteration 4284 (1.20966 iter/s, 9.92013s/12 iters), loss = 2.54673 +I0410 14:01:31.183820 18414 solver.cpp:237] Train net output #0: loss = 2.54673 (* 1 = 2.54673 loss) +I0410 14:01:31.183832 18414 sgd_solver.cpp:105] Iteration 4284, lr = 0.00428014 +I0410 14:01:35.257284 18414 solver.cpp:218] Iteration 4296 (2.94599 iter/s, 4.07333s/12 iters), loss = 2.55562 +I0410 14:01:35.257339 18414 solver.cpp:237] Train net output #0: loss = 2.55562 (* 1 = 2.55562 loss) +I0410 14:01:35.257350 18414 sgd_solver.cpp:105] Iteration 4296, lr = 0.00426998 +I0410 14:01:40.168298 18414 solver.cpp:218] Iteration 4308 (2.44359 iter/s, 4.9108s/12 iters), loss = 2.4171 +I0410 14:01:40.168354 18414 solver.cpp:237] Train net output #0: loss = 2.4171 (* 1 = 2.4171 loss) +I0410 14:01:40.168368 18414 sgd_solver.cpp:105] Iteration 4308, lr = 0.00425984 +I0410 14:01:45.034011 18414 solver.cpp:218] Iteration 4320 (2.46634 iter/s, 4.8655s/12 iters), loss = 2.72478 +I0410 14:01:45.034075 18414 solver.cpp:237] Train net output #0: loss = 2.72478 (* 1 = 2.72478 loss) +I0410 14:01:45.034088 18414 sgd_solver.cpp:105] Iteration 4320, lr = 0.00424972 +I0410 14:01:49.907608 18414 solver.cpp:218] Iteration 4332 (2.46236 iter/s, 4.87338s/12 iters), loss = 2.4895 +I0410 14:01:49.907667 18414 solver.cpp:237] Train net output #0: loss = 2.4895 (* 1 = 2.4895 loss) +I0410 14:01:49.907680 18414 sgd_solver.cpp:105] Iteration 4332, lr = 0.00423964 +I0410 14:01:54.900946 18414 solver.cpp:218] Iteration 4344 (2.4033 iter/s, 4.99313s/12 iters), loss = 2.484 +I0410 14:01:54.900981 18414 solver.cpp:237] Train net output #0: loss = 2.484 (* 1 = 2.484 loss) +I0410 14:01:54.900990 18414 sgd_solver.cpp:105] Iteration 4344, lr = 0.00422957 +I0410 14:01:56.775885 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:00.231731 18414 solver.cpp:218] Iteration 4356 (2.25116 iter/s, 5.33058s/12 iters), loss = 2.42662 +I0410 14:02:00.231779 18414 solver.cpp:237] Train net output #0: loss = 2.42662 (* 1 = 2.42662 loss) +I0410 14:02:00.231789 18414 sgd_solver.cpp:105] Iteration 4356, lr = 0.00421953 +I0410 14:02:05.266218 18414 solver.cpp:218] Iteration 4368 (2.38366 iter/s, 5.03428s/12 iters), loss = 2.57138 +I0410 14:02:05.266283 18414 solver.cpp:237] Train net output #0: loss = 2.57138 (* 1 = 2.57138 loss) +I0410 14:02:05.266297 18414 sgd_solver.cpp:105] Iteration 4368, lr = 0.00420951 +I0410 14:02:10.218008 18414 solver.cpp:218] Iteration 4380 (2.42348 iter/s, 4.95157s/12 iters), loss = 2.28366 +I0410 14:02:10.218073 18414 solver.cpp:237] Train net output #0: loss = 2.28366 (* 1 = 2.28366 loss) +I0410 14:02:10.218088 18414 sgd_solver.cpp:105] Iteration 4380, lr = 0.00419952 +I0410 14:02:12.233098 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4386.caffemodel +I0410 14:02:12.544100 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4386.solverstate +I0410 14:02:12.764894 18414 solver.cpp:330] Iteration 4386, Testing net (#0) +I0410 14:02:12.764926 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:02:15.682173 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:17.417742 18414 solver.cpp:397] Test net output #0: accuracy = 0.347426 +I0410 14:02:17.417804 18414 solver.cpp:397] Test net output #1: loss = 2.52323 (* 1 = 2.52323 loss) +I0410 14:02:19.333441 18414 solver.cpp:218] Iteration 4392 (1.3165 iter/s, 9.11508s/12 iters), loss = 2.45253 +I0410 14:02:19.333518 18414 solver.cpp:237] Train net output #0: loss = 2.45253 (* 1 = 2.45253 loss) +I0410 14:02:19.333536 18414 sgd_solver.cpp:105] Iteration 4392, lr = 0.00418954 +I0410 14:02:24.390537 18414 solver.cpp:218] Iteration 4404 (2.37301 iter/s, 5.05687s/12 iters), loss = 2.16032 +I0410 14:02:24.390578 18414 solver.cpp:237] Train net output #0: loss = 2.16032 (* 1 = 2.16032 loss) +I0410 14:02:24.390585 18414 sgd_solver.cpp:105] Iteration 4404, lr = 0.0041796 +I0410 14:02:29.276520 18414 solver.cpp:218] Iteration 4416 (2.45611 iter/s, 4.88578s/12 iters), loss = 2.45917 +I0410 14:02:29.276608 18414 solver.cpp:237] Train net output #0: loss = 2.45917 (* 1 = 2.45917 loss) +I0410 14:02:29.276619 18414 sgd_solver.cpp:105] Iteration 4416, lr = 0.00416967 +I0410 14:02:34.453112 18414 solver.cpp:218] Iteration 4428 (2.31824 iter/s, 5.17634s/12 iters), loss = 2.40949 +I0410 14:02:34.453155 18414 solver.cpp:237] Train net output #0: loss = 2.40949 (* 1 = 2.40949 loss) +I0410 14:02:34.453164 18414 sgd_solver.cpp:105] Iteration 4428, lr = 0.00415977 +I0410 14:02:39.342815 18414 solver.cpp:218] Iteration 4440 (2.45424 iter/s, 4.8895s/12 iters), loss = 2.50414 +I0410 14:02:39.342866 18414 solver.cpp:237] Train net output #0: loss = 2.50414 (* 1 = 2.50414 loss) +I0410 14:02:39.342880 18414 sgd_solver.cpp:105] Iteration 4440, lr = 0.0041499 +I0410 14:02:43.344833 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:44.286103 18414 solver.cpp:218] Iteration 4452 (2.42764 iter/s, 4.94307s/12 iters), loss = 2.30117 +I0410 14:02:44.286159 18414 solver.cpp:237] Train net output #0: loss = 2.30117 (* 1 = 2.30117 loss) +I0410 14:02:44.286170 18414 sgd_solver.cpp:105] Iteration 4452, lr = 0.00414005 +I0410 14:02:49.474768 18414 solver.cpp:218] Iteration 4464 (2.31283 iter/s, 5.18844s/12 iters), loss = 2.34118 +I0410 14:02:49.474822 18414 solver.cpp:237] Train net output #0: loss = 2.34118 (* 1 = 2.34118 loss) +I0410 14:02:49.474833 18414 sgd_solver.cpp:105] Iteration 4464, lr = 0.00413022 +I0410 14:02:54.447268 18414 solver.cpp:218] Iteration 4476 (2.41338 iter/s, 4.97229s/12 iters), loss = 2.31643 +I0410 14:02:54.447319 18414 solver.cpp:237] Train net output #0: loss = 2.31643 (* 1 = 2.31643 loss) +I0410 14:02:54.447329 18414 sgd_solver.cpp:105] Iteration 4476, lr = 0.00412041 +I0410 14:02:58.949576 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4488.caffemodel +I0410 14:02:59.263324 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4488.solverstate +I0410 14:02:59.626415 18414 solver.cpp:330] Iteration 4488, Testing net (#0) +I0410 14:02:59.626549 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:03:02.332475 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:04.142942 18414 solver.cpp:397] Test net output #0: accuracy = 0.373162 +I0410 14:03:04.142976 18414 solver.cpp:397] Test net output #1: loss = 2.39807 (* 1 = 2.39807 loss) +I0410 14:03:04.225935 18414 solver.cpp:218] Iteration 4488 (1.22721 iter/s, 9.77832s/12 iters), loss = 2.34088 +I0410 14:03:04.226014 18414 solver.cpp:237] Train net output #0: loss = 2.34088 (* 1 = 2.34088 loss) +I0410 14:03:04.226027 18414 sgd_solver.cpp:105] Iteration 4488, lr = 0.00411063 +I0410 14:03:08.375540 18414 solver.cpp:218] Iteration 4500 (2.89199 iter/s, 4.14939s/12 iters), loss = 2.3684 +I0410 14:03:08.375583 18414 solver.cpp:237] Train net output #0: loss = 2.3684 (* 1 = 2.3684 loss) +I0410 14:03:08.375592 18414 sgd_solver.cpp:105] Iteration 4500, lr = 0.00410087 +I0410 14:03:13.301244 18414 solver.cpp:218] Iteration 4512 (2.4363 iter/s, 4.9255s/12 iters), loss = 2.37274 +I0410 14:03:13.301303 18414 solver.cpp:237] Train net output #0: loss = 2.37274 (* 1 = 2.37274 loss) +I0410 14:03:13.301317 18414 sgd_solver.cpp:105] Iteration 4512, lr = 0.00409113 +I0410 14:03:18.211583 18414 solver.cpp:218] Iteration 4524 (2.44393 iter/s, 4.91012s/12 iters), loss = 2.1132 +I0410 14:03:18.211645 18414 solver.cpp:237] Train net output #0: loss = 2.1132 (* 1 = 2.1132 loss) +I0410 14:03:18.211658 18414 sgd_solver.cpp:105] Iteration 4524, lr = 0.00408142 +I0410 14:03:23.154806 18414 solver.cpp:218] Iteration 4536 (2.42767 iter/s, 4.943s/12 iters), loss = 2.23513 +I0410 14:03:23.154868 18414 solver.cpp:237] Train net output #0: loss = 2.23513 (* 1 = 2.23513 loss) +I0410 14:03:23.154881 18414 sgd_solver.cpp:105] Iteration 4536, lr = 0.00407173 +I0410 14:03:28.087304 18414 solver.cpp:218] Iteration 4548 (2.43295 iter/s, 4.93228s/12 iters), loss = 2.41148 +I0410 14:03:28.087350 18414 solver.cpp:237] Train net output #0: loss = 2.41148 (* 1 = 2.41148 loss) +I0410 14:03:28.087359 18414 sgd_solver.cpp:105] Iteration 4548, lr = 0.00406206 +I0410 14:03:29.306751 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:33.003424 18414 solver.cpp:218] Iteration 4560 (2.44105 iter/s, 4.91592s/12 iters), loss = 2.14062 +I0410 14:03:33.003527 18414 solver.cpp:237] Train net output #0: loss = 2.14062 (* 1 = 2.14062 loss) +I0410 14:03:33.003540 18414 sgd_solver.cpp:105] Iteration 4560, lr = 0.00405242 +I0410 14:03:37.927881 18414 solver.cpp:218] Iteration 4572 (2.43695 iter/s, 4.9242s/12 iters), loss = 2.30613 +I0410 14:03:37.927937 18414 solver.cpp:237] Train net output #0: loss = 2.30613 (* 1 = 2.30613 loss) +I0410 14:03:37.927951 18414 sgd_solver.cpp:105] Iteration 4572, lr = 0.0040428 +I0410 14:03:42.882622 18414 solver.cpp:218] Iteration 4584 (2.42203 iter/s, 4.95453s/12 iters), loss = 2.2986 +I0410 14:03:42.882680 18414 solver.cpp:237] Train net output #0: loss = 2.2986 (* 1 = 2.2986 loss) +I0410 14:03:42.882694 18414 sgd_solver.cpp:105] Iteration 4584, lr = 0.0040332 +I0410 14:03:44.829561 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4590.caffemodel +I0410 14:03:45.145336 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4590.solverstate +I0410 14:03:45.354544 18414 solver.cpp:330] Iteration 4590, Testing net (#0) +I0410 14:03:45.354568 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:03:47.914117 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:49.775494 18414 solver.cpp:397] Test net output #0: accuracy = 0.340074 +I0410 14:03:49.775528 18414 solver.cpp:397] Test net output #1: loss = 2.50666 (* 1 = 2.50666 loss) +I0410 14:03:51.588933 18414 solver.cpp:218] Iteration 4596 (1.37836 iter/s, 8.70599s/12 iters), loss = 2.37106 +I0410 14:03:51.588987 18414 solver.cpp:237] Train net output #0: loss = 2.37106 (* 1 = 2.37106 loss) +I0410 14:03:51.589000 18414 sgd_solver.cpp:105] Iteration 4596, lr = 0.00402362 +I0410 14:03:56.565462 18414 solver.cpp:218] Iteration 4608 (2.41142 iter/s, 4.97632s/12 iters), loss = 2.18917 +I0410 14:03:56.565517 18414 solver.cpp:237] Train net output #0: loss = 2.18917 (* 1 = 2.18917 loss) +I0410 14:03:56.565531 18414 sgd_solver.cpp:105] Iteration 4608, lr = 0.00401407 +I0410 14:04:01.507630 18414 solver.cpp:218] Iteration 4620 (2.42819 iter/s, 4.94195s/12 iters), loss = 2.21332 +I0410 14:04:01.507683 18414 solver.cpp:237] Train net output #0: loss = 2.21332 (* 1 = 2.21332 loss) +I0410 14:04:01.507696 18414 sgd_solver.cpp:105] Iteration 4620, lr = 0.00400454 +I0410 14:04:06.480552 18414 solver.cpp:218] Iteration 4632 (2.41317 iter/s, 4.97271s/12 iters), loss = 2.29576 +I0410 14:04:06.480706 18414 solver.cpp:237] Train net output #0: loss = 2.29576 (* 1 = 2.29576 loss) +I0410 14:04:06.480718 18414 sgd_solver.cpp:105] Iteration 4632, lr = 0.00399503 +I0410 14:04:11.422371 18414 solver.cpp:218] Iteration 4644 (2.42841 iter/s, 4.94151s/12 iters), loss = 2.04189 +I0410 14:04:11.422422 18414 solver.cpp:237] Train net output #0: loss = 2.04189 (* 1 = 2.04189 loss) +I0410 14:04:11.422435 18414 sgd_solver.cpp:105] Iteration 4644, lr = 0.00398555 +I0410 14:04:14.808686 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:04:16.410308 18414 solver.cpp:218] Iteration 4656 (2.40591 iter/s, 4.98772s/12 iters), loss = 2.24202 +I0410 14:04:16.410365 18414 solver.cpp:237] Train net output #0: loss = 2.24202 (* 1 = 2.24202 loss) +I0410 14:04:16.410378 18414 sgd_solver.cpp:105] Iteration 4656, lr = 0.00397608 +I0410 14:04:21.351442 18414 solver.cpp:218] Iteration 4668 (2.4287 iter/s, 4.94092s/12 iters), loss = 2.30526 +I0410 14:04:21.351501 18414 solver.cpp:237] Train net output #0: loss = 2.30526 (* 1 = 2.30526 loss) +I0410 14:04:21.351514 18414 sgd_solver.cpp:105] Iteration 4668, lr = 0.00396664 +I0410 14:04:26.247016 18414 solver.cpp:218] Iteration 4680 (2.4513 iter/s, 4.89536s/12 iters), loss = 2.43121 +I0410 14:04:26.247068 18414 solver.cpp:237] Train net output #0: loss = 2.43121 (* 1 = 2.43121 loss) +I0410 14:04:26.247079 18414 sgd_solver.cpp:105] Iteration 4680, lr = 0.00395723 +I0410 14:04:30.717337 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4692.caffemodel +I0410 14:04:31.043011 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4692.solverstate +I0410 14:04:31.252470 18414 solver.cpp:330] Iteration 4692, Testing net (#0) +I0410 14:04:31.252499 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:04:33.840610 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:04:35.692467 18414 solver.cpp:397] Test net output #0: accuracy = 0.368873 +I0410 14:04:35.692517 18414 solver.cpp:397] Test net output #1: loss = 2.36165 (* 1 = 2.36165 loss) +I0410 14:04:35.775476 18414 solver.cpp:218] Iteration 4692 (1.25943 iter/s, 9.52812s/12 iters), loss = 2.21889 +I0410 14:04:35.775528 18414 solver.cpp:237] Train net output #0: loss = 2.21889 (* 1 = 2.21889 loss) +I0410 14:04:35.775540 18414 sgd_solver.cpp:105] Iteration 4692, lr = 0.00394783 +I0410 14:04:40.016005 18414 solver.cpp:218] Iteration 4704 (2.82996 iter/s, 4.24034s/12 iters), loss = 2.0089 +I0410 14:04:40.016081 18414 solver.cpp:237] Train net output #0: loss = 2.0089 (* 1 = 2.0089 loss) +I0410 14:04:40.016094 18414 sgd_solver.cpp:105] Iteration 4704, lr = 0.00393846 +I0410 14:04:44.864478 18414 solver.cpp:218] Iteration 4716 (2.47513 iter/s, 4.84824s/12 iters), loss = 2.07954 +I0410 14:04:44.864521 18414 solver.cpp:237] Train net output #0: loss = 2.07954 (* 1 = 2.07954 loss) +I0410 14:04:44.864531 18414 sgd_solver.cpp:105] Iteration 4716, lr = 0.00392911 +I0410 14:04:49.742425 18414 solver.cpp:218] Iteration 4728 (2.46015 iter/s, 4.87774s/12 iters), loss = 2.20523 +I0410 14:04:49.742483 18414 solver.cpp:237] Train net output #0: loss = 2.20523 (* 1 = 2.20523 loss) +I0410 14:04:49.742497 18414 sgd_solver.cpp:105] Iteration 4728, lr = 0.00391978 +I0410 14:04:54.893491 18414 solver.cpp:218] Iteration 4740 (2.32972 iter/s, 5.15084s/12 iters), loss = 2.09447 +I0410 14:04:54.893532 18414 solver.cpp:237] Train net output #0: loss = 2.09447 (* 1 = 2.09447 loss) +I0410 14:04:54.893540 18414 sgd_solver.cpp:105] Iteration 4740, lr = 0.00391047 +I0410 14:04:59.855967 18414 solver.cpp:218] Iteration 4752 (2.41825 iter/s, 4.96227s/12 iters), loss = 2.2461 +I0410 14:04:59.856031 18414 solver.cpp:237] Train net output #0: loss = 2.2461 (* 1 = 2.2461 loss) +I0410 14:04:59.856045 18414 sgd_solver.cpp:105] Iteration 4752, lr = 0.00390119 +I0410 14:05:00.383807 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:04.790400 18414 solver.cpp:218] Iteration 4764 (2.432 iter/s, 4.93422s/12 iters), loss = 2.21551 +I0410 14:05:04.790447 18414 solver.cpp:237] Train net output #0: loss = 2.21551 (* 1 = 2.21551 loss) +I0410 14:05:04.790458 18414 sgd_solver.cpp:105] Iteration 4764, lr = 0.00389193 +I0410 14:05:09.776535 18414 solver.cpp:218] Iteration 4776 (2.40677 iter/s, 4.98593s/12 iters), loss = 2.27317 +I0410 14:05:09.776589 18414 solver.cpp:237] Train net output #0: loss = 2.27317 (* 1 = 2.27317 loss) +I0410 14:05:09.776603 18414 sgd_solver.cpp:105] Iteration 4776, lr = 0.00388269 +I0410 14:05:14.828886 18414 solver.cpp:218] Iteration 4788 (2.37524 iter/s, 5.05213s/12 iters), loss = 2.11977 +I0410 14:05:14.829006 18414 solver.cpp:237] Train net output #0: loss = 2.11977 (* 1 = 2.11977 loss) +I0410 14:05:14.829016 18414 sgd_solver.cpp:105] Iteration 4788, lr = 0.00387347 +I0410 14:05:16.854892 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4794.caffemodel +I0410 14:05:17.165350 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4794.solverstate +I0410 14:05:17.373826 18414 solver.cpp:330] Iteration 4794, Testing net (#0) +I0410 14:05:17.373853 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:05:19.931380 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:21.831094 18414 solver.cpp:397] Test net output #0: accuracy = 0.386642 +I0410 14:05:21.831143 18414 solver.cpp:397] Test net output #1: loss = 2.32682 (* 1 = 2.32682 loss) +I0410 14:05:23.668174 18414 solver.cpp:218] Iteration 4800 (1.35764 iter/s, 8.83889s/12 iters), loss = 2.18756 +I0410 14:05:23.668231 18414 solver.cpp:237] Train net output #0: loss = 2.18756 (* 1 = 2.18756 loss) +I0410 14:05:23.668244 18414 sgd_solver.cpp:105] Iteration 4800, lr = 0.00386427 +I0410 14:05:28.702368 18414 solver.cpp:218] Iteration 4812 (2.3838 iter/s, 5.03398s/12 iters), loss = 2.40763 +I0410 14:05:28.702425 18414 solver.cpp:237] Train net output #0: loss = 2.40763 (* 1 = 2.40763 loss) +I0410 14:05:28.702436 18414 sgd_solver.cpp:105] Iteration 4812, lr = 0.0038551 +I0410 14:05:33.634449 18414 solver.cpp:218] Iteration 4824 (2.43316 iter/s, 4.93187s/12 iters), loss = 2.12281 +I0410 14:05:33.634496 18414 solver.cpp:237] Train net output #0: loss = 2.12281 (* 1 = 2.12281 loss) +I0410 14:05:33.634505 18414 sgd_solver.cpp:105] Iteration 4824, lr = 0.00384594 +I0410 14:05:38.592432 18414 solver.cpp:218] Iteration 4836 (2.42044 iter/s, 4.95777s/12 iters), loss = 1.9435 +I0410 14:05:38.592483 18414 solver.cpp:237] Train net output #0: loss = 1.9435 (* 1 = 1.9435 loss) +I0410 14:05:38.592494 18414 sgd_solver.cpp:105] Iteration 4836, lr = 0.00383681 +I0410 14:05:38.954097 18414 blocking_queue.cpp:49] Waiting for data +I0410 14:05:43.614082 18414 solver.cpp:218] Iteration 4848 (2.38975 iter/s, 5.02144s/12 iters), loss = 2.25356 +I0410 14:05:43.614130 18414 solver.cpp:237] Train net output #0: loss = 2.25356 (* 1 = 2.25356 loss) +I0410 14:05:43.614142 18414 sgd_solver.cpp:105] Iteration 4848, lr = 0.0038277 +I0410 14:05:46.271085 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:48.643687 18414 solver.cpp:218] Iteration 4860 (2.38597 iter/s, 5.02939s/12 iters), loss = 1.6811 +I0410 14:05:48.643739 18414 solver.cpp:237] Train net output #0: loss = 1.6811 (* 1 = 1.6811 loss) +I0410 14:05:48.643754 18414 sgd_solver.cpp:105] Iteration 4860, lr = 0.00381862 +I0410 14:05:53.681126 18414 solver.cpp:218] Iteration 4872 (2.38227 iter/s, 5.03722s/12 iters), loss = 1.94442 +I0410 14:05:53.681185 18414 solver.cpp:237] Train net output #0: loss = 1.94442 (* 1 = 1.94442 loss) +I0410 14:05:53.681198 18414 sgd_solver.cpp:105] Iteration 4872, lr = 0.00380955 +I0410 14:05:58.627323 18414 solver.cpp:218] Iteration 4884 (2.42622 iter/s, 4.94597s/12 iters), loss = 2.15385 +I0410 14:05:58.627379 18414 solver.cpp:237] Train net output #0: loss = 2.15385 (* 1 = 2.15385 loss) +I0410 14:05:58.627393 18414 sgd_solver.cpp:105] Iteration 4884, lr = 0.0038005 +I0410 14:06:03.070109 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4896.caffemodel +I0410 14:06:03.950569 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4896.solverstate +I0410 14:06:04.164127 18414 solver.cpp:330] Iteration 4896, Testing net (#0) +I0410 14:06:04.164157 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:06:06.675734 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:06:08.604876 18414 solver.cpp:397] Test net output #0: accuracy = 0.393382 +I0410 14:06:08.604913 18414 solver.cpp:397] Test net output #1: loss = 2.31131 (* 1 = 2.31131 loss) +I0410 14:06:08.687649 18414 solver.cpp:218] Iteration 4896 (1.19285 iter/s, 10.06s/12 iters), loss = 2.08474 +I0410 14:06:08.687695 18414 solver.cpp:237] Train net output #0: loss = 2.08474 (* 1 = 2.08474 loss) +I0410 14:06:08.687705 18414 sgd_solver.cpp:105] Iteration 4896, lr = 0.00379148 +I0410 14:06:13.148077 18414 solver.cpp:218] Iteration 4908 (2.69044 iter/s, 4.46024s/12 iters), loss = 2.12181 +I0410 14:06:13.148129 18414 solver.cpp:237] Train net output #0: loss = 2.12181 (* 1 = 2.12181 loss) +I0410 14:06:13.148142 18414 sgd_solver.cpp:105] Iteration 4908, lr = 0.00378248 +I0410 14:06:18.037402 18414 solver.cpp:218] Iteration 4920 (2.45443 iter/s, 4.88911s/12 iters), loss = 2.13644 +I0410 14:06:18.037546 18414 solver.cpp:237] Train net output #0: loss = 2.13644 (* 1 = 2.13644 loss) +I0410 14:06:18.037560 18414 sgd_solver.cpp:105] Iteration 4920, lr = 0.0037735 +I0410 14:06:22.922582 18414 solver.cpp:218] Iteration 4932 (2.45656 iter/s, 4.88488s/12 iters), loss = 2.06838 +I0410 14:06:22.922628 18414 solver.cpp:237] Train net output #0: loss = 2.06838 (* 1 = 2.06838 loss) +I0410 14:06:22.922641 18414 sgd_solver.cpp:105] Iteration 4932, lr = 0.00376454 +I0410 14:06:27.899281 18414 solver.cpp:218] Iteration 4944 (2.41134 iter/s, 4.97648s/12 iters), loss = 1.93448 +I0410 14:06:27.899340 18414 solver.cpp:237] Train net output #0: loss = 1.93448 (* 1 = 1.93448 loss) +I0410 14:06:27.899354 18414 sgd_solver.cpp:105] Iteration 4944, lr = 0.0037556 +I0410 14:06:32.616598 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:06:32.808260 18414 solver.cpp:218] Iteration 4956 (2.44461 iter/s, 4.90877s/12 iters), loss = 1.92429 +I0410 14:06:32.808305 18414 solver.cpp:237] Train net output #0: loss = 1.92429 (* 1 = 1.92429 loss) +I0410 14:06:32.808313 18414 sgd_solver.cpp:105] Iteration 4956, lr = 0.00374669 +I0410 14:06:37.707438 18414 solver.cpp:218] Iteration 4968 (2.44949 iter/s, 4.89897s/12 iters), loss = 1.81271 +I0410 14:06:37.707494 18414 solver.cpp:237] Train net output #0: loss = 1.81271 (* 1 = 1.81271 loss) +I0410 14:06:37.707509 18414 sgd_solver.cpp:105] Iteration 4968, lr = 0.00373779 +I0410 14:06:42.748921 18414 solver.cpp:218] Iteration 4980 (2.38035 iter/s, 5.04127s/12 iters), loss = 1.76764 +I0410 14:06:42.748961 18414 solver.cpp:237] Train net output #0: loss = 1.76764 (* 1 = 1.76764 loss) +I0410 14:06:42.748970 18414 sgd_solver.cpp:105] Iteration 4980, lr = 0.00372892 +I0410 14:06:48.008517 18414 solver.cpp:218] Iteration 4992 (2.28164 iter/s, 5.25938s/12 iters), loss = 1.9683 +I0410 14:06:48.008574 18414 solver.cpp:237] Train net output #0: loss = 1.9683 (* 1 = 1.9683 loss) +I0410 14:06:48.008589 18414 sgd_solver.cpp:105] Iteration 4992, lr = 0.00372006 +I0410 14:06:50.085268 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4998.caffemodel +I0410 14:06:50.388633 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4998.solverstate +I0410 14:06:50.584743 18414 solver.cpp:330] Iteration 4998, Testing net (#0) +I0410 14:06:50.584764 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:06:53.050520 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:06:55.016012 18414 solver.cpp:397] Test net output #0: accuracy = 0.398897 +I0410 14:06:55.016063 18414 solver.cpp:397] Test net output #1: loss = 2.28344 (* 1 = 2.28344 loss) +I0410 14:06:56.759085 18414 solver.cpp:218] Iteration 5004 (1.37139 iter/s, 8.75024s/12 iters), loss = 1.92985 +I0410 14:06:56.759143 18414 solver.cpp:237] Train net output #0: loss = 1.92985 (* 1 = 1.92985 loss) +I0410 14:06:56.759157 18414 sgd_solver.cpp:105] Iteration 5004, lr = 0.00371123 +I0410 14:07:01.805079 18414 solver.cpp:218] Iteration 5016 (2.37823 iter/s, 5.04578s/12 iters), loss = 2.03553 +I0410 14:07:01.805122 18414 solver.cpp:237] Train net output #0: loss = 2.03553 (* 1 = 2.03553 loss) +I0410 14:07:01.805130 18414 sgd_solver.cpp:105] Iteration 5016, lr = 0.00370242 +I0410 14:07:06.742432 18414 solver.cpp:218] Iteration 5028 (2.43055 iter/s, 4.93715s/12 iters), loss = 2.19006 +I0410 14:07:06.742484 18414 solver.cpp:237] Train net output #0: loss = 2.19006 (* 1 = 2.19006 loss) +I0410 14:07:06.742497 18414 sgd_solver.cpp:105] Iteration 5028, lr = 0.00369363 +I0410 14:07:11.684944 18414 solver.cpp:218] Iteration 5040 (2.42802 iter/s, 4.9423s/12 iters), loss = 2.27043 +I0410 14:07:11.684998 18414 solver.cpp:237] Train net output #0: loss = 2.27043 (* 1 = 2.27043 loss) +I0410 14:07:11.685010 18414 sgd_solver.cpp:105] Iteration 5040, lr = 0.00368486 +I0410 14:07:16.624229 18414 solver.cpp:218] Iteration 5052 (2.42961 iter/s, 4.93907s/12 iters), loss = 1.96993 +I0410 14:07:16.624276 18414 solver.cpp:237] Train net output #0: loss = 1.96993 (* 1 = 1.96993 loss) +I0410 14:07:16.624285 18414 sgd_solver.cpp:105] Iteration 5052, lr = 0.00367611 +I0410 14:07:18.520078 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:07:21.534570 18414 solver.cpp:218] Iteration 5064 (2.44393 iter/s, 4.91013s/12 iters), loss = 2.09901 +I0410 14:07:21.534687 18414 solver.cpp:237] Train net output #0: loss = 2.09901 (* 1 = 2.09901 loss) +I0410 14:07:21.534699 18414 sgd_solver.cpp:105] Iteration 5064, lr = 0.00366738 +I0410 14:07:26.448649 18414 solver.cpp:218] Iteration 5076 (2.4421 iter/s, 4.91381s/12 iters), loss = 2.31146 +I0410 14:07:26.448702 18414 solver.cpp:237] Train net output #0: loss = 2.31146 (* 1 = 2.31146 loss) +I0410 14:07:26.448714 18414 sgd_solver.cpp:105] Iteration 5076, lr = 0.00365868 +I0410 14:07:31.383373 18414 solver.cpp:218] Iteration 5088 (2.43185 iter/s, 4.93451s/12 iters), loss = 1.76715 +I0410 14:07:31.383427 18414 solver.cpp:237] Train net output #0: loss = 1.76715 (* 1 = 1.76715 loss) +I0410 14:07:31.383440 18414 sgd_solver.cpp:105] Iteration 5088, lr = 0.00364999 +I0410 14:07:35.836490 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5100.caffemodel +I0410 14:07:36.159860 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5100.solverstate +I0410 14:07:36.372545 18414 solver.cpp:330] Iteration 5100, Testing net (#0) +I0410 14:07:36.372575 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:07:38.831662 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:07:40.884613 18414 solver.cpp:397] Test net output #0: accuracy = 0.420343 +I0410 14:07:40.884665 18414 solver.cpp:397] Test net output #1: loss = 2.18801 (* 1 = 2.18801 loss) +I0410 14:07:40.967559 18414 solver.cpp:218] Iteration 5100 (1.25211 iter/s, 9.58383s/12 iters), loss = 1.89703 +I0410 14:07:40.967612 18414 solver.cpp:237] Train net output #0: loss = 1.89703 (* 1 = 1.89703 loss) +I0410 14:07:40.967625 18414 sgd_solver.cpp:105] Iteration 5100, lr = 0.00364132 +I0410 14:07:45.308614 18414 solver.cpp:218] Iteration 5112 (2.76443 iter/s, 4.34085s/12 iters), loss = 2.05624 +I0410 14:07:45.308673 18414 solver.cpp:237] Train net output #0: loss = 2.05624 (* 1 = 2.05624 loss) +I0410 14:07:45.308686 18414 sgd_solver.cpp:105] Iteration 5112, lr = 0.00363268 +I0410 14:07:50.226284 18414 solver.cpp:218] Iteration 5124 (2.44029 iter/s, 4.91745s/12 iters), loss = 2.06316 +I0410 14:07:50.226336 18414 solver.cpp:237] Train net output #0: loss = 2.06316 (* 1 = 2.06316 loss) +I0410 14:07:50.226347 18414 sgd_solver.cpp:105] Iteration 5124, lr = 0.00362405 +I0410 14:07:55.164845 18414 solver.cpp:218] Iteration 5136 (2.42996 iter/s, 4.93834s/12 iters), loss = 2.0304 +I0410 14:07:55.164999 18414 solver.cpp:237] Train net output #0: loss = 2.0304 (* 1 = 2.0304 loss) +I0410 14:07:55.165011 18414 sgd_solver.cpp:105] Iteration 5136, lr = 0.00361545 +I0410 14:08:00.091740 18414 solver.cpp:218] Iteration 5148 (2.43577 iter/s, 4.92658s/12 iters), loss = 1.86117 +I0410 14:08:00.091801 18414 solver.cpp:237] Train net output #0: loss = 1.86117 (* 1 = 1.86117 loss) +I0410 14:08:00.091815 18414 sgd_solver.cpp:105] Iteration 5148, lr = 0.00360687 +I0410 14:08:04.047418 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:04.976651 18414 solver.cpp:218] Iteration 5160 (2.45666 iter/s, 4.88469s/12 iters), loss = 1.99456 +I0410 14:08:04.976697 18414 solver.cpp:237] Train net output #0: loss = 1.99456 (* 1 = 1.99456 loss) +I0410 14:08:04.976707 18414 sgd_solver.cpp:105] Iteration 5160, lr = 0.0035983 +I0410 14:08:09.872403 18414 solver.cpp:218] Iteration 5172 (2.45121 iter/s, 4.89555s/12 iters), loss = 2.18147 +I0410 14:08:09.872447 18414 solver.cpp:237] Train net output #0: loss = 2.18147 (* 1 = 2.18147 loss) +I0410 14:08:09.872455 18414 sgd_solver.cpp:105] Iteration 5172, lr = 0.00358976 +I0410 14:08:14.810307 18414 solver.cpp:218] Iteration 5184 (2.43028 iter/s, 4.93769s/12 iters), loss = 2.01357 +I0410 14:08:14.810355 18414 solver.cpp:237] Train net output #0: loss = 2.01357 (* 1 = 2.01357 loss) +I0410 14:08:14.810365 18414 sgd_solver.cpp:105] Iteration 5184, lr = 0.00358124 +I0410 14:08:19.710100 18414 solver.cpp:218] Iteration 5196 (2.44919 iter/s, 4.89958s/12 iters), loss = 1.80509 +I0410 14:08:19.710152 18414 solver.cpp:237] Train net output #0: loss = 1.80509 (* 1 = 1.80509 loss) +I0410 14:08:19.710163 18414 sgd_solver.cpp:105] Iteration 5196, lr = 0.00357273 +I0410 14:08:21.689673 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5202.caffemodel +I0410 14:08:22.005820 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5202.solverstate +I0410 14:08:22.218195 18414 solver.cpp:330] Iteration 5202, Testing net (#0) +I0410 14:08:22.218215 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:08:24.632750 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:26.679730 18414 solver.cpp:397] Test net output #0: accuracy = 0.420343 +I0410 14:08:26.679837 18414 solver.cpp:397] Test net output #1: loss = 2.23219 (* 1 = 2.23219 loss) +I0410 14:08:28.673014 18414 solver.cpp:218] Iteration 5208 (1.3389 iter/s, 8.96258s/12 iters), loss = 1.97189 +I0410 14:08:28.673063 18414 solver.cpp:237] Train net output #0: loss = 1.97189 (* 1 = 1.97189 loss) +I0410 14:08:28.673074 18414 sgd_solver.cpp:105] Iteration 5208, lr = 0.00356425 +I0410 14:08:33.798080 18414 solver.cpp:218] Iteration 5220 (2.34153 iter/s, 5.12485s/12 iters), loss = 1.82681 +I0410 14:08:33.798132 18414 solver.cpp:237] Train net output #0: loss = 1.82681 (* 1 = 1.82681 loss) +I0410 14:08:33.798146 18414 sgd_solver.cpp:105] Iteration 5220, lr = 0.00355579 +I0410 14:08:38.718647 18414 solver.cpp:218] Iteration 5232 (2.43885 iter/s, 4.92035s/12 iters), loss = 1.98373 +I0410 14:08:38.718705 18414 solver.cpp:237] Train net output #0: loss = 1.98373 (* 1 = 1.98373 loss) +I0410 14:08:38.718719 18414 sgd_solver.cpp:105] Iteration 5232, lr = 0.00354735 +I0410 14:08:43.635874 18414 solver.cpp:218] Iteration 5244 (2.44051 iter/s, 4.91701s/12 iters), loss = 1.90931 +I0410 14:08:43.635929 18414 solver.cpp:237] Train net output #0: loss = 1.90931 (* 1 = 1.90931 loss) +I0410 14:08:43.635941 18414 sgd_solver.cpp:105] Iteration 5244, lr = 0.00353892 +I0410 14:08:48.531787 18414 solver.cpp:218] Iteration 5256 (2.45113 iter/s, 4.8957s/12 iters), loss = 2.16591 +I0410 14:08:48.531842 18414 solver.cpp:237] Train net output #0: loss = 2.16591 (* 1 = 2.16591 loss) +I0410 14:08:48.531857 18414 sgd_solver.cpp:105] Iteration 5256, lr = 0.00353052 +I0410 14:08:49.806668 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:53.442453 18414 solver.cpp:218] Iteration 5268 (2.44377 iter/s, 4.91045s/12 iters), loss = 1.91117 +I0410 14:08:53.442503 18414 solver.cpp:237] Train net output #0: loss = 1.91117 (* 1 = 1.91117 loss) +I0410 14:08:53.442513 18414 sgd_solver.cpp:105] Iteration 5268, lr = 0.00352214 +I0410 14:08:58.410555 18414 solver.cpp:218] Iteration 5280 (2.41552 iter/s, 4.96788s/12 iters), loss = 1.7906 +I0410 14:08:58.410686 18414 solver.cpp:237] Train net output #0: loss = 1.7906 (* 1 = 1.7906 loss) +I0410 14:08:58.410698 18414 sgd_solver.cpp:105] Iteration 5280, lr = 0.00351378 +I0410 14:09:03.522944 18414 solver.cpp:218] Iteration 5292 (2.34737 iter/s, 5.11209s/12 iters), loss = 2.04153 +I0410 14:09:03.522998 18414 solver.cpp:237] Train net output #0: loss = 2.04153 (* 1 = 2.04153 loss) +I0410 14:09:03.523010 18414 sgd_solver.cpp:105] Iteration 5292, lr = 0.00350544 +I0410 14:09:08.005401 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5304.caffemodel +I0410 14:09:08.341248 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5304.solverstate +I0410 14:09:08.558202 18414 solver.cpp:330] Iteration 5304, Testing net (#0) +I0410 14:09:08.558231 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:09:11.015028 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:09:13.108561 18414 solver.cpp:397] Test net output #0: accuracy = 0.42402 +I0410 14:09:13.108613 18414 solver.cpp:397] Test net output #1: loss = 2.18543 (* 1 = 2.18543 loss) +I0410 14:09:13.190917 18414 solver.cpp:218] Iteration 5304 (1.24126 iter/s, 9.66761s/12 iters), loss = 1.8809 +I0410 14:09:13.190969 18414 solver.cpp:237] Train net output #0: loss = 1.8809 (* 1 = 1.8809 loss) +I0410 14:09:13.190981 18414 sgd_solver.cpp:105] Iteration 5304, lr = 0.00349711 +I0410 14:09:17.455634 18414 solver.cpp:218] Iteration 5316 (2.81392 iter/s, 4.26451s/12 iters), loss = 1.79894 +I0410 14:09:17.455691 18414 solver.cpp:237] Train net output #0: loss = 1.79894 (* 1 = 1.79894 loss) +I0410 14:09:17.455703 18414 sgd_solver.cpp:105] Iteration 5316, lr = 0.00348881 +I0410 14:09:22.367319 18414 solver.cpp:218] Iteration 5328 (2.44326 iter/s, 4.91146s/12 iters), loss = 2.00959 +I0410 14:09:22.367365 18414 solver.cpp:237] Train net output #0: loss = 2.00959 (* 1 = 2.00959 loss) +I0410 14:09:22.367374 18414 sgd_solver.cpp:105] Iteration 5328, lr = 0.00348053 +I0410 14:09:27.293129 18414 solver.cpp:218] Iteration 5340 (2.43625 iter/s, 4.9256s/12 iters), loss = 1.89632 +I0410 14:09:27.293184 18414 solver.cpp:237] Train net output #0: loss = 1.89632 (* 1 = 1.89632 loss) +I0410 14:09:27.293196 18414 sgd_solver.cpp:105] Iteration 5340, lr = 0.00347226 +I0410 14:09:32.219147 18414 solver.cpp:218] Iteration 5352 (2.43616 iter/s, 4.92579s/12 iters), loss = 1.77822 +I0410 14:09:32.219300 18414 solver.cpp:237] Train net output #0: loss = 1.77822 (* 1 = 1.77822 loss) +I0410 14:09:32.219314 18414 sgd_solver.cpp:105] Iteration 5352, lr = 0.00346402 +I0410 14:09:35.566848 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:09:37.114965 18414 solver.cpp:218] Iteration 5364 (2.45123 iter/s, 4.89551s/12 iters), loss = 1.88802 +I0410 14:09:37.115010 18414 solver.cpp:237] Train net output #0: loss = 1.88802 (* 1 = 1.88802 loss) +I0410 14:09:37.115020 18414 sgd_solver.cpp:105] Iteration 5364, lr = 0.0034558 +I0410 14:09:42.187924 18414 solver.cpp:218] Iteration 5376 (2.36558 iter/s, 5.07274s/12 iters), loss = 1.73644 +I0410 14:09:42.187976 18414 solver.cpp:237] Train net output #0: loss = 1.73644 (* 1 = 1.73644 loss) +I0410 14:09:42.187989 18414 sgd_solver.cpp:105] Iteration 5376, lr = 0.00344759 +I0410 14:09:47.278920 18414 solver.cpp:218] Iteration 5388 (2.3572 iter/s, 5.09078s/12 iters), loss = 1.89767 +I0410 14:09:47.278978 18414 solver.cpp:237] Train net output #0: loss = 1.89767 (* 1 = 1.89767 loss) +I0410 14:09:47.278990 18414 sgd_solver.cpp:105] Iteration 5388, lr = 0.00343941 +I0410 14:09:52.189736 18414 solver.cpp:218] Iteration 5400 (2.4437 iter/s, 4.91059s/12 iters), loss = 1.90474 +I0410 14:09:52.189796 18414 solver.cpp:237] Train net output #0: loss = 1.90474 (* 1 = 1.90474 loss) +I0410 14:09:52.189807 18414 sgd_solver.cpp:105] Iteration 5400, lr = 0.00343124 +I0410 14:09:54.214978 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5406.caffemodel +I0410 14:09:54.534536 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5406.solverstate +I0410 14:09:54.745272 18414 solver.cpp:330] Iteration 5406, Testing net (#0) +I0410 14:09:54.745301 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:09:57.083885 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:09:59.210799 18414 solver.cpp:397] Test net output #0: accuracy = 0.433824 +I0410 14:09:59.210844 18414 solver.cpp:397] Test net output #1: loss = 2.15241 (* 1 = 2.15241 loss) +I0410 14:10:01.154734 18414 solver.cpp:218] Iteration 5412 (1.33859 iter/s, 8.96465s/12 iters), loss = 1.83986 +I0410 14:10:01.154778 18414 solver.cpp:237] Train net output #0: loss = 1.83986 (* 1 = 1.83986 loss) +I0410 14:10:01.154788 18414 sgd_solver.cpp:105] Iteration 5412, lr = 0.00342309 +I0410 14:10:06.288506 18414 solver.cpp:218] Iteration 5424 (2.33756 iter/s, 5.13356s/12 iters), loss = 1.77997 +I0410 14:10:06.288609 18414 solver.cpp:237] Train net output #0: loss = 1.77997 (* 1 = 1.77997 loss) +I0410 14:10:06.288619 18414 sgd_solver.cpp:105] Iteration 5424, lr = 0.00341497 +I0410 14:10:11.370276 18414 solver.cpp:218] Iteration 5436 (2.36151 iter/s, 5.0815s/12 iters), loss = 1.97646 +I0410 14:10:11.370337 18414 solver.cpp:237] Train net output #0: loss = 1.97646 (* 1 = 1.97646 loss) +I0410 14:10:11.370350 18414 sgd_solver.cpp:105] Iteration 5436, lr = 0.00340686 +I0410 14:10:16.266507 18414 solver.cpp:218] Iteration 5448 (2.45098 iter/s, 4.89601s/12 iters), loss = 1.4659 +I0410 14:10:16.266552 18414 solver.cpp:237] Train net output #0: loss = 1.4659 (* 1 = 1.4659 loss) +I0410 14:10:16.266562 18414 sgd_solver.cpp:105] Iteration 5448, lr = 0.00339877 +I0410 14:10:21.189114 18414 solver.cpp:218] Iteration 5460 (2.43784 iter/s, 4.9224s/12 iters), loss = 1.80198 +I0410 14:10:21.189167 18414 solver.cpp:237] Train net output #0: loss = 1.80198 (* 1 = 1.80198 loss) +I0410 14:10:21.189178 18414 sgd_solver.cpp:105] Iteration 5460, lr = 0.0033907 +I0410 14:10:21.753810 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:10:26.096411 18414 solver.cpp:218] Iteration 5472 (2.44545 iter/s, 4.90708s/12 iters), loss = 1.96152 +I0410 14:10:26.096463 18414 solver.cpp:237] Train net output #0: loss = 1.96152 (* 1 = 1.96152 loss) +I0410 14:10:26.096475 18414 sgd_solver.cpp:105] Iteration 5472, lr = 0.00338265 +I0410 14:10:30.999994 18414 solver.cpp:218] Iteration 5484 (2.4473 iter/s, 4.90336s/12 iters), loss = 1.71658 +I0410 14:10:31.000048 18414 solver.cpp:237] Train net output #0: loss = 1.71658 (* 1 = 1.71658 loss) +I0410 14:10:31.000059 18414 sgd_solver.cpp:105] Iteration 5484, lr = 0.00337462 +I0410 14:10:36.022137 18414 solver.cpp:218] Iteration 5496 (2.38953 iter/s, 5.02191s/12 iters), loss = 1.51953 +I0410 14:10:36.022192 18414 solver.cpp:237] Train net output #0: loss = 1.51953 (* 1 = 1.51953 loss) +I0410 14:10:36.022203 18414 sgd_solver.cpp:105] Iteration 5496, lr = 0.00336661 +I0410 14:10:40.649127 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5508.caffemodel +I0410 14:10:40.945878 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5508.solverstate +I0410 14:10:41.157685 18414 solver.cpp:330] Iteration 5508, Testing net (#0) +I0410 14:10:41.157707 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:10:43.417029 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:10:45.588294 18414 solver.cpp:397] Test net output #0: accuracy = 0.452819 +I0410 14:10:45.588343 18414 solver.cpp:397] Test net output #1: loss = 2.10313 (* 1 = 2.10313 loss) +I0410 14:10:45.671418 18414 solver.cpp:218] Iteration 5508 (1.24366 iter/s, 9.64892s/12 iters), loss = 1.68995 +I0410 14:10:45.671470 18414 solver.cpp:237] Train net output #0: loss = 1.68995 (* 1 = 1.68995 loss) +I0410 14:10:45.671483 18414 sgd_solver.cpp:105] Iteration 5508, lr = 0.00335861 +I0410 14:10:50.047451 18414 solver.cpp:218] Iteration 5520 (2.74234 iter/s, 4.37583s/12 iters), loss = 1.88901 +I0410 14:10:50.047508 18414 solver.cpp:237] Train net output #0: loss = 1.88901 (* 1 = 1.88901 loss) +I0410 14:10:50.047520 18414 sgd_solver.cpp:105] Iteration 5520, lr = 0.00335064 +I0410 14:10:50.833501 18414 blocking_queue.cpp:49] Waiting for data +I0410 14:10:54.923020 18414 solver.cpp:218] Iteration 5532 (2.46136 iter/s, 4.87535s/12 iters), loss = 2.05161 +I0410 14:10:54.923074 18414 solver.cpp:237] Train net output #0: loss = 2.05161 (* 1 = 2.05161 loss) +I0410 14:10:54.923087 18414 sgd_solver.cpp:105] Iteration 5532, lr = 0.00334268 +I0410 14:10:59.798012 18414 solver.cpp:218] Iteration 5544 (2.46165 iter/s, 4.87478s/12 iters), loss = 1.69044 +I0410 14:10:59.798069 18414 solver.cpp:237] Train net output #0: loss = 1.69044 (* 1 = 1.69044 loss) +I0410 14:10:59.798084 18414 sgd_solver.cpp:105] Iteration 5544, lr = 0.00333475 +I0410 14:11:05.016223 18414 solver.cpp:218] Iteration 5556 (2.29974 iter/s, 5.21799s/12 iters), loss = 1.59317 +I0410 14:11:05.016273 18414 solver.cpp:237] Train net output #0: loss = 1.59317 (* 1 = 1.59317 loss) +I0410 14:11:05.016285 18414 sgd_solver.cpp:105] Iteration 5556, lr = 0.00332683 +I0410 14:11:07.845228 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:11:10.134531 18414 solver.cpp:218] Iteration 5568 (2.34462 iter/s, 5.11809s/12 iters), loss = 1.66163 +I0410 14:11:10.134582 18414 solver.cpp:237] Train net output #0: loss = 1.66163 (* 1 = 1.66163 loss) +I0410 14:11:10.134593 18414 sgd_solver.cpp:105] Iteration 5568, lr = 0.00331893 +I0410 14:11:15.037711 18414 solver.cpp:218] Iteration 5580 (2.4475 iter/s, 4.90297s/12 iters), loss = 1.63385 +I0410 14:11:15.037838 18414 solver.cpp:237] Train net output #0: loss = 1.63385 (* 1 = 1.63385 loss) +I0410 14:11:15.037853 18414 sgd_solver.cpp:105] Iteration 5580, lr = 0.00331105 +I0410 14:11:19.964114 18414 solver.cpp:218] Iteration 5592 (2.436 iter/s, 4.92612s/12 iters), loss = 1.90603 +I0410 14:11:19.964155 18414 solver.cpp:237] Train net output #0: loss = 1.90603 (* 1 = 1.90603 loss) +I0410 14:11:19.964164 18414 sgd_solver.cpp:105] Iteration 5592, lr = 0.00330319 +I0410 14:11:24.873448 18414 solver.cpp:218] Iteration 5604 (2.44442 iter/s, 4.90913s/12 iters), loss = 1.43032 +I0410 14:11:24.873494 18414 solver.cpp:237] Train net output #0: loss = 1.43032 (* 1 = 1.43032 loss) +I0410 14:11:24.873503 18414 sgd_solver.cpp:105] Iteration 5604, lr = 0.00329535 +I0410 14:11:26.851958 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5610.caffemodel +I0410 14:11:27.140264 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5610.solverstate +I0410 14:11:27.340610 18414 solver.cpp:330] Iteration 5610, Testing net (#0) +I0410 14:11:27.340642 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:11:29.619860 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:11:31.859886 18414 solver.cpp:397] Test net output #0: accuracy = 0.447917 +I0410 14:11:31.859936 18414 solver.cpp:397] Test net output #1: loss = 2.1641 (* 1 = 2.1641 loss) +I0410 14:11:34.183801 18414 solver.cpp:218] Iteration 5616 (1.28894 iter/s, 9.31001s/12 iters), loss = 1.8432 +I0410 14:11:34.183853 18414 solver.cpp:237] Train net output #0: loss = 1.8432 (* 1 = 1.8432 loss) +I0410 14:11:34.183867 18414 sgd_solver.cpp:105] Iteration 5616, lr = 0.00328752 +I0410 14:11:39.093410 18414 solver.cpp:218] Iteration 5628 (2.4443 iter/s, 4.90939s/12 iters), loss = 1.73621 +I0410 14:11:39.093466 18414 solver.cpp:237] Train net output #0: loss = 1.73621 (* 1 = 1.73621 loss) +I0410 14:11:39.093480 18414 sgd_solver.cpp:105] Iteration 5628, lr = 0.00327972 +I0410 14:11:44.073346 18414 solver.cpp:218] Iteration 5640 (2.40978 iter/s, 4.97971s/12 iters), loss = 1.68262 +I0410 14:11:44.073398 18414 solver.cpp:237] Train net output #0: loss = 1.68262 (* 1 = 1.68262 loss) +I0410 14:11:44.073410 18414 sgd_solver.cpp:105] Iteration 5640, lr = 0.00327193 +I0410 14:11:49.012058 18414 solver.cpp:218] Iteration 5652 (2.42989 iter/s, 4.9385s/12 iters), loss = 1.62812 +I0410 14:11:49.012168 18414 solver.cpp:237] Train net output #0: loss = 1.62812 (* 1 = 1.62812 loss) +I0410 14:11:49.012181 18414 sgd_solver.cpp:105] Iteration 5652, lr = 0.00326416 +I0410 14:11:53.758090 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:11:53.927008 18414 solver.cpp:218] Iteration 5664 (2.44167 iter/s, 4.91468s/12 iters), loss = 1.72085 +I0410 14:11:53.927064 18414 solver.cpp:237] Train net output #0: loss = 1.72085 (* 1 = 1.72085 loss) +I0410 14:11:53.927078 18414 sgd_solver.cpp:105] Iteration 5664, lr = 0.00325641 +I0410 14:11:58.872592 18414 solver.cpp:218] Iteration 5676 (2.42651 iter/s, 4.94537s/12 iters), loss = 1.61509 +I0410 14:11:58.872645 18414 solver.cpp:237] Train net output #0: loss = 1.61509 (* 1 = 1.61509 loss) +I0410 14:11:58.872659 18414 sgd_solver.cpp:105] Iteration 5676, lr = 0.00324868 +I0410 14:12:03.784159 18414 solver.cpp:218] Iteration 5688 (2.44332 iter/s, 4.91135s/12 iters), loss = 1.44199 +I0410 14:12:03.784219 18414 solver.cpp:237] Train net output #0: loss = 1.44199 (* 1 = 1.44199 loss) +I0410 14:12:03.784231 18414 sgd_solver.cpp:105] Iteration 5688, lr = 0.00324097 +I0410 14:12:08.705511 18414 solver.cpp:218] Iteration 5700 (2.43846 iter/s, 4.92113s/12 iters), loss = 1.826 +I0410 14:12:08.705562 18414 solver.cpp:237] Train net output #0: loss = 1.826 (* 1 = 1.826 loss) +I0410 14:12:08.705574 18414 sgd_solver.cpp:105] Iteration 5700, lr = 0.00323328 +I0410 14:12:13.146492 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5712.caffemodel +I0410 14:12:13.462473 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5712.solverstate +I0410 14:12:13.669627 18414 solver.cpp:330] Iteration 5712, Testing net (#0) +I0410 14:12:13.669647 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:12:15.963284 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:18.211153 18414 solver.cpp:397] Test net output #0: accuracy = 0.434436 +I0410 14:12:18.211200 18414 solver.cpp:397] Test net output #1: loss = 2.16868 (* 1 = 2.16868 loss) +I0410 14:12:18.294160 18414 solver.cpp:218] Iteration 5712 (1.25153 iter/s, 9.58829s/12 iters), loss = 1.74149 +I0410 14:12:18.294215 18414 solver.cpp:237] Train net output #0: loss = 1.74149 (* 1 = 1.74149 loss) +I0410 14:12:18.294227 18414 sgd_solver.cpp:105] Iteration 5712, lr = 0.0032256 +I0410 14:12:22.492503 18414 solver.cpp:218] Iteration 5724 (2.85841 iter/s, 4.19815s/12 iters), loss = 1.80591 +I0410 14:12:22.492612 18414 solver.cpp:237] Train net output #0: loss = 1.80591 (* 1 = 1.80591 loss) +I0410 14:12:22.492625 18414 sgd_solver.cpp:105] Iteration 5724, lr = 0.00321794 +I0410 14:12:27.427970 18414 solver.cpp:218] Iteration 5736 (2.43152 iter/s, 4.93519s/12 iters), loss = 1.80757 +I0410 14:12:27.428017 18414 solver.cpp:237] Train net output #0: loss = 1.80757 (* 1 = 1.80757 loss) +I0410 14:12:27.428026 18414 sgd_solver.cpp:105] Iteration 5736, lr = 0.0032103 +I0410 14:12:32.274482 18414 solver.cpp:218] Iteration 5748 (2.47612 iter/s, 4.84629s/12 iters), loss = 1.61475 +I0410 14:12:32.274546 18414 solver.cpp:237] Train net output #0: loss = 1.61475 (* 1 = 1.61475 loss) +I0410 14:12:32.274559 18414 sgd_solver.cpp:105] Iteration 5748, lr = 0.00320268 +I0410 14:12:37.174346 18414 solver.cpp:218] Iteration 5760 (2.44916 iter/s, 4.89964s/12 iters), loss = 1.72133 +I0410 14:12:37.174394 18414 solver.cpp:237] Train net output #0: loss = 1.72133 (* 1 = 1.72133 loss) +I0410 14:12:37.174404 18414 sgd_solver.cpp:105] Iteration 5760, lr = 0.00319508 +I0410 14:12:39.072938 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:42.061286 18414 solver.cpp:218] Iteration 5772 (2.45564 iter/s, 4.88672s/12 iters), loss = 1.44874 +I0410 14:12:42.061343 18414 solver.cpp:237] Train net output #0: loss = 1.44874 (* 1 = 1.44874 loss) +I0410 14:12:42.061355 18414 sgd_solver.cpp:105] Iteration 5772, lr = 0.00318749 +I0410 14:12:47.004791 18414 solver.cpp:218] Iteration 5784 (2.42754 iter/s, 4.94329s/12 iters), loss = 1.80078 +I0410 14:12:47.004838 18414 solver.cpp:237] Train net output #0: loss = 1.80078 (* 1 = 1.80078 loss) +I0410 14:12:47.004848 18414 sgd_solver.cpp:105] Iteration 5784, lr = 0.00317992 +I0410 14:12:52.024996 18414 solver.cpp:218] Iteration 5796 (2.39044 iter/s, 5.01999s/12 iters), loss = 1.5335 +I0410 14:12:52.025036 18414 solver.cpp:237] Train net output #0: loss = 1.5335 (* 1 = 1.5335 loss) +I0410 14:12:52.025044 18414 sgd_solver.cpp:105] Iteration 5796, lr = 0.00317237 +I0410 14:12:56.998703 18414 solver.cpp:218] Iteration 5808 (2.41279 iter/s, 4.9735s/12 iters), loss = 1.80893 +I0410 14:12:56.998843 18414 solver.cpp:237] Train net output #0: loss = 1.80893 (* 1 = 1.80893 loss) +I0410 14:12:56.998857 18414 sgd_solver.cpp:105] Iteration 5808, lr = 0.00316484 +I0410 14:12:58.991889 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5814.caffemodel +I0410 14:12:59.278228 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5814.solverstate +I0410 14:12:59.473161 18414 solver.cpp:330] Iteration 5814, Testing net (#0) +I0410 14:12:59.473181 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:13:01.643667 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:03.929199 18414 solver.cpp:397] Test net output #0: accuracy = 0.454657 +I0410 14:13:03.929230 18414 solver.cpp:397] Test net output #1: loss = 2.1196 (* 1 = 2.1196 loss) +I0410 14:13:05.774294 18414 solver.cpp:218] Iteration 5820 (1.3675 iter/s, 8.77517s/12 iters), loss = 1.43304 +I0410 14:13:05.774356 18414 solver.cpp:237] Train net output #0: loss = 1.43304 (* 1 = 1.43304 loss) +I0410 14:13:05.774370 18414 sgd_solver.cpp:105] Iteration 5820, lr = 0.00315733 +I0410 14:13:10.746611 18414 solver.cpp:218] Iteration 5832 (2.41347 iter/s, 4.97209s/12 iters), loss = 1.50841 +I0410 14:13:10.746668 18414 solver.cpp:237] Train net output #0: loss = 1.50841 (* 1 = 1.50841 loss) +I0410 14:13:10.746681 18414 sgd_solver.cpp:105] Iteration 5832, lr = 0.00314983 +I0410 14:13:15.704460 18414 solver.cpp:218] Iteration 5844 (2.42051 iter/s, 4.95763s/12 iters), loss = 1.83568 +I0410 14:13:15.704502 18414 solver.cpp:237] Train net output #0: loss = 1.83568 (* 1 = 1.83568 loss) +I0410 14:13:15.704511 18414 sgd_solver.cpp:105] Iteration 5844, lr = 0.00314235 +I0410 14:13:20.603132 18414 solver.cpp:218] Iteration 5856 (2.44974 iter/s, 4.89847s/12 iters), loss = 1.46659 +I0410 14:13:20.603174 18414 solver.cpp:237] Train net output #0: loss = 1.46659 (* 1 = 1.46659 loss) +I0410 14:13:20.603183 18414 sgd_solver.cpp:105] Iteration 5856, lr = 0.00313489 +I0410 14:13:24.796456 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:25.621407 18414 solver.cpp:218] Iteration 5868 (2.39136 iter/s, 5.01806s/12 iters), loss = 1.50075 +I0410 14:13:25.621449 18414 solver.cpp:237] Train net output #0: loss = 1.50075 (* 1 = 1.50075 loss) +I0410 14:13:25.621459 18414 sgd_solver.cpp:105] Iteration 5868, lr = 0.00312745 +I0410 14:13:30.623497 18414 solver.cpp:218] Iteration 5880 (2.3991 iter/s, 5.00188s/12 iters), loss = 1.57609 +I0410 14:13:30.625260 18414 solver.cpp:237] Train net output #0: loss = 1.57609 (* 1 = 1.57609 loss) +I0410 14:13:30.625273 18414 sgd_solver.cpp:105] Iteration 5880, lr = 0.00312002 +I0410 14:13:35.525029 18414 solver.cpp:218] Iteration 5892 (2.44917 iter/s, 4.89961s/12 iters), loss = 1.42474 +I0410 14:13:35.525072 18414 solver.cpp:237] Train net output #0: loss = 1.42474 (* 1 = 1.42474 loss) +I0410 14:13:35.525081 18414 sgd_solver.cpp:105] Iteration 5892, lr = 0.00311262 +I0410 14:13:40.444159 18414 solver.cpp:218] Iteration 5904 (2.43956 iter/s, 4.91891s/12 iters), loss = 1.46435 +I0410 14:13:40.444221 18414 solver.cpp:237] Train net output #0: loss = 1.46435 (* 1 = 1.46435 loss) +I0410 14:13:40.444236 18414 sgd_solver.cpp:105] Iteration 5904, lr = 0.00310523 +I0410 14:13:45.037509 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5916.caffemodel +I0410 14:13:45.368196 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5916.solverstate +I0410 14:13:45.594982 18414 solver.cpp:330] Iteration 5916, Testing net (#0) +I0410 14:13:45.595013 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:13:47.987701 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:50.311076 18414 solver.cpp:397] Test net output #0: accuracy = 0.452206 +I0410 14:13:50.311125 18414 solver.cpp:397] Test net output #1: loss = 2.12371 (* 1 = 2.12371 loss) +I0410 14:13:50.394094 18414 solver.cpp:218] Iteration 5916 (1.20608 iter/s, 9.94956s/12 iters), loss = 1.7262 +I0410 14:13:50.394146 18414 solver.cpp:237] Train net output #0: loss = 1.7262 (* 1 = 1.7262 loss) +I0410 14:13:50.394165 18414 sgd_solver.cpp:105] Iteration 5916, lr = 0.00309785 +I0410 14:13:54.725409 18414 solver.cpp:218] Iteration 5928 (2.77065 iter/s, 4.33112s/12 iters), loss = 1.70169 +I0410 14:13:54.725468 18414 solver.cpp:237] Train net output #0: loss = 1.70169 (* 1 = 1.70169 loss) +I0410 14:13:54.725481 18414 sgd_solver.cpp:105] Iteration 5928, lr = 0.0030905 +I0410 14:13:59.771517 18414 solver.cpp:218] Iteration 5940 (2.37818 iter/s, 5.04589s/12 iters), loss = 1.4387 +I0410 14:13:59.771555 18414 solver.cpp:237] Train net output #0: loss = 1.4387 (* 1 = 1.4387 loss) +I0410 14:13:59.771564 18414 sgd_solver.cpp:105] Iteration 5940, lr = 0.00308316 +I0410 14:14:04.707123 18414 solver.cpp:218] Iteration 5952 (2.43142 iter/s, 4.9354s/12 iters), loss = 1.68626 +I0410 14:14:04.707267 18414 solver.cpp:237] Train net output #0: loss = 1.68626 (* 1 = 1.68626 loss) +I0410 14:14:04.707283 18414 sgd_solver.cpp:105] Iteration 5952, lr = 0.00307584 +I0410 14:14:09.688844 18414 solver.cpp:218] Iteration 5964 (2.40895 iter/s, 4.98142s/12 iters), loss = 1.56576 +I0410 14:14:09.688906 18414 solver.cpp:237] Train net output #0: loss = 1.56576 (* 1 = 1.56576 loss) +I0410 14:14:09.688920 18414 sgd_solver.cpp:105] Iteration 5964, lr = 0.00306854 +I0410 14:14:11.008410 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:14:14.623256 18414 solver.cpp:218] Iteration 5976 (2.43201 iter/s, 4.93418s/12 iters), loss = 1.21099 +I0410 14:14:14.623304 18414 solver.cpp:237] Train net output #0: loss = 1.21099 (* 1 = 1.21099 loss) +I0410 14:14:14.623314 18414 sgd_solver.cpp:105] Iteration 5976, lr = 0.00306125 +I0410 14:14:19.561092 18414 solver.cpp:218] Iteration 5988 (2.43032 iter/s, 4.93762s/12 iters), loss = 1.42386 +I0410 14:14:19.561139 18414 solver.cpp:237] Train net output #0: loss = 1.42386 (* 1 = 1.42386 loss) +I0410 14:14:19.561151 18414 sgd_solver.cpp:105] Iteration 5988, lr = 0.00305398 +I0410 14:14:24.509713 18414 solver.cpp:218] Iteration 6000 (2.42502 iter/s, 4.94841s/12 iters), loss = 1.5428 +I0410 14:14:24.509764 18414 solver.cpp:237] Train net output #0: loss = 1.5428 (* 1 = 1.5428 loss) +I0410 14:14:24.509778 18414 sgd_solver.cpp:105] Iteration 6000, lr = 0.00304673 +I0410 14:14:29.402601 18414 solver.cpp:218] Iteration 6012 (2.45264 iter/s, 4.89268s/12 iters), loss = 1.32156 +I0410 14:14:29.402642 18414 solver.cpp:237] Train net output #0: loss = 1.32156 (* 1 = 1.32156 loss) +I0410 14:14:29.402652 18414 sgd_solver.cpp:105] Iteration 6012, lr = 0.0030395 +I0410 14:14:31.368404 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6018.caffemodel +I0410 14:14:31.694350 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6018.solverstate +I0410 14:14:31.900483 18414 solver.cpp:330] Iteration 6018, Testing net (#0) +I0410 14:14:31.900503 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:14:33.937105 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:14:36.308902 18414 solver.cpp:397] Test net output #0: accuracy = 0.479779 +I0410 14:14:36.309082 18414 solver.cpp:397] Test net output #1: loss = 1.96977 (* 1 = 1.96977 loss) +I0410 14:14:38.184367 18414 solver.cpp:218] Iteration 6024 (1.36652 iter/s, 8.78144s/12 iters), loss = 1.54766 +I0410 14:14:38.184424 18414 solver.cpp:237] Train net output #0: loss = 1.54766 (* 1 = 1.54766 loss) +I0410 14:14:38.184437 18414 sgd_solver.cpp:105] Iteration 6024, lr = 0.00303228 +I0410 14:14:43.137298 18414 solver.cpp:218] Iteration 6036 (2.42292 iter/s, 4.95271s/12 iters), loss = 1.31264 +I0410 14:14:43.137356 18414 solver.cpp:237] Train net output #0: loss = 1.31264 (* 1 = 1.31264 loss) +I0410 14:14:43.137368 18414 sgd_solver.cpp:105] Iteration 6036, lr = 0.00302508 +I0410 14:14:48.165387 18414 solver.cpp:218] Iteration 6048 (2.3867 iter/s, 5.02786s/12 iters), loss = 1.61528 +I0410 14:14:48.165444 18414 solver.cpp:237] Train net output #0: loss = 1.61528 (* 1 = 1.61528 loss) +I0410 14:14:48.165457 18414 sgd_solver.cpp:105] Iteration 6048, lr = 0.0030179 +I0410 14:14:53.166766 18414 solver.cpp:218] Iteration 6060 (2.39945 iter/s, 5.00115s/12 iters), loss = 1.45114 +I0410 14:14:53.166821 18414 solver.cpp:237] Train net output #0: loss = 1.45114 (* 1 = 1.45114 loss) +I0410 14:14:53.166834 18414 sgd_solver.cpp:105] Iteration 6060, lr = 0.00301074 +I0410 14:14:56.577446 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:14:58.104993 18414 solver.cpp:218] Iteration 6072 (2.43013 iter/s, 4.938s/12 iters), loss = 1.54954 +I0410 14:14:58.105049 18414 solver.cpp:237] Train net output #0: loss = 1.54954 (* 1 = 1.54954 loss) +I0410 14:14:58.105062 18414 sgd_solver.cpp:105] Iteration 6072, lr = 0.00300359 +I0410 14:15:03.091847 18414 solver.cpp:218] Iteration 6084 (2.40643 iter/s, 4.98664s/12 iters), loss = 1.37639 +I0410 14:15:03.091900 18414 solver.cpp:237] Train net output #0: loss = 1.37639 (* 1 = 1.37639 loss) +I0410 14:15:03.091912 18414 sgd_solver.cpp:105] Iteration 6084, lr = 0.00299646 +I0410 14:15:08.111497 18414 solver.cpp:218] Iteration 6096 (2.39071 iter/s, 5.01943s/12 iters), loss = 1.50133 +I0410 14:15:08.111595 18414 solver.cpp:237] Train net output #0: loss = 1.50133 (* 1 = 1.50133 loss) +I0410 14:15:08.111605 18414 sgd_solver.cpp:105] Iteration 6096, lr = 0.00298934 +I0410 14:15:12.969812 18414 solver.cpp:218] Iteration 6108 (2.47013 iter/s, 4.85805s/12 iters), loss = 1.40807 +I0410 14:15:12.969852 18414 solver.cpp:237] Train net output #0: loss = 1.40807 (* 1 = 1.40807 loss) +I0410 14:15:12.969861 18414 sgd_solver.cpp:105] Iteration 6108, lr = 0.00298225 +I0410 14:15:17.486935 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6120.caffemodel +I0410 14:15:17.782084 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6120.solverstate +I0410 14:15:17.980114 18414 solver.cpp:330] Iteration 6120, Testing net (#0) +I0410 14:15:17.980139 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:15:20.018162 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:22.455744 18414 solver.cpp:397] Test net output #0: accuracy = 0.479779 +I0410 14:15:22.455794 18414 solver.cpp:397] Test net output #1: loss = 2.00106 (* 1 = 2.00106 loss) +I0410 14:15:22.538682 18414 solver.cpp:218] Iteration 6120 (1.25411 iter/s, 9.56853s/12 iters), loss = 1.74612 +I0410 14:15:22.538728 18414 solver.cpp:237] Train net output #0: loss = 1.74612 (* 1 = 1.74612 loss) +I0410 14:15:22.538739 18414 sgd_solver.cpp:105] Iteration 6120, lr = 0.00297517 +I0410 14:15:26.739289 18414 solver.cpp:218] Iteration 6132 (2.85686 iter/s, 4.20042s/12 iters), loss = 1.588 +I0410 14:15:26.739339 18414 solver.cpp:237] Train net output #0: loss = 1.588 (* 1 = 1.588 loss) +I0410 14:15:26.739351 18414 sgd_solver.cpp:105] Iteration 6132, lr = 0.0029681 +I0410 14:15:31.644371 18414 solver.cpp:218] Iteration 6144 (2.44655 iter/s, 4.90487s/12 iters), loss = 1.68877 +I0410 14:15:31.644420 18414 solver.cpp:237] Train net output #0: loss = 1.68877 (* 1 = 1.68877 loss) +I0410 14:15:31.644433 18414 sgd_solver.cpp:105] Iteration 6144, lr = 0.00296105 +I0410 14:15:36.576131 18414 solver.cpp:218] Iteration 6156 (2.43331 iter/s, 4.93154s/12 iters), loss = 1.48164 +I0410 14:15:36.576185 18414 solver.cpp:237] Train net output #0: loss = 1.48164 (* 1 = 1.48164 loss) +I0410 14:15:36.576198 18414 sgd_solver.cpp:105] Iteration 6156, lr = 0.00295402 +I0410 14:15:41.464743 18414 solver.cpp:218] Iteration 6168 (2.4548 iter/s, 4.88839s/12 iters), loss = 1.7133 +I0410 14:15:41.465759 18414 solver.cpp:237] Train net output #0: loss = 1.7133 (* 1 = 1.7133 loss) +I0410 14:15:41.465773 18414 sgd_solver.cpp:105] Iteration 6168, lr = 0.00294701 +I0410 14:15:42.048782 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:46.397228 18414 solver.cpp:218] Iteration 6180 (2.43343 iter/s, 4.93131s/12 iters), loss = 1.56315 +I0410 14:15:46.397276 18414 solver.cpp:237] Train net output #0: loss = 1.56315 (* 1 = 1.56315 loss) +I0410 14:15:46.397289 18414 sgd_solver.cpp:105] Iteration 6180, lr = 0.00294001 +I0410 14:15:51.367218 18414 solver.cpp:218] Iteration 6192 (2.4146 iter/s, 4.96977s/12 iters), loss = 1.5137 +I0410 14:15:51.367274 18414 solver.cpp:237] Train net output #0: loss = 1.5137 (* 1 = 1.5137 loss) +I0410 14:15:51.367286 18414 sgd_solver.cpp:105] Iteration 6192, lr = 0.00293303 +I0410 14:15:56.380697 18414 solver.cpp:218] Iteration 6204 (2.39365 iter/s, 5.01326s/12 iters), loss = 1.26872 +I0410 14:15:56.380753 18414 solver.cpp:237] Train net output #0: loss = 1.26872 (* 1 = 1.26872 loss) +I0410 14:15:56.380765 18414 sgd_solver.cpp:105] Iteration 6204, lr = 0.00292607 +I0410 14:16:01.293336 18414 solver.cpp:218] Iteration 6216 (2.44279 iter/s, 4.91242s/12 iters), loss = 1.56036 +I0410 14:16:01.293393 18414 solver.cpp:237] Train net output #0: loss = 1.56036 (* 1 = 1.56036 loss) +I0410 14:16:01.293406 18414 sgd_solver.cpp:105] Iteration 6216, lr = 0.00291912 +I0410 14:16:03.304623 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6222.caffemodel +I0410 14:16:03.629603 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6222.solverstate +I0410 14:16:03.839627 18414 solver.cpp:330] Iteration 6222, Testing net (#0) +I0410 14:16:03.839649 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:16:05.862006 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:16:06.772224 18414 blocking_queue.cpp:49] Waiting for data +I0410 14:16:08.302489 18414 solver.cpp:397] Test net output #0: accuracy = 0.490809 +I0410 14:16:08.302518 18414 solver.cpp:397] Test net output #1: loss = 1.95989 (* 1 = 1.95989 loss) +I0410 14:16:10.185429 18414 solver.cpp:218] Iteration 6228 (1.34957 iter/s, 8.89175s/12 iters), loss = 1.49389 +I0410 14:16:10.185487 18414 solver.cpp:237] Train net output #0: loss = 1.49389 (* 1 = 1.49389 loss) +I0410 14:16:10.185499 18414 sgd_solver.cpp:105] Iteration 6228, lr = 0.00291219 +I0410 14:16:15.037626 18414 solver.cpp:218] Iteration 6240 (2.47322 iter/s, 4.85197s/12 iters), loss = 1.69272 +I0410 14:16:15.037803 18414 solver.cpp:237] Train net output #0: loss = 1.69272 (* 1 = 1.69272 loss) +I0410 14:16:15.037817 18414 sgd_solver.cpp:105] Iteration 6240, lr = 0.00290528 +I0410 14:16:19.959391 18414 solver.cpp:218] Iteration 6252 (2.43832 iter/s, 4.92143s/12 iters), loss = 1.51289 +I0410 14:16:19.959439 18414 solver.cpp:237] Train net output #0: loss = 1.51289 (* 1 = 1.51289 loss) +I0410 14:16:19.959448 18414 sgd_solver.cpp:105] Iteration 6252, lr = 0.00289838 +I0410 14:16:24.901213 18414 solver.cpp:218] Iteration 6264 (2.42836 iter/s, 4.94161s/12 iters), loss = 1.30591 +I0410 14:16:24.901259 18414 solver.cpp:237] Train net output #0: loss = 1.30591 (* 1 = 1.30591 loss) +I0410 14:16:24.901268 18414 sgd_solver.cpp:105] Iteration 6264, lr = 0.0028915 +I0410 14:16:27.552678 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:16:29.785207 18414 solver.cpp:218] Iteration 6276 (2.45711 iter/s, 4.88379s/12 iters), loss = 1.48237 +I0410 14:16:29.785252 18414 solver.cpp:237] Train net output #0: loss = 1.48237 (* 1 = 1.48237 loss) +I0410 14:16:29.785262 18414 sgd_solver.cpp:105] Iteration 6276, lr = 0.00288463 +I0410 14:16:34.971359 18414 solver.cpp:218] Iteration 6288 (2.31395 iter/s, 5.18593s/12 iters), loss = 1.40417 +I0410 14:16:34.971405 18414 solver.cpp:237] Train net output #0: loss = 1.40417 (* 1 = 1.40417 loss) +I0410 14:16:34.971413 18414 sgd_solver.cpp:105] Iteration 6288, lr = 0.00287779 +I0410 14:16:39.843961 18414 solver.cpp:218] Iteration 6300 (2.46286 iter/s, 4.87239s/12 iters), loss = 1.2956 +I0410 14:16:39.844004 18414 solver.cpp:237] Train net output #0: loss = 1.2956 (* 1 = 1.2956 loss) +I0410 14:16:39.844013 18414 sgd_solver.cpp:105] Iteration 6300, lr = 0.00287095 +I0410 14:16:44.951567 18414 solver.cpp:218] Iteration 6312 (2.34954 iter/s, 5.10738s/12 iters), loss = 1.39522 +I0410 14:16:44.951623 18414 solver.cpp:237] Train net output #0: loss = 1.39522 (* 1 = 1.39522 loss) +I0410 14:16:44.951635 18414 sgd_solver.cpp:105] Iteration 6312, lr = 0.00286414 +I0410 14:16:49.451963 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6324.caffemodel +I0410 14:16:49.754173 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6324.solverstate +I0410 14:16:49.953662 18414 solver.cpp:330] Iteration 6324, Testing net (#0) +I0410 14:16:49.953703 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:16:51.914391 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:16:54.541337 18414 solver.cpp:397] Test net output #0: accuracy = 0.490196 +I0410 14:16:54.541378 18414 solver.cpp:397] Test net output #1: loss = 1.9945 (* 1 = 1.9945 loss) +I0410 14:16:54.624186 18414 solver.cpp:218] Iteration 6324 (1.24066 iter/s, 9.67225s/12 iters), loss = 1.49005 +I0410 14:16:54.624231 18414 solver.cpp:237] Train net output #0: loss = 1.49005 (* 1 = 1.49005 loss) +I0410 14:16:54.624241 18414 sgd_solver.cpp:105] Iteration 6324, lr = 0.00285734 +I0410 14:16:59.012274 18414 solver.cpp:218] Iteration 6336 (2.7348 iter/s, 4.38789s/12 iters), loss = 1.60595 +I0410 14:16:59.012326 18414 solver.cpp:237] Train net output #0: loss = 1.60595 (* 1 = 1.60595 loss) +I0410 14:16:59.012338 18414 sgd_solver.cpp:105] Iteration 6336, lr = 0.00285055 +I0410 14:17:03.982146 18414 solver.cpp:218] Iteration 6348 (2.41465 iter/s, 4.96966s/12 iters), loss = 1.59995 +I0410 14:17:03.982198 18414 solver.cpp:237] Train net output #0: loss = 1.59995 (* 1 = 1.59995 loss) +I0410 14:17:03.982210 18414 sgd_solver.cpp:105] Iteration 6348, lr = 0.00284379 +I0410 14:17:08.907235 18414 solver.cpp:218] Iteration 6360 (2.43661 iter/s, 4.92487s/12 iters), loss = 1.72309 +I0410 14:17:08.907285 18414 solver.cpp:237] Train net output #0: loss = 1.72309 (* 1 = 1.72309 loss) +I0410 14:17:08.907296 18414 sgd_solver.cpp:105] Iteration 6360, lr = 0.00283703 +I0410 14:17:13.708006 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:17:13.846244 18414 solver.cpp:218] Iteration 6372 (2.42974 iter/s, 4.93879s/12 iters), loss = 1.52134 +I0410 14:17:13.846294 18414 solver.cpp:237] Train net output #0: loss = 1.52134 (* 1 = 1.52134 loss) +I0410 14:17:13.846307 18414 sgd_solver.cpp:105] Iteration 6372, lr = 0.0028303 +I0410 14:17:18.759430 18414 solver.cpp:218] Iteration 6384 (2.44251 iter/s, 4.91297s/12 iters), loss = 1.51103 +I0410 14:17:18.759479 18414 solver.cpp:237] Train net output #0: loss = 1.51103 (* 1 = 1.51103 loss) +I0410 14:17:18.759490 18414 sgd_solver.cpp:105] Iteration 6384, lr = 0.00282358 +I0410 14:17:23.661325 18414 solver.cpp:218] Iteration 6396 (2.44814 iter/s, 4.90168s/12 iters), loss = 1.22818 +I0410 14:17:23.661474 18414 solver.cpp:237] Train net output #0: loss = 1.22818 (* 1 = 1.22818 loss) +I0410 14:17:23.661486 18414 sgd_solver.cpp:105] Iteration 6396, lr = 0.00281687 +I0410 14:17:28.576238 18414 solver.cpp:218] Iteration 6408 (2.4417 iter/s, 4.9146s/12 iters), loss = 1.30707 +I0410 14:17:28.576294 18414 solver.cpp:237] Train net output #0: loss = 1.30707 (* 1 = 1.30707 loss) +I0410 14:17:28.576306 18414 sgd_solver.cpp:105] Iteration 6408, lr = 0.00281019 +I0410 14:17:33.500514 18414 solver.cpp:218] Iteration 6420 (2.43702 iter/s, 4.92405s/12 iters), loss = 1.37449 +I0410 14:17:33.500572 18414 solver.cpp:237] Train net output #0: loss = 1.37449 (* 1 = 1.37449 loss) +I0410 14:17:33.500586 18414 sgd_solver.cpp:105] Iteration 6420, lr = 0.00280351 +I0410 14:17:35.487210 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6426.caffemodel +I0410 14:17:36.038663 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6426.solverstate +I0410 14:17:36.710187 18414 solver.cpp:330] Iteration 6426, Testing net (#0) +I0410 14:17:36.710219 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:17:38.692742 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:17:41.279533 18414 solver.cpp:397] Test net output #0: accuracy = 0.476103 +I0410 14:17:41.279585 18414 solver.cpp:397] Test net output #1: loss = 2.00542 (* 1 = 2.00542 loss) +I0410 14:17:43.253239 18414 solver.cpp:218] Iteration 6432 (1.23047 iter/s, 9.75236s/12 iters), loss = 1.38057 +I0410 14:17:43.253290 18414 solver.cpp:237] Train net output #0: loss = 1.38057 (* 1 = 1.38057 loss) +I0410 14:17:43.253304 18414 sgd_solver.cpp:105] Iteration 6432, lr = 0.00279686 +I0410 14:17:48.288223 18414 solver.cpp:218] Iteration 6444 (2.38343 iter/s, 5.03477s/12 iters), loss = 1.35614 +I0410 14:17:48.288264 18414 solver.cpp:237] Train net output #0: loss = 1.35614 (* 1 = 1.35614 loss) +I0410 14:17:48.288273 18414 sgd_solver.cpp:105] Iteration 6444, lr = 0.00279022 +I0410 14:17:53.199151 18414 solver.cpp:218] Iteration 6456 (2.44363 iter/s, 4.91072s/12 iters), loss = 1.38394 +I0410 14:17:53.199208 18414 solver.cpp:237] Train net output #0: loss = 1.38394 (* 1 = 1.38394 loss) +I0410 14:17:53.199220 18414 sgd_solver.cpp:105] Iteration 6456, lr = 0.00278359 +I0410 14:17:58.103474 18414 solver.cpp:218] Iteration 6468 (2.44693 iter/s, 4.90411s/12 iters), loss = 1.20771 +I0410 14:17:58.103577 18414 solver.cpp:237] Train net output #0: loss = 1.20771 (* 1 = 1.20771 loss) +I0410 14:17:58.103592 18414 sgd_solver.cpp:105] Iteration 6468, lr = 0.00277698 +I0410 14:18:00.062495 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:03.043721 18414 solver.cpp:218] Iteration 6480 (2.42916 iter/s, 4.93998s/12 iters), loss = 1.44221 +I0410 14:18:03.043772 18414 solver.cpp:237] Train net output #0: loss = 1.44221 (* 1 = 1.44221 loss) +I0410 14:18:03.043783 18414 sgd_solver.cpp:105] Iteration 6480, lr = 0.00277039 +I0410 14:18:07.912861 18414 solver.cpp:218] Iteration 6492 (2.46461 iter/s, 4.86892s/12 iters), loss = 1.36119 +I0410 14:18:07.912916 18414 solver.cpp:237] Train net output #0: loss = 1.36119 (* 1 = 1.36119 loss) +I0410 14:18:07.912928 18414 sgd_solver.cpp:105] Iteration 6492, lr = 0.00276381 +I0410 14:18:12.817446 18414 solver.cpp:218] Iteration 6504 (2.4468 iter/s, 4.90436s/12 iters), loss = 1.18746 +I0410 14:18:12.817502 18414 solver.cpp:237] Train net output #0: loss = 1.18746 (* 1 = 1.18746 loss) +I0410 14:18:12.817515 18414 sgd_solver.cpp:105] Iteration 6504, lr = 0.00275725 +I0410 14:18:17.715210 18414 solver.cpp:218] Iteration 6516 (2.45021 iter/s, 4.89754s/12 iters), loss = 1.20958 +I0410 14:18:17.715270 18414 solver.cpp:237] Train net output #0: loss = 1.20958 (* 1 = 1.20958 loss) +I0410 14:18:17.715282 18414 sgd_solver.cpp:105] Iteration 6516, lr = 0.00275071 +I0410 14:18:22.186545 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6528.caffemodel +I0410 14:18:22.513540 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6528.solverstate +I0410 14:18:22.724182 18414 solver.cpp:330] Iteration 6528, Testing net (#0) +I0410 14:18:22.724215 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:18:24.731848 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:27.446120 18414 solver.cpp:397] Test net output #0: accuracy = 0.488971 +I0410 14:18:27.446167 18414 solver.cpp:397] Test net output #1: loss = 1.98633 (* 1 = 1.98633 loss) +I0410 14:18:27.529527 18414 solver.cpp:218] Iteration 6528 (1.22275 iter/s, 9.81394s/12 iters), loss = 1.11747 +I0410 14:18:27.529579 18414 solver.cpp:237] Train net output #0: loss = 1.11747 (* 1 = 1.11747 loss) +I0410 14:18:27.529592 18414 sgd_solver.cpp:105] Iteration 6528, lr = 0.00274418 +I0410 14:18:31.825594 18414 solver.cpp:218] Iteration 6540 (2.79338 iter/s, 4.29587s/12 iters), loss = 1.48234 +I0410 14:18:31.825734 18414 solver.cpp:237] Train net output #0: loss = 1.48234 (* 1 = 1.48234 loss) +I0410 14:18:31.825745 18414 sgd_solver.cpp:105] Iteration 6540, lr = 0.00273766 +I0410 14:18:36.808933 18414 solver.cpp:218] Iteration 6552 (2.40817 iter/s, 4.98303s/12 iters), loss = 1.47652 +I0410 14:18:36.808984 18414 solver.cpp:237] Train net output #0: loss = 1.47652 (* 1 = 1.47652 loss) +I0410 14:18:36.808993 18414 sgd_solver.cpp:105] Iteration 6552, lr = 0.00273116 +I0410 14:18:41.822680 18414 solver.cpp:218] Iteration 6564 (2.39352 iter/s, 5.01353s/12 iters), loss = 1.22976 +I0410 14:18:41.822727 18414 solver.cpp:237] Train net output #0: loss = 1.22976 (* 1 = 1.22976 loss) +I0410 14:18:41.822736 18414 sgd_solver.cpp:105] Iteration 6564, lr = 0.00272468 +I0410 14:18:46.033044 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:46.800019 18414 solver.cpp:218] Iteration 6576 (2.41103 iter/s, 4.97712s/12 iters), loss = 1.1478 +I0410 14:18:46.800060 18414 solver.cpp:237] Train net output #0: loss = 1.1478 (* 1 = 1.1478 loss) +I0410 14:18:46.800069 18414 sgd_solver.cpp:105] Iteration 6576, lr = 0.00271821 +I0410 14:18:51.858335 18414 solver.cpp:218] Iteration 6588 (2.37243 iter/s, 5.0581s/12 iters), loss = 1.50927 +I0410 14:18:51.858377 18414 solver.cpp:237] Train net output #0: loss = 1.50927 (* 1 = 1.50927 loss) +I0410 14:18:51.858386 18414 sgd_solver.cpp:105] Iteration 6588, lr = 0.00271175 +I0410 14:18:56.862643 18414 solver.cpp:218] Iteration 6600 (2.39804 iter/s, 5.0041s/12 iters), loss = 1.42751 +I0410 14:18:56.862696 18414 solver.cpp:237] Train net output #0: loss = 1.42751 (* 1 = 1.42751 loss) +I0410 14:18:56.862709 18414 sgd_solver.cpp:105] Iteration 6600, lr = 0.00270532 +I0410 14:19:01.783645 18414 solver.cpp:218] Iteration 6612 (2.43864 iter/s, 4.92078s/12 iters), loss = 1.19813 +I0410 14:19:01.783706 18414 solver.cpp:237] Train net output #0: loss = 1.19813 (* 1 = 1.19813 loss) +I0410 14:19:01.783720 18414 sgd_solver.cpp:105] Iteration 6612, lr = 0.00269889 +I0410 14:19:06.711395 18414 solver.cpp:218] Iteration 6624 (2.4353 iter/s, 4.92753s/12 iters), loss = 1.18895 +I0410 14:19:06.711488 18414 solver.cpp:237] Train net output #0: loss = 1.18895 (* 1 = 1.18895 loss) +I0410 14:19:06.711498 18414 sgd_solver.cpp:105] Iteration 6624, lr = 0.00269248 +I0410 14:19:08.721485 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6630.caffemodel +I0410 14:19:09.034420 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6630.solverstate +I0410 14:19:09.237411 18414 solver.cpp:330] Iteration 6630, Testing net (#0) +I0410 14:19:09.237432 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:19:11.143424 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:19:13.740100 18414 solver.cpp:397] Test net output #0: accuracy = 0.482843 +I0410 14:19:13.740149 18414 solver.cpp:397] Test net output #1: loss = 1.99013 (* 1 = 1.99013 loss) +I0410 14:19:15.743167 18414 solver.cpp:218] Iteration 6636 (1.3287 iter/s, 9.03138s/12 iters), loss = 1.38969 +I0410 14:19:15.743221 18414 solver.cpp:237] Train net output #0: loss = 1.38969 (* 1 = 1.38969 loss) +I0410 14:19:15.743233 18414 sgd_solver.cpp:105] Iteration 6636, lr = 0.00268609 +I0410 14:19:20.654672 18414 solver.cpp:218] Iteration 6648 (2.44335 iter/s, 4.91129s/12 iters), loss = 1.43961 +I0410 14:19:20.654729 18414 solver.cpp:237] Train net output #0: loss = 1.43961 (* 1 = 1.43961 loss) +I0410 14:19:20.654742 18414 sgd_solver.cpp:105] Iteration 6648, lr = 0.00267971 +I0410 14:19:25.510977 18414 solver.cpp:218] Iteration 6660 (2.47113 iter/s, 4.85609s/12 iters), loss = 1.32496 +I0410 14:19:25.511018 18414 solver.cpp:237] Train net output #0: loss = 1.32496 (* 1 = 1.32496 loss) +I0410 14:19:25.511029 18414 sgd_solver.cpp:105] Iteration 6660, lr = 0.00267335 +I0410 14:19:30.405907 18414 solver.cpp:218] Iteration 6672 (2.45162 iter/s, 4.89472s/12 iters), loss = 1.34539 +I0410 14:19:30.405951 18414 solver.cpp:237] Train net output #0: loss = 1.34539 (* 1 = 1.34539 loss) +I0410 14:19:30.405987 18414 sgd_solver.cpp:105] Iteration 6672, lr = 0.00266701 +I0410 14:19:31.721521 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:19:35.318152 18414 solver.cpp:218] Iteration 6684 (2.44298 iter/s, 4.91203s/12 iters), loss = 1.2975 +I0410 14:19:35.318199 18414 solver.cpp:237] Train net output #0: loss = 1.2975 (* 1 = 1.2975 loss) +I0410 14:19:35.318218 18414 sgd_solver.cpp:105] Iteration 6684, lr = 0.00266067 +I0410 14:19:40.228660 18414 solver.cpp:218] Iteration 6696 (2.44385 iter/s, 4.91029s/12 iters), loss = 1.11044 +I0410 14:19:40.230110 18414 solver.cpp:237] Train net output #0: loss = 1.11044 (* 1 = 1.11044 loss) +I0410 14:19:40.230120 18414 sgd_solver.cpp:105] Iteration 6696, lr = 0.00265436 +I0410 14:19:45.136044 18414 solver.cpp:218] Iteration 6708 (2.4461 iter/s, 4.90577s/12 iters), loss = 1.17301 +I0410 14:19:45.136096 18414 solver.cpp:237] Train net output #0: loss = 1.17301 (* 1 = 1.17301 loss) +I0410 14:19:45.136107 18414 sgd_solver.cpp:105] Iteration 6708, lr = 0.00264805 +I0410 14:19:50.081454 18414 solver.cpp:218] Iteration 6720 (2.4266 iter/s, 4.94519s/12 iters), loss = 1.2252 +I0410 14:19:50.081509 18414 solver.cpp:237] Train net output #0: loss = 1.2252 (* 1 = 1.2252 loss) +I0410 14:19:50.081522 18414 sgd_solver.cpp:105] Iteration 6720, lr = 0.00264177 +I0410 14:19:54.557574 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6732.caffemodel +I0410 14:19:54.869081 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6732.solverstate +I0410 14:19:55.083308 18414 solver.cpp:330] Iteration 6732, Testing net (#0) +I0410 14:19:55.083340 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:19:56.916867 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:19:59.571962 18414 solver.cpp:397] Test net output #0: accuracy = 0.496324 +I0410 14:19:59.572005 18414 solver.cpp:397] Test net output #1: loss = 1.91183 (* 1 = 1.91183 loss) +I0410 14:19:59.655021 18414 solver.cpp:218] Iteration 6732 (1.2535 iter/s, 9.5732s/12 iters), loss = 1.4546 +I0410 14:19:59.655076 18414 solver.cpp:237] Train net output #0: loss = 1.4546 (* 1 = 1.4546 loss) +I0410 14:19:59.655087 18414 sgd_solver.cpp:105] Iteration 6732, lr = 0.0026355 +I0410 14:20:04.117091 18414 solver.cpp:218] Iteration 6744 (2.68946 iter/s, 4.46186s/12 iters), loss = 1.09215 +I0410 14:20:04.117161 18414 solver.cpp:237] Train net output #0: loss = 1.09215 (* 1 = 1.09215 loss) +I0410 14:20:04.117179 18414 sgd_solver.cpp:105] Iteration 6744, lr = 0.00262924 +I0410 14:20:09.228328 18414 solver.cpp:218] Iteration 6756 (2.34788 iter/s, 5.111s/12 iters), loss = 1.16358 +I0410 14:20:09.228387 18414 solver.cpp:237] Train net output #0: loss = 1.16358 (* 1 = 1.16358 loss) +I0410 14:20:09.228400 18414 sgd_solver.cpp:105] Iteration 6756, lr = 0.002623 +I0410 14:20:14.221498 18414 solver.cpp:218] Iteration 6768 (2.40339 iter/s, 4.99294s/12 iters), loss = 1.31375 +I0410 14:20:14.221668 18414 solver.cpp:237] Train net output #0: loss = 1.31375 (* 1 = 1.31375 loss) +I0410 14:20:14.221683 18414 sgd_solver.cpp:105] Iteration 6768, lr = 0.00261677 +I0410 14:20:17.662461 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:19.185633 18414 solver.cpp:218] Iteration 6780 (2.4175 iter/s, 4.9638s/12 iters), loss = 1.15005 +I0410 14:20:19.185679 18414 solver.cpp:237] Train net output #0: loss = 1.15005 (* 1 = 1.15005 loss) +I0410 14:20:19.185688 18414 sgd_solver.cpp:105] Iteration 6780, lr = 0.00261056 +I0410 14:20:24.096360 18414 solver.cpp:218] Iteration 6792 (2.44374 iter/s, 4.91051s/12 iters), loss = 1.42679 +I0410 14:20:24.096410 18414 solver.cpp:237] Train net output #0: loss = 1.42679 (* 1 = 1.42679 loss) +I0410 14:20:24.096421 18414 sgd_solver.cpp:105] Iteration 6792, lr = 0.00260436 +I0410 14:20:29.059020 18414 solver.cpp:218] Iteration 6804 (2.41817 iter/s, 4.96243s/12 iters), loss = 1.31804 +I0410 14:20:29.059082 18414 solver.cpp:237] Train net output #0: loss = 1.31804 (* 1 = 1.31804 loss) +I0410 14:20:29.059098 18414 sgd_solver.cpp:105] Iteration 6804, lr = 0.00259817 +I0410 14:20:33.925076 18414 solver.cpp:218] Iteration 6816 (2.46617 iter/s, 4.86584s/12 iters), loss = 1.17721 +I0410 14:20:33.925120 18414 solver.cpp:237] Train net output #0: loss = 1.17721 (* 1 = 1.17721 loss) +I0410 14:20:33.925130 18414 sgd_solver.cpp:105] Iteration 6816, lr = 0.00259201 +I0410 14:20:38.866174 18414 solver.cpp:218] Iteration 6828 (2.42872 iter/s, 4.94088s/12 iters), loss = 1.17337 +I0410 14:20:38.866225 18414 solver.cpp:237] Train net output #0: loss = 1.17337 (* 1 = 1.17337 loss) +I0410 14:20:38.866235 18414 sgd_solver.cpp:105] Iteration 6828, lr = 0.00258585 +I0410 14:20:40.858242 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6834.caffemodel +I0410 14:20:41.656901 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6834.solverstate +I0410 14:20:41.917449 18414 solver.cpp:330] Iteration 6834, Testing net (#0) +I0410 14:20:41.917474 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:20:43.685629 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:46.412037 18414 solver.cpp:397] Test net output #0: accuracy = 0.490196 +I0410 14:20:46.412147 18414 solver.cpp:397] Test net output #1: loss = 1.93653 (* 1 = 1.93653 loss) +I0410 14:20:48.374877 18414 solver.cpp:218] Iteration 6840 (1.26205 iter/s, 9.50834s/12 iters), loss = 1.38677 +I0410 14:20:48.374930 18414 solver.cpp:237] Train net output #0: loss = 1.38677 (* 1 = 1.38677 loss) +I0410 14:20:48.374941 18414 sgd_solver.cpp:105] Iteration 6840, lr = 0.00257971 +I0410 14:20:53.452790 18414 solver.cpp:218] Iteration 6852 (2.36328 iter/s, 5.07768s/12 iters), loss = 1.49923 +I0410 14:20:53.452853 18414 solver.cpp:237] Train net output #0: loss = 1.49923 (* 1 = 1.49923 loss) +I0410 14:20:53.452867 18414 sgd_solver.cpp:105] Iteration 6852, lr = 0.00257359 +I0410 14:20:58.314016 18414 solver.cpp:218] Iteration 6864 (2.46863 iter/s, 4.861s/12 iters), loss = 1.08734 +I0410 14:20:58.314074 18414 solver.cpp:237] Train net output #0: loss = 1.08734 (* 1 = 1.08734 loss) +I0410 14:20:58.314086 18414 sgd_solver.cpp:105] Iteration 6864, lr = 0.00256748 +I0410 14:21:03.263959 18414 solver.cpp:218] Iteration 6876 (2.42438 iter/s, 4.94972s/12 iters), loss = 1.23427 +I0410 14:21:03.264008 18414 solver.cpp:237] Train net output #0: loss = 1.23427 (* 1 = 1.23427 loss) +I0410 14:21:03.264017 18414 sgd_solver.cpp:105] Iteration 6876, lr = 0.00256138 +I0410 14:21:03.863543 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:08.147756 18414 solver.cpp:218] Iteration 6888 (2.45721 iter/s, 4.88358s/12 iters), loss = 1.11875 +I0410 14:21:08.147801 18414 solver.cpp:237] Train net output #0: loss = 1.11875 (* 1 = 1.11875 loss) +I0410 14:21:08.147810 18414 sgd_solver.cpp:105] Iteration 6888, lr = 0.0025553 +I0410 14:21:13.219282 18414 solver.cpp:218] Iteration 6900 (2.36625 iter/s, 5.07131s/12 iters), loss = 1.1107 +I0410 14:21:13.219336 18414 solver.cpp:237] Train net output #0: loss = 1.1107 (* 1 = 1.1107 loss) +I0410 14:21:13.219348 18414 sgd_solver.cpp:105] Iteration 6900, lr = 0.00254923 +I0410 14:21:18.170922 18414 solver.cpp:218] Iteration 6912 (2.42355 iter/s, 4.95141s/12 iters), loss = 0.918501 +I0410 14:21:18.171077 18414 solver.cpp:237] Train net output #0: loss = 0.918501 (* 1 = 0.918501 loss) +I0410 14:21:18.171092 18414 sgd_solver.cpp:105] Iteration 6912, lr = 0.00254318 +I0410 14:21:23.066586 18414 solver.cpp:218] Iteration 6924 (2.45131 iter/s, 4.89535s/12 iters), loss = 1.14167 +I0410 14:21:23.066634 18414 solver.cpp:237] Train net output #0: loss = 1.14167 (* 1 = 1.14167 loss) +I0410 14:21:23.066645 18414 sgd_solver.cpp:105] Iteration 6924, lr = 0.00253714 +I0410 14:21:27.529232 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6936.caffemodel +I0410 14:21:27.835186 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6936.solverstate +I0410 14:21:28.045783 18414 solver.cpp:330] Iteration 6936, Testing net (#0) +I0410 14:21:28.045807 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:21:28.315590 18414 blocking_queue.cpp:49] Waiting for data +I0410 14:21:29.781038 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:32.495548 18414 solver.cpp:397] Test net output #0: accuracy = 0.499387 +I0410 14:21:32.495597 18414 solver.cpp:397] Test net output #1: loss = 2.00999 (* 1 = 2.00999 loss) +I0410 14:21:32.578341 18414 solver.cpp:218] Iteration 6936 (1.26164 iter/s, 9.51139s/12 iters), loss = 1.39282 +I0410 14:21:32.578385 18414 solver.cpp:237] Train net output #0: loss = 1.39282 (* 1 = 1.39282 loss) +I0410 14:21:32.578397 18414 sgd_solver.cpp:105] Iteration 6936, lr = 0.00253112 +I0410 14:21:36.867779 18414 solver.cpp:218] Iteration 6948 (2.7977 iter/s, 4.28924s/12 iters), loss = 1.38134 +I0410 14:21:36.867825 18414 solver.cpp:237] Train net output #0: loss = 1.38134 (* 1 = 1.38134 loss) +I0410 14:21:36.867835 18414 sgd_solver.cpp:105] Iteration 6948, lr = 0.00252511 +I0410 14:21:41.811920 18414 solver.cpp:218] Iteration 6960 (2.42722 iter/s, 4.94393s/12 iters), loss = 1.03745 +I0410 14:21:41.811965 18414 solver.cpp:237] Train net output #0: loss = 1.03745 (* 1 = 1.03745 loss) +I0410 14:21:41.811975 18414 sgd_solver.cpp:105] Iteration 6960, lr = 0.00251911 +I0410 14:21:46.788663 18414 solver.cpp:218] Iteration 6972 (2.41132 iter/s, 4.97653s/12 iters), loss = 1.33636 +I0410 14:21:46.788712 18414 solver.cpp:237] Train net output #0: loss = 1.33636 (* 1 = 1.33636 loss) +I0410 14:21:46.788722 18414 sgd_solver.cpp:105] Iteration 6972, lr = 0.00251313 +I0410 14:21:49.503465 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:51.721760 18414 solver.cpp:218] Iteration 6984 (2.43266 iter/s, 4.93288s/12 iters), loss = 1.06884 +I0410 14:21:51.721803 18414 solver.cpp:237] Train net output #0: loss = 1.06884 (* 1 = 1.06884 loss) +I0410 14:21:51.721813 18414 sgd_solver.cpp:105] Iteration 6984, lr = 0.00250717 +I0410 14:21:56.660336 18414 solver.cpp:218] Iteration 6996 (2.42996 iter/s, 4.93836s/12 iters), loss = 1.09023 +I0410 14:21:56.660392 18414 solver.cpp:237] Train net output #0: loss = 1.09023 (* 1 = 1.09023 loss) +I0410 14:21:56.660405 18414 sgd_solver.cpp:105] Iteration 6996, lr = 0.00250121 +I0410 14:22:01.597285 18414 solver.cpp:218] Iteration 7008 (2.43076 iter/s, 4.93672s/12 iters), loss = 0.957894 +I0410 14:22:01.597332 18414 solver.cpp:237] Train net output #0: loss = 0.957894 (* 1 = 0.957894 loss) +I0410 14:22:01.597340 18414 sgd_solver.cpp:105] Iteration 7008, lr = 0.00249528 +I0410 14:22:06.515432 18414 solver.cpp:218] Iteration 7020 (2.44005 iter/s, 4.91794s/12 iters), loss = 1.00498 +I0410 14:22:06.515470 18414 solver.cpp:237] Train net output #0: loss = 1.00498 (* 1 = 1.00498 loss) +I0410 14:22:06.515480 18414 sgd_solver.cpp:105] Iteration 7020, lr = 0.00248935 +I0410 14:22:11.406440 18414 solver.cpp:218] Iteration 7032 (2.45359 iter/s, 4.89079s/12 iters), loss = 1.33821 +I0410 14:22:11.406497 18414 solver.cpp:237] Train net output #0: loss = 1.33821 (* 1 = 1.33821 loss) +I0410 14:22:11.406509 18414 sgd_solver.cpp:105] Iteration 7032, lr = 0.00248344 +I0410 14:22:13.400234 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7038.caffemodel +I0410 14:22:13.689800 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7038.solverstate +I0410 14:22:13.885665 18414 solver.cpp:330] Iteration 7038, Testing net (#0) +I0410 14:22:13.885685 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:22:15.581475 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:22:18.331688 18414 solver.cpp:397] Test net output #0: accuracy = 0.501225 +I0410 14:22:18.331732 18414 solver.cpp:397] Test net output #1: loss = 1.95722 (* 1 = 1.95722 loss) +I0410 14:22:20.226382 18414 solver.cpp:218] Iteration 7044 (1.36061 iter/s, 8.8196s/12 iters), loss = 1.18309 +I0410 14:22:20.226485 18414 solver.cpp:237] Train net output #0: loss = 1.18309 (* 1 = 1.18309 loss) +I0410 14:22:20.226495 18414 sgd_solver.cpp:105] Iteration 7044, lr = 0.00247755 +I0410 14:22:25.136857 18414 solver.cpp:218] Iteration 7056 (2.44389 iter/s, 4.9102s/12 iters), loss = 1.34916 +I0410 14:22:25.136902 18414 solver.cpp:237] Train net output #0: loss = 1.34916 (* 1 = 1.34916 loss) +I0410 14:22:25.136911 18414 sgd_solver.cpp:105] Iteration 7056, lr = 0.00247166 +I0410 14:22:30.089787 18414 solver.cpp:218] Iteration 7068 (2.42291 iter/s, 4.95271s/12 iters), loss = 1.09169 +I0410 14:22:30.089840 18414 solver.cpp:237] Train net output #0: loss = 1.09169 (* 1 = 1.09169 loss) +I0410 14:22:30.089854 18414 sgd_solver.cpp:105] Iteration 7068, lr = 0.0024658 +I0410 14:22:34.896253 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:22:35.003645 18414 solver.cpp:218] Iteration 7080 (2.44218 iter/s, 4.91364s/12 iters), loss = 1.25456 +I0410 14:22:35.003687 18414 solver.cpp:237] Train net output #0: loss = 1.25456 (* 1 = 1.25456 loss) +I0410 14:22:35.003696 18414 sgd_solver.cpp:105] Iteration 7080, lr = 0.00245994 +I0410 14:22:40.035516 18414 solver.cpp:218] Iteration 7092 (2.3849 iter/s, 5.03166s/12 iters), loss = 1.26742 +I0410 14:22:40.035547 18414 solver.cpp:237] Train net output #0: loss = 1.26742 (* 1 = 1.26742 loss) +I0410 14:22:40.035554 18414 sgd_solver.cpp:105] Iteration 7092, lr = 0.0024541 +I0410 14:22:44.981288 18414 solver.cpp:218] Iteration 7104 (2.42641 iter/s, 4.94557s/12 iters), loss = 1.07058 +I0410 14:22:44.981341 18414 solver.cpp:237] Train net output #0: loss = 1.07058 (* 1 = 1.07058 loss) +I0410 14:22:44.981354 18414 sgd_solver.cpp:105] Iteration 7104, lr = 0.00244827 +I0410 14:22:49.913674 18414 solver.cpp:218] Iteration 7116 (2.43301 iter/s, 4.93217s/12 iters), loss = 0.875932 +I0410 14:22:49.913724 18414 solver.cpp:237] Train net output #0: loss = 0.875932 (* 1 = 0.875932 loss) +I0410 14:22:49.913735 18414 sgd_solver.cpp:105] Iteration 7116, lr = 0.00244246 +I0410 14:22:54.843588 18414 solver.cpp:218] Iteration 7128 (2.43423 iter/s, 4.92969s/12 iters), loss = 1.22995 +I0410 14:22:54.843698 18414 solver.cpp:237] Train net output #0: loss = 1.22995 (* 1 = 1.22995 loss) +I0410 14:22:54.843711 18414 sgd_solver.cpp:105] Iteration 7128, lr = 0.00243666 +I0410 14:22:59.319268 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7140.caffemodel +I0410 14:22:59.630162 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7140.solverstate +I0410 14:22:59.842388 18414 solver.cpp:330] Iteration 7140, Testing net (#0) +I0410 14:22:59.842429 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:23:01.618628 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:04.441291 18414 solver.cpp:397] Test net output #0: accuracy = 0.522059 +I0410 14:23:04.441340 18414 solver.cpp:397] Test net output #1: loss = 1.91701 (* 1 = 1.91701 loss) +I0410 14:23:04.524240 18414 solver.cpp:218] Iteration 7140 (1.23964 iter/s, 9.68023s/12 iters), loss = 1.19068 +I0410 14:23:04.524294 18414 solver.cpp:237] Train net output #0: loss = 1.19068 (* 1 = 1.19068 loss) +I0410 14:23:04.524307 18414 sgd_solver.cpp:105] Iteration 7140, lr = 0.00243088 +I0410 14:23:08.866616 18414 solver.cpp:218] Iteration 7152 (2.76359 iter/s, 4.34218s/12 iters), loss = 1.20144 +I0410 14:23:08.866658 18414 solver.cpp:237] Train net output #0: loss = 1.20144 (* 1 = 1.20144 loss) +I0410 14:23:08.866667 18414 sgd_solver.cpp:105] Iteration 7152, lr = 0.00242511 +I0410 14:23:13.863247 18414 solver.cpp:218] Iteration 7164 (2.40172 iter/s, 4.99641s/12 iters), loss = 1.12621 +I0410 14:23:13.863307 18414 solver.cpp:237] Train net output #0: loss = 1.12621 (* 1 = 1.12621 loss) +I0410 14:23:13.863319 18414 sgd_solver.cpp:105] Iteration 7164, lr = 0.00241935 +I0410 14:23:18.814846 18414 solver.cpp:218] Iteration 7176 (2.42357 iter/s, 4.95137s/12 iters), loss = 1.05047 +I0410 14:23:18.814905 18414 solver.cpp:237] Train net output #0: loss = 1.05047 (* 1 = 1.05047 loss) +I0410 14:23:18.814918 18414 sgd_solver.cpp:105] Iteration 7176, lr = 0.0024136 +I0410 14:23:20.890049 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:23.948882 18414 solver.cpp:218] Iteration 7188 (2.33745 iter/s, 5.13381s/12 iters), loss = 1.06799 +I0410 14:23:23.948936 18414 solver.cpp:237] Train net output #0: loss = 1.06799 (* 1 = 1.06799 loss) +I0410 14:23:23.948948 18414 sgd_solver.cpp:105] Iteration 7188, lr = 0.00240787 +I0410 14:23:29.053592 18414 solver.cpp:218] Iteration 7200 (2.35087 iter/s, 5.10449s/12 iters), loss = 0.994151 +I0410 14:23:29.053694 18414 solver.cpp:237] Train net output #0: loss = 0.994151 (* 1 = 0.994151 loss) +I0410 14:23:29.053704 18414 sgd_solver.cpp:105] Iteration 7200, lr = 0.00240216 +I0410 14:23:33.970693 18414 solver.cpp:218] Iteration 7212 (2.4406 iter/s, 4.91683s/12 iters), loss = 1.1656 +I0410 14:23:33.970748 18414 solver.cpp:237] Train net output #0: loss = 1.1656 (* 1 = 1.1656 loss) +I0410 14:23:33.970762 18414 sgd_solver.cpp:105] Iteration 7212, lr = 0.00239645 +I0410 14:23:39.039124 18414 solver.cpp:218] Iteration 7224 (2.3677 iter/s, 5.0682s/12 iters), loss = 1.18154 +I0410 14:23:39.039181 18414 solver.cpp:237] Train net output #0: loss = 1.18154 (* 1 = 1.18154 loss) +I0410 14:23:39.039196 18414 sgd_solver.cpp:105] Iteration 7224, lr = 0.00239076 +I0410 14:23:43.986434 18414 solver.cpp:218] Iteration 7236 (2.42567 iter/s, 4.94708s/12 iters), loss = 1.14384 +I0410 14:23:43.986495 18414 solver.cpp:237] Train net output #0: loss = 1.14384 (* 1 = 1.14384 loss) +I0410 14:23:43.986507 18414 sgd_solver.cpp:105] Iteration 7236, lr = 0.00238509 +I0410 14:23:46.017462 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7242.caffemodel +I0410 14:23:46.544294 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7242.solverstate +I0410 14:23:46.789932 18414 solver.cpp:330] Iteration 7242, Testing net (#0) +I0410 14:23:46.789974 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:23:48.408964 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:51.256851 18414 solver.cpp:397] Test net output #0: accuracy = 0.529412 +I0410 14:23:51.256894 18414 solver.cpp:397] Test net output #1: loss = 1.89503 (* 1 = 1.89503 loss) +I0410 14:23:53.196017 18414 solver.cpp:218] Iteration 7248 (1.30304 iter/s, 9.20922s/12 iters), loss = 1.22897 +I0410 14:23:53.196071 18414 solver.cpp:237] Train net output #0: loss = 1.22897 (* 1 = 1.22897 loss) +I0410 14:23:53.196082 18414 sgd_solver.cpp:105] Iteration 7248, lr = 0.00237942 +I0410 14:23:58.156733 18414 solver.cpp:218] Iteration 7260 (2.41911 iter/s, 4.9605s/12 iters), loss = 1.17619 +I0410 14:23:58.156775 18414 solver.cpp:237] Train net output #0: loss = 1.17619 (* 1 = 1.17619 loss) +I0410 14:23:58.156783 18414 sgd_solver.cpp:105] Iteration 7260, lr = 0.00237378 +I0410 14:24:03.168313 18414 solver.cpp:218] Iteration 7272 (2.39456 iter/s, 5.01137s/12 iters), loss = 1.25402 +I0410 14:24:03.168440 18414 solver.cpp:237] Train net output #0: loss = 1.25402 (* 1 = 1.25402 loss) +I0410 14:24:03.168452 18414 sgd_solver.cpp:105] Iteration 7272, lr = 0.00236814 +I0410 14:24:07.382972 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:08.129170 18414 solver.cpp:218] Iteration 7284 (2.41908 iter/s, 4.96056s/12 iters), loss = 1.18268 +I0410 14:24:08.129220 18414 solver.cpp:237] Train net output #0: loss = 1.18268 (* 1 = 1.18268 loss) +I0410 14:24:08.129230 18414 sgd_solver.cpp:105] Iteration 7284, lr = 0.00236252 +I0410 14:24:13.103788 18414 solver.cpp:218] Iteration 7296 (2.41235 iter/s, 4.9744s/12 iters), loss = 1.10469 +I0410 14:24:13.103832 18414 solver.cpp:237] Train net output #0: loss = 1.10469 (* 1 = 1.10469 loss) +I0410 14:24:13.103842 18414 sgd_solver.cpp:105] Iteration 7296, lr = 0.00235691 +I0410 14:24:17.986011 18414 solver.cpp:218] Iteration 7308 (2.458 iter/s, 4.88201s/12 iters), loss = 1.00048 +I0410 14:24:17.986055 18414 solver.cpp:237] Train net output #0: loss = 1.00048 (* 1 = 1.00048 loss) +I0410 14:24:17.986064 18414 sgd_solver.cpp:105] Iteration 7308, lr = 0.00235131 +I0410 14:24:22.926424 18414 solver.cpp:218] Iteration 7320 (2.42905 iter/s, 4.9402s/12 iters), loss = 1.03816 +I0410 14:24:22.926483 18414 solver.cpp:237] Train net output #0: loss = 1.03816 (* 1 = 1.03816 loss) +I0410 14:24:22.926496 18414 sgd_solver.cpp:105] Iteration 7320, lr = 0.00234573 +I0410 14:24:27.947861 18414 solver.cpp:218] Iteration 7332 (2.38986 iter/s, 5.02121s/12 iters), loss = 1.16795 +I0410 14:24:27.947911 18414 solver.cpp:237] Train net output #0: loss = 1.16795 (* 1 = 1.16795 loss) +I0410 14:24:27.947921 18414 sgd_solver.cpp:105] Iteration 7332, lr = 0.00234016 +I0410 14:24:32.396659 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7344.caffemodel +I0410 14:24:32.702167 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7344.solverstate +I0410 14:24:32.911664 18414 solver.cpp:330] Iteration 7344, Testing net (#0) +I0410 14:24:32.911695 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:24:34.479331 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:37.347826 18414 solver.cpp:397] Test net output #0: accuracy = 0.518382 +I0410 14:24:37.347874 18414 solver.cpp:397] Test net output #1: loss = 1.95744 (* 1 = 1.95744 loss) +I0410 14:24:37.430824 18414 solver.cpp:218] Iteration 7344 (1.26548 iter/s, 9.48259s/12 iters), loss = 1.09488 +I0410 14:24:37.430883 18414 solver.cpp:237] Train net output #0: loss = 1.09488 (* 1 = 1.09488 loss) +I0410 14:24:37.430900 18414 sgd_solver.cpp:105] Iteration 7344, lr = 0.0023346 +I0410 14:24:41.521733 18414 solver.cpp:218] Iteration 7356 (2.93348 iter/s, 4.09071s/12 iters), loss = 1.11793 +I0410 14:24:41.521790 18414 solver.cpp:237] Train net output #0: loss = 1.11793 (* 1 = 1.11793 loss) +I0410 14:24:41.521802 18414 sgd_solver.cpp:105] Iteration 7356, lr = 0.00232906 +I0410 14:24:46.403319 18414 solver.cpp:218] Iteration 7368 (2.45832 iter/s, 4.88138s/12 iters), loss = 1.17063 +I0410 14:24:46.403370 18414 solver.cpp:237] Train net output #0: loss = 1.17063 (* 1 = 1.17063 loss) +I0410 14:24:46.403383 18414 sgd_solver.cpp:105] Iteration 7368, lr = 0.00232353 +I0410 14:24:51.352644 18414 solver.cpp:218] Iteration 7380 (2.42465 iter/s, 4.94917s/12 iters), loss = 1.12744 +I0410 14:24:51.352696 18414 solver.cpp:237] Train net output #0: loss = 1.12744 (* 1 = 1.12744 loss) +I0410 14:24:51.352708 18414 sgd_solver.cpp:105] Iteration 7380, lr = 0.00231802 +I0410 14:24:52.747848 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:56.334121 18414 solver.cpp:218] Iteration 7392 (2.409 iter/s, 4.98132s/12 iters), loss = 1.11898 +I0410 14:24:56.334178 18414 solver.cpp:237] Train net output #0: loss = 1.11898 (* 1 = 1.11898 loss) +I0410 14:24:56.334192 18414 sgd_solver.cpp:105] Iteration 7392, lr = 0.00231251 +I0410 14:25:01.261662 18414 solver.cpp:218] Iteration 7404 (2.43537 iter/s, 4.92738s/12 iters), loss = 1.13995 +I0410 14:25:01.261713 18414 solver.cpp:237] Train net output #0: loss = 1.13995 (* 1 = 1.13995 loss) +I0410 14:25:01.261726 18414 sgd_solver.cpp:105] Iteration 7404, lr = 0.00230702 +I0410 14:25:06.463400 18414 solver.cpp:218] Iteration 7416 (2.307 iter/s, 5.20157s/12 iters), loss = 0.988648 +I0410 14:25:06.463562 18414 solver.cpp:237] Train net output #0: loss = 0.988648 (* 1 = 0.988648 loss) +I0410 14:25:06.463577 18414 sgd_solver.cpp:105] Iteration 7416, lr = 0.00230154 +I0410 14:25:11.500814 18414 solver.cpp:218] Iteration 7428 (2.3823 iter/s, 5.03715s/12 iters), loss = 0.963934 +I0410 14:25:11.500859 18414 solver.cpp:237] Train net output #0: loss = 0.963934 (* 1 = 0.963934 loss) +I0410 14:25:11.500869 18414 sgd_solver.cpp:105] Iteration 7428, lr = 0.00229608 +I0410 14:25:16.409875 18414 solver.cpp:218] Iteration 7440 (2.44454 iter/s, 4.9089s/12 iters), loss = 1.10213 +I0410 14:25:16.409926 18414 solver.cpp:237] Train net output #0: loss = 1.10213 (* 1 = 1.10213 loss) +I0410 14:25:16.409940 18414 sgd_solver.cpp:105] Iteration 7440, lr = 0.00229063 +I0410 14:25:18.411612 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7446.caffemodel +I0410 14:25:18.709646 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7446.solverstate +I0410 14:25:18.908303 18414 solver.cpp:330] Iteration 7446, Testing net (#0) +I0410 14:25:18.908334 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:25:20.520820 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:25:23.510672 18414 solver.cpp:397] Test net output #0: accuracy = 0.522672 +I0410 14:25:23.510704 18414 solver.cpp:397] Test net output #1: loss = 1.90359 (* 1 = 1.90359 loss) +I0410 14:25:25.326786 18414 solver.cpp:218] Iteration 7452 (1.34579 iter/s, 8.91667s/12 iters), loss = 1.14832 +I0410 14:25:25.326851 18414 solver.cpp:237] Train net output #0: loss = 1.14832 (* 1 = 1.14832 loss) +I0410 14:25:25.326864 18414 sgd_solver.cpp:105] Iteration 7452, lr = 0.00228519 +I0410 14:25:30.243257 18414 solver.cpp:218] Iteration 7464 (2.44086 iter/s, 4.9163s/12 iters), loss = 1.13475 +I0410 14:25:30.243306 18414 solver.cpp:237] Train net output #0: loss = 1.13475 (* 1 = 1.13475 loss) +I0410 14:25:30.243316 18414 sgd_solver.cpp:105] Iteration 7464, lr = 0.00227976 +I0410 14:25:35.237241 18414 solver.cpp:218] Iteration 7476 (2.40297 iter/s, 4.99382s/12 iters), loss = 1.06648 +I0410 14:25:35.237294 18414 solver.cpp:237] Train net output #0: loss = 1.06648 (* 1 = 1.06648 loss) +I0410 14:25:35.237306 18414 sgd_solver.cpp:105] Iteration 7476, lr = 0.00227435 +I0410 14:25:38.715538 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:25:40.174268 18414 solver.cpp:218] Iteration 7488 (2.43069 iter/s, 4.93686s/12 iters), loss = 0.984849 +I0410 14:25:40.174320 18414 solver.cpp:237] Train net output #0: loss = 0.984849 (* 1 = 0.984849 loss) +I0410 14:25:40.174335 18414 sgd_solver.cpp:105] Iteration 7488, lr = 0.00226895 +I0410 14:25:45.108705 18414 solver.cpp:218] Iteration 7500 (2.43197 iter/s, 4.93427s/12 iters), loss = 1.06416 +I0410 14:25:45.108758 18414 solver.cpp:237] Train net output #0: loss = 1.06416 (* 1 = 1.06416 loss) +I0410 14:25:45.108772 18414 sgd_solver.cpp:105] Iteration 7500, lr = 0.00226357 +I0410 14:25:50.119803 18414 solver.cpp:218] Iteration 7512 (2.39477 iter/s, 5.01093s/12 iters), loss = 1.03451 +I0410 14:25:50.119863 18414 solver.cpp:237] Train net output #0: loss = 1.03451 (* 1 = 1.03451 loss) +I0410 14:25:50.119874 18414 sgd_solver.cpp:105] Iteration 7512, lr = 0.00225819 +I0410 14:25:55.091442 18414 solver.cpp:218] Iteration 7524 (2.41377 iter/s, 4.97147s/12 iters), loss = 1.12827 +I0410 14:25:55.091488 18414 solver.cpp:237] Train net output #0: loss = 1.12827 (* 1 = 1.12827 loss) +I0410 14:25:55.091500 18414 sgd_solver.cpp:105] Iteration 7524, lr = 0.00225283 +I0410 14:26:00.081185 18414 solver.cpp:218] Iteration 7536 (2.40501 iter/s, 4.98958s/12 iters), loss = 1.1441 +I0410 14:26:00.081243 18414 solver.cpp:237] Train net output #0: loss = 1.1441 (* 1 = 1.1441 loss) +I0410 14:26:00.081255 18414 sgd_solver.cpp:105] Iteration 7536, lr = 0.00224748 +I0410 14:26:04.622696 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7548.caffemodel +I0410 14:26:04.962957 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7548.solverstate +I0410 14:26:05.175971 18414 solver.cpp:330] Iteration 7548, Testing net (#0) +I0410 14:26:05.176000 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:26:06.719589 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:09.818094 18414 solver.cpp:397] Test net output #0: accuracy = 0.510417 +I0410 14:26:09.818208 18414 solver.cpp:397] Test net output #1: loss = 1.99745 (* 1 = 1.99745 loss) +I0410 14:26:09.902570 18414 solver.cpp:218] Iteration 7548 (1.22186 iter/s, 9.82111s/12 iters), loss = 1.12592 +I0410 14:26:09.902632 18414 solver.cpp:237] Train net output #0: loss = 1.12592 (* 1 = 1.12592 loss) +I0410 14:26:09.902647 18414 sgd_solver.cpp:105] Iteration 7548, lr = 0.00224215 +I0410 14:26:14.093571 18414 solver.cpp:218] Iteration 7560 (2.86339 iter/s, 4.19084s/12 iters), loss = 1.26234 +I0410 14:26:14.093626 18414 solver.cpp:237] Train net output #0: loss = 1.26234 (* 1 = 1.26234 loss) +I0410 14:26:14.093637 18414 sgd_solver.cpp:105] Iteration 7560, lr = 0.00223682 +I0410 14:26:19.262477 18414 solver.cpp:218] Iteration 7572 (2.32166 iter/s, 5.16872s/12 iters), loss = 0.789782 +I0410 14:26:19.262534 18414 solver.cpp:237] Train net output #0: loss = 0.789782 (* 1 = 0.789782 loss) +I0410 14:26:19.262547 18414 sgd_solver.cpp:105] Iteration 7572, lr = 0.00223151 +I0410 14:26:24.173043 18414 solver.cpp:218] Iteration 7584 (2.4438 iter/s, 4.91039s/12 iters), loss = 0.979684 +I0410 14:26:24.173094 18414 solver.cpp:237] Train net output #0: loss = 0.979684 (* 1 = 0.979684 loss) +I0410 14:26:24.173105 18414 sgd_solver.cpp:105] Iteration 7584, lr = 0.00222621 +I0410 14:26:24.803530 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:29.103727 18414 solver.cpp:218] Iteration 7596 (2.43382 iter/s, 4.93052s/12 iters), loss = 0.939267 +I0410 14:26:29.103771 18414 solver.cpp:237] Train net output #0: loss = 0.939267 (* 1 = 0.939267 loss) +I0410 14:26:29.103782 18414 sgd_solver.cpp:105] Iteration 7596, lr = 0.00222093 +I0410 14:26:33.993053 18414 solver.cpp:218] Iteration 7608 (2.45441 iter/s, 4.88916s/12 iters), loss = 0.937316 +I0410 14:26:33.993113 18414 solver.cpp:237] Train net output #0: loss = 0.937316 (* 1 = 0.937316 loss) +I0410 14:26:33.993126 18414 sgd_solver.cpp:105] Iteration 7608, lr = 0.00221565 +I0410 14:26:38.932235 18414 solver.cpp:218] Iteration 7620 (2.42964 iter/s, 4.93901s/12 iters), loss = 0.847892 +I0410 14:26:38.932286 18414 solver.cpp:237] Train net output #0: loss = 0.847892 (* 1 = 0.847892 loss) +I0410 14:26:38.932298 18414 sgd_solver.cpp:105] Iteration 7620, lr = 0.00221039 +I0410 14:26:39.688084 18414 blocking_queue.cpp:49] Waiting for data +I0410 14:26:43.831990 18414 solver.cpp:218] Iteration 7632 (2.44919 iter/s, 4.89958s/12 iters), loss = 1.15856 +I0410 14:26:43.832116 18414 solver.cpp:237] Train net output #0: loss = 1.15856 (* 1 = 1.15856 loss) +I0410 14:26:43.832129 18414 sgd_solver.cpp:105] Iteration 7632, lr = 0.00220515 +I0410 14:26:48.787998 18414 solver.cpp:218] Iteration 7644 (2.42142 iter/s, 4.95576s/12 iters), loss = 1.18854 +I0410 14:26:48.788050 18414 solver.cpp:237] Train net output #0: loss = 1.18854 (* 1 = 1.18854 loss) +I0410 14:26:48.788064 18414 sgd_solver.cpp:105] Iteration 7644, lr = 0.00219991 +I0410 14:26:50.789525 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7650.caffemodel +I0410 14:26:51.238842 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7650.solverstate +I0410 14:26:51.458547 18414 solver.cpp:330] Iteration 7650, Testing net (#0) +I0410 14:26:51.458580 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:26:52.930001 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:55.920578 18414 solver.cpp:397] Test net output #0: accuracy = 0.519608 +I0410 14:26:55.920615 18414 solver.cpp:397] Test net output #1: loss = 1.94239 (* 1 = 1.94239 loss) +I0410 14:26:57.820726 18414 solver.cpp:218] Iteration 7656 (1.32854 iter/s, 9.03247s/12 iters), loss = 1.07313 +I0410 14:26:57.820771 18414 solver.cpp:237] Train net output #0: loss = 1.07313 (* 1 = 1.07313 loss) +I0410 14:26:57.820780 18414 sgd_solver.cpp:105] Iteration 7656, lr = 0.00219469 +I0410 14:27:02.835763 18414 solver.cpp:218] Iteration 7668 (2.39288 iter/s, 5.01487s/12 iters), loss = 0.834537 +I0410 14:27:02.835811 18414 solver.cpp:237] Train net output #0: loss = 0.834537 (* 1 = 0.834537 loss) +I0410 14:27:02.835820 18414 sgd_solver.cpp:105] Iteration 7668, lr = 0.00218948 +I0410 14:27:07.815943 18414 solver.cpp:218] Iteration 7680 (2.40963 iter/s, 4.98001s/12 iters), loss = 0.821915 +I0410 14:27:07.815999 18414 solver.cpp:237] Train net output #0: loss = 0.821915 (* 1 = 0.821915 loss) +I0410 14:27:07.816012 18414 sgd_solver.cpp:105] Iteration 7680, lr = 0.00218428 +I0410 14:27:10.531867 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:27:12.723834 18414 solver.cpp:218] Iteration 7692 (2.44513 iter/s, 4.90772s/12 iters), loss = 0.856003 +I0410 14:27:12.723875 18414 solver.cpp:237] Train net output #0: loss = 0.856003 (* 1 = 0.856003 loss) +I0410 14:27:12.723886 18414 sgd_solver.cpp:105] Iteration 7692, lr = 0.00217909 +I0410 14:27:17.646198 18414 solver.cpp:218] Iteration 7704 (2.43793 iter/s, 4.92221s/12 iters), loss = 0.815722 +I0410 14:27:17.646318 18414 solver.cpp:237] Train net output #0: loss = 0.815722 (* 1 = 0.815722 loss) +I0410 14:27:17.646329 18414 sgd_solver.cpp:105] Iteration 7704, lr = 0.00217392 +I0410 14:27:22.509264 18414 solver.cpp:218] Iteration 7716 (2.4677 iter/s, 4.86282s/12 iters), loss = 0.941768 +I0410 14:27:22.509325 18414 solver.cpp:237] Train net output #0: loss = 0.941768 (* 1 = 0.941768 loss) +I0410 14:27:22.509338 18414 sgd_solver.cpp:105] Iteration 7716, lr = 0.00216876 +I0410 14:27:27.381495 18414 solver.cpp:218] Iteration 7728 (2.46303 iter/s, 4.87205s/12 iters), loss = 1.10138 +I0410 14:27:27.381548 18414 solver.cpp:237] Train net output #0: loss = 1.10138 (* 1 = 1.10138 loss) +I0410 14:27:27.381561 18414 sgd_solver.cpp:105] Iteration 7728, lr = 0.00216361 +I0410 14:27:32.354972 18414 solver.cpp:218] Iteration 7740 (2.41288 iter/s, 4.9733s/12 iters), loss = 0.86909 +I0410 14:27:32.355026 18414 solver.cpp:237] Train net output #0: loss = 0.86909 (* 1 = 0.86909 loss) +I0410 14:27:32.355039 18414 sgd_solver.cpp:105] Iteration 7740, lr = 0.00215847 +I0410 14:27:36.808471 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7752.caffemodel +I0410 14:27:38.013335 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7752.solverstate +I0410 14:27:38.214043 18414 solver.cpp:330] Iteration 7752, Testing net (#0) +I0410 14:27:38.214071 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:27:39.623445 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:27:42.687055 18414 solver.cpp:397] Test net output #0: accuracy = 0.526348 +I0410 14:27:42.687088 18414 solver.cpp:397] Test net output #1: loss = 1.92788 (* 1 = 1.92788 loss) +I0410 14:27:42.769855 18414 solver.cpp:218] Iteration 7752 (1.15223 iter/s, 10.4146s/12 iters), loss = 1.22444 +I0410 14:27:42.769901 18414 solver.cpp:237] Train net output #0: loss = 1.22444 (* 1 = 1.22444 loss) +I0410 14:27:42.769910 18414 sgd_solver.cpp:105] Iteration 7752, lr = 0.00215335 +I0410 14:27:47.083998 18414 solver.cpp:218] Iteration 7764 (2.78165 iter/s, 4.31398s/12 iters), loss = 1.07856 +I0410 14:27:47.084060 18414 solver.cpp:237] Train net output #0: loss = 1.07856 (* 1 = 1.07856 loss) +I0410 14:27:47.084074 18414 sgd_solver.cpp:105] Iteration 7764, lr = 0.00214823 +I0410 14:27:52.038280 18414 solver.cpp:218] Iteration 7776 (2.42224 iter/s, 4.9541s/12 iters), loss = 1.03472 +I0410 14:27:52.038456 18414 solver.cpp:237] Train net output #0: loss = 1.03472 (* 1 = 1.03472 loss) +I0410 14:27:52.038470 18414 sgd_solver.cpp:105] Iteration 7776, lr = 0.00214313 +I0410 14:27:56.984282 18414 solver.cpp:218] Iteration 7788 (2.42634 iter/s, 4.94571s/12 iters), loss = 0.945121 +I0410 14:27:56.984328 18414 solver.cpp:237] Train net output #0: loss = 0.945121 (* 1 = 0.945121 loss) +I0410 14:27:56.984339 18414 sgd_solver.cpp:105] Iteration 7788, lr = 0.00213805 +I0410 14:27:56.992394 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:02.097252 18414 solver.cpp:218] Iteration 7800 (2.34705 iter/s, 5.11279s/12 iters), loss = 0.810213 +I0410 14:28:02.097298 18414 solver.cpp:237] Train net output #0: loss = 0.810213 (* 1 = 0.810213 loss) +I0410 14:28:02.097307 18414 sgd_solver.cpp:105] Iteration 7800, lr = 0.00213297 +I0410 14:28:07.094988 18414 solver.cpp:218] Iteration 7812 (2.40117 iter/s, 4.99756s/12 iters), loss = 0.793972 +I0410 14:28:07.095055 18414 solver.cpp:237] Train net output #0: loss = 0.793972 (* 1 = 0.793972 loss) +I0410 14:28:07.095070 18414 sgd_solver.cpp:105] Iteration 7812, lr = 0.00212791 +I0410 14:28:12.080624 18414 solver.cpp:218] Iteration 7824 (2.40701 iter/s, 4.98545s/12 iters), loss = 0.856774 +I0410 14:28:12.080677 18414 solver.cpp:237] Train net output #0: loss = 0.856774 (* 1 = 0.856774 loss) +I0410 14:28:12.080689 18414 sgd_solver.cpp:105] Iteration 7824, lr = 0.00212285 +I0410 14:28:17.001536 18414 solver.cpp:218] Iteration 7836 (2.43866 iter/s, 4.92073s/12 iters), loss = 1.03895 +I0410 14:28:17.001597 18414 solver.cpp:237] Train net output #0: loss = 1.03895 (* 1 = 1.03895 loss) +I0410 14:28:17.001610 18414 sgd_solver.cpp:105] Iteration 7836, lr = 0.00211781 +I0410 14:28:21.909407 18414 solver.cpp:218] Iteration 7848 (2.44514 iter/s, 4.90769s/12 iters), loss = 1.00368 +I0410 14:28:21.909467 18414 solver.cpp:237] Train net output #0: loss = 1.00368 (* 1 = 1.00368 loss) +I0410 14:28:21.909480 18414 sgd_solver.cpp:105] Iteration 7848, lr = 0.00211279 +I0410 14:28:23.884295 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7854.caffemodel +I0410 14:28:24.211887 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7854.solverstate +I0410 14:28:24.423677 18414 solver.cpp:330] Iteration 7854, Testing net (#0) +I0410 14:28:24.423700 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:28:25.722909 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:28.795946 18414 solver.cpp:397] Test net output #0: accuracy = 0.519608 +I0410 14:28:28.795994 18414 solver.cpp:397] Test net output #1: loss = 1.96342 (* 1 = 1.96342 loss) +I0410 14:28:30.583029 18414 solver.cpp:218] Iteration 7860 (1.38355 iter/s, 8.67335s/12 iters), loss = 0.987862 +I0410 14:28:30.583087 18414 solver.cpp:237] Train net output #0: loss = 0.987862 (* 1 = 0.987862 loss) +I0410 14:28:30.583101 18414 sgd_solver.cpp:105] Iteration 7860, lr = 0.00210777 +I0410 14:28:35.435228 18414 solver.cpp:218] Iteration 7872 (2.4732 iter/s, 4.85202s/12 iters), loss = 0.949833 +I0410 14:28:35.435278 18414 solver.cpp:237] Train net output #0: loss = 0.949833 (* 1 = 0.949833 loss) +I0410 14:28:35.435289 18414 sgd_solver.cpp:105] Iteration 7872, lr = 0.00210277 +I0410 14:28:40.517856 18414 solver.cpp:218] Iteration 7884 (2.36107 iter/s, 5.08245s/12 iters), loss = 0.877397 +I0410 14:28:40.517920 18414 solver.cpp:237] Train net output #0: loss = 0.877397 (* 1 = 0.877397 loss) +I0410 14:28:40.517936 18414 sgd_solver.cpp:105] Iteration 7884, lr = 0.00209777 +I0410 14:28:42.656886 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:45.626358 18414 solver.cpp:218] Iteration 7896 (2.34912 iter/s, 5.1083s/12 iters), loss = 1.01841 +I0410 14:28:45.626441 18414 solver.cpp:237] Train net output #0: loss = 1.01841 (* 1 = 1.01841 loss) +I0410 14:28:45.626451 18414 sgd_solver.cpp:105] Iteration 7896, lr = 0.00209279 +I0410 14:28:50.582767 18414 solver.cpp:218] Iteration 7908 (2.42121 iter/s, 4.9562s/12 iters), loss = 0.841044 +I0410 14:28:50.582823 18414 solver.cpp:237] Train net output #0: loss = 0.841044 (* 1 = 0.841044 loss) +I0410 14:28:50.582835 18414 sgd_solver.cpp:105] Iteration 7908, lr = 0.00208782 +I0410 14:28:55.525161 18414 solver.cpp:218] Iteration 7920 (2.42806 iter/s, 4.94221s/12 iters), loss = 0.937692 +I0410 14:28:55.525297 18414 solver.cpp:237] Train net output #0: loss = 0.937692 (* 1 = 0.937692 loss) +I0410 14:28:55.525311 18414 sgd_solver.cpp:105] Iteration 7920, lr = 0.00208287 +I0410 14:29:00.452898 18414 solver.cpp:218] Iteration 7932 (2.43532 iter/s, 4.92748s/12 iters), loss = 0.8132 +I0410 14:29:00.452951 18414 solver.cpp:237] Train net output #0: loss = 0.8132 (* 1 = 0.8132 loss) +I0410 14:29:00.452965 18414 sgd_solver.cpp:105] Iteration 7932, lr = 0.00207792 +I0410 14:29:05.341290 18414 solver.cpp:218] Iteration 7944 (2.45488 iter/s, 4.88821s/12 iters), loss = 0.904703 +I0410 14:29:05.341351 18414 solver.cpp:237] Train net output #0: loss = 0.904703 (* 1 = 0.904703 loss) +I0410 14:29:05.341364 18414 sgd_solver.cpp:105] Iteration 7944, lr = 0.00207299 +I0410 14:29:09.760804 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7956.caffemodel +I0410 14:29:10.099877 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7956.solverstate +I0410 14:29:10.311187 18414 solver.cpp:330] Iteration 7956, Testing net (#0) +I0410 14:29:10.311206 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:29:11.658978 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:29:14.817823 18414 solver.cpp:397] Test net output #0: accuracy = 0.530637 +I0410 14:29:14.817864 18414 solver.cpp:397] Test net output #1: loss = 1.90331 (* 1 = 1.90331 loss) +I0410 14:29:14.901131 18414 solver.cpp:218] Iteration 7956 (1.25529 iter/s, 9.55955s/12 iters), loss = 0.963569 +I0410 14:29:14.901175 18414 solver.cpp:237] Train net output #0: loss = 0.963569 (* 1 = 0.963569 loss) +I0410 14:29:14.901185 18414 sgd_solver.cpp:105] Iteration 7956, lr = 0.00206807 +I0410 14:29:19.076848 18414 solver.cpp:218] Iteration 7968 (2.87386 iter/s, 4.17556s/12 iters), loss = 0.870006 +I0410 14:29:19.076905 18414 solver.cpp:237] Train net output #0: loss = 0.870006 (* 1 = 0.870006 loss) +I0410 14:29:19.076917 18414 sgd_solver.cpp:105] Iteration 7968, lr = 0.00206316 +I0410 14:29:23.985778 18414 solver.cpp:218] Iteration 7980 (2.44462 iter/s, 4.90874s/12 iters), loss = 0.914662 +I0410 14:29:23.985838 18414 solver.cpp:237] Train net output #0: loss = 0.914662 (* 1 = 0.914662 loss) +I0410 14:29:23.985852 18414 sgd_solver.cpp:105] Iteration 7980, lr = 0.00205826 +I0410 14:29:28.185251 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:29:28.949348 18414 solver.cpp:218] Iteration 7992 (2.41771 iter/s, 4.96337s/12 iters), loss = 0.930073 +I0410 14:29:28.949424 18414 solver.cpp:237] Train net output #0: loss = 0.930073 (* 1 = 0.930073 loss) +I0410 14:29:28.949442 18414 sgd_solver.cpp:105] Iteration 7992, lr = 0.00205337 +I0410 14:29:33.976307 18414 solver.cpp:218] Iteration 8004 (2.38722 iter/s, 5.02676s/12 iters), loss = 1.00502 +I0410 14:29:33.976356 18414 solver.cpp:237] Train net output #0: loss = 1.00502 (* 1 = 1.00502 loss) +I0410 14:29:33.976367 18414 sgd_solver.cpp:105] Iteration 8004, lr = 0.0020485 +I0410 14:29:38.875025 18414 solver.cpp:218] Iteration 8016 (2.44971 iter/s, 4.89853s/12 iters), loss = 1.04516 +I0410 14:29:38.875075 18414 solver.cpp:237] Train net output #0: loss = 1.04516 (* 1 = 1.04516 loss) +I0410 14:29:38.875087 18414 sgd_solver.cpp:105] Iteration 8016, lr = 0.00204363 +I0410 14:29:43.779429 18414 solver.cpp:218] Iteration 8028 (2.44687 iter/s, 4.90422s/12 iters), loss = 0.875851 +I0410 14:29:43.779482 18414 solver.cpp:237] Train net output #0: loss = 0.875851 (* 1 = 0.875851 loss) +I0410 14:29:43.779492 18414 sgd_solver.cpp:105] Iteration 8028, lr = 0.00203878 +I0410 14:29:48.841082 18414 solver.cpp:218] Iteration 8040 (2.37085 iter/s, 5.06147s/12 iters), loss = 1.08528 +I0410 14:29:48.841125 18414 solver.cpp:237] Train net output #0: loss = 1.08528 (* 1 = 1.08528 loss) +I0410 14:29:48.841135 18414 sgd_solver.cpp:105] Iteration 8040, lr = 0.00203394 +I0410 14:29:53.827847 18414 solver.cpp:218] Iteration 8052 (2.40645 iter/s, 4.98659s/12 iters), loss = 0.921939 +I0410 14:29:53.827895 18414 solver.cpp:237] Train net output #0: loss = 0.921939 (* 1 = 0.921939 loss) +I0410 14:29:53.827905 18414 sgd_solver.cpp:105] Iteration 8052, lr = 0.00202911 +I0410 14:29:55.861199 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8058.caffemodel +I0410 14:29:56.186614 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8058.solverstate +I0410 14:29:56.402258 18414 solver.cpp:330] Iteration 8058, Testing net (#0) +I0410 14:29:56.402288 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:29:57.680546 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:30:00.832747 18414 solver.cpp:397] Test net output #0: accuracy = 0.526961 +I0410 14:30:00.832866 18414 solver.cpp:397] Test net output #1: loss = 2.06348 (* 1 = 2.06348 loss) +I0410 14:30:02.803745 18414 solver.cpp:218] Iteration 8064 (1.33696 iter/s, 8.97561s/12 iters), loss = 1.04126 +I0410 14:30:02.803807 18414 solver.cpp:237] Train net output #0: loss = 1.04126 (* 1 = 1.04126 loss) +I0410 14:30:02.803820 18414 sgd_solver.cpp:105] Iteration 8064, lr = 0.00202429 +I0410 14:30:07.734998 18414 solver.cpp:218] Iteration 8076 (2.43356 iter/s, 4.93106s/12 iters), loss = 0.914768 +I0410 14:30:07.735057 18414 solver.cpp:237] Train net output #0: loss = 0.914768 (* 1 = 0.914768 loss) +I0410 14:30:07.735070 18414 sgd_solver.cpp:105] Iteration 8076, lr = 0.00201949 +I0410 14:30:12.711438 18414 solver.cpp:218] Iteration 8088 (2.41145 iter/s, 4.97625s/12 iters), loss = 0.844847 +I0410 14:30:12.711490 18414 solver.cpp:237] Train net output #0: loss = 0.844847 (* 1 = 0.844847 loss) +I0410 14:30:12.711503 18414 sgd_solver.cpp:105] Iteration 8088, lr = 0.00201469 +I0410 14:30:14.095271 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:30:17.637485 18414 solver.cpp:218] Iteration 8100 (2.43614 iter/s, 4.92582s/12 iters), loss = 1.01425 +I0410 14:30:17.637580 18414 solver.cpp:237] Train net output #0: loss = 1.01425 (* 1 = 1.01425 loss) +I0410 14:30:17.637627 18414 sgd_solver.cpp:105] Iteration 8100, lr = 0.00200991 +I0410 14:30:22.747383 18414 solver.cpp:218] Iteration 8112 (2.34848 iter/s, 5.10969s/12 iters), loss = 0.806604 +I0410 14:30:22.747440 18414 solver.cpp:237] Train net output #0: loss = 0.806604 (* 1 = 0.806604 loss) +I0410 14:30:22.747452 18414 sgd_solver.cpp:105] Iteration 8112, lr = 0.00200514 +I0410 14:30:27.735571 18414 solver.cpp:218] Iteration 8124 (2.40578 iter/s, 4.988s/12 iters), loss = 0.844355 +I0410 14:30:27.735618 18414 solver.cpp:237] Train net output #0: loss = 0.844355 (* 1 = 0.844355 loss) +I0410 14:30:27.735628 18414 sgd_solver.cpp:105] Iteration 8124, lr = 0.00200038 +I0410 14:30:32.594687 18414 solver.cpp:218] Iteration 8136 (2.46968 iter/s, 4.85893s/12 iters), loss = 1.14608 +I0410 14:30:32.594817 18414 solver.cpp:237] Train net output #0: loss = 1.14608 (* 1 = 1.14608 loss) +I0410 14:30:32.594830 18414 sgd_solver.cpp:105] Iteration 8136, lr = 0.00199563 +I0410 14:30:37.459879 18414 solver.cpp:218] Iteration 8148 (2.46663 iter/s, 4.86493s/12 iters), loss = 0.844105 +I0410 14:30:37.459933 18414 solver.cpp:237] Train net output #0: loss = 0.844105 (* 1 = 0.844105 loss) +I0410 14:30:37.459944 18414 sgd_solver.cpp:105] Iteration 8148, lr = 0.00199089 +I0410 14:30:41.911340 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8160.caffemodel +I0410 14:30:42.220844 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8160.solverstate +I0410 14:30:42.490626 18414 solver.cpp:330] Iteration 8160, Testing net (#0) +I0410 14:30:42.490651 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:30:43.720429 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:30:46.899668 18414 solver.cpp:397] Test net output #0: accuracy = 0.520833 +I0410 14:30:46.899713 18414 solver.cpp:397] Test net output #1: loss = 2.07355 (* 1 = 2.07355 loss) +I0410 14:30:46.982544 18414 solver.cpp:218] Iteration 8160 (1.26019 iter/s, 9.52237s/12 iters), loss = 0.92658 +I0410 14:30:46.982592 18414 solver.cpp:237] Train net output #0: loss = 0.92658 (* 1 = 0.92658 loss) +I0410 14:30:46.982604 18414 sgd_solver.cpp:105] Iteration 8160, lr = 0.00198616 +I0410 14:30:51.289670 18414 solver.cpp:218] Iteration 8172 (2.78619 iter/s, 4.30696s/12 iters), loss = 0.796292 +I0410 14:30:51.289718 18414 solver.cpp:237] Train net output #0: loss = 0.796292 (* 1 = 0.796292 loss) +I0410 14:30:51.289729 18414 sgd_solver.cpp:105] Iteration 8172, lr = 0.00198145 +I0410 14:30:56.448854 18414 solver.cpp:218] Iteration 8184 (2.32604 iter/s, 5.15899s/12 iters), loss = 0.765685 +I0410 14:30:56.448916 18414 solver.cpp:237] Train net output #0: loss = 0.765685 (* 1 = 0.765685 loss) +I0410 14:30:56.448931 18414 sgd_solver.cpp:105] Iteration 8184, lr = 0.00197674 +I0410 14:30:59.998064 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:01.440920 18414 solver.cpp:218] Iteration 8196 (2.40391 iter/s, 4.99187s/12 iters), loss = 0.870541 +I0410 14:31:01.440979 18414 solver.cpp:237] Train net output #0: loss = 0.870541 (* 1 = 0.870541 loss) +I0410 14:31:01.440991 18414 sgd_solver.cpp:105] Iteration 8196, lr = 0.00197205 +I0410 14:31:06.364451 18414 solver.cpp:218] Iteration 8208 (2.43737 iter/s, 4.92334s/12 iters), loss = 0.901341 +I0410 14:31:06.364609 18414 solver.cpp:237] Train net output #0: loss = 0.901341 (* 1 = 0.901341 loss) +I0410 14:31:06.364622 18414 sgd_solver.cpp:105] Iteration 8208, lr = 0.00196737 +I0410 14:31:11.284912 18414 solver.cpp:218] Iteration 8220 (2.43894 iter/s, 4.92017s/12 iters), loss = 0.927918 +I0410 14:31:11.284974 18414 solver.cpp:237] Train net output #0: loss = 0.927918 (* 1 = 0.927918 loss) +I0410 14:31:11.284987 18414 sgd_solver.cpp:105] Iteration 8220, lr = 0.0019627 +I0410 14:31:16.159790 18414 solver.cpp:218] Iteration 8232 (2.4617 iter/s, 4.87468s/12 iters), loss = 0.767512 +I0410 14:31:16.159837 18414 solver.cpp:237] Train net output #0: loss = 0.767512 (* 1 = 0.767512 loss) +I0410 14:31:16.159847 18414 sgd_solver.cpp:105] Iteration 8232, lr = 0.00195804 +I0410 14:31:21.151880 18414 solver.cpp:218] Iteration 8244 (2.40389 iter/s, 4.9919s/12 iters), loss = 1.05429 +I0410 14:31:21.151937 18414 solver.cpp:237] Train net output #0: loss = 1.05429 (* 1 = 1.05429 loss) +I0410 14:31:21.151950 18414 sgd_solver.cpp:105] Iteration 8244, lr = 0.00195339 +I0410 14:31:26.041786 18414 solver.cpp:218] Iteration 8256 (2.45413 iter/s, 4.88972s/12 iters), loss = 1.11133 +I0410 14:31:26.041834 18414 solver.cpp:237] Train net output #0: loss = 1.11133 (* 1 = 1.11133 loss) +I0410 14:31:26.041843 18414 sgd_solver.cpp:105] Iteration 8256, lr = 0.00194875 +I0410 14:31:28.039403 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8262.caffemodel +I0410 14:31:28.378412 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8262.solverstate +I0410 14:31:28.591428 18414 solver.cpp:330] Iteration 8262, Testing net (#0) +I0410 14:31:28.591446 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:31:29.716562 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:33.015728 18414 solver.cpp:397] Test net output #0: accuracy = 0.541667 +I0410 14:31:33.015758 18414 solver.cpp:397] Test net output #1: loss = 2.00154 (* 1 = 2.00154 loss) +I0410 14:31:34.810775 18414 solver.cpp:218] Iteration 8268 (1.3685 iter/s, 8.76871s/12 iters), loss = 0.96788 +I0410 14:31:34.810827 18414 solver.cpp:237] Train net output #0: loss = 0.96788 (* 1 = 0.96788 loss) +I0410 14:31:34.810839 18414 sgd_solver.cpp:105] Iteration 8268, lr = 0.00194412 +I0410 14:31:39.743060 18414 solver.cpp:218] Iteration 8280 (2.43304 iter/s, 4.93209s/12 iters), loss = 0.742964 +I0410 14:31:39.743360 18414 solver.cpp:237] Train net output #0: loss = 0.742964 (* 1 = 0.742964 loss) +I0410 14:31:39.743373 18414 sgd_solver.cpp:105] Iteration 8280, lr = 0.00193951 +I0410 14:31:44.613654 18414 solver.cpp:218] Iteration 8292 (2.46399 iter/s, 4.87016s/12 iters), loss = 1.03235 +I0410 14:31:44.613713 18414 solver.cpp:237] Train net output #0: loss = 1.03235 (* 1 = 1.03235 loss) +I0410 14:31:44.613724 18414 sgd_solver.cpp:105] Iteration 8292, lr = 0.0019349 +I0410 14:31:45.304823 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:49.649979 18414 solver.cpp:218] Iteration 8304 (2.38279 iter/s, 5.03612s/12 iters), loss = 0.966962 +I0410 14:31:49.650030 18414 solver.cpp:237] Train net output #0: loss = 0.966962 (* 1 = 0.966962 loss) +I0410 14:31:49.650044 18414 sgd_solver.cpp:105] Iteration 8304, lr = 0.00193031 +I0410 14:31:50.819299 18414 blocking_queue.cpp:49] Waiting for data +I0410 14:31:54.770850 18414 solver.cpp:218] Iteration 8316 (2.34344 iter/s, 5.12068s/12 iters), loss = 0.963788 +I0410 14:31:54.770907 18414 solver.cpp:237] Train net output #0: loss = 0.963788 (* 1 = 0.963788 loss) +I0410 14:31:54.770920 18414 sgd_solver.cpp:105] Iteration 8316, lr = 0.00192573 +I0410 14:31:59.751922 18414 solver.cpp:218] Iteration 8328 (2.40922 iter/s, 4.98087s/12 iters), loss = 0.781656 +I0410 14:31:59.751976 18414 solver.cpp:237] Train net output #0: loss = 0.781656 (* 1 = 0.781656 loss) +I0410 14:31:59.751989 18414 sgd_solver.cpp:105] Iteration 8328, lr = 0.00192115 +I0410 14:32:04.745609 18414 solver.cpp:218] Iteration 8340 (2.40313 iter/s, 4.99349s/12 iters), loss = 1.066 +I0410 14:32:04.745671 18414 solver.cpp:237] Train net output #0: loss = 1.066 (* 1 = 1.066 loss) +I0410 14:32:04.745683 18414 sgd_solver.cpp:105] Iteration 8340, lr = 0.00191659 +I0410 14:32:09.679508 18414 solver.cpp:218] Iteration 8352 (2.43225 iter/s, 4.9337s/12 iters), loss = 0.864438 +I0410 14:32:09.679574 18414 solver.cpp:237] Train net output #0: loss = 0.864438 (* 1 = 0.864438 loss) +I0410 14:32:09.679589 18414 sgd_solver.cpp:105] Iteration 8352, lr = 0.00191204 +I0410 14:32:14.147723 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8364.caffemodel +I0410 14:32:14.440086 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8364.solverstate +I0410 14:32:14.639039 18414 solver.cpp:330] Iteration 8364, Testing net (#0) +I0410 14:32:14.639057 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:32:15.725975 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:32:19.127745 18414 solver.cpp:397] Test net output #0: accuracy = 0.520833 +I0410 14:32:19.127790 18414 solver.cpp:397] Test net output #1: loss = 2.03299 (* 1 = 2.03299 loss) +I0410 14:32:19.212162 18414 solver.cpp:218] Iteration 8364 (1.25887 iter/s, 9.53234s/12 iters), loss = 0.894552 +I0410 14:32:19.212204 18414 solver.cpp:237] Train net output #0: loss = 0.894552 (* 1 = 0.894552 loss) +I0410 14:32:19.212215 18414 sgd_solver.cpp:105] Iteration 8364, lr = 0.0019075 +I0410 14:32:23.418411 18414 solver.cpp:218] Iteration 8376 (2.85302 iter/s, 4.20606s/12 iters), loss = 0.929386 +I0410 14:32:23.418467 18414 solver.cpp:237] Train net output #0: loss = 0.929386 (* 1 = 0.929386 loss) +I0410 14:32:23.418480 18414 sgd_solver.cpp:105] Iteration 8376, lr = 0.00190297 +I0410 14:32:28.368368 18414 solver.cpp:218] Iteration 8388 (2.42436 iter/s, 4.94976s/12 iters), loss = 0.819855 +I0410 14:32:28.368422 18414 solver.cpp:237] Train net output #0: loss = 0.819855 (* 1 = 0.819855 loss) +I0410 14:32:28.368432 18414 sgd_solver.cpp:105] Iteration 8388, lr = 0.00189846 +I0410 14:32:31.158839 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:32:33.293633 18414 solver.cpp:218] Iteration 8400 (2.43651 iter/s, 4.92507s/12 iters), loss = 0.792152 +I0410 14:32:33.293694 18414 solver.cpp:237] Train net output #0: loss = 0.792152 (* 1 = 0.792152 loss) +I0410 14:32:33.293709 18414 sgd_solver.cpp:105] Iteration 8400, lr = 0.00189395 +I0410 14:32:38.311033 18414 solver.cpp:218] Iteration 8412 (2.39178 iter/s, 5.01719s/12 iters), loss = 0.785181 +I0410 14:32:38.311085 18414 solver.cpp:237] Train net output #0: loss = 0.785181 (* 1 = 0.785181 loss) +I0410 14:32:38.311097 18414 sgd_solver.cpp:105] Iteration 8412, lr = 0.00188945 +I0410 14:32:43.421303 18414 solver.cpp:218] Iteration 8424 (2.34831 iter/s, 5.11007s/12 iters), loss = 0.778512 +I0410 14:32:43.421360 18414 solver.cpp:237] Train net output #0: loss = 0.778512 (* 1 = 0.778512 loss) +I0410 14:32:43.421372 18414 sgd_solver.cpp:105] Iteration 8424, lr = 0.00188497 +I0410 14:32:48.499680 18414 solver.cpp:218] Iteration 8436 (2.36305 iter/s, 5.07818s/12 iters), loss = 0.907849 +I0410 14:32:48.499821 18414 solver.cpp:237] Train net output #0: loss = 0.907849 (* 1 = 0.907849 loss) +I0410 14:32:48.499833 18414 sgd_solver.cpp:105] Iteration 8436, lr = 0.00188049 +I0410 14:32:53.499688 18414 solver.cpp:218] Iteration 8448 (2.40013 iter/s, 4.99973s/12 iters), loss = 0.981775 +I0410 14:32:53.499747 18414 solver.cpp:237] Train net output #0: loss = 0.981775 (* 1 = 0.981775 loss) +I0410 14:32:53.499759 18414 sgd_solver.cpp:105] Iteration 8448, lr = 0.00187603 +I0410 14:32:58.549496 18414 solver.cpp:218] Iteration 8460 (2.37642 iter/s, 5.04961s/12 iters), loss = 1.0584 +I0410 14:32:58.549546 18414 solver.cpp:237] Train net output #0: loss = 1.0584 (* 1 = 1.0584 loss) +I0410 14:32:58.549556 18414 sgd_solver.cpp:105] Iteration 8460, lr = 0.00187157 +I0410 14:33:00.589459 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8466.caffemodel +I0410 14:33:00.917985 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8466.solverstate +I0410 14:33:01.132966 18414 solver.cpp:330] Iteration 8466, Testing net (#0) +I0410 14:33:01.132992 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:33:02.265769 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:33:05.798962 18414 solver.cpp:397] Test net output #0: accuracy = 0.532475 +I0410 14:33:05.799010 18414 solver.cpp:397] Test net output #1: loss = 1.96563 (* 1 = 1.96563 loss) +I0410 14:33:07.641901 18414 solver.cpp:218] Iteration 8472 (1.31983 iter/s, 9.09211s/12 iters), loss = 0.953051 +I0410 14:33:07.641968 18414 solver.cpp:237] Train net output #0: loss = 0.953051 (* 1 = 0.953051 loss) +I0410 14:33:07.641979 18414 sgd_solver.cpp:105] Iteration 8472, lr = 0.00186713 +I0410 14:33:12.562494 18414 solver.cpp:218] Iteration 8484 (2.43883 iter/s, 4.9204s/12 iters), loss = 0.809484 +I0410 14:33:12.562544 18414 solver.cpp:237] Train net output #0: loss = 0.809484 (* 1 = 0.809484 loss) +I0410 14:33:12.562556 18414 sgd_solver.cpp:105] Iteration 8484, lr = 0.0018627 +I0410 14:33:17.417482 18414 solver.cpp:218] Iteration 8496 (2.47178 iter/s, 4.8548s/12 iters), loss = 0.696178 +I0410 14:33:17.417539 18414 solver.cpp:237] Train net output #0: loss = 0.696178 (* 1 = 0.696178 loss) +I0410 14:33:17.417553 18414 sgd_solver.cpp:105] Iteration 8496, lr = 0.00185827 +I0410 14:33:17.456312 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:33:22.403517 18414 solver.cpp:218] Iteration 8508 (2.40682 iter/s, 4.98583s/12 iters), loss = 0.909803 +I0410 14:33:22.403614 18414 solver.cpp:237] Train net output #0: loss = 0.909803 (* 1 = 0.909803 loss) +I0410 14:33:22.403625 18414 sgd_solver.cpp:105] Iteration 8508, lr = 0.00185386 +I0410 14:33:27.560356 18414 solver.cpp:218] Iteration 8520 (2.32711 iter/s, 5.1566s/12 iters), loss = 0.690709 +I0410 14:33:27.560389 18414 solver.cpp:237] Train net output #0: loss = 0.690709 (* 1 = 0.690709 loss) +I0410 14:33:27.560396 18414 sgd_solver.cpp:105] Iteration 8520, lr = 0.00184946 +I0410 14:33:32.575435 18414 solver.cpp:218] Iteration 8532 (2.39287 iter/s, 5.0149s/12 iters), loss = 0.673036 +I0410 14:33:32.575477 18414 solver.cpp:237] Train net output #0: loss = 0.673036 (* 1 = 0.673036 loss) +I0410 14:33:32.575486 18414 sgd_solver.cpp:105] Iteration 8532, lr = 0.00184507 +I0410 14:33:37.495810 18414 solver.cpp:218] Iteration 8544 (2.43893 iter/s, 4.92019s/12 iters), loss = 0.99305 +I0410 14:33:37.495860 18414 solver.cpp:237] Train net output #0: loss = 0.99305 (* 1 = 0.99305 loss) +I0410 14:33:37.495873 18414 sgd_solver.cpp:105] Iteration 8544, lr = 0.00184069 +I0410 14:33:42.409433 18414 solver.cpp:218] Iteration 8556 (2.44228 iter/s, 4.91344s/12 iters), loss = 0.802058 +I0410 14:33:42.409477 18414 solver.cpp:237] Train net output #0: loss = 0.802058 (* 1 = 0.802058 loss) +I0410 14:33:42.409487 18414 sgd_solver.cpp:105] Iteration 8556, lr = 0.00183632 +I0410 14:33:46.839553 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8568.caffemodel +I0410 14:33:47.575265 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8568.solverstate +I0410 14:33:47.811269 18414 solver.cpp:330] Iteration 8568, Testing net (#0) +I0410 14:33:47.811292 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:33:49.048265 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:33:52.411481 18414 solver.cpp:397] Test net output #0: accuracy = 0.530025 +I0410 14:33:52.411640 18414 solver.cpp:397] Test net output #1: loss = 2.0326 (* 1 = 2.0326 loss) +I0410 14:33:52.494531 18414 solver.cpp:218] Iteration 8568 (1.18991 iter/s, 10.0848s/12 iters), loss = 0.935903 +I0410 14:33:52.494580 18414 solver.cpp:237] Train net output #0: loss = 0.935903 (* 1 = 0.935903 loss) +I0410 14:33:52.494590 18414 sgd_solver.cpp:105] Iteration 8568, lr = 0.00183196 +I0410 14:33:56.647001 18414 solver.cpp:218] Iteration 8580 (2.88997 iter/s, 4.1523s/12 iters), loss = 0.507921 +I0410 14:33:56.647066 18414 solver.cpp:237] Train net output #0: loss = 0.507921 (* 1 = 0.507921 loss) +I0410 14:33:56.647083 18414 sgd_solver.cpp:105] Iteration 8580, lr = 0.00182761 +I0410 14:34:01.632923 18414 solver.cpp:218] Iteration 8592 (2.40687 iter/s, 4.98572s/12 iters), loss = 0.688685 +I0410 14:34:01.632968 18414 solver.cpp:237] Train net output #0: loss = 0.688685 (* 1 = 0.688685 loss) +I0410 14:34:01.632977 18414 sgd_solver.cpp:105] Iteration 8592, lr = 0.00182327 +I0410 14:34:03.824555 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:06.630748 18414 solver.cpp:218] Iteration 8604 (2.40114 iter/s, 4.99763s/12 iters), loss = 0.847369 +I0410 14:34:06.630810 18414 solver.cpp:237] Train net output #0: loss = 0.847369 (* 1 = 0.847369 loss) +I0410 14:34:06.630821 18414 sgd_solver.cpp:105] Iteration 8604, lr = 0.00181894 +I0410 14:34:11.804000 18414 solver.cpp:218] Iteration 8616 (2.31972 iter/s, 5.17304s/12 iters), loss = 0.939586 +I0410 14:34:11.804054 18414 solver.cpp:237] Train net output #0: loss = 0.939586 (* 1 = 0.939586 loss) +I0410 14:34:11.804067 18414 sgd_solver.cpp:105] Iteration 8616, lr = 0.00181462 +I0410 14:34:16.851480 18414 solver.cpp:218] Iteration 8628 (2.37752 iter/s, 5.04728s/12 iters), loss = 0.808348 +I0410 14:34:16.851528 18414 solver.cpp:237] Train net output #0: loss = 0.808348 (* 1 = 0.808348 loss) +I0410 14:34:16.851538 18414 sgd_solver.cpp:105] Iteration 8628, lr = 0.00181031 +I0410 14:34:21.789696 18414 solver.cpp:218] Iteration 8640 (2.43012 iter/s, 4.93802s/12 iters), loss = 0.723805 +I0410 14:34:21.789745 18414 solver.cpp:237] Train net output #0: loss = 0.723805 (* 1 = 0.723805 loss) +I0410 14:34:21.789755 18414 sgd_solver.cpp:105] Iteration 8640, lr = 0.00180602 +I0410 14:34:26.708482 18414 solver.cpp:218] Iteration 8652 (2.43972 iter/s, 4.9186s/12 iters), loss = 0.715691 +I0410 14:34:26.708586 18414 solver.cpp:237] Train net output #0: loss = 0.715691 (* 1 = 0.715691 loss) +I0410 14:34:26.708597 18414 sgd_solver.cpp:105] Iteration 8652, lr = 0.00180173 +I0410 14:34:31.629269 18414 solver.cpp:218] Iteration 8664 (2.43876 iter/s, 4.92054s/12 iters), loss = 0.802641 +I0410 14:34:31.629330 18414 solver.cpp:237] Train net output #0: loss = 0.802641 (* 1 = 0.802641 loss) +I0410 14:34:31.629344 18414 sgd_solver.cpp:105] Iteration 8664, lr = 0.00179745 +I0410 14:34:33.606207 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8670.caffemodel +I0410 14:34:33.905771 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8670.solverstate +I0410 14:34:34.108810 18414 solver.cpp:330] Iteration 8670, Testing net (#0) +I0410 14:34:34.108842 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:34:35.080973 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:38.649478 18414 solver.cpp:397] Test net output #0: accuracy = 0.528799 +I0410 14:34:38.649513 18414 solver.cpp:397] Test net output #1: loss = 1.98297 (* 1 = 1.98297 loss) +I0410 14:34:40.473474 18414 solver.cpp:218] Iteration 8676 (1.35687 iter/s, 8.8439s/12 iters), loss = 0.764304 +I0410 14:34:40.473529 18414 solver.cpp:237] Train net output #0: loss = 0.764304 (* 1 = 0.764304 loss) +I0410 14:34:40.473542 18414 sgd_solver.cpp:105] Iteration 8676, lr = 0.00179318 +I0410 14:34:45.336782 18414 solver.cpp:218] Iteration 8688 (2.46755 iter/s, 4.86311s/12 iters), loss = 0.768858 +I0410 14:34:45.336830 18414 solver.cpp:237] Train net output #0: loss = 0.768858 (* 1 = 0.768858 loss) +I0410 14:34:45.336843 18414 sgd_solver.cpp:105] Iteration 8688, lr = 0.00178893 +I0410 14:34:49.689927 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:50.363442 18414 solver.cpp:218] Iteration 8700 (2.38736 iter/s, 5.02647s/12 iters), loss = 0.641171 +I0410 14:34:50.363499 18414 solver.cpp:237] Train net output #0: loss = 0.641171 (* 1 = 0.641171 loss) +I0410 14:34:50.363512 18414 sgd_solver.cpp:105] Iteration 8700, lr = 0.00178468 +I0410 14:34:55.334476 18414 solver.cpp:218] Iteration 8712 (2.41408 iter/s, 4.97083s/12 iters), loss = 0.879907 +I0410 14:34:55.334525 18414 solver.cpp:237] Train net output #0: loss = 0.879907 (* 1 = 0.879907 loss) +I0410 14:34:55.334537 18414 sgd_solver.cpp:105] Iteration 8712, lr = 0.00178044 +I0410 14:35:00.283119 18414 solver.cpp:218] Iteration 8724 (2.425 iter/s, 4.94845s/12 iters), loss = 0.69893 +I0410 14:35:00.283258 18414 solver.cpp:237] Train net output #0: loss = 0.69893 (* 1 = 0.69893 loss) +I0410 14:35:00.283269 18414 sgd_solver.cpp:105] Iteration 8724, lr = 0.00177621 +I0410 14:35:05.176573 18414 solver.cpp:218] Iteration 8736 (2.4524 iter/s, 4.89317s/12 iters), loss = 0.592819 +I0410 14:35:05.176625 18414 solver.cpp:237] Train net output #0: loss = 0.592819 (* 1 = 0.592819 loss) +I0410 14:35:05.176635 18414 sgd_solver.cpp:105] Iteration 8736, lr = 0.001772 +I0410 14:35:10.131582 18414 solver.cpp:218] Iteration 8748 (2.42189 iter/s, 4.95481s/12 iters), loss = 0.823669 +I0410 14:35:10.131623 18414 solver.cpp:237] Train net output #0: loss = 0.823669 (* 1 = 0.823669 loss) +I0410 14:35:10.131633 18414 sgd_solver.cpp:105] Iteration 8748, lr = 0.00176779 +I0410 14:35:15.023749 18414 solver.cpp:218] Iteration 8760 (2.453 iter/s, 4.89198s/12 iters), loss = 0.868858 +I0410 14:35:15.023803 18414 solver.cpp:237] Train net output #0: loss = 0.868858 (* 1 = 0.868858 loss) +I0410 14:35:15.023815 18414 sgd_solver.cpp:105] Iteration 8760, lr = 0.00176359 +I0410 14:35:19.480638 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8772.caffemodel +I0410 14:35:19.785866 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8772.solverstate +I0410 14:35:19.980118 18414 solver.cpp:330] Iteration 8772, Testing net (#0) +I0410 14:35:19.980137 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:35:21.017768 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:35:24.444137 18414 solver.cpp:397] Test net output #0: accuracy = 0.545956 +I0410 14:35:24.444178 18414 solver.cpp:397] Test net output #1: loss = 1.98288 (* 1 = 1.98288 loss) +I0410 14:35:24.527467 18414 solver.cpp:218] Iteration 8772 (1.26271 iter/s, 9.50339s/12 iters), loss = 0.907968 +I0410 14:35:24.527529 18414 solver.cpp:237] Train net output #0: loss = 0.907968 (* 1 = 0.907968 loss) +I0410 14:35:24.527542 18414 sgd_solver.cpp:105] Iteration 8772, lr = 0.00175941 +I0410 14:35:28.886421 18414 solver.cpp:218] Iteration 8784 (2.75307 iter/s, 4.35877s/12 iters), loss = 0.621794 +I0410 14:35:28.886480 18414 solver.cpp:237] Train net output #0: loss = 0.621794 (* 1 = 0.621794 loss) +I0410 14:35:28.886492 18414 sgd_solver.cpp:105] Iteration 8784, lr = 0.00175523 +I0410 14:35:33.876574 18414 solver.cpp:218] Iteration 8796 (2.40484 iter/s, 4.98995s/12 iters), loss = 0.816748 +I0410 14:35:33.876729 18414 solver.cpp:237] Train net output #0: loss = 0.816748 (* 1 = 0.816748 loss) +I0410 14:35:33.876744 18414 sgd_solver.cpp:105] Iteration 8796, lr = 0.00175106 +I0410 14:35:35.283294 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:35:38.792675 18414 solver.cpp:218] Iteration 8808 (2.44111 iter/s, 4.9158s/12 iters), loss = 0.686888 +I0410 14:35:38.792727 18414 solver.cpp:237] Train net output #0: loss = 0.686888 (* 1 = 0.686888 loss) +I0410 14:35:38.792737 18414 sgd_solver.cpp:105] Iteration 8808, lr = 0.0017469 +I0410 14:35:43.702554 18414 solver.cpp:218] Iteration 8820 (2.44415 iter/s, 4.90968s/12 iters), loss = 0.823811 +I0410 14:35:43.702603 18414 solver.cpp:237] Train net output #0: loss = 0.823811 (* 1 = 0.823811 loss) +I0410 14:35:43.702615 18414 sgd_solver.cpp:105] Iteration 8820, lr = 0.00174276 +I0410 14:35:48.617918 18414 solver.cpp:218] Iteration 8832 (2.44142 iter/s, 4.91517s/12 iters), loss = 0.603411 +I0410 14:35:48.618001 18414 solver.cpp:237] Train net output #0: loss = 0.603411 (* 1 = 0.603411 loss) +I0410 14:35:48.618016 18414 sgd_solver.cpp:105] Iteration 8832, lr = 0.00173862 +I0410 14:35:53.517201 18414 solver.cpp:218] Iteration 8844 (2.44945 iter/s, 4.89905s/12 iters), loss = 0.641044 +I0410 14:35:53.517261 18414 solver.cpp:237] Train net output #0: loss = 0.641044 (* 1 = 0.641044 loss) +I0410 14:35:53.517275 18414 sgd_solver.cpp:105] Iteration 8844, lr = 0.00173449 +I0410 14:35:58.427006 18414 solver.cpp:218] Iteration 8856 (2.44419 iter/s, 4.9096s/12 iters), loss = 0.807959 +I0410 14:35:58.427053 18414 solver.cpp:237] Train net output #0: loss = 0.807959 (* 1 = 0.807959 loss) +I0410 14:35:58.427064 18414 sgd_solver.cpp:105] Iteration 8856, lr = 0.00173037 +I0410 14:36:03.344431 18414 solver.cpp:218] Iteration 8868 (2.4404 iter/s, 4.91723s/12 iters), loss = 0.8094 +I0410 14:36:03.344475 18414 solver.cpp:237] Train net output #0: loss = 0.8094 (* 1 = 0.8094 loss) +I0410 14:36:03.344483 18414 sgd_solver.cpp:105] Iteration 8868, lr = 0.00172626 +I0410 14:36:05.363629 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8874.caffemodel +I0410 14:36:05.668165 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8874.solverstate +I0410 14:36:05.865525 18414 solver.cpp:330] Iteration 8874, Testing net (#0) +I0410 14:36:05.865554 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:36:06.775990 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:36:10.288751 18414 solver.cpp:397] Test net output #0: accuracy = 0.540441 +I0410 14:36:10.288795 18414 solver.cpp:397] Test net output #1: loss = 1.93966 (* 1 = 1.93966 loss) +I0410 14:36:12.164181 18414 solver.cpp:218] Iteration 8880 (1.36063 iter/s, 8.81945s/12 iters), loss = 0.770907 +I0410 14:36:12.164238 18414 solver.cpp:237] Train net output #0: loss = 0.770907 (* 1 = 0.770907 loss) +I0410 14:36:12.164252 18414 sgd_solver.cpp:105] Iteration 8880, lr = 0.00172217 +I0410 14:36:17.058516 18414 solver.cpp:218] Iteration 8892 (2.45191 iter/s, 4.89413s/12 iters), loss = 0.709561 +I0410 14:36:17.058560 18414 solver.cpp:237] Train net output #0: loss = 0.709561 (* 1 = 0.709561 loss) +I0410 14:36:17.058573 18414 sgd_solver.cpp:105] Iteration 8892, lr = 0.00171808 +I0410 14:36:20.615054 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:36:21.977376 18414 solver.cpp:218] Iteration 8904 (2.43969 iter/s, 4.91867s/12 iters), loss = 0.597866 +I0410 14:36:21.977434 18414 solver.cpp:237] Train net output #0: loss = 0.597866 (* 1 = 0.597866 loss) +I0410 14:36:21.977447 18414 sgd_solver.cpp:105] Iteration 8904, lr = 0.001714 +I0410 14:36:26.932087 18414 solver.cpp:218] Iteration 8916 (2.42204 iter/s, 4.9545s/12 iters), loss = 0.651379 +I0410 14:36:26.932132 18414 solver.cpp:237] Train net output #0: loss = 0.651379 (* 1 = 0.651379 loss) +I0410 14:36:26.932142 18414 sgd_solver.cpp:105] Iteration 8916, lr = 0.00170993 +I0410 14:36:31.845855 18414 solver.cpp:218] Iteration 8928 (2.44221 iter/s, 4.91357s/12 iters), loss = 0.78054 +I0410 14:36:31.845909 18414 solver.cpp:237] Train net output #0: loss = 0.78054 (* 1 = 0.78054 loss) +I0410 14:36:31.845922 18414 sgd_solver.cpp:105] Iteration 8928, lr = 0.00170587 +I0410 14:36:36.798410 18414 solver.cpp:218] Iteration 8940 (2.42309 iter/s, 4.95235s/12 iters), loss = 0.936956 +I0410 14:36:36.800815 18414 solver.cpp:237] Train net output #0: loss = 0.936956 (* 1 = 0.936956 loss) +I0410 14:36:36.800829 18414 sgd_solver.cpp:105] Iteration 8940, lr = 0.00170182 +I0410 14:36:41.733444 18414 solver.cpp:218] Iteration 8952 (2.43285 iter/s, 4.93249s/12 iters), loss = 0.653108 +I0410 14:36:41.733496 18414 solver.cpp:237] Train net output #0: loss = 0.653108 (* 1 = 0.653108 loss) +I0410 14:36:41.733507 18414 sgd_solver.cpp:105] Iteration 8952, lr = 0.00169778 +I0410 14:36:46.672366 18414 solver.cpp:218] Iteration 8964 (2.42978 iter/s, 4.93872s/12 iters), loss = 0.87614 +I0410 14:36:46.672426 18414 solver.cpp:237] Train net output #0: loss = 0.87614 (* 1 = 0.87614 loss) +I0410 14:36:46.672439 18414 sgd_solver.cpp:105] Iteration 8964, lr = 0.00169375 +I0410 14:36:51.151377 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8976.caffemodel +I0410 14:36:51.561492 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8976.solverstate +I0410 14:36:51.826493 18414 solver.cpp:330] Iteration 8976, Testing net (#0) +I0410 14:36:51.826522 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:36:52.702642 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:36:56.200641 18414 solver.cpp:397] Test net output #0: accuracy = 0.536152 +I0410 14:36:56.200676 18414 solver.cpp:397] Test net output #1: loss = 1.99656 (* 1 = 1.99656 loss) +I0410 14:36:56.283663 18414 solver.cpp:218] Iteration 8976 (1.24857 iter/s, 9.61096s/12 iters), loss = 0.823134 +I0410 14:36:56.283710 18414 solver.cpp:237] Train net output #0: loss = 0.823134 (* 1 = 0.823134 loss) +I0410 14:36:56.283720 18414 sgd_solver.cpp:105] Iteration 8976, lr = 0.00168973 +I0410 14:37:00.408322 18414 solver.cpp:218] Iteration 8988 (2.90946 iter/s, 4.12448s/12 iters), loss = 0.59165 +I0410 14:37:00.408382 18414 solver.cpp:237] Train net output #0: loss = 0.59165 (* 1 = 0.59165 loss) +I0410 14:37:00.408396 18414 sgd_solver.cpp:105] Iteration 8988, lr = 0.00168571 +I0410 14:37:02.017624 18414 blocking_queue.cpp:49] Waiting for data +I0410 14:37:05.442418 18414 solver.cpp:218] Iteration 9000 (2.38384 iter/s, 5.03389s/12 iters), loss = 0.730048 +I0410 14:37:05.442462 18414 solver.cpp:237] Train net output #0: loss = 0.730048 (* 1 = 0.730048 loss) +I0410 14:37:05.442471 18414 sgd_solver.cpp:105] Iteration 9000, lr = 0.00168171 +I0410 14:37:06.156522 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:10.444382 18414 solver.cpp:218] Iteration 9012 (2.39915 iter/s, 5.00176s/12 iters), loss = 0.747812 +I0410 14:37:10.444479 18414 solver.cpp:237] Train net output #0: loss = 0.747812 (* 1 = 0.747812 loss) +I0410 14:37:10.444489 18414 sgd_solver.cpp:105] Iteration 9012, lr = 0.00167772 +I0410 14:37:15.412506 18414 solver.cpp:218] Iteration 9024 (2.41552 iter/s, 4.96788s/12 iters), loss = 0.688679 +I0410 14:37:15.412552 18414 solver.cpp:237] Train net output #0: loss = 0.688679 (* 1 = 0.688679 loss) +I0410 14:37:15.412562 18414 sgd_solver.cpp:105] Iteration 9024, lr = 0.00167374 +I0410 14:37:20.411808 18414 solver.cpp:218] Iteration 9036 (2.40043 iter/s, 4.9991s/12 iters), loss = 0.584457 +I0410 14:37:20.411854 18414 solver.cpp:237] Train net output #0: loss = 0.584457 (* 1 = 0.584457 loss) +I0410 14:37:20.411864 18414 sgd_solver.cpp:105] Iteration 9036, lr = 0.00166976 +I0410 14:37:25.420385 18414 solver.cpp:218] Iteration 9048 (2.39599 iter/s, 5.00837s/12 iters), loss = 0.80201 +I0410 14:37:25.420444 18414 solver.cpp:237] Train net output #0: loss = 0.80201 (* 1 = 0.80201 loss) +I0410 14:37:25.420455 18414 sgd_solver.cpp:105] Iteration 9048, lr = 0.0016658 +I0410 14:37:30.333690 18414 solver.cpp:218] Iteration 9060 (2.44245 iter/s, 4.9131s/12 iters), loss = 0.814795 +I0410 14:37:30.333739 18414 solver.cpp:237] Train net output #0: loss = 0.814795 (* 1 = 0.814795 loss) +I0410 14:37:30.333748 18414 sgd_solver.cpp:105] Iteration 9060, lr = 0.00166184 +I0410 14:37:35.251608 18414 solver.cpp:218] Iteration 9072 (2.44016 iter/s, 4.91772s/12 iters), loss = 0.610867 +I0410 14:37:35.251663 18414 solver.cpp:237] Train net output #0: loss = 0.610867 (* 1 = 0.610867 loss) +I0410 14:37:35.251677 18414 sgd_solver.cpp:105] Iteration 9072, lr = 0.0016579 +I0410 14:37:37.265720 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9078.caffemodel +I0410 14:37:37.572623 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9078.solverstate +I0410 14:37:37.796666 18414 solver.cpp:330] Iteration 9078, Testing net (#0) +I0410 14:37:37.796690 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:37:38.896378 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:42.657948 18414 solver.cpp:397] Test net output #0: accuracy = 0.550245 +I0410 14:37:42.658125 18414 solver.cpp:397] Test net output #1: loss = 1.8616 (* 1 = 1.8616 loss) +I0410 14:37:44.514706 18414 solver.cpp:218] Iteration 9084 (1.29551 iter/s, 9.26278s/12 iters), loss = 0.679617 +I0410 14:37:44.514750 18414 solver.cpp:237] Train net output #0: loss = 0.679617 (* 1 = 0.679617 loss) +I0410 14:37:44.514760 18414 sgd_solver.cpp:105] Iteration 9084, lr = 0.00165396 +I0410 14:37:49.393178 18414 solver.cpp:218] Iteration 9096 (2.45989 iter/s, 4.87828s/12 iters), loss = 0.773406 +I0410 14:37:49.393224 18414 solver.cpp:237] Train net output #0: loss = 0.773406 (* 1 = 0.773406 loss) +I0410 14:37:49.393234 18414 sgd_solver.cpp:105] Iteration 9096, lr = 0.00165003 +I0410 14:37:52.305719 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:54.365139 18414 solver.cpp:218] Iteration 9108 (2.41363 iter/s, 4.97176s/12 iters), loss = 0.63665 +I0410 14:37:54.365191 18414 solver.cpp:237] Train net output #0: loss = 0.63665 (* 1 = 0.63665 loss) +I0410 14:37:54.365206 18414 sgd_solver.cpp:105] Iteration 9108, lr = 0.00164612 +I0410 14:37:59.595955 18414 solver.cpp:218] Iteration 9120 (2.29419 iter/s, 5.23061s/12 iters), loss = 0.716428 +I0410 14:37:59.596007 18414 solver.cpp:237] Train net output #0: loss = 0.716428 (* 1 = 0.716428 loss) +I0410 14:37:59.596020 18414 sgd_solver.cpp:105] Iteration 9120, lr = 0.00164221 +I0410 14:38:04.513991 18414 solver.cpp:218] Iteration 9132 (2.4401 iter/s, 4.91782s/12 iters), loss = 0.625302 +I0410 14:38:04.514048 18414 solver.cpp:237] Train net output #0: loss = 0.625302 (* 1 = 0.625302 loss) +I0410 14:38:04.514060 18414 sgd_solver.cpp:105] Iteration 9132, lr = 0.00163831 +I0410 14:38:09.509104 18414 solver.cpp:218] Iteration 9144 (2.40245 iter/s, 4.99491s/12 iters), loss = 0.739622 +I0410 14:38:09.509161 18414 solver.cpp:237] Train net output #0: loss = 0.739622 (* 1 = 0.739622 loss) +I0410 14:38:09.509176 18414 sgd_solver.cpp:105] Iteration 9144, lr = 0.00163442 +I0410 14:38:14.528131 18414 solver.cpp:218] Iteration 9156 (2.391 iter/s, 5.01881s/12 iters), loss = 0.899157 +I0410 14:38:14.528256 18414 solver.cpp:237] Train net output #0: loss = 0.899157 (* 1 = 0.899157 loss) +I0410 14:38:14.528270 18414 sgd_solver.cpp:105] Iteration 9156, lr = 0.00163054 +I0410 14:38:19.505203 18414 solver.cpp:218] Iteration 9168 (2.41119 iter/s, 4.9768s/12 iters), loss = 0.768072 +I0410 14:38:19.505256 18414 solver.cpp:237] Train net output #0: loss = 0.768072 (* 1 = 0.768072 loss) +I0410 14:38:19.505267 18414 sgd_solver.cpp:105] Iteration 9168, lr = 0.00162667 +I0410 14:38:23.998102 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9180.caffemodel +I0410 14:38:24.324663 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9180.solverstate +I0410 14:38:24.535616 18414 solver.cpp:330] Iteration 9180, Testing net (#0) +I0410 14:38:24.535641 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:38:25.409303 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:38:28.993861 18414 solver.cpp:397] Test net output #0: accuracy = 0.54473 +I0410 14:38:28.993913 18414 solver.cpp:397] Test net output #1: loss = 1.99985 (* 1 = 1.99985 loss) +I0410 14:38:29.077008 18414 solver.cpp:218] Iteration 9180 (1.25373 iter/s, 9.57148s/12 iters), loss = 0.632207 +I0410 14:38:29.077065 18414 solver.cpp:237] Train net output #0: loss = 0.632207 (* 1 = 0.632207 loss) +I0410 14:38:29.077078 18414 sgd_solver.cpp:105] Iteration 9180, lr = 0.00162281 +I0410 14:38:33.473417 18414 solver.cpp:218] Iteration 9192 (2.72962 iter/s, 4.39622s/12 iters), loss = 0.826682 +I0410 14:38:33.473464 18414 solver.cpp:237] Train net output #0: loss = 0.826682 (* 1 = 0.826682 loss) +I0410 14:38:33.473474 18414 sgd_solver.cpp:105] Iteration 9192, lr = 0.00161895 +I0410 14:38:38.440662 18414 solver.cpp:218] Iteration 9204 (2.41592 iter/s, 4.96704s/12 iters), loss = 0.635372 +I0410 14:38:38.440721 18414 solver.cpp:237] Train net output #0: loss = 0.635372 (* 1 = 0.635372 loss) +I0410 14:38:38.440735 18414 sgd_solver.cpp:105] Iteration 9204, lr = 0.00161511 +I0410 14:38:38.513849 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:38:43.443893 18414 solver.cpp:218] Iteration 9216 (2.39855 iter/s, 5.00302s/12 iters), loss = 0.785794 +I0410 14:38:43.443948 18414 solver.cpp:237] Train net output #0: loss = 0.785794 (* 1 = 0.785794 loss) +I0410 14:38:43.443960 18414 sgd_solver.cpp:105] Iteration 9216, lr = 0.00161128 +I0410 14:38:48.450665 18414 solver.cpp:218] Iteration 9228 (2.39685 iter/s, 5.00657s/12 iters), loss = 0.525295 +I0410 14:38:48.450800 18414 solver.cpp:237] Train net output #0: loss = 0.525295 (* 1 = 0.525295 loss) +I0410 14:38:48.450810 18414 sgd_solver.cpp:105] Iteration 9228, lr = 0.00160745 +I0410 14:38:53.415324 18414 solver.cpp:218] Iteration 9240 (2.41722 iter/s, 4.96437s/12 iters), loss = 0.434166 +I0410 14:38:53.415380 18414 solver.cpp:237] Train net output #0: loss = 0.434166 (* 1 = 0.434166 loss) +I0410 14:38:53.415393 18414 sgd_solver.cpp:105] Iteration 9240, lr = 0.00160363 +I0410 14:38:58.445546 18414 solver.cpp:218] Iteration 9252 (2.38568 iter/s, 5.03001s/12 iters), loss = 0.694101 +I0410 14:38:58.445598 18414 solver.cpp:237] Train net output #0: loss = 0.694101 (* 1 = 0.694101 loss) +I0410 14:38:58.445608 18414 sgd_solver.cpp:105] Iteration 9252, lr = 0.00159983 +I0410 14:39:03.444638 18414 solver.cpp:218] Iteration 9264 (2.40053 iter/s, 4.99889s/12 iters), loss = 0.589266 +I0410 14:39:03.444694 18414 solver.cpp:237] Train net output #0: loss = 0.589266 (* 1 = 0.589266 loss) +I0410 14:39:03.444707 18414 sgd_solver.cpp:105] Iteration 9264, lr = 0.00159603 +I0410 14:39:08.389410 18414 solver.cpp:218] Iteration 9276 (2.42691 iter/s, 4.94456s/12 iters), loss = 0.786945 +I0410 14:39:08.389470 18414 solver.cpp:237] Train net output #0: loss = 0.786945 (* 1 = 0.786945 loss) +I0410 14:39:08.389483 18414 sgd_solver.cpp:105] Iteration 9276, lr = 0.00159224 +I0410 14:39:10.408373 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9282.caffemodel +I0410 14:39:10.737116 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9282.solverstate +I0410 14:39:10.946974 18414 solver.cpp:330] Iteration 9282, Testing net (#0) +I0410 14:39:10.947001 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:39:11.753351 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:39:15.493651 18414 solver.cpp:397] Test net output #0: accuracy = 0.571691 +I0410 14:39:15.493700 18414 solver.cpp:397] Test net output #1: loss = 1.83631 (* 1 = 1.83631 loss) +I0410 14:39:17.250289 18414 solver.cpp:218] Iteration 9288 (1.35432 iter/s, 8.86056s/12 iters), loss = 0.68914 +I0410 14:39:17.250355 18414 solver.cpp:237] Train net output #0: loss = 0.68914 (* 1 = 0.68914 loss) +I0410 14:39:17.250368 18414 sgd_solver.cpp:105] Iteration 9288, lr = 0.00158846 +I0410 14:39:22.132295 18414 solver.cpp:218] Iteration 9300 (2.45812 iter/s, 4.88179s/12 iters), loss = 0.442613 +I0410 14:39:22.132797 18414 solver.cpp:237] Train net output #0: loss = 0.442613 (* 1 = 0.442613 loss) +I0410 14:39:22.132808 18414 sgd_solver.cpp:105] Iteration 9300, lr = 0.00158469 +I0410 14:39:24.279884 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:39:26.993129 18414 solver.cpp:218] Iteration 9312 (2.46904 iter/s, 4.86018s/12 iters), loss = 0.662062 +I0410 14:39:26.993188 18414 solver.cpp:237] Train net output #0: loss = 0.662062 (* 1 = 0.662062 loss) +I0410 14:39:26.993201 18414 sgd_solver.cpp:105] Iteration 9312, lr = 0.00158092 +I0410 14:39:31.822940 18414 solver.cpp:218] Iteration 9324 (2.48468 iter/s, 4.8296s/12 iters), loss = 0.699768 +I0410 14:39:31.822999 18414 solver.cpp:237] Train net output #0: loss = 0.699768 (* 1 = 0.699768 loss) +I0410 14:39:31.823010 18414 sgd_solver.cpp:105] Iteration 9324, lr = 0.00157717 +I0410 14:39:36.682313 18414 solver.cpp:218] Iteration 9336 (2.46956 iter/s, 4.85916s/12 iters), loss = 0.67838 +I0410 14:39:36.682370 18414 solver.cpp:237] Train net output #0: loss = 0.67838 (* 1 = 0.67838 loss) +I0410 14:39:36.682384 18414 sgd_solver.cpp:105] Iteration 9336, lr = 0.00157343 +I0410 14:39:41.550693 18414 solver.cpp:218] Iteration 9348 (2.46499 iter/s, 4.86818s/12 iters), loss = 0.685725 +I0410 14:39:41.550753 18414 solver.cpp:237] Train net output #0: loss = 0.685725 (* 1 = 0.685725 loss) +I0410 14:39:41.550765 18414 sgd_solver.cpp:105] Iteration 9348, lr = 0.00156969 +I0410 14:39:46.400058 18414 solver.cpp:218] Iteration 9360 (2.47466 iter/s, 4.84916s/12 iters), loss = 0.716692 +I0410 14:39:46.400117 18414 solver.cpp:237] Train net output #0: loss = 0.716692 (* 1 = 0.716692 loss) +I0410 14:39:46.400131 18414 sgd_solver.cpp:105] Iteration 9360, lr = 0.00156596 +I0410 14:39:51.260393 18414 solver.cpp:218] Iteration 9372 (2.46907 iter/s, 4.86012s/12 iters), loss = 0.836972 +I0410 14:39:51.260453 18414 solver.cpp:237] Train net output #0: loss = 0.836972 (* 1 = 0.836972 loss) +I0410 14:39:51.260465 18414 sgd_solver.cpp:105] Iteration 9372, lr = 0.00156225 +I0410 14:39:55.701588 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9384.caffemodel +I0410 14:39:56.027362 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9384.solverstate +I0410 14:39:56.234083 18414 solver.cpp:330] Iteration 9384, Testing net (#0) +I0410 14:39:56.234109 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:39:57.003648 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:00.710093 18414 solver.cpp:397] Test net output #0: accuracy = 0.560662 +I0410 14:40:00.710131 18414 solver.cpp:397] Test net output #1: loss = 1.88304 (* 1 = 1.88304 loss) +I0410 14:40:00.793226 18414 solver.cpp:218] Iteration 9384 (1.25885 iter/s, 9.53249s/12 iters), loss = 0.624714 +I0410 14:40:00.793282 18414 solver.cpp:237] Train net output #0: loss = 0.624714 (* 1 = 0.624714 loss) +I0410 14:40:00.793294 18414 sgd_solver.cpp:105] Iteration 9384, lr = 0.00155854 +I0410 14:40:04.953572 18414 solver.cpp:218] Iteration 9396 (2.88451 iter/s, 4.16016s/12 iters), loss = 0.638775 +I0410 14:40:04.953625 18414 solver.cpp:237] Train net output #0: loss = 0.638775 (* 1 = 0.638775 loss) +I0410 14:40:04.953637 18414 sgd_solver.cpp:105] Iteration 9396, lr = 0.00155484 +I0410 14:40:09.232969 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:09.877050 18414 solver.cpp:218] Iteration 9408 (2.4374 iter/s, 4.92328s/12 iters), loss = 0.608639 +I0410 14:40:09.877096 18414 solver.cpp:237] Train net output #0: loss = 0.608639 (* 1 = 0.608639 loss) +I0410 14:40:09.877106 18414 sgd_solver.cpp:105] Iteration 9408, lr = 0.00155114 +I0410 14:40:14.784365 18414 solver.cpp:218] Iteration 9420 (2.44543 iter/s, 4.90712s/12 iters), loss = 0.597965 +I0410 14:40:14.784420 18414 solver.cpp:237] Train net output #0: loss = 0.597965 (* 1 = 0.597965 loss) +I0410 14:40:14.784432 18414 sgd_solver.cpp:105] Iteration 9420, lr = 0.00154746 +I0410 14:40:19.716338 18414 solver.cpp:218] Iteration 9432 (2.43321 iter/s, 4.93177s/12 iters), loss = 0.600003 +I0410 14:40:19.716389 18414 solver.cpp:237] Train net output #0: loss = 0.600003 (* 1 = 0.600003 loss) +I0410 14:40:19.716400 18414 sgd_solver.cpp:105] Iteration 9432, lr = 0.00154379 +I0410 14:40:24.617851 18414 solver.cpp:218] Iteration 9444 (2.44833 iter/s, 4.90131s/12 iters), loss = 0.57225 +I0410 14:40:24.617903 18414 solver.cpp:237] Train net output #0: loss = 0.57225 (* 1 = 0.57225 loss) +I0410 14:40:24.617914 18414 sgd_solver.cpp:105] Iteration 9444, lr = 0.00154012 +I0410 14:40:29.525718 18414 solver.cpp:218] Iteration 9456 (2.44516 iter/s, 4.90766s/12 iters), loss = 0.699787 +I0410 14:40:29.525878 18414 solver.cpp:237] Train net output #0: loss = 0.699787 (* 1 = 0.699787 loss) +I0410 14:40:29.525892 18414 sgd_solver.cpp:105] Iteration 9456, lr = 0.00153647 +I0410 14:40:34.457267 18414 solver.cpp:218] Iteration 9468 (2.43347 iter/s, 4.93124s/12 iters), loss = 0.605433 +I0410 14:40:34.457312 18414 solver.cpp:237] Train net output #0: loss = 0.605433 (* 1 = 0.605433 loss) +I0410 14:40:34.457322 18414 sgd_solver.cpp:105] Iteration 9468, lr = 0.00153282 +I0410 14:40:39.382369 18414 solver.cpp:218] Iteration 9480 (2.43659 iter/s, 4.92491s/12 iters), loss = 0.709078 +I0410 14:40:39.382417 18414 solver.cpp:237] Train net output #0: loss = 0.709078 (* 1 = 0.709078 loss) +I0410 14:40:39.382427 18414 sgd_solver.cpp:105] Iteration 9480, lr = 0.00152918 +I0410 14:40:41.640817 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9486.caffemodel +I0410 14:40:42.383343 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9486.solverstate +I0410 14:40:42.778234 18414 solver.cpp:330] Iteration 9486, Testing net (#0) +I0410 14:40:42.778261 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:40:43.509119 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:47.237108 18414 solver.cpp:397] Test net output #0: accuracy = 0.551471 +I0410 14:40:47.237143 18414 solver.cpp:397] Test net output #1: loss = 1.8796 (* 1 = 1.8796 loss) +I0410 14:40:48.963083 18414 solver.cpp:218] Iteration 9492 (1.25256 iter/s, 9.58038s/12 iters), loss = 0.60428 +I0410 14:40:48.963140 18414 solver.cpp:237] Train net output #0: loss = 0.60428 (* 1 = 0.60428 loss) +I0410 14:40:48.963150 18414 sgd_solver.cpp:105] Iteration 9492, lr = 0.00152555 +I0410 14:40:54.035302 18414 solver.cpp:218] Iteration 9504 (2.36593 iter/s, 5.07201s/12 iters), loss = 0.42748 +I0410 14:40:54.035360 18414 solver.cpp:237] Train net output #0: loss = 0.42748 (* 1 = 0.42748 loss) +I0410 14:40:54.035374 18414 sgd_solver.cpp:105] Iteration 9504, lr = 0.00152193 +I0410 14:40:55.472649 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:58.901587 18414 solver.cpp:218] Iteration 9516 (2.46606 iter/s, 4.86607s/12 iters), loss = 0.876114 +I0410 14:40:58.901645 18414 solver.cpp:237] Train net output #0: loss = 0.876114 (* 1 = 0.876114 loss) +I0410 14:40:58.901659 18414 sgd_solver.cpp:105] Iteration 9516, lr = 0.00151831 +I0410 14:41:03.801429 18414 solver.cpp:218] Iteration 9528 (2.44916 iter/s, 4.89963s/12 iters), loss = 0.567398 +I0410 14:41:03.801554 18414 solver.cpp:237] Train net output #0: loss = 0.567398 (* 1 = 0.567398 loss) +I0410 14:41:03.801568 18414 sgd_solver.cpp:105] Iteration 9528, lr = 0.00151471 +I0410 14:41:08.680946 18414 solver.cpp:218] Iteration 9540 (2.4594 iter/s, 4.87924s/12 iters), loss = 0.425231 +I0410 14:41:08.680999 18414 solver.cpp:237] Train net output #0: loss = 0.425231 (* 1 = 0.425231 loss) +I0410 14:41:08.681010 18414 sgd_solver.cpp:105] Iteration 9540, lr = 0.00151111 +I0410 14:41:13.644317 18414 solver.cpp:218] Iteration 9552 (2.41781 iter/s, 4.96317s/12 iters), loss = 0.767437 +I0410 14:41:13.644366 18414 solver.cpp:237] Train net output #0: loss = 0.767437 (* 1 = 0.767437 loss) +I0410 14:41:13.644376 18414 sgd_solver.cpp:105] Iteration 9552, lr = 0.00150752 +I0410 14:41:18.714700 18414 solver.cpp:218] Iteration 9564 (2.36678 iter/s, 5.07018s/12 iters), loss = 0.594944 +I0410 14:41:18.714745 18414 solver.cpp:237] Train net output #0: loss = 0.594944 (* 1 = 0.594944 loss) +I0410 14:41:18.714754 18414 sgd_solver.cpp:105] Iteration 9564, lr = 0.00150395 +I0410 14:41:23.818776 18414 solver.cpp:218] Iteration 9576 (2.35116 iter/s, 5.10387s/12 iters), loss = 0.59932 +I0410 14:41:23.818830 18414 solver.cpp:237] Train net output #0: loss = 0.59932 (* 1 = 0.59932 loss) +I0410 14:41:23.818843 18414 sgd_solver.cpp:105] Iteration 9576, lr = 0.00150037 +I0410 14:41:28.473346 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9588.caffemodel +I0410 14:41:28.789641 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9588.solverstate +I0410 14:41:28.996212 18414 solver.cpp:330] Iteration 9588, Testing net (#0) +I0410 14:41:28.996240 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:41:29.821887 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:33.633633 18414 solver.cpp:397] Test net output #0: accuracy = 0.573529 +I0410 14:41:33.633671 18414 solver.cpp:397] Test net output #1: loss = 1.79167 (* 1 = 1.79167 loss) +I0410 14:41:33.716745 18414 solver.cpp:218] Iteration 9588 (1.21241 iter/s, 9.89762s/12 iters), loss = 0.525336 +I0410 14:41:33.716804 18414 solver.cpp:237] Train net output #0: loss = 0.525336 (* 1 = 0.525336 loss) +I0410 14:41:33.716818 18414 sgd_solver.cpp:105] Iteration 9588, lr = 0.00149681 +I0410 14:41:38.136175 18414 solver.cpp:218] Iteration 9600 (2.7154 iter/s, 4.41923s/12 iters), loss = 0.701471 +I0410 14:41:38.136345 18414 solver.cpp:237] Train net output #0: loss = 0.701471 (* 1 = 0.701471 loss) +I0410 14:41:38.136360 18414 sgd_solver.cpp:105] Iteration 9600, lr = 0.00149326 +I0410 14:41:41.721050 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:43.091298 18414 solver.cpp:218] Iteration 9612 (2.42189 iter/s, 4.95481s/12 iters), loss = 0.56613 +I0410 14:41:43.091354 18414 solver.cpp:237] Train net output #0: loss = 0.56613 (* 1 = 0.56613 loss) +I0410 14:41:43.091365 18414 sgd_solver.cpp:105] Iteration 9612, lr = 0.00148971 +I0410 14:41:48.064365 18414 solver.cpp:218] Iteration 9624 (2.4131 iter/s, 4.97286s/12 iters), loss = 0.500358 +I0410 14:41:48.064406 18414 solver.cpp:237] Train net output #0: loss = 0.500358 (* 1 = 0.500358 loss) +I0410 14:41:48.064415 18414 sgd_solver.cpp:105] Iteration 9624, lr = 0.00148618 +I0410 14:41:52.996464 18414 solver.cpp:218] Iteration 9636 (2.43314 iter/s, 4.9319s/12 iters), loss = 0.649055 +I0410 14:41:52.996518 18414 solver.cpp:237] Train net output #0: loss = 0.649055 (* 1 = 0.649055 loss) +I0410 14:41:52.996532 18414 sgd_solver.cpp:105] Iteration 9636, lr = 0.00148265 +I0410 14:41:57.891806 18414 solver.cpp:218] Iteration 9648 (2.45141 iter/s, 4.89513s/12 iters), loss = 0.616539 +I0410 14:41:57.891865 18414 solver.cpp:237] Train net output #0: loss = 0.616539 (* 1 = 0.616539 loss) +I0410 14:41:57.891878 18414 sgd_solver.cpp:105] Iteration 9648, lr = 0.00147913 +I0410 14:42:02.824293 18414 solver.cpp:218] Iteration 9660 (2.43295 iter/s, 4.93228s/12 iters), loss = 0.496746 +I0410 14:42:02.824349 18414 solver.cpp:237] Train net output #0: loss = 0.496746 (* 1 = 0.496746 loss) +I0410 14:42:02.824364 18414 sgd_solver.cpp:105] Iteration 9660, lr = 0.00147562 +I0410 14:42:07.703495 18414 solver.cpp:218] Iteration 9672 (2.45953 iter/s, 4.87899s/12 iters), loss = 0.71815 +I0410 14:42:07.703550 18414 solver.cpp:237] Train net output #0: loss = 0.71815 (* 1 = 0.71815 loss) +I0410 14:42:07.703562 18414 sgd_solver.cpp:105] Iteration 9672, lr = 0.00147211 +I0410 14:42:12.726176 18414 solver.cpp:218] Iteration 9684 (2.38926 iter/s, 5.02247s/12 iters), loss = 0.504905 +I0410 14:42:12.726274 18414 solver.cpp:237] Train net output #0: loss = 0.504905 (* 1 = 0.504905 loss) +I0410 14:42:12.726284 18414 sgd_solver.cpp:105] Iteration 9684, lr = 0.00146862 +I0410 14:42:14.778883 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9690.caffemodel +I0410 14:42:15.082206 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9690.solverstate +I0410 14:42:15.286859 18414 solver.cpp:330] Iteration 9690, Testing net (#0) +I0410 14:42:15.286883 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:42:15.930521 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:42:18.415040 18414 blocking_queue.cpp:49] Waiting for data +I0410 14:42:19.756588 18414 solver.cpp:397] Test net output #0: accuracy = 0.568627 +I0410 14:42:19.756633 18414 solver.cpp:397] Test net output #1: loss = 1.86029 (* 1 = 1.86029 loss) +I0410 14:42:21.713918 18414 solver.cpp:218] Iteration 9696 (1.33521 iter/s, 8.98738s/12 iters), loss = 0.521212 +I0410 14:42:21.713992 18414 solver.cpp:237] Train net output #0: loss = 0.521212 (* 1 = 0.521212 loss) +I0410 14:42:21.714006 18414 sgd_solver.cpp:105] Iteration 9696, lr = 0.00146513 +I0410 14:42:26.858467 18414 solver.cpp:218] Iteration 9708 (2.33267 iter/s, 5.14432s/12 iters), loss = 0.62321 +I0410 14:42:26.858518 18414 solver.cpp:237] Train net output #0: loss = 0.62321 (* 1 = 0.62321 loss) +I0410 14:42:26.858530 18414 sgd_solver.cpp:105] Iteration 9708, lr = 0.00146165 +I0410 14:42:27.613322 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:42:31.847939 18414 solver.cpp:218] Iteration 9720 (2.40517 iter/s, 4.98926s/12 iters), loss = 0.498186 +I0410 14:42:31.847990 18414 solver.cpp:237] Train net output #0: loss = 0.498186 (* 1 = 0.498186 loss) +I0410 14:42:31.848001 18414 sgd_solver.cpp:105] Iteration 9720, lr = 0.00145818 +I0410 14:42:36.806617 18414 solver.cpp:218] Iteration 9732 (2.4201 iter/s, 4.95847s/12 iters), loss = 0.734831 +I0410 14:42:36.806679 18414 solver.cpp:237] Train net output #0: loss = 0.734831 (* 1 = 0.734831 loss) +I0410 14:42:36.806694 18414 sgd_solver.cpp:105] Iteration 9732, lr = 0.00145472 +I0410 14:42:41.722359 18414 solver.cpp:218] Iteration 9744 (2.44125 iter/s, 4.91552s/12 iters), loss = 0.727718 +I0410 14:42:41.722411 18414 solver.cpp:237] Train net output #0: loss = 0.727718 (* 1 = 0.727718 loss) +I0410 14:42:41.722421 18414 sgd_solver.cpp:105] Iteration 9744, lr = 0.00145127 +I0410 14:42:46.816112 18414 solver.cpp:218] Iteration 9756 (2.35592 iter/s, 5.09354s/12 iters), loss = 0.962466 +I0410 14:42:46.816242 18414 solver.cpp:237] Train net output #0: loss = 0.962466 (* 1 = 0.962466 loss) +I0410 14:42:46.816252 18414 sgd_solver.cpp:105] Iteration 9756, lr = 0.00144782 +I0410 14:42:51.760136 18414 solver.cpp:218] Iteration 9768 (2.42731 iter/s, 4.94373s/12 iters), loss = 0.749103 +I0410 14:42:51.760206 18414 solver.cpp:237] Train net output #0: loss = 0.749103 (* 1 = 0.749103 loss) +I0410 14:42:51.760224 18414 sgd_solver.cpp:105] Iteration 9768, lr = 0.00144438 +I0410 14:42:56.676993 18414 solver.cpp:218] Iteration 9780 (2.44069 iter/s, 4.91664s/12 iters), loss = 0.784109 +I0410 14:42:56.677043 18414 solver.cpp:237] Train net output #0: loss = 0.784109 (* 1 = 0.784109 loss) +I0410 14:42:56.677057 18414 sgd_solver.cpp:105] Iteration 9780, lr = 0.00144095 +I0410 14:43:01.200186 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9792.caffemodel +I0410 14:43:01.503175 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9792.solverstate +I0410 14:43:01.704700 18414 solver.cpp:330] Iteration 9792, Testing net (#0) +I0410 14:43:01.704730 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:43:02.317991 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:43:06.171291 18414 solver.cpp:397] Test net output #0: accuracy = 0.568015 +I0410 14:43:06.171348 18414 solver.cpp:397] Test net output #1: loss = 1.84652 (* 1 = 1.84652 loss) +I0410 14:43:06.254473 18414 solver.cpp:218] Iteration 9792 (1.25298 iter/s, 9.57714s/12 iters), loss = 0.567772 +I0410 14:43:06.254528 18414 solver.cpp:237] Train net output #0: loss = 0.567772 (* 1 = 0.567772 loss) +I0410 14:43:06.254539 18414 sgd_solver.cpp:105] Iteration 9792, lr = 0.00143753 +I0410 14:43:10.627009 18414 solver.cpp:218] Iteration 9804 (2.74453 iter/s, 4.37234s/12 iters), loss = 0.613607 +I0410 14:43:10.627068 18414 solver.cpp:237] Train net output #0: loss = 0.613607 (* 1 = 0.613607 loss) +I0410 14:43:10.627079 18414 sgd_solver.cpp:105] Iteration 9804, lr = 0.00143412 +I0410 14:43:13.606930 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:43:15.624326 18414 solver.cpp:218] Iteration 9816 (2.40139 iter/s, 4.9971s/12 iters), loss = 0.525517 +I0410 14:43:15.624382 18414 solver.cpp:237] Train net output #0: loss = 0.525517 (* 1 = 0.525517 loss) +I0410 14:43:15.624395 18414 sgd_solver.cpp:105] Iteration 9816, lr = 0.00143072 +I0410 14:43:20.582648 18414 solver.cpp:218] Iteration 9828 (2.42027 iter/s, 4.95811s/12 iters), loss = 0.396072 +I0410 14:43:20.582787 18414 solver.cpp:237] Train net output #0: loss = 0.396072 (* 1 = 0.396072 loss) +I0410 14:43:20.582798 18414 sgd_solver.cpp:105] Iteration 9828, lr = 0.00142732 +I0410 14:43:25.567440 18414 solver.cpp:218] Iteration 9840 (2.40746 iter/s, 4.9845s/12 iters), loss = 0.544813 +I0410 14:43:25.567493 18414 solver.cpp:237] Train net output #0: loss = 0.544813 (* 1 = 0.544813 loss) +I0410 14:43:25.567504 18414 sgd_solver.cpp:105] Iteration 9840, lr = 0.00142393 +I0410 14:43:30.500474 18414 solver.cpp:218] Iteration 9852 (2.43268 iter/s, 4.93282s/12 iters), loss = 0.601261 +I0410 14:43:30.500535 18414 solver.cpp:237] Train net output #0: loss = 0.601261 (* 1 = 0.601261 loss) +I0410 14:43:30.500551 18414 sgd_solver.cpp:105] Iteration 9852, lr = 0.00142055 +I0410 14:43:35.501883 18414 solver.cpp:218] Iteration 9864 (2.39943 iter/s, 5.00119s/12 iters), loss = 0.58732 +I0410 14:43:35.501936 18414 solver.cpp:237] Train net output #0: loss = 0.58732 (* 1 = 0.58732 loss) +I0410 14:43:35.501945 18414 sgd_solver.cpp:105] Iteration 9864, lr = 0.00141718 +I0410 14:43:40.534276 18414 solver.cpp:218] Iteration 9876 (2.38465 iter/s, 5.03218s/12 iters), loss = 0.682785 +I0410 14:43:40.534327 18414 solver.cpp:237] Train net output #0: loss = 0.682785 (* 1 = 0.682785 loss) +I0410 14:43:40.534337 18414 sgd_solver.cpp:105] Iteration 9876, lr = 0.00141381 +I0410 14:43:45.574187 18414 solver.cpp:218] Iteration 9888 (2.38109 iter/s, 5.0397s/12 iters), loss = 0.551942 +I0410 14:43:45.574240 18414 solver.cpp:237] Train net output #0: loss = 0.551942 (* 1 = 0.551942 loss) +I0410 14:43:45.574252 18414 sgd_solver.cpp:105] Iteration 9888, lr = 0.00141045 +I0410 14:43:47.610139 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9894.caffemodel +I0410 14:43:48.008137 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9894.solverstate +I0410 14:43:48.213501 18414 solver.cpp:330] Iteration 9894, Testing net (#0) +I0410 14:43:48.213521 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:43:48.793740 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:43:52.706112 18414 solver.cpp:397] Test net output #0: accuracy = 0.559436 +I0410 14:43:52.706235 18414 solver.cpp:397] Test net output #1: loss = 1.92606 (* 1 = 1.92606 loss) +I0410 14:43:54.461333 18414 solver.cpp:218] Iteration 9900 (1.35031 iter/s, 8.88683s/12 iters), loss = 0.611119 +I0410 14:43:54.461380 18414 solver.cpp:237] Train net output #0: loss = 0.611119 (* 1 = 0.611119 loss) +I0410 14:43:54.461391 18414 sgd_solver.cpp:105] Iteration 9900, lr = 0.00140711 +I0410 14:43:59.410238 18414 solver.cpp:218] Iteration 9912 (2.42488 iter/s, 4.94869s/12 iters), loss = 0.62072 +I0410 14:43:59.410288 18414 solver.cpp:237] Train net output #0: loss = 0.62072 (* 1 = 0.62072 loss) +I0410 14:43:59.410300 18414 sgd_solver.cpp:105] Iteration 9912, lr = 0.00140377 +I0410 14:43:59.509263 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:04.364137 18414 solver.cpp:218] Iteration 9924 (2.42243 iter/s, 4.9537s/12 iters), loss = 0.478863 +I0410 14:44:04.364183 18414 solver.cpp:237] Train net output #0: loss = 0.478863 (* 1 = 0.478863 loss) +I0410 14:44:04.364192 18414 sgd_solver.cpp:105] Iteration 9924, lr = 0.00140043 +I0410 14:44:09.343176 18414 solver.cpp:218] Iteration 9936 (2.4102 iter/s, 4.97883s/12 iters), loss = 0.546958 +I0410 14:44:09.343233 18414 solver.cpp:237] Train net output #0: loss = 0.546958 (* 1 = 0.546958 loss) +I0410 14:44:09.343245 18414 sgd_solver.cpp:105] Iteration 9936, lr = 0.00139711 +I0410 14:44:14.313755 18414 solver.cpp:218] Iteration 9948 (2.41431 iter/s, 4.97036s/12 iters), loss = 0.544818 +I0410 14:44:14.313825 18414 solver.cpp:237] Train net output #0: loss = 0.544818 (* 1 = 0.544818 loss) +I0410 14:44:14.313843 18414 sgd_solver.cpp:105] Iteration 9948, lr = 0.00139379 +I0410 14:44:19.240980 18414 solver.cpp:218] Iteration 9960 (2.43556 iter/s, 4.92701s/12 iters), loss = 0.592983 +I0410 14:44:19.241040 18414 solver.cpp:237] Train net output #0: loss = 0.592983 (* 1 = 0.592983 loss) +I0410 14:44:19.241055 18414 sgd_solver.cpp:105] Iteration 9960, lr = 0.00139048 +I0410 14:44:24.221575 18414 solver.cpp:218] Iteration 9972 (2.40945 iter/s, 4.98038s/12 iters), loss = 0.577307 +I0410 14:44:24.221745 18414 solver.cpp:237] Train net output #0: loss = 0.577307 (* 1 = 0.577307 loss) +I0410 14:44:24.221760 18414 sgd_solver.cpp:105] Iteration 9972, lr = 0.00138718 +I0410 14:44:29.275480 18414 solver.cpp:218] Iteration 9984 (2.37455 iter/s, 5.05358s/12 iters), loss = 0.61398 +I0410 14:44:29.275540 18414 solver.cpp:237] Train net output #0: loss = 0.61398 (* 1 = 0.61398 loss) +I0410 14:44:29.275552 18414 sgd_solver.cpp:105] Iteration 9984, lr = 0.00138389 +I0410 14:44:33.798441 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9996.caffemodel +I0410 14:44:34.099210 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9996.solverstate +I0410 14:44:34.297539 18414 solver.cpp:330] Iteration 9996, Testing net (#0) +I0410 14:44:34.297569 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:44:34.722812 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:38.758143 18414 solver.cpp:397] Test net output #0: accuracy = 0.571691 +I0410 14:44:38.758180 18414 solver.cpp:397] Test net output #1: loss = 1.84927 (* 1 = 1.84927 loss) +I0410 14:44:38.841049 18414 solver.cpp:218] Iteration 9996 (1.25455 iter/s, 9.56522s/12 iters), loss = 0.555609 +I0410 14:44:38.841110 18414 solver.cpp:237] Train net output #0: loss = 0.555609 (* 1 = 0.555609 loss) +I0410 14:44:38.841123 18414 sgd_solver.cpp:105] Iteration 9996, lr = 0.0013806 +I0410 14:44:42.932351 18414 solver.cpp:218] Iteration 10008 (2.93319 iter/s, 4.09111s/12 iters), loss = 0.572214 +I0410 14:44:42.932410 18414 solver.cpp:237] Train net output #0: loss = 0.572214 (* 1 = 0.572214 loss) +I0410 14:44:42.932421 18414 sgd_solver.cpp:105] Iteration 10008, lr = 0.00137732 +I0410 14:44:45.109884 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:47.807368 18414 solver.cpp:218] Iteration 10020 (2.46164 iter/s, 4.8748s/12 iters), loss = 0.49675 +I0410 14:44:47.807411 18414 solver.cpp:237] Train net output #0: loss = 0.49675 (* 1 = 0.49675 loss) +I0410 14:44:47.807420 18414 sgd_solver.cpp:105] Iteration 10020, lr = 0.00137405 +I0410 14:44:53.091578 18414 solver.cpp:218] Iteration 10032 (2.27101 iter/s, 5.284s/12 iters), loss = 0.604721 +I0410 14:44:53.091634 18414 solver.cpp:237] Train net output #0: loss = 0.604721 (* 1 = 0.604721 loss) +I0410 14:44:53.091650 18414 sgd_solver.cpp:105] Iteration 10032, lr = 0.00137079 +I0410 14:44:58.103410 18414 solver.cpp:218] Iteration 10044 (2.39444 iter/s, 5.01162s/12 iters), loss = 0.518714 +I0410 14:44:58.103500 18414 solver.cpp:237] Train net output #0: loss = 0.518714 (* 1 = 0.518714 loss) +I0410 14:44:58.103511 18414 sgd_solver.cpp:105] Iteration 10044, lr = 0.00136754 +I0410 14:45:03.016285 18414 solver.cpp:218] Iteration 10056 (2.44269 iter/s, 4.91263s/12 iters), loss = 0.49 +I0410 14:45:03.016347 18414 solver.cpp:237] Train net output #0: loss = 0.49 (* 1 = 0.49 loss) +I0410 14:45:03.016360 18414 sgd_solver.cpp:105] Iteration 10056, lr = 0.00136429 +I0410 14:45:07.932196 18414 solver.cpp:218] Iteration 10068 (2.44116 iter/s, 4.91569s/12 iters), loss = 0.432297 +I0410 14:45:07.932256 18414 solver.cpp:237] Train net output #0: loss = 0.432297 (* 1 = 0.432297 loss) +I0410 14:45:07.932269 18414 sgd_solver.cpp:105] Iteration 10068, lr = 0.00136105 +I0410 14:45:12.838721 18414 solver.cpp:218] Iteration 10080 (2.44583 iter/s, 4.90631s/12 iters), loss = 0.688353 +I0410 14:45:12.838780 18414 solver.cpp:237] Train net output #0: loss = 0.688353 (* 1 = 0.688353 loss) +I0410 14:45:12.838793 18414 sgd_solver.cpp:105] Iteration 10080, lr = 0.00135782 +I0410 14:45:17.776590 18414 solver.cpp:218] Iteration 10092 (2.43031 iter/s, 4.93765s/12 iters), loss = 0.485915 +I0410 14:45:17.776652 18414 solver.cpp:237] Train net output #0: loss = 0.485915 (* 1 = 0.485915 loss) +I0410 14:45:17.776666 18414 sgd_solver.cpp:105] Iteration 10092, lr = 0.0013546 +I0410 14:45:19.833076 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10098.caffemodel +I0410 14:45:20.160262 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10098.solverstate +I0410 14:45:20.372012 18414 solver.cpp:330] Iteration 10098, Testing net (#0) +I0410 14:45:20.372035 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:45:20.822044 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:45:24.743923 18414 solver.cpp:397] Test net output #0: accuracy = 0.5625 +I0410 14:45:24.743970 18414 solver.cpp:397] Test net output #1: loss = 1.93858 (* 1 = 1.93858 loss) +I0410 14:45:26.637703 18414 solver.cpp:218] Iteration 10104 (1.35428 iter/s, 8.86079s/12 iters), loss = 0.596084 +I0410 14:45:26.637749 18414 solver.cpp:237] Train net output #0: loss = 0.596084 (* 1 = 0.596084 loss) +I0410 14:45:26.637759 18414 sgd_solver.cpp:105] Iteration 10104, lr = 0.00135138 +I0410 14:45:30.896934 18418 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:45:31.510788 18414 solver.cpp:218] Iteration 10116 (2.46261 iter/s, 4.87288s/12 iters), loss = 0.559046 +I0410 14:45:31.510848 18414 solver.cpp:237] Train net output #0: loss = 0.559046 (* 1 = 0.559046 loss) +I0410 14:45:31.510862 18414 sgd_solver.cpp:105] Iteration 10116, lr = 0.00134817 +I0410 14:45:36.451548 18414 solver.cpp:218] Iteration 10128 (2.42888 iter/s, 4.94055s/12 iters), loss = 0.522692 +I0410 14:45:36.451588 18414 solver.cpp:237] Train net output #0: loss = 0.522692 (* 1 = 0.522692 loss) +I0410 14:45:36.451598 18414 sgd_solver.cpp:105] Iteration 10128, lr = 0.00134497 +I0410 14:45:41.439944 18414 solver.cpp:218] Iteration 10140 (2.40568 iter/s, 4.9882s/12 iters), loss = 0.562347 +I0410 14:45:41.439997 18414 solver.cpp:237] Train net output #0: loss = 0.562347 (* 1 = 0.562347 loss) +I0410 14:45:41.440011 18414 sgd_solver.cpp:105] Iteration 10140, lr = 0.00134178 +I0410 14:45:46.683318 18414 solver.cpp:218] Iteration 10152 (2.2887 iter/s, 5.24316s/12 iters), loss = 0.555397 +I0410 14:45:46.683362 18414 solver.cpp:237] Train net output #0: loss = 0.555397 (* 1 = 0.555397 loss) +I0410 14:45:46.683372 18414 sgd_solver.cpp:105] Iteration 10152, lr = 0.00133859 +I0410 14:45:51.560411 18414 solver.cpp:218] Iteration 10164 (2.46058 iter/s, 4.87689s/12 iters), loss = 0.699276 +I0410 14:45:51.560456 18414 solver.cpp:237] Train net output #0: loss = 0.699276 (* 1 = 0.699276 loss) +I0410 14:45:51.560465 18414 sgd_solver.cpp:105] Iteration 10164, lr = 0.00133541 +I0410 14:45:56.444880 18414 solver.cpp:218] Iteration 10176 (2.45687 iter/s, 4.88427s/12 iters), loss = 0.668431 +I0410 14:45:56.444936 18414 solver.cpp:237] Train net output #0: loss = 0.668431 (* 1 = 0.668431 loss) +I0410 14:45:56.444949 18414 sgd_solver.cpp:105] Iteration 10176, lr = 0.00133224 +I0410 14:46:01.356637 18414 solver.cpp:218] Iteration 10188 (2.44323 iter/s, 4.91154s/12 iters), loss = 0.551761 +I0410 14:46:01.356783 18414 solver.cpp:237] Train net output #0: loss = 0.551761 (* 1 = 0.551761 loss) +I0410 14:46:01.356798 18414 sgd_solver.cpp:105] Iteration 10188, lr = 0.00132908 +I0410 14:46:05.803455 18414 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10200.caffemodel +I0410 14:46:06.128473 18414 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10200.solverstate +I0410 14:46:06.363831 18414 solver.cpp:310] Iteration 10200, loss = 0.566473 +I0410 14:46:06.363865 18414 solver.cpp:330] Iteration 10200, Testing net (#0) +I0410 14:46:06.363874 18414 net.cpp:676] Ignoring source layer train-data +I0410 14:46:06.778292 18419 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:46:10.782084 18414 solver.cpp:397] Test net output #0: accuracy = 0.571078 +I0410 14:46:10.782135 18414 solver.cpp:397] Test net output #1: loss = 1.85916 (* 1 = 1.85916 loss) +I0410 14:46:10.782146 18414 solver.cpp:315] Optimization Done. +I0410 14:46:10.782153 18414 caffe.cpp:259] Optimization Done. diff --git a/cars/architecture-investigations/fc/2-layers/256/conf.csv b/cars/architecture-investigations/fc/2-layers/256/conf.csv new file mode 100644 index 0000000..441a4a7 --- /dev/null +++ b/cars/architecture-investigations/fc/2-layers/256/conf.csv @@ -0,0 +1,197 @@ +,AM General Hummer SUV 2000,Acura RL Sedan 2012,Acura TL Sedan 2012,Acura TL Type-S 2008,Acura TSX Sedan 2012,Acura Integra Type R 2001,Acura ZDX Hatchback 2012,Aston Martin V8 Vantage Convertible 2012,Aston Martin V8 Vantage Coupe 2012,Aston Martin Virage Convertible 2012,Aston Martin Virage Coupe 2012,Audi RS 4 Convertible 2008,Audi A5 Coupe 2012,Audi TTS Coupe 2012,Audi R8 Coupe 2012,Audi V8 Sedan 1994,Audi 100 Sedan 1994,Audi 100 Wagon 1994,Audi TT Hatchback 2011,Audi S6 Sedan 2011,Audi S5 Convertible 2012,Audi S5 Coupe 2012,Audi S4 Sedan 2012,Audi S4 Sedan 2007,Audi TT RS Coupe 2012,BMW ActiveHybrid 5 Sedan 2012,BMW 1 Series Convertible 2012,BMW 1 Series Coupe 2012,BMW 3 Series Sedan 2012,BMW 3 Series Wagon 2012,BMW 6 Series Convertible 2007,BMW X5 SUV 2007,BMW X6 SUV 2012,BMW M3 Coupe 2012,BMW M5 Sedan 2010,BMW M6 Convertible 2010,BMW X3 SUV 2012,BMW Z4 Convertible 2012,Bentley Continental Supersports Conv. Convertible 2012,Bentley Arnage Sedan 2009,Bentley Mulsanne Sedan 2011,Bentley Continental GT Coupe 2012,Bentley Continental GT Coupe 2007,Bentley Continental Flying Spur Sedan 2007,Bugatti Veyron 16.4 Convertible 2009,Bugatti Veyron 16.4 Coupe 2009,Buick Regal GS 2012,Buick Rainier SUV 2007,Buick Verano Sedan 2012,Buick Enclave SUV 2012,Cadillac CTS-V Sedan 2012,Cadillac SRX SUV 2012,Cadillac Escalade EXT Crew Cab 2007,Chevrolet Silverado 1500 Hybrid Crew Cab 2012,Chevrolet Corvette Convertible 2012,Chevrolet Corvette ZR1 2012,Chevrolet Corvette Ron Fellows Edition Z06 2007,Chevrolet Traverse SUV 2012,Chevrolet Camaro Convertible 2012,Chevrolet HHR SS 2010,Chevrolet Impala Sedan 2007,Chevrolet Tahoe Hybrid SUV 2012,Chevrolet Sonic Sedan 2012,Chevrolet Express Cargo Van 2007,Chevrolet Avalanche Crew Cab 2012,Chevrolet Cobalt SS 2010,Chevrolet Malibu Hybrid Sedan 2010,Chevrolet TrailBlazer SS 2009,Chevrolet Silverado 2500HD Regular Cab 2012,Chevrolet Silverado 1500 Classic Extended Cab 2007,Chevrolet Express Van 2007,Chevrolet Monte Carlo Coupe 2007,Chevrolet Malibu Sedan 2007,Chevrolet Silverado 1500 Extended Cab 2012,Chevrolet Silverado 1500 Regular Cab 2012,Chrysler Aspen SUV 2009,Chrysler Sebring Convertible 2010,Chrysler Town and Country Minivan 2012,Chrysler 300 SRT-8 2010,Chrysler Crossfire Convertible 2008,Chrysler PT Cruiser Convertible 2008,Daewoo Nubira Wagon 2002,Dodge Caliber Wagon 2012,Dodge Caliber Wagon 2007,Dodge Caravan Minivan 1997,Dodge Ram Pickup 3500 Crew Cab 2010,Dodge Ram Pickup 3500 Quad Cab 2009,Dodge Sprinter Cargo Van 2009,Dodge Journey SUV 2012,Dodge Dakota Crew Cab 2010,Dodge Dakota Club Cab 2007,Dodge Magnum Wagon 2008,Dodge Challenger SRT8 2011,Dodge Durango SUV 2012,Dodge Durango SUV 2007,Dodge Charger Sedan 2012,Dodge Charger SRT-8 2009,Eagle Talon Hatchback 1998,FIAT 500 Abarth 2012,FIAT 500 Convertible 2012,Ferrari FF Coupe 2012,Ferrari California Convertible 2012,Ferrari 458 Italia Convertible 2012,Ferrari 458 Italia Coupe 2012,Fisker Karma Sedan 2012,Ford F-450 Super Duty Crew Cab 2012,Ford Mustang Convertible 2007,Ford Freestar Minivan 2007,Ford Expedition EL SUV 2009,Ford Edge SUV 2012,Ford Ranger SuperCab 2011,Ford GT Coupe 2006,Ford F-150 Regular Cab 2012,Ford F-150 Regular Cab 2007,Ford Focus Sedan 2007,Ford E-Series Wagon Van 2012,Ford Fiesta Sedan 2012,GMC Terrain SUV 2012,GMC Savana Van 2012,GMC Yukon Hybrid SUV 2012,GMC Acadia SUV 2012,GMC Canyon Extended Cab 2012,Geo Metro Convertible 1993,HUMMER H3T Crew Cab 2010,HUMMER H2 SUT Crew Cab 2009,Honda Odyssey Minivan 2012,Honda Odyssey Minivan 2007,Honda Accord Coupe 2012,Honda Accord Sedan 2012,Hyundai Veloster Hatchback 2012,Hyundai Santa Fe SUV 2012,Hyundai Tucson SUV 2012,Hyundai Veracruz SUV 2012,Hyundai Sonata Hybrid Sedan 2012,Hyundai Elantra Sedan 2007,Hyundai Accent Sedan 2012,Hyundai Genesis Sedan 2012,Hyundai Sonata Sedan 2012,Hyundai Elantra Touring Hatchback 2012,Hyundai Azera Sedan 2012,Infiniti G Coupe IPL 2012,Infiniti QX56 SUV 2011,Isuzu Ascender SUV 2008,Jaguar XK XKR 2012,Jeep Patriot SUV 2012,Jeep Wrangler SUV 2012,Jeep Liberty SUV 2012,Jeep Grand Cherokee SUV 2012,Jeep Compass SUV 2012,Lamborghini Reventon Coupe 2008,Lamborghini Aventador Coupe 2012,Lamborghini Gallardo LP 570-4 Superleggera 2012,Lamborghini Diablo Coupe 2001,Land Rover Range Rover SUV 2012,Land Rover LR2 SUV 2012,Lincoln Town Car Sedan 2011,MINI Cooper Roadster Convertible 2012,Maybach Landaulet Convertible 2012,Mazda Tribute SUV 2011,McLaren MP4-12C Coupe 2012,Mercedes-Benz 300-Class Convertible 1993,Mercedes-Benz C-Class Sedan 2012,Mercedes-Benz SL-Class Coupe 2009,Mercedes-Benz E-Class Sedan 2012,Mercedes-Benz S-Class Sedan 2012,Mercedes-Benz Sprinter Van 2012,Mitsubishi Lancer Sedan 2012,Nissan Leaf Hatchback 2012,Nissan NV Passenger Van 2012,Nissan Juke Hatchback 2012,Nissan 240SX Coupe 1998,Plymouth Neon Coupe 1999,Porsche Panamera Sedan 2012,Ram C/V Cargo Van Minivan 2012,Rolls-Royce Phantom Drophead Coupe Convertible 2012,Rolls-Royce Ghost Sedan 2012,Rolls-Royce Phantom Sedan 2012,Scion xD Hatchback 2012,Spyker C8 Convertible 2009,Spyker C8 Coupe 2009,Suzuki Aerio Sedan 2007,Suzuki Kizashi Sedan 2012,Suzuki SX4 Hatchback 2012,Suzuki SX4 Sedan 2012,Tesla Model S Sedan 2012,Toyota Sequoia SUV 2012,Toyota Camry Sedan 2012,Toyota Corolla Sedan 2012,Toyota 4Runner SUV 2012,Volkswagen Golf Hatchback 2012,Volkswagen Golf Hatchback 1991,Volkswagen Beetle Hatchback 2012,Volvo C30 Hatchback 2012,Volvo 240 Sedan 1993,Volvo XC90 SUV 2007,smart fortwo Convertible 2012,Per-class accuracy +AM General Hummer SUV 2000,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Acura RL Sedan 2012,0,3,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.5% +Acura TL Sedan 2012,0,1,5,0,2,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,50.0% +Acura TL Type-S 2008,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Acura TSX Sedan 2012,0,0,1,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,57.14% +Acura Integra Type R 2001,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Acura ZDX Hatchback 2012,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Aston Martin V8 Vantage Convertible 2012,0,0,0,0,0,0,0,1,4,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9.09% +Aston Martin V8 Vantage Coupe 2012,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,83.33% +Aston Martin Virage Convertible 2012,0,0,0,0,0,0,0,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Aston Martin Virage Coupe 2012,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +Audi RS 4 Convertible 2008,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Audi A5 Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,6,1,0,0,0,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Audi TTS Coupe 2012,0,0,0,0,0,0,0,1,0,0,0,0,1,4,0,0,0,0,3,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Audi R8 Coupe 2012,0,0,0,0,0,0,0,0,2,0,0,0,0,1,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,54.55% +Audi V8 Sedan 1994,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.5% +Audi 100 Sedan 1994,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Audi 100 Wagon 1994,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45.45% +Audi TT Hatchback 2011,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,2,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,28.57% +Audi S6 Sedan 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Audi S5 Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,1,1,1,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12.5% +Audi S5 Coupe 2012,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,25.0% +Audi S4 Sedan 2012,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,83.33% +Audi S4 Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,1,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Audi TT RS Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,2,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +BMW ActiveHybrid 5 Sedan 2012,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +BMW 1 Series Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,16.67% +BMW 1 Series Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,1,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.14% +BMW 3 Series Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,2,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +BMW 3 Series Wagon 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +BMW 6 Series Convertible 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +BMW X5 SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +BMW X6 SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,7,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,53.85% +BMW M3 Coupe 2012,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +BMW M5 Sedan 2010,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +BMW M6 Convertible 2010,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11.11% +BMW X3 SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80.0% +BMW Z4 Convertible 2012,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12.5% +Bentley Continental Supersports Conv. Convertible 2012,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Bentley Arnage Sedan 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Bentley Mulsanne Sedan 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Bentley Continental GT Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Bentley Continental GT Coupe 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,4,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Bentley Continental Flying Spur Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80.0% +Bugatti Veyron 16.4 Convertible 2009,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,20.0% +Bugatti Veyron 16.4 Coupe 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Buick Regal GS 2012,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,2,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45.45% +Buick Rainier SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80.0% +Buick Verano Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,77.78% +Buick Enclave SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,28.57% +Cadillac CTS-V Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Cadillac SRX SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Cadillac Escalade EXT Crew Cab 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,87.5% +Chevrolet Silverado 1500 Hybrid Crew Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,3,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,11.11% +Chevrolet Corvette Convertible 2012,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,2,2,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,30.77% +Chevrolet Corvette ZR1 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,2,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,28.57% +Chevrolet Corvette Ron Fellows Edition Z06 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,50.0% +Chevrolet Traverse SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Chevrolet Camaro Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Chevrolet HHR SS 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Chevrolet Impala Sedan 2007,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.5% +Chevrolet Tahoe Hybrid SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,4,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,44.44% +Chevrolet Sonic Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Chevrolet Express Cargo Van 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Chevrolet Avalanche Crew Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Chevrolet Cobalt SS 2010,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,3,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,37.5% +Chevrolet Malibu Hybrid Sedan 2010,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,50.0% +Chevrolet TrailBlazer SS 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +Chevrolet Silverado 2500HD Regular Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,1,0,0,0,1,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,45.45% +Chevrolet Silverado 1500 Classic Extended Cab 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Chevrolet Express Van 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,22.22% +Chevrolet Monte Carlo Coupe 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.5% +Chevrolet Malibu Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Chevrolet Silverado 1500 Extended Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Chevrolet Silverado 1500 Regular Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Chrysler Aspen SUV 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,71.43% +Chrysler Sebring Convertible 2010,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12.5% +Chrysler Town and Country Minivan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Chrysler 300 SRT-8 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2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Ford Freestar Minivan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80.0% +Ford Expedition EL SUV 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,63.64% +Ford Edge SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,70.0% +Ford Ranger SuperCab 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Ford GT Coupe 2006,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Ford F-150 Regular Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,71.43% +Ford F-150 Regular Cab 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,7,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,53.85% +Ford Focus Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,46.15% +Ford E-Series Wagon Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +Ford Fiesta Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +GMC Terrain SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,72.73% +GMC Savana Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,69.23% +GMC Yukon Hybrid SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,71.43% +GMC Acadia SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +GMC Canyon Extended Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Geo Metro Convertible 1993,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,61.54% +HUMMER H3T Crew Cab 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,42.86% +HUMMER H2 SUT Crew Cab 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +Honda Odyssey Minivan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,1,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Honda Odyssey Minivan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,25.0% +Honda Accord Coupe 2012,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,66.67% +Honda Accord Sedan 2012,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Hyundai Veloster Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,66.67% +Hyundai Santa Fe SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,85.71% +Hyundai Tucson SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Hyundai Veracruz SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +Hyundai Sonata Hybrid Sedan 2012,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,71.43% +Hyundai Elantra Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Hyundai Accent Sedan 2012,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0.0% +Hyundai Genesis Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,4,0,0,2,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,44.44% +Hyundai Sonata Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Hyundai Elantra Touring Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Hyundai Azera Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,4,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Infiniti G Coupe IPL 2012,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Infiniti QX56 SUV 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,80.0% +Isuzu Ascender SUV 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,62.5% +Jaguar XK XKR 2012,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.14% +Jeep Patriot SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,70.0% +Jeep Wrangler SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,55.56% +Jeep Liberty SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,72.73% +Jeep Grand Cherokee SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,54.55% +Jeep Compass SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,50.0% +Lamborghini Reventon Coupe 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,85.71% +Lamborghini Aventador Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Lamborghini Gallardo LP 570-4 Superleggera 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Lamborghini Diablo Coupe 2001,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,83.33% +Land Rover Range Rover SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,83.33% +Land Rover LR2 SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,57.14% +Lincoln Town Car Sedan 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,85.71% +MINI Cooper Roadster Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Maybach Landaulet Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +Mazda Tribute SUV 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +McLaren MP4-12C Coupe 2012,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,3,0,1,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,40.0% +Mercedes-Benz 300-Class Convertible 1993,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,37.5% +Mercedes-Benz C-Class Sedan 2012,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Mercedes-Benz SL-Class Coupe 2009,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,62.5% +Mercedes-Benz E-Class Sedan 2012,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,14.29% +Mercedes-Benz S-Class Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,57.14% +Mercedes-Benz Sprinter Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Mitsubishi Lancer Sedan 2012,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Nissan Leaf Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,66.67% +Nissan NV Passenger Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,81.82% +Nissan Juke Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,3,0,0,0,0,0,0,0,1,0,0,0,0,1,0,0,0,0,0,0,0,0,0,1,0,0,0,18.75% +Nissan 240SX Coupe 1998,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,64.29% +Plymouth Neon Coupe 1999,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,25.0% +Porsche Panamera Sedan 2012,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,41.67% +Ram C/V Cargo Van Minivan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Rolls-Royce Phantom Drophead Coupe Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,33.33% +Rolls-Royce Ghost Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,4,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,44.44% +Rolls-Royce Phantom Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,71.43% +Scion xD Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,1,2,0,0,0,0,0,0,0,0,0,0,0,0,42.86% +Spyker C8 Convertible 2009,0,0,0,0,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,58.33% +Spyker C8 Coupe 2009,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,30.0% +Suzuki Aerio Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,75.0% +Suzuki Kizashi Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,60.0% +Suzuki SX4 Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,1,0,0,0,0,0,0,0,0,0,0,0,0,61.54% +Suzuki SX4 Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,50.0% +Tesla Model S Sedan 2012,0,1,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,50.0% +Toyota Sequoia SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,100.0% +Toyota Camry Sedan 2012,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,1,0,0,0,0,0,0,0,0,28.57% +Toyota Corolla Sedan 2012,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,46.15% +Toyota 4Runner SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,6,0,0,0,0,0,0,0,50.0% +Volkswagen Golf Hatchback 2012,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,2,0,0,0,0,0,8,0,0,0,0,0,0,61.54% +Volkswagen Golf Hatchback 1991,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,1,0,42.86% +Volkswagen Beetle Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,36.36% +Volvo C30 Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,1,0,0,0,0,0,0,0,0,0,0,3,0,0,0,50.0% +Volvo 240 Sedan 1993,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,66.67% +Volvo XC90 SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,75.0% +smart fortwo Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,61.54% diff --git a/cars/architecture-investigations/fc/2-layers/256/deploy.prototxt b/cars/architecture-investigations/fc/2-layers/256/deploy.prototxt new file mode 100644 index 0000000..6edf1d2 --- /dev/null +++ b/cars/architecture-investigations/fc/2-layers/256/deploy.prototxt @@ -0,0 +1,341 @@ +input: "data" +input_shape { + dim: 1 + dim: 3 + dim: 227 + dim: 227 +} +layer { + name: "conv1" + type: "Convolution" + bottom: "data" + top: "conv1" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu1" + type: "ReLU" + bottom: "conv1" + top: "conv1" +} +layer { + name: "norm1" + type: "LRN" + bottom: "conv1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool1" + type: "Pooling" + bottom: "norm1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv2" + type: "Convolution" + bottom: "pool1" + top: "conv2" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu2" + type: "ReLU" + bottom: "conv2" + top: "conv2" +} +layer { + name: "norm2" + type: "LRN" + bottom: "conv2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool2" + type: "Pooling" + bottom: "norm2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv3" + type: "Convolution" + bottom: "pool2" + top: "conv3" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu3" + type: "ReLU" + bottom: "conv3" + top: "conv3" +} +layer { + name: "conv4" + type: "Convolution" + bottom: "conv3" + top: "conv4" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu4" + type: "ReLU" + bottom: "conv4" + top: "conv4" +} +layer { + name: "conv5" + type: "Convolution" + bottom: "conv4" + top: "conv5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu5" + type: "ReLU" + bottom: "conv5" + top: "conv5" +} +layer { + name: "pool5" + type: "Pooling" + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "fc6" + type: "InnerProduct" + bottom: "pool5" + top: "fc6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu6" + type: "ReLU" + bottom: "fc6" + top: "fc6" +} +layer { + name: "drop6" + type: "Dropout" + bottom: "fc6" + top: "fc6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7" + type: "InnerProduct" + bottom: "fc6" + top: "fc7" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7" + type: "ReLU" + bottom: "fc7" + top: "fc7" +} +layer { + name: "drop7" + type: "Dropout" + bottom: "fc7" + top: "fc7" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc8" + type: "InnerProduct" + bottom: "fc7" + top: "fc8" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 196 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "softmax" + type: "Softmax" + bottom: "fc8" + top: "softmax" +} diff --git a/cars/architecture-investigations/fc/2-layers/256/large.png b/cars/architecture-investigations/fc/2-layers/256/large.png new file mode 100644 index 0000000000000000000000000000000000000000..e9f4c34d868e073832508bde771b41872b6c4225 GIT binary patch literal 279478 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b/cars/architecture-investigations/fc/2-layers/256/original.prototxt new file mode 100644 index 0000000..c4efc20 --- /dev/null +++ b/cars/architecture-investigations/fc/2-layers/256/original.prototxt @@ -0,0 +1,388 @@ +name: "AlexNet" +layer { + name: "train-data" + type: "Data" + top: "data" + top: "label" + include { + stage: "train" + } + transform_param { + mirror: true + crop_size: 227 + } + data_param { + batch_size: 128 + } +} +layer { + name: "val-data" + type: "Data" + top: "data" + top: "label" + include { + stage: "val" + } + transform_param { + crop_size: 227 + } + data_param { + batch_size: 32 + } +} +layer { + name: "conv1" + type: "Convolution" + bottom: "data" + top: "conv1" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu1" + type: "ReLU" + bottom: "conv1" + top: "conv1" +} +layer { + name: "norm1" + type: "LRN" + bottom: "conv1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool1" + type: "Pooling" + bottom: "norm1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv2" + type: "Convolution" + bottom: "pool1" + top: "conv2" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu2" + type: "ReLU" + bottom: "conv2" + top: "conv2" +} +layer { + name: "norm2" + type: "LRN" + bottom: "conv2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool2" + type: "Pooling" + bottom: "norm2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv3" + type: "Convolution" + bottom: "pool2" + top: "conv3" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu3" + type: "ReLU" + bottom: "conv3" + top: "conv3" +} +layer { + name: "conv4" + type: "Convolution" + bottom: "conv3" + top: "conv4" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu4" + type: "ReLU" + bottom: "conv4" + top: "conv4" +} +layer { + name: "conv5" + type: "Convolution" + bottom: "conv4" + top: "conv5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu5" + type: "ReLU" + bottom: "conv5" + top: "conv5" +} +layer { + name: "pool5" + type: "Pooling" + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "fc6" + type: "InnerProduct" + bottom: "pool5" + top: "fc6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu6" + type: "ReLU" + bottom: "fc6" + top: "fc6" +} +layer { + name: "drop6" + type: "Dropout" + bottom: "fc6" + top: "fc6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7" + type: "InnerProduct" + bottom: "fc6" + top: "fc7" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7" + type: "ReLU" + bottom: "fc7" + top: "fc7" +} +layer { + name: "drop7" + type: "Dropout" + bottom: "fc7" + top: "fc7" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc8" + type: "InnerProduct" + bottom: "fc7" + top: "fc8" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "accuracy" + type: "Accuracy" + bottom: "fc8" + bottom: "label" + top: "accuracy" + include { + stage: "val" + } +} +layer { + name: "loss" + type: "SoftmaxWithLoss" + bottom: "fc8" + bottom: "label" + top: "loss" + exclude { + stage: "deploy" + } +} +layer { + name: "softmax" + type: "Softmax" + bottom: "fc8" + top: "softmax" + include { + stage: "deploy" + } +} diff --git a/cars/architecture-investigations/fc/2-layers/256/pred.csv b/cars/architecture-investigations/fc/2-layers/256/pred.csv new file mode 100644 index 0000000..1db328a --- /dev/null +++ b/cars/architecture-investigations/fc/2-layers/256/pred.csv @@ -0,0 +1,1619 @@ +1 /scratch/Teaching/cars/car_ims/012117.jpg Jeep Grand Cherokee SUV 2012 Jeep Compass SUV 2012 39.76% Jeep Grand Cherokee SUV 2012 38.78% GMC Terrain SUV 2012 21.16% BMW X3 SUV 2012 0.26% Mazda Tribute SUV 2011 0.01% +2 /scratch/Teaching/cars/car_ims/008738.jpg Ford Mustang Convertible 2007 Audi 100 Wagon 1994 34.13% Ford F-150 Regular Cab 2007 18.49% Mercedes-Benz 300-Class Convertible 1993 7.73% Geo Metro Convertible 1993 6.8% Daewoo Nubira Wagon 2002 4.09% +3 /scratch/Teaching/cars/car_ims/015794.jpg Volkswagen Beetle Hatchback 2012 FIAT 500 Convertible 2012 88.31% Volkswagen Beetle Hatchback 2012 3.71% Nissan Leaf Hatchback 2012 1.95% Nissan Juke Hatchback 2012 1.91% smart fortwo Convertible 2012 1.86% +4 /scratch/Teaching/cars/car_ims/004173.jpg Cadillac SRX SUV 2012 Cadillac SRX SUV 2012 90.6% GMC Acadia SUV 2012 4.42% GMC Terrain SUV 2012 2.13% Chevrolet Traverse SUV 2012 0.54% Suzuki SX4 Sedan 2012 0.35% +5 /scratch/Teaching/cars/car_ims/005889.jpg Chevrolet Malibu Sedan 2007 Chevrolet Impala Sedan 2007 40.31% Chevrolet Malibu Sedan 2007 17.41% Chevrolet Malibu Hybrid Sedan 2010 8.6% Ford Focus Sedan 2007 6.2% Honda Odyssey Minivan 2012 4.7% +6 /scratch/Teaching/cars/car_ims/001393.jpg Audi 100 Wagon 1994 Audi 100 Sedan 1994 87.51% Audi V8 Sedan 1994 8.91% Audi 100 Wagon 1994 3.4% Volkswagen Golf Hatchback 1991 0.16% Volvo 240 Sedan 1993 0.01% +7 /scratch/Teaching/cars/car_ims/001507.jpg Audi TT Hatchback 2011 Audi A5 Coupe 2012 37.77% Audi S4 Sedan 2012 27.81% Audi S5 Coupe 2012 10.54% Audi S6 Sedan 2011 6.28% Audi S5 Convertible 2012 5.55% +8 /scratch/Teaching/cars/car_ims/002597.jpg BMW X5 SUV 2007 BMW X5 SUV 2007 48.76% BMW X3 SUV 2012 19.94% BMW X6 SUV 2012 10.7% Dodge Caliber Wagon 2012 7.48% Jeep Grand Cherokee SUV 2012 4.65% +9 /scratch/Teaching/cars/car_ims/000071.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 32.27% HUMMER H3T Crew Cab 2010 24.98% HUMMER H2 SUT Crew Cab 2009 18.66% Jeep Patriot SUV 2012 17.66% Jeep Wrangler SUV 2012 1.64% +10 /scratch/Teaching/cars/car_ims/008059.jpg FIAT 500 Abarth 2012 FIAT 500 Abarth 2012 100.0% Bentley Arnage Sedan 2009 0.0% Chrysler 300 SRT-8 2010 0.0% Jeep Liberty SUV 2012 0.0% Nissan Juke Hatchback 2012 0.0% +11 /scratch/Teaching/cars/car_ims/001659.jpg Audi S5 Convertible 2012 Audi S4 Sedan 2012 95.51% Audi S5 Convertible 2012 1.82% Audi S5 Coupe 2012 1.73% Audi A5 Coupe 2012 0.77% Audi S6 Sedan 2011 0.1% +12 /scratch/Teaching/cars/car_ims/004557.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Jaguar XK XKR 2012 17.04% Ferrari 458 Italia Coupe 2012 13.23% Chevrolet Monte Carlo Coupe 2007 12.05% Ferrari California Convertible 2012 11.3% Aston Martin V8 Vantage Coupe 2012 10.28% +13 /scratch/Teaching/cars/car_ims/004311.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 88.89% Chevrolet Silverado 2500HD Regular Cab 2012 8.83% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 1.16% Chevrolet Silverado 1500 Extended Cab 2012 0.98% Chevrolet Avalanche Crew Cab 2012 0.11% +14 /scratch/Teaching/cars/car_ims/006145.jpg Chrysler Aspen SUV 2009 Ford Freestar Minivan 2007 85.3% Chrysler Town and Country Minivan 2012 3.62% Lincoln Town Car Sedan 2011 2.8% Dodge Caravan Minivan 1997 2.12% Audi 100 Wagon 1994 1.78% +15 /scratch/Teaching/cars/car_ims/012832.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 59.03% Chevrolet Impala Sedan 2007 32.51% Chevrolet Malibu Sedan 2007 6.51% Ford Focus Sedan 2007 1.12% Audi 100 Wagon 1994 0.42% +16 /scratch/Teaching/cars/car_ims/006057.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 92.99% Chevrolet Silverado 2500HD Regular Cab 2012 6.08% Chevrolet Silverado 1500 Extended Cab 2012 0.47% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.45% Chevrolet Avalanche Crew Cab 2012 0.0% +17 /scratch/Teaching/cars/car_ims/005195.jpg Chevrolet Avalanche Crew Cab 2012 HUMMER H3T Crew Cab 2010 26.83% Dodge Ram Pickup 3500 Quad Cab 2009 25.82% HUMMER H2 SUT Crew Cab 2009 18.14% Dodge Ram Pickup 3500 Crew Cab 2010 9.28% GMC Canyon Extended Cab 2012 7.38% +18 /scratch/Teaching/cars/car_ims/013970.jpg Nissan Juke Hatchback 2012 Nissan Juke Hatchback 2012 94.36% Buick Enclave SUV 2012 3.78% Ford Edge SUV 2012 0.49% Hyundai Tucson SUV 2012 0.44% Hyundai Veracruz SUV 2012 0.41% +19 /scratch/Teaching/cars/car_ims/000910.jpg Audi RS 4 Convertible 2008 BMW M6 Convertible 2010 38.37% Audi RS 4 Convertible 2008 33.67% Audi S4 Sedan 2007 9.79% Mercedes-Benz 300-Class Convertible 1993 5.91% BMW 6 Series Convertible 2007 3.06% +20 /scratch/Teaching/cars/car_ims/008161.jpg FIAT 500 Convertible 2012 FIAT 500 Convertible 2012 81.31% smart fortwo Convertible 2012 18.6% Suzuki Kizashi Sedan 2012 0.02% Volvo C30 Hatchback 2012 0.02% Suzuki SX4 Hatchback 2012 0.02% +21 /scratch/Teaching/cars/car_ims/001019.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 94.17% Audi S5 Coupe 2012 3.18% Audi S4 Sedan 2012 1.59% Audi S4 Sedan 2007 1.02% Audi S5 Convertible 2012 0.02% +22 /scratch/Teaching/cars/car_ims/002588.jpg BMW X5 SUV 2007 Buick Rainier SUV 2007 53.07% BMW X5 SUV 2007 39.62% Jeep Liberty SUV 2012 3.22% Buick Enclave SUV 2012 2.24% Mazda Tribute SUV 2011 0.8% +23 /scratch/Teaching/cars/car_ims/004884.jpg Chevrolet Impala Sedan 2007 Chevrolet Impala Sedan 2007 97.08% Chevrolet Monte Carlo Coupe 2007 1.63% Chevrolet Malibu Sedan 2007 0.91% Ford Focus Sedan 2007 0.16% Lincoln Town Car Sedan 2011 0.08% +24 /scratch/Teaching/cars/car_ims/001972.jpg Audi S4 Sedan 2007 Audi S4 Sedan 2007 87.7% BMW 3 Series Wagon 2012 4.17% Audi S6 Sedan 2011 3.28% Audi A5 Coupe 2012 1.97% BMW X3 SUV 2012 1.55% +25 /scratch/Teaching/cars/car_ims/001030.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 87.29% Audi S4 Sedan 2012 7.0% Audi S5 Coupe 2012 4.23% Audi TT Hatchback 2011 0.49% Audi TTS Coupe 2012 0.45% +26 /scratch/Teaching/cars/car_ims/002376.jpg BMW 3 Series Wagon 2012 BMW 3 Series Wagon 2012 92.84% BMW X3 SUV 2012 5.07% BMW X5 SUV 2007 0.89% Audi S4 Sedan 2007 0.36% BMW ActiveHybrid 5 Sedan 2012 0.13% +27 /scratch/Teaching/cars/car_ims/009940.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 99.22% Chevrolet Traverse SUV 2012 0.77% Jeep Grand Cherokee SUV 2012 0.0% Mazda Tribute SUV 2011 0.0% Cadillac SRX SUV 2012 0.0% +28 /scratch/Teaching/cars/car_ims/012396.jpg Lamborghini Aventador Coupe 2012 Ferrari 458 Italia Convertible 2012 35.69% Ferrari 458 Italia Coupe 2012 35.19% Lamborghini Aventador Coupe 2012 20.45% McLaren MP4-12C Coupe 2012 6.28% Ferrari FF Coupe 2012 1.49% +29 /scratch/Teaching/cars/car_ims/006287.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 99.74% Ford Freestar Minivan 2007 0.24% Ram C/V Cargo Van Minivan 2012 0.02% Dodge Caliber Wagon 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% +30 /scratch/Teaching/cars/car_ims/006286.jpg Chrysler Town and Country Minivan 2012 Ram C/V Cargo Van Minivan 2012 95.38% Chrysler Town and Country Minivan 2012 3.77% Suzuki SX4 Sedan 2012 0.48% Mazda Tribute SUV 2011 0.13% Suzuki SX4 Hatchback 2012 0.12% +31 /scratch/Teaching/cars/car_ims/001090.jpg Audi TTS Coupe 2012 Audi TT Hatchback 2011 50.04% Audi TTS Coupe 2012 49.08% Audi S4 Sedan 2012 0.25% Audi S5 Coupe 2012 0.19% Audi TT RS Coupe 2012 0.19% +32 /scratch/Teaching/cars/car_ims/003162.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental Supersports Conv. Convertible 2012 99.96% Bentley Mulsanne Sedan 2011 0.02% Maybach Landaulet Convertible 2012 0.01% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Bentley Continental Flying Spur Sedan 2007 0.0% +33 /scratch/Teaching/cars/car_ims/009978.jpg GMC Canyon Extended Cab 2012 GMC Canyon Extended Cab 2012 38.19% Chevrolet Silverado 1500 Regular Cab 2012 32.91% Chevrolet Silverado 1500 Extended Cab 2012 10.82% Chevrolet Silverado 2500HD Regular Cab 2012 10.17% Dodge Dakota Club Cab 2007 3.97% +34 /scratch/Teaching/cars/car_ims/013824.jpg Nissan Leaf Hatchback 2012 Nissan Leaf Hatchback 2012 37.15% Ford Fiesta Sedan 2012 23.65% Ford Focus Sedan 2007 10.8% Hyundai Tucson SUV 2012 8.63% Plymouth Neon Coupe 1999 7.14% +35 /scratch/Teaching/cars/car_ims/003698.jpg Bugatti Veyron 16.4 Coupe 2009 Bugatti Veyron 16.4 Coupe 2009 99.15% Bugatti Veyron 16.4 Convertible 2009 0.63% Spyker C8 Convertible 2009 0.08% Audi R8 Coupe 2012 0.07% Audi TTS Coupe 2012 0.04% +36 /scratch/Teaching/cars/car_ims/007674.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 96.42% Dodge Journey SUV 2012 3.02% Dodge Caliber Wagon 2012 0.53% Dodge Charger Sedan 2012 0.01% Dodge Magnum Wagon 2008 0.01% +37 /scratch/Teaching/cars/car_ims/012705.jpg Land Rover LR2 SUV 2012 Land Rover LR2 SUV 2012 65.26% Toyota 4Runner SUV 2012 30.45% Land Rover Range Rover SUV 2012 2.43% Ford Edge SUV 2012 1.4% GMC Terrain SUV 2012 0.37% +38 /scratch/Teaching/cars/car_ims/007644.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 99.18% Chevrolet Avalanche Crew Cab 2012 0.67% Dodge Journey SUV 2012 0.11% Chevrolet TrailBlazer SS 2009 0.03% Dodge Magnum Wagon 2008 0.01% +39 /scratch/Teaching/cars/car_ims/007457.jpg Dodge Dakota Club Cab 2007 Dodge Dakota Club Cab 2007 84.07% GMC Canyon Extended Cab 2012 12.28% Ford F-150 Regular Cab 2007 3.37% Chevrolet Silverado 1500 Extended Cab 2012 0.12% Dodge Ram Pickup 3500 Quad Cab 2009 0.05% +40 /scratch/Teaching/cars/car_ims/005424.jpg Chevrolet Malibu Hybrid Sedan 2010 Acura RL Sedan 2012 32.23% Hyundai Elantra Sedan 2007 31.72% Buick Verano Sedan 2012 19.9% Acura TSX Sedan 2012 6.12% Toyota Camry Sedan 2012 3.14% +41 /scratch/Teaching/cars/car_ims/003712.jpg Bugatti Veyron 16.4 Coupe 2009 Lamborghini Reventon Coupe 2008 37.86% Aston Martin V8 Vantage Coupe 2012 34.46% Lamborghini Aventador Coupe 2012 7.63% Aston Martin V8 Vantage Convertible 2012 7.55% Audi R8 Coupe 2012 6.2% +42 /scratch/Teaching/cars/car_ims/007814.jpg Dodge Charger Sedan 2012 Dodge Charger Sedan 2012 94.34% Mitsubishi Lancer Sedan 2012 2.53% Audi S4 Sedan 2012 1.16% Dodge Charger SRT-8 2009 0.74% Audi A5 Coupe 2012 0.49% +43 /scratch/Teaching/cars/car_ims/015765.jpg Volkswagen Beetle Hatchback 2012 Volkswagen Beetle Hatchback 2012 61.99% Suzuki Kizashi Sedan 2012 18.77% Cadillac CTS-V Sedan 2012 8.1% FIAT 500 Abarth 2012 5.94% Nissan Juke Hatchback 2012 3.85% +44 /scratch/Teaching/cars/car_ims/012091.jpg Jeep Liberty SUV 2012 Chevrolet Avalanche Crew Cab 2012 40.67% Chevrolet Tahoe Hybrid SUV 2012 16.29% GMC Canyon Extended Cab 2012 8.66% Chevrolet Silverado 1500 Extended Cab 2012 8.54% Isuzu Ascender SUV 2008 7.47% +45 /scratch/Teaching/cars/car_ims/015546.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 95.55% Land Rover LR2 SUV 2012 3.28% Toyota Sequoia SUV 2012 0.48% GMC Terrain SUV 2012 0.29% Ford Edge SUV 2012 0.14% +46 /scratch/Teaching/cars/car_ims/012984.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 29.25% Bentley Continental Flying Spur Sedan 2007 18.34% Bentley Mulsanne Sedan 2011 12.1% Rolls-Royce Phantom Sedan 2012 7.04% Bentley Continental GT Coupe 2007 5.04% +47 /scratch/Teaching/cars/car_ims/007744.jpg Dodge Durango SUV 2007 Dodge Caliber Wagon 2012 53.12% Dodge Durango SUV 2007 45.68% Dodge Caliber Wagon 2007 0.67% Dodge Dakota Crew Cab 2010 0.47% Dodge Magnum Wagon 2008 0.05% +48 /scratch/Teaching/cars/car_ims/001459.jpg Audi 100 Wagon 1994 Audi 100 Wagon 1994 68.91% Dodge Caravan Minivan 1997 28.44% Ford Focus Sedan 2007 1.04% Plymouth Neon Coupe 1999 0.66% Volkswagen Golf Hatchback 1991 0.61% +49 /scratch/Teaching/cars/car_ims/004803.jpg Chevrolet Camaro Convertible 2012 Chevrolet Camaro Convertible 2012 70.76% Dodge Charger Sedan 2012 27.44% Chrysler Crossfire Convertible 2008 0.98% Dodge Charger SRT-8 2009 0.42% Ford Mustang Convertible 2007 0.16% +50 /scratch/Teaching/cars/car_ims/013803.jpg Nissan Leaf Hatchback 2012 Nissan Leaf Hatchback 2012 100.0% Scion xD Hatchback 2012 0.0% Nissan Juke Hatchback 2012 0.0% Ford Fiesta Sedan 2012 0.0% Hyundai Tucson SUV 2012 0.0% +51 /scratch/Teaching/cars/car_ims/009797.jpg GMC Yukon Hybrid SUV 2012 Chevrolet Silverado 1500 Regular Cab 2012 70.27% Chevrolet Avalanche Crew Cab 2012 12.98% Chevrolet Silverado 1500 Extended Cab 2012 11.39% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 1.87% Chevrolet Silverado 2500HD Regular Cab 2012 1.12% +52 /scratch/Teaching/cars/car_ims/014728.jpg Spyker C8 Convertible 2009 Bugatti Veyron 16.4 Coupe 2009 51.8% Spyker C8 Convertible 2009 28.45% Bugatti Veyron 16.4 Convertible 2009 17.65% Spyker C8 Coupe 2009 0.73% Mercedes-Benz SL-Class Coupe 2009 0.54% +53 /scratch/Teaching/cars/car_ims/007389.jpg Dodge Dakota Club Cab 2007 Chevrolet Silverado 2500HD Regular Cab 2012 29.34% Chevrolet Silverado 1500 Extended Cab 2012 28.13% Chevrolet Silverado 1500 Regular Cab 2012 17.31% Dodge Dakota Club Cab 2007 12.42% GMC Canyon Extended Cab 2012 5.08% +54 /scratch/Teaching/cars/car_ims/011599.jpg Infiniti G Coupe IPL 2012 Acura RL Sedan 2012 52.6% Acura TL Type-S 2008 27.09% BMW ActiveHybrid 5 Sedan 2012 13.0% Infiniti G Coupe IPL 2012 4.59% BMW 6 Series Convertible 2007 0.86% +55 /scratch/Teaching/cars/car_ims/006305.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 96.22% Chevrolet Malibu Sedan 2007 1.48% Ram C/V Cargo Van Minivan 2012 0.93% Honda Odyssey Minivan 2007 0.83% Ford Freestar Minivan 2007 0.21% +56 /scratch/Teaching/cars/car_ims/010055.jpg GMC Savana Van 2012 GMC Savana Van 2012 70.3% Chevrolet Express Van 2007 18.89% Chevrolet Express Cargo Van 2007 10.81% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.0% Volkswagen Golf Hatchback 1991 0.0% +57 /scratch/Teaching/cars/car_ims/014172.jpg Plymouth Neon Coupe 1999 Lincoln Town Car Sedan 2011 68.6% Audi 100 Wagon 1994 28.45% Volvo 240 Sedan 1993 2.34% Daewoo Nubira Wagon 2002 0.25% Ford Focus Sedan 2007 0.09% +58 /scratch/Teaching/cars/car_ims/004832.jpg Chevrolet HHR SS 2010 Chevrolet HHR SS 2010 99.99% Dodge Magnum Wagon 2008 0.01% Dodge Charger SRT-8 2009 0.0% Volvo C30 Hatchback 2012 0.0% Chevrolet Cobalt SS 2010 0.0% +59 /scratch/Teaching/cars/car_ims/001935.jpg Audi S4 Sedan 2007 Mitsubishi Lancer Sedan 2012 99.31% Audi S4 Sedan 2012 0.62% Toyota Camry Sedan 2012 0.05% Audi A5 Coupe 2012 0.01% Audi S4 Sedan 2007 0.0% +60 /scratch/Teaching/cars/car_ims/014928.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 99.67% Buick Verano Sedan 2012 0.15% Suzuki SX4 Sedan 2012 0.07% Volvo C30 Hatchback 2012 0.04% Chevrolet Sonic Sedan 2012 0.03% +61 /scratch/Teaching/cars/car_ims/008224.jpg Ferrari FF Coupe 2012 Dodge Challenger SRT8 2011 36.11% Dodge Charger Sedan 2012 28.29% Aston Martin Virage Coupe 2012 10.15% Fisker Karma Sedan 2012 8.47% Aston Martin Virage Convertible 2012 4.68% +62 /scratch/Teaching/cars/car_ims/005419.jpg Chevrolet Malibu Hybrid Sedan 2010 Chevrolet Malibu Hybrid Sedan 2010 90.09% GMC Terrain SUV 2012 9.59% Buick Verano Sedan 2012 0.15% Hyundai Veracruz SUV 2012 0.05% Chevrolet Traverse SUV 2012 0.05% +63 /scratch/Teaching/cars/car_ims/000617.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin V8 Vantage Coupe 2012 74.94% Aston Martin V8 Vantage Convertible 2012 18.47% Aston Martin Virage Convertible 2012 6.09% Fisker Karma Sedan 2012 0.32% Aston Martin Virage Coupe 2012 0.04% +64 /scratch/Teaching/cars/car_ims/004587.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 99.95% Chevrolet Corvette Convertible 2012 0.04% Chevrolet Corvette ZR1 2012 0.01% Ferrari California Convertible 2012 0.0% Jaguar XK XKR 2012 0.0% +65 /scratch/Teaching/cars/car_ims/014717.jpg Spyker C8 Convertible 2009 Aston Martin Virage Coupe 2012 47.97% Spyker C8 Coupe 2009 35.91% McLaren MP4-12C Coupe 2012 11.74% Spyker C8 Convertible 2009 3.19% Aston Martin V8 Vantage Coupe 2012 0.31% +66 /scratch/Teaching/cars/car_ims/014933.jpg Suzuki Kizashi Sedan 2012 Infiniti G Coupe IPL 2012 22.68% Hyundai Genesis Sedan 2012 22.0% Hyundai Azera Sedan 2012 8.82% Suzuki Kizashi Sedan 2012 8.27% Honda Accord Sedan 2012 8.26% +67 /scratch/Teaching/cars/car_ims/015065.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Sedan 2012 90.7% Volkswagen Golf Hatchback 2012 4.33% Suzuki SX4 Hatchback 2012 1.56% Scion xD Hatchback 2012 1.49% Suzuki Aerio Sedan 2007 0.42% +68 /scratch/Teaching/cars/car_ims/002362.jpg BMW 3 Series Wagon 2012 BMW 3 Series Wagon 2012 71.5% Acura TL Type-S 2008 5.65% Mercedes-Benz C-Class Sedan 2012 3.33% Hyundai Genesis Sedan 2012 2.7% Honda Accord Sedan 2012 2.09% +69 /scratch/Teaching/cars/car_ims/001718.jpg Audi S5 Convertible 2012 Audi S5 Coupe 2012 40.27% Audi S5 Convertible 2012 26.12% Audi S4 Sedan 2012 23.3% Audi A5 Coupe 2012 4.81% Audi RS 4 Convertible 2008 2.51% +70 /scratch/Teaching/cars/car_ims/007698.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 65.63% Dodge Charger Sedan 2012 20.73% Dodge Charger SRT-8 2009 9.82% Dodge Magnum Wagon 2008 3.2% Chevrolet TrailBlazer SS 2009 0.25% +71 /scratch/Teaching/cars/car_ims/006352.jpg Chrysler 300 SRT-8 2010 Chrysler 300 SRT-8 2010 100.0% Rolls-Royce Ghost Sedan 2012 0.0% Dodge Charger SRT-8 2009 0.0% Rolls-Royce Phantom Sedan 2012 0.0% Chevrolet TrailBlazer SS 2009 0.0% +72 /scratch/Teaching/cars/car_ims/008545.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 99.08% Aston Martin V8 Vantage Coupe 2012 0.55% Dodge Challenger SRT8 2011 0.12% Tesla Model S Sedan 2012 0.1% Aston Martin Virage Convertible 2012 0.06% +73 /scratch/Teaching/cars/car_ims/000555.jpg Acura ZDX Hatchback 2012 Hyundai Veracruz SUV 2012 55.92% Acura ZDX Hatchback 2012 27.26% Honda Accord Sedan 2012 11.29% Buick Verano Sedan 2012 3.34% Cadillac SRX SUV 2012 0.31% +74 /scratch/Teaching/cars/car_ims/010155.jpg Geo Metro Convertible 1993 Chrysler Town and Country Minivan 2012 39.56% Audi 100 Wagon 1994 22.68% Lincoln Town Car Sedan 2011 10.46% Chrysler Sebring Convertible 2010 8.28% Mercedes-Benz 300-Class Convertible 1993 2.54% +75 /scratch/Teaching/cars/car_ims/006070.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 56.04% Chevrolet Silverado 1500 Extended Cab 2012 18.39% Chevrolet Silverado 1500 Regular Cab 2012 16.47% Chevrolet Silverado 2500HD Regular Cab 2012 8.91% GMC Canyon Extended Cab 2012 0.1% +76 /scratch/Teaching/cars/car_ims/010758.jpg Hyundai Santa Fe SUV 2012 Mercedes-Benz Sprinter Van 2012 87.82% Hyundai Genesis Sedan 2012 7.57% Dodge Sprinter Cargo Van 2009 2.5% Mercedes-Benz C-Class Sedan 2012 1.23% Mercedes-Benz E-Class Sedan 2012 0.32% +77 /scratch/Teaching/cars/car_ims/014203.jpg Porsche Panamera Sedan 2012 FIAT 500 Abarth 2012 44.43% Bentley Arnage Sedan 2009 23.57% Cadillac CTS-V Sedan 2012 9.72% Nissan Juke Hatchback 2012 4.49% Bentley Mulsanne Sedan 2011 3.4% +78 /scratch/Teaching/cars/car_ims/006788.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2012 63.36% Jeep Grand Cherokee SUV 2012 8.93% BMW X5 SUV 2007 7.69% Volvo XC90 SUV 2007 5.4% Dodge Caliber Wagon 2007 4.92% +79 /scratch/Teaching/cars/car_ims/005775.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Monte Carlo Coupe 2007 48.95% Chevrolet Impala Sedan 2007 48.44% Chevrolet Malibu Sedan 2007 1.01% Lincoln Town Car Sedan 2011 0.69% Nissan 240SX Coupe 1998 0.5% +80 /scratch/Teaching/cars/car_ims/013231.jpg Mercedes-Benz 300-Class Convertible 1993 Mercedes-Benz 300-Class Convertible 1993 99.67% Lincoln Town Car Sedan 2011 0.28% Audi 100 Wagon 1994 0.04% Audi 100 Sedan 1994 0.01% Volvo 240 Sedan 1993 0.0% +81 /scratch/Teaching/cars/car_ims/006212.jpg Chrysler Sebring Convertible 2010 Hyundai Elantra Sedan 2007 69.0% Chrysler Sebring Convertible 2010 27.53% Honda Accord Sedan 2012 2.56% Honda Odyssey Minivan 2007 0.47% Chevrolet Malibu Sedan 2007 0.11% +82 /scratch/Teaching/cars/car_ims/003269.jpg Bentley Mulsanne Sedan 2011 Bentley Mulsanne Sedan 2011 99.99% Rolls-Royce Phantom Sedan 2012 0.01% Bentley Arnage Sedan 2009 0.0% Cadillac CTS-V Sedan 2012 0.0% Bentley Continental GT Coupe 2012 0.0% +83 /scratch/Teaching/cars/car_ims/000569.jpg Acura ZDX Hatchback 2012 Hyundai Veracruz SUV 2012 51.86% Hyundai Sonata Sedan 2012 18.13% Acura ZDX Hatchback 2012 18.07% Honda Accord Sedan 2012 5.05% Buick Verano Sedan 2012 3.68% +84 /scratch/Teaching/cars/car_ims/013843.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 99.76% GMC Yukon Hybrid SUV 2012 0.22% Ford F-150 Regular Cab 2007 0.02% Ford E-Series Wagon Van 2012 0.0% Ford F-150 Regular Cab 2012 0.0% +85 /scratch/Teaching/cars/car_ims/002828.jpg BMW M5 Sedan 2010 BMW M5 Sedan 2010 63.66% Acura RL Sedan 2012 27.85% Acura TL Type-S 2008 4.37% Acura TSX Sedan 2012 2.17% BMW ActiveHybrid 5 Sedan 2012 1.31% +86 /scratch/Teaching/cars/car_ims/015020.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 60.29% Mazda Tribute SUV 2011 18.26% Hyundai Santa Fe SUV 2012 17.62% Chevrolet Traverse SUV 2012 1.57% Dodge Journey SUV 2012 0.83% +87 /scratch/Teaching/cars/car_ims/007528.jpg Dodge Magnum Wagon 2008 BMW X3 SUV 2012 24.94% Rolls-Royce Ghost Sedan 2012 19.91% Dodge Durango SUV 2012 19.52% Dodge Charger Sedan 2012 11.86% Dodge Magnum Wagon 2008 7.33% +88 /scratch/Teaching/cars/car_ims/001985.jpg Audi TT RS Coupe 2012 Audi TT Hatchback 2011 38.49% Toyota Camry Sedan 2012 27.59% Audi TT RS Coupe 2012 10.16% Audi TTS Coupe 2012 5.17% Mitsubishi Lancer Sedan 2012 3.92% +89 /scratch/Teaching/cars/car_ims/002403.jpg BMW 3 Series Wagon 2012 Audi R8 Coupe 2012 13.41% Chrysler 300 SRT-8 2010 6.29% Dodge Challenger SRT8 2011 5.82% BMW M6 Convertible 2010 5.69% Lamborghini Reventon Coupe 2008 5.67% +90 /scratch/Teaching/cars/car_ims/014148.jpg Plymouth Neon Coupe 1999 Nissan 240SX Coupe 1998 44.06% Audi V8 Sedan 1994 31.58% Audi 100 Wagon 1994 12.59% Audi 100 Sedan 1994 3.7% Plymouth Neon Coupe 1999 3.32% +91 /scratch/Teaching/cars/car_ims/004645.jpg Chevrolet Traverse SUV 2012 Spyker C8 Convertible 2009 71.29% Ford GT Coupe 2006 5.4% Fisker Karma Sedan 2012 4.37% Dodge Challenger SRT8 2011 3.95% Lamborghini Reventon Coupe 2008 3.5% +92 /scratch/Teaching/cars/car_ims/007318.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 63.05% Dodge Durango SUV 2012 16.17% Dodge Durango SUV 2007 6.89% Chevrolet Avalanche Crew Cab 2012 3.61% Dodge Dakota Club Cab 2007 2.46% +93 /scratch/Teaching/cars/car_ims/001070.jpg Audi TTS Coupe 2012 Audi A5 Coupe 2012 62.49% Audi S5 Coupe 2012 14.66% Audi TTS Coupe 2012 7.15% Audi S4 Sedan 2012 6.02% Audi S4 Sedan 2007 5.56% +94 /scratch/Teaching/cars/car_ims/004489.jpg Chevrolet Corvette ZR1 2012 Bugatti Veyron 16.4 Coupe 2009 21.49% McLaren MP4-12C Coupe 2012 12.59% Lamborghini Reventon Coupe 2008 11.39% Lamborghini Gallardo LP 570-4 Superleggera 2012 8.5% Chevrolet Corvette ZR1 2012 8.27% +95 /scratch/Teaching/cars/car_ims/013414.jpg Mercedes-Benz E-Class Sedan 2012 Acura TL Type-S 2008 30.48% Audi S4 Sedan 2007 18.47% BMW 3 Series Wagon 2012 13.78% BMW ActiveHybrid 5 Sedan 2012 13.02% BMW M5 Sedan 2010 8.25% +96 /scratch/Teaching/cars/car_ims/008628.jpg Ford F-450 Super Duty Crew Cab 2012 AM General Hummer SUV 2000 49.98% Bentley Arnage Sedan 2009 12.94% HUMMER H2 SUT Crew Cab 2009 7.91% Lamborghini Reventon Coupe 2008 7.37% FIAT 500 Abarth 2012 4.57% +97 /scratch/Teaching/cars/car_ims/012921.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 92.88% Cadillac CTS-V Sedan 2012 7.11% Bentley Mulsanne Sedan 2011 0.01% Ford F-450 Super Duty Crew Cab 2012 0.0% Maybach Landaulet Convertible 2012 0.0% +98 /scratch/Teaching/cars/car_ims/005304.jpg Chevrolet Cobalt SS 2010 Acura Integra Type R 2001 33.02% Chevrolet Corvette Convertible 2012 25.36% Dodge Challenger SRT8 2011 10.43% Aston Martin V8 Vantage Coupe 2012 5.66% Lamborghini Gallardo LP 570-4 Superleggera 2012 5.47% +99 /scratch/Teaching/cars/car_ims/000951.jpg Audi RS 4 Convertible 2008 BMW M6 Convertible 2010 32.11% Jaguar XK XKR 2012 23.47% Chevrolet Camaro Convertible 2012 6.93% Ford Mustang Convertible 2007 6.07% BMW 6 Series Convertible 2007 4.71% +100 /scratch/Teaching/cars/car_ims/006517.jpg Chrysler Crossfire Convertible 2008 Chrysler Crossfire Convertible 2008 56.27% Mercedes-Benz S-Class Sedan 2012 26.2% Chrysler Sebring Convertible 2010 14.66% Mercedes-Benz E-Class Sedan 2012 0.52% Mercedes-Benz C-Class Sedan 2012 0.42% +101 /scratch/Teaching/cars/car_ims/007067.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 99.05% Dodge Dakota Club Cab 2007 0.55% Dodge Ram Pickup 3500 Crew Cab 2010 0.29% Dodge Dakota Crew Cab 2010 0.11% GMC Canyon Extended Cab 2012 0.01% +102 /scratch/Teaching/cars/car_ims/013445.jpg Mercedes-Benz E-Class Sedan 2012 Audi S4 Sedan 2007 86.41% Audi S6 Sedan 2011 7.04% BMW ActiveHybrid 5 Sedan 2012 2.41% BMW 3 Series Wagon 2012 1.45% Audi S4 Sedan 2012 0.8% +103 /scratch/Teaching/cars/car_ims/005331.jpg Chevrolet Cobalt SS 2010 Chevrolet Malibu Hybrid Sedan 2010 86.21% Buick Verano Sedan 2012 6.11% Hyundai Sonata Hybrid Sedan 2012 1.39% Honda Accord Sedan 2012 1.11% Chevrolet Cobalt SS 2010 0.9% +104 /scratch/Teaching/cars/car_ims/005569.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 64.12% Chevrolet Silverado 2500HD Regular Cab 2012 25.04% GMC Canyon Extended Cab 2012 5.74% Chevrolet Silverado 1500 Extended Cab 2012 4.41% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.57% +105 /scratch/Teaching/cars/car_ims/011571.jpg Infiniti G Coupe IPL 2012 Infiniti G Coupe IPL 2012 96.94% Acura RL Sedan 2012 0.95% Hyundai Azera Sedan 2012 0.83% Acura TL Type-S 2008 0.27% Honda Accord Sedan 2012 0.18% +106 /scratch/Teaching/cars/car_ims/015756.jpg Volkswagen Golf Hatchback 1991 Volvo XC90 SUV 2007 31.18% Audi 100 Wagon 1994 26.13% Volvo 240 Sedan 1993 20.08% Buick Rainier SUV 2007 15.33% Volkswagen Golf Hatchback 1991 4.26% +107 /scratch/Teaching/cars/car_ims/001231.jpg Audi V8 Sedan 1994 Audi V8 Sedan 1994 98.25% Audi 100 Sedan 1994 1.67% Volkswagen Golf Hatchback 1991 0.04% Audi 100 Wagon 1994 0.04% Nissan 240SX Coupe 1998 0.0% +108 /scratch/Teaching/cars/car_ims/004435.jpg Chevrolet Corvette Convertible 2012 Lamborghini Aventador Coupe 2012 53.14% Chevrolet Corvette Ron Fellows Edition Z06 2007 14.88% Ford GT Coupe 2006 9.09% Bentley Continental Supersports Conv. Convertible 2012 5.9% Lamborghini Gallardo LP 570-4 Superleggera 2012 4.75% +109 /scratch/Teaching/cars/car_ims/006110.jpg Chrysler Aspen SUV 2009 Chrysler Aspen SUV 2009 97.97% Dodge Durango SUV 2007 2.03% Chrysler Town and Country Minivan 2012 0.0% Volvo XC90 SUV 2007 0.0% Isuzu Ascender SUV 2008 0.0% +110 /scratch/Teaching/cars/car_ims/012879.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 99.99% Bentley Continental Supersports Conv. Convertible 2012 0.0% FIAT 500 Convertible 2012 0.0% Bugatti Veyron 16.4 Convertible 2009 0.0% Spyker C8 Convertible 2009 0.0% +111 /scratch/Teaching/cars/car_ims/015062.jpg Suzuki SX4 Hatchback 2012 Dodge Caliber Wagon 2012 47.63% Chrysler Town and Country Minivan 2012 9.85% Ram C/V Cargo Van Minivan 2012 9.05% Dodge Caliber Wagon 2007 5.49% Volvo XC90 SUV 2007 4.52% +112 /scratch/Teaching/cars/car_ims/009405.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 72.25% Daewoo Nubira Wagon 2002 27.74% Audi 100 Wagon 1994 0.01% Plymouth Neon Coupe 1999 0.0% Chevrolet Impala Sedan 2007 0.0% +113 /scratch/Teaching/cars/car_ims/012882.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 76.01% Cadillac CTS-V Sedan 2012 21.29% Bentley Continental GT Coupe 2012 0.89% Bentley Mulsanne Sedan 2011 0.58% Bentley Continental Supersports Conv. Convertible 2012 0.42% +114 /scratch/Teaching/cars/car_ims/010887.jpg Hyundai Tucson SUV 2012 Hyundai Veracruz SUV 2012 27.3% Hyundai Tucson SUV 2012 23.32% Buick Enclave SUV 2012 12.23% Chevrolet Traverse SUV 2012 9.52% Acura ZDX Hatchback 2012 7.62% +115 /scratch/Teaching/cars/car_ims/000441.jpg Acura Integra Type R 2001 Acura Integra Type R 2001 81.93% Chevrolet Cobalt SS 2010 6.45% Lamborghini Diablo Coupe 2001 4.02% Dodge Challenger SRT8 2011 2.23% Audi RS 4 Convertible 2008 1.16% +116 /scratch/Teaching/cars/car_ims/010536.jpg Honda Accord Coupe 2012 Acura TL Type-S 2008 91.41% Honda Accord Coupe 2012 4.44% Honda Accord Sedan 2012 2.87% Acura TSX Sedan 2012 1.08% Acura RL Sedan 2012 0.13% +117 /scratch/Teaching/cars/car_ims/013656.jpg Mercedes-Benz Sprinter Van 2012 Dodge Sprinter Cargo Van 2009 65.41% Mercedes-Benz Sprinter Van 2012 34.55% Audi 100 Sedan 1994 0.04% Audi 100 Wagon 1994 0.0% Volkswagen Golf Hatchback 1991 0.0% +118 /scratch/Teaching/cars/car_ims/009218.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 82.75% Ford F-450 Super Duty Crew Cab 2012 17.14% Ford E-Series Wagon Van 2012 0.11% Dodge Ram Pickup 3500 Crew Cab 2010 0.0% Ford F-150 Regular Cab 2007 0.0% +119 /scratch/Teaching/cars/car_ims/015198.jpg Tesla Model S Sedan 2012 Aston Martin Virage Convertible 2012 20.28% Maybach Landaulet Convertible 2012 13.94% Spyker C8 Coupe 2009 13.38% Bugatti Veyron 16.4 Convertible 2009 12.27% Fisker Karma Sedan 2012 10.72% +120 /scratch/Teaching/cars/car_ims/008421.jpg Ferrari 458 Italia Coupe 2012 Fisker Karma Sedan 2012 32.03% FIAT 500 Abarth 2012 27.54% Bentley Arnage Sedan 2009 15.35% Lamborghini Reventon Coupe 2008 6.18% Chrysler 300 SRT-8 2010 5.93% +121 /scratch/Teaching/cars/car_ims/013496.jpg Mercedes-Benz S-Class Sedan 2012 Mercedes-Benz E-Class Sedan 2012 72.63% Mercedes-Benz S-Class Sedan 2012 23.87% Chrysler Sebring Convertible 2010 2.84% Maybach Landaulet Convertible 2012 0.28% Chrysler PT Cruiser Convertible 2008 0.23% +122 /scratch/Teaching/cars/car_ims/009437.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 99.68% Plymouth Neon Coupe 1999 0.16% Dodge Caravan Minivan 1997 0.12% Daewoo Nubira Wagon 2002 0.04% Suzuki Aerio Sedan 2007 0.0% +123 /scratch/Teaching/cars/car_ims/012516.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 Lamborghini Gallardo LP 570-4 Superleggera 2012 100.0% Bentley Continental Supersports Conv. Convertible 2012 0.0% Lamborghini Diablo Coupe 2001 0.0% Acura Integra Type R 2001 0.0% AM General Hummer SUV 2000 0.0% +124 /scratch/Teaching/cars/car_ims/015679.jpg Volkswagen Golf Hatchback 1991 Audi 100 Wagon 1994 59.45% Audi 100 Sedan 1994 11.95% Lincoln Town Car Sedan 2011 10.71% Daewoo Nubira Wagon 2002 3.59% Audi V8 Sedan 1994 3.25% +125 /scratch/Teaching/cars/car_ims/002639.jpg BMW X6 SUV 2012 Audi R8 Coupe 2012 34.5% BMW M3 Coupe 2012 7.26% Audi TTS Coupe 2012 6.65% Audi S4 Sedan 2012 6.01% Audi TT RS Coupe 2012 5.87% +126 /scratch/Teaching/cars/car_ims/008918.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 99.28% Toyota Sequoia SUV 2012 0.39% Land Rover Range Rover SUV 2012 0.18% Land Rover LR2 SUV 2012 0.15% Hyundai Santa Fe SUV 2012 0.0% +127 /scratch/Teaching/cars/car_ims/004135.jpg Cadillac SRX SUV 2012 Ram C/V Cargo Van Minivan 2012 78.58% GMC Acadia SUV 2012 15.04% Chrysler Town and Country Minivan 2012 2.24% Suzuki SX4 Sedan 2012 1.76% GMC Yukon Hybrid SUV 2012 0.65% +128 /scratch/Teaching/cars/car_ims/008676.jpg Ford Mustang Convertible 2007 Lamborghini Diablo Coupe 2001 48.82% Acura Integra Type R 2001 15.39% Bugatti Veyron 16.4 Coupe 2009 11.94% Spyker C8 Convertible 2009 9.6% Lamborghini Gallardo LP 570-4 Superleggera 2012 8.45% +129 /scratch/Teaching/cars/car_ims/014637.jpg Scion xD Hatchback 2012 Scion xD Hatchback 2012 100.0% Suzuki SX4 Sedan 2012 0.0% Suzuki SX4 Hatchback 2012 0.0% Nissan Leaf Hatchback 2012 0.0% Ford Fiesta Sedan 2012 0.0% +130 /scratch/Teaching/cars/car_ims/005759.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Impala Sedan 2007 36.16% Chevrolet Malibu Sedan 2007 34.39% Suzuki Aerio Sedan 2007 8.97% Suzuki SX4 Sedan 2012 5.52% Ram C/V Cargo Van Minivan 2012 5.31% +131 /scratch/Teaching/cars/car_ims/001181.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 99.78% Lamborghini Aventador Coupe 2012 0.14% Lamborghini Reventon Coupe 2008 0.02% Audi RS 4 Convertible 2008 0.01% BMW M6 Convertible 2010 0.01% +132 /scratch/Teaching/cars/car_ims/016126.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 99.92% FIAT 500 Convertible 2012 0.07% Suzuki SX4 Hatchback 2012 0.0% Ford Fiesta Sedan 2012 0.0% Chrysler PT Cruiser Convertible 2008 0.0% +133 /scratch/Teaching/cars/car_ims/016061.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 94.25% Jeep Liberty SUV 2012 1.6% Nissan NV Passenger Van 2012 1.4% BMW X5 SUV 2007 0.93% GMC Acadia SUV 2012 0.93% +134 /scratch/Teaching/cars/car_ims/004335.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 64.92% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 24.28% Dodge Dakota Club Cab 2007 3.26% GMC Canyon Extended Cab 2012 3.04% Dodge Dakota Crew Cab 2010 1.29% +135 /scratch/Teaching/cars/car_ims/006750.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2012 76.2% Dodge Caliber Wagon 2007 23.8% Dodge Journey SUV 2012 0.0% Dodge Magnum Wagon 2008 0.0% Dodge Dakota Crew Cab 2010 0.0% +136 /scratch/Teaching/cars/car_ims/000446.jpg Acura Integra Type R 2001 Acura Integra Type R 2001 47.47% Chevrolet Monte Carlo Coupe 2007 14.23% Dodge Challenger SRT8 2011 11.1% Chevrolet Cobalt SS 2010 8.37% Dodge Charger SRT-8 2009 6.19% +137 /scratch/Teaching/cars/car_ims/010470.jpg Honda Odyssey Minivan 2007 Honda Odyssey Minivan 2007 100.0% Hyundai Elantra Sedan 2007 0.0% Hyundai Veracruz SUV 2012 0.0% Honda Accord Sedan 2012 0.0% Honda Odyssey Minivan 2012 0.0% +138 /scratch/Teaching/cars/car_ims/002896.jpg BMW M6 Convertible 2010 BMW 6 Series Convertible 2007 53.25% BMW M6 Convertible 2010 26.5% Jaguar XK XKR 2012 18.37% Acura TL Type-S 2008 0.86% BMW M3 Coupe 2012 0.54% +139 /scratch/Teaching/cars/car_ims/002910.jpg BMW M6 Convertible 2010 Acura TL Type-S 2008 56.36% BMW 6 Series Convertible 2007 20.69% Acura TSX Sedan 2012 9.69% Chevrolet Monte Carlo Coupe 2007 6.05% Acura RL Sedan 2012 2.54% +140 /scratch/Teaching/cars/car_ims/014739.jpg Spyker C8 Convertible 2009 Fisker Karma Sedan 2012 53.51% Spyker C8 Convertible 2009 27.67% Aston Martin Virage Convertible 2012 3.17% Aston Martin Virage Coupe 2012 3.0% Tesla Model S Sedan 2012 2.39% +141 /scratch/Teaching/cars/car_ims/011972.jpg Jeep Wrangler SUV 2012 Jeep Wrangler SUV 2012 39.81% GMC Canyon Extended Cab 2012 22.95% Jeep Patriot SUV 2012 15.95% GMC Yukon Hybrid SUV 2012 3.54% Ford F-150 Regular Cab 2007 3.17% +142 /scratch/Teaching/cars/car_ims/015837.jpg Volkswagen Beetle Hatchback 2012 Nissan Juke Hatchback 2012 51.69% FIAT 500 Convertible 2012 17.99% Nissan Leaf Hatchback 2012 11.67% Volkswagen Beetle Hatchback 2012 7.65% Chrysler PT Cruiser Convertible 2008 4.78% +143 /scratch/Teaching/cars/car_ims/012094.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 71.03% Bentley Arnage Sedan 2009 14.15% Jeep Patriot SUV 2012 10.48% Buick Enclave SUV 2012 0.99% Nissan NV Passenger Van 2012 0.97% +144 /scratch/Teaching/cars/car_ims/007379.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 99.96% Dodge Caliber Wagon 2007 0.04% Dodge Caliber Wagon 2012 0.0% Dodge Charger Sedan 2012 0.0% Dodge Journey SUV 2012 0.0% +145 /scratch/Teaching/cars/car_ims/012130.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 61.76% Cadillac SRX SUV 2012 17.72% GMC Acadia SUV 2012 6.79% BMW X3 SUV 2012 6.26% Toyota Sequoia SUV 2012 2.98% +146 /scratch/Teaching/cars/car_ims/003988.jpg Buick Enclave SUV 2012 Infiniti QX56 SUV 2011 17.43% Honda Accord Sedan 2012 6.09% Hyundai Veracruz SUV 2012 5.35% Volkswagen Golf Hatchback 2012 4.72% BMW X3 SUV 2012 3.94% +147 /scratch/Teaching/cars/car_ims/009771.jpg GMC Savana Van 2012 GMC Savana Van 2012 62.04% Chevrolet Express Van 2007 33.68% Chevrolet Express Cargo Van 2007 4.28% Volkswagen Golf Hatchback 1991 0.0% Daewoo Nubira Wagon 2002 0.0% +148 /scratch/Teaching/cars/car_ims/007198.jpg Dodge Sprinter Cargo Van 2009 Dodge Sprinter Cargo Van 2009 93.96% Mercedes-Benz Sprinter Van 2012 4.4% Volkswagen Golf Hatchback 1991 1.07% Audi 100 Wagon 1994 0.14% Dodge Durango SUV 2007 0.14% +149 /scratch/Teaching/cars/car_ims/015552.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 81.17% Toyota Sequoia SUV 2012 5.51% GMC Acadia SUV 2012 3.32% Land Rover LR2 SUV 2012 2.8% GMC Terrain SUV 2012 2.29% +150 /scratch/Teaching/cars/car_ims/010126.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 99.99% Plymouth Neon Coupe 1999 0.01% Mercedes-Benz 300-Class Convertible 1993 0.0% Chevrolet Monte Carlo Coupe 2007 0.0% Eagle Talon Hatchback 1998 0.0% +151 /scratch/Teaching/cars/car_ims/006590.jpg Chrysler PT Cruiser Convertible 2008 Chrysler PT Cruiser Convertible 2008 31.73% Ford Mustang Convertible 2007 30.43% Ford F-150 Regular Cab 2007 8.31% Mercedes-Benz 300-Class Convertible 1993 3.91% Volvo XC90 SUV 2007 3.3% +152 /scratch/Teaching/cars/car_ims/001275.jpg Audi V8 Sedan 1994 Lincoln Town Car Sedan 2011 57.66% Audi 100 Wagon 1994 33.24% Volvo 240 Sedan 1993 6.98% Mercedes-Benz 300-Class Convertible 1993 1.97% Audi 100 Sedan 1994 0.14% +153 /scratch/Teaching/cars/car_ims/006732.jpg Dodge Caliber Wagon 2012 Suzuki SX4 Sedan 2012 44.99% Cadillac SRX SUV 2012 24.58% Dodge Caliber Wagon 2012 11.76% Ram C/V Cargo Van Minivan 2012 9.03% Chrysler Town and Country Minivan 2012 7.18% +154 /scratch/Teaching/cars/car_ims/006313.jpg Chrysler Town and Country Minivan 2012 Ram C/V Cargo Van Minivan 2012 79.5% Chrysler Town and Country Minivan 2012 20.35% Honda Odyssey Minivan 2007 0.07% Ford Freestar Minivan 2007 0.05% Chrysler Aspen SUV 2009 0.01% +155 /scratch/Teaching/cars/car_ims/006413.jpg Chrysler 300 SRT-8 2010 Chrysler 300 SRT-8 2010 88.69% Rolls-Royce Ghost Sedan 2012 6.19% Rolls-Royce Phantom Sedan 2012 2.61% Dodge Charger Sedan 2012 1.14% Dodge Charger SRT-8 2009 0.93% +156 /scratch/Teaching/cars/car_ims/002546.jpg BMW X5 SUV 2007 BMW X5 SUV 2007 88.15% BMW X3 SUV 2012 5.99% Chrysler 300 SRT-8 2010 1.47% Buick Enclave SUV 2012 1.24% Jeep Liberty SUV 2012 0.93% +157 /scratch/Teaching/cars/car_ims/003794.jpg Buick Regal GS 2012 Infiniti G Coupe IPL 2012 35.2% Buick Regal GS 2012 18.91% Toyota Camry Sedan 2012 18.7% Mitsubishi Lancer Sedan 2012 14.06% Acura RL Sedan 2012 3.87% +158 /scratch/Teaching/cars/car_ims/004370.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Toyota 4Runner SUV 2012 86.74% Chevrolet Tahoe Hybrid SUV 2012 4.81% Chevrolet Avalanche Crew Cab 2012 4.65% GMC Canyon Extended Cab 2012 1.37% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.63% +159 /scratch/Teaching/cars/car_ims/012547.jpg Lamborghini Diablo Coupe 2001 McLaren MP4-12C Coupe 2012 92.4% Lamborghini Diablo Coupe 2001 5.72% Aston Martin Virage Coupe 2012 0.72% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.41% Aston Martin V8 Vantage Coupe 2012 0.37% +160 /scratch/Teaching/cars/car_ims/003093.jpg BMW Z4 Convertible 2012 Dodge Charger SRT-8 2009 24.82% Jaguar XK XKR 2012 13.04% Honda Accord Coupe 2012 12.62% BMW 3 Series Sedan 2012 10.73% Dodge Charger Sedan 2012 10.59% +161 /scratch/Teaching/cars/car_ims/011134.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 99.65% Honda Odyssey Minivan 2007 0.35% Honda Accord Sedan 2012 0.0% Honda Odyssey Minivan 2012 0.0% Chrysler Sebring Convertible 2010 0.0% +162 /scratch/Teaching/cars/car_ims/000466.jpg Acura Integra Type R 2001 BMW 6 Series Convertible 2007 18.7% BMW M5 Sedan 2010 12.1% BMW M3 Coupe 2012 11.2% Acura Integra Type R 2001 9.48% BMW Z4 Convertible 2012 5.64% +163 /scratch/Teaching/cars/car_ims/004251.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 99.29% GMC Yukon Hybrid SUV 2012 0.7% Toyota 4Runner SUV 2012 0.01% Cadillac SRX SUV 2012 0.0% Toyota Sequoia SUV 2012 0.0% +164 /scratch/Teaching/cars/car_ims/012043.jpg Jeep Liberty SUV 2012 Audi V8 Sedan 1994 41.52% Volkswagen Golf Hatchback 1991 17.82% Audi 100 Sedan 1994 8.65% Dodge Ram Pickup 3500 Crew Cab 2010 8.22% Volvo 240 Sedan 1993 7.68% +165 /scratch/Teaching/cars/car_ims/013956.jpg Nissan Juke Hatchback 2012 MINI Cooper Roadster Convertible 2012 33.49% Chrysler PT Cruiser Convertible 2008 6.48% Maybach Landaulet Convertible 2012 5.1% Bentley Continental Supersports Conv. Convertible 2012 3.77% Mercedes-Benz E-Class Sedan 2012 3.34% +166 /scratch/Teaching/cars/car_ims/011227.jpg Hyundai Genesis Sedan 2012 Hyundai Genesis Sedan 2012 99.97% Hyundai Azera Sedan 2012 0.02% Mercedes-Benz C-Class Sedan 2012 0.01% Honda Accord Sedan 2012 0.0% Hyundai Sonata Sedan 2012 0.0% +167 /scratch/Teaching/cars/car_ims/009636.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 92.67% Toyota 4Runner SUV 2012 5.14% Chevrolet Avalanche Crew Cab 2012 0.85% Chevrolet Silverado 1500 Regular Cab 2012 0.78% GMC Canyon Extended Cab 2012 0.25% +168 /scratch/Teaching/cars/car_ims/001345.jpg Audi 100 Sedan 1994 Audi 100 Wagon 1994 92.05% Audi 100 Sedan 1994 7.25% Volvo 240 Sedan 1993 0.64% Ford F-150 Regular Cab 2007 0.02% Ford Ranger SuperCab 2011 0.02% +169 /scratch/Teaching/cars/car_ims/006159.jpg Chrysler Aspen SUV 2009 Chrysler Aspen SUV 2009 99.71% Volvo XC90 SUV 2007 0.18% Chrysler Town and Country Minivan 2012 0.11% Dodge Durango SUV 2007 0.01% Chrysler PT Cruiser Convertible 2008 0.0% +170 /scratch/Teaching/cars/car_ims/014729.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 53.93% Fisker Karma Sedan 2012 13.82% Aston Martin Virage Convertible 2012 10.41% Chevrolet Corvette ZR1 2012 4.99% Mercedes-Benz SL-Class Coupe 2009 3.92% +171 /scratch/Teaching/cars/car_ims/003356.jpg Bentley Continental GT Coupe 2012 Bentley Continental GT Coupe 2007 79.36% Bentley Continental GT Coupe 2012 18.01% BMW Z4 Convertible 2012 1.57% Bentley Continental Flying Spur Sedan 2007 0.3% BMW 6 Series Convertible 2007 0.28% +172 /scratch/Teaching/cars/car_ims/000255.jpg Acura TL Type-S 2008 Acura TL Type-S 2008 62.15% Acura RL Sedan 2012 36.83% Acura TSX Sedan 2012 0.96% Acura TL Sedan 2012 0.04% Hyundai Elantra Sedan 2007 0.01% +173 /scratch/Teaching/cars/car_ims/001575.jpg Audi S6 Sedan 2011 Audi S4 Sedan 2007 45.82% Audi S4 Sedan 2012 37.58% Audi S5 Coupe 2012 10.61% Audi S5 Convertible 2012 2.22% Audi A5 Coupe 2012 1.64% +174 /scratch/Teaching/cars/car_ims/003495.jpg Bentley Continental Flying Spur Sedan 2007 BMW ActiveHybrid 5 Sedan 2012 43.69% Bentley Continental Flying Spur Sedan 2007 14.4% Daewoo Nubira Wagon 2002 13.68% Lincoln Town Car Sedan 2011 12.21% Audi 100 Wagon 1994 10.2% +175 /scratch/Teaching/cars/car_ims/015738.jpg Volkswagen Golf Hatchback 1991 Volkswagen Golf Hatchback 1991 93.67% Jeep Liberty SUV 2012 2.25% Ford Mustang Convertible 2007 1.15% BMW X5 SUV 2007 1.08% Volvo 240 Sedan 1993 0.84% +176 /scratch/Teaching/cars/car_ims/011241.jpg Hyundai Genesis Sedan 2012 Toyota Corolla Sedan 2012 44.01% Mitsubishi Lancer Sedan 2012 23.39% Honda Accord Coupe 2012 5.93% Honda Accord Sedan 2012 4.85% Toyota Camry Sedan 2012 4.44% +177 /scratch/Teaching/cars/car_ims/007077.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 10.59% Ford F-150 Regular Cab 2007 7.73% Audi 100 Sedan 1994 6.34% Volkswagen Golf Hatchback 1991 6.16% Audi 100 Wagon 1994 6.12% +178 /scratch/Teaching/cars/car_ims/008495.jpg Ferrari 458 Italia Coupe 2012 Ferrari 458 Italia Convertible 2012 86.8% Ferrari 458 Italia Coupe 2012 13.1% Ferrari California Convertible 2012 0.09% Chevrolet Corvette Convertible 2012 0.01% McLaren MP4-12C Coupe 2012 0.0% +179 /scratch/Teaching/cars/car_ims/010613.jpg Honda Accord Sedan 2012 Honda Accord Sedan 2012 98.84% Honda Odyssey Minivan 2012 0.63% Acura RL Sedan 2012 0.19% Honda Odyssey Minivan 2007 0.12% Chevrolet Malibu Hybrid Sedan 2010 0.1% +180 /scratch/Teaching/cars/car_ims/006821.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2012 97.38% Dodge Caliber Wagon 2007 2.49% Ram C/V Cargo Van Minivan 2012 0.02% Dodge Durango SUV 2007 0.02% Jeep Grand Cherokee SUV 2012 0.02% +181 /scratch/Teaching/cars/car_ims/003406.jpg Bentley Continental GT Coupe 2007 Bentley Continental GT Coupe 2007 85.62% Bentley Continental Flying Spur Sedan 2007 8.65% Bentley Continental GT Coupe 2012 4.78% Bentley Mulsanne Sedan 2011 0.71% Bentley Continental Supersports Conv. Convertible 2012 0.09% +182 /scratch/Teaching/cars/car_ims/000523.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 60.65% Buick Verano Sedan 2012 26.02% Cadillac SRX SUV 2012 10.74% Hyundai Veracruz SUV 2012 1.97% Suzuki SX4 Sedan 2012 0.29% +183 /scratch/Teaching/cars/car_ims/010431.jpg Honda Odyssey Minivan 2012 Honda Odyssey Minivan 2012 67.22% Hyundai Veracruz SUV 2012 12.87% Hyundai Sonata Sedan 2012 10.59% Hyundai Elantra Sedan 2007 3.91% Honda Accord Sedan 2012 3.89% +184 /scratch/Teaching/cars/car_ims/002193.jpg BMW 1 Series Convertible 2012 Chevrolet Camaro Convertible 2012 35.89% Audi S4 Sedan 2012 25.15% Dodge Charger Sedan 2012 10.7% BMW 1 Series Convertible 2012 5.68% Mitsubishi Lancer Sedan 2012 4.84% +185 /scratch/Teaching/cars/car_ims/002106.jpg BMW ActiveHybrid 5 Sedan 2012 BMW 6 Series Convertible 2007 21.42% Aston Martin Virage Convertible 2012 13.73% Jaguar XK XKR 2012 5.92% BMW M6 Convertible 2010 5.57% Chevrolet Camaro Convertible 2012 3.98% +186 /scratch/Teaching/cars/car_ims/009326.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 88.17% Ford F-150 Regular Cab 2012 11.82% GMC Yukon Hybrid SUV 2012 0.01% Nissan NV Passenger Van 2012 0.0% GMC Canyon Extended Cab 2012 0.0% +187 /scratch/Teaching/cars/car_ims/004448.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Convertible 2012 69.88% McLaren MP4-12C Coupe 2012 15.51% Chevrolet Camaro Convertible 2012 3.88% Aston Martin V8 Vantage Convertible 2012 1.95% Lamborghini Diablo Coupe 2001 1.89% +188 /scratch/Teaching/cars/car_ims/013876.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 99.23% Ford F-150 Regular Cab 2007 0.43% GMC Yukon Hybrid SUV 2012 0.16% Ford F-150 Regular Cab 2012 0.11% Ram C/V Cargo Van Minivan 2012 0.03% +189 /scratch/Teaching/cars/car_ims/009358.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 22.18% Chevrolet Avalanche Crew Cab 2012 12.34% Ram C/V Cargo Van Minivan 2012 10.32% GMC Yukon Hybrid SUV 2012 9.99% Dodge Caliber Wagon 2012 9.47% +190 /scratch/Teaching/cars/car_ims/014404.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Sedan 2012 88.25% Rolls-Royce Ghost Sedan 2012 9.59% Rolls-Royce Phantom Drophead Coupe Convertible 2012 2.16% Chrysler 300 SRT-8 2010 0.0% Dodge Challenger SRT8 2011 0.0% +191 /scratch/Teaching/cars/car_ims/009561.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 58.02% Scion xD Hatchback 2012 41.91% Nissan Leaf Hatchback 2012 0.05% Hyundai Accent Sedan 2012 0.01% Toyota Camry Sedan 2012 0.0% +192 /scratch/Teaching/cars/car_ims/011623.jpg Infiniti QX56 SUV 2011 Infiniti QX56 SUV 2011 88.26% Land Rover LR2 SUV 2012 8.87% Ford Edge SUV 2012 1.53% Honda Odyssey Minivan 2012 0.49% Hyundai Veracruz SUV 2012 0.23% +193 /scratch/Teaching/cars/car_ims/009392.jpg Ford Focus Sedan 2007 Suzuki SX4 Hatchback 2012 32.75% Daewoo Nubira Wagon 2002 21.44% Suzuki SX4 Sedan 2012 20.2% Suzuki Aerio Sedan 2007 9.14% FIAT 500 Convertible 2012 2.83% +194 /scratch/Teaching/cars/car_ims/008462.jpg Ferrari 458 Italia Coupe 2012 Spyker C8 Coupe 2009 28.34% Ferrari 458 Italia Coupe 2012 24.38% McLaren MP4-12C Coupe 2012 7.67% Aston Martin V8 Vantage Coupe 2012 7.28% Aston Martin Virage Coupe 2012 5.61% +195 /scratch/Teaching/cars/car_ims/005643.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chevrolet Silverado 2500HD Regular Cab 2012 46.06% Chevrolet Silverado 1500 Regular Cab 2012 30.46% Chevrolet Silverado 1500 Extended Cab 2012 13.21% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 9.52% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.45% +196 /scratch/Teaching/cars/car_ims/016142.jpg smart fortwo Convertible 2012 Nissan Juke Hatchback 2012 54.42% smart fortwo Convertible 2012 22.56% Scion xD Hatchback 2012 12.17% Nissan Leaf Hatchback 2012 4.61% Suzuki SX4 Hatchback 2012 2.89% +197 /scratch/Teaching/cars/car_ims/013939.jpg Nissan Juke Hatchback 2012 Suzuki SX4 Hatchback 2012 34.25% Nissan Juke Hatchback 2012 12.22% Dodge Caliber Wagon 2012 9.06% BMW X6 SUV 2012 6.71% Dodge Journey SUV 2012 6.66% +198 /scratch/Teaching/cars/car_ims/010662.jpg Honda Accord Sedan 2012 Honda Accord Sedan 2012 99.91% Hyundai Genesis Sedan 2012 0.06% Chrysler Sebring Convertible 2010 0.01% Honda Odyssey Minivan 2012 0.01% Honda Accord Coupe 2012 0.0% +199 /scratch/Teaching/cars/car_ims/011023.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 99.94% Buick Regal GS 2012 0.05% Hyundai Accent Sedan 2012 0.0% Toyota Camry Sedan 2012 0.0% Acura TL Sedan 2012 0.0% +200 /scratch/Teaching/cars/car_ims/005575.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 52.82% Chevrolet Silverado 1500 Regular Cab 2012 29.41% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 9.64% Chevrolet Silverado 1500 Extended Cab 2012 7.3% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.41% +201 /scratch/Teaching/cars/car_ims/002201.jpg BMW 1 Series Coupe 2012 BMW 3 Series Sedan 2012 97.7% Mercedes-Benz C-Class Sedan 2012 1.73% Audi S4 Sedan 2012 0.51% BMW M6 Convertible 2010 0.02% BMW M3 Coupe 2012 0.01% +202 /scratch/Teaching/cars/car_ims/004506.jpg Chevrolet Corvette ZR1 2012 Chevrolet Corvette Ron Fellows Edition Z06 2007 41.17% Chevrolet Corvette ZR1 2012 24.55% Fisker Karma Sedan 2012 11.97% Spyker C8 Convertible 2009 6.18% Lamborghini Gallardo LP 570-4 Superleggera 2012 4.64% +203 /scratch/Teaching/cars/car_ims/010099.jpg Geo Metro Convertible 1993 smart fortwo Convertible 2012 47.79% Ford Fiesta Sedan 2012 15.85% Hyundai Veloster Hatchback 2012 9.6% Scion xD Hatchback 2012 5.7% Hyundai Tucson SUV 2012 2.43% +204 /scratch/Teaching/cars/car_ims/014813.jpg Spyker C8 Coupe 2009 Hyundai Veloster Hatchback 2012 93.94% Spyker C8 Coupe 2009 5.48% smart fortwo Convertible 2012 0.21% Volvo C30 Hatchback 2012 0.19% Ford GT Coupe 2006 0.06% +205 /scratch/Teaching/cars/car_ims/005180.jpg Chevrolet Express Cargo Van 2007 GMC Savana Van 2012 46.13% Chevrolet Express Cargo Van 2007 33.27% Chevrolet Express Van 2007 20.59% Volkswagen Golf Hatchback 1991 0.0% Acura Integra Type R 2001 0.0% +206 /scratch/Teaching/cars/car_ims/015822.jpg Volkswagen Beetle Hatchback 2012 Porsche Panamera Sedan 2012 23.96% Chevrolet Corvette ZR1 2012 23.91% Chevrolet Corvette Ron Fellows Edition Z06 2007 11.79% Ferrari 458 Italia Coupe 2012 9.46% Ferrari FF Coupe 2012 8.49% +207 /scratch/Teaching/cars/car_ims/008501.jpg Ferrari 458 Italia Coupe 2012 Ferrari 458 Italia Convertible 2012 53.47% Lamborghini Aventador Coupe 2012 26.27% Ferrari 458 Italia Coupe 2012 14.7% McLaren MP4-12C Coupe 2012 4.43% HUMMER H3T Crew Cab 2010 0.41% +208 /scratch/Teaching/cars/car_ims/003132.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental Supersports Conv. Convertible 2012 86.26% Rolls-Royce Phantom Drophead Coupe Convertible 2012 7.29% Audi R8 Coupe 2012 3.64% Fisker Karma Sedan 2012 0.55% BMW M6 Convertible 2010 0.49% +209 /scratch/Teaching/cars/car_ims/004268.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 99.77% GMC Yukon Hybrid SUV 2012 0.22% Chevrolet Tahoe Hybrid SUV 2012 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% Land Rover Range Rover SUV 2012 0.0% +210 /scratch/Teaching/cars/car_ims/014799.jpg Spyker C8 Coupe 2009 Hyundai Veloster Hatchback 2012 64.33% Spyker C8 Coupe 2009 35.2% Aston Martin Virage Coupe 2012 0.25% Dodge Charger Sedan 2012 0.07% Volvo C30 Hatchback 2012 0.07% +211 /scratch/Teaching/cars/car_ims/009257.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 99.95% Ford F-150 Regular Cab 2007 0.03% Ford E-Series Wagon Van 2012 0.01% Nissan NV Passenger Van 2012 0.0% Ford F-450 Super Duty Crew Cab 2012 0.0% +212 /scratch/Teaching/cars/car_ims/005514.jpg Chevrolet TrailBlazer SS 2009 Chevrolet TrailBlazer SS 2009 87.72% Chevrolet Avalanche Crew Cab 2012 12.14% Chevrolet Tahoe Hybrid SUV 2012 0.13% GMC Terrain SUV 2012 0.0% Land Rover Range Rover SUV 2012 0.0% +213 /scratch/Teaching/cars/car_ims/000813.jpg Aston Martin Virage Coupe 2012 Aston Martin Virage Coupe 2012 87.76% Aston Martin V8 Vantage Coupe 2012 11.94% Aston Martin V8 Vantage Convertible 2012 0.1% Spyker C8 Coupe 2009 0.07% Aston Martin Virage Convertible 2012 0.07% +214 /scratch/Teaching/cars/car_ims/015343.jpg Toyota Camry Sedan 2012 Hyundai Accent Sedan 2012 37.12% Hyundai Sonata Hybrid Sedan 2012 30.72% Honda Accord Coupe 2012 18.04% Toyota Corolla Sedan 2012 5.78% Hyundai Sonata Sedan 2012 4.07% +215 /scratch/Teaching/cars/car_ims/014452.jpg Rolls-Royce Ghost Sedan 2012 Fisker Karma Sedan 2012 52.17% Tesla Model S Sedan 2012 38.46% BMW 6 Series Convertible 2007 2.54% BMW M6 Convertible 2010 1.82% Rolls-Royce Ghost Sedan 2012 1.65% +216 /scratch/Teaching/cars/car_ims/005861.jpg Chevrolet Malibu Sedan 2007 Chevrolet Malibu Sedan 2007 60.2% Chevrolet Impala Sedan 2007 38.18% Chevrolet Monte Carlo Coupe 2007 0.96% Hyundai Elantra Sedan 2007 0.45% Lincoln Town Car Sedan 2011 0.09% +217 /scratch/Teaching/cars/car_ims/003121.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental Supersports Conv. Convertible 2012 35.6% BMW Z4 Convertible 2012 19.85% Bentley Continental GT Coupe 2012 16.07% Bentley Continental GT Coupe 2007 9.17% BMW M6 Convertible 2010 6.9% +218 /scratch/Teaching/cars/car_ims/003017.jpg BMW X3 SUV 2012 BMW X3 SUV 2012 50.67% BMW X5 SUV 2007 47.86% BMW X6 SUV 2012 0.68% Bentley Mulsanne Sedan 2011 0.23% Bentley Continental Flying Spur Sedan 2007 0.2% +219 /scratch/Teaching/cars/car_ims/014597.jpg Scion xD Hatchback 2012 Scion xD Hatchback 2012 99.82% Ford Fiesta Sedan 2012 0.14% Suzuki SX4 Hatchback 2012 0.04% Nissan Leaf Hatchback 2012 0.0% Suzuki SX4 Sedan 2012 0.0% +220 /scratch/Teaching/cars/car_ims/011717.jpg Isuzu Ascender SUV 2008 Isuzu Ascender SUV 2008 70.16% GMC Yukon Hybrid SUV 2012 11.65% Chevrolet Tahoe Hybrid SUV 2012 7.27% Cadillac Escalade EXT Crew Cab 2007 4.29% GMC Acadia SUV 2012 2.38% +221 /scratch/Teaching/cars/car_ims/009772.jpg GMC Savana Van 2012 GMC Savana Van 2012 67.83% Chevrolet Express Van 2007 23.6% Chevrolet Express Cargo Van 2007 8.56% Volkswagen Golf Hatchback 1991 0.0% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.0% +222 /scratch/Teaching/cars/car_ims/003355.jpg Bentley Continental GT Coupe 2012 Mitsubishi Lancer Sedan 2012 64.06% Bentley Continental GT Coupe 2012 33.1% Buick Regal GS 2012 1.05% Audi TTS Coupe 2012 0.81% BMW Z4 Convertible 2012 0.23% +223 /scratch/Teaching/cars/car_ims/008636.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 99.98% Toyota Sequoia SUV 2012 0.01% Ford F-150 Regular Cab 2012 0.0% Ford E-Series Wagon Van 2012 0.0% Ford Expedition EL SUV 2009 0.0% +224 /scratch/Teaching/cars/car_ims/016134.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 99.97% FIAT 500 Convertible 2012 0.03% Nissan Juke Hatchback 2012 0.0% Scion xD Hatchback 2012 0.0% Suzuki SX4 Hatchback 2012 0.0% +225 /scratch/Teaching/cars/car_ims/006048.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 81.21% Chevrolet Silverado 1500 Extended Cab 2012 16.09% GMC Canyon Extended Cab 2012 2.27% Chevrolet Silverado 2500HD Regular Cab 2012 0.24% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.13% +226 /scratch/Teaching/cars/car_ims/001833.jpg Audi S4 Sedan 2012 Audi S4 Sedan 2012 64.71% Audi S5 Convertible 2012 16.41% Audi S5 Coupe 2012 10.16% Audi A5 Coupe 2012 6.58% Audi S6 Sedan 2011 1.66% +227 /scratch/Teaching/cars/car_ims/007571.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 88.43% Dodge Charger SRT-8 2009 11.4% Dodge Charger Sedan 2012 0.16% Chrysler 300 SRT-8 2010 0.01% Chevrolet Camaro Convertible 2012 0.0% +228 /scratch/Teaching/cars/car_ims/001141.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 99.65% Lamborghini Reventon Coupe 2008 0.12% Mercedes-Benz SL-Class Coupe 2009 0.08% Audi TTS Coupe 2012 0.03% Bugatti Veyron 16.4 Coupe 2009 0.03% +229 /scratch/Teaching/cars/car_ims/006985.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 99.9% Dodge Ram Pickup 3500 Quad Cab 2009 0.08% Ford F-450 Super Duty Crew Cab 2012 0.02% Ford E-Series Wagon Van 2012 0.0% Dodge Durango SUV 2007 0.0% +230 /scratch/Teaching/cars/car_ims/001795.jpg Audi S5 Coupe 2012 Mitsubishi Lancer Sedan 2012 95.2% Audi S4 Sedan 2012 1.2% Audi TTS Coupe 2012 1.06% Audi A5 Coupe 2012 0.71% Audi S4 Sedan 2007 0.35% +231 /scratch/Teaching/cars/car_ims/013009.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 100.0% Suzuki SX4 Hatchback 2012 0.0% GMC Acadia SUV 2012 0.0% Buick Rainier SUV 2007 0.0% Hyundai Santa Fe SUV 2012 0.0% +232 /scratch/Teaching/cars/car_ims/001230.jpg Audi V8 Sedan 1994 Audi 100 Sedan 1994 62.04% Audi 100 Wagon 1994 37.79% Audi V8 Sedan 1994 0.13% Mercedes-Benz 300-Class Convertible 1993 0.04% Lincoln Town Car Sedan 2011 0.01% +233 /scratch/Teaching/cars/car_ims/014300.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 59.21% Lincoln Town Car Sedan 2011 17.45% Ford Freestar Minivan 2007 13.58% Chrysler Town and Country Minivan 2012 4.36% Chevrolet Malibu Sedan 2007 1.83% +234 /scratch/Teaching/cars/car_ims/014169.jpg Plymouth Neon Coupe 1999 Plymouth Neon Coupe 1999 99.98% Ford Focus Sedan 2007 0.02% Dodge Caravan Minivan 1997 0.0% Nissan 240SX Coupe 1998 0.0% Eagle Talon Hatchback 1998 0.0% +235 /scratch/Teaching/cars/car_ims/013258.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 72.68% Hyundai Genesis Sedan 2012 22.2% Mercedes-Benz S-Class Sedan 2012 4.4% Mercedes-Benz E-Class Sedan 2012 0.24% Audi S6 Sedan 2011 0.23% +236 /scratch/Teaching/cars/car_ims/015661.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 61.5% Honda Accord Sedan 2012 9.63% Suzuki SX4 Sedan 2012 6.12% Toyota Corolla Sedan 2012 5.92% Suzuki Aerio Sedan 2007 5.06% +237 /scratch/Teaching/cars/car_ims/011790.jpg Jaguar XK XKR 2012 Jaguar XK XKR 2012 93.31% BMW M6 Convertible 2010 4.42% Chevrolet Camaro Convertible 2012 0.67% Audi S4 Sedan 2012 0.36% Honda Accord Coupe 2012 0.28% +238 /scratch/Teaching/cars/car_ims/007625.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 93.12% Dodge Caliber Wagon 2012 3.7% Dodge Durango SUV 2007 2.65% Dodge Magnum Wagon 2008 0.34% Jeep Grand Cherokee SUV 2012 0.09% +239 /scratch/Teaching/cars/car_ims/000226.jpg Acura TL Sedan 2012 Tesla Model S Sedan 2012 28.19% Acura TL Sedan 2012 27.19% Buick Regal GS 2012 9.83% Fisker Karma Sedan 2012 8.22% Chevrolet Malibu Hybrid Sedan 2010 5.22% +240 /scratch/Teaching/cars/car_ims/011515.jpg Hyundai Azera Sedan 2012 Honda Odyssey Minivan 2012 31.99% Land Rover LR2 SUV 2012 31.96% Hyundai Genesis Sedan 2012 16.01% Honda Accord Sedan 2012 7.63% Hyundai Azera Sedan 2012 4.09% +241 /scratch/Teaching/cars/car_ims/002699.jpg BMW M3 Coupe 2012 BMW M3 Coupe 2012 71.13% BMW M6 Convertible 2010 5.96% BMW M5 Sedan 2010 4.03% BMW 3 Series Sedan 2012 3.88% BMW 6 Series Convertible 2007 3.57% +242 /scratch/Teaching/cars/car_ims/012239.jpg Jeep Compass SUV 2012 Jeep Wrangler SUV 2012 60.3% Jeep Compass SUV 2012 28.73% Jeep Patriot SUV 2012 10.28% HUMMER H3T Crew Cab 2010 0.57% GMC Canyon Extended Cab 2012 0.06% +243 /scratch/Teaching/cars/car_ims/010522.jpg Honda Accord Coupe 2012 Honda Accord Coupe 2012 100.0% Chevrolet Cobalt SS 2010 0.0% Toyota Corolla Sedan 2012 0.0% Honda Accord Sedan 2012 0.0% Nissan 240SX Coupe 1998 0.0% +244 /scratch/Teaching/cars/car_ims/007178.jpg Dodge Sprinter Cargo Van 2009 Mercedes-Benz Sprinter Van 2012 68.85% Dodge Sprinter Cargo Van 2009 28.94% Audi 100 Wagon 1994 0.85% Audi 100 Sedan 1994 0.64% Chrysler Town and Country Minivan 2012 0.18% +245 /scratch/Teaching/cars/car_ims/016121.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 42.59% Hyundai Elantra Touring Hatchback 2012 18.23% Chevrolet Sonic Sedan 2012 16.46% Volvo C30 Hatchback 2012 8.75% Suzuki Kizashi Sedan 2012 6.25% +246 /scratch/Teaching/cars/car_ims/014422.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Phantom Sedan 2012 63.68% Rolls-Royce Ghost Sedan 2012 29.14% Chrysler 300 SRT-8 2010 7.03% Audi S6 Sedan 2011 0.07% Bentley Mulsanne Sedan 2011 0.06% +247 /scratch/Teaching/cars/car_ims/005261.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 73.66% Chevrolet Tahoe Hybrid SUV 2012 13.32% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 6.5% Chevrolet Silverado 1500 Extended Cab 2012 5.12% Chevrolet Silverado 1500 Regular Cab 2012 1.31% +248 /scratch/Teaching/cars/car_ims/000853.jpg Aston Martin Virage Coupe 2012 Aston Martin Virage Coupe 2012 89.9% Aston Martin V8 Vantage Coupe 2012 10.06% Aston Martin V8 Vantage Convertible 2012 0.03% Dodge Challenger SRT8 2011 0.0% Spyker C8 Coupe 2009 0.0% +249 /scratch/Teaching/cars/car_ims/001391.jpg Audi 100 Wagon 1994 Audi 100 Wagon 1994 82.18% Audi 100 Sedan 1994 17.01% Lincoln Town Car Sedan 2011 0.4% Mercedes-Benz 300-Class Convertible 1993 0.27% Volvo 240 Sedan 1993 0.07% +250 /scratch/Teaching/cars/car_ims/009933.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 99.9% Chevrolet Traverse SUV 2012 0.08% Mazda Tribute SUV 2011 0.01% Buick Enclave SUV 2012 0.01% Cadillac SRX SUV 2012 0.0% +251 /scratch/Teaching/cars/car_ims/015495.jpg Toyota Corolla Sedan 2012 Toyota Corolla Sedan 2012 77.71% Toyota Camry Sedan 2012 21.18% Mitsubishi Lancer Sedan 2012 0.7% Acura TSX Sedan 2012 0.17% Hyundai Accent Sedan 2012 0.14% +252 /scratch/Teaching/cars/car_ims/002817.jpg BMW M5 Sedan 2010 Acura TSX Sedan 2012 86.43% Acura RL Sedan 2012 8.83% Acura TL Type-S 2008 3.06% BMW M5 Sedan 2010 0.91% Toyota Camry Sedan 2012 0.22% +253 /scratch/Teaching/cars/car_ims/012192.jpg Jeep Grand Cherokee SUV 2012 Toyota Sequoia SUV 2012 78.37% Dodge Durango SUV 2012 7.82% GMC Acadia SUV 2012 5.21% Mazda Tribute SUV 2011 3.26% Cadillac SRX SUV 2012 1.21% +254 /scratch/Teaching/cars/car_ims/014214.jpg Porsche Panamera Sedan 2012 Porsche Panamera Sedan 2012 96.9% Fisker Karma Sedan 2012 2.62% Chevrolet Corvette ZR1 2012 0.45% Ferrari FF Coupe 2012 0.01% Mercedes-Benz SL-Class Coupe 2009 0.01% +255 /scratch/Teaching/cars/car_ims/008646.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 99.99% Ford F-150 Regular Cab 2012 0.01% Dodge Ram Pickup 3500 Crew Cab 2010 0.0% Cadillac Escalade EXT Crew Cab 2007 0.0% Ford E-Series Wagon Van 2012 0.0% +256 /scratch/Teaching/cars/car_ims/012906.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 86.09% Cadillac CTS-V Sedan 2012 11.49% Audi S5 Convertible 2012 0.91% Audi TTS Coupe 2012 0.56% Bentley Continental GT Coupe 2012 0.27% +257 /scratch/Teaching/cars/car_ims/009128.jpg Ford GT Coupe 2006 Chevrolet Corvette Ron Fellows Edition Z06 2007 64.97% Chevrolet Corvette Convertible 2012 26.33% Ford GT Coupe 2006 4.11% Chevrolet Corvette ZR1 2012 2.09% Bentley Continental Supersports Conv. Convertible 2012 1.04% +258 /scratch/Teaching/cars/car_ims/007474.jpg Dodge Magnum Wagon 2008 Land Rover Range Rover SUV 2012 26.59% Chrysler 300 SRT-8 2010 14.94% Dodge Magnum Wagon 2008 13.15% Volvo XC90 SUV 2007 10.22% Dodge Durango SUV 2012 6.86% +259 /scratch/Teaching/cars/car_ims/014815.jpg Spyker C8 Coupe 2009 Bugatti Veyron 16.4 Convertible 2009 67.77% Spyker C8 Coupe 2009 11.51% Bugatti Veyron 16.4 Coupe 2009 11.02% Lamborghini Aventador Coupe 2012 1.78% Spyker C8 Convertible 2009 1.49% +260 /scratch/Teaching/cars/car_ims/011980.jpg Jeep Wrangler SUV 2012 GMC Canyon Extended Cab 2012 42.17% HUMMER H3T Crew Cab 2010 23.51% Jeep Wrangler SUV 2012 8.92% Dodge Dakota Club Cab 2007 5.04% Chevrolet Silverado 1500 Extended Cab 2012 4.91% +261 /scratch/Teaching/cars/car_ims/003373.jpg Bentley Continental GT Coupe 2012 Bentley Continental GT Coupe 2007 32.94% Bentley Mulsanne Sedan 2011 28.29% Bentley Continental GT Coupe 2012 24.79% Bentley Continental Flying Spur Sedan 2007 13.34% Cadillac CTS-V Sedan 2012 0.22% +262 /scratch/Teaching/cars/car_ims/006316.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 99.91% Ram C/V Cargo Van Minivan 2012 0.09% Lincoln Town Car Sedan 2011 0.0% Ford Freestar Minivan 2007 0.0% Dodge Caliber Wagon 2012 0.0% +263 /scratch/Teaching/cars/car_ims/014191.jpg Porsche Panamera Sedan 2012 BMW 3 Series Sedan 2012 46.48% Chrysler 300 SRT-8 2010 16.78% Audi S6 Sedan 2011 9.01% BMW 3 Series Wagon 2012 8.76% BMW M5 Sedan 2010 6.43% +264 /scratch/Teaching/cars/car_ims/015602.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 99.14% Hyundai Elantra Touring Hatchback 2012 0.52% Toyota Camry Sedan 2012 0.09% Toyota Corolla Sedan 2012 0.05% Ford Focus Sedan 2007 0.05% +265 /scratch/Teaching/cars/car_ims/009702.jpg GMC Terrain SUV 2012 Toyota 4Runner SUV 2012 67.18% Land Rover LR2 SUV 2012 15.52% Cadillac SRX SUV 2012 6.89% Hyundai Veracruz SUV 2012 3.49% Ford Edge SUV 2012 3.03% +266 /scratch/Teaching/cars/car_ims/007788.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 56.7% Dodge Dakota Club Cab 2007 14.55% Dodge Ram Pickup 3500 Quad Cab 2009 9.25% Dodge Ram Pickup 3500 Crew Cab 2010 5.53% Dodge Dakota Crew Cab 2010 3.78% +267 /scratch/Teaching/cars/car_ims/011684.jpg Isuzu Ascender SUV 2008 Isuzu Ascender SUV 2008 60.27% Buick Rainier SUV 2007 29.84% Ford Expedition EL SUV 2009 4.94% Ford Freestar Minivan 2007 3.45% Dodge Caravan Minivan 1997 0.52% +268 /scratch/Teaching/cars/car_ims/014740.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 25.08% Mercedes-Benz SL-Class Coupe 2009 12.45% Lamborghini Reventon Coupe 2008 8.7% Fisker Karma Sedan 2012 8.13% Ford GT Coupe 2006 7.55% +269 /scratch/Teaching/cars/car_ims/003392.jpg Bentley Continental GT Coupe 2012 Bentley Continental GT Coupe 2012 70.54% Bentley Continental GT Coupe 2007 29.41% Bentley Continental Flying Spur Sedan 2007 0.04% Bentley Mulsanne Sedan 2011 0.01% Cadillac CTS-V Sedan 2012 0.0% +270 /scratch/Teaching/cars/car_ims/002205.jpg BMW 1 Series Coupe 2012 BMW 1 Series Coupe 2012 98.72% BMW X6 SUV 2012 0.59% BMW 3 Series Sedan 2012 0.34% Volvo C30 Hatchback 2012 0.17% BMW 1 Series Convertible 2012 0.09% +271 /scratch/Teaching/cars/car_ims/012049.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 80.29% GMC Acadia SUV 2012 16.92% Jeep Compass SUV 2012 0.75% Jeep Patriot SUV 2012 0.68% GMC Yukon Hybrid SUV 2012 0.58% +272 /scratch/Teaching/cars/car_ims/008724.jpg Ford Mustang Convertible 2007 Ford Mustang Convertible 2007 91.29% Eagle Talon Hatchback 1998 5.61% Acura Integra Type R 2001 1.89% Audi V8 Sedan 1994 0.34% Nissan 240SX Coupe 1998 0.33% +273 /scratch/Teaching/cars/car_ims/008524.jpg Fisker Karma Sedan 2012 BMW 6 Series Convertible 2007 47.59% Fisker Karma Sedan 2012 30.86% Tesla Model S Sedan 2012 8.36% Aston Martin Virage Convertible 2012 3.72% Bentley Continental GT Coupe 2007 2.86% +274 /scratch/Teaching/cars/car_ims/015516.jpg Toyota 4Runner SUV 2012 Ford Expedition EL SUV 2009 64.55% Chevrolet Tahoe Hybrid SUV 2012 32.05% Land Rover Range Rover SUV 2012 1.01% Land Rover LR2 SUV 2012 0.96% GMC Yukon Hybrid SUV 2012 0.92% +275 /scratch/Teaching/cars/car_ims/004373.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 52.39% Chevrolet Silverado 1500 Extended Cab 2012 25.97% Chevrolet Silverado 1500 Regular Cab 2012 12.2% Chevrolet Silverado 2500HD Regular Cab 2012 8.7% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.31% +276 /scratch/Teaching/cars/car_ims/008948.jpg Ford Edge SUV 2012 Chevrolet Sonic Sedan 2012 41.43% Ford Edge SUV 2012 8.85% Nissan Juke Hatchback 2012 8.34% Scion xD Hatchback 2012 8.33% Volvo C30 Hatchback 2012 8.27% +277 /scratch/Teaching/cars/car_ims/011319.jpg Hyundai Sonata Sedan 2012 Hyundai Sonata Sedan 2012 88.26% Hyundai Azera Sedan 2012 7.38% Honda Accord Sedan 2012 2.2% Hyundai Elantra Sedan 2007 1.97% Hyundai Genesis Sedan 2012 0.09% +278 /scratch/Teaching/cars/car_ims/016185.jpg smart fortwo Convertible 2012 Ford Fiesta Sedan 2012 80.6% Hyundai Tucson SUV 2012 9.86% Hyundai Veloster Hatchback 2012 6.02% smart fortwo Convertible 2012 3.08% Nissan Juke Hatchback 2012 0.24% +279 /scratch/Teaching/cars/car_ims/009506.jpg Ford E-Series Wagon Van 2012 Ford E-Series Wagon Van 2012 93.09% Ford F-150 Regular Cab 2012 6.86% Nissan NV Passenger Van 2012 0.04% Ford F-150 Regular Cab 2007 0.01% Ford Ranger SuperCab 2011 0.0% +280 /scratch/Teaching/cars/car_ims/010110.jpg Geo Metro Convertible 1993 Plymouth Neon Coupe 1999 38.66% Chevrolet Express Van 2007 10.28% Nissan 240SX Coupe 1998 7.69% Geo Metro Convertible 1993 7.55% Acura Integra Type R 2001 6.49% +281 /scratch/Teaching/cars/car_ims/015510.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 89.58% Ford Expedition EL SUV 2009 5.52% Toyota Sequoia SUV 2012 3.02% Land Rover LR2 SUV 2012 1.02% Land Rover Range Rover SUV 2012 0.67% +282 /scratch/Teaching/cars/car_ims/008054.jpg Eagle Talon Hatchback 1998 Toyota Corolla Sedan 2012 36.48% Honda Accord Coupe 2012 23.08% Eagle Talon Hatchback 1998 20.45% Toyota Camry Sedan 2012 11.98% Nissan 240SX Coupe 1998 4.67% +283 /scratch/Teaching/cars/car_ims/005535.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 89.12% Chevrolet Silverado 1500 Extended Cab 2012 3.86% Chevrolet Silverado 2500HD Regular Cab 2012 3.79% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 1.52% Chevrolet Avalanche Crew Cab 2012 1.3% +284 /scratch/Teaching/cars/car_ims/009341.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 95.75% Ford F-150 Regular Cab 2012 4.18% GMC Canyon Extended Cab 2012 0.06% Chevrolet Silverado 1500 Regular Cab 2012 0.0% GMC Yukon Hybrid SUV 2012 0.0% +285 /scratch/Teaching/cars/car_ims/014486.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 36.81% Dodge Challenger SRT8 2011 20.01% Rolls-Royce Ghost Sedan 2012 16.72% Rolls-Royce Phantom Sedan 2012 9.35% BMW 6 Series Convertible 2007 7.02% +286 /scratch/Teaching/cars/car_ims/007525.jpg Dodge Magnum Wagon 2008 Chevrolet Malibu Sedan 2007 75.66% Chevrolet Impala Sedan 2007 12.59% Lincoln Town Car Sedan 2011 5.05% Chevrolet Monte Carlo Coupe 2007 3.19% Ford Focus Sedan 2007 1.66% +287 /scratch/Teaching/cars/car_ims/004555.jpg Chevrolet Corvette ZR1 2012 Chevrolet Corvette ZR1 2012 64.97% Porsche Panamera Sedan 2012 22.24% Bugatti Veyron 16.4 Convertible 2009 8.49% Chevrolet Corvette Ron Fellows Edition Z06 2007 1.44% Volkswagen Beetle Hatchback 2012 1.17% +288 /scratch/Teaching/cars/car_ims/012913.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 90.81% Ford F-450 Super Duty Crew Cab 2012 6.09% Cadillac CTS-V Sedan 2012 1.09% Ford F-150 Regular Cab 2012 0.43% Nissan NV Passenger Van 2012 0.41% +289 /scratch/Teaching/cars/car_ims/009843.jpg GMC Yukon Hybrid SUV 2012 GMC Yukon Hybrid SUV 2012 80.11% Chevrolet Tahoe Hybrid SUV 2012 19.67% Chevrolet Avalanche Crew Cab 2012 0.09% Cadillac Escalade EXT Crew Cab 2007 0.05% Isuzu Ascender SUV 2008 0.05% +290 /scratch/Teaching/cars/car_ims/008907.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 97.05% Chevrolet Tahoe Hybrid SUV 2012 2.73% GMC Yukon Hybrid SUV 2012 0.08% Chrysler Aspen SUV 2009 0.03% Land Rover LR2 SUV 2012 0.03% +291 /scratch/Teaching/cars/car_ims/001105.jpg Audi TTS Coupe 2012 Audi TTS Coupe 2012 64.6% Audi TT Hatchback 2011 32.18% Audi TT RS Coupe 2012 1.75% Audi S4 Sedan 2012 0.78% Audi A5 Coupe 2012 0.17% +292 /scratch/Teaching/cars/car_ims/013839.jpg Nissan Leaf Hatchback 2012 Maybach Landaulet Convertible 2012 28.69% FIAT 500 Convertible 2012 25.58% Nissan Leaf Hatchback 2012 19.38% Suzuki SX4 Sedan 2012 8.06% Acura ZDX Hatchback 2012 7.28% +293 /scratch/Teaching/cars/car_ims/005266.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 95.86% Chevrolet Tahoe Hybrid SUV 2012 2.62% Chevrolet Silverado 1500 Regular Cab 2012 1.01% GMC Yukon Hybrid SUV 2012 0.16% Chevrolet Silverado 1500 Extended Cab 2012 0.16% +294 /scratch/Teaching/cars/car_ims/007367.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 95.44% Chevrolet Avalanche Crew Cab 2012 3.17% Dodge Dakota Club Cab 2007 0.83% Chevrolet Silverado 1500 Extended Cab 2012 0.37% Isuzu Ascender SUV 2008 0.15% +295 /scratch/Teaching/cars/car_ims/011359.jpg Hyundai Sonata Sedan 2012 Hyundai Sonata Sedan 2012 52.0% Hyundai Sonata Hybrid Sedan 2012 12.26% Hyundai Elantra Sedan 2007 12.18% Buick Verano Sedan 2012 6.64% Hyundai Azera Sedan 2012 5.93% +296 /scratch/Teaching/cars/car_ims/014464.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Phantom Sedan 2012 99.94% Rolls-Royce Ghost Sedan 2012 0.05% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.01% Volvo 240 Sedan 1993 0.0% Chrysler 300 SRT-8 2010 0.0% +297 /scratch/Teaching/cars/car_ims/006729.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2012 65.6% Dodge Caliber Wagon 2007 34.09% Dodge Journey SUV 2012 0.28% Suzuki SX4 Hatchback 2012 0.01% Dodge Durango SUV 2007 0.01% +298 /scratch/Teaching/cars/car_ims/006580.jpg Chrysler PT Cruiser Convertible 2008 Dodge Caliber Wagon 2012 52.62% Chrysler PT Cruiser Convertible 2008 37.29% Dodge Caliber Wagon 2007 5.04% Dodge Journey SUV 2012 1.42% Mazda Tribute SUV 2011 0.65% +299 /scratch/Teaching/cars/car_ims/006265.jpg Chrysler Sebring Convertible 2010 Honda Accord Sedan 2012 28.07% Chrysler Sebring Convertible 2010 27.12% Hyundai Sonata Sedan 2012 16.79% Hyundai Azera Sedan 2012 14.37% Hyundai Genesis Sedan 2012 5.45% +300 /scratch/Teaching/cars/car_ims/015297.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.75% Hyundai Santa Fe SUV 2012 0.15% Chrysler Aspen SUV 2009 0.05% Ford Expedition EL SUV 2009 0.03% Land Rover LR2 SUV 2012 0.01% +301 /scratch/Teaching/cars/car_ims/011484.jpg Hyundai Azera Sedan 2012 Hyundai Azera Sedan 2012 36.68% Infiniti G Coupe IPL 2012 33.46% Audi S4 Sedan 2012 15.88% Hyundai Genesis Sedan 2012 6.99% Mercedes-Benz C-Class Sedan 2012 1.13% +302 /scratch/Teaching/cars/car_ims/003613.jpg Bugatti Veyron 16.4 Convertible 2009 BMW Z4 Convertible 2012 11.23% BMW 1 Series Convertible 2012 7.27% Bentley Continental Supersports Conv. Convertible 2012 5.32% Bugatti Veyron 16.4 Convertible 2009 5.04% Bentley Continental GT Coupe 2012 3.89% +303 /scratch/Teaching/cars/car_ims/002787.jpg BMW M3 Coupe 2012 BMW M5 Sedan 2010 80.36% BMW M3 Coupe 2012 19.63% BMW 3 Series Sedan 2012 0.01% BMW 1 Series Coupe 2012 0.0% BMW 3 Series Wagon 2012 0.0% +304 /scratch/Teaching/cars/car_ims/000912.jpg Audi RS 4 Convertible 2008 Audi RS 4 Convertible 2008 97.05% BMW Z4 Convertible 2012 2.65% Audi S4 Sedan 2007 0.11% BMW M6 Convertible 2010 0.05% Audi TTS Coupe 2012 0.04% +305 /scratch/Teaching/cars/car_ims/013209.jpg Mercedes-Benz 300-Class Convertible 1993 Geo Metro Convertible 1993 73.56% Mercedes-Benz 300-Class Convertible 1993 21.04% Audi 100 Wagon 1994 2.88% Ford F-150 Regular Cab 2007 2.02% Audi 100 Sedan 1994 0.4% +306 /scratch/Teaching/cars/car_ims/006547.jpg Chrysler PT Cruiser Convertible 2008 Chrysler PT Cruiser Convertible 2008 73.78% Mercedes-Benz E-Class Sedan 2012 18.28% Infiniti QX56 SUV 2011 3.91% Land Rover LR2 SUV 2012 1.05% Cadillac SRX SUV 2012 0.86% +307 /scratch/Teaching/cars/car_ims/002290.jpg BMW 3 Series Sedan 2012 BMW M5 Sedan 2010 27.5% Mitsubishi Lancer Sedan 2012 22.84% BMW 3 Series Wagon 2012 22.41% BMW 1 Series Coupe 2012 15.66% BMW 1 Series Convertible 2012 4.38% +308 /scratch/Teaching/cars/car_ims/013562.jpg Mercedes-Benz S-Class Sedan 2012 Mercedes-Benz S-Class Sedan 2012 53.45% Mercedes-Benz C-Class Sedan 2012 30.63% Mercedes-Benz E-Class Sedan 2012 12.23% Hyundai Genesis Sedan 2012 3.65% Audi S6 Sedan 2011 0.01% +309 /scratch/Teaching/cars/car_ims/016027.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 99.74% Audi 100 Wagon 1994 0.07% Chrysler Town and Country Minivan 2012 0.06% BMW X5 SUV 2007 0.03% Chrysler Aspen SUV 2009 0.03% +310 /scratch/Teaching/cars/car_ims/008859.jpg Ford Expedition EL SUV 2009 Chevrolet HHR SS 2010 47.85% Mazda Tribute SUV 2011 12.71% Dodge Journey SUV 2012 7.38% Suzuki SX4 Sedan 2012 6.41% Ram C/V Cargo Van Minivan 2012 5.22% +311 /scratch/Teaching/cars/car_ims/003480.jpg Bentley Continental GT Coupe 2007 Bentley Continental GT Coupe 2007 96.82% Bentley Continental Flying Spur Sedan 2007 2.84% Bentley Continental GT Coupe 2012 0.33% Bentley Mulsanne Sedan 2011 0.01% Fisker Karma Sedan 2012 0.0% +312 /scratch/Teaching/cars/car_ims/005221.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 71.59% Dodge Dakota Crew Cab 2010 9.88% Isuzu Ascender SUV 2008 8.31% Dodge Dakota Club Cab 2007 2.98% Chevrolet Silverado 1500 Extended Cab 2012 1.89% +313 /scratch/Teaching/cars/car_ims/001094.jpg Audi TTS Coupe 2012 Audi TTS Coupe 2012 76.73% Audi TT Hatchback 2011 21.56% Audi S4 Sedan 2012 0.57% Audi TT RS Coupe 2012 0.51% Audi R8 Coupe 2012 0.35% +314 /scratch/Teaching/cars/car_ims/005591.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 51.36% Chevrolet Silverado 1500 Regular Cab 2012 45.69% Chevrolet Silverado 1500 Extended Cab 2012 1.99% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.84% GMC Canyon Extended Cab 2012 0.05% +315 /scratch/Teaching/cars/car_ims/013904.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 99.14% GMC Yukon Hybrid SUV 2012 0.8% Jeep Wrangler SUV 2012 0.02% Jeep Liberty SUV 2012 0.02% Jeep Patriot SUV 2012 0.01% +316 /scratch/Teaching/cars/car_ims/006434.jpg Chrysler 300 SRT-8 2010 Audi S6 Sedan 2011 24.96% BMW X3 SUV 2012 24.46% Chrysler 300 SRT-8 2010 17.32% Bentley Continental GT Coupe 2012 5.0% BMW X5 SUV 2007 4.23% +317 /scratch/Teaching/cars/car_ims/003946.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 99.99% Buick Regal GS 2012 0.01% Chevrolet Sonic Sedan 2012 0.0% Acura RL Sedan 2012 0.0% Acura ZDX Hatchback 2012 0.0% +318 /scratch/Teaching/cars/car_ims/005945.jpg Chevrolet Silverado 1500 Extended Cab 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 52.97% Chevrolet Silverado 1500 Extended Cab 2012 25.21% Chevrolet Silverado 1500 Regular Cab 2012 19.28% Chevrolet Avalanche Crew Cab 2012 1.53% Chevrolet Silverado 2500HD Regular Cab 2012 0.95% +319 /scratch/Teaching/cars/car_ims/006819.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2012 94.8% Dodge Caliber Wagon 2007 5.2% Dodge Journey SUV 2012 0.0% Dodge Magnum Wagon 2008 0.0% Ram C/V Cargo Van Minivan 2012 0.0% +320 /scratch/Teaching/cars/car_ims/010120.jpg Geo Metro Convertible 1993 McLaren MP4-12C Coupe 2012 73.76% Aston Martin Virage Coupe 2012 6.89% Spyker C8 Coupe 2009 6.09% Lamborghini Aventador Coupe 2012 5.03% Bugatti Veyron 16.4 Coupe 2009 1.97% +321 /scratch/Teaching/cars/car_ims/004932.jpg Chevrolet Impala Sedan 2007 Acura RL Sedan 2012 23.1% Acura TL Type-S 2008 8.75% BMW M5 Sedan 2010 6.75% Buick Verano Sedan 2012 5.73% Acura TSX Sedan 2012 5.17% +322 /scratch/Teaching/cars/car_ims/000277.jpg Acura TL Type-S 2008 Acura TSX Sedan 2012 83.58% Acura TL Type-S 2008 14.87% Acura RL Sedan 2012 1.12% Toyota Camry Sedan 2012 0.15% Mitsubishi Lancer Sedan 2012 0.14% +323 /scratch/Teaching/cars/car_ims/007678.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 99.99% Dodge Caliber Wagon 2012 0.01% Dodge Journey SUV 2012 0.0% Dodge Magnum Wagon 2008 0.0% Dodge Durango SUV 2007 0.0% +324 /scratch/Teaching/cars/car_ims/008349.jpg Ferrari 458 Italia Convertible 2012 Ferrari 458 Italia Convertible 2012 57.96% Ferrari 458 Italia Coupe 2012 38.87% Ferrari California Convertible 2012 1.63% Lamborghini Aventador Coupe 2012 0.38% McLaren MP4-12C Coupe 2012 0.31% +325 /scratch/Teaching/cars/car_ims/003694.jpg Bugatti Veyron 16.4 Coupe 2009 Lamborghini Reventon Coupe 2008 38.11% Mercedes-Benz SL-Class Coupe 2009 21.75% Bugatti Veyron 16.4 Coupe 2009 13.65% Audi R8 Coupe 2012 12.72% Bugatti Veyron 16.4 Convertible 2009 5.52% +326 /scratch/Teaching/cars/car_ims/010035.jpg GMC Savana Van 2012 Chevrolet Express Van 2007 59.11% GMC Savana Van 2012 38.55% Chevrolet Express Cargo Van 2007 2.07% Volkswagen Golf Hatchback 1991 0.13% AM General Hummer SUV 2000 0.04% +327 /scratch/Teaching/cars/car_ims/015965.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 99.49% Volvo XC90 SUV 2007 0.27% Audi 100 Wagon 1994 0.17% Volkswagen Golf Hatchback 1991 0.05% Audi 100 Sedan 1994 0.02% +328 /scratch/Teaching/cars/car_ims/002291.jpg BMW 3 Series Sedan 2012 BMW 3 Series Sedan 2012 58.52% Acura TL Type-S 2008 6.41% Ferrari FF Coupe 2012 5.44% BMW M3 Coupe 2012 4.85% BMW M5 Sedan 2010 3.46% +329 /scratch/Teaching/cars/car_ims/014383.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 49.67% Bentley Continental Supersports Conv. Convertible 2012 21.52% Mercedes-Benz 300-Class Convertible 1993 12.65% Mercedes-Benz SL-Class Coupe 2009 6.93% Maybach Landaulet Convertible 2012 2.85% +330 /scratch/Teaching/cars/car_ims/001160.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 93.11% Mercedes-Benz SL-Class Coupe 2009 3.1% Lamborghini Reventon Coupe 2008 3.02% Lamborghini Aventador Coupe 2012 0.29% BMW M6 Convertible 2010 0.13% +331 /scratch/Teaching/cars/car_ims/000145.jpg Acura RL Sedan 2012 Acura TSX Sedan 2012 94.73% Acura RL Sedan 2012 4.95% Toyota Camry Sedan 2012 0.22% Acura TL Sedan 2012 0.09% Acura TL Type-S 2008 0.01% +332 /scratch/Teaching/cars/car_ims/012308.jpg Lamborghini Reventon Coupe 2008 Lamborghini Reventon Coupe 2008 99.94% Lamborghini Aventador Coupe 2012 0.06% Aston Martin V8 Vantage Coupe 2012 0.0% Bugatti Veyron 16.4 Coupe 2009 0.0% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.0% +333 /scratch/Teaching/cars/car_ims/012830.jpg Lincoln Town Car Sedan 2011 Audi 100 Wagon 1994 56.14% Lincoln Town Car Sedan 2011 28.65% Ford Focus Sedan 2007 7.09% Daewoo Nubira Wagon 2002 3.25% Volvo 240 Sedan 1993 1.73% +334 /scratch/Teaching/cars/car_ims/014310.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 99.89% Chrysler Town and Country Minivan 2012 0.1% Ford Freestar Minivan 2007 0.01% Dodge Caliber Wagon 2012 0.0% Suzuki SX4 Sedan 2012 0.0% +335 /scratch/Teaching/cars/car_ims/008263.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 70.62% Chevrolet Corvette Convertible 2012 15.64% Jaguar XK XKR 2012 5.84% Ferrari 458 Italia Convertible 2012 5.52% Ferrari FF Coupe 2012 0.9% +336 /scratch/Teaching/cars/car_ims/005342.jpg Chevrolet Cobalt SS 2010 Toyota Corolla Sedan 2012 74.02% Chevrolet Cobalt SS 2010 24.65% Toyota Camry Sedan 2012 0.4% Hyundai Elantra Sedan 2007 0.32% Chevrolet Monte Carlo Coupe 2007 0.19% +337 /scratch/Teaching/cars/car_ims/008726.jpg Ford Mustang Convertible 2007 Ford Mustang Convertible 2007 92.23% Mercedes-Benz 300-Class Convertible 1993 7.22% Dodge Charger SRT-8 2009 0.23% Chrysler Crossfire Convertible 2008 0.15% Dodge Charger Sedan 2012 0.07% +338 /scratch/Teaching/cars/car_ims/008665.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 73.82% Toyota Sequoia SUV 2012 24.58% Land Rover Range Rover SUV 2012 0.92% Infiniti QX56 SUV 2011 0.59% Cadillac Escalade EXT Crew Cab 2007 0.04% +339 /scratch/Teaching/cars/car_ims/002664.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 99.91% Volvo C30 Hatchback 2012 0.07% Suzuki SX4 Hatchback 2012 0.01% Dodge Caliber Wagon 2007 0.0% BMW 1 Series Coupe 2012 0.0% +340 /scratch/Teaching/cars/car_ims/000024.jpg AM General Hummer SUV 2000 HUMMER H2 SUT Crew Cab 2009 66.72% AM General Hummer SUV 2000 28.8% HUMMER H3T Crew Cab 2010 1.95% McLaren MP4-12C Coupe 2012 0.91% Spyker C8 Coupe 2009 0.5% +341 /scratch/Teaching/cars/car_ims/015973.jpg Volvo 240 Sedan 1993 Lincoln Town Car Sedan 2011 99.94% Audi 100 Wagon 1994 0.03% Volvo 240 Sedan 1993 0.02% Mercedes-Benz 300-Class Convertible 1993 0.01% Dodge Magnum Wagon 2008 0.0% +342 /scratch/Teaching/cars/car_ims/014127.jpg Plymouth Neon Coupe 1999 Plymouth Neon Coupe 1999 73.34% Ford Focus Sedan 2007 26.54% Daewoo Nubira Wagon 2002 0.04% Geo Metro Convertible 1993 0.03% Chevrolet Impala Sedan 2007 0.02% +343 /scratch/Teaching/cars/car_ims/007476.jpg Dodge Magnum Wagon 2008 Dodge Magnum Wagon 2008 97.51% Chevrolet HHR SS 2010 2.4% Dodge Charger SRT-8 2009 0.06% Dodge Caliber Wagon 2012 0.01% Dodge Durango SUV 2012 0.01% +344 /scratch/Teaching/cars/car_ims/015381.jpg Toyota Camry Sedan 2012 Acura TSX Sedan 2012 39.88% Toyota Corolla Sedan 2012 21.81% Acura TL Type-S 2008 12.5% Toyota Camry Sedan 2012 8.17% BMW M5 Sedan 2010 4.26% +345 /scratch/Teaching/cars/car_ims/007769.jpg Dodge Durango SUV 2007 Buick Rainier SUV 2007 62.92% Isuzu Ascender SUV 2008 13.51% Chevrolet Tahoe Hybrid SUV 2012 6.78% Ford Freestar Minivan 2007 5.27% Mazda Tribute SUV 2011 4.04% +346 /scratch/Teaching/cars/car_ims/009388.jpg Ford Focus Sedan 2007 Chevrolet Impala Sedan 2007 44.44% Honda Odyssey Minivan 2007 9.57% Chevrolet Malibu Sedan 2007 8.01% Ford Focus Sedan 2007 7.46% Hyundai Elantra Sedan 2007 4.39% +347 /scratch/Teaching/cars/car_ims/014738.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 89.8% Spyker C8 Coupe 2009 8.31% Bugatti Veyron 16.4 Coupe 2009 1.73% Bugatti Veyron 16.4 Convertible 2009 0.14% McLaren MP4-12C Coupe 2012 0.01% +348 /scratch/Teaching/cars/car_ims/006310.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 99.14% Ram C/V Cargo Van Minivan 2012 0.83% Honda Odyssey Minivan 2007 0.01% Ford Freestar Minivan 2007 0.01% Chevrolet Malibu Sedan 2007 0.01% +349 /scratch/Teaching/cars/car_ims/016167.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 90.92% FIAT 500 Convertible 2012 5.7% MINI Cooper Roadster Convertible 2012 2.84% Nissan Juke Hatchback 2012 0.2% Bugatti Veyron 16.4 Convertible 2009 0.1% +350 /scratch/Teaching/cars/car_ims/015279.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.86% Chrysler Aspen SUV 2009 0.03% Ford Expedition EL SUV 2009 0.03% Cadillac SRX SUV 2012 0.03% Cadillac Escalade EXT Crew Cab 2007 0.02% +351 /scratch/Teaching/cars/car_ims/015944.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 52.58% Bentley Arnage Sedan 2009 38.77% Jeep Patriot SUV 2012 4.16% Chrysler 300 SRT-8 2010 1.6% Jeep Liberty SUV 2012 1.32% +352 /scratch/Teaching/cars/car_ims/015578.jpg Toyota 4Runner SUV 2012 Toyota Sequoia SUV 2012 95.1% Cadillac SRX SUV 2012 2.43% Cadillac Escalade EXT Crew Cab 2007 0.7% Land Rover LR2 SUV 2012 0.62% Dodge Durango SUV 2012 0.39% +353 /scratch/Teaching/cars/car_ims/009330.jpg Ford F-150 Regular Cab 2007 Volvo 240 Sedan 1993 33.02% Mercedes-Benz 300-Class Convertible 1993 9.06% Audi 100 Sedan 1994 8.8% Audi 100 Wagon 1994 7.99% Audi V8 Sedan 1994 4.41% +354 /scratch/Teaching/cars/car_ims/003812.jpg Buick Rainier SUV 2007 Jeep Liberty SUV 2012 34.78% Jeep Patriot SUV 2012 26.44% GMC Yukon Hybrid SUV 2012 24.09% Land Rover Range Rover SUV 2012 4.74% Dodge Durango SUV 2007 3.7% +355 /scratch/Teaching/cars/car_ims/003823.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 99.94% Isuzu Ascender SUV 2008 0.02% Ford Freestar Minivan 2007 0.02% Dodge Durango SUV 2007 0.01% Audi 100 Wagon 1994 0.01% +356 /scratch/Teaching/cars/car_ims/003564.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 78.71% Bentley Continental GT Coupe 2007 18.69% Bentley Continental GT Coupe 2012 1.3% Bentley Mulsanne Sedan 2011 1.26% Maybach Landaulet Convertible 2012 0.03% +357 /scratch/Teaching/cars/car_ims/012659.jpg Land Rover Range Rover SUV 2012 Land Rover Range Rover SUV 2012 87.97% Land Rover LR2 SUV 2012 7.46% Ford Expedition EL SUV 2009 4.44% Dodge Durango SUV 2012 0.06% Toyota Sequoia SUV 2012 0.02% +358 /scratch/Teaching/cars/car_ims/015287.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.91% Cadillac SRX SUV 2012 0.09% Cadillac Escalade EXT Crew Cab 2007 0.0% Toyota 4Runner SUV 2012 0.0% Land Rover LR2 SUV 2012 0.0% +359 /scratch/Teaching/cars/car_ims/009173.jpg Ford GT Coupe 2006 Lamborghini Diablo Coupe 2001 94.73% McLaren MP4-12C Coupe 2012 4.34% Spyker C8 Coupe 2009 0.39% Ford GT Coupe 2006 0.26% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.12% +360 /scratch/Teaching/cars/car_ims/013266.jpg Mercedes-Benz C-Class Sedan 2012 Hyundai Genesis Sedan 2012 75.71% Mercedes-Benz C-Class Sedan 2012 23.05% Honda Accord Sedan 2012 0.46% Mercedes-Benz E-Class Sedan 2012 0.4% Mercedes-Benz S-Class Sedan 2012 0.31% +361 /scratch/Teaching/cars/car_ims/004553.jpg Chevrolet Corvette ZR1 2012 Suzuki SX4 Sedan 2012 46.55% Porsche Panamera Sedan 2012 13.0% Volkswagen Beetle Hatchback 2012 6.87% Audi S4 Sedan 2007 5.83% Chevrolet Cobalt SS 2010 5.8% +362 /scratch/Teaching/cars/car_ims/009374.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2012 62.46% Ford F-150 Regular Cab 2007 32.5% Ford E-Series Wagon Van 2012 3.34% Ford Ranger SuperCab 2011 1.55% Dodge Ram Pickup 3500 Quad Cab 2009 0.04% +363 /scratch/Teaching/cars/car_ims/015096.jpg Suzuki SX4 Sedan 2012 Honda Odyssey Minivan 2007 74.31% Hyundai Veracruz SUV 2012 15.81% Suzuki SX4 Sedan 2012 8.89% Chrysler Town and Country Minivan 2012 0.3% Chevrolet Traverse SUV 2012 0.29% +364 /scratch/Teaching/cars/car_ims/008828.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 99.17% Dodge Caravan Minivan 1997 0.47% Audi 100 Wagon 1994 0.29% Lincoln Town Car Sedan 2011 0.05% Chrysler Town and Country Minivan 2012 0.01% +365 /scratch/Teaching/cars/car_ims/013404.jpg Mercedes-Benz SL-Class Coupe 2009 Suzuki Aerio Sedan 2007 23.46% Volkswagen Golf Hatchback 2012 21.63% Mercedes-Benz Sprinter Van 2012 15.81% Mercedes-Benz C-Class Sedan 2012 10.41% Hyundai Genesis Sedan 2012 7.8% +366 /scratch/Teaching/cars/car_ims/010800.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 96.38% Hyundai Veracruz SUV 2012 3.4% Chevrolet Traverse SUV 2012 0.13% Ford Edge SUV 2012 0.06% Toyota Sequoia SUV 2012 0.01% +367 /scratch/Teaching/cars/car_ims/014414.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 92.87% Dodge Challenger SRT8 2011 2.44% Rolls-Royce Phantom Sedan 2012 2.42% Rolls-Royce Ghost Sedan 2012 1.77% Chevrolet Monte Carlo Coupe 2007 0.13% +368 /scratch/Teaching/cars/car_ims/002266.jpg BMW 1 Series Coupe 2012 BMW 1 Series Coupe 2012 55.48% BMW 1 Series Convertible 2012 30.51% Suzuki Kizashi Sedan 2012 4.66% BMW 3 Series Sedan 2012 3.22% BMW 3 Series Wagon 2012 1.71% +369 /scratch/Teaching/cars/car_ims/009733.jpg GMC Savana Van 2012 GMC Savana Van 2012 77.64% Chevrolet Express Cargo Van 2007 16.09% Chevrolet Express Van 2007 6.27% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.0% Volkswagen Golf Hatchback 1991 0.0% +370 /scratch/Teaching/cars/car_ims/003846.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 50.32% Isuzu Ascender SUV 2008 9.76% Volvo XC90 SUV 2007 8.99% Ford Freestar Minivan 2007 4.43% Jeep Liberty SUV 2012 3.25% +371 /scratch/Teaching/cars/car_ims/014244.jpg Porsche Panamera Sedan 2012 Porsche Panamera Sedan 2012 44.43% Chevrolet Corvette Ron Fellows Edition Z06 2007 14.38% Acura TL Sedan 2012 11.52% Fisker Karma Sedan 2012 3.99% Jaguar XK XKR 2012 3.69% +372 /scratch/Teaching/cars/car_ims/005903.jpg Chevrolet Malibu Sedan 2007 Chevrolet Malibu Sedan 2007 68.13% Chevrolet Impala Sedan 2007 9.83% Scion xD Hatchback 2012 5.94% Ram C/V Cargo Van Minivan 2012 2.78% Honda Odyssey Minivan 2012 1.7% +373 /scratch/Teaching/cars/car_ims/000029.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 51.5% HUMMER H2 SUT Crew Cab 2009 5.99% Jeep Wrangler SUV 2012 3.15% Bentley Arnage Sedan 2009 2.48% GMC Savana Van 2012 2.18% +374 /scratch/Teaching/cars/car_ims/014423.jpg Rolls-Royce Ghost Sedan 2012 Lincoln Town Car Sedan 2011 37.74% Volvo 240 Sedan 1993 26.47% Rolls-Royce Phantom Sedan 2012 12.17% Bentley Arnage Sedan 2009 4.98% Chevrolet Impala Sedan 2007 4.39% +375 /scratch/Teaching/cars/car_ims/011224.jpg Hyundai Genesis Sedan 2012 Infiniti G Coupe IPL 2012 73.64% Hyundai Azera Sedan 2012 18.98% Toyota Camry Sedan 2012 3.38% Hyundai Genesis Sedan 2012 0.98% Acura RL Sedan 2012 0.94% +376 /scratch/Teaching/cars/car_ims/001451.jpg Audi 100 Wagon 1994 Chevrolet Malibu Sedan 2007 59.2% Chevrolet Impala Sedan 2007 10.76% Honda Odyssey Minivan 2007 10.52% Honda Odyssey Minivan 2012 3.85% Lincoln Town Car Sedan 2011 3.16% +377 /scratch/Teaching/cars/car_ims/011438.jpg Hyundai Elantra Touring Hatchback 2012 Hyundai Elantra Touring Hatchback 2012 65.31% Volkswagen Golf Hatchback 2012 29.92% Suzuki SX4 Hatchback 2012 4.13% Volvo C30 Hatchback 2012 0.22% Hyundai Santa Fe SUV 2012 0.12% +378 /scratch/Teaching/cars/car_ims/001650.jpg Audi S5 Convertible 2012 Audi S4 Sedan 2007 23.11% Audi S4 Sedan 2012 18.93% BMW 1 Series Convertible 2012 15.15% BMW 3 Series Wagon 2012 14.76% BMW 1 Series Coupe 2012 11.19% +379 /scratch/Teaching/cars/car_ims/007592.jpg Dodge Challenger SRT8 2011 Jaguar XK XKR 2012 22.96% Infiniti G Coupe IPL 2012 22.19% Audi S4 Sedan 2012 9.7% Audi S4 Sedan 2007 8.56% BMW M3 Coupe 2012 8.3% +380 /scratch/Teaching/cars/car_ims/002115.jpg BMW ActiveHybrid 5 Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 99.76% BMW 3 Series Wagon 2012 0.18% Rolls-Royce Ghost Sedan 2012 0.03% BMW 3 Series Sedan 2012 0.02% BMW M6 Convertible 2010 0.0% +381 /scratch/Teaching/cars/car_ims/011727.jpg Isuzu Ascender SUV 2008 Isuzu Ascender SUV 2008 99.81% Chevrolet Tahoe Hybrid SUV 2012 0.15% Chevrolet Avalanche Crew Cab 2012 0.03% Jeep Patriot SUV 2012 0.01% GMC Yukon Hybrid SUV 2012 0.0% +382 /scratch/Teaching/cars/car_ims/013469.jpg Mercedes-Benz E-Class Sedan 2012 Hyundai Genesis Sedan 2012 34.06% Mercedes-Benz E-Class Sedan 2012 20.66% Hyundai Azera Sedan 2012 19.49% Infiniti G Coupe IPL 2012 12.82% Mercedes-Benz C-Class Sedan 2012 7.69% +383 /scratch/Teaching/cars/car_ims/001052.jpg Audi TTS Coupe 2012 Audi TT Hatchback 2011 28.97% Audi S5 Convertible 2012 22.2% Audi TTS Coupe 2012 16.06% Audi S5 Coupe 2012 12.45% Audi RS 4 Convertible 2008 5.39% +384 /scratch/Teaching/cars/car_ims/009676.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 100.0% Chevrolet Avalanche Crew Cab 2012 0.0% Toyota 4Runner SUV 2012 0.0% Chevrolet Tahoe Hybrid SUV 2012 0.0% Chevrolet Silverado 1500 Regular Cab 2012 0.0% +385 /scratch/Teaching/cars/car_ims/011540.jpg Hyundai Azera Sedan 2012 Nissan Juke Hatchback 2012 35.9% Jaguar XK XKR 2012 25.97% Ford Edge SUV 2012 10.17% Hyundai Azera Sedan 2012 6.38% Dodge Charger Sedan 2012 6.19% +386 /scratch/Teaching/cars/car_ims/004615.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 85.8% Chevrolet Corvette ZR1 2012 4.28% Chevrolet Corvette Convertible 2012 3.97% Ferrari 458 Italia Convertible 2012 1.69% Ferrari 458 Italia Coupe 2012 1.28% +387 /scratch/Teaching/cars/car_ims/009898.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 99.94% Chevrolet Traverse SUV 2012 0.06% Buick Enclave SUV 2012 0.0% Cadillac SRX SUV 2012 0.0% Hyundai Veracruz SUV 2012 0.0% +388 /scratch/Teaching/cars/car_ims/001026.jpg Audi A5 Coupe 2012 Audi S4 Sedan 2007 85.37% Audi A5 Coupe 2012 12.98% Audi S4 Sedan 2012 1.49% Mitsubishi Lancer Sedan 2012 0.09% Audi S5 Coupe 2012 0.08% +389 /scratch/Teaching/cars/car_ims/012162.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 95.02% Jeep Compass SUV 2012 3.93% Mazda Tribute SUV 2011 0.76% GMC Terrain SUV 2012 0.11% GMC Acadia SUV 2012 0.08% +390 /scratch/Teaching/cars/car_ims/011125.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 99.89% Toyota Corolla Sedan 2012 0.07% Suzuki SX4 Sedan 2012 0.01% Buick Verano Sedan 2012 0.01% Acura RL Sedan 2012 0.01% +391 /scratch/Teaching/cars/car_ims/015324.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.99% Land Rover LR2 SUV 2012 0.01% Infiniti QX56 SUV 2011 0.0% Ford Expedition EL SUV 2009 0.0% Land Rover Range Rover SUV 2012 0.0% +392 /scratch/Teaching/cars/car_ims/004953.jpg Chevrolet Impala Sedan 2007 Chevrolet Malibu Hybrid Sedan 2010 33.06% Honda Accord Sedan 2012 19.71% Honda Odyssey Minivan 2012 7.07% Chrysler 300 SRT-8 2010 4.84% Buick Verano Sedan 2012 3.62% +393 /scratch/Teaching/cars/car_ims/011876.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 96.59% GMC Yukon Hybrid SUV 2012 2.78% Jeep Liberty SUV 2012 0.42% Jeep Wrangler SUV 2012 0.17% Bentley Arnage Sedan 2009 0.01% +394 /scratch/Teaching/cars/car_ims/007754.jpg Dodge Durango SUV 2007 Ford Ranger SuperCab 2011 75.72% Isuzu Ascender SUV 2008 22.08% Ford F-150 Regular Cab 2007 0.86% Dodge Durango SUV 2007 0.62% GMC Canyon Extended Cab 2012 0.14% +395 /scratch/Teaching/cars/car_ims/008589.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 94.38% Aston Martin V8 Vantage Coupe 2012 2.46% BMW M6 Convertible 2010 0.99% Aston Martin Virage Convertible 2012 0.6% Dodge Challenger SRT8 2011 0.39% +396 /scratch/Teaching/cars/car_ims/008551.jpg Fisker Karma Sedan 2012 Spyker C8 Coupe 2009 38.12% Hyundai Veloster Hatchback 2012 12.74% Buick Regal GS 2012 6.31% Bugatti Veyron 16.4 Convertible 2009 4.19% Spyker C8 Convertible 2009 4.14% +397 /scratch/Teaching/cars/car_ims/010555.jpg Honda Accord Coupe 2012 Volkswagen Beetle Hatchback 2012 30.24% Suzuki Kizashi Sedan 2012 6.83% Porsche Panamera Sedan 2012 5.99% Chevrolet Corvette ZR1 2012 5.09% Volvo C30 Hatchback 2012 5.08% +398 /scratch/Teaching/cars/car_ims/009647.jpg GMC Terrain SUV 2012 Mazda Tribute SUV 2011 34.26% Jeep Grand Cherokee SUV 2012 12.36% Chevrolet Traverse SUV 2012 8.37% Hyundai Veracruz SUV 2012 6.19% Dodge Durango SUV 2012 4.55% +399 /scratch/Teaching/cars/car_ims/012971.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 98.04% Daewoo Nubira Wagon 2002 0.92% Bentley Continental Flying Spur Sedan 2007 0.68% Suzuki Aerio Sedan 2007 0.2% FIAT 500 Convertible 2012 0.05% +400 /scratch/Teaching/cars/car_ims/013113.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 99.96% Lamborghini Diablo Coupe 2001 0.01% Aston Martin Virage Coupe 2012 0.01% Lamborghini Aventador Coupe 2012 0.01% Spyker C8 Coupe 2009 0.0% +401 /scratch/Teaching/cars/car_ims/006956.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 99.24% Ford Freestar Minivan 2007 0.49% Audi 100 Wagon 1994 0.06% Chevrolet Express Van 2007 0.04% Dodge Sprinter Cargo Van 2009 0.04% +402 /scratch/Teaching/cars/car_ims/010404.jpg Honda Odyssey Minivan 2012 Hyundai Veracruz SUV 2012 83.54% Honda Odyssey Minivan 2012 11.44% Chevrolet Traverse SUV 2012 1.68% Honda Odyssey Minivan 2007 0.96% Land Rover LR2 SUV 2012 0.57% +403 /scratch/Teaching/cars/car_ims/013135.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 99.79% Spyker C8 Coupe 2009 0.15% Lamborghini Aventador Coupe 2012 0.05% Aston Martin Virage Coupe 2012 0.0% Spyker C8 Convertible 2009 0.0% +404 /scratch/Teaching/cars/car_ims/011991.jpg Jeep Wrangler SUV 2012 Jeep Wrangler SUV 2012 76.28% HUMMER H3T Crew Cab 2010 19.74% GMC Canyon Extended Cab 2012 2.13% HUMMER H2 SUT Crew Cab 2009 0.85% AM General Hummer SUV 2000 0.47% +405 /scratch/Teaching/cars/car_ims/002250.jpg BMW 1 Series Coupe 2012 BMW 1 Series Coupe 2012 85.8% BMW 1 Series Convertible 2012 12.19% BMW 3 Series Wagon 2012 1.34% Suzuki Kizashi Sedan 2012 0.24% BMW M5 Sedan 2010 0.11% +406 /scratch/Teaching/cars/car_ims/013497.jpg Mercedes-Benz S-Class Sedan 2012 BMW 3 Series Sedan 2012 32.41% Audi 100 Wagon 1994 21.29% Mercedes-Benz S-Class Sedan 2012 16.95% Audi V8 Sedan 1994 11.14% BMW 3 Series Wagon 2012 6.2% +407 /scratch/Teaching/cars/car_ims/011077.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 60.1% Acura TSX Sedan 2012 15.78% Acura RL Sedan 2012 13.07% Toyota Camry Sedan 2012 2.37% Acura TL Sedan 2012 1.71% +408 /scratch/Teaching/cars/car_ims/015949.jpg Volvo 240 Sedan 1993 Lincoln Town Car Sedan 2011 63.09% Volvo 240 Sedan 1993 27.93% Audi 100 Wagon 1994 8.95% Mercedes-Benz 300-Class Convertible 1993 0.02% Audi 100 Sedan 1994 0.0% +409 /scratch/Teaching/cars/car_ims/003900.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 73.13% Acura ZDX Hatchback 2012 13.61% Hyundai Veracruz SUV 2012 5.12% Suzuki SX4 Sedan 2012 1.63% Acura RL Sedan 2012 1.44% +410 /scratch/Teaching/cars/car_ims/009294.jpg Ford F-150 Regular Cab 2007 Honda Accord Sedan 2012 35.06% Hyundai Genesis Sedan 2012 9.61% Suzuki SX4 Sedan 2012 5.64% Acura RL Sedan 2012 5.45% Toyota Corolla Sedan 2012 3.85% +411 /scratch/Teaching/cars/car_ims/013363.jpg Mercedes-Benz SL-Class Coupe 2009 Mercedes-Benz SL-Class Coupe 2009 58.08% BMW ActiveHybrid 5 Sedan 2012 11.53% Porsche Panamera Sedan 2012 8.49% BMW M5 Sedan 2010 5.26% BMW M3 Coupe 2012 3.2% +412 /scratch/Teaching/cars/car_ims/005909.jpg Chevrolet Malibu Sedan 2007 Honda Accord Sedan 2012 45.55% Honda Odyssey Minivan 2012 23.74% Chevrolet Malibu Hybrid Sedan 2010 6.86% Hyundai Sonata Sedan 2012 3.95% Honda Accord Coupe 2012 3.51% +413 /scratch/Teaching/cars/car_ims/012223.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 98.87% Jeep Grand Cherokee SUV 2012 1.13% Jeep Liberty SUV 2012 0.01% Jeep Patriot SUV 2012 0.0% Jeep Wrangler SUV 2012 0.0% +414 /scratch/Teaching/cars/car_ims/001412.jpg Audi 100 Wagon 1994 Audi 100 Wagon 1994 53.03% Audi 100 Sedan 1994 26.29% Mercedes-Benz 300-Class Convertible 1993 11.52% Lincoln Town Car Sedan 2011 2.96% Geo Metro Convertible 1993 1.39% +415 /scratch/Teaching/cars/car_ims/012399.jpg Lamborghini Aventador Coupe 2012 Lamborghini Aventador Coupe 2012 96.86% McLaren MP4-12C Coupe 2012 2.64% Audi R8 Coupe 2012 0.26% Lamborghini Reventon Coupe 2008 0.12% Bugatti Veyron 16.4 Coupe 2009 0.02% +416 /scratch/Teaching/cars/car_ims/007952.jpg Dodge Charger SRT-8 2009 Dodge Charger SRT-8 2009 99.92% Dodge Charger Sedan 2012 0.07% Chevrolet TrailBlazer SS 2009 0.01% Dodge Challenger SRT8 2011 0.0% Chevrolet Camaro Convertible 2012 0.0% +417 /scratch/Teaching/cars/car_ims/009266.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 34.29% GMC Yukon Hybrid SUV 2012 17.06% Chevrolet Silverado 1500 Regular Cab 2012 12.02% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 10.39% GMC Canyon Extended Cab 2012 10.06% +418 /scratch/Teaching/cars/car_ims/009440.jpg Ford Focus Sedan 2007 BMW ActiveHybrid 5 Sedan 2012 23.41% Mercedes-Benz S-Class Sedan 2012 17.8% BMW 1 Series Convertible 2012 17.69% BMW 3 Series Wagon 2012 9.35% Audi S4 Sedan 2007 7.21% +419 /scratch/Teaching/cars/car_ims/013751.jpg Mitsubishi Lancer Sedan 2012 Mitsubishi Lancer Sedan 2012 95.66% Acura TL Type-S 2008 3.7% Acura RL Sedan 2012 0.27% Honda Odyssey Minivan 2012 0.14% Chevrolet Malibu Hybrid Sedan 2010 0.05% +420 /scratch/Teaching/cars/car_ims/013403.jpg Mercedes-Benz SL-Class Coupe 2009 Mercedes-Benz SL-Class Coupe 2009 99.83% Hyundai Genesis Sedan 2012 0.07% Mercedes-Benz C-Class Sedan 2012 0.06% Porsche Panamera Sedan 2012 0.02% Mercedes-Benz Sprinter Van 2012 0.01% +421 /scratch/Teaching/cars/car_ims/005810.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Impala Sedan 2007 34.47% Acura TL Type-S 2008 15.5% Chevrolet Monte Carlo Coupe 2007 13.25% Chevrolet Malibu Hybrid Sedan 2010 11.09% Hyundai Elantra Sedan 2007 7.72% +422 /scratch/Teaching/cars/car_ims/000698.jpg Aston Martin V8 Vantage Coupe 2012 Aston Martin V8 Vantage Coupe 2012 95.54% Aston Martin V8 Vantage Convertible 2012 4.4% Aston Martin Virage Convertible 2012 0.06% Fisker Karma Sedan 2012 0.0% Tesla Model S Sedan 2012 0.0% +423 /scratch/Teaching/cars/car_ims/002327.jpg BMW 3 Series Sedan 2012 BMW 3 Series Sedan 2012 61.74% BMW 1 Series Coupe 2012 15.81% BMW 3 Series Wagon 2012 13.66% BMW M3 Coupe 2012 5.06% BMW M5 Sedan 2010 1.2% +424 /scratch/Teaching/cars/car_ims/005186.jpg Chevrolet Express Cargo Van 2007 GMC Savana Van 2012 35.82% Chevrolet Express Van 2007 35.63% Chevrolet Express Cargo Van 2007 28.55% Volkswagen Golf Hatchback 1991 0.0% Nissan NV Passenger Van 2012 0.0% +425 /scratch/Teaching/cars/car_ims/002812.jpg BMW M5 Sedan 2010 BMW M5 Sedan 2010 91.78% BMW M3 Coupe 2012 5.65% BMW 1 Series Coupe 2012 2.04% BMW Z4 Convertible 2012 0.26% Mitsubishi Lancer Sedan 2012 0.17% +426 /scratch/Teaching/cars/car_ims/014385.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Sedan 2012 99.98% Rolls-Royce Ghost Sedan 2012 0.01% Bentley Mulsanne Sedan 2011 0.01% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Bentley Arnage Sedan 2009 0.0% +427 /scratch/Teaching/cars/car_ims/009864.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 99.94% Chevrolet Traverse SUV 2012 0.06% Cadillac SRX SUV 2012 0.01% Hyundai Veracruz SUV 2012 0.0% Ford F-150 Regular Cab 2007 0.0% +428 /scratch/Teaching/cars/car_ims/005652.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chevrolet Silverado 1500 Classic Extended Cab 2007 99.18% Chevrolet Silverado 1500 Extended Cab 2012 0.2% Ford Ranger SuperCab 2011 0.14% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.13% Chevrolet Silverado 2500HD Regular Cab 2012 0.1% +429 /scratch/Teaching/cars/car_ims/009984.jpg GMC Canyon Extended Cab 2012 GMC Canyon Extended Cab 2012 90.77% HUMMER H3T Crew Cab 2010 2.71% Dodge Ram Pickup 3500 Quad Cab 2009 2.18% Dodge Dakota Club Cab 2007 1.22% Dodge Dakota Crew Cab 2010 0.82% +430 /scratch/Teaching/cars/car_ims/014469.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Ghost Sedan 2012 78.8% BMW M6 Convertible 2010 14.41% BMW 6 Series Convertible 2007 4.02% BMW ActiveHybrid 5 Sedan 2012 1.43% Fisker Karma Sedan 2012 0.58% +431 /scratch/Teaching/cars/car_ims/005406.jpg Chevrolet Malibu Hybrid Sedan 2010 Toyota Camry Sedan 2012 55.67% Mitsubishi Lancer Sedan 2012 17.91% Acura TSX Sedan 2012 10.16% Toyota Corolla Sedan 2012 4.84% Honda Accord Coupe 2012 2.91% +432 /scratch/Teaching/cars/car_ims/003969.jpg Buick Enclave SUV 2012 Buick Enclave SUV 2012 100.0% BMW X5 SUV 2007 0.0% GMC Acadia SUV 2012 0.0% Chevrolet Traverse SUV 2012 0.0% BMW X6 SUV 2012 0.0% +433 /scratch/Teaching/cars/car_ims/012313.jpg Lamborghini Reventon Coupe 2008 Lamborghini Reventon Coupe 2008 99.98% Lamborghini Aventador Coupe 2012 0.01% Bugatti Veyron 16.4 Coupe 2009 0.0% Audi R8 Coupe 2012 0.0% Fisker Karma Sedan 2012 0.0% +434 /scratch/Teaching/cars/car_ims/014768.jpg Spyker C8 Coupe 2009 Bugatti Veyron 16.4 Coupe 2009 40.36% Spyker C8 Coupe 2009 27.14% Bugatti Veyron 16.4 Convertible 2009 24.6% Spyker C8 Convertible 2009 5.57% Ford GT Coupe 2006 1.92% +435 /scratch/Teaching/cars/car_ims/002802.jpg BMW M5 Sedan 2010 Audi S5 Coupe 2012 47.7% Audi S4 Sedan 2012 27.65% Audi S6 Sedan 2011 9.72% Audi S5 Convertible 2012 6.02% Audi S4 Sedan 2007 4.11% +436 /scratch/Teaching/cars/car_ims/013139.jpg McLaren MP4-12C Coupe 2012 Lamborghini Aventador Coupe 2012 52.1% McLaren MP4-12C Coupe 2012 42.57% Aston Martin V8 Vantage Coupe 2012 3.64% Aston Martin V8 Vantage Convertible 2012 0.48% Spyker C8 Coupe 2009 0.27% +437 /scratch/Teaching/cars/car_ims/004653.jpg Chevrolet Traverse SUV 2012 Hyundai Veracruz SUV 2012 46.81% Chevrolet Traverse SUV 2012 45.52% Hyundai Tucson SUV 2012 5.17% Buick Enclave SUV 2012 0.85% GMC Acadia SUV 2012 0.51% +438 /scratch/Teaching/cars/car_ims/004806.jpg Chevrolet Camaro Convertible 2012 Chevrolet Camaro Convertible 2012 63.35% Honda Accord Coupe 2012 29.0% Chevrolet Cobalt SS 2010 1.89% Chrysler Crossfire Convertible 2008 1.61% Dodge Charger Sedan 2012 1.5% +439 /scratch/Teaching/cars/car_ims/007292.jpg Dodge Journey SUV 2012 Honda Accord Coupe 2012 46.73% Mercedes-Benz C-Class Sedan 2012 46.33% Hyundai Genesis Sedan 2012 3.0% Dodge Journey SUV 2012 2.79% Nissan 240SX Coupe 1998 0.52% +440 /scratch/Teaching/cars/car_ims/003526.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 79.84% Bentley Mulsanne Sedan 2011 20.15% Bentley Continental GT Coupe 2007 0.0% Bentley Arnage Sedan 2009 0.0% Bentley Continental GT Coupe 2012 0.0% +441 /scratch/Teaching/cars/car_ims/012011.jpg Jeep Wrangler SUV 2012 McLaren MP4-12C Coupe 2012 29.36% Spyker C8 Coupe 2009 19.84% AM General Hummer SUV 2000 8.96% HUMMER H2 SUT Crew Cab 2009 8.82% Ford GT Coupe 2006 7.13% +442 /scratch/Teaching/cars/car_ims/012291.jpg Lamborghini Reventon Coupe 2008 Lamborghini Reventon Coupe 2008 99.06% Lamborghini Aventador Coupe 2012 0.94% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.0% Aston Martin V8 Vantage Coupe 2012 0.0% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.0% +443 /scratch/Teaching/cars/car_ims/013933.jpg Nissan Juke Hatchback 2012 Nissan Juke Hatchback 2012 53.22% Hyundai Tucson SUV 2012 21.42% Nissan Leaf Hatchback 2012 19.17% smart fortwo Convertible 2012 2.87% Ford Fiesta Sedan 2012 1.44% +444 /scratch/Teaching/cars/car_ims/007158.jpg Dodge Sprinter Cargo Van 2009 Mercedes-Benz Sprinter Van 2012 60.26% Dodge Sprinter Cargo Van 2009 35.5% Honda Odyssey Minivan 2007 2.26% Chrysler Town and Country Minivan 2012 0.98% Dodge Caravan Minivan 1997 0.58% +445 /scratch/Teaching/cars/car_ims/010652.jpg Honda Accord Sedan 2012 Honda Accord Sedan 2012 99.94% Hyundai Genesis Sedan 2012 0.04% Honda Odyssey Minivan 2007 0.01% Honda Odyssey Minivan 2012 0.0% Acura RL Sedan 2012 0.0% +446 /scratch/Teaching/cars/car_ims/000416.jpg Acura Integra Type R 2001 Acura Integra Type R 2001 99.84% Lamborghini Diablo Coupe 2001 0.11% Geo Metro Convertible 1993 0.03% Chevrolet Corvette Convertible 2012 0.02% Chevrolet Cobalt SS 2010 0.0% +447 /scratch/Teaching/cars/car_ims/014945.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 75.54% Cadillac CTS-V Sedan 2012 16.3% Chevrolet Sonic Sedan 2012 2.4% Nissan Juke Hatchback 2012 1.95% Buick Verano Sedan 2012 1.16% +448 /scratch/Teaching/cars/car_ims/005530.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 52.73% Chevrolet Silverado 2500HD Regular Cab 2012 39.32% Chevrolet Silverado 1500 Extended Cab 2012 3.28% GMC Canyon Extended Cab 2012 1.3% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 1.08% +449 /scratch/Teaching/cars/car_ims/001845.jpg Audi S4 Sedan 2012 Audi S4 Sedan 2012 85.11% Mitsubishi Lancer Sedan 2012 4.23% Audi TTS Coupe 2012 1.98% Audi A5 Coupe 2012 1.9% Audi S5 Coupe 2012 1.79% +450 /scratch/Teaching/cars/car_ims/004226.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 98.18% GMC Yukon Hybrid SUV 2012 1.41% Chevrolet Avalanche Crew Cab 2012 0.24% Chevrolet Tahoe Hybrid SUV 2012 0.16% Land Rover Range Rover SUV 2012 0.01% +451 /scratch/Teaching/cars/car_ims/002516.jpg BMW 6 Series Convertible 2007 BMW 6 Series Convertible 2007 71.47% BMW M6 Convertible 2010 20.12% Jaguar XK XKR 2012 4.26% BMW Z4 Convertible 2012 3.99% Aston Martin V8 Vantage Convertible 2012 0.05% +452 /scratch/Teaching/cars/car_ims/011648.jpg Infiniti QX56 SUV 2011 Honda Accord Sedan 2012 63.11% Acura RL Sedan 2012 12.15% Honda Odyssey Minivan 2012 9.52% Buick Verano Sedan 2012 8.06% Honda Odyssey Minivan 2007 2.14% +453 /scratch/Teaching/cars/car_ims/005093.jpg Chevrolet Sonic Sedan 2012 Chevrolet Sonic Sedan 2012 75.75% Toyota Corolla Sedan 2012 13.07% Suzuki SX4 Hatchback 2012 5.83% Volvo C30 Hatchback 2012 4.29% Mitsubishi Lancer Sedan 2012 0.31% +454 /scratch/Teaching/cars/car_ims/008321.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 92.51% Ferrari 458 Italia Convertible 2012 5.61% Chevrolet Corvette Convertible 2012 1.27% Ferrari 458 Italia Coupe 2012 0.59% Ferrari FF Coupe 2012 0.02% +455 /scratch/Teaching/cars/car_ims/014458.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Ghost Sedan 2012 99.98% Rolls-Royce Phantom Sedan 2012 0.02% Chrysler 300 SRT-8 2010 0.0% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Dodge Challenger SRT8 2011 0.0% +456 /scratch/Teaching/cars/car_ims/011027.jpg Hyundai Sonata Hybrid Sedan 2012 McLaren MP4-12C Coupe 2012 34.78% Aston Martin Virage Coupe 2012 22.3% Spyker C8 Coupe 2009 7.62% Aston Martin V8 Vantage Coupe 2012 5.81% Lamborghini Diablo Coupe 2001 4.99% +457 /scratch/Teaching/cars/car_ims/010038.jpg GMC Savana Van 2012 GMC Savana Van 2012 58.78% Chevrolet Express Cargo Van 2007 25.94% Chevrolet Express Van 2007 14.81% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.23% Volkswagen Golf Hatchback 1991 0.12% +458 /scratch/Teaching/cars/car_ims/009238.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 78.3% Ford F-450 Super Duty Crew Cab 2012 19.95% Ford Expedition EL SUV 2009 0.39% Toyota Sequoia SUV 2012 0.34% Ford E-Series Wagon Van 2012 0.27% +459 /scratch/Teaching/cars/car_ims/002093.jpg BMW ActiveHybrid 5 Sedan 2012 Dodge Challenger SRT8 2011 28.12% Fisker Karma Sedan 2012 9.95% BMW M6 Convertible 2010 9.54% Aston Martin V8 Vantage Coupe 2012 7.16% Jaguar XK XKR 2012 5.35% +460 /scratch/Teaching/cars/car_ims/007336.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Club Cab 2007 78.82% GMC Canyon Extended Cab 2012 9.79% Dodge Dakota Crew Cab 2010 9.55% Chevrolet Silverado 1500 Extended Cab 2012 1.41% Chevrolet Avalanche Crew Cab 2012 0.12% +461 /scratch/Teaching/cars/car_ims/011947.jpg Jeep Wrangler SUV 2012 Jeep Wrangler SUV 2012 99.65% Jeep Patriot SUV 2012 0.35% AM General Hummer SUV 2000 0.0% GMC Canyon Extended Cab 2012 0.0% HUMMER H3T Crew Cab 2010 0.0% +462 /scratch/Teaching/cars/car_ims/003886.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 80.42% Isuzu Ascender SUV 2008 8.84% Ford Freestar Minivan 2007 4.1% Ford Expedition EL SUV 2009 1.67% Dodge Durango SUV 2007 0.69% +463 /scratch/Teaching/cars/car_ims/013212.jpg Mercedes-Benz 300-Class Convertible 1993 Lincoln Town Car Sedan 2011 75.03% Mercedes-Benz 300-Class Convertible 1993 14.55% Audi 100 Wagon 1994 7.13% Nissan 240SX Coupe 1998 2.97% Audi 100 Sedan 1994 0.09% +464 /scratch/Teaching/cars/car_ims/006447.jpg Chrysler Crossfire Convertible 2008 Hyundai Genesis Sedan 2012 14.97% Honda Accord Coupe 2012 12.54% Acura TL Type-S 2008 8.69% Honda Accord Sedan 2012 7.77% Audi A5 Coupe 2012 7.34% +465 /scratch/Teaching/cars/car_ims/014069.jpg Nissan 240SX Coupe 1998 Nissan 240SX Coupe 1998 44.7% BMW 3 Series Sedan 2012 28.56% Audi R8 Coupe 2012 9.0% Eagle Talon Hatchback 1998 7.68% BMW M3 Coupe 2012 4.5% +466 /scratch/Teaching/cars/car_ims/001355.jpg Audi 100 Sedan 1994 Audi 100 Sedan 1994 64.5% Audi 100 Wagon 1994 34.97% Audi V8 Sedan 1994 0.28% Volkswagen Golf Hatchback 1991 0.25% Volvo 240 Sedan 1993 0.0% +467 /scratch/Teaching/cars/car_ims/012077.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 83.71% Volvo 240 Sedan 1993 5.24% Volkswagen Golf Hatchback 1991 3.6% Buick Rainier SUV 2007 2.91% BMW X5 SUV 2007 2.41% +468 /scratch/Teaching/cars/car_ims/005632.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chevrolet TrailBlazer SS 2009 33.46% Ford Expedition EL SUV 2009 23.17% Land Rover Range Rover SUV 2012 14.4% Ford Edge SUV 2012 5.8% Land Rover LR2 SUV 2012 4.26% +469 /scratch/Teaching/cars/car_ims/000453.jpg Acura Integra Type R 2001 Acura Integra Type R 2001 52.29% BMW M5 Sedan 2010 17.06% BMW M3 Coupe 2012 12.28% Chevrolet Corvette ZR1 2012 7.26% Porsche Panamera Sedan 2012 2.41% +470 /scratch/Teaching/cars/car_ims/015438.jpg Toyota Corolla Sedan 2012 Hyundai Accent Sedan 2012 28.91% Chevrolet Sonic Sedan 2012 20.71% Ford Edge SUV 2012 11.51% Hyundai Sonata Hybrid Sedan 2012 11.49% Ford Fiesta Sedan 2012 8.33% +471 /scratch/Teaching/cars/car_ims/011934.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 99.29% Jeep Wrangler SUV 2012 0.63% Jeep Liberty SUV 2012 0.08% Jeep Compass SUV 2012 0.0% Nissan NV Passenger Van 2012 0.0% +472 /scratch/Teaching/cars/car_ims/007109.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 98.6% Dodge Dakota Club Cab 2007 0.78% Dodge Ram Pickup 3500 Crew Cab 2010 0.34% Dodge Dakota Crew Cab 2010 0.25% GMC Canyon Extended Cab 2012 0.03% +473 /scratch/Teaching/cars/car_ims/001523.jpg Audi TT Hatchback 2011 Audi S4 Sedan 2012 58.97% Audi TT Hatchback 2011 17.5% Audi TTS Coupe 2012 13.62% Audi S5 Convertible 2012 3.85% Audi S5 Coupe 2012 2.49% +474 /scratch/Teaching/cars/car_ims/012994.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 50.53% Jeep Grand Cherokee SUV 2012 27.3% GMC Terrain SUV 2012 8.49% GMC Acadia SUV 2012 2.6% Chevrolet Traverse SUV 2012 2.55% +475 /scratch/Teaching/cars/car_ims/005420.jpg Chevrolet Malibu Hybrid Sedan 2010 Chevrolet Malibu Hybrid Sedan 2010 43.18% Acura RL Sedan 2012 39.89% Buick Verano Sedan 2012 8.91% Honda Accord Sedan 2012 6.26% Chevrolet Cobalt SS 2010 0.34% +476 /scratch/Teaching/cars/car_ims/003607.jpg Bugatti Veyron 16.4 Convertible 2009 Bugatti Veyron 16.4 Convertible 2009 39.81% Audi TT Hatchback 2011 24.18% Buick Regal GS 2012 12.81% Audi TT RS Coupe 2012 9.22% Hyundai Veloster Hatchback 2012 3.44% +477 /scratch/Teaching/cars/car_ims/014653.jpg Scion xD Hatchback 2012 Scion xD Hatchback 2012 99.0% Suzuki SX4 Hatchback 2012 0.86% Suzuki SX4 Sedan 2012 0.09% Chevrolet Sonic Sedan 2012 0.01% Nissan Juke Hatchback 2012 0.01% +478 /scratch/Teaching/cars/car_ims/002912.jpg BMW M6 Convertible 2010 BMW 6 Series Convertible 2007 19.1% Jaguar XK XKR 2012 18.37% Mitsubishi Lancer Sedan 2012 12.75% Chevrolet Cobalt SS 2010 8.9% Chevrolet Monte Carlo Coupe 2007 8.1% +479 /scratch/Teaching/cars/car_ims/011037.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 86.28% Acura TL Sedan 2012 6.67% Chevrolet Malibu Hybrid Sedan 2010 4.13% Buick Verano Sedan 2012 0.68% Honda Odyssey Minivan 2012 0.51% +480 /scratch/Teaching/cars/car_ims/013104.jpg McLaren MP4-12C Coupe 2012 Aston Martin V8 Vantage Coupe 2012 33.69% Fisker Karma Sedan 2012 30.94% Jaguar XK XKR 2012 11.43% Aston Martin Virage Convertible 2012 6.38% Porsche Panamera Sedan 2012 4.93% +481 /scratch/Teaching/cars/car_ims/003769.jpg Buick Regal GS 2012 Buick Regal GS 2012 87.64% Mitsubishi Lancer Sedan 2012 10.81% Buick Verano Sedan 2012 0.43% Chevrolet Sonic Sedan 2012 0.35% Suzuki Kizashi Sedan 2012 0.11% +482 /scratch/Teaching/cars/car_ims/006031.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 48.08% Chevrolet Silverado 1500 Extended Cab 2012 18.19% Chevrolet Silverado 2500HD Regular Cab 2012 12.99% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 12.4% GMC Canyon Extended Cab 2012 7.88% +483 /scratch/Teaching/cars/car_ims/002655.jpg BMW X6 SUV 2012 Buick Verano Sedan 2012 56.41% Mitsubishi Lancer Sedan 2012 9.94% Acura RL Sedan 2012 8.61% Buick Regal GS 2012 5.87% Chevrolet Malibu Hybrid Sedan 2010 5.79% +484 /scratch/Teaching/cars/car_ims/014170.jpg Plymouth Neon Coupe 1999 Ford Focus Sedan 2007 62.21% Plymouth Neon Coupe 1999 37.38% Chevrolet Impala Sedan 2007 0.18% Daewoo Nubira Wagon 2002 0.12% Nissan 240SX Coupe 1998 0.06% +485 /scratch/Teaching/cars/car_ims/006724.jpg Dodge Caliber Wagon 2012 Ram C/V Cargo Van Minivan 2012 90.8% Ford Freestar Minivan 2007 4.9% Mazda Tribute SUV 2011 3.0% Chrysler Town and Country Minivan 2012 0.62% Dodge Durango SUV 2007 0.27% +486 /scratch/Teaching/cars/car_ims/002363.jpg BMW 3 Series Wagon 2012 BMW 3 Series Sedan 2012 99.99% BMW 3 Series Wagon 2012 0.01% BMW M3 Coupe 2012 0.0% Audi V8 Sedan 1994 0.0% BMW M5 Sedan 2010 0.0% +487 /scratch/Teaching/cars/car_ims/000128.jpg Acura RL Sedan 2012 Acura RL Sedan 2012 97.19% Acura TSX Sedan 2012 2.18% Hyundai Elantra Sedan 2007 0.2% Acura TL Type-S 2008 0.15% Honda Accord Sedan 2012 0.09% +488 /scratch/Teaching/cars/car_ims/000984.jpg Audi A5 Coupe 2012 Audi TTS Coupe 2012 58.21% Audi A5 Coupe 2012 22.04% Audi S4 Sedan 2012 11.69% Audi S5 Coupe 2012 3.83% Mitsubishi Lancer Sedan 2012 2.36% +489 /scratch/Teaching/cars/car_ims/007998.jpg Eagle Talon Hatchback 1998 Plymouth Neon Coupe 1999 27.0% Chevrolet Impala Sedan 2007 23.71% Chevrolet Monte Carlo Coupe 2007 20.24% Lincoln Town Car Sedan 2011 9.79% Chevrolet Corvette Ron Fellows Edition Z06 2007 5.79% +490 /scratch/Teaching/cars/car_ims/013245.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 99.68% Hyundai Genesis Sedan 2012 0.32% Mercedes-Benz S-Class Sedan 2012 0.0% Mercedes-Benz SL-Class Coupe 2009 0.0% Mercedes-Benz E-Class Sedan 2012 0.0% +491 /scratch/Teaching/cars/car_ims/009214.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 99.97% Ford F-150 Regular Cab 2007 0.03% Cadillac Escalade EXT Crew Cab 2007 0.0% Ford F-450 Super Duty Crew Cab 2012 0.0% GMC Yukon Hybrid SUV 2012 0.0% +492 /scratch/Teaching/cars/car_ims/013574.jpg Mercedes-Benz S-Class Sedan 2012 Mercedes-Benz S-Class Sedan 2012 99.22% Mercedes-Benz E-Class Sedan 2012 0.78% Mercedes-Benz C-Class Sedan 2012 0.0% Hyundai Genesis Sedan 2012 0.0% Chrysler Crossfire Convertible 2008 0.0% +493 /scratch/Teaching/cars/car_ims/015307.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 98.59% Ford Expedition EL SUV 2009 1.16% Land Rover LR2 SUV 2012 0.18% Hyundai Santa Fe SUV 2012 0.07% Chrysler Aspen SUV 2009 0.0% +494 /scratch/Teaching/cars/car_ims/015848.jpg Volvo C30 Hatchback 2012 Volvo C30 Hatchback 2012 95.79% Audi S4 Sedan 2012 2.61% Mitsubishi Lancer Sedan 2012 1.54% Chevrolet Sonic Sedan 2012 0.02% Suzuki Kizashi Sedan 2012 0.02% +495 /scratch/Teaching/cars/car_ims/010136.jpg Geo Metro Convertible 1993 Audi 100 Wagon 1994 26.77% Volkswagen Golf Hatchback 1991 19.57% Geo Metro Convertible 1993 17.87% Daewoo Nubira Wagon 2002 10.02% Dodge Sprinter Cargo Van 2009 8.54% +496 /scratch/Teaching/cars/car_ims/003459.jpg Bentley Continental GT Coupe 2007 Chevrolet Camaro Convertible 2012 20.04% Rolls-Royce Phantom Drophead Coupe Convertible 2012 8.06% BMW M6 Convertible 2010 6.84% Chrysler Crossfire Convertible 2008 5.37% Mercedes-Benz 300-Class Convertible 1993 4.83% +497 /scratch/Teaching/cars/car_ims/015818.jpg Volkswagen Beetle Hatchback 2012 Dodge Journey SUV 2012 59.37% Chevrolet Sonic Sedan 2012 26.55% Ford Edge SUV 2012 3.34% Chrysler PT Cruiser Convertible 2008 1.89% Volvo C30 Hatchback 2012 1.65% +498 /scratch/Teaching/cars/car_ims/007766.jpg Dodge Durango SUV 2007 Dodge Dakota Club Cab 2007 66.78% Dodge Durango SUV 2007 13.34% Dodge Dakota Crew Cab 2010 11.42% Dodge Ram Pickup 3500 Quad Cab 2009 8.1% Dodge Ram Pickup 3500 Crew Cab 2010 0.34% +499 /scratch/Teaching/cars/car_ims/003391.jpg Bentley Continental GT Coupe 2012 Bentley Continental GT Coupe 2012 24.82% Bentley Continental GT Coupe 2007 20.96% Fisker Karma Sedan 2012 17.07% Cadillac CTS-V Sedan 2012 13.14% Bentley Mulsanne Sedan 2011 10.0% +500 /scratch/Teaching/cars/car_ims/007805.jpg Dodge Charger Sedan 2012 Mitsubishi Lancer Sedan 2012 30.98% Dodge Charger Sedan 2012 16.9% Chevrolet Sonic Sedan 2012 9.41% Dodge Charger SRT-8 2009 3.85% Toyota Camry Sedan 2012 3.71% +501 /scratch/Teaching/cars/car_ims/002965.jpg BMW X3 SUV 2012 BMW X3 SUV 2012 99.25% BMW X5 SUV 2007 0.65% BMW X6 SUV 2012 0.06% Cadillac SRX SUV 2012 0.02% Jeep Compass SUV 2012 0.01% +502 /scratch/Teaching/cars/car_ims/007262.jpg Dodge Journey SUV 2012 Dodge Journey SUV 2012 99.98% Dodge Durango SUV 2012 0.01% Hyundai Santa Fe SUV 2012 0.0% Volvo C30 Hatchback 2012 0.0% Ford Edge SUV 2012 0.0% +503 /scratch/Teaching/cars/car_ims/005585.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 1500 Classic Extended Cab 2007 34.74% Chevrolet Silverado 1500 Extended Cab 2012 15.52% GMC Canyon Extended Cab 2012 14.49% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 11.95% Chevrolet Silverado 2500HD Regular Cab 2012 9.42% +504 /scratch/Teaching/cars/car_ims/015036.jpg Suzuki SX4 Hatchback 2012 Chevrolet Traverse SUV 2012 55.43% GMC Acadia SUV 2012 20.65% Buick Enclave SUV 2012 5.7% Scion xD Hatchback 2012 4.62% Hyundai Veracruz SUV 2012 4.31% +505 /scratch/Teaching/cars/car_ims/000892.jpg Audi RS 4 Convertible 2008 BMW M6 Convertible 2010 62.06% BMW 6 Series Convertible 2007 19.62% Chrysler Crossfire Convertible 2008 4.52% Acura TL Type-S 2008 3.15% Audi RS 4 Convertible 2008 1.15% +506 /scratch/Teaching/cars/car_ims/002195.jpg BMW 1 Series Coupe 2012 BMW M3 Coupe 2012 98.23% BMW 1 Series Coupe 2012 1.75% BMW M5 Sedan 2010 0.02% BMW Z4 Convertible 2012 0.01% Mitsubishi Lancer Sedan 2012 0.0% +507 /scratch/Teaching/cars/car_ims/000546.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 32.37% Buick Verano Sedan 2012 28.41% Cadillac SRX SUV 2012 17.7% Suzuki Kizashi Sedan 2012 4.36% Chevrolet Sonic Sedan 2012 3.86% +508 /scratch/Teaching/cars/car_ims/001117.jpg Audi TTS Coupe 2012 Audi TT Hatchback 2011 73.74% Audi TTS Coupe 2012 23.36% Audi TT RS Coupe 2012 1.75% Audi S4 Sedan 2012 0.66% Audi S5 Convertible 2012 0.33% +509 /scratch/Teaching/cars/car_ims/014807.jpg Spyker C8 Coupe 2009 Spyker C8 Coupe 2009 48.47% Audi TT RS Coupe 2012 10.41% Ferrari FF Coupe 2012 6.17% Ferrari California Convertible 2012 5.38% Aston Martin V8 Vantage Convertible 2012 5.32% +510 /scratch/Teaching/cars/car_ims/012191.jpg Jeep Grand Cherokee SUV 2012 GMC Acadia SUV 2012 81.69% Chevrolet Traverse SUV 2012 9.2% Jeep Grand Cherokee SUV 2012 5.42% Volvo XC90 SUV 2007 1.5% Buick Enclave SUV 2012 0.64% +511 /scratch/Teaching/cars/car_ims/007101.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Dakota Club Cab 2007 58.31% Ford F-150 Regular Cab 2007 22.33% Chevrolet Silverado 1500 Extended Cab 2012 5.81% Chevrolet Silverado 1500 Regular Cab 2012 5.73% GMC Canyon Extended Cab 2012 3.25% +512 /scratch/Teaching/cars/car_ims/011872.jpg Jeep Patriot SUV 2012 Jeep Liberty SUV 2012 80.32% Jeep Patriot SUV 2012 15.5% Jeep Grand Cherokee SUV 2012 3.4% Jeep Compass SUV 2012 0.69% GMC Acadia SUV 2012 0.07% +513 /scratch/Teaching/cars/car_ims/015234.jpg Tesla Model S Sedan 2012 Tesla Model S Sedan 2012 97.51% Fisker Karma Sedan 2012 2.45% Bentley Continental GT Coupe 2012 0.01% Acura TL Sedan 2012 0.01% Audi TTS Coupe 2012 0.01% +514 /scratch/Teaching/cars/car_ims/014883.jpg Suzuki Aerio Sedan 2007 Suzuki Aerio Sedan 2007 25.57% Toyota Corolla Sedan 2012 19.3% Suzuki SX4 Hatchback 2012 17.61% Suzuki SX4 Sedan 2012 9.79% Volkswagen Golf Hatchback 2012 9.21% +515 /scratch/Teaching/cars/car_ims/009194.jpg Ford GT Coupe 2006 Ford GT Coupe 2006 86.09% Spyker C8 Convertible 2009 9.31% Lamborghini Aventador Coupe 2012 2.11% Bugatti Veyron 16.4 Coupe 2009 1.43% Lamborghini Reventon Coupe 2008 0.48% +516 /scratch/Teaching/cars/car_ims/016080.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 46.5% Dodge Durango SUV 2007 19.19% Isuzu Ascender SUV 2008 15.43% Dodge Caliber Wagon 2012 5.95% Jeep Grand Cherokee SUV 2012 4.65% +517 /scratch/Teaching/cars/car_ims/008820.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 99.79% Lincoln Town Car Sedan 2011 0.17% Audi 100 Wagon 1994 0.03% Chrysler Town and Country Minivan 2012 0.0% Volvo XC90 SUV 2007 0.0% +518 /scratch/Teaching/cars/car_ims/008045.jpg Eagle Talon Hatchback 1998 Ferrari FF Coupe 2012 23.23% BMW M3 Coupe 2012 11.17% Audi TT RS Coupe 2012 10.8% Chevrolet Corvette ZR1 2012 9.25% Eagle Talon Hatchback 1998 8.94% +519 /scratch/Teaching/cars/car_ims/003819.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 62.97% Chevrolet HHR SS 2010 21.82% Volkswagen Golf Hatchback 1991 3.82% Jeep Liberty SUV 2012 3.17% Mazda Tribute SUV 2011 3.13% +520 /scratch/Teaching/cars/car_ims/001680.jpg Audi S5 Convertible 2012 Audi RS 4 Convertible 2008 29.15% Audi S5 Convertible 2012 19.3% Audi A5 Coupe 2012 13.68% Audi S5 Coupe 2012 12.06% Audi S6 Sedan 2011 10.14% +521 /scratch/Teaching/cars/car_ims/012267.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 93.07% Jeep Grand Cherokee SUV 2012 6.93% Jeep Patriot SUV 2012 0.0% GMC Terrain SUV 2012 0.0% Jeep Liberty SUV 2012 0.0% +522 /scratch/Teaching/cars/car_ims/008598.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 99.99% Dodge Ram Pickup 3500 Crew Cab 2010 0.01% Ford E-Series Wagon Van 2012 0.0% Ford F-150 Regular Cab 2012 0.0% Toyota Sequoia SUV 2012 0.0% +523 /scratch/Teaching/cars/car_ims/000229.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 97.01% Acura TSX Sedan 2012 1.74% Acura RL Sedan 2012 0.41% Toyota Camry Sedan 2012 0.39% Buick Regal GS 2012 0.12% +524 /scratch/Teaching/cars/car_ims/012148.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 97.34% Jeep Compass SUV 2012 2.66% BMW X6 SUV 2012 0.0% BMW X5 SUV 2007 0.0% GMC Terrain SUV 2012 0.0% +525 /scratch/Teaching/cars/car_ims/000342.jpg Acura TSX Sedan 2012 Hyundai Elantra Sedan 2007 41.52% Acura TSX Sedan 2012 36.39% Acura TL Sedan 2012 13.25% Chevrolet Impala Sedan 2007 3.72% Chevrolet Monte Carlo Coupe 2007 1.81% +526 /scratch/Teaching/cars/car_ims/001909.jpg Audi S4 Sedan 2007 Audi S6 Sedan 2011 78.26% Mercedes-Benz E-Class Sedan 2012 6.45% Audi S4 Sedan 2007 4.73% BMW X3 SUV 2012 3.74% Mercedes-Benz S-Class Sedan 2012 3.72% +527 /scratch/Teaching/cars/car_ims/012118.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 99.83% Jeep Compass SUV 2012 0.16% GMC Acadia SUV 2012 0.0% Mazda Tribute SUV 2011 0.0% Jeep Liberty SUV 2012 0.0% +528 /scratch/Teaching/cars/car_ims/007485.jpg Dodge Magnum Wagon 2008 Dodge Magnum Wagon 2008 80.04% Chrysler 300 SRT-8 2010 2.84% Volvo XC90 SUV 2007 2.62% Dodge Durango SUV 2012 2.41% Chrysler Town and Country Minivan 2012 2.03% +529 /scratch/Teaching/cars/car_ims/009914.jpg GMC Acadia SUV 2012 Ram C/V Cargo Van Minivan 2012 51.57% Chrysler Town and Country Minivan 2012 33.43% Mazda Tribute SUV 2011 3.05% GMC Acadia SUV 2012 2.46% Dodge Caliber Wagon 2012 2.19% +530 /scratch/Teaching/cars/car_ims/015487.jpg Toyota Corolla Sedan 2012 Toyota Corolla Sedan 2012 55.0% Hyundai Accent Sedan 2012 37.94% Toyota Camry Sedan 2012 4.95% Ford Fiesta Sedan 2012 2.02% Chevrolet Sonic Sedan 2012 0.07% +531 /scratch/Teaching/cars/car_ims/015946.jpg Volvo 240 Sedan 1993 Lincoln Town Car Sedan 2011 67.38% Volvo 240 Sedan 1993 32.19% Audi 100 Wagon 1994 0.38% Mercedes-Benz 300-Class Convertible 1993 0.02% Rolls-Royce Phantom Sedan 2012 0.0% +532 /scratch/Teaching/cars/car_ims/008766.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 100.0% Chrysler Town and Country Minivan 2012 0.0% Dodge Caravan Minivan 1997 0.0% Ram C/V Cargo Van Minivan 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% +533 /scratch/Teaching/cars/car_ims/012625.jpg Land Rover Range Rover SUV 2012 Land Rover LR2 SUV 2012 27.24% Dodge Durango SUV 2012 19.32% Land Rover Range Rover SUV 2012 18.88% Ford Edge SUV 2012 7.62% Chevrolet TrailBlazer SS 2009 6.64% +534 /scratch/Teaching/cars/car_ims/013688.jpg Mitsubishi Lancer Sedan 2012 Mitsubishi Lancer Sedan 2012 99.99% Toyota Camry Sedan 2012 0.01% Acura TSX Sedan 2012 0.0% Toyota Corolla Sedan 2012 0.0% Honda Accord Coupe 2012 0.0% +535 /scratch/Teaching/cars/car_ims/013807.jpg Nissan Leaf Hatchback 2012 Nissan Leaf Hatchback 2012 86.65% Volkswagen Beetle Hatchback 2012 12.26% Suzuki SX4 Sedan 2012 0.5% Nissan Juke Hatchback 2012 0.18% Suzuki Kizashi Sedan 2012 0.18% +536 /scratch/Teaching/cars/car_ims/013924.jpg Nissan Juke Hatchback 2012 Nissan Juke Hatchback 2012 70.19% Ford Edge SUV 2012 18.4% Hyundai Veracruz SUV 2012 4.87% Hyundai Tucson SUV 2012 1.35% Land Rover LR2 SUV 2012 1.29% +537 /scratch/Teaching/cars/car_ims/008198.jpg Ferrari FF Coupe 2012 Ferrari FF Coupe 2012 34.34% Aston Martin V8 Vantage Coupe 2012 32.13% Ferrari California Convertible 2012 10.56% Aston Martin V8 Vantage Convertible 2012 9.2% Jaguar XK XKR 2012 4.48% +538 /scratch/Teaching/cars/car_ims/006493.jpg Chrysler Crossfire Convertible 2008 Chevrolet Camaro Convertible 2012 33.62% Ford Mustang Convertible 2007 11.56% Chevrolet Corvette Convertible 2012 9.98% Chrysler Crossfire Convertible 2008 8.9% Ford GT Coupe 2006 4.59% +539 /scratch/Teaching/cars/car_ims/003322.jpg Bentley Mulsanne Sedan 2011 Rolls-Royce Phantom Sedan 2012 61.65% Rolls-Royce Ghost Sedan 2012 16.66% Chrysler 300 SRT-8 2010 12.41% Volvo 240 Sedan 1993 6.36% Rolls-Royce Phantom Drophead Coupe Convertible 2012 1.16% +540 /scratch/Teaching/cars/car_ims/015298.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.92% Land Rover Range Rover SUV 2012 0.05% Ford Expedition EL SUV 2009 0.01% Land Rover LR2 SUV 2012 0.01% Infiniti QX56 SUV 2011 0.01% +541 /scratch/Teaching/cars/car_ims/004771.jpg Chevrolet Camaro Convertible 2012 Chevrolet Camaro Convertible 2012 42.25% Hyundai Veloster Hatchback 2012 20.52% Volvo C30 Hatchback 2012 13.44% Honda Accord Coupe 2012 10.13% Dodge Charger Sedan 2012 2.82% +542 /scratch/Teaching/cars/car_ims/011062.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 99.93% Hyundai Accent Sedan 2012 0.04% Hyundai Sonata Sedan 2012 0.01% Ford Edge SUV 2012 0.01% Buick Regal GS 2012 0.0% +543 /scratch/Teaching/cars/car_ims/012742.jpg Land Rover LR2 SUV 2012 Land Rover LR2 SUV 2012 86.66% Toyota 4Runner SUV 2012 8.31% Ford Edge SUV 2012 2.27% Hyundai Veracruz SUV 2012 1.16% Chevrolet Avalanche Crew Cab 2012 0.51% +544 /scratch/Teaching/cars/car_ims/015518.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 65.93% GMC Terrain SUV 2012 33.64% Land Rover LR2 SUV 2012 0.35% Ford Edge SUV 2012 0.07% Chevrolet Avalanche Crew Cab 2012 0.01% +545 /scratch/Teaching/cars/car_ims/013472.jpg Mercedes-Benz E-Class Sedan 2012 Bentley Arnage Sedan 2009 27.53% Bentley Mulsanne Sedan 2011 22.56% Rolls-Royce Phantom Sedan 2012 17.2% Chrysler 300 SRT-8 2010 15.17% Fisker Karma Sedan 2012 4.03% +546 /scratch/Teaching/cars/car_ims/003839.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 45.24% Volvo XC90 SUV 2007 21.06% Isuzu Ascender SUV 2008 19.34% Dodge Durango SUV 2007 8.9% Jeep Liberty SUV 2012 1.6% +547 /scratch/Teaching/cars/car_ims/007108.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 51.77% Dodge Ram Pickup 3500 Crew Cab 2010 42.98% Dodge Dakota Club Cab 2007 3.85% Dodge Dakota Crew Cab 2010 1.26% Dodge Durango SUV 2007 0.1% +548 /scratch/Teaching/cars/car_ims/007273.jpg Dodge Journey SUV 2012 Ford Edge SUV 2012 81.32% Land Rover LR2 SUV 2012 11.71% Infiniti QX56 SUV 2011 4.93% Chevrolet Sonic Sedan 2012 0.73% Honda Odyssey Minivan 2012 0.51% +549 /scratch/Teaching/cars/car_ims/004666.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 79.34% Hyundai Veracruz SUV 2012 9.95% GMC Acadia SUV 2012 7.05% Buick Enclave SUV 2012 3.08% Hyundai Santa Fe SUV 2012 0.27% +550 /scratch/Teaching/cars/car_ims/010722.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 99.54% Mitsubishi Lancer Sedan 2012 0.29% Chevrolet Sonic Sedan 2012 0.15% Spyker C8 Coupe 2009 0.01% Buick Regal GS 2012 0.01% +551 /scratch/Teaching/cars/car_ims/000919.jpg Audi RS 4 Convertible 2008 Audi S4 Sedan 2007 31.14% Audi RS 4 Convertible 2008 21.38% Audi A5 Coupe 2012 16.95% Audi S5 Coupe 2012 15.64% Audi S5 Convertible 2012 5.63% +552 /scratch/Teaching/cars/car_ims/003108.jpg BMW Z4 Convertible 2012 BMW M3 Coupe 2012 62.9% BMW Z4 Convertible 2012 36.38% BMW 1 Series Coupe 2012 0.7% BMW M6 Convertible 2010 0.01% BMW 1 Series Convertible 2012 0.0% +553 /scratch/Teaching/cars/car_ims/006228.jpg Chrysler Sebring Convertible 2010 Chrysler Crossfire Convertible 2008 25.01% Chrysler Sebring Convertible 2010 22.06% BMW 1 Series Convertible 2012 16.66% BMW 6 Series Convertible 2007 6.98% Chevrolet Cobalt SS 2010 4.39% +554 /scratch/Teaching/cars/car_ims/015713.jpg Volkswagen Golf Hatchback 1991 Daewoo Nubira Wagon 2002 67.69% Audi 100 Wagon 1994 24.87% Ford Focus Sedan 2007 3.37% Volkswagen Golf Hatchback 1991 1.58% Suzuki Aerio Sedan 2007 1.33% +555 /scratch/Teaching/cars/car_ims/003552.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 99.99% Bentley Continental GT Coupe 2007 0.01% Bentley Mulsanne Sedan 2011 0.0% Maybach Landaulet Convertible 2012 0.0% Bentley Arnage Sedan 2009 0.0% +556 /scratch/Teaching/cars/car_ims/005717.jpg Chevrolet Express Van 2007 Chevrolet Express Cargo Van 2007 95.59% GMC Savana Van 2012 2.44% Chevrolet Express Van 2007 1.97% Dodge Sprinter Cargo Van 2009 0.0% Geo Metro Convertible 1993 0.0% +557 /scratch/Teaching/cars/car_ims/009534.jpg Ford E-Series Wagon Van 2012 Ford E-Series Wagon Van 2012 99.97% Nissan NV Passenger Van 2012 0.03% Ford F-450 Super Duty Crew Cab 2012 0.0% GMC Savana Van 2012 0.0% Chrysler Aspen SUV 2009 0.0% +558 /scratch/Teaching/cars/car_ims/003906.jpg Buick Verano Sedan 2012 Cadillac CTS-V Sedan 2012 64.19% Tesla Model S Sedan 2012 9.31% Buick Regal GS 2012 4.98% Fisker Karma Sedan 2012 3.49% Porsche Panamera Sedan 2012 2.66% +559 /scratch/Teaching/cars/car_ims/015003.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 94.18% Toyota Camry Sedan 2012 2.62% Chevrolet Sonic Sedan 2012 0.95% Volvo C30 Hatchback 2012 0.76% Toyota Corolla Sedan 2012 0.51% +560 /scratch/Teaching/cars/car_ims/002850.jpg BMW M5 Sedan 2010 Acura RL Sedan 2012 33.13% BMW M5 Sedan 2010 31.49% Acura TL Type-S 2008 17.45% BMW ActiveHybrid 5 Sedan 2012 5.27% BMW 3 Series Wagon 2012 4.67% +561 /scratch/Teaching/cars/car_ims/003100.jpg BMW Z4 Convertible 2012 BMW 6 Series Convertible 2007 64.46% BMW M6 Convertible 2010 15.36% BMW Z4 Convertible 2012 11.05% BMW ActiveHybrid 5 Sedan 2012 5.85% BMW M5 Sedan 2010 1.84% +562 /scratch/Teaching/cars/car_ims/014344.jpg Ram C/V Cargo Van Minivan 2012 Ford Freestar Minivan 2007 98.36% Dodge Caravan Minivan 1997 0.52% Chrysler Town and Country Minivan 2012 0.26% Ram C/V Cargo Van Minivan 2012 0.22% Isuzu Ascender SUV 2008 0.13% +563 /scratch/Teaching/cars/car_ims/004836.jpg Chevrolet HHR SS 2010 Chevrolet HHR SS 2010 53.0% Audi S6 Sedan 2011 12.82% BMW X5 SUV 2007 6.16% Suzuki Kizashi Sedan 2012 5.73% Ford Mustang Convertible 2007 4.72% +564 /scratch/Teaching/cars/car_ims/016180.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 86.6% Nissan Juke Hatchback 2012 7.24% Nissan Leaf Hatchback 2012 5.25% Scion xD Hatchback 2012 0.61% Ford Fiesta Sedan 2012 0.18% +565 /scratch/Teaching/cars/car_ims/009217.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 99.67% Ford F-150 Regular Cab 2007 0.33% GMC Canyon Extended Cab 2012 0.0% Ford F-450 Super Duty Crew Cab 2012 0.0% GMC Yukon Hybrid SUV 2012 0.0% +566 /scratch/Teaching/cars/car_ims/008334.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 98.58% Ferrari 458 Italia Coupe 2012 0.99% Ferrari FF Coupe 2012 0.31% Chevrolet Corvette Convertible 2012 0.05% Ferrari 458 Italia Convertible 2012 0.04% +567 /scratch/Teaching/cars/car_ims/015474.jpg Toyota Corolla Sedan 2012 Toyota Corolla Sedan 2012 79.38% Toyota Camry Sedan 2012 18.35% Hyundai Accent Sedan 2012 1.27% Mitsubishi Lancer Sedan 2012 0.47% Chevrolet Sonic Sedan 2012 0.41% +568 /scratch/Teaching/cars/car_ims/016106.jpg smart fortwo Convertible 2012 Nissan Leaf Hatchback 2012 31.07% FIAT 500 Convertible 2012 15.02% Nissan Juke Hatchback 2012 14.95% Suzuki SX4 Sedan 2012 12.56% Scion xD Hatchback 2012 10.89% +569 /scratch/Teaching/cars/car_ims/004993.jpg Chevrolet Tahoe Hybrid SUV 2012 Chevrolet Avalanche Crew Cab 2012 48.24% Chevrolet TrailBlazer SS 2009 27.4% Dodge Charger SRT-8 2009 4.69% Chevrolet Cobalt SS 2010 3.78% Chevrolet Silverado 1500 Regular Cab 2012 2.3% +570 /scratch/Teaching/cars/car_ims/000765.jpg Aston Martin Virage Convertible 2012 Aston Martin V8 Vantage Coupe 2012 58.49% Aston Martin V8 Vantage Convertible 2012 33.34% Fisker Karma Sedan 2012 3.03% BMW M6 Convertible 2010 2.2% Aston Martin Virage Convertible 2012 1.46% +571 /scratch/Teaching/cars/car_ims/009609.jpg Ford Fiesta Sedan 2012 Buick Verano Sedan 2012 95.14% Acura ZDX Hatchback 2012 1.41% Nissan Juke Hatchback 2012 0.86% Chevrolet Sonic Sedan 2012 0.77% Hyundai Veracruz SUV 2012 0.49% +572 /scratch/Teaching/cars/car_ims/006166.jpg Chrysler Aspen SUV 2009 Chrysler Aspen SUV 2009 84.43% Dodge Durango SUV 2007 8.36% Cadillac Escalade EXT Crew Cab 2007 6.2% Chrysler Town and Country Minivan 2012 0.67% Volvo XC90 SUV 2007 0.08% +573 /scratch/Teaching/cars/car_ims/009438.jpg Ford Focus Sedan 2007 Suzuki Aerio Sedan 2007 26.6% Mercedes-Benz C-Class Sedan 2012 20.7% Chrysler Sebring Convertible 2010 15.16% Ford Focus Sedan 2007 12.34% Honda Accord Sedan 2012 7.09% +574 /scratch/Teaching/cars/car_ims/008504.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 99.28% Aston Martin Virage Convertible 2012 0.39% Tesla Model S Sedan 2012 0.17% Porsche Panamera Sedan 2012 0.08% Aston Martin V8 Vantage Coupe 2012 0.06% +575 /scratch/Teaching/cars/car_ims/002457.jpg BMW 6 Series Convertible 2007 Chevrolet Camaro Convertible 2012 48.5% Honda Accord Coupe 2012 23.12% Dodge Charger SRT-8 2009 9.59% Chrysler Crossfire Convertible 2008 5.54% Nissan 240SX Coupe 1998 4.67% +576 /scratch/Teaching/cars/car_ims/013755.jpg Mitsubishi Lancer Sedan 2012 Hyundai Veloster Hatchback 2012 33.99% BMW M3 Coupe 2012 27.95% Mitsubishi Lancer Sedan 2012 15.55% Volvo C30 Hatchback 2012 9.99% BMW 1 Series Coupe 2012 5.4% +577 /scratch/Teaching/cars/car_ims/001706.jpg Audi S5 Convertible 2012 BMW 1 Series Coupe 2012 76.82% BMW 3 Series Sedan 2012 21.48% Audi S4 Sedan 2012 0.81% BMW 1 Series Convertible 2012 0.53% Volvo C30 Hatchback 2012 0.2% +578 /scratch/Teaching/cars/car_ims/000395.jpg Acura TSX Sedan 2012 Acura TSX Sedan 2012 74.0% Acura TL Sedan 2012 12.4% Toyota Camry Sedan 2012 5.85% Acura RL Sedan 2012 4.18% Toyota Corolla Sedan 2012 0.63% +579 /scratch/Teaching/cars/car_ims/014349.jpg Ram C/V Cargo Van Minivan 2012 Dodge Caliber Wagon 2012 86.62% Ram C/V Cargo Van Minivan 2012 9.45% Dodge Journey SUV 2012 2.2% Chevrolet Malibu Sedan 2007 0.99% Dodge Magnum Wagon 2008 0.23% +580 /scratch/Teaching/cars/car_ims/004627.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 94.21% Jaguar XK XKR 2012 2.16% Aston Martin V8 Vantage Coupe 2012 1.09% Chevrolet Corvette ZR1 2012 0.8% Aston Martin V8 Vantage Convertible 2012 0.51% +581 /scratch/Teaching/cars/car_ims/008247.jpg Ferrari FF Coupe 2012 BMW 3 Series Wagon 2012 32.71% BMW 3 Series Sedan 2012 31.23% BMW 1 Series Coupe 2012 23.61% BMW M5 Sedan 2010 11.22% BMW X5 SUV 2007 0.55% +582 /scratch/Teaching/cars/car_ims/013470.jpg Mercedes-Benz E-Class Sedan 2012 Mercedes-Benz E-Class Sedan 2012 85.5% Mercedes-Benz S-Class Sedan 2012 12.81% Audi S5 Coupe 2012 0.63% Audi S5 Convertible 2012 0.33% Audi S6 Sedan 2011 0.33% +583 /scratch/Teaching/cars/car_ims/015022.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 99.13% BMW X6 SUV 2012 0.67% Mazda Tribute SUV 2011 0.05% Chevrolet Sonic Sedan 2012 0.04% Dodge Caliber Wagon 2007 0.03% +584 /scratch/Teaching/cars/car_ims/008559.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 17.4% MINI Cooper Roadster Convertible 2012 15.41% Ford GT Coupe 2006 12.46% Spyker C8 Coupe 2009 10.03% Spyker C8 Convertible 2009 7.68% +585 /scratch/Teaching/cars/car_ims/003568.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 14.38% Chevrolet Monte Carlo Coupe 2007 11.52% Fisker Karma Sedan 2012 10.91% Dodge Challenger SRT8 2011 10.61% Rolls-Royce Phantom Drophead Coupe Convertible 2012 6.57% +586 /scratch/Teaching/cars/car_ims/002865.jpg BMW M5 Sedan 2010 Buick Verano Sedan 2012 43.67% Buick Regal GS 2012 28.19% Acura RL Sedan 2012 6.5% BMW M5 Sedan 2010 5.72% Suzuki Kizashi Sedan 2012 3.01% +587 /scratch/Teaching/cars/car_ims/005797.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Impala Sedan 2007 87.04% Chevrolet Malibu Sedan 2007 7.11% Chevrolet Monte Carlo Coupe 2007 4.24% Lincoln Town Car Sedan 2011 0.81% Chevrolet Malibu Hybrid Sedan 2010 0.79% +588 /scratch/Teaching/cars/car_ims/015378.jpg Toyota Camry Sedan 2012 Toyota Camry Sedan 2012 96.13% Toyota Corolla Sedan 2012 3.3% Mitsubishi Lancer Sedan 2012 0.55% Acura TSX Sedan 2012 0.03% Hyundai Accent Sedan 2012 0.0% +589 /scratch/Teaching/cars/car_ims/004432.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Convertible 2012 97.24% Chevrolet Corvette ZR1 2012 2.36% Ferrari California Convertible 2012 0.2% Jaguar XK XKR 2012 0.12% Aston Martin V8 Vantage Convertible 2012 0.07% +590 /scratch/Teaching/cars/car_ims/001529.jpg Audi TT Hatchback 2011 Audi TT RS Coupe 2012 56.37% Audi TT Hatchback 2011 42.82% Audi TTS Coupe 2012 0.79% Audi S4 Sedan 2012 0.01% Audi S5 Convertible 2012 0.0% +591 /scratch/Teaching/cars/car_ims/008896.jpg Ford Expedition EL SUV 2009 Volvo XC90 SUV 2007 32.42% Land Rover Range Rover SUV 2012 21.5% Dodge Durango SUV 2007 18.81% Jeep Liberty SUV 2012 17.35% Jeep Patriot SUV 2012 3.44% +592 /scratch/Teaching/cars/car_ims/014448.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Ghost Sedan 2012 59.04% Rolls-Royce Phantom Sedan 2012 40.05% Chrysler 300 SRT-8 2010 0.65% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.25% Bentley Mulsanne Sedan 2011 0.02% +593 /scratch/Teaching/cars/car_ims/004929.jpg Chevrolet Impala Sedan 2007 Hyundai Elantra Sedan 2007 49.33% Chevrolet Malibu Sedan 2007 25.03% Acura TSX Sedan 2012 7.72% Honda Odyssey Minivan 2012 6.04% Toyota Corolla Sedan 2012 3.73% +594 /scratch/Teaching/cars/car_ims/005217.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 98.25% Chevrolet Tahoe Hybrid SUV 2012 1.58% Chevrolet Silverado 1500 Regular Cab 2012 0.05% Chevrolet TrailBlazer SS 2009 0.05% Chevrolet Silverado 1500 Extended Cab 2012 0.04% +595 /scratch/Teaching/cars/car_ims/015873.jpg Volvo C30 Hatchback 2012 Chevrolet HHR SS 2010 71.12% Chevrolet Cobalt SS 2010 8.36% Volvo C30 Hatchback 2012 7.37% Mitsubishi Lancer Sedan 2012 4.26% Dodge Charger Sedan 2012 2.13% +596 /scratch/Teaching/cars/car_ims/000758.jpg Aston Martin Virage Convertible 2012 Aston Martin Virage Convertible 2012 15.85% Aston Martin V8 Vantage Coupe 2012 10.75% Chevrolet Monte Carlo Coupe 2007 8.85% Aston Martin V8 Vantage Convertible 2012 6.58% Fisker Karma Sedan 2012 6.17% +597 /scratch/Teaching/cars/car_ims/002913.jpg BMW M6 Convertible 2010 BMW 6 Series Convertible 2007 47.77% BMW M6 Convertible 2010 34.32% Fisker Karma Sedan 2012 8.17% Jaguar XK XKR 2012 4.34% BMW Z4 Convertible 2012 1.29% +598 /scratch/Teaching/cars/car_ims/012741.jpg Land Rover LR2 SUV 2012 Ram C/V Cargo Van Minivan 2012 36.1% GMC Yukon Hybrid SUV 2012 24.55% Mazda Tribute SUV 2011 17.8% Chevrolet Tahoe Hybrid SUV 2012 9.25% GMC Acadia SUV 2012 1.94% +599 /scratch/Teaching/cars/car_ims/002523.jpg BMW 6 Series Convertible 2007 Chevrolet Monte Carlo Coupe 2007 28.62% BMW 6 Series Convertible 2007 25.37% Nissan 240SX Coupe 1998 25.24% BMW M6 Convertible 2010 8.85% Eagle Talon Hatchback 1998 4.61% +600 /scratch/Teaching/cars/car_ims/007048.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 95.91% Dodge Ram Pickup 3500 Crew Cab 2010 4.09% Dodge Dakota Club Cab 2007 0.0% Dodge Durango SUV 2007 0.0% Dodge Dakota Crew Cab 2010 0.0% +601 /scratch/Teaching/cars/car_ims/006641.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 99.6% Ford Focus Sedan 2007 0.39% Bentley Continental Flying Spur Sedan 2007 0.01% Suzuki Aerio Sedan 2007 0.0% Audi 100 Wagon 1994 0.0% +602 /scratch/Teaching/cars/car_ims/015522.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 94.01% GMC Terrain SUV 2012 5.98% Land Rover LR2 SUV 2012 0.01% Ford Edge SUV 2012 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% +603 /scratch/Teaching/cars/car_ims/004214.jpg Cadillac SRX SUV 2012 Suzuki SX4 Sedan 2012 25.51% Hyundai Veracruz SUV 2012 23.02% Cadillac SRX SUV 2012 19.1% Chevrolet Traverse SUV 2012 8.46% GMC Acadia SUV 2012 4.48% +604 /scratch/Teaching/cars/car_ims/016144.jpg smart fortwo Convertible 2012 Nissan Juke Hatchback 2012 22.91% Chevrolet Sonic Sedan 2012 21.34% smart fortwo Convertible 2012 19.65% Ford Edge SUV 2012 7.46% Hyundai Tucson SUV 2012 5.06% +605 /scratch/Teaching/cars/car_ims/001971.jpg Audi S4 Sedan 2007 Audi S4 Sedan 2007 70.63% Audi A5 Coupe 2012 11.62% Audi S5 Coupe 2012 10.58% Audi S4 Sedan 2012 3.86% Audi S6 Sedan 2011 1.57% +606 /scratch/Teaching/cars/car_ims/009309.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 97.24% Ford F-150 Regular Cab 2012 2.29% Cadillac Escalade EXT Crew Cab 2007 0.32% GMC Yukon Hybrid SUV 2012 0.12% Ford Ranger SuperCab 2011 0.02% +607 /scratch/Teaching/cars/car_ims/000893.jpg Audi RS 4 Convertible 2008 Infiniti G Coupe IPL 2012 31.26% Audi S4 Sedan 2007 14.77% Audi S5 Coupe 2012 12.99% Audi S4 Sedan 2012 7.92% Mercedes-Benz E-Class Sedan 2012 7.87% +608 /scratch/Teaching/cars/car_ims/005124.jpg Chevrolet Sonic Sedan 2012 Chevrolet Sonic Sedan 2012 99.82% Mitsubishi Lancer Sedan 2012 0.14% Buick Verano Sedan 2012 0.03% Buick Regal GS 2012 0.01% Suzuki Kizashi Sedan 2012 0.0% +609 /scratch/Teaching/cars/car_ims/006393.jpg Chrysler 300 SRT-8 2010 Chevrolet Malibu Sedan 2007 6.19% Ram C/V Cargo Van Minivan 2012 5.88% Dodge Caliber Wagon 2012 5.71% Dodge Magnum Wagon 2008 4.94% Ford Freestar Minivan 2007 3.66% +610 /scratch/Teaching/cars/car_ims/000591.jpg Aston Martin V8 Vantage Convertible 2012 Jaguar XK XKR 2012 29.37% Aston Martin Virage Convertible 2012 15.02% Ferrari California Convertible 2012 6.42% Porsche Panamera Sedan 2012 5.41% Ferrari FF Coupe 2012 5.19% +611 /scratch/Teaching/cars/car_ims/010263.jpg HUMMER H3T Crew Cab 2010 HUMMER H3T Crew Cab 2010 97.09% Jeep Wrangler SUV 2012 1.39% GMC Canyon Extended Cab 2012 0.62% HUMMER H2 SUT Crew Cab 2009 0.62% Jeep Patriot SUV 2012 0.23% +612 /scratch/Teaching/cars/car_ims/006805.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2012 88.22% Dodge Caliber Wagon 2007 11.77% Dodge Journey SUV 2012 0.01% Dodge Dakota Crew Cab 2010 0.0% Dodge Durango SUV 2007 0.0% +613 /scratch/Teaching/cars/car_ims/013816.jpg Nissan Leaf Hatchback 2012 Nissan Leaf Hatchback 2012 75.07% Scion xD Hatchback 2012 17.79% Nissan Juke Hatchback 2012 6.86% Hyundai Tucson SUV 2012 0.27% Hyundai Veracruz SUV 2012 0.01% +614 /scratch/Teaching/cars/car_ims/000652.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin Virage Convertible 2012 40.76% Aston Martin V8 Vantage Coupe 2012 28.17% Aston Martin V8 Vantage Convertible 2012 13.22% BMW M6 Convertible 2010 8.27% Fisker Karma Sedan 2012 6.1% +615 /scratch/Teaching/cars/car_ims/005034.jpg Chevrolet Tahoe Hybrid SUV 2012 Cadillac Escalade EXT Crew Cab 2007 81.74% GMC Yukon Hybrid SUV 2012 17.73% Chevrolet Tahoe Hybrid SUV 2012 0.49% Chevrolet Avalanche Crew Cab 2012 0.03% Land Rover Range Rover SUV 2012 0.0% +616 /scratch/Teaching/cars/car_ims/004339.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 48.91% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 35.88% Chevrolet Avalanche Crew Cab 2012 13.09% Chevrolet Silverado 1500 Regular Cab 2012 1.03% Chevrolet Tahoe Hybrid SUV 2012 0.65% +617 /scratch/Teaching/cars/car_ims/013997.jpg Nissan Juke Hatchback 2012 Scion xD Hatchback 2012 31.18% Hyundai Tucson SUV 2012 19.24% Chevrolet Traverse SUV 2012 18.22% Nissan Juke Hatchback 2012 15.84% Hyundai Veracruz SUV 2012 5.33% +618 /scratch/Teaching/cars/car_ims/004603.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 100.0% Jaguar XK XKR 2012 0.0% Chevrolet Corvette Convertible 2012 0.0% Chevrolet Corvette ZR1 2012 0.0% Porsche Panamera Sedan 2012 0.0% +619 /scratch/Teaching/cars/car_ims/010145.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 46.0% Plymouth Neon Coupe 1999 13.65% Ford Focus Sedan 2007 10.13% Chevrolet Impala Sedan 2007 6.96% Daewoo Nubira Wagon 2002 4.54% +620 /scratch/Teaching/cars/car_ims/002622.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 99.91% BMW X5 SUV 2007 0.08% BMW 1 Series Coupe 2012 0.0% BMW X3 SUV 2012 0.0% Jeep Compass SUV 2012 0.0% +621 /scratch/Teaching/cars/car_ims/006477.jpg Chrysler Crossfire Convertible 2008 Hyundai Genesis Sedan 2012 60.18% Chrysler Sebring Convertible 2010 20.24% Chrysler Crossfire Convertible 2008 8.08% Hyundai Azera Sedan 2012 3.86% Mercedes-Benz E-Class Sedan 2012 2.32% +622 /scratch/Teaching/cars/car_ims/011090.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 99.84% Honda Odyssey Minivan 2007 0.13% Honda Accord Sedan 2012 0.02% Hyundai Sonata Sedan 2012 0.01% Honda Odyssey Minivan 2012 0.0% +623 /scratch/Teaching/cars/car_ims/007581.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 97.73% Dodge Charger SRT-8 2009 1.38% Chevrolet Camaro Convertible 2012 0.39% Aston Martin V8 Vantage Coupe 2012 0.11% Chevrolet Cobalt SS 2010 0.11% +624 /scratch/Teaching/cars/car_ims/009268.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 99.73% Ford F-450 Super Duty Crew Cab 2012 0.27% Ford F-150 Regular Cab 2007 0.0% Cadillac Escalade EXT Crew Cab 2007 0.0% GMC Canyon Extended Cab 2012 0.0% +625 /scratch/Teaching/cars/car_ims/006895.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 76.81% Plymouth Neon Coupe 1999 23.05% Nissan 240SX Coupe 1998 0.12% Ford Focus Sedan 2007 0.02% Audi 100 Wagon 1994 0.0% +626 /scratch/Teaching/cars/car_ims/010704.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 99.92% Ford Fiesta Sedan 2012 0.05% Hyundai Accent Sedan 2012 0.03% Hyundai Sonata Hybrid Sedan 2012 0.01% Chevrolet Sonic Sedan 2012 0.0% +627 /scratch/Teaching/cars/car_ims/006608.jpg Chrysler PT Cruiser Convertible 2008 Chrysler PT Cruiser Convertible 2008 97.24% Dodge Caliber Wagon 2012 2.23% Dodge Journey SUV 2012 0.39% Dodge Caliber Wagon 2007 0.06% Chrysler Town and Country Minivan 2012 0.05% +628 /scratch/Teaching/cars/car_ims/004696.jpg Chevrolet Traverse SUV 2012 Buick Verano Sedan 2012 36.09% BMW X3 SUV 2012 5.68% Hyundai Veracruz SUV 2012 3.94% GMC Acadia SUV 2012 3.84% Buick Regal GS 2012 3.55% +629 /scratch/Teaching/cars/car_ims/009757.jpg GMC Savana Van 2012 Chevrolet Express Van 2007 60.18% Chevrolet Express Cargo Van 2007 30.8% GMC Savana Van 2012 8.29% Volkswagen Golf Hatchback 1991 0.43% Dodge Caravan Minivan 1997 0.21% +630 /scratch/Teaching/cars/car_ims/003003.jpg BMW X3 SUV 2012 BMW X3 SUV 2012 99.34% BMW X5 SUV 2007 0.23% Jeep Grand Cherokee SUV 2012 0.19% Jeep Compass SUV 2012 0.15% Dodge Durango SUV 2012 0.05% +631 /scratch/Teaching/cars/car_ims/014395.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Sedan 2012 49.25% Rolls-Royce Phantom Drophead Coupe Convertible 2012 45.56% Rolls-Royce Ghost Sedan 2012 4.62% Dodge Challenger SRT8 2011 0.4% Bentley Mulsanne Sedan 2011 0.06% +632 /scratch/Teaching/cars/car_ims/002554.jpg BMW X5 SUV 2007 BMW 3 Series Wagon 2012 50.49% BMW ActiveHybrid 5 Sedan 2012 25.19% BMW M5 Sedan 2010 21.81% BMW 3 Series Sedan 2012 0.74% BMW M3 Coupe 2012 0.68% +633 /scratch/Teaching/cars/car_ims/013908.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 99.28% Jeep Wrangler SUV 2012 0.45% Ford F-150 Regular Cab 2007 0.11% Ford Ranger SuperCab 2011 0.05% Ford F-150 Regular Cab 2012 0.03% +634 /scratch/Teaching/cars/car_ims/014579.jpg Rolls-Royce Phantom Sedan 2012 Rolls-Royce Phantom Sedan 2012 97.33% Rolls-Royce Ghost Sedan 2012 2.67% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.0% Chrysler 300 SRT-8 2010 0.0% Bentley Mulsanne Sedan 2011 0.0% +635 /scratch/Teaching/cars/car_ims/014999.jpg Suzuki Kizashi Sedan 2012 Audi S5 Coupe 2012 25.15% Audi S4 Sedan 2007 18.9% Audi A5 Coupe 2012 17.54% Suzuki Kizashi Sedan 2012 5.64% Cadillac CTS-V Sedan 2012 4.18% +636 /scratch/Teaching/cars/car_ims/008716.jpg Ford Mustang Convertible 2007 Ford Mustang Convertible 2007 94.22% Eagle Talon Hatchback 1998 4.34% Mercedes-Benz 300-Class Convertible 1993 0.59% Geo Metro Convertible 1993 0.48% Chrysler Crossfire Convertible 2008 0.29% +637 /scratch/Teaching/cars/car_ims/004416.jpg Chevrolet Corvette Convertible 2012 Suzuki SX4 Hatchback 2012 40.19% Chevrolet HHR SS 2010 18.05% Daewoo Nubira Wagon 2002 11.6% Suzuki Aerio Sedan 2007 4.4% GMC Savana Van 2012 4.39% +638 /scratch/Teaching/cars/car_ims/002442.jpg BMW 3 Series Wagon 2012 BMW 3 Series Wagon 2012 87.35% BMW M5 Sedan 2010 8.51% Acura TL Type-S 2008 1.48% Suzuki Aerio Sedan 2007 0.81% BMW ActiveHybrid 5 Sedan 2012 0.21% +639 /scratch/Teaching/cars/car_ims/003992.jpg Buick Enclave SUV 2012 Chevrolet Traverse SUV 2012 76.53% Buick Enclave SUV 2012 15.58% Hyundai Veracruz SUV 2012 4.34% GMC Acadia SUV 2012 2.85% Hyundai Santa Fe SUV 2012 0.35% +640 /scratch/Teaching/cars/car_ims/006082.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 64.52% Chevrolet Silverado 1500 Extended Cab 2012 32.91% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 1.21% Chevrolet Avalanche Crew Cab 2012 1.0% Chevrolet Silverado 2500HD Regular Cab 2012 0.23% +641 /scratch/Teaching/cars/car_ims/011625.jpg Infiniti QX56 SUV 2011 Infiniti QX56 SUV 2011 100.0% Dodge Durango SUV 2012 0.0% Land Rover Range Rover SUV 2012 0.0% Toyota Sequoia SUV 2012 0.0% BMW X3 SUV 2012 0.0% +642 /scratch/Teaching/cars/car_ims/006980.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Nissan NV Passenger Van 2012 23.25% Bentley Continental Supersports Conv. Convertible 2012 10.14% Lamborghini Reventon Coupe 2008 9.03% Jeep Liberty SUV 2012 6.52% Bentley Arnage Sedan 2009 5.51% +643 /scratch/Teaching/cars/car_ims/008322.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 99.98% Ferrari FF Coupe 2012 0.01% Ferrari 458 Italia Coupe 2012 0.0% Jaguar XK XKR 2012 0.0% Chevrolet Corvette Convertible 2012 0.0% +644 /scratch/Teaching/cars/car_ims/009348.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 43.82% GMC Canyon Extended Cab 2012 23.44% Ford Ranger SuperCab 2011 6.33% Ford F-150 Regular Cab 2012 6.0% Chevrolet Silverado 2500HD Regular Cab 2012 5.57% +645 /scratch/Teaching/cars/car_ims/011815.jpg Jaguar XK XKR 2012 Jaguar XK XKR 2012 68.77% Aston Martin V8 Vantage Coupe 2012 16.51% Aston Martin V8 Vantage Convertible 2012 8.87% Chevrolet Corvette Ron Fellows Edition Z06 2007 5.73% Chevrolet Corvette Convertible 2012 0.03% +646 /scratch/Teaching/cars/car_ims/004434.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Convertible 2012 76.29% Ferrari California Convertible 2012 6.47% Ferrari 458 Italia Convertible 2012 5.59% Chevrolet Camaro Convertible 2012 4.09% Chevrolet Corvette ZR1 2012 1.98% +647 /scratch/Teaching/cars/car_ims/010411.jpg Honda Odyssey Minivan 2012 Suzuki SX4 Sedan 2012 86.42% Buick Verano Sedan 2012 2.57% Hyundai Veracruz SUV 2012 2.16% BMW X3 SUV 2012 1.68% Daewoo Nubira Wagon 2002 1.44% +648 /scratch/Teaching/cars/car_ims/003908.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 94.8% Buick Regal GS 2012 2.31% Cadillac CTS-V Sedan 2012 1.01% Chevrolet Sonic Sedan 2012 0.84% Infiniti QX56 SUV 2011 0.25% +649 /scratch/Teaching/cars/car_ims/015223.jpg Tesla Model S Sedan 2012 Acura RL Sedan 2012 30.42% Acura TL Type-S 2008 13.07% Buick Verano Sedan 2012 12.02% Infiniti G Coupe IPL 2012 7.44% Honda Accord Sedan 2012 6.49% +650 /scratch/Teaching/cars/car_ims/011392.jpg Hyundai Elantra Touring Hatchback 2012 Ford Focus Sedan 2007 95.33% Audi 100 Wagon 1994 1.26% Dodge Caravan Minivan 1997 0.84% Hyundai Elantra Touring Hatchback 2012 0.39% Honda Accord Coupe 2012 0.38% +651 /scratch/Teaching/cars/car_ims/015246.jpg Tesla Model S Sedan 2012 Tesla Model S Sedan 2012 32.68% Fisker Karma Sedan 2012 14.22% Bentley Continental GT Coupe 2007 14.15% Bentley Continental GT Coupe 2012 7.91% Chevrolet Malibu Hybrid Sedan 2010 7.14% +652 /scratch/Teaching/cars/car_ims/000143.jpg Acura RL Sedan 2012 Audi S4 Sedan 2007 20.29% BMW 3 Series Wagon 2012 14.29% Acura RL Sedan 2012 11.73% Acura TL Type-S 2008 11.55% Hyundai Genesis Sedan 2012 9.51% +653 /scratch/Teaching/cars/car_ims/009657.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 99.8% Chevrolet Avalanche Crew Cab 2012 0.19% Chevrolet Tahoe Hybrid SUV 2012 0.0% GMC Yukon Hybrid SUV 2012 0.0% Cadillac Escalade EXT Crew Cab 2007 0.0% +654 /scratch/Teaching/cars/car_ims/009563.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 98.82% Scion xD Hatchback 2012 1.04% Hyundai Tucson SUV 2012 0.11% Acura ZDX Hatchback 2012 0.01% Nissan Leaf Hatchback 2012 0.01% +655 /scratch/Teaching/cars/car_ims/004966.jpg Chevrolet Impala Sedan 2007 BMW 6 Series Convertible 2007 33.33% Acura TL Type-S 2008 30.55% Chevrolet Monte Carlo Coupe 2007 25.68% Chevrolet Malibu Hybrid Sedan 2010 4.41% Chevrolet Impala Sedan 2007 3.98% +656 /scratch/Teaching/cars/car_ims/014411.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Mercedes-Benz 300-Class Convertible 1993 40.93% Lincoln Town Car Sedan 2011 19.78% Chevrolet Monte Carlo Coupe 2007 11.37% Rolls-Royce Phantom Drophead Coupe Convertible 2012 5.35% Audi 100 Wagon 1994 3.39% +657 /scratch/Teaching/cars/car_ims/004441.jpg Chevrolet Corvette Convertible 2012 Lamborghini Diablo Coupe 2001 69.0% Acura Integra Type R 2001 18.31% Ferrari 458 Italia Convertible 2012 1.77% Aston Martin V8 Vantage Coupe 2012 1.72% Aston Martin Virage Coupe 2012 1.55% +658 /scratch/Teaching/cars/car_ims/011300.jpg Hyundai Sonata Sedan 2012 Hyundai Sonata Sedan 2012 99.65% Hyundai Azera Sedan 2012 0.31% Hyundai Sonata Hybrid Sedan 2012 0.04% Hyundai Elantra Sedan 2007 0.0% Honda Accord Sedan 2012 0.0% +659 /scratch/Teaching/cars/car_ims/002102.jpg BMW ActiveHybrid 5 Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 56.1% BMW 3 Series Wagon 2012 26.27% Rolls-Royce Ghost Sedan 2012 17.16% BMW 3 Series Sedan 2012 0.21% BMW M6 Convertible 2010 0.08% +660 /scratch/Teaching/cars/car_ims/008892.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 99.89% Chevrolet Tahoe Hybrid SUV 2012 0.04% Land Rover LR2 SUV 2012 0.03% Toyota Sequoia SUV 2012 0.03% Land Rover Range Rover SUV 2012 0.0% +661 /scratch/Teaching/cars/car_ims/000600.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin V8 Vantage Convertible 2012 28.82% Jaguar XK XKR 2012 23.45% Aston Martin V8 Vantage Coupe 2012 17.88% Ferrari California Convertible 2012 17.58% Aston Martin Virage Convertible 2012 6.5% +662 /scratch/Teaching/cars/car_ims/004782.jpg Chevrolet Camaro Convertible 2012 McLaren MP4-12C Coupe 2012 14.44% Ford GT Coupe 2006 10.94% Spyker C8 Coupe 2009 10.03% Ferrari 458 Italia Coupe 2012 9.82% Ferrari FF Coupe 2012 7.35% +663 /scratch/Teaching/cars/car_ims/012429.jpg Lamborghini Aventador Coupe 2012 Lamborghini Reventon Coupe 2008 70.1% Bugatti Veyron 16.4 Coupe 2009 15.37% Aston Martin V8 Vantage Coupe 2012 4.24% Lamborghini Aventador Coupe 2012 2.66% Fisker Karma Sedan 2012 2.41% +664 /scratch/Teaching/cars/car_ims/007575.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 99.89% Dodge Charger SRT-8 2009 0.08% Fisker Karma Sedan 2012 0.02% Chrysler 300 SRT-8 2010 0.0% Rolls-Royce Ghost Sedan 2012 0.0% +665 /scratch/Teaching/cars/car_ims/006747.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2012 88.22% Dodge Caliber Wagon 2007 11.77% Dodge Journey SUV 2012 0.01% Dodge Dakota Crew Cab 2010 0.0% Dodge Durango SUV 2007 0.0% +666 /scratch/Teaching/cars/car_ims/011650.jpg Infiniti QX56 SUV 2011 Infiniti QX56 SUV 2011 99.52% Toyota Sequoia SUV 2012 0.32% Land Rover Range Rover SUV 2012 0.11% Land Rover LR2 SUV 2012 0.04% Cadillac SRX SUV 2012 0.01% +667 /scratch/Teaching/cars/car_ims/010408.jpg Honda Odyssey Minivan 2012 Honda Odyssey Minivan 2012 99.34% Honda Odyssey Minivan 2007 0.48% Hyundai Veracruz SUV 2012 0.11% Honda Accord Sedan 2012 0.05% Land Rover LR2 SUV 2012 0.01% +668 /scratch/Teaching/cars/car_ims/002225.jpg BMW 1 Series Coupe 2012 BMW 1 Series Coupe 2012 81.61% BMW X6 SUV 2012 10.78% BMW 3 Series Sedan 2012 2.79% Volvo C30 Hatchback 2012 2.73% BMW 1 Series Convertible 2012 1.92% +669 /scratch/Teaching/cars/car_ims/012883.jpg MINI Cooper Roadster Convertible 2012 Spyker C8 Convertible 2009 36.09% Bentley Continental Supersports Conv. Convertible 2012 14.45% Ford GT Coupe 2006 14.38% Bugatti Veyron 16.4 Coupe 2009 11.21% Lamborghini Reventon Coupe 2008 8.64% +670 /scratch/Teaching/cars/car_ims/013917.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 32.74% Mazda Tribute SUV 2011 29.67% Toyota Sequoia SUV 2012 13.85% Jeep Liberty SUV 2012 10.51% Ford E-Series Wagon Van 2012 4.37% +671 /scratch/Teaching/cars/car_ims/009827.jpg GMC Yukon Hybrid SUV 2012 GMC Yukon Hybrid SUV 2012 99.52% Cadillac Escalade EXT Crew Cab 2007 0.47% Ford F-150 Regular Cab 2007 0.01% Ford F-150 Regular Cab 2012 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% +672 /scratch/Teaching/cars/car_ims/014721.jpg Spyker C8 Convertible 2009 Jaguar XK XKR 2012 61.39% Chevrolet Corvette ZR1 2012 19.83% Spyker C8 Coupe 2009 2.41% Ford GT Coupe 2006 1.98% Ferrari FF Coupe 2012 1.68% +673 /scratch/Teaching/cars/car_ims/001746.jpg Audi S5 Coupe 2012 Acura RL Sedan 2012 35.26% Infiniti G Coupe IPL 2012 27.61% Toyota Camry Sedan 2012 7.25% Mitsubishi Lancer Sedan 2012 4.32% Honda Accord Sedan 2012 3.9% +674 /scratch/Teaching/cars/car_ims/015475.jpg Toyota Corolla Sedan 2012 Hyundai Sonata Sedan 2012 35.8% Hyundai Elantra Sedan 2007 35.48% Honda Accord Sedan 2012 14.33% Acura RL Sedan 2012 9.45% Honda Odyssey Minivan 2012 1.31% +675 /scratch/Teaching/cars/car_ims/013396.jpg Mercedes-Benz SL-Class Coupe 2009 Mercedes-Benz SL-Class Coupe 2009 99.77% Porsche Panamera Sedan 2012 0.13% BMW M6 Convertible 2010 0.04% BMW M3 Coupe 2012 0.02% Chevrolet Corvette ZR1 2012 0.01% +676 /scratch/Teaching/cars/car_ims/004427.jpg Chevrolet Corvette Convertible 2012 Chevrolet Camaro Convertible 2012 30.74% Aston Martin V8 Vantage Convertible 2012 26.49% Jaguar XK XKR 2012 15.69% BMW M6 Convertible 2010 15.45% Aston Martin Virage Convertible 2012 2.59% +677 /scratch/Teaching/cars/car_ims/010890.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 99.74% Hyundai Veracruz SUV 2012 0.2% Ford Fiesta Sedan 2012 0.04% Hyundai Sonata Hybrid Sedan 2012 0.01% Chevrolet Traverse SUV 2012 0.01% +678 /scratch/Teaching/cars/car_ims/013957.jpg Nissan Juke Hatchback 2012 Audi S4 Sedan 2012 15.96% Dodge Journey SUV 2012 6.81% Chevrolet Sonic Sedan 2012 5.7% Volvo C30 Hatchback 2012 4.98% BMW X6 SUV 2012 4.51% +679 /scratch/Teaching/cars/car_ims/012211.jpg Jeep Compass SUV 2012 Jeep Grand Cherokee SUV 2012 62.0% Jeep Compass SUV 2012 17.58% BMW X5 SUV 2007 11.69% BMW X3 SUV 2012 3.6% Volvo XC90 SUV 2007 2.29% +680 /scratch/Teaching/cars/car_ims/014328.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 90.77% Chrysler Town and Country Minivan 2012 6.65% Ford Freestar Minivan 2007 0.93% Chevrolet Malibu Sedan 2007 0.47% Suzuki SX4 Sedan 2012 0.35% +681 /scratch/Teaching/cars/car_ims/001464.jpg Audi 100 Wagon 1994 Chrysler 300 SRT-8 2010 61.46% Volvo XC90 SUV 2007 13.76% Dodge Durango SUV 2007 3.91% Audi 100 Wagon 1994 3.41% Volvo 240 Sedan 1993 3.34% +682 /scratch/Teaching/cars/car_ims/010220.jpg HUMMER H3T Crew Cab 2010 GMC Canyon Extended Cab 2012 85.56% Chevrolet Silverado 1500 Extended Cab 2012 13.36% Chevrolet Silverado 1500 Regular Cab 2012 0.36% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.33% Dodge Dakota Club Cab 2007 0.15% +683 /scratch/Teaching/cars/car_ims/009050.jpg Ford Ranger SuperCab 2011 Ford Ranger SuperCab 2011 26.48% Dodge Dakota Club Cab 2007 24.84% Ford F-150 Regular Cab 2007 20.05% GMC Canyon Extended Cab 2012 9.51% Dodge Ram Pickup 3500 Quad Cab 2009 4.87% +684 /scratch/Teaching/cars/car_ims/008465.jpg Ferrari 458 Italia Coupe 2012 BMW 3 Series Sedan 2012 11.78% Mercedes-Benz C-Class Sedan 2012 8.54% BMW 3 Series Wagon 2012 7.06% Chrysler 300 SRT-8 2010 6.84% Volkswagen Golf Hatchback 1991 3.65% +685 /scratch/Teaching/cars/car_ims/010568.jpg Honda Accord Coupe 2012 Honda Accord Coupe 2012 95.95% Acura TL Type-S 2008 3.73% Mitsubishi Lancer Sedan 2012 0.26% Nissan 240SX Coupe 1998 0.02% Toyota Camry Sedan 2012 0.01% +686 /scratch/Teaching/cars/car_ims/002226.jpg BMW 1 Series Coupe 2012 BMW M3 Coupe 2012 39.73% BMW Z4 Convertible 2012 14.15% BMW 1 Series Convertible 2012 12.71% Audi RS 4 Convertible 2008 9.09% Audi S4 Sedan 2007 8.06% +687 /scratch/Teaching/cars/car_ims/005122.jpg Chevrolet Sonic Sedan 2012 Hyundai Accent Sedan 2012 70.09% Toyota Corolla Sedan 2012 24.74% Toyota Camry Sedan 2012 2.77% Ford Fiesta Sedan 2012 1.14% Chevrolet Sonic Sedan 2012 0.94% +688 /scratch/Teaching/cars/car_ims/007993.jpg Eagle Talon Hatchback 1998 Eagle Talon Hatchback 1998 99.96% Plymouth Neon Coupe 1999 0.02% Nissan 240SX Coupe 1998 0.01% Ferrari 458 Italia Coupe 2012 0.01% Aston Martin V8 Vantage Convertible 2012 0.0% +689 /scratch/Teaching/cars/car_ims/016051.jpg Volvo XC90 SUV 2007 Honda Odyssey Minivan 2007 32.78% Daewoo Nubira Wagon 2002 16.79% Hyundai Veracruz SUV 2012 13.74% Chevrolet Traverse SUV 2012 10.63% Chevrolet Malibu Sedan 2007 6.85% +690 /scratch/Teaching/cars/car_ims/000033.jpg AM General Hummer SUV 2000 HUMMER H2 SUT Crew Cab 2009 67.17% AM General Hummer SUV 2000 19.06% HUMMER H3T Crew Cab 2010 8.01% Jeep Wrangler SUV 2012 5.73% GMC Canyon Extended Cab 2012 0.03% +691 /scratch/Teaching/cars/car_ims/015077.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 91.05% Scion xD Hatchback 2012 4.61% Suzuki SX4 Sedan 2012 2.17% Mazda Tribute SUV 2011 1.22% Dodge Caliber Wagon 2012 0.37% +692 /scratch/Teaching/cars/car_ims/011526.jpg Hyundai Azera Sedan 2012 Infiniti G Coupe IPL 2012 58.99% Buick Verano Sedan 2012 14.26% Buick Regal GS 2012 12.27% Mitsubishi Lancer Sedan 2012 6.84% Toyota Camry Sedan 2012 3.23% +693 /scratch/Teaching/cars/car_ims/015147.jpg Suzuki SX4 Sedan 2012 Land Rover LR2 SUV 2012 8.3% Chrysler PT Cruiser Convertible 2008 7.42% Land Rover Range Rover SUV 2012 4.51% Ford Expedition EL SUV 2009 4.41% Hyundai Santa Fe SUV 2012 4.34% +694 /scratch/Teaching/cars/car_ims/014145.jpg Plymouth Neon Coupe 1999 Chevrolet Monte Carlo Coupe 2007 51.04% Jaguar XK XKR 2012 8.13% Chevrolet Impala Sedan 2007 4.67% Nissan 240SX Coupe 1998 4.04% Chevrolet Corvette Convertible 2012 3.87% +695 /scratch/Teaching/cars/car_ims/007728.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 99.83% Chrysler Aspen SUV 2009 0.17% Isuzu Ascender SUV 2008 0.0% Dodge Caliber Wagon 2012 0.0% Volvo XC90 SUV 2007 0.0% +696 /scratch/Teaching/cars/car_ims/014074.jpg Nissan 240SX Coupe 1998 Nissan 240SX Coupe 1998 82.65% Mercedes-Benz 300-Class Convertible 1993 6.37% Audi 100 Wagon 1994 4.8% Audi 100 Sedan 1994 2.06% Audi V8 Sedan 1994 1.15% +697 /scratch/Teaching/cars/car_ims/015644.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 99.98% Suzuki Aerio Sedan 2007 0.02% Toyota Camry Sedan 2012 0.0% Toyota Corolla Sedan 2012 0.0% Acura TSX Sedan 2012 0.0% +698 /scratch/Teaching/cars/car_ims/014953.jpg Suzuki Kizashi Sedan 2012 Infiniti G Coupe IPL 2012 32.09% BMW M5 Sedan 2010 12.75% Toyota Corolla Sedan 2012 10.51% Suzuki Kizashi Sedan 2012 10.39% Toyota Camry Sedan 2012 5.89% +699 /scratch/Teaching/cars/car_ims/000732.jpg Aston Martin V8 Vantage Coupe 2012 Aston Martin V8 Vantage Coupe 2012 91.0% Aston Martin V8 Vantage Convertible 2012 6.75% Aston Martin Virage Convertible 2012 2.12% Ferrari FF Coupe 2012 0.05% Fisker Karma Sedan 2012 0.04% +700 /scratch/Teaching/cars/car_ims/012590.jpg Lamborghini Diablo Coupe 2001 Lamborghini Diablo Coupe 2001 99.86% McLaren MP4-12C Coupe 2012 0.08% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.06% Acura Integra Type R 2001 0.0% AM General Hummer SUV 2000 0.0% +701 /scratch/Teaching/cars/car_ims/008074.jpg FIAT 500 Abarth 2012 FIAT 500 Abarth 2012 30.21% Jeep Liberty SUV 2012 29.08% BMW X5 SUV 2007 12.45% Chrysler 300 SRT-8 2010 8.18% Infiniti QX56 SUV 2011 5.49% +702 /scratch/Teaching/cars/car_ims/014033.jpg Nissan 240SX Coupe 1998 Nissan 240SX Coupe 1998 89.93% Eagle Talon Hatchback 1998 4.29% Plymouth Neon Coupe 1999 2.63% Ford Focus Sedan 2007 0.85% Audi V8 Sedan 1994 0.77% +703 /scratch/Teaching/cars/car_ims/014859.jpg Suzuki Aerio Sedan 2007 Suzuki Aerio Sedan 2007 51.72% Volkswagen Golf Hatchback 2012 47.31% Ford Focus Sedan 2007 0.67% Suzuki SX4 Sedan 2012 0.09% Toyota Corolla Sedan 2012 0.05% +704 /scratch/Teaching/cars/car_ims/008489.jpg Ferrari 458 Italia Coupe 2012 Ferrari 458 Italia Coupe 2012 56.65% Chevrolet Corvette ZR1 2012 29.59% Porsche Panamera Sedan 2012 3.61% Ferrari FF Coupe 2012 2.63% Eagle Talon Hatchback 1998 2.02% +705 /scratch/Teaching/cars/car_ims/002980.jpg BMW X3 SUV 2012 Land Rover LR2 SUV 2012 97.19% Dodge Durango SUV 2012 0.64% Ford Edge SUV 2012 0.58% Mazda Tribute SUV 2011 0.48% Honda Odyssey Minivan 2012 0.36% +706 /scratch/Teaching/cars/car_ims/010980.jpg Hyundai Veracruz SUV 2012 Hyundai Veracruz SUV 2012 33.29% Chevrolet Malibu Hybrid Sedan 2010 12.54% Honda Accord Sedan 2012 8.36% Buick Verano Sedan 2012 7.19% Acura ZDX Hatchback 2012 5.47% +707 /scratch/Teaching/cars/car_ims/011681.jpg Isuzu Ascender SUV 2008 Isuzu Ascender SUV 2008 72.01% Chevrolet Tahoe Hybrid SUV 2012 19.44% Ford Expedition EL SUV 2009 5.8% Buick Rainier SUV 2007 0.94% Mazda Tribute SUV 2011 0.57% +708 /scratch/Teaching/cars/car_ims/014655.jpg Scion xD Hatchback 2012 Suzuki SX4 Hatchback 2012 72.61% Scion xD Hatchback 2012 15.33% Chevrolet Sonic Sedan 2012 6.05% Volvo C30 Hatchback 2012 2.77% Ford Fiesta Sedan 2012 0.93% +709 /scratch/Teaching/cars/car_ims/014848.jpg Suzuki Aerio Sedan 2007 Nissan Leaf Hatchback 2012 32.24% Acura ZDX Hatchback 2012 12.02% Suzuki Aerio Sedan 2007 8.75% Volkswagen Golf Hatchback 2012 8.16% Ford Fiesta Sedan 2012 7.49% +710 /scratch/Teaching/cars/car_ims/001427.jpg Audi 100 Wagon 1994 Lincoln Town Car Sedan 2011 76.8% Audi 100 Wagon 1994 23.06% Volvo 240 Sedan 1993 0.07% Mercedes-Benz 300-Class Convertible 1993 0.03% Audi 100 Sedan 1994 0.03% +711 /scratch/Teaching/cars/car_ims/011775.jpg Jaguar XK XKR 2012 Aston Martin V8 Vantage Coupe 2012 58.78% Dodge Challenger SRT8 2011 19.38% Jaguar XK XKR 2012 15.36% Fisker Karma Sedan 2012 3.0% Aston Martin V8 Vantage Convertible 2012 1.54% +712 /scratch/Teaching/cars/car_ims/000818.jpg Aston Martin Virage Coupe 2012 Aston Martin Virage Coupe 2012 99.34% Aston Martin V8 Vantage Coupe 2012 0.66% McLaren MP4-12C Coupe 2012 0.0% Aston Martin V8 Vantage Convertible 2012 0.0% Ferrari California Convertible 2012 0.0% +713 /scratch/Teaching/cars/car_ims/000009.jpg AM General Hummer SUV 2000 Jeep Wrangler SUV 2012 47.07% AM General Hummer SUV 2000 28.58% Jeep Patriot SUV 2012 18.91% HUMMER H3T Crew Cab 2010 3.72% GMC Canyon Extended Cab 2012 0.63% +714 /scratch/Teaching/cars/car_ims/013636.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 98.31% Dodge Sprinter Cargo Van 2009 1.69% Ram C/V Cargo Van Minivan 2012 0.0% Chrysler Town and Country Minivan 2012 0.0% Audi 100 Wagon 1994 0.0% +715 /scratch/Teaching/cars/car_ims/008656.jpg Ford F-450 Super Duty Crew Cab 2012 Bentley Arnage Sedan 2009 26.4% Rolls-Royce Phantom Sedan 2012 11.69% AM General Hummer SUV 2000 9.05% Jeep Patriot SUV 2012 6.9% Jeep Liberty SUV 2012 5.62% +716 /scratch/Teaching/cars/car_ims/011167.jpg Hyundai Accent Sedan 2012 Toyota Camry Sedan 2012 52.36% Hyundai Azera Sedan 2012 11.92% Toyota Corolla Sedan 2012 11.82% Hyundai Accent Sedan 2012 5.45% Suzuki Kizashi Sedan 2012 4.46% +717 /scratch/Teaching/cars/car_ims/012951.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 96.15% FIAT 500 Convertible 2012 1.64% Bentley Continental Supersports Conv. Convertible 2012 1.16% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.38% Bugatti Veyron 16.4 Convertible 2009 0.26% +718 /scratch/Teaching/cars/car_ims/010140.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 100.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Ford F-150 Regular Cab 2007 0.0% Plymouth Neon Coupe 1999 0.0% Chevrolet Monte Carlo Coupe 2007 0.0% +719 /scratch/Teaching/cars/car_ims/013084.jpg McLaren MP4-12C Coupe 2012 Lamborghini Diablo Coupe 2001 42.12% McLaren MP4-12C Coupe 2012 23.17% Aston Martin Virage Coupe 2012 8.81% Spyker C8 Coupe 2009 3.67% AM General Hummer SUV 2000 3.24% +720 /scratch/Teaching/cars/car_ims/007168.jpg Dodge Sprinter Cargo Van 2009 Dodge Sprinter Cargo Van 2009 62.5% Mercedes-Benz Sprinter Van 2012 37.49% Ram C/V Cargo Van Minivan 2012 0.01% Audi 100 Wagon 1994 0.0% Dodge Caravan Minivan 1997 0.0% +721 /scratch/Teaching/cars/car_ims/013590.jpg Mercedes-Benz Sprinter Van 2012 Dodge Sprinter Cargo Van 2009 63.05% Mercedes-Benz Sprinter Van 2012 24.59% Mercedes-Benz SL-Class Coupe 2009 5.35% Lamborghini Reventon Coupe 2008 1.35% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.96% +722 /scratch/Teaching/cars/car_ims/015424.jpg Toyota Corolla Sedan 2012 Acura TSX Sedan 2012 55.82% Toyota Camry Sedan 2012 18.32% Suzuki SX4 Sedan 2012 15.92% Toyota Corolla Sedan 2012 6.58% Acura RL Sedan 2012 1.27% +723 /scratch/Teaching/cars/car_ims/012976.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 81.03% Bentley Continental Supersports Conv. Convertible 2012 8.75% Bugatti Veyron 16.4 Convertible 2009 3.33% Mercedes-Benz SL-Class Coupe 2009 1.98% FIAT 500 Convertible 2012 1.73% +724 /scratch/Teaching/cars/car_ims/006812.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2012 92.78% Dodge Caliber Wagon 2007 7.21% Dodge Magnum Wagon 2008 0.01% Dodge Durango SUV 2007 0.01% Dodge Journey SUV 2012 0.0% +725 /scratch/Teaching/cars/car_ims/000349.jpg Acura TSX Sedan 2012 Acura TSX Sedan 2012 98.56% Toyota Camry Sedan 2012 0.75% Acura RL Sedan 2012 0.62% Acura TL Sedan 2012 0.03% Mitsubishi Lancer Sedan 2012 0.02% +726 /scratch/Teaching/cars/car_ims/013355.jpg Mercedes-Benz SL-Class Coupe 2009 Mercedes-Benz SL-Class Coupe 2009 77.68% Audi TT Hatchback 2011 5.08% Audi TTS Coupe 2012 3.64% Audi TT RS Coupe 2012 3.53% Bugatti Veyron 16.4 Convertible 2009 2.08% +727 /scratch/Teaching/cars/car_ims/001618.jpg Audi S6 Sedan 2011 Audi S6 Sedan 2011 98.53% Audi S5 Convertible 2012 0.64% Audi S5 Coupe 2012 0.49% Audi RS 4 Convertible 2008 0.1% Audi S4 Sedan 2007 0.09% +728 /scratch/Teaching/cars/car_ims/001863.jpg Audi S4 Sedan 2012 Audi S4 Sedan 2012 43.66% Audi R8 Coupe 2012 21.85% Audi TT Hatchback 2011 12.62% Audi A5 Coupe 2012 5.76% Audi S5 Convertible 2012 4.99% +729 /scratch/Teaching/cars/car_ims/015511.jpg Toyota 4Runner SUV 2012 Hyundai Veracruz SUV 2012 84.72% Chevrolet Traverse SUV 2012 5.83% Land Rover LR2 SUV 2012 4.38% Chevrolet Malibu Sedan 2007 3.1% Toyota 4Runner SUV 2012 0.56% +730 /scratch/Teaching/cars/car_ims/008480.jpg Ferrari 458 Italia Coupe 2012 Eagle Talon Hatchback 1998 90.7% Plymouth Neon Coupe 1999 7.56% Aston Martin V8 Vantage Coupe 2012 0.95% Nissan 240SX Coupe 1998 0.58% Ford GT Coupe 2006 0.05% +731 /scratch/Teaching/cars/car_ims/002609.jpg BMW X5 SUV 2007 BMW X5 SUV 2007 70.7% Jeep Grand Cherokee SUV 2012 18.87% BMW X6 SUV 2012 5.23% BMW X3 SUV 2012 3.46% Jeep Compass SUV 2012 0.77% +732 /scratch/Teaching/cars/car_ims/003279.jpg Bentley Mulsanne Sedan 2011 Bentley Continental GT Coupe 2007 42.15% Fisker Karma Sedan 2012 25.74% Tesla Model S Sedan 2012 6.91% Bentley Continental GT Coupe 2012 5.93% Bentley Continental Flying Spur Sedan 2007 5.07% +733 /scratch/Teaching/cars/car_ims/010913.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 55.9% Chevrolet Traverse SUV 2012 20.05% Hyundai Veracruz SUV 2012 16.62% Buick Enclave SUV 2012 3.92% Nissan Juke Hatchback 2012 0.98% +734 /scratch/Teaching/cars/car_ims/004762.jpg Chevrolet Camaro Convertible 2012 Chevrolet Camaro Convertible 2012 98.7% Dodge Challenger SRT8 2011 0.48% Chrysler Crossfire Convertible 2008 0.38% Dodge Charger Sedan 2012 0.18% Honda Accord Coupe 2012 0.15% +735 /scratch/Teaching/cars/car_ims/009327.jpg Ford F-150 Regular Cab 2007 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 22.38% Chevrolet Avalanche Crew Cab 2012 14.99% Chevrolet Silverado 1500 Regular Cab 2012 13.79% GMC Canyon Extended Cab 2012 11.98% Chevrolet Silverado 1500 Extended Cab 2012 11.67% +736 /scratch/Teaching/cars/car_ims/003600.jpg Bugatti Veyron 16.4 Convertible 2009 Bugatti Veyron 16.4 Coupe 2009 84.04% Bugatti Veyron 16.4 Convertible 2009 7.61% Spyker C8 Convertible 2009 4.85% Spyker C8 Coupe 2009 1.2% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.72% +737 /scratch/Teaching/cars/car_ims/003857.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 99.97% Isuzu Ascender SUV 2008 0.01% Volkswagen Golf Hatchback 1991 0.01% Audi 100 Wagon 1994 0.0% Jeep Liberty SUV 2012 0.0% +738 /scratch/Teaching/cars/car_ims/014370.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Drophead Coupe Convertible 2012 65.22% Chevrolet Monte Carlo Coupe 2007 26.93% Rolls-Royce Ghost Sedan 2012 2.88% Lincoln Town Car Sedan 2011 2.75% Mercedes-Benz 300-Class Convertible 1993 0.98% +739 /scratch/Teaching/cars/car_ims/002307.jpg BMW 3 Series Sedan 2012 BMW 1 Series Coupe 2012 47.27% BMW M3 Coupe 2012 21.8% BMW 3 Series Sedan 2012 21.63% BMW M5 Sedan 2010 5.48% Volvo C30 Hatchback 2012 0.85% +740 /scratch/Teaching/cars/car_ims/015777.jpg Volkswagen Beetle Hatchback 2012 Nissan Leaf Hatchback 2012 60.69% Acura ZDX Hatchback 2012 14.4% FIAT 500 Convertible 2012 9.84% Volkswagen Beetle Hatchback 2012 6.49% Maybach Landaulet Convertible 2012 3.97% +741 /scratch/Teaching/cars/car_ims/001337.jpg Audi 100 Sedan 1994 Audi 100 Wagon 1994 98.81% Lincoln Town Car Sedan 2011 0.69% Audi 100 Sedan 1994 0.39% Mercedes-Benz 300-Class Convertible 1993 0.09% Ford Freestar Minivan 2007 0.02% +742 /scratch/Teaching/cars/car_ims/007051.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Crew Cab 2010 80.25% Dodge Ram Pickup 3500 Quad Cab 2009 19.19% Dodge Dakota Club Cab 2007 0.44% Dodge Durango SUV 2007 0.03% GMC Canyon Extended Cab 2012 0.02% +743 /scratch/Teaching/cars/car_ims/013230.jpg Mercedes-Benz 300-Class Convertible 1993 Dodge Charger SRT-8 2009 98.52% Dodge Charger Sedan 2012 1.38% Dodge Magnum Wagon 2008 0.09% Dodge Challenger SRT8 2011 0.01% Chevrolet Camaro Convertible 2012 0.0% +744 /scratch/Teaching/cars/car_ims/007872.jpg Dodge Charger Sedan 2012 Dodge Charger Sedan 2012 94.34% Audi S4 Sedan 2012 4.59% Jaguar XK XKR 2012 0.29% Honda Accord Coupe 2012 0.18% Volvo C30 Hatchback 2012 0.09% +745 /scratch/Teaching/cars/car_ims/006685.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 30.54% Chevrolet Malibu Sedan 2007 18.21% Ford Freestar Minivan 2007 13.05% Lincoln Town Car Sedan 2011 11.66% Chevrolet Impala Sedan 2007 10.04% +746 /scratch/Teaching/cars/car_ims/015192.jpg Tesla Model S Sedan 2012 Tesla Model S Sedan 2012 62.02% BMW M5 Sedan 2010 17.88% Fisker Karma Sedan 2012 8.17% Porsche Panamera Sedan 2012 3.34% Acura TL Type-S 2008 2.37% +747 /scratch/Teaching/cars/car_ims/013967.jpg Nissan Juke Hatchback 2012 Hyundai Veracruz SUV 2012 26.17% Hyundai Santa Fe SUV 2012 24.72% Buick Enclave SUV 2012 14.1% Mazda Tribute SUV 2011 7.46% Land Rover LR2 SUV 2012 7.15% +748 /scratch/Teaching/cars/car_ims/002079.jpg BMW ActiveHybrid 5 Sedan 2012 BMW X3 SUV 2012 73.78% BMW X5 SUV 2007 12.02% BMW ActiveHybrid 5 Sedan 2012 5.9% BMW 3 Series Wagon 2012 3.27% Rolls-Royce Ghost Sedan 2012 0.69% +749 /scratch/Teaching/cars/car_ims/016002.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 99.04% Audi 100 Wagon 1994 0.83% Lincoln Town Car Sedan 2011 0.05% Volvo XC90 SUV 2007 0.03% Volkswagen Golf Hatchback 1991 0.03% +750 /scratch/Teaching/cars/car_ims/007936.jpg Dodge Charger SRT-8 2009 Chevrolet Camaro Convertible 2012 35.04% Dodge Challenger SRT8 2011 16.63% Dodge Charger SRT-8 2009 14.35% Chrysler Crossfire Convertible 2008 6.36% Chevrolet TrailBlazer SS 2009 6.33% +751 /scratch/Teaching/cars/car_ims/010130.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 82.91% Chevrolet Corvette Convertible 2012 10.42% Eagle Talon Hatchback 1998 3.54% Mercedes-Benz 300-Class Convertible 1993 1.71% Ford Mustang Convertible 2007 1.1% +752 /scratch/Teaching/cars/car_ims/003523.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 67.64% Bentley Arnage Sedan 2009 8.2% Bentley Continental GT Coupe 2007 3.05% Daewoo Nubira Wagon 2002 2.99% Ford Mustang Convertible 2007 2.97% +753 /scratch/Teaching/cars/car_ims/015824.jpg Volkswagen Beetle Hatchback 2012 Porsche Panamera Sedan 2012 53.17% BMW M5 Sedan 2010 41.2% Tesla Model S Sedan 2012 2.46% BMW ActiveHybrid 5 Sedan 2012 0.96% Acura TL Sedan 2012 0.74% +754 /scratch/Teaching/cars/car_ims/008826.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 96.84% Audi 100 Wagon 1994 1.53% Ford F-150 Regular Cab 2007 1.03% Lincoln Town Car Sedan 2011 0.34% Buick Rainier SUV 2007 0.14% +755 /scratch/Teaching/cars/car_ims/001420.jpg Audi 100 Wagon 1994 Audi 100 Wagon 1994 60.54% Audi 100 Sedan 1994 18.5% Volvo 240 Sedan 1993 14.22% Volkswagen Golf Hatchback 1991 2.4% Mercedes-Benz 300-Class Convertible 1993 1.56% +756 /scratch/Teaching/cars/car_ims/013730.jpg Mitsubishi Lancer Sedan 2012 Mitsubishi Lancer Sedan 2012 62.49% Bentley Continental GT Coupe 2012 23.95% Audi TTS Coupe 2012 6.35% Aston Martin Virage Coupe 2012 2.75% Dodge Charger Sedan 2012 1.59% +757 /scratch/Teaching/cars/car_ims/004698.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 42.36% Chevrolet TrailBlazer SS 2009 30.34% Hyundai Santa Fe SUV 2012 8.37% Ford Edge SUV 2012 6.5% Dodge Journey SUV 2012 2.5% +758 /scratch/Teaching/cars/car_ims/003921.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 99.62% Buick Regal GS 2012 0.34% Acura ZDX Hatchback 2012 0.02% Suzuki Kizashi Sedan 2012 0.01% Chevrolet Sonic Sedan 2012 0.01% +759 /scratch/Teaching/cars/car_ims/002297.jpg BMW 3 Series Sedan 2012 BMW 3 Series Wagon 2012 84.48% Acura TL Type-S 2008 9.43% BMW ActiveHybrid 5 Sedan 2012 4.43% BMW M5 Sedan 2010 1.22% BMW 3 Series Sedan 2012 0.29% +760 /scratch/Teaching/cars/car_ims/008484.jpg Ferrari 458 Italia Coupe 2012 Ferrari 458 Italia Convertible 2012 67.63% Ferrari 458 Italia Coupe 2012 29.75% Ferrari California Convertible 2012 1.77% Lamborghini Aventador Coupe 2012 0.28% Chevrolet Corvette Convertible 2012 0.27% +761 /scratch/Teaching/cars/car_ims/014198.jpg Porsche Panamera Sedan 2012 Bentley Continental Flying Spur Sedan 2007 64.62% Fisker Karma Sedan 2012 12.55% Chrysler 300 SRT-8 2010 7.79% Buick Enclave SUV 2012 4.52% Bentley Arnage Sedan 2009 3.02% +762 /scratch/Teaching/cars/car_ims/010816.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 55.88% Hyundai Azera Sedan 2012 19.83% Hyundai Genesis Sedan 2012 12.1% Hyundai Sonata Sedan 2012 3.47% Infiniti QX56 SUV 2011 2.2% +763 /scratch/Teaching/cars/car_ims/007710.jpg Dodge Durango SUV 2007 Dodge Magnum Wagon 2008 38.17% Dodge Caliber Wagon 2012 29.94% Dodge Durango SUV 2007 29.0% Dodge Durango SUV 2012 2.25% Chevrolet HHR SS 2010 0.38% +764 /scratch/Teaching/cars/car_ims/006589.jpg Chrysler PT Cruiser Convertible 2008 Chrysler PT Cruiser Convertible 2008 99.9% Chrysler Town and Country Minivan 2012 0.1% Mercedes-Benz E-Class Sedan 2012 0.0% Cadillac SRX SUV 2012 0.0% Chrysler Aspen SUV 2009 0.0% +765 /scratch/Teaching/cars/car_ims/008316.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 99.49% Ferrari FF Coupe 2012 0.24% Ferrari 458 Italia Coupe 2012 0.15% Jaguar XK XKR 2012 0.07% Aston Martin V8 Vantage Coupe 2012 0.03% +766 /scratch/Teaching/cars/car_ims/006133.jpg Chrysler Aspen SUV 2009 Dodge Durango SUV 2007 61.55% Isuzu Ascender SUV 2008 31.94% Volvo XC90 SUV 2007 2.25% Jeep Liberty SUV 2012 1.67% Chrysler Aspen SUV 2009 0.52% +767 /scratch/Teaching/cars/car_ims/002056.jpg BMW ActiveHybrid 5 Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 99.78% BMW M5 Sedan 2010 0.11% Acura TL Type-S 2008 0.05% BMW 3 Series Wagon 2012 0.03% Acura RL Sedan 2012 0.03% +768 /scratch/Teaching/cars/car_ims/012823.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 96.79% Mercedes-Benz 300-Class Convertible 1993 2.49% Audi 100 Wagon 1994 0.38% Volvo 240 Sedan 1993 0.33% Dodge Magnum Wagon 2008 0.01% +769 /scratch/Teaching/cars/car_ims/001121.jpg Audi TTS Coupe 2012 Audi TT RS Coupe 2012 64.96% Audi TTS Coupe 2012 22.4% Audi R8 Coupe 2012 8.6% Audi TT Hatchback 2011 2.93% Audi S4 Sedan 2012 0.62% +770 /scratch/Teaching/cars/car_ims/013075.jpg McLaren MP4-12C Coupe 2012 Lamborghini Aventador Coupe 2012 64.3% McLaren MP4-12C Coupe 2012 29.7% Spyker C8 Coupe 2009 2.66% Ford GT Coupe 2006 2.51% Spyker C8 Convertible 2009 0.45% +771 /scratch/Teaching/cars/car_ims/012908.jpg MINI Cooper Roadster Convertible 2012 MINI Cooper Roadster Convertible 2012 96.3% Cadillac CTS-V Sedan 2012 3.25% Spyker C8 Convertible 2009 0.31% Bentley Mulsanne Sedan 2011 0.09% Bentley Continental GT Coupe 2012 0.03% +772 /scratch/Teaching/cars/car_ims/005847.jpg Chevrolet Malibu Sedan 2007 Nissan Juke Hatchback 2012 23.58% Ford Edge SUV 2012 10.38% Suzuki Kizashi Sedan 2012 8.55% Cadillac CTS-V Sedan 2012 8.03% Dodge Charger Sedan 2012 7.46% +773 /scratch/Teaching/cars/car_ims/012960.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 88.96% Bentley Continental Supersports Conv. Convertible 2012 3.28% Bentley Continental Flying Spur Sedan 2007 2.15% Chevrolet Corvette Ron Fellows Edition Z06 2007 1.02% FIAT 500 Convertible 2012 0.9% +774 /scratch/Teaching/cars/car_ims/000627.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin V8 Vantage Coupe 2012 55.42% Aston Martin V8 Vantage Convertible 2012 25.14% Aston Martin Virage Convertible 2012 14.37% Jaguar XK XKR 2012 3.23% Fisker Karma Sedan 2012 1.13% +775 /scratch/Teaching/cars/car_ims/005723.jpg Chevrolet Express Van 2007 Chevrolet Express Cargo Van 2007 90.6% Chevrolet Express Van 2007 7.8% GMC Savana Van 2012 1.56% Dodge Sprinter Cargo Van 2009 0.03% Dodge Caravan Minivan 1997 0.01% +776 /scratch/Teaching/cars/car_ims/011465.jpg Hyundai Azera Sedan 2012 Hyundai Azera Sedan 2012 40.82% Hyundai Sonata Sedan 2012 29.57% Honda Accord Sedan 2012 21.67% Hyundai Genesis Sedan 2012 7.78% Honda Odyssey Minivan 2012 0.07% +777 /scratch/Teaching/cars/car_ims/004650.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 94.69% Hyundai Veracruz SUV 2012 2.39% Hyundai Tucson SUV 2012 2.08% Buick Enclave SUV 2012 0.46% GMC Acadia SUV 2012 0.24% +778 /scratch/Teaching/cars/car_ims/014580.jpg Rolls-Royce Phantom Sedan 2012 Rolls-Royce Phantom Sedan 2012 98.81% Chrysler 300 SRT-8 2010 0.47% Rolls-Royce Ghost Sedan 2012 0.37% Bentley Arnage Sedan 2009 0.26% Volvo 240 Sedan 1993 0.09% +779 /scratch/Teaching/cars/car_ims/006959.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 99.89% Ford Freestar Minivan 2007 0.06% Audi 100 Wagon 1994 0.04% Chevrolet Express Van 2007 0.0% Buick Rainier SUV 2007 0.0% +780 /scratch/Teaching/cars/car_ims/000632.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin V8 Vantage Coupe 2012 81.8% Aston Martin V8 Vantage Convertible 2012 18.01% Aston Martin Virage Convertible 2012 0.12% BMW M6 Convertible 2010 0.04% Jaguar XK XKR 2012 0.02% +781 /scratch/Teaching/cars/car_ims/003032.jpg BMW Z4 Convertible 2012 Ferrari California Convertible 2012 54.37% Ferrari 458 Italia Coupe 2012 29.53% Ferrari FF Coupe 2012 6.4% Chevrolet Corvette Convertible 2012 3.37% Ferrari 458 Italia Convertible 2012 2.07% +782 /scratch/Teaching/cars/car_ims/006364.jpg Chrysler 300 SRT-8 2010 Chevrolet Corvette Ron Fellows Edition Z06 2007 18.07% Ferrari 458 Italia Coupe 2012 13.33% Chevrolet Corvette ZR1 2012 11.62% Ferrari FF Coupe 2012 10.81% Jaguar XK XKR 2012 9.4% +783 /scratch/Teaching/cars/car_ims/007496.jpg Dodge Magnum Wagon 2008 Dodge Magnum Wagon 2008 99.86% Dodge Charger SRT-8 2009 0.1% Chevrolet HHR SS 2010 0.02% Dodge Caliber Wagon 2012 0.01% Dodge Charger Sedan 2012 0.0% +784 /scratch/Teaching/cars/car_ims/008279.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 59.28% Chevrolet Corvette Convertible 2012 20.69% Ferrari 458 Italia Convertible 2012 13.91% Ferrari 458 Italia Coupe 2012 5.24% Ferrari FF Coupe 2012 0.29% +785 /scratch/Teaching/cars/car_ims/008861.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 72.86% Ford Ranger SuperCab 2011 8.11% Chevrolet Silverado 1500 Classic Extended Cab 2007 7.73% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 4.11% Chrysler Aspen SUV 2009 3.14% +786 /scratch/Teaching/cars/car_ims/010412.jpg Honda Odyssey Minivan 2012 Honda Accord Sedan 2012 53.71% Honda Odyssey Minivan 2012 35.9% Hyundai Elantra Sedan 2007 4.49% Acura TL Type-S 2008 2.55% Honda Odyssey Minivan 2007 1.41% +787 /scratch/Teaching/cars/car_ims/001203.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 39.04% Rolls-Royce Ghost Sedan 2012 18.78% Audi S4 Sedan 2007 7.62% Audi S6 Sedan 2011 7.3% Audi RS 4 Convertible 2008 6.12% +788 /scratch/Teaching/cars/car_ims/003807.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 84.81% Volkswagen Golf Hatchback 1991 13.16% Ford Focus Sedan 2007 1.24% Audi 100 Wagon 1994 0.55% Daewoo Nubira Wagon 2002 0.07% +789 /scratch/Teaching/cars/car_ims/008503.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 99.18% Bentley Continental Flying Spur Sedan 2007 0.28% Bentley Continental GT Coupe 2007 0.24% Porsche Panamera Sedan 2012 0.19% Dodge Challenger SRT8 2011 0.07% +790 /scratch/Teaching/cars/car_ims/012426.jpg Lamborghini Aventador Coupe 2012 Lamborghini Reventon Coupe 2008 99.22% Aston Martin V8 Vantage Coupe 2012 0.53% Lamborghini Aventador Coupe 2012 0.22% Audi R8 Coupe 2012 0.02% Aston Martin V8 Vantage Convertible 2012 0.01% +791 /scratch/Teaching/cars/car_ims/001176.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 84.08% Bugatti Veyron 16.4 Coupe 2009 8.07% Audi TTS Coupe 2012 3.84% Audi TT RS Coupe 2012 3.07% Audi TT Hatchback 2011 0.78% +792 /scratch/Teaching/cars/car_ims/002185.jpg BMW 1 Series Convertible 2012 BMW 1 Series Coupe 2012 30.67% BMW 3 Series Wagon 2012 18.78% BMW 1 Series Convertible 2012 18.11% BMW M5 Sedan 2010 7.61% Mitsubishi Lancer Sedan 2012 6.06% +793 /scratch/Teaching/cars/car_ims/003826.jpg Buick Rainier SUV 2007 Buick Rainier SUV 2007 99.94% Isuzu Ascender SUV 2008 0.05% Ford Freestar Minivan 2007 0.01% Jeep Liberty SUV 2012 0.0% Dodge Durango SUV 2007 0.0% +794 /scratch/Teaching/cars/car_ims/010670.jpg Honda Accord Sedan 2012 Hyundai Elantra Sedan 2007 88.67% Honda Accord Sedan 2012 9.68% Chevrolet Malibu Sedan 2007 0.49% Honda Odyssey Minivan 2012 0.34% Chevrolet Impala Sedan 2007 0.32% +795 /scratch/Teaching/cars/car_ims/007448.jpg Dodge Dakota Club Cab 2007 Dodge Dakota Club Cab 2007 45.74% Chevrolet Avalanche Crew Cab 2012 24.96% Dodge Dakota Crew Cab 2010 11.69% Cadillac Escalade EXT Crew Cab 2007 9.88% Isuzu Ascender SUV 2008 2.08% +796 /scratch/Teaching/cars/car_ims/000723.jpg Aston Martin V8 Vantage Coupe 2012 Aston Martin V8 Vantage Coupe 2012 95.24% Aston Martin V8 Vantage Convertible 2012 4.57% Jaguar XK XKR 2012 0.08% Aston Martin Virage Convertible 2012 0.05% Ferrari California Convertible 2012 0.04% +797 /scratch/Teaching/cars/car_ims/009184.jpg Ford GT Coupe 2006 Ford GT Coupe 2006 64.8% Lamborghini Aventador Coupe 2012 34.92% Spyker C8 Coupe 2009 0.09% Bugatti Veyron 16.4 Coupe 2009 0.07% Lamborghini Reventon Coupe 2008 0.05% +798 /scratch/Teaching/cars/car_ims/000066.jpg AM General Hummer SUV 2000 Mazda Tribute SUV 2011 32.18% Land Rover LR2 SUV 2012 20.17% GMC Yukon Hybrid SUV 2012 8.21% Chevrolet Tahoe Hybrid SUV 2012 4.32% Ford Expedition EL SUV 2009 3.35% +799 /scratch/Teaching/cars/car_ims/012992.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 99.53% Land Rover LR2 SUV 2012 0.27% Suzuki SX4 Hatchback 2012 0.19% Scion xD Hatchback 2012 0.01% Toyota Sequoia SUV 2012 0.0% +800 /scratch/Teaching/cars/car_ims/013728.jpg Mitsubishi Lancer Sedan 2012 Chevrolet Cobalt SS 2010 39.87% Mitsubishi Lancer Sedan 2012 36.04% Honda Accord Coupe 2012 15.24% Chevrolet Malibu Hybrid Sedan 2010 3.14% Chevrolet Monte Carlo Coupe 2007 2.25% +801 /scratch/Teaching/cars/car_ims/009624.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 57.07% Hyundai Tucson SUV 2012 42.7% Acura ZDX Hatchback 2012 0.09% Hyundai Veracruz SUV 2012 0.05% Hyundai Veloster Hatchback 2012 0.04% +802 /scratch/Teaching/cars/car_ims/008594.jpg Ford F-450 Super Duty Crew Cab 2012 Dodge Ram Pickup 3500 Quad Cab 2009 31.71% HUMMER H3T Crew Cab 2010 9.61% Dodge Dakota Crew Cab 2010 6.74% Dodge Ram Pickup 3500 Crew Cab 2010 5.86% GMC Canyon Extended Cab 2012 3.9% +803 /scratch/Teaching/cars/car_ims/005287.jpg Chevrolet Cobalt SS 2010 Chevrolet Cobalt SS 2010 99.42% Acura Integra Type R 2001 0.32% Dodge Charger Sedan 2012 0.08% Chevrolet Monte Carlo Coupe 2007 0.07% Lamborghini Diablo Coupe 2001 0.05% +804 /scratch/Teaching/cars/car_ims/000508.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 92.88% Buick Verano Sedan 2012 2.36% Honda Accord Sedan 2012 0.98% Volkswagen Golf Hatchback 2012 0.87% Hyundai Veracruz SUV 2012 0.66% +805 /scratch/Teaching/cars/car_ims/005798.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Impala Sedan 2007 50.54% Chevrolet Monte Carlo Coupe 2007 39.17% Lincoln Town Car Sedan 2011 5.65% Chevrolet Malibu Sedan 2007 4.63% Ford Focus Sedan 2007 0.0% +806 /scratch/Teaching/cars/car_ims/013129.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 59.97% Lamborghini Aventador Coupe 2012 31.43% Spyker C8 Coupe 2009 6.12% Ford GT Coupe 2006 1.12% Ferrari 458 Italia Coupe 2012 0.62% +807 /scratch/Teaching/cars/car_ims/008759.jpg Ford Mustang Convertible 2007 Ford Mustang Convertible 2007 34.65% BMW X5 SUV 2007 18.09% Buick Enclave SUV 2012 15.16% Chrysler 300 SRT-8 2010 13.45% Audi 100 Wagon 1994 7.13% +808 /scratch/Teaching/cars/car_ims/010445.jpg Honda Odyssey Minivan 2007 Chrysler Town and Country Minivan 2012 10.55% Ram C/V Cargo Van Minivan 2012 9.79% Dodge Caliber Wagon 2012 9.0% Volvo XC90 SUV 2007 7.01% GMC Acadia SUV 2012 3.81% +809 /scratch/Teaching/cars/car_ims/005005.jpg Chevrolet Tahoe Hybrid SUV 2012 Toyota 4Runner SUV 2012 33.41% HUMMER H2 SUT Crew Cab 2009 14.97% Land Rover LR2 SUV 2012 12.02% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 3.45% HUMMER H3T Crew Cab 2010 2.85% +810 /scratch/Teaching/cars/car_ims/015755.jpg Volkswagen Golf Hatchback 1991 Volkswagen Golf Hatchback 1991 98.43% Audi V8 Sedan 1994 0.52% Audi 100 Wagon 1994 0.45% Chevrolet Express Van 2007 0.14% GMC Savana Van 2012 0.12% +811 /scratch/Teaching/cars/car_ims/005182.jpg Chevrolet Express Cargo Van 2007 Chevrolet Express Cargo Van 2007 68.31% GMC Savana Van 2012 23.36% Chevrolet Express Van 2007 8.32% Dodge Sprinter Cargo Van 2009 0.0% Geo Metro Convertible 1993 0.0% +812 /scratch/Teaching/cars/car_ims/003909.jpg Buick Verano Sedan 2012 Hyundai Azera Sedan 2012 61.6% Toyota Camry Sedan 2012 12.36% Hyundai Sonata Sedan 2012 10.13% Hyundai Sonata Hybrid Sedan 2012 3.97% Hyundai Elantra Sedan 2007 3.11% +813 /scratch/Teaching/cars/car_ims/004818.jpg Chevrolet HHR SS 2010 Ram C/V Cargo Van Minivan 2012 14.14% Daewoo Nubira Wagon 2002 11.07% Chevrolet Malibu Sedan 2007 10.72% Suzuki Aerio Sedan 2007 6.73% Suzuki SX4 Sedan 2012 5.07% +814 /scratch/Teaching/cars/car_ims/005640.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chevrolet Silverado 1500 Classic Extended Cab 2007 100.0% Chevrolet Silverado 2500HD Regular Cab 2012 0.0% Ford Ranger SuperCab 2011 0.0% Chevrolet Silverado 1500 Extended Cab 2012 0.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.0% +815 /scratch/Teaching/cars/car_ims/011143.jpg Hyundai Elantra Sedan 2007 Buick Verano Sedan 2012 16.76% Chevrolet Sonic Sedan 2012 10.87% Mitsubishi Lancer Sedan 2012 5.83% Honda Odyssey Minivan 2012 5.02% Hyundai Accent Sedan 2012 4.99% +816 /scratch/Teaching/cars/car_ims/009085.jpg Ford Ranger SuperCab 2011 Ford Ranger SuperCab 2011 96.03% Ford F-150 Regular Cab 2007 1.92% Ford E-Series Wagon Van 2012 1.65% Ford F-150 Regular Cab 2012 0.24% GMC Canyon Extended Cab 2012 0.12% +817 /scratch/Teaching/cars/car_ims/011897.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 100.0% Jeep Liberty SUV 2012 0.0% Jeep Wrangler SUV 2012 0.0% Jeep Compass SUV 2012 0.0% GMC Yukon Hybrid SUV 2012 0.0% +818 /scratch/Teaching/cars/car_ims/013878.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 94.77% Jeep Liberty SUV 2012 1.99% Bentley Arnage Sedan 2009 0.93% Bentley Continental Supersports Conv. Convertible 2012 0.55% MINI Cooper Roadster Convertible 2012 0.54% +819 /scratch/Teaching/cars/car_ims/008951.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 99.98% Honda Odyssey Minivan 2012 0.01% Hyundai Veracruz SUV 2012 0.01% Hyundai Santa Fe SUV 2012 0.0% Land Rover LR2 SUV 2012 0.0% +820 /scratch/Teaching/cars/car_ims/005235.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 59.3% Chevrolet Silverado 1500 Extended Cab 2012 14.29% Chevrolet Silverado 1500 Regular Cab 2012 12.16% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 6.66% Chevrolet Tahoe Hybrid SUV 2012 2.07% +821 /scratch/Teaching/cars/car_ims/009642.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 100.0% Toyota 4Runner SUV 2012 0.0% Cadillac Escalade EXT Crew Cab 2007 0.0% Land Rover LR2 SUV 2012 0.0% Cadillac SRX SUV 2012 0.0% +822 /scratch/Teaching/cars/car_ims/015583.jpg Volkswagen Golf Hatchback 2012 Suzuki SX4 Sedan 2012 57.92% Suzuki Aerio Sedan 2007 9.78% Suzuki Kizashi Sedan 2012 7.83% Volkswagen Golf Hatchback 2012 4.53% Buick Verano Sedan 2012 3.22% +823 /scratch/Teaching/cars/car_ims/007324.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 99.56% Dodge Dakota Club Cab 2007 0.16% Dodge Ram Pickup 3500 Quad Cab 2009 0.1% Isuzu Ascender SUV 2008 0.06% HUMMER H3T Crew Cab 2010 0.04% +824 /scratch/Teaching/cars/car_ims/004568.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Chevrolet Corvette Ron Fellows Edition Z06 2007 98.96% Lamborghini Reventon Coupe 2008 0.4% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.37% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.13% Aston Martin V8 Vantage Convertible 2012 0.03% +825 /scratch/Teaching/cars/car_ims/009680.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 99.97% Toyota 4Runner SUV 2012 0.01% Chevrolet Avalanche Crew Cab 2012 0.01% Jeep Grand Cherokee SUV 2012 0.0% Jeep Compass SUV 2012 0.0% +826 /scratch/Teaching/cars/car_ims/002483.jpg BMW 6 Series Convertible 2007 BMW 6 Series Convertible 2007 61.14% BMW M6 Convertible 2010 38.54% Jaguar XK XKR 2012 0.14% Acura TL Type-S 2008 0.13% BMW Z4 Convertible 2012 0.03% +827 /scratch/Teaching/cars/car_ims/012401.jpg Lamborghini Aventador Coupe 2012 Audi TT RS Coupe 2012 57.17% Bugatti Veyron 16.4 Convertible 2009 12.37% Audi TT Hatchback 2011 11.86% Bugatti Veyron 16.4 Coupe 2009 6.48% Audi R8 Coupe 2012 3.55% +828 /scratch/Teaching/cars/car_ims/015111.jpg Suzuki SX4 Sedan 2012 Daewoo Nubira Wagon 2002 36.75% Suzuki Aerio Sedan 2007 27.59% Suzuki SX4 Sedan 2012 23.18% Honda Odyssey Minivan 2007 5.18% Acura ZDX Hatchback 2012 1.54% +829 /scratch/Teaching/cars/car_ims/006490.jpg Chrysler Crossfire Convertible 2008 Chrysler Crossfire Convertible 2008 27.86% Mercedes-Benz C-Class Sedan 2012 21.95% Nissan 240SX Coupe 1998 11.81% Ford Mustang Convertible 2007 10.34% Chevrolet Camaro Convertible 2012 4.13% +830 /scratch/Teaching/cars/car_ims/009972.jpg GMC Canyon Extended Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 53.45% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 14.59% GMC Canyon Extended Cab 2012 9.49% Chevrolet Silverado 2500HD Regular Cab 2012 9.24% Chevrolet Silverado 1500 Regular Cab 2012 7.56% +831 /scratch/Teaching/cars/car_ims/015504.jpg Toyota 4Runner SUV 2012 Toyota 4Runner SUV 2012 92.5% GMC Terrain SUV 2012 3.24% GMC Acadia SUV 2012 3.05% Jeep Grand Cherokee SUV 2012 0.96% Chevrolet Traverse SUV 2012 0.11% +832 /scratch/Teaching/cars/car_ims/000020.jpg AM General Hummer SUV 2000 HUMMER H2 SUT Crew Cab 2009 44.18% AM General Hummer SUV 2000 28.49% Jeep Wrangler SUV 2012 23.77% HUMMER H3T Crew Cab 2010 2.28% GMC Canyon Extended Cab 2012 0.57% +833 /scratch/Teaching/cars/car_ims/013888.jpg Nissan NV Passenger Van 2012 Dodge Ram Pickup 3500 Quad Cab 2009 21.05% Dodge Ram Pickup 3500 Crew Cab 2010 12.71% Dodge Durango SUV 2007 7.92% Volvo XC90 SUV 2007 7.05% Jeep Liberty SUV 2012 6.63% +834 /scratch/Teaching/cars/car_ims/014080.jpg Nissan 240SX Coupe 1998 Nissan 240SX Coupe 1998 91.54% Eagle Talon Hatchback 1998 2.83% Plymouth Neon Coupe 1999 2.64% Dodge Caravan Minivan 1997 1.03% Honda Accord Coupe 2012 0.97% +835 /scratch/Teaching/cars/car_ims/006105.jpg Chrysler Aspen SUV 2009 Chrysler Aspen SUV 2009 43.72% Dodge Durango SUV 2007 31.92% Cadillac Escalade EXT Crew Cab 2007 10.05% Chrysler Town and Country Minivan 2012 2.8% Ram C/V Cargo Van Minivan 2012 2.09% +836 /scratch/Teaching/cars/car_ims/000567.jpg Acura ZDX Hatchback 2012 Hyundai Sonata Hybrid Sedan 2012 15.66% Hyundai Veloster Hatchback 2012 14.81% Buick Regal GS 2012 7.69% Jaguar XK XKR 2012 5.91% Tesla Model S Sedan 2012 5.2% +837 /scratch/Teaching/cars/car_ims/004196.jpg Cadillac SRX SUV 2012 Cadillac SRX SUV 2012 61.76% Hyundai Veracruz SUV 2012 15.26% Acura ZDX Hatchback 2012 6.11% Honda Accord Sedan 2012 4.68% Chevrolet Traverse SUV 2012 2.88% +838 /scratch/Teaching/cars/car_ims/009663.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 100.0% Toyota 4Runner SUV 2012 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% Jeep Grand Cherokee SUV 2012 0.0% Jeep Compass SUV 2012 0.0% +839 /scratch/Teaching/cars/car_ims/001143.jpg Audi R8 Coupe 2012 Ford GT Coupe 2006 90.76% Spyker C8 Convertible 2009 5.79% Spyker C8 Coupe 2009 1.73% Bugatti Veyron 16.4 Coupe 2009 1.59% Chevrolet Corvette ZR1 2012 0.06% +840 /scratch/Teaching/cars/car_ims/009447.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 99.59% Plymouth Neon Coupe 1999 0.28% Daewoo Nubira Wagon 2002 0.1% Suzuki Aerio Sedan 2007 0.01% Chrysler Sebring Convertible 2010 0.01% +841 /scratch/Teaching/cars/car_ims/015480.jpg Toyota Corolla Sedan 2012 Hyundai Elantra Sedan 2007 39.94% Buick Verano Sedan 2012 34.32% Hyundai Accent Sedan 2012 9.07% Hyundai Sonata Sedan 2012 4.41% Toyota Corolla Sedan 2012 2.79% +842 /scratch/Teaching/cars/car_ims/010121.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 98.89% Lamborghini Gallardo LP 570-4 Superleggera 2012 1.08% Acura Integra Type R 2001 0.02% Plymouth Neon Coupe 1999 0.0% Lamborghini Diablo Coupe 2001 0.0% +843 /scratch/Teaching/cars/car_ims/007070.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 91.07% GMC Canyon Extended Cab 2012 6.34% Ford F-450 Super Duty Crew Cab 2012 1.42% Dodge Ram Pickup 3500 Crew Cab 2010 0.47% Ford Ranger SuperCab 2011 0.25% +844 /scratch/Teaching/cars/car_ims/004134.jpg Cadillac SRX SUV 2012 Cadillac SRX SUV 2012 79.68% GMC Acadia SUV 2012 20.04% Chevrolet Traverse SUV 2012 0.11% Cadillac Escalade EXT Crew Cab 2007 0.09% Dodge Caliber Wagon 2012 0.05% +845 /scratch/Teaching/cars/car_ims/013374.jpg Mercedes-Benz SL-Class Coupe 2009 BMW Z4 Convertible 2012 43.16% BMW M6 Convertible 2010 40.9% BMW 6 Series Convertible 2007 6.36% Jaguar XK XKR 2012 4.89% Audi RS 4 Convertible 2008 0.75% +846 /scratch/Teaching/cars/car_ims/001167.jpg Audi R8 Coupe 2012 Audi R8 Coupe 2012 99.92% Lamborghini Reventon Coupe 2008 0.03% BMW M6 Convertible 2010 0.02% Bugatti Veyron 16.4 Coupe 2009 0.01% Lamborghini Aventador Coupe 2012 0.01% +847 /scratch/Teaching/cars/car_ims/006421.jpg Chrysler 300 SRT-8 2010 Lincoln Town Car Sedan 2011 38.14% Chevrolet Malibu Sedan 2007 26.06% Ford Freestar Minivan 2007 22.6% Ram C/V Cargo Van Minivan 2012 8.91% Chrysler Town and Country Minivan 2012 1.54% +848 /scratch/Teaching/cars/car_ims/002925.jpg BMW M6 Convertible 2010 BMW 6 Series Convertible 2007 53.39% BMW M6 Convertible 2010 17.64% Acura TL Type-S 2008 10.44% Chevrolet Monte Carlo Coupe 2007 8.73% Jaguar XK XKR 2012 6.85% +849 /scratch/Teaching/cars/car_ims/009373.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 99.47% Ford F-150 Regular Cab 2012 0.48% GMC Yukon Hybrid SUV 2012 0.01% Ford Freestar Minivan 2007 0.01% Ford Ranger SuperCab 2011 0.01% +850 /scratch/Teaching/cars/car_ims/003176.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental GT Coupe 2007 28.64% Bentley Continental Flying Spur Sedan 2007 20.7% Fisker Karma Sedan 2012 15.28% Chevrolet Malibu Hybrid Sedan 2010 5.04% Dodge Challenger SRT8 2011 4.88% +851 /scratch/Teaching/cars/car_ims/007264.jpg Dodge Journey SUV 2012 Dodge Journey SUV 2012 45.15% Chevrolet HHR SS 2010 12.85% Chevrolet Malibu Sedan 2007 11.76% Dodge Magnum Wagon 2008 11.14% Dodge Durango SUV 2012 8.27% +852 /scratch/Teaching/cars/car_ims/015908.jpg Volvo C30 Hatchback 2012 Spyker C8 Coupe 2009 40.34% smart fortwo Convertible 2012 36.62% Spyker C8 Convertible 2009 16.04% Volvo C30 Hatchback 2012 3.1% Hyundai Veloster Hatchback 2012 2.47% +853 /scratch/Teaching/cars/car_ims/014023.jpg Nissan 240SX Coupe 1998 Nissan 240SX Coupe 1998 91.13% Dodge Charger SRT-8 2009 5.82% Honda Accord Coupe 2012 1.2% Ford Mustang Convertible 2007 0.74% BMW 3 Series Sedan 2012 0.57% +854 /scratch/Teaching/cars/car_ims/015655.jpg Volkswagen Golf Hatchback 2012 Acura ZDX Hatchback 2012 34.39% Volkswagen Golf Hatchback 2012 13.19% Ford Fiesta Sedan 2012 8.63% Nissan Leaf Hatchback 2012 7.5% Hyundai Veracruz SUV 2012 5.58% +855 /scratch/Teaching/cars/car_ims/007139.jpg Dodge Sprinter Cargo Van 2009 Dodge Sprinter Cargo Van 2009 92.52% Mercedes-Benz Sprinter Van 2012 5.84% Ram C/V Cargo Van Minivan 2012 0.84% Nissan NV Passenger Van 2012 0.35% Chevrolet Express Cargo Van 2007 0.15% +856 /scratch/Teaching/cars/car_ims/006712.jpg Dodge Caliber Wagon 2012 Suzuki SX4 Hatchback 2012 56.85% Dodge Caliber Wagon 2012 26.22% Mazda Tribute SUV 2011 7.53% Suzuki SX4 Sedan 2012 5.31% Ram C/V Cargo Van Minivan 2012 2.29% +857 /scratch/Teaching/cars/car_ims/006965.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 93.1% Dodge Durango SUV 2007 6.86% Dodge Ram Pickup 3500 Quad Cab 2009 0.02% Chrysler Aspen SUV 2009 0.01% Volvo XC90 SUV 2007 0.01% +858 /scratch/Teaching/cars/car_ims/008228.jpg Ferrari FF Coupe 2012 Ferrari FF Coupe 2012 98.14% Jaguar XK XKR 2012 0.9% BMW 3 Series Sedan 2012 0.43% Honda Accord Coupe 2012 0.24% Dodge Charger Sedan 2012 0.1% +859 /scratch/Teaching/cars/car_ims/001966.jpg Audi S4 Sedan 2007 Audi S4 Sedan 2007 32.83% Audi S5 Coupe 2012 10.09% Audi A5 Coupe 2012 9.6% Bentley Continental GT Coupe 2012 9.48% Bentley Continental GT Coupe 2007 5.73% +860 /scratch/Teaching/cars/car_ims/000398.jpg Acura TSX Sedan 2012 Acura TSX Sedan 2012 46.86% Acura TL Sedan 2012 18.5% Acura RL Sedan 2012 17.05% Acura TL Type-S 2008 13.76% Mitsubishi Lancer Sedan 2012 1.95% +861 /scratch/Teaching/cars/car_ims/010351.jpg HUMMER H2 SUT Crew Cab 2009 HUMMER H2 SUT Crew Cab 2009 57.38% AM General Hummer SUV 2000 28.33% HUMMER H3T Crew Cab 2010 5.54% Jeep Wrangler SUV 2012 4.62% Land Rover LR2 SUV 2012 0.68% +862 /scratch/Teaching/cars/car_ims/012458.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 Lamborghini Gallardo LP 570-4 Superleggera 2012 99.94% Acura Integra Type R 2001 0.03% Lamborghini Diablo Coupe 2001 0.02% Bentley Continental Supersports Conv. Convertible 2012 0.0% AM General Hummer SUV 2000 0.0% +863 /scratch/Teaching/cars/car_ims/011103.jpg Hyundai Elantra Sedan 2007 Hyundai Sonata Sedan 2012 81.07% Hyundai Elantra Sedan 2007 18.7% Honda Accord Sedan 2012 0.12% Honda Odyssey Minivan 2012 0.06% Hyundai Veracruz SUV 2012 0.05% +864 /scratch/Teaching/cars/car_ims/004419.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Ron Fellows Edition Z06 2007 99.79% Chevrolet Corvette Convertible 2012 0.14% Chevrolet Corvette ZR1 2012 0.05% Jaguar XK XKR 2012 0.01% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.0% +865 /scratch/Teaching/cars/car_ims/006967.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 52.15% Dodge Ram Pickup 3500 Quad Cab 2009 44.12% HUMMER H3T Crew Cab 2010 1.14% Ford F-450 Super Duty Crew Cab 2012 0.92% HUMMER H2 SUT Crew Cab 2009 0.86% +866 /scratch/Teaching/cars/car_ims/004018.jpg Buick Enclave SUV 2012 Chevrolet Traverse SUV 2012 32.01% Hyundai Veracruz SUV 2012 27.54% GMC Acadia SUV 2012 18.01% Cadillac SRX SUV 2012 13.03% Buick Enclave SUV 2012 4.54% +867 /scratch/Teaching/cars/car_ims/012576.jpg Lamborghini Diablo Coupe 2001 Lamborghini Diablo Coupe 2001 80.61% Dodge Challenger SRT8 2011 9.79% Acura Integra Type R 2001 8.42% Ford Mustang Convertible 2007 0.74% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.15% +868 /scratch/Teaching/cars/car_ims/013596.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 86.51% Dodge Sprinter Cargo Van 2009 13.49% Ram C/V Cargo Van Minivan 2012 0.0% Nissan NV Passenger Van 2012 0.0% Chevrolet Express Cargo Van 2007 0.0% +869 /scratch/Teaching/cars/car_ims/011106.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 99.98% Chrysler Sebring Convertible 2010 0.01% Hyundai Sonata Sedan 2012 0.01% Acura RL Sedan 2012 0.0% Honda Accord Sedan 2012 0.0% +870 /scratch/Teaching/cars/car_ims/002486.jpg BMW 6 Series Convertible 2007 Rolls-Royce Phantom Drophead Coupe Convertible 2012 33.18% Bentley Continental Supersports Conv. Convertible 2012 12.56% BMW 6 Series Convertible 2007 9.1% Fisker Karma Sedan 2012 5.93% Aston Martin V8 Vantage Convertible 2012 5.64% +871 /scratch/Teaching/cars/car_ims/011343.jpg Hyundai Sonata Sedan 2012 Hyundai Sonata Sedan 2012 49.49% Honda Accord Sedan 2012 43.63% Hyundai Elantra Sedan 2007 2.33% Honda Odyssey Minivan 2012 2.16% Hyundai Azera Sedan 2012 1.48% +872 /scratch/Teaching/cars/car_ims/011861.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 81.59% Jeep Compass SUV 2012 16.04% HUMMER H3T Crew Cab 2010 1.04% GMC Terrain SUV 2012 0.8% Jeep Grand Cherokee SUV 2012 0.28% +873 /scratch/Teaching/cars/car_ims/012238.jpg Jeep Compass SUV 2012 BMW 1 Series Convertible 2012 21.81% BMW M6 Convertible 2010 21.59% BMW 3 Series Wagon 2012 18.92% BMW Z4 Convertible 2012 16.08% BMW 6 Series Convertible 2007 6.29% +874 /scratch/Teaching/cars/car_ims/005355.jpg Chevrolet Cobalt SS 2010 Hyundai Elantra Touring Hatchback 2012 37.09% Chevrolet Cobalt SS 2010 18.2% Volkswagen Golf Hatchback 2012 11.35% Hyundai Veloster Hatchback 2012 8.61% Suzuki Kizashi Sedan 2012 6.07% +875 /scratch/Teaching/cars/car_ims/003970.jpg Buick Enclave SUV 2012 Chevrolet Traverse SUV 2012 56.42% Cadillac SRX SUV 2012 15.47% Hyundai Veracruz SUV 2012 12.97% GMC Acadia SUV 2012 10.97% Buick Enclave SUV 2012 3.97% +876 /scratch/Teaching/cars/car_ims/003067.jpg BMW Z4 Convertible 2012 BMW Z4 Convertible 2012 53.46% BMW M6 Convertible 2010 23.22% BMW M3 Coupe 2012 13.6% BMW 6 Series Convertible 2007 8.63% BMW 1 Series Convertible 2012 0.49% +877 /scratch/Teaching/cars/car_ims/009449.jpg Ford Focus Sedan 2007 Daewoo Nubira Wagon 2002 15.03% Audi 100 Wagon 1994 11.88% Dodge Caravan Minivan 1997 11.41% Suzuki Aerio Sedan 2007 9.81% Ford Focus Sedan 2007 9.04% +878 /scratch/Teaching/cars/car_ims/004934.jpg Chevrolet Impala Sedan 2007 Chevrolet Impala Sedan 2007 90.43% Chevrolet Monte Carlo Coupe 2007 8.3% Plymouth Neon Coupe 1999 1.16% Lincoln Town Car Sedan 2011 0.07% Ford Focus Sedan 2007 0.02% +879 /scratch/Teaching/cars/car_ims/004901.jpg Chevrolet Impala Sedan 2007 Chevrolet Impala Sedan 2007 28.83% Chevrolet Monte Carlo Coupe 2007 21.9% Honda Accord Coupe 2012 13.98% Hyundai Sonata Hybrid Sedan 2012 7.23% Acura TL Sedan 2012 4.77% +880 /scratch/Teaching/cars/car_ims/001385.jpg Audi 100 Wagon 1994 Audi 100 Wagon 1994 79.32% Mercedes-Benz Sprinter Van 2012 6.7% Daewoo Nubira Wagon 2002 4.06% Volkswagen Golf Hatchback 1991 2.11% Ford Freestar Minivan 2007 1.86% +881 /scratch/Teaching/cars/car_ims/005731.jpg Chevrolet Express Van 2007 Chevrolet Express Cargo Van 2007 58.79% Chevrolet Express Van 2007 28.16% GMC Savana Van 2012 12.95% Dodge Sprinter Cargo Van 2009 0.03% Nissan NV Passenger Van 2012 0.02% +882 /scratch/Teaching/cars/car_ims/014791.jpg Spyker C8 Coupe 2009 Rolls-Royce Phantom Sedan 2012 53.81% Dodge Challenger SRT8 2011 9.97% Bentley Arnage Sedan 2009 6.98% Rolls-Royce Phantom Drophead Coupe Convertible 2012 6.46% Bentley Mulsanne Sedan 2011 4.51% +883 /scratch/Teaching/cars/car_ims/006018.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 53.05% Chevrolet Silverado 1500 Regular Cab 2012 31.99% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 7.56% Chevrolet Silverado 2500HD Regular Cab 2012 4.46% GMC Canyon Extended Cab 2012 2.59% +884 /scratch/Teaching/cars/car_ims/000789.jpg Aston Martin Virage Convertible 2012 Aston Martin Virage Convertible 2012 61.61% Fisker Karma Sedan 2012 29.56% Aston Martin V8 Vantage Coupe 2012 4.8% Tesla Model S Sedan 2012 1.79% Aston Martin Virage Coupe 2012 1.14% +885 /scratch/Teaching/cars/car_ims/001233.jpg Audi V8 Sedan 1994 Audi 100 Sedan 1994 83.51% Audi V8 Sedan 1994 15.57% Audi 100 Wagon 1994 0.65% Volkswagen Golf Hatchback 1991 0.21% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.06% +886 /scratch/Teaching/cars/car_ims/014230.jpg Porsche Panamera Sedan 2012 Porsche Panamera Sedan 2012 62.09% Infiniti G Coupe IPL 2012 27.19% Fisker Karma Sedan 2012 1.83% Tesla Model S Sedan 2012 1.26% Bentley Continental GT Coupe 2007 1.05% +887 /scratch/Teaching/cars/car_ims/007378.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 43.57% Dodge Caliber Wagon 2012 30.32% Dodge Caliber Wagon 2007 10.27% Dodge Dakota Club Cab 2007 6.1% Dodge Durango SUV 2007 5.49% +888 /scratch/Teaching/cars/car_ims/007154.jpg Dodge Sprinter Cargo Van 2009 Mercedes-Benz Sprinter Van 2012 85.5% Dodge Sprinter Cargo Van 2009 8.41% Ram C/V Cargo Van Minivan 2012 6.01% Chrysler Town and Country Minivan 2012 0.08% Chrysler Aspen SUV 2009 0.0% +889 /scratch/Teaching/cars/car_ims/009739.jpg GMC Savana Van 2012 GMC Savana Van 2012 68.86% Chevrolet Express Cargo Van 2007 19.28% Chevrolet Express Van 2007 11.85% Volkswagen Golf Hatchback 1991 0.0% Nissan NV Passenger Van 2012 0.0% +890 /scratch/Teaching/cars/car_ims/014264.jpg Porsche Panamera Sedan 2012 Porsche Panamera Sedan 2012 65.61% Tesla Model S Sedan 2012 16.12% Fisker Karma Sedan 2012 5.64% BMW M5 Sedan 2010 3.52% Infiniti G Coupe IPL 2012 2.3% +891 /scratch/Teaching/cars/car_ims/012998.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 92.21% Jeep Grand Cherokee SUV 2012 6.14% Jeep Compass SUV 2012 1.03% Jeep Patriot SUV 2012 0.2% GMC Acadia SUV 2012 0.18% +892 /scratch/Teaching/cars/car_ims/015916.jpg Volvo C30 Hatchback 2012 Volvo C30 Hatchback 2012 67.64% FIAT 500 Abarth 2012 12.92% Spyker C8 Coupe 2009 8.17% Spyker C8 Convertible 2009 3.14% Aston Martin Virage Coupe 2012 1.73% +893 /scratch/Teaching/cars/car_ims/001148.jpg Audi R8 Coupe 2012 Audi TTS Coupe 2012 39.72% Audi R8 Coupe 2012 15.55% Mitsubishi Lancer Sedan 2012 11.86% Dodge Charger Sedan 2012 4.21% Aston Martin Virage Coupe 2012 2.82% +894 /scratch/Teaching/cars/car_ims/007607.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 99.67% Dodge Charger SRT-8 2009 0.32% Chrysler 300 SRT-8 2010 0.01% Rolls-Royce Ghost Sedan 2012 0.0% Dodge Charger Sedan 2012 0.0% +895 /scratch/Teaching/cars/car_ims/009813.jpg GMC Yukon Hybrid SUV 2012 GMC Yukon Hybrid SUV 2012 99.98% Chevrolet Tahoe Hybrid SUV 2012 0.02% Cadillac Escalade EXT Crew Cab 2007 0.01% Chevrolet Avalanche Crew Cab 2012 0.0% Ford F-150 Regular Cab 2007 0.0% +896 /scratch/Teaching/cars/car_ims/004076.jpg Cadillac CTS-V Sedan 2012 Cadillac CTS-V Sedan 2012 92.75% Cadillac SRX SUV 2012 2.94% Suzuki Kizashi Sedan 2012 2.3% Chevrolet Sonic Sedan 2012 0.96% Ford Edge SUV 2012 0.28% +897 /scratch/Teaching/cars/car_ims/003788.jpg Buick Regal GS 2012 Buick Verano Sedan 2012 88.65% Buick Regal GS 2012 10.41% Chevrolet Sonic Sedan 2012 0.6% BMW X6 SUV 2012 0.24% BMW X3 SUV 2012 0.06% +898 /scratch/Teaching/cars/car_ims/014521.jpg Rolls-Royce Phantom Sedan 2012 Rolls-Royce Phantom Sedan 2012 57.46% Rolls-Royce Ghost Sedan 2012 27.58% Chrysler 300 SRT-8 2010 5.38% Rolls-Royce Phantom Drophead Coupe Convertible 2012 3.15% Dodge Challenger SRT8 2011 1.3% +899 /scratch/Teaching/cars/car_ims/009619.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 100.0% Hyundai Tucson SUV 2012 0.0% Scion xD Hatchback 2012 0.0% Hyundai Accent Sedan 2012 0.0% Acura ZDX Hatchback 2012 0.0% +900 /scratch/Teaching/cars/car_ims/009020.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 100.0% Hyundai Veracruz SUV 2012 0.0% Toyota 4Runner SUV 2012 0.0% Hyundai Santa Fe SUV 2012 0.0% Land Rover LR2 SUV 2012 0.0% +901 /scratch/Teaching/cars/car_ims/005526.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 44.55% Chevrolet Silverado 1500 Regular Cab 2012 42.47% Chevrolet Silverado 1500 Extended Cab 2012 10.18% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 2.16% GMC Canyon Extended Cab 2012 0.57% +902 /scratch/Teaching/cars/car_ims/008575.jpg Fisker Karma Sedan 2012 Acura TL Sedan 2012 90.26% Acura TSX Sedan 2012 3.55% Tesla Model S Sedan 2012 1.66% Jaguar XK XKR 2012 1.44% Hyundai Sonata Hybrid Sedan 2012 0.67% +903 /scratch/Teaching/cars/car_ims/007366.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Club Cab 2007 86.6% Chevrolet Silverado 1500 Extended Cab 2012 6.53% Dodge Dakota Crew Cab 2010 3.4% GMC Canyon Extended Cab 2012 0.97% Dodge Ram Pickup 3500 Quad Cab 2009 0.95% +904 /scratch/Teaching/cars/car_ims/006213.jpg Chrysler Sebring Convertible 2010 Honda Accord Sedan 2012 26.69% Acura RL Sedan 2012 24.17% Hyundai Sonata Sedan 2012 20.43% Hyundai Azera Sedan 2012 10.59% Hyundai Elantra Sedan 2007 3.36% +905 /scratch/Teaching/cars/car_ims/010402.jpg Honda Odyssey Minivan 2012 Honda Odyssey Minivan 2012 72.25% Honda Accord Sedan 2012 13.1% Acura RL Sedan 2012 6.55% Hyundai Elantra Sedan 2007 4.49% Chevrolet Malibu Hybrid Sedan 2010 1.24% +906 /scratch/Teaching/cars/car_ims/015604.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 99.64% Toyota Camry Sedan 2012 0.17% Honda Accord Sedan 2012 0.09% Toyota Corolla Sedan 2012 0.03% Hyundai Elantra Touring Hatchback 2012 0.02% +907 /scratch/Teaching/cars/car_ims/007699.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 99.82% Dodge Journey SUV 2012 0.18% Dodge Caliber Wagon 2012 0.0% Dodge Charger Sedan 2012 0.0% Chevrolet TrailBlazer SS 2009 0.0% +908 /scratch/Teaching/cars/car_ims/009072.jpg Ford Ranger SuperCab 2011 Jeep Wrangler SUV 2012 45.05% GMC Canyon Extended Cab 2012 33.68% AM General Hummer SUV 2000 5.96% Ford F-150 Regular Cab 2007 4.87% Dodge Dakota Club Cab 2007 2.82% +909 /scratch/Teaching/cars/car_ims/008015.jpg Eagle Talon Hatchback 1998 Nissan 240SX Coupe 1998 57.36% Eagle Talon Hatchback 1998 32.24% Plymouth Neon Coupe 1999 2.66% Ford Focus Sedan 2007 1.42% Chevrolet Monte Carlo Coupe 2007 1.28% +910 /scratch/Teaching/cars/car_ims/009026.jpg Ford Ranger SuperCab 2011 Ford F-150 Regular Cab 2007 74.81% Ford Ranger SuperCab 2011 14.45% Ford F-150 Regular Cab 2012 6.43% GMC Canyon Extended Cab 2012 1.11% Volvo XC90 SUV 2007 0.81% +911 /scratch/Teaching/cars/car_ims/004421.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette ZR1 2012 89.3% Chevrolet Corvette Convertible 2012 10.7% Jaguar XK XKR 2012 0.0% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.0% Porsche Panamera Sedan 2012 0.0% +912 /scratch/Teaching/cars/car_ims/008106.jpg FIAT 500 Abarth 2012 FIAT 500 Abarth 2012 99.99% Spyker C8 Convertible 2009 0.01% Nissan Juke Hatchback 2012 0.0% Volvo C30 Hatchback 2012 0.0% Ford GT Coupe 2006 0.0% +913 /scratch/Teaching/cars/car_ims/003418.jpg Bentley Continental GT Coupe 2007 Chevrolet Malibu Hybrid Sedan 2010 66.61% Bentley Continental Flying Spur Sedan 2007 22.63% Bentley Continental GT Coupe 2007 5.51% Bentley Mulsanne Sedan 2011 2.6% Buick Verano Sedan 2012 0.63% +914 /scratch/Teaching/cars/car_ims/005333.jpg Chevrolet Cobalt SS 2010 Chevrolet Cobalt SS 2010 96.39% Honda Accord Coupe 2012 2.8% Chevrolet Monte Carlo Coupe 2007 0.4% Dodge Charger SRT-8 2009 0.27% Dodge Charger Sedan 2012 0.06% +915 /scratch/Teaching/cars/car_ims/000917.jpg Audi RS 4 Convertible 2008 Audi RS 4 Convertible 2008 73.54% Audi S5 Convertible 2012 8.98% Ford Mustang Convertible 2007 3.94% Chrysler Crossfire Convertible 2008 3.3% Acura Integra Type R 2001 1.14% +916 /scratch/Teaching/cars/car_ims/004408.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette ZR1 2012 98.09% Chevrolet Corvette Convertible 2012 1.4% Bugatti Veyron 16.4 Convertible 2009 0.24% Porsche Panamera Sedan 2012 0.21% Jaguar XK XKR 2012 0.02% +917 /scratch/Teaching/cars/car_ims/012045.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 33.32% GMC Savana Van 2012 22.71% Buick Rainier SUV 2007 8.99% Isuzu Ascender SUV 2008 6.14% Ford E-Series Wagon Van 2012 6.08% +918 /scratch/Teaching/cars/car_ims/009074.jpg Ford Ranger SuperCab 2011 Ford Ranger SuperCab 2011 100.0% Isuzu Ascender SUV 2008 0.0% Ford F-150 Regular Cab 2007 0.0% Chrysler Aspen SUV 2009 0.0% GMC Canyon Extended Cab 2012 0.0% +919 /scratch/Teaching/cars/car_ims/006203.jpg Chrysler Sebring Convertible 2010 Chrysler Sebring Convertible 2010 87.82% Honda Accord Sedan 2012 6.98% Mercedes-Benz E-Class Sedan 2012 2.37% Chrysler Crossfire Convertible 2008 0.71% Hyundai Genesis Sedan 2012 0.68% +920 /scratch/Teaching/cars/car_ims/011446.jpg Hyundai Elantra Touring Hatchback 2012 Ford Focus Sedan 2007 55.89% Volkswagen Golf Hatchback 2012 10.14% Suzuki Aerio Sedan 2007 8.32% Chevrolet Impala Sedan 2007 7.95% Hyundai Elantra Touring Hatchback 2012 4.18% +921 /scratch/Teaching/cars/car_ims/009880.jpg GMC Acadia SUV 2012 Buick Rainier SUV 2007 35.31% Mazda Tribute SUV 2011 15.95% Dodge Durango SUV 2007 11.67% Jeep Liberty SUV 2012 6.78% GMC Acadia SUV 2012 5.78% +922 /scratch/Teaching/cars/car_ims/013039.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 99.99% Suzuki SX4 Hatchback 2012 0.01% Ram C/V Cargo Van Minivan 2012 0.0% Land Rover LR2 SUV 2012 0.0% Hyundai Santa Fe SUV 2012 0.0% +923 /scratch/Teaching/cars/car_ims/008658.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-150 Regular Cab 2012 68.25% GMC Canyon Extended Cab 2012 8.53% Ford F-150 Regular Cab 2007 7.51% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 6.11% Chevrolet Silverado 1500 Regular Cab 2012 1.96% +924 /scratch/Teaching/cars/car_ims/009235.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 99.99% Ford F-150 Regular Cab 2007 0.01% Ford F-450 Super Duty Crew Cab 2012 0.0% Ford E-Series Wagon Van 2012 0.0% Chrysler Aspen SUV 2009 0.0% +925 /scratch/Teaching/cars/car_ims/007739.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 99.14% Dodge Dakota Club Cab 2007 0.57% Dodge Dakota Crew Cab 2010 0.11% Dodge Caliber Wagon 2012 0.09% Dodge Magnum Wagon 2008 0.07% +926 /scratch/Teaching/cars/car_ims/002147.jpg BMW 1 Series Convertible 2012 Suzuki SX4 Sedan 2012 20.5% Chevrolet Sonic Sedan 2012 17.66% Toyota Corolla Sedan 2012 10.2% Suzuki Aerio Sedan 2007 7.05% BMW 3 Series Wagon 2012 5.65% +927 /scratch/Teaching/cars/car_ims/016030.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 95.28% Audi 100 Wagon 1994 3.86% Ford Freestar Minivan 2007 0.3% Ford F-150 Regular Cab 2007 0.18% Ford Ranger SuperCab 2011 0.11% +928 /scratch/Teaching/cars/car_ims/003296.jpg Bentley Mulsanne Sedan 2011 Bentley Mulsanne Sedan 2011 84.64% Bentley Arnage Sedan 2009 9.76% Rolls-Royce Phantom Sedan 2012 5.58% Bentley Continental Flying Spur Sedan 2007 0.01% Rolls-Royce Ghost Sedan 2012 0.0% +929 /scratch/Teaching/cars/car_ims/010208.jpg HUMMER H3T Crew Cab 2010 GMC Canyon Extended Cab 2012 42.57% Chevrolet Silverado 1500 Regular Cab 2012 41.36% Chevrolet Silverado 1500 Extended Cab 2012 13.64% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 1.49% HUMMER H3T Crew Cab 2010 0.44% +930 /scratch/Teaching/cars/car_ims/005686.jpg Chevrolet Express Van 2007 Chevrolet Express Cargo Van 2007 44.94% GMC Savana Van 2012 39.04% Chevrolet Express Van 2007 16.02% Volkswagen Golf Hatchback 1991 0.0% Nissan NV Passenger Van 2012 0.0% +931 /scratch/Teaching/cars/car_ims/001115.jpg Audi TTS Coupe 2012 Aston Martin V8 Vantage Convertible 2012 50.7% Aston Martin V8 Vantage Coupe 2012 38.3% Lamborghini Reventon Coupe 2008 2.45% Aston Martin Virage Convertible 2012 2.28% Audi R8 Coupe 2012 1.33% +932 /scratch/Teaching/cars/car_ims/012283.jpg Jeep Compass SUV 2012 BMW X3 SUV 2012 84.83% Jeep Compass SUV 2012 6.94% GMC Terrain SUV 2012 5.05% Rolls-Royce Ghost Sedan 2012 1.37% Jeep Grand Cherokee SUV 2012 0.95% +933 /scratch/Teaching/cars/car_ims/012179.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 54.79% GMC Terrain SUV 2012 39.29% Jeep Compass SUV 2012 5.89% Toyota 4Runner SUV 2012 0.03% Chevrolet Traverse SUV 2012 0.0% +934 /scratch/Teaching/cars/car_ims/012403.jpg Lamborghini Aventador Coupe 2012 Audi TT RS Coupe 2012 59.46% Ferrari 458 Italia Coupe 2012 20.78% Lamborghini Aventador Coupe 2012 6.31% Ferrari 458 Italia Convertible 2012 5.64% McLaren MP4-12C Coupe 2012 3.69% +935 /scratch/Teaching/cars/car_ims/003556.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 64.04% Hyundai Elantra Touring Hatchback 2012 8.79% Volkswagen Golf Hatchback 2012 8.63% Chevrolet Malibu Hybrid Sedan 2010 6.33% Daewoo Nubira Wagon 2002 4.73% +936 /scratch/Teaching/cars/car_ims/000637.jpg Aston Martin V8 Vantage Convertible 2012 Dodge Charger SRT-8 2009 47.85% Chevrolet HHR SS 2010 28.94% Dodge Magnum Wagon 2008 5.25% Chevrolet TrailBlazer SS 2009 5.2% Chevrolet Cobalt SS 2010 2.87% +937 /scratch/Teaching/cars/car_ims/008797.jpg Ford Freestar Minivan 2007 Lincoln Town Car Sedan 2011 54.22% Ford Freestar Minivan 2007 25.59% Daewoo Nubira Wagon 2002 10.58% Audi 100 Wagon 1994 4.11% Chevrolet Malibu Sedan 2007 1.97% +938 /scratch/Teaching/cars/car_ims/007510.jpg Dodge Magnum Wagon 2008 Dodge Magnum Wagon 2008 75.31% Chevrolet Malibu Sedan 2007 12.41% Chevrolet HHR SS 2010 6.26% Dodge Durango SUV 2012 2.44% Chevrolet Cobalt SS 2010 1.71% +939 /scratch/Teaching/cars/car_ims/011048.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 100.0% Buick Regal GS 2012 0.0% Hyundai Veloster Hatchback 2012 0.0% Buick Verano Sedan 2012 0.0% Ford Edge SUV 2012 0.0% +940 /scratch/Teaching/cars/car_ims/000228.jpg Acura TL Sedan 2012 Acura ZDX Hatchback 2012 67.1% Acura TL Sedan 2012 9.46% Chevrolet Corvette Ron Fellows Edition Z06 2007 4.92% Fisker Karma Sedan 2012 2.74% Nissan Leaf Hatchback 2012 1.77% +941 /scratch/Teaching/cars/car_ims/007213.jpg Dodge Sprinter Cargo Van 2009 Dodge Sprinter Cargo Van 2009 71.34% Mercedes-Benz Sprinter Van 2012 28.65% Audi 100 Sedan 1994 0.01% Audi 100 Wagon 1994 0.0% Ram C/V Cargo Van Minivan 2012 0.0% +942 /scratch/Teaching/cars/car_ims/006041.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 85.52% Chevrolet Silverado 2500HD Regular Cab 2012 10.28% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 2.53% Chevrolet Silverado 1500 Extended Cab 2012 1.66% GMC Canyon Extended Cab 2012 0.01% +943 /scratch/Teaching/cars/car_ims/010693.jpg Hyundai Veloster Hatchback 2012 Hyundai Accent Sedan 2012 40.22% Toyota Camry Sedan 2012 29.08% Toyota Corolla Sedan 2012 10.99% Ford Fiesta Sedan 2012 5.35% Chevrolet Sonic Sedan 2012 2.96% +944 /scratch/Teaching/cars/car_ims/013371.jpg Mercedes-Benz SL-Class Coupe 2009 Mercedes-Benz SL-Class Coupe 2009 99.9% Aston Martin Virage Convertible 2012 0.01% Hyundai Genesis Sedan 2012 0.01% Audi S5 Convertible 2012 0.01% Mercedes-Benz Sprinter Van 2012 0.01% +945 /scratch/Teaching/cars/car_ims/002175.jpg BMW 1 Series Convertible 2012 BMW 3 Series Wagon 2012 69.19% BMW M5 Sedan 2010 28.35% Volkswagen Golf Hatchback 2012 0.56% Acura RL Sedan 2012 0.55% BMW ActiveHybrid 5 Sedan 2012 0.39% +946 /scratch/Teaching/cars/car_ims/013290.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 99.99% BMW 3 Series Sedan 2012 0.01% Hyundai Genesis Sedan 2012 0.0% Audi S4 Sedan 2012 0.0% Honda Accord Coupe 2012 0.0% +947 /scratch/Teaching/cars/car_ims/003560.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 86.29% Bentley Continental GT Coupe 2007 13.7% Bentley Mulsanne Sedan 2011 0.0% Bentley Continental GT Coupe 2012 0.0% Maybach Landaulet Convertible 2012 0.0% +948 /scratch/Teaching/cars/car_ims/010817.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 98.32% Ford Edge SUV 2012 1.23% Hyundai Veracruz SUV 2012 0.42% Honda Odyssey Minivan 2012 0.02% Dodge Journey SUV 2012 0.01% +949 /scratch/Teaching/cars/car_ims/004769.jpg Chevrolet Camaro Convertible 2012 Jaguar XK XKR 2012 31.52% Porsche Panamera Sedan 2012 25.91% Chevrolet Corvette ZR1 2012 12.67% Fisker Karma Sedan 2012 8.74% Aston Martin Virage Convertible 2012 4.95% +950 /scratch/Teaching/cars/car_ims/014713.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 92.3% Spyker C8 Coupe 2009 5.17% FIAT 500 Abarth 2012 1.18% Chevrolet Corvette ZR1 2012 0.63% Nissan Juke Hatchback 2012 0.56% +951 /scratch/Teaching/cars/car_ims/001087.jpg Audi TTS Coupe 2012 Mitsubishi Lancer Sedan 2012 87.94% Audi A5 Coupe 2012 2.91% Chevrolet Malibu Hybrid Sedan 2010 2.28% Honda Accord Coupe 2012 1.73% Chevrolet Cobalt SS 2010 1.41% +952 /scratch/Teaching/cars/car_ims/008190.jpg Ferrari FF Coupe 2012 Spyker C8 Coupe 2009 23.91% Ford GT Coupe 2006 16.82% Lamborghini Aventador Coupe 2012 11.99% Chevrolet Corvette Ron Fellows Edition Z06 2007 6.52% McLaren MP4-12C Coupe 2012 5.67% +953 /scratch/Teaching/cars/car_ims/002508.jpg BMW 6 Series Convertible 2007 BMW 6 Series Convertible 2007 60.67% Mitsubishi Lancer Sedan 2012 12.01% Dodge Charger Sedan 2012 6.97% BMW M6 Convertible 2010 5.96% Audi S4 Sedan 2007 4.31% +954 /scratch/Teaching/cars/car_ims/006276.jpg Chrysler Town and Country Minivan 2012 Ram C/V Cargo Van Minivan 2012 64.76% Suzuki SX4 Sedan 2012 32.84% Chrysler Town and Country Minivan 2012 2.14% Suzuki SX4 Hatchback 2012 0.13% Dodge Caliber Wagon 2012 0.08% +955 /scratch/Teaching/cars/car_ims/008633.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 98.92% Cadillac Escalade EXT Crew Cab 2007 0.82% Toyota Sequoia SUV 2012 0.21% Ford F-150 Regular Cab 2012 0.04% Land Rover Range Rover SUV 2012 0.01% +956 /scratch/Teaching/cars/car_ims/009557.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 94.11% Scion xD Hatchback 2012 3.51% Hyundai Accent Sedan 2012 2.24% Toyota Corolla Sedan 2012 0.07% Suzuki SX4 Hatchback 2012 0.03% +957 /scratch/Teaching/cars/car_ims/006446.jpg Chrysler Crossfire Convertible 2008 BMW 1 Series Convertible 2012 47.05% BMW 6 Series Convertible 2007 18.78% BMW Z4 Convertible 2012 9.36% BMW M6 Convertible 2010 8.19% Audi RS 4 Convertible 2008 7.42% +958 /scratch/Teaching/cars/car_ims/010714.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 99.97% Ford Fiesta Sedan 2012 0.02% Hyundai Accent Sedan 2012 0.0% Hyundai Elantra Touring Hatchback 2012 0.0% Chevrolet Sonic Sedan 2012 0.0% +959 /scratch/Teaching/cars/car_ims/013880.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 100.0% Jeep Patriot SUV 2012 0.0% Ford F-150 Regular Cab 2007 0.0% GMC Yukon Hybrid SUV 2012 0.0% Jeep Liberty SUV 2012 0.0% +960 /scratch/Teaching/cars/car_ims/016170.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 91.76% Suzuki SX4 Hatchback 2012 4.08% FIAT 500 Convertible 2012 3.01% Scion xD Hatchback 2012 1.08% Ford Fiesta Sedan 2012 0.03% +961 /scratch/Teaching/cars/car_ims/004672.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 99.91% Hyundai Veracruz SUV 2012 0.05% GMC Acadia SUV 2012 0.03% Jeep Grand Cherokee SUV 2012 0.01% Toyota 4Runner SUV 2012 0.0% +962 /scratch/Teaching/cars/car_ims/001197.jpg Audi R8 Coupe 2012 Jaguar XK XKR 2012 35.2% Acura TL Type-S 2008 30.6% Acura TL Sedan 2012 7.72% Porsche Panamera Sedan 2012 3.26% Chevrolet Malibu Hybrid Sedan 2010 3.18% +963 /scratch/Teaching/cars/car_ims/012142.jpg Jeep Grand Cherokee SUV 2012 Chevrolet Traverse SUV 2012 22.48% Ford Edge SUV 2012 8.32% Hyundai Veracruz SUV 2012 7.48% Buick Enclave SUV 2012 6.89% BMW X6 SUV 2012 6.27% +964 /scratch/Teaching/cars/car_ims/001506.jpg Audi TT Hatchback 2011 Audi TT Hatchback 2011 46.4% Audi S4 Sedan 2012 24.93% Audi TT RS Coupe 2012 11.03% Toyota Camry Sedan 2012 7.35% Mitsubishi Lancer Sedan 2012 4.15% +965 /scratch/Teaching/cars/car_ims/007421.jpg Dodge Dakota Club Cab 2007 Dodge Dakota Club Cab 2007 79.1% Dodge Dakota Crew Cab 2010 20.9% Dodge Durango SUV 2007 0.0% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% Isuzu Ascender SUV 2008 0.0% +966 /scratch/Teaching/cars/car_ims/012202.jpg Jeep Grand Cherokee SUV 2012 Jeep Compass SUV 2012 62.92% Jeep Grand Cherokee SUV 2012 37.08% Jeep Liberty SUV 2012 0.0% BMW X3 SUV 2012 0.0% Jeep Patriot SUV 2012 0.0% +967 /scratch/Teaching/cars/car_ims/002656.jpg BMW X6 SUV 2012 Dodge Caliber Wagon 2012 59.02% Dodge Journey SUV 2012 9.02% Nissan Juke Hatchback 2012 7.17% Dodge Caliber Wagon 2007 4.42% Ford Edge SUV 2012 4.11% +968 /scratch/Teaching/cars/car_ims/013926.jpg Nissan Juke Hatchback 2012 Hyundai Tucson SUV 2012 39.24% Nissan Juke Hatchback 2012 37.12% Hyundai Veracruz SUV 2012 10.55% Acura ZDX Hatchback 2012 5.64% Scion xD Hatchback 2012 3.46% +969 /scratch/Teaching/cars/car_ims/013382.jpg Mercedes-Benz SL-Class Coupe 2009 Acura TL Type-S 2008 34.94% Mercedes-Benz SL-Class Coupe 2009 15.2% Porsche Panamera Sedan 2012 15.11% BMW M6 Convertible 2010 9.08% Fisker Karma Sedan 2012 7.65% +970 /scratch/Teaching/cars/car_ims/003445.jpg Bentley Continental GT Coupe 2007 Bentley Continental GT Coupe 2007 60.05% Bentley Continental GT Coupe 2012 37.7% Bentley Continental Flying Spur Sedan 2007 0.99% Buick Verano Sedan 2012 0.56% BMW M5 Sedan 2010 0.23% +971 /scratch/Teaching/cars/car_ims/003412.jpg Bentley Continental GT Coupe 2007 Bentley Continental GT Coupe 2007 50.41% Bentley Continental GT Coupe 2012 17.15% Bentley Continental Flying Spur Sedan 2007 15.8% Bentley Mulsanne Sedan 2011 13.36% Cadillac CTS-V Sedan 2012 2.55% +972 /scratch/Teaching/cars/car_ims/009981.jpg GMC Canyon Extended Cab 2012 GMC Canyon Extended Cab 2012 36.0% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 29.99% Chevrolet Silverado 1500 Extended Cab 2012 28.72% Chevrolet Silverado 2500HD Regular Cab 2012 2.43% Chevrolet Silverado 1500 Regular Cab 2012 2.36% +973 /scratch/Teaching/cars/car_ims/000490.jpg Acura Integra Type R 2001 Lamborghini Gallardo LP 570-4 Superleggera 2012 29.96% Acura Integra Type R 2001 21.66% GMC Savana Van 2012 13.61% Lamborghini Diablo Coupe 2001 8.69% McLaren MP4-12C Coupe 2012 4.63% +974 /scratch/Teaching/cars/car_ims/004062.jpg Cadillac CTS-V Sedan 2012 Cadillac CTS-V Sedan 2012 99.96% Bentley Mulsanne Sedan 2011 0.03% MINI Cooper Roadster Convertible 2012 0.0% Bentley Continental GT Coupe 2012 0.0% Bentley Continental GT Coupe 2007 0.0% +975 /scratch/Teaching/cars/car_ims/007422.jpg Dodge Dakota Club Cab 2007 Dodge Dakota Club Cab 2007 96.35% Dodge Ram Pickup 3500 Quad Cab 2009 1.89% Ford Ranger SuperCab 2011 0.84% GMC Canyon Extended Cab 2012 0.64% Dodge Dakota Crew Cab 2010 0.14% +976 /scratch/Teaching/cars/car_ims/002178.jpg BMW 1 Series Convertible 2012 Dodge Charger Sedan 2012 26.6% Chrysler Crossfire Convertible 2008 16.32% BMW 1 Series Convertible 2012 15.14% Audi S4 Sedan 2012 14.46% Audi A5 Coupe 2012 8.68% +977 /scratch/Teaching/cars/car_ims/004266.jpg Cadillac Escalade EXT Crew Cab 2007 Chevrolet Avalanche Crew Cab 2012 92.33% Cadillac Escalade EXT Crew Cab 2007 4.07% Chevrolet Tahoe Hybrid SUV 2012 3.27% Isuzu Ascender SUV 2008 0.13% Chevrolet Silverado 1500 Extended Cab 2012 0.04% +978 /scratch/Teaching/cars/car_ims/015188.jpg Tesla Model S Sedan 2012 Dodge Challenger SRT8 2011 17.42% Aston Martin Virage Convertible 2012 11.26% Fisker Karma Sedan 2012 11.17% Chevrolet Malibu Hybrid Sedan 2010 8.36% Jaguar XK XKR 2012 7.31% +979 /scratch/Teaching/cars/car_ims/002002.jpg Audi TT RS Coupe 2012 Audi TT RS Coupe 2012 94.21% Audi TT Hatchback 2011 2.25% Mitsubishi Lancer Sedan 2012 1.34% Audi TTS Coupe 2012 0.96% Audi S4 Sedan 2012 0.77% +980 /scratch/Teaching/cars/car_ims/008840.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 97.1% Ram C/V Cargo Van Minivan 2012 1.35% Chrysler Town and Country Minivan 2012 0.83% Dodge Caravan Minivan 1997 0.37% Chevrolet Malibu Sedan 2007 0.23% +981 /scratch/Teaching/cars/car_ims/004274.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 86.45% GMC Yukon Hybrid SUV 2012 12.39% Chevrolet Tahoe Hybrid SUV 2012 0.87% Chevrolet Avalanche Crew Cab 2012 0.29% GMC Terrain SUV 2012 0.0% +982 /scratch/Teaching/cars/car_ims/008583.jpg Fisker Karma Sedan 2012 BMW M6 Convertible 2010 66.53% BMW 6 Series Convertible 2007 23.24% Acura TL Type-S 2008 4.61% Jaguar XK XKR 2012 1.7% Honda Accord Coupe 2012 1.19% +983 /scratch/Teaching/cars/car_ims/012221.jpg Jeep Compass SUV 2012 Volvo XC90 SUV 2007 33.01% Chevrolet TrailBlazer SS 2009 27.69% Dodge Durango SUV 2007 6.08% Land Rover Range Rover SUV 2012 5.91% Buick Enclave SUV 2012 4.12% +984 /scratch/Teaching/cars/car_ims/015598.jpg Volkswagen Golf Hatchback 2012 Suzuki Aerio Sedan 2007 63.01% Volkswagen Golf Hatchback 2012 34.62% Ford Focus Sedan 2007 2.13% Toyota Corolla Sedan 2012 0.17% Hyundai Elantra Touring Hatchback 2012 0.02% +985 /scratch/Teaching/cars/car_ims/002822.jpg BMW M5 Sedan 2010 BMW M5 Sedan 2010 73.55% BMW 3 Series Wagon 2012 21.88% Acura RL Sedan 2012 1.85% BMW ActiveHybrid 5 Sedan 2012 1.32% BMW 1 Series Convertible 2012 0.8% +986 /scratch/Teaching/cars/car_ims/006494.jpg Chrysler Crossfire Convertible 2008 Ford Mustang Convertible 2007 28.48% Chevrolet Monte Carlo Coupe 2007 16.36% Jaguar XK XKR 2012 12.88% Dodge Charger SRT-8 2009 9.93% Dodge Charger Sedan 2012 3.18% +987 /scratch/Teaching/cars/car_ims/014565.jpg Rolls-Royce Phantom Sedan 2012 Rolls-Royce Phantom Sedan 2012 94.33% Bentley Mulsanne Sedan 2011 5.1% Rolls-Royce Ghost Sedan 2012 0.54% Chrysler 300 SRT-8 2010 0.02% Bentley Arnage Sedan 2009 0.01% +988 /scratch/Teaching/cars/car_ims/002923.jpg BMW M6 Convertible 2010 BMW 6 Series Convertible 2007 77.5% BMW M6 Convertible 2010 21.06% Acura TL Type-S 2008 1.22% Jaguar XK XKR 2012 0.15% BMW Z4 Convertible 2012 0.04% +989 /scratch/Teaching/cars/car_ims/003244.jpg Bentley Arnage Sedan 2009 Bentley Arnage Sedan 2009 99.11% Bentley Continental Flying Spur Sedan 2007 0.37% Bentley Mulsanne Sedan 2011 0.32% Bentley Continental GT Coupe 2007 0.06% Rolls-Royce Phantom Sedan 2012 0.04% +990 /scratch/Teaching/cars/car_ims/006647.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 65.02% Ford Focus Sedan 2007 33.82% Audi 100 Wagon 1994 0.62% Suzuki Aerio Sedan 2007 0.31% Plymouth Neon Coupe 1999 0.09% +991 /scratch/Teaching/cars/car_ims/001498.jpg Audi TT Hatchback 2011 Audi TT Hatchback 2011 57.36% Audi TTS Coupe 2012 32.18% Audi S4 Sedan 2012 3.47% Audi S5 Coupe 2012 3.32% Audi A5 Coupe 2012 1.9% +992 /scratch/Teaching/cars/car_ims/000974.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 85.39% Audi S4 Sedan 2007 13.6% Audi S5 Coupe 2012 0.76% Audi S4 Sedan 2012 0.23% Rolls-Royce Ghost Sedan 2012 0.01% +993 /scratch/Teaching/cars/car_ims/009660.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 100.0% Toyota 4Runner SUV 2012 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% Jeep Grand Cherokee SUV 2012 0.0% Chevrolet Traverse SUV 2012 0.0% +994 /scratch/Teaching/cars/car_ims/010604.jpg Honda Accord Sedan 2012 Acura RL Sedan 2012 41.7% Honda Accord Sedan 2012 28.86% Acura TSX Sedan 2012 13.83% Acura TL Type-S 2008 12.42% Hyundai Elantra Sedan 2007 1.91% +995 /scratch/Teaching/cars/car_ims/007023.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 98.42% Dodge Ram Pickup 3500 Quad Cab 2009 1.55% Ford F-450 Super Duty Crew Cab 2012 0.03% Dodge Durango SUV 2007 0.0% Chrysler Aspen SUV 2009 0.0% +996 /scratch/Teaching/cars/car_ims/014533.jpg Rolls-Royce Phantom Sedan 2012 Volvo 240 Sedan 1993 18.72% Lincoln Town Car Sedan 2011 17.26% Rolls-Royce Phantom Sedan 2012 15.06% Dodge Dakota Club Cab 2007 7.77% Dodge Magnum Wagon 2008 7.53% +997 /scratch/Teaching/cars/car_ims/016011.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 99.73% Lincoln Town Car Sedan 2011 0.19% Jeep Patriot SUV 2012 0.03% Audi 100 Wagon 1994 0.03% Volvo XC90 SUV 2007 0.01% +998 /scratch/Teaching/cars/car_ims/007080.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 61.57% GMC Canyon Extended Cab 2012 27.35% Dodge Dakota Club Cab 2007 6.86% Dodge Dakota Crew Cab 2010 2.99% HUMMER H3T Crew Cab 2010 0.79% +999 /scratch/Teaching/cars/car_ims/011700.jpg Isuzu Ascender SUV 2008 Chrysler Aspen SUV 2009 27.82% Chrysler Town and Country Minivan 2012 15.1% Ford Expedition EL SUV 2009 13.34% Volvo XC90 SUV 2007 9.76% GMC Acadia SUV 2012 8.5% +1000 /scratch/Teaching/cars/car_ims/005453.jpg Chevrolet TrailBlazer SS 2009 Chevrolet TrailBlazer SS 2009 99.88% Chevrolet Avalanche Crew Cab 2012 0.07% Chevrolet Tahoe Hybrid SUV 2012 0.03% Isuzu Ascender SUV 2008 0.02% Buick Rainier SUV 2007 0.0% +1001 /scratch/Teaching/cars/car_ims/004598.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Toyota Camry Sedan 2012 41.42% Buick Regal GS 2012 12.34% Jaguar XK XKR 2012 9.22% Acura TSX Sedan 2012 5.57% Mitsubishi Lancer Sedan 2012 5.11% +1002 /scratch/Teaching/cars/car_ims/008155.jpg FIAT 500 Convertible 2012 FIAT 500 Convertible 2012 100.0% smart fortwo Convertible 2012 0.0% Maybach Landaulet Convertible 2012 0.0% Suzuki SX4 Sedan 2012 0.0% Suzuki Aerio Sedan 2007 0.0% +1003 /scratch/Teaching/cars/car_ims/012847.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 99.99% Chevrolet Impala Sedan 2007 0.01% Chevrolet Malibu Sedan 2007 0.0% Chevrolet Monte Carlo Coupe 2007 0.0% Audi 100 Wagon 1994 0.0% +1004 /scratch/Teaching/cars/car_ims/012355.jpg Lamborghini Reventon Coupe 2008 Lamborghini Reventon Coupe 2008 99.97% Lamborghini Aventador Coupe 2012 0.01% Fisker Karma Sedan 2012 0.01% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.0% Aston Martin V8 Vantage Coupe 2012 0.0% +1005 /scratch/Teaching/cars/car_ims/000141.jpg Acura RL Sedan 2012 Acura TSX Sedan 2012 91.62% Acura TL Sedan 2012 7.88% Acura RL Sedan 2012 0.42% Toyota Camry Sedan 2012 0.08% Acura TL Type-S 2008 0.0% +1006 /scratch/Teaching/cars/car_ims/014822.jpg Spyker C8 Coupe 2009 Aston Martin Virage Coupe 2012 89.96% BMW M3 Coupe 2012 1.57% Spyker C8 Coupe 2009 1.17% Aston Martin V8 Vantage Coupe 2012 1.09% BMW Z4 Convertible 2012 0.96% +1007 /scratch/Teaching/cars/car_ims/007071.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 78.81% GMC Canyon Extended Cab 2012 12.72% Chevrolet Silverado 1500 Classic Extended Cab 2007 2.98% Dodge Ram Pickup 3500 Crew Cab 2010 2.42% Chevrolet Silverado 2500HD Regular Cab 2012 0.82% +1008 /scratch/Teaching/cars/car_ims/005872.jpg Chevrolet Malibu Sedan 2007 Chevrolet Impala Sedan 2007 44.62% Chevrolet Malibu Sedan 2007 24.77% Acura TL Type-S 2008 11.37% Chevrolet Monte Carlo Coupe 2007 7.42% Hyundai Elantra Sedan 2007 6.22% +1009 /scratch/Teaching/cars/car_ims/008052.jpg Eagle Talon Hatchback 1998 Chevrolet Traverse SUV 2012 28.09% Dodge Caravan Minivan 1997 21.21% Daewoo Nubira Wagon 2002 10.26% Hyundai Veracruz SUV 2012 9.22% Ford Freestar Minivan 2007 4.31% +1010 /scratch/Teaching/cars/car_ims/010944.jpg Hyundai Veracruz SUV 2012 Hyundai Veracruz SUV 2012 80.41% Chevrolet Traverse SUV 2012 19.15% Chevrolet Malibu Sedan 2007 0.25% Honda Odyssey Minivan 2007 0.11% Hyundai Elantra Sedan 2007 0.02% +1011 /scratch/Teaching/cars/car_ims/000392.jpg Acura TSX Sedan 2012 Toyota Camry Sedan 2012 79.14% Acura TSX Sedan 2012 10.76% Toyota Corolla Sedan 2012 9.06% Mitsubishi Lancer Sedan 2012 0.38% Hyundai Accent Sedan 2012 0.17% +1012 /scratch/Teaching/cars/car_ims/002633.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 79.96% BMW X5 SUV 2007 19.05% Jeep Grand Cherokee SUV 2012 0.85% Buick Enclave SUV 2012 0.1% Jeep Compass SUV 2012 0.02% +1013 /scratch/Teaching/cars/car_ims/003169.jpg Bentley Continental Supersports Conv. Convertible 2012 Acura ZDX Hatchback 2012 39.59% Buick Verano Sedan 2012 10.32% Maybach Landaulet Convertible 2012 9.77% Chevrolet Corvette Ron Fellows Edition Z06 2007 7.71% Bentley Continental Flying Spur Sedan 2007 5.62% +1014 /scratch/Teaching/cars/car_ims/004231.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 99.98% GMC Yukon Hybrid SUV 2012 0.02% Cadillac SRX SUV 2012 0.0% Chrysler Town and Country Minivan 2012 0.0% Land Rover Range Rover SUV 2012 0.0% +1015 /scratch/Teaching/cars/car_ims/005814.jpg Chevrolet Monte Carlo Coupe 2007 Eagle Talon Hatchback 1998 24.73% Plymouth Neon Coupe 1999 18.98% Geo Metro Convertible 1993 14.6% Nissan 240SX Coupe 1998 12.55% Mercedes-Benz 300-Class Convertible 1993 7.17% +1016 /scratch/Teaching/cars/car_ims/002179.jpg BMW 1 Series Convertible 2012 BMW 1 Series Convertible 2012 54.9% Audi S5 Convertible 2012 26.89% BMW M3 Coupe 2012 7.57% BMW Z4 Convertible 2012 3.06% Audi RS 4 Convertible 2008 2.42% +1017 /scratch/Teaching/cars/car_ims/002834.jpg BMW M5 Sedan 2010 BMW M5 Sedan 2010 35.47% Acura TSX Sedan 2012 17.28% Suzuki SX4 Sedan 2012 13.23% BMW 3 Series Wagon 2012 10.38% Mitsubishi Lancer Sedan 2012 7.14% +1018 /scratch/Teaching/cars/car_ims/015390.jpg Toyota Camry Sedan 2012 Hyundai Azera Sedan 2012 78.59% Hyundai Genesis Sedan 2012 5.88% Infiniti G Coupe IPL 2012 5.68% Mercedes-Benz E-Class Sedan 2012 5.31% Infiniti QX56 SUV 2011 1.7% +1019 /scratch/Teaching/cars/car_ims/009812.jpg GMC Yukon Hybrid SUV 2012 GMC Yukon Hybrid SUV 2012 91.83% Cadillac Escalade EXT Crew Cab 2007 7.37% Chevrolet Tahoe Hybrid SUV 2012 0.36% GMC Terrain SUV 2012 0.2% Land Rover Range Rover SUV 2012 0.11% +1020 /scratch/Teaching/cars/car_ims/003228.jpg Bentley Arnage Sedan 2009 Bentley Arnage Sedan 2009 60.12% AM General Hummer SUV 2000 12.98% FIAT 500 Abarth 2012 3.76% Ford GT Coupe 2006 3.27% Jeep Liberty SUV 2012 2.62% +1021 /scratch/Teaching/cars/car_ims/011527.jpg Hyundai Azera Sedan 2012 Buick Verano Sedan 2012 44.67% Suzuki Kizashi Sedan 2012 12.75% Acura ZDX Hatchback 2012 11.26% Infiniti QX56 SUV 2011 3.85% Hyundai Azera Sedan 2012 3.14% +1022 /scratch/Teaching/cars/car_ims/015630.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 68.74% Hyundai Elantra Touring Hatchback 2012 16.27% Buick Enclave SUV 2012 6.53% Hyundai Veracruz SUV 2012 4.46% Ford Focus Sedan 2007 0.58% +1023 /scratch/Teaching/cars/car_ims/010264.jpg HUMMER H3T Crew Cab 2010 Jeep Compass SUV 2012 49.13% HUMMER H3T Crew Cab 2010 37.06% GMC Terrain SUV 2012 7.45% Jeep Grand Cherokee SUV 2012 3.44% Dodge Dakota Club Cab 2007 0.6% +1024 /scratch/Teaching/cars/car_ims/009295.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2007 90.47% Ford F-150 Regular Cab 2012 2.76% Chevrolet Silverado 1500 Regular Cab 2012 1.5% GMC Yukon Hybrid SUV 2012 1.27% GMC Canyon Extended Cab 2012 1.06% +1025 /scratch/Teaching/cars/car_ims/013922.jpg Nissan Juke Hatchback 2012 Dodge Journey SUV 2012 42.67% Ford Edge SUV 2012 18.56% Hyundai Santa Fe SUV 2012 7.67% Nissan Juke Hatchback 2012 4.6% Dodge Durango SUV 2012 4.3% +1026 /scratch/Teaching/cars/car_ims/013465.jpg Mercedes-Benz E-Class Sedan 2012 Mercedes-Benz S-Class Sedan 2012 51.95% Mercedes-Benz E-Class Sedan 2012 14.21% Audi S6 Sedan 2011 5.95% BMW ActiveHybrid 5 Sedan 2012 5.15% Bentley Mulsanne Sedan 2011 2.93% +1027 /scratch/Teaching/cars/car_ims/009411.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 61.07% Daewoo Nubira Wagon 2002 35.34% Suzuki Aerio Sedan 2007 1.92% Lincoln Town Car Sedan 2011 1.13% Audi 100 Wagon 1994 0.41% +1028 /scratch/Teaching/cars/car_ims/007733.jpg Dodge Durango SUV 2007 Dodge Durango SUV 2007 99.97% Dodge Caliber Wagon 2012 0.02% Chrysler Aspen SUV 2009 0.0% Dodge Magnum Wagon 2008 0.0% Volvo XC90 SUV 2007 0.0% +1029 /scratch/Teaching/cars/car_ims/011307.jpg Hyundai Sonata Sedan 2012 Hyundai Sonata Sedan 2012 95.55% Hyundai Azera Sedan 2012 4.42% Hyundai Elantra Sedan 2007 0.02% Honda Accord Sedan 2012 0.0% Honda Odyssey Minivan 2012 0.0% +1030 /scratch/Teaching/cars/car_ims/004403.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Ron Fellows Edition Z06 2007 75.38% Fisker Karma Sedan 2012 6.52% Lamborghini Reventon Coupe 2008 3.96% Aston Martin V8 Vantage Coupe 2012 2.65% Rolls-Royce Phantom Drophead Coupe Convertible 2012 2.0% +1031 /scratch/Teaching/cars/car_ims/000219.jpg Acura TL Sedan 2012 Acura TSX Sedan 2012 62.39% Acura TL Sedan 2012 29.81% Toyota Camry Sedan 2012 5.53% Acura TL Type-S 2008 1.01% Mitsubishi Lancer Sedan 2012 0.7% +1032 /scratch/Teaching/cars/car_ims/010368.jpg Honda Odyssey Minivan 2012 Honda Odyssey Minivan 2012 99.34% Land Rover LR2 SUV 2012 0.31% Honda Odyssey Minivan 2007 0.25% Honda Accord Sedan 2012 0.05% Hyundai Veracruz SUV 2012 0.05% +1033 /scratch/Teaching/cars/car_ims/011290.jpg Hyundai Genesis Sedan 2012 Hyundai Azera Sedan 2012 78.77% Hyundai Genesis Sedan 2012 17.0% Infiniti G Coupe IPL 2012 2.22% Hyundai Sonata Sedan 2012 1.72% Honda Accord Sedan 2012 0.25% +1034 /scratch/Teaching/cars/car_ims/003115.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental GT Coupe 2012 27.29% Ford GT Coupe 2006 18.93% Bentley Continental GT Coupe 2007 15.56% Bentley Arnage Sedan 2009 13.17% Bentley Mulsanne Sedan 2011 10.17% +1035 /scratch/Teaching/cars/car_ims/000002.jpg AM General Hummer SUV 2000 HUMMER H2 SUT Crew Cab 2009 53.59% HUMMER H3T Crew Cab 2010 35.06% AM General Hummer SUV 2000 11.33% Jeep Wrangler SUV 2012 0.02% Chevrolet Silverado 1500 Extended Cab 2012 0.0% +1036 /scratch/Teaching/cars/car_ims/009463.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 89.04% Plymouth Neon Coupe 1999 5.98% Chevrolet Impala Sedan 2007 3.71% Daewoo Nubira Wagon 2002 1.13% Suzuki Aerio Sedan 2007 0.09% +1037 /scratch/Teaching/cars/car_ims/008366.jpg Ferrari 458 Italia Convertible 2012 Ferrari 458 Italia Convertible 2012 64.14% Ferrari 458 Italia Coupe 2012 35.78% Lamborghini Aventador Coupe 2012 0.07% Ferrari California Convertible 2012 0.01% McLaren MP4-12C Coupe 2012 0.0% +1038 /scratch/Teaching/cars/car_ims/007368.jpg Dodge Dakota Crew Cab 2010 Chevrolet Avalanche Crew Cab 2012 15.27% Isuzu Ascender SUV 2008 13.72% Chevrolet TrailBlazer SS 2009 7.63% Dodge Magnum Wagon 2008 7.32% Dodge Dakota Crew Cab 2010 6.36% +1039 /scratch/Teaching/cars/car_ims/014075.jpg Nissan 240SX Coupe 1998 Nissan 240SX Coupe 1998 64.12% Ford Focus Sedan 2007 15.91% Plymouth Neon Coupe 1999 13.12% Eagle Talon Hatchback 1998 2.55% Chevrolet Monte Carlo Coupe 2007 2.54% +1040 /scratch/Teaching/cars/car_ims/015807.jpg Volkswagen Beetle Hatchback 2012 Volkswagen Beetle Hatchback 2012 65.37% Nissan Leaf Hatchback 2012 11.67% Scion xD Hatchback 2012 11.2% FIAT 500 Convertible 2012 4.31% Suzuki SX4 Hatchback 2012 4.23% +1041 /scratch/Teaching/cars/car_ims/012874.jpg MINI Cooper Roadster Convertible 2012 Mercedes-Benz E-Class Sedan 2012 21.27% Porsche Panamera Sedan 2012 18.21% Mercedes-Benz S-Class Sedan 2012 13.33% Maybach Landaulet Convertible 2012 11.73% Mercedes-Benz SL-Class Coupe 2009 6.48% +1042 /scratch/Teaching/cars/car_ims/005741.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 48.14% Chevrolet Express Cargo Van 2007 46.78% Chevrolet Express Van 2007 4.69% Nissan NV Passenger Van 2012 0.24% Ford F-150 Regular Cab 2007 0.09% +1043 /scratch/Teaching/cars/car_ims/006241.jpg Chrysler Sebring Convertible 2010 Chrysler Town and Country Minivan 2012 62.98% Honda Odyssey Minivan 2007 30.19% Honda Accord Sedan 2012 3.11% Hyundai Veracruz SUV 2012 1.21% Chrysler Sebring Convertible 2010 1.0% +1044 /scratch/Teaching/cars/car_ims/016097.jpg Volvo XC90 SUV 2007 GMC Acadia SUV 2012 68.56% GMC Yukon Hybrid SUV 2012 14.59% Cadillac Escalade EXT Crew Cab 2007 6.32% Ford Freestar Minivan 2007 3.59% Volvo XC90 SUV 2007 2.31% +1045 /scratch/Teaching/cars/car_ims/006340.jpg Chrysler Town and Country Minivan 2012 Chrysler Town and Country Minivan 2012 89.83% Ram C/V Cargo Van Minivan 2012 4.17% Honda Odyssey Minivan 2007 3.16% Suzuki SX4 Sedan 2012 2.81% Dodge Caliber Wagon 2012 0.02% +1046 /scratch/Teaching/cars/car_ims/014079.jpg Nissan 240SX Coupe 1998 Eagle Talon Hatchback 1998 84.07% Plymouth Neon Coupe 1999 9.83% Nissan 240SX Coupe 1998 4.54% Ford Focus Sedan 2007 1.23% Hyundai Elantra Touring Hatchback 2012 0.07% +1047 /scratch/Teaching/cars/car_ims/009567.jpg Ford Fiesta Sedan 2012 Dodge Caravan Minivan 1997 18.21% Ford Fiesta Sedan 2012 16.87% Chrysler Sebring Convertible 2010 7.7% Hyundai Santa Fe SUV 2012 6.36% Ford Focus Sedan 2007 4.43% +1048 /scratch/Teaching/cars/car_ims/015538.jpg Toyota 4Runner SUV 2012 Toyota Sequoia SUV 2012 58.89% Toyota 4Runner SUV 2012 31.38% Land Rover LR2 SUV 2012 5.17% Mazda Tribute SUV 2011 2.65% GMC Acadia SUV 2012 1.05% +1049 /scratch/Teaching/cars/car_ims/013973.jpg Nissan Juke Hatchback 2012 Chevrolet Sonic Sedan 2012 37.78% Volvo C30 Hatchback 2012 24.26% Suzuki Kizashi Sedan 2012 13.5% Nissan Juke Hatchback 2012 8.89% Suzuki SX4 Hatchback 2012 4.41% +1050 /scratch/Teaching/cars/car_ims/012102.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 99.85% Jeep Patriot SUV 2012 0.13% BMW X5 SUV 2007 0.01% Jeep Grand Cherokee SUV 2012 0.0% Jeep Compass SUV 2012 0.0% +1051 /scratch/Teaching/cars/car_ims/008870.jpg Ford Expedition EL SUV 2009 Dodge Durango SUV 2012 43.58% Land Rover LR2 SUV 2012 25.32% Land Rover Range Rover SUV 2012 8.37% Ford Expedition EL SUV 2009 4.91% Toyota Sequoia SUV 2012 4.21% +1052 /scratch/Teaching/cars/car_ims/004459.jpg Chevrolet Corvette Convertible 2012 Chevrolet Corvette Convertible 2012 39.24% Chevrolet Monte Carlo Coupe 2007 19.99% Ferrari California Convertible 2012 8.07% Ferrari 458 Italia Convertible 2012 7.34% Jaguar XK XKR 2012 7.23% +1053 /scratch/Teaching/cars/car_ims/005611.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chevrolet Silverado 1500 Classic Extended Cab 2007 100.0% Ford Ranger SuperCab 2011 0.0% Chevrolet Silverado 1500 Extended Cab 2012 0.0% Audi 100 Sedan 1994 0.0% Chevrolet Silverado 2500HD Regular Cab 2012 0.0% +1054 /scratch/Teaching/cars/car_ims/016149.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 62.44% FIAT 500 Convertible 2012 11.16% Suzuki Kizashi Sedan 2012 8.02% Chevrolet Sonic Sedan 2012 7.3% Volvo C30 Hatchback 2012 4.79% +1055 /scratch/Teaching/cars/car_ims/012076.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 99.94% Jeep Patriot SUV 2012 0.06% Jeep Compass SUV 2012 0.0% BMW X5 SUV 2007 0.0% Jeep Grand Cherokee SUV 2012 0.0% +1056 /scratch/Teaching/cars/car_ims/012761.jpg Land Rover LR2 SUV 2012 Ford Expedition EL SUV 2009 55.85% Hyundai Santa Fe SUV 2012 24.72% Land Rover LR2 SUV 2012 6.19% Land Rover Range Rover SUV 2012 2.67% Toyota Sequoia SUV 2012 2.59% +1057 /scratch/Teaching/cars/car_ims/003792.jpg Buick Regal GS 2012 Buick Regal GS 2012 99.67% Chevrolet Sonic Sedan 2012 0.17% Suzuki Kizashi Sedan 2012 0.15% Buick Verano Sedan 2012 0.01% Mitsubishi Lancer Sedan 2012 0.0% +1058 /scratch/Teaching/cars/car_ims/014273.jpg Porsche Panamera Sedan 2012 Acura RL Sedan 2012 40.01% Buick Verano Sedan 2012 33.91% Acura TL Sedan 2012 9.11% Acura ZDX Hatchback 2012 6.3% Buick Regal GS 2012 3.37% +1059 /scratch/Teaching/cars/car_ims/007323.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 84.63% Dodge Caliber Wagon 2007 6.26% Dodge Caliber Wagon 2012 4.69% Dodge Durango SUV 2007 3.34% Dodge Journey SUV 2012 0.64% +1060 /scratch/Teaching/cars/car_ims/004675.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 99.82% Hyundai Veracruz SUV 2012 0.12% Hyundai Tucson SUV 2012 0.06% GMC Acadia SUV 2012 0.0% Buick Enclave SUV 2012 0.0% +1061 /scratch/Teaching/cars/car_ims/008262.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 95.85% Ferrari 458 Italia Coupe 2012 2.18% Ferrari 458 Italia Convertible 2012 0.97% Chevrolet Corvette Convertible 2012 0.81% Ferrari FF Coupe 2012 0.12% +1062 /scratch/Teaching/cars/car_ims/006998.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 99.19% Dodge Ram Pickup 3500 Quad Cab 2009 0.81% Dodge Durango SUV 2007 0.0% Ford F-450 Super Duty Crew Cab 2012 0.0% Chrysler Aspen SUV 2009 0.0% +1063 /scratch/Teaching/cars/car_ims/008120.jpg FIAT 500 Convertible 2012 FIAT 500 Convertible 2012 79.27% Chrysler PT Cruiser Convertible 2008 3.87% Mercedes-Benz Sprinter Van 2012 3.57% Maybach Landaulet Convertible 2012 3.37% smart fortwo Convertible 2012 2.12% +1064 /scratch/Teaching/cars/car_ims/009140.jpg Ford GT Coupe 2006 Aston Martin V8 Vantage Convertible 2012 28.79% Aston Martin V8 Vantage Coupe 2012 27.85% McLaren MP4-12C Coupe 2012 11.32% Chevrolet Corvette ZR1 2012 7.41% Lamborghini Aventador Coupe 2012 3.42% +1065 /scratch/Teaching/cars/car_ims/007690.jpg Dodge Durango SUV 2012 Dodge Journey SUV 2012 77.39% Dodge Durango SUV 2012 22.6% Dodge Caliber Wagon 2012 0.0% Chevrolet Malibu Sedan 2007 0.0% Ford Edge SUV 2012 0.0% +1066 /scratch/Teaching/cars/car_ims/001313.jpg Audi 100 Sedan 1994 Dodge Caravan Minivan 1997 35.67% Audi 100 Wagon 1994 19.15% Plymouth Neon Coupe 1999 16.92% Lincoln Town Car Sedan 2011 5.8% Ford Focus Sedan 2007 5.67% +1067 /scratch/Teaching/cars/car_ims/008110.jpg FIAT 500 Convertible 2012 FIAT 500 Convertible 2012 99.33% smart fortwo Convertible 2012 0.41% MINI Cooper Roadster Convertible 2012 0.14% Maybach Landaulet Convertible 2012 0.04% Nissan Juke Hatchback 2012 0.02% +1068 /scratch/Teaching/cars/car_ims/000989.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 83.54% Audi S4 Sedan 2007 11.19% Audi S4 Sedan 2012 2.85% Audi S5 Coupe 2012 2.29% Audi S5 Convertible 2012 0.05% +1069 /scratch/Teaching/cars/car_ims/007554.jpg Dodge Challenger SRT8 2011 Mercedes-Benz S-Class Sedan 2012 36.72% Mercedes-Benz C-Class Sedan 2012 21.32% Audi S4 Sedan 2007 7.87% Mercedes-Benz E-Class Sedan 2012 3.58% Chrysler Crossfire Convertible 2008 3.01% +1070 /scratch/Teaching/cars/car_ims/013859.jpg Nissan NV Passenger Van 2012 Chrysler PT Cruiser Convertible 2008 20.57% Nissan NV Passenger Van 2012 16.29% Nissan Juke Hatchback 2012 13.11% MINI Cooper Roadster Convertible 2012 7.25% Ford F-150 Regular Cab 2012 6.71% +1071 /scratch/Teaching/cars/car_ims/011773.jpg Jaguar XK XKR 2012 Jaguar XK XKR 2012 74.93% Chevrolet Corvette Ron Fellows Edition Z06 2007 21.61% Porsche Panamera Sedan 2012 0.72% Aston Martin V8 Vantage Coupe 2012 0.6% Chevrolet Corvette ZR1 2012 0.46% +1072 /scratch/Teaching/cars/car_ims/015588.jpg Volkswagen Golf Hatchback 2012 Suzuki SX4 Sedan 2012 54.03% Buick Verano Sedan 2012 13.93% Hyundai Veracruz SUV 2012 5.89% Acura ZDX Hatchback 2012 3.95% Cadillac SRX SUV 2012 3.39% +1073 /scratch/Teaching/cars/car_ims/000592.jpg Aston Martin V8 Vantage Convertible 2012 Suzuki Kizashi Sedan 2012 38.48% Hyundai Veloster Hatchback 2012 7.62% Volvo C30 Hatchback 2012 5.09% BMW 1 Series Coupe 2012 4.41% Volkswagen Golf Hatchback 2012 3.99% +1074 /scratch/Teaching/cars/car_ims/014017.jpg Nissan 240SX Coupe 1998 Audi 100 Wagon 1994 33.03% Volvo 240 Sedan 1993 30.79% Lincoln Town Car Sedan 2011 12.47% Audi 100 Sedan 1994 5.69% Audi V8 Sedan 1994 4.73% +1075 /scratch/Teaching/cars/car_ims/007508.jpg Dodge Magnum Wagon 2008 Chevrolet HHR SS 2010 28.37% Dodge Magnum Wagon 2008 13.88% BMW 3 Series Sedan 2012 12.5% BMW 3 Series Wagon 2012 9.37% BMW 1 Series Coupe 2012 8.19% +1076 /scratch/Teaching/cars/car_ims/014750.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 99.98% Spyker C8 Coupe 2009 0.02% Bugatti Veyron 16.4 Coupe 2009 0.0% Ford GT Coupe 2006 0.0% FIAT 500 Abarth 2012 0.0% +1077 /scratch/Teaching/cars/car_ims/009180.jpg Ford GT Coupe 2006 Ford GT Coupe 2006 33.75% Rolls-Royce Phantom Sedan 2012 23.88% Bentley Continental Supersports Conv. Convertible 2012 13.32% Rolls-Royce Phantom Drophead Coupe Convertible 2012 7.42% Bentley Arnage Sedan 2009 3.46% +1078 /scratch/Teaching/cars/car_ims/000686.jpg Aston Martin V8 Vantage Coupe 2012 Aston Martin V8 Vantage Coupe 2012 40.19% Aston Martin Virage Coupe 2012 17.43% Spyker C8 Coupe 2009 9.25% Ferrari California Convertible 2012 7.3% Jaguar XK XKR 2012 6.2% +1079 /scratch/Teaching/cars/car_ims/004701.jpg Chevrolet Traverse SUV 2012 Hyundai Veracruz SUV 2012 84.14% Chevrolet Traverse SUV 2012 12.25% Hyundai Tucson SUV 2012 3.61% Acura ZDX Hatchback 2012 0.0% Buick Enclave SUV 2012 0.0% +1080 /scratch/Teaching/cars/car_ims/011950.jpg Jeep Wrangler SUV 2012 Ford Mustang Convertible 2007 15.93% Dodge Dakota Crew Cab 2010 8.92% Volvo XC90 SUV 2007 5.29% Ford Ranger SuperCab 2011 4.56% Dodge Caliber Wagon 2007 3.87% +1081 /scratch/Teaching/cars/car_ims/015611.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 99.75% Honda Accord Sedan 2012 0.19% Toyota Camry Sedan 2012 0.04% Acura TSX Sedan 2012 0.0% Hyundai Accent Sedan 2012 0.0% +1082 /scratch/Teaching/cars/car_ims/004995.jpg Chevrolet Tahoe Hybrid SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 93.32% Chevrolet Avalanche Crew Cab 2012 5.21% Chevrolet TrailBlazer SS 2009 1.11% Isuzu Ascender SUV 2008 0.17% GMC Yukon Hybrid SUV 2012 0.11% +1083 /scratch/Teaching/cars/car_ims/003748.jpg Buick Regal GS 2012 Acura TL Type-S 2008 73.85% Honda Accord Coupe 2012 9.14% BMW 3 Series Wagon 2012 7.64% Mitsubishi Lancer Sedan 2012 2.4% Honda Accord Sedan 2012 1.9% +1084 /scratch/Teaching/cars/car_ims/015992.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 99.76% Rolls-Royce Phantom Sedan 2012 0.23% Lincoln Town Car Sedan 2011 0.01% Rolls-Royce Ghost Sedan 2012 0.0% Chrysler 300 SRT-8 2010 0.0% +1085 /scratch/Teaching/cars/car_ims/008030.jpg Eagle Talon Hatchback 1998 Aston Martin V8 Vantage Coupe 2012 71.36% Eagle Talon Hatchback 1998 8.82% Aston Martin V8 Vantage Convertible 2012 8.75% Nissan 240SX Coupe 1998 3.42% Aston Martin Virage Convertible 2012 1.7% +1086 /scratch/Teaching/cars/car_ims/002055.jpg BMW ActiveHybrid 5 Sedan 2012 Acura TL Type-S 2008 91.44% BMW M5 Sedan 2010 3.19% BMW 3 Series Wagon 2012 2.03% BMW 3 Series Sedan 2012 1.24% Porsche Panamera Sedan 2012 0.69% +1087 /scratch/Teaching/cars/car_ims/015999.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 99.99% Lincoln Town Car Sedan 2011 0.01% Audi 100 Wagon 1994 0.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Volkswagen Golf Hatchback 1991 0.0% +1088 /scratch/Teaching/cars/car_ims/009576.jpg Ford Fiesta Sedan 2012 Ford Fiesta Sedan 2012 99.91% Hyundai Tucson SUV 2012 0.06% Hyundai Accent Sedan 2012 0.03% Scion xD Hatchback 2012 0.0% Hyundai Veloster Hatchback 2012 0.0% +1089 /scratch/Teaching/cars/car_ims/015026.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 84.64% Chevrolet Sonic Sedan 2012 8.54% Volvo C30 Hatchback 2012 1.96% Toyota Corolla Sedan 2012 1.7% Scion xD Hatchback 2012 0.97% +1090 /scratch/Teaching/cars/car_ims/001039.jpg Audi A5 Coupe 2012 Audi S5 Coupe 2012 44.58% Audi A5 Coupe 2012 38.81% Audi S4 Sedan 2007 10.17% Audi S4 Sedan 2012 4.67% Audi S5 Convertible 2012 1.19% +1091 /scratch/Teaching/cars/car_ims/013301.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 76.34% Hyundai Genesis Sedan 2012 12.78% Mercedes-Benz S-Class Sedan 2012 4.96% Mercedes-Benz E-Class Sedan 2012 3.51% Mercedes-Benz SL-Class Coupe 2009 1.47% +1092 /scratch/Teaching/cars/car_ims/008407.jpg Ferrari 458 Italia Convertible 2012 Ferrari 458 Italia Convertible 2012 50.0% Ferrari 458 Italia Coupe 2012 10.39% Lamborghini Aventador Coupe 2012 8.29% Spyker C8 Coupe 2009 8.24% McLaren MP4-12C Coupe 2012 7.0% +1093 /scratch/Teaching/cars/car_ims/000568.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 99.5% Hyundai Veracruz SUV 2012 0.16% Acura RL Sedan 2012 0.12% Acura TL Sedan 2012 0.08% Acura TSX Sedan 2012 0.05% +1094 /scratch/Teaching/cars/car_ims/010012.jpg GMC Canyon Extended Cab 2012 Dodge Ram Pickup 3500 Quad Cab 2009 20.47% Chevrolet Silverado 2500HD Regular Cab 2012 19.29% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 15.89% GMC Canyon Extended Cab 2012 14.95% Chevrolet Silverado 1500 Classic Extended Cab 2007 9.87% +1095 /scratch/Teaching/cars/car_ims/013059.jpg McLaren MP4-12C Coupe 2012 McLaren MP4-12C Coupe 2012 67.06% Ferrari 458 Italia Coupe 2012 14.27% Ferrari 458 Italia Convertible 2012 12.93% Chevrolet Corvette Convertible 2012 1.47% Aston Martin Virage Coupe 2012 1.23% +1096 /scratch/Teaching/cars/car_ims/009753.jpg GMC Savana Van 2012 GMC Savana Van 2012 39.59% Volkswagen Golf Hatchback 1991 17.65% Dodge Ram Pickup 3500 Crew Cab 2010 15.1% Dodge Ram Pickup 3500 Quad Cab 2009 15.01% Audi 100 Sedan 1994 4.2% +1097 /scratch/Teaching/cars/car_ims/010563.jpg Honda Accord Coupe 2012 Honda Accord Coupe 2012 99.97% Chevrolet Cobalt SS 2010 0.01% Acura TL Type-S 2008 0.01% Nissan 240SX Coupe 1998 0.0% Toyota Corolla Sedan 2012 0.0% +1098 /scratch/Teaching/cars/car_ims/004714.jpg Chevrolet Traverse SUV 2012 Chevrolet Traverse SUV 2012 99.86% Hyundai Veracruz SUV 2012 0.13% Hyundai Tucson SUV 2012 0.01% GMC Acadia SUV 2012 0.0% Buick Enclave SUV 2012 0.0% +1099 /scratch/Teaching/cars/car_ims/002407.jpg BMW 3 Series Wagon 2012 Chevrolet Malibu Sedan 2007 34.16% Honda Odyssey Minivan 2012 23.57% Chevrolet Impala Sedan 2007 22.17% Acura TL Type-S 2008 8.42% Chevrolet Cobalt SS 2010 2.8% +1100 /scratch/Teaching/cars/car_ims/015130.jpg Suzuki SX4 Sedan 2012 Suzuki SX4 Sedan 2012 99.98% Suzuki Aerio Sedan 2007 0.02% Hyundai Elantra Sedan 2007 0.0% Ram C/V Cargo Van Minivan 2012 0.0% Acura TSX Sedan 2012 0.0% +1101 /scratch/Teaching/cars/car_ims/008515.jpg Fisker Karma Sedan 2012 Daewoo Nubira Wagon 2002 69.28% BMW X5 SUV 2007 4.45% Maybach Landaulet Convertible 2012 2.99% Suzuki Aerio Sedan 2007 2.86% Suzuki SX4 Sedan 2012 2.49% +1102 /scratch/Teaching/cars/car_ims/012610.jpg Land Rover Range Rover SUV 2012 Land Rover Range Rover SUV 2012 83.17% Chevrolet Avalanche Crew Cab 2012 6.96% Chevrolet TrailBlazer SS 2009 5.8% Chevrolet Tahoe Hybrid SUV 2012 1.66% Dodge Durango SUV 2012 1.25% +1103 /scratch/Teaching/cars/car_ims/004795.jpg Chevrolet Camaro Convertible 2012 Fisker Karma Sedan 2012 54.15% BMW M6 Convertible 2010 14.71% BMW 6 Series Convertible 2007 10.95% Tesla Model S Sedan 2012 6.39% Aston Martin V8 Vantage Coupe 2012 4.46% +1104 /scratch/Teaching/cars/car_ims/006544.jpg Chrysler PT Cruiser Convertible 2008 Mercedes-Benz E-Class Sedan 2012 47.32% Infiniti QX56 SUV 2011 18.51% Mercedes-Benz S-Class Sedan 2012 11.44% Chrysler PT Cruiser Convertible 2008 7.69% Cadillac SRX SUV 2012 6.44% +1105 /scratch/Teaching/cars/car_ims/001975.jpg Audi S4 Sedan 2007 Audi S4 Sedan 2007 65.15% Audi S6 Sedan 2011 24.13% Audi A5 Coupe 2012 5.67% Rolls-Royce Ghost Sedan 2012 4.01% Audi RS 4 Convertible 2008 0.54% +1106 /scratch/Teaching/cars/car_ims/000017.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 97.16% Jeep Wrangler SUV 2012 1.41% GMC Savana Van 2012 0.7% Jeep Patriot SUV 2012 0.52% Chevrolet Express Van 2007 0.07% +1107 /scratch/Teaching/cars/car_ims/012250.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 99.3% Jeep Grand Cherokee SUV 2012 0.61% Jeep Patriot SUV 2012 0.09% Jeep Liberty SUV 2012 0.0% GMC Terrain SUV 2012 0.0% +1108 /scratch/Teaching/cars/car_ims/009230.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2007 84.94% Ford F-150 Regular Cab 2012 8.95% Ford E-Series Wagon Van 2012 5.39% Ford Ranger SuperCab 2011 0.56% Nissan NV Passenger Van 2012 0.14% +1109 /scratch/Teaching/cars/car_ims/009058.jpg Ford Ranger SuperCab 2011 Ford F-150 Regular Cab 2007 42.63% Ford Ranger SuperCab 2011 18.74% Audi 100 Wagon 1994 10.48% Audi 100 Sedan 1994 8.53% Ford Freestar Minivan 2007 3.98% +1110 /scratch/Teaching/cars/car_ims/015778.jpg Volkswagen Beetle Hatchback 2012 BMW 6 Series Convertible 2007 36.67% BMW M6 Convertible 2010 11.53% Acura TL Type-S 2008 8.48% Jaguar XK XKR 2012 6.76% Chevrolet Monte Carlo Coupe 2007 3.82% +1111 /scratch/Teaching/cars/car_ims/005742.jpg Chevrolet Express Van 2007 Chevrolet Express Cargo Van 2007 59.24% GMC Savana Van 2012 32.42% Chevrolet Express Van 2007 8.34% Nissan NV Passenger Van 2012 0.0% Dodge Sprinter Cargo Van 2009 0.0% +1112 /scratch/Teaching/cars/car_ims/005803.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Monte Carlo Coupe 2007 76.95% Chevrolet Impala Sedan 2007 20.49% Chevrolet Malibu Hybrid Sedan 2010 1.22% Chevrolet Malibu Sedan 2007 0.76% Chevrolet Cobalt SS 2010 0.41% +1113 /scratch/Teaching/cars/car_ims/004059.jpg Cadillac CTS-V Sedan 2012 BMW M5 Sedan 2010 50.45% Mitsubishi Lancer Sedan 2012 11.15% BMW 3 Series Wagon 2012 7.01% Infiniti G Coupe IPL 2012 6.0% Suzuki Kizashi Sedan 2012 5.14% +1114 /scratch/Teaching/cars/car_ims/010921.jpg Hyundai Tucson SUV 2012 Hyundai Veracruz SUV 2012 33.04% Chevrolet Traverse SUV 2012 14.06% Hyundai Elantra Touring Hatchback 2012 13.9% Hyundai Tucson SUV 2012 9.35% Buick Enclave SUV 2012 7.6% +1115 /scratch/Teaching/cars/car_ims/001738.jpg Audi S5 Coupe 2012 Audi S5 Convertible 2012 54.96% Audi S4 Sedan 2012 34.76% Audi S5 Coupe 2012 4.9% Audi TT Hatchback 2011 2.44% Audi A5 Coupe 2012 2.04% +1116 /scratch/Teaching/cars/car_ims/015727.jpg Volkswagen Golf Hatchback 1991 Volkswagen Golf Hatchback 1991 84.08% Audi 100 Wagon 1994 3.24% Audi V8 Sedan 1994 2.1% Buick Rainier SUV 2007 1.54% Daewoo Nubira Wagon 2002 1.15% +1117 /scratch/Teaching/cars/car_ims/011005.jpg Hyundai Veracruz SUV 2012 Hyundai Veracruz SUV 2012 92.09% Acura ZDX Hatchback 2012 2.84% Cadillac SRX SUV 2012 1.8% Buick Enclave SUV 2012 0.79% Nissan Juke Hatchback 2012 0.63% +1118 /scratch/Teaching/cars/car_ims/012806.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 100.0% Audi 100 Wagon 1994 0.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Ford Freestar Minivan 2007 0.0% Chevrolet Malibu Sedan 2007 0.0% +1119 /scratch/Teaching/cars/car_ims/011874.jpg Jeep Patriot SUV 2012 Jeep Compass SUV 2012 51.0% Jeep Patriot SUV 2012 16.21% Bentley Continental Supersports Conv. Convertible 2012 5.82% Rolls-Royce Phantom Sedan 2012 5.23% Jeep Liberty SUV 2012 5.15% +1120 /scratch/Teaching/cars/car_ims/013938.jpg Nissan Juke Hatchback 2012 Nissan Leaf Hatchback 2012 68.81% Ford Fiesta Sedan 2012 25.94% Scion xD Hatchback 2012 3.18% Nissan Juke Hatchback 2012 1.39% Hyundai Veloster Hatchback 2012 0.27% +1121 /scratch/Teaching/cars/car_ims/001564.jpg Audi S6 Sedan 2011 Mitsubishi Lancer Sedan 2012 78.37% Acura TL Type-S 2008 7.03% BMW 3 Series Wagon 2012 4.82% Acura RL Sedan 2012 2.55% Chevrolet Malibu Hybrid Sedan 2010 1.28% +1122 /scratch/Teaching/cars/car_ims/008698.jpg Ford Mustang Convertible 2007 Audi V8 Sedan 1994 47.57% Audi 100 Sedan 1994 17.15% Ford Mustang Convertible 2007 16.66% Audi 100 Wagon 1994 4.77% Acura Integra Type R 2001 4.67% +1123 /scratch/Teaching/cars/car_ims/005863.jpg Chevrolet Malibu Sedan 2007 Chevrolet Malibu Sedan 2007 93.62% Ram C/V Cargo Van Minivan 2012 6.28% Suzuki SX4 Sedan 2012 0.07% Chevrolet Impala Sedan 2007 0.02% Honda Odyssey Minivan 2007 0.0% +1124 /scratch/Teaching/cars/car_ims/000378.jpg Acura TSX Sedan 2012 Acura TL Sedan 2012 53.35% Acura TSX Sedan 2012 38.84% Acura RL Sedan 2012 7.63% Acura ZDX Hatchback 2012 0.17% Toyota Camry Sedan 2012 0.01% +1125 /scratch/Teaching/cars/car_ims/006093.jpg Chevrolet Silverado 1500 Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 93.88% Chevrolet Silverado 2500HD Regular Cab 2012 5.08% Chevrolet Silverado 1500 Extended Cab 2012 0.65% Chevrolet Avalanche Crew Cab 2012 0.22% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.16% +1126 /scratch/Teaching/cars/car_ims/015490.jpg Toyota Corolla Sedan 2012 Chevrolet Malibu Sedan 2007 73.72% Hyundai Elantra Sedan 2007 22.14% Toyota Corolla Sedan 2012 1.46% Honda Odyssey Minivan 2007 1.16% Chevrolet Impala Sedan 2007 0.67% +1127 /scratch/Teaching/cars/car_ims/015847.jpg Volvo C30 Hatchback 2012 Volvo C30 Hatchback 2012 88.18% Chevrolet HHR SS 2010 10.44% Mitsubishi Lancer Sedan 2012 1.0% Chevrolet Sonic Sedan 2012 0.14% Dodge Charger Sedan 2012 0.14% +1128 /scratch/Teaching/cars/car_ims/005267.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet TrailBlazer SS 2009 18.78% Ford Ranger SuperCab 2011 11.55% Chevrolet Silverado 1500 Classic Extended Cab 2007 9.9% Volkswagen Golf Hatchback 1991 7.12% Ford Expedition EL SUV 2009 7.11% +1129 /scratch/Teaching/cars/car_ims/014061.jpg Nissan 240SX Coupe 1998 Audi R8 Coupe 2012 38.25% BMW 3 Series Sedan 2012 17.73% BMW M3 Coupe 2012 6.68% BMW M6 Convertible 2010 6.07% Audi RS 4 Convertible 2008 4.81% +1130 /scratch/Teaching/cars/car_ims/003691.jpg Bugatti Veyron 16.4 Coupe 2009 Eagle Talon Hatchback 1998 99.54% Nissan 240SX Coupe 1998 0.34% Chevrolet Camaro Convertible 2012 0.07% Audi R8 Coupe 2012 0.02% BMW M6 Convertible 2010 0.02% +1131 /scratch/Teaching/cars/car_ims/009509.jpg Ford E-Series Wagon Van 2012 Ford E-Series Wagon Van 2012 97.42% Ford F-150 Regular Cab 2012 1.46% Ford F-450 Super Duty Crew Cab 2012 1.05% Nissan NV Passenger Van 2012 0.06% Chrysler Aspen SUV 2009 0.01% +1132 /scratch/Teaching/cars/car_ims/006354.jpg Chrysler 300 SRT-8 2010 Rolls-Royce Ghost Sedan 2012 50.05% Dodge Challenger SRT8 2011 16.07% Chevrolet Malibu Hybrid Sedan 2010 12.51% Chrysler 300 SRT-8 2010 5.26% Rolls-Royce Phantom Sedan 2012 4.63% +1133 /scratch/Teaching/cars/car_ims/007736.jpg Dodge Durango SUV 2007 Jeep Liberty SUV 2012 77.42% Jeep Patriot SUV 2012 8.58% Buick Rainier SUV 2007 4.36% Isuzu Ascender SUV 2008 3.34% Mazda Tribute SUV 2011 1.74% +1134 /scratch/Teaching/cars/car_ims/010883.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 97.68% Hyundai Veracruz SUV 2012 1.82% Chevrolet Traverse SUV 2012 0.48% Ford Fiesta Sedan 2012 0.01% Buick Enclave SUV 2012 0.0% +1135 /scratch/Teaching/cars/car_ims/014271.jpg Porsche Panamera Sedan 2012 Toyota Camry Sedan 2012 46.74% Acura TSX Sedan 2012 12.61% Toyota Corolla Sedan 2012 5.38% Hyundai Elantra Sedan 2007 4.55% Buick Verano Sedan 2012 4.49% +1136 /scratch/Teaching/cars/car_ims/002762.jpg BMW M3 Coupe 2012 BMW M3 Coupe 2012 71.65% BMW 1 Series Coupe 2012 11.28% BMW Z4 Convertible 2012 4.43% Dodge Charger Sedan 2012 2.31% BMW 1 Series Convertible 2012 2.13% +1137 /scratch/Teaching/cars/car_ims/011888.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 99.86% Jeep Liberty SUV 2012 0.1% Jeep Wrangler SUV 2012 0.02% GMC Yukon Hybrid SUV 2012 0.02% Jeep Compass SUV 2012 0.0% +1138 /scratch/Teaching/cars/car_ims/000751.jpg Aston Martin Virage Convertible 2012 BMW 6 Series Convertible 2007 54.86% BMW M6 Convertible 2010 15.27% Aston Martin Virage Convertible 2012 11.21% Jaguar XK XKR 2012 10.22% Infiniti G Coupe IPL 2012 2.03% +1139 /scratch/Teaching/cars/car_ims/007403.jpg Dodge Dakota Club Cab 2007 Cadillac Escalade EXT Crew Cab 2007 52.39% Dodge Durango SUV 2007 27.65% Volvo XC90 SUV 2007 5.09% Isuzu Ascender SUV 2008 4.98% Dodge Magnum Wagon 2008 3.16% +1140 /scratch/Teaching/cars/car_ims/009025.jpg Ford Ranger SuperCab 2011 Dodge Dakota Club Cab 2007 18.53% Chevrolet Silverado 2500HD Regular Cab 2012 18.08% Chevrolet Silverado 1500 Extended Cab 2012 16.49% GMC Canyon Extended Cab 2012 11.75% Chevrolet Silverado 1500 Classic Extended Cab 2007 10.15% +1141 /scratch/Teaching/cars/car_ims/013509.jpg Mercedes-Benz S-Class Sedan 2012 Mercedes-Benz S-Class Sedan 2012 88.73% Mercedes-Benz C-Class Sedan 2012 8.55% Mercedes-Benz E-Class Sedan 2012 1.72% Mercedes-Benz SL-Class Coupe 2009 0.69% Hyundai Genesis Sedan 2012 0.25% +1142 /scratch/Teaching/cars/car_ims/001054.jpg Audi TTS Coupe 2012 Audi TTS Coupe 2012 27.66% Audi TT Hatchback 2011 22.43% Audi S5 Coupe 2012 9.03% Bentley Continental GT Coupe 2012 5.59% Cadillac CTS-V Sedan 2012 4.55% +1143 /scratch/Teaching/cars/car_ims/014942.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 97.34% Chevrolet Sonic Sedan 2012 1.54% Buick Verano Sedan 2012 0.56% Cadillac SRX SUV 2012 0.25% Cadillac CTS-V Sedan 2012 0.18% +1144 /scratch/Teaching/cars/car_ims/008194.jpg Ferrari FF Coupe 2012 McLaren MP4-12C Coupe 2012 7.92% HUMMER H2 SUT Crew Cab 2009 5.44% Lamborghini Diablo Coupe 2001 5.32% Lamborghini Aventador Coupe 2012 4.72% AM General Hummer SUV 2000 4.58% +1145 /scratch/Teaching/cars/car_ims/006466.jpg Chrysler Crossfire Convertible 2008 Chevrolet Camaro Convertible 2012 71.51% BMW M6 Convertible 2010 17.94% BMW 6 Series Convertible 2007 7.82% Jaguar XK XKR 2012 0.59% Aston Martin V8 Vantage Convertible 2012 0.58% +1146 /scratch/Teaching/cars/car_ims/013641.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 79.42% Dodge Sprinter Cargo Van 2009 20.58% Ram C/V Cargo Van Minivan 2012 0.0% Chrysler Town and Country Minivan 2012 0.0% Audi 100 Wagon 1994 0.0% +1147 /scratch/Teaching/cars/car_ims/013204.jpg Mercedes-Benz 300-Class Convertible 1993 BMW 6 Series Convertible 2007 30.25% Chevrolet Monte Carlo Coupe 2007 25.35% BMW M6 Convertible 2010 21.08% Nissan 240SX Coupe 1998 9.49% Mercedes-Benz 300-Class Convertible 1993 5.08% +1148 /scratch/Teaching/cars/car_ims/000208.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 34.37% Acura TSX Sedan 2012 33.02% Acura RL Sedan 2012 16.69% Acura ZDX Hatchback 2012 15.88% Hyundai Sonata Hybrid Sedan 2012 0.02% +1149 /scratch/Teaching/cars/car_ims/015286.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 69.49% Mazda Tribute SUV 2011 12.35% Land Rover LR2 SUV 2012 6.73% Chrysler Town and Country Minivan 2012 2.82% Hyundai Santa Fe SUV 2012 1.99% +1150 /scratch/Teaching/cars/car_ims/009923.jpg GMC Acadia SUV 2012 Buick Enclave SUV 2012 25.53% Hyundai Santa Fe SUV 2012 12.7% Chevrolet Traverse SUV 2012 11.27% Volvo XC90 SUV 2007 10.73% GMC Acadia SUV 2012 6.5% +1151 /scratch/Teaching/cars/car_ims/003545.jpg Bentley Continental Flying Spur Sedan 2007 Bentley Continental Flying Spur Sedan 2007 57.28% BMW ActiveHybrid 5 Sedan 2012 22.94% Acura RL Sedan 2012 5.28% Maybach Landaulet Convertible 2012 5.07% Chevrolet Malibu Hybrid Sedan 2010 4.9% +1152 /scratch/Teaching/cars/car_ims/009202.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 48.4% Ford E-Series Wagon Van 2012 19.08% Ford F-150 Regular Cab 2007 17.83% Ford Ranger SuperCab 2011 3.58% Nissan NV Passenger Van 2012 2.16% +1153 /scratch/Teaching/cars/car_ims/009857.jpg GMC Yukon Hybrid SUV 2012 GMC Yukon Hybrid SUV 2012 98.06% Ford F-150 Regular Cab 2007 1.61% Cadillac Escalade EXT Crew Cab 2007 0.3% Ford F-150 Regular Cab 2012 0.02% Chevrolet Avalanche Crew Cab 2012 0.01% +1154 /scratch/Teaching/cars/car_ims/015306.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.95% Mazda Tribute SUV 2011 0.04% Land Rover LR2 SUV 2012 0.01% Toyota 4Runner SUV 2012 0.0% GMC Acadia SUV 2012 0.0% +1155 /scratch/Teaching/cars/car_ims/010908.jpg Hyundai Tucson SUV 2012 Hyundai Veracruz SUV 2012 49.57% Hyundai Tucson SUV 2012 49.42% Chevrolet Traverse SUV 2012 1.0% Buick Enclave SUV 2012 0.01% Nissan Juke Hatchback 2012 0.0% +1156 /scratch/Teaching/cars/car_ims/011179.jpg Hyundai Accent Sedan 2012 Toyota Corolla Sedan 2012 29.99% Hyundai Accent Sedan 2012 29.44% Toyota Camry Sedan 2012 19.89% Chevrolet Sonic Sedan 2012 6.75% Mitsubishi Lancer Sedan 2012 3.0% +1157 /scratch/Teaching/cars/car_ims/003435.jpg Bentley Continental GT Coupe 2007 Bentley Continental Supersports Conv. Convertible 2012 15.75% Rolls-Royce Phantom Sedan 2012 11.9% Audi R8 Coupe 2012 9.41% Lamborghini Aventador Coupe 2012 8.96% Rolls-Royce Phantom Drophead Coupe Convertible 2012 6.65% +1158 /scratch/Teaching/cars/car_ims/009602.jpg Ford Fiesta Sedan 2012 Scion xD Hatchback 2012 59.02% Hyundai Tucson SUV 2012 37.12% Hyundai Veracruz SUV 2012 2.89% Ford Fiesta Sedan 2012 0.93% Chevrolet Traverse SUV 2012 0.04% +1159 /scratch/Teaching/cars/car_ims/013038.jpg Mazda Tribute SUV 2011 Mazda Tribute SUV 2011 98.11% Suzuki SX4 Hatchback 2012 1.37% GMC Acadia SUV 2012 0.23% Jeep Compass SUV 2012 0.04% Dodge Caliber Wagon 2012 0.03% +1160 /scratch/Teaching/cars/car_ims/005572.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 62.13% Chevrolet Silverado 2500HD Regular Cab 2012 20.02% Chevrolet Silverado 1500 Extended Cab 2012 9.08% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 8.72% Chevrolet Avalanche Crew Cab 2012 0.03% +1161 /scratch/Teaching/cars/car_ims/000093.jpg Acura RL Sedan 2012 Acura RL Sedan 2012 99.23% Suzuki SX4 Sedan 2012 0.27% Honda Accord Sedan 2012 0.18% Acura TSX Sedan 2012 0.18% Acura TL Type-S 2008 0.12% +1162 /scratch/Teaching/cars/car_ims/006588.jpg Chrysler PT Cruiser Convertible 2008 BMW X3 SUV 2012 38.91% Chrysler PT Cruiser Convertible 2008 14.43% Land Rover LR2 SUV 2012 11.18% Land Rover Range Rover SUV 2012 7.11% Cadillac SRX SUV 2012 3.84% +1163 /scratch/Teaching/cars/car_ims/004105.jpg Cadillac CTS-V Sedan 2012 Cadillac CTS-V Sedan 2012 69.38% MINI Cooper Roadster Convertible 2012 30.6% Suzuki Kizashi Sedan 2012 0.01% Bentley Mulsanne Sedan 2011 0.0% Bentley Continental GT Coupe 2012 0.0% +1164 /scratch/Teaching/cars/car_ims/015664.jpg Volkswagen Golf Hatchback 2012 Chevrolet Impala Sedan 2007 75.93% Chevrolet Malibu Sedan 2007 16.85% Chevrolet Malibu Hybrid Sedan 2010 5.07% Chevrolet Monte Carlo Coupe 2007 1.61% Honda Odyssey Minivan 2012 0.19% +1165 /scratch/Teaching/cars/car_ims/013306.jpg Mercedes-Benz C-Class Sedan 2012 Acura TL Type-S 2008 33.44% Mercedes-Benz C-Class Sedan 2012 28.38% Honda Accord Coupe 2012 18.03% Hyundai Genesis Sedan 2012 4.39% BMW 3 Series Sedan 2012 3.12% +1166 /scratch/Teaching/cars/car_ims/002824.jpg BMW M5 Sedan 2010 BMW M5 Sedan 2010 97.06% BMW M3 Coupe 2012 1.38% BMW 3 Series Wagon 2012 0.89% Acura TL Type-S 2008 0.21% Mitsubishi Lancer Sedan 2012 0.07% +1167 /scratch/Teaching/cars/car_ims/004726.jpg Chevrolet Camaro Convertible 2012 Ford Mustang Convertible 2007 57.97% Chrysler Crossfire Convertible 2008 24.17% Chevrolet Camaro Convertible 2012 14.48% BMW 1 Series Convertible 2012 2.04% Audi RS 4 Convertible 2008 0.42% +1168 /scratch/Teaching/cars/car_ims/007118.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Ford F-150 Regular Cab 2007 62.37% GMC Canyon Extended Cab 2012 20.93% Ford F-150 Regular Cab 2012 10.91% Dodge Dakota Club Cab 2007 2.58% Ford Ranger SuperCab 2011 1.09% +1169 /scratch/Teaching/cars/car_ims/014786.jpg Spyker C8 Coupe 2009 Spyker C8 Convertible 2009 79.12% Spyker C8 Coupe 2009 7.84% Aston Martin Virage Coupe 2012 6.74% Aston Martin Virage Convertible 2012 3.13% Fisker Karma Sedan 2012 2.0% +1170 /scratch/Teaching/cars/car_ims/013280.jpg Mercedes-Benz C-Class Sedan 2012 Chrysler Sebring Convertible 2010 39.75% Chevrolet Cobalt SS 2010 18.9% Chrysler Crossfire Convertible 2008 11.97% Honda Accord Sedan 2012 7.56% Hyundai Genesis Sedan 2012 5.58% +1171 /scratch/Teaching/cars/car_ims/010762.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 98.81% Dodge Journey SUV 2012 0.34% Hyundai Veracruz SUV 2012 0.2% Chevrolet Traverse SUV 2012 0.19% Mazda Tribute SUV 2011 0.14% +1172 /scratch/Teaching/cars/car_ims/015885.jpg Volvo C30 Hatchback 2012 Suzuki Kizashi Sedan 2012 32.36% Volkswagen Beetle Hatchback 2012 9.73% Volvo C30 Hatchback 2012 6.66% Suzuki SX4 Hatchback 2012 6.42% BMW 1 Series Coupe 2012 5.87% +1173 /scratch/Teaching/cars/car_ims/010409.jpg Honda Odyssey Minivan 2012 Honda Odyssey Minivan 2007 63.13% Honda Odyssey Minivan 2012 36.69% Hyundai Veracruz SUV 2012 0.1% Hyundai Elantra Sedan 2007 0.07% Honda Accord Sedan 2012 0.02% +1174 /scratch/Teaching/cars/car_ims/012344.jpg Lamborghini Reventon Coupe 2008 Lamborghini Reventon Coupe 2008 99.91% Lamborghini Aventador Coupe 2012 0.08% Audi R8 Coupe 2012 0.01% Bugatti Veyron 16.4 Coupe 2009 0.01% Aston Martin V8 Vantage Coupe 2012 0.0% +1175 /scratch/Teaching/cars/car_ims/001648.jpg Audi S5 Convertible 2012 Audi S5 Convertible 2012 46.34% Audi RS 4 Convertible 2008 39.4% BMW 1 Series Convertible 2012 5.85% Audi S5 Coupe 2012 2.61% BMW Z4 Convertible 2012 1.88% +1176 /scratch/Teaching/cars/car_ims/005555.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 38.17% Chevrolet Silverado 1500 Regular Cab 2012 24.6% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 19.63% Chevrolet Silverado 1500 Extended Cab 2012 14.92% GMC Canyon Extended Cab 2012 1.85% +1177 /scratch/Teaching/cars/car_ims/006375.jpg Chrysler 300 SRT-8 2010 Chrysler 300 SRT-8 2010 46.5% Dodge Charger Sedan 2012 21.36% Dodge Charger SRT-8 2009 13.03% Dodge Magnum Wagon 2008 9.16% Chevrolet TrailBlazer SS 2009 2.46% +1178 /scratch/Teaching/cars/car_ims/015238.jpg Tesla Model S Sedan 2012 Tesla Model S Sedan 2012 100.0% Fisker Karma Sedan 2012 0.0% Aston Martin V8 Vantage Coupe 2012 0.0% BMW M6 Convertible 2010 0.0% BMW 6 Series Convertible 2007 0.0% +1179 /scratch/Teaching/cars/car_ims/004215.jpg Cadillac SRX SUV 2012 Cadillac SRX SUV 2012 99.98% Cadillac Escalade EXT Crew Cab 2007 0.01% Land Rover LR2 SUV 2012 0.0% Toyota 4Runner SUV 2012 0.0% GMC Acadia SUV 2012 0.0% +1180 /scratch/Teaching/cars/car_ims/001301.jpg Audi 100 Sedan 1994 Audi 100 Sedan 1994 57.3% Audi V8 Sedan 1994 39.23% Audi 100 Wagon 1994 2.65% Volkswagen Golf Hatchback 1991 0.66% Mercedes-Benz 300-Class Convertible 1993 0.07% +1181 /scratch/Teaching/cars/car_ims/012479.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 McLaren MP4-12C Coupe 2012 70.05% Lamborghini Diablo Coupe 2001 12.65% Ferrari 458 Italia Convertible 2012 3.71% Aston Martin V8 Vantage Coupe 2012 3.29% Ferrari 458 Italia Coupe 2012 3.14% +1182 /scratch/Teaching/cars/car_ims/011568.jpg Infiniti G Coupe IPL 2012 Acura TL Sedan 2012 57.54% Acura TSX Sedan 2012 16.42% Acura RL Sedan 2012 15.53% Infiniti G Coupe IPL 2012 5.11% Acura TL Type-S 2008 2.29% +1183 /scratch/Teaching/cars/car_ims/010848.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 49.33% Hyundai Veracruz SUV 2012 30.76% Chevrolet Traverse SUV 2012 13.5% Scion xD Hatchback 2012 6.13% Ford Fiesta Sedan 2012 0.15% +1184 /scratch/Teaching/cars/car_ims/014995.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 95.66% BMW M5 Sedan 2010 2.76% Buick Verano Sedan 2012 0.41% Infiniti G Coupe IPL 2012 0.36% Audi S4 Sedan 2007 0.22% +1185 /scratch/Teaching/cars/car_ims/011881.jpg Jeep Patriot SUV 2012 Chevrolet Silverado 1500 Regular Cab 2012 70.87% Chevrolet Avalanche Crew Cab 2012 15.77% Chevrolet Silverado 1500 Extended Cab 2012 5.4% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 3.2% GMC Yukon Hybrid SUV 2012 1.8% +1186 /scratch/Teaching/cars/car_ims/011410.jpg Hyundai Elantra Touring Hatchback 2012 Hyundai Elantra Touring Hatchback 2012 99.94% Buick Enclave SUV 2012 0.04% Volkswagen Golf Hatchback 2012 0.02% Ford Focus Sedan 2007 0.01% Daewoo Nubira Wagon 2002 0.0% +1187 /scratch/Teaching/cars/car_ims/010039.jpg GMC Savana Van 2012 Chevrolet Express Cargo Van 2007 68.58% GMC Savana Van 2012 23.33% Chevrolet Express Van 2007 8.08% Nissan NV Passenger Van 2012 0.01% Dodge Sprinter Cargo Van 2009 0.0% +1188 /scratch/Teaching/cars/car_ims/013224.jpg Mercedes-Benz 300-Class Convertible 1993 Mercedes-Benz 300-Class Convertible 1993 52.97% Audi RS 4 Convertible 2008 20.44% Chrysler Crossfire Convertible 2008 7.8% Ford Mustang Convertible 2007 7.68% Mercedes-Benz SL-Class Coupe 2009 2.06% +1189 /scratch/Teaching/cars/car_ims/003997.jpg Buick Enclave SUV 2012 Buick Enclave SUV 2012 99.37% Hyundai Elantra Touring Hatchback 2012 0.35% Nissan Juke Hatchback 2012 0.19% Daewoo Nubira Wagon 2002 0.03% Hyundai Veracruz SUV 2012 0.02% +1190 /scratch/Teaching/cars/car_ims/015619.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 66.69% Ford Fiesta Sedan 2012 28.59% Hyundai Elantra Touring Hatchback 2012 4.19% Nissan Leaf Hatchback 2012 0.21% Scion xD Hatchback 2012 0.14% +1191 /scratch/Teaching/cars/car_ims/004153.jpg Cadillac SRX SUV 2012 Cadillac SRX SUV 2012 99.92% Toyota Sequoia SUV 2012 0.08% BMW X3 SUV 2012 0.0% Infiniti QX56 SUV 2011 0.0% Chrysler PT Cruiser Convertible 2008 0.0% +1192 /scratch/Teaching/cars/car_ims/010746.jpg Hyundai Veloster Hatchback 2012 Spyker C8 Coupe 2009 61.96% Hyundai Veloster Hatchback 2012 35.74% Aston Martin Virage Coupe 2012 1.82% McLaren MP4-12C Coupe 2012 0.39% Spyker C8 Convertible 2009 0.08% +1193 /scratch/Teaching/cars/car_ims/001152.jpg Audi R8 Coupe 2012 Aston Martin V8 Vantage Coupe 2012 89.96% Aston Martin V8 Vantage Convertible 2012 8.94% Eagle Talon Hatchback 1998 0.61% Nissan 240SX Coupe 1998 0.2% Aston Martin Virage Convertible 2012 0.12% +1194 /scratch/Teaching/cars/car_ims/013711.jpg Mitsubishi Lancer Sedan 2012 Acura RL Sedan 2012 35.68% Buick Verano Sedan 2012 18.87% Acura TSX Sedan 2012 8.17% BMW 6 Series Convertible 2007 6.26% Mitsubishi Lancer Sedan 2012 5.65% +1195 /scratch/Teaching/cars/car_ims/012074.jpg Jeep Liberty SUV 2012 Bentley Arnage Sedan 2009 70.58% Bentley Continental Flying Spur Sedan 2007 8.57% Jeep Liberty SUV 2012 5.13% BMW X5 SUV 2007 2.78% Chrysler 300 SRT-8 2010 2.63% +1196 /scratch/Teaching/cars/car_ims/006280.jpg Chrysler Town and Country Minivan 2012 Chevrolet Malibu Sedan 2007 85.96% Chevrolet Impala Sedan 2007 5.26% Lincoln Town Car Sedan 2011 4.19% Hyundai Elantra Sedan 2007 2.0% Ram C/V Cargo Van Minivan 2012 0.54% +1197 /scratch/Teaching/cars/car_ims/005720.jpg Chevrolet Express Van 2007 Chevrolet Express Cargo Van 2007 84.94% Chevrolet Express Van 2007 12.73% GMC Savana Van 2012 2.34% Dodge Caravan Minivan 1997 0.0% Dodge Sprinter Cargo Van 2009 0.0% +1198 /scratch/Teaching/cars/car_ims/012588.jpg Lamborghini Diablo Coupe 2001 Lamborghini Diablo Coupe 2001 94.47% Lamborghini Gallardo LP 570-4 Superleggera 2012 3.75% Acura Integra Type R 2001 1.78% McLaren MP4-12C Coupe 2012 0.01% Chevrolet Corvette ZR1 2012 0.0% +1199 /scratch/Teaching/cars/car_ims/005327.jpg Chevrolet Cobalt SS 2010 Chevrolet Sonic Sedan 2012 57.19% Chevrolet HHR SS 2010 17.56% Dodge Magnum Wagon 2008 7.46% Chevrolet Cobalt SS 2010 6.86% Suzuki Kizashi Sedan 2012 2.92% +1200 /scratch/Teaching/cars/car_ims/014640.jpg Scion xD Hatchback 2012 Suzuki SX4 Sedan 2012 43.5% Suzuki SX4 Hatchback 2012 32.69% FIAT 500 Convertible 2012 7.94% Suzuki Kizashi Sedan 2012 6.45% Chevrolet Sonic Sedan 2012 3.23% +1201 /scratch/Teaching/cars/car_ims/004163.jpg Cadillac SRX SUV 2012 Hyundai Tucson SUV 2012 73.69% Ford Fiesta Sedan 2012 5.68% Chevrolet Traverse SUV 2012 5.65% Nissan Juke Hatchback 2012 4.98% Hyundai Veracruz SUV 2012 2.72% +1202 /scratch/Teaching/cars/car_ims/000148.jpg Acura RL Sedan 2012 Acura TSX Sedan 2012 76.86% Acura TL Sedan 2012 17.77% Toyota Camry Sedan 2012 2.42% Hyundai Elantra Sedan 2007 1.47% Acura RL Sedan 2012 0.49% +1203 /scratch/Teaching/cars/car_ims/006869.jpg Dodge Caliber Wagon 2007 BMW X6 SUV 2012 40.56% Dodge Caliber Wagon 2012 34.87% Dodge Caliber Wagon 2007 20.14% Jeep Grand Cherokee SUV 2012 4.0% Dodge Journey SUV 2012 0.15% +1204 /scratch/Teaching/cars/car_ims/001861.jpg Audi S4 Sedan 2012 Audi S4 Sedan 2012 47.57% Acura TL Type-S 2008 16.34% Mitsubishi Lancer Sedan 2012 12.84% BMW M5 Sedan 2010 5.21% Hyundai Genesis Sedan 2012 4.13% +1205 /scratch/Teaching/cars/car_ims/008282.jpg Ferrari California Convertible 2012 Ferrari California Convertible 2012 97.45% Ferrari FF Coupe 2012 1.04% Aston Martin V8 Vantage Coupe 2012 0.79% Jaguar XK XKR 2012 0.29% Ferrari 458 Italia Coupe 2012 0.25% +1206 /scratch/Teaching/cars/car_ims/000155.jpg Acura TL Sedan 2012 Acura TSX Sedan 2012 75.07% Acura TL Type-S 2008 14.79% Acura TL Sedan 2012 7.37% Acura RL Sedan 2012 2.72% Toyota Camry Sedan 2012 0.03% +1207 /scratch/Teaching/cars/car_ims/004388.jpg Chevrolet Corvette Convertible 2012 Acura Integra Type R 2001 98.86% Chevrolet Corvette Convertible 2012 1.02% Chevrolet Corvette ZR1 2012 0.07% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.01% Lamborghini Diablo Coupe 2001 0.01% +1208 /scratch/Teaching/cars/car_ims/006706.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 20.67% Honda Odyssey Minivan 2007 17.51% Lincoln Town Car Sedan 2011 15.35% Chrysler Town and Country Minivan 2012 11.55% Suzuki Aerio Sedan 2007 8.18% +1209 /scratch/Teaching/cars/car_ims/005698.jpg Chevrolet Express Van 2007 Chevrolet Express Van 2007 65.69% GMC Savana Van 2012 19.99% Chevrolet Express Cargo Van 2007 14.31% Volkswagen Golf Hatchback 1991 0.0% Chevrolet Silverado 1500 Classic Extended Cab 2007 0.0% +1210 /scratch/Teaching/cars/car_ims/005502.jpg Chevrolet TrailBlazer SS 2009 Chevrolet TrailBlazer SS 2009 59.76% Dodge Charger SRT-8 2009 15.45% Chevrolet Camaro Convertible 2012 3.4% Chevrolet Avalanche Crew Cab 2012 3.36% Dodge Journey SUV 2012 3.0% +1211 /scratch/Teaching/cars/car_ims/002873.jpg BMW M6 Convertible 2010 BMW M6 Convertible 2010 76.19% BMW 6 Series Convertible 2007 14.06% Jaguar XK XKR 2012 7.54% Aston Martin Virage Convertible 2012 0.94% Infiniti G Coupe IPL 2012 0.22% +1212 /scratch/Teaching/cars/car_ims/000206.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 92.14% Acura TSX Sedan 2012 5.58% Acura RL Sedan 2012 2.15% Acura TL Type-S 2008 0.08% Acura ZDX Hatchback 2012 0.05% +1213 /scratch/Teaching/cars/car_ims/000956.jpg Audi RS 4 Convertible 2008 Audi RS 4 Convertible 2008 94.51% Audi S5 Convertible 2012 1.51% Audi S4 Sedan 2007 1.01% Audi TTS Coupe 2012 0.85% Bentley Continental GT Coupe 2012 0.82% +1214 /scratch/Teaching/cars/car_ims/005301.jpg Chevrolet Cobalt SS 2010 Chevrolet Cobalt SS 2010 56.56% Dodge Charger SRT-8 2009 18.83% Dodge Charger Sedan 2012 11.41% Dodge Challenger SRT8 2011 9.01% Chevrolet Camaro Convertible 2012 2.17% +1215 /scratch/Teaching/cars/car_ims/009658.jpg GMC Terrain SUV 2012 Rolls-Royce Phantom Sedan 2012 91.55% Rolls-Royce Ghost Sedan 2012 4.51% Bentley Mulsanne Sedan 2011 1.82% Chrysler 300 SRT-8 2010 1.32% Land Rover Range Rover SUV 2012 0.69% +1216 /scratch/Teaching/cars/car_ims/001969.jpg Audi S4 Sedan 2007 Audi A5 Coupe 2012 47.91% Audi S4 Sedan 2007 35.06% Audi S4 Sedan 2012 12.49% Audi S5 Coupe 2012 2.93% Mitsubishi Lancer Sedan 2012 1.26% +1217 /scratch/Teaching/cars/car_ims/003042.jpg BMW Z4 Convertible 2012 Aston Martin Virage Coupe 2012 73.04% BMW Z4 Convertible 2012 12.98% Audi TTS Coupe 2012 2.92% Aston Martin V8 Vantage Coupe 2012 2.17% BMW M3 Coupe 2012 1.53% +1218 /scratch/Teaching/cars/car_ims/014243.jpg Porsche Panamera Sedan 2012 Jaguar XK XKR 2012 24.06% BMW M6 Convertible 2010 16.88% Fisker Karma Sedan 2012 13.03% Chrysler 300 SRT-8 2010 5.58% BMW 3 Series Sedan 2012 4.23% +1219 /scratch/Teaching/cars/car_ims/005431.jpg Chevrolet Malibu Hybrid Sedan 2010 Chevrolet Impala Sedan 2007 60.53% Chevrolet Malibu Sedan 2007 22.22% Hyundai Elantra Sedan 2007 16.75% Chevrolet Monte Carlo Coupe 2007 0.21% Acura TL Type-S 2008 0.08% +1220 /scratch/Teaching/cars/car_ims/002433.jpg BMW 3 Series Wagon 2012 BMW 3 Series Wagon 2012 97.89% BMW 3 Series Sedan 2012 1.35% BMW M5 Sedan 2010 0.68% BMW 1 Series Coupe 2012 0.05% Acura TL Type-S 2008 0.02% +1221 /scratch/Teaching/cars/car_ims/006663.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 99.36% Volkswagen Golf Hatchback 1991 0.37% Ford Focus Sedan 2007 0.17% Audi 100 Wagon 1994 0.09% Suzuki Aerio Sedan 2007 0.01% +1222 /scratch/Teaching/cars/car_ims/007433.jpg Dodge Dakota Club Cab 2007 Dodge Dakota Club Cab 2007 76.94% Chevrolet Silverado 1500 Extended Cab 2012 11.95% Chevrolet Silverado 1500 Regular Cab 2012 6.2% Chevrolet Avalanche Crew Cab 2012 3.37% Ford F-150 Regular Cab 2007 1.0% +1223 /scratch/Teaching/cars/car_ims/011964.jpg Jeep Wrangler SUV 2012 GMC Canyon Extended Cab 2012 71.83% Jeep Wrangler SUV 2012 26.5% HUMMER H3T Crew Cab 2010 0.82% Ford F-150 Regular Cab 2007 0.3% Chevrolet Silverado 1500 Extended Cab 2012 0.19% +1224 /scratch/Teaching/cars/car_ims/012047.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 82.47% Jeep Patriot SUV 2012 17.52% Jeep Compass SUV 2012 0.01% Jeep Grand Cherokee SUV 2012 0.0% Jeep Wrangler SUV 2012 0.0% +1225 /scratch/Teaching/cars/car_ims/008226.jpg Ferrari FF Coupe 2012 Jaguar XK XKR 2012 29.61% Honda Accord Coupe 2012 16.59% Ferrari FF Coupe 2012 15.3% Tesla Model S Sedan 2012 5.82% Toyota Camry Sedan 2012 4.15% +1226 /scratch/Teaching/cars/car_ims/001270.jpg Audi V8 Sedan 1994 Lincoln Town Car Sedan 2011 45.24% Mercedes-Benz 300-Class Convertible 1993 20.76% Audi 100 Wagon 1994 18.59% Volvo 240 Sedan 1993 11.05% Audi 100 Sedan 1994 2.67% +1227 /scratch/Teaching/cars/car_ims/004621.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Ford GT Coupe 2006 73.12% Chevrolet Corvette Ron Fellows Edition Z06 2007 18.4% Fisker Karma Sedan 2012 2.08% Nissan Leaf Hatchback 2012 1.08% Nissan Juke Hatchback 2012 0.84% +1228 /scratch/Teaching/cars/car_ims/000674.jpg Aston Martin V8 Vantage Coupe 2012 Aston Martin V8 Vantage Coupe 2012 91.84% Aston Martin V8 Vantage Convertible 2012 8.09% Aston Martin Virage Convertible 2012 0.03% Jaguar XK XKR 2012 0.02% Dodge Challenger SRT8 2011 0.01% +1229 /scratch/Teaching/cars/car_ims/000047.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 91.22% Jeep Wrangler SUV 2012 8.75% HUMMER H3T Crew Cab 2010 0.02% HUMMER H2 SUT Crew Cab 2009 0.01% Jeep Patriot SUV 2012 0.0% +1230 /scratch/Teaching/cars/car_ims/007641.jpg Dodge Durango SUV 2012 Dodge Journey SUV 2012 99.56% Dodge Durango SUV 2012 0.44% Dodge Charger Sedan 2012 0.0% Dodge Charger SRT-8 2009 0.0% Chevrolet HHR SS 2010 0.0% +1231 /scratch/Teaching/cars/car_ims/004064.jpg Cadillac CTS-V Sedan 2012 Chrysler 300 SRT-8 2010 94.94% Rolls-Royce Ghost Sedan 2012 3.09% Rolls-Royce Phantom Sedan 2012 1.37% Dodge Charger Sedan 2012 0.19% Audi R8 Coupe 2012 0.1% +1232 /scratch/Teaching/cars/car_ims/011299.jpg Hyundai Sonata Sedan 2012 Chevrolet Malibu Hybrid Sedan 2010 45.37% Buick Verano Sedan 2012 36.89% Honda Accord Sedan 2012 12.59% Acura RL Sedan 2012 3.81% Acura ZDX Hatchback 2012 0.39% +1233 /scratch/Teaching/cars/car_ims/006658.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 75.61% Ford Focus Sedan 2007 22.57% Suzuki Aerio Sedan 2007 0.95% Chevrolet Impala Sedan 2007 0.8% Plymouth Neon Coupe 1999 0.06% +1234 /scratch/Teaching/cars/car_ims/002584.jpg BMW X5 SUV 2007 Audi R8 Coupe 2012 42.27% Fisker Karma Sedan 2012 29.7% Tesla Model S Sedan 2012 6.49% Lamborghini Reventon Coupe 2008 4.04% Audi TTS Coupe 2012 2.66% +1235 /scratch/Teaching/cars/car_ims/003177.jpg Bentley Continental Supersports Conv. Convertible 2012 Chevrolet Corvette Ron Fellows Edition Z06 2007 59.65% Chevrolet Corvette ZR1 2012 20.5% Porsche Panamera Sedan 2012 10.1% Volkswagen Beetle Hatchback 2012 6.54% Chevrolet Corvette Convertible 2012 1.48% +1236 /scratch/Teaching/cars/car_ims/011552.jpg Infiniti G Coupe IPL 2012 Infiniti G Coupe IPL 2012 87.59% Hyundai Azera Sedan 2012 3.53% Hyundai Genesis Sedan 2012 2.75% Acura RL Sedan 2012 2.02% Acura TL Type-S 2008 1.27% +1237 /scratch/Teaching/cars/car_ims/003529.jpg Bentley Continental Flying Spur Sedan 2007 Chevrolet Malibu Hybrid Sedan 2010 26.45% Hyundai Veracruz SUV 2012 21.92% Chevrolet Impala Sedan 2007 5.6% Honda Accord Sedan 2012 4.52% Acura ZDX Hatchback 2012 4.23% +1238 /scratch/Teaching/cars/car_ims/016015.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 47.54% Volkswagen Golf Hatchback 1991 46.92% Audi 100 Wagon 1994 2.82% Audi V8 Sedan 1994 2.49% Audi 100 Sedan 1994 0.22% +1239 /scratch/Teaching/cars/car_ims/009160.jpg Ford GT Coupe 2006 Bugatti Veyron 16.4 Coupe 2009 29.31% Chevrolet Corvette ZR1 2012 14.12% Mercedes-Benz SL-Class Coupe 2009 4.63% Eagle Talon Hatchback 1998 4.48% Spyker C8 Convertible 2009 3.35% +1240 /scratch/Teaching/cars/car_ims/007978.jpg Eagle Talon Hatchback 1998 Eagle Talon Hatchback 1998 97.4% Plymouth Neon Coupe 1999 2.27% Geo Metro Convertible 1993 0.17% Nissan 240SX Coupe 1998 0.13% Ford Focus Sedan 2007 0.01% +1241 /scratch/Teaching/cars/car_ims/004731.jpg Chevrolet Camaro Convertible 2012 Chevrolet Camaro Convertible 2012 98.39% Honda Accord Coupe 2012 0.5% Chrysler Crossfire Convertible 2008 0.39% Dodge Charger SRT-8 2009 0.15% Eagle Talon Hatchback 1998 0.14% +1242 /scratch/Teaching/cars/car_ims/004773.jpg Chevrolet Camaro Convertible 2012 Chevrolet Camaro Convertible 2012 88.65% Dodge Challenger SRT8 2011 3.82% Chevrolet Cobalt SS 2010 2.34% Dodge Charger Sedan 2012 1.73% Chrysler Crossfire Convertible 2008 0.95% +1243 /scratch/Teaching/cars/car_ims/008087.jpg FIAT 500 Abarth 2012 FIAT 500 Abarth 2012 100.0% Bentley Arnage Sedan 2009 0.0% Ford GT Coupe 2006 0.0% Jeep Liberty SUV 2012 0.0% Nissan Juke Hatchback 2012 0.0% +1244 /scratch/Teaching/cars/car_ims/004574.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Porsche Panamera Sedan 2012 60.37% Chevrolet Corvette Ron Fellows Edition Z06 2007 13.36% Chevrolet Corvette ZR1 2012 12.67% Fisker Karma Sedan 2012 4.25% Jaguar XK XKR 2012 3.12% +1245 /scratch/Teaching/cars/car_ims/008917.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 100.0% Chrysler Aspen SUV 2009 0.0% Ford E-Series Wagon Van 2012 0.0% Toyota Sequoia SUV 2012 0.0% Land Rover Range Rover SUV 2012 0.0% +1246 /scratch/Teaching/cars/car_ims/010032.jpg GMC Savana Van 2012 GMC Savana Van 2012 83.88% Chevrolet Express Van 2007 12.41% Chevrolet Express Cargo Van 2007 3.7% Volkswagen Golf Hatchback 1991 0.01% Ford E-Series Wagon Van 2012 0.0% +1247 /scratch/Teaching/cars/car_ims/009014.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 99.99% Hyundai Veracruz SUV 2012 0.01% Honda Odyssey Minivan 2012 0.0% Hyundai Sonata Hybrid Sedan 2012 0.0% Land Rover LR2 SUV 2012 0.0% +1248 /scratch/Teaching/cars/car_ims/002645.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 99.56% Jeep Grand Cherokee SUV 2012 0.34% Jeep Compass SUV 2012 0.05% Chevrolet Sonic Sedan 2012 0.02% Nissan Juke Hatchback 2012 0.01% +1249 /scratch/Teaching/cars/car_ims/008094.jpg FIAT 500 Abarth 2012 FIAT 500 Abarth 2012 99.67% Volvo C30 Hatchback 2012 0.2% Dodge Charger Sedan 2012 0.03% Nissan Juke Hatchback 2012 0.03% BMW 3 Series Sedan 2012 0.02% +1250 /scratch/Teaching/cars/car_ims/009876.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 97.03% Buick Enclave SUV 2012 1.57% Chevrolet Traverse SUV 2012 0.7% GMC Yukon Hybrid SUV 2012 0.38% Jeep Liberty SUV 2012 0.12% +1251 /scratch/Teaching/cars/car_ims/003933.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 98.33% Chevrolet Malibu Hybrid Sedan 2010 0.34% Cadillac SRX SUV 2012 0.23% Suzuki Kizashi Sedan 2012 0.18% Acura RL Sedan 2012 0.15% +1252 /scratch/Teaching/cars/car_ims/001216.jpg Audi V8 Sedan 1994 Audi 100 Sedan 1994 56.88% Audi V8 Sedan 1994 28.17% Audi 100 Wagon 1994 10.96% Volkswagen Golf Hatchback 1991 2.99% Dodge Sprinter Cargo Van 2009 0.28% +1253 /scratch/Teaching/cars/car_ims/006426.jpg Chrysler 300 SRT-8 2010 Chevrolet Impala Sedan 2007 34.1% Chrysler 300 SRT-8 2010 22.45% Lincoln Town Car Sedan 2011 12.42% Chevrolet Malibu Hybrid Sedan 2010 12.31% Ford Focus Sedan 2007 4.03% +1254 /scratch/Teaching/cars/car_ims/003740.jpg Buick Regal GS 2012 Buick Regal GS 2012 99.84% Buick Verano Sedan 2012 0.09% Chevrolet Sonic Sedan 2012 0.02% Mitsubishi Lancer Sedan 2012 0.01% Hyundai Sonata Hybrid Sedan 2012 0.01% +1255 /scratch/Teaching/cars/car_ims/000430.jpg Acura Integra Type R 2001 Lamborghini Gallardo LP 570-4 Superleggera 2012 86.34% McLaren MP4-12C Coupe 2012 5.6% Lamborghini Diablo Coupe 2001 3.39% Chevrolet Corvette ZR1 2012 0.71% Chevrolet Corvette Convertible 2012 0.71% +1256 /scratch/Teaching/cars/car_ims/014909.jpg Suzuki Aerio Sedan 2007 Suzuki Aerio Sedan 2007 75.72% Suzuki SX4 Sedan 2012 10.75% Daewoo Nubira Wagon 2002 5.52% Volkswagen Golf Hatchback 2012 3.97% BMW 3 Series Wagon 2012 1.79% +1257 /scratch/Teaching/cars/car_ims/014372.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Sedan 2012 98.97% Rolls-Royce Ghost Sedan 2012 0.53% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.48% Bentley Mulsanne Sedan 2011 0.02% Bentley Arnage Sedan 2009 0.01% +1258 /scratch/Teaching/cars/car_ims/001836.jpg Audi S4 Sedan 2012 Audi S4 Sedan 2012 82.37% Audi S5 Coupe 2012 7.4% Audi A5 Coupe 2012 6.95% Audi S4 Sedan 2007 1.96% Audi S5 Convertible 2012 1.0% +1259 /scratch/Teaching/cars/car_ims/010997.jpg Hyundai Veracruz SUV 2012 Hyundai Veracruz SUV 2012 49.92% Chevrolet Traverse SUV 2012 25.17% Hyundai Santa Fe SUV 2012 15.47% Ford Edge SUV 2012 7.24% Hyundai Tucson SUV 2012 1.5% +1260 /scratch/Teaching/cars/car_ims/004286.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 99.4% GMC Yukon Hybrid SUV 2012 0.51% GMC Acadia SUV 2012 0.03% Cadillac SRX SUV 2012 0.02% Toyota Sequoia SUV 2012 0.01% +1261 /scratch/Teaching/cars/car_ims/007124.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 88.59% Dodge Ram Pickup 3500 Crew Cab 2010 9.29% Dodge Dakota Club Cab 2007 1.37% GMC Canyon Extended Cab 2012 0.43% HUMMER H3T Crew Cab 2010 0.17% +1262 /scratch/Teaching/cars/car_ims/007215.jpg Dodge Journey SUV 2012 Dodge Journey SUV 2012 99.96% Honda Accord Coupe 2012 0.04% Volvo C30 Hatchback 2012 0.0% Dodge Charger Sedan 2012 0.0% Mercedes-Benz C-Class Sedan 2012 0.0% +1263 /scratch/Teaching/cars/car_ims/010212.jpg HUMMER H3T Crew Cab 2010 HUMMER H3T Crew Cab 2010 71.79% HUMMER H2 SUT Crew Cab 2009 28.07% Jeep Wrangler SUV 2012 0.11% AM General Hummer SUV 2000 0.02% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% +1264 /scratch/Teaching/cars/car_ims/001513.jpg Audi TT Hatchback 2011 Buick Regal GS 2012 57.79% Infiniti G Coupe IPL 2012 9.81% Tesla Model S Sedan 2012 7.23% Audi TTS Coupe 2012 4.43% Audi TT Hatchback 2011 3.78% +1265 /scratch/Teaching/cars/car_ims/001712.jpg Audi S5 Convertible 2012 Audi TTS Coupe 2012 39.29% Audi S5 Convertible 2012 23.38% Audi RS 4 Convertible 2008 15.07% BMW M6 Convertible 2010 8.6% Audi S5 Coupe 2012 4.27% +1266 /scratch/Teaching/cars/car_ims/002494.jpg BMW 6 Series Convertible 2007 BMW 6 Series Convertible 2007 80.5% BMW M6 Convertible 2010 15.02% Chevrolet Monte Carlo Coupe 2007 2.19% Jaguar XK XKR 2012 1.37% Honda Accord Coupe 2012 0.37% +1267 /scratch/Teaching/cars/car_ims/008811.jpg Ford Freestar Minivan 2007 Ram C/V Cargo Van Minivan 2012 91.81% Ford Freestar Minivan 2007 7.84% Chrysler Town and Country Minivan 2012 0.33% Chevrolet Malibu Sedan 2007 0.02% Dodge Caravan Minivan 1997 0.0% +1268 /scratch/Teaching/cars/car_ims/010732.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 99.88% Volvo C30 Hatchback 2012 0.06% Spyker C8 Coupe 2009 0.02% Ford Fiesta Sedan 2012 0.02% smart fortwo Convertible 2012 0.01% +1269 /scratch/Teaching/cars/car_ims/012382.jpg Lamborghini Aventador Coupe 2012 Lamborghini Aventador Coupe 2012 99.45% McLaren MP4-12C Coupe 2012 0.31% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.11% Lamborghini Reventon Coupe 2008 0.1% Ford GT Coupe 2006 0.02% +1270 /scratch/Teaching/cars/car_ims/010739.jpg Hyundai Veloster Hatchback 2012 Toyota Camry Sedan 2012 34.62% Scion xD Hatchback 2012 16.85% Ford Fiesta Sedan 2012 12.03% Hyundai Accent Sedan 2012 9.62% Toyota Corolla Sedan 2012 9.02% +1271 /scratch/Teaching/cars/car_ims/008547.jpg Fisker Karma Sedan 2012 Jaguar XK XKR 2012 88.36% Ferrari FF Coupe 2012 9.15% Hyundai Sonata Hybrid Sedan 2012 0.62% Buick Regal GS 2012 0.31% Porsche Panamera Sedan 2012 0.29% +1272 /scratch/Teaching/cars/car_ims/003323.jpg Bentley Mulsanne Sedan 2011 Rolls-Royce Phantom Sedan 2012 57.76% Bentley Mulsanne Sedan 2011 29.19% Bentley Continental Flying Spur Sedan 2007 10.12% Bentley Arnage Sedan 2009 1.68% Rolls-Royce Ghost Sedan 2012 1.18% +1273 /scratch/Teaching/cars/car_ims/016077.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 30.26% Volkswagen Golf Hatchback 1991 12.88% Buick Rainier SUV 2007 12.69% Bentley Arnage Sedan 2009 8.29% BMW X5 SUV 2007 7.76% +1274 /scratch/Teaching/cars/car_ims/000085.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 99.95% HUMMER H2 SUT Crew Cab 2009 0.03% Jeep Wrangler SUV 2012 0.01% HUMMER H3T Crew Cab 2010 0.0% Lamborghini Diablo Coupe 2001 0.0% +1275 /scratch/Teaching/cars/car_ims/005924.jpg Chevrolet Malibu Sedan 2007 Chevrolet Malibu Sedan 2007 99.34% Chevrolet Monte Carlo Coupe 2007 0.31% Lincoln Town Car Sedan 2011 0.27% Chevrolet Impala Sedan 2007 0.08% Ford Freestar Minivan 2007 0.0% +1276 /scratch/Teaching/cars/car_ims/003140.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental Supersports Conv. Convertible 2012 99.74% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.14% Lamborghini Reventon Coupe 2008 0.02% Maybach Landaulet Convertible 2012 0.02% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.02% +1277 /scratch/Teaching/cars/car_ims/002722.jpg BMW M3 Coupe 2012 Acura TL Type-S 2008 25.43% BMW M5 Sedan 2010 20.99% BMW 3 Series Sedan 2012 15.73% Audi S4 Sedan 2007 11.07% Audi S4 Sedan 2012 8.89% +1278 /scratch/Teaching/cars/car_ims/013259.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 62.01% Hyundai Genesis Sedan 2012 31.12% Mercedes-Benz S-Class Sedan 2012 6.17% Mercedes-Benz E-Class Sedan 2012 0.69% Mercedes-Benz Sprinter Van 2012 0.0% +1279 /scratch/Teaching/cars/car_ims/011274.jpg Hyundai Genesis Sedan 2012 Hyundai Genesis Sedan 2012 62.04% Honda Accord Sedan 2012 33.39% Hyundai Elantra Sedan 2007 1.9% Chrysler Town and Country Minivan 2012 1.49% Honda Odyssey Minivan 2012 0.71% +1280 /scratch/Teaching/cars/car_ims/008990.jpg Ford Edge SUV 2012 Hyundai Veracruz SUV 2012 45.76% Ford Edge SUV 2012 23.8% Chevrolet Traverse SUV 2012 17.59% Buick Enclave SUV 2012 4.82% Nissan Juke Hatchback 2012 2.49% +1281 /scratch/Teaching/cars/car_ims/003079.jpg BMW Z4 Convertible 2012 Acura ZDX Hatchback 2012 74.42% Buick Regal GS 2012 5.3% Hyundai Sonata Hybrid Sedan 2012 4.65% Acura TL Sedan 2012 2.89% Volkswagen Golf Hatchback 2012 2.75% +1282 /scratch/Teaching/cars/car_ims/006904.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 90.11% Plymouth Neon Coupe 1999 9.7% Audi 100 Wagon 1994 0.11% Ford Focus Sedan 2007 0.05% Ford Freestar Minivan 2007 0.02% +1283 /scratch/Teaching/cars/car_ims/012720.jpg Land Rover LR2 SUV 2012 Land Rover LR2 SUV 2012 80.08% Mazda Tribute SUV 2011 6.62% Chevrolet HHR SS 2010 3.35% HUMMER H2 SUT Crew Cab 2009 2.46% Jeep Compass SUV 2012 1.39% +1284 /scratch/Teaching/cars/car_ims/012469.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 Lamborghini Gallardo LP 570-4 Superleggera 2012 99.98% Acura Integra Type R 2001 0.01% Chevrolet Corvette Ron Fellows Edition Z06 2007 0.0% Bentley Continental Supersports Conv. Convertible 2012 0.0% Chevrolet Corvette Convertible 2012 0.0% +1285 /scratch/Teaching/cars/car_ims/006501.jpg Chrysler Crossfire Convertible 2008 Chevrolet TrailBlazer SS 2009 39.22% Dodge Charger SRT-8 2009 25.26% Chrysler 300 SRT-8 2010 14.49% Nissan 240SX Coupe 1998 5.35% Dodge Challenger SRT8 2011 4.31% +1286 /scratch/Teaching/cars/car_ims/009232.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2012 99.73% Ford F-150 Regular Cab 2007 0.27% GMC Canyon Extended Cab 2012 0.0% Ford F-450 Super Duty Crew Cab 2012 0.0% Cadillac Escalade EXT Crew Cab 2007 0.0% +1287 /scratch/Teaching/cars/car_ims/001116.jpg Audi TTS Coupe 2012 Audi TTS Coupe 2012 37.28% Audi S5 Coupe 2012 28.67% Audi A5 Coupe 2012 9.24% Audi S4 Sedan 2012 9.19% Infiniti G Coupe IPL 2012 3.52% +1288 /scratch/Teaching/cars/car_ims/012692.jpg Land Rover LR2 SUV 2012 Land Rover LR2 SUV 2012 99.89% Land Rover Range Rover SUV 2012 0.09% Toyota 4Runner SUV 2012 0.01% Ford Edge SUV 2012 0.0% Honda Odyssey Minivan 2012 0.0% +1289 /scratch/Teaching/cars/car_ims/002661.jpg BMW X6 SUV 2012 BMW X5 SUV 2007 43.93% BMW X6 SUV 2012 30.31% Jeep Grand Cherokee SUV 2012 16.94% Dodge Durango SUV 2007 2.44% Jeep Liberty SUV 2012 1.17% +1290 /scratch/Teaching/cars/car_ims/014596.jpg Scion xD Hatchback 2012 Suzuki SX4 Sedan 2012 63.8% Suzuki SX4 Hatchback 2012 24.69% Mazda Tribute SUV 2011 6.79% Dodge Caliber Wagon 2012 1.75% Ram C/V Cargo Van Minivan 2012 1.58% +1291 /scratch/Teaching/cars/car_ims/008508.jpg Fisker Karma Sedan 2012 BMW M6 Convertible 2010 71.14% BMW 3 Series Sedan 2012 6.98% Chrysler 300 SRT-8 2010 3.73% Audi R8 Coupe 2012 3.34% Fisker Karma Sedan 2012 3.24% +1292 /scratch/Teaching/cars/car_ims/004323.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Regular Cab 2012 40.18% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 24.15% Chevrolet Silverado 1500 Extended Cab 2012 18.66% Chevrolet Silverado 2500HD Regular Cab 2012 6.95% Chevrolet Avalanche Crew Cab 2012 3.81% +1293 /scratch/Teaching/cars/car_ims/014085.jpg Nissan 240SX Coupe 1998 Eagle Talon Hatchback 1998 72.49% Nissan 240SX Coupe 1998 27.37% Plymouth Neon Coupe 1999 0.11% Honda Accord Coupe 2012 0.03% Chevrolet Camaro Convertible 2012 0.0% +1294 /scratch/Teaching/cars/car_ims/010191.jpg HUMMER H3T Crew Cab 2010 Jeep Compass SUV 2012 55.29% Jeep Grand Cherokee SUV 2012 43.13% GMC Terrain SUV 2012 0.72% Nissan Juke Hatchback 2012 0.3% Toyota 4Runner SUV 2012 0.22% +1295 /scratch/Teaching/cars/car_ims/009119.jpg Ford GT Coupe 2006 Spyker C8 Coupe 2009 40.96% Nissan Juke Hatchback 2012 13.25% Bugatti Veyron 16.4 Coupe 2009 12.56% Spyker C8 Convertible 2009 7.54% Bugatti Veyron 16.4 Convertible 2009 7.32% +1296 /scratch/Teaching/cars/car_ims/002119.jpg BMW ActiveHybrid 5 Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 37.3% BMW 6 Series Convertible 2007 33.07% Acura TL Type-S 2008 15.05% BMW M5 Sedan 2010 5.48% BMW M6 Convertible 2010 4.54% +1297 /scratch/Teaching/cars/car_ims/001378.jpg Audi 100 Sedan 1994 Audi 100 Wagon 1994 85.22% Audi 100 Sedan 1994 5.83% Lincoln Town Car Sedan 2011 5.51% Audi V8 Sedan 1994 1.56% Volvo 240 Sedan 1993 1.26% +1298 /scratch/Teaching/cars/car_ims/014277.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 99.9% Chrysler Town and Country Minivan 2012 0.08% Chevrolet Malibu Sedan 2007 0.01% Suzuki SX4 Sedan 2012 0.0% Ford Freestar Minivan 2007 0.0% +1299 /scratch/Teaching/cars/car_ims/001048.jpg Audi TTS Coupe 2012 Audi S4 Sedan 2007 40.69% Audi A5 Coupe 2012 18.67% BMW ActiveHybrid 5 Sedan 2012 14.75% BMW Z4 Convertible 2012 8.79% Audi S5 Coupe 2012 3.62% +1300 /scratch/Teaching/cars/car_ims/011379.jpg Hyundai Elantra Touring Hatchback 2012 Hyundai Elantra Touring Hatchback 2012 98.97% Volkswagen Golf Hatchback 2012 0.6% Chevrolet Sonic Sedan 2012 0.29% Hyundai Accent Sedan 2012 0.11% Toyota Corolla Sedan 2012 0.03% +1301 /scratch/Teaching/cars/car_ims/000289.jpg Acura TL Type-S 2008 Honda Accord Coupe 2012 99.85% Toyota Camry Sedan 2012 0.06% Mitsubishi Lancer Sedan 2012 0.05% Toyota Corolla Sedan 2012 0.03% Acura TL Type-S 2008 0.01% +1302 /scratch/Teaching/cars/car_ims/008798.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 81.2% Ram C/V Cargo Van Minivan 2012 5.51% Lincoln Town Car Sedan 2011 3.76% Chevrolet Malibu Sedan 2007 2.7% Chrysler Town and Country Minivan 2012 2.09% +1303 /scratch/Teaching/cars/car_ims/012540.jpg Lamborghini Diablo Coupe 2001 Lamborghini Diablo Coupe 2001 99.92% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.04% McLaren MP4-12C Coupe 2012 0.02% Acura Integra Type R 2001 0.01% Ferrari 458 Italia Convertible 2012 0.0% +1304 /scratch/Teaching/cars/car_ims/007703.jpg Dodge Durango SUV 2012 Dodge Magnum Wagon 2008 35.4% Chevrolet Malibu Sedan 2007 27.29% Dodge Durango SUV 2012 24.13% Chevrolet Avalanche Crew Cab 2012 7.22% Dodge Caliber Wagon 2012 2.3% +1305 /scratch/Teaching/cars/car_ims/012505.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 McLaren MP4-12C Coupe 2012 99.98% Aston Martin Virage Coupe 2012 0.01% Spyker C8 Coupe 2009 0.0% Lamborghini Diablo Coupe 2001 0.0% Lamborghini Aventador Coupe 2012 0.0% +1306 /scratch/Teaching/cars/car_ims/015699.jpg Volkswagen Golf Hatchback 1991 Lamborghini Gallardo LP 570-4 Superleggera 2012 91.17% Lamborghini Diablo Coupe 2001 5.96% Acura Integra Type R 2001 1.46% McLaren MP4-12C Coupe 2012 0.41% AM General Hummer SUV 2000 0.26% +1307 /scratch/Teaching/cars/car_ims/001763.jpg Audi S5 Coupe 2012 Audi S4 Sedan 2012 56.34% Audi A5 Coupe 2012 31.13% Audi S5 Coupe 2012 10.48% Audi TTS Coupe 2012 0.58% Audi S4 Sedan 2007 0.4% +1308 /scratch/Teaching/cars/car_ims/013750.jpg Mitsubishi Lancer Sedan 2012 Mitsubishi Lancer Sedan 2012 97.37% BMW 3 Series Wagon 2012 0.43% Audi S4 Sedan 2012 0.42% Toyota Corolla Sedan 2012 0.27% Audi S4 Sedan 2007 0.24% +1309 /scratch/Teaching/cars/car_ims/002060.jpg BMW ActiveHybrid 5 Sedan 2012 BMW ActiveHybrid 5 Sedan 2012 21.96% BMW 3 Series Wagon 2012 15.99% BMW 3 Series Sedan 2012 11.57% Audi S4 Sedan 2007 9.37% Audi S6 Sedan 2011 7.41% +1310 /scratch/Teaching/cars/car_ims/008410.jpg Ferrari 458 Italia Convertible 2012 Ferrari 458 Italia Convertible 2012 69.77% Ferrari 458 Italia Coupe 2012 29.51% Ferrari California Convertible 2012 0.71% Chevrolet Corvette Convertible 2012 0.01% Ferrari FF Coupe 2012 0.0% +1311 /scratch/Teaching/cars/car_ims/009147.jpg Ford GT Coupe 2006 Spyker C8 Coupe 2009 59.53% Ford GT Coupe 2006 18.84% McLaren MP4-12C Coupe 2012 6.48% Spyker C8 Convertible 2009 5.42% Hyundai Veloster Hatchback 2012 2.4% +1312 /scratch/Teaching/cars/car_ims/011104.jpg Hyundai Elantra Sedan 2007 Hyundai Elantra Sedan 2007 83.58% Hyundai Sonata Sedan 2012 5.45% Honda Accord Sedan 2012 2.8% Hyundai Genesis Sedan 2012 2.64% Hyundai Azera Sedan 2012 2.33% +1313 /scratch/Teaching/cars/car_ims/000769.jpg Aston Martin Virage Convertible 2012 Fisker Karma Sedan 2012 23.34% BMW M6 Convertible 2010 18.57% Jaguar XK XKR 2012 18.15% Chevrolet Corvette Ron Fellows Edition Z06 2007 9.74% BMW 6 Series Convertible 2007 8.86% +1314 /scratch/Teaching/cars/car_ims/014094.jpg Nissan 240SX Coupe 1998 Plymouth Neon Coupe 1999 59.71% Ford Focus Sedan 2007 29.44% Nissan 240SX Coupe 1998 9.82% Volkswagen Golf Hatchback 1991 0.74% Hyundai Elantra Touring Hatchback 2012 0.14% +1315 /scratch/Teaching/cars/car_ims/011535.jpg Hyundai Azera Sedan 2012 Buick Verano Sedan 2012 36.06% Honda Accord Sedan 2012 25.72% Acura RL Sedan 2012 14.26% Acura ZDX Hatchback 2012 7.56% Volkswagen Golf Hatchback 2012 2.31% +1316 /scratch/Teaching/cars/car_ims/015564.jpg Toyota 4Runner SUV 2012 Land Rover LR2 SUV 2012 89.02% Hyundai Veracruz SUV 2012 4.93% Toyota Sequoia SUV 2012 2.47% Ford Edge SUV 2012 1.83% Toyota 4Runner SUV 2012 1.03% +1317 /scratch/Teaching/cars/car_ims/014217.jpg Porsche Panamera Sedan 2012 Porsche Panamera Sedan 2012 89.96% Fisker Karma Sedan 2012 7.94% Chevrolet Corvette ZR1 2012 1.17% Ferrari FF Coupe 2012 0.64% Tesla Model S Sedan 2012 0.13% +1318 /scratch/Teaching/cars/car_ims/008660.jpg Ford F-450 Super Duty Crew Cab 2012 Ford F-450 Super Duty Crew Cab 2012 99.99% Ford F-150 Regular Cab 2012 0.01% Dodge Ram Pickup 3500 Crew Cab 2010 0.0% Cadillac Escalade EXT Crew Cab 2007 0.0% Ford E-Series Wagon Van 2012 0.0% +1319 /scratch/Teaching/cars/car_ims/011270.jpg Hyundai Genesis Sedan 2012 Hyundai Genesis Sedan 2012 94.75% Honda Accord Sedan 2012 1.69% Hyundai Azera Sedan 2012 0.77% Dodge Journey SUV 2012 0.7% Hyundai Santa Fe SUV 2012 0.6% +1320 /scratch/Teaching/cars/car_ims/013974.jpg Nissan Juke Hatchback 2012 Hyundai Santa Fe SUV 2012 47.63% Chevrolet Traverse SUV 2012 29.31% Hyundai Veracruz SUV 2012 15.46% Hyundai Tucson SUV 2012 5.39% Ford Edge SUV 2012 1.11% +1321 /scratch/Teaching/cars/car_ims/007285.jpg Dodge Journey SUV 2012 Dodge Journey SUV 2012 99.99% Toyota Corolla Sedan 2012 0.0% Hyundai Santa Fe SUV 2012 0.0% Honda Accord Coupe 2012 0.0% Dodge Durango SUV 2012 0.0% +1322 /scratch/Teaching/cars/car_ims/005881.jpg Chevrolet Malibu Sedan 2007 Chevrolet Malibu Sedan 2007 95.92% Chevrolet Impala Sedan 2007 4.08% Chevrolet Monte Carlo Coupe 2007 0.0% Lincoln Town Car Sedan 2011 0.0% Hyundai Elantra Sedan 2007 0.0% +1323 /scratch/Teaching/cars/car_ims/002050.jpg Audi TT RS Coupe 2012 BMW 3 Series Wagon 2012 28.57% BMW M5 Sedan 2010 10.34% Acura TL Type-S 2008 9.02% BMW 3 Series Sedan 2012 7.74% Acura RL Sedan 2012 6.75% +1324 /scratch/Teaching/cars/car_ims/000887.jpg Audi RS 4 Convertible 2008 Audi RS 4 Convertible 2008 44.08% Mercedes-Benz C-Class Sedan 2012 15.75% Audi S6 Sedan 2011 9.73% BMW 3 Series Sedan 2012 7.36% Audi S5 Convertible 2012 5.03% +1325 /scratch/Teaching/cars/car_ims/014762.jpg Spyker C8 Coupe 2009 Spyker C8 Coupe 2009 96.65% Spyker C8 Convertible 2009 1.42% Hyundai Veloster Hatchback 2012 0.72% Ferrari 458 Italia Convertible 2012 0.4% Ford GT Coupe 2006 0.27% +1326 /scratch/Teaching/cars/car_ims/000494.jpg Acura ZDX Hatchback 2012 Acura ZDX Hatchback 2012 51.55% Acura TL Sedan 2012 13.81% Acura TSX Sedan 2012 8.79% Toyota Camry Sedan 2012 8.35% Buick Regal GS 2012 4.66% +1327 /scratch/Teaching/cars/car_ims/006450.jpg Chrysler Crossfire Convertible 2008 Ford Mustang Convertible 2007 23.1% Chevrolet Corvette Convertible 2012 13.01% Chevrolet Cobalt SS 2010 10.9% Chrysler Crossfire Convertible 2008 9.33% Bentley Continental Supersports Conv. Convertible 2012 7.6% +1328 /scratch/Teaching/cars/car_ims/010301.jpg HUMMER H2 SUT Crew Cab 2009 HUMMER H2 SUT Crew Cab 2009 82.87% HUMMER H3T Crew Cab 2010 15.77% Jeep Wrangler SUV 2012 0.7% AM General Hummer SUV 2000 0.64% GMC Canyon Extended Cab 2012 0.02% +1329 /scratch/Teaching/cars/car_ims/013990.jpg Nissan Juke Hatchback 2012 Volvo C30 Hatchback 2012 41.91% Nissan Juke Hatchback 2012 41.49% Mercedes-Benz C-Class Sedan 2012 5.07% BMW 3 Series Sedan 2012 4.72% Suzuki Kizashi Sedan 2012 1.68% +1330 /scratch/Teaching/cars/car_ims/004935.jpg Chevrolet Impala Sedan 2007 Buick Verano Sedan 2012 9.02% Hyundai Elantra Sedan 2007 8.74% Hyundai Sonata Sedan 2012 6.13% Honda Accord Coupe 2012 5.35% Toyota Corolla Sedan 2012 4.65% +1331 /scratch/Teaching/cars/car_ims/013528.jpg Mercedes-Benz S-Class Sedan 2012 Mercedes-Benz S-Class Sedan 2012 82.26% Mercedes-Benz E-Class Sedan 2012 17.53% Mercedes-Benz C-Class Sedan 2012 0.18% Hyundai Genesis Sedan 2012 0.03% Mercedes-Benz SL-Class Coupe 2009 0.0% +1332 /scratch/Teaching/cars/car_ims/007439.jpg Dodge Dakota Club Cab 2007 GMC Canyon Extended Cab 2012 38.44% Jeep Patriot SUV 2012 31.41% Dodge Dakota Club Cab 2007 24.09% Jeep Wrangler SUV 2012 1.33% Ford Ranger SuperCab 2011 1.27% +1333 /scratch/Teaching/cars/car_ims/008494.jpg Ferrari 458 Italia Coupe 2012 Ferrari 458 Italia Coupe 2012 72.0% Ferrari 458 Italia Convertible 2012 22.55% Chevrolet Corvette ZR1 2012 2.0% Ferrari California Convertible 2012 0.79% Ferrari FF Coupe 2012 0.76% +1334 /scratch/Teaching/cars/car_ims/008964.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 97.58% Hyundai Veracruz SUV 2012 2.36% Hyundai Tucson SUV 2012 0.02% Hyundai Sonata Hybrid Sedan 2012 0.02% Hyundai Sonata Sedan 2012 0.01% +1335 /scratch/Teaching/cars/car_ims/000062.jpg AM General Hummer SUV 2000 AM General Hummer SUV 2000 84.55% HUMMER H2 SUT Crew Cab 2009 7.82% HUMMER H3T Crew Cab 2010 4.88% Jeep Wrangler SUV 2012 2.67% Jeep Patriot SUV 2012 0.06% +1336 /scratch/Teaching/cars/car_ims/003985.jpg Buick Enclave SUV 2012 GMC Acadia SUV 2012 65.42% Buick Enclave SUV 2012 24.11% Chevrolet Traverse SUV 2012 8.44% Hyundai Veracruz SUV 2012 0.95% Mazda Tribute SUV 2011 0.31% +1337 /scratch/Teaching/cars/car_ims/009512.jpg Ford E-Series Wagon Van 2012 Ford E-Series Wagon Van 2012 99.25% Nissan NV Passenger Van 2012 0.33% GMC Savana Van 2012 0.24% Ford F-150 Regular Cab 2007 0.04% Ford Ranger SuperCab 2011 0.04% +1338 /scratch/Teaching/cars/car_ims/015320.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 99.97% Infiniti QX56 SUV 2011 0.01% Cadillac SRX SUV 2012 0.01% Land Rover LR2 SUV 2012 0.01% Dodge Durango SUV 2012 0.0% +1339 /scratch/Teaching/cars/car_ims/002971.jpg BMW X3 SUV 2012 BMW X3 SUV 2012 99.87% BMW X5 SUV 2007 0.13% Jeep Compass SUV 2012 0.0% BMW X6 SUV 2012 0.0% Cadillac SRX SUV 2012 0.0% +1340 /scratch/Teaching/cars/car_ims/003780.jpg Buick Regal GS 2012 Buick Regal GS 2012 99.96% Hyundai Sonata Hybrid Sedan 2012 0.02% Buick Verano Sedan 2012 0.01% Jaguar XK XKR 2012 0.0% Acura TL Sedan 2012 0.0% +1341 /scratch/Teaching/cars/car_ims/011908.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 98.58% Jeep Compass SUV 2012 1.28% Jeep Wrangler SUV 2012 0.06% Jeep Grand Cherokee SUV 2012 0.05% Jeep Liberty SUV 2012 0.02% +1342 /scratch/Teaching/cars/car_ims/009296.jpg Ford F-150 Regular Cab 2007 Ford F-150 Regular Cab 2012 55.21% Ford F-150 Regular Cab 2007 23.82% GMC Canyon Extended Cab 2012 16.94% Ford Ranger SuperCab 2011 1.83% Dodge Ram Pickup 3500 Quad Cab 2009 0.79% +1343 /scratch/Teaching/cars/car_ims/014367.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 Rolls-Royce Phantom Sedan 2012 90.39% Rolls-Royce Ghost Sedan 2012 8.34% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.65% Chrysler 300 SRT-8 2010 0.21% Bentley Arnage Sedan 2009 0.19% +1344 /scratch/Teaching/cars/car_ims/012525.jpg Lamborghini Diablo Coupe 2001 Lamborghini Diablo Coupe 2001 78.05% Acura Integra Type R 2001 21.26% Lamborghini Gallardo LP 570-4 Superleggera 2012 0.27% Geo Metro Convertible 1993 0.14% GMC Savana Van 2012 0.08% +1345 /scratch/Teaching/cars/car_ims/003869.jpg Buick Rainier SUV 2007 Jeep Liberty SUV 2012 83.54% Dodge Durango SUV 2007 4.81% Mazda Tribute SUV 2011 2.66% Volvo XC90 SUV 2007 2.32% BMW X5 SUV 2007 1.58% +1346 /scratch/Teaching/cars/car_ims/012241.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 98.82% Jeep Grand Cherokee SUV 2012 0.9% BMW X3 SUV 2012 0.19% BMW X6 SUV 2012 0.05% HUMMER H3T Crew Cab 2010 0.02% +1347 /scratch/Teaching/cars/car_ims/003232.jpg Bentley Arnage Sedan 2009 Bentley Arnage Sedan 2009 56.99% Rolls-Royce Phantom Sedan 2012 28.42% Chrysler 300 SRT-8 2010 6.14% Volvo 240 Sedan 1993 5.14% Rolls-Royce Ghost Sedan 2012 1.56% +1348 /scratch/Teaching/cars/car_ims/006218.jpg Chrysler Sebring Convertible 2010 Acura TL Type-S 2008 53.49% Chevrolet Malibu Hybrid Sedan 2010 14.87% Acura RL Sedan 2012 10.23% Honda Accord Sedan 2012 8.28% Honda Odyssey Minivan 2012 6.14% +1349 /scratch/Teaching/cars/car_ims/011792.jpg Jaguar XK XKR 2012 Ferrari 458 Italia Convertible 2012 38.55% Ferrari 458 Italia Coupe 2012 33.68% Chevrolet Corvette Convertible 2012 7.05% Ferrari California Convertible 2012 4.64% Jaguar XK XKR 2012 4.59% +1350 /scratch/Teaching/cars/car_ims/004319.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 76.59% Chevrolet Silverado 1500 Regular Cab 2012 16.5% Chevrolet Silverado 1500 Extended Cab 2012 4.01% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 1.72% Chevrolet Tahoe Hybrid SUV 2012 1.13% +1351 /scratch/Teaching/cars/car_ims/012092.jpg Jeep Liberty SUV 2012 Jeep Liberty SUV 2012 99.95% Jeep Patriot SUV 2012 0.05% Jeep Compass SUV 2012 0.0% Bentley Arnage Sedan 2009 0.0% Buick Enclave SUV 2012 0.0% +1352 /scratch/Teaching/cars/car_ims/015334.jpg Toyota Camry Sedan 2012 Toyota Corolla Sedan 2012 85.37% Toyota Camry Sedan 2012 14.63% Acura TSX Sedan 2012 0.0% Mitsubishi Lancer Sedan 2012 0.0% Hyundai Accent Sedan 2012 0.0% +1353 /scratch/Teaching/cars/car_ims/010831.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 99.94% Hyundai Veracruz SUV 2012 0.02% Dodge Journey SUV 2012 0.02% Ford Edge SUV 2012 0.01% Chevrolet Traverse SUV 2012 0.01% +1354 /scratch/Teaching/cars/car_ims/009879.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 99.9% Chevrolet Traverse SUV 2012 0.1% Buick Enclave SUV 2012 0.01% Mazda Tribute SUV 2011 0.0% Hyundai Veracruz SUV 2012 0.0% +1355 /scratch/Teaching/cars/car_ims/014688.jpg Spyker C8 Convertible 2009 Audi R8 Coupe 2012 36.27% Bugatti Veyron 16.4 Coupe 2009 34.29% Lamborghini Reventon Coupe 2008 8.28% Aston Martin V8 Vantage Coupe 2012 7.33% Aston Martin V8 Vantage Convertible 2012 2.58% +1356 /scratch/Teaching/cars/car_ims/008883.jpg Ford Expedition EL SUV 2009 Toyota Sequoia SUV 2012 75.64% Ford Expedition EL SUV 2009 17.66% Cadillac Escalade EXT Crew Cab 2007 4.38% Chrysler Aspen SUV 2009 1.03% Dodge Durango SUV 2012 0.51% +1357 /scratch/Teaching/cars/car_ims/003755.jpg Buick Regal GS 2012 Buick Regal GS 2012 54.37% Mitsubishi Lancer Sedan 2012 26.7% Chevrolet Sonic Sedan 2012 15.64% Buick Verano Sedan 2012 2.01% Toyota Camry Sedan 2012 0.31% +1358 /scratch/Teaching/cars/car_ims/013132.jpg McLaren MP4-12C Coupe 2012 Jaguar XK XKR 2012 35.63% Aston Martin V8 Vantage Coupe 2012 16.53% Aston Martin Virage Coupe 2012 8.44% Chevrolet Camaro Convertible 2012 5.01% BMW Z4 Convertible 2012 4.14% +1359 /scratch/Teaching/cars/car_ims/005564.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 38.06% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 32.23% Chevrolet Silverado 2500HD Regular Cab 2012 15.86% Chevrolet Silverado 1500 Regular Cab 2012 13.1% GMC Canyon Extended Cab 2012 0.48% +1360 /scratch/Teaching/cars/car_ims/015454.jpg Toyota Corolla Sedan 2012 Acura TSX Sedan 2012 71.34% Toyota Camry Sedan 2012 22.26% Acura TL Sedan 2012 4.98% Toyota Corolla Sedan 2012 0.66% Acura RL Sedan 2012 0.5% +1361 /scratch/Teaching/cars/car_ims/006504.jpg Chrysler Crossfire Convertible 2008 Bentley Mulsanne Sedan 2011 48.92% Bentley Continental Flying Spur Sedan 2007 21.33% Maybach Landaulet Convertible 2012 10.4% Rolls-Royce Phantom Sedan 2012 7.33% Bentley Continental GT Coupe 2007 3.33% +1362 /scratch/Teaching/cars/car_ims/004983.jpg Chevrolet Tahoe Hybrid SUV 2012 Isuzu Ascender SUV 2008 58.33% Chevrolet Tahoe Hybrid SUV 2012 29.26% Chevrolet Avalanche Crew Cab 2012 9.84% Chevrolet TrailBlazer SS 2009 0.96% Dodge Dakota Crew Cab 2010 0.75% +1363 /scratch/Teaching/cars/car_ims/012376.jpg Lamborghini Aventador Coupe 2012 Lamborghini Aventador Coupe 2012 99.98% Lamborghini Reventon Coupe 2008 0.02% Audi R8 Coupe 2012 0.0% McLaren MP4-12C Coupe 2012 0.0% Ford GT Coupe 2006 0.0% +1364 /scratch/Teaching/cars/car_ims/014072.jpg Nissan 240SX Coupe 1998 Nissan 240SX Coupe 1998 30.16% Eagle Talon Hatchback 1998 24.25% Chevrolet Monte Carlo Coupe 2007 12.09% Honda Accord Coupe 2012 9.89% Chevrolet Impala Sedan 2007 4.71% +1365 /scratch/Teaching/cars/car_ims/014702.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 47.44% MINI Cooper Roadster Convertible 2012 21.37% Audi S5 Convertible 2012 6.5% Spyker C8 Coupe 2009 3.6% Chevrolet Camaro Convertible 2012 2.83% +1366 /scratch/Teaching/cars/car_ims/002465.jpg BMW 6 Series Convertible 2007 BMW 6 Series Convertible 2007 53.2% BMW M6 Convertible 2010 43.88% Jaguar XK XKR 2012 2.67% BMW Z4 Convertible 2012 0.2% Honda Accord Coupe 2012 0.04% +1367 /scratch/Teaching/cars/car_ims/003962.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 97.03% Suzuki SX4 Sedan 2012 2.45% Acura RL Sedan 2012 0.35% Acura ZDX Hatchback 2012 0.13% Chevrolet Malibu Hybrid Sedan 2010 0.03% +1368 /scratch/Teaching/cars/car_ims/009088.jpg Ford Ranger SuperCab 2011 Ford Ranger SuperCab 2011 64.97% GMC Canyon Extended Cab 2012 15.72% Dodge Dakota Club Cab 2007 8.04% Ford F-150 Regular Cab 2007 6.41% Dodge Ram Pickup 3500 Quad Cab 2009 1.23% +1369 /scratch/Teaching/cars/car_ims/011008.jpg Hyundai Veracruz SUV 2012 Hyundai Veracruz SUV 2012 99.84% Honda Odyssey Minivan 2007 0.09% Acura ZDX Hatchback 2012 0.03% Chevrolet Traverse SUV 2012 0.02% Hyundai Tucson SUV 2012 0.0% +1370 /scratch/Teaching/cars/car_ims/000220.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 61.42% Acura ZDX Hatchback 2012 7.1% Acura RL Sedan 2012 6.47% Chevrolet Malibu Hybrid Sedan 2010 4.44% Hyundai Sonata Hybrid Sedan 2012 3.75% +1371 /scratch/Teaching/cars/car_ims/002755.jpg BMW M3 Coupe 2012 BMW M6 Convertible 2010 21.62% BMW M3 Coupe 2012 16.62% BMW M5 Sedan 2010 15.73% BMW ActiveHybrid 5 Sedan 2012 15.09% Acura TL Type-S 2008 14.92% +1372 /scratch/Teaching/cars/car_ims/008438.jpg Ferrari 458 Italia Coupe 2012 Ferrari California Convertible 2012 67.61% Chevrolet Corvette Convertible 2012 13.28% Jaguar XK XKR 2012 6.38% Ferrari 458 Italia Convertible 2012 6.2% Ferrari FF Coupe 2012 2.37% +1373 /scratch/Teaching/cars/car_ims/014284.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 95.58% Chevrolet Malibu Sedan 2007 1.94% Suzuki SX4 Sedan 2012 1.21% Suzuki Aerio Sedan 2007 0.64% Chrysler Town and Country Minivan 2012 0.38% +1374 /scratch/Teaching/cars/car_ims/015029.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 86.88% Mazda Tribute SUV 2011 9.89% Suzuki SX4 Sedan 2012 2.61% Dodge Caliber Wagon 2012 0.24% Ram C/V Cargo Van Minivan 2012 0.1% +1375 /scratch/Teaching/cars/car_ims/002875.jpg BMW M6 Convertible 2010 Nissan 240SX Coupe 1998 58.08% BMW M6 Convertible 2010 13.86% Eagle Talon Hatchback 1998 9.78% Aston Martin V8 Vantage Coupe 2012 4.76% Aston Martin V8 Vantage Convertible 2012 2.52% +1376 /scratch/Teaching/cars/car_ims/010491.jpg Honda Odyssey Minivan 2007 Chevrolet Impala Sedan 2007 81.31% Hyundai Elantra Sedan 2007 9.38% Honda Odyssey Minivan 2007 5.77% Chevrolet Malibu Sedan 2007 1.74% Suzuki Aerio Sedan 2007 0.65% +1377 /scratch/Teaching/cars/car_ims/001402.jpg Audi 100 Wagon 1994 Chrysler Sebring Convertible 2010 10.0% Hyundai Sonata Sedan 2012 8.84% Honda Accord Sedan 2012 7.99% Hyundai Elantra Sedan 2007 7.58% Hyundai Veracruz SUV 2012 7.56% +1378 /scratch/Teaching/cars/car_ims/012673.jpg Land Rover Range Rover SUV 2012 Land Rover Range Rover SUV 2012 57.94% Land Rover LR2 SUV 2012 42.0% Dodge Durango SUV 2012 0.02% Toyota 4Runner SUV 2012 0.01% Infiniti QX56 SUV 2011 0.01% +1379 /scratch/Teaching/cars/car_ims/009875.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 59.52% GMC Yukon Hybrid SUV 2012 29.81% Mazda Tribute SUV 2011 2.77% Volvo XC90 SUV 2007 1.96% Cadillac Escalade EXT Crew Cab 2007 1.16% +1380 /scratch/Teaching/cars/car_ims/001290.jpg Audi V8 Sedan 1994 Audi V8 Sedan 1994 78.04% Audi 100 Sedan 1994 20.43% Audi 100 Wagon 1994 1.32% Volkswagen Golf Hatchback 1991 0.14% Mercedes-Benz SL-Class Coupe 2009 0.02% +1381 /scratch/Teaching/cars/car_ims/002698.jpg BMW X6 SUV 2012 Nissan Juke Hatchback 2012 61.05% Volvo C30 Hatchback 2012 25.43% FIAT 500 Abarth 2012 4.75% Ford Edge SUV 2012 3.26% BMW X6 SUV 2012 1.58% +1382 /scratch/Teaching/cars/car_ims/000107.jpg Acura RL Sedan 2012 Acura RL Sedan 2012 47.9% Acura TSX Sedan 2012 20.97% Suzuki SX4 Sedan 2012 15.18% Suzuki Aerio Sedan 2007 3.01% Buick Verano Sedan 2012 1.72% +1383 /scratch/Teaching/cars/car_ims/002390.jpg BMW 3 Series Wagon 2012 BMW 3 Series Wagon 2012 78.72% Acura TL Type-S 2008 15.54% BMW ActiveHybrid 5 Sedan 2012 4.03% BMW M5 Sedan 2010 1.23% BMW 3 Series Sedan 2012 0.34% +1384 /scratch/Teaching/cars/car_ims/009104.jpg Ford Ranger SuperCab 2011 Ford Ranger SuperCab 2011 99.18% Isuzu Ascender SUV 2008 0.6% Volvo XC90 SUV 2007 0.11% Ford F-150 Regular Cab 2007 0.05% Ford Freestar Minivan 2007 0.02% +1385 /scratch/Teaching/cars/car_ims/015276.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 100.0% Cadillac SRX SUV 2012 0.0% Infiniti QX56 SUV 2011 0.0% Dodge Durango SUV 2012 0.0% Land Rover LR2 SUV 2012 0.0% +1386 /scratch/Teaching/cars/car_ims/005523.jpg Chevrolet Silverado 2500HD Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 88.42% Chevrolet Silverado 1500 Regular Cab 2012 10.71% Chevrolet Silverado 1500 Extended Cab 2012 0.51% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.22% Ford F-150 Regular Cab 2007 0.06% +1387 /scratch/Teaching/cars/car_ims/011279.jpg Hyundai Genesis Sedan 2012 Hyundai Azera Sedan 2012 47.95% Hyundai Genesis Sedan 2012 47.49% Infiniti G Coupe IPL 2012 1.34% Audi S4 Sedan 2012 0.94% Hyundai Sonata Sedan 2012 0.49% +1388 /scratch/Teaching/cars/car_ims/004537.jpg Chevrolet Corvette ZR1 2012 Chevrolet Corvette ZR1 2012 60.97% Porsche Panamera Sedan 2012 37.88% Volkswagen Beetle Hatchback 2012 0.63% Jaguar XK XKR 2012 0.18% Nissan Leaf Hatchback 2012 0.12% +1389 /scratch/Teaching/cars/car_ims/003789.jpg Buick Regal GS 2012 Mitsubishi Lancer Sedan 2012 69.68% Hyundai Sonata Hybrid Sedan 2012 13.64% Buick Regal GS 2012 10.86% Tesla Model S Sedan 2012 2.33% Honda Accord Coupe 2012 1.42% +1390 /scratch/Teaching/cars/car_ims/014512.jpg Rolls-Royce Phantom Sedan 2012 Bentley Arnage Sedan 2009 70.32% Rolls-Royce Phantom Sedan 2012 29.48% Jeep Patriot SUV 2012 0.18% Bentley Mulsanne Sedan 2011 0.01% Jeep Liberty SUV 2012 0.01% +1391 /scratch/Teaching/cars/car_ims/015459.jpg Toyota Corolla Sedan 2012 Toyota Corolla Sedan 2012 88.92% Toyota Camry Sedan 2012 10.94% Acura TSX Sedan 2012 0.06% Suzuki SX4 Sedan 2012 0.04% Mitsubishi Lancer Sedan 2012 0.03% +1392 /scratch/Teaching/cars/car_ims/008952.jpg Ford Edge SUV 2012 Buick Regal GS 2012 48.32% Mitsubishi Lancer Sedan 2012 46.39% Chevrolet Sonic Sedan 2012 2.93% Toyota Camry Sedan 2012 1.74% Hyundai Sonata Hybrid Sedan 2012 0.15% +1393 /scratch/Teaching/cars/car_ims/011166.jpg Hyundai Accent Sedan 2012 Acura RL Sedan 2012 59.68% Honda Accord Sedan 2012 16.65% Buick Verano Sedan 2012 9.89% Suzuki SX4 Sedan 2012 5.21% Acura ZDX Hatchback 2012 2.19% +1394 /scratch/Teaching/cars/car_ims/007727.jpg Dodge Durango SUV 2007 Mazda Tribute SUV 2011 25.56% GMC Yukon Hybrid SUV 2012 17.43% Isuzu Ascender SUV 2008 14.88% Chevrolet Tahoe Hybrid SUV 2012 9.24% Buick Rainier SUV 2007 6.09% +1395 /scratch/Teaching/cars/car_ims/005110.jpg Chevrolet Sonic Sedan 2012 Suzuki Aerio Sedan 2007 64.45% Suzuki SX4 Sedan 2012 20.34% Toyota Corolla Sedan 2012 10.43% Volkswagen Golf Hatchback 2012 2.23% Hyundai Elantra Sedan 2007 0.6% +1396 /scratch/Teaching/cars/car_ims/012339.jpg Lamborghini Reventon Coupe 2008 Audi R8 Coupe 2012 83.16% Audi S6 Sedan 2011 6.78% Audi RS 4 Convertible 2008 1.67% Chrysler 300 SRT-8 2010 1.53% Mercedes-Benz SL-Class Coupe 2009 1.25% +1397 /scratch/Teaching/cars/car_ims/006699.jpg Daewoo Nubira Wagon 2002 Daewoo Nubira Wagon 2002 38.55% Scion xD Hatchback 2012 13.18% Suzuki Aerio Sedan 2007 9.46% Acura ZDX Hatchback 2012 8.67% Nissan Leaf Hatchback 2012 7.56% +1398 /scratch/Teaching/cars/car_ims/008420.jpg Ferrari 458 Italia Coupe 2012 Spyker C8 Coupe 2009 81.9% Ferrari 458 Italia Coupe 2012 5.58% Ford GT Coupe 2006 4.51% Ferrari 458 Italia Convertible 2012 3.7% Ferrari California Convertible 2012 1.83% +1399 /scratch/Teaching/cars/car_ims/010390.jpg Honda Odyssey Minivan 2012 Honda Odyssey Minivan 2012 50.87% Hyundai Veracruz SUV 2012 35.4% Honda Accord Sedan 2012 4.98% Hyundai Elantra Sedan 2007 4.35% Honda Odyssey Minivan 2007 2.74% +1400 /scratch/Teaching/cars/car_ims/014792.jpg Spyker C8 Coupe 2009 Spyker C8 Coupe 2009 99.92% Spyker C8 Convertible 2009 0.04% Hyundai Veloster Hatchback 2012 0.02% Bugatti Veyron 16.4 Convertible 2009 0.01% Bugatti Veyron 16.4 Coupe 2009 0.01% +1401 /scratch/Teaching/cars/car_ims/000454.jpg Acura Integra Type R 2001 Nissan 240SX Coupe 1998 41.62% Lincoln Town Car Sedan 2011 14.89% Audi 100 Wagon 1994 10.36% Dodge Magnum Wagon 2008 5.41% Audi V8 Sedan 1994 3.91% +1402 /scratch/Teaching/cars/car_ims/010181.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 100.0% Ford F-150 Regular Cab 2007 0.0% Mercedes-Benz 300-Class Convertible 1993 0.0% Plymouth Neon Coupe 1999 0.0% Chevrolet Express Cargo Van 2007 0.0% +1403 /scratch/Teaching/cars/car_ims/005233.jpg Chevrolet Avalanche Crew Cab 2012 Chevrolet Avalanche Crew Cab 2012 98.86% Chevrolet Tahoe Hybrid SUV 2012 1.07% Chevrolet TrailBlazer SS 2009 0.07% Isuzu Ascender SUV 2008 0.0% Chevrolet Silverado 1500 Extended Cab 2012 0.0% +1404 /scratch/Teaching/cars/car_ims/015663.jpg Volkswagen Golf Hatchback 2012 Volkswagen Golf Hatchback 2012 90.41% Suzuki Aerio Sedan 2007 9.53% Suzuki SX4 Sedan 2012 0.03% BMW M5 Sedan 2010 0.02% Toyota Corolla Sedan 2012 0.0% +1405 /scratch/Teaching/cars/car_ims/008991.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 100.0% Hyundai Veracruz SUV 2012 0.0% Hyundai Sonata Hybrid Sedan 2012 0.0% Hyundai Tucson SUV 2012 0.0% Chevrolet Sonic Sedan 2012 0.0% +1406 /scratch/Teaching/cars/car_ims/001612.jpg Audi S6 Sedan 2011 Audi S6 Sedan 2011 99.15% Audi S4 Sedan 2007 0.44% Audi RS 4 Convertible 2008 0.24% Audi S5 Coupe 2012 0.1% Audi A5 Coupe 2012 0.04% +1407 /scratch/Teaching/cars/car_ims/001454.jpg Audi 100 Wagon 1994 Chrysler Town and Country Minivan 2012 44.97% Dodge Magnum Wagon 2008 33.9% Lincoln Town Car Sedan 2011 8.22% Chevrolet Malibu Sedan 2007 6.65% Chrysler Sebring Convertible 2010 6.03% +1408 /scratch/Teaching/cars/car_ims/010958.jpg Hyundai Veracruz SUV 2012 Hyundai Veracruz SUV 2012 72.86% Chevrolet Traverse SUV 2012 26.21% Scion xD Hatchback 2012 0.45% Hyundai Tucson SUV 2012 0.11% Chevrolet Malibu Sedan 2007 0.1% +1409 /scratch/Teaching/cars/car_ims/001015.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 88.47% Audi S4 Sedan 2012 7.81% Audi S5 Coupe 2012 2.28% Audi S4 Sedan 2007 1.26% Audi S6 Sedan 2011 0.1% +1410 /scratch/Teaching/cars/car_ims/007609.jpg Dodge Challenger SRT8 2011 Jaguar XK XKR 2012 66.82% BMW M6 Convertible 2010 11.33% Audi TTS Coupe 2012 5.63% Dodge Challenger SRT8 2011 5.3% Aston Martin V8 Vantage Coupe 2012 2.63% +1411 /scratch/Teaching/cars/car_ims/014554.jpg Rolls-Royce Phantom Sedan 2012 Rolls-Royce Phantom Sedan 2012 99.03% Rolls-Royce Ghost Sedan 2012 0.83% Chrysler 300 SRT-8 2010 0.07% Bentley Arnage Sedan 2009 0.06% Rolls-Royce Phantom Drophead Coupe Convertible 2012 0.01% +1412 /scratch/Teaching/cars/car_ims/015356.jpg Toyota Camry Sedan 2012 Honda Accord Sedan 2012 36.8% Acura RL Sedan 2012 31.26% Acura TL Type-S 2008 10.35% Chevrolet Malibu Hybrid Sedan 2010 8.45% Hyundai Elantra Sedan 2007 3.33% +1413 /scratch/Teaching/cars/car_ims/011019.jpg Hyundai Sonata Hybrid Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 95.18% Acura TL Sedan 2012 1.53% Buick Verano Sedan 2012 1.39% Buick Regal GS 2012 1.35% Toyota Camry Sedan 2012 0.14% +1414 /scratch/Teaching/cars/car_ims/012852.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 99.97% Audi 100 Wagon 1994 0.02% Mercedes-Benz 300-Class Convertible 1993 0.01% Dodge Magnum Wagon 2008 0.0% Volvo 240 Sedan 1993 0.0% +1415 /scratch/Teaching/cars/car_ims/005882.jpg Chevrolet Malibu Sedan 2007 Chevrolet Impala Sedan 2007 68.59% Chevrolet Malibu Sedan 2007 30.46% Chevrolet Monte Carlo Coupe 2007 0.95% Lincoln Town Car Sedan 2011 0.0% Chevrolet Malibu Hybrid Sedan 2010 0.0% +1416 /scratch/Teaching/cars/car_ims/002331.jpg BMW 3 Series Sedan 2012 BMW 3 Series Wagon 2012 39.68% BMW 3 Series Sedan 2012 30.1% Chrysler 300 SRT-8 2010 4.95% Audi S4 Sedan 2007 3.16% BMW M5 Sedan 2010 3.11% +1417 /scratch/Teaching/cars/car_ims/008134.jpg FIAT 500 Convertible 2012 FIAT 500 Convertible 2012 31.5% Bentley Continental Supersports Conv. Convertible 2012 28.36% smart fortwo Convertible 2012 9.82% Maybach Landaulet Convertible 2012 7.66% MINI Cooper Roadster Convertible 2012 7.24% +1418 /scratch/Teaching/cars/car_ims/012487.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 Lamborghini Gallardo LP 570-4 Superleggera 2012 86.3% Aston Martin V8 Vantage Convertible 2012 3.47% Chevrolet Corvette Ron Fellows Edition Z06 2007 1.98% Aston Martin V8 Vantage Coupe 2012 1.69% Bentley Continental Supersports Conv. Convertible 2012 1.67% +1419 /scratch/Teaching/cars/car_ims/005011.jpg Chevrolet Tahoe Hybrid SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 88.58% Chevrolet Avalanche Crew Cab 2012 11.11% Isuzu Ascender SUV 2008 0.18% Chevrolet TrailBlazer SS 2009 0.07% Chevrolet Silverado 1500 Extended Cab 2012 0.04% +1420 /scratch/Teaching/cars/car_ims/004372.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 61.46% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 20.28% Chevrolet Silverado 1500 Regular Cab 2012 12.91% Chevrolet Avalanche Crew Cab 2012 5.01% Chevrolet Silverado 2500HD Regular Cab 2012 0.15% +1421 /scratch/Teaching/cars/car_ims/000857.jpg Aston Martin Virage Coupe 2012 Aston Martin Virage Coupe 2012 99.92% Aston Martin V8 Vantage Coupe 2012 0.03% McLaren MP4-12C Coupe 2012 0.03% Spyker C8 Coupe 2009 0.01% Dodge Charger Sedan 2012 0.0% +1422 /scratch/Teaching/cars/car_ims/001844.jpg Audi S4 Sedan 2012 Acura RL Sedan 2012 44.18% Honda Accord Sedan 2012 18.34% Mercedes-Benz E-Class Sedan 2012 7.41% Audi S4 Sedan 2007 6.55% BMW ActiveHybrid 5 Sedan 2012 5.17% +1423 /scratch/Teaching/cars/car_ims/009420.jpg Ford Focus Sedan 2007 Ford Focus Sedan 2007 44.16% Daewoo Nubira Wagon 2002 24.5% Suzuki Aerio Sedan 2007 14.97% Chevrolet Impala Sedan 2007 8.43% Plymouth Neon Coupe 1999 2.66% +1424 /scratch/Teaching/cars/car_ims/003218.jpg Bentley Arnage Sedan 2009 Audi 100 Wagon 1994 66.38% Audi V8 Sedan 1994 13.59% Audi 100 Sedan 1994 12.46% Volvo 240 Sedan 1993 3.83% Volkswagen Golf Hatchback 1991 3.15% +1425 /scratch/Teaching/cars/car_ims/009866.jpg GMC Acadia SUV 2012 GMC Acadia SUV 2012 94.94% Cadillac SRX SUV 2012 3.3% Chevrolet Traverse SUV 2012 0.66% Nissan Juke Hatchback 2012 0.43% Buick Enclave SUV 2012 0.36% +1426 /scratch/Teaching/cars/car_ims/009886.jpg GMC Acadia SUV 2012 Nissan Juke Hatchback 2012 37.92% Ford Edge SUV 2012 28.85% Jeep Grand Cherokee SUV 2012 21.46% BMW X6 SUV 2012 9.33% Jeep Compass SUV 2012 0.5% +1427 /scratch/Teaching/cars/car_ims/003624.jpg Bugatti Veyron 16.4 Convertible 2009 Acura ZDX Hatchback 2012 11.76% Bentley Continental GT Coupe 2007 9.19% Hyundai Veloster Hatchback 2012 6.26% BMW 6 Series Convertible 2007 5.48% Maybach Landaulet Convertible 2012 4.44% +1428 /scratch/Teaching/cars/car_ims/008311.jpg Ferrari California Convertible 2012 Ferrari FF Coupe 2012 39.82% Ferrari California Convertible 2012 26.51% Ferrari 458 Italia Coupe 2012 16.44% Ferrari 458 Italia Convertible 2012 16.42% Spyker C8 Coupe 2009 0.49% +1429 /scratch/Teaching/cars/car_ims/014188.jpg Porsche Panamera Sedan 2012 Tesla Model S Sedan 2012 37.04% Porsche Panamera Sedan 2012 31.65% Fisker Karma Sedan 2012 9.01% Buick Verano Sedan 2012 3.01% BMW M5 Sedan 2010 2.8% +1430 /scratch/Teaching/cars/car_ims/008213.jpg Ferrari FF Coupe 2012 Lamborghini Reventon Coupe 2008 39.95% Fisker Karma Sedan 2012 16.72% Porsche Panamera Sedan 2012 5.74% Mercedes-Benz SL-Class Coupe 2009 4.05% Tesla Model S Sedan 2012 2.74% +1431 /scratch/Teaching/cars/car_ims/011930.jpg Jeep Patriot SUV 2012 Jeep Patriot SUV 2012 100.0% Jeep Compass SUV 2012 0.0% Jeep Liberty SUV 2012 0.0% GMC Terrain SUV 2012 0.0% Jeep Grand Cherokee SUV 2012 0.0% +1432 /scratch/Teaching/cars/car_ims/006592.jpg Chrysler PT Cruiser Convertible 2008 Jaguar XK XKR 2012 20.13% Hyundai Veloster Hatchback 2012 13.12% Chevrolet Camaro Convertible 2012 10.4% Spyker C8 Coupe 2009 7.21% Chevrolet Cobalt SS 2010 4.68% +1433 /scratch/Teaching/cars/car_ims/002670.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 50.92% Dodge Caliber Wagon 2007 7.83% Chevrolet Sonic Sedan 2012 6.03% Volvo C30 Hatchback 2012 5.62% Suzuki SX4 Hatchback 2012 3.49% +1434 /scratch/Teaching/cars/car_ims/012748.jpg Land Rover LR2 SUV 2012 Toyota 4Runner SUV 2012 68.89% Land Rover LR2 SUV 2012 13.94% GMC Terrain SUV 2012 9.58% Land Rover Range Rover SUV 2012 1.9% Chevrolet Tahoe Hybrid SUV 2012 1.59% +1435 /scratch/Teaching/cars/car_ims/014923.jpg Suzuki Kizashi Sedan 2012 Suzuki Kizashi Sedan 2012 63.08% Suzuki SX4 Sedan 2012 35.52% Buick Verano Sedan 2012 0.49% Suzuki Aerio Sedan 2007 0.27% BMW M5 Sedan 2010 0.26% +1436 /scratch/Teaching/cars/car_ims/004479.jpg Chevrolet Corvette ZR1 2012 Chevrolet Corvette Convertible 2012 62.99% Ferrari 458 Italia Convertible 2012 15.04% Ferrari California Convertible 2012 7.37% Ford GT Coupe 2006 3.2% Chevrolet Corvette ZR1 2012 2.7% +1437 /scratch/Teaching/cars/car_ims/011339.jpg Hyundai Sonata Sedan 2012 Hyundai Accent Sedan 2012 42.71% Toyota Corolla Sedan 2012 19.33% Toyota Camry Sedan 2012 7.81% Honda Accord Coupe 2012 7.46% Hyundai Sonata Hybrid Sedan 2012 5.12% +1438 /scratch/Teaching/cars/car_ims/012004.jpg Jeep Wrangler SUV 2012 Jeep Wrangler SUV 2012 99.28% GMC Canyon Extended Cab 2012 0.29% HUMMER H3T Crew Cab 2010 0.27% Jeep Compass SUV 2012 0.12% Jeep Patriot SUV 2012 0.02% +1439 /scratch/Teaching/cars/car_ims/015148.jpg Suzuki SX4 Sedan 2012 Suzuki SX4 Sedan 2012 73.76% Suzuki Aerio Sedan 2007 24.84% Suzuki SX4 Hatchback 2012 0.75% Volkswagen Golf Hatchback 2012 0.52% Ram C/V Cargo Van Minivan 2012 0.12% +1440 /scratch/Teaching/cars/car_ims/002682.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 91.58% BMW X5 SUV 2007 8.24% BMW 1 Series Coupe 2012 0.12% Jeep Grand Cherokee SUV 2012 0.03% BMW X3 SUV 2012 0.01% +1441 /scratch/Teaching/cars/car_ims/012905.jpg MINI Cooper Roadster Convertible 2012 Cadillac CTS-V Sedan 2012 49.14% MINI Cooper Roadster Convertible 2012 38.79% Ford F-450 Super Duty Crew Cab 2012 5.54% Bentley Mulsanne Sedan 2011 5.44% Cadillac SRX SUV 2012 0.61% +1442 /scratch/Teaching/cars/car_ims/009970.jpg GMC Canyon Extended Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 58.63% Chevrolet Silverado 1500 Regular Cab 2012 12.27% Chevrolet Silverado 1500 Extended Cab 2012 10.2% GMC Canyon Extended Cab 2012 7.28% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 4.99% +1443 /scratch/Teaching/cars/car_ims/006480.jpg Chrysler Crossfire Convertible 2008 Chrysler Crossfire Convertible 2008 99.88% Chrysler Sebring Convertible 2010 0.1% Hyundai Genesis Sedan 2012 0.01% Honda Accord Coupe 2012 0.0% Chevrolet Cobalt SS 2010 0.0% +1444 /scratch/Teaching/cars/car_ims/000325.jpg Acura TSX Sedan 2012 Acura TSX Sedan 2012 95.46% Acura RL Sedan 2012 3.73% Toyota Camry Sedan 2012 0.52% Acura TL Sedan 2012 0.16% Acura TL Type-S 2008 0.08% +1445 /scratch/Teaching/cars/car_ims/000405.jpg Acura Integra Type R 2001 Chevrolet Corvette Convertible 2012 37.07% Chevrolet Corvette ZR1 2012 32.52% Acura Integra Type R 2001 13.52% Ferrari 458 Italia Convertible 2012 4.03% Lamborghini Gallardo LP 570-4 Superleggera 2012 3.09% +1446 /scratch/Teaching/cars/car_ims/014665.jpg Scion xD Hatchback 2012 Ford Edge SUV 2012 66.03% Chevrolet Sonic Sedan 2012 20.34% Land Rover LR2 SUV 2012 5.5% Nissan Juke Hatchback 2012 5.24% Scion xD Hatchback 2012 1.24% +1447 /scratch/Teaching/cars/car_ims/006913.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 95.25% Ford Freestar Minivan 2007 2.75% Audi 100 Wagon 1994 1.27% Dodge Sprinter Cargo Van 2009 0.31% Chevrolet Express Van 2007 0.09% +1448 /scratch/Teaching/cars/car_ims/013848.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 83.41% Ford F-150 Regular Cab 2007 11.94% Audi 100 Wagon 1994 2.32% Daewoo Nubira Wagon 2002 1.08% Chevrolet Express Cargo Van 2007 0.48% +1449 /scratch/Teaching/cars/car_ims/012668.jpg Land Rover Range Rover SUV 2012 Land Rover Range Rover SUV 2012 98.22% Dodge Durango SUV 2012 1.0% Chevrolet TrailBlazer SS 2009 0.61% Land Rover LR2 SUV 2012 0.13% Ford Edge SUV 2012 0.01% +1450 /scratch/Teaching/cars/car_ims/015840.jpg Volkswagen Beetle Hatchback 2012 Volkswagen Beetle Hatchback 2012 99.62% Nissan Leaf Hatchback 2012 0.32% Nissan Juke Hatchback 2012 0.02% Porsche Panamera Sedan 2012 0.01% FIAT 500 Convertible 2012 0.01% +1451 /scratch/Teaching/cars/car_ims/008207.jpg Ferrari FF Coupe 2012 BMW 3 Series Sedan 2012 60.26% Ferrari FF Coupe 2012 30.51% Nissan 240SX Coupe 1998 4.58% Honda Accord Coupe 2012 3.19% Eagle Talon Hatchback 1998 0.57% +1452 /scratch/Teaching/cars/car_ims/009360.jpg Ford F-150 Regular Cab 2007 GMC Yukon Hybrid SUV 2012 30.25% Cadillac Escalade EXT Crew Cab 2007 19.89% Toyota Sequoia SUV 2012 8.07% GMC Acadia SUV 2012 6.86% Chevrolet Tahoe Hybrid SUV 2012 5.9% +1453 /scratch/Teaching/cars/car_ims/003473.jpg Bentley Continental GT Coupe 2007 Bentley Continental GT Coupe 2012 74.71% Bentley Mulsanne Sedan 2011 19.67% Bentley Continental GT Coupe 2007 5.33% Bentley Continental Supersports Conv. Convertible 2012 0.26% Bentley Continental Flying Spur Sedan 2007 0.03% +1454 /scratch/Teaching/cars/car_ims/003444.jpg Bentley Continental GT Coupe 2007 Bentley Continental Flying Spur Sedan 2007 33.47% Bentley Continental GT Coupe 2007 33.39% Bentley Continental GT Coupe 2012 9.02% Chevrolet Malibu Hybrid Sedan 2010 8.66% BMW 6 Series Convertible 2007 4.68% +1455 /scratch/Teaching/cars/car_ims/004542.jpg Chevrolet Corvette ZR1 2012 Ford GT Coupe 2006 65.84% Spyker C8 Convertible 2009 8.76% Chevrolet Corvette Convertible 2012 5.68% Chevrolet Corvette ZR1 2012 5.55% Spyker C8 Coupe 2009 5.54% +1456 /scratch/Teaching/cars/car_ims/013201.jpg Mercedes-Benz 300-Class Convertible 1993 Mercedes-Benz 300-Class Convertible 1993 45.26% Nissan 240SX Coupe 1998 30.12% Audi 100 Wagon 1994 6.08% Chrysler Sebring Convertible 2010 4.21% Chrysler Crossfire Convertible 2008 4.13% +1457 /scratch/Teaching/cars/car_ims/014143.jpg Plymouth Neon Coupe 1999 Hyundai Elantra Touring Hatchback 2012 64.15% Volkswagen Golf Hatchback 2012 32.51% Ford Focus Sedan 2007 2.16% Plymouth Neon Coupe 1999 0.57% Chevrolet Impala Sedan 2007 0.46% +1458 /scratch/Teaching/cars/car_ims/016125.jpg smart fortwo Convertible 2012 Nissan Juke Hatchback 2012 50.62% Hyundai Tucson SUV 2012 28.63% Ford Edge SUV 2012 8.21% Hyundai Veracruz SUV 2012 7.84% Chevrolet Sonic Sedan 2012 0.95% +1459 /scratch/Teaching/cars/car_ims/015945.jpg Volvo 240 Sedan 1993 Audi 100 Wagon 1994 59.57% Volvo 240 Sedan 1993 20.09% Audi V8 Sedan 1994 8.53% Volkswagen Golf Hatchback 1991 8.08% Audi 100 Sedan 1994 1.77% +1460 /scratch/Teaching/cars/car_ims/011783.jpg Jaguar XK XKR 2012 Jaguar XK XKR 2012 53.61% BMW M6 Convertible 2010 17.3% Chevrolet Corvette ZR1 2012 11.12% Porsche Panamera Sedan 2012 8.76% Aston Martin Virage Convertible 2012 2.93% +1461 /scratch/Teaching/cars/car_ims/007800.jpg Dodge Charger Sedan 2012 Chevrolet Cobalt SS 2010 77.17% Dodge Charger Sedan 2012 18.5% Dodge Challenger SRT8 2011 1.96% Dodge Charger SRT-8 2009 1.43% Chevrolet Camaro Convertible 2012 0.55% +1462 /scratch/Teaching/cars/car_ims/002900.jpg BMW M6 Convertible 2010 Jaguar XK XKR 2012 57.06% Aston Martin V8 Vantage Convertible 2012 17.9% BMW M6 Convertible 2010 5.51% Aston Martin Virage Convertible 2012 5.43% BMW 6 Series Convertible 2007 4.3% +1463 /scratch/Teaching/cars/car_ims/007606.jpg Dodge Challenger SRT8 2011 Dodge Challenger SRT8 2011 92.88% Dodge Charger SRT-8 2009 7.11% Dodge Charger Sedan 2012 0.0% Chevrolet Camaro Convertible 2012 0.0% Chevrolet TrailBlazer SS 2009 0.0% +1464 /scratch/Teaching/cars/car_ims/012979.jpg Maybach Landaulet Convertible 2012 Maybach Landaulet Convertible 2012 75.01% Rolls-Royce Phantom Drophead Coupe Convertible 2012 11.23% Bentley Continental Flying Spur Sedan 2007 5.94% Rolls-Royce Phantom Sedan 2012 2.68% BMW 6 Series Convertible 2007 1.81% +1465 /scratch/Teaching/cars/car_ims/009732.jpg GMC Savana Van 2012 Chevrolet Express Van 2007 50.13% GMC Savana Van 2012 25.03% Volkswagen Golf Hatchback 1991 9.29% Daewoo Nubira Wagon 2002 9.09% Buick Rainier SUV 2007 6.11% +1466 /scratch/Teaching/cars/car_ims/011633.jpg Infiniti QX56 SUV 2011 Infiniti QX56 SUV 2011 98.2% Dodge Durango SUV 2012 1.59% Land Rover LR2 SUV 2012 0.1% Land Rover Range Rover SUV 2012 0.09% Toyota Sequoia SUV 2012 0.01% +1467 /scratch/Teaching/cars/car_ims/013761.jpg Nissan Leaf Hatchback 2012 Rolls-Royce Phantom Sedan 2012 22.27% Dodge Challenger SRT8 2011 22.19% Rolls-Royce Phantom Drophead Coupe Convertible 2012 11.44% Fisker Karma Sedan 2012 7.87% Rolls-Royce Ghost Sedan 2012 6.48% +1468 /scratch/Teaching/cars/car_ims/004228.jpg Cadillac Escalade EXT Crew Cab 2007 Cadillac Escalade EXT Crew Cab 2007 99.88% GMC Yukon Hybrid SUV 2012 0.1% Chevrolet Tahoe Hybrid SUV 2012 0.01% Chevrolet Avalanche Crew Cab 2012 0.01% Chrysler Town and Country Minivan 2012 0.0% +1469 /scratch/Teaching/cars/car_ims/011529.jpg Hyundai Azera Sedan 2012 Hyundai Azera Sedan 2012 97.53% Infiniti G Coupe IPL 2012 1.64% Hyundai Genesis Sedan 2012 0.68% Hyundai Sonata Sedan 2012 0.1% Mercedes-Benz E-Class Sedan 2012 0.05% +1470 /scratch/Teaching/cars/car_ims/011960.jpg Jeep Wrangler SUV 2012 Jeep Wrangler SUV 2012 99.61% GMC Canyon Extended Cab 2012 0.26% Jeep Patriot SUV 2012 0.07% HUMMER H3T Crew Cab 2010 0.03% AM General Hummer SUV 2000 0.03% +1471 /scratch/Teaching/cars/car_ims/015080.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 95.15% Scion xD Hatchback 2012 3.18% Suzuki SX4 Sedan 2012 1.64% Suzuki Aerio Sedan 2007 0.03% Volkswagen Golf Hatchback 2012 0.0% +1472 /scratch/Teaching/cars/car_ims/015270.jpg Toyota Sequoia SUV 2012 Toyota Sequoia SUV 2012 72.89% Ford Expedition EL SUV 2009 9.6% Land Rover LR2 SUV 2012 8.76% Land Rover Range Rover SUV 2012 4.09% Chrysler Aspen SUV 2009 3.58% +1473 /scratch/Teaching/cars/car_ims/006000.jpg Chevrolet Silverado 1500 Extended Cab 2012 Chevrolet Silverado 1500 Extended Cab 2012 19.52% Chevrolet Tahoe Hybrid SUV 2012 14.39% GMC Yukon Hybrid SUV 2012 12.35% Chevrolet Avalanche Crew Cab 2012 10.46% Isuzu Ascender SUV 2008 9.15% +1474 /scratch/Teaching/cars/car_ims/006961.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 99.65% Ford Freestar Minivan 2007 0.34% Audi 100 Wagon 1994 0.01% Plymouth Neon Coupe 1999 0.0% Geo Metro Convertible 1993 0.0% +1475 /scratch/Teaching/cars/car_ims/013612.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 74.02% Dodge Sprinter Cargo Van 2009 25.97% Ram C/V Cargo Van Minivan 2012 0.0% Nissan NV Passenger Van 2012 0.0% Audi 100 Wagon 1994 0.0% +1476 /scratch/Teaching/cars/car_ims/010690.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 52.96% Spyker C8 Coupe 2009 44.51% Buick Regal GS 2012 0.41% Hyundai Sonata Hybrid Sedan 2012 0.27% Chevrolet Sonic Sedan 2012 0.17% +1477 /scratch/Teaching/cars/car_ims/009412.jpg Ford Focus Sedan 2007 Plymouth Neon Coupe 1999 80.22% Ford Focus Sedan 2007 16.11% Dodge Caravan Minivan 1997 3.07% Nissan 240SX Coupe 1998 0.52% Chevrolet Impala Sedan 2007 0.04% +1478 /scratch/Teaching/cars/car_ims/015218.jpg Tesla Model S Sedan 2012 Aston Martin Virage Convertible 2012 21.21% Fisker Karma Sedan 2012 20.99% Porsche Panamera Sedan 2012 13.95% Jaguar XK XKR 2012 6.06% Aston Martin V8 Vantage Coupe 2012 6.01% +1479 /scratch/Teaching/cars/car_ims/008775.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 62.49% Lincoln Town Car Sedan 2011 19.89% Audi 100 Wagon 1994 7.36% Chevrolet Malibu Sedan 2007 5.13% Dodge Caravan Minivan 1997 1.35% +1480 /scratch/Teaching/cars/car_ims/015101.jpg Suzuki SX4 Sedan 2012 Suzuki SX4 Sedan 2012 99.77% Suzuki SX4 Hatchback 2012 0.12% Ram C/V Cargo Van Minivan 2012 0.06% Scion xD Hatchback 2012 0.02% Honda Odyssey Minivan 2007 0.01% +1481 /scratch/Teaching/cars/car_ims/000576.jpg Aston Martin V8 Vantage Convertible 2012 Eagle Talon Hatchback 1998 38.23% Ford GT Coupe 2006 23.96% Lamborghini Diablo Coupe 2001 22.04% Chevrolet Corvette ZR1 2012 6.0% Plymouth Neon Coupe 1999 5.1% +1482 /scratch/Teaching/cars/car_ims/012289.jpg Lamborghini Reventon Coupe 2008 Lamborghini Reventon Coupe 2008 98.34% Plymouth Neon Coupe 1999 0.45% Eagle Talon Hatchback 1998 0.21% Lamborghini Aventador Coupe 2012 0.15% Audi V8 Sedan 1994 0.12% +1483 /scratch/Teaching/cars/car_ims/009430.jpg Ford Focus Sedan 2007 Lincoln Town Car Sedan 2011 54.52% Audi 100 Wagon 1994 19.22% Chevrolet Monte Carlo Coupe 2007 7.05% Chevrolet Impala Sedan 2007 5.09% Nissan 240SX Coupe 1998 2.77% +1484 /scratch/Teaching/cars/car_ims/016136.jpg smart fortwo Convertible 2012 smart fortwo Convertible 2012 67.23% Nissan Juke Hatchback 2012 4.79% Scion xD Hatchback 2012 4.71% Chevrolet Sonic Sedan 2012 4.36% Hyundai Elantra Touring Hatchback 2012 3.59% +1485 /scratch/Teaching/cars/car_ims/011715.jpg Isuzu Ascender SUV 2008 Volvo XC90 SUV 2007 96.57% BMW X5 SUV 2007 0.86% GMC Acadia SUV 2012 0.62% Dodge Durango SUV 2007 0.41% Chrysler Aspen SUV 2009 0.33% +1486 /scratch/Teaching/cars/car_ims/014341.jpg Ram C/V Cargo Van Minivan 2012 Ram C/V Cargo Van Minivan 2012 68.78% Dodge Caliber Wagon 2012 14.31% Chevrolet Malibu Sedan 2007 8.21% Suzuki SX4 Sedan 2012 2.86% Dodge Magnum Wagon 2008 2.85% +1487 /scratch/Teaching/cars/car_ims/011329.jpg Hyundai Sonata Sedan 2012 Hyundai Sonata Sedan 2012 55.81% Hyundai Azera Sedan 2012 30.52% Hyundai Genesis Sedan 2012 9.68% Honda Accord Sedan 2012 3.85% Honda Odyssey Minivan 2012 0.11% +1488 /scratch/Teaching/cars/car_ims/001727.jpg Audi S5 Coupe 2012 Volvo C30 Hatchback 2012 11.62% Suzuki Kizashi Sedan 2012 8.36% Chevrolet Sonic Sedan 2012 5.51% Hyundai Veloster Hatchback 2012 4.02% Mitsubishi Lancer Sedan 2012 3.78% +1489 /scratch/Teaching/cars/car_ims/009223.jpg Ford F-150 Regular Cab 2012 Chevrolet Silverado 2500HD Regular Cab 2012 36.66% Chevrolet Silverado 1500 Classic Extended Cab 2007 34.12% Chevrolet Silverado 1500 Extended Cab 2012 6.18% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 5.71% Chevrolet Silverado 1500 Regular Cab 2012 4.37% +1490 /scratch/Teaching/cars/car_ims/011174.jpg Hyundai Accent Sedan 2012 BMW 3 Series Sedan 2012 8.98% Dodge Caliber Wagon 2012 8.22% Dodge Caliber Wagon 2007 8.11% Hyundai Elantra Sedan 2007 5.81% Dodge Magnum Wagon 2008 5.18% +1491 /scratch/Teaching/cars/car_ims/006627.jpg Daewoo Nubira Wagon 2002 Dodge Caliber Wagon 2012 30.16% Chrysler Town and Country Minivan 2012 25.19% Chrysler PT Cruiser Convertible 2008 11.56% Volvo XC90 SUV 2007 8.04% Ram C/V Cargo Van Minivan 2012 5.38% +1492 /scratch/Teaching/cars/car_ims/013292.jpg Mercedes-Benz C-Class Sedan 2012 Mercedes-Benz C-Class Sedan 2012 68.08% Mercedes-Benz E-Class Sedan 2012 14.26% Suzuki Kizashi Sedan 2012 6.42% Mercedes-Benz S-Class Sedan 2012 6.28% Hyundai Genesis Sedan 2012 1.4% +1493 /scratch/Teaching/cars/car_ims/008722.jpg Ford Mustang Convertible 2007 Nissan 240SX Coupe 1998 28.29% Honda Accord Coupe 2012 19.79% Chevrolet Cobalt SS 2010 16.57% Chevrolet Camaro Convertible 2012 16.4% Dodge Challenger SRT8 2011 4.11% +1494 /scratch/Teaching/cars/car_ims/004986.jpg Chevrolet Tahoe Hybrid SUV 2012 Chevrolet Avalanche Crew Cab 2012 73.33% Chevrolet Tahoe Hybrid SUV 2012 23.26% Chevrolet Silverado 1500 Regular Cab 2012 1.61% Chevrolet Silverado 1500 Extended Cab 2012 1.15% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 0.31% +1495 /scratch/Teaching/cars/car_ims/007960.jpg Dodge Charger SRT-8 2009 Dodge Charger SRT-8 2009 99.28% Dodge Charger Sedan 2012 0.69% Dodge Magnum Wagon 2008 0.03% Chevrolet Camaro Convertible 2012 0.0% Dodge Challenger SRT8 2011 0.0% +1496 /scratch/Teaching/cars/car_ims/016023.jpg Volvo XC90 SUV 2007 Volvo XC90 SUV 2007 92.16% Ford Freestar Minivan 2007 4.7% Chrysler Town and Country Minivan 2012 3.05% Lincoln Town Car Sedan 2011 0.05% Audi 100 Wagon 1994 0.03% +1497 /scratch/Teaching/cars/car_ims/011732.jpg Isuzu Ascender SUV 2008 Jeep Patriot SUV 2012 90.95% Chevrolet Tahoe Hybrid SUV 2012 7.58% GMC Yukon Hybrid SUV 2012 0.62% Jeep Liberty SUV 2012 0.6% Mazda Tribute SUV 2011 0.12% +1498 /scratch/Teaching/cars/car_ims/006880.jpg Dodge Caravan Minivan 1997 Acura TL Type-S 2008 61.18% Nissan 240SX Coupe 1998 14.78% Lincoln Town Car Sedan 2011 10.25% Chevrolet Monte Carlo Coupe 2007 4.38% Chevrolet Impala Sedan 2007 3.96% +1499 /scratch/Teaching/cars/car_ims/010117.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 99.77% Mercedes-Benz 300-Class Convertible 1993 0.19% Ford Mustang Convertible 2007 0.02% Ford F-150 Regular Cab 2007 0.01% Chevrolet Monte Carlo Coupe 2007 0.0% +1500 /scratch/Teaching/cars/car_ims/015476.jpg Toyota Corolla Sedan 2012 Buick Verano Sedan 2012 18.0% Acura TSX Sedan 2012 13.52% Acura ZDX Hatchback 2012 9.83% Honda Accord Sedan 2012 6.89% Toyota Corolla Sedan 2012 6.82% +1501 /scratch/Teaching/cars/car_ims/000812.jpg Aston Martin Virage Coupe 2012 Aston Martin Virage Coupe 2012 99.98% McLaren MP4-12C Coupe 2012 0.01% Aston Martin V8 Vantage Coupe 2012 0.01% Dodge Charger Sedan 2012 0.0% Dodge Challenger SRT8 2011 0.0% +1502 /scratch/Teaching/cars/car_ims/006900.jpg Dodge Caravan Minivan 1997 Dodge Caravan Minivan 1997 99.85% Ford Freestar Minivan 2007 0.14% Audi 100 Wagon 1994 0.01% Chevrolet Malibu Sedan 2007 0.0% Lincoln Town Car Sedan 2011 0.0% +1503 /scratch/Teaching/cars/car_ims/003161.jpg Bentley Continental Supersports Conv. Convertible 2012 Bentley Continental Supersports Conv. Convertible 2012 84.9% Rolls-Royce Phantom Drophead Coupe Convertible 2012 5.44% Maybach Landaulet Convertible 2012 5.09% Chevrolet Corvette Ron Fellows Edition Z06 2007 1.99% Rolls-Royce Phantom Sedan 2012 1.06% +1504 /scratch/Teaching/cars/car_ims/006498.jpg Chrysler Crossfire Convertible 2008 Chrysler Crossfire Convertible 2008 99.54% Chrysler Sebring Convertible 2010 0.26% Mercedes-Benz S-Class Sedan 2012 0.08% Audi RS 4 Convertible 2008 0.07% Audi S5 Convertible 2012 0.02% +1505 /scratch/Teaching/cars/car_ims/013583.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 97.78% Dodge Sprinter Cargo Van 2009 2.2% Mercedes-Benz SL-Class Coupe 2009 0.01% Audi 100 Wagon 1994 0.0% Audi 100 Sedan 1994 0.0% +1506 /scratch/Teaching/cars/car_ims/009838.jpg GMC Yukon Hybrid SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 88.61% Chevrolet Avalanche Crew Cab 2012 7.48% GMC Yukon Hybrid SUV 2012 3.81% Isuzu Ascender SUV 2008 0.07% Chevrolet Silverado 1500 Extended Cab 2012 0.03% +1507 /scratch/Teaching/cars/car_ims/015092.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 95.05% Suzuki SX4 Sedan 2012 2.89% Dodge Caliber Wagon 2012 1.63% Dodge Journey SUV 2012 0.1% Chevrolet Sonic Sedan 2012 0.09% +1508 /scratch/Teaching/cars/car_ims/007177.jpg Dodge Sprinter Cargo Van 2009 Dodge Sprinter Cargo Van 2009 72.88% Mercedes-Benz Sprinter Van 2012 27.11% Ram C/V Cargo Van Minivan 2012 0.0% Dodge Caravan Minivan 1997 0.0% Audi 100 Wagon 1994 0.0% +1509 /scratch/Teaching/cars/car_ims/007289.jpg Dodge Journey SUV 2012 Chevrolet Sonic Sedan 2012 57.0% Dodge Journey SUV 2012 10.14% Mitsubishi Lancer Sedan 2012 9.36% Ford Edge SUV 2012 4.67% Volvo C30 Hatchback 2012 3.14% +1510 /scratch/Teaching/cars/car_ims/007647.jpg Dodge Durango SUV 2012 Dodge Durango SUV 2012 99.04% Dodge Journey SUV 2012 0.42% Dodge Magnum Wagon 2008 0.35% Chevrolet HHR SS 2010 0.11% Chevrolet TrailBlazer SS 2009 0.03% +1511 /scratch/Teaching/cars/car_ims/015449.jpg Toyota Corolla Sedan 2012 Toyota Corolla Sedan 2012 90.49% Toyota Camry Sedan 2012 9.5% Mitsubishi Lancer Sedan 2012 0.01% Hyundai Accent Sedan 2012 0.0% Chevrolet Sonic Sedan 2012 0.0% +1512 /scratch/Teaching/cars/car_ims/004145.jpg Cadillac SRX SUV 2012 Cadillac SRX SUV 2012 65.51% BMW X3 SUV 2012 10.14% Buick Enclave SUV 2012 4.53% GMC Acadia SUV 2012 3.72% Dodge Durango SUV 2012 2.59% +1513 /scratch/Teaching/cars/car_ims/015083.jpg Suzuki SX4 Hatchback 2012 Ford Fiesta Sedan 2012 70.34% Scion xD Hatchback 2012 23.96% Nissan Leaf Hatchback 2012 2.44% Volkswagen Golf Hatchback 2012 1.04% Hyundai Elantra Touring Hatchback 2012 0.76% +1514 /scratch/Teaching/cars/car_ims/001774.jpg Audi S5 Coupe 2012 Audi S5 Coupe 2012 35.97% Audi S4 Sedan 2012 33.8% Audi S5 Convertible 2012 20.44% Audi A5 Coupe 2012 7.59% Audi TT Hatchback 2011 0.9% +1515 /scratch/Teaching/cars/car_ims/010206.jpg HUMMER H3T Crew Cab 2010 HUMMER H3T Crew Cab 2010 73.16% HUMMER H2 SUT Crew Cab 2009 26.83% AM General Hummer SUV 2000 0.01% Jeep Wrangler SUV 2012 0.0% McLaren MP4-12C Coupe 2012 0.0% +1516 /scratch/Teaching/cars/car_ims/008923.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 62.67% Ford F-450 Super Duty Crew Cab 2012 12.07% Ford F-150 Regular Cab 2012 7.13% Ford E-Series Wagon Van 2012 5.91% Land Rover LR2 SUV 2012 2.82% +1517 /scratch/Teaching/cars/car_ims/002014.jpg Audi TT RS Coupe 2012 Audi TT RS Coupe 2012 99.91% Audi TT Hatchback 2011 0.09% Audi TTS Coupe 2012 0.0% Audi S4 Sedan 2012 0.0% Ferrari 458 Italia Coupe 2012 0.0% +1518 /scratch/Teaching/cars/car_ims/011188.jpg Hyundai Accent Sedan 2012 Hyundai Sonata Hybrid Sedan 2012 48.94% Hyundai Accent Sedan 2012 46.43% Ford Edge SUV 2012 2.95% Ford Fiesta Sedan 2012 0.48% Honda Accord Coupe 2012 0.47% +1519 /scratch/Teaching/cars/car_ims/015046.jpg Suzuki SX4 Hatchback 2012 Hyundai Veracruz SUV 2012 29.51% Scion xD Hatchback 2012 23.19% Suzuki SX4 Hatchback 2012 15.07% Suzuki SX4 Sedan 2012 10.12% Chevrolet Traverse SUV 2012 3.86% +1520 /scratch/Teaching/cars/car_ims/008104.jpg FIAT 500 Abarth 2012 FIAT 500 Abarth 2012 100.0% Nissan Juke Hatchback 2012 0.0% Volvo C30 Hatchback 2012 0.0% Spyker C8 Convertible 2009 0.0% Ford GT Coupe 2006 0.0% +1521 /scratch/Teaching/cars/car_ims/010880.jpg Hyundai Tucson SUV 2012 Hyundai Tucson SUV 2012 96.63% Hyundai Veracruz SUV 2012 3.35% Chevrolet Traverse SUV 2012 0.02% Ford Fiesta Sedan 2012 0.0% Hyundai Sonata Hybrid Sedan 2012 0.0% +1522 /scratch/Teaching/cars/car_ims/014073.jpg Nissan 240SX Coupe 1998 Nissan 240SX Coupe 1998 53.73% Dodge Challenger SRT8 2011 8.9% Fisker Karma Sedan 2012 8.29% Acura TL Type-S 2008 6.94% Dodge Charger SRT-8 2009 3.7% +1523 /scratch/Teaching/cars/car_ims/000739.jpg Aston Martin V8 Vantage Coupe 2012 Jaguar XK XKR 2012 44.75% Aston Martin V8 Vantage Coupe 2012 26.19% Chevrolet Monte Carlo Coupe 2007 14.61% Dodge Challenger SRT8 2011 5.13% Chevrolet Camaro Convertible 2012 2.8% +1524 /scratch/Teaching/cars/car_ims/007972.jpg Eagle Talon Hatchback 1998 Ferrari FF Coupe 2012 19.82% Toyota Corolla Sedan 2012 8.63% Hyundai Accent Sedan 2012 8.06% Volvo C30 Hatchback 2012 6.83% Audi TT RS Coupe 2012 6.71% +1525 /scratch/Teaching/cars/car_ims/001931.jpg Audi S4 Sedan 2007 Audi A5 Coupe 2012 73.85% Audi S5 Coupe 2012 11.27% Audi S4 Sedan 2007 10.47% Audi S4 Sedan 2012 2.53% Audi S6 Sedan 2011 1.01% +1526 /scratch/Teaching/cars/car_ims/011269.jpg Hyundai Genesis Sedan 2012 Hyundai Genesis Sedan 2012 91.58% Mercedes-Benz C-Class Sedan 2012 4.28% Mercedes-Benz E-Class Sedan 2012 2.27% Hyundai Azera Sedan 2012 0.89% Mercedes-Benz S-Class Sedan 2012 0.58% +1527 /scratch/Teaching/cars/car_ims/014691.jpg Spyker C8 Convertible 2009 Spyker C8 Convertible 2009 99.73% Chevrolet Corvette ZR1 2012 0.08% Fisker Karma Sedan 2012 0.08% Bugatti Veyron 16.4 Coupe 2009 0.04% Spyker C8 Coupe 2009 0.04% +1528 /scratch/Teaching/cars/car_ims/008526.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 41.02% Chevrolet Corvette Ron Fellows Edition Z06 2007 19.6% Aston Martin V8 Vantage Coupe 2012 14.18% Aston Martin V8 Vantage Convertible 2012 6.23% Lamborghini Reventon Coupe 2008 5.42% +1529 /scratch/Teaching/cars/car_ims/014456.jpg Rolls-Royce Ghost Sedan 2012 Rolls-Royce Ghost Sedan 2012 69.62% Dodge Challenger SRT8 2011 9.09% Chevrolet Malibu Hybrid Sedan 2010 4.54% Dodge Charger Sedan 2012 3.79% BMW 6 Series Convertible 2007 2.1% +1530 /scratch/Teaching/cars/car_ims/001760.jpg Audi S5 Coupe 2012 Acura RL Sedan 2012 78.64% Honda Accord Sedan 2012 16.3% Suzuki SX4 Sedan 2012 1.83% Suzuki Aerio Sedan 2007 0.72% Acura TSX Sedan 2012 0.65% +1531 /scratch/Teaching/cars/car_ims/011603.jpg Infiniti G Coupe IPL 2012 BMW ActiveHybrid 5 Sedan 2012 57.05% BMW 6 Series Convertible 2007 18.12% Acura TL Type-S 2008 8.9% BMW M6 Convertible 2010 5.7% BMW M5 Sedan 2010 2.68% +1532 /scratch/Teaching/cars/car_ims/000210.jpg Acura TL Sedan 2012 Acura RL Sedan 2012 41.2% Acura TSX Sedan 2012 32.9% Acura TL Sedan 2012 25.05% Acura ZDX Hatchback 2012 0.51% Hyundai Elantra Sedan 2007 0.13% +1533 /scratch/Teaching/cars/car_ims/015090.jpg Suzuki SX4 Hatchback 2012 Suzuki SX4 Hatchback 2012 48.24% Buick Rainier SUV 2007 36.98% Chevrolet HHR SS 2010 11.62% Mazda Tribute SUV 2011 1.95% Dodge Caliber Wagon 2007 0.27% +1534 /scratch/Teaching/cars/car_ims/005019.jpg Chevrolet Tahoe Hybrid SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 45.3% Chevrolet Avalanche Crew Cab 2012 30.05% Isuzu Ascender SUV 2008 11.66% GMC Yukon Hybrid SUV 2012 9.81% Cadillac Escalade EXT Crew Cab 2007 1.04% +1535 /scratch/Teaching/cars/car_ims/007715.jpg Dodge Durango SUV 2007 Rolls-Royce Phantom Sedan 2012 59.51% Rolls-Royce Ghost Sedan 2012 14.7% Chrysler 300 SRT-8 2010 8.25% Volvo 240 Sedan 1993 4.79% Bentley Arnage Sedan 2009 3.42% +1536 /scratch/Teaching/cars/car_ims/005418.jpg Chevrolet Malibu Hybrid Sedan 2010 Chevrolet Malibu Hybrid Sedan 2010 99.99% Chevrolet Impala Sedan 2007 0.01% Honda Accord Sedan 2012 0.0% Buick Verano Sedan 2012 0.0% Chevrolet Monte Carlo Coupe 2007 0.0% +1537 /scratch/Teaching/cars/car_ims/012690.jpg Land Rover Range Rover SUV 2012 Land Rover Range Rover SUV 2012 88.33% Land Rover LR2 SUV 2012 9.8% Infiniti QX56 SUV 2011 1.01% Dodge Durango SUV 2012 0.83% Toyota Sequoia SUV 2012 0.01% +1538 /scratch/Teaching/cars/car_ims/007134.jpg Dodge Ram Pickup 3500 Quad Cab 2009 Dodge Ram Pickup 3500 Quad Cab 2009 60.75% Dodge Dakota Club Cab 2007 20.48% Dodge Dakota Crew Cab 2010 13.17% GMC Canyon Extended Cab 2012 2.24% HUMMER H3T Crew Cab 2010 0.86% +1539 /scratch/Teaching/cars/car_ims/013235.jpg Mercedes-Benz 300-Class Convertible 1993 Rolls-Royce Ghost Sedan 2012 25.07% BMW M6 Convertible 2010 22.22% Rolls-Royce Phantom Drophead Coupe Convertible 2012 20.73% BMW 6 Series Convertible 2007 7.28% Chrysler 300 SRT-8 2010 3.47% +1540 /scratch/Teaching/cars/car_ims/008464.jpg Ferrari 458 Italia Coupe 2012 Lamborghini Gallardo LP 570-4 Superleggera 2012 66.53% McLaren MP4-12C Coupe 2012 16.3% Lamborghini Aventador Coupe 2012 14.08% Aston Martin V8 Vantage Coupe 2012 1.05% Lamborghini Diablo Coupe 2001 0.87% +1541 /scratch/Teaching/cars/car_ims/012425.jpg Lamborghini Aventador Coupe 2012 Lamborghini Aventador Coupe 2012 26.35% Lamborghini Reventon Coupe 2008 23.13% Bugatti Veyron 16.4 Coupe 2009 16.45% Audi R8 Coupe 2012 10.99% Bugatti Veyron 16.4 Convertible 2009 4.74% +1542 /scratch/Teaching/cars/car_ims/006779.jpg Dodge Caliber Wagon 2012 Dodge Caliber Wagon 2012 85.23% Dodge Caliber Wagon 2007 14.7% Dodge Journey SUV 2012 0.03% Dodge Magnum Wagon 2008 0.02% Dodge Dakota Crew Cab 2010 0.01% +1543 /scratch/Teaching/cars/car_ims/009242.jpg Ford F-150 Regular Cab 2012 Chevrolet Silverado 1500 Hybrid Crew Cab 2012 36.17% Chevrolet Silverado 1500 Extended Cab 2012 28.02% Chevrolet Silverado 2500HD Regular Cab 2012 14.46% Chevrolet Silverado 1500 Regular Cab 2012 5.98% Chevrolet Avalanche Crew Cab 2012 4.02% +1544 /scratch/Teaching/cars/car_ims/000614.jpg Aston Martin V8 Vantage Convertible 2012 Lamborghini Reventon Coupe 2008 97.42% Lamborghini Aventador Coupe 2012 1.08% Aston Martin V8 Vantage Coupe 2012 0.73% Audi R8 Coupe 2012 0.23% Aston Martin V8 Vantage Convertible 2012 0.17% +1545 /scratch/Teaching/cars/car_ims/010172.jpg Geo Metro Convertible 1993 Geo Metro Convertible 1993 99.8% Plymouth Neon Coupe 1999 0.1% Acura Integra Type R 2001 0.06% Ford Focus Sedan 2007 0.01% Chevrolet Monte Carlo Coupe 2007 0.01% +1546 /scratch/Teaching/cars/car_ims/002685.jpg BMW X6 SUV 2012 BMW X3 SUV 2012 47.43% BMW X5 SUV 2007 18.17% BMW X6 SUV 2012 7.2% Buick Verano Sedan 2012 5.05% BMW 3 Series Wagon 2012 4.34% +1547 /scratch/Teaching/cars/car_ims/006255.jpg Chrysler Sebring Convertible 2010 Chrysler Town and Country Minivan 2012 46.68% Chrysler Sebring Convertible 2010 25.52% Dodge Magnum Wagon 2008 15.68% Dodge Caliber Wagon 2012 3.55% Lincoln Town Car Sedan 2011 1.77% +1548 /scratch/Teaching/cars/car_ims/010701.jpg Hyundai Veloster Hatchback 2012 Hyundai Veloster Hatchback 2012 80.29% Chevrolet Sonic Sedan 2012 17.67% Mitsubishi Lancer Sedan 2012 1.52% Volvo C30 Hatchback 2012 0.44% Hyundai Accent Sedan 2012 0.03% +1549 /scratch/Teaching/cars/car_ims/008937.jpg Ford Expedition EL SUV 2009 Ford Expedition EL SUV 2009 99.58% Land Rover Range Rover SUV 2012 0.22% Hyundai Santa Fe SUV 2012 0.1% Chrysler Aspen SUV 2009 0.06% Toyota Sequoia SUV 2012 0.03% +1550 /scratch/Teaching/cars/car_ims/011221.jpg Hyundai Genesis Sedan 2012 Honda Accord Sedan 2012 39.18% Acura RL Sedan 2012 29.93% Hyundai Genesis Sedan 2012 15.77% Acura TL Type-S 2008 4.41% Toyota Corolla Sedan 2012 4.02% +1551 /scratch/Teaching/cars/car_ims/000611.jpg Aston Martin V8 Vantage Convertible 2012 Aston Martin V8 Vantage Coupe 2012 61.88% Aston Martin V8 Vantage Convertible 2012 37.82% Aston Martin Virage Convertible 2012 0.14% Fisker Karma Sedan 2012 0.09% BMW M6 Convertible 2010 0.03% +1552 /scratch/Teaching/cars/car_ims/009229.jpg Ford F-150 Regular Cab 2012 Ford F-150 Regular Cab 2007 46.97% Nissan NV Passenger Van 2012 13.71% Ford F-150 Regular Cab 2012 11.32% Dodge Sprinter Cargo Van 2009 7.65% Ford E-Series Wagon Van 2012 5.4% +1553 /scratch/Teaching/cars/car_ims/013895.jpg Nissan NV Passenger Van 2012 Nissan NV Passenger Van 2012 100.0% Ford E-Series Wagon Van 2012 0.0% GMC Yukon Hybrid SUV 2012 0.0% Ford F-150 Regular Cab 2007 0.0% GMC Savana Van 2012 0.0% +1554 /scratch/Teaching/cars/car_ims/001569.jpg Audi S6 Sedan 2011 Audi S4 Sedan 2007 94.88% Audi A5 Coupe 2012 4.28% Audi S6 Sedan 2011 0.59% Audi S5 Coupe 2012 0.19% Audi S4 Sedan 2012 0.05% +1555 /scratch/Teaching/cars/car_ims/006173.jpg Chrysler Aspen SUV 2009 Chrysler Aspen SUV 2009 99.41% Dodge Ram Pickup 3500 Crew Cab 2010 0.26% Ford F-150 Regular Cab 2012 0.13% Dodge Durango SUV 2007 0.05% Ford E-Series Wagon Van 2012 0.04% +1556 /scratch/Teaching/cars/car_ims/001960.jpg Audi S4 Sedan 2007 Audi A5 Coupe 2012 51.41% Audi S5 Coupe 2012 21.64% Audi S4 Sedan 2007 14.83% Audi S4 Sedan 2012 6.1% Audi RS 4 Convertible 2008 2.95% +1557 /scratch/Teaching/cars/car_ims/013514.jpg Mercedes-Benz S-Class Sedan 2012 Cadillac CTS-V Sedan 2012 58.38% Suzuki Kizashi Sedan 2012 17.25% MINI Cooper Roadster Convertible 2012 8.43% Nissan Juke Hatchback 2012 3.99% BMW X3 SUV 2012 2.05% +1558 /scratch/Teaching/cars/car_ims/003636.jpg Bugatti Veyron 16.4 Convertible 2009 Bugatti Veyron 16.4 Coupe 2009 56.73% Bugatti Veyron 16.4 Convertible 2009 27.46% Lamborghini Gallardo LP 570-4 Superleggera 2012 6.1% Spyker C8 Convertible 2009 3.2% Spyker C8 Coupe 2009 1.82% +1559 /scratch/Teaching/cars/car_ims/013698.jpg Mitsubishi Lancer Sedan 2012 Lamborghini Aventador Coupe 2012 78.89% McLaren MP4-12C Coupe 2012 8.01% HUMMER H2 SUT Crew Cab 2009 2.52% Ford GT Coupe 2006 2.47% HUMMER H3T Crew Cab 2010 1.68% +1560 /scratch/Teaching/cars/car_ims/009760.jpg GMC Savana Van 2012 GMC Savana Van 2012 70.95% Chevrolet Express Cargo Van 2007 7.79% Chevrolet Express Van 2007 6.08% Dodge Sprinter Cargo Van 2009 4.23% Nissan NV Passenger Van 2012 2.46% +1561 /scratch/Teaching/cars/car_ims/008162.jpg FIAT 500 Convertible 2012 FIAT 500 Convertible 2012 99.66% Nissan Leaf Hatchback 2012 0.33% Volkswagen Beetle Hatchback 2012 0.0% MINI Cooper Roadster Convertible 2012 0.0% Nissan Juke Hatchback 2012 0.0% +1562 /scratch/Teaching/cars/car_ims/014001.jpg Nissan Juke Hatchback 2012 Audi TTS Coupe 2012 63.19% Tesla Model S Sedan 2012 9.84% Audi TT Hatchback 2011 6.88% Cadillac CTS-V Sedan 2012 3.85% Bentley Continental GT Coupe 2012 3.54% +1563 /scratch/Teaching/cars/car_ims/011483.jpg Hyundai Azera Sedan 2012 Hyundai Azera Sedan 2012 95.45% Hyundai Genesis Sedan 2012 4.33% Hyundai Sonata Sedan 2012 0.18% Infiniti G Coupe IPL 2012 0.04% Honda Accord Sedan 2012 0.0% +1564 /scratch/Teaching/cars/car_ims/011017.jpg Hyundai Sonata Hybrid Sedan 2012 Acura ZDX Hatchback 2012 31.93% Buick Verano Sedan 2012 28.56% Buick Regal GS 2012 17.23% Hyundai Sonata Hybrid Sedan 2012 7.81% Acura TL Sedan 2012 4.88% +1565 /scratch/Teaching/cars/car_ims/012165.jpg Jeep Grand Cherokee SUV 2012 Jeep Grand Cherokee SUV 2012 65.95% GMC Acadia SUV 2012 24.82% Chevrolet Traverse SUV 2012 2.35% Jeep Compass SUV 2012 2.17% GMC Terrain SUV 2012 1.7% +1566 /scratch/Teaching/cars/car_ims/001027.jpg Audi A5 Coupe 2012 Audi A5 Coupe 2012 56.06% Mitsubishi Lancer Sedan 2012 38.17% Audi S4 Sedan 2012 2.83% Audi S4 Sedan 2007 1.06% Honda Accord Coupe 2012 0.53% +1567 /scratch/Teaching/cars/car_ims/001665.jpg Audi S5 Convertible 2012 Jaguar XK XKR 2012 36.36% Honda Accord Coupe 2012 33.85% BMW M6 Convertible 2010 8.8% Audi S4 Sedan 2012 6.56% Acura TL Type-S 2008 6.55% +1568 /scratch/Teaching/cars/car_ims/005675.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 Chevrolet Silverado 1500 Classic Extended Cab 2007 33.73% Chevrolet Silverado 1500 Extended Cab 2012 24.48% Chevrolet Silverado 1500 Hybrid Crew Cab 2012 8.79% Chevrolet Avalanche Crew Cab 2012 4.25% Isuzu Ascender SUV 2008 3.53% +1569 /scratch/Teaching/cars/car_ims/015576.jpg Toyota 4Runner SUV 2012 Land Rover LR2 SUV 2012 95.84% Honda Odyssey Minivan 2012 2.17% Hyundai Veracruz SUV 2012 0.95% Land Rover Range Rover SUV 2012 0.55% Honda Odyssey Minivan 2007 0.29% +1570 /scratch/Teaching/cars/car_ims/013128.jpg McLaren MP4-12C Coupe 2012 Lamborghini Aventador Coupe 2012 78.19% McLaren MP4-12C Coupe 2012 14.07% Lamborghini Gallardo LP 570-4 Superleggera 2012 4.38% Lamborghini Reventon Coupe 2008 1.51% Bugatti Veyron 16.4 Coupe 2009 0.6% +1571 /scratch/Teaching/cars/car_ims/007383.jpg Dodge Dakota Crew Cab 2010 Dodge Dakota Crew Cab 2010 98.72% Dodge Dakota Club Cab 2007 1.28% Dodge Ram Pickup 3500 Quad Cab 2009 0.0% Chevrolet Silverado 1500 Extended Cab 2012 0.0% GMC Canyon Extended Cab 2012 0.0% +1572 /scratch/Teaching/cars/car_ims/006760.jpg Dodge Caliber Wagon 2012 Chevrolet Malibu Sedan 2007 67.81% Honda Odyssey Minivan 2007 10.48% Hyundai Veracruz SUV 2012 7.53% Land Rover LR2 SUV 2012 2.56% Honda Odyssey Minivan 2012 2.53% +1573 /scratch/Teaching/cars/car_ims/005733.jpg Chevrolet Express Van 2007 Chevrolet Express Van 2007 60.84% Chevrolet Express Cargo Van 2007 26.21% GMC Savana Van 2012 11.37% Plymouth Neon Coupe 1999 0.57% Volkswagen Golf Hatchback 1991 0.51% +1574 /scratch/Teaching/cars/car_ims/003803.jpg Buick Regal GS 2012 Cadillac CTS-V Sedan 2012 42.73% Audi S5 Coupe 2012 18.18% Bentley Continental GT Coupe 2012 9.33% Audi TTS Coupe 2012 6.43% Suzuki Kizashi Sedan 2012 5.48% +1575 /scratch/Teaching/cars/car_ims/008956.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 95.74% Land Rover LR2 SUV 2012 4.08% Toyota 4Runner SUV 2012 0.13% Honda Odyssey Minivan 2012 0.03% Hyundai Veracruz SUV 2012 0.02% +1576 /scratch/Teaching/cars/car_ims/014087.jpg Nissan 240SX Coupe 1998 Nissan 240SX Coupe 1998 99.58% Honda Accord Coupe 2012 0.31% BMW M6 Convertible 2010 0.08% Acura TL Type-S 2008 0.01% BMW 3 Series Sedan 2012 0.01% +1577 /scratch/Teaching/cars/car_ims/008802.jpg Ford Freestar Minivan 2007 Ford Freestar Minivan 2007 99.71% Lincoln Town Car Sedan 2011 0.19% Dodge Caravan Minivan 1997 0.05% Audi 100 Wagon 1994 0.04% Chevrolet Malibu Sedan 2007 0.01% +1578 /scratch/Teaching/cars/car_ims/013409.jpg Mercedes-Benz E-Class Sedan 2012 BMW 3 Series Wagon 2012 21.48% Honda Accord Sedan 2012 15.71% Acura TL Type-S 2008 13.17% Audi S4 Sedan 2007 11.12% Acura RL Sedan 2012 5.95% +1579 /scratch/Teaching/cars/car_ims/004847.jpg Chevrolet HHR SS 2010 Chevrolet HHR SS 2010 99.46% Dodge Magnum Wagon 2008 0.46% BMW 3 Series Wagon 2012 0.04% BMW 1 Series Coupe 2012 0.02% Mitsubishi Lancer Sedan 2012 0.01% +1580 /scratch/Teaching/cars/car_ims/003903.jpg Buick Verano Sedan 2012 Buick Verano Sedan 2012 85.52% Buick Regal GS 2012 3.22% Suzuki Kizashi Sedan 2012 2.26% Hyundai Azera Sedan 2012 1.67% Acura RL Sedan 2012 1.41% +1581 /scratch/Teaching/cars/car_ims/009008.jpg Ford Edge SUV 2012 Ford Edge SUV 2012 85.29% Chevrolet Sonic Sedan 2012 3.3% Nissan Juke Hatchback 2012 2.8% BMW X6 SUV 2012 2.22% Dodge Journey SUV 2012 1.66% +1582 /scratch/Teaching/cars/car_ims/001253.jpg Audi V8 Sedan 1994 Audi V8 Sedan 1994 76.12% Audi 100 Wagon 1994 10.4% Audi 100 Sedan 1994 5.91% Volkswagen Golf Hatchback 1991 3.18% Volvo 240 Sedan 1993 2.36% +1583 /scratch/Teaching/cars/car_ims/008715.jpg Ford Mustang Convertible 2007 Audi S4 Sedan 2007 13.28% Suzuki SX4 Sedan 2012 10.14% BMW 1 Series Convertible 2012 8.28% Suzuki Kizashi Sedan 2012 7.9% Mercedes-Benz E-Class Sedan 2012 5.63% +1584 /scratch/Teaching/cars/car_ims/004985.jpg Chevrolet Tahoe Hybrid SUV 2012 Chevrolet Tahoe Hybrid SUV 2012 69.23% GMC Yukon Hybrid SUV 2012 24.02% Chevrolet Avalanche Crew Cab 2012 3.8% Chevrolet Silverado 1500 Extended Cab 2012 0.67% Jeep Patriot SUV 2012 0.58% +1585 /scratch/Teaching/cars/car_ims/015428.jpg Toyota Corolla Sedan 2012 Toyota Corolla Sedan 2012 93.72% Toyota Camry Sedan 2012 6.25% Hyundai Accent Sedan 2012 0.02% Chevrolet Sonic Sedan 2012 0.0% Suzuki SX4 Hatchback 2012 0.0% +1586 /scratch/Teaching/cars/car_ims/001193.jpg Audi R8 Coupe 2012 Aston Martin V8 Vantage Coupe 2012 32.12% Lamborghini Reventon Coupe 2008 30.29% Lamborghini Aventador Coupe 2012 21.09% Aston Martin V8 Vantage Convertible 2012 7.25% Audi R8 Coupe 2012 2.87% +1587 /scratch/Teaching/cars/car_ims/007763.jpg Dodge Durango SUV 2007 Dodge Dakota Crew Cab 2010 52.17% Dodge Durango SUV 2007 11.53% Chevrolet Avalanche Crew Cab 2012 9.37% Dodge Caliber Wagon 2012 5.67% Dodge Dakota Club Cab 2007 5.46% +1588 /scratch/Teaching/cars/car_ims/010777.jpg Hyundai Santa Fe SUV 2012 Hyundai Santa Fe SUV 2012 78.6% Hyundai Veracruz SUV 2012 14.16% Honda Odyssey Minivan 2012 6.99% Honda Odyssey Minivan 2007 0.24% Honda Accord Sedan 2012 0.01% +1589 /scratch/Teaching/cars/car_ims/001538.jpg Audi TT Hatchback 2011 Toyota Camry Sedan 2012 41.89% Mitsubishi Lancer Sedan 2012 37.68% Hyundai Accent Sedan 2012 6.49% Audi TT Hatchback 2011 4.8% Toyota Corolla Sedan 2012 2.33% +1590 /scratch/Teaching/cars/car_ims/013652.jpg Mercedes-Benz Sprinter Van 2012 Mercedes-Benz Sprinter Van 2012 98.27% Dodge Sprinter Cargo Van 2009 1.32% Ram C/V Cargo Van Minivan 2012 0.22% Nissan NV Passenger Van 2012 0.18% Audi 100 Wagon 1994 0.0% +1591 /scratch/Teaching/cars/car_ims/008561.jpg Fisker Karma Sedan 2012 Fisker Karma Sedan 2012 27.16% BMW M6 Convertible 2010 14.97% Aston Martin Virage Convertible 2012 11.88% Aston Martin V8 Vantage Coupe 2012 6.93% Aston Martin V8 Vantage Convertible 2012 6.58% +1592 /scratch/Teaching/cars/car_ims/014119.jpg Plymouth Neon Coupe 1999 Buick Rainier SUV 2007 24.1% Audi 100 Wagon 1994 17.21% Chevrolet Express Van 2007 13.42% Plymouth Neon Coupe 1999 12.04% Daewoo Nubira Wagon 2002 9.06% +1593 /scratch/Teaching/cars/car_ims/009661.jpg GMC Terrain SUV 2012 GMC Terrain SUV 2012 100.0% Toyota 4Runner SUV 2012 0.0% Chevrolet Traverse SUV 2012 0.0% Chevrolet Avalanche Crew Cab 2012 0.0% Chevrolet Silverado 1500 Regular Cab 2012 0.0% +1594 /scratch/Teaching/cars/car_ims/003797.jpg Buick Regal GS 2012 Buick Verano Sedan 2012 87.29% Buick Regal GS 2012 4.42% Chevrolet Sonic Sedan 2012 3.6% Mitsubishi Lancer Sedan 2012 0.95% Tesla Model S Sedan 2012 0.56% +1595 /scratch/Teaching/cars/car_ims/004624.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 Bentley Continental Supersports Conv. Convertible 2012 75.02% Rolls-Royce Phantom Drophead Coupe Convertible 2012 13.58% Fisker Karma Sedan 2012 1.79% BMW Z4 Convertible 2012 1.45% BMW M6 Convertible 2010 1.27% +1596 /scratch/Teaching/cars/car_ims/012206.jpg Jeep Compass SUV 2012 Jeep Compass SUV 2012 37.23% Jeep Grand Cherokee SUV 2012 22.47% BMW X5 SUV 2007 22.0% Jeep Liberty SUV 2012 10.67% BMW X3 SUV 2012 2.56% +1597 /scratch/Teaching/cars/car_ims/000959.jpg Audi A5 Coupe 2012 Audi S5 Convertible 2012 26.49% Audi S4 Sedan 2012 23.71% Audi S5 Coupe 2012 20.38% Audi S6 Sedan 2011 19.26% Audi A5 Coupe 2012 4.4% +1598 /scratch/Teaching/cars/car_ims/001742.jpg Audi S5 Coupe 2012 Audi S5 Coupe 2012 29.69% Audi S6 Sedan 2011 25.64% Audi S5 Convertible 2012 16.26% Audi RS 4 Convertible 2008 8.97% Audi A5 Coupe 2012 8.31% +1599 /scratch/Teaching/cars/car_ims/010453.jpg Honda Odyssey Minivan 2007 Honda Odyssey Minivan 2012 40.38% Honda Odyssey Minivan 2007 36.8% Honda Accord Sedan 2012 18.78% Hyundai Veracruz SUV 2012 2.05% Hyundai Elantra Sedan 2007 1.01% +1600 /scratch/Teaching/cars/car_ims/014991.jpg Suzuki Kizashi Sedan 2012 Hyundai Genesis Sedan 2012 36.25% Mercedes-Benz C-Class Sedan 2012 20.39% Toyota Corolla Sedan 2012 10.5% Honda Accord Sedan 2012 6.54% Toyota Camry Sedan 2012 5.77% +1601 /scratch/Teaching/cars/car_ims/006866.jpg Dodge Caliber Wagon 2007 Dodge Caliber Wagon 2012 73.69% Dodge Caliber Wagon 2007 26.22% Dodge Journey SUV 2012 0.06% Dodge Magnum Wagon 2008 0.01% Dodge Charger Sedan 2012 0.0% +1602 /scratch/Teaching/cars/car_ims/002615.jpg BMW X6 SUV 2012 BMW X6 SUV 2012 98.36% BMW X5 SUV 2007 1.19% Jeep Grand Cherokee SUV 2012 0.3% BMW X3 SUV 2012 0.07% Jeep Compass SUV 2012 0.03% +1603 /scratch/Teaching/cars/car_ims/014002.jpg Nissan Juke Hatchback 2012 Ford GT Coupe 2006 8.28% Spyker C8 Coupe 2009 6.82% Nissan Juke Hatchback 2012 4.96% Bentley Continental Supersports Conv. Convertible 2012 3.62% Hyundai Veloster Hatchback 2012 3.44% +1604 /scratch/Teaching/cars/car_ims/010528.jpg Honda Accord Coupe 2012 Honda Accord Coupe 2012 88.29% Acura TL Type-S 2008 7.8% Honda Accord Sedan 2012 3.68% Acura TSX Sedan 2012 0.05% Acura RL Sedan 2012 0.04% +1605 /scratch/Teaching/cars/car_ims/015780.jpg Volkswagen Beetle Hatchback 2012 Volkswagen Beetle Hatchback 2012 99.77% Cadillac CTS-V Sedan 2012 0.09% Suzuki Kizashi Sedan 2012 0.08% Porsche Panamera Sedan 2012 0.04% Nissan Leaf Hatchback 2012 0.01% +1606 /scratch/Teaching/cars/car_ims/000119.jpg Acura RL Sedan 2012 Chevrolet Monte Carlo Coupe 2007 44.13% Chevrolet Impala Sedan 2007 26.63% Chevrolet Malibu Sedan 2007 15.16% Chevrolet Cobalt SS 2010 3.61% Chevrolet Malibu Hybrid Sedan 2010 3.2% +1607 /scratch/Teaching/cars/car_ims/000214.jpg Acura TL Sedan 2012 Acura TL Sedan 2012 99.9% Acura TSX Sedan 2012 0.06% Acura RL Sedan 2012 0.02% Acura ZDX Hatchback 2012 0.01% Toyota Camry Sedan 2012 0.0% +1608 /scratch/Teaching/cars/car_ims/005466.jpg Chevrolet TrailBlazer SS 2009 Chevrolet TrailBlazer SS 2009 99.97% Chevrolet Avalanche Crew Cab 2012 0.03% Dodge Charger SRT-8 2009 0.0% Ford Edge SUV 2012 0.0% Dodge Journey SUV 2012 0.0% +1609 /scratch/Teaching/cars/car_ims/011729.jpg Isuzu Ascender SUV 2008 Isuzu Ascender SUV 2008 61.17% Chevrolet Avalanche Crew Cab 2012 23.05% Chevrolet Tahoe Hybrid SUV 2012 15.54% Chevrolet TrailBlazer SS 2009 0.1% Dodge Dakota Crew Cab 2010 0.08% +1610 /scratch/Teaching/cars/car_ims/015370.jpg Toyota Camry Sedan 2012 Toyota Camry Sedan 2012 80.96% Acura TSX Sedan 2012 10.0% Toyota Corolla Sedan 2012 7.77% Hyundai Accent Sedan 2012 0.63% Volkswagen Golf Hatchback 2012 0.32% +1611 /scratch/Teaching/cars/car_ims/011835.jpg Jaguar XK XKR 2012 BMW M3 Coupe 2012 22.34% Suzuki Kizashi Sedan 2012 13.86% Jaguar XK XKR 2012 11.68% BMW M5 Sedan 2010 8.59% Suzuki Aerio Sedan 2007 6.36% +1612 /scratch/Teaching/cars/car_ims/003714.jpg Bugatti Veyron 16.4 Coupe 2009 Bugatti Veyron 16.4 Coupe 2009 96.52% Bugatti Veyron 16.4 Convertible 2009 2.11% Audi R8 Coupe 2012 1.33% Lamborghini Reventon Coupe 2008 0.01% Mercedes-Benz SL-Class Coupe 2009 0.01% +1613 /scratch/Teaching/cars/car_ims/008459.jpg Ferrari 458 Italia Coupe 2012 McLaren MP4-12C Coupe 2012 45.31% Ferrari 458 Italia Coupe 2012 38.54% Spyker C8 Coupe 2009 8.91% Aston Martin Virage Coupe 2012 3.23% Aston Martin V8 Vantage Coupe 2012 1.69% +1614 /scratch/Teaching/cars/car_ims/015939.jpg Volvo 240 Sedan 1993 Volvo 240 Sedan 1993 99.12% Audi 100 Wagon 1994 0.72% Volvo XC90 SUV 2007 0.06% Bentley Arnage Sedan 2009 0.04% Volkswagen Golf Hatchback 1991 0.04% +1615 /scratch/Teaching/cars/car_ims/007031.jpg Dodge Ram Pickup 3500 Crew Cab 2010 Dodge Ram Pickup 3500 Crew Cab 2010 99.53% Dodge Ram Pickup 3500 Quad Cab 2009 0.37% Dodge Durango SUV 2007 0.07% Chrysler Aspen SUV 2009 0.02% Ford F-450 Super Duty Crew Cab 2012 0.01% +1616 /scratch/Teaching/cars/car_ims/005796.jpg Chevrolet Monte Carlo Coupe 2007 Chevrolet Monte Carlo Coupe 2007 35.31% Chevrolet Malibu Sedan 2007 30.48% Chevrolet Impala Sedan 2007 30.3% Chevrolet Cobalt SS 2010 1.63% Lincoln Town Car Sedan 2011 0.76% +1617 /scratch/Teaching/cars/car_ims/012842.jpg Lincoln Town Car Sedan 2011 Lincoln Town Car Sedan 2011 92.79% Chevrolet Malibu Sedan 2007 2.39% Audi 100 Wagon 1994 1.58% Ford Freestar Minivan 2007 1.09% Chrysler Town and Country Minivan 2012 0.68% +1618 /scratch/Teaching/cars/car_ims/004377.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 Ford Expedition EL SUV 2009 41.3% Land Rover Range Rover SUV 2012 7.81% Chevrolet Silverado 1500 Classic Extended Cab 2007 6.47% Toyota Sequoia SUV 2012 4.53% Hyundai Santa Fe SUV 2012 2.85% +1619 /scratch/Teaching/cars/car_ims/003059.jpg BMW Z4 Convertible 2012 BMW M6 Convertible 2010 34.19% Jaguar XK XKR 2012 17.49% BMW 6 Series Convertible 2007 12.79% Acura TL Type-S 2008 11.81% Fisker Karma Sedan 2012 10.04% \ No newline at end of file diff --git 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b/cars/architecture-investigations/fc/2-layers/256/solver.prototxt new file mode 100644 index 0000000..803ddda --- /dev/null +++ b/cars/architecture-investigations/fc/2-layers/256/solver.prototxt @@ -0,0 +1,14 @@ +test_iter: 51 +test_interval: 102 +base_lr: 0.00999999977648 +display: 12 +max_iter: 10200 +lr_policy: "exp" +gamma: 0.999801933765 +momentum: 0.899999976158 +weight_decay: 9.99999974738e-05 +snapshot: 102 +snapshot_prefix: "snapshot" +solver_mode: GPU +net: "train_val.prototxt" +solver_type: SGD diff --git a/cars/architecture-investigations/fc/2-layers/256/train_val.prototxt b/cars/architecture-investigations/fc/2-layers/256/train_val.prototxt new file mode 100644 index 0000000..49fc7f1 --- /dev/null +++ b/cars/architecture-investigations/fc/2-layers/256/train_val.prototxt @@ -0,0 +1,382 @@ +layer { + name: "train-data" + type: "Data" + top: "data" + top: "label" + include { + phase: TRAIN + } + transform_param { + mirror: true + crop_size: 227 + mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" + } + data_param { + source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db" + batch_size: 128 + backend: LMDB + } +} +layer { + name: "val-data" + type: "Data" + top: "data" + top: "label" + include { + phase: TEST + } + transform_param { + crop_size: 227 + mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" + } + data_param { + source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db" + batch_size: 32 + backend: LMDB + } +} +layer { + name: "conv1" + type: "Convolution" + bottom: "data" + top: "conv1" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu1" + type: "ReLU" + bottom: "conv1" + top: "conv1" +} +layer { + name: "norm1" + type: "LRN" + bottom: "conv1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool1" + type: "Pooling" + bottom: "norm1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv2" + type: "Convolution" + bottom: "pool1" + top: "conv2" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu2" + type: "ReLU" + bottom: "conv2" + top: "conv2" +} +layer { + name: "norm2" + type: "LRN" + bottom: "conv2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool2" + type: "Pooling" + bottom: "norm2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv3" + type: "Convolution" + bottom: "pool2" + top: "conv3" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu3" + type: "ReLU" + bottom: "conv3" + top: "conv3" +} +layer { + name: "conv4" + type: "Convolution" + bottom: "conv3" + top: "conv4" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu4" + type: "ReLU" + bottom: "conv4" + top: "conv4" +} +layer { + name: "conv5" + type: "Convolution" + bottom: "conv4" + top: "conv5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu5" + type: "ReLU" + bottom: "conv5" + top: "conv5" +} +layer { + name: "pool5" + type: "Pooling" + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "fc6" + type: "InnerProduct" + bottom: "pool5" + top: "fc6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu6" + type: "ReLU" + bottom: "fc6" + top: "fc6" +} +layer { + name: "drop6" + type: "Dropout" + bottom: "fc6" + top: "fc6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7" + type: "InnerProduct" + bottom: "fc6" + top: "fc7" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7" + type: "ReLU" + bottom: "fc7" + top: "fc7" +} +layer { + name: "drop7" + type: "Dropout" + bottom: "fc7" + top: "fc7" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc8" + type: "InnerProduct" + bottom: "fc7" + top: "fc8" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 196 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "accuracy" + type: "Accuracy" + bottom: "fc8" + bottom: "label" + top: "accuracy" + include { + phase: TEST + } +} +layer { + name: "loss" + type: "SoftmaxWithLoss" + bottom: "fc8" + bottom: "label" + top: "loss" +} diff --git a/cars/architecture-investigations/fc/3-layers/256/caffe_output.log b/cars/architecture-investigations/fc/3-layers/256/caffe_output.log new file mode 100644 index 0000000..3939fcd --- /dev/null +++ b/cars/architecture-investigations/fc/3-layers/256/caffe_output.log @@ -0,0 +1,4694 @@ +I0410 13:29:53.663193 18534 upgrade_proto.cpp:1082] Attempting to upgrade input file specified using deprecated 'solver_type' field (enum)': /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210410-132952-4f7e/solver.prototxt +I0410 13:29:53.663447 18534 upgrade_proto.cpp:1089] Successfully upgraded file specified using deprecated 'solver_type' field (enum) to 'type' field (string). +W0410 13:29:53.663457 18534 upgrade_proto.cpp:1091] Note that future Caffe releases will only support 'type' field (string) for a solver's type. +I0410 13:29:53.663565 18534 caffe.cpp:218] Using GPUs 2 +I0410 13:29:53.690752 18534 caffe.cpp:223] GPU 2: GeForce GTX 1080 Ti +I0410 13:29:53.985544 18534 solver.cpp:44] Initializing solver from parameters: +test_iter: 51 +test_interval: 102 +base_lr: 0.01 +display: 12 +max_iter: 10200 +lr_policy: "exp" +gamma: 0.99980193 +momentum: 0.9 +weight_decay: 0.0001 +snapshot: 102 +snapshot_prefix: "snapshot" +solver_mode: GPU +device_id: 2 +net: "train_val.prototxt" +train_state { +level: 0 +stage: "" +} +type: "SGD" +I0410 13:29:53.989303 18534 solver.cpp:87] Creating training net from net file: train_val.prototxt +I0410 13:29:53.989905 18534 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer val-data +I0410 13:29:53.989920 18534 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer accuracy +I0410 13:29:53.990103 18534 net.cpp:51] Initializing net from parameters: +state { +phase: TRAIN +level: 0 +stage: "" +} +layer { +name: "train-data" +type: "Data" +top: "data" +top: "label" +include { +phase: TRAIN +} +transform_param { +mirror: true +crop_size: 227 +mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" +} +data_param { +source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db" +batch_size: 128 +backend: LMDB +} +} +layer { +name: "conv1" +type: "Convolution" +bottom: "data" +top: "conv1" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 96 +kernel_size: 11 +stride: 4 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu1" +type: "ReLU" +bottom: "conv1" +top: "conv1" +} +layer { +name: "norm1" +type: "LRN" +bottom: "conv1" +top: "norm1" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool1" +type: "Pooling" +bottom: "norm1" +top: "pool1" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv2" +type: "Convolution" +bottom: "pool1" +top: "conv2" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 2 +kernel_size: 5 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu2" +type: "ReLU" +bottom: "conv2" +top: "conv2" +} +layer { +name: "norm2" +type: "LRN" +bottom: "conv2" +top: "norm2" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool2" +type: "Pooling" +bottom: "norm2" +top: "pool2" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv3" +type: "Convolution" +bottom: "pool2" +top: "conv3" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu3" +type: "ReLU" +bottom: "conv3" +top: "conv3" +} +layer { +name: "conv4" +type: "Convolution" +bottom: "conv3" +top: "conv4" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu4" +type: "ReLU" +bottom: "conv4" +top: "conv4" +} +layer { +name: "conv5" +type: "Convolution" +bottom: "conv4" +top: "conv5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu5" +type: "ReLU" +bottom: "conv5" +top: "conv5" +} +layer { +name: "pool5" +type: "Pooling" +bottom: "conv5" +top: "pool5" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "fc6" +type: "InnerProduct" +bottom: "pool5" +top: "fc6" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu6" +type: "ReLU" +bottom: "fc6" +top: "fc6" +} +layer { +name: "drop6" +type: "Dropout" +bottom: "fc6" +top: "fc6" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7" +type: "InnerProduct" +bottom: "fc6" +top: "fc7" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7" +type: "ReLU" +bottom: "fc7" +top: "fc7" +} +layer { +name: "drop7" +type: "Dropout" +bottom: "fc7" +top: "fc7" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7.5" +type: "InnerProduct" +bottom: "fc7" +top: "fc7.5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7.5" +type: "ReLU" +bottom: "fc7.5" +top: "fc7.5" +} +layer { +name: "drop7.5" +type: "Dropout" +bottom: "fc7.5" +top: "fc7.5" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc8" +type: "InnerProduct" +bottom: "fc7.5" +top: "fc8" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 196 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "loss" +type: "SoftmaxWithLoss" +bottom: "fc8" +bottom: "label" +top: "loss" +} +I0410 13:29:53.990195 18534 layer_factory.hpp:77] Creating layer train-data +I0410 13:29:53.992305 18534 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db +I0410 13:29:53.992511 18534 net.cpp:84] Creating Layer train-data +I0410 13:29:53.992522 18534 net.cpp:380] train-data -> data +I0410 13:29:53.992542 18534 net.cpp:380] train-data -> label +I0410 13:29:53.992552 18534 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto +I0410 13:29:53.997439 18534 data_layer.cpp:45] output data size: 128,3,227,227 +I0410 13:29:54.124639 18534 net.cpp:122] Setting up train-data +I0410 13:29:54.124661 18534 net.cpp:129] Top shape: 128 3 227 227 (19787136) +I0410 13:29:54.124666 18534 net.cpp:129] Top shape: 128 (128) +I0410 13:29:54.124671 18534 net.cpp:137] Memory required for data: 79149056 +I0410 13:29:54.124681 18534 layer_factory.hpp:77] Creating layer conv1 +I0410 13:29:54.124701 18534 net.cpp:84] Creating Layer conv1 +I0410 13:29:54.124707 18534 net.cpp:406] conv1 <- data +I0410 13:29:54.124719 18534 net.cpp:380] conv1 -> conv1 +I0410 13:29:54.706710 18534 net.cpp:122] Setting up conv1 +I0410 13:29:54.706732 18534 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:29:54.706737 18534 net.cpp:137] Memory required for data: 227833856 +I0410 13:29:54.706758 18534 layer_factory.hpp:77] Creating layer relu1 +I0410 13:29:54.706787 18534 net.cpp:84] Creating Layer relu1 +I0410 13:29:54.706791 18534 net.cpp:406] relu1 <- conv1 +I0410 13:29:54.706797 18534 net.cpp:367] relu1 -> conv1 (in-place) +I0410 13:29:54.707087 18534 net.cpp:122] Setting up relu1 +I0410 13:29:54.707094 18534 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:29:54.707098 18534 net.cpp:137] Memory required for data: 376518656 +I0410 13:29:54.707103 18534 layer_factory.hpp:77] Creating layer norm1 +I0410 13:29:54.707111 18534 net.cpp:84] Creating Layer norm1 +I0410 13:29:54.707114 18534 net.cpp:406] norm1 <- conv1 +I0410 13:29:54.707119 18534 net.cpp:380] norm1 -> norm1 +I0410 13:29:54.707556 18534 net.cpp:122] Setting up norm1 +I0410 13:29:54.707566 18534 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:29:54.707569 18534 net.cpp:137] Memory required for data: 525203456 +I0410 13:29:54.707573 18534 layer_factory.hpp:77] Creating layer pool1 +I0410 13:29:54.707581 18534 net.cpp:84] Creating Layer pool1 +I0410 13:29:54.707584 18534 net.cpp:406] pool1 <- norm1 +I0410 13:29:54.707589 18534 net.cpp:380] pool1 -> pool1 +I0410 13:29:54.707625 18534 net.cpp:122] Setting up pool1 +I0410 13:29:54.707633 18534 net.cpp:129] Top shape: 128 96 27 27 (8957952) +I0410 13:29:54.707635 18534 net.cpp:137] Memory required for data: 561035264 +I0410 13:29:54.707639 18534 layer_factory.hpp:77] Creating layer conv2 +I0410 13:29:54.707649 18534 net.cpp:84] Creating Layer conv2 +I0410 13:29:54.707653 18534 net.cpp:406] conv2 <- pool1 +I0410 13:29:54.707657 18534 net.cpp:380] conv2 -> conv2 +I0410 13:29:54.716485 18534 net.cpp:122] Setting up conv2 +I0410 13:29:54.716496 18534 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:29:54.716500 18534 net.cpp:137] Memory required for data: 656586752 +I0410 13:29:54.716508 18534 layer_factory.hpp:77] Creating layer relu2 +I0410 13:29:54.716516 18534 net.cpp:84] Creating Layer relu2 +I0410 13:29:54.716519 18534 net.cpp:406] relu2 <- conv2 +I0410 13:29:54.716526 18534 net.cpp:367] relu2 -> conv2 (in-place) +I0410 13:29:54.717005 18534 net.cpp:122] Setting up relu2 +I0410 13:29:54.717015 18534 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:29:54.717020 18534 net.cpp:137] Memory required for data: 752138240 +I0410 13:29:54.717022 18534 layer_factory.hpp:77] Creating layer norm2 +I0410 13:29:54.717031 18534 net.cpp:84] Creating Layer norm2 +I0410 13:29:54.717034 18534 net.cpp:406] norm2 <- conv2 +I0410 13:29:54.717041 18534 net.cpp:380] norm2 -> norm2 +I0410 13:29:54.717384 18534 net.cpp:122] Setting up norm2 +I0410 13:29:54.717396 18534 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:29:54.717401 18534 net.cpp:137] Memory required for data: 847689728 +I0410 13:29:54.717406 18534 layer_factory.hpp:77] Creating layer pool2 +I0410 13:29:54.717414 18534 net.cpp:84] Creating Layer pool2 +I0410 13:29:54.717419 18534 net.cpp:406] pool2 <- norm2 +I0410 13:29:54.717428 18534 net.cpp:380] pool2 -> pool2 +I0410 13:29:54.717469 18534 net.cpp:122] Setting up pool2 +I0410 13:29:54.717476 18534 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:29:54.717481 18534 net.cpp:137] Memory required for data: 869840896 +I0410 13:29:54.717485 18534 layer_factory.hpp:77] Creating layer conv3 +I0410 13:29:54.717501 18534 net.cpp:84] Creating Layer conv3 +I0410 13:29:54.717506 18534 net.cpp:406] conv3 <- pool2 +I0410 13:29:54.717514 18534 net.cpp:380] conv3 -> conv3 +I0410 13:29:54.732287 18534 net.cpp:122] Setting up conv3 +I0410 13:29:54.732301 18534 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:29:54.732306 18534 net.cpp:137] Memory required for data: 903067648 +I0410 13:29:54.732316 18534 layer_factory.hpp:77] Creating layer relu3 +I0410 13:29:54.732326 18534 net.cpp:84] Creating Layer relu3 +I0410 13:29:54.732329 18534 net.cpp:406] relu3 <- conv3 +I0410 13:29:54.732334 18534 net.cpp:367] relu3 -> conv3 (in-place) +I0410 13:29:54.732810 18534 net.cpp:122] Setting up relu3 +I0410 13:29:54.732820 18534 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:29:54.732822 18534 net.cpp:137] Memory required for data: 936294400 +I0410 13:29:54.732826 18534 layer_factory.hpp:77] Creating layer conv4 +I0410 13:29:54.732853 18534 net.cpp:84] Creating Layer conv4 +I0410 13:29:54.732858 18534 net.cpp:406] conv4 <- conv3 +I0410 13:29:54.732864 18534 net.cpp:380] conv4 -> conv4 +I0410 13:29:54.743155 18534 net.cpp:122] Setting up conv4 +I0410 13:29:54.743170 18534 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:29:54.743175 18534 net.cpp:137] Memory required for data: 969521152 +I0410 13:29:54.743182 18534 layer_factory.hpp:77] Creating layer relu4 +I0410 13:29:54.743191 18534 net.cpp:84] Creating Layer relu4 +I0410 13:29:54.743194 18534 net.cpp:406] relu4 <- conv4 +I0410 13:29:54.743199 18534 net.cpp:367] relu4 -> conv4 (in-place) +I0410 13:29:54.743535 18534 net.cpp:122] Setting up relu4 +I0410 13:29:54.743543 18534 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:29:54.743546 18534 net.cpp:137] Memory required for data: 1002747904 +I0410 13:29:54.743549 18534 layer_factory.hpp:77] Creating layer conv5 +I0410 13:29:54.743561 18534 net.cpp:84] Creating Layer conv5 +I0410 13:29:54.743563 18534 net.cpp:406] conv5 <- conv4 +I0410 13:29:54.743571 18534 net.cpp:380] conv5 -> conv5 +I0410 13:29:54.752957 18534 net.cpp:122] Setting up conv5 +I0410 13:29:54.752971 18534 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:29:54.752975 18534 net.cpp:137] Memory required for data: 1024899072 +I0410 13:29:54.752987 18534 layer_factory.hpp:77] Creating layer relu5 +I0410 13:29:54.752995 18534 net.cpp:84] Creating Layer relu5 +I0410 13:29:54.752998 18534 net.cpp:406] relu5 <- conv5 +I0410 13:29:54.753006 18534 net.cpp:367] relu5 -> conv5 (in-place) +I0410 13:29:54.753476 18534 net.cpp:122] Setting up relu5 +I0410 13:29:54.753485 18534 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:29:54.753489 18534 net.cpp:137] Memory required for data: 1047050240 +I0410 13:29:54.753492 18534 layer_factory.hpp:77] Creating layer pool5 +I0410 13:29:54.753500 18534 net.cpp:84] Creating Layer pool5 +I0410 13:29:54.753504 18534 net.cpp:406] pool5 <- conv5 +I0410 13:29:54.753509 18534 net.cpp:380] pool5 -> pool5 +I0410 13:29:54.753547 18534 net.cpp:122] Setting up pool5 +I0410 13:29:54.753553 18534 net.cpp:129] Top shape: 128 256 6 6 (1179648) +I0410 13:29:54.753556 18534 net.cpp:137] Memory required for data: 1051768832 +I0410 13:29:54.753559 18534 layer_factory.hpp:77] Creating layer fc6 +I0410 13:29:54.753568 18534 net.cpp:84] Creating Layer fc6 +I0410 13:29:54.753571 18534 net.cpp:406] fc6 <- pool5 +I0410 13:29:54.753577 18534 net.cpp:380] fc6 -> fc6 +I0410 13:29:54.776508 18534 net.cpp:122] Setting up fc6 +I0410 13:29:54.776526 18534 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:54.776530 18534 net.cpp:137] Memory required for data: 1051899904 +I0410 13:29:54.776540 18534 layer_factory.hpp:77] Creating layer relu6 +I0410 13:29:54.776547 18534 net.cpp:84] Creating Layer relu6 +I0410 13:29:54.776551 18534 net.cpp:406] relu6 <- fc6 +I0410 13:29:54.776559 18534 net.cpp:367] relu6 -> fc6 (in-place) +I0410 13:29:54.777164 18534 net.cpp:122] Setting up relu6 +I0410 13:29:54.777173 18534 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:54.777176 18534 net.cpp:137] Memory required for data: 1052030976 +I0410 13:29:54.777180 18534 layer_factory.hpp:77] Creating layer drop6 +I0410 13:29:54.777189 18534 net.cpp:84] Creating Layer drop6 +I0410 13:29:54.777192 18534 net.cpp:406] drop6 <- fc6 +I0410 13:29:54.777199 18534 net.cpp:367] drop6 -> fc6 (in-place) +I0410 13:29:54.777225 18534 net.cpp:122] Setting up drop6 +I0410 13:29:54.777230 18534 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:54.777233 18534 net.cpp:137] Memory required for data: 1052162048 +I0410 13:29:54.777236 18534 layer_factory.hpp:77] Creating layer fc7 +I0410 13:29:54.777245 18534 net.cpp:84] Creating Layer fc7 +I0410 13:29:54.777247 18534 net.cpp:406] fc7 <- fc6 +I0410 13:29:54.777253 18534 net.cpp:380] fc7 -> fc7 +I0410 13:29:54.777886 18534 net.cpp:122] Setting up fc7 +I0410 13:29:54.777892 18534 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:54.777895 18534 net.cpp:137] Memory required for data: 1052293120 +I0410 13:29:54.777900 18534 layer_factory.hpp:77] Creating layer relu7 +I0410 13:29:54.777923 18534 net.cpp:84] Creating Layer relu7 +I0410 13:29:54.777927 18534 net.cpp:406] relu7 <- fc7 +I0410 13:29:54.777932 18534 net.cpp:367] relu7 -> fc7 (in-place) +I0410 13:29:54.778425 18534 net.cpp:122] Setting up relu7 +I0410 13:29:54.778434 18534 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:54.778437 18534 net.cpp:137] Memory required for data: 1052424192 +I0410 13:29:54.778441 18534 layer_factory.hpp:77] Creating layer drop7 +I0410 13:29:54.778448 18534 net.cpp:84] Creating Layer drop7 +I0410 13:29:54.778451 18534 net.cpp:406] drop7 <- fc7 +I0410 13:29:54.778456 18534 net.cpp:367] drop7 -> fc7 (in-place) +I0410 13:29:54.778481 18534 net.cpp:122] Setting up drop7 +I0410 13:29:54.778486 18534 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:54.778487 18534 net.cpp:137] Memory required for data: 1052555264 +I0410 13:29:54.778491 18534 layer_factory.hpp:77] Creating layer fc7.5 +I0410 13:29:54.778496 18534 net.cpp:84] Creating Layer fc7.5 +I0410 13:29:54.778499 18534 net.cpp:406] fc7.5 <- fc7 +I0410 13:29:54.778506 18534 net.cpp:380] fc7.5 -> fc7.5 +I0410 13:29:54.779145 18534 net.cpp:122] Setting up fc7.5 +I0410 13:29:54.779151 18534 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:54.779155 18534 net.cpp:137] Memory required for data: 1052686336 +I0410 13:29:54.779160 18534 layer_factory.hpp:77] Creating layer relu7.5 +I0410 13:29:54.779165 18534 net.cpp:84] Creating Layer relu7.5 +I0410 13:29:54.779170 18534 net.cpp:406] relu7.5 <- fc7.5 +I0410 13:29:54.779173 18534 net.cpp:367] relu7.5 -> fc7.5 (in-place) +I0410 13:29:54.779654 18534 net.cpp:122] Setting up relu7.5 +I0410 13:29:54.779662 18534 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:54.779665 18534 net.cpp:137] Memory required for data: 1052817408 +I0410 13:29:54.779668 18534 layer_factory.hpp:77] Creating layer drop7.5 +I0410 13:29:54.779675 18534 net.cpp:84] Creating Layer drop7.5 +I0410 13:29:54.779678 18534 net.cpp:406] drop7.5 <- fc7.5 +I0410 13:29:54.779685 18534 net.cpp:367] drop7.5 -> fc7.5 (in-place) +I0410 13:29:54.779707 18534 net.cpp:122] Setting up drop7.5 +I0410 13:29:54.779711 18534 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:29:54.779714 18534 net.cpp:137] Memory required for data: 1052948480 +I0410 13:29:54.779718 18534 layer_factory.hpp:77] Creating layer fc8 +I0410 13:29:54.779723 18534 net.cpp:84] Creating Layer fc8 +I0410 13:29:54.779727 18534 net.cpp:406] fc8 <- fc7.5 +I0410 13:29:54.779732 18534 net.cpp:380] fc8 -> fc8 +I0410 13:29:54.780239 18534 net.cpp:122] Setting up fc8 +I0410 13:29:54.780246 18534 net.cpp:129] Top shape: 128 196 (25088) +I0410 13:29:54.780248 18534 net.cpp:137] Memory required for data: 1053048832 +I0410 13:29:54.780258 18534 layer_factory.hpp:77] Creating layer loss +I0410 13:29:54.780264 18534 net.cpp:84] Creating Layer loss +I0410 13:29:54.780268 18534 net.cpp:406] loss <- fc8 +I0410 13:29:54.780272 18534 net.cpp:406] loss <- label +I0410 13:29:54.780277 18534 net.cpp:380] loss -> loss +I0410 13:29:54.780290 18534 layer_factory.hpp:77] Creating layer loss +I0410 13:29:54.780858 18534 net.cpp:122] Setting up loss +I0410 13:29:54.780866 18534 net.cpp:129] Top shape: (1) +I0410 13:29:54.780869 18534 net.cpp:132] with loss weight 1 +I0410 13:29:54.780885 18534 net.cpp:137] Memory required for data: 1053048836 +I0410 13:29:54.780889 18534 net.cpp:198] loss needs backward computation. +I0410 13:29:54.780896 18534 net.cpp:198] fc8 needs backward computation. +I0410 13:29:54.780900 18534 net.cpp:198] drop7.5 needs backward computation. +I0410 13:29:54.780902 18534 net.cpp:198] relu7.5 needs backward computation. +I0410 13:29:54.780905 18534 net.cpp:198] fc7.5 needs backward computation. +I0410 13:29:54.780910 18534 net.cpp:198] drop7 needs backward computation. +I0410 13:29:54.780912 18534 net.cpp:198] relu7 needs backward computation. +I0410 13:29:54.780915 18534 net.cpp:198] fc7 needs backward computation. +I0410 13:29:54.780918 18534 net.cpp:198] drop6 needs backward computation. +I0410 13:29:54.780921 18534 net.cpp:198] relu6 needs backward computation. +I0410 13:29:54.780925 18534 net.cpp:198] fc6 needs backward computation. +I0410 13:29:54.780938 18534 net.cpp:198] pool5 needs backward computation. +I0410 13:29:54.780941 18534 net.cpp:198] relu5 needs backward computation. +I0410 13:29:54.780944 18534 net.cpp:198] conv5 needs backward computation. +I0410 13:29:54.780948 18534 net.cpp:198] relu4 needs backward computation. +I0410 13:29:54.780953 18534 net.cpp:198] conv4 needs backward computation. +I0410 13:29:54.780956 18534 net.cpp:198] relu3 needs backward computation. +I0410 13:29:54.780961 18534 net.cpp:198] conv3 needs backward computation. +I0410 13:29:54.780964 18534 net.cpp:198] pool2 needs backward computation. +I0410 13:29:54.780967 18534 net.cpp:198] norm2 needs backward computation. +I0410 13:29:54.780972 18534 net.cpp:198] relu2 needs backward computation. +I0410 13:29:54.780974 18534 net.cpp:198] conv2 needs backward computation. +I0410 13:29:54.780977 18534 net.cpp:198] pool1 needs backward computation. +I0410 13:29:54.780982 18534 net.cpp:198] norm1 needs backward computation. +I0410 13:29:54.780984 18534 net.cpp:198] relu1 needs backward computation. +I0410 13:29:54.780988 18534 net.cpp:198] conv1 needs backward computation. +I0410 13:29:54.780992 18534 net.cpp:200] train-data does not need backward computation. +I0410 13:29:54.780995 18534 net.cpp:242] This network produces output loss +I0410 13:29:54.781011 18534 net.cpp:255] Network initialization done. +I0410 13:29:54.781498 18534 solver.cpp:172] Creating test net (#0) specified by net file: train_val.prototxt +I0410 13:29:54.781529 18534 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer train-data +I0410 13:29:54.781684 18534 net.cpp:51] Initializing net from parameters: +state { +phase: TEST +} +layer { +name: "val-data" +type: "Data" +top: "data" +top: "label" +include { +phase: TEST +} +transform_param { +crop_size: 227 +mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" +} +data_param { +source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db" +batch_size: 32 +backend: LMDB +} +} +layer { +name: "conv1" +type: "Convolution" +bottom: "data" +top: "conv1" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 96 +kernel_size: 11 +stride: 4 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu1" +type: "ReLU" +bottom: "conv1" +top: "conv1" +} +layer { +name: "norm1" +type: "LRN" +bottom: "conv1" +top: "norm1" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool1" +type: "Pooling" +bottom: "norm1" +top: "pool1" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv2" +type: "Convolution" +bottom: "pool1" +top: "conv2" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 2 +kernel_size: 5 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu2" +type: "ReLU" +bottom: "conv2" +top: "conv2" +} +layer { +name: "norm2" +type: "LRN" +bottom: "conv2" +top: "norm2" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool2" +type: "Pooling" +bottom: "norm2" +top: "pool2" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv3" +type: "Convolution" +bottom: "pool2" +top: "conv3" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu3" +type: "ReLU" +bottom: "conv3" +top: "conv3" +} +layer { +name: "conv4" +type: "Convolution" +bottom: "conv3" +top: "conv4" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu4" +type: "ReLU" +bottom: "conv4" +top: "conv4" +} +layer { +name: "conv5" +type: "Convolution" +bottom: "conv4" +top: "conv5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu5" +type: "ReLU" +bottom: "conv5" +top: "conv5" +} +layer { +name: "pool5" +type: "Pooling" +bottom: "conv5" +top: "pool5" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "fc6" +type: "InnerProduct" +bottom: "pool5" +top: "fc6" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu6" +type: "ReLU" +bottom: "fc6" +top: "fc6" +} +layer { +name: "drop6" +type: "Dropout" +bottom: "fc6" +top: "fc6" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7" +type: "InnerProduct" +bottom: "fc6" +top: "fc7" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7" +type: "ReLU" +bottom: "fc7" +top: "fc7" +} +layer { +name: "drop7" +type: "Dropout" +bottom: "fc7" +top: "fc7" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7.5" +type: "InnerProduct" +bottom: "fc7" +top: "fc7.5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7.5" +type: "ReLU" +bottom: "fc7.5" +top: "fc7.5" +} +layer { +name: "drop7.5" +type: "Dropout" +bottom: "fc7.5" +top: "fc7.5" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc8" +type: "InnerProduct" +bottom: "fc7.5" +top: "fc8" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 196 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "accuracy" +type: "Accuracy" +bottom: "fc8" +bottom: "label" +top: "accuracy" +include { +phase: TEST +} +} +layer { +name: "loss" +type: "SoftmaxWithLoss" +bottom: "fc8" +bottom: "label" +top: "loss" +} +I0410 13:29:54.781777 18534 layer_factory.hpp:77] Creating layer val-data +I0410 13:29:54.783335 18534 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db +I0410 13:29:54.783538 18534 net.cpp:84] Creating Layer val-data +I0410 13:29:54.783548 18534 net.cpp:380] val-data -> data +I0410 13:29:54.783556 18534 net.cpp:380] val-data -> label +I0410 13:29:54.783562 18534 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto +I0410 13:29:54.787456 18534 data_layer.cpp:45] output data size: 32,3,227,227 +I0410 13:29:54.819896 18534 net.cpp:122] Setting up val-data +I0410 13:29:54.819916 18534 net.cpp:129] Top shape: 32 3 227 227 (4946784) +I0410 13:29:54.819921 18534 net.cpp:129] Top shape: 32 (32) +I0410 13:29:54.819924 18534 net.cpp:137] Memory required for data: 19787264 +I0410 13:29:54.819948 18534 layer_factory.hpp:77] Creating layer label_val-data_1_split +I0410 13:29:54.819960 18534 net.cpp:84] Creating Layer label_val-data_1_split +I0410 13:29:54.819964 18534 net.cpp:406] label_val-data_1_split <- label +I0410 13:29:54.819972 18534 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_0 +I0410 13:29:54.819979 18534 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_1 +I0410 13:29:54.820088 18534 net.cpp:122] Setting up label_val-data_1_split +I0410 13:29:54.820094 18534 net.cpp:129] Top shape: 32 (32) +I0410 13:29:54.820097 18534 net.cpp:129] Top shape: 32 (32) +I0410 13:29:54.820101 18534 net.cpp:137] Memory required for data: 19787520 +I0410 13:29:54.820104 18534 layer_factory.hpp:77] Creating layer conv1 +I0410 13:29:54.820116 18534 net.cpp:84] Creating Layer conv1 +I0410 13:29:54.820118 18534 net.cpp:406] conv1 <- data +I0410 13:29:54.820124 18534 net.cpp:380] conv1 -> conv1 +I0410 13:29:54.822129 18534 net.cpp:122] Setting up conv1 +I0410 13:29:54.822139 18534 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:29:54.822142 18534 net.cpp:137] Memory required for data: 56958720 +I0410 13:29:54.822152 18534 layer_factory.hpp:77] Creating layer relu1 +I0410 13:29:54.822158 18534 net.cpp:84] Creating Layer relu1 +I0410 13:29:54.822162 18534 net.cpp:406] relu1 <- conv1 +I0410 13:29:54.822167 18534 net.cpp:367] relu1 -> conv1 (in-place) +I0410 13:29:54.822643 18534 net.cpp:122] Setting up relu1 +I0410 13:29:54.822654 18534 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:29:54.822656 18534 net.cpp:137] Memory required for data: 94129920 +I0410 13:29:54.822660 18534 layer_factory.hpp:77] Creating layer norm1 +I0410 13:29:54.822669 18534 net.cpp:84] Creating Layer norm1 +I0410 13:29:54.822672 18534 net.cpp:406] norm1 <- conv1 +I0410 13:29:54.822677 18534 net.cpp:380] norm1 -> norm1 +I0410 13:29:54.824062 18534 net.cpp:122] Setting up norm1 +I0410 13:29:54.824071 18534 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:29:54.824075 18534 net.cpp:137] Memory required for data: 131301120 +I0410 13:29:54.824079 18534 layer_factory.hpp:77] Creating layer pool1 +I0410 13:29:54.824086 18534 net.cpp:84] Creating Layer pool1 +I0410 13:29:54.824090 18534 net.cpp:406] pool1 <- norm1 +I0410 13:29:54.824095 18534 net.cpp:380] pool1 -> pool1 +I0410 13:29:54.824124 18534 net.cpp:122] Setting up pool1 +I0410 13:29:54.824129 18534 net.cpp:129] Top shape: 32 96 27 27 (2239488) +I0410 13:29:54.824132 18534 net.cpp:137] Memory required for data: 140259072 +I0410 13:29:54.824136 18534 layer_factory.hpp:77] Creating layer conv2 +I0410 13:29:54.824144 18534 net.cpp:84] Creating Layer conv2 +I0410 13:29:54.824147 18534 net.cpp:406] conv2 <- pool1 +I0410 13:29:54.824152 18534 net.cpp:380] conv2 -> conv2 +I0410 13:29:54.833151 18534 net.cpp:122] Setting up conv2 +I0410 13:29:54.833166 18534 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:29:54.833169 18534 net.cpp:137] Memory required for data: 164146944 +I0410 13:29:54.833179 18534 layer_factory.hpp:77] Creating layer relu2 +I0410 13:29:54.833187 18534 net.cpp:84] Creating Layer relu2 +I0410 13:29:54.833190 18534 net.cpp:406] relu2 <- conv2 +I0410 13:29:54.833197 18534 net.cpp:367] relu2 -> conv2 (in-place) +I0410 13:29:54.833691 18534 net.cpp:122] Setting up relu2 +I0410 13:29:54.833700 18534 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:29:54.833703 18534 net.cpp:137] Memory required for data: 188034816 +I0410 13:29:54.833707 18534 layer_factory.hpp:77] Creating layer norm2 +I0410 13:29:54.833717 18534 net.cpp:84] Creating Layer norm2 +I0410 13:29:54.833720 18534 net.cpp:406] norm2 <- conv2 +I0410 13:29:54.833727 18534 net.cpp:380] norm2 -> norm2 +I0410 13:29:54.834112 18534 net.cpp:122] Setting up norm2 +I0410 13:29:54.834121 18534 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:29:54.834125 18534 net.cpp:137] Memory required for data: 211922688 +I0410 13:29:54.834128 18534 layer_factory.hpp:77] Creating layer pool2 +I0410 13:29:54.834136 18534 net.cpp:84] Creating Layer pool2 +I0410 13:29:54.834139 18534 net.cpp:406] pool2 <- norm2 +I0410 13:29:54.834164 18534 net.cpp:380] pool2 -> pool2 +I0410 13:29:54.834195 18534 net.cpp:122] Setting up pool2 +I0410 13:29:54.834201 18534 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:29:54.834204 18534 net.cpp:137] Memory required for data: 217460480 +I0410 13:29:54.834208 18534 layer_factory.hpp:77] Creating layer conv3 +I0410 13:29:54.834216 18534 net.cpp:84] Creating Layer conv3 +I0410 13:29:54.834220 18534 net.cpp:406] conv3 <- pool2 +I0410 13:29:54.834226 18534 net.cpp:380] conv3 -> conv3 +I0410 13:29:54.845543 18534 net.cpp:122] Setting up conv3 +I0410 13:29:54.845563 18534 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:29:54.845566 18534 net.cpp:137] Memory required for data: 225767168 +I0410 13:29:54.845579 18534 layer_factory.hpp:77] Creating layer relu3 +I0410 13:29:54.845589 18534 net.cpp:84] Creating Layer relu3 +I0410 13:29:54.845593 18534 net.cpp:406] relu3 <- conv3 +I0410 13:29:54.845599 18534 net.cpp:367] relu3 -> conv3 (in-place) +I0410 13:29:54.845949 18534 net.cpp:122] Setting up relu3 +I0410 13:29:54.845980 18534 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:29:54.845984 18534 net.cpp:137] Memory required for data: 234073856 +I0410 13:29:54.845988 18534 layer_factory.hpp:77] Creating layer conv4 +I0410 13:29:54.846004 18534 net.cpp:84] Creating Layer conv4 +I0410 13:29:54.846007 18534 net.cpp:406] conv4 <- conv3 +I0410 13:29:54.846014 18534 net.cpp:380] conv4 -> conv4 +I0410 13:29:54.856132 18534 net.cpp:122] Setting up conv4 +I0410 13:29:54.856148 18534 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:29:54.856151 18534 net.cpp:137] Memory required for data: 242380544 +I0410 13:29:54.856159 18534 layer_factory.hpp:77] Creating layer relu4 +I0410 13:29:54.856168 18534 net.cpp:84] Creating Layer relu4 +I0410 13:29:54.856173 18534 net.cpp:406] relu4 <- conv4 +I0410 13:29:54.856178 18534 net.cpp:367] relu4 -> conv4 (in-place) +I0410 13:29:54.856786 18534 net.cpp:122] Setting up relu4 +I0410 13:29:54.856796 18534 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:29:54.856798 18534 net.cpp:137] Memory required for data: 250687232 +I0410 13:29:54.856802 18534 layer_factory.hpp:77] Creating layer conv5 +I0410 13:29:54.856813 18534 net.cpp:84] Creating Layer conv5 +I0410 13:29:54.856817 18534 net.cpp:406] conv5 <- conv4 +I0410 13:29:54.856823 18534 net.cpp:380] conv5 -> conv5 +I0410 13:29:54.865550 18534 net.cpp:122] Setting up conv5 +I0410 13:29:54.865566 18534 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:29:54.865569 18534 net.cpp:137] Memory required for data: 256225024 +I0410 13:29:54.865581 18534 layer_factory.hpp:77] Creating layer relu5 +I0410 13:29:54.865589 18534 net.cpp:84] Creating Layer relu5 +I0410 13:29:54.865593 18534 net.cpp:406] relu5 <- conv5 +I0410 13:29:54.865602 18534 net.cpp:367] relu5 -> conv5 (in-place) +I0410 13:29:54.866328 18534 net.cpp:122] Setting up relu5 +I0410 13:29:54.866338 18534 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:29:54.866343 18534 net.cpp:137] Memory required for data: 261762816 +I0410 13:29:54.866345 18534 layer_factory.hpp:77] Creating layer pool5 +I0410 13:29:54.866356 18534 net.cpp:84] Creating Layer pool5 +I0410 13:29:54.866359 18534 net.cpp:406] pool5 <- conv5 +I0410 13:29:54.866365 18534 net.cpp:380] pool5 -> pool5 +I0410 13:29:54.866405 18534 net.cpp:122] Setting up pool5 +I0410 13:29:54.866411 18534 net.cpp:129] Top shape: 32 256 6 6 (294912) +I0410 13:29:54.866415 18534 net.cpp:137] Memory required for data: 262942464 +I0410 13:29:54.866417 18534 layer_factory.hpp:77] Creating layer fc6 +I0410 13:29:54.866425 18534 net.cpp:84] Creating Layer fc6 +I0410 13:29:54.866427 18534 net.cpp:406] fc6 <- pool5 +I0410 13:29:54.866433 18534 net.cpp:380] fc6 -> fc6 +I0410 13:29:54.892019 18534 net.cpp:122] Setting up fc6 +I0410 13:29:54.892038 18534 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:54.892042 18534 net.cpp:137] Memory required for data: 262975232 +I0410 13:29:54.892051 18534 layer_factory.hpp:77] Creating layer relu6 +I0410 13:29:54.892060 18534 net.cpp:84] Creating Layer relu6 +I0410 13:29:54.892064 18534 net.cpp:406] relu6 <- fc6 +I0410 13:29:54.892089 18534 net.cpp:367] relu6 -> fc6 (in-place) +I0410 13:29:54.892510 18534 net.cpp:122] Setting up relu6 +I0410 13:29:54.892518 18534 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:54.892521 18534 net.cpp:137] Memory required for data: 263008000 +I0410 13:29:54.892525 18534 layer_factory.hpp:77] Creating layer drop6 +I0410 13:29:54.892531 18534 net.cpp:84] Creating Layer drop6 +I0410 13:29:54.892535 18534 net.cpp:406] drop6 <- fc6 +I0410 13:29:54.892541 18534 net.cpp:367] drop6 -> fc6 (in-place) +I0410 13:29:54.892566 18534 net.cpp:122] Setting up drop6 +I0410 13:29:54.892571 18534 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:54.892575 18534 net.cpp:137] Memory required for data: 263040768 +I0410 13:29:54.892577 18534 layer_factory.hpp:77] Creating layer fc7 +I0410 13:29:54.892583 18534 net.cpp:84] Creating Layer fc7 +I0410 13:29:54.892586 18534 net.cpp:406] fc7 <- fc6 +I0410 13:29:54.892592 18534 net.cpp:380] fc7 -> fc7 +I0410 13:29:54.893234 18534 net.cpp:122] Setting up fc7 +I0410 13:29:54.893240 18534 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:54.893244 18534 net.cpp:137] Memory required for data: 263073536 +I0410 13:29:54.893249 18534 layer_factory.hpp:77] Creating layer relu7 +I0410 13:29:54.893255 18534 net.cpp:84] Creating Layer relu7 +I0410 13:29:54.893260 18534 net.cpp:406] relu7 <- fc7 +I0410 13:29:54.893263 18534 net.cpp:367] relu7 -> fc7 (in-place) +I0410 13:29:54.893846 18534 net.cpp:122] Setting up relu7 +I0410 13:29:54.893853 18534 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:54.893857 18534 net.cpp:137] Memory required for data: 263106304 +I0410 13:29:54.893860 18534 layer_factory.hpp:77] Creating layer drop7 +I0410 13:29:54.893867 18534 net.cpp:84] Creating Layer drop7 +I0410 13:29:54.893870 18534 net.cpp:406] drop7 <- fc7 +I0410 13:29:54.893877 18534 net.cpp:367] drop7 -> fc7 (in-place) +I0410 13:29:54.893899 18534 net.cpp:122] Setting up drop7 +I0410 13:29:54.893904 18534 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:54.893908 18534 net.cpp:137] Memory required for data: 263139072 +I0410 13:29:54.893910 18534 layer_factory.hpp:77] Creating layer fc7.5 +I0410 13:29:54.893918 18534 net.cpp:84] Creating Layer fc7.5 +I0410 13:29:54.893920 18534 net.cpp:406] fc7.5 <- fc7 +I0410 13:29:54.893926 18534 net.cpp:380] fc7.5 -> fc7.5 +I0410 13:29:54.894587 18534 net.cpp:122] Setting up fc7.5 +I0410 13:29:54.894594 18534 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:54.894598 18534 net.cpp:137] Memory required for data: 263171840 +I0410 13:29:54.894603 18534 layer_factory.hpp:77] Creating layer relu7.5 +I0410 13:29:54.894609 18534 net.cpp:84] Creating Layer relu7.5 +I0410 13:29:54.894613 18534 net.cpp:406] relu7.5 <- fc7.5 +I0410 13:29:54.894618 18534 net.cpp:367] relu7.5 -> fc7.5 (in-place) +I0410 13:29:54.895108 18534 net.cpp:122] Setting up relu7.5 +I0410 13:29:54.895117 18534 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:54.895119 18534 net.cpp:137] Memory required for data: 263204608 +I0410 13:29:54.895123 18534 layer_factory.hpp:77] Creating layer drop7.5 +I0410 13:29:54.895128 18534 net.cpp:84] Creating Layer drop7.5 +I0410 13:29:54.895133 18534 net.cpp:406] drop7.5 <- fc7.5 +I0410 13:29:54.895138 18534 net.cpp:367] drop7.5 -> fc7.5 (in-place) +I0410 13:29:54.895161 18534 net.cpp:122] Setting up drop7.5 +I0410 13:29:54.895166 18534 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:29:54.895169 18534 net.cpp:137] Memory required for data: 263237376 +I0410 13:29:54.895172 18534 layer_factory.hpp:77] Creating layer fc8 +I0410 13:29:54.895179 18534 net.cpp:84] Creating Layer fc8 +I0410 13:29:54.895184 18534 net.cpp:406] fc8 <- fc7.5 +I0410 13:29:54.895190 18534 net.cpp:380] fc8 -> fc8 +I0410 13:29:54.895700 18534 net.cpp:122] Setting up fc8 +I0410 13:29:54.895707 18534 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:29:54.895710 18534 net.cpp:137] Memory required for data: 263262464 +I0410 13:29:54.895720 18534 layer_factory.hpp:77] Creating layer fc8_fc8_0_split +I0410 13:29:54.895725 18534 net.cpp:84] Creating Layer fc8_fc8_0_split +I0410 13:29:54.895730 18534 net.cpp:406] fc8_fc8_0_split <- fc8 +I0410 13:29:54.895735 18534 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_0 +I0410 13:29:54.895750 18534 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_1 +I0410 13:29:54.895783 18534 net.cpp:122] Setting up fc8_fc8_0_split +I0410 13:29:54.895788 18534 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:29:54.895792 18534 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:29:54.895794 18534 net.cpp:137] Memory required for data: 263312640 +I0410 13:29:54.895798 18534 layer_factory.hpp:77] Creating layer accuracy +I0410 13:29:54.895805 18534 net.cpp:84] Creating Layer accuracy +I0410 13:29:54.895809 18534 net.cpp:406] accuracy <- fc8_fc8_0_split_0 +I0410 13:29:54.895814 18534 net.cpp:406] accuracy <- label_val-data_1_split_0 +I0410 13:29:54.895820 18534 net.cpp:380] accuracy -> accuracy +I0410 13:29:54.895828 18534 net.cpp:122] Setting up accuracy +I0410 13:29:54.895833 18534 net.cpp:129] Top shape: (1) +I0410 13:29:54.895834 18534 net.cpp:137] Memory required for data: 263312644 +I0410 13:29:54.895838 18534 layer_factory.hpp:77] Creating layer loss +I0410 13:29:54.895843 18534 net.cpp:84] Creating Layer loss +I0410 13:29:54.895846 18534 net.cpp:406] loss <- fc8_fc8_0_split_1 +I0410 13:29:54.895850 18534 net.cpp:406] loss <- label_val-data_1_split_1 +I0410 13:29:54.895856 18534 net.cpp:380] loss -> loss +I0410 13:29:54.895864 18534 layer_factory.hpp:77] Creating layer loss +I0410 13:29:54.897456 18534 net.cpp:122] Setting up loss +I0410 13:29:54.897465 18534 net.cpp:129] Top shape: (1) +I0410 13:29:54.897469 18534 net.cpp:132] with loss weight 1 +I0410 13:29:54.897478 18534 net.cpp:137] Memory required for data: 263312648 +I0410 13:29:54.897482 18534 net.cpp:198] loss needs backward computation. +I0410 13:29:54.897487 18534 net.cpp:200] accuracy does not need backward computation. +I0410 13:29:54.897491 18534 net.cpp:198] fc8_fc8_0_split needs backward computation. +I0410 13:29:54.897495 18534 net.cpp:198] fc8 needs backward computation. +I0410 13:29:54.897498 18534 net.cpp:198] drop7.5 needs backward computation. +I0410 13:29:54.897501 18534 net.cpp:198] relu7.5 needs backward computation. +I0410 13:29:54.897505 18534 net.cpp:198] fc7.5 needs backward computation. +I0410 13:29:54.897508 18534 net.cpp:198] drop7 needs backward computation. +I0410 13:29:54.897511 18534 net.cpp:198] relu7 needs backward computation. +I0410 13:29:54.897514 18534 net.cpp:198] fc7 needs backward computation. +I0410 13:29:54.897517 18534 net.cpp:198] drop6 needs backward computation. +I0410 13:29:54.897521 18534 net.cpp:198] relu6 needs backward computation. +I0410 13:29:54.897523 18534 net.cpp:198] fc6 needs backward computation. +I0410 13:29:54.897527 18534 net.cpp:198] pool5 needs backward computation. +I0410 13:29:54.897531 18534 net.cpp:198] relu5 needs backward computation. +I0410 13:29:54.897534 18534 net.cpp:198] conv5 needs backward computation. +I0410 13:29:54.897538 18534 net.cpp:198] relu4 needs backward computation. +I0410 13:29:54.897542 18534 net.cpp:198] conv4 needs backward computation. +I0410 13:29:54.897545 18534 net.cpp:198] relu3 needs backward computation. +I0410 13:29:54.897549 18534 net.cpp:198] conv3 needs backward computation. +I0410 13:29:54.897553 18534 net.cpp:198] pool2 needs backward computation. +I0410 13:29:54.897557 18534 net.cpp:198] norm2 needs backward computation. +I0410 13:29:54.897560 18534 net.cpp:198] relu2 needs backward computation. +I0410 13:29:54.897563 18534 net.cpp:198] conv2 needs backward computation. +I0410 13:29:54.897567 18534 net.cpp:198] pool1 needs backward computation. +I0410 13:29:54.897572 18534 net.cpp:198] norm1 needs backward computation. +I0410 13:29:54.897575 18534 net.cpp:198] relu1 needs backward computation. +I0410 13:29:54.897580 18534 net.cpp:198] conv1 needs backward computation. +I0410 13:29:54.897584 18534 net.cpp:200] label_val-data_1_split does not need backward computation. +I0410 13:29:54.897588 18534 net.cpp:200] val-data does not need backward computation. +I0410 13:29:54.897591 18534 net.cpp:242] This network produces output accuracy +I0410 13:29:54.897595 18534 net.cpp:242] This network produces output loss +I0410 13:29:54.897612 18534 net.cpp:255] Network initialization done. +I0410 13:29:54.897693 18534 solver.cpp:56] Solver scaffolding done. +I0410 13:29:54.898193 18534 caffe.cpp:248] Starting Optimization +I0410 13:29:54.898202 18534 solver.cpp:272] Solving +I0410 13:29:54.898206 18534 solver.cpp:273] Learning Rate Policy: exp +I0410 13:29:54.898998 18534 solver.cpp:330] Iteration 0, Testing net (#0) +I0410 13:29:54.899008 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:29:54.901469 18534 blocking_queue.cpp:49] Waiting for data +I0410 13:29:59.473608 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:29:59.517617 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:29:59.517664 18534 solver.cpp:397] Test net output #1: loss = 5.27848 (* 1 = 5.27848 loss) +I0410 13:29:59.608510 18534 solver.cpp:218] Iteration 0 (0 iter/s, 4.7101s/12 iters), loss = 5.28161 +I0410 13:29:59.610020 18534 solver.cpp:237] Train net output #0: loss = 5.28161 (* 1 = 5.28161 loss) +I0410 13:29:59.610054 18534 sgd_solver.cpp:105] Iteration 0, lr = 0.01 +I0410 13:30:03.371474 18534 solver.cpp:218] Iteration 12 (3.19039 iter/s, 3.7613s/12 iters), loss = 5.27475 +I0410 13:30:03.371522 18534 solver.cpp:237] Train net output #0: loss = 5.27475 (* 1 = 5.27475 loss) +I0410 13:30:03.371534 18534 sgd_solver.cpp:105] Iteration 12, lr = 0.00997626 +I0410 13:30:08.161870 18534 solver.cpp:218] Iteration 24 (2.50513 iter/s, 4.79016s/12 iters), loss = 5.27852 +I0410 13:30:08.161918 18534 solver.cpp:237] Train net output #0: loss = 5.27852 (* 1 = 5.27852 loss) +I0410 13:30:08.161931 18534 sgd_solver.cpp:105] Iteration 24, lr = 0.00995257 +I0410 13:30:12.911378 18534 solver.cpp:218] Iteration 36 (2.5267 iter/s, 4.74928s/12 iters), loss = 5.27605 +I0410 13:30:12.911429 18534 solver.cpp:237] Train net output #0: loss = 5.27605 (* 1 = 5.27605 loss) +I0410 13:30:12.911442 18534 sgd_solver.cpp:105] Iteration 36, lr = 0.00992894 +I0410 13:30:17.739624 18534 solver.cpp:218] Iteration 48 (2.4855 iter/s, 4.828s/12 iters), loss = 5.28252 +I0410 13:30:17.739675 18534 solver.cpp:237] Train net output #0: loss = 5.28252 (* 1 = 5.28252 loss) +I0410 13:30:17.739687 18534 sgd_solver.cpp:105] Iteration 48, lr = 0.00990537 +I0410 13:30:22.616101 18534 solver.cpp:218] Iteration 60 (2.46091 iter/s, 4.87624s/12 iters), loss = 5.27403 +I0410 13:30:22.616142 18534 solver.cpp:237] Train net output #0: loss = 5.27403 (* 1 = 5.27403 loss) +I0410 13:30:22.616151 18534 sgd_solver.cpp:105] Iteration 60, lr = 0.00988185 +I0410 13:30:27.412252 18534 solver.cpp:218] Iteration 72 (2.50213 iter/s, 4.79592s/12 iters), loss = 5.27676 +I0410 13:30:27.412359 18534 solver.cpp:237] Train net output #0: loss = 5.27676 (* 1 = 5.27676 loss) +I0410 13:30:27.412372 18534 sgd_solver.cpp:105] Iteration 72, lr = 0.00985839 +I0410 13:30:32.304652 18534 solver.cpp:218] Iteration 84 (2.45293 iter/s, 4.8921s/12 iters), loss = 5.28257 +I0410 13:30:32.304710 18534 solver.cpp:237] Train net output #0: loss = 5.28257 (* 1 = 5.28257 loss) +I0410 13:30:32.304723 18534 sgd_solver.cpp:105] Iteration 84, lr = 0.00983498 +I0410 13:30:37.105619 18534 solver.cpp:218] Iteration 96 (2.49963 iter/s, 4.80071s/12 iters), loss = 5.28458 +I0410 13:30:37.105676 18534 solver.cpp:237] Train net output #0: loss = 5.28458 (* 1 = 5.28458 loss) +I0410 13:30:37.105687 18534 sgd_solver.cpp:105] Iteration 96, lr = 0.00981163 +I0410 13:30:38.739358 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:30:39.043084 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_102.caffemodel +I0410 13:30:39.369868 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_102.solverstate +I0410 13:30:39.611589 18534 solver.cpp:330] Iteration 102, Testing net (#0) +I0410 13:30:39.611620 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:30:43.968668 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:30:44.051288 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:30:44.051337 18534 solver.cpp:397] Test net output #1: loss = 5.27909 (* 1 = 5.27909 loss) +I0410 13:30:45.924911 18534 solver.cpp:218] Iteration 108 (1.36071 iter/s, 8.8189s/12 iters), loss = 5.2773 +I0410 13:30:45.924962 18534 solver.cpp:237] Train net output #0: loss = 5.2773 (* 1 = 5.2773 loss) +I0410 13:30:45.924973 18534 sgd_solver.cpp:105] Iteration 108, lr = 0.00978834 +I0410 13:30:50.852160 18534 solver.cpp:218] Iteration 120 (2.43556 iter/s, 4.927s/12 iters), loss = 5.27674 +I0410 13:30:50.852216 18534 solver.cpp:237] Train net output #0: loss = 5.27674 (* 1 = 5.27674 loss) +I0410 13:30:50.852227 18534 sgd_solver.cpp:105] Iteration 120, lr = 0.0097651 +I0410 13:30:55.723656 18534 solver.cpp:218] Iteration 132 (2.46344 iter/s, 4.87124s/12 iters), loss = 5.26321 +I0410 13:30:55.723709 18534 solver.cpp:237] Train net output #0: loss = 5.26321 (* 1 = 5.26321 loss) +I0410 13:30:55.723722 18534 sgd_solver.cpp:105] Iteration 132, lr = 0.00974192 +I0410 13:31:00.533746 18534 solver.cpp:218] Iteration 144 (2.49488 iter/s, 4.80984s/12 iters), loss = 5.28312 +I0410 13:31:00.533900 18534 solver.cpp:237] Train net output #0: loss = 5.28312 (* 1 = 5.28312 loss) +I0410 13:31:00.533913 18534 sgd_solver.cpp:105] Iteration 144, lr = 0.00971879 +I0410 13:31:05.323438 18534 solver.cpp:218] Iteration 156 (2.50556 iter/s, 4.78935s/12 iters), loss = 5.26666 +I0410 13:31:05.323482 18534 solver.cpp:237] Train net output #0: loss = 5.26666 (* 1 = 5.26666 loss) +I0410 13:31:05.323491 18534 sgd_solver.cpp:105] Iteration 156, lr = 0.00969571 +I0410 13:31:10.105538 18534 solver.cpp:218] Iteration 168 (2.50948 iter/s, 4.78186s/12 iters), loss = 5.27579 +I0410 13:31:10.105583 18534 solver.cpp:237] Train net output #0: loss = 5.27579 (* 1 = 5.27579 loss) +I0410 13:31:10.105592 18534 sgd_solver.cpp:105] Iteration 168, lr = 0.00967269 +I0410 13:31:14.895036 18534 solver.cpp:218] Iteration 180 (2.50561 iter/s, 4.78926s/12 iters), loss = 5.27202 +I0410 13:31:14.895079 18534 solver.cpp:237] Train net output #0: loss = 5.27202 (* 1 = 5.27202 loss) +I0410 13:31:14.895088 18534 sgd_solver.cpp:105] Iteration 180, lr = 0.00964973 +I0410 13:31:19.685078 18534 solver.cpp:218] Iteration 192 (2.50532 iter/s, 4.78981s/12 iters), loss = 5.27785 +I0410 13:31:19.685119 18534 solver.cpp:237] Train net output #0: loss = 5.27785 (* 1 = 5.27785 loss) +I0410 13:31:19.685127 18534 sgd_solver.cpp:105] Iteration 192, lr = 0.00962682 +I0410 13:31:23.368081 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:24.020737 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_204.caffemodel +I0410 13:31:24.321892 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_204.solverstate +I0410 13:31:24.533603 18534 solver.cpp:330] Iteration 204, Testing net (#0) +I0410 13:31:24.533622 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:31:28.893201 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:29.017606 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:31:29.017653 18534 solver.cpp:397] Test net output #1: loss = 5.28011 (* 1 = 5.28011 loss) +I0410 13:31:29.098984 18534 solver.cpp:218] Iteration 204 (1.27477 iter/s, 9.4135s/12 iters), loss = 5.27588 +I0410 13:31:29.099030 18534 solver.cpp:237] Train net output #0: loss = 5.27588 (* 1 = 5.27588 loss) +I0410 13:31:29.099040 18534 sgd_solver.cpp:105] Iteration 204, lr = 0.00960396 +I0410 13:31:33.218127 18534 solver.cpp:218] Iteration 216 (2.91338 iter/s, 4.11892s/12 iters), loss = 5.27831 +I0410 13:31:33.218215 18534 solver.cpp:237] Train net output #0: loss = 5.27831 (* 1 = 5.27831 loss) +I0410 13:31:33.218228 18534 sgd_solver.cpp:105] Iteration 216, lr = 0.00958116 +I0410 13:31:38.180310 18534 solver.cpp:218] Iteration 228 (2.41843 iter/s, 4.96189s/12 iters), loss = 5.26715 +I0410 13:31:38.180366 18534 solver.cpp:237] Train net output #0: loss = 5.26715 (* 1 = 5.26715 loss) +I0410 13:31:38.180380 18534 sgd_solver.cpp:105] Iteration 228, lr = 0.00955841 +I0410 13:31:43.090833 18534 solver.cpp:218] Iteration 240 (2.44386 iter/s, 4.91027s/12 iters), loss = 5.28166 +I0410 13:31:43.090879 18534 solver.cpp:237] Train net output #0: loss = 5.28166 (* 1 = 5.28166 loss) +I0410 13:31:43.090888 18534 sgd_solver.cpp:105] Iteration 240, lr = 0.00953572 +I0410 13:31:48.063540 18534 solver.cpp:218] Iteration 252 (2.41329 iter/s, 4.97246s/12 iters), loss = 5.26818 +I0410 13:31:48.063583 18534 solver.cpp:237] Train net output #0: loss = 5.26818 (* 1 = 5.26818 loss) +I0410 13:31:48.063593 18534 sgd_solver.cpp:105] Iteration 252, lr = 0.00951308 +I0410 13:31:52.918509 18534 solver.cpp:218] Iteration 264 (2.47182 iter/s, 4.85473s/12 iters), loss = 5.27261 +I0410 13:31:52.918552 18534 solver.cpp:237] Train net output #0: loss = 5.27261 (* 1 = 5.27261 loss) +I0410 13:31:52.918560 18534 sgd_solver.cpp:105] Iteration 264, lr = 0.00949049 +I0410 13:31:57.742635 18534 solver.cpp:218] Iteration 276 (2.48762 iter/s, 4.82388s/12 iters), loss = 5.28407 +I0410 13:31:57.742691 18534 solver.cpp:237] Train net output #0: loss = 5.28407 (* 1 = 5.28407 loss) +I0410 13:31:57.742703 18534 sgd_solver.cpp:105] Iteration 276, lr = 0.00946796 +I0410 13:32:02.541939 18534 solver.cpp:218] Iteration 288 (2.50049 iter/s, 4.79905s/12 iters), loss = 5.2788 +I0410 13:32:02.541996 18534 solver.cpp:237] Train net output #0: loss = 5.2788 (* 1 = 5.2788 loss) +I0410 13:32:02.542006 18534 sgd_solver.cpp:105] Iteration 288, lr = 0.00944548 +I0410 13:32:07.318933 18534 solver.cpp:218] Iteration 300 (2.51217 iter/s, 4.77674s/12 iters), loss = 5.27725 +I0410 13:32:07.319036 18534 solver.cpp:237] Train net output #0: loss = 5.27725 (* 1 = 5.27725 loss) +I0410 13:32:07.319046 18534 sgd_solver.cpp:105] Iteration 300, lr = 0.00942305 +I0410 13:32:08.272953 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:09.289129 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_306.caffemodel +I0410 13:32:09.589613 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_306.solverstate +I0410 13:32:09.786068 18534 solver.cpp:330] Iteration 306, Testing net (#0) +I0410 13:32:09.786087 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:32:14.020292 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:14.176368 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:32:14.176398 18534 solver.cpp:397] Test net output #1: loss = 5.28117 (* 1 = 5.28117 loss) +I0410 13:32:16.078338 18534 solver.cpp:218] Iteration 312 (1.37003 iter/s, 8.75896s/12 iters), loss = 5.28115 +I0410 13:32:16.078388 18534 solver.cpp:237] Train net output #0: loss = 5.28115 (* 1 = 5.28115 loss) +I0410 13:32:16.078398 18534 sgd_solver.cpp:105] Iteration 312, lr = 0.00940068 +I0410 13:32:21.071646 18534 solver.cpp:218] Iteration 324 (2.40334 iter/s, 4.99306s/12 iters), loss = 5.25676 +I0410 13:32:21.071693 18534 solver.cpp:237] Train net output #0: loss = 5.25676 (* 1 = 5.25676 loss) +I0410 13:32:21.071704 18534 sgd_solver.cpp:105] Iteration 324, lr = 0.00937836 +I0410 13:32:26.272891 18534 solver.cpp:218] Iteration 336 (2.30726 iter/s, 5.20098s/12 iters), loss = 5.26438 +I0410 13:32:26.272941 18534 solver.cpp:237] Train net output #0: loss = 5.26438 (* 1 = 5.26438 loss) +I0410 13:32:26.272953 18534 sgd_solver.cpp:105] Iteration 336, lr = 0.0093561 +I0410 13:32:31.064895 18534 solver.cpp:218] Iteration 348 (2.5043 iter/s, 4.79175s/12 iters), loss = 5.26767 +I0410 13:32:31.064952 18534 solver.cpp:237] Train net output #0: loss = 5.26767 (* 1 = 5.26767 loss) +I0410 13:32:31.064965 18534 sgd_solver.cpp:105] Iteration 348, lr = 0.00933388 +I0410 13:32:35.903517 18534 solver.cpp:218] Iteration 360 (2.48017 iter/s, 4.83837s/12 iters), loss = 5.28826 +I0410 13:32:35.903569 18534 solver.cpp:237] Train net output #0: loss = 5.28826 (* 1 = 5.28826 loss) +I0410 13:32:35.903581 18534 sgd_solver.cpp:105] Iteration 360, lr = 0.00931172 +I0410 13:32:40.753170 18534 solver.cpp:218] Iteration 372 (2.47453 iter/s, 4.8494s/12 iters), loss = 5.27248 +I0410 13:32:40.753332 18534 solver.cpp:237] Train net output #0: loss = 5.27248 (* 1 = 5.27248 loss) +I0410 13:32:40.753347 18534 sgd_solver.cpp:105] Iteration 372, lr = 0.00928961 +I0410 13:32:45.603082 18534 solver.cpp:218] Iteration 384 (2.47445 iter/s, 4.84955s/12 iters), loss = 5.27624 +I0410 13:32:45.603139 18534 solver.cpp:237] Train net output #0: loss = 5.27624 (* 1 = 5.27624 loss) +I0410 13:32:45.603152 18534 sgd_solver.cpp:105] Iteration 384, lr = 0.00926756 +I0410 13:32:50.537994 18534 solver.cpp:218] Iteration 396 (2.43178 iter/s, 4.93465s/12 iters), loss = 5.27089 +I0410 13:32:50.538051 18534 solver.cpp:237] Train net output #0: loss = 5.27089 (* 1 = 5.27089 loss) +I0410 13:32:50.538062 18534 sgd_solver.cpp:105] Iteration 396, lr = 0.00924556 +I0410 13:32:53.611829 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:54.984066 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_408.caffemodel +I0410 13:32:55.322871 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_408.solverstate +I0410 13:32:55.538416 18534 solver.cpp:330] Iteration 408, Testing net (#0) +I0410 13:32:55.538445 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:32:59.773816 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:59.975656 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:32:59.975703 18534 solver.cpp:397] Test net output #1: loss = 5.2828 (* 1 = 5.2828 loss) +I0410 13:33:00.057114 18534 solver.cpp:218] Iteration 408 (1.26068 iter/s, 9.51868s/12 iters), loss = 5.27624 +I0410 13:33:00.057193 18534 solver.cpp:237] Train net output #0: loss = 5.27624 (* 1 = 5.27624 loss) +I0410 13:33:00.057210 18534 sgd_solver.cpp:105] Iteration 408, lr = 0.00922361 +I0410 13:33:04.165495 18534 solver.cpp:218] Iteration 420 (2.92103 iter/s, 4.10814s/12 iters), loss = 5.27614 +I0410 13:33:04.165549 18534 solver.cpp:237] Train net output #0: loss = 5.27614 (* 1 = 5.27614 loss) +I0410 13:33:04.165560 18534 sgd_solver.cpp:105] Iteration 420, lr = 0.00920171 +I0410 13:33:08.953805 18534 solver.cpp:218] Iteration 432 (2.50623 iter/s, 4.78806s/12 iters), loss = 5.27 +I0410 13:33:08.953864 18534 solver.cpp:237] Train net output #0: loss = 5.27 (* 1 = 5.27 loss) +I0410 13:33:08.953876 18534 sgd_solver.cpp:105] Iteration 432, lr = 0.00917986 +I0410 13:33:13.735204 18534 solver.cpp:218] Iteration 444 (2.50986 iter/s, 4.78114s/12 iters), loss = 5.28157 +I0410 13:33:13.735319 18534 solver.cpp:237] Train net output #0: loss = 5.28157 (* 1 = 5.28157 loss) +I0410 13:33:13.735332 18534 sgd_solver.cpp:105] Iteration 444, lr = 0.00915807 +I0410 13:33:18.538532 18534 solver.cpp:218] Iteration 456 (2.49843 iter/s, 4.80302s/12 iters), loss = 5.2802 +I0410 13:33:18.538580 18534 solver.cpp:237] Train net output #0: loss = 5.2802 (* 1 = 5.2802 loss) +I0410 13:33:18.538590 18534 sgd_solver.cpp:105] Iteration 456, lr = 0.00913632 +I0410 13:33:23.335702 18534 solver.cpp:218] Iteration 468 (2.5016 iter/s, 4.79692s/12 iters), loss = 5.27886 +I0410 13:33:23.335747 18534 solver.cpp:237] Train net output #0: loss = 5.27886 (* 1 = 5.27886 loss) +I0410 13:33:23.335757 18534 sgd_solver.cpp:105] Iteration 468, lr = 0.00911463 +I0410 13:33:28.157419 18534 solver.cpp:218] Iteration 480 (2.48887 iter/s, 4.82147s/12 iters), loss = 5.26992 +I0410 13:33:28.157472 18534 solver.cpp:237] Train net output #0: loss = 5.26992 (* 1 = 5.26992 loss) +I0410 13:33:28.157485 18534 sgd_solver.cpp:105] Iteration 480, lr = 0.00909299 +I0410 13:33:33.001309 18534 solver.cpp:218] Iteration 492 (2.47748 iter/s, 4.84363s/12 iters), loss = 5.28213 +I0410 13:33:33.001370 18534 solver.cpp:237] Train net output #0: loss = 5.28213 (* 1 = 5.28213 loss) +I0410 13:33:33.001382 18534 sgd_solver.cpp:105] Iteration 492, lr = 0.0090714 +I0410 13:33:37.867831 18534 solver.cpp:218] Iteration 504 (2.46596 iter/s, 4.86626s/12 iters), loss = 5.2691 +I0410 13:33:37.867884 18534 solver.cpp:237] Train net output #0: loss = 5.2691 (* 1 = 5.2691 loss) +I0410 13:33:37.867895 18534 sgd_solver.cpp:105] Iteration 504, lr = 0.00904986 +I0410 13:33:38.115304 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:33:39.810492 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_510.caffemodel +I0410 13:33:41.329054 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_510.solverstate +I0410 13:33:41.536455 18534 solver.cpp:330] Iteration 510, Testing net (#0) +I0410 13:33:41.536479 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:33:45.747658 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:33:45.983698 18534 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:33:45.983745 18534 solver.cpp:397] Test net output #1: loss = 5.28307 (* 1 = 5.28307 loss) +I0410 13:33:47.740131 18534 solver.cpp:218] Iteration 516 (1.21558 iter/s, 9.87185s/12 iters), loss = 5.27985 +I0410 13:33:47.740190 18534 solver.cpp:237] Train net output #0: loss = 5.27985 (* 1 = 5.27985 loss) +I0410 13:33:47.740202 18534 sgd_solver.cpp:105] Iteration 516, lr = 0.00902838 +I0410 13:33:52.547663 18534 solver.cpp:218] Iteration 528 (2.49622 iter/s, 4.80727s/12 iters), loss = 5.26805 +I0410 13:33:52.547725 18534 solver.cpp:237] Train net output #0: loss = 5.26805 (* 1 = 5.26805 loss) +I0410 13:33:52.547737 18534 sgd_solver.cpp:105] Iteration 528, lr = 0.00900694 +I0410 13:33:57.413000 18534 solver.cpp:218] Iteration 540 (2.46656 iter/s, 4.86507s/12 iters), loss = 5.27231 +I0410 13:33:57.413060 18534 solver.cpp:237] Train net output #0: loss = 5.27231 (* 1 = 5.27231 loss) +I0410 13:33:57.413072 18534 sgd_solver.cpp:105] Iteration 540, lr = 0.00898556 +I0410 13:34:02.264195 18534 solver.cpp:218] Iteration 552 (2.47375 iter/s, 4.85093s/12 iters), loss = 5.26956 +I0410 13:34:02.264250 18534 solver.cpp:237] Train net output #0: loss = 5.26956 (* 1 = 5.26956 loss) +I0410 13:34:02.264259 18534 sgd_solver.cpp:105] Iteration 552, lr = 0.00896423 +I0410 13:34:07.129266 18534 solver.cpp:218] Iteration 564 (2.46669 iter/s, 4.86481s/12 iters), loss = 5.26224 +I0410 13:34:07.129317 18534 solver.cpp:237] Train net output #0: loss = 5.26224 (* 1 = 5.26224 loss) +I0410 13:34:07.129329 18534 sgd_solver.cpp:105] Iteration 564, lr = 0.00894294 +I0410 13:34:11.950103 18534 solver.cpp:218] Iteration 576 (2.48933 iter/s, 4.82058s/12 iters), loss = 5.27795 +I0410 13:34:11.950165 18534 solver.cpp:237] Train net output #0: loss = 5.27795 (* 1 = 5.27795 loss) +I0410 13:34:11.950176 18534 sgd_solver.cpp:105] Iteration 576, lr = 0.00892171 +I0410 13:34:16.942466 18534 solver.cpp:218] Iteration 588 (2.4038 iter/s, 4.9921s/12 iters), loss = 5.26649 +I0410 13:34:16.942584 18534 solver.cpp:237] Train net output #0: loss = 5.26649 (* 1 = 5.26649 loss) +I0410 13:34:16.942597 18534 sgd_solver.cpp:105] Iteration 588, lr = 0.00890053 +I0410 13:34:21.777030 18534 solver.cpp:218] Iteration 600 (2.48229 iter/s, 4.83425s/12 iters), loss = 5.26037 +I0410 13:34:21.777086 18534 solver.cpp:237] Train net output #0: loss = 5.26037 (* 1 = 5.26037 loss) +I0410 13:34:21.777098 18534 sgd_solver.cpp:105] Iteration 600, lr = 0.0088794 +I0410 13:34:24.098258 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:26.158953 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_612.caffemodel +I0410 13:34:26.652654 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_612.solverstate +I0410 13:34:26.875074 18534 solver.cpp:330] Iteration 612, Testing net (#0) +I0410 13:34:26.875097 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:34:31.177489 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:31.460793 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:34:31.460839 18534 solver.cpp:397] Test net output #1: loss = 5.28377 (* 1 = 5.28377 loss) +I0410 13:34:31.543380 18534 solver.cpp:218] Iteration 612 (1.22876 iter/s, 9.7659s/12 iters), loss = 5.27557 +I0410 13:34:31.543452 18534 solver.cpp:237] Train net output #0: loss = 5.27557 (* 1 = 5.27557 loss) +I0410 13:34:31.543468 18534 sgd_solver.cpp:105] Iteration 612, lr = 0.00885831 +I0410 13:34:35.732069 18534 solver.cpp:218] Iteration 624 (2.86502 iter/s, 4.18845s/12 iters), loss = 5.28132 +I0410 13:34:35.732106 18534 solver.cpp:237] Train net output #0: loss = 5.28132 (* 1 = 5.28132 loss) +I0410 13:34:35.732113 18534 sgd_solver.cpp:105] Iteration 624, lr = 0.00883728 +I0410 13:34:40.541985 18534 solver.cpp:218] Iteration 636 (2.49498 iter/s, 4.80966s/12 iters), loss = 5.28425 +I0410 13:34:40.542032 18534 solver.cpp:237] Train net output #0: loss = 5.28425 (* 1 = 5.28425 loss) +I0410 13:34:40.542042 18534 sgd_solver.cpp:105] Iteration 636, lr = 0.0088163 +I0410 13:34:45.397914 18534 solver.cpp:218] Iteration 648 (2.47133 iter/s, 4.85568s/12 iters), loss = 5.2738 +I0410 13:34:45.397980 18534 solver.cpp:237] Train net output #0: loss = 5.2738 (* 1 = 5.2738 loss) +I0410 13:34:45.397991 18534 sgd_solver.cpp:105] Iteration 648, lr = 0.00879537 +I0410 13:34:50.259383 18534 solver.cpp:218] Iteration 660 (2.46852 iter/s, 4.8612s/12 iters), loss = 5.26752 +I0410 13:34:50.259496 18534 solver.cpp:237] Train net output #0: loss = 5.26752 (* 1 = 5.26752 loss) +I0410 13:34:50.259505 18534 sgd_solver.cpp:105] Iteration 660, lr = 0.00877449 +I0410 13:34:55.138547 18534 solver.cpp:218] Iteration 672 (2.45959 iter/s, 4.87885s/12 iters), loss = 5.27453 +I0410 13:34:55.138593 18534 solver.cpp:237] Train net output #0: loss = 5.27453 (* 1 = 5.27453 loss) +I0410 13:34:55.138602 18534 sgd_solver.cpp:105] Iteration 672, lr = 0.00875366 +I0410 13:34:59.112092 18534 blocking_queue.cpp:49] Waiting for data +I0410 13:34:59.968622 18534 solver.cpp:218] Iteration 684 (2.48456 iter/s, 4.82983s/12 iters), loss = 5.27293 +I0410 13:34:59.968675 18534 solver.cpp:237] Train net output #0: loss = 5.27293 (* 1 = 5.27293 loss) +I0410 13:34:59.968686 18534 sgd_solver.cpp:105] Iteration 684, lr = 0.00873287 +I0410 13:35:04.809859 18534 solver.cpp:218] Iteration 696 (2.47883 iter/s, 4.84099s/12 iters), loss = 5.269 +I0410 13:35:04.809916 18534 solver.cpp:237] Train net output #0: loss = 5.269 (* 1 = 5.269 loss) +I0410 13:35:04.809927 18534 sgd_solver.cpp:105] Iteration 696, lr = 0.00871214 +I0410 13:35:09.483995 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:09.851850 18534 solver.cpp:218] Iteration 708 (2.38014 iter/s, 5.04173s/12 iters), loss = 5.26117 +I0410 13:35:09.851902 18534 solver.cpp:237] Train net output #0: loss = 5.26117 (* 1 = 5.26117 loss) +I0410 13:35:09.851913 18534 sgd_solver.cpp:105] Iteration 708, lr = 0.00869145 +I0410 13:35:11.810812 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_714.caffemodel +I0410 13:35:12.119690 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_714.solverstate +I0410 13:35:12.335443 18534 solver.cpp:330] Iteration 714, Testing net (#0) +I0410 13:35:12.335470 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:35:16.369786 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:16.691017 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:35:16.691066 18534 solver.cpp:397] Test net output #1: loss = 5.28506 (* 1 = 5.28506 loss) +I0410 13:35:18.424029 18534 solver.cpp:218] Iteration 720 (1.39994 iter/s, 8.57179s/12 iters), loss = 5.27203 +I0410 13:35:18.424075 18534 solver.cpp:237] Train net output #0: loss = 5.27203 (* 1 = 5.27203 loss) +I0410 13:35:18.424083 18534 sgd_solver.cpp:105] Iteration 720, lr = 0.00867082 +I0410 13:35:23.410380 18534 solver.cpp:218] Iteration 732 (2.40669 iter/s, 4.9861s/12 iters), loss = 5.27484 +I0410 13:35:23.412896 18534 solver.cpp:237] Train net output #0: loss = 5.27484 (* 1 = 5.27484 loss) +I0410 13:35:23.412905 18534 sgd_solver.cpp:105] Iteration 732, lr = 0.00865023 +I0410 13:35:28.255098 18534 solver.cpp:218] Iteration 744 (2.47831 iter/s, 4.842s/12 iters), loss = 5.2771 +I0410 13:35:28.255141 18534 solver.cpp:237] Train net output #0: loss = 5.2771 (* 1 = 5.2771 loss) +I0410 13:35:28.255149 18534 sgd_solver.cpp:105] Iteration 744, lr = 0.0086297 +I0410 13:35:33.182710 18534 solver.cpp:218] Iteration 756 (2.43538 iter/s, 4.92737s/12 iters), loss = 5.27571 +I0410 13:35:33.182757 18534 solver.cpp:237] Train net output #0: loss = 5.27571 (* 1 = 5.27571 loss) +I0410 13:35:33.182766 18534 sgd_solver.cpp:105] Iteration 756, lr = 0.00860921 +I0410 13:35:38.007187 18534 solver.cpp:218] Iteration 768 (2.48744 iter/s, 4.82423s/12 iters), loss = 5.27662 +I0410 13:35:38.007248 18534 solver.cpp:237] Train net output #0: loss = 5.27662 (* 1 = 5.27662 loss) +I0410 13:35:38.007261 18534 sgd_solver.cpp:105] Iteration 768, lr = 0.00858877 +I0410 13:35:42.848177 18534 solver.cpp:218] Iteration 780 (2.47896 iter/s, 4.84073s/12 iters), loss = 5.26435 +I0410 13:35:42.848228 18534 solver.cpp:237] Train net output #0: loss = 5.26435 (* 1 = 5.26435 loss) +I0410 13:35:42.848239 18534 sgd_solver.cpp:105] Iteration 780, lr = 0.00856838 +I0410 13:35:47.659857 18534 solver.cpp:218] Iteration 792 (2.49406 iter/s, 4.81143s/12 iters), loss = 5.2665 +I0410 13:35:47.659904 18534 solver.cpp:237] Train net output #0: loss = 5.2665 (* 1 = 5.2665 loss) +I0410 13:35:47.659914 18534 sgd_solver.cpp:105] Iteration 792, lr = 0.00854803 +I0410 13:35:52.504144 18534 solver.cpp:218] Iteration 804 (2.47727 iter/s, 4.84404s/12 iters), loss = 5.2861 +I0410 13:35:52.504195 18534 solver.cpp:237] Train net output #0: loss = 5.2861 (* 1 = 5.2861 loss) +I0410 13:35:52.504206 18534 sgd_solver.cpp:105] Iteration 804, lr = 0.00852774 +I0410 13:35:54.190066 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:56.885318 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_816.caffemodel +I0410 13:35:57.185425 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_816.solverstate +I0410 13:35:57.394968 18534 solver.cpp:330] Iteration 816, Testing net (#0) +I0410 13:35:57.394994 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:36:01.453764 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:36:01.815716 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:36:01.815764 18534 solver.cpp:397] Test net output #1: loss = 5.28532 (* 1 = 5.28532 loss) +I0410 13:36:01.897536 18534 solver.cpp:218] Iteration 816 (1.27755 iter/s, 9.39297s/12 iters), loss = 5.27614 +I0410 13:36:01.897585 18534 solver.cpp:237] Train net output #0: loss = 5.27614 (* 1 = 5.27614 loss) +I0410 13:36:01.897598 18534 sgd_solver.cpp:105] Iteration 816, lr = 0.00850749 +I0410 13:36:06.074225 18534 solver.cpp:218] Iteration 828 (2.87324 iter/s, 4.17647s/12 iters), loss = 5.28136 +I0410 13:36:06.074278 18534 solver.cpp:237] Train net output #0: loss = 5.28136 (* 1 = 5.28136 loss) +I0410 13:36:06.074293 18534 sgd_solver.cpp:105] Iteration 828, lr = 0.00848729 +I0410 13:36:10.890159 18534 solver.cpp:218] Iteration 840 (2.49186 iter/s, 4.81568s/12 iters), loss = 5.2318 +I0410 13:36:10.890215 18534 solver.cpp:237] Train net output #0: loss = 5.2318 (* 1 = 5.2318 loss) +I0410 13:36:10.890226 18534 sgd_solver.cpp:105] Iteration 840, lr = 0.00846714 +I0410 13:36:15.718786 18534 solver.cpp:218] Iteration 852 (2.48531 iter/s, 4.82836s/12 iters), loss = 5.29634 +I0410 13:36:15.718843 18534 solver.cpp:237] Train net output #0: loss = 5.29634 (* 1 = 5.29634 loss) +I0410 13:36:15.718856 18534 sgd_solver.cpp:105] Iteration 852, lr = 0.00844704 +I0410 13:36:20.583461 18534 solver.cpp:218] Iteration 864 (2.4669 iter/s, 4.86441s/12 iters), loss = 5.26108 +I0410 13:36:20.583513 18534 solver.cpp:237] Train net output #0: loss = 5.26108 (* 1 = 5.26108 loss) +I0410 13:36:20.583525 18534 sgd_solver.cpp:105] Iteration 864, lr = 0.00842698 +I0410 13:36:25.402231 18534 solver.cpp:218] Iteration 876 (2.49039 iter/s, 4.81852s/12 iters), loss = 5.26896 +I0410 13:36:25.402349 18534 solver.cpp:237] Train net output #0: loss = 5.26896 (* 1 = 5.26896 loss) +I0410 13:36:25.402360 18534 sgd_solver.cpp:105] Iteration 876, lr = 0.00840698 +I0410 13:36:30.314301 18534 solver.cpp:218] Iteration 888 (2.44312 iter/s, 4.91175s/12 iters), loss = 5.26325 +I0410 13:36:30.314363 18534 solver.cpp:237] Train net output #0: loss = 5.26325 (* 1 = 5.26325 loss) +I0410 13:36:30.314375 18534 sgd_solver.cpp:105] Iteration 888, lr = 0.00838702 +I0410 13:36:35.156154 18534 solver.cpp:218] Iteration 900 (2.47852 iter/s, 4.84159s/12 iters), loss = 5.2733 +I0410 13:36:35.156204 18534 solver.cpp:237] Train net output #0: loss = 5.2733 (* 1 = 5.2733 loss) +I0410 13:36:35.156214 18534 sgd_solver.cpp:105] Iteration 900, lr = 0.0083671 +I0410 13:36:38.875677 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:36:39.947882 18534 solver.cpp:218] Iteration 912 (2.50444 iter/s, 4.79148s/12 iters), loss = 5.26026 +I0410 13:36:39.947937 18534 solver.cpp:237] Train net output #0: loss = 5.26026 (* 1 = 5.26026 loss) +I0410 13:36:39.947948 18534 sgd_solver.cpp:105] Iteration 912, lr = 0.00834724 +I0410 13:36:41.937578 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_918.caffemodel +I0410 13:36:42.258810 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_918.solverstate +I0410 13:36:42.472784 18534 solver.cpp:330] Iteration 918, Testing net (#0) +I0410 13:36:42.472815 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:36:46.452205 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:36:46.875205 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:36:46.875252 18534 solver.cpp:397] Test net output #1: loss = 5.28555 (* 1 = 5.28555 loss) +I0410 13:36:48.630923 18534 solver.cpp:218] Iteration 924 (1.38207 iter/s, 8.68264s/12 iters), loss = 5.28608 +I0410 13:36:48.630977 18534 solver.cpp:237] Train net output #0: loss = 5.28608 (* 1 = 5.28608 loss) +I0410 13:36:48.630988 18534 sgd_solver.cpp:105] Iteration 924, lr = 0.00832742 +I0410 13:36:54.103402 18534 solver.cpp:218] Iteration 936 (2.1929 iter/s, 5.4722s/12 iters), loss = 5.25781 +I0410 13:36:54.103446 18534 solver.cpp:237] Train net output #0: loss = 5.25781 (* 1 = 5.25781 loss) +I0410 13:36:54.103454 18534 sgd_solver.cpp:105] Iteration 936, lr = 0.00830765 +I0410 13:36:58.902216 18534 solver.cpp:218] Iteration 948 (2.50074 iter/s, 4.79857s/12 iters), loss = 5.2872 +I0410 13:36:58.902284 18534 solver.cpp:237] Train net output #0: loss = 5.2872 (* 1 = 5.2872 loss) +I0410 13:36:58.902293 18534 sgd_solver.cpp:105] Iteration 948, lr = 0.00828793 +I0410 13:37:03.757905 18534 solver.cpp:218] Iteration 960 (2.47147 iter/s, 4.85542s/12 iters), loss = 5.2595 +I0410 13:37:03.757951 18534 solver.cpp:237] Train net output #0: loss = 5.2595 (* 1 = 5.2595 loss) +I0410 13:37:03.757977 18534 sgd_solver.cpp:105] Iteration 960, lr = 0.00826825 +I0410 13:37:08.758894 18534 solver.cpp:218] Iteration 972 (2.39965 iter/s, 5.00074s/12 iters), loss = 5.27295 +I0410 13:37:08.758944 18534 solver.cpp:237] Train net output #0: loss = 5.27295 (* 1 = 5.27295 loss) +I0410 13:37:08.758955 18534 sgd_solver.cpp:105] Iteration 972, lr = 0.00824862 +I0410 13:37:13.776257 18534 solver.cpp:218] Iteration 984 (2.39182 iter/s, 5.01711s/12 iters), loss = 5.28891 +I0410 13:37:13.776311 18534 solver.cpp:237] Train net output #0: loss = 5.28891 (* 1 = 5.28891 loss) +I0410 13:37:13.776322 18534 sgd_solver.cpp:105] Iteration 984, lr = 0.00822903 +I0410 13:37:18.628089 18534 solver.cpp:218] Iteration 996 (2.47342 iter/s, 4.85158s/12 iters), loss = 5.27786 +I0410 13:37:18.628135 18534 solver.cpp:237] Train net output #0: loss = 5.27786 (* 1 = 5.27786 loss) +I0410 13:37:18.628145 18534 sgd_solver.cpp:105] Iteration 996, lr = 0.0082095 +I0410 13:37:23.492348 18534 solver.cpp:218] Iteration 1008 (2.4671 iter/s, 4.86401s/12 iters), loss = 5.2849 +I0410 13:37:23.492403 18534 solver.cpp:237] Train net output #0: loss = 5.2849 (* 1 = 5.2849 loss) +I0410 13:37:23.492414 18534 sgd_solver.cpp:105] Iteration 1008, lr = 0.00819001 +I0410 13:37:24.488366 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:27.916412 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1020.caffemodel +I0410 13:37:28.244669 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1020.solverstate +I0410 13:37:28.463104 18534 solver.cpp:330] Iteration 1020, Testing net (#0) +I0410 13:37:28.463127 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:37:32.504130 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:32.935128 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:37:32.935178 18534 solver.cpp:397] Test net output #1: loss = 5.28564 (* 1 = 5.28564 loss) +I0410 13:37:33.017513 18534 solver.cpp:218] Iteration 1020 (1.25988 iter/s, 9.52473s/12 iters), loss = 5.28479 +I0410 13:37:33.017567 18534 solver.cpp:237] Train net output #0: loss = 5.28479 (* 1 = 5.28479 loss) +I0410 13:37:33.017580 18534 sgd_solver.cpp:105] Iteration 1020, lr = 0.00817056 +I0410 13:37:37.065877 18534 solver.cpp:218] Iteration 1032 (2.96432 iter/s, 4.04814s/12 iters), loss = 5.24847 +I0410 13:37:37.065927 18534 solver.cpp:237] Train net output #0: loss = 5.24847 (* 1 = 5.24847 loss) +I0410 13:37:37.065935 18534 sgd_solver.cpp:105] Iteration 1032, lr = 0.00815116 +I0410 13:37:42.016116 18534 solver.cpp:218] Iteration 1044 (2.42425 iter/s, 4.94998s/12 iters), loss = 5.25597 +I0410 13:37:42.016176 18534 solver.cpp:237] Train net output #0: loss = 5.25597 (* 1 = 5.25597 loss) +I0410 13:37:42.016188 18534 sgd_solver.cpp:105] Iteration 1044, lr = 0.00813181 +I0410 13:37:46.838300 18534 solver.cpp:218] Iteration 1056 (2.48863 iter/s, 4.82193s/12 iters), loss = 5.26657 +I0410 13:37:46.838348 18534 solver.cpp:237] Train net output #0: loss = 5.26657 (* 1 = 5.26657 loss) +I0410 13:37:46.838356 18534 sgd_solver.cpp:105] Iteration 1056, lr = 0.0081125 +I0410 13:37:51.683388 18534 solver.cpp:218] Iteration 1068 (2.47686 iter/s, 4.84484s/12 iters), loss = 5.28865 +I0410 13:37:51.683444 18534 solver.cpp:237] Train net output #0: loss = 5.28865 (* 1 = 5.28865 loss) +I0410 13:37:51.683456 18534 sgd_solver.cpp:105] Iteration 1068, lr = 0.00809324 +I0410 13:37:56.530668 18534 solver.cpp:218] Iteration 1080 (2.47574 iter/s, 4.84703s/12 iters), loss = 5.27137 +I0410 13:37:56.530712 18534 solver.cpp:237] Train net output #0: loss = 5.27137 (* 1 = 5.27137 loss) +I0410 13:37:56.530720 18534 sgd_solver.cpp:105] Iteration 1080, lr = 0.00807403 +I0410 13:38:01.514587 18534 solver.cpp:218] Iteration 1092 (2.40786 iter/s, 4.98367s/12 iters), loss = 5.28335 +I0410 13:38:01.514636 18534 solver.cpp:237] Train net output #0: loss = 5.28335 (* 1 = 5.28335 loss) +I0410 13:38:01.514647 18534 sgd_solver.cpp:105] Iteration 1092, lr = 0.00805486 +I0410 13:38:06.429992 18534 solver.cpp:218] Iteration 1104 (2.44143 iter/s, 4.91515s/12 iters), loss = 5.27348 +I0410 13:38:06.430083 18534 solver.cpp:237] Train net output #0: loss = 5.27348 (* 1 = 5.27348 loss) +I0410 13:38:06.430092 18534 sgd_solver.cpp:105] Iteration 1104, lr = 0.00803573 +I0410 13:38:09.500939 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:38:11.283672 18534 solver.cpp:218] Iteration 1116 (2.4725 iter/s, 4.85339s/12 iters), loss = 5.27346 +I0410 13:38:11.283720 18534 solver.cpp:237] Train net output #0: loss = 5.27346 (* 1 = 5.27346 loss) +I0410 13:38:11.283730 18534 sgd_solver.cpp:105] Iteration 1116, lr = 0.00801666 +I0410 13:38:13.238874 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1122.caffemodel +I0410 13:38:13.528414 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1122.solverstate +I0410 13:38:13.727325 18534 solver.cpp:330] Iteration 1122, Testing net (#0) +I0410 13:38:13.727353 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:38:17.685722 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:38:18.161461 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:38:18.161505 18534 solver.cpp:397] Test net output #1: loss = 5.28589 (* 1 = 5.28589 loss) +I0410 13:38:20.030804 18534 solver.cpp:218] Iteration 1128 (1.37194 iter/s, 8.74673s/12 iters), loss = 5.2726 +I0410 13:38:20.030861 18534 solver.cpp:237] Train net output #0: loss = 5.2726 (* 1 = 5.2726 loss) +I0410 13:38:20.030875 18534 sgd_solver.cpp:105] Iteration 1128, lr = 0.00799762 +I0410 13:38:24.868975 18534 solver.cpp:218] Iteration 1140 (2.48041 iter/s, 4.83791s/12 iters), loss = 5.26804 +I0410 13:38:24.869033 18534 solver.cpp:237] Train net output #0: loss = 5.26804 (* 1 = 5.26804 loss) +I0410 13:38:24.869045 18534 sgd_solver.cpp:105] Iteration 1140, lr = 0.00797863 +I0410 13:38:29.718784 18534 solver.cpp:218] Iteration 1152 (2.47446 iter/s, 4.84955s/12 iters), loss = 5.2789 +I0410 13:38:29.718845 18534 solver.cpp:237] Train net output #0: loss = 5.2789 (* 1 = 5.2789 loss) +I0410 13:38:29.718858 18534 sgd_solver.cpp:105] Iteration 1152, lr = 0.00795969 +I0410 13:38:34.570839 18534 solver.cpp:218] Iteration 1164 (2.47331 iter/s, 4.8518s/12 iters), loss = 5.27529 +I0410 13:38:34.570888 18534 solver.cpp:237] Train net output #0: loss = 5.27529 (* 1 = 5.27529 loss) +I0410 13:38:34.570896 18534 sgd_solver.cpp:105] Iteration 1164, lr = 0.00794079 +I0410 13:38:39.382244 18534 solver.cpp:218] Iteration 1176 (2.4942 iter/s, 4.81116s/12 iters), loss = 5.28766 +I0410 13:38:39.382339 18534 solver.cpp:237] Train net output #0: loss = 5.28766 (* 1 = 5.28766 loss) +I0410 13:38:39.382349 18534 sgd_solver.cpp:105] Iteration 1176, lr = 0.00792194 +I0410 13:38:44.229672 18534 solver.cpp:218] Iteration 1188 (2.47569 iter/s, 4.84713s/12 iters), loss = 5.27054 +I0410 13:38:44.229725 18534 solver.cpp:237] Train net output #0: loss = 5.27054 (* 1 = 5.27054 loss) +I0410 13:38:44.229737 18534 sgd_solver.cpp:105] Iteration 1188, lr = 0.00790313 +I0410 13:38:49.118588 18534 solver.cpp:218] Iteration 1200 (2.45466 iter/s, 4.88867s/12 iters), loss = 5.28757 +I0410 13:38:49.118639 18534 solver.cpp:237] Train net output #0: loss = 5.28757 (* 1 = 5.28757 loss) +I0410 13:38:49.118650 18534 sgd_solver.cpp:105] Iteration 1200, lr = 0.00788437 +I0410 13:38:53.992424 18534 solver.cpp:218] Iteration 1212 (2.46226 iter/s, 4.87358s/12 iters), loss = 5.26516 +I0410 13:38:53.992483 18534 solver.cpp:237] Train net output #0: loss = 5.26516 (* 1 = 5.26516 loss) +I0410 13:38:53.992497 18534 sgd_solver.cpp:105] Iteration 1212, lr = 0.00786565 +I0410 13:38:54.270185 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:38:58.375242 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1224.caffemodel +I0410 13:38:59.705274 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1224.solverstate +I0410 13:38:59.923827 18534 solver.cpp:330] Iteration 1224, Testing net (#0) +I0410 13:38:59.923856 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:39:03.884922 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:04.394629 18534 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:39:04.394670 18534 solver.cpp:397] Test net output #1: loss = 5.28598 (* 1 = 5.28598 loss) +I0410 13:39:04.477064 18534 solver.cpp:218] Iteration 1224 (1.14458 iter/s, 10.4842s/12 iters), loss = 5.28163 +I0410 13:39:04.477113 18534 solver.cpp:237] Train net output #0: loss = 5.28163 (* 1 = 5.28163 loss) +I0410 13:39:04.477121 18534 sgd_solver.cpp:105] Iteration 1224, lr = 0.00784697 +I0410 13:39:08.597750 18534 solver.cpp:218] Iteration 1236 (2.91229 iter/s, 4.12046s/12 iters), loss = 5.26979 +I0410 13:39:08.597801 18534 solver.cpp:237] Train net output #0: loss = 5.26979 (* 1 = 5.26979 loss) +I0410 13:39:08.597813 18534 sgd_solver.cpp:105] Iteration 1236, lr = 0.00782834 +I0410 13:39:13.477164 18534 solver.cpp:218] Iteration 1248 (2.45944 iter/s, 4.87916s/12 iters), loss = 5.27968 +I0410 13:39:13.477263 18534 solver.cpp:237] Train net output #0: loss = 5.27968 (* 1 = 5.27968 loss) +I0410 13:39:13.477272 18534 sgd_solver.cpp:105] Iteration 1248, lr = 0.00780976 +I0410 13:39:18.346927 18534 solver.cpp:218] Iteration 1260 (2.46434 iter/s, 4.86947s/12 iters), loss = 5.27254 +I0410 13:39:18.346974 18534 solver.cpp:237] Train net output #0: loss = 5.27254 (* 1 = 5.27254 loss) +I0410 13:39:18.346984 18534 sgd_solver.cpp:105] Iteration 1260, lr = 0.00779122 +I0410 13:39:23.253991 18534 solver.cpp:218] Iteration 1272 (2.44558 iter/s, 4.9068s/12 iters), loss = 5.24685 +I0410 13:39:23.254040 18534 solver.cpp:237] Train net output #0: loss = 5.24685 (* 1 = 5.24685 loss) +I0410 13:39:23.254052 18534 sgd_solver.cpp:105] Iteration 1272, lr = 0.00777272 +I0410 13:39:28.134604 18534 solver.cpp:218] Iteration 1284 (2.45883 iter/s, 4.88036s/12 iters), loss = 5.28184 +I0410 13:39:28.134662 18534 solver.cpp:237] Train net output #0: loss = 5.28184 (* 1 = 5.28184 loss) +I0410 13:39:28.134673 18534 sgd_solver.cpp:105] Iteration 1284, lr = 0.00775426 +I0410 13:39:33.047551 18534 solver.cpp:218] Iteration 1296 (2.44265 iter/s, 4.91269s/12 iters), loss = 5.26901 +I0410 13:39:33.047600 18534 solver.cpp:237] Train net output #0: loss = 5.26901 (* 1 = 5.26901 loss) +I0410 13:39:33.047611 18534 sgd_solver.cpp:105] Iteration 1296, lr = 0.00773585 +I0410 13:39:38.055063 18534 solver.cpp:218] Iteration 1308 (2.39652 iter/s, 5.00726s/12 iters), loss = 5.25573 +I0410 13:39:38.055102 18534 solver.cpp:237] Train net output #0: loss = 5.25573 (* 1 = 5.25573 loss) +I0410 13:39:38.055111 18534 sgd_solver.cpp:105] Iteration 1308, lr = 0.00771749 +I0410 13:39:40.509371 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:42.919997 18534 solver.cpp:218] Iteration 1320 (2.46676 iter/s, 4.86469s/12 iters), loss = 5.27207 +I0410 13:39:42.920054 18534 solver.cpp:237] Train net output #0: loss = 5.27207 (* 1 = 5.27207 loss) +I0410 13:39:42.920068 18534 sgd_solver.cpp:105] Iteration 1320, lr = 0.00769916 +I0410 13:39:44.893997 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1326.caffemodel +I0410 13:39:45.216480 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1326.solverstate +I0410 13:39:45.427958 18534 solver.cpp:330] Iteration 1326, Testing net (#0) +I0410 13:39:45.427979 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:39:49.309180 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:49.863237 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:39:49.863286 18534 solver.cpp:397] Test net output #1: loss = 5.28663 (* 1 = 5.28663 loss) +I0410 13:39:51.627775 18534 solver.cpp:218] Iteration 1332 (1.37814 iter/s, 8.70737s/12 iters), loss = 5.28842 +I0410 13:39:51.627837 18534 solver.cpp:237] Train net output #0: loss = 5.28842 (* 1 = 5.28842 loss) +I0410 13:39:51.627849 18534 sgd_solver.cpp:105] Iteration 1332, lr = 0.00768088 +I0410 13:39:56.412345 18534 solver.cpp:218] Iteration 1344 (2.5082 iter/s, 4.78431s/12 iters), loss = 5.28654 +I0410 13:39:56.412405 18534 solver.cpp:237] Train net output #0: loss = 5.28654 (* 1 = 5.28654 loss) +I0410 13:39:56.412417 18534 sgd_solver.cpp:105] Iteration 1344, lr = 0.00766265 +I0410 13:40:01.174154 18534 solver.cpp:218] Iteration 1356 (2.52019 iter/s, 4.76155s/12 iters), loss = 5.27615 +I0410 13:40:01.174214 18534 solver.cpp:237] Train net output #0: loss = 5.27615 (* 1 = 5.27615 loss) +I0410 13:40:01.174226 18534 sgd_solver.cpp:105] Iteration 1356, lr = 0.00764446 +I0410 13:40:05.521457 18534 blocking_queue.cpp:49] Waiting for data +I0410 13:40:06.050148 18534 solver.cpp:218] Iteration 1368 (2.46117 iter/s, 4.87573s/12 iters), loss = 5.2694 +I0410 13:40:06.050191 18534 solver.cpp:237] Train net output #0: loss = 5.2694 (* 1 = 5.2694 loss) +I0410 13:40:06.050199 18534 sgd_solver.cpp:105] Iteration 1368, lr = 0.00762631 +I0410 13:40:11.108291 18534 solver.cpp:218] Iteration 1380 (2.37253 iter/s, 5.05789s/12 iters), loss = 5.27038 +I0410 13:40:11.108337 18534 solver.cpp:237] Train net output #0: loss = 5.27038 (* 1 = 5.27038 loss) +I0410 13:40:11.108348 18534 sgd_solver.cpp:105] Iteration 1380, lr = 0.0076082 +I0410 13:40:16.028270 18534 solver.cpp:218] Iteration 1392 (2.43916 iter/s, 4.91973s/12 iters), loss = 5.2717 +I0410 13:40:16.028395 18534 solver.cpp:237] Train net output #0: loss = 5.2717 (* 1 = 5.2717 loss) +I0410 13:40:16.028407 18534 sgd_solver.cpp:105] Iteration 1392, lr = 0.00759014 +I0410 13:40:20.996186 18534 solver.cpp:218] Iteration 1404 (2.41566 iter/s, 4.96759s/12 iters), loss = 5.2763 +I0410 13:40:20.996235 18534 solver.cpp:237] Train net output #0: loss = 5.2763 (* 1 = 5.2763 loss) +I0410 13:40:20.996244 18534 sgd_solver.cpp:105] Iteration 1404, lr = 0.00757212 +I0410 13:40:25.579975 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:25.929078 18534 solver.cpp:218] Iteration 1416 (2.43277 iter/s, 4.93264s/12 iters), loss = 5.2601 +I0410 13:40:25.929126 18534 solver.cpp:237] Train net output #0: loss = 5.2601 (* 1 = 5.2601 loss) +I0410 13:40:25.929134 18534 sgd_solver.cpp:105] Iteration 1416, lr = 0.00755414 +I0410 13:40:30.472674 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1428.caffemodel +I0410 13:40:30.771234 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1428.solverstate +I0410 13:40:30.968163 18534 solver.cpp:330] Iteration 1428, Testing net (#0) +I0410 13:40:30.968183 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:40:34.693394 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:35.281253 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:40:35.281287 18534 solver.cpp:397] Test net output #1: loss = 5.28625 (* 1 = 5.28625 loss) +I0410 13:40:35.362166 18534 solver.cpp:218] Iteration 1428 (1.27217 iter/s, 9.43266s/12 iters), loss = 5.27638 +I0410 13:40:35.362213 18534 solver.cpp:237] Train net output #0: loss = 5.27638 (* 1 = 5.27638 loss) +I0410 13:40:35.362222 18534 sgd_solver.cpp:105] Iteration 1428, lr = 0.0075362 +I0410 13:40:39.442085 18534 solver.cpp:218] Iteration 1440 (2.94139 iter/s, 4.0797s/12 iters), loss = 5.28258 +I0410 13:40:39.442131 18534 solver.cpp:237] Train net output #0: loss = 5.28258 (* 1 = 5.28258 loss) +I0410 13:40:39.442139 18534 sgd_solver.cpp:105] Iteration 1440, lr = 0.00751831 +I0410 13:40:44.290338 18534 solver.cpp:218] Iteration 1452 (2.47524 iter/s, 4.848s/12 iters), loss = 5.27833 +I0410 13:40:44.290382 18534 solver.cpp:237] Train net output #0: loss = 5.27833 (* 1 = 5.27833 loss) +I0410 13:40:44.290391 18534 sgd_solver.cpp:105] Iteration 1452, lr = 0.00750046 +I0410 13:40:49.079349 18534 solver.cpp:218] Iteration 1464 (2.50586 iter/s, 4.78877s/12 iters), loss = 5.27424 +I0410 13:40:49.079460 18534 solver.cpp:237] Train net output #0: loss = 5.27424 (* 1 = 5.27424 loss) +I0410 13:40:49.079473 18534 sgd_solver.cpp:105] Iteration 1464, lr = 0.00748265 +I0410 13:40:53.977725 18534 solver.cpp:218] Iteration 1476 (2.44995 iter/s, 4.89807s/12 iters), loss = 5.27581 +I0410 13:40:53.977771 18534 solver.cpp:237] Train net output #0: loss = 5.27581 (* 1 = 5.27581 loss) +I0410 13:40:53.977780 18534 sgd_solver.cpp:105] Iteration 1476, lr = 0.00746489 +I0410 13:40:58.930330 18534 solver.cpp:218] Iteration 1488 (2.42309 iter/s, 4.95235s/12 iters), loss = 5.25515 +I0410 13:40:58.930370 18534 solver.cpp:237] Train net output #0: loss = 5.25515 (* 1 = 5.25515 loss) +I0410 13:40:58.930378 18534 sgd_solver.cpp:105] Iteration 1488, lr = 0.00744716 +I0410 13:41:03.732648 18534 solver.cpp:218] Iteration 1500 (2.49892 iter/s, 4.80208s/12 iters), loss = 5.26916 +I0410 13:41:03.732694 18534 solver.cpp:237] Train net output #0: loss = 5.26916 (* 1 = 5.26916 loss) +I0410 13:41:03.732703 18534 sgd_solver.cpp:105] Iteration 1500, lr = 0.00742948 +I0410 13:41:08.573686 18534 solver.cpp:218] Iteration 1512 (2.47893 iter/s, 4.84079s/12 iters), loss = 5.28331 +I0410 13:41:08.573735 18534 solver.cpp:237] Train net output #0: loss = 5.28331 (* 1 = 5.28331 loss) +I0410 13:41:08.573745 18534 sgd_solver.cpp:105] Iteration 1512, lr = 0.00741184 +I0410 13:41:10.323379 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:41:13.459836 18534 solver.cpp:218] Iteration 1524 (2.45605 iter/s, 4.8859s/12 iters), loss = 5.27187 +I0410 13:41:13.459880 18534 solver.cpp:237] Train net output #0: loss = 5.27187 (* 1 = 5.27187 loss) +I0410 13:41:13.459888 18534 sgd_solver.cpp:105] Iteration 1524, lr = 0.00739425 +I0410 13:41:15.493710 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1530.caffemodel +I0410 13:41:15.782516 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1530.solverstate +I0410 13:41:15.982985 18534 solver.cpp:330] Iteration 1530, Testing net (#0) +I0410 13:41:15.983011 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:41:19.817205 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:41:20.450618 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:41:20.450656 18534 solver.cpp:397] Test net output #1: loss = 5.28617 (* 1 = 5.28617 loss) +I0410 13:41:22.262660 18534 solver.cpp:218] Iteration 1536 (1.36326 iter/s, 8.80243s/12 iters), loss = 5.27731 +I0410 13:41:22.262717 18534 solver.cpp:237] Train net output #0: loss = 5.27731 (* 1 = 5.27731 loss) +I0410 13:41:22.262728 18534 sgd_solver.cpp:105] Iteration 1536, lr = 0.00737669 +I0410 13:41:27.169088 18534 solver.cpp:218] Iteration 1548 (2.4459 iter/s, 4.90617s/12 iters), loss = 5.2331 +I0410 13:41:27.169131 18534 solver.cpp:237] Train net output #0: loss = 5.2331 (* 1 = 5.2331 loss) +I0410 13:41:27.169139 18534 sgd_solver.cpp:105] Iteration 1548, lr = 0.00735918 +I0410 13:41:32.074345 18534 solver.cpp:218] Iteration 1560 (2.44648 iter/s, 4.90501s/12 iters), loss = 5.28892 +I0410 13:41:32.074388 18534 solver.cpp:237] Train net output #0: loss = 5.28892 (* 1 = 5.28892 loss) +I0410 13:41:32.074398 18534 sgd_solver.cpp:105] Iteration 1560, lr = 0.00734171 +I0410 13:41:37.045097 18534 solver.cpp:218] Iteration 1572 (2.41424 iter/s, 4.97051s/12 iters), loss = 5.26062 +I0410 13:41:37.045140 18534 solver.cpp:237] Train net output #0: loss = 5.26062 (* 1 = 5.26062 loss) +I0410 13:41:37.045150 18534 sgd_solver.cpp:105] Iteration 1572, lr = 0.00732427 +I0410 13:41:41.968989 18534 solver.cpp:218] Iteration 1584 (2.43722 iter/s, 4.92364s/12 iters), loss = 5.26571 +I0410 13:41:41.969043 18534 solver.cpp:237] Train net output #0: loss = 5.26571 (* 1 = 5.26571 loss) +I0410 13:41:41.969055 18534 sgd_solver.cpp:105] Iteration 1584, lr = 0.00730688 +I0410 13:41:46.947049 18534 solver.cpp:218] Iteration 1596 (2.4107 iter/s, 4.9778s/12 iters), loss = 5.26948 +I0410 13:41:46.947096 18534 solver.cpp:237] Train net output #0: loss = 5.26948 (* 1 = 5.26948 loss) +I0410 13:41:46.947105 18534 sgd_solver.cpp:105] Iteration 1596, lr = 0.00728954 +I0410 13:41:51.816301 18534 solver.cpp:218] Iteration 1608 (2.46457 iter/s, 4.869s/12 iters), loss = 5.26525 +I0410 13:41:51.816375 18534 solver.cpp:237] Train net output #0: loss = 5.26525 (* 1 = 5.26525 loss) +I0410 13:41:51.816386 18534 sgd_solver.cpp:105] Iteration 1608, lr = 0.00727223 +I0410 13:41:55.776684 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:41:56.849591 18534 solver.cpp:218] Iteration 1620 (2.38426 iter/s, 5.03301s/12 iters), loss = 5.2584 +I0410 13:41:56.849624 18534 solver.cpp:237] Train net output #0: loss = 5.2584 (* 1 = 5.2584 loss) +I0410 13:41:56.849633 18534 sgd_solver.cpp:105] Iteration 1620, lr = 0.00725496 +I0410 13:42:01.283069 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1632.caffemodel +I0410 13:42:02.530117 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1632.solverstate +I0410 13:42:03.373245 18534 solver.cpp:330] Iteration 1632, Testing net (#0) +I0410 13:42:03.373277 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:42:07.239606 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:42:07.908511 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:42:07.908546 18534 solver.cpp:397] Test net output #1: loss = 5.28635 (* 1 = 5.28635 loss) +I0410 13:42:07.990150 18534 solver.cpp:218] Iteration 1632 (1.07719 iter/s, 11.1401s/12 iters), loss = 5.28953 +I0410 13:42:07.990195 18534 solver.cpp:237] Train net output #0: loss = 5.28953 (* 1 = 5.28953 loss) +I0410 13:42:07.990204 18534 sgd_solver.cpp:105] Iteration 1632, lr = 0.00723774 +I0410 13:42:12.118046 18534 solver.cpp:218] Iteration 1644 (2.90721 iter/s, 4.12767s/12 iters), loss = 5.25694 +I0410 13:42:12.118099 18534 solver.cpp:237] Train net output #0: loss = 5.25694 (* 1 = 5.25694 loss) +I0410 13:42:12.118110 18534 sgd_solver.cpp:105] Iteration 1644, lr = 0.00722056 +I0410 13:42:16.962599 18534 solver.cpp:218] Iteration 1656 (2.47714 iter/s, 4.8443s/12 iters), loss = 5.29322 +I0410 13:42:16.962652 18534 solver.cpp:237] Train net output #0: loss = 5.29322 (* 1 = 5.29322 loss) +I0410 13:42:16.962662 18534 sgd_solver.cpp:105] Iteration 1656, lr = 0.00720341 +I0410 13:42:21.919958 18534 solver.cpp:218] Iteration 1668 (2.42077 iter/s, 4.9571s/12 iters), loss = 5.25956 +I0410 13:42:21.920083 18534 solver.cpp:237] Train net output #0: loss = 5.25956 (* 1 = 5.25956 loss) +I0410 13:42:21.920095 18534 sgd_solver.cpp:105] Iteration 1668, lr = 0.00718631 +I0410 13:42:26.855760 18534 solver.cpp:218] Iteration 1680 (2.43138 iter/s, 4.93548s/12 iters), loss = 5.27437 +I0410 13:42:26.855803 18534 solver.cpp:237] Train net output #0: loss = 5.27437 (* 1 = 5.27437 loss) +I0410 13:42:26.855811 18534 sgd_solver.cpp:105] Iteration 1680, lr = 0.00716925 +I0410 13:42:31.695783 18534 solver.cpp:218] Iteration 1692 (2.47945 iter/s, 4.83978s/12 iters), loss = 5.28934 +I0410 13:42:31.695829 18534 solver.cpp:237] Train net output #0: loss = 5.28934 (* 1 = 5.28934 loss) +I0410 13:42:31.695838 18534 sgd_solver.cpp:105] Iteration 1692, lr = 0.00715223 +I0410 13:42:36.633426 18534 solver.cpp:218] Iteration 1704 (2.43043 iter/s, 4.93739s/12 iters), loss = 5.27153 +I0410 13:42:36.633479 18534 solver.cpp:237] Train net output #0: loss = 5.27153 (* 1 = 5.27153 loss) +I0410 13:42:36.633491 18534 sgd_solver.cpp:105] Iteration 1704, lr = 0.00713525 +I0410 13:42:41.541481 18534 solver.cpp:218] Iteration 1716 (2.44509 iter/s, 4.9078s/12 iters), loss = 5.2827 +I0410 13:42:41.541534 18534 solver.cpp:237] Train net output #0: loss = 5.2827 (* 1 = 5.2827 loss) +I0410 13:42:41.541546 18534 sgd_solver.cpp:105] Iteration 1716, lr = 0.00711831 +I0410 13:42:42.556828 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:42:46.404891 18534 solver.cpp:218] Iteration 1728 (2.46753 iter/s, 4.86316s/12 iters), loss = 5.2833 +I0410 13:42:46.404942 18534 solver.cpp:237] Train net output #0: loss = 5.2833 (* 1 = 5.2833 loss) +I0410 13:42:46.404954 18534 sgd_solver.cpp:105] Iteration 1728, lr = 0.00710141 +I0410 13:42:48.374109 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1734.caffemodel +I0410 13:42:48.712298 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1734.solverstate +I0410 13:42:48.986196 18534 solver.cpp:330] Iteration 1734, Testing net (#0) +I0410 13:42:48.986224 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:42:52.870054 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:42:53.653672 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:42:53.653712 18534 solver.cpp:397] Test net output #1: loss = 5.28667 (* 1 = 5.28667 loss) +I0410 13:42:55.439415 18534 solver.cpp:218] Iteration 1740 (1.3283 iter/s, 9.03411s/12 iters), loss = 5.25524 +I0410 13:42:55.439476 18534 solver.cpp:237] Train net output #0: loss = 5.25524 (* 1 = 5.25524 loss) +I0410 13:42:55.439487 18534 sgd_solver.cpp:105] Iteration 1740, lr = 0.00708455 +I0410 13:43:00.253151 18534 solver.cpp:218] Iteration 1752 (2.493 iter/s, 4.81348s/12 iters), loss = 5.26547 +I0410 13:43:00.253204 18534 solver.cpp:237] Train net output #0: loss = 5.26547 (* 1 = 5.26547 loss) +I0410 13:43:00.253216 18534 sgd_solver.cpp:105] Iteration 1752, lr = 0.00706773 +I0410 13:43:05.288933 18534 solver.cpp:218] Iteration 1764 (2.38307 iter/s, 5.03552s/12 iters), loss = 5.26562 +I0410 13:43:05.288978 18534 solver.cpp:237] Train net output #0: loss = 5.26562 (* 1 = 5.26562 loss) +I0410 13:43:05.288987 18534 sgd_solver.cpp:105] Iteration 1764, lr = 0.00705094 +I0410 13:43:10.443536 18534 solver.cpp:218] Iteration 1776 (2.32813 iter/s, 5.15434s/12 iters), loss = 5.28033 +I0410 13:43:10.443589 18534 solver.cpp:237] Train net output #0: loss = 5.28033 (* 1 = 5.28033 loss) +I0410 13:43:10.443603 18534 sgd_solver.cpp:105] Iteration 1776, lr = 0.0070342 +I0410 13:43:15.497172 18534 solver.cpp:218] Iteration 1788 (2.37465 iter/s, 5.05337s/12 iters), loss = 5.26145 +I0410 13:43:15.497231 18534 solver.cpp:237] Train net output #0: loss = 5.26145 (* 1 = 5.26145 loss) +I0410 13:43:15.497241 18534 sgd_solver.cpp:105] Iteration 1788, lr = 0.0070175 +I0410 13:43:20.376101 18534 solver.cpp:218] Iteration 1800 (2.45968 iter/s, 4.87867s/12 iters), loss = 5.2771 +I0410 13:43:20.376145 18534 solver.cpp:237] Train net output #0: loss = 5.2771 (* 1 = 5.2771 loss) +I0410 13:43:20.376154 18534 sgd_solver.cpp:105] Iteration 1800, lr = 0.00700084 +I0410 13:43:25.361191 18534 solver.cpp:218] Iteration 1812 (2.4073 iter/s, 4.98484s/12 iters), loss = 5.26824 +I0410 13:43:25.361346 18534 solver.cpp:237] Train net output #0: loss = 5.26824 (* 1 = 5.26824 loss) +I0410 13:43:25.361361 18534 sgd_solver.cpp:105] Iteration 1812, lr = 0.00698422 +I0410 13:43:28.470266 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:43:30.230392 18534 solver.cpp:218] Iteration 1824 (2.46465 iter/s, 4.86885s/12 iters), loss = 5.27174 +I0410 13:43:30.230449 18534 solver.cpp:237] Train net output #0: loss = 5.27174 (* 1 = 5.27174 loss) +I0410 13:43:30.230461 18534 sgd_solver.cpp:105] Iteration 1824, lr = 0.00696764 +I0410 13:43:34.622071 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1836.caffemodel +I0410 13:43:34.914342 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1836.solverstate +I0410 13:43:35.112812 18534 solver.cpp:330] Iteration 1836, Testing net (#0) +I0410 13:43:35.112833 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:43:38.733146 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:43:39.483863 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:43:39.483897 18534 solver.cpp:397] Test net output #1: loss = 5.28617 (* 1 = 5.28617 loss) +I0410 13:43:39.559962 18534 solver.cpp:218] Iteration 1836 (1.28629 iter/s, 9.32915s/12 iters), loss = 5.27303 +I0410 13:43:39.560007 18534 solver.cpp:237] Train net output #0: loss = 5.27303 (* 1 = 5.27303 loss) +I0410 13:43:39.560016 18534 sgd_solver.cpp:105] Iteration 1836, lr = 0.0069511 +I0410 13:43:43.825582 18534 solver.cpp:218] Iteration 1848 (2.81334 iter/s, 4.2654s/12 iters), loss = 5.27249 +I0410 13:43:43.825628 18534 solver.cpp:237] Train net output #0: loss = 5.27249 (* 1 = 5.27249 loss) +I0410 13:43:43.825639 18534 sgd_solver.cpp:105] Iteration 1848, lr = 0.00693459 +I0410 13:43:48.736793 18534 solver.cpp:218] Iteration 1860 (2.44351 iter/s, 4.91097s/12 iters), loss = 5.28343 +I0410 13:43:48.736835 18534 solver.cpp:237] Train net output #0: loss = 5.28343 (* 1 = 5.28343 loss) +I0410 13:43:48.736846 18534 sgd_solver.cpp:105] Iteration 1860, lr = 0.00691813 +I0410 13:43:53.675109 18534 solver.cpp:218] Iteration 1872 (2.4301 iter/s, 4.93807s/12 iters), loss = 5.26734 +I0410 13:43:53.675163 18534 solver.cpp:237] Train net output #0: loss = 5.26734 (* 1 = 5.26734 loss) +I0410 13:43:53.675176 18534 sgd_solver.cpp:105] Iteration 1872, lr = 0.0069017 +I0410 13:43:58.709173 18534 solver.cpp:218] Iteration 1884 (2.38388 iter/s, 5.0338s/12 iters), loss = 5.28415 +I0410 13:43:58.713330 18534 solver.cpp:237] Train net output #0: loss = 5.28415 (* 1 = 5.28415 loss) +I0410 13:43:58.713343 18534 sgd_solver.cpp:105] Iteration 1884, lr = 0.00688532 +I0410 13:44:03.644413 18534 solver.cpp:218] Iteration 1896 (2.43364 iter/s, 4.93088s/12 iters), loss = 5.26649 +I0410 13:44:03.644474 18534 solver.cpp:237] Train net output #0: loss = 5.26649 (* 1 = 5.26649 loss) +I0410 13:44:03.644485 18534 sgd_solver.cpp:105] Iteration 1896, lr = 0.00686897 +I0410 13:44:08.561659 18534 solver.cpp:218] Iteration 1908 (2.44052 iter/s, 4.91698s/12 iters), loss = 5.28576 +I0410 13:44:08.561714 18534 solver.cpp:237] Train net output #0: loss = 5.28576 (* 1 = 5.28576 loss) +I0410 13:44:08.561726 18534 sgd_solver.cpp:105] Iteration 1908, lr = 0.00685266 +I0410 13:44:13.511379 18534 solver.cpp:218] Iteration 1920 (2.42451 iter/s, 4.94946s/12 iters), loss = 5.27432 +I0410 13:44:13.511425 18534 solver.cpp:237] Train net output #0: loss = 5.27432 (* 1 = 5.27432 loss) +I0410 13:44:13.511436 18534 sgd_solver.cpp:105] Iteration 1920, lr = 0.00683639 +I0410 13:44:13.822059 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:18.407060 18534 solver.cpp:218] Iteration 1932 (2.45126 iter/s, 4.89543s/12 iters), loss = 5.28252 +I0410 13:44:18.407111 18534 solver.cpp:237] Train net output #0: loss = 5.28252 (* 1 = 5.28252 loss) +I0410 13:44:18.407121 18534 sgd_solver.cpp:105] Iteration 1932, lr = 0.00682016 +I0410 13:44:20.382221 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1938.caffemodel +I0410 13:44:20.692525 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1938.solverstate +I0410 13:44:20.894696 18534 solver.cpp:330] Iteration 1938, Testing net (#0) +I0410 13:44:20.894716 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:44:24.497129 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:25.280117 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:44:25.280162 18534 solver.cpp:397] Test net output #1: loss = 5.28662 (* 1 = 5.28662 loss) +I0410 13:44:27.112540 18534 solver.cpp:218] Iteration 1944 (1.3785 iter/s, 8.70508s/12 iters), loss = 5.27493 +I0410 13:44:27.112581 18534 solver.cpp:237] Train net output #0: loss = 5.27493 (* 1 = 5.27493 loss) +I0410 13:44:27.112591 18534 sgd_solver.cpp:105] Iteration 1944, lr = 0.00680397 +I0410 13:44:31.949651 18534 solver.cpp:218] Iteration 1956 (2.48094 iter/s, 4.83687s/12 iters), loss = 5.27989 +I0410 13:44:31.949754 18534 solver.cpp:237] Train net output #0: loss = 5.27989 (* 1 = 5.27989 loss) +I0410 13:44:31.949764 18534 sgd_solver.cpp:105] Iteration 1956, lr = 0.00678782 +I0410 13:44:36.836545 18534 solver.cpp:218] Iteration 1968 (2.4557 iter/s, 4.88659s/12 iters), loss = 5.27226 +I0410 13:44:36.836597 18534 solver.cpp:237] Train net output #0: loss = 5.27226 (* 1 = 5.27226 loss) +I0410 13:44:36.836609 18534 sgd_solver.cpp:105] Iteration 1968, lr = 0.0067717 +I0410 13:44:41.755842 18534 solver.cpp:218] Iteration 1980 (2.4395 iter/s, 4.91904s/12 iters), loss = 5.257 +I0410 13:44:41.755899 18534 solver.cpp:237] Train net output #0: loss = 5.257 (* 1 = 5.257 loss) +I0410 13:44:41.755911 18534 sgd_solver.cpp:105] Iteration 1980, lr = 0.00675562 +I0410 13:44:46.767843 18534 solver.cpp:218] Iteration 1992 (2.39438 iter/s, 5.01173s/12 iters), loss = 5.28134 +I0410 13:44:46.767900 18534 solver.cpp:237] Train net output #0: loss = 5.28134 (* 1 = 5.28134 loss) +I0410 13:44:46.767913 18534 sgd_solver.cpp:105] Iteration 1992, lr = 0.00673958 +I0410 13:44:51.608670 18534 solver.cpp:218] Iteration 2004 (2.47905 iter/s, 4.84057s/12 iters), loss = 5.2775 +I0410 13:44:51.608721 18534 solver.cpp:237] Train net output #0: loss = 5.2775 (* 1 = 5.2775 loss) +I0410 13:44:51.608732 18534 sgd_solver.cpp:105] Iteration 2004, lr = 0.00672358 +I0410 13:44:56.517414 18534 solver.cpp:218] Iteration 2016 (2.44474 iter/s, 4.90849s/12 iters), loss = 5.25399 +I0410 13:44:56.517462 18534 solver.cpp:237] Train net output #0: loss = 5.25399 (* 1 = 5.25399 loss) +I0410 13:44:56.517472 18534 sgd_solver.cpp:105] Iteration 2016, lr = 0.00670762 +I0410 13:44:58.970155 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:01.373481 18534 solver.cpp:218] Iteration 2028 (2.47126 iter/s, 4.85582s/12 iters), loss = 5.27698 +I0410 13:45:01.373528 18534 solver.cpp:237] Train net output #0: loss = 5.27698 (* 1 = 5.27698 loss) +I0410 13:45:01.373536 18534 sgd_solver.cpp:105] Iteration 2028, lr = 0.00669169 +I0410 13:45:05.813743 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2040.caffemodel +I0410 13:45:06.122370 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2040.solverstate +I0410 13:45:06.332306 18534 solver.cpp:330] Iteration 2040, Testing net (#0) +I0410 13:45:06.332336 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:45:10.320626 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:11.155006 18534 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:45:11.155045 18534 solver.cpp:397] Test net output #1: loss = 5.28634 (* 1 = 5.28634 loss) +I0410 13:45:11.236682 18534 solver.cpp:218] Iteration 2040 (1.2167 iter/s, 9.86276s/12 iters), loss = 5.28346 +I0410 13:45:11.236727 18534 solver.cpp:237] Train net output #0: loss = 5.28346 (* 1 = 5.28346 loss) +I0410 13:45:11.236735 18534 sgd_solver.cpp:105] Iteration 2040, lr = 0.00667581 +I0410 13:45:15.395424 18534 solver.cpp:218] Iteration 2052 (2.88564 iter/s, 4.15852s/12 iters), loss = 5.28439 +I0410 13:45:15.395474 18534 solver.cpp:237] Train net output #0: loss = 5.28439 (* 1 = 5.28439 loss) +I0410 13:45:15.395486 18534 sgd_solver.cpp:105] Iteration 2052, lr = 0.00665996 +I0410 13:45:15.395787 18534 blocking_queue.cpp:49] Waiting for data +I0410 13:45:20.260733 18534 solver.cpp:218] Iteration 2064 (2.46657 iter/s, 4.86505s/12 iters), loss = 5.27439 +I0410 13:45:20.260798 18534 solver.cpp:237] Train net output #0: loss = 5.27439 (* 1 = 5.27439 loss) +I0410 13:45:20.260812 18534 sgd_solver.cpp:105] Iteration 2064, lr = 0.00664414 +I0410 13:45:25.184263 18534 solver.cpp:218] Iteration 2076 (2.4374 iter/s, 4.92327s/12 iters), loss = 5.27902 +I0410 13:45:25.184309 18534 solver.cpp:237] Train net output #0: loss = 5.27902 (* 1 = 5.27902 loss) +I0410 13:45:25.184319 18534 sgd_solver.cpp:105] Iteration 2076, lr = 0.00662837 +I0410 13:45:30.090042 18534 solver.cpp:218] Iteration 2088 (2.44622 iter/s, 4.90552s/12 iters), loss = 5.27517 +I0410 13:45:30.090106 18534 solver.cpp:237] Train net output #0: loss = 5.27517 (* 1 = 5.27517 loss) +I0410 13:45:30.090119 18534 sgd_solver.cpp:105] Iteration 2088, lr = 0.00661263 +I0410 13:45:35.027304 18534 solver.cpp:218] Iteration 2100 (2.43063 iter/s, 4.93699s/12 iters), loss = 5.26904 +I0410 13:45:35.027366 18534 solver.cpp:237] Train net output #0: loss = 5.26904 (* 1 = 5.26904 loss) +I0410 13:45:35.027379 18534 sgd_solver.cpp:105] Iteration 2100, lr = 0.00659693 +I0410 13:45:40.035570 18534 solver.cpp:218] Iteration 2112 (2.39617 iter/s, 5.008s/12 iters), loss = 5.28467 +I0410 13:45:40.035674 18534 solver.cpp:237] Train net output #0: loss = 5.28467 (* 1 = 5.28467 loss) +I0410 13:45:40.035684 18534 sgd_solver.cpp:105] Iteration 2112, lr = 0.00658127 +I0410 13:45:44.590283 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:44.901757 18534 solver.cpp:218] Iteration 2124 (2.46615 iter/s, 4.86589s/12 iters), loss = 5.25463 +I0410 13:45:44.901810 18534 solver.cpp:237] Train net output #0: loss = 5.25463 (* 1 = 5.25463 loss) +I0410 13:45:44.901821 18534 sgd_solver.cpp:105] Iteration 2124, lr = 0.00656564 +I0410 13:45:49.751251 18534 solver.cpp:218] Iteration 2136 (2.47461 iter/s, 4.84924s/12 iters), loss = 5.2764 +I0410 13:45:49.751308 18534 solver.cpp:237] Train net output #0: loss = 5.2764 (* 1 = 5.2764 loss) +I0410 13:45:49.751320 18534 sgd_solver.cpp:105] Iteration 2136, lr = 0.00655006 +I0410 13:45:51.770931 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2142.caffemodel +I0410 13:45:52.062979 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2142.solverstate +I0410 13:45:52.260489 18534 solver.cpp:330] Iteration 2142, Testing net (#0) +I0410 13:45:52.260512 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:45:55.822860 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:56.682685 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:45:56.682734 18534 solver.cpp:397] Test net output #1: loss = 5.28657 (* 1 = 5.28657 loss) +I0410 13:45:58.560966 18534 solver.cpp:218] Iteration 2148 (1.3622 iter/s, 8.8093s/12 iters), loss = 5.28078 +I0410 13:45:58.561023 18534 solver.cpp:237] Train net output #0: loss = 5.28078 (* 1 = 5.28078 loss) +I0410 13:45:58.561036 18534 sgd_solver.cpp:105] Iteration 2148, lr = 0.00653451 +I0410 13:46:03.478660 18534 solver.cpp:218] Iteration 2160 (2.4403 iter/s, 4.91744s/12 iters), loss = 5.2848 +I0410 13:46:03.478705 18534 solver.cpp:237] Train net output #0: loss = 5.2848 (* 1 = 5.2848 loss) +I0410 13:46:03.478714 18534 sgd_solver.cpp:105] Iteration 2160, lr = 0.00651899 +I0410 13:46:08.418728 18534 solver.cpp:218] Iteration 2172 (2.42924 iter/s, 4.93981s/12 iters), loss = 5.27221 +I0410 13:46:08.418787 18534 solver.cpp:237] Train net output #0: loss = 5.27221 (* 1 = 5.27221 loss) +I0410 13:46:08.418798 18534 sgd_solver.cpp:105] Iteration 2172, lr = 0.00650351 +I0410 13:46:13.468091 18534 solver.cpp:218] Iteration 2184 (2.37666 iter/s, 5.0491s/12 iters), loss = 5.27447 +I0410 13:46:13.468217 18534 solver.cpp:237] Train net output #0: loss = 5.27447 (* 1 = 5.27447 loss) +I0410 13:46:13.468228 18534 sgd_solver.cpp:105] Iteration 2184, lr = 0.00648807 +I0410 13:46:18.346036 18534 solver.cpp:218] Iteration 2196 (2.46021 iter/s, 4.87762s/12 iters), loss = 5.25488 +I0410 13:46:18.346081 18534 solver.cpp:237] Train net output #0: loss = 5.25488 (* 1 = 5.25488 loss) +I0410 13:46:18.346091 18534 sgd_solver.cpp:105] Iteration 2196, lr = 0.00647267 +I0410 13:46:23.377676 18534 solver.cpp:218] Iteration 2208 (2.38503 iter/s, 5.03138s/12 iters), loss = 5.26895 +I0410 13:46:23.377737 18534 solver.cpp:237] Train net output #0: loss = 5.26895 (* 1 = 5.26895 loss) +I0410 13:46:23.377749 18534 sgd_solver.cpp:105] Iteration 2208, lr = 0.0064573 +I0410 13:46:28.342695 18534 solver.cpp:218] Iteration 2220 (2.41704 iter/s, 4.96476s/12 iters), loss = 5.28312 +I0410 13:46:28.342739 18534 solver.cpp:237] Train net output #0: loss = 5.28312 (* 1 = 5.28312 loss) +I0410 13:46:28.342747 18534 sgd_solver.cpp:105] Iteration 2220, lr = 0.00644197 +I0410 13:46:30.066275 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:46:33.157220 18534 solver.cpp:218] Iteration 2232 (2.49258 iter/s, 4.81428s/12 iters), loss = 5.28436 +I0410 13:46:33.157269 18534 solver.cpp:237] Train net output #0: loss = 5.28436 (* 1 = 5.28436 loss) +I0410 13:46:33.157277 18534 sgd_solver.cpp:105] Iteration 2232, lr = 0.00642668 +I0410 13:46:37.573470 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2244.caffemodel +I0410 13:46:37.885687 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2244.solverstate +I0410 13:46:38.097815 18534 solver.cpp:330] Iteration 2244, Testing net (#0) +I0410 13:46:38.097836 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:46:41.822669 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:46:42.728652 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:46:42.728691 18534 solver.cpp:397] Test net output #1: loss = 5.28652 (* 1 = 5.28652 loss) +I0410 13:46:42.810940 18534 solver.cpp:218] Iteration 2244 (1.2431 iter/s, 9.65329s/12 iters), loss = 5.27566 +I0410 13:46:42.810993 18534 solver.cpp:237] Train net output #0: loss = 5.27566 (* 1 = 5.27566 loss) +I0410 13:46:42.811002 18534 sgd_solver.cpp:105] Iteration 2244, lr = 0.00641142 +I0410 13:46:46.972930 18534 solver.cpp:218] Iteration 2256 (2.8834 iter/s, 4.16176s/12 iters), loss = 5.24245 +I0410 13:46:46.973021 18534 solver.cpp:237] Train net output #0: loss = 5.24245 (* 1 = 5.24245 loss) +I0410 13:46:46.973033 18534 sgd_solver.cpp:105] Iteration 2256, lr = 0.0063962 +I0410 13:46:51.905190 18534 solver.cpp:218] Iteration 2268 (2.43311 iter/s, 4.93197s/12 iters), loss = 5.28528 +I0410 13:46:51.905246 18534 solver.cpp:237] Train net output #0: loss = 5.28528 (* 1 = 5.28528 loss) +I0410 13:46:51.905257 18534 sgd_solver.cpp:105] Iteration 2268, lr = 0.00638101 +I0410 13:46:56.732141 18534 solver.cpp:218] Iteration 2280 (2.48617 iter/s, 4.8267s/12 iters), loss = 5.25228 +I0410 13:46:56.732197 18534 solver.cpp:237] Train net output #0: loss = 5.25228 (* 1 = 5.25228 loss) +I0410 13:46:56.732209 18534 sgd_solver.cpp:105] Iteration 2280, lr = 0.00636586 +I0410 13:47:01.681000 18534 solver.cpp:218] Iteration 2292 (2.42493 iter/s, 4.9486s/12 iters), loss = 5.27268 +I0410 13:47:01.681066 18534 solver.cpp:237] Train net output #0: loss = 5.27268 (* 1 = 5.27268 loss) +I0410 13:47:01.681079 18534 sgd_solver.cpp:105] Iteration 2292, lr = 0.00635075 +I0410 13:47:06.642146 18534 solver.cpp:218] Iteration 2304 (2.41892 iter/s, 4.96088s/12 iters), loss = 5.26897 +I0410 13:47:06.642189 18534 solver.cpp:237] Train net output #0: loss = 5.26897 (* 1 = 5.26897 loss) +I0410 13:47:06.642200 18534 sgd_solver.cpp:105] Iteration 2304, lr = 0.00633567 +I0410 13:47:11.588977 18534 solver.cpp:218] Iteration 2316 (2.42591 iter/s, 4.94659s/12 iters), loss = 5.26201 +I0410 13:47:11.589020 18534 solver.cpp:237] Train net output #0: loss = 5.26201 (* 1 = 5.26201 loss) +I0410 13:47:11.589027 18534 sgd_solver.cpp:105] Iteration 2316, lr = 0.00632063 +I0410 13:47:15.462493 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:16.492455 18534 solver.cpp:218] Iteration 2328 (2.44736 iter/s, 4.90323s/12 iters), loss = 5.25837 +I0410 13:47:16.492501 18534 solver.cpp:237] Train net output #0: loss = 5.25837 (* 1 = 5.25837 loss) +I0410 13:47:16.492511 18534 sgd_solver.cpp:105] Iteration 2328, lr = 0.00630562 +I0410 13:47:21.359845 18534 solver.cpp:218] Iteration 2340 (2.46551 iter/s, 4.86714s/12 iters), loss = 5.29248 +I0410 13:47:21.359975 18534 solver.cpp:237] Train net output #0: loss = 5.29248 (* 1 = 5.29248 loss) +I0410 13:47:21.359984 18534 sgd_solver.cpp:105] Iteration 2340, lr = 0.00629065 +I0410 13:47:23.344362 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2346.caffemodel +I0410 13:47:23.651834 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2346.solverstate +I0410 13:47:23.861552 18534 solver.cpp:330] Iteration 2346, Testing net (#0) +I0410 13:47:23.861573 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:47:27.476670 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:28.416282 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:47:28.416312 18534 solver.cpp:397] Test net output #1: loss = 5.28685 (* 1 = 5.28685 loss) +I0410 13:47:30.286339 18534 solver.cpp:218] Iteration 2352 (1.34439 iter/s, 8.92601s/12 iters), loss = 5.25741 +I0410 13:47:30.286387 18534 solver.cpp:237] Train net output #0: loss = 5.25741 (* 1 = 5.25741 loss) +I0410 13:47:30.286397 18534 sgd_solver.cpp:105] Iteration 2352, lr = 0.00627571 +I0410 13:47:35.157807 18534 solver.cpp:218] Iteration 2364 (2.46345 iter/s, 4.87122s/12 iters), loss = 5.30509 +I0410 13:47:35.157853 18534 solver.cpp:237] Train net output #0: loss = 5.30509 (* 1 = 5.30509 loss) +I0410 13:47:35.157862 18534 sgd_solver.cpp:105] Iteration 2364, lr = 0.00626081 +I0410 13:47:40.007349 18534 solver.cpp:218] Iteration 2376 (2.47459 iter/s, 4.8493s/12 iters), loss = 5.2617 +I0410 13:47:40.007398 18534 solver.cpp:237] Train net output #0: loss = 5.2617 (* 1 = 5.2617 loss) +I0410 13:47:40.007411 18534 sgd_solver.cpp:105] Iteration 2376, lr = 0.00624595 +I0410 13:47:44.850766 18534 solver.cpp:218] Iteration 2388 (2.47772 iter/s, 4.84317s/12 iters), loss = 5.27417 +I0410 13:47:44.850816 18534 solver.cpp:237] Train net output #0: loss = 5.27417 (* 1 = 5.27417 loss) +I0410 13:47:44.850827 18534 sgd_solver.cpp:105] Iteration 2388, lr = 0.00623112 +I0410 13:47:49.808379 18534 solver.cpp:218] Iteration 2400 (2.42064 iter/s, 4.95736s/12 iters), loss = 5.28426 +I0410 13:47:49.808434 18534 solver.cpp:237] Train net output #0: loss = 5.28426 (* 1 = 5.28426 loss) +I0410 13:47:49.808445 18534 sgd_solver.cpp:105] Iteration 2400, lr = 0.00621633 +I0410 13:47:54.645371 18534 solver.cpp:218] Iteration 2412 (2.48101 iter/s, 4.83674s/12 iters), loss = 5.27203 +I0410 13:47:54.645522 18534 solver.cpp:237] Train net output #0: loss = 5.27203 (* 1 = 5.27203 loss) +I0410 13:47:54.645534 18534 sgd_solver.cpp:105] Iteration 2412, lr = 0.00620157 +I0410 13:47:59.484714 18534 solver.cpp:218] Iteration 2424 (2.47986 iter/s, 4.83899s/12 iters), loss = 5.27404 +I0410 13:47:59.484766 18534 solver.cpp:237] Train net output #0: loss = 5.27404 (* 1 = 5.27404 loss) +I0410 13:47:59.484778 18534 sgd_solver.cpp:105] Iteration 2424, lr = 0.00618684 +I0410 13:48:00.523298 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:48:04.370589 18534 solver.cpp:218] Iteration 2436 (2.45619 iter/s, 4.88562s/12 iters), loss = 5.27835 +I0410 13:48:04.370635 18534 solver.cpp:237] Train net output #0: loss = 5.27835 (* 1 = 5.27835 loss) +I0410 13:48:04.370644 18534 sgd_solver.cpp:105] Iteration 2436, lr = 0.00617215 +I0410 13:48:08.786798 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2448.caffemodel +I0410 13:48:09.092365 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2448.solverstate +I0410 13:48:09.289813 18534 solver.cpp:330] Iteration 2448, Testing net (#0) +I0410 13:48:09.289832 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:48:12.764746 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:48:13.737673 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:48:13.737711 18534 solver.cpp:397] Test net output #1: loss = 5.28661 (* 1 = 5.28661 loss) +I0410 13:48:13.820058 18534 solver.cpp:218] Iteration 2448 (1.26997 iter/s, 9.44905s/12 iters), loss = 5.25639 +I0410 13:48:13.820104 18534 solver.cpp:237] Train net output #0: loss = 5.25639 (* 1 = 5.25639 loss) +I0410 13:48:13.820113 18534 sgd_solver.cpp:105] Iteration 2448, lr = 0.0061575 +I0410 13:48:17.818037 18534 solver.cpp:218] Iteration 2460 (3.00168 iter/s, 3.99777s/12 iters), loss = 5.26547 +I0410 13:48:17.818079 18534 solver.cpp:237] Train net output #0: loss = 5.26547 (* 1 = 5.26547 loss) +I0410 13:48:17.818089 18534 sgd_solver.cpp:105] Iteration 2460, lr = 0.00614288 +I0410 13:48:22.726689 18534 solver.cpp:218] Iteration 2472 (2.44479 iter/s, 4.9084s/12 iters), loss = 5.27031 +I0410 13:48:22.726747 18534 solver.cpp:237] Train net output #0: loss = 5.27031 (* 1 = 5.27031 loss) +I0410 13:48:22.726758 18534 sgd_solver.cpp:105] Iteration 2472, lr = 0.0061283 +I0410 13:48:27.657912 18534 solver.cpp:218] Iteration 2484 (2.4336 iter/s, 4.93096s/12 iters), loss = 5.2742 +I0410 13:48:27.658041 18534 solver.cpp:237] Train net output #0: loss = 5.2742 (* 1 = 5.2742 loss) +I0410 13:48:27.658056 18534 sgd_solver.cpp:105] Iteration 2484, lr = 0.00611375 +I0410 13:48:32.566123 18534 solver.cpp:218] Iteration 2496 (2.44505 iter/s, 4.90788s/12 iters), loss = 5.27137 +I0410 13:48:32.566164 18534 solver.cpp:237] Train net output #0: loss = 5.27137 (* 1 = 5.27137 loss) +I0410 13:48:32.566174 18534 sgd_solver.cpp:105] Iteration 2496, lr = 0.00609923 +I0410 13:48:37.438905 18534 solver.cpp:218] Iteration 2508 (2.46278 iter/s, 4.87254s/12 iters), loss = 5.28655 +I0410 13:48:37.438951 18534 solver.cpp:237] Train net output #0: loss = 5.28655 (* 1 = 5.28655 loss) +I0410 13:48:37.438961 18534 sgd_solver.cpp:105] Iteration 2508, lr = 0.00608475 +I0410 13:48:42.270000 18534 solver.cpp:218] Iteration 2520 (2.48404 iter/s, 4.83085s/12 iters), loss = 5.27688 +I0410 13:48:42.270042 18534 solver.cpp:237] Train net output #0: loss = 5.27688 (* 1 = 5.27688 loss) +I0410 13:48:42.270051 18534 sgd_solver.cpp:105] Iteration 2520, lr = 0.0060703 +I0410 13:48:45.393015 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:48:47.151089 18534 solver.cpp:218] Iteration 2532 (2.45859 iter/s, 4.88085s/12 iters), loss = 5.28173 +I0410 13:48:47.151134 18534 solver.cpp:237] Train net output #0: loss = 5.28173 (* 1 = 5.28173 loss) +I0410 13:48:47.151142 18534 sgd_solver.cpp:105] Iteration 2532, lr = 0.00605589 +I0410 13:48:52.059047 18534 solver.cpp:218] Iteration 2544 (2.44513 iter/s, 4.90771s/12 iters), loss = 5.27289 +I0410 13:48:52.059095 18534 solver.cpp:237] Train net output #0: loss = 5.27289 (* 1 = 5.27289 loss) +I0410 13:48:52.059104 18534 sgd_solver.cpp:105] Iteration 2544, lr = 0.00604151 +I0410 13:48:54.030054 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2550.caffemodel +I0410 13:48:55.469806 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2550.solverstate +I0410 13:48:55.920276 18534 solver.cpp:330] Iteration 2550, Testing net (#0) +I0410 13:48:55.920305 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:48:59.407665 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:00.428134 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:49:00.428184 18534 solver.cpp:397] Test net output #1: loss = 5.2865 (* 1 = 5.2865 loss) +I0410 13:49:02.315357 18534 solver.cpp:218] Iteration 2556 (1.17006 iter/s, 10.2558s/12 iters), loss = 5.28037 +I0410 13:49:02.315410 18534 solver.cpp:237] Train net output #0: loss = 5.28037 (* 1 = 5.28037 loss) +I0410 13:49:02.315421 18534 sgd_solver.cpp:105] Iteration 2556, lr = 0.00602717 +I0410 13:49:07.199365 18534 solver.cpp:218] Iteration 2568 (2.45712 iter/s, 4.88376s/12 iters), loss = 5.28386 +I0410 13:49:07.199412 18534 solver.cpp:237] Train net output #0: loss = 5.28386 (* 1 = 5.28386 loss) +I0410 13:49:07.199424 18534 sgd_solver.cpp:105] Iteration 2568, lr = 0.00601286 +I0410 13:49:12.251444 18534 solver.cpp:218] Iteration 2580 (2.37538 iter/s, 5.05182s/12 iters), loss = 5.27017 +I0410 13:49:12.251495 18534 solver.cpp:237] Train net output #0: loss = 5.27017 (* 1 = 5.27017 loss) +I0410 13:49:12.251507 18534 sgd_solver.cpp:105] Iteration 2580, lr = 0.00599858 +I0410 13:49:17.176956 18534 solver.cpp:218] Iteration 2592 (2.43642 iter/s, 4.92526s/12 iters), loss = 5.28825 +I0410 13:49:17.177002 18534 solver.cpp:237] Train net output #0: loss = 5.28825 (* 1 = 5.28825 loss) +I0410 13:49:17.177012 18534 sgd_solver.cpp:105] Iteration 2592, lr = 0.00598434 +I0410 13:49:22.086643 18534 solver.cpp:218] Iteration 2604 (2.44427 iter/s, 4.90944s/12 iters), loss = 5.25854 +I0410 13:49:22.086697 18534 solver.cpp:237] Train net output #0: loss = 5.25854 (* 1 = 5.25854 loss) +I0410 13:49:22.086710 18534 sgd_solver.cpp:105] Iteration 2604, lr = 0.00597013 +I0410 13:49:27.006229 18534 solver.cpp:218] Iteration 2616 (2.43936 iter/s, 4.91933s/12 iters), loss = 5.28425 +I0410 13:49:27.006273 18534 solver.cpp:237] Train net output #0: loss = 5.28425 (* 1 = 5.28425 loss) +I0410 13:49:27.006281 18534 sgd_solver.cpp:105] Iteration 2616, lr = 0.00595596 +I0410 13:49:31.911867 18534 solver.cpp:218] Iteration 2628 (2.44629 iter/s, 4.90539s/12 iters), loss = 5.27786 +I0410 13:49:31.911993 18534 solver.cpp:237] Train net output #0: loss = 5.27786 (* 1 = 5.27786 loss) +I0410 13:49:31.912004 18534 sgd_solver.cpp:105] Iteration 2628, lr = 0.00594182 +I0410 13:49:32.349289 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:36.903359 18534 solver.cpp:218] Iteration 2640 (2.40425 iter/s, 4.99116s/12 iters), loss = 5.27955 +I0410 13:49:36.903414 18534 solver.cpp:237] Train net output #0: loss = 5.27955 (* 1 = 5.27955 loss) +I0410 13:49:36.903426 18534 sgd_solver.cpp:105] Iteration 2640, lr = 0.00592771 +I0410 13:49:41.390265 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2652.caffemodel +I0410 13:49:41.717594 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2652.solverstate +I0410 13:49:41.932211 18534 solver.cpp:330] Iteration 2652, Testing net (#0) +I0410 13:49:41.932231 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:49:45.235688 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:46.288867 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:49:46.288918 18534 solver.cpp:397] Test net output #1: loss = 5.28672 (* 1 = 5.28672 loss) +I0410 13:49:46.371248 18534 solver.cpp:218] Iteration 2652 (1.2675 iter/s, 9.46746s/12 iters), loss = 5.2716 +I0410 13:49:46.371294 18534 solver.cpp:237] Train net output #0: loss = 5.2716 (* 1 = 5.2716 loss) +I0410 13:49:46.371305 18534 sgd_solver.cpp:105] Iteration 2652, lr = 0.00591364 +I0410 13:49:50.519181 18534 solver.cpp:218] Iteration 2664 (2.89316 iter/s, 4.14772s/12 iters), loss = 5.28109 +I0410 13:49:50.519234 18534 solver.cpp:237] Train net output #0: loss = 5.28109 (* 1 = 5.28109 loss) +I0410 13:49:50.519246 18534 sgd_solver.cpp:105] Iteration 2664, lr = 0.0058996 +I0410 13:49:55.353940 18534 solver.cpp:218] Iteration 2676 (2.48216 iter/s, 4.8345s/12 iters), loss = 5.26909 +I0410 13:49:55.354005 18534 solver.cpp:237] Train net output #0: loss = 5.26909 (* 1 = 5.26909 loss) +I0410 13:49:55.354014 18534 sgd_solver.cpp:105] Iteration 2676, lr = 0.00588559 +I0410 13:50:00.256740 18534 solver.cpp:218] Iteration 2688 (2.44771 iter/s, 4.90253s/12 iters), loss = 5.25793 +I0410 13:50:00.256788 18534 solver.cpp:237] Train net output #0: loss = 5.25793 (* 1 = 5.25793 loss) +I0410 13:50:00.256799 18534 sgd_solver.cpp:105] Iteration 2688, lr = 0.00587162 +I0410 13:50:05.194787 18534 solver.cpp:218] Iteration 2700 (2.43023 iter/s, 4.9378s/12 iters), loss = 5.27926 +I0410 13:50:05.194943 18534 solver.cpp:237] Train net output #0: loss = 5.27926 (* 1 = 5.27926 loss) +I0410 13:50:05.194954 18534 sgd_solver.cpp:105] Iteration 2700, lr = 0.00585768 +I0410 13:50:10.079912 18534 solver.cpp:218] Iteration 2712 (2.45661 iter/s, 4.88477s/12 iters), loss = 5.28214 +I0410 13:50:10.079954 18534 solver.cpp:237] Train net output #0: loss = 5.28214 (* 1 = 5.28214 loss) +I0410 13:50:10.079962 18534 sgd_solver.cpp:105] Iteration 2712, lr = 0.00584377 +I0410 13:50:14.998870 18534 solver.cpp:218] Iteration 2724 (2.43966 iter/s, 4.91871s/12 iters), loss = 5.25766 +I0410 13:50:14.998917 18534 solver.cpp:237] Train net output #0: loss = 5.25766 (* 1 = 5.25766 loss) +I0410 13:50:14.998926 18534 sgd_solver.cpp:105] Iteration 2724, lr = 0.0058299 +I0410 13:50:17.532485 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:19.906102 18534 solver.cpp:218] Iteration 2736 (2.4455 iter/s, 4.90698s/12 iters), loss = 5.28042 +I0410 13:50:19.906160 18534 solver.cpp:237] Train net output #0: loss = 5.28042 (* 1 = 5.28042 loss) +I0410 13:50:19.906172 18534 sgd_solver.cpp:105] Iteration 2736, lr = 0.00581605 +I0410 13:50:24.858215 18534 solver.cpp:218] Iteration 2748 (2.42334 iter/s, 4.95185s/12 iters), loss = 5.2766 +I0410 13:50:24.858274 18534 solver.cpp:237] Train net output #0: loss = 5.2766 (* 1 = 5.2766 loss) +I0410 13:50:24.858287 18534 sgd_solver.cpp:105] Iteration 2748, lr = 0.00580225 +I0410 13:50:26.820363 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2754.caffemodel +I0410 13:50:27.944939 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2754.solverstate +I0410 13:50:28.333932 18534 solver.cpp:330] Iteration 2754, Testing net (#0) +I0410 13:50:28.333981 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:50:31.131075 18534 blocking_queue.cpp:49] Waiting for data +I0410 13:50:31.730337 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:33.049293 18534 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:50:33.049343 18534 solver.cpp:397] Test net output #1: loss = 5.28656 (* 1 = 5.28656 loss) +I0410 13:50:34.845121 18534 solver.cpp:218] Iteration 2760 (1.20163 iter/s, 9.98645s/12 iters), loss = 5.27607 +I0410 13:50:34.845176 18534 solver.cpp:237] Train net output #0: loss = 5.27607 (* 1 = 5.27607 loss) +I0410 13:50:34.845188 18534 sgd_solver.cpp:105] Iteration 2760, lr = 0.00578847 +I0410 13:50:39.731323 18534 solver.cpp:218] Iteration 2772 (2.45601 iter/s, 4.88597s/12 iters), loss = 5.27817 +I0410 13:50:39.734297 18534 solver.cpp:237] Train net output #0: loss = 5.27817 (* 1 = 5.27817 loss) +I0410 13:50:39.734310 18534 sgd_solver.cpp:105] Iteration 2772, lr = 0.00577473 +I0410 13:50:44.596092 18534 solver.cpp:218] Iteration 2784 (2.4683 iter/s, 4.86165s/12 iters), loss = 5.27476 +I0410 13:50:44.596148 18534 solver.cpp:237] Train net output #0: loss = 5.27476 (* 1 = 5.27476 loss) +I0410 13:50:44.596158 18534 sgd_solver.cpp:105] Iteration 2784, lr = 0.00576102 +I0410 13:50:49.477886 18534 solver.cpp:218] Iteration 2796 (2.45822 iter/s, 4.88158s/12 iters), loss = 5.27196 +I0410 13:50:49.477937 18534 solver.cpp:237] Train net output #0: loss = 5.27196 (* 1 = 5.27196 loss) +I0410 13:50:49.477947 18534 sgd_solver.cpp:105] Iteration 2796, lr = 0.00574734 +I0410 13:50:54.403802 18534 solver.cpp:218] Iteration 2808 (2.4362 iter/s, 4.92571s/12 iters), loss = 5.26155 +I0410 13:50:54.403842 18534 solver.cpp:237] Train net output #0: loss = 5.26155 (* 1 = 5.26155 loss) +I0410 13:50:54.403851 18534 sgd_solver.cpp:105] Iteration 2808, lr = 0.00573369 +I0410 13:50:59.278251 18534 solver.cpp:218] Iteration 2820 (2.46192 iter/s, 4.87425s/12 iters), loss = 5.27682 +I0410 13:50:59.278295 18534 solver.cpp:237] Train net output #0: loss = 5.27682 (* 1 = 5.27682 loss) +I0410 13:50:59.278303 18534 sgd_solver.cpp:105] Iteration 2820, lr = 0.00572008 +I0410 13:51:03.935477 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:51:04.222401 18534 solver.cpp:218] Iteration 2832 (2.42737 iter/s, 4.94362s/12 iters), loss = 5.26175 +I0410 13:51:04.222458 18534 solver.cpp:237] Train net output #0: loss = 5.26175 (* 1 = 5.26175 loss) +I0410 13:51:04.222470 18534 sgd_solver.cpp:105] Iteration 2832, lr = 0.0057065 +I0410 13:51:09.158187 18534 solver.cpp:218] Iteration 2844 (2.43133 iter/s, 4.93557s/12 iters), loss = 5.26725 +I0410 13:51:09.158246 18534 solver.cpp:237] Train net output #0: loss = 5.26725 (* 1 = 5.26725 loss) +I0410 13:51:09.158258 18534 sgd_solver.cpp:105] Iteration 2844, lr = 0.00569295 +I0410 13:51:13.581038 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2856.caffemodel +I0410 13:51:13.995906 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2856.solverstate +I0410 13:51:14.208585 18534 solver.cpp:330] Iteration 2856, Testing net (#0) +I0410 13:51:14.208613 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:51:17.513069 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:51:18.649106 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:51:18.649155 18534 solver.cpp:397] Test net output #1: loss = 5.28682 (* 1 = 5.28682 loss) +I0410 13:51:18.731928 18534 solver.cpp:218] Iteration 2856 (1.25347 iter/s, 9.57339s/12 iters), loss = 5.28775 +I0410 13:51:18.731983 18534 solver.cpp:237] Train net output #0: loss = 5.28775 (* 1 = 5.28775 loss) +I0410 13:51:18.731994 18534 sgd_solver.cpp:105] Iteration 2856, lr = 0.00567944 +I0410 13:51:22.875000 18534 solver.cpp:218] Iteration 2868 (2.89653 iter/s, 4.14289s/12 iters), loss = 5.28143 +I0410 13:51:22.875041 18534 solver.cpp:237] Train net output #0: loss = 5.28143 (* 1 = 5.28143 loss) +I0410 13:51:22.875048 18534 sgd_solver.cpp:105] Iteration 2868, lr = 0.00566595 +I0410 13:51:27.755273 18534 solver.cpp:218] Iteration 2880 (2.45898 iter/s, 4.88008s/12 iters), loss = 5.27903 +I0410 13:51:27.755321 18534 solver.cpp:237] Train net output #0: loss = 5.27903 (* 1 = 5.27903 loss) +I0410 13:51:27.755328 18534 sgd_solver.cpp:105] Iteration 2880, lr = 0.0056525 +I0410 13:51:32.787595 18534 solver.cpp:218] Iteration 2892 (2.38468 iter/s, 5.03211s/12 iters), loss = 5.27356 +I0410 13:51:32.787643 18534 solver.cpp:237] Train net output #0: loss = 5.27356 (* 1 = 5.27356 loss) +I0410 13:51:32.787653 18534 sgd_solver.cpp:105] Iteration 2892, lr = 0.00563908 +I0410 13:51:37.711936 18534 solver.cpp:218] Iteration 2904 (2.43698 iter/s, 4.92413s/12 iters), loss = 5.25599 +I0410 13:51:37.711987 18534 solver.cpp:237] Train net output #0: loss = 5.25599 (* 1 = 5.25599 loss) +I0410 13:51:37.711998 18534 sgd_solver.cpp:105] Iteration 2904, lr = 0.00562569 +I0410 13:51:42.824540 18534 solver.cpp:218] Iteration 2916 (2.34724 iter/s, 5.11239s/12 iters), loss = 5.27277 +I0410 13:51:42.824592 18534 solver.cpp:237] Train net output #0: loss = 5.27277 (* 1 = 5.27277 loss) +I0410 13:51:42.824604 18534 sgd_solver.cpp:105] Iteration 2916, lr = 0.00561233 +I0410 13:51:47.748306 18534 solver.cpp:218] Iteration 2928 (2.43726 iter/s, 4.92355s/12 iters), loss = 5.27804 +I0410 13:51:47.748435 18534 solver.cpp:237] Train net output #0: loss = 5.27804 (* 1 = 5.27804 loss) +I0410 13:51:47.748445 18534 sgd_solver.cpp:105] Iteration 2928, lr = 0.00559901 +I0410 13:51:49.553267 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:51:52.669625 18534 solver.cpp:218] Iteration 2940 (2.43851 iter/s, 4.92103s/12 iters), loss = 5.28208 +I0410 13:51:52.669672 18534 solver.cpp:237] Train net output #0: loss = 5.28208 (* 1 = 5.28208 loss) +I0410 13:51:52.669682 18534 sgd_solver.cpp:105] Iteration 2940, lr = 0.00558572 +I0410 13:51:57.598073 18534 solver.cpp:218] Iteration 2952 (2.43495 iter/s, 4.92824s/12 iters), loss = 5.28108 +I0410 13:51:57.598116 18534 solver.cpp:237] Train net output #0: loss = 5.28108 (* 1 = 5.28108 loss) +I0410 13:51:57.598125 18534 sgd_solver.cpp:105] Iteration 2952, lr = 0.00557245 +I0410 13:51:59.564602 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2958.caffemodel +I0410 13:51:59.854683 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2958.solverstate +I0410 13:52:00.051337 18534 solver.cpp:330] Iteration 2958, Testing net (#0) +I0410 13:52:00.051355 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:52:03.535028 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:52:04.711851 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:52:04.711900 18534 solver.cpp:397] Test net output #1: loss = 5.28655 (* 1 = 5.28655 loss) +I0410 13:52:06.444269 18534 solver.cpp:218] Iteration 2964 (1.35656 iter/s, 8.84588s/12 iters), loss = 5.24114 +I0410 13:52:06.444325 18534 solver.cpp:237] Train net output #0: loss = 5.24114 (* 1 = 5.24114 loss) +I0410 13:52:06.444336 18534 sgd_solver.cpp:105] Iteration 2964, lr = 0.00555922 +I0410 13:52:11.304877 18534 solver.cpp:218] Iteration 2976 (2.46894 iter/s, 4.8604s/12 iters), loss = 5.28295 +I0410 13:52:11.304929 18534 solver.cpp:237] Train net output #0: loss = 5.28295 (* 1 = 5.28295 loss) +I0410 13:52:11.304940 18534 sgd_solver.cpp:105] Iteration 2976, lr = 0.00554603 +I0410 13:52:16.217334 18534 solver.cpp:218] Iteration 2988 (2.44287 iter/s, 4.91225s/12 iters), loss = 5.26275 +I0410 13:52:16.217375 18534 solver.cpp:237] Train net output #0: loss = 5.26275 (* 1 = 5.26275 loss) +I0410 13:52:16.217384 18534 sgd_solver.cpp:105] Iteration 2988, lr = 0.00553286 +I0410 13:52:21.063481 18534 solver.cpp:218] Iteration 3000 (2.4763 iter/s, 4.84594s/12 iters), loss = 5.26714 +I0410 13:52:21.063587 18534 solver.cpp:237] Train net output #0: loss = 5.26714 (* 1 = 5.26714 loss) +I0410 13:52:21.063598 18534 sgd_solver.cpp:105] Iteration 3000, lr = 0.00551972 +I0410 13:52:25.877792 18534 solver.cpp:218] Iteration 3012 (2.4927 iter/s, 4.81405s/12 iters), loss = 5.27472 +I0410 13:52:25.877837 18534 solver.cpp:237] Train net output #0: loss = 5.27472 (* 1 = 5.27472 loss) +I0410 13:52:25.877847 18534 sgd_solver.cpp:105] Iteration 3012, lr = 0.00550662 +I0410 13:52:30.778385 18534 solver.cpp:218] Iteration 3024 (2.44879 iter/s, 4.90039s/12 iters), loss = 5.25925 +I0410 13:52:30.778434 18534 solver.cpp:237] Train net output #0: loss = 5.25925 (* 1 = 5.25925 loss) +I0410 13:52:30.778443 18534 sgd_solver.cpp:105] Iteration 3024, lr = 0.00549354 +I0410 13:52:34.676970 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:52:35.671218 18534 solver.cpp:218] Iteration 3036 (2.45267 iter/s, 4.89262s/12 iters), loss = 5.25829 +I0410 13:52:35.671270 18534 solver.cpp:237] Train net output #0: loss = 5.25829 (* 1 = 5.25829 loss) +I0410 13:52:35.671281 18534 sgd_solver.cpp:105] Iteration 3036, lr = 0.0054805 +I0410 13:52:40.526640 18534 solver.cpp:218] Iteration 3048 (2.47157 iter/s, 4.85521s/12 iters), loss = 5.29219 +I0410 13:52:40.526695 18534 solver.cpp:237] Train net output #0: loss = 5.29219 (* 1 = 5.29219 loss) +I0410 13:52:40.526706 18534 sgd_solver.cpp:105] Iteration 3048, lr = 0.00546749 +I0410 13:52:44.937613 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3060.caffemodel +I0410 13:52:46.369163 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3060.solverstate +I0410 13:52:47.555792 18534 solver.cpp:330] Iteration 3060, Testing net (#0) +I0410 13:52:47.555819 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:52:50.815780 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:52:52.042230 18534 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:52:52.042393 18534 solver.cpp:397] Test net output #1: loss = 5.28637 (* 1 = 5.28637 loss) +I0410 13:52:52.128418 18534 solver.cpp:218] Iteration 3060 (1.03436 iter/s, 11.6014s/12 iters), loss = 5.2571 +I0410 13:52:52.128473 18534 solver.cpp:237] Train net output #0: loss = 5.2571 (* 1 = 5.2571 loss) +I0410 13:52:52.128484 18534 sgd_solver.cpp:105] Iteration 3060, lr = 0.00545451 +I0410 13:52:56.365445 18534 solver.cpp:218] Iteration 3072 (2.83231 iter/s, 4.23683s/12 iters), loss = 5.30645 +I0410 13:52:56.365504 18534 solver.cpp:237] Train net output #0: loss = 5.30645 (* 1 = 5.30645 loss) +I0410 13:52:56.365516 18534 sgd_solver.cpp:105] Iteration 3072, lr = 0.00544156 +I0410 13:53:01.333005 18534 solver.cpp:218] Iteration 3084 (2.41578 iter/s, 4.96734s/12 iters), loss = 5.27315 +I0410 13:53:01.333053 18534 solver.cpp:237] Train net output #0: loss = 5.27315 (* 1 = 5.27315 loss) +I0410 13:53:01.333062 18534 sgd_solver.cpp:105] Iteration 3084, lr = 0.00542864 +I0410 13:53:06.195055 18534 solver.cpp:218] Iteration 3096 (2.4682 iter/s, 4.86184s/12 iters), loss = 5.27319 +I0410 13:53:06.195108 18534 solver.cpp:237] Train net output #0: loss = 5.27319 (* 1 = 5.27319 loss) +I0410 13:53:06.195119 18534 sgd_solver.cpp:105] Iteration 3096, lr = 0.00541575 +I0410 13:53:11.138078 18534 solver.cpp:218] Iteration 3108 (2.42777 iter/s, 4.9428s/12 iters), loss = 5.27974 +I0410 13:53:11.138130 18534 solver.cpp:237] Train net output #0: loss = 5.27974 (* 1 = 5.27974 loss) +I0410 13:53:11.138140 18534 sgd_solver.cpp:105] Iteration 3108, lr = 0.00540289 +I0410 13:53:16.007977 18534 solver.cpp:218] Iteration 3120 (2.46422 iter/s, 4.86969s/12 iters), loss = 5.26781 +I0410 13:53:16.008021 18534 solver.cpp:237] Train net output #0: loss = 5.26781 (* 1 = 5.26781 loss) +I0410 13:53:16.008031 18534 sgd_solver.cpp:105] Iteration 3120, lr = 0.00539006 +I0410 13:53:20.886519 18534 solver.cpp:218] Iteration 3132 (2.45986 iter/s, 4.87833s/12 iters), loss = 5.27547 +I0410 13:53:20.886574 18534 solver.cpp:237] Train net output #0: loss = 5.27547 (* 1 = 5.27547 loss) +I0410 13:53:20.886586 18534 sgd_solver.cpp:105] Iteration 3132, lr = 0.00537727 +I0410 13:53:21.961688 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:25.735515 18534 solver.cpp:218] Iteration 3144 (2.47485 iter/s, 4.84878s/12 iters), loss = 5.28116 +I0410 13:53:25.735637 18534 solver.cpp:237] Train net output #0: loss = 5.28116 (* 1 = 5.28116 loss) +I0410 13:53:25.735652 18534 sgd_solver.cpp:105] Iteration 3144, lr = 0.0053645 +I0410 13:53:30.601389 18534 solver.cpp:218] Iteration 3156 (2.4663 iter/s, 4.86559s/12 iters), loss = 5.25061 +I0410 13:53:30.601438 18534 solver.cpp:237] Train net output #0: loss = 5.25061 (* 1 = 5.25061 loss) +I0410 13:53:30.601446 18534 sgd_solver.cpp:105] Iteration 3156, lr = 0.00535176 +I0410 13:53:32.575497 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3162.caffemodel +I0410 13:53:32.903156 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3162.solverstate +I0410 13:53:33.115986 18534 solver.cpp:330] Iteration 3162, Testing net (#0) +I0410 13:53:33.116004 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:53:36.406147 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:37.667325 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:53:37.667374 18534 solver.cpp:397] Test net output #1: loss = 5.28654 (* 1 = 5.28654 loss) +I0410 13:53:39.474241 18534 solver.cpp:218] Iteration 3168 (1.35249 iter/s, 8.87251s/12 iters), loss = 5.26818 +I0410 13:53:39.474298 18534 solver.cpp:237] Train net output #0: loss = 5.26818 (* 1 = 5.26818 loss) +I0410 13:53:39.474310 18534 sgd_solver.cpp:105] Iteration 3168, lr = 0.00533906 +I0410 13:53:44.561215 18534 solver.cpp:218] Iteration 3180 (2.35907 iter/s, 5.08675s/12 iters), loss = 5.27377 +I0410 13:53:44.561259 18534 solver.cpp:237] Train net output #0: loss = 5.27377 (* 1 = 5.27377 loss) +I0410 13:53:44.561269 18534 sgd_solver.cpp:105] Iteration 3180, lr = 0.00532638 +I0410 13:53:49.435550 18534 solver.cpp:218] Iteration 3192 (2.46198 iter/s, 4.87412s/12 iters), loss = 5.27766 +I0410 13:53:49.435604 18534 solver.cpp:237] Train net output #0: loss = 5.27766 (* 1 = 5.27766 loss) +I0410 13:53:49.435616 18534 sgd_solver.cpp:105] Iteration 3192, lr = 0.00531374 +I0410 13:53:54.327687 18534 solver.cpp:218] Iteration 3204 (2.45303 iter/s, 4.89192s/12 iters), loss = 5.26376 +I0410 13:53:54.327736 18534 solver.cpp:237] Train net output #0: loss = 5.26376 (* 1 = 5.26376 loss) +I0410 13:53:54.327747 18534 sgd_solver.cpp:105] Iteration 3204, lr = 0.00530112 +I0410 13:53:59.210074 18534 solver.cpp:218] Iteration 3216 (2.45792 iter/s, 4.88217s/12 iters), loss = 5.29043 +I0410 13:53:59.210201 18534 solver.cpp:237] Train net output #0: loss = 5.29043 (* 1 = 5.29043 loss) +I0410 13:53:59.210209 18534 sgd_solver.cpp:105] Iteration 3216, lr = 0.00528853 +I0410 13:54:04.109467 18534 solver.cpp:218] Iteration 3228 (2.44943 iter/s, 4.8991s/12 iters), loss = 5.27741 +I0410 13:54:04.109516 18534 solver.cpp:237] Train net output #0: loss = 5.27741 (* 1 = 5.27741 loss) +I0410 13:54:04.109527 18534 sgd_solver.cpp:105] Iteration 3228, lr = 0.00527598 +I0410 13:54:07.289515 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:54:08.996781 18534 solver.cpp:218] Iteration 3240 (2.45544 iter/s, 4.8871s/12 iters), loss = 5.27958 +I0410 13:54:08.996834 18534 solver.cpp:237] Train net output #0: loss = 5.27958 (* 1 = 5.27958 loss) +I0410 13:54:08.996846 18534 sgd_solver.cpp:105] Iteration 3240, lr = 0.00526345 +I0410 13:54:13.854673 18534 solver.cpp:218] Iteration 3252 (2.47032 iter/s, 4.85767s/12 iters), loss = 5.27332 +I0410 13:54:13.854722 18534 solver.cpp:237] Train net output #0: loss = 5.27332 (* 1 = 5.27332 loss) +I0410 13:54:13.854730 18534 sgd_solver.cpp:105] Iteration 3252, lr = 0.00525095 +I0410 13:54:18.331359 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3264.caffemodel +I0410 13:54:18.648033 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3264.solverstate +I0410 13:54:18.852330 18534 solver.cpp:330] Iteration 3264, Testing net (#0) +I0410 13:54:18.852360 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:54:22.073942 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:54:23.464251 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:54:23.464301 18534 solver.cpp:397] Test net output #1: loss = 5.28706 (* 1 = 5.28706 loss) +I0410 13:54:23.545702 18534 solver.cpp:218] Iteration 3264 (1.23831 iter/s, 9.69066s/12 iters), loss = 5.27891 +I0410 13:54:23.545753 18534 solver.cpp:237] Train net output #0: loss = 5.27891 (* 1 = 5.27891 loss) +I0410 13:54:23.545764 18534 sgd_solver.cpp:105] Iteration 3264, lr = 0.00523849 +I0410 13:54:27.519101 18534 solver.cpp:218] Iteration 3276 (3.02023 iter/s, 3.97321s/12 iters), loss = 5.29063 +I0410 13:54:27.519140 18534 solver.cpp:237] Train net output #0: loss = 5.29063 (* 1 = 5.29063 loss) +I0410 13:54:27.519148 18534 sgd_solver.cpp:105] Iteration 3276, lr = 0.00522605 +I0410 13:54:32.681118 18534 solver.cpp:218] Iteration 3288 (2.32477 iter/s, 5.1618s/12 iters), loss = 5.26022 +I0410 13:54:32.681232 18534 solver.cpp:237] Train net output #0: loss = 5.26022 (* 1 = 5.26022 loss) +I0410 13:54:32.681244 18534 sgd_solver.cpp:105] Iteration 3288, lr = 0.00521364 +I0410 13:54:37.611120 18534 solver.cpp:218] Iteration 3300 (2.43421 iter/s, 4.92972s/12 iters), loss = 5.28152 +I0410 13:54:37.611160 18534 solver.cpp:237] Train net output #0: loss = 5.28152 (* 1 = 5.28152 loss) +I0410 13:54:37.611171 18534 sgd_solver.cpp:105] Iteration 3300, lr = 0.00520126 +I0410 13:54:42.682767 18534 solver.cpp:218] Iteration 3312 (2.3662 iter/s, 5.07143s/12 iters), loss = 5.25691 +I0410 13:54:42.682818 18534 solver.cpp:237] Train net output #0: loss = 5.25691 (* 1 = 5.25691 loss) +I0410 13:54:42.682830 18534 sgd_solver.cpp:105] Iteration 3312, lr = 0.00518892 +I0410 13:54:47.633766 18534 solver.cpp:218] Iteration 3324 (2.42386 iter/s, 4.95078s/12 iters), loss = 5.28168 +I0410 13:54:47.633822 18534 solver.cpp:237] Train net output #0: loss = 5.28168 (* 1 = 5.28168 loss) +I0410 13:54:47.633834 18534 sgd_solver.cpp:105] Iteration 3324, lr = 0.0051766 +I0410 13:54:52.568141 18534 solver.cpp:218] Iteration 3336 (2.43203 iter/s, 4.93415s/12 iters), loss = 5.27565 +I0410 13:54:52.568182 18534 solver.cpp:237] Train net output #0: loss = 5.27565 (* 1 = 5.27565 loss) +I0410 13:54:52.568192 18534 sgd_solver.cpp:105] Iteration 3336, lr = 0.00516431 +I0410 13:54:53.042114 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:54:57.530052 18534 solver.cpp:218] Iteration 3348 (2.41853 iter/s, 4.9617s/12 iters), loss = 5.27632 +I0410 13:54:57.530107 18534 solver.cpp:237] Train net output #0: loss = 5.27632 (* 1 = 5.27632 loss) +I0410 13:54:57.530118 18534 sgd_solver.cpp:105] Iteration 3348, lr = 0.00515204 +I0410 13:55:02.408170 18534 solver.cpp:218] Iteration 3360 (2.46008 iter/s, 4.87789s/12 iters), loss = 5.26746 +I0410 13:55:02.408226 18534 solver.cpp:237] Train net output #0: loss = 5.26746 (* 1 = 5.26746 loss) +I0410 13:55:02.408237 18534 sgd_solver.cpp:105] Iteration 3360, lr = 0.00513981 +I0410 13:55:04.385883 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3366.caffemodel +I0410 13:55:04.713044 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3366.solverstate +I0410 13:55:04.924924 18534 solver.cpp:330] Iteration 3366, Testing net (#0) +I0410 13:55:04.924954 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:55:08.093315 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:55:09.423844 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:55:09.423889 18534 solver.cpp:397] Test net output #1: loss = 5.28673 (* 1 = 5.28673 loss) +I0410 13:55:11.288753 18534 solver.cpp:218] Iteration 3372 (1.35132 iter/s, 8.88023s/12 iters), loss = 5.28676 +I0410 13:55:11.288801 18534 solver.cpp:237] Train net output #0: loss = 5.28676 (* 1 = 5.28676 loss) +I0410 13:55:11.288810 18534 sgd_solver.cpp:105] Iteration 3372, lr = 0.00512761 +I0410 13:55:16.247691 18534 solver.cpp:218] Iteration 3384 (2.41998 iter/s, 4.95872s/12 iters), loss = 5.26803 +I0410 13:55:16.247742 18534 solver.cpp:237] Train net output #0: loss = 5.26803 (* 1 = 5.26803 loss) +I0410 13:55:16.247753 18534 sgd_solver.cpp:105] Iteration 3384, lr = 0.00511544 +I0410 13:55:21.186200 18534 solver.cpp:218] Iteration 3396 (2.43 iter/s, 4.93828s/12 iters), loss = 5.26322 +I0410 13:55:21.186257 18534 solver.cpp:237] Train net output #0: loss = 5.26322 (* 1 = 5.26322 loss) +I0410 13:55:21.186269 18534 sgd_solver.cpp:105] Iteration 3396, lr = 0.00510329 +I0410 13:55:26.064620 18534 solver.cpp:218] Iteration 3408 (2.45993 iter/s, 4.87818s/12 iters), loss = 5.28842 +I0410 13:55:26.064680 18534 solver.cpp:237] Train net output #0: loss = 5.28842 (* 1 = 5.28842 loss) +I0410 13:55:26.064692 18534 sgd_solver.cpp:105] Iteration 3408, lr = 0.00509117 +I0410 13:55:31.097153 18534 solver.cpp:218] Iteration 3420 (2.3846 iter/s, 5.0323s/12 iters), loss = 5.27726 +I0410 13:55:31.097204 18534 solver.cpp:237] Train net output #0: loss = 5.27726 (* 1 = 5.27726 loss) +I0410 13:55:31.097215 18534 sgd_solver.cpp:105] Iteration 3420, lr = 0.00507909 +I0410 13:55:35.930235 18534 solver.cpp:218] Iteration 3432 (2.483 iter/s, 4.83286s/12 iters), loss = 5.25867 +I0410 13:55:35.936615 18534 solver.cpp:237] Train net output #0: loss = 5.25867 (* 1 = 5.25867 loss) +I0410 13:55:35.936628 18534 sgd_solver.cpp:105] Iteration 3432, lr = 0.00506703 +I0410 13:55:38.459511 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:55:40.840502 18534 solver.cpp:218] Iteration 3444 (2.44712 iter/s, 4.90372s/12 iters), loss = 5.27741 +I0410 13:55:40.840554 18534 solver.cpp:237] Train net output #0: loss = 5.27741 (* 1 = 5.27741 loss) +I0410 13:55:40.840567 18534 sgd_solver.cpp:105] Iteration 3444, lr = 0.005055 +I0410 13:55:45.750393 18534 solver.cpp:218] Iteration 3456 (2.44416 iter/s, 4.90967s/12 iters), loss = 5.27324 +I0410 13:55:45.750447 18534 solver.cpp:237] Train net output #0: loss = 5.27324 (* 1 = 5.27324 loss) +I0410 13:55:45.750459 18534 sgd_solver.cpp:105] Iteration 3456, lr = 0.005043 +I0410 13:55:50.177436 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3468.caffemodel +I0410 13:55:51.559549 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3468.solverstate +I0410 13:55:52.828866 18534 solver.cpp:330] Iteration 3468, Testing net (#0) +I0410 13:55:52.828888 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:55:52.852106 18534 blocking_queue.cpp:49] Waiting for data +I0410 13:55:55.897608 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:55:57.273559 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:55:57.273602 18534 solver.cpp:397] Test net output #1: loss = 5.28695 (* 1 = 5.28695 loss) +I0410 13:55:57.356009 18534 solver.cpp:218] Iteration 3468 (1.03402 iter/s, 11.6052s/12 iters), loss = 5.27228 +I0410 13:55:57.356058 18534 solver.cpp:237] Train net output #0: loss = 5.27228 (* 1 = 5.27228 loss) +I0410 13:55:57.356068 18534 sgd_solver.cpp:105] Iteration 3468, lr = 0.00503102 +I0410 13:56:01.548080 18534 solver.cpp:218] Iteration 3480 (2.86268 iter/s, 4.19187s/12 iters), loss = 5.27969 +I0410 13:56:01.548125 18534 solver.cpp:237] Train net output #0: loss = 5.27969 (* 1 = 5.27969 loss) +I0410 13:56:01.548135 18534 sgd_solver.cpp:105] Iteration 3480, lr = 0.00501908 +I0410 13:56:06.452253 18534 solver.cpp:218] Iteration 3492 (2.447 iter/s, 4.90396s/12 iters), loss = 5.29013 +I0410 13:56:06.452379 18534 solver.cpp:237] Train net output #0: loss = 5.29013 (* 1 = 5.29013 loss) +I0410 13:56:06.452391 18534 sgd_solver.cpp:105] Iteration 3492, lr = 0.00500716 +I0410 13:56:11.352530 18534 solver.cpp:218] Iteration 3504 (2.44899 iter/s, 4.89998s/12 iters), loss = 5.27107 +I0410 13:56:11.352581 18534 solver.cpp:237] Train net output #0: loss = 5.27107 (* 1 = 5.27107 loss) +I0410 13:56:11.352592 18534 sgd_solver.cpp:105] Iteration 3504, lr = 0.00499527 +I0410 13:56:16.285550 18534 solver.cpp:218] Iteration 3516 (2.4327 iter/s, 4.9328s/12 iters), loss = 5.26419 +I0410 13:56:16.285595 18534 solver.cpp:237] Train net output #0: loss = 5.26419 (* 1 = 5.26419 loss) +I0410 13:56:16.285604 18534 sgd_solver.cpp:105] Iteration 3516, lr = 0.00498341 +I0410 13:56:21.198030 18534 solver.cpp:218] Iteration 3528 (2.44287 iter/s, 4.91226s/12 iters), loss = 5.27082 +I0410 13:56:21.198086 18534 solver.cpp:237] Train net output #0: loss = 5.27082 (* 1 = 5.27082 loss) +I0410 13:56:21.198099 18534 sgd_solver.cpp:105] Iteration 3528, lr = 0.00497158 +I0410 13:56:25.854604 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:26.112296 18534 solver.cpp:218] Iteration 3540 (2.44198 iter/s, 4.91404s/12 iters), loss = 5.25907 +I0410 13:56:26.112346 18534 solver.cpp:237] Train net output #0: loss = 5.25907 (* 1 = 5.25907 loss) +I0410 13:56:26.112358 18534 sgd_solver.cpp:105] Iteration 3540, lr = 0.00495978 +I0410 13:56:31.059653 18534 solver.cpp:218] Iteration 3552 (2.42565 iter/s, 4.94713s/12 iters), loss = 5.26499 +I0410 13:56:31.059710 18534 solver.cpp:237] Train net output #0: loss = 5.26499 (* 1 = 5.26499 loss) +I0410 13:56:31.059720 18534 sgd_solver.cpp:105] Iteration 3552, lr = 0.004948 +I0410 13:56:35.981331 18534 solver.cpp:218] Iteration 3564 (2.4383 iter/s, 4.92145s/12 iters), loss = 5.29169 +I0410 13:56:35.981375 18534 solver.cpp:237] Train net output #0: loss = 5.29169 (* 1 = 5.29169 loss) +I0410 13:56:35.981384 18534 sgd_solver.cpp:105] Iteration 3564, lr = 0.00493626 +I0410 13:56:37.971051 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3570.caffemodel +I0410 13:56:38.267185 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3570.solverstate +I0410 13:56:38.475437 18534 solver.cpp:330] Iteration 3570, Testing net (#0) +I0410 13:56:38.475455 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:56:41.554607 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:42.985621 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:56:42.985672 18534 solver.cpp:397] Test net output #1: loss = 5.28686 (* 1 = 5.28686 loss) +I0410 13:56:44.710381 18534 solver.cpp:218] Iteration 3576 (1.37478 iter/s, 8.7287s/12 iters), loss = 5.28262 +I0410 13:56:44.710433 18534 solver.cpp:237] Train net output #0: loss = 5.28262 (* 1 = 5.28262 loss) +I0410 13:56:44.710443 18534 sgd_solver.cpp:105] Iteration 3576, lr = 0.00492454 +I0410 13:56:49.617306 18534 solver.cpp:218] Iteration 3588 (2.44564 iter/s, 4.90669s/12 iters), loss = 5.27672 +I0410 13:56:49.617362 18534 solver.cpp:237] Train net output #0: loss = 5.27672 (* 1 = 5.27672 loss) +I0410 13:56:49.617374 18534 sgd_solver.cpp:105] Iteration 3588, lr = 0.00491284 +I0410 13:56:54.739559 18534 solver.cpp:218] Iteration 3600 (2.34283 iter/s, 5.12201s/12 iters), loss = 5.263 +I0410 13:56:54.739610 18534 solver.cpp:237] Train net output #0: loss = 5.263 (* 1 = 5.263 loss) +I0410 13:56:54.739622 18534 sgd_solver.cpp:105] Iteration 3600, lr = 0.00490118 +I0410 13:56:59.749919 18534 solver.cpp:218] Iteration 3612 (2.39515 iter/s, 5.01013s/12 iters), loss = 5.24175 +I0410 13:56:59.749997 18534 solver.cpp:237] Train net output #0: loss = 5.24175 (* 1 = 5.24175 loss) +I0410 13:56:59.750008 18534 sgd_solver.cpp:105] Iteration 3612, lr = 0.00488954 +I0410 13:57:04.594909 18534 solver.cpp:218] Iteration 3624 (2.47691 iter/s, 4.84474s/12 iters), loss = 5.27466 +I0410 13:57:04.594947 18534 solver.cpp:237] Train net output #0: loss = 5.27466 (* 1 = 5.27466 loss) +I0410 13:57:04.594955 18534 sgd_solver.cpp:105] Iteration 3624, lr = 0.00487793 +I0410 13:57:09.507524 18534 solver.cpp:218] Iteration 3636 (2.4428 iter/s, 4.91239s/12 iters), loss = 5.2805 +I0410 13:57:09.507616 18534 solver.cpp:237] Train net output #0: loss = 5.2805 (* 1 = 5.2805 loss) +I0410 13:57:09.507627 18534 sgd_solver.cpp:105] Iteration 3636, lr = 0.00486635 +I0410 13:57:11.356223 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:14.405850 18534 solver.cpp:218] Iteration 3648 (2.44995 iter/s, 4.89806s/12 iters), loss = 5.28628 +I0410 13:57:14.405897 18534 solver.cpp:237] Train net output #0: loss = 5.28628 (* 1 = 5.28628 loss) +I0410 13:57:14.405906 18534 sgd_solver.cpp:105] Iteration 3648, lr = 0.0048548 +I0410 13:57:19.265648 18534 solver.cpp:218] Iteration 3660 (2.46935 iter/s, 4.85957s/12 iters), loss = 5.27537 +I0410 13:57:19.265695 18534 solver.cpp:237] Train net output #0: loss = 5.27537 (* 1 = 5.27537 loss) +I0410 13:57:19.265704 18534 sgd_solver.cpp:105] Iteration 3660, lr = 0.00484327 +I0410 13:57:23.642071 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3672.caffemodel +I0410 13:57:23.966810 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3672.solverstate +I0410 13:57:24.181293 18534 solver.cpp:330] Iteration 3672, Testing net (#0) +I0410 13:57:24.181314 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:57:27.102458 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:28.578889 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:57:28.578936 18534 solver.cpp:397] Test net output #1: loss = 5.28629 (* 1 = 5.28629 loss) +I0410 13:57:28.657272 18534 solver.cpp:218] Iteration 3672 (1.27779 iter/s, 9.39125s/12 iters), loss = 5.25118 +I0410 13:57:28.657330 18534 solver.cpp:237] Train net output #0: loss = 5.25118 (* 1 = 5.25118 loss) +I0410 13:57:28.657344 18534 sgd_solver.cpp:105] Iteration 3672, lr = 0.00483177 +I0410 13:57:32.776001 18534 solver.cpp:218] Iteration 3684 (2.91367 iter/s, 4.11852s/12 iters), loss = 5.26885 +I0410 13:57:32.776058 18534 solver.cpp:237] Train net output #0: loss = 5.26885 (* 1 = 5.26885 loss) +I0410 13:57:32.776068 18534 sgd_solver.cpp:105] Iteration 3684, lr = 0.0048203 +I0410 13:57:37.583217 18534 solver.cpp:218] Iteration 3696 (2.49637 iter/s, 4.80698s/12 iters), loss = 5.26058 +I0410 13:57:37.583276 18534 solver.cpp:237] Train net output #0: loss = 5.26058 (* 1 = 5.26058 loss) +I0410 13:57:37.583287 18534 sgd_solver.cpp:105] Iteration 3696, lr = 0.00480886 +I0410 13:57:42.419710 18534 solver.cpp:218] Iteration 3708 (2.48126 iter/s, 4.83625s/12 iters), loss = 5.26908 +I0410 13:57:42.419848 18534 solver.cpp:237] Train net output #0: loss = 5.26908 (* 1 = 5.26908 loss) +I0410 13:57:42.419860 18534 sgd_solver.cpp:105] Iteration 3708, lr = 0.00479744 +I0410 13:57:47.227048 18534 solver.cpp:218] Iteration 3720 (2.49635 iter/s, 4.80703s/12 iters), loss = 5.27118 +I0410 13:57:47.227111 18534 solver.cpp:237] Train net output #0: loss = 5.27118 (* 1 = 5.27118 loss) +I0410 13:57:47.227124 18534 sgd_solver.cpp:105] Iteration 3720, lr = 0.00478605 +I0410 13:57:52.165319 18534 solver.cpp:218] Iteration 3732 (2.43012 iter/s, 4.93803s/12 iters), loss = 5.25511 +I0410 13:57:52.165366 18534 solver.cpp:237] Train net output #0: loss = 5.25511 (* 1 = 5.25511 loss) +I0410 13:57:52.165377 18534 sgd_solver.cpp:105] Iteration 3732, lr = 0.00477469 +I0410 13:57:56.073307 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:57.065570 18534 solver.cpp:218] Iteration 3744 (2.44897 iter/s, 4.90002s/12 iters), loss = 5.25759 +I0410 13:57:57.065625 18534 solver.cpp:237] Train net output #0: loss = 5.25759 (* 1 = 5.25759 loss) +I0410 13:57:57.065637 18534 sgd_solver.cpp:105] Iteration 3744, lr = 0.00476335 +I0410 13:58:01.977952 18534 solver.cpp:218] Iteration 3756 (2.44292 iter/s, 4.91215s/12 iters), loss = 5.2806 +I0410 13:58:01.978009 18534 solver.cpp:237] Train net output #0: loss = 5.2806 (* 1 = 5.2806 loss) +I0410 13:58:01.978018 18534 sgd_solver.cpp:105] Iteration 3756, lr = 0.00475204 +I0410 13:58:06.889197 18534 solver.cpp:218] Iteration 3768 (2.44349 iter/s, 4.91101s/12 iters), loss = 5.26327 +I0410 13:58:06.889256 18534 solver.cpp:237] Train net output #0: loss = 5.26327 (* 1 = 5.26327 loss) +I0410 13:58:06.889268 18534 sgd_solver.cpp:105] Iteration 3768, lr = 0.00474076 +I0410 13:58:08.876515 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3774.caffemodel +I0410 13:58:09.202071 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3774.solverstate +I0410 13:58:09.416577 18534 solver.cpp:330] Iteration 3774, Testing net (#0) +I0410 13:58:09.416600 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:58:12.360644 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:58:13.849270 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:58:13.849368 18534 solver.cpp:397] Test net output #1: loss = 5.28716 (* 1 = 5.28716 loss) +I0410 13:58:15.687021 18534 solver.cpp:218] Iteration 3780 (1.36403 iter/s, 8.79746s/12 iters), loss = 5.30948 +I0410 13:58:15.687062 18534 solver.cpp:237] Train net output #0: loss = 5.30948 (* 1 = 5.30948 loss) +I0410 13:58:15.687072 18534 sgd_solver.cpp:105] Iteration 3780, lr = 0.00472951 +I0410 13:58:20.624857 18534 solver.cpp:218] Iteration 3792 (2.43032 iter/s, 4.93761s/12 iters), loss = 5.27702 +I0410 13:58:20.624898 18534 solver.cpp:237] Train net output #0: loss = 5.27702 (* 1 = 5.27702 loss) +I0410 13:58:20.624907 18534 sgd_solver.cpp:105] Iteration 3792, lr = 0.00471828 +I0410 13:58:25.608675 18534 solver.cpp:218] Iteration 3804 (2.4079 iter/s, 4.98359s/12 iters), loss = 5.26806 +I0410 13:58:25.608732 18534 solver.cpp:237] Train net output #0: loss = 5.26806 (* 1 = 5.26806 loss) +I0410 13:58:25.608745 18534 sgd_solver.cpp:105] Iteration 3804, lr = 0.00470707 +I0410 13:58:30.409615 18534 solver.cpp:218] Iteration 3816 (2.49963 iter/s, 4.8007s/12 iters), loss = 5.27194 +I0410 13:58:30.409675 18534 solver.cpp:237] Train net output #0: loss = 5.27194 (* 1 = 5.27194 loss) +I0410 13:58:30.409687 18534 sgd_solver.cpp:105] Iteration 3816, lr = 0.0046959 +I0410 13:58:35.417536 18534 solver.cpp:218] Iteration 3828 (2.39632 iter/s, 5.00767s/12 iters), loss = 5.26481 +I0410 13:58:35.417590 18534 solver.cpp:237] Train net output #0: loss = 5.26481 (* 1 = 5.26481 loss) +I0410 13:58:35.417603 18534 sgd_solver.cpp:105] Iteration 3828, lr = 0.00468475 +I0410 13:58:40.321696 18534 solver.cpp:218] Iteration 3840 (2.44702 iter/s, 4.90393s/12 iters), loss = 5.26797 +I0410 13:58:40.321755 18534 solver.cpp:237] Train net output #0: loss = 5.26797 (* 1 = 5.26797 loss) +I0410 13:58:40.321768 18534 sgd_solver.cpp:105] Iteration 3840, lr = 0.00467363 +I0410 13:58:41.450762 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:58:45.258486 18534 solver.cpp:218] Iteration 3852 (2.43085 iter/s, 4.93655s/12 iters), loss = 5.27317 +I0410 13:58:45.258611 18534 solver.cpp:237] Train net output #0: loss = 5.27317 (* 1 = 5.27317 loss) +I0410 13:58:45.258625 18534 sgd_solver.cpp:105] Iteration 3852, lr = 0.00466253 +I0410 13:58:50.129521 18534 solver.cpp:218] Iteration 3864 (2.46369 iter/s, 4.87074s/12 iters), loss = 5.25396 +I0410 13:58:50.129565 18534 solver.cpp:237] Train net output #0: loss = 5.25396 (* 1 = 5.25396 loss) +I0410 13:58:50.129575 18534 sgd_solver.cpp:105] Iteration 3864, lr = 0.00465146 +I0410 13:58:54.586144 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3876.caffemodel +I0410 13:58:54.878114 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3876.solverstate +I0410 13:58:55.074946 18534 solver.cpp:330] Iteration 3876, Testing net (#0) +I0410 13:58:55.074968 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:58:57.928241 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:58:59.465678 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:58:59.465708 18534 solver.cpp:397] Test net output #1: loss = 5.28669 (* 1 = 5.28669 loss) +I0410 13:58:59.547889 18534 solver.cpp:218] Iteration 3876 (1.27416 iter/s, 9.41799s/12 iters), loss = 5.27159 +I0410 13:58:59.547931 18534 solver.cpp:237] Train net output #0: loss = 5.27159 (* 1 = 5.27159 loss) +I0410 13:58:59.547940 18534 sgd_solver.cpp:105] Iteration 3876, lr = 0.00464042 +I0410 13:59:03.599046 18534 solver.cpp:218] Iteration 3888 (2.96225 iter/s, 4.05097s/12 iters), loss = 5.26901 +I0410 13:59:03.599089 18534 solver.cpp:237] Train net output #0: loss = 5.26901 (* 1 = 5.26901 loss) +I0410 13:59:03.599097 18534 sgd_solver.cpp:105] Iteration 3888, lr = 0.0046294 +I0410 13:59:08.544872 18534 solver.cpp:218] Iteration 3900 (2.4264 iter/s, 4.9456s/12 iters), loss = 5.27367 +I0410 13:59:08.544915 18534 solver.cpp:237] Train net output #0: loss = 5.27367 (* 1 = 5.27367 loss) +I0410 13:59:08.544924 18534 sgd_solver.cpp:105] Iteration 3900, lr = 0.00461841 +I0410 13:59:13.625157 18534 solver.cpp:218] Iteration 3912 (2.36218 iter/s, 5.08005s/12 iters), loss = 5.26214 +I0410 13:59:13.625212 18534 solver.cpp:237] Train net output #0: loss = 5.26214 (* 1 = 5.26214 loss) +I0410 13:59:13.625224 18534 sgd_solver.cpp:105] Iteration 3912, lr = 0.00460744 +I0410 13:59:18.470074 18534 solver.cpp:218] Iteration 3924 (2.47694 iter/s, 4.84468s/12 iters), loss = 5.29213 +I0410 13:59:18.470201 18534 solver.cpp:237] Train net output #0: loss = 5.29213 (* 1 = 5.29213 loss) +I0410 13:59:18.470214 18534 sgd_solver.cpp:105] Iteration 3924, lr = 0.0045965 +I0410 13:59:23.263891 18534 solver.cpp:218] Iteration 3936 (2.50338 iter/s, 4.79351s/12 iters), loss = 5.27368 +I0410 13:59:23.263948 18534 solver.cpp:237] Train net output #0: loss = 5.27368 (* 1 = 5.27368 loss) +I0410 13:59:23.263960 18534 sgd_solver.cpp:105] Iteration 3936, lr = 0.00458559 +I0410 13:59:26.513597 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:28.096388 18534 solver.cpp:218] Iteration 3948 (2.48331 iter/s, 4.83226s/12 iters), loss = 5.28531 +I0410 13:59:28.096451 18534 solver.cpp:237] Train net output #0: loss = 5.28531 (* 1 = 5.28531 loss) +I0410 13:59:28.096462 18534 sgd_solver.cpp:105] Iteration 3948, lr = 0.0045747 +I0410 13:59:32.900781 18534 solver.cpp:218] Iteration 3960 (2.49784 iter/s, 4.80415s/12 iters), loss = 5.27059 +I0410 13:59:32.900840 18534 solver.cpp:237] Train net output #0: loss = 5.27059 (* 1 = 5.27059 loss) +I0410 13:59:32.900851 18534 sgd_solver.cpp:105] Iteration 3960, lr = 0.00456384 +I0410 13:59:37.722442 18534 solver.cpp:218] Iteration 3972 (2.48889 iter/s, 4.82143s/12 iters), loss = 5.27986 +I0410 13:59:37.722501 18534 solver.cpp:237] Train net output #0: loss = 5.27986 (* 1 = 5.27986 loss) +I0410 13:59:37.722512 18534 sgd_solver.cpp:105] Iteration 3972, lr = 0.00455301 +I0410 13:59:39.683574 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3978.caffemodel +I0410 13:59:39.992170 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3978.solverstate +I0410 13:59:40.202196 18534 solver.cpp:330] Iteration 3978, Testing net (#0) +I0410 13:59:40.202219 18534 net.cpp:676] Ignoring source layer train-data +I0410 13:59:43.038408 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:44.612443 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:59:44.612475 18534 solver.cpp:397] Test net output #1: loss = 5.28652 (* 1 = 5.28652 loss) +I0410 13:59:46.374650 18534 solver.cpp:218] Iteration 3984 (1.38699 iter/s, 8.65184s/12 iters), loss = 5.2827 +I0410 13:59:46.374707 18534 solver.cpp:237] Train net output #0: loss = 5.2827 (* 1 = 5.2827 loss) +I0410 13:59:46.374718 18534 sgd_solver.cpp:105] Iteration 3984, lr = 0.0045422 +I0410 13:59:51.280862 18534 solver.cpp:218] Iteration 3996 (2.446 iter/s, 4.90597s/12 iters), loss = 5.26268 +I0410 13:59:51.280973 18534 solver.cpp:237] Train net output #0: loss = 5.26268 (* 1 = 5.26268 loss) +I0410 13:59:51.280985 18534 sgd_solver.cpp:105] Iteration 3996, lr = 0.00453141 +I0410 13:59:56.186911 18534 solver.cpp:218] Iteration 4008 (2.44611 iter/s, 4.90576s/12 iters), loss = 5.28665 +I0410 13:59:56.186964 18534 solver.cpp:237] Train net output #0: loss = 5.28665 (* 1 = 5.28665 loss) +I0410 13:59:56.186976 18534 sgd_solver.cpp:105] Iteration 4008, lr = 0.00452066 +I0410 14:00:01.065727 18534 solver.cpp:218] Iteration 4020 (2.45973 iter/s, 4.87859s/12 iters), loss = 5.25567 +I0410 14:00:01.065768 18534 solver.cpp:237] Train net output #0: loss = 5.25567 (* 1 = 5.25567 loss) +I0410 14:00:01.065778 18534 sgd_solver.cpp:105] Iteration 4020, lr = 0.00450992 +I0410 14:00:05.957449 18534 solver.cpp:218] Iteration 4032 (2.45324 iter/s, 4.8915s/12 iters), loss = 5.27469 +I0410 14:00:05.957502 18534 solver.cpp:237] Train net output #0: loss = 5.27469 (* 1 = 5.27469 loss) +I0410 14:00:05.957515 18534 sgd_solver.cpp:105] Iteration 4032, lr = 0.00449921 +I0410 14:00:10.826404 18534 solver.cpp:218] Iteration 4044 (2.46471 iter/s, 4.86872s/12 iters), loss = 5.27338 +I0410 14:00:10.826459 18534 solver.cpp:237] Train net output #0: loss = 5.27338 (* 1 = 5.27338 loss) +I0410 14:00:10.826470 18534 sgd_solver.cpp:105] Iteration 4044, lr = 0.00448853 +I0410 14:00:11.326936 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:15.706691 18534 solver.cpp:218] Iteration 4056 (2.45899 iter/s, 4.88005s/12 iters), loss = 5.2729 +I0410 14:00:15.706738 18534 solver.cpp:237] Train net output #0: loss = 5.2729 (* 1 = 5.2729 loss) +I0410 14:00:15.706749 18534 sgd_solver.cpp:105] Iteration 4056, lr = 0.00447788 +I0410 14:00:20.579270 18534 solver.cpp:218] Iteration 4068 (2.46288 iter/s, 4.87235s/12 iters), loss = 5.27384 +I0410 14:00:20.579319 18534 solver.cpp:237] Train net output #0: loss = 5.27384 (* 1 = 5.27384 loss) +I0410 14:00:20.579329 18534 sgd_solver.cpp:105] Iteration 4068, lr = 0.00446724 +I0410 14:00:25.114763 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4080.caffemodel +I0410 14:00:25.443506 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4080.solverstate +I0410 14:00:25.658491 18534 solver.cpp:330] Iteration 4080, Testing net (#0) +I0410 14:00:25.658515 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:00:28.433228 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:30.037674 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:00:30.037724 18534 solver.cpp:397] Test net output #1: loss = 5.28706 (* 1 = 5.28706 loss) +I0410 14:00:30.120396 18534 solver.cpp:218] Iteration 4080 (1.25777 iter/s, 9.54073s/12 iters), loss = 5.28422 +I0410 14:00:30.120474 18534 solver.cpp:237] Train net output #0: loss = 5.28422 (* 1 = 5.28422 loss) +I0410 14:00:30.120491 18534 sgd_solver.cpp:105] Iteration 4080, lr = 0.00445664 +I0410 14:00:34.250809 18534 solver.cpp:218] Iteration 4092 (2.90544 iter/s, 4.13019s/12 iters), loss = 5.26395 +I0410 14:00:34.250862 18534 solver.cpp:237] Train net output #0: loss = 5.26395 (* 1 = 5.26395 loss) +I0410 14:00:34.250874 18534 sgd_solver.cpp:105] Iteration 4092, lr = 0.00444606 +I0410 14:00:39.044597 18534 solver.cpp:218] Iteration 4104 (2.50336 iter/s, 4.79355s/12 iters), loss = 5.26388 +I0410 14:00:39.044652 18534 solver.cpp:237] Train net output #0: loss = 5.26388 (* 1 = 5.26388 loss) +I0410 14:00:39.044665 18534 sgd_solver.cpp:105] Iteration 4104, lr = 0.0044355 +I0410 14:00:44.008086 18534 solver.cpp:218] Iteration 4116 (2.41777 iter/s, 4.96325s/12 iters), loss = 5.29101 +I0410 14:00:44.008133 18534 solver.cpp:237] Train net output #0: loss = 5.29101 (* 1 = 5.29101 loss) +I0410 14:00:44.008144 18534 sgd_solver.cpp:105] Iteration 4116, lr = 0.00442497 +I0410 14:00:48.892021 18534 solver.cpp:218] Iteration 4128 (2.45715 iter/s, 4.88371s/12 iters), loss = 5.26641 +I0410 14:00:48.892063 18534 solver.cpp:237] Train net output #0: loss = 5.26641 (* 1 = 5.26641 loss) +I0410 14:00:48.892071 18534 sgd_solver.cpp:105] Iteration 4128, lr = 0.00441447 +I0410 14:00:53.826246 18534 solver.cpp:218] Iteration 4140 (2.43211 iter/s, 4.934s/12 iters), loss = 5.26064 +I0410 14:00:53.826300 18534 solver.cpp:237] Train net output #0: loss = 5.26064 (* 1 = 5.26064 loss) +I0410 14:00:53.826313 18534 sgd_solver.cpp:105] Iteration 4140, lr = 0.00440398 +I0410 14:00:56.418938 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:58.769977 18534 solver.cpp:218] Iteration 4152 (2.42744 iter/s, 4.94347s/12 iters), loss = 5.27218 +I0410 14:00:58.770038 18534 solver.cpp:237] Train net output #0: loss = 5.27218 (* 1 = 5.27218 loss) +I0410 14:00:58.770051 18534 sgd_solver.cpp:105] Iteration 4152, lr = 0.00439353 +I0410 14:00:58.770494 18534 blocking_queue.cpp:49] Waiting for data +I0410 14:01:03.679359 18534 solver.cpp:218] Iteration 4164 (2.44442 iter/s, 4.90914s/12 iters), loss = 5.26368 +I0410 14:01:03.679402 18534 solver.cpp:237] Train net output #0: loss = 5.26368 (* 1 = 5.26368 loss) +I0410 14:01:03.679411 18534 sgd_solver.cpp:105] Iteration 4164, lr = 0.0043831 +I0410 14:01:08.550801 18534 solver.cpp:218] Iteration 4176 (2.46345 iter/s, 4.87122s/12 iters), loss = 5.2665 +I0410 14:01:08.550849 18534 solver.cpp:237] Train net output #0: loss = 5.2665 (* 1 = 5.2665 loss) +I0410 14:01:08.550859 18534 sgd_solver.cpp:105] Iteration 4176, lr = 0.00437269 +I0410 14:01:10.534106 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4182.caffemodel +I0410 14:01:11.054617 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4182.solverstate +I0410 14:01:11.974507 18534 solver.cpp:330] Iteration 4182, Testing net (#0) +I0410 14:01:11.974535 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:01:14.745904 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:01:16.399490 18534 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 14:01:16.399523 18534 solver.cpp:397] Test net output #1: loss = 5.28668 (* 1 = 5.28668 loss) +I0410 14:01:18.126052 18534 solver.cpp:218] Iteration 4188 (1.25328 iter/s, 9.57485s/12 iters), loss = 5.26747 +I0410 14:01:18.126106 18534 solver.cpp:237] Train net output #0: loss = 5.26747 (* 1 = 5.26747 loss) +I0410 14:01:18.126116 18534 sgd_solver.cpp:105] Iteration 4188, lr = 0.00436231 +I0410 14:01:23.035342 18534 solver.cpp:218] Iteration 4200 (2.44447 iter/s, 4.90905s/12 iters), loss = 5.28457 +I0410 14:01:23.035392 18534 solver.cpp:237] Train net output #0: loss = 5.28457 (* 1 = 5.28457 loss) +I0410 14:01:23.035400 18534 sgd_solver.cpp:105] Iteration 4200, lr = 0.00435195 +I0410 14:01:27.942524 18534 solver.cpp:218] Iteration 4212 (2.44551 iter/s, 4.90695s/12 iters), loss = 5.27002 +I0410 14:01:27.942639 18534 solver.cpp:237] Train net output #0: loss = 5.27002 (* 1 = 5.27002 loss) +I0410 14:01:27.942651 18534 sgd_solver.cpp:105] Iteration 4212, lr = 0.00434162 +I0410 14:01:33.049587 18534 solver.cpp:218] Iteration 4224 (2.34983 iter/s, 5.10675s/12 iters), loss = 5.26431 +I0410 14:01:33.049634 18534 solver.cpp:237] Train net output #0: loss = 5.26431 (* 1 = 5.26431 loss) +I0410 14:01:33.049643 18534 sgd_solver.cpp:105] Iteration 4224, lr = 0.00433131 +I0410 14:01:38.062141 18534 solver.cpp:218] Iteration 4236 (2.3941 iter/s, 5.01231s/12 iters), loss = 5.26836 +I0410 14:01:38.062188 18534 solver.cpp:237] Train net output #0: loss = 5.26836 (* 1 = 5.26836 loss) +I0410 14:01:38.062198 18534 sgd_solver.cpp:105] Iteration 4236, lr = 0.00432103 +I0410 14:01:42.710424 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:01:42.935158 18534 solver.cpp:218] Iteration 4248 (2.46266 iter/s, 4.87278s/12 iters), loss = 5.24199 +I0410 14:01:42.935207 18534 solver.cpp:237] Train net output #0: loss = 5.24199 (* 1 = 5.24199 loss) +I0410 14:01:42.935220 18534 sgd_solver.cpp:105] Iteration 4248, lr = 0.00431077 +I0410 14:01:47.822834 18534 solver.cpp:218] Iteration 4260 (2.45527 iter/s, 4.88744s/12 iters), loss = 5.2661 +I0410 14:01:47.822890 18534 solver.cpp:237] Train net output #0: loss = 5.2661 (* 1 = 5.2661 loss) +I0410 14:01:47.822902 18534 sgd_solver.cpp:105] Iteration 4260, lr = 0.00430053 +I0410 14:01:53.055656 18534 solver.cpp:218] Iteration 4272 (2.29333 iter/s, 5.23257s/12 iters), loss = 5.29128 +I0410 14:01:53.055703 18534 solver.cpp:237] Train net output #0: loss = 5.29128 (* 1 = 5.29128 loss) +I0410 14:01:53.055712 18534 sgd_solver.cpp:105] Iteration 4272, lr = 0.00429032 +I0410 14:01:57.678666 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4284.caffemodel +I0410 14:01:57.981794 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4284.solverstate +I0410 14:01:58.179260 18534 solver.cpp:330] Iteration 4284, Testing net (#0) +I0410 14:01:58.179280 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:02:01.022521 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:02.714507 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:02:02.714558 18534 solver.cpp:397] Test net output #1: loss = 5.28679 (* 1 = 5.28679 loss) +I0410 14:02:02.797042 18534 solver.cpp:218] Iteration 4284 (1.23191 iter/s, 9.74098s/12 iters), loss = 5.27796 +I0410 14:02:02.797094 18534 solver.cpp:237] Train net output #0: loss = 5.27796 (* 1 = 5.27796 loss) +I0410 14:02:02.797106 18534 sgd_solver.cpp:105] Iteration 4284, lr = 0.00428014 +I0410 14:02:06.928781 18534 solver.cpp:218] Iteration 4296 (2.90449 iter/s, 4.13153s/12 iters), loss = 5.27674 +I0410 14:02:06.928828 18534 solver.cpp:237] Train net output #0: loss = 5.27674 (* 1 = 5.27674 loss) +I0410 14:02:06.928838 18534 sgd_solver.cpp:105] Iteration 4296, lr = 0.00426998 +I0410 14:02:11.796927 18534 solver.cpp:218] Iteration 4308 (2.46512 iter/s, 4.86791s/12 iters), loss = 5.26318 +I0410 14:02:11.796978 18534 solver.cpp:237] Train net output #0: loss = 5.26318 (* 1 = 5.26318 loss) +I0410 14:02:11.796990 18534 sgd_solver.cpp:105] Iteration 4308, lr = 0.00425984 +I0410 14:02:16.721012 18534 solver.cpp:218] Iteration 4320 (2.43712 iter/s, 4.92384s/12 iters), loss = 5.24947 +I0410 14:02:16.721079 18534 solver.cpp:237] Train net output #0: loss = 5.24947 (* 1 = 5.24947 loss) +I0410 14:02:16.721099 18534 sgd_solver.cpp:105] Iteration 4320, lr = 0.00424972 +I0410 14:02:21.630014 18534 solver.cpp:218] Iteration 4332 (2.44461 iter/s, 4.90876s/12 iters), loss = 5.278 +I0410 14:02:21.630060 18534 solver.cpp:237] Train net output #0: loss = 5.278 (* 1 = 5.278 loss) +I0410 14:02:21.630069 18534 sgd_solver.cpp:105] Iteration 4332, lr = 0.00423964 +I0410 14:02:26.701479 18534 solver.cpp:218] Iteration 4344 (2.36629 iter/s, 5.07122s/12 iters), loss = 5.28056 +I0410 14:02:26.701532 18534 solver.cpp:237] Train net output #0: loss = 5.28056 (* 1 = 5.28056 loss) +I0410 14:02:26.701543 18534 sgd_solver.cpp:105] Iteration 4344, lr = 0.00422957 +I0410 14:02:28.582222 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:31.638788 18534 solver.cpp:218] Iteration 4356 (2.43059 iter/s, 4.93707s/12 iters), loss = 5.29065 +I0410 14:02:31.638837 18534 solver.cpp:237] Train net output #0: loss = 5.29065 (* 1 = 5.29065 loss) +I0410 14:02:31.638849 18534 sgd_solver.cpp:105] Iteration 4356, lr = 0.00421953 +I0410 14:02:36.499662 18534 solver.cpp:218] Iteration 4368 (2.46881 iter/s, 4.86064s/12 iters), loss = 5.2746 +I0410 14:02:36.499711 18534 solver.cpp:237] Train net output #0: loss = 5.2746 (* 1 = 5.2746 loss) +I0410 14:02:36.499719 18534 sgd_solver.cpp:105] Iteration 4368, lr = 0.00420951 +I0410 14:02:41.381331 18534 solver.cpp:218] Iteration 4380 (2.45829 iter/s, 4.88143s/12 iters), loss = 5.26128 +I0410 14:02:41.381374 18534 solver.cpp:237] Train net output #0: loss = 5.26128 (* 1 = 5.26128 loss) +I0410 14:02:41.381383 18534 sgd_solver.cpp:105] Iteration 4380, lr = 0.00419952 +I0410 14:02:43.338568 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4386.caffemodel +I0410 14:02:43.717167 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4386.solverstate +I0410 14:02:43.926362 18534 solver.cpp:330] Iteration 4386, Testing net (#0) +I0410 14:02:43.926380 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:02:46.586336 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:48.343533 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:02:48.343582 18534 solver.cpp:397] Test net output #1: loss = 5.28674 (* 1 = 5.28674 loss) +I0410 14:02:50.202044 18534 solver.cpp:218] Iteration 4392 (1.36049 iter/s, 8.82034s/12 iters), loss = 5.26825 +I0410 14:02:50.202101 18534 solver.cpp:237] Train net output #0: loss = 5.26825 (* 1 = 5.26825 loss) +I0410 14:02:50.202112 18534 sgd_solver.cpp:105] Iteration 4392, lr = 0.00418954 +I0410 14:02:55.031904 18534 solver.cpp:218] Iteration 4404 (2.48467 iter/s, 4.82962s/12 iters), loss = 5.26546 +I0410 14:02:55.031961 18534 solver.cpp:237] Train net output #0: loss = 5.26546 (* 1 = 5.26546 loss) +I0410 14:02:55.031972 18534 sgd_solver.cpp:105] Iteration 4404, lr = 0.0041796 +I0410 14:02:59.963778 18534 solver.cpp:218] Iteration 4416 (2.43327 iter/s, 4.93162s/12 iters), loss = 5.26398 +I0410 14:02:59.963855 18534 solver.cpp:237] Train net output #0: loss = 5.26398 (* 1 = 5.26398 loss) +I0410 14:02:59.963865 18534 sgd_solver.cpp:105] Iteration 4416, lr = 0.00416967 +I0410 14:03:04.874770 18534 solver.cpp:218] Iteration 4428 (2.44363 iter/s, 4.91072s/12 iters), loss = 5.26908 +I0410 14:03:04.874830 18534 solver.cpp:237] Train net output #0: loss = 5.26908 (* 1 = 5.26908 loss) +I0410 14:03:04.874842 18534 sgd_solver.cpp:105] Iteration 4428, lr = 0.00415977 +I0410 14:03:09.781232 18534 solver.cpp:218] Iteration 4440 (2.44587 iter/s, 4.90622s/12 iters), loss = 5.26285 +I0410 14:03:09.781280 18534 solver.cpp:237] Train net output #0: loss = 5.26285 (* 1 = 5.26285 loss) +I0410 14:03:09.781288 18534 sgd_solver.cpp:105] Iteration 4440, lr = 0.0041499 +I0410 14:03:13.756917 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:14.709981 18534 solver.cpp:218] Iteration 4452 (2.43482 iter/s, 4.9285s/12 iters), loss = 5.25755 +I0410 14:03:14.710029 18534 solver.cpp:237] Train net output #0: loss = 5.25755 (* 1 = 5.25755 loss) +I0410 14:03:14.710037 18534 sgd_solver.cpp:105] Iteration 4452, lr = 0.00414005 +I0410 14:03:19.630417 18534 solver.cpp:218] Iteration 4464 (2.43893 iter/s, 4.92019s/12 iters), loss = 5.27974 +I0410 14:03:19.630465 18534 solver.cpp:237] Train net output #0: loss = 5.27974 (* 1 = 5.27974 loss) +I0410 14:03:19.630472 18534 sgd_solver.cpp:105] Iteration 4464, lr = 0.00413022 +I0410 14:03:24.550278 18534 solver.cpp:218] Iteration 4476 (2.43921 iter/s, 4.91963s/12 iters), loss = 5.25846 +I0410 14:03:24.550333 18534 solver.cpp:237] Train net output #0: loss = 5.25846 (* 1 = 5.25846 loss) +I0410 14:03:24.550344 18534 sgd_solver.cpp:105] Iteration 4476, lr = 0.00412041 +I0410 14:03:29.001111 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4488.caffemodel +I0410 14:03:29.701809 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4488.solverstate +I0410 14:03:29.917263 18534 solver.cpp:330] Iteration 4488, Testing net (#0) +I0410 14:03:29.917285 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:03:32.550026 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:34.429863 18534 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 14:03:34.429908 18534 solver.cpp:397] Test net output #1: loss = 5.28657 (* 1 = 5.28657 loss) +I0410 14:03:34.512379 18534 solver.cpp:218] Iteration 4488 (1.20462 iter/s, 9.96168s/12 iters), loss = 5.30794 +I0410 14:03:34.512430 18534 solver.cpp:237] Train net output #0: loss = 5.30794 (* 1 = 5.30794 loss) +I0410 14:03:34.512441 18534 sgd_solver.cpp:105] Iteration 4488, lr = 0.00411063 +I0410 14:03:38.738265 18534 solver.cpp:218] Iteration 4500 (2.83979 iter/s, 4.22567s/12 iters), loss = 5.27322 +I0410 14:03:38.738320 18534 solver.cpp:237] Train net output #0: loss = 5.27322 (* 1 = 5.27322 loss) +I0410 14:03:38.738332 18534 sgd_solver.cpp:105] Iteration 4500, lr = 0.00410087 +I0410 14:03:43.542407 18534 solver.cpp:218] Iteration 4512 (2.49797 iter/s, 4.8039s/12 iters), loss = 5.26936 +I0410 14:03:43.542472 18534 solver.cpp:237] Train net output #0: loss = 5.26936 (* 1 = 5.26936 loss) +I0410 14:03:43.542484 18534 sgd_solver.cpp:105] Iteration 4512, lr = 0.00409113 +I0410 14:03:48.359696 18534 solver.cpp:218] Iteration 4524 (2.49116 iter/s, 4.81704s/12 iters), loss = 5.27562 +I0410 14:03:48.359758 18534 solver.cpp:237] Train net output #0: loss = 5.27562 (* 1 = 5.27562 loss) +I0410 14:03:48.359769 18534 sgd_solver.cpp:105] Iteration 4524, lr = 0.00408142 +I0410 14:03:53.167125 18534 solver.cpp:218] Iteration 4536 (2.49626 iter/s, 4.80718s/12 iters), loss = 5.26714 +I0410 14:03:53.167179 18534 solver.cpp:237] Train net output #0: loss = 5.26714 (* 1 = 5.26714 loss) +I0410 14:03:53.167191 18534 sgd_solver.cpp:105] Iteration 4536, lr = 0.00407173 +I0410 14:03:58.006799 18534 solver.cpp:218] Iteration 4548 (2.47963 iter/s, 4.83943s/12 iters), loss = 5.26371 +I0410 14:03:58.006853 18534 solver.cpp:237] Train net output #0: loss = 5.26371 (* 1 = 5.26371 loss) +I0410 14:03:58.006865 18534 sgd_solver.cpp:105] Iteration 4548, lr = 0.00406206 +I0410 14:03:59.214498 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:04:02.820570 18534 solver.cpp:218] Iteration 4560 (2.49297 iter/s, 4.81353s/12 iters), loss = 5.27468 +I0410 14:04:02.820688 18534 solver.cpp:237] Train net output #0: loss = 5.27468 (* 1 = 5.27468 loss) +I0410 14:04:02.820699 18534 sgd_solver.cpp:105] Iteration 4560, lr = 0.00405242 +I0410 14:04:07.655377 18534 solver.cpp:218] Iteration 4572 (2.48216 iter/s, 4.83451s/12 iters), loss = 5.26442 +I0410 14:04:07.655432 18534 solver.cpp:237] Train net output #0: loss = 5.26442 (* 1 = 5.26442 loss) +I0410 14:04:07.655445 18534 sgd_solver.cpp:105] Iteration 4572, lr = 0.0040428 +I0410 14:04:12.451408 18534 solver.cpp:218] Iteration 4584 (2.5022 iter/s, 4.79579s/12 iters), loss = 5.27686 +I0410 14:04:12.451472 18534 solver.cpp:237] Train net output #0: loss = 5.27686 (* 1 = 5.27686 loss) +I0410 14:04:12.451484 18534 sgd_solver.cpp:105] Iteration 4584, lr = 0.0040332 +I0410 14:04:14.405803 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4590.caffemodel +I0410 14:04:14.845055 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4590.solverstate +I0410 14:04:15.723942 18534 solver.cpp:330] Iteration 4590, Testing net (#0) +I0410 14:04:15.723974 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:04:18.305682 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:04:20.223507 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:04:20.223556 18534 solver.cpp:397] Test net output #1: loss = 5.28653 (* 1 = 5.28653 loss) +I0410 14:04:22.136904 18534 solver.cpp:218] Iteration 4596 (1.23902 iter/s, 9.68508s/12 iters), loss = 5.27441 +I0410 14:04:22.136946 18534 solver.cpp:237] Train net output #0: loss = 5.27441 (* 1 = 5.27441 loss) +I0410 14:04:22.136955 18534 sgd_solver.cpp:105] Iteration 4596, lr = 0.00402362 +I0410 14:04:27.064935 18534 solver.cpp:218] Iteration 4608 (2.43517 iter/s, 4.9278s/12 iters), loss = 5.27198 +I0410 14:04:27.064990 18534 solver.cpp:237] Train net output #0: loss = 5.27198 (* 1 = 5.27198 loss) +I0410 14:04:27.065001 18534 sgd_solver.cpp:105] Iteration 4608, lr = 0.00401407 +I0410 14:04:31.990592 18534 solver.cpp:218] Iteration 4620 (2.43634 iter/s, 4.92541s/12 iters), loss = 5.26378 +I0410 14:04:31.990644 18534 solver.cpp:237] Train net output #0: loss = 5.26378 (* 1 = 5.26378 loss) +I0410 14:04:31.990656 18534 sgd_solver.cpp:105] Iteration 4620, lr = 0.00400454 +I0410 14:04:36.989692 18534 solver.cpp:218] Iteration 4632 (2.40055 iter/s, 4.99885s/12 iters), loss = 5.29385 +I0410 14:04:36.989861 18534 solver.cpp:237] Train net output #0: loss = 5.29385 (* 1 = 5.29385 loss) +I0410 14:04:36.989873 18534 sgd_solver.cpp:105] Iteration 4632, lr = 0.00399503 +I0410 14:04:41.968421 18534 solver.cpp:218] Iteration 4644 (2.41043 iter/s, 4.97837s/12 iters), loss = 5.26678 +I0410 14:04:41.968477 18534 solver.cpp:237] Train net output #0: loss = 5.26678 (* 1 = 5.26678 loss) +I0410 14:04:41.968489 18534 sgd_solver.cpp:105] Iteration 4644, lr = 0.00398555 +I0410 14:04:45.368018 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:04:46.944702 18534 solver.cpp:218] Iteration 4656 (2.41156 iter/s, 4.97604s/12 iters), loss = 5.2796 +I0410 14:04:46.944742 18534 solver.cpp:237] Train net output #0: loss = 5.2796 (* 1 = 5.2796 loss) +I0410 14:04:46.944751 18534 sgd_solver.cpp:105] Iteration 4656, lr = 0.00397608 +I0410 14:04:51.915709 18534 solver.cpp:218] Iteration 4668 (2.41411 iter/s, 4.97078s/12 iters), loss = 5.26708 +I0410 14:04:51.915745 18534 solver.cpp:237] Train net output #0: loss = 5.26708 (* 1 = 5.26708 loss) +I0410 14:04:51.915753 18534 sgd_solver.cpp:105] Iteration 4668, lr = 0.00396664 +I0410 14:04:56.803104 18534 solver.cpp:218] Iteration 4680 (2.45541 iter/s, 4.88717s/12 iters), loss = 5.27805 +I0410 14:04:56.803158 18534 solver.cpp:237] Train net output #0: loss = 5.27805 (* 1 = 5.27805 loss) +I0410 14:04:56.803170 18534 sgd_solver.cpp:105] Iteration 4680, lr = 0.00395723 +I0410 14:05:01.239760 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4692.caffemodel +I0410 14:05:01.586781 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4692.solverstate +I0410 14:05:02.369922 18534 solver.cpp:330] Iteration 4692, Testing net (#0) +I0410 14:05:02.369951 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:05:04.914810 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:06.878151 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:05:06.878193 18534 solver.cpp:397] Test net output #1: loss = 5.28686 (* 1 = 5.28686 loss) +I0410 14:05:06.960556 18534 solver.cpp:218] Iteration 4692 (1.18145 iter/s, 10.157s/12 iters), loss = 5.27109 +I0410 14:05:06.960626 18534 solver.cpp:237] Train net output #0: loss = 5.27109 (* 1 = 5.27109 loss) +I0410 14:05:06.960639 18534 sgd_solver.cpp:105] Iteration 4692, lr = 0.00394783 +I0410 14:05:11.026480 18534 solver.cpp:218] Iteration 4704 (2.95152 iter/s, 4.0657s/12 iters), loss = 5.26382 +I0410 14:05:11.026623 18534 solver.cpp:237] Train net output #0: loss = 5.26382 (* 1 = 5.26382 loss) +I0410 14:05:11.026633 18534 sgd_solver.cpp:105] Iteration 4704, lr = 0.00393846 +I0410 14:05:15.861261 18534 solver.cpp:218] Iteration 4716 (2.48219 iter/s, 4.83445s/12 iters), loss = 5.2789 +I0410 14:05:15.861320 18534 solver.cpp:237] Train net output #0: loss = 5.2789 (* 1 = 5.2789 loss) +I0410 14:05:15.861331 18534 sgd_solver.cpp:105] Iteration 4716, lr = 0.00392911 +I0410 14:05:20.666013 18534 solver.cpp:218] Iteration 4728 (2.49766 iter/s, 4.80451s/12 iters), loss = 5.26211 +I0410 14:05:20.666069 18534 solver.cpp:237] Train net output #0: loss = 5.26211 (* 1 = 5.26211 loss) +I0410 14:05:20.666080 18534 sgd_solver.cpp:105] Iteration 4728, lr = 0.00391978 +I0410 14:05:25.507814 18534 solver.cpp:218] Iteration 4740 (2.47854 iter/s, 4.84156s/12 iters), loss = 5.27805 +I0410 14:05:25.507877 18534 solver.cpp:237] Train net output #0: loss = 5.27805 (* 1 = 5.27805 loss) +I0410 14:05:25.507889 18534 sgd_solver.cpp:105] Iteration 4740, lr = 0.00391047 +I0410 14:05:30.450191 18534 solver.cpp:218] Iteration 4752 (2.42811 iter/s, 4.94212s/12 iters), loss = 5.28027 +I0410 14:05:30.450249 18534 solver.cpp:237] Train net output #0: loss = 5.28027 (* 1 = 5.28027 loss) +I0410 14:05:30.450271 18534 sgd_solver.cpp:105] Iteration 4752, lr = 0.00390119 +I0410 14:05:30.968282 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:35.384714 18534 solver.cpp:218] Iteration 4764 (2.43197 iter/s, 4.93427s/12 iters), loss = 5.28063 +I0410 14:05:35.384766 18534 solver.cpp:237] Train net output #0: loss = 5.28063 (* 1 = 5.28063 loss) +I0410 14:05:35.384779 18534 sgd_solver.cpp:105] Iteration 4764, lr = 0.00389193 +I0410 14:05:40.299165 18534 solver.cpp:218] Iteration 4776 (2.4419 iter/s, 4.91421s/12 iters), loss = 5.26558 +I0410 14:05:40.299211 18534 solver.cpp:237] Train net output #0: loss = 5.26558 (* 1 = 5.26558 loss) +I0410 14:05:40.299221 18534 sgd_solver.cpp:105] Iteration 4776, lr = 0.00388269 +I0410 14:05:45.228041 18534 solver.cpp:218] Iteration 4788 (2.43475 iter/s, 4.92863s/12 iters), loss = 5.29316 +I0410 14:05:45.228137 18534 solver.cpp:237] Train net output #0: loss = 5.29316 (* 1 = 5.29316 loss) +I0410 14:05:45.228150 18534 sgd_solver.cpp:105] Iteration 4788, lr = 0.00387347 +I0410 14:05:47.206262 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4794.caffemodel +I0410 14:05:47.507973 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4794.solverstate +I0410 14:05:48.368285 18534 solver.cpp:330] Iteration 4794, Testing net (#0) +I0410 14:05:48.368311 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:05:51.039597 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:52.963642 18534 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 14:05:52.963680 18534 solver.cpp:397] Test net output #1: loss = 5.28616 (* 1 = 5.28616 loss) +I0410 14:05:54.833989 18534 solver.cpp:218] Iteration 4800 (1.24928 iter/s, 9.6055s/12 iters), loss = 5.27253 +I0410 14:05:54.834036 18534 solver.cpp:237] Train net output #0: loss = 5.27253 (* 1 = 5.27253 loss) +I0410 14:05:54.834045 18534 sgd_solver.cpp:105] Iteration 4800, lr = 0.00386427 +I0410 14:05:59.776341 18534 solver.cpp:218] Iteration 4812 (2.42811 iter/s, 4.94212s/12 iters), loss = 5.26268 +I0410 14:05:59.776386 18534 solver.cpp:237] Train net output #0: loss = 5.26268 (* 1 = 5.26268 loss) +I0410 14:05:59.776394 18534 sgd_solver.cpp:105] Iteration 4812, lr = 0.0038551 +I0410 14:06:04.676218 18534 solver.cpp:218] Iteration 4824 (2.44916 iter/s, 4.89964s/12 iters), loss = 5.29238 +I0410 14:06:04.676260 18534 solver.cpp:237] Train net output #0: loss = 5.29238 (* 1 = 5.29238 loss) +I0410 14:06:04.676268 18534 sgd_solver.cpp:105] Iteration 4824, lr = 0.00384594 +I0410 14:06:09.669991 18534 solver.cpp:218] Iteration 4836 (2.40311 iter/s, 4.99352s/12 iters), loss = 5.2619 +I0410 14:06:09.670049 18534 solver.cpp:237] Train net output #0: loss = 5.2619 (* 1 = 5.2619 loss) +I0410 14:06:09.670061 18534 sgd_solver.cpp:105] Iteration 4836, lr = 0.00383681 +I0410 14:06:10.030827 18534 blocking_queue.cpp:49] Waiting for data +I0410 14:06:14.563694 18534 solver.cpp:218] Iteration 4848 (2.45226 iter/s, 4.89345s/12 iters), loss = 5.26811 +I0410 14:06:14.563737 18534 solver.cpp:237] Train net output #0: loss = 5.26811 (* 1 = 5.26811 loss) +I0410 14:06:14.563746 18534 sgd_solver.cpp:105] Iteration 4848, lr = 0.0038277 +I0410 14:06:17.137907 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:06:19.457038 18534 solver.cpp:218] Iteration 4860 (2.45243 iter/s, 4.89311s/12 iters), loss = 5.26794 +I0410 14:06:19.457087 18534 solver.cpp:237] Train net output #0: loss = 5.26794 (* 1 = 5.26794 loss) +I0410 14:06:19.457096 18534 sgd_solver.cpp:105] Iteration 4860, lr = 0.00381862 +I0410 14:06:24.390699 18534 solver.cpp:218] Iteration 4872 (2.43239 iter/s, 4.93341s/12 iters), loss = 5.26412 +I0410 14:06:24.390745 18534 solver.cpp:237] Train net output #0: loss = 5.26412 (* 1 = 5.26412 loss) +I0410 14:06:24.390754 18534 sgd_solver.cpp:105] Iteration 4872, lr = 0.00380955 +I0410 14:06:29.305686 18534 solver.cpp:218] Iteration 4884 (2.44163 iter/s, 4.91475s/12 iters), loss = 5.26737 +I0410 14:06:29.305747 18534 solver.cpp:237] Train net output #0: loss = 5.26737 (* 1 = 5.26737 loss) +I0410 14:06:29.305759 18534 sgd_solver.cpp:105] Iteration 4884, lr = 0.0038005 +I0410 14:06:33.879088 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4896.caffemodel +I0410 14:06:34.609182 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4896.solverstate +I0410 14:06:34.822939 18534 solver.cpp:330] Iteration 4896, Testing net (#0) +I0410 14:06:34.822962 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:06:37.238111 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:06:39.171339 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:06:39.171383 18534 solver.cpp:397] Test net output #1: loss = 5.28701 (* 1 = 5.28701 loss) +I0410 14:06:39.252513 18534 solver.cpp:218] Iteration 4896 (1.20647 iter/s, 9.9464s/12 iters), loss = 5.26946 +I0410 14:06:39.252562 18534 solver.cpp:237] Train net output #0: loss = 5.26946 (* 1 = 5.26946 loss) +I0410 14:06:39.252573 18534 sgd_solver.cpp:105] Iteration 4896, lr = 0.00379148 +I0410 14:06:43.415050 18534 solver.cpp:218] Iteration 4908 (2.88301 iter/s, 4.16232s/12 iters), loss = 5.29033 +I0410 14:06:43.415093 18534 solver.cpp:237] Train net output #0: loss = 5.29033 (* 1 = 5.29033 loss) +I0410 14:06:43.415102 18534 sgd_solver.cpp:105] Iteration 4908, lr = 0.00378248 +I0410 14:06:48.418200 18534 solver.cpp:218] Iteration 4920 (2.3986 iter/s, 5.00291s/12 iters), loss = 5.27149 +I0410 14:06:48.418323 18534 solver.cpp:237] Train net output #0: loss = 5.27149 (* 1 = 5.27149 loss) +I0410 14:06:48.418334 18534 sgd_solver.cpp:105] Iteration 4920, lr = 0.0037735 +I0410 14:06:53.282511 18534 solver.cpp:218] Iteration 4932 (2.4671 iter/s, 4.86401s/12 iters), loss = 5.26398 +I0410 14:06:53.282557 18534 solver.cpp:237] Train net output #0: loss = 5.26398 (* 1 = 5.26398 loss) +I0410 14:06:53.282565 18534 sgd_solver.cpp:105] Iteration 4932, lr = 0.00376454 +I0410 14:06:58.140475 18534 solver.cpp:218] Iteration 4944 (2.47029 iter/s, 4.85773s/12 iters), loss = 5.2659 +I0410 14:06:58.140520 18534 solver.cpp:237] Train net output #0: loss = 5.2659 (* 1 = 5.2659 loss) +I0410 14:06:58.140529 18534 sgd_solver.cpp:105] Iteration 4944, lr = 0.0037556 +I0410 14:07:02.888422 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:07:03.079031 18534 solver.cpp:218] Iteration 4956 (2.42998 iter/s, 4.93832s/12 iters), loss = 5.25053 +I0410 14:07:03.079073 18534 solver.cpp:237] Train net output #0: loss = 5.25053 (* 1 = 5.25053 loss) +I0410 14:07:03.079082 18534 sgd_solver.cpp:105] Iteration 4956, lr = 0.00374669 +I0410 14:07:07.959661 18534 solver.cpp:218] Iteration 4968 (2.45882 iter/s, 4.8804s/12 iters), loss = 5.26377 +I0410 14:07:07.959714 18534 solver.cpp:237] Train net output #0: loss = 5.26377 (* 1 = 5.26377 loss) +I0410 14:07:07.959725 18534 sgd_solver.cpp:105] Iteration 4968, lr = 0.00373779 +I0410 14:07:12.890306 18534 solver.cpp:218] Iteration 4980 (2.43388 iter/s, 4.9304s/12 iters), loss = 5.29271 +I0410 14:07:12.890348 18534 solver.cpp:237] Train net output #0: loss = 5.29271 (* 1 = 5.29271 loss) +I0410 14:07:12.890359 18534 sgd_solver.cpp:105] Iteration 4980, lr = 0.00372892 +I0410 14:07:17.798513 18534 solver.cpp:218] Iteration 4992 (2.445 iter/s, 4.90798s/12 iters), loss = 5.2835 +I0410 14:07:17.798554 18534 solver.cpp:237] Train net output #0: loss = 5.2835 (* 1 = 5.2835 loss) +I0410 14:07:17.798564 18534 sgd_solver.cpp:105] Iteration 4992, lr = 0.00372006 +I0410 14:07:19.798645 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4998.caffemodel +I0410 14:07:20.347246 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4998.solverstate +I0410 14:07:20.914685 18534 solver.cpp:330] Iteration 4998, Testing net (#0) +I0410 14:07:20.914716 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:07:23.291375 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:07:25.277034 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:07:25.277083 18534 solver.cpp:397] Test net output #1: loss = 5.28682 (* 1 = 5.28682 loss) +I0410 14:07:27.196889 18534 solver.cpp:218] Iteration 5004 (1.27687 iter/s, 9.39798s/12 iters), loss = 5.27917 +I0410 14:07:27.196936 18534 solver.cpp:237] Train net output #0: loss = 5.27917 (* 1 = 5.27917 loss) +I0410 14:07:27.196946 18534 sgd_solver.cpp:105] Iteration 5004, lr = 0.00371123 +I0410 14:07:32.089864 18534 solver.cpp:218] Iteration 5016 (2.45262 iter/s, 4.89274s/12 iters), loss = 5.26752 +I0410 14:07:32.089912 18534 solver.cpp:237] Train net output #0: loss = 5.26752 (* 1 = 5.26752 loss) +I0410 14:07:32.089920 18534 sgd_solver.cpp:105] Iteration 5016, lr = 0.00370242 +I0410 14:07:36.924360 18534 solver.cpp:218] Iteration 5028 (2.48228 iter/s, 4.83426s/12 iters), loss = 5.25019 +I0410 14:07:36.924404 18534 solver.cpp:237] Train net output #0: loss = 5.25019 (* 1 = 5.25019 loss) +I0410 14:07:36.924413 18534 sgd_solver.cpp:105] Iteration 5028, lr = 0.00369363 +I0410 14:07:41.779165 18534 solver.cpp:218] Iteration 5040 (2.4719 iter/s, 4.85457s/12 iters), loss = 5.28451 +I0410 14:07:41.779212 18534 solver.cpp:237] Train net output #0: loss = 5.28451 (* 1 = 5.28451 loss) +I0410 14:07:41.779220 18534 sgd_solver.cpp:105] Iteration 5040, lr = 0.00368486 +I0410 14:07:46.690609 18534 solver.cpp:218] Iteration 5052 (2.4434 iter/s, 4.9112s/12 iters), loss = 5.27084 +I0410 14:07:46.690667 18534 solver.cpp:237] Train net output #0: loss = 5.27084 (* 1 = 5.27084 loss) +I0410 14:07:46.690680 18534 sgd_solver.cpp:105] Iteration 5052, lr = 0.00367611 +I0410 14:07:48.630232 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:07:51.655778 18534 solver.cpp:218] Iteration 5064 (2.41696 iter/s, 4.96491s/12 iters), loss = 5.29019 +I0410 14:07:51.655907 18534 solver.cpp:237] Train net output #0: loss = 5.29019 (* 1 = 5.29019 loss) +I0410 14:07:51.655920 18534 sgd_solver.cpp:105] Iteration 5064, lr = 0.00366738 +I0410 14:07:56.544926 18534 solver.cpp:218] Iteration 5076 (2.45457 iter/s, 4.88883s/12 iters), loss = 5.27279 +I0410 14:07:56.544976 18534 solver.cpp:237] Train net output #0: loss = 5.27279 (* 1 = 5.27279 loss) +I0410 14:07:56.544988 18534 sgd_solver.cpp:105] Iteration 5076, lr = 0.00365868 +I0410 14:08:01.517330 18534 solver.cpp:218] Iteration 5088 (2.41344 iter/s, 4.97216s/12 iters), loss = 5.2646 +I0410 14:08:01.517382 18534 solver.cpp:237] Train net output #0: loss = 5.2646 (* 1 = 5.2646 loss) +I0410 14:08:01.517393 18534 sgd_solver.cpp:105] Iteration 5088, lr = 0.00364999 +I0410 14:08:05.981436 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5100.caffemodel +I0410 14:08:07.316174 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5100.solverstate +I0410 14:08:07.529420 18534 solver.cpp:330] Iteration 5100, Testing net (#0) +I0410 14:08:07.529448 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:08:09.899732 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:11.914623 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:08:11.914657 18534 solver.cpp:397] Test net output #1: loss = 5.28653 (* 1 = 5.28653 loss) +I0410 14:08:11.997216 18534 solver.cpp:218] Iteration 5100 (1.1451 iter/s, 10.4794s/12 iters), loss = 5.26652 +I0410 14:08:11.997272 18534 solver.cpp:237] Train net output #0: loss = 5.26652 (* 1 = 5.26652 loss) +I0410 14:08:11.997283 18534 sgd_solver.cpp:105] Iteration 5100, lr = 0.00364132 +I0410 14:08:16.163930 18534 solver.cpp:218] Iteration 5112 (2.88012 iter/s, 4.16649s/12 iters), loss = 5.264 +I0410 14:08:16.163981 18534 solver.cpp:237] Train net output #0: loss = 5.264 (* 1 = 5.264 loss) +I0410 14:08:16.163992 18534 sgd_solver.cpp:105] Iteration 5112, lr = 0.00363268 +I0410 14:08:21.083678 18534 solver.cpp:218] Iteration 5124 (2.43927 iter/s, 4.91951s/12 iters), loss = 5.27266 +I0410 14:08:21.083724 18534 solver.cpp:237] Train net output #0: loss = 5.27266 (* 1 = 5.27266 loss) +I0410 14:08:21.083734 18534 sgd_solver.cpp:105] Iteration 5124, lr = 0.00362405 +I0410 14:08:26.067891 18534 solver.cpp:218] Iteration 5136 (2.40772 iter/s, 4.98397s/12 iters), loss = 5.27026 +I0410 14:08:26.068042 18534 solver.cpp:237] Train net output #0: loss = 5.27026 (* 1 = 5.27026 loss) +I0410 14:08:26.068056 18534 sgd_solver.cpp:105] Iteration 5136, lr = 0.00361545 +I0410 14:08:30.917809 18534 solver.cpp:218] Iteration 5148 (2.47444 iter/s, 4.84958s/12 iters), loss = 5.26115 +I0410 14:08:30.917860 18534 solver.cpp:237] Train net output #0: loss = 5.26115 (* 1 = 5.26115 loss) +I0410 14:08:30.917871 18534 sgd_solver.cpp:105] Iteration 5148, lr = 0.00360687 +I0410 14:08:35.033205 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:35.938796 18534 solver.cpp:218] Iteration 5160 (2.39009 iter/s, 5.02074s/12 iters), loss = 5.25612 +I0410 14:08:35.938835 18534 solver.cpp:237] Train net output #0: loss = 5.25612 (* 1 = 5.25612 loss) +I0410 14:08:35.938844 18534 sgd_solver.cpp:105] Iteration 5160, lr = 0.0035983 +I0410 14:08:40.798403 18534 solver.cpp:218] Iteration 5172 (2.46945 iter/s, 4.85937s/12 iters), loss = 5.27784 +I0410 14:08:40.798460 18534 solver.cpp:237] Train net output #0: loss = 5.27784 (* 1 = 5.27784 loss) +I0410 14:08:40.798472 18534 sgd_solver.cpp:105] Iteration 5172, lr = 0.00358976 +I0410 14:08:45.768537 18534 solver.cpp:218] Iteration 5184 (2.41454 iter/s, 4.96988s/12 iters), loss = 5.27205 +I0410 14:08:45.768589 18534 solver.cpp:237] Train net output #0: loss = 5.27205 (* 1 = 5.27205 loss) +I0410 14:08:45.768601 18534 sgd_solver.cpp:105] Iteration 5184, lr = 0.00358124 +I0410 14:08:50.582741 18534 solver.cpp:218] Iteration 5196 (2.49275 iter/s, 4.81396s/12 iters), loss = 5.30738 +I0410 14:08:50.582793 18534 solver.cpp:237] Train net output #0: loss = 5.30738 (* 1 = 5.30738 loss) +I0410 14:08:50.582806 18534 sgd_solver.cpp:105] Iteration 5196, lr = 0.00357273 +I0410 14:08:52.614343 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5202.caffemodel +I0410 14:08:53.100692 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5202.solverstate +I0410 14:08:53.718741 18534 solver.cpp:330] Iteration 5202, Testing net (#0) +I0410 14:08:53.718770 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:08:56.119937 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:58.165135 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:08:58.165180 18534 solver.cpp:397] Test net output #1: loss = 5.28669 (* 1 = 5.28669 loss) +I0410 14:09:00.003630 18534 solver.cpp:218] Iteration 5208 (1.27382 iter/s, 9.42048s/12 iters), loss = 5.27279 +I0410 14:09:00.003686 18534 solver.cpp:237] Train net output #0: loss = 5.27279 (* 1 = 5.27279 loss) +I0410 14:09:00.003700 18534 sgd_solver.cpp:105] Iteration 5208, lr = 0.00356425 +I0410 14:09:04.930722 18534 solver.cpp:218] Iteration 5220 (2.43563 iter/s, 4.92685s/12 iters), loss = 5.27384 +I0410 14:09:04.930770 18534 solver.cpp:237] Train net output #0: loss = 5.27384 (* 1 = 5.27384 loss) +I0410 14:09:04.930781 18534 sgd_solver.cpp:105] Iteration 5220, lr = 0.00355579 +I0410 14:09:09.917428 18534 solver.cpp:218] Iteration 5232 (2.40652 iter/s, 4.98646s/12 iters), loss = 5.2804 +I0410 14:09:09.917470 18534 solver.cpp:237] Train net output #0: loss = 5.2804 (* 1 = 5.2804 loss) +I0410 14:09:09.917479 18534 sgd_solver.cpp:105] Iteration 5232, lr = 0.00354735 +I0410 14:09:14.979001 18534 solver.cpp:218] Iteration 5244 (2.37092 iter/s, 5.06133s/12 iters), loss = 5.27066 +I0410 14:09:14.979043 18534 solver.cpp:237] Train net output #0: loss = 5.27066 (* 1 = 5.27066 loss) +I0410 14:09:14.979050 18534 sgd_solver.cpp:105] Iteration 5244, lr = 0.00353892 +I0410 14:09:19.863624 18534 solver.cpp:218] Iteration 5256 (2.45681 iter/s, 4.88439s/12 iters), loss = 5.25703 +I0410 14:09:19.863684 18534 solver.cpp:237] Train net output #0: loss = 5.25703 (* 1 = 5.25703 loss) +I0410 14:09:19.863698 18534 sgd_solver.cpp:105] Iteration 5256, lr = 0.00353052 +I0410 14:09:21.117172 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:09:24.742910 18534 solver.cpp:218] Iteration 5268 (2.4595 iter/s, 4.87904s/12 iters), loss = 5.27696 +I0410 14:09:24.742959 18534 solver.cpp:237] Train net output #0: loss = 5.27696 (* 1 = 5.27696 loss) +I0410 14:09:24.742967 18534 sgd_solver.cpp:105] Iteration 5268, lr = 0.00352214 +I0410 14:09:29.620543 18534 solver.cpp:218] Iteration 5280 (2.46033 iter/s, 4.87739s/12 iters), loss = 5.2674 +I0410 14:09:29.620692 18534 solver.cpp:237] Train net output #0: loss = 5.2674 (* 1 = 5.2674 loss) +I0410 14:09:29.620707 18534 sgd_solver.cpp:105] Iteration 5280, lr = 0.00351378 +I0410 14:09:34.456787 18534 solver.cpp:218] Iteration 5292 (2.48144 iter/s, 4.83591s/12 iters), loss = 5.27698 +I0410 14:09:34.456840 18534 solver.cpp:237] Train net output #0: loss = 5.27698 (* 1 = 5.27698 loss) +I0410 14:09:34.456851 18534 sgd_solver.cpp:105] Iteration 5292, lr = 0.00350544 +I0410 14:09:38.940742 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5304.caffemodel +I0410 14:09:39.479388 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5304.solverstate +I0410 14:09:40.085136 18534 solver.cpp:330] Iteration 5304, Testing net (#0) +I0410 14:09:40.085165 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:09:42.333761 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:09:44.423508 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:09:44.423547 18534 solver.cpp:397] Test net output #1: loss = 5.28647 (* 1 = 5.28647 loss) +I0410 14:09:44.504168 18534 solver.cpp:218] Iteration 5304 (1.19439 iter/s, 10.0469s/12 iters), loss = 5.27081 +I0410 14:09:44.504227 18534 solver.cpp:237] Train net output #0: loss = 5.27081 (* 1 = 5.27081 loss) +I0410 14:09:44.504238 18534 sgd_solver.cpp:105] Iteration 5304, lr = 0.00349711 +I0410 14:09:48.658756 18534 solver.cpp:218] Iteration 5316 (2.88853 iter/s, 4.15437s/12 iters), loss = 5.26819 +I0410 14:09:48.658794 18534 solver.cpp:237] Train net output #0: loss = 5.26819 (* 1 = 5.26819 loss) +I0410 14:09:48.658803 18534 sgd_solver.cpp:105] Iteration 5316, lr = 0.00348881 +I0410 14:09:53.622570 18534 solver.cpp:218] Iteration 5328 (2.41761 iter/s, 4.96357s/12 iters), loss = 5.25997 +I0410 14:09:53.622625 18534 solver.cpp:237] Train net output #0: loss = 5.25997 (* 1 = 5.25997 loss) +I0410 14:09:53.622637 18534 sgd_solver.cpp:105] Iteration 5328, lr = 0.00348053 +I0410 14:09:58.543323 18534 solver.cpp:218] Iteration 5340 (2.43878 iter/s, 4.9205s/12 iters), loss = 5.30224 +I0410 14:09:58.543376 18534 solver.cpp:237] Train net output #0: loss = 5.30224 (* 1 = 5.30224 loss) +I0410 14:09:58.543388 18534 sgd_solver.cpp:105] Iteration 5340, lr = 0.00347226 +I0410 14:10:03.391250 18534 solver.cpp:218] Iteration 5352 (2.47541 iter/s, 4.84768s/12 iters), loss = 5.27602 +I0410 14:10:03.391397 18534 solver.cpp:237] Train net output #0: loss = 5.27602 (* 1 = 5.27602 loss) +I0410 14:10:03.391409 18534 sgd_solver.cpp:105] Iteration 5352, lr = 0.00346402 +I0410 14:10:06.666225 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:10:08.186883 18534 solver.cpp:218] Iteration 5364 (2.50245 iter/s, 4.7953s/12 iters), loss = 5.27655 +I0410 14:10:08.186928 18534 solver.cpp:237] Train net output #0: loss = 5.27655 (* 1 = 5.27655 loss) +I0410 14:10:08.186936 18534 sgd_solver.cpp:105] Iteration 5364, lr = 0.0034558 +I0410 14:10:13.081660 18534 solver.cpp:218] Iteration 5376 (2.45171 iter/s, 4.89453s/12 iters), loss = 5.26539 +I0410 14:10:13.081719 18534 solver.cpp:237] Train net output #0: loss = 5.26539 (* 1 = 5.26539 loss) +I0410 14:10:13.081732 18534 sgd_solver.cpp:105] Iteration 5376, lr = 0.00344759 +I0410 14:10:17.892290 18534 solver.cpp:218] Iteration 5388 (2.4946 iter/s, 4.81039s/12 iters), loss = 5.26667 +I0410 14:10:17.892340 18534 solver.cpp:237] Train net output #0: loss = 5.26667 (* 1 = 5.26667 loss) +I0410 14:10:17.892351 18534 sgd_solver.cpp:105] Iteration 5388, lr = 0.00343941 +I0410 14:10:22.677450 18534 solver.cpp:218] Iteration 5400 (2.50788 iter/s, 4.78492s/12 iters), loss = 5.2698 +I0410 14:10:22.677500 18534 solver.cpp:237] Train net output #0: loss = 5.2698 (* 1 = 5.2698 loss) +I0410 14:10:22.677510 18534 sgd_solver.cpp:105] Iteration 5400, lr = 0.00343124 +I0410 14:10:24.646152 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5406.caffemodel +I0410 14:10:24.969197 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5406.solverstate +I0410 14:10:25.180004 18534 solver.cpp:330] Iteration 5406, Testing net (#0) +I0410 14:10:25.180037 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:10:27.587338 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:10:29.699530 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:10:29.699568 18534 solver.cpp:397] Test net output #1: loss = 5.28658 (* 1 = 5.28658 loss) +I0410 14:10:31.553289 18534 solver.cpp:218] Iteration 5412 (1.35204 iter/s, 8.87545s/12 iters), loss = 5.26411 +I0410 14:10:31.553351 18534 solver.cpp:237] Train net output #0: loss = 5.26411 (* 1 = 5.26411 loss) +I0410 14:10:31.553364 18534 sgd_solver.cpp:105] Iteration 5412, lr = 0.00342309 +I0410 14:10:36.500613 18534 solver.cpp:218] Iteration 5424 (2.42568 iter/s, 4.94707s/12 iters), loss = 5.27958 +I0410 14:10:36.500710 18534 solver.cpp:237] Train net output #0: loss = 5.27958 (* 1 = 5.27958 loss) +I0410 14:10:36.500720 18534 sgd_solver.cpp:105] Iteration 5424, lr = 0.00341497 +I0410 14:10:41.379899 18534 solver.cpp:218] Iteration 5436 (2.45952 iter/s, 4.87899s/12 iters), loss = 5.26717 +I0410 14:10:41.379947 18534 solver.cpp:237] Train net output #0: loss = 5.26717 (* 1 = 5.26717 loss) +I0410 14:10:41.379956 18534 sgd_solver.cpp:105] Iteration 5436, lr = 0.00340686 +I0410 14:10:46.351294 18534 solver.cpp:218] Iteration 5448 (2.41393 iter/s, 4.97115s/12 iters), loss = 5.27909 +I0410 14:10:46.351351 18534 solver.cpp:237] Train net output #0: loss = 5.27909 (* 1 = 5.27909 loss) +I0410 14:10:46.351361 18534 sgd_solver.cpp:105] Iteration 5448, lr = 0.00339877 +I0410 14:10:51.219871 18534 solver.cpp:218] Iteration 5460 (2.46491 iter/s, 4.86833s/12 iters), loss = 5.27997 +I0410 14:10:51.219928 18534 solver.cpp:237] Train net output #0: loss = 5.27997 (* 1 = 5.27997 loss) +I0410 14:10:51.219940 18534 sgd_solver.cpp:105] Iteration 5460, lr = 0.0033907 +I0410 14:10:51.761358 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:10:56.115741 18534 solver.cpp:218] Iteration 5472 (2.45117 iter/s, 4.89562s/12 iters), loss = 5.27826 +I0410 14:10:56.115789 18534 solver.cpp:237] Train net output #0: loss = 5.27826 (* 1 = 5.27826 loss) +I0410 14:10:56.115801 18534 sgd_solver.cpp:105] Iteration 5472, lr = 0.00338265 +I0410 14:11:01.050582 18534 solver.cpp:218] Iteration 5484 (2.43181 iter/s, 4.9346s/12 iters), loss = 5.27448 +I0410 14:11:01.050637 18534 solver.cpp:237] Train net output #0: loss = 5.27448 (* 1 = 5.27448 loss) +I0410 14:11:01.050648 18534 sgd_solver.cpp:105] Iteration 5484, lr = 0.00337462 +I0410 14:11:06.001469 18534 solver.cpp:218] Iteration 5496 (2.42393 iter/s, 4.95064s/12 iters), loss = 5.29228 +I0410 14:11:06.001515 18534 solver.cpp:237] Train net output #0: loss = 5.29228 (* 1 = 5.29228 loss) +I0410 14:11:06.001524 18534 sgd_solver.cpp:105] Iteration 5496, lr = 0.00336661 +I0410 14:11:10.415592 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5508.caffemodel +I0410 14:11:10.731891 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5508.solverstate +I0410 14:11:10.935155 18534 solver.cpp:330] Iteration 5508, Testing net (#0) +I0410 14:11:10.935182 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:11:13.217383 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:11:15.388444 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:11:15.388485 18534 solver.cpp:397] Test net output #1: loss = 5.2875 (* 1 = 5.2875 loss) +I0410 14:11:15.470726 18534 solver.cpp:218] Iteration 5508 (1.26731 iter/s, 9.46885s/12 iters), loss = 5.27688 +I0410 14:11:15.470774 18534 solver.cpp:237] Train net output #0: loss = 5.27688 (* 1 = 5.27688 loss) +I0410 14:11:15.470784 18534 sgd_solver.cpp:105] Iteration 5508, lr = 0.00335861 +I0410 14:11:19.605052 18534 solver.cpp:218] Iteration 5520 (2.90268 iter/s, 4.13411s/12 iters), loss = 5.27598 +I0410 14:11:19.605098 18534 solver.cpp:237] Train net output #0: loss = 5.27598 (* 1 = 5.27598 loss) +I0410 14:11:19.605106 18534 sgd_solver.cpp:105] Iteration 5520, lr = 0.00335064 +I0410 14:11:20.361567 18534 blocking_queue.cpp:49] Waiting for data +I0410 14:11:24.443722 18534 solver.cpp:218] Iteration 5532 (2.48014 iter/s, 4.83843s/12 iters), loss = 5.28887 +I0410 14:11:24.443768 18534 solver.cpp:237] Train net output #0: loss = 5.28887 (* 1 = 5.28887 loss) +I0410 14:11:24.443778 18534 sgd_solver.cpp:105] Iteration 5532, lr = 0.00334268 +I0410 14:11:29.311197 18534 solver.cpp:218] Iteration 5544 (2.46547 iter/s, 4.86723s/12 iters), loss = 5.25797 +I0410 14:11:29.311249 18534 solver.cpp:237] Train net output #0: loss = 5.25797 (* 1 = 5.25797 loss) +I0410 14:11:29.311261 18534 sgd_solver.cpp:105] Iteration 5544, lr = 0.00333475 +I0410 14:11:34.217281 18534 solver.cpp:218] Iteration 5556 (2.44607 iter/s, 4.90583s/12 iters), loss = 5.26917 +I0410 14:11:34.217339 18534 solver.cpp:237] Train net output #0: loss = 5.26917 (* 1 = 5.26917 loss) +I0410 14:11:34.217350 18534 sgd_solver.cpp:105] Iteration 5556, lr = 0.00332683 +I0410 14:11:36.858814 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:11:39.120335 18534 solver.cpp:218] Iteration 5568 (2.44758 iter/s, 4.90281s/12 iters), loss = 5.27776 +I0410 14:11:39.120388 18534 solver.cpp:237] Train net output #0: loss = 5.27776 (* 1 = 5.27776 loss) +I0410 14:11:39.120400 18534 sgd_solver.cpp:105] Iteration 5568, lr = 0.00331893 +I0410 14:11:44.096726 18534 solver.cpp:218] Iteration 5580 (2.41151 iter/s, 4.97614s/12 iters), loss = 5.25968 +I0410 14:11:44.096805 18534 solver.cpp:237] Train net output #0: loss = 5.25968 (* 1 = 5.25968 loss) +I0410 14:11:44.096817 18534 sgd_solver.cpp:105] Iteration 5580, lr = 0.00331105 +I0410 14:11:49.036504 18534 solver.cpp:218] Iteration 5592 (2.42939 iter/s, 4.93951s/12 iters), loss = 5.26885 +I0410 14:11:49.036545 18534 solver.cpp:237] Train net output #0: loss = 5.26885 (* 1 = 5.26885 loss) +I0410 14:11:49.036554 18534 sgd_solver.cpp:105] Iteration 5592, lr = 0.00330319 +I0410 14:11:53.932282 18534 solver.cpp:218] Iteration 5604 (2.45121 iter/s, 4.89555s/12 iters), loss = 5.26367 +I0410 14:11:53.932320 18534 solver.cpp:237] Train net output #0: loss = 5.26367 (* 1 = 5.26367 loss) +I0410 14:11:53.932329 18534 sgd_solver.cpp:105] Iteration 5604, lr = 0.00329535 +I0410 14:11:55.933638 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5610.caffemodel +I0410 14:11:56.236804 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5610.solverstate +I0410 14:11:56.464804 18534 solver.cpp:330] Iteration 5610, Testing net (#0) +I0410 14:11:56.464828 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:11:58.798918 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:01.104566 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:12:01.104615 18534 solver.cpp:397] Test net output #1: loss = 5.28684 (* 1 = 5.28684 loss) +I0410 14:12:02.902381 18534 solver.cpp:218] Iteration 5616 (1.33783 iter/s, 8.96972s/12 iters), loss = 5.29348 +I0410 14:12:02.902428 18534 solver.cpp:237] Train net output #0: loss = 5.29348 (* 1 = 5.29348 loss) +I0410 14:12:02.902439 18534 sgd_solver.cpp:105] Iteration 5616, lr = 0.00328752 +I0410 14:12:07.811568 18534 solver.cpp:218] Iteration 5628 (2.44452 iter/s, 4.90894s/12 iters), loss = 5.27392 +I0410 14:12:07.811612 18534 solver.cpp:237] Train net output #0: loss = 5.27392 (* 1 = 5.27392 loss) +I0410 14:12:07.811621 18534 sgd_solver.cpp:105] Iteration 5628, lr = 0.00327972 +I0410 14:12:12.704025 18534 solver.cpp:218] Iteration 5640 (2.45287 iter/s, 4.89222s/12 iters), loss = 5.26338 +I0410 14:12:12.704068 18534 solver.cpp:237] Train net output #0: loss = 5.26338 (* 1 = 5.26338 loss) +I0410 14:12:12.704079 18534 sgd_solver.cpp:105] Iteration 5640, lr = 0.00327193 +I0410 14:12:17.632879 18534 solver.cpp:218] Iteration 5652 (2.43476 iter/s, 4.92861s/12 iters), loss = 5.26535 +I0410 14:12:17.633042 18534 solver.cpp:237] Train net output #0: loss = 5.26535 (* 1 = 5.26535 loss) +I0410 14:12:17.633057 18534 sgd_solver.cpp:105] Iteration 5652, lr = 0.00326416 +I0410 14:12:22.465842 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:22.623638 18534 solver.cpp:218] Iteration 5664 (2.40462 iter/s, 4.9904s/12 iters), loss = 5.25089 +I0410 14:12:22.623692 18534 solver.cpp:237] Train net output #0: loss = 5.25089 (* 1 = 5.25089 loss) +I0410 14:12:22.623704 18534 sgd_solver.cpp:105] Iteration 5664, lr = 0.00325641 +I0410 14:12:27.511411 18534 solver.cpp:218] Iteration 5676 (2.45523 iter/s, 4.88752s/12 iters), loss = 5.265 +I0410 14:12:27.511485 18534 solver.cpp:237] Train net output #0: loss = 5.265 (* 1 = 5.265 loss) +I0410 14:12:27.511503 18534 sgd_solver.cpp:105] Iteration 5676, lr = 0.00324868 +I0410 14:12:32.376303 18534 solver.cpp:218] Iteration 5688 (2.46679 iter/s, 4.86463s/12 iters), loss = 5.29405 +I0410 14:12:32.376353 18534 solver.cpp:237] Train net output #0: loss = 5.29405 (* 1 = 5.29405 loss) +I0410 14:12:32.376363 18534 sgd_solver.cpp:105] Iteration 5688, lr = 0.00324097 +I0410 14:12:37.282078 18534 solver.cpp:218] Iteration 5700 (2.44622 iter/s, 4.90553s/12 iters), loss = 5.28705 +I0410 14:12:37.282137 18534 solver.cpp:237] Train net output #0: loss = 5.28705 (* 1 = 5.28705 loss) +I0410 14:12:37.282148 18534 sgd_solver.cpp:105] Iteration 5700, lr = 0.00323328 +I0410 14:12:41.711927 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5712.caffemodel +I0410 14:12:42.029397 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5712.solverstate +I0410 14:12:42.241655 18534 solver.cpp:330] Iteration 5712, Testing net (#0) +I0410 14:12:42.241674 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:12:44.447324 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:46.681407 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:12:46.681458 18534 solver.cpp:397] Test net output #1: loss = 5.28681 (* 1 = 5.28681 loss) +I0410 14:12:46.763864 18534 solver.cpp:218] Iteration 5712 (1.26564 iter/s, 9.48137s/12 iters), loss = 5.27858 +I0410 14:12:46.763907 18534 solver.cpp:237] Train net output #0: loss = 5.27858 (* 1 = 5.27858 loss) +I0410 14:12:46.763916 18534 sgd_solver.cpp:105] Iteration 5712, lr = 0.0032256 +I0410 14:12:50.975705 18534 solver.cpp:218] Iteration 5724 (2.84926 iter/s, 4.21162s/12 iters), loss = 5.26452 +I0410 14:12:50.975821 18534 solver.cpp:237] Train net output #0: loss = 5.26452 (* 1 = 5.26452 loss) +I0410 14:12:50.975831 18534 sgd_solver.cpp:105] Iteration 5724, lr = 0.00321794 +I0410 14:12:55.918490 18534 solver.cpp:218] Iteration 5736 (2.42793 iter/s, 4.94247s/12 iters), loss = 5.24267 +I0410 14:12:55.918540 18534 solver.cpp:237] Train net output #0: loss = 5.24267 (* 1 = 5.24267 loss) +I0410 14:12:55.918550 18534 sgd_solver.cpp:105] Iteration 5736, lr = 0.0032103 +I0410 14:13:00.803385 18534 solver.cpp:218] Iteration 5748 (2.45667 iter/s, 4.88465s/12 iters), loss = 5.27843 +I0410 14:13:00.803428 18534 solver.cpp:237] Train net output #0: loss = 5.27843 (* 1 = 5.27843 loss) +I0410 14:13:00.803437 18534 sgd_solver.cpp:105] Iteration 5748, lr = 0.00320268 +I0410 14:13:05.659471 18534 solver.cpp:218] Iteration 5760 (2.47125 iter/s, 4.85585s/12 iters), loss = 5.26456 +I0410 14:13:05.659525 18534 solver.cpp:237] Train net output #0: loss = 5.26456 (* 1 = 5.26456 loss) +I0410 14:13:05.659535 18534 sgd_solver.cpp:105] Iteration 5760, lr = 0.00319508 +I0410 14:13:07.680017 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:10.666508 18534 solver.cpp:218] Iteration 5772 (2.39675 iter/s, 5.00678s/12 iters), loss = 5.29057 +I0410 14:13:10.666554 18534 solver.cpp:237] Train net output #0: loss = 5.29057 (* 1 = 5.29057 loss) +I0410 14:13:10.666564 18534 sgd_solver.cpp:105] Iteration 5772, lr = 0.00318749 +I0410 14:13:15.556952 18534 solver.cpp:218] Iteration 5784 (2.45389 iter/s, 4.8902s/12 iters), loss = 5.26989 +I0410 14:13:15.557005 18534 solver.cpp:237] Train net output #0: loss = 5.26989 (* 1 = 5.26989 loss) +I0410 14:13:15.557016 18534 sgd_solver.cpp:105] Iteration 5784, lr = 0.00317992 +I0410 14:13:20.450242 18534 solver.cpp:218] Iteration 5796 (2.45246 iter/s, 4.89305s/12 iters), loss = 5.27271 +I0410 14:13:20.450284 18534 solver.cpp:237] Train net output #0: loss = 5.27271 (* 1 = 5.27271 loss) +I0410 14:13:20.450291 18534 sgd_solver.cpp:105] Iteration 5796, lr = 0.00317237 +I0410 14:13:25.267078 18534 solver.cpp:218] Iteration 5808 (2.49138 iter/s, 4.8166s/12 iters), loss = 5.26507 +I0410 14:13:25.267163 18534 solver.cpp:237] Train net output #0: loss = 5.26507 (* 1 = 5.26507 loss) +I0410 14:13:25.267171 18534 sgd_solver.cpp:105] Iteration 5808, lr = 0.00316484 +I0410 14:13:27.223489 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5814.caffemodel +I0410 14:13:28.074947 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5814.solverstate +I0410 14:13:28.435148 18534 solver.cpp:330] Iteration 5814, Testing net (#0) +I0410 14:13:28.435178 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:13:30.574834 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:32.857719 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:13:32.857767 18534 solver.cpp:397] Test net output #1: loss = 5.28673 (* 1 = 5.28673 loss) +I0410 14:13:34.757620 18534 solver.cpp:218] Iteration 5820 (1.26448 iter/s, 9.4901s/12 iters), loss = 5.27288 +I0410 14:13:34.757675 18534 solver.cpp:237] Train net output #0: loss = 5.27288 (* 1 = 5.27288 loss) +I0410 14:13:34.757688 18534 sgd_solver.cpp:105] Iteration 5820, lr = 0.00315733 +I0410 14:13:39.655989 18534 solver.cpp:218] Iteration 5832 (2.44992 iter/s, 4.89812s/12 iters), loss = 5.27203 +I0410 14:13:39.656039 18534 solver.cpp:237] Train net output #0: loss = 5.27203 (* 1 = 5.27203 loss) +I0410 14:13:39.656051 18534 sgd_solver.cpp:105] Iteration 5832, lr = 0.00314983 +I0410 14:13:44.486552 18534 solver.cpp:218] Iteration 5844 (2.48431 iter/s, 4.83032s/12 iters), loss = 5.26297 +I0410 14:13:44.486605 18534 solver.cpp:237] Train net output #0: loss = 5.26297 (* 1 = 5.26297 loss) +I0410 14:13:44.486616 18534 sgd_solver.cpp:105] Iteration 5844, lr = 0.00314235 +I0410 14:13:49.401065 18534 solver.cpp:218] Iteration 5856 (2.44187 iter/s, 4.91427s/12 iters), loss = 5.2605 +I0410 14:13:49.401108 18534 solver.cpp:237] Train net output #0: loss = 5.2605 (* 1 = 5.2605 loss) +I0410 14:13:49.401116 18534 sgd_solver.cpp:105] Iteration 5856, lr = 0.00313489 +I0410 14:13:53.519115 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:54.305675 18534 solver.cpp:218] Iteration 5868 (2.4468 iter/s, 4.90437s/12 iters), loss = 5.25517 +I0410 14:13:54.305744 18534 solver.cpp:237] Train net output #0: loss = 5.25517 (* 1 = 5.25517 loss) +I0410 14:13:54.305760 18534 sgd_solver.cpp:105] Iteration 5868, lr = 0.00312745 +I0410 14:13:59.237139 18534 solver.cpp:218] Iteration 5880 (2.43348 iter/s, 4.9312s/12 iters), loss = 5.27875 +I0410 14:13:59.237288 18534 solver.cpp:237] Train net output #0: loss = 5.27875 (* 1 = 5.27875 loss) +I0410 14:13:59.237301 18534 sgd_solver.cpp:105] Iteration 5880, lr = 0.00312002 +I0410 14:14:04.101250 18534 solver.cpp:218] Iteration 5892 (2.46722 iter/s, 4.86377s/12 iters), loss = 5.26982 +I0410 14:14:04.101295 18534 solver.cpp:237] Train net output #0: loss = 5.26982 (* 1 = 5.26982 loss) +I0410 14:14:04.101305 18534 sgd_solver.cpp:105] Iteration 5892, lr = 0.00311262 +I0410 14:14:08.951406 18534 solver.cpp:218] Iteration 5904 (2.47427 iter/s, 4.84991s/12 iters), loss = 5.30357 +I0410 14:14:08.951462 18534 solver.cpp:237] Train net output #0: loss = 5.30357 (* 1 = 5.30357 loss) +I0410 14:14:08.951473 18534 sgd_solver.cpp:105] Iteration 5904, lr = 0.00310523 +I0410 14:14:13.369752 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5916.caffemodel +I0410 14:14:13.682626 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5916.solverstate +I0410 14:14:13.883208 18534 solver.cpp:330] Iteration 5916, Testing net (#0) +I0410 14:14:13.883235 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:14:15.932950 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:14:18.250443 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:14:18.250505 18534 solver.cpp:397] Test net output #1: loss = 5.28677 (* 1 = 5.28677 loss) +I0410 14:14:18.332823 18534 solver.cpp:218] Iteration 5916 (1.27918 iter/s, 9.381s/12 iters), loss = 5.26682 +I0410 14:14:18.332877 18534 solver.cpp:237] Train net output #0: loss = 5.26682 (* 1 = 5.26682 loss) +I0410 14:14:18.332888 18534 sgd_solver.cpp:105] Iteration 5916, lr = 0.00309785 +I0410 14:14:22.387260 18534 solver.cpp:218] Iteration 5928 (2.95988 iter/s, 4.05422s/12 iters), loss = 5.2718 +I0410 14:14:22.387315 18534 solver.cpp:237] Train net output #0: loss = 5.2718 (* 1 = 5.2718 loss) +I0410 14:14:22.387326 18534 sgd_solver.cpp:105] Iteration 5928, lr = 0.0030905 +I0410 14:14:27.266561 18534 solver.cpp:218] Iteration 5940 (2.45949 iter/s, 4.87905s/12 iters), loss = 5.28019 +I0410 14:14:27.266618 18534 solver.cpp:237] Train net output #0: loss = 5.28019 (* 1 = 5.28019 loss) +I0410 14:14:27.266631 18534 sgd_solver.cpp:105] Iteration 5940, lr = 0.00308316 +I0410 14:14:32.192191 18534 solver.cpp:218] Iteration 5952 (2.43636 iter/s, 4.92538s/12 iters), loss = 5.27425 +I0410 14:14:32.192293 18534 solver.cpp:237] Train net output #0: loss = 5.27425 (* 1 = 5.27425 loss) +I0410 14:14:32.192304 18534 sgd_solver.cpp:105] Iteration 5952, lr = 0.00307584 +I0410 14:14:37.120944 18534 solver.cpp:218] Iteration 5964 (2.43484 iter/s, 4.92846s/12 iters), loss = 5.25872 +I0410 14:14:37.120998 18534 solver.cpp:237] Train net output #0: loss = 5.25872 (* 1 = 5.25872 loss) +I0410 14:14:37.121009 18534 sgd_solver.cpp:105] Iteration 5964, lr = 0.00306854 +I0410 14:14:38.400094 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:14:42.002702 18534 solver.cpp:218] Iteration 5976 (2.45825 iter/s, 4.88151s/12 iters), loss = 5.27573 +I0410 14:14:42.002756 18534 solver.cpp:237] Train net output #0: loss = 5.27573 (* 1 = 5.27573 loss) +I0410 14:14:42.002768 18534 sgd_solver.cpp:105] Iteration 5976, lr = 0.00306125 +I0410 14:14:46.934674 18534 solver.cpp:218] Iteration 5988 (2.43323 iter/s, 4.93172s/12 iters), loss = 5.26303 +I0410 14:14:46.934722 18534 solver.cpp:237] Train net output #0: loss = 5.26303 (* 1 = 5.26303 loss) +I0410 14:14:46.934731 18534 sgd_solver.cpp:105] Iteration 5988, lr = 0.00305398 +I0410 14:14:51.825636 18534 solver.cpp:218] Iteration 6000 (2.45363 iter/s, 4.89072s/12 iters), loss = 5.28248 +I0410 14:14:51.825683 18534 solver.cpp:237] Train net output #0: loss = 5.28248 (* 1 = 5.28248 loss) +I0410 14:14:51.825692 18534 sgd_solver.cpp:105] Iteration 6000, lr = 0.00304673 +I0410 14:14:56.696138 18534 solver.cpp:218] Iteration 6012 (2.46393 iter/s, 4.87026s/12 iters), loss = 5.26995 +I0410 14:14:56.696187 18534 solver.cpp:237] Train net output #0: loss = 5.26995 (* 1 = 5.26995 loss) +I0410 14:14:56.696197 18534 sgd_solver.cpp:105] Iteration 6012, lr = 0.0030395 +I0410 14:14:58.689178 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6018.caffemodel +I0410 14:14:59.095253 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6018.solverstate +I0410 14:14:59.295331 18534 solver.cpp:330] Iteration 6018, Testing net (#0) +I0410 14:14:59.295359 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:15:01.343220 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:03.743261 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:15:03.743422 18534 solver.cpp:397] Test net output #1: loss = 5.28679 (* 1 = 5.28679 loss) +I0410 14:15:05.538898 18534 solver.cpp:218] Iteration 6024 (1.3571 iter/s, 8.84237s/12 iters), loss = 5.26611 +I0410 14:15:05.538947 18534 solver.cpp:237] Train net output #0: loss = 5.26611 (* 1 = 5.26611 loss) +I0410 14:15:05.538959 18534 sgd_solver.cpp:105] Iteration 6024, lr = 0.00303228 +I0410 14:15:10.385726 18534 solver.cpp:218] Iteration 6036 (2.47597 iter/s, 4.84658s/12 iters), loss = 5.26077 +I0410 14:15:10.385782 18534 solver.cpp:237] Train net output #0: loss = 5.26077 (* 1 = 5.26077 loss) +I0410 14:15:10.385794 18534 sgd_solver.cpp:105] Iteration 6036, lr = 0.00302508 +I0410 14:15:15.249887 18534 solver.cpp:218] Iteration 6048 (2.46715 iter/s, 4.86391s/12 iters), loss = 5.30352 +I0410 14:15:15.249939 18534 solver.cpp:237] Train net output #0: loss = 5.30352 (* 1 = 5.30352 loss) +I0410 14:15:15.249950 18534 sgd_solver.cpp:105] Iteration 6048, lr = 0.0030179 +I0410 14:15:20.165072 18534 solver.cpp:218] Iteration 6060 (2.44154 iter/s, 4.91494s/12 iters), loss = 5.27576 +I0410 14:15:20.165127 18534 solver.cpp:237] Train net output #0: loss = 5.27576 (* 1 = 5.27576 loss) +I0410 14:15:20.165139 18534 sgd_solver.cpp:105] Iteration 6060, lr = 0.00301074 +I0410 14:15:23.578868 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:25.104750 18534 solver.cpp:218] Iteration 6072 (2.42944 iter/s, 4.93942s/12 iters), loss = 5.27482 +I0410 14:15:25.104805 18534 solver.cpp:237] Train net output #0: loss = 5.27482 (* 1 = 5.27482 loss) +I0410 14:15:25.104816 18534 sgd_solver.cpp:105] Iteration 6072, lr = 0.00300359 +I0410 14:15:30.024454 18534 solver.cpp:218] Iteration 6084 (2.4393 iter/s, 4.91945s/12 iters), loss = 5.2581 +I0410 14:15:30.024513 18534 solver.cpp:237] Train net output #0: loss = 5.2581 (* 1 = 5.2581 loss) +I0410 14:15:30.024524 18534 sgd_solver.cpp:105] Iteration 6084, lr = 0.00299646 +I0410 14:15:34.947295 18534 solver.cpp:218] Iteration 6096 (2.43774 iter/s, 4.92259s/12 iters), loss = 5.26012 +I0410 14:15:34.947391 18534 solver.cpp:237] Train net output #0: loss = 5.26012 (* 1 = 5.26012 loss) +I0410 14:15:34.947402 18534 sgd_solver.cpp:105] Iteration 6096, lr = 0.00298934 +I0410 14:15:39.914614 18534 solver.cpp:218] Iteration 6108 (2.41593 iter/s, 4.96703s/12 iters), loss = 5.27179 +I0410 14:15:39.914670 18534 solver.cpp:237] Train net output #0: loss = 5.27179 (* 1 = 5.27179 loss) +I0410 14:15:39.914681 18534 sgd_solver.cpp:105] Iteration 6108, lr = 0.00298225 +I0410 14:15:44.463094 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6120.caffemodel +I0410 14:15:44.775282 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6120.solverstate +I0410 14:15:44.979826 18534 solver.cpp:330] Iteration 6120, Testing net (#0) +I0410 14:15:44.979856 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:15:47.131232 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:49.544443 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:15:49.544488 18534 solver.cpp:397] Test net output #1: loss = 5.28674 (* 1 = 5.28674 loss) +I0410 14:15:49.627120 18534 solver.cpp:218] Iteration 6120 (1.23557 iter/s, 9.71208s/12 iters), loss = 5.26559 +I0410 14:15:49.627166 18534 solver.cpp:237] Train net output #0: loss = 5.26559 (* 1 = 5.26559 loss) +I0410 14:15:49.627177 18534 sgd_solver.cpp:105] Iteration 6120, lr = 0.00297517 +I0410 14:15:54.011569 18534 solver.cpp:218] Iteration 6132 (2.73708 iter/s, 4.38423s/12 iters), loss = 5.27311 +I0410 14:15:54.011618 18534 solver.cpp:237] Train net output #0: loss = 5.27311 (* 1 = 5.27311 loss) +I0410 14:15:54.011629 18534 sgd_solver.cpp:105] Iteration 6132, lr = 0.0029681 +I0410 14:15:58.850450 18534 solver.cpp:218] Iteration 6144 (2.48004 iter/s, 4.83864s/12 iters), loss = 5.27149 +I0410 14:15:58.850503 18534 solver.cpp:237] Train net output #0: loss = 5.27149 (* 1 = 5.27149 loss) +I0410 14:15:58.850515 18534 sgd_solver.cpp:105] Iteration 6144, lr = 0.00296105 +I0410 14:16:03.763655 18534 solver.cpp:218] Iteration 6156 (2.44252 iter/s, 4.91296s/12 iters), loss = 5.27921 +I0410 14:16:03.763703 18534 solver.cpp:237] Train net output #0: loss = 5.27921 (* 1 = 5.27921 loss) +I0410 14:16:03.763712 18534 sgd_solver.cpp:105] Iteration 6156, lr = 0.00295402 +I0410 14:16:08.625376 18534 solver.cpp:218] Iteration 6168 (2.46839 iter/s, 4.86147s/12 iters), loss = 5.28973 +I0410 14:16:08.626041 18534 solver.cpp:237] Train net output #0: loss = 5.28973 (* 1 = 5.28973 loss) +I0410 14:16:08.626052 18534 sgd_solver.cpp:105] Iteration 6168, lr = 0.00294701 +I0410 14:16:09.211099 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:16:13.579851 18534 solver.cpp:218] Iteration 6180 (2.42247 iter/s, 4.95362s/12 iters), loss = 5.28083 +I0410 14:16:13.579900 18534 solver.cpp:237] Train net output #0: loss = 5.28083 (* 1 = 5.28083 loss) +I0410 14:16:13.579910 18534 sgd_solver.cpp:105] Iteration 6180, lr = 0.00294001 +I0410 14:16:18.451295 18534 solver.cpp:218] Iteration 6192 (2.46346 iter/s, 4.8712s/12 iters), loss = 5.26592 +I0410 14:16:18.451349 18534 solver.cpp:237] Train net output #0: loss = 5.26592 (* 1 = 5.26592 loss) +I0410 14:16:18.451360 18534 sgd_solver.cpp:105] Iteration 6192, lr = 0.00293303 +I0410 14:16:23.323843 18534 solver.cpp:218] Iteration 6204 (2.4629 iter/s, 4.8723s/12 iters), loss = 5.28763 +I0410 14:16:23.323889 18534 solver.cpp:237] Train net output #0: loss = 5.28763 (* 1 = 5.28763 loss) +I0410 14:16:23.323897 18534 sgd_solver.cpp:105] Iteration 6204, lr = 0.00292607 +I0410 14:16:28.123170 18534 solver.cpp:218] Iteration 6216 (2.50047 iter/s, 4.79909s/12 iters), loss = 5.2784 +I0410 14:16:28.123216 18534 solver.cpp:237] Train net output #0: loss = 5.2784 (* 1 = 5.2784 loss) +I0410 14:16:28.123229 18534 sgd_solver.cpp:105] Iteration 6216, lr = 0.00291912 +I0410 14:16:30.109663 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6222.caffemodel +I0410 14:16:30.938685 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6222.solverstate +I0410 14:16:31.178357 18534 solver.cpp:330] Iteration 6222, Testing net (#0) +I0410 14:16:31.178381 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:16:33.075348 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:16:33.997843 18534 blocking_queue.cpp:49] Waiting for data +I0410 14:16:35.561115 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:16:35.561161 18534 solver.cpp:397] Test net output #1: loss = 5.28656 (* 1 = 5.28656 loss) +I0410 14:16:37.373445 18534 solver.cpp:218] Iteration 6228 (1.29732 iter/s, 9.24987s/12 iters), loss = 5.27612 +I0410 14:16:37.373497 18534 solver.cpp:237] Train net output #0: loss = 5.27612 (* 1 = 5.27612 loss) +I0410 14:16:37.373508 18534 sgd_solver.cpp:105] Iteration 6228, lr = 0.00291219 +I0410 14:16:42.305296 18534 solver.cpp:218] Iteration 6240 (2.43329 iter/s, 4.9316s/12 iters), loss = 5.27893 +I0410 14:16:42.305416 18534 solver.cpp:237] Train net output #0: loss = 5.27893 (* 1 = 5.27893 loss) +I0410 14:16:42.305428 18534 sgd_solver.cpp:105] Iteration 6240, lr = 0.00290528 +I0410 14:16:47.260113 18534 solver.cpp:218] Iteration 6252 (2.42204 iter/s, 4.9545s/12 iters), loss = 5.25924 +I0410 14:16:47.260157 18534 solver.cpp:237] Train net output #0: loss = 5.25924 (* 1 = 5.25924 loss) +I0410 14:16:47.260166 18534 sgd_solver.cpp:105] Iteration 6252, lr = 0.00289838 +I0410 14:16:52.184348 18534 solver.cpp:218] Iteration 6264 (2.43705 iter/s, 4.92399s/12 iters), loss = 5.26705 +I0410 14:16:52.184403 18534 solver.cpp:237] Train net output #0: loss = 5.26705 (* 1 = 5.26705 loss) +I0410 14:16:52.184415 18534 sgd_solver.cpp:105] Iteration 6264, lr = 0.0028915 +I0410 14:16:54.814631 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:16:56.998263 18534 solver.cpp:218] Iteration 6276 (2.4929 iter/s, 4.81367s/12 iters), loss = 5.27804 +I0410 14:16:56.998318 18534 solver.cpp:237] Train net output #0: loss = 5.27804 (* 1 = 5.27804 loss) +I0410 14:16:56.998330 18534 sgd_solver.cpp:105] Iteration 6276, lr = 0.00288463 +I0410 14:17:01.948585 18534 solver.cpp:218] Iteration 6288 (2.42421 iter/s, 4.95007s/12 iters), loss = 5.26047 +I0410 14:17:01.948635 18534 solver.cpp:237] Train net output #0: loss = 5.26047 (* 1 = 5.26047 loss) +I0410 14:17:01.948647 18534 sgd_solver.cpp:105] Iteration 6288, lr = 0.00287779 +I0410 14:17:06.860680 18534 solver.cpp:218] Iteration 6300 (2.44307 iter/s, 4.91185s/12 iters), loss = 5.26993 +I0410 14:17:06.860735 18534 solver.cpp:237] Train net output #0: loss = 5.26993 (* 1 = 5.26993 loss) +I0410 14:17:06.860747 18534 sgd_solver.cpp:105] Iteration 6300, lr = 0.00287095 +I0410 14:17:11.787189 18534 solver.cpp:218] Iteration 6312 (2.43592 iter/s, 4.92626s/12 iters), loss = 5.26255 +I0410 14:17:11.787235 18534 solver.cpp:237] Train net output #0: loss = 5.26255 (* 1 = 5.26255 loss) +I0410 14:17:11.787246 18534 sgd_solver.cpp:105] Iteration 6312, lr = 0.00286414 +I0410 14:17:16.266422 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6324.caffemodel +I0410 14:17:16.574748 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6324.solverstate +I0410 14:17:16.789392 18534 solver.cpp:330] Iteration 6324, Testing net (#0) +I0410 14:17:16.789420 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:17:18.686586 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:17:21.172159 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:17:21.172207 18534 solver.cpp:397] Test net output #1: loss = 5.28668 (* 1 = 5.28668 loss) +I0410 14:17:21.253196 18534 solver.cpp:218] Iteration 6324 (1.26775 iter/s, 9.4656s/12 iters), loss = 5.29864 +I0410 14:17:21.253248 18534 solver.cpp:237] Train net output #0: loss = 5.29864 (* 1 = 5.29864 loss) +I0410 14:17:21.253260 18534 sgd_solver.cpp:105] Iteration 6324, lr = 0.00285734 +I0410 14:17:25.507558 18534 solver.cpp:218] Iteration 6336 (2.82079 iter/s, 4.25413s/12 iters), loss = 5.27084 +I0410 14:17:25.507611 18534 solver.cpp:237] Train net output #0: loss = 5.27084 (* 1 = 5.27084 loss) +I0410 14:17:25.507622 18534 sgd_solver.cpp:105] Iteration 6336, lr = 0.00285055 +I0410 14:17:30.427506 18534 solver.cpp:218] Iteration 6348 (2.43917 iter/s, 4.9197s/12 iters), loss = 5.25941 +I0410 14:17:30.427567 18534 solver.cpp:237] Train net output #0: loss = 5.25941 (* 1 = 5.25941 loss) +I0410 14:17:30.427578 18534 sgd_solver.cpp:105] Iteration 6348, lr = 0.00284379 +I0410 14:17:35.392849 18534 solver.cpp:218] Iteration 6360 (2.41688 iter/s, 4.96508s/12 iters), loss = 5.26696 +I0410 14:17:35.392910 18534 solver.cpp:237] Train net output #0: loss = 5.26696 (* 1 = 5.26696 loss) +I0410 14:17:35.392922 18534 sgd_solver.cpp:105] Iteration 6360, lr = 0.00283703 +I0410 14:17:40.213997 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:17:40.353595 18534 solver.cpp:218] Iteration 6372 (2.41912 iter/s, 4.96049s/12 iters), loss = 5.25305 +I0410 14:17:40.353653 18534 solver.cpp:237] Train net output #0: loss = 5.25305 (* 1 = 5.25305 loss) +I0410 14:17:40.353664 18534 sgd_solver.cpp:105] Iteration 6372, lr = 0.0028303 +I0410 14:17:45.376929 18534 solver.cpp:218] Iteration 6384 (2.38897 iter/s, 5.02308s/12 iters), loss = 5.26748 +I0410 14:17:45.376982 18534 solver.cpp:237] Train net output #0: loss = 5.26748 (* 1 = 5.26748 loss) +I0410 14:17:45.376994 18534 sgd_solver.cpp:105] Iteration 6384, lr = 0.00282358 +I0410 14:17:50.302618 18534 solver.cpp:218] Iteration 6396 (2.43633 iter/s, 4.92544s/12 iters), loss = 5.29587 +I0410 14:17:50.302724 18534 solver.cpp:237] Train net output #0: loss = 5.29587 (* 1 = 5.29587 loss) +I0410 14:17:50.302734 18534 sgd_solver.cpp:105] Iteration 6396, lr = 0.00281687 +I0410 14:17:55.244793 18534 solver.cpp:218] Iteration 6408 (2.42823 iter/s, 4.94188s/12 iters), loss = 5.28409 +I0410 14:17:55.244843 18534 solver.cpp:237] Train net output #0: loss = 5.28409 (* 1 = 5.28409 loss) +I0410 14:17:55.244854 18534 sgd_solver.cpp:105] Iteration 6408, lr = 0.00281019 +I0410 14:18:00.226231 18534 solver.cpp:218] Iteration 6420 (2.40907 iter/s, 4.98118s/12 iters), loss = 5.27931 +I0410 14:18:00.226289 18534 solver.cpp:237] Train net output #0: loss = 5.27931 (* 1 = 5.27931 loss) +I0410 14:18:00.226300 18534 sgd_solver.cpp:105] Iteration 6420, lr = 0.00280351 +I0410 14:18:02.257938 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6426.caffemodel +I0410 14:18:02.566195 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6426.solverstate +I0410 14:18:02.780706 18534 solver.cpp:330] Iteration 6426, Testing net (#0) +I0410 14:18:02.780736 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:18:04.743849 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:07.471700 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:18:07.471750 18534 solver.cpp:397] Test net output #1: loss = 5.28664 (* 1 = 5.28664 loss) +I0410 14:18:09.246771 18534 solver.cpp:218] Iteration 6432 (1.33036 iter/s, 9.02013s/12 iters), loss = 5.27047 +I0410 14:18:09.246836 18534 solver.cpp:237] Train net output #0: loss = 5.27047 (* 1 = 5.27047 loss) +I0410 14:18:09.246848 18534 sgd_solver.cpp:105] Iteration 6432, lr = 0.00279686 +I0410 14:18:14.218901 18534 solver.cpp:218] Iteration 6444 (2.41358 iter/s, 4.97187s/12 iters), loss = 5.24393 +I0410 14:18:14.218950 18534 solver.cpp:237] Train net output #0: loss = 5.24393 (* 1 = 5.24393 loss) +I0410 14:18:14.218958 18534 sgd_solver.cpp:105] Iteration 6444, lr = 0.00279022 +I0410 14:18:19.127144 18534 solver.cpp:218] Iteration 6456 (2.44499 iter/s, 4.908s/12 iters), loss = 5.27463 +I0410 14:18:19.127202 18534 solver.cpp:237] Train net output #0: loss = 5.27463 (* 1 = 5.27463 loss) +I0410 14:18:19.127213 18534 sgd_solver.cpp:105] Iteration 6456, lr = 0.00278359 +I0410 14:18:24.149919 18534 solver.cpp:218] Iteration 6468 (2.38924 iter/s, 5.02252s/12 iters), loss = 5.26401 +I0410 14:18:24.150032 18534 solver.cpp:237] Train net output #0: loss = 5.26401 (* 1 = 5.26401 loss) +I0410 14:18:24.150041 18534 sgd_solver.cpp:105] Iteration 6468, lr = 0.00277698 +I0410 14:18:26.205685 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:29.156422 18534 solver.cpp:218] Iteration 6480 (2.39703 iter/s, 5.0062s/12 iters), loss = 5.28845 +I0410 14:18:29.156463 18534 solver.cpp:237] Train net output #0: loss = 5.28845 (* 1 = 5.28845 loss) +I0410 14:18:29.156471 18534 sgd_solver.cpp:105] Iteration 6480, lr = 0.00277039 +I0410 14:18:34.118367 18534 solver.cpp:218] Iteration 6492 (2.41853 iter/s, 4.9617s/12 iters), loss = 5.26915 +I0410 14:18:34.118422 18534 solver.cpp:237] Train net output #0: loss = 5.26915 (* 1 = 5.26915 loss) +I0410 14:18:34.118432 18534 sgd_solver.cpp:105] Iteration 6492, lr = 0.00276381 +I0410 14:18:39.148717 18534 solver.cpp:218] Iteration 6504 (2.38564 iter/s, 5.0301s/12 iters), loss = 5.2716 +I0410 14:18:39.148762 18534 solver.cpp:237] Train net output #0: loss = 5.2716 (* 1 = 5.2716 loss) +I0410 14:18:39.148772 18534 sgd_solver.cpp:105] Iteration 6504, lr = 0.00275725 +I0410 14:18:43.991930 18534 solver.cpp:218] Iteration 6516 (2.47782 iter/s, 4.84297s/12 iters), loss = 5.26337 +I0410 14:18:43.991981 18534 solver.cpp:237] Train net output #0: loss = 5.26337 (* 1 = 5.26337 loss) +I0410 14:18:43.991992 18534 sgd_solver.cpp:105] Iteration 6516, lr = 0.00275071 +I0410 14:18:48.419986 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6528.caffemodel +I0410 14:18:48.761438 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6528.solverstate +I0410 14:18:48.968361 18534 solver.cpp:330] Iteration 6528, Testing net (#0) +I0410 14:18:48.968389 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:18:50.914991 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:53.468370 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:18:53.468418 18534 solver.cpp:397] Test net output #1: loss = 5.28671 (* 1 = 5.28671 loss) +I0410 14:18:53.551291 18534 solver.cpp:218] Iteration 6528 (1.25537 iter/s, 9.55894s/12 iters), loss = 5.2707 +I0410 14:18:53.551360 18534 solver.cpp:237] Train net output #0: loss = 5.2707 (* 1 = 5.2707 loss) +I0410 14:18:53.551376 18534 sgd_solver.cpp:105] Iteration 6528, lr = 0.00274418 +I0410 14:18:57.725013 18534 solver.cpp:218] Iteration 6540 (2.87529 iter/s, 4.17349s/12 iters), loss = 5.27021 +I0410 14:18:57.726384 18534 solver.cpp:237] Train net output #0: loss = 5.27021 (* 1 = 5.27021 loss) +I0410 14:18:57.726397 18534 sgd_solver.cpp:105] Iteration 6540, lr = 0.00273766 +I0410 14:19:02.563851 18534 solver.cpp:218] Iteration 6552 (2.48073 iter/s, 4.83728s/12 iters), loss = 5.26443 +I0410 14:19:02.563901 18534 solver.cpp:237] Train net output #0: loss = 5.26443 (* 1 = 5.26443 loss) +I0410 14:19:02.563912 18534 sgd_solver.cpp:105] Iteration 6552, lr = 0.00273116 +I0410 14:19:07.465669 18534 solver.cpp:218] Iteration 6564 (2.44819 iter/s, 4.90157s/12 iters), loss = 5.25746 +I0410 14:19:07.465718 18534 solver.cpp:237] Train net output #0: loss = 5.25746 (* 1 = 5.25746 loss) +I0410 14:19:07.465730 18534 sgd_solver.cpp:105] Iteration 6564, lr = 0.00272468 +I0410 14:19:11.616585 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:19:12.379623 18534 solver.cpp:218] Iteration 6576 (2.44215 iter/s, 4.91371s/12 iters), loss = 5.25794 +I0410 14:19:12.379669 18534 solver.cpp:237] Train net output #0: loss = 5.25794 (* 1 = 5.25794 loss) +I0410 14:19:12.379679 18534 sgd_solver.cpp:105] Iteration 6576, lr = 0.00271821 +I0410 14:19:17.333271 18534 solver.cpp:218] Iteration 6588 (2.42258 iter/s, 4.9534s/12 iters), loss = 5.27871 +I0410 14:19:17.333324 18534 solver.cpp:237] Train net output #0: loss = 5.27871 (* 1 = 5.27871 loss) +I0410 14:19:17.333336 18534 sgd_solver.cpp:105] Iteration 6588, lr = 0.00271175 +I0410 14:19:22.232640 18534 solver.cpp:218] Iteration 6600 (2.44942 iter/s, 4.89912s/12 iters), loss = 5.27518 +I0410 14:19:22.232681 18534 solver.cpp:237] Train net output #0: loss = 5.27518 (* 1 = 5.27518 loss) +I0410 14:19:22.232689 18534 sgd_solver.cpp:105] Iteration 6600, lr = 0.00270532 +I0410 14:19:27.192431 18534 solver.cpp:218] Iteration 6612 (2.41957 iter/s, 4.95955s/12 iters), loss = 5.30447 +I0410 14:19:27.192489 18534 solver.cpp:237] Train net output #0: loss = 5.30447 (* 1 = 5.30447 loss) +I0410 14:19:27.192502 18534 sgd_solver.cpp:105] Iteration 6612, lr = 0.00269889 +I0410 14:19:32.166489 18534 solver.cpp:218] Iteration 6624 (2.41264 iter/s, 4.9738s/12 iters), loss = 5.2699 +I0410 14:19:32.166697 18534 solver.cpp:237] Train net output #0: loss = 5.2699 (* 1 = 5.2699 loss) +I0410 14:19:32.166709 18534 sgd_solver.cpp:105] Iteration 6624, lr = 0.00269248 +I0410 14:19:34.194006 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6630.caffemodel +I0410 14:19:34.483778 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6630.solverstate +I0410 14:19:34.701807 18534 solver.cpp:330] Iteration 6630, Testing net (#0) +I0410 14:19:34.701830 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:19:36.521003 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:19:39.107044 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:19:39.107093 18534 solver.cpp:397] Test net output #1: loss = 5.28682 (* 1 = 5.28682 loss) +I0410 14:19:40.880911 18534 solver.cpp:218] Iteration 6636 (1.37711 iter/s, 8.71388s/12 iters), loss = 5.27434 +I0410 14:19:40.880956 18534 solver.cpp:237] Train net output #0: loss = 5.27434 (* 1 = 5.27434 loss) +I0410 14:19:40.880965 18534 sgd_solver.cpp:105] Iteration 6636, lr = 0.00268609 +I0410 14:19:45.823406 18534 solver.cpp:218] Iteration 6648 (2.42804 iter/s, 4.94225s/12 iters), loss = 5.27723 +I0410 14:19:45.823462 18534 solver.cpp:237] Train net output #0: loss = 5.27723 (* 1 = 5.27723 loss) +I0410 14:19:45.823473 18534 sgd_solver.cpp:105] Iteration 6648, lr = 0.00267971 +I0410 14:19:50.698124 18534 solver.cpp:218] Iteration 6660 (2.46181 iter/s, 4.87447s/12 iters), loss = 5.28245 +I0410 14:19:50.698174 18534 solver.cpp:237] Train net output #0: loss = 5.28245 (* 1 = 5.28245 loss) +I0410 14:19:50.698185 18534 sgd_solver.cpp:105] Iteration 6660, lr = 0.00267335 +I0410 14:19:55.679049 18534 solver.cpp:218] Iteration 6672 (2.40931 iter/s, 4.98067s/12 iters), loss = 5.2623 +I0410 14:19:55.679096 18534 solver.cpp:237] Train net output #0: loss = 5.2623 (* 1 = 5.2623 loss) +I0410 14:19:55.679106 18534 sgd_solver.cpp:105] Iteration 6672, lr = 0.00266701 +I0410 14:19:56.990444 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:00.661365 18534 solver.cpp:218] Iteration 6684 (2.40864 iter/s, 4.98207s/12 iters), loss = 5.27493 +I0410 14:20:00.661408 18534 solver.cpp:237] Train net output #0: loss = 5.27493 (* 1 = 5.27493 loss) +I0410 14:20:00.661418 18534 sgd_solver.cpp:105] Iteration 6684, lr = 0.00266067 +I0410 14:20:05.649133 18534 solver.cpp:218] Iteration 6696 (2.406 iter/s, 4.98752s/12 iters), loss = 5.26815 +I0410 14:20:05.649289 18534 solver.cpp:237] Train net output #0: loss = 5.26815 (* 1 = 5.26815 loss) +I0410 14:20:05.649303 18534 sgd_solver.cpp:105] Iteration 6696, lr = 0.00265436 +I0410 14:20:10.568164 18534 solver.cpp:218] Iteration 6708 (2.43968 iter/s, 4.91869s/12 iters), loss = 5.27316 +I0410 14:20:10.568212 18534 solver.cpp:237] Train net output #0: loss = 5.27316 (* 1 = 5.27316 loss) +I0410 14:20:10.568220 18534 sgd_solver.cpp:105] Iteration 6708, lr = 0.00264805 +I0410 14:20:15.478951 18534 solver.cpp:218] Iteration 6720 (2.44372 iter/s, 4.91054s/12 iters), loss = 5.26959 +I0410 14:20:15.478996 18534 solver.cpp:237] Train net output #0: loss = 5.26959 (* 1 = 5.26959 loss) +I0410 14:20:15.479007 18534 sgd_solver.cpp:105] Iteration 6720, lr = 0.00264177 +I0410 14:20:19.977720 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6732.caffemodel +I0410 14:20:20.276520 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6732.solverstate +I0410 14:20:20.477159 18534 solver.cpp:330] Iteration 6732, Testing net (#0) +I0410 14:20:20.477190 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:20:22.299719 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:24.938423 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:20:24.938472 18534 solver.cpp:397] Test net output #1: loss = 5.28657 (* 1 = 5.28657 loss) +I0410 14:20:25.020817 18534 solver.cpp:218] Iteration 6732 (1.25767 iter/s, 9.54145s/12 iters), loss = 5.26895 +I0410 14:20:25.020866 18534 solver.cpp:237] Train net output #0: loss = 5.26895 (* 1 = 5.26895 loss) +I0410 14:20:25.020879 18534 sgd_solver.cpp:105] Iteration 6732, lr = 0.0026355 +I0410 14:20:29.193075 18534 solver.cpp:218] Iteration 6744 (2.87629 iter/s, 4.17204s/12 iters), loss = 5.25947 +I0410 14:20:29.193128 18534 solver.cpp:237] Train net output #0: loss = 5.25947 (* 1 = 5.25947 loss) +I0410 14:20:29.193140 18534 sgd_solver.cpp:105] Iteration 6744, lr = 0.00262924 +I0410 14:20:34.104079 18534 solver.cpp:218] Iteration 6756 (2.44362 iter/s, 4.91075s/12 iters), loss = 5.29319 +I0410 14:20:34.104135 18534 solver.cpp:237] Train net output #0: loss = 5.29319 (* 1 = 5.29319 loss) +I0410 14:20:34.104146 18534 sgd_solver.cpp:105] Iteration 6756, lr = 0.002623 +I0410 14:20:38.984037 18534 solver.cpp:218] Iteration 6768 (2.45916 iter/s, 4.87971s/12 iters), loss = 5.27287 +I0410 14:20:38.984181 18534 solver.cpp:237] Train net output #0: loss = 5.27287 (* 1 = 5.27287 loss) +I0410 14:20:38.984194 18534 sgd_solver.cpp:105] Iteration 6768, lr = 0.00261677 +I0410 14:20:42.385710 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:43.866673 18534 solver.cpp:218] Iteration 6780 (2.45786 iter/s, 4.8823s/12 iters), loss = 5.27693 +I0410 14:20:43.866734 18534 solver.cpp:237] Train net output #0: loss = 5.27693 (* 1 = 5.27693 loss) +I0410 14:20:43.866745 18534 sgd_solver.cpp:105] Iteration 6780, lr = 0.00261056 +I0410 14:20:48.842367 18534 solver.cpp:218] Iteration 6792 (2.41185 iter/s, 4.97544s/12 iters), loss = 5.25698 +I0410 14:20:48.842406 18534 solver.cpp:237] Train net output #0: loss = 5.25698 (* 1 = 5.25698 loss) +I0410 14:20:48.842414 18534 sgd_solver.cpp:105] Iteration 6792, lr = 0.00260436 +I0410 14:20:53.789712 18534 solver.cpp:218] Iteration 6804 (2.42566 iter/s, 4.9471s/12 iters), loss = 5.26502 +I0410 14:20:53.789763 18534 solver.cpp:237] Train net output #0: loss = 5.26502 (* 1 = 5.26502 loss) +I0410 14:20:53.789774 18534 sgd_solver.cpp:105] Iteration 6804, lr = 0.00259817 +I0410 14:20:58.720852 18534 solver.cpp:218] Iteration 6816 (2.43364 iter/s, 4.93089s/12 iters), loss = 5.27941 +I0410 14:20:58.720911 18534 solver.cpp:237] Train net output #0: loss = 5.27941 (* 1 = 5.27941 loss) +I0410 14:20:58.720923 18534 sgd_solver.cpp:105] Iteration 6816, lr = 0.00259201 +I0410 14:21:03.672516 18534 solver.cpp:218] Iteration 6828 (2.42355 iter/s, 4.95141s/12 iters), loss = 5.2658 +I0410 14:21:03.672564 18534 solver.cpp:237] Train net output #0: loss = 5.2658 (* 1 = 5.2658 loss) +I0410 14:21:03.672572 18534 sgd_solver.cpp:105] Iteration 6828, lr = 0.00258585 +I0410 14:21:05.686369 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6834.caffemodel +I0410 14:21:05.977036 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6834.solverstate +I0410 14:21:06.185125 18534 solver.cpp:330] Iteration 6834, Testing net (#0) +I0410 14:21:06.185149 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:21:07.962358 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:10.631592 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:21:10.631707 18534 solver.cpp:397] Test net output #1: loss = 5.28732 (* 1 = 5.28732 loss) +I0410 14:21:12.577600 18534 solver.cpp:218] Iteration 6840 (1.3476 iter/s, 8.90469s/12 iters), loss = 5.27623 +I0410 14:21:12.577644 18534 solver.cpp:237] Train net output #0: loss = 5.27623 (* 1 = 5.27623 loss) +I0410 14:21:12.577653 18534 sgd_solver.cpp:105] Iteration 6840, lr = 0.00257971 +I0410 14:21:17.557493 18534 solver.cpp:218] Iteration 6852 (2.40981 iter/s, 4.97965s/12 iters), loss = 5.27322 +I0410 14:21:17.557538 18534 solver.cpp:237] Train net output #0: loss = 5.27322 (* 1 = 5.27322 loss) +I0410 14:21:17.557546 18534 sgd_solver.cpp:105] Iteration 6852, lr = 0.00257359 +I0410 14:21:22.413193 18534 solver.cpp:218] Iteration 6864 (2.47145 iter/s, 4.85546s/12 iters), loss = 5.2786 +I0410 14:21:22.413245 18534 solver.cpp:237] Train net output #0: loss = 5.2786 (* 1 = 5.2786 loss) +I0410 14:21:22.413257 18534 sgd_solver.cpp:105] Iteration 6864, lr = 0.00256748 +I0410 14:21:27.320550 18534 solver.cpp:218] Iteration 6876 (2.44543 iter/s, 4.90711s/12 iters), loss = 5.2829 +I0410 14:21:27.320598 18534 solver.cpp:237] Train net output #0: loss = 5.2829 (* 1 = 5.2829 loss) +I0410 14:21:27.320608 18534 sgd_solver.cpp:105] Iteration 6876, lr = 0.00256138 +I0410 14:21:27.935735 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:32.519451 18534 solver.cpp:218] Iteration 6888 (2.3083 iter/s, 5.19864s/12 iters), loss = 5.28253 +I0410 14:21:32.519511 18534 solver.cpp:237] Train net output #0: loss = 5.28253 (* 1 = 5.28253 loss) +I0410 14:21:32.519526 18534 sgd_solver.cpp:105] Iteration 6888, lr = 0.0025553 +I0410 14:21:37.365483 18534 solver.cpp:218] Iteration 6900 (2.47638 iter/s, 4.84578s/12 iters), loss = 5.26713 +I0410 14:21:37.365530 18534 solver.cpp:237] Train net output #0: loss = 5.26713 (* 1 = 5.26713 loss) +I0410 14:21:37.365537 18534 sgd_solver.cpp:105] Iteration 6900, lr = 0.00254923 +I0410 14:21:42.274930 18534 solver.cpp:218] Iteration 6912 (2.44439 iter/s, 4.90919s/12 iters), loss = 5.28754 +I0410 14:21:42.275091 18534 solver.cpp:237] Train net output #0: loss = 5.28754 (* 1 = 5.28754 loss) +I0410 14:21:42.275105 18534 sgd_solver.cpp:105] Iteration 6912, lr = 0.00254318 +I0410 14:21:47.128556 18534 solver.cpp:218] Iteration 6924 (2.47256 iter/s, 4.85327s/12 iters), loss = 5.28134 +I0410 14:21:47.128608 18534 solver.cpp:237] Train net output #0: loss = 5.28134 (* 1 = 5.28134 loss) +I0410 14:21:47.128618 18534 sgd_solver.cpp:105] Iteration 6924, lr = 0.00253714 +I0410 14:21:51.493674 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6936.caffemodel +I0410 14:21:51.909672 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6936.solverstate +I0410 14:21:52.127871 18534 solver.cpp:330] Iteration 6936, Testing net (#0) +I0410 14:21:52.127898 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:21:52.422577 18534 blocking_queue.cpp:49] Waiting for data +I0410 14:21:54.026145 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:56.798872 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:21:56.798903 18534 solver.cpp:397] Test net output #1: loss = 5.28704 (* 1 = 5.28704 loss) +I0410 14:21:56.880982 18534 solver.cpp:218] Iteration 6936 (1.23052 iter/s, 9.752s/12 iters), loss = 5.28341 +I0410 14:21:56.881026 18534 solver.cpp:237] Train net output #0: loss = 5.28341 (* 1 = 5.28341 loss) +I0410 14:21:56.881036 18534 sgd_solver.cpp:105] Iteration 6936, lr = 0.00253112 +I0410 14:22:01.068248 18534 solver.cpp:218] Iteration 6948 (2.86598 iter/s, 4.18705s/12 iters), loss = 5.277 +I0410 14:22:01.068305 18534 solver.cpp:237] Train net output #0: loss = 5.277 (* 1 = 5.277 loss) +I0410 14:22:01.068318 18534 sgd_solver.cpp:105] Iteration 6948, lr = 0.00252511 +I0410 14:22:06.097451 18534 solver.cpp:218] Iteration 6960 (2.38619 iter/s, 5.02895s/12 iters), loss = 5.26397 +I0410 14:22:06.097501 18534 solver.cpp:237] Train net output #0: loss = 5.26397 (* 1 = 5.26397 loss) +I0410 14:22:06.097513 18534 sgd_solver.cpp:105] Iteration 6960, lr = 0.00251911 +I0410 14:22:11.049865 18534 solver.cpp:218] Iteration 6972 (2.42318 iter/s, 4.95217s/12 iters), loss = 5.26613 +I0410 14:22:11.049919 18534 solver.cpp:237] Train net output #0: loss = 5.26613 (* 1 = 5.26613 loss) +I0410 14:22:11.049930 18534 sgd_solver.cpp:105] Iteration 6972, lr = 0.00251313 +I0410 14:22:13.779012 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:22:15.956043 18534 solver.cpp:218] Iteration 6984 (2.44602 iter/s, 4.90593s/12 iters), loss = 5.27623 +I0410 14:22:15.956094 18534 solver.cpp:237] Train net output #0: loss = 5.27623 (* 1 = 5.27623 loss) +I0410 14:22:15.956104 18534 sgd_solver.cpp:105] Iteration 6984, lr = 0.00250717 +I0410 14:22:20.861727 18534 solver.cpp:218] Iteration 6996 (2.44627 iter/s, 4.90543s/12 iters), loss = 5.25854 +I0410 14:22:20.861780 18534 solver.cpp:237] Train net output #0: loss = 5.25854 (* 1 = 5.25854 loss) +I0410 14:22:20.861794 18534 sgd_solver.cpp:105] Iteration 6996, lr = 0.00250121 +I0410 14:22:25.849655 18534 solver.cpp:218] Iteration 7008 (2.40593 iter/s, 4.98768s/12 iters), loss = 5.25967 +I0410 14:22:25.849704 18534 solver.cpp:237] Train net output #0: loss = 5.25967 (* 1 = 5.25967 loss) +I0410 14:22:25.849712 18534 sgd_solver.cpp:105] Iteration 7008, lr = 0.00249528 +I0410 14:22:30.759609 18534 solver.cpp:218] Iteration 7020 (2.44414 iter/s, 4.9097s/12 iters), loss = 5.25895 +I0410 14:22:30.759667 18534 solver.cpp:237] Train net output #0: loss = 5.25895 (* 1 = 5.25895 loss) +I0410 14:22:30.759680 18534 sgd_solver.cpp:105] Iteration 7020, lr = 0.00248935 +I0410 14:22:35.688169 18534 solver.cpp:218] Iteration 7032 (2.43491 iter/s, 4.92831s/12 iters), loss = 5.30403 +I0410 14:22:35.688220 18534 solver.cpp:237] Train net output #0: loss = 5.30403 (* 1 = 5.30403 loss) +I0410 14:22:35.688231 18534 sgd_solver.cpp:105] Iteration 7032, lr = 0.00248344 +I0410 14:22:37.667681 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7038.caffemodel +I0410 14:22:37.970818 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7038.solverstate +I0410 14:22:38.175235 18534 solver.cpp:330] Iteration 7038, Testing net (#0) +I0410 14:22:38.175266 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:22:39.731312 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:22:42.474036 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:22:42.474084 18534 solver.cpp:397] Test net output #1: loss = 5.28675 (* 1 = 5.28675 loss) +I0410 14:22:44.164357 18534 solver.cpp:218] Iteration 7044 (1.41579 iter/s, 8.47581s/12 iters), loss = 5.27153 +I0410 14:22:44.164491 18534 solver.cpp:237] Train net output #0: loss = 5.27153 (* 1 = 5.27153 loss) +I0410 14:22:44.164502 18534 sgd_solver.cpp:105] Iteration 7044, lr = 0.00247755 +I0410 14:22:49.228929 18534 solver.cpp:218] Iteration 7056 (2.36955 iter/s, 5.06424s/12 iters), loss = 5.27028 +I0410 14:22:49.228972 18534 solver.cpp:237] Train net output #0: loss = 5.27028 (* 1 = 5.27028 loss) +I0410 14:22:49.228981 18534 sgd_solver.cpp:105] Iteration 7056, lr = 0.00247166 +I0410 14:22:54.202136 18534 solver.cpp:218] Iteration 7068 (2.41305 iter/s, 4.97296s/12 iters), loss = 5.26722 +I0410 14:22:54.202194 18534 solver.cpp:237] Train net output #0: loss = 5.26722 (* 1 = 5.26722 loss) +I0410 14:22:54.202206 18534 sgd_solver.cpp:105] Iteration 7068, lr = 0.0024658 +I0410 14:22:58.976999 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:22:59.085641 18534 solver.cpp:218] Iteration 7080 (2.45738 iter/s, 4.88325s/12 iters), loss = 5.24365 +I0410 14:22:59.085700 18534 solver.cpp:237] Train net output #0: loss = 5.24365 (* 1 = 5.24365 loss) +I0410 14:22:59.085711 18534 sgd_solver.cpp:105] Iteration 7080, lr = 0.00245994 +I0410 14:23:03.990491 18534 solver.cpp:218] Iteration 7092 (2.44668 iter/s, 4.9046s/12 iters), loss = 5.26754 +I0410 14:23:03.990543 18534 solver.cpp:237] Train net output #0: loss = 5.26754 (* 1 = 5.26754 loss) +I0410 14:23:03.990556 18534 sgd_solver.cpp:105] Iteration 7092, lr = 0.0024541 +I0410 14:23:08.898495 18534 solver.cpp:218] Iteration 7104 (2.44511 iter/s, 4.90776s/12 iters), loss = 5.29487 +I0410 14:23:08.898541 18534 solver.cpp:237] Train net output #0: loss = 5.29487 (* 1 = 5.29487 loss) +I0410 14:23:08.898550 18534 sgd_solver.cpp:105] Iteration 7104, lr = 0.00244827 +I0410 14:23:13.774649 18534 solver.cpp:218] Iteration 7116 (2.46108 iter/s, 4.87591s/12 iters), loss = 5.27444 +I0410 14:23:13.774699 18534 solver.cpp:237] Train net output #0: loss = 5.27444 (* 1 = 5.27444 loss) +I0410 14:23:13.774711 18534 sgd_solver.cpp:105] Iteration 7116, lr = 0.00244246 +I0410 14:23:18.662684 18534 solver.cpp:218] Iteration 7128 (2.4551 iter/s, 4.88778s/12 iters), loss = 5.275 +I0410 14:23:18.662806 18534 solver.cpp:237] Train net output #0: loss = 5.275 (* 1 = 5.275 loss) +I0410 14:23:18.662819 18534 sgd_solver.cpp:105] Iteration 7128, lr = 0.00243666 +I0410 14:23:23.047569 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7140.caffemodel +I0410 14:23:23.344727 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7140.solverstate +I0410 14:23:23.543838 18534 solver.cpp:330] Iteration 7140, Testing net (#0) +I0410 14:23:23.543866 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:23:25.136636 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:27.923447 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:23:27.923487 18534 solver.cpp:397] Test net output #1: loss = 5.28695 (* 1 = 5.28695 loss) +I0410 14:23:28.005707 18534 solver.cpp:218] Iteration 7140 (1.28445 iter/s, 9.34254s/12 iters), loss = 5.26389 +I0410 14:23:28.005766 18534 solver.cpp:237] Train net output #0: loss = 5.26389 (* 1 = 5.26389 loss) +I0410 14:23:28.005777 18534 sgd_solver.cpp:105] Iteration 7140, lr = 0.00243088 +I0410 14:23:32.351891 18534 solver.cpp:218] Iteration 7152 (2.76119 iter/s, 4.34594s/12 iters), loss = 5.24745 +I0410 14:23:32.351948 18534 solver.cpp:237] Train net output #0: loss = 5.24745 (* 1 = 5.24745 loss) +I0410 14:23:32.351960 18534 sgd_solver.cpp:105] Iteration 7152, lr = 0.00242511 +I0410 14:23:37.178519 18534 solver.cpp:218] Iteration 7164 (2.48634 iter/s, 4.82638s/12 iters), loss = 5.27238 +I0410 14:23:37.178572 18534 solver.cpp:237] Train net output #0: loss = 5.27238 (* 1 = 5.27238 loss) +I0410 14:23:37.178584 18534 sgd_solver.cpp:105] Iteration 7164, lr = 0.00241935 +I0410 14:23:42.079854 18534 solver.cpp:218] Iteration 7176 (2.44844 iter/s, 4.90109s/12 iters), loss = 5.25712 +I0410 14:23:42.079903 18534 solver.cpp:237] Train net output #0: loss = 5.25712 (* 1 = 5.25712 loss) +I0410 14:23:42.079914 18534 sgd_solver.cpp:105] Iteration 7176, lr = 0.0024136 +I0410 14:23:44.132684 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:46.937322 18534 solver.cpp:218] Iteration 7188 (2.47055 iter/s, 4.85723s/12 iters), loss = 5.27437 +I0410 14:23:46.937361 18534 solver.cpp:237] Train net output #0: loss = 5.27437 (* 1 = 5.27437 loss) +I0410 14:23:46.937369 18534 sgd_solver.cpp:105] Iteration 7188, lr = 0.00240787 +I0410 14:23:51.828631 18534 solver.cpp:218] Iteration 7200 (2.45345 iter/s, 4.89107s/12 iters), loss = 5.27128 +I0410 14:23:51.830272 18534 solver.cpp:237] Train net output #0: loss = 5.27128 (* 1 = 5.27128 loss) +I0410 14:23:51.830283 18534 sgd_solver.cpp:105] Iteration 7200, lr = 0.00240216 +I0410 14:23:56.857633 18534 solver.cpp:218] Iteration 7212 (2.38703 iter/s, 5.02716s/12 iters), loss = 5.27979 +I0410 14:23:56.857683 18534 solver.cpp:237] Train net output #0: loss = 5.27979 (* 1 = 5.27979 loss) +I0410 14:23:56.857695 18534 sgd_solver.cpp:105] Iteration 7212, lr = 0.00239645 +I0410 14:24:01.743615 18534 solver.cpp:218] Iteration 7224 (2.45613 iter/s, 4.88574s/12 iters), loss = 5.26562 +I0410 14:24:01.743674 18534 solver.cpp:237] Train net output #0: loss = 5.26562 (* 1 = 5.26562 loss) +I0410 14:24:01.743685 18534 sgd_solver.cpp:105] Iteration 7224, lr = 0.00239076 +I0410 14:24:06.723536 18534 solver.cpp:218] Iteration 7236 (2.4098 iter/s, 4.97966s/12 iters), loss = 5.2737 +I0410 14:24:06.723594 18534 solver.cpp:237] Train net output #0: loss = 5.2737 (* 1 = 5.2737 loss) +I0410 14:24:06.723606 18534 sgd_solver.cpp:105] Iteration 7236, lr = 0.00238509 +I0410 14:24:08.709991 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7242.caffemodel +I0410 14:24:09.033625 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7242.solverstate +I0410 14:24:09.246851 18534 solver.cpp:330] Iteration 7242, Testing net (#0) +I0410 14:24:09.246870 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:24:10.814785 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:13.787343 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:24:13.787380 18534 solver.cpp:397] Test net output #1: loss = 5.28657 (* 1 = 5.28657 loss) +I0410 14:24:15.603013 18534 solver.cpp:218] Iteration 7248 (1.35149 iter/s, 8.87907s/12 iters), loss = 5.27323 +I0410 14:24:15.603073 18534 solver.cpp:237] Train net output #0: loss = 5.27323 (* 1 = 5.27323 loss) +I0410 14:24:15.603085 18534 sgd_solver.cpp:105] Iteration 7248, lr = 0.00237942 +I0410 14:24:20.460618 18534 solver.cpp:218] Iteration 7260 (2.47048 iter/s, 4.85735s/12 iters), loss = 5.27021 +I0410 14:24:20.460667 18534 solver.cpp:237] Train net output #0: loss = 5.27021 (* 1 = 5.27021 loss) +I0410 14:24:20.460676 18534 sgd_solver.cpp:105] Iteration 7260, lr = 0.00237378 +I0410 14:24:25.342530 18534 solver.cpp:218] Iteration 7272 (2.45817 iter/s, 4.88167s/12 iters), loss = 5.25394 +I0410 14:24:25.342640 18534 solver.cpp:237] Train net output #0: loss = 5.25394 (* 1 = 5.25394 loss) +I0410 14:24:25.342649 18534 sgd_solver.cpp:105] Iteration 7272, lr = 0.00236814 +I0410 14:24:29.512686 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:30.237151 18534 solver.cpp:218] Iteration 7284 (2.45183 iter/s, 4.89431s/12 iters), loss = 5.2574 +I0410 14:24:30.237210 18534 solver.cpp:237] Train net output #0: loss = 5.2574 (* 1 = 5.2574 loss) +I0410 14:24:30.237221 18534 sgd_solver.cpp:105] Iteration 7284, lr = 0.00236252 +I0410 14:24:35.257568 18534 solver.cpp:218] Iteration 7296 (2.39036 iter/s, 5.02016s/12 iters), loss = 5.27963 +I0410 14:24:35.257616 18534 solver.cpp:237] Train net output #0: loss = 5.27963 (* 1 = 5.27963 loss) +I0410 14:24:35.257624 18534 sgd_solver.cpp:105] Iteration 7296, lr = 0.00235691 +I0410 14:24:40.086499 18534 solver.cpp:218] Iteration 7308 (2.48515 iter/s, 4.82869s/12 iters), loss = 5.2834 +I0410 14:24:40.086556 18534 solver.cpp:237] Train net output #0: loss = 5.2834 (* 1 = 5.2834 loss) +I0410 14:24:40.086568 18534 sgd_solver.cpp:105] Iteration 7308, lr = 0.00235131 +I0410 14:24:45.206450 18534 solver.cpp:218] Iteration 7320 (2.34389 iter/s, 5.1197s/12 iters), loss = 5.29403 +I0410 14:24:45.206502 18534 solver.cpp:237] Train net output #0: loss = 5.29403 (* 1 = 5.29403 loss) +I0410 14:24:45.206512 18534 sgd_solver.cpp:105] Iteration 7320, lr = 0.00234573 +I0410 14:24:50.198258 18534 solver.cpp:218] Iteration 7332 (2.40403 iter/s, 4.99162s/12 iters), loss = 5.26801 +I0410 14:24:50.198305 18534 solver.cpp:237] Train net output #0: loss = 5.26801 (* 1 = 5.26801 loss) +I0410 14:24:50.198314 18534 sgd_solver.cpp:105] Iteration 7332, lr = 0.00234016 +I0410 14:24:54.549685 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7344.caffemodel +I0410 14:24:54.839073 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7344.solverstate +I0410 14:24:55.052605 18534 solver.cpp:330] Iteration 7344, Testing net (#0) +I0410 14:24:55.052628 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:24:56.586037 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:59.506505 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:24:59.506553 18534 solver.cpp:397] Test net output #1: loss = 5.28745 (* 1 = 5.28745 loss) +I0410 14:24:59.589107 18534 solver.cpp:218] Iteration 7344 (1.27788 iter/s, 9.39054s/12 iters), loss = 5.27724 +I0410 14:24:59.589156 18534 solver.cpp:237] Train net output #0: loss = 5.27724 (* 1 = 5.27724 loss) +I0410 14:24:59.589166 18534 sgd_solver.cpp:105] Iteration 7344, lr = 0.0023346 +I0410 14:25:03.745592 18534 solver.cpp:218] Iteration 7356 (2.88717 iter/s, 4.15631s/12 iters), loss = 5.28251 +I0410 14:25:03.745640 18534 solver.cpp:237] Train net output #0: loss = 5.28251 (* 1 = 5.28251 loss) +I0410 14:25:03.745651 18534 sgd_solver.cpp:105] Iteration 7356, lr = 0.00232906 +I0410 14:25:08.708521 18534 solver.cpp:218] Iteration 7368 (2.41802 iter/s, 4.96274s/12 iters), loss = 5.27584 +I0410 14:25:08.708580 18534 solver.cpp:237] Train net output #0: loss = 5.27584 (* 1 = 5.27584 loss) +I0410 14:25:08.708591 18534 sgd_solver.cpp:105] Iteration 7368, lr = 0.00232353 +I0410 14:25:13.599236 18534 solver.cpp:218] Iteration 7380 (2.45373 iter/s, 4.89052s/12 iters), loss = 5.26325 +I0410 14:25:13.599279 18534 solver.cpp:237] Train net output #0: loss = 5.26325 (* 1 = 5.26325 loss) +I0410 14:25:13.599288 18534 sgd_solver.cpp:105] Iteration 7380, lr = 0.00231802 +I0410 14:25:14.947996 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:25:18.434053 18534 solver.cpp:218] Iteration 7392 (2.48209 iter/s, 4.83464s/12 iters), loss = 5.27412 +I0410 14:25:18.434101 18534 solver.cpp:237] Train net output #0: loss = 5.27412 (* 1 = 5.27412 loss) +I0410 14:25:18.434113 18534 sgd_solver.cpp:105] Iteration 7392, lr = 0.00231251 +I0410 14:25:23.289120 18534 solver.cpp:218] Iteration 7404 (2.47174 iter/s, 4.85488s/12 iters), loss = 5.27016 +I0410 14:25:23.289180 18534 solver.cpp:237] Train net output #0: loss = 5.27016 (* 1 = 5.27016 loss) +I0410 14:25:23.289192 18534 sgd_solver.cpp:105] Iteration 7404, lr = 0.00230702 +I0410 14:25:28.342814 18534 solver.cpp:218] Iteration 7416 (2.3746 iter/s, 5.05349s/12 iters), loss = 5.26757 +I0410 14:25:28.342965 18534 solver.cpp:237] Train net output #0: loss = 5.26757 (* 1 = 5.26757 loss) +I0410 14:25:28.342978 18534 sgd_solver.cpp:105] Iteration 7416, lr = 0.00230154 +I0410 14:25:33.350728 18534 solver.cpp:218] Iteration 7428 (2.39635 iter/s, 5.00762s/12 iters), loss = 5.27857 +I0410 14:25:33.350780 18534 solver.cpp:237] Train net output #0: loss = 5.27857 (* 1 = 5.27857 loss) +I0410 14:25:33.350791 18534 sgd_solver.cpp:105] Iteration 7428, lr = 0.00229608 +I0410 14:25:38.226027 18534 solver.cpp:218] Iteration 7440 (2.46149 iter/s, 4.8751s/12 iters), loss = 5.25873 +I0410 14:25:38.226086 18534 solver.cpp:237] Train net output #0: loss = 5.25873 (* 1 = 5.25873 loss) +I0410 14:25:38.226099 18534 sgd_solver.cpp:105] Iteration 7440, lr = 0.00229063 +I0410 14:25:40.202126 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7446.caffemodel +I0410 14:25:40.928267 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7446.solverstate +I0410 14:25:41.139859 18534 solver.cpp:330] Iteration 7446, Testing net (#0) +I0410 14:25:41.139878 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:25:42.663367 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:25:45.569358 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:25:45.569407 18534 solver.cpp:397] Test net output #1: loss = 5.2868 (* 1 = 5.2868 loss) +I0410 14:25:47.462594 18534 solver.cpp:218] Iteration 7452 (1.29923 iter/s, 9.23625s/12 iters), loss = 5.26637 +I0410 14:25:47.462649 18534 solver.cpp:237] Train net output #0: loss = 5.26637 (* 1 = 5.26637 loss) +I0410 14:25:47.462661 18534 sgd_solver.cpp:105] Iteration 7452, lr = 0.00228519 +I0410 14:25:52.437141 18534 solver.cpp:218] Iteration 7464 (2.41238 iter/s, 4.97435s/12 iters), loss = 5.2873 +I0410 14:25:52.437197 18534 solver.cpp:237] Train net output #0: loss = 5.2873 (* 1 = 5.2873 loss) +I0410 14:25:52.437209 18534 sgd_solver.cpp:105] Iteration 7464, lr = 0.00227976 +I0410 14:25:57.443336 18534 solver.cpp:218] Iteration 7476 (2.39713 iter/s, 5.00599s/12 iters), loss = 5.27512 +I0410 14:25:57.443394 18534 solver.cpp:237] Train net output #0: loss = 5.27512 (* 1 = 5.27512 loss) +I0410 14:25:57.443406 18534 sgd_solver.cpp:105] Iteration 7476, lr = 0.00227435 +I0410 14:26:00.857740 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:02.274735 18534 solver.cpp:218] Iteration 7488 (2.48386 iter/s, 4.83119s/12 iters), loss = 5.26971 +I0410 14:26:02.274796 18534 solver.cpp:237] Train net output #0: loss = 5.26971 (* 1 = 5.26971 loss) +I0410 14:26:02.274807 18534 sgd_solver.cpp:105] Iteration 7488, lr = 0.00226895 +I0410 14:26:07.155196 18534 solver.cpp:218] Iteration 7500 (2.45888 iter/s, 4.88026s/12 iters), loss = 5.25974 +I0410 14:26:07.155244 18534 solver.cpp:237] Train net output #0: loss = 5.25974 (* 1 = 5.25974 loss) +I0410 14:26:07.155256 18534 sgd_solver.cpp:105] Iteration 7500, lr = 0.00226357 +I0410 14:26:12.068393 18534 solver.cpp:218] Iteration 7512 (2.4425 iter/s, 4.91301s/12 iters), loss = 5.26086 +I0410 14:26:12.068437 18534 solver.cpp:237] Train net output #0: loss = 5.26086 (* 1 = 5.26086 loss) +I0410 14:26:12.068445 18534 sgd_solver.cpp:105] Iteration 7512, lr = 0.00225819 +I0410 14:26:16.969256 18534 solver.cpp:218] Iteration 7524 (2.44864 iter/s, 4.90067s/12 iters), loss = 5.26759 +I0410 14:26:16.969300 18534 solver.cpp:237] Train net output #0: loss = 5.26759 (* 1 = 5.26759 loss) +I0410 14:26:16.969310 18534 sgd_solver.cpp:105] Iteration 7524, lr = 0.00225283 +I0410 14:26:21.929252 18534 solver.cpp:218] Iteration 7536 (2.41945 iter/s, 4.9598s/12 iters), loss = 5.26247 +I0410 14:26:21.929296 18534 solver.cpp:237] Train net output #0: loss = 5.26247 (* 1 = 5.26247 loss) +I0410 14:26:21.929303 18534 sgd_solver.cpp:105] Iteration 7536, lr = 0.00224748 +I0410 14:26:26.390494 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7548.caffemodel +I0410 14:26:26.711891 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7548.solverstate +I0410 14:26:27.364814 18534 solver.cpp:330] Iteration 7548, Testing net (#0) +I0410 14:26:27.364846 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:26:28.883224 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:31.849004 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:26:31.849153 18534 solver.cpp:397] Test net output #1: loss = 5.28694 (* 1 = 5.28694 loss) +I0410 14:26:31.931658 18534 solver.cpp:218] Iteration 7548 (1.19975 iter/s, 10.0021s/12 iters), loss = 5.28221 +I0410 14:26:31.931705 18534 solver.cpp:237] Train net output #0: loss = 5.28221 (* 1 = 5.28221 loss) +I0410 14:26:31.931716 18534 sgd_solver.cpp:105] Iteration 7548, lr = 0.00224215 +I0410 14:26:36.158416 18534 solver.cpp:218] Iteration 7560 (2.83917 iter/s, 4.22658s/12 iters), loss = 5.26955 +I0410 14:26:36.158460 18534 solver.cpp:237] Train net output #0: loss = 5.26955 (* 1 = 5.26955 loss) +I0410 14:26:36.158470 18534 sgd_solver.cpp:105] Iteration 7560, lr = 0.00223682 +I0410 14:26:41.046540 18534 solver.cpp:218] Iteration 7572 (2.45503 iter/s, 4.88792s/12 iters), loss = 5.27978 +I0410 14:26:41.046586 18534 solver.cpp:237] Train net output #0: loss = 5.27978 (* 1 = 5.27978 loss) +I0410 14:26:41.046595 18534 sgd_solver.cpp:105] Iteration 7572, lr = 0.00223151 +I0410 14:26:45.853057 18534 solver.cpp:218] Iteration 7584 (2.49671 iter/s, 4.80633s/12 iters), loss = 5.28675 +I0410 14:26:45.853103 18534 solver.cpp:237] Train net output #0: loss = 5.28675 (* 1 = 5.28675 loss) +I0410 14:26:45.853113 18534 sgd_solver.cpp:105] Iteration 7584, lr = 0.00222621 +I0410 14:26:46.480399 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:50.868544 18534 solver.cpp:218] Iteration 7596 (2.39268 iter/s, 5.01529s/12 iters), loss = 5.27826 +I0410 14:26:50.868599 18534 solver.cpp:237] Train net output #0: loss = 5.27826 (* 1 = 5.27826 loss) +I0410 14:26:50.868611 18534 sgd_solver.cpp:105] Iteration 7596, lr = 0.00222093 +I0410 14:26:55.853731 18534 solver.cpp:218] Iteration 7608 (2.40723 iter/s, 4.98498s/12 iters), loss = 5.26342 +I0410 14:26:55.853775 18534 solver.cpp:237] Train net output #0: loss = 5.26342 (* 1 = 5.26342 loss) +I0410 14:26:55.853782 18534 sgd_solver.cpp:105] Iteration 7608, lr = 0.00221565 +I0410 14:27:00.771147 18534 solver.cpp:218] Iteration 7620 (2.4404 iter/s, 4.91722s/12 iters), loss = 5.27991 +I0410 14:27:00.771201 18534 solver.cpp:237] Train net output #0: loss = 5.27991 (* 1 = 5.27991 loss) +I0410 14:27:00.771214 18534 sgd_solver.cpp:105] Iteration 7620, lr = 0.00221039 +I0410 14:27:01.546363 18534 blocking_queue.cpp:49] Waiting for data +I0410 14:27:05.668231 18534 solver.cpp:218] Iteration 7632 (2.45054 iter/s, 4.89688s/12 iters), loss = 5.2809 +I0410 14:27:05.668342 18534 solver.cpp:237] Train net output #0: loss = 5.2809 (* 1 = 5.2809 loss) +I0410 14:27:05.668355 18534 sgd_solver.cpp:105] Iteration 7632, lr = 0.00220515 +I0410 14:27:10.552171 18534 solver.cpp:218] Iteration 7644 (2.45716 iter/s, 4.88368s/12 iters), loss = 5.28322 +I0410 14:27:10.552222 18534 solver.cpp:237] Train net output #0: loss = 5.28322 (* 1 = 5.28322 loss) +I0410 14:27:10.552232 18534 sgd_solver.cpp:105] Iteration 7644, lr = 0.00219991 +I0410 14:27:12.541599 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7650.caffemodel +I0410 14:27:12.849092 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7650.solverstate +I0410 14:27:13.047585 18534 solver.cpp:330] Iteration 7650, Testing net (#0) +I0410 14:27:13.047608 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:27:14.481367 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:27:17.701433 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:27:17.701476 18534 solver.cpp:397] Test net output #1: loss = 5.2871 (* 1 = 5.2871 loss) +I0410 14:27:19.483928 18534 solver.cpp:218] Iteration 7656 (1.34357 iter/s, 8.93144s/12 iters), loss = 5.27372 +I0410 14:27:19.483978 18534 solver.cpp:237] Train net output #0: loss = 5.27372 (* 1 = 5.27372 loss) +I0410 14:27:19.483985 18534 sgd_solver.cpp:105] Iteration 7656, lr = 0.00219469 +I0410 14:27:24.354461 18534 solver.cpp:218] Iteration 7668 (2.4639 iter/s, 4.87033s/12 iters), loss = 5.26632 +I0410 14:27:24.354511 18534 solver.cpp:237] Train net output #0: loss = 5.26632 (* 1 = 5.26632 loss) +I0410 14:27:24.354521 18534 sgd_solver.cpp:105] Iteration 7668, lr = 0.00218948 +I0410 14:27:29.302521 18534 solver.cpp:218] Iteration 7680 (2.42529 iter/s, 4.94786s/12 iters), loss = 5.26284 +I0410 14:27:29.302567 18534 solver.cpp:237] Train net output #0: loss = 5.26284 (* 1 = 5.26284 loss) +I0410 14:27:29.302577 18534 sgd_solver.cpp:105] Iteration 7680, lr = 0.00218428 +I0410 14:27:31.984057 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:27:34.162211 18534 solver.cpp:218] Iteration 7692 (2.4694 iter/s, 4.85949s/12 iters), loss = 5.27152 +I0410 14:27:34.162257 18534 solver.cpp:237] Train net output #0: loss = 5.27152 (* 1 = 5.27152 loss) +I0410 14:27:34.162266 18534 sgd_solver.cpp:105] Iteration 7692, lr = 0.00217909 +I0410 14:27:39.185878 18534 solver.cpp:218] Iteration 7704 (2.38879 iter/s, 5.02345s/12 iters), loss = 5.25265 +I0410 14:27:39.186061 18534 solver.cpp:237] Train net output #0: loss = 5.25265 (* 1 = 5.25265 loss) +I0410 14:27:39.186074 18534 sgd_solver.cpp:105] Iteration 7704, lr = 0.00217392 +I0410 14:27:44.042750 18534 solver.cpp:218] Iteration 7716 (2.47089 iter/s, 4.85654s/12 iters), loss = 5.25494 +I0410 14:27:44.042800 18534 solver.cpp:237] Train net output #0: loss = 5.25494 (* 1 = 5.25494 loss) +I0410 14:27:44.042811 18534 sgd_solver.cpp:105] Iteration 7716, lr = 0.00216876 +I0410 14:27:49.004338 18534 solver.cpp:218] Iteration 7728 (2.41868 iter/s, 4.96138s/12 iters), loss = 5.25944 +I0410 14:27:49.004392 18534 solver.cpp:237] Train net output #0: loss = 5.25944 (* 1 = 5.25944 loss) +I0410 14:27:49.004403 18534 sgd_solver.cpp:105] Iteration 7728, lr = 0.00216361 +I0410 14:27:54.041695 18534 solver.cpp:218] Iteration 7740 (2.3823 iter/s, 5.03715s/12 iters), loss = 5.30004 +I0410 14:27:54.041744 18534 solver.cpp:237] Train net output #0: loss = 5.30004 (* 1 = 5.30004 loss) +I0410 14:27:54.041755 18534 sgd_solver.cpp:105] Iteration 7740, lr = 0.00215847 +I0410 14:27:58.473068 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7752.caffemodel +I0410 14:27:58.808727 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7752.solverstate +I0410 14:27:59.021808 18534 solver.cpp:330] Iteration 7752, Testing net (#0) +I0410 14:27:59.021828 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:28:00.346575 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:03.376361 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:28:03.376426 18534 solver.cpp:397] Test net output #1: loss = 5.28673 (* 1 = 5.28673 loss) +I0410 14:28:03.458766 18534 solver.cpp:218] Iteration 7752 (1.27433 iter/s, 9.41673s/12 iters), loss = 5.26782 +I0410 14:28:03.458834 18534 solver.cpp:237] Train net output #0: loss = 5.26782 (* 1 = 5.26782 loss) +I0410 14:28:03.458853 18534 sgd_solver.cpp:105] Iteration 7752, lr = 0.00215335 +I0410 14:28:07.615664 18534 solver.cpp:218] Iteration 7764 (2.88691 iter/s, 4.1567s/12 iters), loss = 5.27586 +I0410 14:28:07.615715 18534 solver.cpp:237] Train net output #0: loss = 5.27586 (* 1 = 5.27586 loss) +I0410 14:28:07.615725 18534 sgd_solver.cpp:105] Iteration 7764, lr = 0.00214823 +I0410 14:28:12.482583 18534 solver.cpp:218] Iteration 7776 (2.46573 iter/s, 4.86672s/12 iters), loss = 5.2716 +I0410 14:28:12.482719 18534 solver.cpp:237] Train net output #0: loss = 5.2716 (* 1 = 5.2716 loss) +I0410 14:28:12.482728 18534 sgd_solver.cpp:105] Iteration 7776, lr = 0.00214313 +I0410 14:28:17.373790 18534 solver.cpp:218] Iteration 7788 (2.45353 iter/s, 4.89092s/12 iters), loss = 5.24465 +I0410 14:28:17.373834 18534 solver.cpp:237] Train net output #0: loss = 5.24465 (* 1 = 5.24465 loss) +I0410 14:28:17.373843 18534 sgd_solver.cpp:105] Iteration 7788, lr = 0.00213805 +I0410 14:28:17.381892 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:22.286185 18534 solver.cpp:218] Iteration 7800 (2.4429 iter/s, 4.91219s/12 iters), loss = 5.26847 +I0410 14:28:22.286232 18534 solver.cpp:237] Train net output #0: loss = 5.26847 (* 1 = 5.26847 loss) +I0410 14:28:22.286242 18534 sgd_solver.cpp:105] Iteration 7800, lr = 0.00213297 +I0410 14:28:27.258455 18534 solver.cpp:218] Iteration 7812 (2.41349 iter/s, 4.97206s/12 iters), loss = 5.29476 +I0410 14:28:27.258512 18534 solver.cpp:237] Train net output #0: loss = 5.29476 (* 1 = 5.29476 loss) +I0410 14:28:27.258527 18534 sgd_solver.cpp:105] Iteration 7812, lr = 0.00212791 +I0410 14:28:32.098582 18534 solver.cpp:218] Iteration 7824 (2.47938 iter/s, 4.83991s/12 iters), loss = 5.27495 +I0410 14:28:32.098636 18534 solver.cpp:237] Train net output #0: loss = 5.27495 (* 1 = 5.27495 loss) +I0410 14:28:32.098649 18534 sgd_solver.cpp:105] Iteration 7824, lr = 0.00212285 +I0410 14:28:37.005991 18534 solver.cpp:218] Iteration 7836 (2.44539 iter/s, 4.9072s/12 iters), loss = 5.27511 +I0410 14:28:37.006048 18534 solver.cpp:237] Train net output #0: loss = 5.27511 (* 1 = 5.27511 loss) +I0410 14:28:37.006060 18534 sgd_solver.cpp:105] Iteration 7836, lr = 0.00211781 +I0410 14:28:41.944347 18534 solver.cpp:218] Iteration 7848 (2.43006 iter/s, 4.93814s/12 iters), loss = 5.25846 +I0410 14:28:41.944393 18534 solver.cpp:237] Train net output #0: loss = 5.25846 (* 1 = 5.25846 loss) +I0410 14:28:41.944402 18534 sgd_solver.cpp:105] Iteration 7848, lr = 0.00211279 +I0410 14:28:43.939393 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7854.caffemodel +I0410 14:28:44.243006 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7854.solverstate +I0410 14:28:44.451164 18534 solver.cpp:330] Iteration 7854, Testing net (#0) +I0410 14:28:44.451187 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:28:45.802464 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:48.918627 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:28:48.918678 18534 solver.cpp:397] Test net output #1: loss = 5.2866 (* 1 = 5.2866 loss) +I0410 14:28:50.725531 18534 solver.cpp:218] Iteration 7860 (1.36661 iter/s, 8.78086s/12 iters), loss = 5.24451 +I0410 14:28:50.725587 18534 solver.cpp:237] Train net output #0: loss = 5.24451 (* 1 = 5.24451 loss) +I0410 14:28:50.725598 18534 sgd_solver.cpp:105] Iteration 7860, lr = 0.00210777 +I0410 14:28:55.635769 18534 solver.cpp:218] Iteration 7872 (2.44398 iter/s, 4.91002s/12 iters), loss = 5.26781 +I0410 14:28:55.635828 18534 solver.cpp:237] Train net output #0: loss = 5.26781 (* 1 = 5.26781 loss) +I0410 14:28:55.635838 18534 sgd_solver.cpp:105] Iteration 7872, lr = 0.00210277 +I0410 14:29:00.522688 18534 solver.cpp:218] Iteration 7884 (2.45564 iter/s, 4.8867s/12 iters), loss = 5.25864 +I0410 14:29:00.522747 18534 solver.cpp:237] Train net output #0: loss = 5.25864 (* 1 = 5.25864 loss) +I0410 14:29:00.522758 18534 sgd_solver.cpp:105] Iteration 7884, lr = 0.00209777 +I0410 14:29:02.634622 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:29:05.458137 18534 solver.cpp:218] Iteration 7896 (2.4315 iter/s, 4.93523s/12 iters), loss = 5.27728 +I0410 14:29:05.458194 18534 solver.cpp:237] Train net output #0: loss = 5.27728 (* 1 = 5.27728 loss) +I0410 14:29:05.458204 18534 sgd_solver.cpp:105] Iteration 7896, lr = 0.00209279 +I0410 14:29:10.482496 18534 solver.cpp:218] Iteration 7908 (2.38847 iter/s, 5.02414s/12 iters), loss = 5.27079 +I0410 14:29:10.482547 18534 solver.cpp:237] Train net output #0: loss = 5.27079 (* 1 = 5.27079 loss) +I0410 14:29:10.482559 18534 sgd_solver.cpp:105] Iteration 7908, lr = 0.00208782 +I0410 14:29:15.325157 18534 solver.cpp:218] Iteration 7920 (2.47808 iter/s, 4.84245s/12 iters), loss = 5.28563 +I0410 14:29:15.325316 18534 solver.cpp:237] Train net output #0: loss = 5.28563 (* 1 = 5.28563 loss) +I0410 14:29:15.325330 18534 sgd_solver.cpp:105] Iteration 7920, lr = 0.00208287 +I0410 14:29:20.205035 18534 solver.cpp:218] Iteration 7932 (2.45924 iter/s, 4.87956s/12 iters), loss = 5.26264 +I0410 14:29:20.205090 18534 solver.cpp:237] Train net output #0: loss = 5.26264 (* 1 = 5.26264 loss) +I0410 14:29:20.205101 18534 sgd_solver.cpp:105] Iteration 7932, lr = 0.00207792 +I0410 14:29:25.116825 18534 solver.cpp:218] Iteration 7944 (2.44321 iter/s, 4.91158s/12 iters), loss = 5.26603 +I0410 14:29:25.116875 18534 solver.cpp:237] Train net output #0: loss = 5.26603 (* 1 = 5.26603 loss) +I0410 14:29:25.116887 18534 sgd_solver.cpp:105] Iteration 7944, lr = 0.00207299 +I0410 14:29:29.526546 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7956.caffemodel +I0410 14:29:30.176432 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7956.solverstate +I0410 14:29:31.270143 18534 solver.cpp:330] Iteration 7956, Testing net (#0) +I0410 14:29:31.270176 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:29:32.678119 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:29:35.780568 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:29:35.780619 18534 solver.cpp:397] Test net output #1: loss = 5.28709 (* 1 = 5.28709 loss) +I0410 14:29:35.863178 18534 solver.cpp:218] Iteration 7956 (1.1167 iter/s, 10.746s/12 iters), loss = 5.27569 +I0410 14:29:35.863229 18534 solver.cpp:237] Train net output #0: loss = 5.27569 (* 1 = 5.27569 loss) +I0410 14:29:35.863241 18534 sgd_solver.cpp:105] Iteration 7956, lr = 0.00206807 +I0410 14:29:40.110378 18534 solver.cpp:218] Iteration 7968 (2.82552 iter/s, 4.24701s/12 iters), loss = 5.27367 +I0410 14:29:40.110422 18534 solver.cpp:237] Train net output #0: loss = 5.27367 (* 1 = 5.27367 loss) +I0410 14:29:40.110430 18534 sgd_solver.cpp:105] Iteration 7968, lr = 0.00206316 +I0410 14:29:45.038086 18534 solver.cpp:218] Iteration 7980 (2.43531 iter/s, 4.9275s/12 iters), loss = 5.25594 +I0410 14:29:45.038142 18534 solver.cpp:237] Train net output #0: loss = 5.25594 (* 1 = 5.25594 loss) +I0410 14:29:45.038154 18534 sgd_solver.cpp:105] Iteration 7980, lr = 0.00205826 +I0410 14:29:49.243217 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:29:49.951041 18534 solver.cpp:218] Iteration 7992 (2.44263 iter/s, 4.91273s/12 iters), loss = 5.25546 +I0410 14:29:49.951100 18534 solver.cpp:237] Train net output #0: loss = 5.25546 (* 1 = 5.25546 loss) +I0410 14:29:49.951112 18534 sgd_solver.cpp:105] Iteration 7992, lr = 0.00205337 +I0410 14:29:54.838815 18534 solver.cpp:218] Iteration 8004 (2.45521 iter/s, 4.88756s/12 iters), loss = 5.27815 +I0410 14:29:54.838856 18534 solver.cpp:237] Train net output #0: loss = 5.27815 (* 1 = 5.27815 loss) +I0410 14:29:54.838865 18534 sgd_solver.cpp:105] Iteration 8004, lr = 0.0020485 +I0410 14:30:00.045169 18534 solver.cpp:218] Iteration 8016 (2.30497 iter/s, 5.20614s/12 iters), loss = 5.27619 +I0410 14:30:00.045228 18534 solver.cpp:237] Train net output #0: loss = 5.27619 (* 1 = 5.27619 loss) +I0410 14:30:00.045243 18534 sgd_solver.cpp:105] Iteration 8016, lr = 0.00204363 +I0410 14:30:04.928294 18534 solver.cpp:218] Iteration 8028 (2.45755 iter/s, 4.88291s/12 iters), loss = 5.29255 +I0410 14:30:04.928342 18534 solver.cpp:237] Train net output #0: loss = 5.29255 (* 1 = 5.29255 loss) +I0410 14:30:04.928354 18534 sgd_solver.cpp:105] Iteration 8028, lr = 0.00203878 +I0410 14:30:09.817688 18534 solver.cpp:218] Iteration 8040 (2.4544 iter/s, 4.88918s/12 iters), loss = 5.26388 +I0410 14:30:09.817745 18534 solver.cpp:237] Train net output #0: loss = 5.26388 (* 1 = 5.26388 loss) +I0410 14:30:09.817757 18534 sgd_solver.cpp:105] Iteration 8040, lr = 0.00203394 +I0410 14:30:14.753882 18534 solver.cpp:218] Iteration 8052 (2.43113 iter/s, 4.93598s/12 iters), loss = 5.28111 +I0410 14:30:14.753934 18534 solver.cpp:237] Train net output #0: loss = 5.28111 (* 1 = 5.28111 loss) +I0410 14:30:14.753945 18534 sgd_solver.cpp:105] Iteration 8052, lr = 0.00202911 +I0410 14:30:16.763394 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8058.caffemodel +I0410 14:30:17.098662 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8058.solverstate +I0410 14:30:17.313076 18534 solver.cpp:330] Iteration 8058, Testing net (#0) +I0410 14:30:17.313095 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:30:18.549439 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:30:21.691536 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:30:21.691689 18534 solver.cpp:397] Test net output #1: loss = 5.28702 (* 1 = 5.28702 loss) +I0410 14:30:23.554507 18534 solver.cpp:218] Iteration 8064 (1.36359 iter/s, 8.80029s/12 iters), loss = 5.27813 +I0410 14:30:23.554549 18534 solver.cpp:237] Train net output #0: loss = 5.27813 (* 1 = 5.27813 loss) +I0410 14:30:23.554558 18534 sgd_solver.cpp:105] Iteration 8064, lr = 0.00202429 +I0410 14:30:28.472692 18534 solver.cpp:218] Iteration 8076 (2.44003 iter/s, 4.91798s/12 iters), loss = 5.27839 +I0410 14:30:28.472745 18534 solver.cpp:237] Train net output #0: loss = 5.27839 (* 1 = 5.27839 loss) +I0410 14:30:28.472759 18534 sgd_solver.cpp:105] Iteration 8076, lr = 0.00201949 +I0410 14:30:33.349077 18534 solver.cpp:218] Iteration 8088 (2.46095 iter/s, 4.87617s/12 iters), loss = 5.26207 +I0410 14:30:33.349123 18534 solver.cpp:237] Train net output #0: loss = 5.26207 (* 1 = 5.26207 loss) +I0410 14:30:33.349134 18534 sgd_solver.cpp:105] Iteration 8088, lr = 0.00201469 +I0410 14:30:34.761649 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:30:38.282990 18534 solver.cpp:218] Iteration 8100 (2.43225 iter/s, 4.9337s/12 iters), loss = 5.26187 +I0410 14:30:38.283048 18534 solver.cpp:237] Train net output #0: loss = 5.26187 (* 1 = 5.26187 loss) +I0410 14:30:38.283059 18534 sgd_solver.cpp:105] Iteration 8100, lr = 0.00200991 +I0410 14:30:43.200706 18534 solver.cpp:218] Iteration 8112 (2.44027 iter/s, 4.91749s/12 iters), loss = 5.2672 +I0410 14:30:43.200753 18534 solver.cpp:237] Train net output #0: loss = 5.2672 (* 1 = 5.2672 loss) +I0410 14:30:43.200762 18534 sgd_solver.cpp:105] Iteration 8112, lr = 0.00200514 +I0410 14:30:48.115396 18534 solver.cpp:218] Iteration 8124 (2.44177 iter/s, 4.91448s/12 iters), loss = 5.27198 +I0410 14:30:48.115448 18534 solver.cpp:237] Train net output #0: loss = 5.27198 (* 1 = 5.27198 loss) +I0410 14:30:48.115459 18534 sgd_solver.cpp:105] Iteration 8124, lr = 0.00200038 +I0410 14:30:52.957980 18534 solver.cpp:218] Iteration 8136 (2.47813 iter/s, 4.84236s/12 iters), loss = 5.28417 +I0410 14:30:52.958062 18534 solver.cpp:237] Train net output #0: loss = 5.28417 (* 1 = 5.28417 loss) +I0410 14:30:52.958074 18534 sgd_solver.cpp:105] Iteration 8136, lr = 0.00199563 +I0410 14:30:57.796039 18534 solver.cpp:218] Iteration 8148 (2.48046 iter/s, 4.83781s/12 iters), loss = 5.25062 +I0410 14:30:57.796097 18534 solver.cpp:237] Train net output #0: loss = 5.25062 (* 1 = 5.25062 loss) +I0410 14:30:57.796110 18534 sgd_solver.cpp:105] Iteration 8148, lr = 0.00199089 +I0410 14:31:02.197263 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8160.caffemodel +I0410 14:31:02.564682 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8160.solverstate +I0410 14:31:02.773102 18534 solver.cpp:330] Iteration 8160, Testing net (#0) +I0410 14:31:02.773129 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:31:03.927732 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:07.190523 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:31:07.190574 18534 solver.cpp:397] Test net output #1: loss = 5.28678 (* 1 = 5.28678 loss) +I0410 14:31:07.272962 18534 solver.cpp:218] Iteration 8160 (1.26628 iter/s, 9.47656s/12 iters), loss = 5.26228 +I0410 14:31:07.273013 18534 solver.cpp:237] Train net output #0: loss = 5.26228 (* 1 = 5.26228 loss) +I0410 14:31:07.273025 18534 sgd_solver.cpp:105] Iteration 8160, lr = 0.00198616 +I0410 14:31:11.461845 18534 solver.cpp:218] Iteration 8172 (2.86486 iter/s, 4.18868s/12 iters), loss = 5.28501 +I0410 14:31:11.461903 18534 solver.cpp:237] Train net output #0: loss = 5.28501 (* 1 = 5.28501 loss) +I0410 14:31:11.461915 18534 sgd_solver.cpp:105] Iteration 8172, lr = 0.00198145 +I0410 14:31:16.401306 18534 solver.cpp:218] Iteration 8184 (2.42952 iter/s, 4.93924s/12 iters), loss = 5.27118 +I0410 14:31:16.401350 18534 solver.cpp:237] Train net output #0: loss = 5.27118 (* 1 = 5.27118 loss) +I0410 14:31:16.401358 18534 sgd_solver.cpp:105] Iteration 8184, lr = 0.00197674 +I0410 14:31:19.900761 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:21.323877 18534 solver.cpp:218] Iteration 8196 (2.43785 iter/s, 4.92236s/12 iters), loss = 5.27555 +I0410 14:31:21.323927 18534 solver.cpp:237] Train net output #0: loss = 5.27555 (* 1 = 5.27555 loss) +I0410 14:31:21.323938 18534 sgd_solver.cpp:105] Iteration 8196, lr = 0.00197205 +I0410 14:31:26.250902 18534 solver.cpp:218] Iteration 8208 (2.43565 iter/s, 4.92681s/12 iters), loss = 5.25857 +I0410 14:31:26.251039 18534 solver.cpp:237] Train net output #0: loss = 5.25857 (* 1 = 5.25857 loss) +I0410 14:31:26.251050 18534 sgd_solver.cpp:105] Iteration 8208, lr = 0.00196737 +I0410 14:31:31.144044 18534 solver.cpp:218] Iteration 8220 (2.45256 iter/s, 4.89284s/12 iters), loss = 5.26462 +I0410 14:31:31.144091 18534 solver.cpp:237] Train net output #0: loss = 5.26462 (* 1 = 5.26462 loss) +I0410 14:31:31.144100 18534 sgd_solver.cpp:105] Iteration 8220, lr = 0.0019627 +I0410 14:31:36.008179 18534 solver.cpp:218] Iteration 8232 (2.46715 iter/s, 4.86392s/12 iters), loss = 5.2691 +I0410 14:31:36.008234 18534 solver.cpp:237] Train net output #0: loss = 5.2691 (* 1 = 5.2691 loss) +I0410 14:31:36.008245 18534 sgd_solver.cpp:105] Iteration 8232, lr = 0.00195804 +I0410 14:31:40.932679 18534 solver.cpp:218] Iteration 8244 (2.43691 iter/s, 4.92428s/12 iters), loss = 5.25197 +I0410 14:31:40.932729 18534 solver.cpp:237] Train net output #0: loss = 5.25197 (* 1 = 5.25197 loss) +I0410 14:31:40.932739 18534 sgd_solver.cpp:105] Iteration 8244, lr = 0.00195339 +I0410 14:31:45.795751 18534 solver.cpp:218] Iteration 8256 (2.46768 iter/s, 4.86286s/12 iters), loss = 5.27264 +I0410 14:31:45.795804 18534 solver.cpp:237] Train net output #0: loss = 5.27264 (* 1 = 5.27264 loss) +I0410 14:31:45.795815 18534 sgd_solver.cpp:105] Iteration 8256, lr = 0.00194875 +I0410 14:31:47.824065 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8262.caffemodel +I0410 14:31:48.269388 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8262.solverstate +I0410 14:31:48.742169 18534 solver.cpp:330] Iteration 8262, Testing net (#0) +I0410 14:31:48.742197 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:31:49.918627 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:53.199921 18534 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 14:31:53.199966 18534 solver.cpp:397] Test net output #1: loss = 5.28688 (* 1 = 5.28688 loss) +I0410 14:31:55.035481 18534 solver.cpp:218] Iteration 8268 (1.29879 iter/s, 9.23937s/12 iters), loss = 5.27955 +I0410 14:31:55.035529 18534 solver.cpp:237] Train net output #0: loss = 5.27955 (* 1 = 5.27955 loss) +I0410 14:31:55.035537 18534 sgd_solver.cpp:105] Iteration 8268, lr = 0.00194412 +I0410 14:31:59.975734 18534 solver.cpp:218] Iteration 8280 (2.42914 iter/s, 4.94003s/12 iters), loss = 5.28477 +I0410 14:31:59.975879 18534 solver.cpp:237] Train net output #0: loss = 5.28477 (* 1 = 5.28477 loss) +I0410 14:31:59.975891 18534 sgd_solver.cpp:105] Iteration 8280, lr = 0.00193951 +I0410 14:32:04.912088 18534 solver.cpp:218] Iteration 8292 (2.4311 iter/s, 4.93604s/12 iters), loss = 5.29 +I0410 14:32:04.912145 18534 solver.cpp:237] Train net output #0: loss = 5.29 (* 1 = 5.29 loss) +I0410 14:32:04.912158 18534 sgd_solver.cpp:105] Iteration 8292, lr = 0.0019349 +I0410 14:32:05.584585 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:32:09.847795 18534 solver.cpp:218] Iteration 8304 (2.43137 iter/s, 4.93548s/12 iters), loss = 5.27918 +I0410 14:32:09.847849 18534 solver.cpp:237] Train net output #0: loss = 5.27918 (* 1 = 5.27918 loss) +I0410 14:32:09.847859 18534 sgd_solver.cpp:105] Iteration 8304, lr = 0.00193031 +I0410 14:32:11.025053 18534 blocking_queue.cpp:49] Waiting for data +I0410 14:32:14.733578 18534 solver.cpp:218] Iteration 8316 (2.45621 iter/s, 4.88557s/12 iters), loss = 5.2722 +I0410 14:32:14.733621 18534 solver.cpp:237] Train net output #0: loss = 5.2722 (* 1 = 5.2722 loss) +I0410 14:32:14.733630 18534 sgd_solver.cpp:105] Iteration 8316, lr = 0.00192573 +I0410 14:32:19.652295 18534 solver.cpp:218] Iteration 8328 (2.43976 iter/s, 4.91851s/12 iters), loss = 5.28281 +I0410 14:32:19.652333 18534 solver.cpp:237] Train net output #0: loss = 5.28281 (* 1 = 5.28281 loss) +I0410 14:32:19.652343 18534 sgd_solver.cpp:105] Iteration 8328, lr = 0.00192115 +I0410 14:32:24.511675 18534 solver.cpp:218] Iteration 8340 (2.46956 iter/s, 4.85917s/12 iters), loss = 5.27261 +I0410 14:32:24.511732 18534 solver.cpp:237] Train net output #0: loss = 5.27261 (* 1 = 5.27261 loss) +I0410 14:32:24.511744 18534 sgd_solver.cpp:105] Iteration 8340, lr = 0.00191659 +I0410 14:32:29.405973 18534 solver.cpp:218] Iteration 8352 (2.45195 iter/s, 4.89406s/12 iters), loss = 5.28843 +I0410 14:32:29.406023 18534 solver.cpp:237] Train net output #0: loss = 5.28843 (* 1 = 5.28843 loss) +I0410 14:32:29.406034 18534 sgd_solver.cpp:105] Iteration 8352, lr = 0.00191204 +I0410 14:32:33.793655 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8364.caffemodel +I0410 14:32:34.408493 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8364.solverstate +I0410 14:32:36.739197 18534 solver.cpp:330] Iteration 8364, Testing net (#0) +I0410 14:32:36.739233 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:32:37.924805 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:32:41.328150 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:32:41.328198 18534 solver.cpp:397] Test net output #1: loss = 5.28658 (* 1 = 5.28658 loss) +I0410 14:32:41.409932 18534 solver.cpp:218] Iteration 8364 (0.999707 iter/s, 12.0035s/12 iters), loss = 5.26614 +I0410 14:32:41.410020 18534 solver.cpp:237] Train net output #0: loss = 5.26614 (* 1 = 5.26614 loss) +I0410 14:32:41.410032 18534 sgd_solver.cpp:105] Iteration 8364, lr = 0.0019075 +I0410 14:32:45.565613 18534 solver.cpp:218] Iteration 8376 (2.88778 iter/s, 4.15545s/12 iters), loss = 5.26389 +I0410 14:32:45.565665 18534 solver.cpp:237] Train net output #0: loss = 5.26389 (* 1 = 5.26389 loss) +I0410 14:32:45.565673 18534 sgd_solver.cpp:105] Iteration 8376, lr = 0.00190297 +I0410 14:32:50.450071 18534 solver.cpp:218] Iteration 8388 (2.45688 iter/s, 4.88423s/12 iters), loss = 5.26132 +I0410 14:32:50.450125 18534 solver.cpp:237] Train net output #0: loss = 5.26132 (* 1 = 5.26132 loss) +I0410 14:32:50.450137 18534 sgd_solver.cpp:105] Iteration 8388, lr = 0.00189846 +I0410 14:32:53.177510 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:32:55.282930 18534 solver.cpp:218] Iteration 8400 (2.48312 iter/s, 4.83264s/12 iters), loss = 5.26521 +I0410 14:32:55.282987 18534 solver.cpp:237] Train net output #0: loss = 5.26521 (* 1 = 5.26521 loss) +I0410 14:32:55.282999 18534 sgd_solver.cpp:105] Iteration 8400, lr = 0.00189395 +I0410 14:33:00.192636 18534 solver.cpp:218] Iteration 8412 (2.44425 iter/s, 4.90948s/12 iters), loss = 5.24965 +I0410 14:33:00.192677 18534 solver.cpp:237] Train net output #0: loss = 5.24965 (* 1 = 5.24965 loss) +I0410 14:33:00.192684 18534 sgd_solver.cpp:105] Iteration 8412, lr = 0.00188945 +I0410 14:33:05.099927 18534 solver.cpp:218] Iteration 8424 (2.44545 iter/s, 4.90707s/12 iters), loss = 5.2533 +I0410 14:33:05.100076 18534 solver.cpp:237] Train net output #0: loss = 5.2533 (* 1 = 5.2533 loss) +I0410 14:33:05.100090 18534 sgd_solver.cpp:105] Iteration 8424, lr = 0.00188497 +I0410 14:33:09.986829 18534 solver.cpp:218] Iteration 8436 (2.4557 iter/s, 4.88659s/12 iters), loss = 5.25579 +I0410 14:33:09.986878 18534 solver.cpp:237] Train net output #0: loss = 5.25579 (* 1 = 5.25579 loss) +I0410 14:33:09.986889 18534 sgd_solver.cpp:105] Iteration 8436, lr = 0.00188049 +I0410 14:33:14.838001 18534 solver.cpp:218] Iteration 8448 (2.47374 iter/s, 4.85096s/12 iters), loss = 5.29365 +I0410 14:33:14.838049 18534 solver.cpp:237] Train net output #0: loss = 5.29365 (* 1 = 5.29365 loss) +I0410 14:33:14.838058 18534 sgd_solver.cpp:105] Iteration 8448, lr = 0.00187603 +I0410 14:33:19.652624 18534 solver.cpp:218] Iteration 8460 (2.49252 iter/s, 4.8144s/12 iters), loss = 5.27324 +I0410 14:33:19.652680 18534 solver.cpp:237] Train net output #0: loss = 5.27324 (* 1 = 5.27324 loss) +I0410 14:33:19.652690 18534 sgd_solver.cpp:105] Iteration 8460, lr = 0.00187157 +I0410 14:33:21.652381 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8466.caffemodel +I0410 14:33:21.971352 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8466.solverstate +I0410 14:33:22.184382 18534 solver.cpp:330] Iteration 8466, Testing net (#0) +I0410 14:33:22.184410 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:33:23.370661 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:33:26.720651 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:33:26.720698 18534 solver.cpp:397] Test net output #1: loss = 5.28659 (* 1 = 5.28659 loss) +I0410 14:33:28.596499 18534 solver.cpp:218] Iteration 8472 (1.34175 iter/s, 8.94352s/12 iters), loss = 5.27191 +I0410 14:33:28.596546 18534 solver.cpp:237] Train net output #0: loss = 5.27191 (* 1 = 5.27191 loss) +I0410 14:33:28.596555 18534 sgd_solver.cpp:105] Iteration 8472, lr = 0.00186713 +I0410 14:33:33.412909 18534 solver.cpp:218] Iteration 8484 (2.4916 iter/s, 4.81619s/12 iters), loss = 5.27183 +I0410 14:33:33.412961 18534 solver.cpp:237] Train net output #0: loss = 5.27183 (* 1 = 5.27183 loss) +I0410 14:33:33.412973 18534 sgd_solver.cpp:105] Iteration 8484, lr = 0.0018627 +I0410 14:33:38.300338 18534 solver.cpp:218] Iteration 8496 (2.45539 iter/s, 4.8872s/12 iters), loss = 5.25561 +I0410 14:33:38.300426 18534 solver.cpp:237] Train net output #0: loss = 5.25561 (* 1 = 5.25561 loss) +I0410 14:33:38.300439 18534 sgd_solver.cpp:105] Iteration 8496, lr = 0.00185827 +I0410 14:33:38.347656 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:33:43.193272 18534 solver.cpp:218] Iteration 8508 (2.45265 iter/s, 4.89267s/12 iters), loss = 5.27599 +I0410 14:33:43.193320 18534 solver.cpp:237] Train net output #0: loss = 5.27599 (* 1 = 5.27599 loss) +I0410 14:33:43.193328 18534 sgd_solver.cpp:105] Iteration 8508, lr = 0.00185386 +I0410 14:33:48.275388 18534 solver.cpp:218] Iteration 8520 (2.36133 iter/s, 5.08189s/12 iters), loss = 5.29549 +I0410 14:33:48.275439 18534 solver.cpp:237] Train net output #0: loss = 5.29549 (* 1 = 5.29549 loss) +I0410 14:33:48.275449 18534 sgd_solver.cpp:105] Iteration 8520, lr = 0.00184946 +I0410 14:33:53.385335 18534 solver.cpp:218] Iteration 8532 (2.34847 iter/s, 5.10972s/12 iters), loss = 5.2702 +I0410 14:33:53.385381 18534 solver.cpp:237] Train net output #0: loss = 5.2702 (* 1 = 5.2702 loss) +I0410 14:33:53.385392 18534 sgd_solver.cpp:105] Iteration 8532, lr = 0.00184507 +I0410 14:33:58.321379 18534 solver.cpp:218] Iteration 8544 (2.43121 iter/s, 4.93582s/12 iters), loss = 5.27097 +I0410 14:33:58.321434 18534 solver.cpp:237] Train net output #0: loss = 5.27097 (* 1 = 5.27097 loss) +I0410 14:33:58.321444 18534 sgd_solver.cpp:105] Iteration 8544, lr = 0.00184069 +I0410 14:34:03.246930 18534 solver.cpp:218] Iteration 8556 (2.43639 iter/s, 4.92532s/12 iters), loss = 5.2573 +I0410 14:34:03.246978 18534 solver.cpp:237] Train net output #0: loss = 5.2573 (* 1 = 5.2573 loss) +I0410 14:34:03.246990 18534 sgd_solver.cpp:105] Iteration 8556, lr = 0.00183632 +I0410 14:34:07.789397 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8568.caffemodel +I0410 14:34:08.207758 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8568.solverstate +I0410 14:34:08.497849 18534 solver.cpp:330] Iteration 8568, Testing net (#0) +I0410 14:34:08.497992 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:34:09.644883 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:13.132200 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:34:13.132241 18534 solver.cpp:397] Test net output #1: loss = 5.28668 (* 1 = 5.28668 loss) +I0410 14:34:13.214177 18534 solver.cpp:218] Iteration 8568 (1.20399 iter/s, 9.96686s/12 iters), loss = 5.24694 +I0410 14:34:13.214227 18534 solver.cpp:237] Train net output #0: loss = 5.24694 (* 1 = 5.24694 loss) +I0410 14:34:13.214236 18534 sgd_solver.cpp:105] Iteration 8568, lr = 0.00183196 +I0410 14:34:17.439345 18534 solver.cpp:218] Iteration 8580 (2.84026 iter/s, 4.22497s/12 iters), loss = 5.26408 +I0410 14:34:17.439390 18534 solver.cpp:237] Train net output #0: loss = 5.26408 (* 1 = 5.26408 loss) +I0410 14:34:17.439399 18534 sgd_solver.cpp:105] Iteration 8580, lr = 0.00182761 +I0410 14:34:22.318568 18534 solver.cpp:218] Iteration 8592 (2.45952 iter/s, 4.87901s/12 iters), loss = 5.25017 +I0410 14:34:22.318614 18534 solver.cpp:237] Train net output #0: loss = 5.25017 (* 1 = 5.25017 loss) +I0410 14:34:22.318624 18534 sgd_solver.cpp:105] Iteration 8592, lr = 0.00182327 +I0410 14:34:24.439246 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:27.213641 18534 solver.cpp:218] Iteration 8604 (2.45155 iter/s, 4.89486s/12 iters), loss = 5.26897 +I0410 14:34:27.213686 18534 solver.cpp:237] Train net output #0: loss = 5.26897 (* 1 = 5.26897 loss) +I0410 14:34:27.213696 18534 sgd_solver.cpp:105] Iteration 8604, lr = 0.00181894 +I0410 14:34:32.136782 18534 solver.cpp:218] Iteration 8616 (2.43758 iter/s, 4.92292s/12 iters), loss = 5.26494 +I0410 14:34:32.136827 18534 solver.cpp:237] Train net output #0: loss = 5.26494 (* 1 = 5.26494 loss) +I0410 14:34:32.136835 18534 sgd_solver.cpp:105] Iteration 8616, lr = 0.00181462 +I0410 14:34:37.202816 18534 solver.cpp:218] Iteration 8628 (2.36882 iter/s, 5.06581s/12 iters), loss = 5.28461 +I0410 14:34:37.202862 18534 solver.cpp:237] Train net output #0: loss = 5.28461 (* 1 = 5.28461 loss) +I0410 14:34:37.202870 18534 sgd_solver.cpp:105] Iteration 8628, lr = 0.00181031 +I0410 14:34:42.052062 18534 solver.cpp:218] Iteration 8640 (2.47472 iter/s, 4.84903s/12 iters), loss = 5.26333 +I0410 14:34:42.052142 18534 solver.cpp:237] Train net output #0: loss = 5.26333 (* 1 = 5.26333 loss) +I0410 14:34:42.052152 18534 sgd_solver.cpp:105] Iteration 8640, lr = 0.00180602 +I0410 14:34:46.927572 18534 solver.cpp:218] Iteration 8652 (2.46141 iter/s, 4.87525s/12 iters), loss = 5.26694 +I0410 14:34:46.927628 18534 solver.cpp:237] Train net output #0: loss = 5.26694 (* 1 = 5.26694 loss) +I0410 14:34:46.927641 18534 sgd_solver.cpp:105] Iteration 8652, lr = 0.00180173 +I0410 14:34:51.879143 18534 solver.cpp:218] Iteration 8664 (2.42359 iter/s, 4.95134s/12 iters), loss = 5.27219 +I0410 14:34:51.879197 18534 solver.cpp:237] Train net output #0: loss = 5.27219 (* 1 = 5.27219 loss) +I0410 14:34:51.879209 18534 sgd_solver.cpp:105] Iteration 8664, lr = 0.00179745 +I0410 14:34:53.860750 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8670.caffemodel +I0410 14:34:54.180966 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8670.solverstate +I0410 14:34:54.398124 18534 solver.cpp:330] Iteration 8670, Testing net (#0) +I0410 14:34:54.398149 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:34:55.352093 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:58.774746 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:34:58.774793 18534 solver.cpp:397] Test net output #1: loss = 5.28701 (* 1 = 5.28701 loss) +I0410 14:35:00.706579 18534 solver.cpp:218] Iteration 8676 (1.35945 iter/s, 8.82708s/12 iters), loss = 5.27619 +I0410 14:35:00.706626 18534 solver.cpp:237] Train net output #0: loss = 5.27619 (* 1 = 5.27619 loss) +I0410 14:35:00.706637 18534 sgd_solver.cpp:105] Iteration 8676, lr = 0.00179318 +I0410 14:35:05.807847 18534 solver.cpp:218] Iteration 8688 (2.35246 iter/s, 5.10104s/12 iters), loss = 5.26013 +I0410 14:35:05.807893 18534 solver.cpp:237] Train net output #0: loss = 5.26013 (* 1 = 5.26013 loss) +I0410 14:35:05.807901 18534 sgd_solver.cpp:105] Iteration 8688, lr = 0.00178893 +I0410 14:35:09.976940 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:35:10.661283 18534 solver.cpp:218] Iteration 8700 (2.47259 iter/s, 4.85321s/12 iters), loss = 5.26497 +I0410 14:35:10.661336 18534 solver.cpp:237] Train net output #0: loss = 5.26497 (* 1 = 5.26497 loss) +I0410 14:35:10.661347 18534 sgd_solver.cpp:105] Iteration 8700, lr = 0.00178468 +I0410 14:35:15.575369 18534 solver.cpp:218] Iteration 8712 (2.44207 iter/s, 4.91386s/12 iters), loss = 5.27875 +I0410 14:35:15.575502 18534 solver.cpp:237] Train net output #0: loss = 5.27875 (* 1 = 5.27875 loss) +I0410 14:35:15.575512 18534 sgd_solver.cpp:105] Iteration 8712, lr = 0.00178044 +I0410 14:35:20.510854 18534 solver.cpp:218] Iteration 8724 (2.43152 iter/s, 4.93518s/12 iters), loss = 5.28232 +I0410 14:35:20.510905 18534 solver.cpp:237] Train net output #0: loss = 5.28232 (* 1 = 5.28232 loss) +I0410 14:35:20.510916 18534 sgd_solver.cpp:105] Iteration 8724, lr = 0.00177621 +I0410 14:35:25.451347 18534 solver.cpp:218] Iteration 8736 (2.42902 iter/s, 4.94026s/12 iters), loss = 5.29446 +I0410 14:35:25.451400 18534 solver.cpp:237] Train net output #0: loss = 5.29446 (* 1 = 5.29446 loss) +I0410 14:35:25.451409 18534 sgd_solver.cpp:105] Iteration 8736, lr = 0.001772 +I0410 14:35:30.366479 18534 solver.cpp:218] Iteration 8748 (2.44155 iter/s, 4.91491s/12 iters), loss = 5.26925 +I0410 14:35:30.366523 18534 solver.cpp:237] Train net output #0: loss = 5.26925 (* 1 = 5.26925 loss) +I0410 14:35:30.366534 18534 sgd_solver.cpp:105] Iteration 8748, lr = 0.00176779 +I0410 14:35:35.263356 18534 solver.cpp:218] Iteration 8760 (2.45065 iter/s, 4.89666s/12 iters), loss = 5.27815 +I0410 14:35:35.263402 18534 solver.cpp:237] Train net output #0: loss = 5.27815 (* 1 = 5.27815 loss) +I0410 14:35:35.263411 18534 sgd_solver.cpp:105] Iteration 8760, lr = 0.00176359 +I0410 14:35:39.754894 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8772.caffemodel +I0410 14:35:40.050676 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8772.solverstate +I0410 14:35:40.251843 18534 solver.cpp:330] Iteration 8772, Testing net (#0) +I0410 14:35:40.251873 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:35:41.220921 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:35:44.683475 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:35:44.683503 18534 solver.cpp:397] Test net output #1: loss = 5.28706 (* 1 = 5.28706 loss) +I0410 14:35:44.765581 18534 solver.cpp:218] Iteration 8772 (1.26291 iter/s, 9.50185s/12 iters), loss = 5.28196 +I0410 14:35:44.765625 18534 solver.cpp:237] Train net output #0: loss = 5.28196 (* 1 = 5.28196 loss) +I0410 14:35:44.765631 18534 sgd_solver.cpp:105] Iteration 8772, lr = 0.00175941 +I0410 14:35:48.980731 18534 solver.cpp:218] Iteration 8784 (2.84701 iter/s, 4.21495s/12 iters), loss = 5.27435 +I0410 14:35:48.980849 18534 solver.cpp:237] Train net output #0: loss = 5.27435 (* 1 = 5.27435 loss) +I0410 14:35:48.980859 18534 sgd_solver.cpp:105] Iteration 8784, lr = 0.00175523 +I0410 14:35:53.881867 18534 solver.cpp:218] Iteration 8796 (2.44856 iter/s, 4.90085s/12 iters), loss = 5.25869 +I0410 14:35:53.881912 18534 solver.cpp:237] Train net output #0: loss = 5.25869 (* 1 = 5.25869 loss) +I0410 14:35:53.881920 18534 sgd_solver.cpp:105] Iteration 8796, lr = 0.00175106 +I0410 14:35:55.279943 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:35:58.749042 18534 solver.cpp:218] Iteration 8808 (2.46561 iter/s, 4.86696s/12 iters), loss = 5.26374 +I0410 14:35:58.749089 18534 solver.cpp:237] Train net output #0: loss = 5.26374 (* 1 = 5.26374 loss) +I0410 14:35:58.749099 18534 sgd_solver.cpp:105] Iteration 8808, lr = 0.0017469 +I0410 14:36:03.671788 18534 solver.cpp:218] Iteration 8820 (2.43777 iter/s, 4.92252s/12 iters), loss = 5.26572 +I0410 14:36:03.671833 18534 solver.cpp:237] Train net output #0: loss = 5.26572 (* 1 = 5.26572 loss) +I0410 14:36:03.671841 18534 sgd_solver.cpp:105] Iteration 8820, lr = 0.00174276 +I0410 14:36:08.609969 18534 solver.cpp:218] Iteration 8832 (2.43016 iter/s, 4.93794s/12 iters), loss = 5.26413 +I0410 14:36:08.610018 18534 solver.cpp:237] Train net output #0: loss = 5.26413 (* 1 = 5.26413 loss) +I0410 14:36:08.610029 18534 sgd_solver.cpp:105] Iteration 8832, lr = 0.00173862 +I0410 14:36:13.578114 18534 solver.cpp:218] Iteration 8844 (2.4155 iter/s, 4.96791s/12 iters), loss = 5.29702 +I0410 14:36:13.578172 18534 solver.cpp:237] Train net output #0: loss = 5.29702 (* 1 = 5.29702 loss) +I0410 14:36:13.578184 18534 sgd_solver.cpp:105] Iteration 8844, lr = 0.00173449 +I0410 14:36:18.675695 18534 solver.cpp:218] Iteration 8856 (2.35417 iter/s, 5.09734s/12 iters), loss = 5.2592 +I0410 14:36:18.675747 18534 solver.cpp:237] Train net output #0: loss = 5.2592 (* 1 = 5.2592 loss) +I0410 14:36:18.675758 18534 sgd_solver.cpp:105] Iteration 8856, lr = 0.00173037 +I0410 14:36:23.605824 18534 solver.cpp:218] Iteration 8868 (2.43413 iter/s, 4.9299s/12 iters), loss = 5.25776 +I0410 14:36:23.605947 18534 solver.cpp:237] Train net output #0: loss = 5.25776 (* 1 = 5.25776 loss) +I0410 14:36:23.605986 18534 sgd_solver.cpp:105] Iteration 8868, lr = 0.00172626 +I0410 14:36:25.783789 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8874.caffemodel +I0410 14:36:26.102437 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8874.solverstate +I0410 14:36:26.313583 18534 solver.cpp:330] Iteration 8874, Testing net (#0) +I0410 14:36:26.313608 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:36:27.238596 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:36:30.692951 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:36:30.693001 18534 solver.cpp:397] Test net output #1: loss = 5.28685 (* 1 = 5.28685 loss) +I0410 14:36:32.644193 18534 solver.cpp:218] Iteration 8880 (1.32774 iter/s, 9.03793s/12 iters), loss = 5.28048 +I0410 14:36:32.644258 18534 solver.cpp:237] Train net output #0: loss = 5.28048 (* 1 = 5.28048 loss) +I0410 14:36:32.644271 18534 sgd_solver.cpp:105] Iteration 8880, lr = 0.00172217 +I0410 14:36:37.552856 18534 solver.cpp:218] Iteration 8892 (2.44478 iter/s, 4.90842s/12 iters), loss = 5.27877 +I0410 14:36:37.552915 18534 solver.cpp:237] Train net output #0: loss = 5.27877 (* 1 = 5.27877 loss) +I0410 14:36:37.552927 18534 sgd_solver.cpp:105] Iteration 8892, lr = 0.00171808 +I0410 14:36:41.028270 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:36:42.428454 18534 solver.cpp:218] Iteration 8904 (2.46135 iter/s, 4.87536s/12 iters), loss = 5.27727 +I0410 14:36:42.428505 18534 solver.cpp:237] Train net output #0: loss = 5.27727 (* 1 = 5.27727 loss) +I0410 14:36:42.428514 18534 sgd_solver.cpp:105] Iteration 8904, lr = 0.001714 +I0410 14:36:47.345211 18534 solver.cpp:218] Iteration 8916 (2.44075 iter/s, 4.91652s/12 iters), loss = 5.26288 +I0410 14:36:47.345284 18534 solver.cpp:237] Train net output #0: loss = 5.26288 (* 1 = 5.26288 loss) +I0410 14:36:47.345300 18534 sgd_solver.cpp:105] Iteration 8916, lr = 0.00170993 +I0410 14:36:52.245093 18534 solver.cpp:218] Iteration 8928 (2.44916 iter/s, 4.89964s/12 iters), loss = 5.26071 +I0410 14:36:52.245141 18534 solver.cpp:237] Train net output #0: loss = 5.26071 (* 1 = 5.26071 loss) +I0410 14:36:52.245152 18534 sgd_solver.cpp:105] Iteration 8928, lr = 0.00170587 +I0410 14:36:57.344802 18534 solver.cpp:218] Iteration 8940 (2.35318 iter/s, 5.09948s/12 iters), loss = 5.26749 +I0410 14:36:57.344972 18534 solver.cpp:237] Train net output #0: loss = 5.26749 (* 1 = 5.26749 loss) +I0410 14:36:57.344985 18534 sgd_solver.cpp:105] Iteration 8940, lr = 0.00170182 +I0410 14:37:02.217079 18534 solver.cpp:218] Iteration 8952 (2.46309 iter/s, 4.87194s/12 iters), loss = 5.25679 +I0410 14:37:02.217123 18534 solver.cpp:237] Train net output #0: loss = 5.25679 (* 1 = 5.25679 loss) +I0410 14:37:02.217133 18534 sgd_solver.cpp:105] Iteration 8952, lr = 0.00169778 +I0410 14:37:07.061348 18534 solver.cpp:218] Iteration 8964 (2.47726 iter/s, 4.84405s/12 iters), loss = 5.27621 +I0410 14:37:07.061391 18534 solver.cpp:237] Train net output #0: loss = 5.27621 (* 1 = 5.27621 loss) +I0410 14:37:07.061400 18534 sgd_solver.cpp:105] Iteration 8964, lr = 0.00169375 +I0410 14:37:11.544476 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8976.caffemodel +I0410 14:37:11.844229 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8976.solverstate +I0410 14:37:12.050913 18534 solver.cpp:330] Iteration 8976, Testing net (#0) +I0410 14:37:12.050935 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:37:12.936185 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:16.449309 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:37:16.449359 18534 solver.cpp:397] Test net output #1: loss = 5.28692 (* 1 = 5.28692 loss) +I0410 14:37:16.531803 18534 solver.cpp:218] Iteration 8976 (1.26715 iter/s, 9.47008s/12 iters), loss = 5.27752 +I0410 14:37:16.531855 18534 solver.cpp:237] Train net output #0: loss = 5.27752 (* 1 = 5.27752 loss) +I0410 14:37:16.531867 18534 sgd_solver.cpp:105] Iteration 8976, lr = 0.00168973 +I0410 14:37:20.644439 18534 solver.cpp:218] Iteration 8988 (2.91798 iter/s, 4.11243s/12 iters), loss = 5.2843 +I0410 14:37:20.644493 18534 solver.cpp:237] Train net output #0: loss = 5.2843 (* 1 = 5.2843 loss) +I0410 14:37:20.644503 18534 sgd_solver.cpp:105] Iteration 8988, lr = 0.00168571 +I0410 14:37:22.240063 18534 blocking_queue.cpp:49] Waiting for data +I0410 14:37:25.568576 18534 solver.cpp:218] Iteration 9000 (2.43709 iter/s, 4.92391s/12 iters), loss = 5.28755 +I0410 14:37:25.568622 18534 solver.cpp:237] Train net output #0: loss = 5.28755 (* 1 = 5.28755 loss) +I0410 14:37:25.568631 18534 sgd_solver.cpp:105] Iteration 9000, lr = 0.00168171 +I0410 14:37:26.281314 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:30.447643 18534 solver.cpp:218] Iteration 9012 (2.4596 iter/s, 4.87884s/12 iters), loss = 5.28455 +I0410 14:37:30.447731 18534 solver.cpp:237] Train net output #0: loss = 5.28455 (* 1 = 5.28455 loss) +I0410 14:37:30.447741 18534 sgd_solver.cpp:105] Iteration 9012, lr = 0.00167772 +I0410 14:37:35.353680 18534 solver.cpp:218] Iteration 9024 (2.44609 iter/s, 4.90578s/12 iters), loss = 5.26485 +I0410 14:37:35.353727 18534 solver.cpp:237] Train net output #0: loss = 5.26485 (* 1 = 5.26485 loss) +I0410 14:37:35.353736 18534 sgd_solver.cpp:105] Iteration 9024, lr = 0.00167374 +I0410 14:37:40.499500 18534 solver.cpp:218] Iteration 9036 (2.3321 iter/s, 5.14558s/12 iters), loss = 5.27227 +I0410 14:37:40.499547 18534 solver.cpp:237] Train net output #0: loss = 5.27227 (* 1 = 5.27227 loss) +I0410 14:37:40.499557 18534 sgd_solver.cpp:105] Iteration 9036, lr = 0.00166976 +I0410 14:37:45.372189 18534 solver.cpp:218] Iteration 9048 (2.46282 iter/s, 4.87246s/12 iters), loss = 5.27458 +I0410 14:37:45.372241 18534 solver.cpp:237] Train net output #0: loss = 5.27458 (* 1 = 5.27458 loss) +I0410 14:37:45.372251 18534 sgd_solver.cpp:105] Iteration 9048, lr = 0.0016658 +I0410 14:37:50.208413 18534 solver.cpp:218] Iteration 9060 (2.48139 iter/s, 4.836s/12 iters), loss = 5.29085 +I0410 14:37:50.208456 18534 solver.cpp:237] Train net output #0: loss = 5.29085 (* 1 = 5.29085 loss) +I0410 14:37:50.208462 18534 sgd_solver.cpp:105] Iteration 9060, lr = 0.00166184 +I0410 14:37:55.138998 18534 solver.cpp:218] Iteration 9072 (2.4339 iter/s, 4.93036s/12 iters), loss = 5.26972 +I0410 14:37:55.139041 18534 solver.cpp:237] Train net output #0: loss = 5.26972 (* 1 = 5.26972 loss) +I0410 14:37:55.139050 18534 sgd_solver.cpp:105] Iteration 9072, lr = 0.0016579 +I0410 14:37:57.140014 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9078.caffemodel +I0410 14:37:57.471968 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9078.solverstate +I0410 14:37:57.687340 18534 solver.cpp:330] Iteration 9078, Testing net (#0) +I0410 14:37:57.687366 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:37:58.563740 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:38:02.099165 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:38:02.099296 18534 solver.cpp:397] Test net output #1: loss = 5.28711 (* 1 = 5.28711 loss) +I0410 14:38:04.004760 18534 solver.cpp:218] Iteration 9084 (1.35358 iter/s, 8.86541s/12 iters), loss = 5.25947 +I0410 14:38:04.004802 18534 solver.cpp:237] Train net output #0: loss = 5.25947 (* 1 = 5.25947 loss) +I0410 14:38:04.004812 18534 sgd_solver.cpp:105] Iteration 9084, lr = 0.00165396 +I0410 14:38:08.990329 18534 solver.cpp:218] Iteration 9096 (2.40706 iter/s, 4.98534s/12 iters), loss = 5.26602 +I0410 14:38:08.990381 18534 solver.cpp:237] Train net output #0: loss = 5.26602 (* 1 = 5.26602 loss) +I0410 14:38:08.990391 18534 sgd_solver.cpp:105] Iteration 9096, lr = 0.00165003 +I0410 14:38:11.881014 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:38:13.898654 18534 solver.cpp:218] Iteration 9108 (2.44494 iter/s, 4.9081s/12 iters), loss = 5.26136 +I0410 14:38:13.898711 18534 solver.cpp:237] Train net output #0: loss = 5.26136 (* 1 = 5.26136 loss) +I0410 14:38:13.898722 18534 sgd_solver.cpp:105] Iteration 9108, lr = 0.00164612 +I0410 14:38:18.711611 18534 solver.cpp:218] Iteration 9120 (2.49339 iter/s, 4.81272s/12 iters), loss = 5.25239 +I0410 14:38:18.711668 18534 solver.cpp:237] Train net output #0: loss = 5.25239 (* 1 = 5.25239 loss) +I0410 14:38:18.711679 18534 sgd_solver.cpp:105] Iteration 9120, lr = 0.00164221 +I0410 14:38:23.556483 18534 solver.cpp:218] Iteration 9132 (2.47697 iter/s, 4.84464s/12 iters), loss = 5.25114 +I0410 14:38:23.556538 18534 solver.cpp:237] Train net output #0: loss = 5.25114 (* 1 = 5.25114 loss) +I0410 14:38:23.556550 18534 sgd_solver.cpp:105] Iteration 9132, lr = 0.00163831 +I0410 14:38:28.533200 18534 solver.cpp:218] Iteration 9144 (2.41134 iter/s, 4.97648s/12 iters), loss = 5.25909 +I0410 14:38:28.533247 18534 solver.cpp:237] Train net output #0: loss = 5.25909 (* 1 = 5.25909 loss) +I0410 14:38:28.533257 18534 sgd_solver.cpp:105] Iteration 9144, lr = 0.00163442 +I0410 14:38:33.661669 18534 solver.cpp:218] Iteration 9156 (2.33999 iter/s, 5.12824s/12 iters), loss = 5.29006 +I0410 14:38:33.661782 18534 solver.cpp:237] Train net output #0: loss = 5.29006 (* 1 = 5.29006 loss) +I0410 14:38:33.661792 18534 sgd_solver.cpp:105] Iteration 9156, lr = 0.00163054 +I0410 14:38:38.554606 18534 solver.cpp:218] Iteration 9168 (2.45266 iter/s, 4.89265s/12 iters), loss = 5.27295 +I0410 14:38:38.554651 18534 solver.cpp:237] Train net output #0: loss = 5.27295 (* 1 = 5.27295 loss) +I0410 14:38:38.554661 18534 sgd_solver.cpp:105] Iteration 9168, lr = 0.00162667 +I0410 14:38:43.035560 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9180.caffemodel +I0410 14:38:43.376971 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9180.solverstate +I0410 14:38:43.635232 18534 solver.cpp:330] Iteration 9180, Testing net (#0) +I0410 14:38:43.635257 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:38:44.374014 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:38:47.928078 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:38:47.928107 18534 solver.cpp:397] Test net output #1: loss = 5.28737 (* 1 = 5.28737 loss) +I0410 14:38:48.010412 18534 solver.cpp:218] Iteration 9180 (1.26911 iter/s, 9.45543s/12 iters), loss = 5.27327 +I0410 14:38:48.010452 18534 solver.cpp:237] Train net output #0: loss = 5.27327 (* 1 = 5.27327 loss) +I0410 14:38:48.010460 18534 sgd_solver.cpp:105] Iteration 9180, lr = 0.00162281 +I0410 14:38:52.375545 18534 solver.cpp:218] Iteration 9192 (2.74919 iter/s, 4.36493s/12 iters), loss = 5.27415 +I0410 14:38:52.375600 18534 solver.cpp:237] Train net output #0: loss = 5.27415 (* 1 = 5.27415 loss) +I0410 14:38:52.375613 18534 sgd_solver.cpp:105] Iteration 9192, lr = 0.00161895 +I0410 14:38:57.221160 18534 solver.cpp:218] Iteration 9204 (2.47659 iter/s, 4.84538s/12 iters), loss = 5.26523 +I0410 14:38:57.221213 18534 solver.cpp:237] Train net output #0: loss = 5.26523 (* 1 = 5.26523 loss) +I0410 14:38:57.221225 18534 sgd_solver.cpp:105] Iteration 9204, lr = 0.00161511 +I0410 14:38:57.289160 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:39:02.126996 18534 solver.cpp:218] Iteration 9216 (2.44618 iter/s, 4.9056s/12 iters), loss = 5.27712 +I0410 14:39:02.127038 18534 solver.cpp:237] Train net output #0: loss = 5.27712 (* 1 = 5.27712 loss) +I0410 14:39:02.127048 18534 sgd_solver.cpp:105] Iteration 9216, lr = 0.00161128 +I0410 14:39:06.995559 18534 solver.cpp:218] Iteration 9228 (2.46491 iter/s, 4.86834s/12 iters), loss = 5.28449 +I0410 14:39:06.995708 18534 solver.cpp:237] Train net output #0: loss = 5.28449 (* 1 = 5.28449 loss) +I0410 14:39:06.995720 18534 sgd_solver.cpp:105] Iteration 9228, lr = 0.00160745 +I0410 14:39:11.925366 18534 solver.cpp:218] Iteration 9240 (2.43433 iter/s, 4.92948s/12 iters), loss = 5.26139 +I0410 14:39:11.925406 18534 solver.cpp:237] Train net output #0: loss = 5.26139 (* 1 = 5.26139 loss) +I0410 14:39:11.925415 18534 sgd_solver.cpp:105] Iteration 9240, lr = 0.00160363 +I0410 14:39:16.820528 18534 solver.cpp:218] Iteration 9252 (2.45151 iter/s, 4.89494s/12 iters), loss = 5.27384 +I0410 14:39:16.820580 18534 solver.cpp:237] Train net output #0: loss = 5.27384 (* 1 = 5.27384 loss) +I0410 14:39:16.820590 18534 sgd_solver.cpp:105] Iteration 9252, lr = 0.00159983 +I0410 14:39:21.742328 18534 solver.cpp:218] Iteration 9264 (2.43825 iter/s, 4.92157s/12 iters), loss = 5.26196 +I0410 14:39:21.742377 18534 solver.cpp:237] Train net output #0: loss = 5.26196 (* 1 = 5.26196 loss) +I0410 14:39:21.742386 18534 sgd_solver.cpp:105] Iteration 9264, lr = 0.00159603 +I0410 14:39:26.683415 18534 solver.cpp:218] Iteration 9276 (2.42873 iter/s, 4.94085s/12 iters), loss = 5.2485 +I0410 14:39:26.683476 18534 solver.cpp:237] Train net output #0: loss = 5.2485 (* 1 = 5.2485 loss) +I0410 14:39:26.683488 18534 sgd_solver.cpp:105] Iteration 9276, lr = 0.00159224 +I0410 14:39:28.706398 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9282.caffemodel +I0410 14:39:29.365659 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9282.solverstate +I0410 14:39:31.298689 18534 solver.cpp:330] Iteration 9282, Testing net (#0) +I0410 14:39:31.298719 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:39:32.012977 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:39:35.737516 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:39:35.737562 18534 solver.cpp:397] Test net output #1: loss = 5.2869 (* 1 = 5.2869 loss) +I0410 14:39:37.716691 18534 solver.cpp:218] Iteration 9288 (1.08766 iter/s, 11.0328s/12 iters), loss = 5.26793 +I0410 14:39:37.716821 18534 solver.cpp:237] Train net output #0: loss = 5.26793 (* 1 = 5.26793 loss) +I0410 14:39:37.716835 18534 sgd_solver.cpp:105] Iteration 9288, lr = 0.00158846 +I0410 14:39:42.810187 18534 solver.cpp:218] Iteration 9300 (2.35609 iter/s, 5.09318s/12 iters), loss = 5.2495 +I0410 14:39:42.810237 18534 solver.cpp:237] Train net output #0: loss = 5.2495 (* 1 = 5.2495 loss) +I0410 14:39:42.810248 18534 sgd_solver.cpp:105] Iteration 9300, lr = 0.00158469 +I0410 14:39:44.974876 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:39:47.707216 18534 solver.cpp:218] Iteration 9312 (2.45058 iter/s, 4.8968s/12 iters), loss = 5.27182 +I0410 14:39:47.707262 18534 solver.cpp:237] Train net output #0: loss = 5.27182 (* 1 = 5.27182 loss) +I0410 14:39:47.707271 18534 sgd_solver.cpp:105] Iteration 9312, lr = 0.00158092 +I0410 14:39:52.576191 18534 solver.cpp:218] Iteration 9324 (2.4647 iter/s, 4.86874s/12 iters), loss = 5.27793 +I0410 14:39:52.576253 18534 solver.cpp:237] Train net output #0: loss = 5.27793 (* 1 = 5.27793 loss) +I0410 14:39:52.576265 18534 sgd_solver.cpp:105] Iteration 9324, lr = 0.00157717 +I0410 14:39:57.411928 18534 solver.cpp:218] Iteration 9336 (2.48165 iter/s, 4.8355s/12 iters), loss = 5.2858 +I0410 14:39:57.411980 18534 solver.cpp:237] Train net output #0: loss = 5.2858 (* 1 = 5.2858 loss) +I0410 14:39:57.411993 18534 sgd_solver.cpp:105] Iteration 9336, lr = 0.00157343 +I0410 14:40:02.374550 18534 solver.cpp:218] Iteration 9348 (2.41819 iter/s, 4.96239s/12 iters), loss = 5.27055 +I0410 14:40:02.374591 18534 solver.cpp:237] Train net output #0: loss = 5.27055 (* 1 = 5.27055 loss) +I0410 14:40:02.374603 18534 sgd_solver.cpp:105] Iteration 9348, lr = 0.00156969 +I0410 14:40:07.243772 18534 solver.cpp:218] Iteration 9360 (2.46457 iter/s, 4.869s/12 iters), loss = 5.27083 +I0410 14:40:07.243820 18534 solver.cpp:237] Train net output #0: loss = 5.27083 (* 1 = 5.27083 loss) +I0410 14:40:07.243831 18534 sgd_solver.cpp:105] Iteration 9360, lr = 0.00156596 +I0410 14:40:12.131211 18534 solver.cpp:218] Iteration 9372 (2.45539 iter/s, 4.8872s/12 iters), loss = 5.27133 +I0410 14:40:12.133354 18534 solver.cpp:237] Train net output #0: loss = 5.27133 (* 1 = 5.27133 loss) +I0410 14:40:12.133374 18534 sgd_solver.cpp:105] Iteration 9372, lr = 0.00156225 +I0410 14:40:16.637193 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9384.caffemodel +I0410 14:40:16.921741 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9384.solverstate +I0410 14:40:17.119387 18534 solver.cpp:330] Iteration 9384, Testing net (#0) +I0410 14:40:17.119415 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:40:17.854401 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:21.496146 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:40:21.496196 18534 solver.cpp:397] Test net output #1: loss = 5.28695 (* 1 = 5.28695 loss) +I0410 14:40:21.580355 18534 solver.cpp:218] Iteration 9384 (1.27029 iter/s, 9.44668s/12 iters), loss = 5.2768 +I0410 14:40:21.580395 18534 solver.cpp:237] Train net output #0: loss = 5.2768 (* 1 = 5.2768 loss) +I0410 14:40:21.580406 18534 sgd_solver.cpp:105] Iteration 9384, lr = 0.00155854 +I0410 14:40:25.754703 18534 solver.cpp:218] Iteration 9396 (2.87484 iter/s, 4.17415s/12 iters), loss = 5.26557 +I0410 14:40:25.754757 18534 solver.cpp:237] Train net output #0: loss = 5.26557 (* 1 = 5.26557 loss) +I0410 14:40:25.754770 18534 sgd_solver.cpp:105] Iteration 9396, lr = 0.00155484 +I0410 14:40:29.964058 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:30.597025 18534 solver.cpp:218] Iteration 9408 (2.47827 iter/s, 4.84209s/12 iters), loss = 5.26946 +I0410 14:40:30.597079 18534 solver.cpp:237] Train net output #0: loss = 5.26946 (* 1 = 5.26946 loss) +I0410 14:40:30.597091 18534 sgd_solver.cpp:105] Iteration 9408, lr = 0.00155114 +I0410 14:40:35.495460 18534 solver.cpp:218] Iteration 9420 (2.44988 iter/s, 4.89819s/12 iters), loss = 5.27759 +I0410 14:40:35.495518 18534 solver.cpp:237] Train net output #0: loss = 5.27759 (* 1 = 5.27759 loss) +I0410 14:40:35.495532 18534 sgd_solver.cpp:105] Iteration 9420, lr = 0.00154746 +I0410 14:40:40.416676 18534 solver.cpp:218] Iteration 9432 (2.43854 iter/s, 4.92097s/12 iters), loss = 5.28384 +I0410 14:40:40.416733 18534 solver.cpp:237] Train net output #0: loss = 5.28384 (* 1 = 5.28384 loss) +I0410 14:40:40.416744 18534 sgd_solver.cpp:105] Iteration 9432, lr = 0.00154379 +I0410 14:40:45.365904 18534 solver.cpp:218] Iteration 9444 (2.42474 iter/s, 4.94899s/12 iters), loss = 5.28561 +I0410 14:40:45.366076 18534 solver.cpp:237] Train net output #0: loss = 5.28561 (* 1 = 5.28561 loss) +I0410 14:40:45.366091 18534 sgd_solver.cpp:105] Iteration 9444, lr = 0.00154012 +I0410 14:40:50.317328 18534 solver.cpp:218] Iteration 9456 (2.42372 iter/s, 4.95107s/12 iters), loss = 5.26621 +I0410 14:40:50.317380 18534 solver.cpp:237] Train net output #0: loss = 5.26621 (* 1 = 5.26621 loss) +I0410 14:40:50.317390 18534 sgd_solver.cpp:105] Iteration 9456, lr = 0.00153647 +I0410 14:40:55.138219 18534 solver.cpp:218] Iteration 9468 (2.48929 iter/s, 4.82066s/12 iters), loss = 5.2801 +I0410 14:40:55.138278 18534 solver.cpp:237] Train net output #0: loss = 5.2801 (* 1 = 5.2801 loss) +I0410 14:40:55.138288 18534 sgd_solver.cpp:105] Iteration 9468, lr = 0.00153282 +I0410 14:41:00.117871 18534 solver.cpp:218] Iteration 9480 (2.40992 iter/s, 4.97941s/12 iters), loss = 5.27566 +I0410 14:41:00.117918 18534 solver.cpp:237] Train net output #0: loss = 5.27566 (* 1 = 5.27566 loss) +I0410 14:41:00.117928 18534 sgd_solver.cpp:105] Iteration 9480, lr = 0.00152918 +I0410 14:41:02.268798 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9486.caffemodel +I0410 14:41:02.597779 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9486.solverstate +I0410 14:41:02.827877 18534 solver.cpp:330] Iteration 9486, Testing net (#0) +I0410 14:41:02.827898 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:41:03.544096 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:07.259699 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:41:07.259761 18534 solver.cpp:397] Test net output #1: loss = 5.28641 (* 1 = 5.28641 loss) +I0410 14:41:09.116180 18534 solver.cpp:218] Iteration 9492 (1.33364 iter/s, 8.99793s/12 iters), loss = 5.26913 +I0410 14:41:09.116240 18534 solver.cpp:237] Train net output #0: loss = 5.26913 (* 1 = 5.26913 loss) +I0410 14:41:09.116252 18534 sgd_solver.cpp:105] Iteration 9492, lr = 0.00152555 +I0410 14:41:13.990206 18534 solver.cpp:218] Iteration 9504 (2.46216 iter/s, 4.87378s/12 iters), loss = 5.25857 +I0410 14:41:13.990267 18534 solver.cpp:237] Train net output #0: loss = 5.25857 (* 1 = 5.25857 loss) +I0410 14:41:13.990284 18534 sgd_solver.cpp:105] Iteration 9504, lr = 0.00152193 +I0410 14:41:15.444636 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:18.912691 18534 solver.cpp:218] Iteration 9516 (2.43791 iter/s, 4.92225s/12 iters), loss = 5.2647 +I0410 14:41:18.912737 18534 solver.cpp:237] Train net output #0: loss = 5.2647 (* 1 = 5.2647 loss) +I0410 14:41:18.912748 18534 sgd_solver.cpp:105] Iteration 9516, lr = 0.00151831 +I0410 14:41:23.839149 18534 solver.cpp:218] Iteration 9528 (2.43594 iter/s, 4.92623s/12 iters), loss = 5.26302 +I0410 14:41:23.839190 18534 solver.cpp:237] Train net output #0: loss = 5.26302 (* 1 = 5.26302 loss) +I0410 14:41:23.839197 18534 sgd_solver.cpp:105] Iteration 9528, lr = 0.00151471 +I0410 14:41:28.708808 18534 solver.cpp:218] Iteration 9540 (2.46435 iter/s, 4.86943s/12 iters), loss = 5.24907 +I0410 14:41:28.708861 18534 solver.cpp:237] Train net output #0: loss = 5.24907 (* 1 = 5.24907 loss) +I0410 14:41:28.708874 18534 sgd_solver.cpp:105] Iteration 9540, lr = 0.00151111 +I0410 14:41:33.575366 18534 solver.cpp:218] Iteration 9552 (2.46593 iter/s, 4.86632s/12 iters), loss = 5.29919 +I0410 14:41:33.575423 18534 solver.cpp:237] Train net output #0: loss = 5.29919 (* 1 = 5.29919 loss) +I0410 14:41:33.575434 18534 sgd_solver.cpp:105] Iteration 9552, lr = 0.00150752 +I0410 14:41:38.440847 18534 solver.cpp:218] Iteration 9564 (2.46648 iter/s, 4.86524s/12 iters), loss = 5.25451 +I0410 14:41:38.440907 18534 solver.cpp:237] Train net output #0: loss = 5.25451 (* 1 = 5.25451 loss) +I0410 14:41:38.440919 18534 sgd_solver.cpp:105] Iteration 9564, lr = 0.00150395 +I0410 14:41:43.329890 18534 solver.cpp:218] Iteration 9576 (2.45459 iter/s, 4.8888s/12 iters), loss = 5.2613 +I0410 14:41:43.329936 18534 solver.cpp:237] Train net output #0: loss = 5.2613 (* 1 = 5.2613 loss) +I0410 14:41:43.329946 18534 sgd_solver.cpp:105] Iteration 9576, lr = 0.00150037 +I0410 14:41:47.750336 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9588.caffemodel +I0410 14:41:48.062877 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9588.solverstate +I0410 14:41:48.273653 18534 solver.cpp:330] Iteration 9588, Testing net (#0) +I0410 14:41:48.273685 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:41:48.944903 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:52.791396 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:41:52.791431 18534 solver.cpp:397] Test net output #1: loss = 5.28671 (* 1 = 5.28671 loss) +I0410 14:41:52.871284 18534 solver.cpp:218] Iteration 9588 (1.25773 iter/s, 9.54101s/12 iters), loss = 5.27474 +I0410 14:41:52.871327 18534 solver.cpp:237] Train net output #0: loss = 5.27474 (* 1 = 5.27474 loss) +I0410 14:41:52.871335 18534 sgd_solver.cpp:105] Iteration 9588, lr = 0.00149681 +I0410 14:41:56.976614 18534 solver.cpp:218] Iteration 9600 (2.92317 iter/s, 4.10513s/12 iters), loss = 5.27428 +I0410 14:41:56.976671 18534 solver.cpp:237] Train net output #0: loss = 5.27428 (* 1 = 5.27428 loss) +I0410 14:41:56.976682 18534 sgd_solver.cpp:105] Iteration 9600, lr = 0.00149326 +I0410 14:42:00.583621 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:42:01.909068 18534 solver.cpp:218] Iteration 9612 (2.43299 iter/s, 4.93221s/12 iters), loss = 5.271 +I0410 14:42:01.909123 18534 solver.cpp:237] Train net output #0: loss = 5.271 (* 1 = 5.271 loss) +I0410 14:42:01.909134 18534 sgd_solver.cpp:105] Iteration 9612, lr = 0.00148971 +I0410 14:42:06.824822 18534 solver.cpp:218] Iteration 9624 (2.44125 iter/s, 4.91551s/12 iters), loss = 5.26716 +I0410 14:42:06.824877 18534 solver.cpp:237] Train net output #0: loss = 5.26716 (* 1 = 5.26716 loss) +I0410 14:42:06.824888 18534 sgd_solver.cpp:105] Iteration 9624, lr = 0.00148618 +I0410 14:42:11.694464 18534 solver.cpp:218] Iteration 9636 (2.46437 iter/s, 4.86941s/12 iters), loss = 5.25756 +I0410 14:42:11.694511 18534 solver.cpp:237] Train net output #0: loss = 5.25756 (* 1 = 5.25756 loss) +I0410 14:42:11.694520 18534 sgd_solver.cpp:105] Iteration 9636, lr = 0.00148265 +I0410 14:42:16.512610 18534 solver.cpp:218] Iteration 9648 (2.49071 iter/s, 4.81791s/12 iters), loss = 5.26307 +I0410 14:42:16.512668 18534 solver.cpp:237] Train net output #0: loss = 5.26307 (* 1 = 5.26307 loss) +I0410 14:42:16.512679 18534 sgd_solver.cpp:105] Iteration 9648, lr = 0.00147913 +I0410 14:42:21.373912 18534 solver.cpp:218] Iteration 9660 (2.46859 iter/s, 4.86107s/12 iters), loss = 5.25538 +I0410 14:42:21.374008 18534 solver.cpp:237] Train net output #0: loss = 5.25538 (* 1 = 5.25538 loss) +I0410 14:42:21.374022 18534 sgd_solver.cpp:105] Iteration 9660, lr = 0.00147562 +I0410 14:42:26.291224 18534 solver.cpp:218] Iteration 9672 (2.4405 iter/s, 4.91703s/12 iters), loss = 5.27257 +I0410 14:42:26.291280 18534 solver.cpp:237] Train net output #0: loss = 5.27257 (* 1 = 5.27257 loss) +I0410 14:42:26.291291 18534 sgd_solver.cpp:105] Iteration 9672, lr = 0.00147211 +I0410 14:42:31.300559 18534 solver.cpp:218] Iteration 9684 (2.39564 iter/s, 5.00909s/12 iters), loss = 5.28967 +I0410 14:42:31.300611 18534 solver.cpp:237] Train net output #0: loss = 5.28967 (* 1 = 5.28967 loss) +I0410 14:42:31.300623 18534 sgd_solver.cpp:105] Iteration 9684, lr = 0.00146862 +I0410 14:42:33.330945 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9690.caffemodel +I0410 14:42:33.640813 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9690.solverstate +I0410 14:42:33.854280 18534 solver.cpp:330] Iteration 9690, Testing net (#0) +I0410 14:42:33.854308 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:42:34.537315 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:42:37.010867 18534 blocking_queue.cpp:49] Waiting for data +I0410 14:42:38.350757 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:42:38.350805 18534 solver.cpp:397] Test net output #1: loss = 5.2869 (* 1 = 5.2869 loss) +I0410 14:42:40.124269 18534 solver.cpp:218] Iteration 9696 (1.36003 iter/s, 8.82334s/12 iters), loss = 5.28561 +I0410 14:42:40.124328 18534 solver.cpp:237] Train net output #0: loss = 5.28561 (* 1 = 5.28561 loss) +I0410 14:42:40.124341 18534 sgd_solver.cpp:105] Iteration 9696, lr = 0.00146513 +I0410 14:42:44.944679 18534 solver.cpp:218] Iteration 9708 (2.48954 iter/s, 4.82017s/12 iters), loss = 5.2865 +I0410 14:42:44.944731 18534 solver.cpp:237] Train net output #0: loss = 5.2865 (* 1 = 5.2865 loss) +I0410 14:42:44.944743 18534 sgd_solver.cpp:105] Iteration 9708, lr = 0.00146165 +I0410 14:42:45.659914 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:42:49.792291 18534 solver.cpp:218] Iteration 9720 (2.47557 iter/s, 4.84738s/12 iters), loss = 5.28686 +I0410 14:42:49.792337 18534 solver.cpp:237] Train net output #0: loss = 5.28686 (* 1 = 5.28686 loss) +I0410 14:42:49.792347 18534 sgd_solver.cpp:105] Iteration 9720, lr = 0.00145818 +I0410 14:42:54.662698 18534 solver.cpp:218] Iteration 9732 (2.46397 iter/s, 4.87018s/12 iters), loss = 5.264 +I0410 14:42:54.662822 18534 solver.cpp:237] Train net output #0: loss = 5.264 (* 1 = 5.264 loss) +I0410 14:42:54.662830 18534 sgd_solver.cpp:105] Iteration 9732, lr = 0.00145472 +I0410 14:42:59.474611 18534 solver.cpp:218] Iteration 9744 (2.49397 iter/s, 4.81161s/12 iters), loss = 5.26706 +I0410 14:42:59.474669 18534 solver.cpp:237] Train net output #0: loss = 5.26706 (* 1 = 5.26706 loss) +I0410 14:42:59.474680 18534 sgd_solver.cpp:105] Iteration 9744, lr = 0.00145127 +I0410 14:43:04.561570 18534 solver.cpp:218] Iteration 9756 (2.35909 iter/s, 5.08671s/12 iters), loss = 5.27334 +I0410 14:43:04.561626 18534 solver.cpp:237] Train net output #0: loss = 5.27334 (* 1 = 5.27334 loss) +I0410 14:43:04.561638 18534 sgd_solver.cpp:105] Iteration 9756, lr = 0.00144782 +I0410 14:43:09.601624 18534 solver.cpp:218] Iteration 9768 (2.38105 iter/s, 5.0398s/12 iters), loss = 5.28596 +I0410 14:43:09.601676 18534 solver.cpp:237] Train net output #0: loss = 5.28596 (* 1 = 5.28596 loss) +I0410 14:43:09.601687 18534 sgd_solver.cpp:105] Iteration 9768, lr = 0.00144438 +I0410 14:43:14.424707 18534 solver.cpp:218] Iteration 9780 (2.48815 iter/s, 4.82286s/12 iters), loss = 5.27236 +I0410 14:43:14.424753 18534 solver.cpp:237] Train net output #0: loss = 5.27236 (* 1 = 5.27236 loss) +I0410 14:43:14.424764 18534 sgd_solver.cpp:105] Iteration 9780, lr = 0.00144095 +I0410 14:43:18.907091 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9792.caffemodel +I0410 14:43:19.339547 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9792.solverstate +I0410 14:43:19.628669 18534 solver.cpp:330] Iteration 9792, Testing net (#0) +I0410 14:43:19.628695 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:43:20.270030 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:43:24.110319 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:43:24.110356 18534 solver.cpp:397] Test net output #1: loss = 5.28667 (* 1 = 5.28667 loss) +I0410 14:43:24.192762 18534 solver.cpp:218] Iteration 9792 (1.22854 iter/s, 9.76765s/12 iters), loss = 5.25243 +I0410 14:43:24.192821 18534 solver.cpp:237] Train net output #0: loss = 5.25243 (* 1 = 5.25243 loss) +I0410 14:43:24.192831 18534 sgd_solver.cpp:105] Iteration 9792, lr = 0.00143753 +I0410 14:43:28.321949 18534 solver.cpp:218] Iteration 9804 (2.90629 iter/s, 4.12897s/12 iters), loss = 5.27066 +I0410 14:43:28.322127 18534 solver.cpp:237] Train net output #0: loss = 5.27066 (* 1 = 5.27066 loss) +I0410 14:43:28.322139 18534 sgd_solver.cpp:105] Iteration 9804, lr = 0.00143412 +I0410 14:43:31.228132 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:43:33.202606 18534 solver.cpp:218] Iteration 9816 (2.45887 iter/s, 4.8803s/12 iters), loss = 5.2628 +I0410 14:43:33.202661 18534 solver.cpp:237] Train net output #0: loss = 5.2628 (* 1 = 5.2628 loss) +I0410 14:43:33.202672 18534 sgd_solver.cpp:105] Iteration 9816, lr = 0.00143072 +I0410 14:43:38.024194 18534 solver.cpp:218] Iteration 9828 (2.48893 iter/s, 4.82135s/12 iters), loss = 5.25514 +I0410 14:43:38.024245 18534 solver.cpp:237] Train net output #0: loss = 5.25514 (* 1 = 5.25514 loss) +I0410 14:43:38.024255 18534 sgd_solver.cpp:105] Iteration 9828, lr = 0.00142732 +I0410 14:43:43.038004 18534 solver.cpp:218] Iteration 9840 (2.3935 iter/s, 5.01357s/12 iters), loss = 5.2511 +I0410 14:43:43.038055 18534 solver.cpp:237] Train net output #0: loss = 5.2511 (* 1 = 5.2511 loss) +I0410 14:43:43.038067 18534 sgd_solver.cpp:105] Iteration 9840, lr = 0.00142393 +I0410 14:43:47.973176 18534 solver.cpp:218] Iteration 9852 (2.43164 iter/s, 4.93493s/12 iters), loss = 5.27009 +I0410 14:43:47.973232 18534 solver.cpp:237] Train net output #0: loss = 5.27009 (* 1 = 5.27009 loss) +I0410 14:43:47.973244 18534 sgd_solver.cpp:105] Iteration 9852, lr = 0.00142055 +I0410 14:43:52.985687 18534 solver.cpp:218] Iteration 9864 (2.39413 iter/s, 5.01226s/12 iters), loss = 5.28889 +I0410 14:43:52.985747 18534 solver.cpp:237] Train net output #0: loss = 5.28889 (* 1 = 5.28889 loss) +I0410 14:43:52.985759 18534 sgd_solver.cpp:105] Iteration 9864, lr = 0.00141718 +I0410 14:43:57.830960 18534 solver.cpp:218] Iteration 9876 (2.47677 iter/s, 4.84503s/12 iters), loss = 5.2701 +I0410 14:43:57.831022 18534 solver.cpp:237] Train net output #0: loss = 5.2701 (* 1 = 5.2701 loss) +I0410 14:43:57.831033 18534 sgd_solver.cpp:105] Iteration 9876, lr = 0.00141381 +I0410 14:44:02.712857 18534 solver.cpp:218] Iteration 9888 (2.45818 iter/s, 4.88165s/12 iters), loss = 5.27584 +I0410 14:44:02.712934 18534 solver.cpp:237] Train net output #0: loss = 5.27584 (* 1 = 5.27584 loss) +I0410 14:44:02.712946 18534 sgd_solver.cpp:105] Iteration 9888, lr = 0.00141045 +I0410 14:44:04.679339 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9894.caffemodel +I0410 14:44:04.999131 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9894.solverstate +I0410 14:44:05.208710 18534 solver.cpp:330] Iteration 9894, Testing net (#0) +I0410 14:44:05.208730 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:44:05.731173 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:09.725765 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:44:09.725801 18534 solver.cpp:397] Test net output #1: loss = 5.28701 (* 1 = 5.28701 loss) +I0410 14:44:11.665619 18534 solver.cpp:218] Iteration 9900 (1.34043 iter/s, 8.95236s/12 iters), loss = 5.27479 +I0410 14:44:11.665668 18534 solver.cpp:237] Train net output #0: loss = 5.27479 (* 1 = 5.27479 loss) +I0410 14:44:11.665678 18534 sgd_solver.cpp:105] Iteration 9900, lr = 0.00140711 +I0410 14:44:16.565385 18534 solver.cpp:218] Iteration 9912 (2.44921 iter/s, 4.89953s/12 iters), loss = 5.25696 +I0410 14:44:16.565438 18534 solver.cpp:237] Train net output #0: loss = 5.25696 (* 1 = 5.25696 loss) +I0410 14:44:16.565448 18534 sgd_solver.cpp:105] Iteration 9912, lr = 0.00140377 +I0410 14:44:16.667649 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:21.463059 18534 solver.cpp:218] Iteration 9924 (2.45026 iter/s, 4.89744s/12 iters), loss = 5.27099 +I0410 14:44:21.463115 18534 solver.cpp:237] Train net output #0: loss = 5.27099 (* 1 = 5.27099 loss) +I0410 14:44:21.463125 18534 sgd_solver.cpp:105] Iteration 9924, lr = 0.00140043 +I0410 14:44:26.342335 18534 solver.cpp:218] Iteration 9936 (2.4595 iter/s, 4.87904s/12 iters), loss = 5.2885 +I0410 14:44:26.342379 18534 solver.cpp:237] Train net output #0: loss = 5.2885 (* 1 = 5.2885 loss) +I0410 14:44:26.342388 18534 sgd_solver.cpp:105] Iteration 9936, lr = 0.00139711 +I0410 14:44:31.262145 18534 solver.cpp:218] Iteration 9948 (2.43923 iter/s, 4.91958s/12 iters), loss = 5.25951 +I0410 14:44:31.262193 18534 solver.cpp:237] Train net output #0: loss = 5.25951 (* 1 = 5.25951 loss) +I0410 14:44:31.262204 18534 sgd_solver.cpp:105] Iteration 9948, lr = 0.00139379 +I0410 14:44:36.158255 18534 solver.cpp:218] Iteration 9960 (2.45104 iter/s, 4.89588s/12 iters), loss = 5.26968 +I0410 14:44:36.158423 18534 solver.cpp:237] Train net output #0: loss = 5.26968 (* 1 = 5.26968 loss) +I0410 14:44:36.158437 18534 sgd_solver.cpp:105] Iteration 9960, lr = 0.00139048 +I0410 14:44:41.086592 18534 solver.cpp:218] Iteration 9972 (2.43507 iter/s, 4.92799s/12 iters), loss = 5.26316 +I0410 14:44:41.086642 18534 solver.cpp:237] Train net output #0: loss = 5.26316 (* 1 = 5.26316 loss) +I0410 14:44:41.086654 18534 sgd_solver.cpp:105] Iteration 9972, lr = 0.00138718 +I0410 14:44:45.993822 18534 solver.cpp:218] Iteration 9984 (2.44549 iter/s, 4.90699s/12 iters), loss = 5.24719 +I0410 14:44:45.993872 18534 solver.cpp:237] Train net output #0: loss = 5.24719 (* 1 = 5.24719 loss) +I0410 14:44:45.993881 18534 sgd_solver.cpp:105] Iteration 9984, lr = 0.00138389 +I0410 14:44:50.393821 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9996.caffemodel +I0410 14:44:51.212801 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9996.solverstate +I0410 14:44:51.434640 18534 solver.cpp:330] Iteration 9996, Testing net (#0) +I0410 14:44:51.434669 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:44:51.953509 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:55.839910 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:44:55.839960 18534 solver.cpp:397] Test net output #1: loss = 5.28746 (* 1 = 5.28746 loss) +I0410 14:44:55.922309 18534 solver.cpp:218] Iteration 9996 (1.20869 iter/s, 9.92808s/12 iters), loss = 5.27029 +I0410 14:44:55.922356 18534 solver.cpp:237] Train net output #0: loss = 5.27029 (* 1 = 5.27029 loss) +I0410 14:44:55.922367 18534 sgd_solver.cpp:105] Iteration 9996, lr = 0.0013806 +I0410 14:45:00.100855 18534 solver.cpp:218] Iteration 10008 (2.87195 iter/s, 4.17834s/12 iters), loss = 5.24436 +I0410 14:45:00.100899 18534 solver.cpp:237] Train net output #0: loss = 5.24436 (* 1 = 5.24436 loss) +I0410 14:45:00.100909 18534 sgd_solver.cpp:105] Iteration 10008, lr = 0.00137732 +I0410 14:45:02.283413 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:45:04.961716 18534 solver.cpp:218] Iteration 10020 (2.46881 iter/s, 4.86063s/12 iters), loss = 5.26846 +I0410 14:45:04.961762 18534 solver.cpp:237] Train net output #0: loss = 5.26846 (* 1 = 5.26846 loss) +I0410 14:45:04.961771 18534 sgd_solver.cpp:105] Iteration 10020, lr = 0.00137405 +I0410 14:45:09.897856 18534 solver.cpp:218] Iteration 10032 (2.43117 iter/s, 4.9359s/12 iters), loss = 5.27802 +I0410 14:45:09.897987 18534 solver.cpp:237] Train net output #0: loss = 5.27802 (* 1 = 5.27802 loss) +I0410 14:45:09.898000 18534 sgd_solver.cpp:105] Iteration 10032, lr = 0.00137079 +I0410 14:45:14.793913 18534 solver.cpp:218] Iteration 10044 (2.45111 iter/s, 4.89574s/12 iters), loss = 5.28471 +I0410 14:45:14.793985 18534 solver.cpp:237] Train net output #0: loss = 5.28471 (* 1 = 5.28471 loss) +I0410 14:45:14.793998 18534 sgd_solver.cpp:105] Iteration 10044, lr = 0.00136754 +I0410 14:45:19.651749 18534 solver.cpp:218] Iteration 10056 (2.47037 iter/s, 4.85758s/12 iters), loss = 5.2768 +I0410 14:45:19.651798 18534 solver.cpp:237] Train net output #0: loss = 5.2768 (* 1 = 5.2768 loss) +I0410 14:45:19.651808 18534 sgd_solver.cpp:105] Iteration 10056, lr = 0.00136429 +I0410 14:45:24.804180 18534 solver.cpp:218] Iteration 10068 (2.32911 iter/s, 5.15218s/12 iters), loss = 5.274 +I0410 14:45:24.804237 18534 solver.cpp:237] Train net output #0: loss = 5.274 (* 1 = 5.274 loss) +I0410 14:45:24.804250 18534 sgd_solver.cpp:105] Iteration 10068, lr = 0.00136105 +I0410 14:45:29.649468 18534 solver.cpp:218] Iteration 10080 (2.47675 iter/s, 4.84505s/12 iters), loss = 5.26335 +I0410 14:45:29.649518 18534 solver.cpp:237] Train net output #0: loss = 5.26335 (* 1 = 5.26335 loss) +I0410 14:45:29.649528 18534 sgd_solver.cpp:105] Iteration 10080, lr = 0.00135782 +I0410 14:45:34.484151 18534 solver.cpp:218] Iteration 10092 (2.48219 iter/s, 4.83444s/12 iters), loss = 5.27394 +I0410 14:45:34.484195 18534 solver.cpp:237] Train net output #0: loss = 5.27394 (* 1 = 5.27394 loss) +I0410 14:45:34.484205 18534 sgd_solver.cpp:105] Iteration 10092, lr = 0.0013546 +I0410 14:45:36.463091 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10098.caffemodel +I0410 14:45:36.789631 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10098.solverstate +I0410 14:45:37.006826 18534 solver.cpp:330] Iteration 10098, Testing net (#0) +I0410 14:45:37.006855 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:45:37.477396 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:45:41.597610 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:45:41.597715 18534 solver.cpp:397] Test net output #1: loss = 5.28708 (* 1 = 5.28708 loss) +I0410 14:45:43.541239 18534 solver.cpp:218] Iteration 10104 (1.32498 iter/s, 9.05671s/12 iters), loss = 5.27303 +I0410 14:45:43.541290 18534 solver.cpp:237] Train net output #0: loss = 5.27303 (* 1 = 5.27303 loss) +I0410 14:45:43.541301 18534 sgd_solver.cpp:105] Iteration 10104, lr = 0.00135138 +I0410 14:45:47.807780 18538 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:45:48.419661 18534 solver.cpp:218] Iteration 10116 (2.45993 iter/s, 4.87819s/12 iters), loss = 5.26127 +I0410 14:45:48.419701 18534 solver.cpp:237] Train net output #0: loss = 5.26127 (* 1 = 5.26127 loss) +I0410 14:45:48.419710 18534 sgd_solver.cpp:105] Iteration 10116, lr = 0.00134817 +I0410 14:45:53.336786 18534 solver.cpp:218] Iteration 10128 (2.44056 iter/s, 4.9169s/12 iters), loss = 5.27442 +I0410 14:45:53.336838 18534 solver.cpp:237] Train net output #0: loss = 5.27442 (* 1 = 5.27442 loss) +I0410 14:45:53.336849 18534 sgd_solver.cpp:105] Iteration 10128, lr = 0.00134497 +I0410 14:45:58.254907 18534 solver.cpp:218] Iteration 10140 (2.44007 iter/s, 4.91788s/12 iters), loss = 5.28133 +I0410 14:45:58.254961 18534 solver.cpp:237] Train net output #0: loss = 5.28133 (* 1 = 5.28133 loss) +I0410 14:45:58.254971 18534 sgd_solver.cpp:105] Iteration 10140, lr = 0.00134178 +I0410 14:46:03.121620 18534 solver.cpp:218] Iteration 10152 (2.46585 iter/s, 4.86647s/12 iters), loss = 5.27674 +I0410 14:46:03.121675 18534 solver.cpp:237] Train net output #0: loss = 5.27674 (* 1 = 5.27674 loss) +I0410 14:46:03.121686 18534 sgd_solver.cpp:105] Iteration 10152, lr = 0.00133859 +I0410 14:46:08.065168 18534 solver.cpp:218] Iteration 10164 (2.42752 iter/s, 4.94331s/12 iters), loss = 5.26675 +I0410 14:46:08.065207 18534 solver.cpp:237] Train net output #0: loss = 5.26675 (* 1 = 5.26675 loss) +I0410 14:46:08.065214 18534 sgd_solver.cpp:105] Iteration 10164, lr = 0.00133541 +I0410 14:46:12.953562 18534 solver.cpp:218] Iteration 10176 (2.4549 iter/s, 4.88817s/12 iters), loss = 5.2773 +I0410 14:46:12.953626 18534 solver.cpp:237] Train net output #0: loss = 5.2773 (* 1 = 5.2773 loss) +I0410 14:46:12.953634 18534 sgd_solver.cpp:105] Iteration 10176, lr = 0.00133224 +I0410 14:46:17.822516 18534 solver.cpp:218] Iteration 10188 (2.46473 iter/s, 4.86869s/12 iters), loss = 5.27726 +I0410 14:46:17.822579 18534 solver.cpp:237] Train net output #0: loss = 5.27726 (* 1 = 5.27726 loss) +I0410 14:46:17.822592 18534 sgd_solver.cpp:105] Iteration 10188, lr = 0.00132908 +I0410 14:46:22.383455 18534 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10200.caffemodel +I0410 14:46:22.689483 18534 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10200.solverstate +I0410 14:46:22.910619 18534 solver.cpp:310] Iteration 10200, loss = 5.26505 +I0410 14:46:22.910642 18534 solver.cpp:330] Iteration 10200, Testing net (#0) +I0410 14:46:22.910647 18534 net.cpp:676] Ignoring source layer train-data +I0410 14:46:23.250124 18546 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:46:27.188465 18534 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:46:27.188511 18534 solver.cpp:397] Test net output #1: loss = 5.28643 (* 1 = 5.28643 loss) +I0410 14:46:27.188522 18534 solver.cpp:315] Optimization Done. +I0410 14:46:27.188529 18534 caffe.cpp:259] Optimization Done. diff --git a/cars/architecture-investigations/fc/3-layers/256/conf.csv b/cars/architecture-investigations/fc/3-layers/256/conf.csv new file mode 100644 index 0000000..e1b505f --- /dev/null +++ b/cars/architecture-investigations/fc/3-layers/256/conf.csv @@ -0,0 +1,197 @@ +,AM General Hummer SUV 2000,Acura RL Sedan 2012,Acura TL Sedan 2012,Acura TL Type-S 2008,Acura TSX Sedan 2012,Acura Integra Type R 2001,Acura ZDX Hatchback 2012,Aston Martin V8 Vantage Convertible 2012,Aston Martin V8 Vantage Coupe 2012,Aston Martin Virage Convertible 2012,Aston Martin Virage Coupe 2012,Audi RS 4 Convertible 2008,Audi A5 Coupe 2012,Audi TTS Coupe 2012,Audi R8 Coupe 2012,Audi V8 Sedan 1994,Audi 100 Sedan 1994,Audi 100 Wagon 1994,Audi TT Hatchback 2011,Audi S6 Sedan 2011,Audi S5 Convertible 2012,Audi S5 Coupe 2012,Audi S4 Sedan 2012,Audi S4 Sedan 2007,Audi TT RS Coupe 2012,BMW ActiveHybrid 5 Sedan 2012,BMW 1 Series Convertible 2012,BMW 1 Series Coupe 2012,BMW 3 Series Sedan 2012,BMW 3 Series Wagon 2012,BMW 6 Series Convertible 2007,BMW X5 SUV 2007,BMW X6 SUV 2012,BMW M3 Coupe 2012,BMW M5 Sedan 2010,BMW M6 Convertible 2010,BMW X3 SUV 2012,BMW Z4 Convertible 2012,Bentley Continental Supersports Conv. Convertible 2012,Bentley Arnage Sedan 2009,Bentley Mulsanne Sedan 2011,Bentley Continental GT Coupe 2012,Bentley Continental GT Coupe 2007,Bentley Continental Flying Spur Sedan 2007,Bugatti Veyron 16.4 Convertible 2009,Bugatti Veyron 16.4 Coupe 2009,Buick Regal GS 2012,Buick Rainier SUV 2007,Buick Verano Sedan 2012,Buick Enclave SUV 2012,Cadillac CTS-V Sedan 2012,Cadillac SRX SUV 2012,Cadillac Escalade EXT Crew Cab 2007,Chevrolet Silverado 1500 Hybrid Crew Cab 2012,Chevrolet Corvette Convertible 2012,Chevrolet Corvette ZR1 2012,Chevrolet Corvette Ron Fellows Edition Z06 2007,Chevrolet Traverse SUV 2012,Chevrolet Camaro Convertible 2012,Chevrolet HHR SS 2010,Chevrolet Impala Sedan 2007,Chevrolet Tahoe Hybrid SUV 2012,Chevrolet Sonic Sedan 2012,Chevrolet Express Cargo Van 2007,Chevrolet Avalanche Crew Cab 2012,Chevrolet Cobalt SS 2010,Chevrolet Malibu Hybrid Sedan 2010,Chevrolet TrailBlazer SS 2009,Chevrolet Silverado 2500HD Regular Cab 2012,Chevrolet Silverado 1500 Classic Extended Cab 2007,Chevrolet Express Van 2007,Chevrolet Monte Carlo Coupe 2007,Chevrolet Malibu Sedan 2007,Chevrolet Silverado 1500 Extended Cab 2012,Chevrolet Silverado 1500 Regular Cab 2012,Chrysler Aspen SUV 2009,Chrysler Sebring Convertible 2010,Chrysler Town and Country Minivan 2012,Chrysler 300 SRT-8 2010,Chrysler Crossfire Convertible 2008,Chrysler PT Cruiser Convertible 2008,Daewoo Nubira Wagon 2002,Dodge Caliber Wagon 2012,Dodge Caliber Wagon 2007,Dodge Caravan Minivan 1997,Dodge Ram Pickup 3500 Crew Cab 2010,Dodge Ram Pickup 3500 Quad Cab 2009,Dodge Sprinter Cargo Van 2009,Dodge Journey SUV 2012,Dodge Dakota Crew Cab 2010,Dodge Dakota Club Cab 2007,Dodge Magnum Wagon 2008,Dodge Challenger SRT8 2011,Dodge Durango SUV 2012,Dodge Durango SUV 2007,Dodge Charger Sedan 2012,Dodge Charger SRT-8 2009,Eagle Talon Hatchback 1998,FIAT 500 Abarth 2012,FIAT 500 Convertible 2012,Ferrari FF Coupe 2012,Ferrari California Convertible 2012,Ferrari 458 Italia Convertible 2012,Ferrari 458 Italia Coupe 2012,Fisker Karma Sedan 2012,Ford F-450 Super Duty Crew Cab 2012,Ford Mustang Convertible 2007,Ford Freestar Minivan 2007,Ford Expedition EL SUV 2009,Ford Edge SUV 2012,Ford Ranger SuperCab 2011,Ford GT Coupe 2006,Ford F-150 Regular Cab 2012,Ford F-150 Regular Cab 2007,Ford Focus Sedan 2007,Ford E-Series Wagon Van 2012,Ford Fiesta Sedan 2012,GMC Terrain SUV 2012,GMC Savana Van 2012,GMC Yukon Hybrid SUV 2012,GMC Acadia SUV 2012,GMC Canyon Extended Cab 2012,Geo Metro Convertible 1993,HUMMER H3T Crew Cab 2010,HUMMER H2 SUT Crew Cab 2009,Honda Odyssey Minivan 2012,Honda Odyssey Minivan 2007,Honda Accord Coupe 2012,Honda Accord Sedan 2012,Hyundai Veloster Hatchback 2012,Hyundai Santa Fe SUV 2012,Hyundai Tucson SUV 2012,Hyundai Veracruz SUV 2012,Hyundai Sonata Hybrid Sedan 2012,Hyundai Elantra Sedan 2007,Hyundai Accent Sedan 2012,Hyundai Genesis Sedan 2012,Hyundai Sonata Sedan 2012,Hyundai Elantra Touring Hatchback 2012,Hyundai Azera Sedan 2012,Infiniti G Coupe IPL 2012,Infiniti QX56 SUV 2011,Isuzu Ascender SUV 2008,Jaguar XK XKR 2012,Jeep Patriot SUV 2012,Jeep Wrangler SUV 2012,Jeep Liberty SUV 2012,Jeep Grand Cherokee SUV 2012,Jeep Compass SUV 2012,Lamborghini Reventon Coupe 2008,Lamborghini Aventador Coupe 2012,Lamborghini Gallardo LP 570-4 Superleggera 2012,Lamborghini Diablo Coupe 2001,Land Rover Range Rover SUV 2012,Land Rover LR2 SUV 2012,Lincoln Town Car Sedan 2011,MINI Cooper Roadster Convertible 2012,Maybach Landaulet Convertible 2012,Mazda Tribute SUV 2011,McLaren MP4-12C Coupe 2012,Mercedes-Benz 300-Class Convertible 1993,Mercedes-Benz C-Class Sedan 2012,Mercedes-Benz SL-Class Coupe 2009,Mercedes-Benz E-Class Sedan 2012,Mercedes-Benz S-Class Sedan 2012,Mercedes-Benz Sprinter Van 2012,Mitsubishi Lancer Sedan 2012,Nissan Leaf Hatchback 2012,Nissan NV Passenger Van 2012,Nissan Juke Hatchback 2012,Nissan 240SX Coupe 1998,Plymouth Neon Coupe 1999,Porsche Panamera Sedan 2012,Ram C/V Cargo Van Minivan 2012,Rolls-Royce Phantom Drophead Coupe Convertible 2012,Rolls-Royce Ghost Sedan 2012,Rolls-Royce Phantom Sedan 2012,Scion xD Hatchback 2012,Spyker C8 Convertible 2009,Spyker C8 Coupe 2009,Suzuki Aerio Sedan 2007,Suzuki Kizashi Sedan 2012,Suzuki SX4 Hatchback 2012,Suzuki SX4 Sedan 2012,Tesla Model S Sedan 2012,Toyota Sequoia SUV 2012,Toyota Camry Sedan 2012,Toyota Corolla Sedan 2012,Toyota 4Runner SUV 2012,Volkswagen Golf Hatchback 2012,Volkswagen Golf Hatchback 1991,Volkswagen Beetle Hatchback 2012,Volvo C30 Hatchback 2012,Volvo 240 Sedan 1993,Volvo XC90 SUV 2007,smart fortwo Convertible 2012,Per-class accuracy +AM General Hummer SUV 2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura RL Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura TL Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura TL Type-S 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura TSX Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura Integra Type R 2001,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura ZDX Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Aston Martin V8 Vantage Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Aston Martin V8 Vantage Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Aston Martin Virage Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Aston Martin Virage Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Audi RS 4 Convertible 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Audi A5 Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Audi TTS Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Audi R8 Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Audi V8 Sedan 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +BMW M5 Sedan 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +BMW M6 Convertible 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +BMW X3 SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +BMW Z4 Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Continental Supersports Conv. Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Arnage Sedan 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Mulsanne Sedan 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Continental GT Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Continental GT Coupe 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Continental Flying Spur Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bugatti Veyron 16.4 Convertible 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bugatti Veyron 16.4 Coupe 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Buick Regal GS 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Buick Rainier SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Buick Verano Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Buick Enclave SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Cadillac CTS-V Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Cadillac SRX SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Cadillac Escalade EXT Crew Cab 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Silverado 1500 Hybrid Crew Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Corvette Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Corvette ZR1 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Corvette Ron Fellows Edition Z06 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Traverse SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Camaro Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet HHR SS 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Impala Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Tahoe Hybrid SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Sonic Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Express Cargo Van 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Avalanche Crew Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Cobalt SS 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Malibu Hybrid Sedan 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet TrailBlazer SS 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Silverado 2500HD Regular Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Silverado 1500 Classic Extended Cab 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Express Van 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Monte Carlo Coupe 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Malibu Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Silverado 1500 Extended Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Silverado 1500 Regular Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chrysler Aspen SUV 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chrysler Sebring Convertible 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +GMC Terrain SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +GMC Savana Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,100.0% +GMC Yukon Hybrid SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +GMC Acadia SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +GMC Canyon Extended Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Geo Metro Convertible 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Hyundai Veloster Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Hyundai Santa Fe SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Hyundai Tucson SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Hyundai Veracruz SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Hyundai Sonata Hybrid Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Hyundai Elantra Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Hyundai Accent Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Hyundai Genesis Sedan 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Hyundai Azera Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Infiniti G Coupe IPL 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Infiniti QX56 SUV 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Isuzu Ascender SUV 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Jeep Wrangler SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Jeep Liberty SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Jeep Grand Cherokee SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Jeep Compass SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Lamborghini Reventon Coupe 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Lamborghini Aventador Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Lamborghini Gallardo LP 570-4 Superleggera 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Lamborghini Diablo Coupe 2001,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Land Rover Range Rover SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Land Rover LR2 SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Lincoln Town Car Sedan 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +MINI Cooper Roadster Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Maybach Landaulet Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mazda Tribute SUV 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +McLaren MP4-12C Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mercedes-Benz 300-Class Convertible 1993,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mercedes-Benz C-Class Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mercedes-Benz SL-Class Coupe 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Suzuki SX4 Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Tesla Model S Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Toyota Sequoia SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Toyota Camry Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Toyota Corolla Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Toyota 4Runner SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Volkswagen Golf Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Volkswagen Golf Hatchback 1991,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Volkswagen Beetle Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Volvo C30 Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Volvo 240 Sedan 1993,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Volvo XC90 SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +smart fortwo Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% diff --git a/cars/architecture-investigations/fc/3-layers/256/deploy.prototxt b/cars/architecture-investigations/fc/3-layers/256/deploy.prototxt new file mode 100644 index 0000000..945ff2e --- /dev/null +++ b/cars/architecture-investigations/fc/3-layers/256/deploy.prototxt @@ -0,0 +1,381 @@ +input: "data" +input_shape { + dim: 1 + dim: 3 + dim: 227 + dim: 227 +} +layer { + name: "conv1" + type: "Convolution" + bottom: "data" + top: "conv1" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu1" + type: "ReLU" + bottom: "conv1" + top: "conv1" +} +layer { + name: "norm1" + type: "LRN" + bottom: "conv1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool1" + type: "Pooling" + bottom: "norm1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv2" + type: "Convolution" + bottom: "pool1" + top: "conv2" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu2" + type: "ReLU" + bottom: "conv2" + top: "conv2" +} +layer { + name: "norm2" + type: "LRN" + bottom: "conv2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool2" + type: "Pooling" + bottom: "norm2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv3" + type: "Convolution" + bottom: "pool2" + top: "conv3" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu3" + type: "ReLU" + bottom: "conv3" + top: "conv3" +} +layer { + name: "conv4" + type: "Convolution" + bottom: "conv3" + top: "conv4" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu4" + type: "ReLU" + bottom: "conv4" + top: "conv4" +} +layer { + name: "conv5" + type: "Convolution" + bottom: "conv4" + top: "conv5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu5" + type: "ReLU" + bottom: "conv5" + top: "conv5" +} +layer { + name: "pool5" + type: "Pooling" + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "fc6" + type: "InnerProduct" + bottom: "pool5" + top: "fc6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu6" + type: "ReLU" + bottom: "fc6" + top: "fc6" +} +layer { + name: "drop6" + type: "Dropout" + bottom: "fc6" + top: "fc6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7" + type: "InnerProduct" + bottom: "fc6" + top: "fc7" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7" + type: "ReLU" + bottom: "fc7" + top: "fc7" +} +layer { + name: "drop7" + type: "Dropout" + bottom: "fc7" + top: "fc7" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7.5" + type: "InnerProduct" + bottom: "fc7" + top: "fc7.5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7.5" + type: "ReLU" + bottom: "fc7.5" + top: "fc7.5" +} +layer { + name: "drop7.5" + type: "Dropout" + bottom: "fc7.5" + top: "fc7.5" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc8" + type: "InnerProduct" + bottom: "fc7.5" + top: "fc8" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + 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zaGvS7p%!2pSoj#cu!y=r=wrce3-VQ!n-wT8i7Dx9X$?AYufs|fnazx1*K|M$4qkbK zg{HdIA`Xv-4VQ(=d*Kfedf9{)_){@~{z@%u6VRXm__54A*|el{4yLXlw1H zj?@gLV}Cqszc>9er*H^Df7f}~(oX)fAW3?djXd*o;-AH!MCn|l$TLPKj+Xapi;q_F zb4G!Q|3kApeGmQ5V&pjJ1@Px5Z~tcW@gJ$`(rw&6DD}=ii{Uv-CvW{9(Ep#>_^IZr zS#+&Qelk3!cl{07@?#`@!L^cn!hbXRcybp^#ts?aM0-fZE3S_W^q;ndzIvgWZP32~ DQSL0d literal 0 HcmV?d00001 diff --git a/cars/architecture-investigations/fc/3-layers/256/solver.prototxt b/cars/architecture-investigations/fc/3-layers/256/solver.prototxt new file mode 100644 index 0000000..803ddda --- /dev/null +++ b/cars/architecture-investigations/fc/3-layers/256/solver.prototxt @@ -0,0 +1,14 @@ +test_iter: 51 +test_interval: 102 +base_lr: 0.00999999977648 +display: 12 +max_iter: 10200 +lr_policy: "exp" +gamma: 0.999801933765 +momentum: 0.899999976158 +weight_decay: 9.99999974738e-05 +snapshot: 102 +snapshot_prefix: "snapshot" +solver_mode: GPU +net: "train_val.prototxt" +solver_type: SGD diff --git a/cars/architecture-investigations/fc/3-layers/256/train_val.prototxt b/cars/architecture-investigations/fc/3-layers/256/train_val.prototxt new file mode 100644 index 0000000..c16b6eb --- /dev/null +++ b/cars/architecture-investigations/fc/3-layers/256/train_val.prototxt @@ -0,0 +1,422 @@ +layer { + name: "train-data" + type: "Data" + top: "data" + top: "label" + include { + phase: TRAIN + } + transform_param { + mirror: true + crop_size: 227 + mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" + } + data_param { + source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db" + batch_size: 128 + backend: LMDB + } +} +layer { + name: "val-data" + type: "Data" + top: "data" + top: "label" + include { + phase: TEST + } + transform_param { + crop_size: 227 + mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" + } + data_param { + source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db" + batch_size: 32 + backend: LMDB + } +} +layer { + name: "conv1" + type: "Convolution" + bottom: "data" + top: "conv1" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu1" + type: "ReLU" + bottom: "conv1" + top: "conv1" +} +layer { + name: "norm1" + type: "LRN" + bottom: "conv1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool1" + type: "Pooling" + bottom: "norm1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv2" + type: "Convolution" + bottom: "pool1" + top: "conv2" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu2" + type: "ReLU" + bottom: "conv2" + top: "conv2" +} +layer { + name: "norm2" + type: "LRN" + bottom: "conv2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool2" + type: "Pooling" + bottom: "norm2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv3" + type: "Convolution" + bottom: "pool2" + top: "conv3" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu3" + type: "ReLU" + bottom: "conv3" + top: "conv3" +} +layer { + name: "conv4" + type: "Convolution" + bottom: "conv3" + top: "conv4" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu4" + type: "ReLU" + bottom: "conv4" + top: "conv4" +} +layer { + name: "conv5" + type: "Convolution" + bottom: "conv4" + top: "conv5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu5" + type: "ReLU" + bottom: "conv5" + top: "conv5" +} +layer { + name: "pool5" + type: "Pooling" + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "fc6" + type: "InnerProduct" + bottom: "pool5" + top: "fc6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu6" + type: "ReLU" + bottom: "fc6" + top: "fc6" +} +layer { + name: "drop6" + type: "Dropout" + bottom: "fc6" + top: "fc6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7" + type: "InnerProduct" + bottom: "fc6" + top: "fc7" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7" + type: "ReLU" + bottom: "fc7" + top: "fc7" +} +layer { + name: "drop7" + type: "Dropout" + bottom: "fc7" + top: "fc7" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7.5" + type: "InnerProduct" + bottom: "fc7" + top: "fc7.5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7.5" + type: "ReLU" + bottom: "fc7.5" + top: "fc7.5" +} +layer { + name: "drop7.5" + type: "Dropout" + bottom: "fc7.5" + top: "fc7.5" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc8" + type: "InnerProduct" + bottom: "fc7.5" + top: "fc8" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 196 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "accuracy" + type: "Accuracy" + bottom: "fc8" + bottom: "label" + top: "accuracy" + include { + phase: TEST + } +} +layer { + name: "loss" + type: "SoftmaxWithLoss" + bottom: "fc8" + bottom: "label" + top: "loss" +} diff --git a/cars/architecture-investigations/fc/4-layers/256/caffe_output.log b/cars/architecture-investigations/fc/4-layers/256/caffe_output.log new file mode 100644 index 0000000..7ada5b8 --- /dev/null +++ b/cars/architecture-investigations/fc/4-layers/256/caffe_output.log @@ -0,0 +1,4822 @@ +I0410 13:30:23.774256 18606 upgrade_proto.cpp:1082] Attempting to upgrade input file specified using deprecated 'solver_type' field (enum)': /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210410-133021-4b8a/solver.prototxt +I0410 13:30:23.774418 18606 upgrade_proto.cpp:1089] Successfully upgraded file specified using deprecated 'solver_type' field (enum) to 'type' field (string). +W0410 13:30:23.774425 18606 upgrade_proto.cpp:1091] Note that future Caffe releases will only support 'type' field (string) for a solver's type. +I0410 13:30:23.774482 18606 caffe.cpp:218] Using GPUs 3 +I0410 13:30:23.797574 18606 caffe.cpp:223] GPU 3: GeForce GTX 1080 Ti +I0410 13:30:24.089777 18606 solver.cpp:44] Initializing solver from parameters: +test_iter: 51 +test_interval: 102 +base_lr: 0.01 +display: 12 +max_iter: 10200 +lr_policy: "exp" +gamma: 0.99980193 +momentum: 0.9 +weight_decay: 0.0001 +snapshot: 102 +snapshot_prefix: "snapshot" +solver_mode: GPU +device_id: 3 +net: "train_val.prototxt" +train_state { +level: 0 +stage: "" +} +type: "SGD" +I0410 13:30:24.090523 18606 solver.cpp:87] Creating training net from net file: train_val.prototxt +I0410 13:30:24.091147 18606 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer val-data +I0410 13:30:24.091167 18606 net.cpp:294] The NetState phase (0) differed from the phase (1) specified by a rule in layer accuracy +I0410 13:30:24.091339 18606 net.cpp:51] Initializing net from parameters: +state { +phase: TRAIN +level: 0 +stage: "" +} +layer { +name: "train-data" +type: "Data" +top: "data" +top: "label" +include { +phase: TRAIN +} +transform_param { +mirror: true +crop_size: 227 +mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" +} +data_param { +source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db" +batch_size: 128 +backend: LMDB +} +} +layer { +name: "conv1" +type: "Convolution" +bottom: "data" +top: "conv1" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 96 +kernel_size: 11 +stride: 4 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu1" +type: "ReLU" +bottom: "conv1" +top: "conv1" +} +layer { +name: "norm1" +type: "LRN" +bottom: "conv1" +top: "norm1" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool1" +type: "Pooling" +bottom: "norm1" +top: "pool1" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv2" +type: "Convolution" +bottom: "pool1" +top: "conv2" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 2 +kernel_size: 5 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu2" +type: "ReLU" +bottom: "conv2" +top: "conv2" +} +layer { +name: "norm2" +type: "LRN" +bottom: "conv2" +top: "norm2" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool2" +type: "Pooling" +bottom: "norm2" +top: "pool2" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv3" +type: "Convolution" +bottom: "pool2" +top: "conv3" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu3" +type: "ReLU" +bottom: "conv3" +top: "conv3" +} +layer { +name: "conv4" +type: "Convolution" +bottom: "conv3" +top: "conv4" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu4" +type: "ReLU" +bottom: "conv4" +top: "conv4" +} +layer { +name: "conv5" +type: "Convolution" +bottom: "conv4" +top: "conv5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu5" +type: "ReLU" +bottom: "conv5" +top: "conv5" +} +layer { +name: "pool5" +type: "Pooling" +bottom: "conv5" +top: "pool5" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "fc6" +type: "InnerProduct" +bottom: "pool5" +top: "fc6" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu6" +type: "ReLU" +bottom: "fc6" +top: "fc6" +} +layer { +name: "drop6" +type: "Dropout" +bottom: "fc6" +top: "fc6" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7" +type: "InnerProduct" +bottom: "fc6" +top: "fc7" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7" +type: "ReLU" +bottom: "fc7" +top: "fc7" +} +layer { +name: "drop7" +type: "Dropout" +bottom: "fc7" +top: "fc7" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7.5" +type: "InnerProduct" +bottom: "fc7" +top: "fc7.5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7.5" +type: "ReLU" +bottom: "fc7.5" +top: "fc7.5" +} +layer { +name: "drop7.5" +type: "Dropout" +bottom: "fc7.5" +top: "fc7.5" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7.6" +type: "InnerProduct" +bottom: "fc7.5" +top: "fc7.6" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7.6" +type: "ReLU" +bottom: "fc7.6" +top: "fc7.6" +} +layer { +name: "drop7.6" +type: "Dropout" +bottom: "fc7.6" +top: "fc7.6" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc8" +type: "InnerProduct" +bottom: "fc7.6" +top: "fc8" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 196 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "loss" +type: "SoftmaxWithLoss" +bottom: "fc8" +bottom: "label" +top: "loss" +} +I0410 13:30:24.091445 18606 layer_factory.hpp:77] Creating layer train-data +I0410 13:30:24.093165 18606 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/train_db +I0410 13:30:24.093561 18606 net.cpp:84] Creating Layer train-data +I0410 13:30:24.093585 18606 net.cpp:380] train-data -> data +I0410 13:30:24.093623 18606 net.cpp:380] train-data -> label +I0410 13:30:24.093647 18606 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto +I0410 13:30:24.104099 18606 data_layer.cpp:45] output data size: 128,3,227,227 +I0410 13:30:24.269528 18606 net.cpp:122] Setting up train-data +I0410 13:30:24.269552 18606 net.cpp:129] Top shape: 128 3 227 227 (19787136) +I0410 13:30:24.269558 18606 net.cpp:129] Top shape: 128 (128) +I0410 13:30:24.269562 18606 net.cpp:137] Memory required for data: 79149056 +I0410 13:30:24.269593 18606 layer_factory.hpp:77] Creating layer conv1 +I0410 13:30:24.269614 18606 net.cpp:84] Creating Layer conv1 +I0410 13:30:24.269621 18606 net.cpp:406] conv1 <- data +I0410 13:30:24.269634 18606 net.cpp:380] conv1 -> conv1 +I0410 13:30:24.876385 18606 net.cpp:122] Setting up conv1 +I0410 13:30:24.876408 18606 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:30:24.876412 18606 net.cpp:137] Memory required for data: 227833856 +I0410 13:30:24.876432 18606 layer_factory.hpp:77] Creating layer relu1 +I0410 13:30:24.876444 18606 net.cpp:84] Creating Layer relu1 +I0410 13:30:24.876448 18606 net.cpp:406] relu1 <- conv1 +I0410 13:30:24.876456 18606 net.cpp:367] relu1 -> conv1 (in-place) +I0410 13:30:24.876765 18606 net.cpp:122] Setting up relu1 +I0410 13:30:24.876773 18606 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:30:24.876777 18606 net.cpp:137] Memory required for data: 376518656 +I0410 13:30:24.876781 18606 layer_factory.hpp:77] Creating layer norm1 +I0410 13:30:24.876791 18606 net.cpp:84] Creating Layer norm1 +I0410 13:30:24.876794 18606 net.cpp:406] norm1 <- conv1 +I0410 13:30:24.876799 18606 net.cpp:380] norm1 -> norm1 +I0410 13:30:24.877271 18606 net.cpp:122] Setting up norm1 +I0410 13:30:24.877282 18606 net.cpp:129] Top shape: 128 96 55 55 (37171200) +I0410 13:30:24.877285 18606 net.cpp:137] Memory required for data: 525203456 +I0410 13:30:24.877290 18606 layer_factory.hpp:77] Creating layer pool1 +I0410 13:30:24.877297 18606 net.cpp:84] Creating Layer pool1 +I0410 13:30:24.877301 18606 net.cpp:406] pool1 <- norm1 +I0410 13:30:24.877306 18606 net.cpp:380] pool1 -> pool1 +I0410 13:30:24.877346 18606 net.cpp:122] Setting up pool1 +I0410 13:30:24.877351 18606 net.cpp:129] Top shape: 128 96 27 27 (8957952) +I0410 13:30:24.877355 18606 net.cpp:137] Memory required for data: 561035264 +I0410 13:30:24.877358 18606 layer_factory.hpp:77] Creating layer conv2 +I0410 13:30:24.877368 18606 net.cpp:84] Creating Layer conv2 +I0410 13:30:24.877372 18606 net.cpp:406] conv2 <- pool1 +I0410 13:30:24.877377 18606 net.cpp:380] conv2 -> conv2 +I0410 13:30:24.884753 18606 net.cpp:122] Setting up conv2 +I0410 13:30:24.884770 18606 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:30:24.884774 18606 net.cpp:137] Memory required for data: 656586752 +I0410 13:30:24.884784 18606 layer_factory.hpp:77] Creating layer relu2 +I0410 13:30:24.884793 18606 net.cpp:84] Creating Layer relu2 +I0410 13:30:24.884796 18606 net.cpp:406] relu2 <- conv2 +I0410 13:30:24.884801 18606 net.cpp:367] relu2 -> conv2 (in-place) +I0410 13:30:24.885254 18606 net.cpp:122] Setting up relu2 +I0410 13:30:24.885264 18606 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:30:24.885268 18606 net.cpp:137] Memory required for data: 752138240 +I0410 13:30:24.885272 18606 layer_factory.hpp:77] Creating layer norm2 +I0410 13:30:24.885280 18606 net.cpp:84] Creating Layer norm2 +I0410 13:30:24.885284 18606 net.cpp:406] norm2 <- conv2 +I0410 13:30:24.885289 18606 net.cpp:380] norm2 -> norm2 +I0410 13:30:24.885599 18606 net.cpp:122] Setting up norm2 +I0410 13:30:24.885607 18606 net.cpp:129] Top shape: 128 256 27 27 (23887872) +I0410 13:30:24.885612 18606 net.cpp:137] Memory required for data: 847689728 +I0410 13:30:24.885614 18606 layer_factory.hpp:77] Creating layer pool2 +I0410 13:30:24.885622 18606 net.cpp:84] Creating Layer pool2 +I0410 13:30:24.885627 18606 net.cpp:406] pool2 <- norm2 +I0410 13:30:24.885632 18606 net.cpp:380] pool2 -> pool2 +I0410 13:30:24.885660 18606 net.cpp:122] Setting up pool2 +I0410 13:30:24.885665 18606 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:30:24.885668 18606 net.cpp:137] Memory required for data: 869840896 +I0410 13:30:24.885671 18606 layer_factory.hpp:77] Creating layer conv3 +I0410 13:30:24.885681 18606 net.cpp:84] Creating Layer conv3 +I0410 13:30:24.885684 18606 net.cpp:406] conv3 <- pool2 +I0410 13:30:24.885689 18606 net.cpp:380] conv3 -> conv3 +I0410 13:30:24.906244 18606 net.cpp:122] Setting up conv3 +I0410 13:30:24.906261 18606 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:30:24.906265 18606 net.cpp:137] Memory required for data: 903067648 +I0410 13:30:24.906294 18606 layer_factory.hpp:77] Creating layer relu3 +I0410 13:30:24.906306 18606 net.cpp:84] Creating Layer relu3 +I0410 13:30:24.906311 18606 net.cpp:406] relu3 <- conv3 +I0410 13:30:24.906318 18606 net.cpp:367] relu3 -> conv3 (in-place) +I0410 13:30:24.906838 18606 net.cpp:122] Setting up relu3 +I0410 13:30:24.906848 18606 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:30:24.906852 18606 net.cpp:137] Memory required for data: 936294400 +I0410 13:30:24.906857 18606 layer_factory.hpp:77] Creating layer conv4 +I0410 13:30:24.906870 18606 net.cpp:84] Creating Layer conv4 +I0410 13:30:24.906874 18606 net.cpp:406] conv4 <- conv3 +I0410 13:30:24.906880 18606 net.cpp:380] conv4 -> conv4 +I0410 13:30:24.922952 18606 net.cpp:122] Setting up conv4 +I0410 13:30:24.922971 18606 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:30:24.922976 18606 net.cpp:137] Memory required for data: 969521152 +I0410 13:30:24.922984 18606 layer_factory.hpp:77] Creating layer relu4 +I0410 13:30:24.922996 18606 net.cpp:84] Creating Layer relu4 +I0410 13:30:24.922999 18606 net.cpp:406] relu4 <- conv4 +I0410 13:30:24.923007 18606 net.cpp:367] relu4 -> conv4 (in-place) +I0410 13:30:24.923377 18606 net.cpp:122] Setting up relu4 +I0410 13:30:24.923385 18606 net.cpp:129] Top shape: 128 384 13 13 (8306688) +I0410 13:30:24.923389 18606 net.cpp:137] Memory required for data: 1002747904 +I0410 13:30:24.923394 18606 layer_factory.hpp:77] Creating layer conv5 +I0410 13:30:24.923406 18606 net.cpp:84] Creating Layer conv5 +I0410 13:30:24.923410 18606 net.cpp:406] conv5 <- conv4 +I0410 13:30:24.923418 18606 net.cpp:380] conv5 -> conv5 +I0410 13:30:24.947127 18606 net.cpp:122] Setting up conv5 +I0410 13:30:24.947149 18606 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:30:24.947152 18606 net.cpp:137] Memory required for data: 1024899072 +I0410 13:30:24.947167 18606 layer_factory.hpp:77] Creating layer relu5 +I0410 13:30:24.947177 18606 net.cpp:84] Creating Layer relu5 +I0410 13:30:24.947182 18606 net.cpp:406] relu5 <- conv5 +I0410 13:30:24.947190 18606 net.cpp:367] relu5 -> conv5 (in-place) +I0410 13:30:24.947758 18606 net.cpp:122] Setting up relu5 +I0410 13:30:24.947770 18606 net.cpp:129] Top shape: 128 256 13 13 (5537792) +I0410 13:30:24.947774 18606 net.cpp:137] Memory required for data: 1047050240 +I0410 13:30:24.947778 18606 layer_factory.hpp:77] Creating layer pool5 +I0410 13:30:24.947788 18606 net.cpp:84] Creating Layer pool5 +I0410 13:30:24.947793 18606 net.cpp:406] pool5 <- conv5 +I0410 13:30:24.947799 18606 net.cpp:380] pool5 -> pool5 +I0410 13:30:24.947841 18606 net.cpp:122] Setting up pool5 +I0410 13:30:24.947849 18606 net.cpp:129] Top shape: 128 256 6 6 (1179648) +I0410 13:30:24.947851 18606 net.cpp:137] Memory required for data: 1051768832 +I0410 13:30:24.947854 18606 layer_factory.hpp:77] Creating layer fc6 +I0410 13:30:24.947865 18606 net.cpp:84] Creating Layer fc6 +I0410 13:30:24.947870 18606 net.cpp:406] fc6 <- pool5 +I0410 13:30:24.947875 18606 net.cpp:380] fc6 -> fc6 +I0410 13:30:24.972143 18606 net.cpp:122] Setting up fc6 +I0410 13:30:24.972163 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.972167 18606 net.cpp:137] Memory required for data: 1051899904 +I0410 13:30:24.972177 18606 layer_factory.hpp:77] Creating layer relu6 +I0410 13:30:24.972185 18606 net.cpp:84] Creating Layer relu6 +I0410 13:30:24.972190 18606 net.cpp:406] relu6 <- fc6 +I0410 13:30:24.972196 18606 net.cpp:367] relu6 -> fc6 (in-place) +I0410 13:30:24.972859 18606 net.cpp:122] Setting up relu6 +I0410 13:30:24.972868 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.972872 18606 net.cpp:137] Memory required for data: 1052030976 +I0410 13:30:24.972875 18606 layer_factory.hpp:77] Creating layer drop6 +I0410 13:30:24.972883 18606 net.cpp:84] Creating Layer drop6 +I0410 13:30:24.972887 18606 net.cpp:406] drop6 <- fc6 +I0410 13:30:24.972893 18606 net.cpp:367] drop6 -> fc6 (in-place) +I0410 13:30:24.972923 18606 net.cpp:122] Setting up drop6 +I0410 13:30:24.972927 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.972950 18606 net.cpp:137] Memory required for data: 1052162048 +I0410 13:30:24.972954 18606 layer_factory.hpp:77] Creating layer fc7 +I0410 13:30:24.972963 18606 net.cpp:84] Creating Layer fc7 +I0410 13:30:24.972967 18606 net.cpp:406] fc7 <- fc6 +I0410 13:30:24.972972 18606 net.cpp:380] fc7 -> fc7 +I0410 13:30:24.973672 18606 net.cpp:122] Setting up fc7 +I0410 13:30:24.973680 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.973682 18606 net.cpp:137] Memory required for data: 1052293120 +I0410 13:30:24.973688 18606 layer_factory.hpp:77] Creating layer relu7 +I0410 13:30:24.973695 18606 net.cpp:84] Creating Layer relu7 +I0410 13:30:24.973699 18606 net.cpp:406] relu7 <- fc7 +I0410 13:30:24.973703 18606 net.cpp:367] relu7 -> fc7 (in-place) +I0410 13:30:24.974231 18606 net.cpp:122] Setting up relu7 +I0410 13:30:24.974241 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.974243 18606 net.cpp:137] Memory required for data: 1052424192 +I0410 13:30:24.974247 18606 layer_factory.hpp:77] Creating layer drop7 +I0410 13:30:24.974253 18606 net.cpp:84] Creating Layer drop7 +I0410 13:30:24.974257 18606 net.cpp:406] drop7 <- fc7 +I0410 13:30:24.974263 18606 net.cpp:367] drop7 -> fc7 (in-place) +I0410 13:30:24.974289 18606 net.cpp:122] Setting up drop7 +I0410 13:30:24.974294 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.974298 18606 net.cpp:137] Memory required for data: 1052555264 +I0410 13:30:24.974300 18606 layer_factory.hpp:77] Creating layer fc7.5 +I0410 13:30:24.974306 18606 net.cpp:84] Creating Layer fc7.5 +I0410 13:30:24.974310 18606 net.cpp:406] fc7.5 <- fc7 +I0410 13:30:24.974316 18606 net.cpp:380] fc7.5 -> fc7.5 +I0410 13:30:24.975018 18606 net.cpp:122] Setting up fc7.5 +I0410 13:30:24.975025 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.975028 18606 net.cpp:137] Memory required for data: 1052686336 +I0410 13:30:24.975034 18606 layer_factory.hpp:77] Creating layer relu7.5 +I0410 13:30:24.975042 18606 net.cpp:84] Creating Layer relu7.5 +I0410 13:30:24.975046 18606 net.cpp:406] relu7.5 <- fc7.5 +I0410 13:30:24.975050 18606 net.cpp:367] relu7.5 -> fc7.5 (in-place) +I0410 13:30:24.975571 18606 net.cpp:122] Setting up relu7.5 +I0410 13:30:24.975580 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.975584 18606 net.cpp:137] Memory required for data: 1052817408 +I0410 13:30:24.975587 18606 layer_factory.hpp:77] Creating layer drop7.5 +I0410 13:30:24.975594 18606 net.cpp:84] Creating Layer drop7.5 +I0410 13:30:24.975597 18606 net.cpp:406] drop7.5 <- fc7.5 +I0410 13:30:24.975605 18606 net.cpp:367] drop7.5 -> fc7.5 (in-place) +I0410 13:30:24.975630 18606 net.cpp:122] Setting up drop7.5 +I0410 13:30:24.975636 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.975638 18606 net.cpp:137] Memory required for data: 1052948480 +I0410 13:30:24.975641 18606 layer_factory.hpp:77] Creating layer fc7.6 +I0410 13:30:24.975647 18606 net.cpp:84] Creating Layer fc7.6 +I0410 13:30:24.975651 18606 net.cpp:406] fc7.6 <- fc7.5 +I0410 13:30:24.975657 18606 net.cpp:380] fc7.6 -> fc7.6 +I0410 13:30:24.976347 18606 net.cpp:122] Setting up fc7.6 +I0410 13:30:24.976353 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.976357 18606 net.cpp:137] Memory required for data: 1053079552 +I0410 13:30:24.976369 18606 layer_factory.hpp:77] Creating layer relu7.6 +I0410 13:30:24.976374 18606 net.cpp:84] Creating Layer relu7.6 +I0410 13:30:24.976378 18606 net.cpp:406] relu7.6 <- fc7.6 +I0410 13:30:24.976383 18606 net.cpp:367] relu7.6 -> fc7.6 (in-place) +I0410 13:30:24.982831 18606 net.cpp:122] Setting up relu7.6 +I0410 13:30:24.982841 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.982844 18606 net.cpp:137] Memory required for data: 1053210624 +I0410 13:30:24.982848 18606 layer_factory.hpp:77] Creating layer drop7.6 +I0410 13:30:24.982856 18606 net.cpp:84] Creating Layer drop7.6 +I0410 13:30:24.982859 18606 net.cpp:406] drop7.6 <- fc7.6 +I0410 13:30:24.982867 18606 net.cpp:367] drop7.6 -> fc7.6 (in-place) +I0410 13:30:24.982889 18606 net.cpp:122] Setting up drop7.6 +I0410 13:30:24.982895 18606 net.cpp:129] Top shape: 128 256 (32768) +I0410 13:30:24.982908 18606 net.cpp:137] Memory required for data: 1053341696 +I0410 13:30:24.982913 18606 layer_factory.hpp:77] Creating layer fc8 +I0410 13:30:24.982920 18606 net.cpp:84] Creating Layer fc8 +I0410 13:30:24.982923 18606 net.cpp:406] fc8 <- fc7.6 +I0410 13:30:24.982930 18606 net.cpp:380] fc8 -> fc8 +I0410 13:30:24.983494 18606 net.cpp:122] Setting up fc8 +I0410 13:30:24.983501 18606 net.cpp:129] Top shape: 128 196 (25088) +I0410 13:30:24.983505 18606 net.cpp:137] Memory required for data: 1053442048 +I0410 13:30:24.983511 18606 layer_factory.hpp:77] Creating layer loss +I0410 13:30:24.983517 18606 net.cpp:84] Creating Layer loss +I0410 13:30:24.983521 18606 net.cpp:406] loss <- fc8 +I0410 13:30:24.983525 18606 net.cpp:406] loss <- label +I0410 13:30:24.983531 18606 net.cpp:380] loss -> loss +I0410 13:30:24.983539 18606 layer_factory.hpp:77] Creating layer loss +I0410 13:30:24.984172 18606 net.cpp:122] Setting up loss +I0410 13:30:24.984182 18606 net.cpp:129] Top shape: (1) +I0410 13:30:24.984186 18606 net.cpp:132] with loss weight 1 +I0410 13:30:24.984205 18606 net.cpp:137] Memory required for data: 1053442052 +I0410 13:30:24.984210 18606 net.cpp:198] loss needs backward computation. +I0410 13:30:24.984216 18606 net.cpp:198] fc8 needs backward computation. +I0410 13:30:24.984220 18606 net.cpp:198] drop7.6 needs backward computation. +I0410 13:30:24.984225 18606 net.cpp:198] relu7.6 needs backward computation. +I0410 13:30:24.984227 18606 net.cpp:198] fc7.6 needs backward computation. +I0410 13:30:24.984231 18606 net.cpp:198] drop7.5 needs backward computation. +I0410 13:30:24.984234 18606 net.cpp:198] relu7.5 needs backward computation. +I0410 13:30:24.984237 18606 net.cpp:198] fc7.5 needs backward computation. +I0410 13:30:24.984241 18606 net.cpp:198] drop7 needs backward computation. +I0410 13:30:24.984246 18606 net.cpp:198] relu7 needs backward computation. +I0410 13:30:24.984249 18606 net.cpp:198] fc7 needs backward computation. +I0410 13:30:24.984252 18606 net.cpp:198] drop6 needs backward computation. +I0410 13:30:24.984256 18606 net.cpp:198] relu6 needs backward computation. +I0410 13:30:24.984261 18606 net.cpp:198] fc6 needs backward computation. +I0410 13:30:24.984264 18606 net.cpp:198] pool5 needs backward computation. +I0410 13:30:24.984268 18606 net.cpp:198] relu5 needs backward computation. +I0410 13:30:24.984272 18606 net.cpp:198] conv5 needs backward computation. +I0410 13:30:24.984277 18606 net.cpp:198] relu4 needs backward computation. +I0410 13:30:24.984280 18606 net.cpp:198] conv4 needs backward computation. +I0410 13:30:24.984285 18606 net.cpp:198] relu3 needs backward computation. +I0410 13:30:24.984289 18606 net.cpp:198] conv3 needs backward computation. +I0410 13:30:24.984293 18606 net.cpp:198] pool2 needs backward computation. +I0410 13:30:24.984297 18606 net.cpp:198] norm2 needs backward computation. +I0410 13:30:24.984302 18606 net.cpp:198] relu2 needs backward computation. +I0410 13:30:24.984305 18606 net.cpp:198] conv2 needs backward computation. +I0410 13:30:24.984309 18606 net.cpp:198] pool1 needs backward computation. +I0410 13:30:24.984313 18606 net.cpp:198] norm1 needs backward computation. +I0410 13:30:24.984318 18606 net.cpp:198] relu1 needs backward computation. +I0410 13:30:24.984321 18606 net.cpp:198] conv1 needs backward computation. +I0410 13:30:24.984325 18606 net.cpp:200] train-data does not need backward computation. +I0410 13:30:24.984328 18606 net.cpp:242] This network produces output loss +I0410 13:30:24.984346 18606 net.cpp:255] Network initialization done. +I0410 13:30:24.984916 18606 solver.cpp:172] Creating test net (#0) specified by net file: train_val.prototxt +I0410 13:30:24.984951 18606 net.cpp:294] The NetState phase (1) differed from the phase (0) specified by a rule in layer train-data +I0410 13:30:24.985126 18606 net.cpp:51] Initializing net from parameters: +state { +phase: TEST +} +layer { +name: "val-data" +type: "Data" +top: "data" +top: "label" +include { +phase: TEST +} +transform_param { +crop_size: 227 +mean_file: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto" +} +data_param { +source: "/mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db" +batch_size: 32 +backend: LMDB +} +} +layer { +name: "conv1" +type: "Convolution" +bottom: "data" +top: "conv1" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 96 +kernel_size: 11 +stride: 4 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu1" +type: "ReLU" +bottom: "conv1" +top: "conv1" +} +layer { +name: "norm1" +type: "LRN" +bottom: "conv1" +top: "norm1" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool1" +type: "Pooling" +bottom: "norm1" +top: "pool1" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv2" +type: "Convolution" +bottom: "pool1" +top: "conv2" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 2 +kernel_size: 5 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu2" +type: "ReLU" +bottom: "conv2" +top: "conv2" +} +layer { +name: "norm2" +type: "LRN" +bottom: "conv2" +top: "norm2" +lrn_param { +local_size: 5 +alpha: 0.0001 +beta: 0.75 +} +} +layer { +name: "pool2" +type: "Pooling" +bottom: "norm2" +top: "pool2" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "conv3" +type: "Convolution" +bottom: "pool2" +top: "conv3" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "relu3" +type: "ReLU" +bottom: "conv3" +top: "conv3" +} +layer { +name: "conv4" +type: "Convolution" +bottom: "conv3" +top: "conv4" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 384 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu4" +type: "ReLU" +bottom: "conv4" +top: "conv4" +} +layer { +name: "conv5" +type: "Convolution" +bottom: "conv4" +top: "conv5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +convolution_param { +num_output: 256 +pad: 1 +kernel_size: 3 +group: 2 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu5" +type: "ReLU" +bottom: "conv5" +top: "conv5" +} +layer { +name: "pool5" +type: "Pooling" +bottom: "conv5" +top: "pool5" +pooling_param { +pool: MAX +kernel_size: 3 +stride: 2 +} +} +layer { +name: "fc6" +type: "InnerProduct" +bottom: "pool5" +top: "fc6" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu6" +type: "ReLU" +bottom: "fc6" +top: "fc6" +} +layer { +name: "drop6" +type: "Dropout" +bottom: "fc6" +top: "fc6" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7" +type: "InnerProduct" +bottom: "fc6" +top: "fc7" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7" +type: "ReLU" +bottom: "fc7" +top: "fc7" +} +layer { +name: "drop7" +type: "Dropout" +bottom: "fc7" +top: "fc7" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7.5" +type: "InnerProduct" +bottom: "fc7" +top: "fc7.5" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7.5" +type: "ReLU" +bottom: "fc7.5" +top: "fc7.5" +} +layer { +name: "drop7.5" +type: "Dropout" +bottom: "fc7.5" +top: "fc7.5" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc7.6" +type: "InnerProduct" +bottom: "fc7.5" +top: "fc7.6" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 256 +weight_filler { +type: "gaussian" +std: 0.005 +} +bias_filler { +type: "constant" +value: 0.1 +} +} +} +layer { +name: "relu7.6" +type: "ReLU" +bottom: "fc7.6" +top: "fc7.6" +} +layer { +name: "drop7.6" +type: "Dropout" +bottom: "fc7.6" +top: "fc7.6" +dropout_param { +dropout_ratio: 0.5 +} +} +layer { +name: "fc8" +type: "InnerProduct" +bottom: "fc7.6" +top: "fc8" +param { +lr_mult: 1 +decay_mult: 1 +} +param { +lr_mult: 2 +decay_mult: 0 +} +inner_product_param { +num_output: 196 +weight_filler { +type: "gaussian" +std: 0.01 +} +bias_filler { +type: "constant" +value: 0 +} +} +} +layer { +name: "accuracy" +type: "Accuracy" +bottom: "fc8" +bottom: "label" +top: "accuracy" +include { +phase: TEST +} +} +layer { +name: "loss" +type: "SoftmaxWithLoss" +bottom: "fc8" +bottom: "label" +top: "loss" +} +I0410 13:30:24.985237 18606 layer_factory.hpp:77] Creating layer val-data +I0410 13:30:24.986884 18606 db_lmdb.cpp:35] Opened lmdb /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/val_db +I0410 13:30:24.987090 18606 net.cpp:84] Creating Layer val-data +I0410 13:30:24.987099 18606 net.cpp:380] val-data -> data +I0410 13:30:24.987109 18606 net.cpp:380] val-data -> label +I0410 13:30:24.987116 18606 data_transformer.cpp:25] Loading mean file from: /mnt/bigdisk/DIGITS-MAN-2/digits/jobs/20210407-214532-d396/mean.binaryproto +I0410 13:30:24.991339 18606 data_layer.cpp:45] output data size: 32,3,227,227 +I0410 13:30:25.024708 18606 net.cpp:122] Setting up val-data +I0410 13:30:25.024727 18606 net.cpp:129] Top shape: 32 3 227 227 (4946784) +I0410 13:30:25.024732 18606 net.cpp:129] Top shape: 32 (32) +I0410 13:30:25.024735 18606 net.cpp:137] Memory required for data: 19787264 +I0410 13:30:25.024741 18606 layer_factory.hpp:77] Creating layer label_val-data_1_split +I0410 13:30:25.024753 18606 net.cpp:84] Creating Layer label_val-data_1_split +I0410 13:30:25.024758 18606 net.cpp:406] label_val-data_1_split <- label +I0410 13:30:25.024765 18606 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_0 +I0410 13:30:25.024775 18606 net.cpp:380] label_val-data_1_split -> label_val-data_1_split_1 +I0410 13:30:25.024829 18606 net.cpp:122] Setting up label_val-data_1_split +I0410 13:30:25.024835 18606 net.cpp:129] Top shape: 32 (32) +I0410 13:30:25.024839 18606 net.cpp:129] Top shape: 32 (32) +I0410 13:30:25.024842 18606 net.cpp:137] Memory required for data: 19787520 +I0410 13:30:25.024847 18606 layer_factory.hpp:77] Creating layer conv1 +I0410 13:30:25.024857 18606 net.cpp:84] Creating Layer conv1 +I0410 13:30:25.024861 18606 net.cpp:406] conv1 <- data +I0410 13:30:25.024868 18606 net.cpp:380] conv1 -> conv1 +I0410 13:30:25.028849 18606 net.cpp:122] Setting up conv1 +I0410 13:30:25.028861 18606 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:30:25.028863 18606 net.cpp:137] Memory required for data: 56958720 +I0410 13:30:25.028874 18606 layer_factory.hpp:77] Creating layer relu1 +I0410 13:30:25.028882 18606 net.cpp:84] Creating Layer relu1 +I0410 13:30:25.028887 18606 net.cpp:406] relu1 <- conv1 +I0410 13:30:25.028892 18606 net.cpp:367] relu1 -> conv1 (in-place) +I0410 13:30:25.033108 18606 net.cpp:122] Setting up relu1 +I0410 13:30:25.033121 18606 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:30:25.033125 18606 net.cpp:137] Memory required for data: 94129920 +I0410 13:30:25.033129 18606 layer_factory.hpp:77] Creating layer norm1 +I0410 13:30:25.033138 18606 net.cpp:84] Creating Layer norm1 +I0410 13:30:25.033143 18606 net.cpp:406] norm1 <- conv1 +I0410 13:30:25.033149 18606 net.cpp:380] norm1 -> norm1 +I0410 13:30:25.033640 18606 net.cpp:122] Setting up norm1 +I0410 13:30:25.033650 18606 net.cpp:129] Top shape: 32 96 55 55 (9292800) +I0410 13:30:25.033654 18606 net.cpp:137] Memory required for data: 131301120 +I0410 13:30:25.033658 18606 layer_factory.hpp:77] Creating layer pool1 +I0410 13:30:25.033665 18606 net.cpp:84] Creating Layer pool1 +I0410 13:30:25.033669 18606 net.cpp:406] pool1 <- norm1 +I0410 13:30:25.033674 18606 net.cpp:380] pool1 -> pool1 +I0410 13:30:25.033705 18606 net.cpp:122] Setting up pool1 +I0410 13:30:25.033711 18606 net.cpp:129] Top shape: 32 96 27 27 (2239488) +I0410 13:30:25.033715 18606 net.cpp:137] Memory required for data: 140259072 +I0410 13:30:25.033717 18606 layer_factory.hpp:77] Creating layer conv2 +I0410 13:30:25.033726 18606 net.cpp:84] Creating Layer conv2 +I0410 13:30:25.033730 18606 net.cpp:406] conv2 <- pool1 +I0410 13:30:25.033735 18606 net.cpp:380] conv2 -> conv2 +I0410 13:30:25.040444 18606 net.cpp:122] Setting up conv2 +I0410 13:30:25.040459 18606 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:30:25.040463 18606 net.cpp:137] Memory required for data: 164146944 +I0410 13:30:25.040474 18606 layer_factory.hpp:77] Creating layer relu2 +I0410 13:30:25.040482 18606 net.cpp:84] Creating Layer relu2 +I0410 13:30:25.040485 18606 net.cpp:406] relu2 <- conv2 +I0410 13:30:25.040493 18606 net.cpp:367] relu2 -> conv2 (in-place) +I0410 13:30:25.040866 18606 net.cpp:122] Setting up relu2 +I0410 13:30:25.040875 18606 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:30:25.040879 18606 net.cpp:137] Memory required for data: 188034816 +I0410 13:30:25.040882 18606 layer_factory.hpp:77] Creating layer norm2 +I0410 13:30:25.040892 18606 net.cpp:84] Creating Layer norm2 +I0410 13:30:25.040896 18606 net.cpp:406] norm2 <- conv2 +I0410 13:30:25.040901 18606 net.cpp:380] norm2 -> norm2 +I0410 13:30:25.041487 18606 net.cpp:122] Setting up norm2 +I0410 13:30:25.041497 18606 net.cpp:129] Top shape: 32 256 27 27 (5971968) +I0410 13:30:25.041501 18606 net.cpp:137] Memory required for data: 211922688 +I0410 13:30:25.041505 18606 layer_factory.hpp:77] Creating layer pool2 +I0410 13:30:25.041513 18606 net.cpp:84] Creating Layer pool2 +I0410 13:30:25.041517 18606 net.cpp:406] pool2 <- norm2 +I0410 13:30:25.041523 18606 net.cpp:380] pool2 -> pool2 +I0410 13:30:25.041555 18606 net.cpp:122] Setting up pool2 +I0410 13:30:25.041560 18606 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:30:25.041563 18606 net.cpp:137] Memory required for data: 217460480 +I0410 13:30:25.041568 18606 layer_factory.hpp:77] Creating layer conv3 +I0410 13:30:25.041576 18606 net.cpp:84] Creating Layer conv3 +I0410 13:30:25.041580 18606 net.cpp:406] conv3 <- pool2 +I0410 13:30:25.041586 18606 net.cpp:380] conv3 -> conv3 +I0410 13:30:25.054193 18606 net.cpp:122] Setting up conv3 +I0410 13:30:25.054211 18606 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:30:25.054215 18606 net.cpp:137] Memory required for data: 225767168 +I0410 13:30:25.054227 18606 layer_factory.hpp:77] Creating layer relu3 +I0410 13:30:25.054239 18606 net.cpp:84] Creating Layer relu3 +I0410 13:30:25.054242 18606 net.cpp:406] relu3 <- conv3 +I0410 13:30:25.054250 18606 net.cpp:367] relu3 -> conv3 (in-place) +I0410 13:30:25.054797 18606 net.cpp:122] Setting up relu3 +I0410 13:30:25.054807 18606 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:30:25.054811 18606 net.cpp:137] Memory required for data: 234073856 +I0410 13:30:25.054816 18606 layer_factory.hpp:77] Creating layer conv4 +I0410 13:30:25.054826 18606 net.cpp:84] Creating Layer conv4 +I0410 13:30:25.054831 18606 net.cpp:406] conv4 <- conv3 +I0410 13:30:25.054857 18606 net.cpp:380] conv4 -> conv4 +I0410 13:30:25.065182 18606 net.cpp:122] Setting up conv4 +I0410 13:30:25.065201 18606 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:30:25.065204 18606 net.cpp:137] Memory required for data: 242380544 +I0410 13:30:25.065213 18606 layer_factory.hpp:77] Creating layer relu4 +I0410 13:30:25.065224 18606 net.cpp:84] Creating Layer relu4 +I0410 13:30:25.065228 18606 net.cpp:406] relu4 <- conv4 +I0410 13:30:25.065237 18606 net.cpp:367] relu4 -> conv4 (in-place) +I0410 13:30:25.069399 18606 net.cpp:122] Setting up relu4 +I0410 13:30:25.069412 18606 net.cpp:129] Top shape: 32 384 13 13 (2076672) +I0410 13:30:25.069416 18606 net.cpp:137] Memory required for data: 250687232 +I0410 13:30:25.069420 18606 layer_factory.hpp:77] Creating layer conv5 +I0410 13:30:25.069434 18606 net.cpp:84] Creating Layer conv5 +I0410 13:30:25.069438 18606 net.cpp:406] conv5 <- conv4 +I0410 13:30:25.069444 18606 net.cpp:380] conv5 -> conv5 +I0410 13:30:25.083218 18606 net.cpp:122] Setting up conv5 +I0410 13:30:25.083237 18606 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:30:25.083241 18606 net.cpp:137] Memory required for data: 256225024 +I0410 13:30:25.083253 18606 layer_factory.hpp:77] Creating layer relu5 +I0410 13:30:25.083263 18606 net.cpp:84] Creating Layer relu5 +I0410 13:30:25.083267 18606 net.cpp:406] relu5 <- conv5 +I0410 13:30:25.083276 18606 net.cpp:367] relu5 -> conv5 (in-place) +I0410 13:30:25.083660 18606 net.cpp:122] Setting up relu5 +I0410 13:30:25.083669 18606 net.cpp:129] Top shape: 32 256 13 13 (1384448) +I0410 13:30:25.083673 18606 net.cpp:137] Memory required for data: 261762816 +I0410 13:30:25.083676 18606 layer_factory.hpp:77] Creating layer pool5 +I0410 13:30:25.083688 18606 net.cpp:84] Creating Layer pool5 +I0410 13:30:25.083691 18606 net.cpp:406] pool5 <- conv5 +I0410 13:30:25.083698 18606 net.cpp:380] pool5 -> pool5 +I0410 13:30:25.083737 18606 net.cpp:122] Setting up pool5 +I0410 13:30:25.083743 18606 net.cpp:129] Top shape: 32 256 6 6 (294912) +I0410 13:30:25.083746 18606 net.cpp:137] Memory required for data: 262942464 +I0410 13:30:25.083750 18606 layer_factory.hpp:77] Creating layer fc6 +I0410 13:30:25.083757 18606 net.cpp:84] Creating Layer fc6 +I0410 13:30:25.083760 18606 net.cpp:406] fc6 <- pool5 +I0410 13:30:25.083767 18606 net.cpp:380] fc6 -> fc6 +I0410 13:30:25.110872 18606 net.cpp:122] Setting up fc6 +I0410 13:30:25.110894 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.110898 18606 net.cpp:137] Memory required for data: 262975232 +I0410 13:30:25.110908 18606 layer_factory.hpp:77] Creating layer relu6 +I0410 13:30:25.110919 18606 net.cpp:84] Creating Layer relu6 +I0410 13:30:25.110924 18606 net.cpp:406] relu6 <- fc6 +I0410 13:30:25.110930 18606 net.cpp:367] relu6 -> fc6 (in-place) +I0410 13:30:25.111964 18606 net.cpp:122] Setting up relu6 +I0410 13:30:25.111974 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.111977 18606 net.cpp:137] Memory required for data: 263008000 +I0410 13:30:25.111981 18606 layer_factory.hpp:77] Creating layer drop6 +I0410 13:30:25.111989 18606 net.cpp:84] Creating Layer drop6 +I0410 13:30:25.111992 18606 net.cpp:406] drop6 <- fc6 +I0410 13:30:25.111999 18606 net.cpp:367] drop6 -> fc6 (in-place) +I0410 13:30:25.112025 18606 net.cpp:122] Setting up drop6 +I0410 13:30:25.112030 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.112032 18606 net.cpp:137] Memory required for data: 263040768 +I0410 13:30:25.112035 18606 layer_factory.hpp:77] Creating layer fc7 +I0410 13:30:25.112044 18606 net.cpp:84] Creating Layer fc7 +I0410 13:30:25.112048 18606 net.cpp:406] fc7 <- fc6 +I0410 13:30:25.112054 18606 net.cpp:380] fc7 -> fc7 +I0410 13:30:25.112751 18606 net.cpp:122] Setting up fc7 +I0410 13:30:25.112758 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.112761 18606 net.cpp:137] Memory required for data: 263073536 +I0410 13:30:25.112767 18606 layer_factory.hpp:77] Creating layer relu7 +I0410 13:30:25.112776 18606 net.cpp:84] Creating Layer relu7 +I0410 13:30:25.112780 18606 net.cpp:406] relu7 <- fc7 +I0410 13:30:25.112784 18606 net.cpp:367] relu7 -> fc7 (in-place) +I0410 13:30:25.113333 18606 net.cpp:122] Setting up relu7 +I0410 13:30:25.113343 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.113345 18606 net.cpp:137] Memory required for data: 263106304 +I0410 13:30:25.113349 18606 layer_factory.hpp:77] Creating layer drop7 +I0410 13:30:25.113355 18606 net.cpp:84] Creating Layer drop7 +I0410 13:30:25.113359 18606 net.cpp:406] drop7 <- fc7 +I0410 13:30:25.113365 18606 net.cpp:367] drop7 -> fc7 (in-place) +I0410 13:30:25.113390 18606 net.cpp:122] Setting up drop7 +I0410 13:30:25.113395 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.113399 18606 net.cpp:137] Memory required for data: 263139072 +I0410 13:30:25.113401 18606 layer_factory.hpp:77] Creating layer fc7.5 +I0410 13:30:25.113410 18606 net.cpp:84] Creating Layer fc7.5 +I0410 13:30:25.113415 18606 net.cpp:406] fc7.5 <- fc7 +I0410 13:30:25.113421 18606 net.cpp:380] fc7.5 -> fc7.5 +I0410 13:30:25.114135 18606 net.cpp:122] Setting up fc7.5 +I0410 13:30:25.114143 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.114146 18606 net.cpp:137] Memory required for data: 263171840 +I0410 13:30:25.114152 18606 layer_factory.hpp:77] Creating layer relu7.5 +I0410 13:30:25.114158 18606 net.cpp:84] Creating Layer relu7.5 +I0410 13:30:25.114161 18606 net.cpp:406] relu7.5 <- fc7.5 +I0410 13:30:25.114166 18606 net.cpp:367] relu7.5 -> fc7.5 (in-place) +I0410 13:30:25.115809 18606 net.cpp:122] Setting up relu7.5 +I0410 13:30:25.115819 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.115823 18606 net.cpp:137] Memory required for data: 263204608 +I0410 13:30:25.115828 18606 layer_factory.hpp:77] Creating layer drop7.5 +I0410 13:30:25.115833 18606 net.cpp:84] Creating Layer drop7.5 +I0410 13:30:25.115837 18606 net.cpp:406] drop7.5 <- fc7.5 +I0410 13:30:25.115844 18606 net.cpp:367] drop7.5 -> fc7.5 (in-place) +I0410 13:30:25.115869 18606 net.cpp:122] Setting up drop7.5 +I0410 13:30:25.115875 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.115877 18606 net.cpp:137] Memory required for data: 263237376 +I0410 13:30:25.115880 18606 layer_factory.hpp:77] Creating layer fc7.6 +I0410 13:30:25.115888 18606 net.cpp:84] Creating Layer fc7.6 +I0410 13:30:25.115891 18606 net.cpp:406] fc7.6 <- fc7.5 +I0410 13:30:25.115897 18606 net.cpp:380] fc7.6 -> fc7.6 +I0410 13:30:25.116597 18606 net.cpp:122] Setting up fc7.6 +I0410 13:30:25.116603 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.116607 18606 net.cpp:137] Memory required for data: 263270144 +I0410 13:30:25.116618 18606 layer_factory.hpp:77] Creating layer relu7.6 +I0410 13:30:25.116623 18606 net.cpp:84] Creating Layer relu7.6 +I0410 13:30:25.116627 18606 net.cpp:406] relu7.6 <- fc7.6 +I0410 13:30:25.116631 18606 net.cpp:367] relu7.6 -> fc7.6 (in-place) +I0410 13:30:25.116999 18606 net.cpp:122] Setting up relu7.6 +I0410 13:30:25.117007 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.117012 18606 net.cpp:137] Memory required for data: 263302912 +I0410 13:30:25.117014 18606 layer_factory.hpp:77] Creating layer drop7.6 +I0410 13:30:25.117022 18606 net.cpp:84] Creating Layer drop7.6 +I0410 13:30:25.117025 18606 net.cpp:406] drop7.6 <- fc7.6 +I0410 13:30:25.117030 18606 net.cpp:367] drop7.6 -> fc7.6 (in-place) +I0410 13:30:25.117054 18606 net.cpp:122] Setting up drop7.6 +I0410 13:30:25.117059 18606 net.cpp:129] Top shape: 32 256 (8192) +I0410 13:30:25.117063 18606 net.cpp:137] Memory required for data: 263335680 +I0410 13:30:25.117065 18606 layer_factory.hpp:77] Creating layer fc8 +I0410 13:30:25.117071 18606 net.cpp:84] Creating Layer fc8 +I0410 13:30:25.117074 18606 net.cpp:406] fc8 <- fc7.6 +I0410 13:30:25.117081 18606 net.cpp:380] fc8 -> fc8 +I0410 13:30:25.117643 18606 net.cpp:122] Setting up fc8 +I0410 13:30:25.117650 18606 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:30:25.117652 18606 net.cpp:137] Memory required for data: 263360768 +I0410 13:30:25.117658 18606 layer_factory.hpp:77] Creating layer fc8_fc8_0_split +I0410 13:30:25.117664 18606 net.cpp:84] Creating Layer fc8_fc8_0_split +I0410 13:30:25.117667 18606 net.cpp:406] fc8_fc8_0_split <- fc8 +I0410 13:30:25.117673 18606 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_0 +I0410 13:30:25.117695 18606 net.cpp:380] fc8_fc8_0_split -> fc8_fc8_0_split_1 +I0410 13:30:25.117727 18606 net.cpp:122] Setting up fc8_fc8_0_split +I0410 13:30:25.117733 18606 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:30:25.117736 18606 net.cpp:129] Top shape: 32 196 (6272) +I0410 13:30:25.117740 18606 net.cpp:137] Memory required for data: 263410944 +I0410 13:30:25.117743 18606 layer_factory.hpp:77] Creating layer accuracy +I0410 13:30:25.117750 18606 net.cpp:84] Creating Layer accuracy +I0410 13:30:25.117754 18606 net.cpp:406] accuracy <- fc8_fc8_0_split_0 +I0410 13:30:25.117758 18606 net.cpp:406] accuracy <- label_val-data_1_split_0 +I0410 13:30:25.117763 18606 net.cpp:380] accuracy -> accuracy +I0410 13:30:25.117770 18606 net.cpp:122] Setting up accuracy +I0410 13:30:25.117774 18606 net.cpp:129] Top shape: (1) +I0410 13:30:25.117777 18606 net.cpp:137] Memory required for data: 263410948 +I0410 13:30:25.117781 18606 layer_factory.hpp:77] Creating layer loss +I0410 13:30:25.117791 18606 net.cpp:84] Creating Layer loss +I0410 13:30:25.117795 18606 net.cpp:406] loss <- fc8_fc8_0_split_1 +I0410 13:30:25.117799 18606 net.cpp:406] loss <- label_val-data_1_split_1 +I0410 13:30:25.117805 18606 net.cpp:380] loss -> loss +I0410 13:30:25.117811 18606 layer_factory.hpp:77] Creating layer loss +I0410 13:30:25.118439 18606 net.cpp:122] Setting up loss +I0410 13:30:25.118449 18606 net.cpp:129] Top shape: (1) +I0410 13:30:25.118453 18606 net.cpp:132] with loss weight 1 +I0410 13:30:25.118463 18606 net.cpp:137] Memory required for data: 263410952 +I0410 13:30:25.118467 18606 net.cpp:198] loss needs backward computation. +I0410 13:30:25.118472 18606 net.cpp:200] accuracy does not need backward computation. +I0410 13:30:25.118476 18606 net.cpp:198] fc8_fc8_0_split needs backward computation. +I0410 13:30:25.118479 18606 net.cpp:198] fc8 needs backward computation. +I0410 13:30:25.118484 18606 net.cpp:198] drop7.6 needs backward computation. +I0410 13:30:25.118486 18606 net.cpp:198] relu7.6 needs backward computation. +I0410 13:30:25.118489 18606 net.cpp:198] fc7.6 needs backward computation. +I0410 13:30:25.118494 18606 net.cpp:198] drop7.5 needs backward computation. +I0410 13:30:25.118496 18606 net.cpp:198] relu7.5 needs backward computation. +I0410 13:30:25.118499 18606 net.cpp:198] fc7.5 needs backward computation. +I0410 13:30:25.118503 18606 net.cpp:198] drop7 needs backward computation. +I0410 13:30:25.118506 18606 net.cpp:198] relu7 needs backward computation. +I0410 13:30:25.118510 18606 net.cpp:198] fc7 needs backward computation. +I0410 13:30:25.118513 18606 net.cpp:198] drop6 needs backward computation. +I0410 13:30:25.118516 18606 net.cpp:198] relu6 needs backward computation. +I0410 13:30:25.118520 18606 net.cpp:198] fc6 needs backward computation. +I0410 13:30:25.118522 18606 net.cpp:198] pool5 needs backward computation. +I0410 13:30:25.118526 18606 net.cpp:198] relu5 needs backward computation. +I0410 13:30:25.118530 18606 net.cpp:198] conv5 needs backward computation. +I0410 13:30:25.118533 18606 net.cpp:198] relu4 needs backward computation. +I0410 13:30:25.118536 18606 net.cpp:198] conv4 needs backward computation. +I0410 13:30:25.118541 18606 net.cpp:198] relu3 needs backward computation. +I0410 13:30:25.118543 18606 net.cpp:198] conv3 needs backward computation. +I0410 13:30:25.118547 18606 net.cpp:198] pool2 needs backward computation. +I0410 13:30:25.118551 18606 net.cpp:198] norm2 needs backward computation. +I0410 13:30:25.118554 18606 net.cpp:198] relu2 needs backward computation. +I0410 13:30:25.118559 18606 net.cpp:198] conv2 needs backward computation. +I0410 13:30:25.118563 18606 net.cpp:198] pool1 needs backward computation. +I0410 13:30:25.118566 18606 net.cpp:198] norm1 needs backward computation. +I0410 13:30:25.118571 18606 net.cpp:198] relu1 needs backward computation. +I0410 13:30:25.118573 18606 net.cpp:198] conv1 needs backward computation. +I0410 13:30:25.118577 18606 net.cpp:200] label_val-data_1_split does not need backward computation. +I0410 13:30:25.118582 18606 net.cpp:200] val-data does not need backward computation. +I0410 13:30:25.118594 18606 net.cpp:242] This network produces output accuracy +I0410 13:30:25.118599 18606 net.cpp:242] This network produces output loss +I0410 13:30:25.118620 18606 net.cpp:255] Network initialization done. +I0410 13:30:25.118702 18606 solver.cpp:56] Solver scaffolding done. +I0410 13:30:25.119271 18606 caffe.cpp:248] Starting Optimization +I0410 13:30:25.119282 18606 solver.cpp:272] Solving +I0410 13:30:25.119284 18606 solver.cpp:273] Learning Rate Policy: exp +I0410 13:30:25.120290 18606 solver.cpp:330] Iteration 0, Testing net (#0) +I0410 13:30:25.120301 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:30:25.122989 18606 blocking_queue.cpp:49] Waiting for data +I0410 13:30:29.729367 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:30:29.773607 18606 solver.cpp:397] Test net output #0: accuracy = 0.00735294 +I0410 13:30:29.773656 18606 solver.cpp:397] Test net output #1: loss = 5.27809 (* 1 = 5.27809 loss) +I0410 13:30:29.859964 18606 solver.cpp:218] Iteration 0 (-6.69562e-37 iter/s, 4.74045s/12 iters), loss = 5.27697 +I0410 13:30:29.860013 18606 solver.cpp:237] Train net output #0: loss = 5.27697 (* 1 = 5.27697 loss) +I0410 13:30:29.860033 18606 sgd_solver.cpp:105] Iteration 0, lr = 0.01 +I0410 13:30:33.700996 18606 solver.cpp:218] Iteration 12 (3.12434 iter/s, 3.84081s/12 iters), loss = 5.27919 +I0410 13:30:33.701058 18606 solver.cpp:237] Train net output #0: loss = 5.27919 (* 1 = 5.27919 loss) +I0410 13:30:33.701071 18606 sgd_solver.cpp:105] Iteration 12, lr = 0.00997626 +I0410 13:30:38.521875 18606 solver.cpp:218] Iteration 24 (2.48931 iter/s, 4.82061s/12 iters), loss = 5.27749 +I0410 13:30:38.521942 18606 solver.cpp:237] Train net output #0: loss = 5.27749 (* 1 = 5.27749 loss) +I0410 13:30:38.521976 18606 sgd_solver.cpp:105] Iteration 24, lr = 0.00995257 +I0410 13:30:43.297777 18606 solver.cpp:218] Iteration 36 (2.51276 iter/s, 4.77563s/12 iters), loss = 5.27866 +I0410 13:30:43.297834 18606 solver.cpp:237] Train net output #0: loss = 5.27866 (* 1 = 5.27866 loss) +I0410 13:30:43.297847 18606 sgd_solver.cpp:105] Iteration 36, lr = 0.00992894 +I0410 13:30:48.232411 18606 solver.cpp:218] Iteration 48 (2.43192 iter/s, 4.93437s/12 iters), loss = 5.27938 +I0410 13:30:48.232457 18606 solver.cpp:237] Train net output #0: loss = 5.27938 (* 1 = 5.27938 loss) +I0410 13:30:48.232468 18606 sgd_solver.cpp:105] Iteration 48, lr = 0.00990537 +I0410 13:30:53.063068 18606 solver.cpp:218] Iteration 60 (2.48427 iter/s, 4.8304s/12 iters), loss = 5.27438 +I0410 13:30:53.063128 18606 solver.cpp:237] Train net output #0: loss = 5.27438 (* 1 = 5.27438 loss) +I0410 13:30:53.063141 18606 sgd_solver.cpp:105] Iteration 60, lr = 0.00988185 +I0410 13:30:57.835345 18606 solver.cpp:218] Iteration 72 (2.51466 iter/s, 4.77201s/12 iters), loss = 5.27799 +I0410 13:30:57.835471 18606 solver.cpp:237] Train net output #0: loss = 5.27799 (* 1 = 5.27799 loss) +I0410 13:30:57.835484 18606 sgd_solver.cpp:105] Iteration 72, lr = 0.00985839 +I0410 13:31:02.605298 18606 solver.cpp:218] Iteration 84 (2.51592 iter/s, 4.76962s/12 iters), loss = 5.27982 +I0410 13:31:02.605356 18606 solver.cpp:237] Train net output #0: loss = 5.27982 (* 1 = 5.27982 loss) +I0410 13:31:02.605367 18606 sgd_solver.cpp:105] Iteration 84, lr = 0.00983498 +I0410 13:31:07.385391 18606 solver.cpp:218] Iteration 96 (2.51055 iter/s, 4.77982s/12 iters), loss = 5.28648 +I0410 13:31:07.385452 18606 solver.cpp:237] Train net output #0: loss = 5.28648 (* 1 = 5.28648 loss) +I0410 13:31:07.385462 18606 sgd_solver.cpp:105] Iteration 96, lr = 0.00981163 +I0410 13:31:09.029522 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:09.334677 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_102.caffemodel +I0410 13:31:09.647948 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_102.solverstate +I0410 13:31:09.847574 18606 solver.cpp:330] Iteration 102, Testing net (#0) +I0410 13:31:09.847597 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:31:14.315831 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:14.392798 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:31:14.392848 18606 solver.cpp:397] Test net output #1: loss = 5.27873 (* 1 = 5.27873 loss) +I0410 13:31:16.106721 18606 solver.cpp:218] Iteration 108 (1.376 iter/s, 8.7209s/12 iters), loss = 5.27826 +I0410 13:31:16.106767 18606 solver.cpp:237] Train net output #0: loss = 5.27826 (* 1 = 5.27826 loss) +I0410 13:31:16.106777 18606 sgd_solver.cpp:105] Iteration 108, lr = 0.00978834 +I0410 13:31:20.905746 18606 solver.cpp:218] Iteration 120 (2.50064 iter/s, 4.79877s/12 iters), loss = 5.2789 +I0410 13:31:20.905799 18606 solver.cpp:237] Train net output #0: loss = 5.2789 (* 1 = 5.2789 loss) +I0410 13:31:20.905812 18606 sgd_solver.cpp:105] Iteration 120, lr = 0.0097651 +I0410 13:31:25.677898 18606 solver.cpp:218] Iteration 132 (2.51473 iter/s, 4.77189s/12 iters), loss = 5.25895 +I0410 13:31:25.677947 18606 solver.cpp:237] Train net output #0: loss = 5.25895 (* 1 = 5.25895 loss) +I0410 13:31:25.677971 18606 sgd_solver.cpp:105] Iteration 132, lr = 0.00974192 +I0410 13:31:30.505519 18606 solver.cpp:218] Iteration 144 (2.48583 iter/s, 4.82736s/12 iters), loss = 5.28369 +I0410 13:31:30.505667 18606 solver.cpp:237] Train net output #0: loss = 5.28369 (* 1 = 5.28369 loss) +I0410 13:31:30.505681 18606 sgd_solver.cpp:105] Iteration 144, lr = 0.00971879 +I0410 13:31:35.334419 18606 solver.cpp:218] Iteration 156 (2.48522 iter/s, 4.82854s/12 iters), loss = 5.26772 +I0410 13:31:35.334468 18606 solver.cpp:237] Train net output #0: loss = 5.26772 (* 1 = 5.26772 loss) +I0410 13:31:35.334479 18606 sgd_solver.cpp:105] Iteration 156, lr = 0.00969571 +I0410 13:31:40.164674 18606 solver.cpp:218] Iteration 168 (2.48448 iter/s, 4.82999s/12 iters), loss = 5.27274 +I0410 13:31:40.164726 18606 solver.cpp:237] Train net output #0: loss = 5.27274 (* 1 = 5.27274 loss) +I0410 13:31:40.164739 18606 sgd_solver.cpp:105] Iteration 168, lr = 0.00967269 +I0410 13:31:45.022190 18606 solver.cpp:218] Iteration 180 (2.47053 iter/s, 4.85725s/12 iters), loss = 5.27071 +I0410 13:31:45.022240 18606 solver.cpp:237] Train net output #0: loss = 5.27071 (* 1 = 5.27071 loss) +I0410 13:31:45.022253 18606 sgd_solver.cpp:105] Iteration 180, lr = 0.00964973 +I0410 13:31:49.827512 18606 solver.cpp:218] Iteration 192 (2.49737 iter/s, 4.80506s/12 iters), loss = 5.27732 +I0410 13:31:49.827574 18606 solver.cpp:237] Train net output #0: loss = 5.27732 (* 1 = 5.27732 loss) +I0410 13:31:49.827586 18606 sgd_solver.cpp:105] Iteration 192, lr = 0.00962682 +I0410 13:31:53.503304 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:54.158974 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_204.caffemodel +I0410 13:31:54.721592 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_204.solverstate +I0410 13:31:54.920779 18606 solver.cpp:330] Iteration 204, Testing net (#0) +I0410 13:31:54.920799 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:31:59.203292 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:31:59.325606 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:31:59.325644 18606 solver.cpp:397] Test net output #1: loss = 5.27988 (* 1 = 5.27988 loss) +I0410 13:31:59.407341 18606 solver.cpp:218] Iteration 204 (1.25269 iter/s, 9.57935s/12 iters), loss = 5.27384 +I0410 13:31:59.407384 18606 solver.cpp:237] Train net output #0: loss = 5.27384 (* 1 = 5.27384 loss) +I0410 13:31:59.407393 18606 sgd_solver.cpp:105] Iteration 204, lr = 0.00960396 +I0410 13:32:03.532560 18606 solver.cpp:218] Iteration 216 (2.9091 iter/s, 4.12499s/12 iters), loss = 5.27642 +I0410 13:32:03.532666 18606 solver.cpp:237] Train net output #0: loss = 5.27642 (* 1 = 5.27642 loss) +I0410 13:32:03.532675 18606 sgd_solver.cpp:105] Iteration 216, lr = 0.00958116 +I0410 13:32:08.314553 18606 solver.cpp:218] Iteration 228 (2.50958 iter/s, 4.78167s/12 iters), loss = 5.26395 +I0410 13:32:08.314608 18606 solver.cpp:237] Train net output #0: loss = 5.26395 (* 1 = 5.26395 loss) +I0410 13:32:08.314620 18606 sgd_solver.cpp:105] Iteration 228, lr = 0.00955841 +I0410 13:32:13.113016 18606 solver.cpp:218] Iteration 240 (2.50094 iter/s, 4.79819s/12 iters), loss = 5.28384 +I0410 13:32:13.113057 18606 solver.cpp:237] Train net output #0: loss = 5.28384 (* 1 = 5.28384 loss) +I0410 13:32:13.113067 18606 sgd_solver.cpp:105] Iteration 240, lr = 0.00953572 +I0410 13:32:17.933226 18606 solver.cpp:218] Iteration 252 (2.48965 iter/s, 4.81995s/12 iters), loss = 5.26896 +I0410 13:32:17.933270 18606 solver.cpp:237] Train net output #0: loss = 5.26896 (* 1 = 5.26896 loss) +I0410 13:32:17.933280 18606 sgd_solver.cpp:105] Iteration 252, lr = 0.00951308 +I0410 13:32:22.749768 18606 solver.cpp:218] Iteration 264 (2.49155 iter/s, 4.81628s/12 iters), loss = 5.27551 +I0410 13:32:22.749817 18606 solver.cpp:237] Train net output #0: loss = 5.27551 (* 1 = 5.27551 loss) +I0410 13:32:22.749827 18606 sgd_solver.cpp:105] Iteration 264, lr = 0.00949049 +I0410 13:32:27.555341 18606 solver.cpp:218] Iteration 276 (2.49724 iter/s, 4.80531s/12 iters), loss = 5.28554 +I0410 13:32:27.555384 18606 solver.cpp:237] Train net output #0: loss = 5.28554 (* 1 = 5.28554 loss) +I0410 13:32:27.555394 18606 sgd_solver.cpp:105] Iteration 276, lr = 0.00946796 +I0410 13:32:32.375418 18606 solver.cpp:218] Iteration 288 (2.48972 iter/s, 4.81981s/12 iters), loss = 5.27832 +I0410 13:32:32.375461 18606 solver.cpp:237] Train net output #0: loss = 5.27832 (* 1 = 5.27832 loss) +I0410 13:32:32.375470 18606 sgd_solver.cpp:105] Iteration 288, lr = 0.00944548 +I0410 13:32:37.217624 18606 solver.cpp:218] Iteration 300 (2.47834 iter/s, 4.84194s/12 iters), loss = 5.27918 +I0410 13:32:37.217736 18606 solver.cpp:237] Train net output #0: loss = 5.27918 (* 1 = 5.27918 loss) +I0410 13:32:37.217748 18606 sgd_solver.cpp:105] Iteration 300, lr = 0.00942305 +I0410 13:32:38.159901 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:39.157706 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_306.caffemodel +I0410 13:32:39.478621 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_306.solverstate +I0410 13:32:39.704670 18606 solver.cpp:330] Iteration 306, Testing net (#0) +I0410 13:32:39.704695 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:32:43.933794 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:32:44.090646 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:32:44.090690 18606 solver.cpp:397] Test net output #1: loss = 5.28102 (* 1 = 5.28102 loss) +I0410 13:32:45.902230 18606 solver.cpp:218] Iteration 312 (1.38183 iter/s, 8.68411s/12 iters), loss = 5.28083 +I0410 13:32:45.902281 18606 solver.cpp:237] Train net output #0: loss = 5.28083 (* 1 = 5.28083 loss) +I0410 13:32:45.902292 18606 sgd_solver.cpp:105] Iteration 312, lr = 0.00940068 +I0410 13:32:50.941581 18606 solver.cpp:218] Iteration 324 (2.38139 iter/s, 5.03907s/12 iters), loss = 5.25802 +I0410 13:32:50.941628 18606 solver.cpp:237] Train net output #0: loss = 5.25802 (* 1 = 5.25802 loss) +I0410 13:32:50.941638 18606 sgd_solver.cpp:105] Iteration 324, lr = 0.00937836 +I0410 13:32:55.747627 18606 solver.cpp:218] Iteration 336 (2.497 iter/s, 4.80577s/12 iters), loss = 5.26499 +I0410 13:32:55.747689 18606 solver.cpp:237] Train net output #0: loss = 5.26499 (* 1 = 5.26499 loss) +I0410 13:32:55.747702 18606 sgd_solver.cpp:105] Iteration 336, lr = 0.0093561 +I0410 13:33:00.629025 18606 solver.cpp:218] Iteration 348 (2.45845 iter/s, 4.88111s/12 iters), loss = 5.26816 +I0410 13:33:00.629078 18606 solver.cpp:237] Train net output #0: loss = 5.26816 (* 1 = 5.26816 loss) +I0410 13:33:00.629091 18606 sgd_solver.cpp:105] Iteration 348, lr = 0.00933388 +I0410 13:33:05.543591 18606 solver.cpp:218] Iteration 360 (2.44186 iter/s, 4.91428s/12 iters), loss = 5.28717 +I0410 13:33:05.543637 18606 solver.cpp:237] Train net output #0: loss = 5.28717 (* 1 = 5.28717 loss) +I0410 13:33:05.543645 18606 sgd_solver.cpp:105] Iteration 360, lr = 0.00931172 +I0410 13:33:10.360301 18606 solver.cpp:218] Iteration 372 (2.49147 iter/s, 4.81644s/12 iters), loss = 5.26809 +I0410 13:33:10.360426 18606 solver.cpp:237] Train net output #0: loss = 5.26809 (* 1 = 5.26809 loss) +I0410 13:33:10.360440 18606 sgd_solver.cpp:105] Iteration 372, lr = 0.00928961 +I0410 13:33:15.174480 18606 solver.cpp:218] Iteration 384 (2.49281 iter/s, 4.81384s/12 iters), loss = 5.27693 +I0410 13:33:15.174525 18606 solver.cpp:237] Train net output #0: loss = 5.27693 (* 1 = 5.27693 loss) +I0410 13:33:15.174537 18606 sgd_solver.cpp:105] Iteration 384, lr = 0.00926756 +I0410 13:33:19.996640 18606 solver.cpp:218] Iteration 396 (2.48865 iter/s, 4.8219s/12 iters), loss = 5.27079 +I0410 13:33:19.996685 18606 solver.cpp:237] Train net output #0: loss = 5.27079 (* 1 = 5.27079 loss) +I0410 13:33:19.996695 18606 sgd_solver.cpp:105] Iteration 396, lr = 0.00924556 +I0410 13:33:23.004659 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:33:24.366647 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_408.caffemodel +I0410 13:33:24.720675 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_408.solverstate +I0410 13:33:26.654757 18606 solver.cpp:330] Iteration 408, Testing net (#0) +I0410 13:33:26.654793 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:33:30.947834 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:33:31.156095 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:33:31.156144 18606 solver.cpp:397] Test net output #1: loss = 5.28271 (* 1 = 5.28271 loss) +I0410 13:33:31.237102 18606 solver.cpp:218] Iteration 408 (1.06762 iter/s, 11.2399s/12 iters), loss = 5.27569 +I0410 13:33:31.237157 18606 solver.cpp:237] Train net output #0: loss = 5.27569 (* 1 = 5.27569 loss) +I0410 13:33:31.237169 18606 sgd_solver.cpp:105] Iteration 408, lr = 0.00922361 +I0410 13:33:35.358408 18606 solver.cpp:218] Iteration 420 (2.91187 iter/s, 4.12106s/12 iters), loss = 5.27596 +I0410 13:33:35.358454 18606 solver.cpp:237] Train net output #0: loss = 5.27596 (* 1 = 5.27596 loss) +I0410 13:33:35.358464 18606 sgd_solver.cpp:105] Iteration 420, lr = 0.00920171 +I0410 13:33:40.189118 18606 solver.cpp:218] Iteration 432 (2.48425 iter/s, 4.83043s/12 iters), loss = 5.2703 +I0410 13:33:40.189178 18606 solver.cpp:237] Train net output #0: loss = 5.2703 (* 1 = 5.2703 loss) +I0410 13:33:40.189191 18606 sgd_solver.cpp:105] Iteration 432, lr = 0.00917986 +I0410 13:33:45.174001 18606 solver.cpp:218] Iteration 444 (2.40742 iter/s, 4.98459s/12 iters), loss = 5.28451 +I0410 13:33:45.174116 18606 solver.cpp:237] Train net output #0: loss = 5.28451 (* 1 = 5.28451 loss) +I0410 13:33:45.174129 18606 sgd_solver.cpp:105] Iteration 444, lr = 0.00915807 +I0410 13:33:49.985504 18606 solver.cpp:218] Iteration 456 (2.4942 iter/s, 4.81117s/12 iters), loss = 5.28084 +I0410 13:33:49.985543 18606 solver.cpp:237] Train net output #0: loss = 5.28084 (* 1 = 5.28084 loss) +I0410 13:33:49.985553 18606 sgd_solver.cpp:105] Iteration 456, lr = 0.00913632 +I0410 13:33:54.778981 18606 solver.cpp:218] Iteration 468 (2.50354 iter/s, 4.79322s/12 iters), loss = 5.28138 +I0410 13:33:54.779036 18606 solver.cpp:237] Train net output #0: loss = 5.28138 (* 1 = 5.28138 loss) +I0410 13:33:54.779048 18606 sgd_solver.cpp:105] Iteration 468, lr = 0.00911463 +I0410 13:33:59.801807 18606 solver.cpp:218] Iteration 480 (2.38923 iter/s, 5.02254s/12 iters), loss = 5.26828 +I0410 13:33:59.801864 18606 solver.cpp:237] Train net output #0: loss = 5.26828 (* 1 = 5.26828 loss) +I0410 13:33:59.801877 18606 sgd_solver.cpp:105] Iteration 480, lr = 0.00909299 +I0410 13:34:04.621285 18606 solver.cpp:218] Iteration 492 (2.49004 iter/s, 4.8192s/12 iters), loss = 5.28477 +I0410 13:34:04.621337 18606 solver.cpp:237] Train net output #0: loss = 5.28477 (* 1 = 5.28477 loss) +I0410 13:34:04.621349 18606 sgd_solver.cpp:105] Iteration 492, lr = 0.0090714 +I0410 13:34:09.410110 18606 solver.cpp:218] Iteration 504 (2.50598 iter/s, 4.78855s/12 iters), loss = 5.26714 +I0410 13:34:09.410169 18606 solver.cpp:237] Train net output #0: loss = 5.26714 (* 1 = 5.26714 loss) +I0410 13:34:09.410181 18606 sgd_solver.cpp:105] Iteration 504, lr = 0.00904986 +I0410 13:34:09.657531 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:11.351917 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_510.caffemodel +I0410 13:34:11.658424 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_510.solverstate +I0410 13:34:11.876214 18606 solver.cpp:330] Iteration 510, Testing net (#0) +I0410 13:34:11.876243 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:34:16.029981 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:16.271086 18606 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:34:16.271136 18606 solver.cpp:397] Test net output #1: loss = 5.28302 (* 1 = 5.28302 loss) +I0410 13:34:18.041715 18606 solver.cpp:218] Iteration 516 (1.39031 iter/s, 8.63116s/12 iters), loss = 5.27643 +I0410 13:34:18.041770 18606 solver.cpp:237] Train net output #0: loss = 5.27643 (* 1 = 5.27643 loss) +I0410 13:34:18.041782 18606 sgd_solver.cpp:105] Iteration 516, lr = 0.00902838 +I0410 13:34:22.923270 18606 solver.cpp:218] Iteration 528 (2.45837 iter/s, 4.88128s/12 iters), loss = 5.27142 +I0410 13:34:22.923319 18606 solver.cpp:237] Train net output #0: loss = 5.27142 (* 1 = 5.27142 loss) +I0410 13:34:22.923331 18606 sgd_solver.cpp:105] Iteration 528, lr = 0.00900694 +I0410 13:34:27.784938 18606 solver.cpp:218] Iteration 540 (2.46843 iter/s, 4.86139s/12 iters), loss = 5.27439 +I0410 13:34:27.784991 18606 solver.cpp:237] Train net output #0: loss = 5.27439 (* 1 = 5.27439 loss) +I0410 13:34:27.785002 18606 sgd_solver.cpp:105] Iteration 540, lr = 0.00898556 +I0410 13:34:32.582572 18606 solver.cpp:218] Iteration 552 (2.50138 iter/s, 4.79736s/12 iters), loss = 5.27134 +I0410 13:34:32.582623 18606 solver.cpp:237] Train net output #0: loss = 5.27134 (* 1 = 5.27134 loss) +I0410 13:34:32.582633 18606 sgd_solver.cpp:105] Iteration 552, lr = 0.00896423 +I0410 13:34:37.359896 18606 solver.cpp:218] Iteration 564 (2.51201 iter/s, 4.77705s/12 iters), loss = 5.25471 +I0410 13:34:37.359956 18606 solver.cpp:237] Train net output #0: loss = 5.25471 (* 1 = 5.25471 loss) +I0410 13:34:37.359969 18606 sgd_solver.cpp:105] Iteration 564, lr = 0.00894294 +I0410 13:34:42.247980 18606 solver.cpp:218] Iteration 576 (2.45509 iter/s, 4.8878s/12 iters), loss = 5.27889 +I0410 13:34:42.248026 18606 solver.cpp:237] Train net output #0: loss = 5.27889 (* 1 = 5.27889 loss) +I0410 13:34:42.248035 18606 sgd_solver.cpp:105] Iteration 576, lr = 0.00892171 +I0410 13:34:47.069393 18606 solver.cpp:218] Iteration 588 (2.48904 iter/s, 4.82114s/12 iters), loss = 5.26492 +I0410 13:34:47.069486 18606 solver.cpp:237] Train net output #0: loss = 5.26492 (* 1 = 5.26492 loss) +I0410 13:34:47.069499 18606 sgd_solver.cpp:105] Iteration 588, lr = 0.00890053 +I0410 13:34:52.068065 18606 solver.cpp:218] Iteration 600 (2.40079 iter/s, 4.99835s/12 iters), loss = 5.26396 +I0410 13:34:52.068111 18606 solver.cpp:237] Train net output #0: loss = 5.26396 (* 1 = 5.26396 loss) +I0410 13:34:52.068120 18606 sgd_solver.cpp:105] Iteration 600, lr = 0.0088794 +I0410 13:34:54.426692 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:34:56.506198 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_612.caffemodel +I0410 13:34:56.837849 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_612.solverstate +I0410 13:34:57.064486 18606 solver.cpp:330] Iteration 612, Testing net (#0) +I0410 13:34:57.064518 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:35:01.369001 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:01.659498 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:35:01.659539 18606 solver.cpp:397] Test net output #1: loss = 5.28372 (* 1 = 5.28372 loss) +I0410 13:35:01.742198 18606 solver.cpp:218] Iteration 612 (1.24048 iter/s, 9.67365s/12 iters), loss = 5.27231 +I0410 13:35:01.742246 18606 solver.cpp:237] Train net output #0: loss = 5.27231 (* 1 = 5.27231 loss) +I0410 13:35:01.742256 18606 sgd_solver.cpp:105] Iteration 612, lr = 0.00885831 +I0410 13:35:05.895210 18606 solver.cpp:218] Iteration 624 (2.88964 iter/s, 4.15276s/12 iters), loss = 5.28595 +I0410 13:35:05.895270 18606 solver.cpp:237] Train net output #0: loss = 5.28595 (* 1 = 5.28595 loss) +I0410 13:35:05.895287 18606 sgd_solver.cpp:105] Iteration 624, lr = 0.00883728 +I0410 13:35:10.739652 18606 solver.cpp:218] Iteration 636 (2.47721 iter/s, 4.84415s/12 iters), loss = 5.28347 +I0410 13:35:10.739708 18606 solver.cpp:237] Train net output #0: loss = 5.28347 (* 1 = 5.28347 loss) +I0410 13:35:10.739722 18606 sgd_solver.cpp:105] Iteration 636, lr = 0.0088163 +I0410 13:35:15.672580 18606 solver.cpp:218] Iteration 648 (2.43277 iter/s, 4.93264s/12 iters), loss = 5.27208 +I0410 13:35:15.672629 18606 solver.cpp:237] Train net output #0: loss = 5.27208 (* 1 = 5.27208 loss) +I0410 13:35:15.672641 18606 sgd_solver.cpp:105] Iteration 648, lr = 0.00879537 +I0410 13:35:20.521415 18606 solver.cpp:218] Iteration 660 (2.47496 iter/s, 4.84856s/12 iters), loss = 5.27148 +I0410 13:35:20.522852 18606 solver.cpp:237] Train net output #0: loss = 5.27148 (* 1 = 5.27148 loss) +I0410 13:35:20.522867 18606 sgd_solver.cpp:105] Iteration 660, lr = 0.00877449 +I0410 13:35:25.345736 18606 solver.cpp:218] Iteration 672 (2.48825 iter/s, 4.82266s/12 iters), loss = 5.27449 +I0410 13:35:25.345796 18606 solver.cpp:237] Train net output #0: loss = 5.27449 (* 1 = 5.27449 loss) +I0410 13:35:25.345808 18606 sgd_solver.cpp:105] Iteration 672, lr = 0.00875366 +I0410 13:35:29.327458 18606 blocking_queue.cpp:49] Waiting for data +I0410 13:35:30.183768 18606 solver.cpp:218] Iteration 684 (2.4805 iter/s, 4.83774s/12 iters), loss = 5.2756 +I0410 13:35:30.183823 18606 solver.cpp:237] Train net output #0: loss = 5.2756 (* 1 = 5.2756 loss) +I0410 13:35:30.183835 18606 sgd_solver.cpp:105] Iteration 684, lr = 0.00873287 +I0410 13:35:35.303030 18606 solver.cpp:218] Iteration 696 (2.34422 iter/s, 5.11897s/12 iters), loss = 5.26553 +I0410 13:35:35.303074 18606 solver.cpp:237] Train net output #0: loss = 5.26553 (* 1 = 5.26553 loss) +I0410 13:35:35.303083 18606 sgd_solver.cpp:105] Iteration 696, lr = 0.00871214 +I0410 13:35:39.753947 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:40.122745 18606 solver.cpp:218] Iteration 708 (2.48992 iter/s, 4.81944s/12 iters), loss = 5.25746 +I0410 13:35:40.122803 18606 solver.cpp:237] Train net output #0: loss = 5.25746 (* 1 = 5.25746 loss) +I0410 13:35:40.122815 18606 sgd_solver.cpp:105] Iteration 708, lr = 0.00869145 +I0410 13:35:42.088063 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_714.caffemodel +I0410 13:35:43.066727 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_714.solverstate +I0410 13:35:43.342692 18606 solver.cpp:330] Iteration 714, Testing net (#0) +I0410 13:35:43.342721 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:35:47.422540 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:35:47.748832 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:35:47.748883 18606 solver.cpp:397] Test net output #1: loss = 5.28506 (* 1 = 5.28506 loss) +I0410 13:35:49.538138 18606 solver.cpp:218] Iteration 720 (1.27457 iter/s, 9.41491s/12 iters), loss = 5.27692 +I0410 13:35:49.538183 18606 solver.cpp:237] Train net output #0: loss = 5.27692 (* 1 = 5.27692 loss) +I0410 13:35:49.538192 18606 sgd_solver.cpp:105] Iteration 720, lr = 0.00867082 +I0410 13:35:54.396360 18606 solver.cpp:218] Iteration 732 (2.47018 iter/s, 4.85795s/12 iters), loss = 5.28045 +I0410 13:35:54.406049 18606 solver.cpp:237] Train net output #0: loss = 5.28045 (* 1 = 5.28045 loss) +I0410 13:35:54.406060 18606 sgd_solver.cpp:105] Iteration 732, lr = 0.00865023 +I0410 13:35:59.230288 18606 solver.cpp:218] Iteration 744 (2.48755 iter/s, 4.82402s/12 iters), loss = 5.27435 +I0410 13:35:59.230340 18606 solver.cpp:237] Train net output #0: loss = 5.27435 (* 1 = 5.27435 loss) +I0410 13:35:59.230353 18606 sgd_solver.cpp:105] Iteration 744, lr = 0.0086297 +I0410 13:36:04.125831 18606 solver.cpp:218] Iteration 756 (2.45135 iter/s, 4.89526s/12 iters), loss = 5.27336 +I0410 13:36:04.125885 18606 solver.cpp:237] Train net output #0: loss = 5.27336 (* 1 = 5.27336 loss) +I0410 13:36:04.125897 18606 sgd_solver.cpp:105] Iteration 756, lr = 0.00860921 +I0410 13:36:08.981253 18606 solver.cpp:218] Iteration 768 (2.47161 iter/s, 4.85514s/12 iters), loss = 5.27874 +I0410 13:36:08.981312 18606 solver.cpp:237] Train net output #0: loss = 5.27874 (* 1 = 5.27874 loss) +I0410 13:36:08.981323 18606 sgd_solver.cpp:105] Iteration 768, lr = 0.00858877 +I0410 13:36:13.815325 18606 solver.cpp:218] Iteration 780 (2.48253 iter/s, 4.83379s/12 iters), loss = 5.2663 +I0410 13:36:13.815380 18606 solver.cpp:237] Train net output #0: loss = 5.2663 (* 1 = 5.2663 loss) +I0410 13:36:13.815392 18606 sgd_solver.cpp:105] Iteration 780, lr = 0.00856838 +I0410 13:36:18.613546 18606 solver.cpp:218] Iteration 792 (2.50108 iter/s, 4.79793s/12 iters), loss = 5.26582 +I0410 13:36:18.613600 18606 solver.cpp:237] Train net output #0: loss = 5.26582 (* 1 = 5.26582 loss) +I0410 13:36:18.613611 18606 sgd_solver.cpp:105] Iteration 792, lr = 0.00854803 +I0410 13:36:23.440753 18606 solver.cpp:218] Iteration 804 (2.48605 iter/s, 4.82693s/12 iters), loss = 5.28368 +I0410 13:36:23.440805 18606 solver.cpp:237] Train net output #0: loss = 5.28368 (* 1 = 5.28368 loss) +I0410 13:36:23.440817 18606 sgd_solver.cpp:105] Iteration 804, lr = 0.00852774 +I0410 13:36:25.111796 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:36:27.782084 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_816.caffemodel +I0410 13:36:28.092840 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_816.solverstate +I0410 13:36:28.308207 18606 solver.cpp:330] Iteration 816, Testing net (#0) +I0410 13:36:28.308239 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:36:32.441428 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:36:32.802034 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:36:32.802083 18606 solver.cpp:397] Test net output #1: loss = 5.2853 (* 1 = 5.2853 loss) +I0410 13:36:32.885155 18606 solver.cpp:218] Iteration 816 (1.27066 iter/s, 9.44392s/12 iters), loss = 5.27441 +I0410 13:36:32.885231 18606 solver.cpp:237] Train net output #0: loss = 5.27441 (* 1 = 5.27441 loss) +I0410 13:36:32.885246 18606 sgd_solver.cpp:105] Iteration 816, lr = 0.00850749 +I0410 13:36:36.958703 18606 solver.cpp:218] Iteration 828 (2.94603 iter/s, 4.07328s/12 iters), loss = 5.28004 +I0410 13:36:36.958765 18606 solver.cpp:237] Train net output #0: loss = 5.28004 (* 1 = 5.28004 loss) +I0410 13:36:36.958779 18606 sgd_solver.cpp:105] Iteration 828, lr = 0.00848729 +I0410 13:36:41.735807 18606 solver.cpp:218] Iteration 840 (2.51213 iter/s, 4.77682s/12 iters), loss = 5.22996 +I0410 13:36:41.735870 18606 solver.cpp:237] Train net output #0: loss = 5.22996 (* 1 = 5.22996 loss) +I0410 13:36:41.735882 18606 sgd_solver.cpp:105] Iteration 840, lr = 0.00846714 +I0410 13:36:46.748353 18606 solver.cpp:218] Iteration 852 (2.39414 iter/s, 5.01225s/12 iters), loss = 5.2974 +I0410 13:36:46.748410 18606 solver.cpp:237] Train net output #0: loss = 5.2974 (* 1 = 5.2974 loss) +I0410 13:36:46.748421 18606 sgd_solver.cpp:105] Iteration 852, lr = 0.00844704 +I0410 13:36:51.632467 18606 solver.cpp:218] Iteration 864 (2.45709 iter/s, 4.88383s/12 iters), loss = 5.2622 +I0410 13:36:51.632515 18606 solver.cpp:237] Train net output #0: loss = 5.2622 (* 1 = 5.2622 loss) +I0410 13:36:51.632526 18606 sgd_solver.cpp:105] Iteration 864, lr = 0.00842698 +I0410 13:36:56.472038 18606 solver.cpp:218] Iteration 876 (2.4797 iter/s, 4.8393s/12 iters), loss = 5.26941 +I0410 13:36:56.472766 18606 solver.cpp:237] Train net output #0: loss = 5.26941 (* 1 = 5.26941 loss) +I0410 13:36:56.472779 18606 sgd_solver.cpp:105] Iteration 876, lr = 0.00840698 +I0410 13:37:01.281888 18606 solver.cpp:218] Iteration 888 (2.49537 iter/s, 4.8089s/12 iters), loss = 5.26553 +I0410 13:37:01.281944 18606 solver.cpp:237] Train net output #0: loss = 5.26553 (* 1 = 5.26553 loss) +I0410 13:37:01.281975 18606 sgd_solver.cpp:105] Iteration 888, lr = 0.00838702 +I0410 13:37:06.172340 18606 solver.cpp:218] Iteration 900 (2.4539 iter/s, 4.89017s/12 iters), loss = 5.27382 +I0410 13:37:06.172394 18606 solver.cpp:237] Train net output #0: loss = 5.27382 (* 1 = 5.27382 loss) +I0410 13:37:06.172406 18606 sgd_solver.cpp:105] Iteration 900, lr = 0.0083671 +I0410 13:37:09.931720 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:11.008677 18606 solver.cpp:218] Iteration 912 (2.48136 iter/s, 4.83606s/12 iters), loss = 5.26068 +I0410 13:37:11.008731 18606 solver.cpp:237] Train net output #0: loss = 5.26068 (* 1 = 5.26068 loss) +I0410 13:37:11.008744 18606 sgd_solver.cpp:105] Iteration 912, lr = 0.00834724 +I0410 13:37:12.967162 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_918.caffemodel +I0410 13:37:13.295271 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_918.solverstate +I0410 13:37:13.512044 18606 solver.cpp:330] Iteration 918, Testing net (#0) +I0410 13:37:13.512068 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:37:17.746731 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:18.147575 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:37:18.147625 18606 solver.cpp:397] Test net output #1: loss = 5.28553 (* 1 = 5.28553 loss) +I0410 13:37:19.983428 18606 solver.cpp:218] Iteration 924 (1.33715 iter/s, 8.97429s/12 iters), loss = 5.28262 +I0410 13:37:19.983474 18606 solver.cpp:237] Train net output #0: loss = 5.28262 (* 1 = 5.28262 loss) +I0410 13:37:19.983482 18606 sgd_solver.cpp:105] Iteration 924, lr = 0.00832742 +I0410 13:37:24.769140 18606 solver.cpp:218] Iteration 936 (2.50761 iter/s, 4.78544s/12 iters), loss = 5.26154 +I0410 13:37:24.769186 18606 solver.cpp:237] Train net output #0: loss = 5.26154 (* 1 = 5.26154 loss) +I0410 13:37:24.769196 18606 sgd_solver.cpp:105] Iteration 936, lr = 0.00830765 +I0410 13:37:29.597201 18606 solver.cpp:218] Iteration 948 (2.48561 iter/s, 4.82779s/12 iters), loss = 5.28423 +I0410 13:37:29.597316 18606 solver.cpp:237] Train net output #0: loss = 5.28423 (* 1 = 5.28423 loss) +I0410 13:37:29.597328 18606 sgd_solver.cpp:105] Iteration 948, lr = 0.00828793 +I0410 13:37:34.683863 18606 solver.cpp:218] Iteration 960 (2.35927 iter/s, 5.08631s/12 iters), loss = 5.25904 +I0410 13:37:34.683907 18606 solver.cpp:237] Train net output #0: loss = 5.25904 (* 1 = 5.25904 loss) +I0410 13:37:34.683917 18606 sgd_solver.cpp:105] Iteration 960, lr = 0.00826825 +I0410 13:37:39.518450 18606 solver.cpp:218] Iteration 972 (2.48225 iter/s, 4.83432s/12 iters), loss = 5.2728 +I0410 13:37:39.518494 18606 solver.cpp:237] Train net output #0: loss = 5.2728 (* 1 = 5.2728 loss) +I0410 13:37:39.518503 18606 sgd_solver.cpp:105] Iteration 972, lr = 0.00824862 +I0410 13:37:44.370689 18606 solver.cpp:218] Iteration 984 (2.47322 iter/s, 4.85197s/12 iters), loss = 5.29006 +I0410 13:37:44.370743 18606 solver.cpp:237] Train net output #0: loss = 5.29006 (* 1 = 5.29006 loss) +I0410 13:37:44.370755 18606 sgd_solver.cpp:105] Iteration 984, lr = 0.00822903 +I0410 13:37:49.149150 18606 solver.cpp:218] Iteration 996 (2.51141 iter/s, 4.77819s/12 iters), loss = 5.27708 +I0410 13:37:49.149188 18606 solver.cpp:237] Train net output #0: loss = 5.27708 (* 1 = 5.27708 loss) +I0410 13:37:49.149196 18606 sgd_solver.cpp:105] Iteration 996, lr = 0.0082095 +I0410 13:37:54.059607 18606 solver.cpp:218] Iteration 1008 (2.4439 iter/s, 4.91018s/12 iters), loss = 5.28658 +I0410 13:37:54.059672 18606 solver.cpp:237] Train net output #0: loss = 5.28658 (* 1 = 5.28658 loss) +I0410 13:37:54.059689 18606 sgd_solver.cpp:105] Iteration 1008, lr = 0.00819001 +I0410 13:37:55.054857 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:37:58.413657 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1020.caffemodel +I0410 13:37:58.724054 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1020.solverstate +I0410 13:37:58.944399 18606 solver.cpp:330] Iteration 1020, Testing net (#0) +I0410 13:37:58.944420 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:38:03.070755 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:38:03.507347 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:38:03.507395 18606 solver.cpp:397] Test net output #1: loss = 5.28557 (* 1 = 5.28557 loss) +I0410 13:38:03.590344 18606 solver.cpp:218] Iteration 1020 (1.25915 iter/s, 9.53025s/12 iters), loss = 5.28942 +I0410 13:38:03.590389 18606 solver.cpp:237] Train net output #0: loss = 5.28942 (* 1 = 5.28942 loss) +I0410 13:38:03.590400 18606 sgd_solver.cpp:105] Iteration 1020, lr = 0.00817056 +I0410 13:38:07.735267 18606 solver.cpp:218] Iteration 1032 (2.89528 iter/s, 4.14468s/12 iters), loss = 5.25158 +I0410 13:38:07.735322 18606 solver.cpp:237] Train net output #0: loss = 5.25158 (* 1 = 5.25158 loss) +I0410 13:38:07.735335 18606 sgd_solver.cpp:105] Iteration 1032, lr = 0.00815116 +I0410 13:38:12.599265 18606 solver.cpp:218] Iteration 1044 (2.46725 iter/s, 4.86372s/12 iters), loss = 5.26016 +I0410 13:38:12.599309 18606 solver.cpp:237] Train net output #0: loss = 5.26016 (* 1 = 5.26016 loss) +I0410 13:38:12.599318 18606 sgd_solver.cpp:105] Iteration 1044, lr = 0.00813181 +I0410 13:38:17.470558 18606 solver.cpp:218] Iteration 1056 (2.46355 iter/s, 4.87102s/12 iters), loss = 5.26212 +I0410 13:38:17.470610 18606 solver.cpp:237] Train net output #0: loss = 5.26212 (* 1 = 5.26212 loss) +I0410 13:38:17.470621 18606 sgd_solver.cpp:105] Iteration 1056, lr = 0.0081125 +I0410 13:38:22.354007 18606 solver.cpp:218] Iteration 1068 (2.45742 iter/s, 4.88317s/12 iters), loss = 5.28613 +I0410 13:38:22.354061 18606 solver.cpp:237] Train net output #0: loss = 5.28613 (* 1 = 5.28613 loss) +I0410 13:38:22.354074 18606 sgd_solver.cpp:105] Iteration 1068, lr = 0.00809324 +I0410 13:38:27.228814 18606 solver.cpp:218] Iteration 1080 (2.46178 iter/s, 4.87452s/12 iters), loss = 5.27022 +I0410 13:38:27.228864 18606 solver.cpp:237] Train net output #0: loss = 5.27022 (* 1 = 5.27022 loss) +I0410 13:38:27.228875 18606 sgd_solver.cpp:105] Iteration 1080, lr = 0.00807403 +I0410 13:38:32.125854 18606 solver.cpp:218] Iteration 1092 (2.4506 iter/s, 4.89676s/12 iters), loss = 5.27983 +I0410 13:38:32.125906 18606 solver.cpp:237] Train net output #0: loss = 5.27983 (* 1 = 5.27983 loss) +I0410 13:38:32.125917 18606 sgd_solver.cpp:105] Iteration 1092, lr = 0.00805486 +I0410 13:38:37.179786 18606 solver.cpp:218] Iteration 1104 (2.37453 iter/s, 5.05364s/12 iters), loss = 5.27313 +I0410 13:38:37.179905 18606 solver.cpp:237] Train net output #0: loss = 5.27313 (* 1 = 5.27313 loss) +I0410 13:38:37.179919 18606 sgd_solver.cpp:105] Iteration 1104, lr = 0.00803573 +I0410 13:38:40.249761 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:38:42.047032 18606 solver.cpp:218] Iteration 1116 (2.46563 iter/s, 4.8669s/12 iters), loss = 5.27112 +I0410 13:38:42.047086 18606 solver.cpp:237] Train net output #0: loss = 5.27112 (* 1 = 5.27112 loss) +I0410 13:38:42.047098 18606 sgd_solver.cpp:105] Iteration 1116, lr = 0.00801666 +I0410 13:38:44.053246 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1122.caffemodel +I0410 13:38:45.008071 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1122.solverstate +I0410 13:38:45.237393 18606 solver.cpp:330] Iteration 1122, Testing net (#0) +I0410 13:38:45.237412 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:38:49.113687 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:38:49.589568 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:38:49.589604 18606 solver.cpp:397] Test net output #1: loss = 5.28589 (* 1 = 5.28589 loss) +I0410 13:38:51.556970 18606 solver.cpp:218] Iteration 1128 (1.2619 iter/s, 9.50945s/12 iters), loss = 5.27635 +I0410 13:38:51.557027 18606 solver.cpp:237] Train net output #0: loss = 5.27635 (* 1 = 5.27635 loss) +I0410 13:38:51.557039 18606 sgd_solver.cpp:105] Iteration 1128, lr = 0.00799762 +I0410 13:38:56.430078 18606 solver.cpp:218] Iteration 1140 (2.46264 iter/s, 4.87282s/12 iters), loss = 5.26577 +I0410 13:38:56.430138 18606 solver.cpp:237] Train net output #0: loss = 5.26577 (* 1 = 5.26577 loss) +I0410 13:38:56.430150 18606 sgd_solver.cpp:105] Iteration 1140, lr = 0.00797863 +I0410 13:39:01.293347 18606 solver.cpp:218] Iteration 1152 (2.46762 iter/s, 4.86298s/12 iters), loss = 5.27865 +I0410 13:39:01.293404 18606 solver.cpp:237] Train net output #0: loss = 5.27865 (* 1 = 5.27865 loss) +I0410 13:39:01.293417 18606 sgd_solver.cpp:105] Iteration 1152, lr = 0.00795969 +I0410 13:39:06.171049 18606 solver.cpp:218] Iteration 1164 (2.46032 iter/s, 4.87742s/12 iters), loss = 5.27239 +I0410 13:39:06.171099 18606 solver.cpp:237] Train net output #0: loss = 5.27239 (* 1 = 5.27239 loss) +I0410 13:39:06.171108 18606 sgd_solver.cpp:105] Iteration 1164, lr = 0.00794079 +I0410 13:39:11.388366 18606 solver.cpp:218] Iteration 1176 (2.30016 iter/s, 5.21703s/12 iters), loss = 5.28569 +I0410 13:39:11.390339 18606 solver.cpp:237] Train net output #0: loss = 5.28569 (* 1 = 5.28569 loss) +I0410 13:39:11.390349 18606 sgd_solver.cpp:105] Iteration 1176, lr = 0.00792194 +I0410 13:39:16.228138 18606 solver.cpp:218] Iteration 1188 (2.48058 iter/s, 4.83758s/12 iters), loss = 5.27054 +I0410 13:39:16.228197 18606 solver.cpp:237] Train net output #0: loss = 5.27054 (* 1 = 5.27054 loss) +I0410 13:39:16.228212 18606 sgd_solver.cpp:105] Iteration 1188, lr = 0.00790313 +I0410 13:39:21.142947 18606 solver.cpp:218] Iteration 1200 (2.44175 iter/s, 4.91451s/12 iters), loss = 5.28611 +I0410 13:39:21.143007 18606 solver.cpp:237] Train net output #0: loss = 5.28611 (* 1 = 5.28611 loss) +I0410 13:39:21.143021 18606 sgd_solver.cpp:105] Iteration 1200, lr = 0.00788437 +I0410 13:39:26.144096 18606 solver.cpp:218] Iteration 1212 (2.39959 iter/s, 5.00086s/12 iters), loss = 5.2632 +I0410 13:39:26.144137 18606 solver.cpp:237] Train net output #0: loss = 5.2632 (* 1 = 5.2632 loss) +I0410 13:39:26.144145 18606 sgd_solver.cpp:105] Iteration 1212, lr = 0.00786565 +I0410 13:39:26.449120 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:30.599543 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1224.caffemodel +I0410 13:39:30.919117 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1224.solverstate +I0410 13:39:31.127737 18606 solver.cpp:330] Iteration 1224, Testing net (#0) +I0410 13:39:31.127755 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:39:35.034444 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:39:35.543975 18606 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:39:35.544025 18606 solver.cpp:397] Test net output #1: loss = 5.28595 (* 1 = 5.28595 loss) +I0410 13:39:35.626756 18606 solver.cpp:218] Iteration 1224 (1.26553 iter/s, 9.48218s/12 iters), loss = 5.2825 +I0410 13:39:35.626809 18606 solver.cpp:237] Train net output #0: loss = 5.2825 (* 1 = 5.2825 loss) +I0410 13:39:35.626822 18606 sgd_solver.cpp:105] Iteration 1224, lr = 0.00784697 +I0410 13:39:39.739409 18606 solver.cpp:218] Iteration 1236 (2.918 iter/s, 4.1124s/12 iters), loss = 5.27117 +I0410 13:39:39.739468 18606 solver.cpp:237] Train net output #0: loss = 5.27117 (* 1 = 5.27117 loss) +I0410 13:39:39.739481 18606 sgd_solver.cpp:105] Iteration 1236, lr = 0.00782834 +I0410 13:39:44.604250 18606 solver.cpp:218] Iteration 1248 (2.46682 iter/s, 4.86455s/12 iters), loss = 5.27749 +I0410 13:39:44.604385 18606 solver.cpp:237] Train net output #0: loss = 5.27749 (* 1 = 5.27749 loss) +I0410 13:39:44.604400 18606 sgd_solver.cpp:105] Iteration 1248, lr = 0.00780976 +I0410 13:39:49.421844 18606 solver.cpp:218] Iteration 1260 (2.49106 iter/s, 4.81723s/12 iters), loss = 5.27181 +I0410 13:39:49.421895 18606 solver.cpp:237] Train net output #0: loss = 5.27181 (* 1 = 5.27181 loss) +I0410 13:39:49.421906 18606 sgd_solver.cpp:105] Iteration 1260, lr = 0.00779122 +I0410 13:39:54.250331 18606 solver.cpp:218] Iteration 1272 (2.48539 iter/s, 4.82821s/12 iters), loss = 5.24661 +I0410 13:39:54.250383 18606 solver.cpp:237] Train net output #0: loss = 5.24661 (* 1 = 5.24661 loss) +I0410 13:39:54.250394 18606 sgd_solver.cpp:105] Iteration 1272, lr = 0.00777272 +I0410 13:39:59.257668 18606 solver.cpp:218] Iteration 1284 (2.39662 iter/s, 5.00705s/12 iters), loss = 5.28171 +I0410 13:39:59.257709 18606 solver.cpp:237] Train net output #0: loss = 5.28171 (* 1 = 5.28171 loss) +I0410 13:39:59.257719 18606 sgd_solver.cpp:105] Iteration 1284, lr = 0.00775426 +I0410 13:40:04.111578 18606 solver.cpp:218] Iteration 1296 (2.47237 iter/s, 4.85364s/12 iters), loss = 5.26894 +I0410 13:40:04.111629 18606 solver.cpp:237] Train net output #0: loss = 5.26894 (* 1 = 5.26894 loss) +I0410 13:40:04.111639 18606 sgd_solver.cpp:105] Iteration 1296, lr = 0.00773585 +I0410 13:40:09.049122 18606 solver.cpp:218] Iteration 1308 (2.4305 iter/s, 4.93726s/12 iters), loss = 5.25388 +I0410 13:40:09.049170 18606 solver.cpp:237] Train net output #0: loss = 5.25388 (* 1 = 5.25388 loss) +I0410 13:40:09.049183 18606 sgd_solver.cpp:105] Iteration 1308, lr = 0.00771749 +I0410 13:40:11.623423 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:14.234570 18606 solver.cpp:218] Iteration 1320 (2.3143 iter/s, 5.18515s/12 iters), loss = 5.27298 +I0410 13:40:14.234629 18606 solver.cpp:237] Train net output #0: loss = 5.27298 (* 1 = 5.27298 loss) +I0410 13:40:14.234640 18606 sgd_solver.cpp:105] Iteration 1320, lr = 0.00769916 +I0410 13:40:16.230947 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1326.caffemodel +I0410 13:40:16.545215 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1326.solverstate +I0410 13:40:16.762457 18606 solver.cpp:330] Iteration 1326, Testing net (#0) +I0410 13:40:16.762482 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:40:20.914196 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:21.468336 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:40:21.468384 18606 solver.cpp:397] Test net output #1: loss = 5.28667 (* 1 = 5.28667 loss) +I0410 13:40:23.397218 18606 solver.cpp:218] Iteration 1332 (1.30973 iter/s, 9.16217s/12 iters), loss = 5.28648 +I0410 13:40:23.397269 18606 solver.cpp:237] Train net output #0: loss = 5.28648 (* 1 = 5.28648 loss) +I0410 13:40:23.397280 18606 sgd_solver.cpp:105] Iteration 1332, lr = 0.00768088 +I0410 13:40:28.228885 18606 solver.cpp:218] Iteration 1344 (2.48376 iter/s, 4.83139s/12 iters), loss = 5.28575 +I0410 13:40:28.228940 18606 solver.cpp:237] Train net output #0: loss = 5.28575 (* 1 = 5.28575 loss) +I0410 13:40:28.228951 18606 sgd_solver.cpp:105] Iteration 1344, lr = 0.00766265 +I0410 13:40:33.195530 18606 solver.cpp:218] Iteration 1356 (2.41626 iter/s, 4.96636s/12 iters), loss = 5.27602 +I0410 13:40:33.195577 18606 solver.cpp:237] Train net output #0: loss = 5.27602 (* 1 = 5.27602 loss) +I0410 13:40:33.195588 18606 sgd_solver.cpp:105] Iteration 1356, lr = 0.00764446 +I0410 13:40:37.607610 18606 blocking_queue.cpp:49] Waiting for data +I0410 13:40:38.109624 18606 solver.cpp:218] Iteration 1368 (2.4421 iter/s, 4.91381s/12 iters), loss = 5.2649 +I0410 13:40:38.109676 18606 solver.cpp:237] Train net output #0: loss = 5.2649 (* 1 = 5.2649 loss) +I0410 13:40:38.109688 18606 sgd_solver.cpp:105] Iteration 1368, lr = 0.00762631 +I0410 13:40:43.060400 18606 solver.cpp:218] Iteration 1380 (2.424 iter/s, 4.95049s/12 iters), loss = 5.27341 +I0410 13:40:43.060447 18606 solver.cpp:237] Train net output #0: loss = 5.27341 (* 1 = 5.27341 loss) +I0410 13:40:43.060457 18606 sgd_solver.cpp:105] Iteration 1380, lr = 0.0076082 +I0410 13:40:47.964228 18606 solver.cpp:218] Iteration 1392 (2.44721 iter/s, 4.90355s/12 iters), loss = 5.27374 +I0410 13:40:47.964360 18606 solver.cpp:237] Train net output #0: loss = 5.27374 (* 1 = 5.27374 loss) +I0410 13:40:47.964375 18606 sgd_solver.cpp:105] Iteration 1392, lr = 0.00759014 +I0410 13:40:52.890309 18606 solver.cpp:218] Iteration 1404 (2.43619 iter/s, 4.92572s/12 iters), loss = 5.27624 +I0410 13:40:52.890365 18606 solver.cpp:237] Train net output #0: loss = 5.27624 (* 1 = 5.27624 loss) +I0410 13:40:52.890378 18606 sgd_solver.cpp:105] Iteration 1404, lr = 0.00757212 +I0410 13:40:57.445298 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:40:57.797433 18606 solver.cpp:218] Iteration 1416 (2.44557 iter/s, 4.90684s/12 iters), loss = 5.25678 +I0410 13:40:57.797477 18606 solver.cpp:237] Train net output #0: loss = 5.25678 (* 1 = 5.25678 loss) +I0410 13:40:57.797485 18606 sgd_solver.cpp:105] Iteration 1416, lr = 0.00755414 +I0410 13:41:02.244244 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1428.caffemodel +I0410 13:41:03.899081 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1428.solverstate +I0410 13:41:04.784505 18606 solver.cpp:330] Iteration 1428, Testing net (#0) +I0410 13:41:04.784531 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:41:08.650705 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:41:09.239159 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:41:09.239208 18606 solver.cpp:397] Test net output #1: loss = 5.28627 (* 1 = 5.28627 loss) +I0410 13:41:09.320161 18606 solver.cpp:218] Iteration 1428 (1.04147 iter/s, 11.5222s/12 iters), loss = 5.27562 +I0410 13:41:09.320228 18606 solver.cpp:237] Train net output #0: loss = 5.27562 (* 1 = 5.27562 loss) +I0410 13:41:09.320245 18606 sgd_solver.cpp:105] Iteration 1428, lr = 0.0075362 +I0410 13:41:13.461740 18606 solver.cpp:218] Iteration 1440 (2.89763 iter/s, 4.14132s/12 iters), loss = 5.2811 +I0410 13:41:13.461784 18606 solver.cpp:237] Train net output #0: loss = 5.2811 (* 1 = 5.2811 loss) +I0410 13:41:13.461796 18606 sgd_solver.cpp:105] Iteration 1440, lr = 0.00751831 +I0410 13:41:18.319852 18606 solver.cpp:218] Iteration 1452 (2.47023 iter/s, 4.85784s/12 iters), loss = 5.28039 +I0410 13:41:18.319949 18606 solver.cpp:237] Train net output #0: loss = 5.28039 (* 1 = 5.28039 loss) +I0410 13:41:18.319962 18606 sgd_solver.cpp:105] Iteration 1452, lr = 0.00750046 +I0410 13:41:23.280968 18606 solver.cpp:218] Iteration 1464 (2.41897 iter/s, 4.96078s/12 iters), loss = 5.27726 +I0410 13:41:23.281025 18606 solver.cpp:237] Train net output #0: loss = 5.27726 (* 1 = 5.27726 loss) +I0410 13:41:23.281038 18606 sgd_solver.cpp:105] Iteration 1464, lr = 0.00748265 +I0410 13:41:28.121016 18606 solver.cpp:218] Iteration 1476 (2.47946 iter/s, 4.83976s/12 iters), loss = 5.277 +I0410 13:41:28.121070 18606 solver.cpp:237] Train net output #0: loss = 5.277 (* 1 = 5.277 loss) +I0410 13:41:28.121083 18606 sgd_solver.cpp:105] Iteration 1476, lr = 0.00746489 +I0410 13:41:32.920446 18606 solver.cpp:218] Iteration 1488 (2.50044 iter/s, 4.79915s/12 iters), loss = 5.25419 +I0410 13:41:32.920500 18606 solver.cpp:237] Train net output #0: loss = 5.25419 (* 1 = 5.25419 loss) +I0410 13:41:32.920512 18606 sgd_solver.cpp:105] Iteration 1488, lr = 0.00744716 +I0410 13:41:37.737365 18606 solver.cpp:218] Iteration 1500 (2.49136 iter/s, 4.81664s/12 iters), loss = 5.26927 +I0410 13:41:37.737413 18606 solver.cpp:237] Train net output #0: loss = 5.26927 (* 1 = 5.26927 loss) +I0410 13:41:37.737421 18606 sgd_solver.cpp:105] Iteration 1500, lr = 0.00742948 +I0410 13:41:42.601138 18606 solver.cpp:218] Iteration 1512 (2.46736 iter/s, 4.8635s/12 iters), loss = 5.28461 +I0410 13:41:42.601183 18606 solver.cpp:237] Train net output #0: loss = 5.28461 (* 1 = 5.28461 loss) +I0410 13:41:42.601194 18606 sgd_solver.cpp:105] Iteration 1512, lr = 0.00741184 +I0410 13:41:44.346756 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:41:47.456384 18606 solver.cpp:218] Iteration 1524 (2.47169 iter/s, 4.85498s/12 iters), loss = 5.27729 +I0410 13:41:47.456429 18606 solver.cpp:237] Train net output #0: loss = 5.27729 (* 1 = 5.27729 loss) +I0410 13:41:47.456437 18606 sgd_solver.cpp:105] Iteration 1524, lr = 0.00739425 +I0410 13:41:49.440754 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1530.caffemodel +I0410 13:41:49.749084 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1530.solverstate +I0410 13:41:49.952121 18606 solver.cpp:330] Iteration 1530, Testing net (#0) +I0410 13:41:49.952142 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:41:53.689368 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:41:54.324106 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:41:54.324143 18606 solver.cpp:397] Test net output #1: loss = 5.28611 (* 1 = 5.28611 loss) +I0410 13:41:56.099144 18606 solver.cpp:218] Iteration 1536 (1.38852 iter/s, 8.64232s/12 iters), loss = 5.27579 +I0410 13:41:56.099189 18606 solver.cpp:237] Train net output #0: loss = 5.27579 (* 1 = 5.27579 loss) +I0410 13:41:56.099198 18606 sgd_solver.cpp:105] Iteration 1536, lr = 0.00737669 +I0410 13:42:00.939739 18606 solver.cpp:218] Iteration 1548 (2.47917 iter/s, 4.84032s/12 iters), loss = 5.23159 +I0410 13:42:00.939782 18606 solver.cpp:237] Train net output #0: loss = 5.23159 (* 1 = 5.23159 loss) +I0410 13:42:00.939790 18606 sgd_solver.cpp:105] Iteration 1548, lr = 0.00735918 +I0410 13:42:05.740132 18606 solver.cpp:218] Iteration 1560 (2.49994 iter/s, 4.80012s/12 iters), loss = 5.29033 +I0410 13:42:05.740182 18606 solver.cpp:237] Train net output #0: loss = 5.29033 (* 1 = 5.29033 loss) +I0410 13:42:05.740193 18606 sgd_solver.cpp:105] Iteration 1560, lr = 0.00734171 +I0410 13:42:10.720075 18606 solver.cpp:218] Iteration 1572 (2.4098 iter/s, 4.97966s/12 iters), loss = 5.2595 +I0410 13:42:10.720121 18606 solver.cpp:237] Train net output #0: loss = 5.2595 (* 1 = 5.2595 loss) +I0410 13:42:10.720130 18606 sgd_solver.cpp:105] Iteration 1572, lr = 0.00732427 +I0410 13:42:15.586423 18606 solver.cpp:218] Iteration 1584 (2.46606 iter/s, 4.86606s/12 iters), loss = 5.26689 +I0410 13:42:15.586477 18606 solver.cpp:237] Train net output #0: loss = 5.26689 (* 1 = 5.26689 loss) +I0410 13:42:15.586486 18606 sgd_solver.cpp:105] Iteration 1584, lr = 0.00730688 +I0410 13:42:20.381984 18606 solver.cpp:218] Iteration 1596 (2.50247 iter/s, 4.79526s/12 iters), loss = 5.26921 +I0410 13:42:20.382091 18606 solver.cpp:237] Train net output #0: loss = 5.26921 (* 1 = 5.26921 loss) +I0410 13:42:20.382103 18606 sgd_solver.cpp:105] Iteration 1596, lr = 0.00728954 +I0410 13:42:25.193534 18606 solver.cpp:218] Iteration 1608 (2.49417 iter/s, 4.81122s/12 iters), loss = 5.26867 +I0410 13:42:25.193575 18606 solver.cpp:237] Train net output #0: loss = 5.26867 (* 1 = 5.26867 loss) +I0410 13:42:25.193583 18606 sgd_solver.cpp:105] Iteration 1608, lr = 0.00727223 +I0410 13:42:28.999239 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:42:30.050801 18606 solver.cpp:218] Iteration 1620 (2.47066 iter/s, 4.85699s/12 iters), loss = 5.2576 +I0410 13:42:30.050841 18606 solver.cpp:237] Train net output #0: loss = 5.2576 (* 1 = 5.2576 loss) +I0410 13:42:30.050849 18606 sgd_solver.cpp:105] Iteration 1620, lr = 0.00725496 +I0410 13:42:34.432169 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1632.caffemodel +I0410 13:42:34.734776 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1632.solverstate +I0410 13:42:34.946393 18606 solver.cpp:330] Iteration 1632, Testing net (#0) +I0410 13:42:34.946424 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:42:38.729387 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:42:39.402719 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:42:39.402770 18606 solver.cpp:397] Test net output #1: loss = 5.28628 (* 1 = 5.28628 loss) +I0410 13:42:39.485903 18606 solver.cpp:218] Iteration 1632 (1.27191 iter/s, 9.43463s/12 iters), loss = 5.28629 +I0410 13:42:39.485978 18606 solver.cpp:237] Train net output #0: loss = 5.28629 (* 1 = 5.28629 loss) +I0410 13:42:39.485991 18606 sgd_solver.cpp:105] Iteration 1632, lr = 0.00723774 +I0410 13:42:43.600980 18606 solver.cpp:218] Iteration 1644 (2.91628 iter/s, 4.11483s/12 iters), loss = 5.25308 +I0410 13:42:43.601030 18606 solver.cpp:237] Train net output #0: loss = 5.25308 (* 1 = 5.25308 loss) +I0410 13:42:43.601042 18606 sgd_solver.cpp:105] Iteration 1644, lr = 0.00722056 +I0410 13:42:48.423717 18606 solver.cpp:218] Iteration 1656 (2.48836 iter/s, 4.82246s/12 iters), loss = 5.28923 +I0410 13:42:48.423776 18606 solver.cpp:237] Train net output #0: loss = 5.28923 (* 1 = 5.28923 loss) +I0410 13:42:48.423789 18606 sgd_solver.cpp:105] Iteration 1656, lr = 0.00720341 +I0410 13:42:53.217044 18606 solver.cpp:218] Iteration 1668 (2.50363 iter/s, 4.79304s/12 iters), loss = 5.26303 +I0410 13:42:53.217172 18606 solver.cpp:237] Train net output #0: loss = 5.26303 (* 1 = 5.26303 loss) +I0410 13:42:53.217185 18606 sgd_solver.cpp:105] Iteration 1668, lr = 0.00718631 +I0410 13:42:57.989080 18606 solver.cpp:218] Iteration 1680 (2.51483 iter/s, 4.77169s/12 iters), loss = 5.27386 +I0410 13:42:57.989138 18606 solver.cpp:237] Train net output #0: loss = 5.27386 (* 1 = 5.27386 loss) +I0410 13:42:57.989151 18606 sgd_solver.cpp:105] Iteration 1680, lr = 0.00716925 +I0410 13:43:02.777607 18606 solver.cpp:218] Iteration 1692 (2.50614 iter/s, 4.78825s/12 iters), loss = 5.28813 +I0410 13:43:02.777658 18606 solver.cpp:237] Train net output #0: loss = 5.28813 (* 1 = 5.28813 loss) +I0410 13:43:02.777669 18606 sgd_solver.cpp:105] Iteration 1692, lr = 0.00715223 +I0410 13:43:07.558552 18606 solver.cpp:218] Iteration 1704 (2.51011 iter/s, 4.78067s/12 iters), loss = 5.27046 +I0410 13:43:07.558611 18606 solver.cpp:237] Train net output #0: loss = 5.27046 (* 1 = 5.27046 loss) +I0410 13:43:07.558624 18606 sgd_solver.cpp:105] Iteration 1704, lr = 0.00713525 +I0410 13:43:12.419327 18606 solver.cpp:218] Iteration 1716 (2.46889 iter/s, 4.86049s/12 iters), loss = 5.27962 +I0410 13:43:12.419370 18606 solver.cpp:237] Train net output #0: loss = 5.27962 (* 1 = 5.27962 loss) +I0410 13:43:12.419379 18606 sgd_solver.cpp:105] Iteration 1716, lr = 0.00711831 +I0410 13:43:13.453244 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:43:17.404920 18606 solver.cpp:218] Iteration 1728 (2.40707 iter/s, 4.98531s/12 iters), loss = 5.28357 +I0410 13:43:17.404992 18606 solver.cpp:237] Train net output #0: loss = 5.28357 (* 1 = 5.28357 loss) +I0410 13:43:17.405010 18606 sgd_solver.cpp:105] Iteration 1728, lr = 0.00710141 +I0410 13:43:19.382721 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1734.caffemodel +I0410 13:43:19.714442 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1734.solverstate +I0410 13:43:19.919009 18606 solver.cpp:330] Iteration 1734, Testing net (#0) +I0410 13:43:19.919036 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:43:23.722165 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:43:24.446286 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:43:24.446336 18606 solver.cpp:397] Test net output #1: loss = 5.28662 (* 1 = 5.28662 loss) +I0410 13:43:26.347728 18606 solver.cpp:218] Iteration 1740 (1.34193 iter/s, 8.94233s/12 iters), loss = 5.25682 +I0410 13:43:26.347781 18606 solver.cpp:237] Train net output #0: loss = 5.25682 (* 1 = 5.25682 loss) +I0410 13:43:26.347792 18606 sgd_solver.cpp:105] Iteration 1740, lr = 0.00708455 +I0410 13:43:31.184676 18606 solver.cpp:218] Iteration 1752 (2.48105 iter/s, 4.83667s/12 iters), loss = 5.26605 +I0410 13:43:31.184729 18606 solver.cpp:237] Train net output #0: loss = 5.26605 (* 1 = 5.26605 loss) +I0410 13:43:31.184741 18606 sgd_solver.cpp:105] Iteration 1752, lr = 0.00706773 +I0410 13:43:36.069973 18606 solver.cpp:218] Iteration 1764 (2.4565 iter/s, 4.885s/12 iters), loss = 5.26488 +I0410 13:43:36.070024 18606 solver.cpp:237] Train net output #0: loss = 5.26488 (* 1 = 5.26488 loss) +I0410 13:43:36.070035 18606 sgd_solver.cpp:105] Iteration 1764, lr = 0.00705094 +I0410 13:43:40.899914 18606 solver.cpp:218] Iteration 1776 (2.48465 iter/s, 4.82966s/12 iters), loss = 5.2812 +I0410 13:43:40.899966 18606 solver.cpp:237] Train net output #0: loss = 5.2812 (* 1 = 5.2812 loss) +I0410 13:43:40.899976 18606 sgd_solver.cpp:105] Iteration 1776, lr = 0.0070342 +I0410 13:43:45.726182 18606 solver.cpp:218] Iteration 1788 (2.48654 iter/s, 4.82599s/12 iters), loss = 5.26247 +I0410 13:43:45.726239 18606 solver.cpp:237] Train net output #0: loss = 5.26247 (* 1 = 5.26247 loss) +I0410 13:43:45.726253 18606 sgd_solver.cpp:105] Iteration 1788, lr = 0.0070175 +I0410 13:43:50.565418 18606 solver.cpp:218] Iteration 1800 (2.47988 iter/s, 4.83895s/12 iters), loss = 5.27885 +I0410 13:43:50.565459 18606 solver.cpp:237] Train net output #0: loss = 5.27885 (* 1 = 5.27885 loss) +I0410 13:43:50.565469 18606 sgd_solver.cpp:105] Iteration 1800, lr = 0.00700084 +I0410 13:43:55.401576 18606 solver.cpp:218] Iteration 1812 (2.48145 iter/s, 4.83589s/12 iters), loss = 5.26749 +I0410 13:43:55.401721 18606 solver.cpp:237] Train net output #0: loss = 5.26749 (* 1 = 5.26749 loss) +I0410 13:43:55.401732 18606 sgd_solver.cpp:105] Iteration 1812, lr = 0.00698422 +I0410 13:43:58.539810 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:00.370806 18606 solver.cpp:218] Iteration 1824 (2.41505 iter/s, 4.96885s/12 iters), loss = 5.27528 +I0410 13:44:00.370865 18606 solver.cpp:237] Train net output #0: loss = 5.27528 (* 1 = 5.27528 loss) +I0410 13:44:00.370877 18606 sgd_solver.cpp:105] Iteration 1824, lr = 0.00696764 +I0410 13:44:04.794447 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1836.caffemodel +I0410 13:44:05.210223 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1836.solverstate +I0410 13:44:05.476802 18606 solver.cpp:330] Iteration 1836, Testing net (#0) +I0410 13:44:05.476830 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:44:09.332299 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:10.078810 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:44:10.078860 18606 solver.cpp:397] Test net output #1: loss = 5.28615 (* 1 = 5.28615 loss) +I0410 13:44:10.162375 18606 solver.cpp:218] Iteration 1836 (1.22561 iter/s, 9.79106s/12 iters), loss = 5.27813 +I0410 13:44:10.162447 18606 solver.cpp:237] Train net output #0: loss = 5.27813 (* 1 = 5.27813 loss) +I0410 13:44:10.162463 18606 sgd_solver.cpp:105] Iteration 1836, lr = 0.0069511 +I0410 13:44:14.352742 18606 solver.cpp:218] Iteration 1848 (2.86389 iter/s, 4.1901s/12 iters), loss = 5.27174 +I0410 13:44:14.352785 18606 solver.cpp:237] Train net output #0: loss = 5.27174 (* 1 = 5.27174 loss) +I0410 13:44:14.352795 18606 sgd_solver.cpp:105] Iteration 1848, lr = 0.00693459 +I0410 13:44:19.229863 18606 solver.cpp:218] Iteration 1860 (2.46061 iter/s, 4.87685s/12 iters), loss = 5.28196 +I0410 13:44:19.229912 18606 solver.cpp:237] Train net output #0: loss = 5.28196 (* 1 = 5.28196 loss) +I0410 13:44:19.229923 18606 sgd_solver.cpp:105] Iteration 1860, lr = 0.00691813 +I0410 13:44:24.080493 18606 solver.cpp:218] Iteration 1872 (2.47405 iter/s, 4.85035s/12 iters), loss = 5.2715 +I0410 13:44:24.080543 18606 solver.cpp:237] Train net output #0: loss = 5.2715 (* 1 = 5.2715 loss) +I0410 13:44:24.080554 18606 sgd_solver.cpp:105] Iteration 1872, lr = 0.0069017 +I0410 13:44:29.004307 18606 solver.cpp:218] Iteration 1884 (2.43727 iter/s, 4.92353s/12 iters), loss = 5.28641 +I0410 13:44:29.004412 18606 solver.cpp:237] Train net output #0: loss = 5.28641 (* 1 = 5.28641 loss) +I0410 13:44:29.004426 18606 sgd_solver.cpp:105] Iteration 1884, lr = 0.00688532 +I0410 13:44:33.941799 18606 solver.cpp:218] Iteration 1896 (2.43055 iter/s, 4.93716s/12 iters), loss = 5.26526 +I0410 13:44:33.941839 18606 solver.cpp:237] Train net output #0: loss = 5.26526 (* 1 = 5.26526 loss) +I0410 13:44:33.941848 18606 sgd_solver.cpp:105] Iteration 1896, lr = 0.00686897 +I0410 13:44:38.831176 18606 solver.cpp:218] Iteration 1908 (2.45444 iter/s, 4.88911s/12 iters), loss = 5.28227 +I0410 13:44:38.831218 18606 solver.cpp:237] Train net output #0: loss = 5.28227 (* 1 = 5.28227 loss) +I0410 13:44:38.831228 18606 sgd_solver.cpp:105] Iteration 1908, lr = 0.00685266 +I0410 13:44:43.751217 18606 solver.cpp:218] Iteration 1920 (2.43914 iter/s, 4.91976s/12 iters), loss = 5.27498 +I0410 13:44:43.751264 18606 solver.cpp:237] Train net output #0: loss = 5.27498 (* 1 = 5.27498 loss) +I0410 13:44:43.751274 18606 sgd_solver.cpp:105] Iteration 1920, lr = 0.00683639 +I0410 13:44:44.103229 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:48.653102 18606 solver.cpp:218] Iteration 1932 (2.44818 iter/s, 4.90161s/12 iters), loss = 5.28023 +I0410 13:44:48.653152 18606 solver.cpp:237] Train net output #0: loss = 5.28023 (* 1 = 5.28023 loss) +I0410 13:44:48.653163 18606 sgd_solver.cpp:105] Iteration 1932, lr = 0.00682016 +I0410 13:44:50.649821 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_1938.caffemodel +I0410 13:44:50.979672 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_1938.solverstate +I0410 13:44:51.200075 18606 solver.cpp:330] Iteration 1938, Testing net (#0) +I0410 13:44:51.200103 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:44:54.841003 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:44:55.623576 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:44:55.623639 18606 solver.cpp:397] Test net output #1: loss = 5.28666 (* 1 = 5.28666 loss) +I0410 13:44:57.524142 18606 solver.cpp:218] Iteration 1944 (1.35279 iter/s, 8.87058s/12 iters), loss = 5.27315 +I0410 13:44:57.524188 18606 solver.cpp:237] Train net output #0: loss = 5.27315 (* 1 = 5.27315 loss) +I0410 13:44:57.524197 18606 sgd_solver.cpp:105] Iteration 1944, lr = 0.00680397 +I0410 13:45:02.397099 18606 solver.cpp:218] Iteration 1956 (2.46271 iter/s, 4.87268s/12 iters), loss = 5.28035 +I0410 13:45:02.397207 18606 solver.cpp:237] Train net output #0: loss = 5.28035 (* 1 = 5.28035 loss) +I0410 13:45:02.397217 18606 sgd_solver.cpp:105] Iteration 1956, lr = 0.00678782 +I0410 13:45:07.205689 18606 solver.cpp:218] Iteration 1968 (2.49571 iter/s, 4.80825s/12 iters), loss = 5.27253 +I0410 13:45:07.205744 18606 solver.cpp:237] Train net output #0: loss = 5.27253 (* 1 = 5.27253 loss) +I0410 13:45:07.205754 18606 sgd_solver.cpp:105] Iteration 1968, lr = 0.0067717 +I0410 13:45:12.366852 18606 solver.cpp:218] Iteration 1980 (2.32519 iter/s, 5.16087s/12 iters), loss = 5.25468 +I0410 13:45:12.366899 18606 solver.cpp:237] Train net output #0: loss = 5.25468 (* 1 = 5.25468 loss) +I0410 13:45:12.366910 18606 sgd_solver.cpp:105] Iteration 1980, lr = 0.00675562 +I0410 13:45:17.156647 18606 solver.cpp:218] Iteration 1992 (2.50547 iter/s, 4.78951s/12 iters), loss = 5.28296 +I0410 13:45:17.156703 18606 solver.cpp:237] Train net output #0: loss = 5.28296 (* 1 = 5.28296 loss) +I0410 13:45:17.156714 18606 sgd_solver.cpp:105] Iteration 1992, lr = 0.00673958 +I0410 13:45:21.993310 18606 solver.cpp:218] Iteration 2004 (2.4812 iter/s, 4.83638s/12 iters), loss = 5.27675 +I0410 13:45:21.993364 18606 solver.cpp:237] Train net output #0: loss = 5.27675 (* 1 = 5.27675 loss) +I0410 13:45:21.993376 18606 sgd_solver.cpp:105] Iteration 2004, lr = 0.00672358 +I0410 13:45:26.853660 18606 solver.cpp:218] Iteration 2016 (2.4691 iter/s, 4.86006s/12 iters), loss = 5.25294 +I0410 13:45:26.853715 18606 solver.cpp:237] Train net output #0: loss = 5.25294 (* 1 = 5.25294 loss) +I0410 13:45:26.853726 18606 sgd_solver.cpp:105] Iteration 2016, lr = 0.00670762 +I0410 13:45:29.310040 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:31.708813 18606 solver.cpp:218] Iteration 2028 (2.47175 iter/s, 4.85487s/12 iters), loss = 5.27605 +I0410 13:45:31.708863 18606 solver.cpp:237] Train net output #0: loss = 5.27605 (* 1 = 5.27605 loss) +I0410 13:45:31.708873 18606 sgd_solver.cpp:105] Iteration 2028, lr = 0.00669169 +I0410 13:45:36.097605 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2040.caffemodel +I0410 13:45:36.424723 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2040.solverstate +I0410 13:45:36.645347 18606 solver.cpp:330] Iteration 2040, Testing net (#0) +I0410 13:45:36.645377 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:45:40.163497 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:45:40.990979 18606 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:45:40.991029 18606 solver.cpp:397] Test net output #1: loss = 5.28638 (* 1 = 5.28638 loss) +I0410 13:45:41.072881 18606 solver.cpp:218] Iteration 2040 (1.28156 iter/s, 9.36359s/12 iters), loss = 5.28077 +I0410 13:45:41.072934 18606 solver.cpp:237] Train net output #0: loss = 5.28077 (* 1 = 5.28077 loss) +I0410 13:45:41.072947 18606 sgd_solver.cpp:105] Iteration 2040, lr = 0.00667581 +I0410 13:45:45.198143 18606 solver.cpp:218] Iteration 2052 (2.90908 iter/s, 4.12501s/12 iters), loss = 5.28284 +I0410 13:45:45.198195 18606 solver.cpp:237] Train net output #0: loss = 5.28284 (* 1 = 5.28284 loss) +I0410 13:45:45.198207 18606 sgd_solver.cpp:105] Iteration 2052, lr = 0.00665996 +I0410 13:45:45.198554 18606 blocking_queue.cpp:49] Waiting for data +I0410 13:45:50.162179 18606 solver.cpp:218] Iteration 2064 (2.41753 iter/s, 4.96375s/12 iters), loss = 5.27134 +I0410 13:45:50.162238 18606 solver.cpp:237] Train net output #0: loss = 5.27134 (* 1 = 5.27134 loss) +I0410 13:45:50.162250 18606 sgd_solver.cpp:105] Iteration 2064, lr = 0.00664414 +I0410 13:45:55.036386 18606 solver.cpp:218] Iteration 2076 (2.46208 iter/s, 4.87392s/12 iters), loss = 5.27945 +I0410 13:45:55.036434 18606 solver.cpp:237] Train net output #0: loss = 5.27945 (* 1 = 5.27945 loss) +I0410 13:45:55.036446 18606 sgd_solver.cpp:105] Iteration 2076, lr = 0.00662837 +I0410 13:45:59.842056 18606 solver.cpp:218] Iteration 2088 (2.4972 iter/s, 4.80539s/12 iters), loss = 5.2734 +I0410 13:45:59.842113 18606 solver.cpp:237] Train net output #0: loss = 5.2734 (* 1 = 5.2734 loss) +I0410 13:45:59.842124 18606 sgd_solver.cpp:105] Iteration 2088, lr = 0.00661263 +I0410 13:46:04.668133 18606 solver.cpp:218] Iteration 2100 (2.48664 iter/s, 4.82579s/12 iters), loss = 5.2707 +I0410 13:46:04.668175 18606 solver.cpp:237] Train net output #0: loss = 5.2707 (* 1 = 5.2707 loss) +I0410 13:46:04.668184 18606 sgd_solver.cpp:105] Iteration 2100, lr = 0.00659693 +I0410 13:46:09.464921 18606 solver.cpp:218] Iteration 2112 (2.50181 iter/s, 4.79652s/12 iters), loss = 5.28061 +I0410 13:46:09.464994 18606 solver.cpp:237] Train net output #0: loss = 5.28061 (* 1 = 5.28061 loss) +I0410 13:46:09.465004 18606 sgd_solver.cpp:105] Iteration 2112, lr = 0.00658127 +I0410 13:46:14.043661 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:46:14.352869 18606 solver.cpp:218] Iteration 2124 (2.45517 iter/s, 4.88764s/12 iters), loss = 5.26034 +I0410 13:46:14.352928 18606 solver.cpp:237] Train net output #0: loss = 5.26034 (* 1 = 5.26034 loss) +I0410 13:46:14.352941 18606 sgd_solver.cpp:105] Iteration 2124, lr = 0.00656564 +I0410 13:46:19.241557 18606 solver.cpp:218] Iteration 2136 (2.45479 iter/s, 4.8884s/12 iters), loss = 5.27511 +I0410 13:46:19.241600 18606 solver.cpp:237] Train net output #0: loss = 5.27511 (* 1 = 5.27511 loss) +I0410 13:46:19.241607 18606 sgd_solver.cpp:105] Iteration 2136, lr = 0.00655006 +I0410 13:46:21.214627 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2142.caffemodel +I0410 13:46:21.515399 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2142.solverstate +I0410 13:46:21.726166 18606 solver.cpp:330] Iteration 2142, Testing net (#0) +I0410 13:46:21.726184 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:46:25.152887 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:46:26.012284 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:46:26.012315 18606 solver.cpp:397] Test net output #1: loss = 5.2866 (* 1 = 5.2866 loss) +I0410 13:46:27.770421 18606 solver.cpp:218] Iteration 2148 (1.40706 iter/s, 8.52841s/12 iters), loss = 5.28094 +I0410 13:46:27.770489 18606 solver.cpp:237] Train net output #0: loss = 5.28094 (* 1 = 5.28094 loss) +I0410 13:46:27.770507 18606 sgd_solver.cpp:105] Iteration 2148, lr = 0.00653451 +I0410 13:46:32.599968 18606 solver.cpp:218] Iteration 2160 (2.48486 iter/s, 4.82925s/12 iters), loss = 5.28516 +I0410 13:46:32.600024 18606 solver.cpp:237] Train net output #0: loss = 5.28516 (* 1 = 5.28516 loss) +I0410 13:46:32.600037 18606 sgd_solver.cpp:105] Iteration 2160, lr = 0.00651899 +I0410 13:46:37.510458 18606 solver.cpp:218] Iteration 2172 (2.44389 iter/s, 4.9102s/12 iters), loss = 5.27503 +I0410 13:46:37.510512 18606 solver.cpp:237] Train net output #0: loss = 5.27503 (* 1 = 5.27503 loss) +I0410 13:46:37.510524 18606 sgd_solver.cpp:105] Iteration 2172, lr = 0.00650351 +I0410 13:46:42.614193 18606 solver.cpp:218] Iteration 2184 (2.35135 iter/s, 5.10344s/12 iters), loss = 5.27399 +I0410 13:46:42.614341 18606 solver.cpp:237] Train net output #0: loss = 5.27399 (* 1 = 5.27399 loss) +I0410 13:46:42.614356 18606 sgd_solver.cpp:105] Iteration 2184, lr = 0.00648807 +I0410 13:46:47.504549 18606 solver.cpp:218] Iteration 2196 (2.454 iter/s, 4.88998s/12 iters), loss = 5.25293 +I0410 13:46:47.504606 18606 solver.cpp:237] Train net output #0: loss = 5.25293 (* 1 = 5.25293 loss) +I0410 13:46:47.504617 18606 sgd_solver.cpp:105] Iteration 2196, lr = 0.00647267 +I0410 13:46:52.402873 18606 solver.cpp:218] Iteration 2208 (2.44996 iter/s, 4.89804s/12 iters), loss = 5.27068 +I0410 13:46:52.402930 18606 solver.cpp:237] Train net output #0: loss = 5.27068 (* 1 = 5.27068 loss) +I0410 13:46:52.402945 18606 sgd_solver.cpp:105] Iteration 2208, lr = 0.0064573 +I0410 13:46:57.324285 18606 solver.cpp:218] Iteration 2220 (2.43847 iter/s, 4.92112s/12 iters), loss = 5.28365 +I0410 13:46:57.324329 18606 solver.cpp:237] Train net output #0: loss = 5.28365 (* 1 = 5.28365 loss) +I0410 13:46:57.324337 18606 sgd_solver.cpp:105] Iteration 2220, lr = 0.00644197 +I0410 13:46:59.083675 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:02.389840 18606 solver.cpp:218] Iteration 2232 (2.36907 iter/s, 5.06527s/12 iters), loss = 5.28621 +I0410 13:47:02.389887 18606 solver.cpp:237] Train net output #0: loss = 5.28621 (* 1 = 5.28621 loss) +I0410 13:47:02.389899 18606 sgd_solver.cpp:105] Iteration 2232, lr = 0.00642668 +I0410 13:47:06.802521 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2244.caffemodel +I0410 13:47:07.094413 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2244.solverstate +I0410 13:47:07.294268 18606 solver.cpp:330] Iteration 2244, Testing net (#0) +I0410 13:47:07.294287 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:47:10.831626 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:11.736234 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:47:11.736274 18606 solver.cpp:397] Test net output #1: loss = 5.28653 (* 1 = 5.28653 loss) +I0410 13:47:11.819046 18606 solver.cpp:218] Iteration 2244 (1.27271 iter/s, 9.42873s/12 iters), loss = 5.2795 +I0410 13:47:11.819094 18606 solver.cpp:237] Train net output #0: loss = 5.2795 (* 1 = 5.2795 loss) +I0410 13:47:11.819103 18606 sgd_solver.cpp:105] Iteration 2244, lr = 0.00641142 +I0410 13:47:15.882097 18606 solver.cpp:218] Iteration 2256 (2.95362 iter/s, 4.06281s/12 iters), loss = 5.24029 +I0410 13:47:15.882210 18606 solver.cpp:237] Train net output #0: loss = 5.24029 (* 1 = 5.24029 loss) +I0410 13:47:15.882222 18606 sgd_solver.cpp:105] Iteration 2256, lr = 0.0063962 +I0410 13:47:20.789948 18606 solver.cpp:218] Iteration 2268 (2.44523 iter/s, 4.90751s/12 iters), loss = 5.28302 +I0410 13:47:20.790019 18606 solver.cpp:237] Train net output #0: loss = 5.28302 (* 1 = 5.28302 loss) +I0410 13:47:20.790031 18606 sgd_solver.cpp:105] Iteration 2268, lr = 0.00638101 +I0410 13:47:25.690582 18606 solver.cpp:218] Iteration 2280 (2.44881 iter/s, 4.90033s/12 iters), loss = 5.25588 +I0410 13:47:25.690634 18606 solver.cpp:237] Train net output #0: loss = 5.25588 (* 1 = 5.25588 loss) +I0410 13:47:25.690646 18606 sgd_solver.cpp:105] Iteration 2280, lr = 0.00636586 +I0410 13:47:30.524320 18606 solver.cpp:218] Iteration 2292 (2.48269 iter/s, 4.83346s/12 iters), loss = 5.27083 +I0410 13:47:30.524374 18606 solver.cpp:237] Train net output #0: loss = 5.27083 (* 1 = 5.27083 loss) +I0410 13:47:30.524387 18606 sgd_solver.cpp:105] Iteration 2292, lr = 0.00635075 +I0410 13:47:35.407256 18606 solver.cpp:218] Iteration 2304 (2.45768 iter/s, 4.88265s/12 iters), loss = 5.26881 +I0410 13:47:35.407307 18606 solver.cpp:237] Train net output #0: loss = 5.26881 (* 1 = 5.26881 loss) +I0410 13:47:35.407320 18606 sgd_solver.cpp:105] Iteration 2304, lr = 0.00633567 +I0410 13:47:40.303778 18606 solver.cpp:218] Iteration 2316 (2.45086 iter/s, 4.89624s/12 iters), loss = 5.26244 +I0410 13:47:40.303831 18606 solver.cpp:237] Train net output #0: loss = 5.26244 (* 1 = 5.26244 loss) +I0410 13:47:40.303843 18606 sgd_solver.cpp:105] Iteration 2316, lr = 0.00632063 +I0410 13:47:44.202314 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:45.220502 18606 solver.cpp:218] Iteration 2328 (2.44079 iter/s, 4.91644s/12 iters), loss = 5.26004 +I0410 13:47:45.220543 18606 solver.cpp:237] Train net output #0: loss = 5.26004 (* 1 = 5.26004 loss) +I0410 13:47:45.220552 18606 sgd_solver.cpp:105] Iteration 2328, lr = 0.00630562 +I0410 13:47:50.024140 18606 solver.cpp:218] Iteration 2340 (2.49825 iter/s, 4.80337s/12 iters), loss = 5.2908 +I0410 13:47:50.024282 18606 solver.cpp:237] Train net output #0: loss = 5.2908 (* 1 = 5.2908 loss) +I0410 13:47:50.024296 18606 sgd_solver.cpp:105] Iteration 2340, lr = 0.00629065 +I0410 13:47:52.001883 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2346.caffemodel +I0410 13:47:52.330806 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2346.solverstate +I0410 13:47:52.552950 18606 solver.cpp:330] Iteration 2346, Testing net (#0) +I0410 13:47:52.552983 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:47:56.182436 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:47:57.122900 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:47:57.122949 18606 solver.cpp:397] Test net output #1: loss = 5.28692 (* 1 = 5.28692 loss) +I0410 13:47:58.907047 18606 solver.cpp:218] Iteration 2352 (1.35099 iter/s, 8.88236s/12 iters), loss = 5.25795 +I0410 13:47:58.907089 18606 solver.cpp:237] Train net output #0: loss = 5.25795 (* 1 = 5.25795 loss) +I0410 13:47:58.907099 18606 sgd_solver.cpp:105] Iteration 2352, lr = 0.00627571 +I0410 13:48:03.759902 18606 solver.cpp:218] Iteration 2364 (2.47291 iter/s, 4.85258s/12 iters), loss = 5.30565 +I0410 13:48:03.759938 18606 solver.cpp:237] Train net output #0: loss = 5.30565 (* 1 = 5.30565 loss) +I0410 13:48:03.759948 18606 sgd_solver.cpp:105] Iteration 2364, lr = 0.00626081 +I0410 13:48:08.636510 18606 solver.cpp:218] Iteration 2376 (2.46086 iter/s, 4.87634s/12 iters), loss = 5.26432 +I0410 13:48:08.636566 18606 solver.cpp:237] Train net output #0: loss = 5.26432 (* 1 = 5.26432 loss) +I0410 13:48:08.636579 18606 sgd_solver.cpp:105] Iteration 2376, lr = 0.00624595 +I0410 13:48:13.470144 18606 solver.cpp:218] Iteration 2388 (2.48275 iter/s, 4.83335s/12 iters), loss = 5.27443 +I0410 13:48:13.470198 18606 solver.cpp:237] Train net output #0: loss = 5.27443 (* 1 = 5.27443 loss) +I0410 13:48:13.470211 18606 sgd_solver.cpp:105] Iteration 2388, lr = 0.00623112 +I0410 13:48:18.365942 18606 solver.cpp:218] Iteration 2400 (2.45123 iter/s, 4.89551s/12 iters), loss = 5.28244 +I0410 13:48:18.366016 18606 solver.cpp:237] Train net output #0: loss = 5.28244 (* 1 = 5.28244 loss) +I0410 13:48:18.366030 18606 sgd_solver.cpp:105] Iteration 2400, lr = 0.00621633 +I0410 13:48:23.254880 18606 solver.cpp:218] Iteration 2412 (2.45467 iter/s, 4.88863s/12 iters), loss = 5.27092 +I0410 13:48:23.255048 18606 solver.cpp:237] Train net output #0: loss = 5.27092 (* 1 = 5.27092 loss) +I0410 13:48:23.255060 18606 sgd_solver.cpp:105] Iteration 2412, lr = 0.00620157 +I0410 13:48:28.163029 18606 solver.cpp:218] Iteration 2424 (2.44511 iter/s, 4.90775s/12 iters), loss = 5.2758 +I0410 13:48:28.163074 18606 solver.cpp:237] Train net output #0: loss = 5.2758 (* 1 = 5.2758 loss) +I0410 13:48:28.163084 18606 sgd_solver.cpp:105] Iteration 2424, lr = 0.00618684 +I0410 13:48:29.194039 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:48:33.037273 18606 solver.cpp:218] Iteration 2436 (2.46206 iter/s, 4.87396s/12 iters), loss = 5.27648 +I0410 13:48:33.037330 18606 solver.cpp:237] Train net output #0: loss = 5.27648 (* 1 = 5.27648 loss) +I0410 13:48:33.037343 18606 sgd_solver.cpp:105] Iteration 2436, lr = 0.00617215 +I0410 13:48:37.473227 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2448.caffemodel +I0410 13:48:37.781875 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2448.solverstate +I0410 13:48:37.984673 18606 solver.cpp:330] Iteration 2448, Testing net (#0) +I0410 13:48:37.984706 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:48:41.446245 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:48:42.419883 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:48:42.419936 18606 solver.cpp:397] Test net output #1: loss = 5.28664 (* 1 = 5.28664 loss) +I0410 13:48:42.502805 18606 solver.cpp:218] Iteration 2448 (1.26782 iter/s, 9.46504s/12 iters), loss = 5.25444 +I0410 13:48:42.502854 18606 solver.cpp:237] Train net output #0: loss = 5.25444 (* 1 = 5.25444 loss) +I0410 13:48:42.502866 18606 sgd_solver.cpp:105] Iteration 2448, lr = 0.0061575 +I0410 13:48:46.680320 18606 solver.cpp:218] Iteration 2460 (2.87269 iter/s, 4.17727s/12 iters), loss = 5.26394 +I0410 13:48:46.680359 18606 solver.cpp:237] Train net output #0: loss = 5.26394 (* 1 = 5.26394 loss) +I0410 13:48:46.680368 18606 sgd_solver.cpp:105] Iteration 2460, lr = 0.00614288 +I0410 13:48:51.543390 18606 solver.cpp:218] Iteration 2472 (2.46772 iter/s, 4.8628s/12 iters), loss = 5.26721 +I0410 13:48:51.543452 18606 solver.cpp:237] Train net output #0: loss = 5.26721 (* 1 = 5.26721 loss) +I0410 13:48:51.543464 18606 sgd_solver.cpp:105] Iteration 2472, lr = 0.0061283 +I0410 13:48:56.364346 18606 solver.cpp:218] Iteration 2484 (2.48928 iter/s, 4.82066s/12 iters), loss = 5.27463 +I0410 13:48:56.364471 18606 solver.cpp:237] Train net output #0: loss = 5.27463 (* 1 = 5.27463 loss) +I0410 13:48:56.364488 18606 sgd_solver.cpp:105] Iteration 2484, lr = 0.00611375 +I0410 13:49:01.148653 18606 solver.cpp:218] Iteration 2496 (2.50838 iter/s, 4.78396s/12 iters), loss = 5.26919 +I0410 13:49:01.148703 18606 solver.cpp:237] Train net output #0: loss = 5.26919 (* 1 = 5.26919 loss) +I0410 13:49:01.148715 18606 sgd_solver.cpp:105] Iteration 2496, lr = 0.00609923 +I0410 13:49:06.007611 18606 solver.cpp:218] Iteration 2508 (2.46981 iter/s, 4.85867s/12 iters), loss = 5.28992 +I0410 13:49:06.007673 18606 solver.cpp:237] Train net output #0: loss = 5.28992 (* 1 = 5.28992 loss) +I0410 13:49:06.007686 18606 sgd_solver.cpp:105] Iteration 2508, lr = 0.00608475 +I0410 13:49:10.845281 18606 solver.cpp:218] Iteration 2520 (2.48068 iter/s, 4.83738s/12 iters), loss = 5.27734 +I0410 13:49:10.845331 18606 solver.cpp:237] Train net output #0: loss = 5.27734 (* 1 = 5.27734 loss) +I0410 13:49:10.845341 18606 sgd_solver.cpp:105] Iteration 2520, lr = 0.0060703 +I0410 13:49:14.034152 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:15.755359 18606 solver.cpp:218] Iteration 2532 (2.44409 iter/s, 4.90979s/12 iters), loss = 5.28345 +I0410 13:49:15.755403 18606 solver.cpp:237] Train net output #0: loss = 5.28345 (* 1 = 5.28345 loss) +I0410 13:49:15.755414 18606 sgd_solver.cpp:105] Iteration 2532, lr = 0.00605589 +I0410 13:49:20.585090 18606 solver.cpp:218] Iteration 2544 (2.48475 iter/s, 4.82946s/12 iters), loss = 5.27455 +I0410 13:49:20.585146 18606 solver.cpp:237] Train net output #0: loss = 5.27455 (* 1 = 5.27455 loss) +I0410 13:49:20.585158 18606 sgd_solver.cpp:105] Iteration 2544, lr = 0.00604151 +I0410 13:49:22.555240 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2550.caffemodel +I0410 13:49:23.052280 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2550.solverstate +I0410 13:49:23.257458 18606 solver.cpp:330] Iteration 2550, Testing net (#0) +I0410 13:49:23.257484 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:49:26.574880 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:49:27.592371 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:49:27.592402 18606 solver.cpp:397] Test net output #1: loss = 5.28659 (* 1 = 5.28659 loss) +I0410 13:49:29.466490 18606 solver.cpp:218] Iteration 2556 (1.35121 iter/s, 8.88094s/12 iters), loss = 5.27975 +I0410 13:49:29.466536 18606 solver.cpp:237] Train net output #0: loss = 5.27975 (* 1 = 5.27975 loss) +I0410 13:49:29.466544 18606 sgd_solver.cpp:105] Iteration 2556, lr = 0.00602717 +I0410 13:49:34.283860 18606 solver.cpp:218] Iteration 2568 (2.49113 iter/s, 4.81709s/12 iters), loss = 5.28757 +I0410 13:49:34.283918 18606 solver.cpp:237] Train net output #0: loss = 5.28757 (* 1 = 5.28757 loss) +I0410 13:49:34.283931 18606 sgd_solver.cpp:105] Iteration 2568, lr = 0.00601286 +I0410 13:49:39.153841 18606 solver.cpp:218] Iteration 2580 (2.46423 iter/s, 4.86968s/12 iters), loss = 5.26716 +I0410 13:49:39.153901 18606 solver.cpp:237] Train net output #0: loss = 5.26716 (* 1 = 5.26716 loss) +I0410 13:49:39.153913 18606 sgd_solver.cpp:105] Iteration 2580, lr = 0.00599858 +I0410 13:49:43.977442 18606 solver.cpp:218] Iteration 2592 (2.48792 iter/s, 4.82331s/12 iters), loss = 5.28773 +I0410 13:49:43.977492 18606 solver.cpp:237] Train net output #0: loss = 5.28773 (* 1 = 5.28773 loss) +I0410 13:49:43.977504 18606 sgd_solver.cpp:105] Iteration 2592, lr = 0.00598434 +I0410 13:49:48.914371 18606 solver.cpp:218] Iteration 2604 (2.4308 iter/s, 4.93665s/12 iters), loss = 5.2589 +I0410 13:49:48.914422 18606 solver.cpp:237] Train net output #0: loss = 5.2589 (* 1 = 5.2589 loss) +I0410 13:49:48.914434 18606 sgd_solver.cpp:105] Iteration 2604, lr = 0.00597013 +I0410 13:49:53.831815 18606 solver.cpp:218] Iteration 2616 (2.44043 iter/s, 4.91716s/12 iters), loss = 5.2784 +I0410 13:49:53.831868 18606 solver.cpp:237] Train net output #0: loss = 5.2784 (* 1 = 5.2784 loss) +I0410 13:49:53.831879 18606 sgd_solver.cpp:105] Iteration 2616, lr = 0.00595596 +I0410 13:49:58.729620 18606 solver.cpp:218] Iteration 2628 (2.45022 iter/s, 4.89752s/12 iters), loss = 5.27931 +I0410 13:49:58.729703 18606 solver.cpp:237] Train net output #0: loss = 5.27931 (* 1 = 5.27931 loss) +I0410 13:49:58.729714 18606 sgd_solver.cpp:105] Iteration 2628, lr = 0.00594182 +I0410 13:49:59.148990 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:03.693575 18606 solver.cpp:218] Iteration 2640 (2.41758 iter/s, 4.96364s/12 iters), loss = 5.27964 +I0410 13:50:03.693622 18606 solver.cpp:237] Train net output #0: loss = 5.27964 (* 1 = 5.27964 loss) +I0410 13:50:03.693632 18606 sgd_solver.cpp:105] Iteration 2640, lr = 0.00592771 +I0410 13:50:08.043200 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2652.caffemodel +I0410 13:50:08.372515 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2652.solverstate +I0410 13:50:08.592008 18606 solver.cpp:330] Iteration 2652, Testing net (#0) +I0410 13:50:08.592038 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:50:11.934973 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:13.074043 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:50:13.074092 18606 solver.cpp:397] Test net output #1: loss = 5.28683 (* 1 = 5.28683 loss) +I0410 13:50:13.157127 18606 solver.cpp:218] Iteration 2652 (1.26809 iter/s, 9.46307s/12 iters), loss = 5.27096 +I0410 13:50:13.157181 18606 solver.cpp:237] Train net output #0: loss = 5.27096 (* 1 = 5.27096 loss) +I0410 13:50:13.157193 18606 sgd_solver.cpp:105] Iteration 2652, lr = 0.00591364 +I0410 13:50:17.240898 18606 solver.cpp:218] Iteration 2664 (2.93864 iter/s, 4.08352s/12 iters), loss = 5.28226 +I0410 13:50:17.240958 18606 solver.cpp:237] Train net output #0: loss = 5.28226 (* 1 = 5.28226 loss) +I0410 13:50:17.240973 18606 sgd_solver.cpp:105] Iteration 2664, lr = 0.0058996 +I0410 13:50:22.152899 18606 solver.cpp:218] Iteration 2676 (2.44314 iter/s, 4.91171s/12 iters), loss = 5.26839 +I0410 13:50:22.152952 18606 solver.cpp:237] Train net output #0: loss = 5.26839 (* 1 = 5.26839 loss) +I0410 13:50:22.152963 18606 sgd_solver.cpp:105] Iteration 2676, lr = 0.00588559 +I0410 13:50:27.045904 18606 solver.cpp:218] Iteration 2688 (2.45262 iter/s, 4.89272s/12 iters), loss = 5.25718 +I0410 13:50:27.045975 18606 solver.cpp:237] Train net output #0: loss = 5.25718 (* 1 = 5.25718 loss) +I0410 13:50:27.045989 18606 sgd_solver.cpp:105] Iteration 2688, lr = 0.00587162 +I0410 13:50:31.945003 18606 solver.cpp:218] Iteration 2700 (2.44957 iter/s, 4.89881s/12 iters), loss = 5.28238 +I0410 13:50:31.945173 18606 solver.cpp:237] Train net output #0: loss = 5.28238 (* 1 = 5.28238 loss) +I0410 13:50:31.945188 18606 sgd_solver.cpp:105] Iteration 2700, lr = 0.00585768 +I0410 13:50:37.139981 18606 solver.cpp:218] Iteration 2712 (2.31011 iter/s, 5.19456s/12 iters), loss = 5.28324 +I0410 13:50:37.140039 18606 solver.cpp:237] Train net output #0: loss = 5.28324 (* 1 = 5.28324 loss) +I0410 13:50:37.140054 18606 sgd_solver.cpp:105] Iteration 2712, lr = 0.00584377 +I0410 13:50:41.956775 18606 solver.cpp:218] Iteration 2724 (2.49141 iter/s, 4.81656s/12 iters), loss = 5.2579 +I0410 13:50:41.956823 18606 solver.cpp:237] Train net output #0: loss = 5.2579 (* 1 = 5.2579 loss) +I0410 13:50:41.956831 18606 sgd_solver.cpp:105] Iteration 2724, lr = 0.0058299 +I0410 13:50:44.428074 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:46.771641 18606 solver.cpp:218] Iteration 2736 (2.4924 iter/s, 4.81463s/12 iters), loss = 5.27978 +I0410 13:50:46.771703 18606 solver.cpp:237] Train net output #0: loss = 5.27978 (* 1 = 5.27978 loss) +I0410 13:50:46.771715 18606 sgd_solver.cpp:105] Iteration 2736, lr = 0.00581605 +I0410 13:50:51.564422 18606 solver.cpp:218] Iteration 2748 (2.50389 iter/s, 4.79254s/12 iters), loss = 5.2778 +I0410 13:50:51.564482 18606 solver.cpp:237] Train net output #0: loss = 5.2778 (* 1 = 5.2778 loss) +I0410 13:50:51.564496 18606 sgd_solver.cpp:105] Iteration 2748, lr = 0.00580225 +I0410 13:50:53.516675 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2754.caffemodel +I0410 13:50:53.843427 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2754.solverstate +I0410 13:50:54.057921 18606 solver.cpp:330] Iteration 2754, Testing net (#0) +I0410 13:50:54.057940 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:50:56.682636 18606 blocking_queue.cpp:49] Waiting for data +I0410 13:50:57.280117 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:50:58.755046 18606 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:50:58.755095 18606 solver.cpp:397] Test net output #1: loss = 5.28665 (* 1 = 5.28665 loss) +I0410 13:51:00.556427 18606 solver.cpp:218] Iteration 2760 (1.33457 iter/s, 8.99163s/12 iters), loss = 5.27992 +I0410 13:51:00.556471 18606 solver.cpp:237] Train net output #0: loss = 5.27992 (* 1 = 5.27992 loss) +I0410 13:51:00.556480 18606 sgd_solver.cpp:105] Iteration 2760, lr = 0.00578847 +I0410 13:51:05.375870 18606 solver.cpp:218] Iteration 2772 (2.49003 iter/s, 4.81921s/12 iters), loss = 5.27658 +I0410 13:51:05.376001 18606 solver.cpp:237] Train net output #0: loss = 5.27658 (* 1 = 5.27658 loss) +I0410 13:51:05.376015 18606 sgd_solver.cpp:105] Iteration 2772, lr = 0.00577473 +I0410 13:51:10.186556 18606 solver.cpp:218] Iteration 2784 (2.49461 iter/s, 4.81038s/12 iters), loss = 5.27678 +I0410 13:51:10.186612 18606 solver.cpp:237] Train net output #0: loss = 5.27678 (* 1 = 5.27678 loss) +I0410 13:51:10.186625 18606 sgd_solver.cpp:105] Iteration 2784, lr = 0.00576102 +I0410 13:51:15.134459 18606 solver.cpp:218] Iteration 2796 (2.42539 iter/s, 4.94766s/12 iters), loss = 5.27292 +I0410 13:51:15.134505 18606 solver.cpp:237] Train net output #0: loss = 5.27292 (* 1 = 5.27292 loss) +I0410 13:51:15.134512 18606 sgd_solver.cpp:105] Iteration 2796, lr = 0.00574734 +I0410 13:51:19.887550 18606 solver.cpp:218] Iteration 2808 (2.52479 iter/s, 4.75286s/12 iters), loss = 5.26401 +I0410 13:51:19.887599 18606 solver.cpp:237] Train net output #0: loss = 5.26401 (* 1 = 5.26401 loss) +I0410 13:51:19.887610 18606 sgd_solver.cpp:105] Iteration 2808, lr = 0.00573369 +I0410 13:51:24.707245 18606 solver.cpp:218] Iteration 2820 (2.48991 iter/s, 4.81946s/12 iters), loss = 5.27641 +I0410 13:51:24.707302 18606 solver.cpp:237] Train net output #0: loss = 5.27641 (* 1 = 5.27641 loss) +I0410 13:51:24.707314 18606 sgd_solver.cpp:105] Iteration 2820, lr = 0.00572008 +I0410 13:51:29.312268 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:51:29.611104 18606 solver.cpp:218] Iteration 2832 (2.44717 iter/s, 4.90362s/12 iters), loss = 5.26147 +I0410 13:51:29.611148 18606 solver.cpp:237] Train net output #0: loss = 5.26147 (* 1 = 5.26147 loss) +I0410 13:51:29.611157 18606 sgd_solver.cpp:105] Iteration 2832, lr = 0.0057065 +I0410 13:51:34.555950 18606 solver.cpp:218] Iteration 2844 (2.42689 iter/s, 4.94461s/12 iters), loss = 5.26933 +I0410 13:51:34.556007 18606 solver.cpp:237] Train net output #0: loss = 5.26933 (* 1 = 5.26933 loss) +I0410 13:51:34.556016 18606 sgd_solver.cpp:105] Iteration 2844, lr = 0.00569295 +I0410 13:51:38.891683 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2856.caffemodel +I0410 13:51:39.233470 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2856.solverstate +I0410 13:51:39.445760 18606 solver.cpp:330] Iteration 2856, Testing net (#0) +I0410 13:51:39.445786 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:51:42.625252 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:51:43.761266 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:51:43.761314 18606 solver.cpp:397] Test net output #1: loss = 5.28693 (* 1 = 5.28693 loss) +I0410 13:51:43.844250 18606 solver.cpp:218] Iteration 2856 (1.292 iter/s, 9.2879s/12 iters), loss = 5.29 +I0410 13:51:43.844301 18606 solver.cpp:237] Train net output #0: loss = 5.29 (* 1 = 5.29 loss) +I0410 13:51:43.844313 18606 sgd_solver.cpp:105] Iteration 2856, lr = 0.00567944 +I0410 13:51:47.981176 18606 solver.cpp:218] Iteration 2868 (2.90085 iter/s, 4.13671s/12 iters), loss = 5.27988 +I0410 13:51:47.981230 18606 solver.cpp:237] Train net output #0: loss = 5.27988 (* 1 = 5.27988 loss) +I0410 13:51:47.981242 18606 sgd_solver.cpp:105] Iteration 2868, lr = 0.00566595 +I0410 13:51:52.923797 18606 solver.cpp:218] Iteration 2880 (2.42798 iter/s, 4.94238s/12 iters), loss = 5.28076 +I0410 13:51:52.923851 18606 solver.cpp:237] Train net output #0: loss = 5.28076 (* 1 = 5.28076 loss) +I0410 13:51:52.923859 18606 sgd_solver.cpp:105] Iteration 2880, lr = 0.0056525 +I0410 13:51:57.719012 18606 solver.cpp:218] Iteration 2892 (2.50262 iter/s, 4.79498s/12 iters), loss = 5.27383 +I0410 13:51:57.719065 18606 solver.cpp:237] Train net output #0: loss = 5.27383 (* 1 = 5.27383 loss) +I0410 13:51:57.719076 18606 sgd_solver.cpp:105] Iteration 2892, lr = 0.00563908 +I0410 13:52:02.673928 18606 solver.cpp:218] Iteration 2904 (2.42196 iter/s, 4.95467s/12 iters), loss = 5.25398 +I0410 13:52:02.673995 18606 solver.cpp:237] Train net output #0: loss = 5.25398 (* 1 = 5.25398 loss) +I0410 13:52:02.674005 18606 sgd_solver.cpp:105] Iteration 2904, lr = 0.00562569 +I0410 13:52:07.719029 18606 solver.cpp:218] Iteration 2916 (2.37867 iter/s, 5.04485s/12 iters), loss = 5.27059 +I0410 13:52:07.719071 18606 solver.cpp:237] Train net output #0: loss = 5.27059 (* 1 = 5.27059 loss) +I0410 13:52:07.719081 18606 sgd_solver.cpp:105] Iteration 2916, lr = 0.00561233 +I0410 13:52:12.520432 18606 solver.cpp:218] Iteration 2928 (2.49939 iter/s, 4.80117s/12 iters), loss = 5.28078 +I0410 13:52:12.523978 18606 solver.cpp:237] Train net output #0: loss = 5.28078 (* 1 = 5.28078 loss) +I0410 13:52:12.523993 18606 sgd_solver.cpp:105] Iteration 2928, lr = 0.00559901 +I0410 13:52:14.277045 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:52:17.308035 18606 solver.cpp:218] Iteration 2940 (2.50842 iter/s, 4.78389s/12 iters), loss = 5.28398 +I0410 13:52:17.308068 18606 solver.cpp:237] Train net output #0: loss = 5.28398 (* 1 = 5.28398 loss) +I0410 13:52:17.308076 18606 sgd_solver.cpp:105] Iteration 2940, lr = 0.00558572 +I0410 13:52:22.157748 18606 solver.cpp:218] Iteration 2952 (2.47449 iter/s, 4.84949s/12 iters), loss = 5.28095 +I0410 13:52:22.157793 18606 solver.cpp:237] Train net output #0: loss = 5.28095 (* 1 = 5.28095 loss) +I0410 13:52:22.157802 18606 sgd_solver.cpp:105] Iteration 2952, lr = 0.00557245 +I0410 13:52:24.133145 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_2958.caffemodel +I0410 13:52:24.438663 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_2958.solverstate +I0410 13:52:24.745038 18606 solver.cpp:330] Iteration 2958, Testing net (#0) +I0410 13:52:24.745069 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:52:27.996328 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:52:29.176324 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:52:29.176365 18606 solver.cpp:397] Test net output #1: loss = 5.28661 (* 1 = 5.28661 loss) +I0410 13:52:30.976379 18606 solver.cpp:218] Iteration 2964 (1.36081 iter/s, 8.81826s/12 iters), loss = 5.24267 +I0410 13:52:30.976423 18606 solver.cpp:237] Train net output #0: loss = 5.24267 (* 1 = 5.24267 loss) +I0410 13:52:30.976430 18606 sgd_solver.cpp:105] Iteration 2964, lr = 0.00555922 +I0410 13:52:35.794276 18606 solver.cpp:218] Iteration 2976 (2.49083 iter/s, 4.81767s/12 iters), loss = 5.28312 +I0410 13:52:35.794327 18606 solver.cpp:237] Train net output #0: loss = 5.28312 (* 1 = 5.28312 loss) +I0410 13:52:35.794337 18606 sgd_solver.cpp:105] Iteration 2976, lr = 0.00554603 +I0410 13:52:40.709540 18606 solver.cpp:218] Iteration 2988 (2.4415 iter/s, 4.91502s/12 iters), loss = 5.26476 +I0410 13:52:40.709599 18606 solver.cpp:237] Train net output #0: loss = 5.26476 (* 1 = 5.26476 loss) +I0410 13:52:40.709611 18606 sgd_solver.cpp:105] Iteration 2988, lr = 0.00553286 +I0410 13:52:45.609686 18606 solver.cpp:218] Iteration 3000 (2.44903 iter/s, 4.8999s/12 iters), loss = 5.26796 +I0410 13:52:45.609819 18606 solver.cpp:237] Train net output #0: loss = 5.26796 (* 1 = 5.26796 loss) +I0410 13:52:45.609833 18606 sgd_solver.cpp:105] Iteration 3000, lr = 0.00551972 +I0410 13:52:50.497213 18606 solver.cpp:218] Iteration 3012 (2.45539 iter/s, 4.8872s/12 iters), loss = 5.27279 +I0410 13:52:50.497273 18606 solver.cpp:237] Train net output #0: loss = 5.27279 (* 1 = 5.27279 loss) +I0410 13:52:50.497285 18606 sgd_solver.cpp:105] Iteration 3012, lr = 0.00550662 +I0410 13:52:55.396157 18606 solver.cpp:218] Iteration 3024 (2.44963 iter/s, 4.89869s/12 iters), loss = 5.25795 +I0410 13:52:55.396211 18606 solver.cpp:237] Train net output #0: loss = 5.25795 (* 1 = 5.25795 loss) +I0410 13:52:55.396222 18606 sgd_solver.cpp:105] Iteration 3024, lr = 0.00549354 +I0410 13:52:59.222633 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:00.226461 18606 solver.cpp:218] Iteration 3036 (2.48444 iter/s, 4.83006s/12 iters), loss = 5.257 +I0410 13:53:00.226505 18606 solver.cpp:237] Train net output #0: loss = 5.257 (* 1 = 5.257 loss) +I0410 13:53:00.226513 18606 sgd_solver.cpp:105] Iteration 3036, lr = 0.0054805 +I0410 13:53:05.116634 18606 solver.cpp:218] Iteration 3048 (2.45402 iter/s, 4.88993s/12 iters), loss = 5.29353 +I0410 13:53:05.116689 18606 solver.cpp:237] Train net output #0: loss = 5.29353 (* 1 = 5.29353 loss) +I0410 13:53:05.116700 18606 sgd_solver.cpp:105] Iteration 3048, lr = 0.00546749 +I0410 13:53:09.578119 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3060.caffemodel +I0410 13:53:09.892972 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3060.solverstate +I0410 13:53:10.104571 18606 solver.cpp:330] Iteration 3060, Testing net (#0) +I0410 13:53:10.104596 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:53:13.241524 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:14.454118 18606 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 13:53:14.454166 18606 solver.cpp:397] Test net output #1: loss = 5.28642 (* 1 = 5.28642 loss) +I0410 13:53:14.537500 18606 solver.cpp:218] Iteration 3060 (1.27382 iter/s, 9.42045s/12 iters), loss = 5.25724 +I0410 13:53:14.537550 18606 solver.cpp:237] Train net output #0: loss = 5.25724 (* 1 = 5.25724 loss) +I0410 13:53:14.537560 18606 sgd_solver.cpp:105] Iteration 3060, lr = 0.00545451 +I0410 13:53:18.701100 18606 solver.cpp:218] Iteration 3072 (2.88228 iter/s, 4.16338s/12 iters), loss = 5.30564 +I0410 13:53:18.701280 18606 solver.cpp:237] Train net output #0: loss = 5.30564 (* 1 = 5.30564 loss) +I0410 13:53:18.701293 18606 sgd_solver.cpp:105] Iteration 3072, lr = 0.00544156 +I0410 13:53:23.606123 18606 solver.cpp:218] Iteration 3084 (2.44666 iter/s, 4.90465s/12 iters), loss = 5.27656 +I0410 13:53:23.606182 18606 solver.cpp:237] Train net output #0: loss = 5.27656 (* 1 = 5.27656 loss) +I0410 13:53:23.606194 18606 sgd_solver.cpp:105] Iteration 3084, lr = 0.00542864 +I0410 13:53:28.396327 18606 solver.cpp:218] Iteration 3096 (2.50524 iter/s, 4.78996s/12 iters), loss = 5.27349 +I0410 13:53:28.396374 18606 solver.cpp:237] Train net output #0: loss = 5.27349 (* 1 = 5.27349 loss) +I0410 13:53:28.396384 18606 sgd_solver.cpp:105] Iteration 3096, lr = 0.00541575 +I0410 13:53:33.209233 18606 solver.cpp:218] Iteration 3108 (2.49342 iter/s, 4.81266s/12 iters), loss = 5.27901 +I0410 13:53:33.209275 18606 solver.cpp:237] Train net output #0: loss = 5.27901 (* 1 = 5.27901 loss) +I0410 13:53:33.209282 18606 sgd_solver.cpp:105] Iteration 3108, lr = 0.00540289 +I0410 13:53:38.040050 18606 solver.cpp:218] Iteration 3120 (2.48418 iter/s, 4.83058s/12 iters), loss = 5.26638 +I0410 13:53:38.040107 18606 solver.cpp:237] Train net output #0: loss = 5.26638 (* 1 = 5.26638 loss) +I0410 13:53:38.040118 18606 sgd_solver.cpp:105] Iteration 3120, lr = 0.00539006 +I0410 13:53:42.885560 18606 solver.cpp:218] Iteration 3132 (2.47665 iter/s, 4.84526s/12 iters), loss = 5.27493 +I0410 13:53:42.885605 18606 solver.cpp:237] Train net output #0: loss = 5.27493 (* 1 = 5.27493 loss) +I0410 13:53:42.885614 18606 sgd_solver.cpp:105] Iteration 3132, lr = 0.00537727 +I0410 13:53:43.964184 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:47.773108 18606 solver.cpp:218] Iteration 3144 (2.45534 iter/s, 4.8873s/12 iters), loss = 5.28097 +I0410 13:53:47.773149 18606 solver.cpp:237] Train net output #0: loss = 5.28097 (* 1 = 5.28097 loss) +I0410 13:53:47.773159 18606 sgd_solver.cpp:105] Iteration 3144, lr = 0.0053645 +I0410 13:53:52.532155 18606 solver.cpp:218] Iteration 3156 (2.52164 iter/s, 4.75881s/12 iters), loss = 5.24982 +I0410 13:53:52.532258 18606 solver.cpp:237] Train net output #0: loss = 5.24982 (* 1 = 5.24982 loss) +I0410 13:53:52.532267 18606 sgd_solver.cpp:105] Iteration 3156, lr = 0.00535176 +I0410 13:53:54.509057 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3162.caffemodel +I0410 13:53:54.796236 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3162.solverstate +I0410 13:53:54.995463 18606 solver.cpp:330] Iteration 3162, Testing net (#0) +I0410 13:53:54.995481 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:53:58.097455 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:53:59.356933 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:53:59.356982 18606 solver.cpp:397] Test net output #1: loss = 5.28657 (* 1 = 5.28657 loss) +I0410 13:54:01.226655 18606 solver.cpp:218] Iteration 3168 (1.38025 iter/s, 8.69406s/12 iters), loss = 5.26476 +I0410 13:54:01.226704 18606 solver.cpp:237] Train net output #0: loss = 5.26476 (* 1 = 5.26476 loss) +I0410 13:54:01.226714 18606 sgd_solver.cpp:105] Iteration 3168, lr = 0.00533906 +I0410 13:54:06.033515 18606 solver.cpp:218] Iteration 3180 (2.49656 iter/s, 4.80661s/12 iters), loss = 5.27326 +I0410 13:54:06.033569 18606 solver.cpp:237] Train net output #0: loss = 5.27326 (* 1 = 5.27326 loss) +I0410 13:54:06.033582 18606 sgd_solver.cpp:105] Iteration 3180, lr = 0.00532638 +I0410 13:54:10.811702 18606 solver.cpp:218] Iteration 3192 (2.51154 iter/s, 4.77794s/12 iters), loss = 5.27821 +I0410 13:54:10.811750 18606 solver.cpp:237] Train net output #0: loss = 5.27821 (* 1 = 5.27821 loss) +I0410 13:54:10.811760 18606 sgd_solver.cpp:105] Iteration 3192, lr = 0.00531374 +I0410 13:54:15.624073 18606 solver.cpp:218] Iteration 3204 (2.4937 iter/s, 4.81213s/12 iters), loss = 5.26109 +I0410 13:54:15.624125 18606 solver.cpp:237] Train net output #0: loss = 5.26109 (* 1 = 5.26109 loss) +I0410 13:54:15.624136 18606 sgd_solver.cpp:105] Iteration 3204, lr = 0.00530112 +I0410 13:54:20.454870 18606 solver.cpp:218] Iteration 3216 (2.48419 iter/s, 4.83055s/12 iters), loss = 5.2867 +I0410 13:54:20.454919 18606 solver.cpp:237] Train net output #0: loss = 5.2867 (* 1 = 5.2867 loss) +I0410 13:54:20.454931 18606 sgd_solver.cpp:105] Iteration 3216, lr = 0.00528853 +I0410 13:54:25.306784 18606 solver.cpp:218] Iteration 3228 (2.47338 iter/s, 4.85167s/12 iters), loss = 5.27848 +I0410 13:54:25.306912 18606 solver.cpp:237] Train net output #0: loss = 5.27848 (* 1 = 5.27848 loss) +I0410 13:54:25.306924 18606 sgd_solver.cpp:105] Iteration 3228, lr = 0.00527598 +I0410 13:54:28.427166 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:54:30.106645 18606 solver.cpp:218] Iteration 3240 (2.50024 iter/s, 4.79954s/12 iters), loss = 5.28399 +I0410 13:54:30.106693 18606 solver.cpp:237] Train net output #0: loss = 5.28399 (* 1 = 5.28399 loss) +I0410 13:54:30.106704 18606 sgd_solver.cpp:105] Iteration 3240, lr = 0.00526345 +I0410 13:54:34.996392 18606 solver.cpp:218] Iteration 3252 (2.45424 iter/s, 4.8895s/12 iters), loss = 5.26868 +I0410 13:54:34.996433 18606 solver.cpp:237] Train net output #0: loss = 5.26868 (* 1 = 5.26868 loss) +I0410 13:54:34.996443 18606 sgd_solver.cpp:105] Iteration 3252, lr = 0.00525095 +I0410 13:54:39.461592 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3264.caffemodel +I0410 13:54:39.911367 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3264.solverstate +I0410 13:54:40.152967 18606 solver.cpp:330] Iteration 3264, Testing net (#0) +I0410 13:54:40.152997 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:54:43.422246 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:54:44.717797 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:54:44.717847 18606 solver.cpp:397] Test net output #1: loss = 5.28711 (* 1 = 5.28711 loss) +I0410 13:54:44.800709 18606 solver.cpp:218] Iteration 3264 (1.224 iter/s, 9.80389s/12 iters), loss = 5.27487 +I0410 13:54:44.800760 18606 solver.cpp:237] Train net output #0: loss = 5.27487 (* 1 = 5.27487 loss) +I0410 13:54:44.800770 18606 sgd_solver.cpp:105] Iteration 3264, lr = 0.00523849 +I0410 13:54:48.914902 18606 solver.cpp:218] Iteration 3276 (2.91689 iter/s, 4.11398s/12 iters), loss = 5.28584 +I0410 13:54:48.914947 18606 solver.cpp:237] Train net output #0: loss = 5.28584 (* 1 = 5.28584 loss) +I0410 13:54:48.914956 18606 sgd_solver.cpp:105] Iteration 3276, lr = 0.00522605 +I0410 13:54:53.811600 18606 solver.cpp:218] Iteration 3288 (2.45076 iter/s, 4.89645s/12 iters), loss = 5.25935 +I0410 13:54:53.811652 18606 solver.cpp:237] Train net output #0: loss = 5.25935 (* 1 = 5.25935 loss) +I0410 13:54:53.811663 18606 sgd_solver.cpp:105] Iteration 3288, lr = 0.00521364 +I0410 13:54:58.637887 18606 solver.cpp:218] Iteration 3300 (2.48651 iter/s, 4.82604s/12 iters), loss = 5.2857 +I0410 13:54:58.638038 18606 solver.cpp:237] Train net output #0: loss = 5.2857 (* 1 = 5.2857 loss) +I0410 13:54:58.638052 18606 sgd_solver.cpp:105] Iteration 3300, lr = 0.00520126 +I0410 13:55:03.483773 18606 solver.cpp:218] Iteration 3312 (2.4765 iter/s, 4.84554s/12 iters), loss = 5.25628 +I0410 13:55:03.483824 18606 solver.cpp:237] Train net output #0: loss = 5.25628 (* 1 = 5.25628 loss) +I0410 13:55:03.483834 18606 sgd_solver.cpp:105] Iteration 3312, lr = 0.00518892 +I0410 13:55:08.346678 18606 solver.cpp:218] Iteration 3324 (2.46779 iter/s, 4.86266s/12 iters), loss = 5.28192 +I0410 13:55:08.346733 18606 solver.cpp:237] Train net output #0: loss = 5.28192 (* 1 = 5.28192 loss) +I0410 13:55:08.346745 18606 sgd_solver.cpp:105] Iteration 3324, lr = 0.0051766 +I0410 13:55:13.239187 18606 solver.cpp:218] Iteration 3336 (2.45286 iter/s, 4.89225s/12 iters), loss = 5.27505 +I0410 13:55:13.239239 18606 solver.cpp:237] Train net output #0: loss = 5.27505 (* 1 = 5.27505 loss) +I0410 13:55:13.239251 18606 sgd_solver.cpp:105] Iteration 3336, lr = 0.00516431 +I0410 13:55:13.692978 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:55:18.145941 18606 solver.cpp:218] Iteration 3348 (2.44573 iter/s, 4.9065s/12 iters), loss = 5.2796 +I0410 13:55:18.145996 18606 solver.cpp:237] Train net output #0: loss = 5.2796 (* 1 = 5.2796 loss) +I0410 13:55:18.146005 18606 sgd_solver.cpp:105] Iteration 3348, lr = 0.00515204 +I0410 13:55:23.025136 18606 solver.cpp:218] Iteration 3360 (2.45955 iter/s, 4.87894s/12 iters), loss = 5.2678 +I0410 13:55:23.025192 18606 solver.cpp:237] Train net output #0: loss = 5.2678 (* 1 = 5.2678 loss) +I0410 13:55:23.025203 18606 sgd_solver.cpp:105] Iteration 3360, lr = 0.00513981 +I0410 13:55:25.102628 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3366.caffemodel +I0410 13:55:25.414201 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3366.solverstate +I0410 13:55:25.644984 18606 solver.cpp:330] Iteration 3366, Testing net (#0) +I0410 13:55:25.645005 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:55:28.737296 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:55:30.070924 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:55:30.070979 18606 solver.cpp:397] Test net output #1: loss = 5.2868 (* 1 = 5.2868 loss) +I0410 13:55:31.957036 18606 solver.cpp:218] Iteration 3372 (1.34356 iter/s, 8.93149s/12 iters), loss = 5.28743 +I0410 13:55:31.957080 18606 solver.cpp:237] Train net output #0: loss = 5.28743 (* 1 = 5.28743 loss) +I0410 13:55:31.957089 18606 sgd_solver.cpp:105] Iteration 3372, lr = 0.00512761 +I0410 13:55:36.814507 18606 solver.cpp:218] Iteration 3384 (2.47055 iter/s, 4.85722s/12 iters), loss = 5.26311 +I0410 13:55:36.814568 18606 solver.cpp:237] Train net output #0: loss = 5.26311 (* 1 = 5.26311 loss) +I0410 13:55:36.814580 18606 sgd_solver.cpp:105] Iteration 3384, lr = 0.00511544 +I0410 13:55:41.657147 18606 solver.cpp:218] Iteration 3396 (2.47812 iter/s, 4.84238s/12 iters), loss = 5.26395 +I0410 13:55:41.657193 18606 solver.cpp:237] Train net output #0: loss = 5.26395 (* 1 = 5.26395 loss) +I0410 13:55:41.657204 18606 sgd_solver.cpp:105] Iteration 3396, lr = 0.00510329 +I0410 13:55:46.512605 18606 solver.cpp:218] Iteration 3408 (2.47157 iter/s, 4.85521s/12 iters), loss = 5.28573 +I0410 13:55:46.512655 18606 solver.cpp:237] Train net output #0: loss = 5.28573 (* 1 = 5.28573 loss) +I0410 13:55:46.512665 18606 sgd_solver.cpp:105] Iteration 3408, lr = 0.00509117 +I0410 13:55:51.373775 18606 solver.cpp:218] Iteration 3420 (2.46867 iter/s, 4.86092s/12 iters), loss = 5.2795 +I0410 13:55:51.373831 18606 solver.cpp:237] Train net output #0: loss = 5.2795 (* 1 = 5.2795 loss) +I0410 13:55:51.373844 18606 sgd_solver.cpp:105] Iteration 3420, lr = 0.00507909 +I0410 13:55:56.250799 18606 solver.cpp:218] Iteration 3432 (2.46065 iter/s, 4.87676s/12 iters), loss = 5.26391 +I0410 13:55:56.250866 18606 solver.cpp:237] Train net output #0: loss = 5.26391 (* 1 = 5.26391 loss) +I0410 13:55:56.250882 18606 sgd_solver.cpp:105] Iteration 3432, lr = 0.00506703 +I0410 13:55:58.753434 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:01.062130 18606 solver.cpp:218] Iteration 3444 (2.49425 iter/s, 4.81107s/12 iters), loss = 5.273 +I0410 13:56:01.062175 18606 solver.cpp:237] Train net output #0: loss = 5.273 (* 1 = 5.273 loss) +I0410 13:56:01.062186 18606 sgd_solver.cpp:105] Iteration 3444, lr = 0.005055 +I0410 13:56:05.947073 18606 solver.cpp:218] Iteration 3456 (2.45665 iter/s, 4.8847s/12 iters), loss = 5.27223 +I0410 13:56:05.947115 18606 solver.cpp:237] Train net output #0: loss = 5.27223 (* 1 = 5.27223 loss) +I0410 13:56:05.947124 18606 sgd_solver.cpp:105] Iteration 3456, lr = 0.005043 +I0410 13:56:10.304541 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3468.caffemodel +I0410 13:56:10.614746 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3468.solverstate +I0410 13:56:10.823207 18606 solver.cpp:330] Iteration 3468, Testing net (#0) +I0410 13:56:10.823233 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:56:10.844612 18606 blocking_queue.cpp:49] Waiting for data +I0410 13:56:13.752207 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:15.128726 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:56:15.128777 18606 solver.cpp:397] Test net output #1: loss = 5.28701 (* 1 = 5.28701 loss) +I0410 13:56:15.212276 18606 solver.cpp:218] Iteration 3468 (1.29523 iter/s, 9.26479s/12 iters), loss = 5.27371 +I0410 13:56:15.212322 18606 solver.cpp:237] Train net output #0: loss = 5.27371 (* 1 = 5.27371 loss) +I0410 13:56:15.212334 18606 sgd_solver.cpp:105] Iteration 3468, lr = 0.00503102 +I0410 13:56:19.330545 18606 solver.cpp:218] Iteration 3480 (2.914 iter/s, 4.11805s/12 iters), loss = 5.2793 +I0410 13:56:19.330590 18606 solver.cpp:237] Train net output #0: loss = 5.2793 (* 1 = 5.2793 loss) +I0410 13:56:19.330600 18606 sgd_solver.cpp:105] Iteration 3480, lr = 0.00501908 +I0410 13:56:24.175390 18606 solver.cpp:218] Iteration 3492 (2.47699 iter/s, 4.8446s/12 iters), loss = 5.29008 +I0410 13:56:24.175438 18606 solver.cpp:237] Train net output #0: loss = 5.29008 (* 1 = 5.29008 loss) +I0410 13:56:24.175449 18606 sgd_solver.cpp:105] Iteration 3492, lr = 0.00500716 +I0410 13:56:29.011658 18606 solver.cpp:218] Iteration 3504 (2.48138 iter/s, 4.83602s/12 iters), loss = 5.27226 +I0410 13:56:29.011751 18606 solver.cpp:237] Train net output #0: loss = 5.27226 (* 1 = 5.27226 loss) +I0410 13:56:29.011760 18606 sgd_solver.cpp:105] Iteration 3504, lr = 0.00499527 +I0410 13:56:33.819505 18606 solver.cpp:218] Iteration 3516 (2.49607 iter/s, 4.80755s/12 iters), loss = 5.26522 +I0410 13:56:33.819555 18606 solver.cpp:237] Train net output #0: loss = 5.26522 (* 1 = 5.26522 loss) +I0410 13:56:33.819563 18606 sgd_solver.cpp:105] Iteration 3516, lr = 0.00498341 +I0410 13:56:38.649109 18606 solver.cpp:218] Iteration 3528 (2.48481 iter/s, 4.82935s/12 iters), loss = 5.27093 +I0410 13:56:38.649152 18606 solver.cpp:237] Train net output #0: loss = 5.27093 (* 1 = 5.27093 loss) +I0410 13:56:38.649160 18606 sgd_solver.cpp:105] Iteration 3528, lr = 0.00497158 +I0410 13:56:43.197898 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:56:43.448704 18606 solver.cpp:218] Iteration 3540 (2.50034 iter/s, 4.79935s/12 iters), loss = 5.25724 +I0410 13:56:43.448745 18606 solver.cpp:237] Train net output #0: loss = 5.25724 (* 1 = 5.25724 loss) +I0410 13:56:43.448752 18606 sgd_solver.cpp:105] Iteration 3540, lr = 0.00495978 +I0410 13:56:48.280727 18606 solver.cpp:218] Iteration 3552 (2.48356 iter/s, 4.83178s/12 iters), loss = 5.26698 +I0410 13:56:48.280773 18606 solver.cpp:237] Train net output #0: loss = 5.26698 (* 1 = 5.26698 loss) +I0410 13:56:48.280781 18606 sgd_solver.cpp:105] Iteration 3552, lr = 0.004948 +I0410 13:56:53.090683 18606 solver.cpp:218] Iteration 3564 (2.49495 iter/s, 4.80971s/12 iters), loss = 5.29157 +I0410 13:56:53.090730 18606 solver.cpp:237] Train net output #0: loss = 5.29157 (* 1 = 5.29157 loss) +I0410 13:56:53.090741 18606 sgd_solver.cpp:105] Iteration 3564, lr = 0.00493626 +I0410 13:56:55.049157 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3570.caffemodel +I0410 13:56:56.077369 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3570.solverstate +I0410 13:56:57.078701 18606 solver.cpp:330] Iteration 3570, Testing net (#0) +I0410 13:56:57.078728 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:57:00.090854 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:01.498852 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:57:01.498880 18606 solver.cpp:397] Test net output #1: loss = 5.28689 (* 1 = 5.28689 loss) +I0410 13:57:03.311437 18606 solver.cpp:218] Iteration 3576 (1.17413 iter/s, 10.2203s/12 iters), loss = 5.28109 +I0410 13:57:03.311498 18606 solver.cpp:237] Train net output #0: loss = 5.28109 (* 1 = 5.28109 loss) +I0410 13:57:03.311511 18606 sgd_solver.cpp:105] Iteration 3576, lr = 0.00492454 +I0410 13:57:08.143740 18606 solver.cpp:218] Iteration 3588 (2.48342 iter/s, 4.83204s/12 iters), loss = 5.2768 +I0410 13:57:08.143785 18606 solver.cpp:237] Train net output #0: loss = 5.2768 (* 1 = 5.2768 loss) +I0410 13:57:08.143795 18606 sgd_solver.cpp:105] Iteration 3588, lr = 0.00491284 +I0410 13:57:13.011135 18606 solver.cpp:218] Iteration 3600 (2.46551 iter/s, 4.86714s/12 iters), loss = 5.26681 +I0410 13:57:13.011180 18606 solver.cpp:237] Train net output #0: loss = 5.26681 (* 1 = 5.26681 loss) +I0410 13:57:13.011189 18606 sgd_solver.cpp:105] Iteration 3600, lr = 0.00490118 +I0410 13:57:17.827821 18606 solver.cpp:218] Iteration 3612 (2.49147 iter/s, 4.81643s/12 iters), loss = 5.24323 +I0410 13:57:17.827881 18606 solver.cpp:237] Train net output #0: loss = 5.24323 (* 1 = 5.24323 loss) +I0410 13:57:17.827894 18606 sgd_solver.cpp:105] Iteration 3612, lr = 0.00488954 +I0410 13:57:22.598490 18606 solver.cpp:218] Iteration 3624 (2.51551 iter/s, 4.7704s/12 iters), loss = 5.27456 +I0410 13:57:22.598548 18606 solver.cpp:237] Train net output #0: loss = 5.27456 (* 1 = 5.27456 loss) +I0410 13:57:22.598560 18606 sgd_solver.cpp:105] Iteration 3624, lr = 0.00487793 +I0410 13:57:27.416333 18606 solver.cpp:218] Iteration 3636 (2.49087 iter/s, 4.81759s/12 iters), loss = 5.27882 +I0410 13:57:27.416368 18606 solver.cpp:237] Train net output #0: loss = 5.27882 (* 1 = 5.27882 loss) +I0410 13:57:27.416376 18606 sgd_solver.cpp:105] Iteration 3636, lr = 0.00486635 +I0410 13:57:29.246310 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:32.237141 18606 solver.cpp:218] Iteration 3648 (2.48933 iter/s, 4.82057s/12 iters), loss = 5.28763 +I0410 13:57:32.239532 18606 solver.cpp:237] Train net output #0: loss = 5.28763 (* 1 = 5.28763 loss) +I0410 13:57:32.239545 18606 sgd_solver.cpp:105] Iteration 3648, lr = 0.0048548 +I0410 13:57:37.047710 18606 solver.cpp:218] Iteration 3660 (2.49585 iter/s, 4.80798s/12 iters), loss = 5.28003 +I0410 13:57:37.047749 18606 solver.cpp:237] Train net output #0: loss = 5.28003 (* 1 = 5.28003 loss) +I0410 13:57:37.047758 18606 sgd_solver.cpp:105] Iteration 3660, lr = 0.00484327 +I0410 13:57:41.418326 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3672.caffemodel +I0410 13:57:41.740329 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3672.solverstate +I0410 13:57:41.952410 18606 solver.cpp:330] Iteration 3672, Testing net (#0) +I0410 13:57:41.952435 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:57:44.871471 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:57:46.381644 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:57:46.381675 18606 solver.cpp:397] Test net output #1: loss = 5.28632 (* 1 = 5.28632 loss) +I0410 13:57:46.454411 18606 solver.cpp:218] Iteration 3672 (1.27574 iter/s, 9.40627s/12 iters), loss = 5.25046 +I0410 13:57:46.454457 18606 solver.cpp:237] Train net output #0: loss = 5.25046 (* 1 = 5.25046 loss) +I0410 13:57:46.454465 18606 sgd_solver.cpp:105] Iteration 3672, lr = 0.00483177 +I0410 13:57:50.669720 18606 solver.cpp:218] Iteration 3684 (2.84692 iter/s, 4.21508s/12 iters), loss = 5.2682 +I0410 13:57:50.669775 18606 solver.cpp:237] Train net output #0: loss = 5.2682 (* 1 = 5.2682 loss) +I0410 13:57:50.669788 18606 sgd_solver.cpp:105] Iteration 3684, lr = 0.0048203 +I0410 13:57:55.432440 18606 solver.cpp:218] Iteration 3696 (2.5197 iter/s, 4.76246s/12 iters), loss = 5.26141 +I0410 13:57:55.432490 18606 solver.cpp:237] Train net output #0: loss = 5.26141 (* 1 = 5.26141 loss) +I0410 13:57:55.432500 18606 sgd_solver.cpp:105] Iteration 3696, lr = 0.00480886 +I0410 13:58:00.273734 18606 solver.cpp:218] Iteration 3708 (2.47881 iter/s, 4.84104s/12 iters), loss = 5.26998 +I0410 13:58:00.273789 18606 solver.cpp:237] Train net output #0: loss = 5.26998 (* 1 = 5.26998 loss) +I0410 13:58:00.273802 18606 sgd_solver.cpp:105] Iteration 3708, lr = 0.00479744 +I0410 13:58:05.102613 18606 solver.cpp:218] Iteration 3720 (2.48518 iter/s, 4.82862s/12 iters), loss = 5.27081 +I0410 13:58:05.102784 18606 solver.cpp:237] Train net output #0: loss = 5.27081 (* 1 = 5.27081 loss) +I0410 13:58:05.102799 18606 sgd_solver.cpp:105] Iteration 3720, lr = 0.00478605 +I0410 13:58:09.981763 18606 solver.cpp:218] Iteration 3732 (2.45963 iter/s, 4.87878s/12 iters), loss = 5.25521 +I0410 13:58:09.981810 18606 solver.cpp:237] Train net output #0: loss = 5.25521 (* 1 = 5.25521 loss) +I0410 13:58:09.981820 18606 sgd_solver.cpp:105] Iteration 3732, lr = 0.00477469 +I0410 13:58:13.863339 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:58:14.828564 18606 solver.cpp:218] Iteration 3744 (2.47599 iter/s, 4.84655s/12 iters), loss = 5.25646 +I0410 13:58:14.828617 18606 solver.cpp:237] Train net output #0: loss = 5.25646 (* 1 = 5.25646 loss) +I0410 13:58:14.828630 18606 sgd_solver.cpp:105] Iteration 3744, lr = 0.00476335 +I0410 13:58:19.655438 18606 solver.cpp:218] Iteration 3756 (2.48621 iter/s, 4.82662s/12 iters), loss = 5.27972 +I0410 13:58:19.655490 18606 solver.cpp:237] Train net output #0: loss = 5.27972 (* 1 = 5.27972 loss) +I0410 13:58:19.655500 18606 sgd_solver.cpp:105] Iteration 3756, lr = 0.00475204 +I0410 13:58:24.458526 18606 solver.cpp:218] Iteration 3768 (2.49853 iter/s, 4.80283s/12 iters), loss = 5.26289 +I0410 13:58:24.458576 18606 solver.cpp:237] Train net output #0: loss = 5.26289 (* 1 = 5.26289 loss) +I0410 13:58:24.458588 18606 sgd_solver.cpp:105] Iteration 3768, lr = 0.00474076 +I0410 13:58:26.419847 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3774.caffemodel +I0410 13:58:26.716773 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3774.solverstate +I0410 13:58:26.922745 18606 solver.cpp:330] Iteration 3774, Testing net (#0) +I0410 13:58:26.922768 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:58:29.824255 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:58:31.495963 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:58:31.496014 18606 solver.cpp:397] Test net output #1: loss = 5.28717 (* 1 = 5.28717 loss) +I0410 13:58:33.198984 18606 solver.cpp:218] Iteration 3780 (1.37299 iter/s, 8.74004s/12 iters), loss = 5.30865 +I0410 13:58:33.199043 18606 solver.cpp:237] Train net output #0: loss = 5.30865 (* 1 = 5.30865 loss) +I0410 13:58:33.199054 18606 sgd_solver.cpp:105] Iteration 3780, lr = 0.00472951 +I0410 13:58:38.130743 18606 solver.cpp:218] Iteration 3792 (2.43334 iter/s, 4.93149s/12 iters), loss = 5.27735 +I0410 13:58:38.130867 18606 solver.cpp:237] Train net output #0: loss = 5.27735 (* 1 = 5.27735 loss) +I0410 13:58:38.130879 18606 sgd_solver.cpp:105] Iteration 3792, lr = 0.00471828 +I0410 13:58:42.975505 18606 solver.cpp:218] Iteration 3804 (2.47707 iter/s, 4.84443s/12 iters), loss = 5.26929 +I0410 13:58:42.975548 18606 solver.cpp:237] Train net output #0: loss = 5.26929 (* 1 = 5.26929 loss) +I0410 13:58:42.975556 18606 sgd_solver.cpp:105] Iteration 3804, lr = 0.00470707 +I0410 13:58:47.773753 18606 solver.cpp:218] Iteration 3816 (2.50105 iter/s, 4.79799s/12 iters), loss = 5.27258 +I0410 13:58:47.773818 18606 solver.cpp:237] Train net output #0: loss = 5.27258 (* 1 = 5.27258 loss) +I0410 13:58:47.773835 18606 sgd_solver.cpp:105] Iteration 3816, lr = 0.0046959 +I0410 13:58:52.690101 18606 solver.cpp:218] Iteration 3828 (2.44097 iter/s, 4.91608s/12 iters), loss = 5.26193 +I0410 13:58:52.690151 18606 solver.cpp:237] Train net output #0: loss = 5.26193 (* 1 = 5.26193 loss) +I0410 13:58:52.690162 18606 sgd_solver.cpp:105] Iteration 3828, lr = 0.00468475 +I0410 13:58:57.528312 18606 solver.cpp:218] Iteration 3840 (2.48039 iter/s, 4.83795s/12 iters), loss = 5.26923 +I0410 13:58:57.528359 18606 solver.cpp:237] Train net output #0: loss = 5.26923 (* 1 = 5.26923 loss) +I0410 13:58:57.528368 18606 sgd_solver.cpp:105] Iteration 3840, lr = 0.00467363 +I0410 13:58:58.637902 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:02.583171 18606 solver.cpp:218] Iteration 3852 (2.37407 iter/s, 5.0546s/12 iters), loss = 5.27472 +I0410 13:59:02.583209 18606 solver.cpp:237] Train net output #0: loss = 5.27472 (* 1 = 5.27472 loss) +I0410 13:59:02.583217 18606 sgd_solver.cpp:105] Iteration 3852, lr = 0.00466253 +I0410 13:59:07.385604 18606 solver.cpp:218] Iteration 3864 (2.49887 iter/s, 4.80218s/12 iters), loss = 5.25224 +I0410 13:59:07.385663 18606 solver.cpp:237] Train net output #0: loss = 5.25224 (* 1 = 5.25224 loss) +I0410 13:59:07.385676 18606 sgd_solver.cpp:105] Iteration 3864, lr = 0.00465146 +I0410 13:59:11.809609 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3876.caffemodel +I0410 13:59:12.141638 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3876.solverstate +I0410 13:59:12.360868 18606 solver.cpp:330] Iteration 3876, Testing net (#0) +I0410 13:59:12.360899 18606 net.cpp:676] Ignoring source layer train-data +I0410 13:59:15.347499 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:16.885103 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 13:59:16.885145 18606 solver.cpp:397] Test net output #1: loss = 5.28669 (* 1 = 5.28669 loss) +I0410 13:59:16.968065 18606 solver.cpp:218] Iteration 3876 (1.25235 iter/s, 9.582s/12 iters), loss = 5.27317 +I0410 13:59:16.968123 18606 solver.cpp:237] Train net output #0: loss = 5.27317 (* 1 = 5.27317 loss) +I0410 13:59:16.968135 18606 sgd_solver.cpp:105] Iteration 3876, lr = 0.00464042 +I0410 13:59:20.990504 18606 solver.cpp:218] Iteration 3888 (2.98344 iter/s, 4.02221s/12 iters), loss = 5.26991 +I0410 13:59:20.990552 18606 solver.cpp:237] Train net output #0: loss = 5.26991 (* 1 = 5.26991 loss) +I0410 13:59:20.990561 18606 sgd_solver.cpp:105] Iteration 3888, lr = 0.0046294 +I0410 13:59:25.877948 18606 solver.cpp:218] Iteration 3900 (2.4554 iter/s, 4.88718s/12 iters), loss = 5.27488 +I0410 13:59:25.878021 18606 solver.cpp:237] Train net output #0: loss = 5.27488 (* 1 = 5.27488 loss) +I0410 13:59:25.878033 18606 sgd_solver.cpp:105] Iteration 3900, lr = 0.00461841 +I0410 13:59:30.780555 18606 solver.cpp:218] Iteration 3912 (2.44782 iter/s, 4.90232s/12 iters), loss = 5.2606 +I0410 13:59:30.780611 18606 solver.cpp:237] Train net output #0: loss = 5.2606 (* 1 = 5.2606 loss) +I0410 13:59:30.780623 18606 sgd_solver.cpp:105] Iteration 3912, lr = 0.00460744 +I0410 13:59:35.559546 18606 solver.cpp:218] Iteration 3924 (2.51113 iter/s, 4.77873s/12 iters), loss = 5.29255 +I0410 13:59:35.559609 18606 solver.cpp:237] Train net output #0: loss = 5.29255 (* 1 = 5.29255 loss) +I0410 13:59:35.559623 18606 sgd_solver.cpp:105] Iteration 3924, lr = 0.0045965 +I0410 13:59:40.466614 18606 solver.cpp:218] Iteration 3936 (2.44559 iter/s, 4.9068s/12 iters), loss = 5.27299 +I0410 13:59:40.466662 18606 solver.cpp:237] Train net output #0: loss = 5.27299 (* 1 = 5.27299 loss) +I0410 13:59:40.466671 18606 sgd_solver.cpp:105] Iteration 3936, lr = 0.00458559 +I0410 13:59:43.719444 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 13:59:45.302263 18606 solver.cpp:218] Iteration 3948 (2.4817 iter/s, 4.83539s/12 iters), loss = 5.28378 +I0410 13:59:45.302311 18606 solver.cpp:237] Train net output #0: loss = 5.28378 (* 1 = 5.28378 loss) +I0410 13:59:45.302321 18606 sgd_solver.cpp:105] Iteration 3948, lr = 0.0045747 +I0410 13:59:50.114696 18606 solver.cpp:218] Iteration 3960 (2.49367 iter/s, 4.81218s/12 iters), loss = 5.27096 +I0410 13:59:50.114740 18606 solver.cpp:237] Train net output #0: loss = 5.27096 (* 1 = 5.27096 loss) +I0410 13:59:50.114751 18606 sgd_solver.cpp:105] Iteration 3960, lr = 0.00456384 +I0410 13:59:55.115056 18606 solver.cpp:218] Iteration 3972 (2.39995 iter/s, 5.0001s/12 iters), loss = 5.28177 +I0410 13:59:55.115108 18606 solver.cpp:237] Train net output #0: loss = 5.28177 (* 1 = 5.28177 loss) +I0410 13:59:55.115119 18606 sgd_solver.cpp:105] Iteration 3972, lr = 0.00455301 +I0410 13:59:57.080972 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_3978.caffemodel +I0410 13:59:57.407989 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_3978.solverstate +I0410 13:59:57.612540 18606 solver.cpp:330] Iteration 3978, Testing net (#0) +I0410 13:59:57.612560 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:00:00.666501 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:02.399937 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:00:02.399971 18606 solver.cpp:397] Test net output #1: loss = 5.28652 (* 1 = 5.28652 loss) +I0410 14:00:04.249752 18606 solver.cpp:218] Iteration 3984 (1.31373 iter/s, 9.13426s/12 iters), loss = 5.28141 +I0410 14:00:04.249794 18606 solver.cpp:237] Train net output #0: loss = 5.28141 (* 1 = 5.28141 loss) +I0410 14:00:04.249804 18606 sgd_solver.cpp:105] Iteration 3984, lr = 0.0045422 +I0410 14:00:09.109678 18606 solver.cpp:218] Iteration 3996 (2.4693 iter/s, 4.85967s/12 iters), loss = 5.26538 +I0410 14:00:09.109724 18606 solver.cpp:237] Train net output #0: loss = 5.26538 (* 1 = 5.26538 loss) +I0410 14:00:09.109735 18606 sgd_solver.cpp:105] Iteration 3996, lr = 0.00453141 +I0410 14:00:13.894639 18606 solver.cpp:218] Iteration 4008 (2.50799 iter/s, 4.78471s/12 iters), loss = 5.28797 +I0410 14:00:13.898034 18606 solver.cpp:237] Train net output #0: loss = 5.28797 (* 1 = 5.28797 loss) +I0410 14:00:13.898046 18606 sgd_solver.cpp:105] Iteration 4008, lr = 0.00452066 +I0410 14:00:18.716637 18606 solver.cpp:218] Iteration 4020 (2.49045 iter/s, 4.8184s/12 iters), loss = 5.25721 +I0410 14:00:18.716676 18606 solver.cpp:237] Train net output #0: loss = 5.25721 (* 1 = 5.25721 loss) +I0410 14:00:18.716684 18606 sgd_solver.cpp:105] Iteration 4020, lr = 0.00450992 +I0410 14:00:23.595978 18606 solver.cpp:218] Iteration 4032 (2.45947 iter/s, 4.87909s/12 iters), loss = 5.27322 +I0410 14:00:23.596024 18606 solver.cpp:237] Train net output #0: loss = 5.27322 (* 1 = 5.27322 loss) +I0410 14:00:23.596033 18606 sgd_solver.cpp:105] Iteration 4032, lr = 0.00449921 +I0410 14:00:28.507310 18606 solver.cpp:218] Iteration 4044 (2.44346 iter/s, 4.91108s/12 iters), loss = 5.27554 +I0410 14:00:28.507352 18606 solver.cpp:237] Train net output #0: loss = 5.27554 (* 1 = 5.27554 loss) +I0410 14:00:28.507361 18606 sgd_solver.cpp:105] Iteration 4044, lr = 0.00448853 +I0410 14:00:28.993311 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:33.425415 18606 solver.cpp:218] Iteration 4056 (2.44009 iter/s, 4.91785s/12 iters), loss = 5.27542 +I0410 14:00:33.425454 18606 solver.cpp:237] Train net output #0: loss = 5.27542 (* 1 = 5.27542 loss) +I0410 14:00:33.425465 18606 sgd_solver.cpp:105] Iteration 4056, lr = 0.00447788 +I0410 14:00:38.290288 18606 solver.cpp:218] Iteration 4068 (2.46679 iter/s, 4.86462s/12 iters), loss = 5.27231 +I0410 14:00:38.290331 18606 solver.cpp:237] Train net output #0: loss = 5.27231 (* 1 = 5.27231 loss) +I0410 14:00:38.290340 18606 sgd_solver.cpp:105] Iteration 4068, lr = 0.00446724 +I0410 14:00:42.751628 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4080.caffemodel +I0410 14:00:43.065873 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4080.solverstate +I0410 14:00:43.277554 18606 solver.cpp:330] Iteration 4080, Testing net (#0) +I0410 14:00:43.277573 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:00:45.997107 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:00:47.607935 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:00:47.607985 18606 solver.cpp:397] Test net output #1: loss = 5.28706 (* 1 = 5.28706 loss) +I0410 14:00:47.691107 18606 solver.cpp:218] Iteration 4080 (1.27654 iter/s, 9.40038s/12 iters), loss = 5.28647 +I0410 14:00:47.691156 18606 solver.cpp:237] Train net output #0: loss = 5.28647 (* 1 = 5.28647 loss) +I0410 14:00:47.691167 18606 sgd_solver.cpp:105] Iteration 4080, lr = 0.00445664 +I0410 14:00:51.878629 18606 solver.cpp:218] Iteration 4092 (2.86582 iter/s, 4.18729s/12 iters), loss = 5.26297 +I0410 14:00:51.878674 18606 solver.cpp:237] Train net output #0: loss = 5.26297 (* 1 = 5.26297 loss) +I0410 14:00:51.878684 18606 sgd_solver.cpp:105] Iteration 4092, lr = 0.00444606 +I0410 14:00:56.782646 18606 solver.cpp:218] Iteration 4104 (2.4471 iter/s, 4.90376s/12 iters), loss = 5.26124 +I0410 14:00:56.782693 18606 solver.cpp:237] Train net output #0: loss = 5.26124 (* 1 = 5.26124 loss) +I0410 14:00:56.782703 18606 sgd_solver.cpp:105] Iteration 4104, lr = 0.0044355 +I0410 14:01:01.693251 18606 solver.cpp:218] Iteration 4116 (2.44382 iter/s, 4.91035s/12 iters), loss = 5.29311 +I0410 14:01:01.693298 18606 solver.cpp:237] Train net output #0: loss = 5.29311 (* 1 = 5.29311 loss) +I0410 14:01:01.693310 18606 sgd_solver.cpp:105] Iteration 4116, lr = 0.00442497 +I0410 14:01:06.720490 18606 solver.cpp:218] Iteration 4128 (2.38712 iter/s, 5.02697s/12 iters), loss = 5.26753 +I0410 14:01:06.720551 18606 solver.cpp:237] Train net output #0: loss = 5.26753 (* 1 = 5.26753 loss) +I0410 14:01:06.720566 18606 sgd_solver.cpp:105] Iteration 4128, lr = 0.00441447 +I0410 14:01:11.517349 18606 solver.cpp:218] Iteration 4140 (2.50178 iter/s, 4.79659s/12 iters), loss = 5.25823 +I0410 14:01:11.517397 18606 solver.cpp:237] Train net output #0: loss = 5.25823 (* 1 = 5.25823 loss) +I0410 14:01:11.517406 18606 sgd_solver.cpp:105] Iteration 4140, lr = 0.00440398 +I0410 14:01:14.067147 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:01:16.331468 18606 solver.cpp:218] Iteration 4152 (2.4928 iter/s, 4.81386s/12 iters), loss = 5.26856 +I0410 14:01:16.331591 18606 solver.cpp:237] Train net output #0: loss = 5.26856 (* 1 = 5.26856 loss) +I0410 14:01:16.331604 18606 sgd_solver.cpp:105] Iteration 4152, lr = 0.00439353 +I0410 14:01:16.331964 18606 blocking_queue.cpp:49] Waiting for data +I0410 14:01:21.162050 18606 solver.cpp:218] Iteration 4164 (2.48434 iter/s, 4.83025s/12 iters), loss = 5.26438 +I0410 14:01:21.162103 18606 solver.cpp:237] Train net output #0: loss = 5.26438 (* 1 = 5.26438 loss) +I0410 14:01:21.162115 18606 sgd_solver.cpp:105] Iteration 4164, lr = 0.0043831 +I0410 14:01:25.981971 18606 solver.cpp:218] Iteration 4176 (2.48981 iter/s, 4.81964s/12 iters), loss = 5.26601 +I0410 14:01:25.982017 18606 solver.cpp:237] Train net output #0: loss = 5.26601 (* 1 = 5.26601 loss) +I0410 14:01:25.982026 18606 sgd_solver.cpp:105] Iteration 4176, lr = 0.00437269 +I0410 14:01:27.936503 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4182.caffemodel +I0410 14:01:28.244376 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4182.solverstate +I0410 14:01:28.462625 18606 solver.cpp:330] Iteration 4182, Testing net (#0) +I0410 14:01:28.462651 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:01:31.439479 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:01:33.252626 18606 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 14:01:33.252655 18606 solver.cpp:397] Test net output #1: loss = 5.28669 (* 1 = 5.28669 loss) +I0410 14:01:35.068053 18606 solver.cpp:218] Iteration 4188 (1.32076 iter/s, 9.08565s/12 iters), loss = 5.26609 +I0410 14:01:35.068107 18606 solver.cpp:237] Train net output #0: loss = 5.26609 (* 1 = 5.26609 loss) +I0410 14:01:35.068117 18606 sgd_solver.cpp:105] Iteration 4188, lr = 0.00436231 +I0410 14:01:39.990592 18606 solver.cpp:218] Iteration 4200 (2.4379 iter/s, 4.92227s/12 iters), loss = 5.28192 +I0410 14:01:39.990648 18606 solver.cpp:237] Train net output #0: loss = 5.28192 (* 1 = 5.28192 loss) +I0410 14:01:39.990661 18606 sgd_solver.cpp:105] Iteration 4200, lr = 0.00435195 +I0410 14:01:44.794421 18606 solver.cpp:218] Iteration 4212 (2.49814 iter/s, 4.80357s/12 iters), loss = 5.27112 +I0410 14:01:44.794476 18606 solver.cpp:237] Train net output #0: loss = 5.27112 (* 1 = 5.27112 loss) +I0410 14:01:44.794488 18606 sgd_solver.cpp:105] Iteration 4212, lr = 0.00434162 +I0410 14:01:49.876324 18606 solver.cpp:218] Iteration 4224 (2.36145 iter/s, 5.08163s/12 iters), loss = 5.26334 +I0410 14:01:49.876499 18606 solver.cpp:237] Train net output #0: loss = 5.26334 (* 1 = 5.26334 loss) +I0410 14:01:49.876514 18606 sgd_solver.cpp:105] Iteration 4224, lr = 0.00433131 +I0410 14:01:54.884364 18606 solver.cpp:218] Iteration 4236 (2.39633 iter/s, 5.00765s/12 iters), loss = 5.26616 +I0410 14:01:54.884410 18606 solver.cpp:237] Train net output #0: loss = 5.26616 (* 1 = 5.26616 loss) +I0410 14:01:54.884420 18606 sgd_solver.cpp:105] Iteration 4236, lr = 0.00432103 +I0410 14:01:59.900601 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:00.117734 18606 solver.cpp:218] Iteration 4248 (2.2931 iter/s, 5.2331s/12 iters), loss = 5.2445 +I0410 14:02:00.117787 18606 solver.cpp:237] Train net output #0: loss = 5.2445 (* 1 = 5.2445 loss) +I0410 14:02:00.117799 18606 sgd_solver.cpp:105] Iteration 4248, lr = 0.00431077 +I0410 14:02:04.940223 18606 solver.cpp:218] Iteration 4260 (2.48848 iter/s, 4.82223s/12 iters), loss = 5.26717 +I0410 14:02:04.940271 18606 solver.cpp:237] Train net output #0: loss = 5.26717 (* 1 = 5.26717 loss) +I0410 14:02:04.940282 18606 sgd_solver.cpp:105] Iteration 4260, lr = 0.00430053 +I0410 14:02:09.718241 18606 solver.cpp:218] Iteration 4272 (2.51164 iter/s, 4.77775s/12 iters), loss = 5.29044 +I0410 14:02:09.718303 18606 solver.cpp:237] Train net output #0: loss = 5.29044 (* 1 = 5.29044 loss) +I0410 14:02:09.718317 18606 sgd_solver.cpp:105] Iteration 4272, lr = 0.00429032 +I0410 14:02:14.053889 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4284.caffemodel +I0410 14:02:14.521123 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4284.solverstate +I0410 14:02:14.995435 18606 solver.cpp:330] Iteration 4284, Testing net (#0) +I0410 14:02:14.995467 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:02:17.641376 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:19.334110 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:02:19.334146 18606 solver.cpp:397] Test net output #1: loss = 5.28685 (* 1 = 5.28685 loss) +I0410 14:02:19.416546 18606 solver.cpp:218] Iteration 4284 (1.23739 iter/s, 9.69783s/12 iters), loss = 5.27777 +I0410 14:02:19.416602 18606 solver.cpp:237] Train net output #0: loss = 5.27777 (* 1 = 5.27777 loss) +I0410 14:02:19.416615 18606 sgd_solver.cpp:105] Iteration 4284, lr = 0.00428014 +I0410 14:02:23.506827 18606 solver.cpp:218] Iteration 4296 (2.93395 iter/s, 4.09005s/12 iters), loss = 5.2748 +I0410 14:02:23.506925 18606 solver.cpp:237] Train net output #0: loss = 5.2748 (* 1 = 5.2748 loss) +I0410 14:02:23.506937 18606 sgd_solver.cpp:105] Iteration 4296, lr = 0.00426998 +I0410 14:02:28.317414 18606 solver.cpp:218] Iteration 4308 (2.49466 iter/s, 4.81028s/12 iters), loss = 5.26258 +I0410 14:02:28.317458 18606 solver.cpp:237] Train net output #0: loss = 5.26258 (* 1 = 5.26258 loss) +I0410 14:02:28.317468 18606 sgd_solver.cpp:105] Iteration 4308, lr = 0.00425984 +I0410 14:02:33.102428 18606 solver.cpp:218] Iteration 4320 (2.50797 iter/s, 4.78476s/12 iters), loss = 5.24858 +I0410 14:02:33.102483 18606 solver.cpp:237] Train net output #0: loss = 5.24858 (* 1 = 5.24858 loss) +I0410 14:02:33.102495 18606 sgd_solver.cpp:105] Iteration 4320, lr = 0.00424972 +I0410 14:02:37.894629 18606 solver.cpp:218] Iteration 4332 (2.50421 iter/s, 4.79194s/12 iters), loss = 5.27726 +I0410 14:02:37.894677 18606 solver.cpp:237] Train net output #0: loss = 5.27726 (* 1 = 5.27726 loss) +I0410 14:02:37.894686 18606 sgd_solver.cpp:105] Iteration 4332, lr = 0.00423964 +I0410 14:02:42.700366 18606 solver.cpp:218] Iteration 4344 (2.49715 iter/s, 4.80547s/12 iters), loss = 5.27867 +I0410 14:02:42.700421 18606 solver.cpp:237] Train net output #0: loss = 5.27867 (* 1 = 5.27867 loss) +I0410 14:02:42.700433 18606 sgd_solver.cpp:105] Iteration 4344, lr = 0.00422957 +I0410 14:02:44.540557 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:02:47.499310 18606 solver.cpp:218] Iteration 4356 (2.50069 iter/s, 4.79868s/12 iters), loss = 5.28731 +I0410 14:02:47.499372 18606 solver.cpp:237] Train net output #0: loss = 5.28731 (* 1 = 5.28731 loss) +I0410 14:02:47.499383 18606 sgd_solver.cpp:105] Iteration 4356, lr = 0.00421953 +I0410 14:02:52.329746 18606 solver.cpp:218] Iteration 4368 (2.48439 iter/s, 4.83016s/12 iters), loss = 5.27677 +I0410 14:02:52.329802 18606 solver.cpp:237] Train net output #0: loss = 5.27677 (* 1 = 5.27677 loss) +I0410 14:02:52.329814 18606 sgd_solver.cpp:105] Iteration 4368, lr = 0.00420951 +I0410 14:02:57.119155 18606 solver.cpp:218] Iteration 4380 (2.50567 iter/s, 4.78914s/12 iters), loss = 5.25975 +I0410 14:02:57.120689 18606 solver.cpp:237] Train net output #0: loss = 5.25975 (* 1 = 5.25975 loss) +I0410 14:02:57.120702 18606 sgd_solver.cpp:105] Iteration 4380, lr = 0.00419952 +I0410 14:02:59.100538 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4386.caffemodel +I0410 14:02:59.638135 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4386.solverstate +I0410 14:02:59.843204 18606 solver.cpp:330] Iteration 4386, Testing net (#0) +I0410 14:02:59.843233 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:03:02.425429 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:04.177682 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:03:04.177712 18606 solver.cpp:397] Test net output #1: loss = 5.28684 (* 1 = 5.28684 loss) +I0410 14:03:06.004812 18606 solver.cpp:218] Iteration 4392 (1.35078 iter/s, 8.88375s/12 iters), loss = 5.26992 +I0410 14:03:06.004868 18606 solver.cpp:237] Train net output #0: loss = 5.26992 (* 1 = 5.26992 loss) +I0410 14:03:06.004880 18606 sgd_solver.cpp:105] Iteration 4392, lr = 0.00418954 +I0410 14:03:10.946521 18606 solver.cpp:218] Iteration 4404 (2.42845 iter/s, 4.94143s/12 iters), loss = 5.26239 +I0410 14:03:10.946578 18606 solver.cpp:237] Train net output #0: loss = 5.26239 (* 1 = 5.26239 loss) +I0410 14:03:10.946589 18606 sgd_solver.cpp:105] Iteration 4404, lr = 0.0041796 +I0410 14:03:15.764753 18606 solver.cpp:218] Iteration 4416 (2.49068 iter/s, 4.81796s/12 iters), loss = 5.2668 +I0410 14:03:15.764807 18606 solver.cpp:237] Train net output #0: loss = 5.2668 (* 1 = 5.2668 loss) +I0410 14:03:15.764820 18606 sgd_solver.cpp:105] Iteration 4416, lr = 0.00416967 +I0410 14:03:20.602330 18606 solver.cpp:218] Iteration 4428 (2.48072 iter/s, 4.83731s/12 iters), loss = 5.26687 +I0410 14:03:20.602376 18606 solver.cpp:237] Train net output #0: loss = 5.26687 (* 1 = 5.26687 loss) +I0410 14:03:20.602386 18606 sgd_solver.cpp:105] Iteration 4428, lr = 0.00415977 +I0410 14:03:25.400290 18606 solver.cpp:218] Iteration 4440 (2.5012 iter/s, 4.7977s/12 iters), loss = 5.26166 +I0410 14:03:25.400350 18606 solver.cpp:237] Train net output #0: loss = 5.26166 (* 1 = 5.26166 loss) +I0410 14:03:25.400363 18606 sgd_solver.cpp:105] Iteration 4440, lr = 0.0041499 +I0410 14:03:29.283332 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:30.206548 18606 solver.cpp:218] Iteration 4452 (2.49689 iter/s, 4.80598s/12 iters), loss = 5.258 +I0410 14:03:30.206605 18606 solver.cpp:237] Train net output #0: loss = 5.258 (* 1 = 5.258 loss) +I0410 14:03:30.206617 18606 sgd_solver.cpp:105] Iteration 4452, lr = 0.00414005 +I0410 14:03:35.030150 18606 solver.cpp:218] Iteration 4464 (2.48791 iter/s, 4.82334s/12 iters), loss = 5.28124 +I0410 14:03:35.030189 18606 solver.cpp:237] Train net output #0: loss = 5.28124 (* 1 = 5.28124 loss) +I0410 14:03:35.030198 18606 sgd_solver.cpp:105] Iteration 4464, lr = 0.00413022 +I0410 14:03:39.810824 18606 solver.cpp:218] Iteration 4476 (2.51024 iter/s, 4.78042s/12 iters), loss = 5.25913 +I0410 14:03:39.810880 18606 solver.cpp:237] Train net output #0: loss = 5.25913 (* 1 = 5.25913 loss) +I0410 14:03:39.810892 18606 sgd_solver.cpp:105] Iteration 4476, lr = 0.00412041 +I0410 14:03:44.176017 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4488.caffemodel +I0410 14:03:44.526525 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4488.solverstate +I0410 14:03:44.741034 18606 solver.cpp:330] Iteration 4488, Testing net (#0) +I0410 14:03:44.741061 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:03:47.460391 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:03:49.226347 18606 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 14:03:49.226379 18606 solver.cpp:397] Test net output #1: loss = 5.28669 (* 1 = 5.28669 loss) +I0410 14:03:49.309085 18606 solver.cpp:218] Iteration 4488 (1.26345 iter/s, 9.4978s/12 iters), loss = 5.30729 +I0410 14:03:49.309126 18606 solver.cpp:237] Train net output #0: loss = 5.30729 (* 1 = 5.30729 loss) +I0410 14:03:49.309135 18606 sgd_solver.cpp:105] Iteration 4488, lr = 0.00411063 +I0410 14:03:53.413986 18606 solver.cpp:218] Iteration 4500 (2.92351 iter/s, 4.10466s/12 iters), loss = 5.26838 +I0410 14:03:53.414050 18606 solver.cpp:237] Train net output #0: loss = 5.26838 (* 1 = 5.26838 loss) +I0410 14:03:53.414063 18606 sgd_solver.cpp:105] Iteration 4500, lr = 0.00410087 +I0410 14:03:58.184864 18606 solver.cpp:218] Iteration 4512 (2.51541 iter/s, 4.7706s/12 iters), loss = 5.26913 +I0410 14:03:58.184921 18606 solver.cpp:237] Train net output #0: loss = 5.26913 (* 1 = 5.26913 loss) +I0410 14:03:58.184932 18606 sgd_solver.cpp:105] Iteration 4512, lr = 0.00409113 +I0410 14:04:02.962983 18606 solver.cpp:218] Iteration 4524 (2.51159 iter/s, 4.77785s/12 iters), loss = 5.27364 +I0410 14:04:02.963075 18606 solver.cpp:237] Train net output #0: loss = 5.27364 (* 1 = 5.27364 loss) +I0410 14:04:02.963088 18606 sgd_solver.cpp:105] Iteration 4524, lr = 0.00408142 +I0410 14:04:07.742954 18606 solver.cpp:218] Iteration 4536 (2.51063 iter/s, 4.77967s/12 iters), loss = 5.26768 +I0410 14:04:07.743016 18606 solver.cpp:237] Train net output #0: loss = 5.26768 (* 1 = 5.26768 loss) +I0410 14:04:07.743027 18606 sgd_solver.cpp:105] Iteration 4536, lr = 0.00407173 +I0410 14:04:12.527788 18606 solver.cpp:218] Iteration 4548 (2.50807 iter/s, 4.78456s/12 iters), loss = 5.2649 +I0410 14:04:12.527851 18606 solver.cpp:237] Train net output #0: loss = 5.2649 (* 1 = 5.2649 loss) +I0410 14:04:12.527863 18606 sgd_solver.cpp:105] Iteration 4548, lr = 0.00406206 +I0410 14:04:13.733393 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:04:17.318883 18606 solver.cpp:218] Iteration 4560 (2.50479 iter/s, 4.79082s/12 iters), loss = 5.27411 +I0410 14:04:17.318946 18606 solver.cpp:237] Train net output #0: loss = 5.27411 (* 1 = 5.27411 loss) +I0410 14:04:17.318958 18606 sgd_solver.cpp:105] Iteration 4560, lr = 0.00405242 +I0410 14:04:22.334690 18606 solver.cpp:218] Iteration 4572 (2.39257 iter/s, 5.01552s/12 iters), loss = 5.26462 +I0410 14:04:22.334745 18606 solver.cpp:237] Train net output #0: loss = 5.26462 (* 1 = 5.26462 loss) +I0410 14:04:22.334758 18606 sgd_solver.cpp:105] Iteration 4572, lr = 0.0040428 +I0410 14:04:27.145838 18606 solver.cpp:218] Iteration 4584 (2.49435 iter/s, 4.81087s/12 iters), loss = 5.27433 +I0410 14:04:27.145892 18606 solver.cpp:237] Train net output #0: loss = 5.27433 (* 1 = 5.27433 loss) +I0410 14:04:27.145905 18606 sgd_solver.cpp:105] Iteration 4584, lr = 0.0040332 +I0410 14:04:29.112999 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4590.caffemodel +I0410 14:04:29.427423 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4590.solverstate +I0410 14:04:29.647044 18606 solver.cpp:330] Iteration 4590, Testing net (#0) +I0410 14:04:29.647073 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:04:32.423566 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:04:34.237346 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:04:34.237457 18606 solver.cpp:397] Test net output #1: loss = 5.28665 (* 1 = 5.28665 loss) +I0410 14:04:35.978222 18606 solver.cpp:218] Iteration 4596 (1.3587 iter/s, 8.83195s/12 iters), loss = 5.27364 +I0410 14:04:35.978284 18606 solver.cpp:237] Train net output #0: loss = 5.27364 (* 1 = 5.27364 loss) +I0410 14:04:35.978296 18606 sgd_solver.cpp:105] Iteration 4596, lr = 0.00402362 +I0410 14:04:40.806964 18606 solver.cpp:218] Iteration 4608 (2.48526 iter/s, 4.82846s/12 iters), loss = 5.27578 +I0410 14:04:40.807015 18606 solver.cpp:237] Train net output #0: loss = 5.27578 (* 1 = 5.27578 loss) +I0410 14:04:40.807025 18606 sgd_solver.cpp:105] Iteration 4608, lr = 0.00401407 +I0410 14:04:45.607440 18606 solver.cpp:218] Iteration 4620 (2.49989 iter/s, 4.80021s/12 iters), loss = 5.26081 +I0410 14:04:45.607497 18606 solver.cpp:237] Train net output #0: loss = 5.26081 (* 1 = 5.26081 loss) +I0410 14:04:45.607509 18606 sgd_solver.cpp:105] Iteration 4620, lr = 0.00400454 +I0410 14:04:50.424844 18606 solver.cpp:218] Iteration 4632 (2.49111 iter/s, 4.81713s/12 iters), loss = 5.29358 +I0410 14:04:50.424902 18606 solver.cpp:237] Train net output #0: loss = 5.29358 (* 1 = 5.29358 loss) +I0410 14:04:50.424914 18606 sgd_solver.cpp:105] Iteration 4632, lr = 0.00399503 +I0410 14:04:55.336522 18606 solver.cpp:218] Iteration 4644 (2.44329 iter/s, 4.91141s/12 iters), loss = 5.26962 +I0410 14:04:55.336571 18606 solver.cpp:237] Train net output #0: loss = 5.26962 (* 1 = 5.26962 loss) +I0410 14:04:55.336580 18606 sgd_solver.cpp:105] Iteration 4644, lr = 0.00398555 +I0410 14:04:58.881211 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:00.492038 18606 solver.cpp:218] Iteration 4656 (2.32773 iter/s, 5.15523s/12 iters), loss = 5.28075 +I0410 14:05:00.492097 18606 solver.cpp:237] Train net output #0: loss = 5.28075 (* 1 = 5.28075 loss) +I0410 14:05:00.492110 18606 sgd_solver.cpp:105] Iteration 4656, lr = 0.00397608 +I0410 14:05:05.482473 18606 solver.cpp:218] Iteration 4668 (2.40473 iter/s, 4.99016s/12 iters), loss = 5.26575 +I0410 14:05:05.482570 18606 solver.cpp:237] Train net output #0: loss = 5.26575 (* 1 = 5.26575 loss) +I0410 14:05:05.482579 18606 sgd_solver.cpp:105] Iteration 4668, lr = 0.00396664 +I0410 14:05:10.328120 18606 solver.cpp:218] Iteration 4680 (2.47661 iter/s, 4.84534s/12 iters), loss = 5.27269 +I0410 14:05:10.328163 18606 solver.cpp:237] Train net output #0: loss = 5.27269 (* 1 = 5.27269 loss) +I0410 14:05:10.328172 18606 sgd_solver.cpp:105] Iteration 4680, lr = 0.00395723 +I0410 14:05:14.665280 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4692.caffemodel +I0410 14:05:14.963277 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4692.solverstate +I0410 14:05:15.165755 18606 solver.cpp:330] Iteration 4692, Testing net (#0) +I0410 14:05:15.165782 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:05:17.619431 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:19.471491 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:05:19.471540 18606 solver.cpp:397] Test net output #1: loss = 5.28696 (* 1 = 5.28696 loss) +I0410 14:05:19.553385 18606 solver.cpp:218] Iteration 4692 (1.30084 iter/s, 9.22482s/12 iters), loss = 5.26712 +I0410 14:05:19.553434 18606 solver.cpp:237] Train net output #0: loss = 5.26712 (* 1 = 5.26712 loss) +I0410 14:05:19.553445 18606 sgd_solver.cpp:105] Iteration 4692, lr = 0.00394783 +I0410 14:05:23.744484 18606 solver.cpp:218] Iteration 4704 (2.86337 iter/s, 4.19086s/12 iters), loss = 5.26622 +I0410 14:05:23.744530 18606 solver.cpp:237] Train net output #0: loss = 5.26622 (* 1 = 5.26622 loss) +I0410 14:05:23.744539 18606 sgd_solver.cpp:105] Iteration 4704, lr = 0.00393846 +I0410 14:05:28.577896 18606 solver.cpp:218] Iteration 4716 (2.48285 iter/s, 4.83315s/12 iters), loss = 5.28245 +I0410 14:05:28.577970 18606 solver.cpp:237] Train net output #0: loss = 5.28245 (* 1 = 5.28245 loss) +I0410 14:05:28.577982 18606 sgd_solver.cpp:105] Iteration 4716, lr = 0.00392911 +I0410 14:05:33.398655 18606 solver.cpp:218] Iteration 4728 (2.48938 iter/s, 4.82049s/12 iters), loss = 5.26216 +I0410 14:05:33.398705 18606 solver.cpp:237] Train net output #0: loss = 5.26216 (* 1 = 5.26216 loss) +I0410 14:05:33.398715 18606 sgd_solver.cpp:105] Iteration 4728, lr = 0.00391978 +I0410 14:05:38.242913 18606 solver.cpp:218] Iteration 4740 (2.4773 iter/s, 4.84399s/12 iters), loss = 5.27482 +I0410 14:05:38.243075 18606 solver.cpp:237] Train net output #0: loss = 5.27482 (* 1 = 5.27482 loss) +I0410 14:05:38.243089 18606 sgd_solver.cpp:105] Iteration 4740, lr = 0.00391047 +I0410 14:05:43.107430 18606 solver.cpp:218] Iteration 4752 (2.46703 iter/s, 4.86414s/12 iters), loss = 5.28013 +I0410 14:05:43.107476 18606 solver.cpp:237] Train net output #0: loss = 5.28013 (* 1 = 5.28013 loss) +I0410 14:05:43.107486 18606 sgd_solver.cpp:105] Iteration 4752, lr = 0.00390119 +I0410 14:05:43.612257 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:05:47.900902 18606 solver.cpp:218] Iteration 4764 (2.50355 iter/s, 4.79319s/12 iters), loss = 5.28101 +I0410 14:05:47.900952 18606 solver.cpp:237] Train net output #0: loss = 5.28101 (* 1 = 5.28101 loss) +I0410 14:05:47.900964 18606 sgd_solver.cpp:105] Iteration 4764, lr = 0.00389193 +I0410 14:05:52.713456 18606 solver.cpp:218] Iteration 4776 (2.49362 iter/s, 4.81228s/12 iters), loss = 5.26553 +I0410 14:05:52.713516 18606 solver.cpp:237] Train net output #0: loss = 5.26553 (* 1 = 5.26553 loss) +I0410 14:05:52.713528 18606 sgd_solver.cpp:105] Iteration 4776, lr = 0.00388269 +I0410 14:05:57.540452 18606 solver.cpp:218] Iteration 4788 (2.48616 iter/s, 4.82671s/12 iters), loss = 5.29171 +I0410 14:05:57.540509 18606 solver.cpp:237] Train net output #0: loss = 5.29171 (* 1 = 5.29171 loss) +I0410 14:05:57.540521 18606 sgd_solver.cpp:105] Iteration 4788, lr = 0.00387347 +I0410 14:05:59.565768 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4794.caffemodel +I0410 14:06:01.324178 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4794.solverstate +I0410 14:06:01.543222 18606 solver.cpp:330] Iteration 4794, Testing net (#0) +I0410 14:06:01.543242 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:06:04.137971 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:06:06.035521 18606 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 14:06:06.035558 18606 solver.cpp:397] Test net output #1: loss = 5.28624 (* 1 = 5.28624 loss) +I0410 14:06:07.834303 18606 solver.cpp:218] Iteration 4800 (1.1658 iter/s, 10.2934s/12 iters), loss = 5.27374 +I0410 14:06:07.834348 18606 solver.cpp:237] Train net output #0: loss = 5.27374 (* 1 = 5.27374 loss) +I0410 14:06:07.834357 18606 sgd_solver.cpp:105] Iteration 4800, lr = 0.00386427 +I0410 14:06:12.741719 18606 solver.cpp:218] Iteration 4812 (2.44541 iter/s, 4.90715s/12 iters), loss = 5.26412 +I0410 14:06:12.741843 18606 solver.cpp:237] Train net output #0: loss = 5.26412 (* 1 = 5.26412 loss) +I0410 14:06:12.741858 18606 sgd_solver.cpp:105] Iteration 4812, lr = 0.0038551 +I0410 14:06:17.687788 18606 solver.cpp:218] Iteration 4824 (2.42634 iter/s, 4.94573s/12 iters), loss = 5.28896 +I0410 14:06:17.687837 18606 solver.cpp:237] Train net output #0: loss = 5.28896 (* 1 = 5.28896 loss) +I0410 14:06:17.687847 18606 sgd_solver.cpp:105] Iteration 4824, lr = 0.00384594 +I0410 14:06:22.552706 18606 solver.cpp:218] Iteration 4836 (2.46678 iter/s, 4.86465s/12 iters), loss = 5.26469 +I0410 14:06:22.552759 18606 solver.cpp:237] Train net output #0: loss = 5.26469 (* 1 = 5.26469 loss) +I0410 14:06:22.552772 18606 sgd_solver.cpp:105] Iteration 4836, lr = 0.00383681 +I0410 14:06:22.917996 18606 blocking_queue.cpp:49] Waiting for data +I0410 14:06:27.383141 18606 solver.cpp:218] Iteration 4848 (2.48439 iter/s, 4.83016s/12 iters), loss = 5.26971 +I0410 14:06:27.383200 18606 solver.cpp:237] Train net output #0: loss = 5.26971 (* 1 = 5.26971 loss) +I0410 14:06:27.383213 18606 sgd_solver.cpp:105] Iteration 4848, lr = 0.0038277 +I0410 14:06:29.953099 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:06:32.199744 18606 solver.cpp:218] Iteration 4860 (2.49153 iter/s, 4.81632s/12 iters), loss = 5.26957 +I0410 14:06:32.199801 18606 solver.cpp:237] Train net output #0: loss = 5.26957 (* 1 = 5.26957 loss) +I0410 14:06:32.199823 18606 sgd_solver.cpp:105] Iteration 4860, lr = 0.00381862 +I0410 14:06:37.043620 18606 solver.cpp:218] Iteration 4872 (2.47749 iter/s, 4.84361s/12 iters), loss = 5.26252 +I0410 14:06:37.043661 18606 solver.cpp:237] Train net output #0: loss = 5.26252 (* 1 = 5.26252 loss) +I0410 14:06:37.043668 18606 sgd_solver.cpp:105] Iteration 4872, lr = 0.00380955 +I0410 14:06:41.825327 18606 solver.cpp:218] Iteration 4884 (2.5097 iter/s, 4.78145s/12 iters), loss = 5.26916 +I0410 14:06:41.825376 18606 solver.cpp:237] Train net output #0: loss = 5.26916 (* 1 = 5.26916 loss) +I0410 14:06:41.825385 18606 sgd_solver.cpp:105] Iteration 4884, lr = 0.0038005 +I0410 14:06:46.182646 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4896.caffemodel +I0410 14:06:46.500566 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4896.solverstate +I0410 14:06:46.717903 18606 solver.cpp:330] Iteration 4896, Testing net (#0) +I0410 14:06:46.717926 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:06:49.144224 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:06:51.071696 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:06:51.071741 18606 solver.cpp:397] Test net output #1: loss = 5.28707 (* 1 = 5.28707 loss) +I0410 14:06:51.154628 18606 solver.cpp:218] Iteration 4896 (1.28633 iter/s, 9.32885s/12 iters), loss = 5.27131 +I0410 14:06:51.154676 18606 solver.cpp:237] Train net output #0: loss = 5.27131 (* 1 = 5.27131 loss) +I0410 14:06:51.154687 18606 sgd_solver.cpp:105] Iteration 4896, lr = 0.00379148 +I0410 14:06:55.235546 18606 solver.cpp:218] Iteration 4908 (2.94068 iter/s, 4.08069s/12 iters), loss = 5.28962 +I0410 14:06:55.235594 18606 solver.cpp:237] Train net output #0: loss = 5.28962 (* 1 = 5.28962 loss) +I0410 14:06:55.235605 18606 sgd_solver.cpp:105] Iteration 4908, lr = 0.00378248 +I0410 14:07:00.155536 18606 solver.cpp:218] Iteration 4920 (2.43916 iter/s, 4.91972s/12 iters), loss = 5.27289 +I0410 14:07:00.155588 18606 solver.cpp:237] Train net output #0: loss = 5.27289 (* 1 = 5.27289 loss) +I0410 14:07:00.155601 18606 sgd_solver.cpp:105] Iteration 4920, lr = 0.0037735 +I0410 14:07:05.043416 18606 solver.cpp:218] Iteration 4932 (2.45519 iter/s, 4.88762s/12 iters), loss = 5.26298 +I0410 14:07:05.043457 18606 solver.cpp:237] Train net output #0: loss = 5.26298 (* 1 = 5.26298 loss) +I0410 14:07:05.043467 18606 sgd_solver.cpp:105] Iteration 4932, lr = 0.00376454 +I0410 14:07:09.928237 18606 solver.cpp:218] Iteration 4944 (2.45672 iter/s, 4.88456s/12 iters), loss = 5.26599 +I0410 14:07:09.928285 18606 solver.cpp:237] Train net output #0: loss = 5.26599 (* 1 = 5.26599 loss) +I0410 14:07:09.928294 18606 sgd_solver.cpp:105] Iteration 4944, lr = 0.0037556 +I0410 14:07:14.640698 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:07:14.831413 18606 solver.cpp:218] Iteration 4956 (2.44753 iter/s, 4.90291s/12 iters), loss = 5.25145 +I0410 14:07:14.831461 18606 solver.cpp:237] Train net output #0: loss = 5.25145 (* 1 = 5.25145 loss) +I0410 14:07:14.831470 18606 sgd_solver.cpp:105] Iteration 4956, lr = 0.00374669 +I0410 14:07:19.757208 18606 solver.cpp:218] Iteration 4968 (2.43629 iter/s, 4.92552s/12 iters), loss = 5.26284 +I0410 14:07:19.757354 18606 solver.cpp:237] Train net output #0: loss = 5.26284 (* 1 = 5.26284 loss) +I0410 14:07:19.757364 18606 sgd_solver.cpp:105] Iteration 4968, lr = 0.00373779 +I0410 14:07:24.693740 18606 solver.cpp:218] Iteration 4980 (2.43104 iter/s, 4.93616s/12 iters), loss = 5.291 +I0410 14:07:24.693794 18606 solver.cpp:237] Train net output #0: loss = 5.291 (* 1 = 5.291 loss) +I0410 14:07:24.693804 18606 sgd_solver.cpp:105] Iteration 4980, lr = 0.00372892 +I0410 14:07:29.492172 18606 solver.cpp:218] Iteration 4992 (2.50096 iter/s, 4.79816s/12 iters), loss = 5.28466 +I0410 14:07:29.492216 18606 solver.cpp:237] Train net output #0: loss = 5.28466 (* 1 = 5.28466 loss) +I0410 14:07:29.492225 18606 sgd_solver.cpp:105] Iteration 4992, lr = 0.00372006 +I0410 14:07:31.454432 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_4998.caffemodel +I0410 14:07:31.809309 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_4998.solverstate +I0410 14:07:32.175355 18606 solver.cpp:330] Iteration 4998, Testing net (#0) +I0410 14:07:32.175377 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:07:34.643828 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:07:36.674137 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:07:36.674187 18606 solver.cpp:397] Test net output #1: loss = 5.28684 (* 1 = 5.28684 loss) +I0410 14:07:38.640343 18606 solver.cpp:218] Iteration 5004 (1.3118 iter/s, 9.14773s/12 iters), loss = 5.27988 +I0410 14:07:38.640403 18606 solver.cpp:237] Train net output #0: loss = 5.27988 (* 1 = 5.27988 loss) +I0410 14:07:38.640414 18606 sgd_solver.cpp:105] Iteration 5004, lr = 0.00371123 +I0410 14:07:43.519879 18606 solver.cpp:218] Iteration 5016 (2.45939 iter/s, 4.87926s/12 iters), loss = 5.26573 +I0410 14:07:43.519927 18606 solver.cpp:237] Train net output #0: loss = 5.26573 (* 1 = 5.26573 loss) +I0410 14:07:43.519934 18606 sgd_solver.cpp:105] Iteration 5016, lr = 0.00370242 +I0410 14:07:48.368839 18606 solver.cpp:218] Iteration 5028 (2.47489 iter/s, 4.8487s/12 iters), loss = 5.25009 +I0410 14:07:48.368880 18606 solver.cpp:237] Train net output #0: loss = 5.25009 (* 1 = 5.25009 loss) +I0410 14:07:48.368889 18606 sgd_solver.cpp:105] Iteration 5028, lr = 0.00369363 +I0410 14:07:53.263875 18606 solver.cpp:218] Iteration 5040 (2.45159 iter/s, 4.89477s/12 iters), loss = 5.28497 +I0410 14:07:53.263955 18606 solver.cpp:237] Train net output #0: loss = 5.28497 (* 1 = 5.28497 loss) +I0410 14:07:53.263967 18606 sgd_solver.cpp:105] Iteration 5040, lr = 0.00368486 +I0410 14:07:58.200531 18606 solver.cpp:218] Iteration 5052 (2.43094 iter/s, 4.93636s/12 iters), loss = 5.27203 +I0410 14:07:58.200577 18606 solver.cpp:237] Train net output #0: loss = 5.27203 (* 1 = 5.27203 loss) +I0410 14:07:58.200588 18606 sgd_solver.cpp:105] Iteration 5052, lr = 0.00367611 +I0410 14:08:00.108194 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:03.248001 18606 solver.cpp:218] Iteration 5064 (2.37756 iter/s, 5.0472s/12 iters), loss = 5.28936 +I0410 14:08:03.248057 18606 solver.cpp:237] Train net output #0: loss = 5.28936 (* 1 = 5.28936 loss) +I0410 14:08:03.248070 18606 sgd_solver.cpp:105] Iteration 5064, lr = 0.00366738 +I0410 14:08:08.234038 18606 solver.cpp:218] Iteration 5076 (2.40685 iter/s, 4.98576s/12 iters), loss = 5.27573 +I0410 14:08:08.234094 18606 solver.cpp:237] Train net output #0: loss = 5.27573 (* 1 = 5.27573 loss) +I0410 14:08:08.234109 18606 sgd_solver.cpp:105] Iteration 5076, lr = 0.00365868 +I0410 14:08:13.172560 18606 solver.cpp:218] Iteration 5088 (2.43001 iter/s, 4.93825s/12 iters), loss = 5.2627 +I0410 14:08:13.172617 18606 solver.cpp:237] Train net output #0: loss = 5.2627 (* 1 = 5.2627 loss) +I0410 14:08:13.172631 18606 sgd_solver.cpp:105] Iteration 5088, lr = 0.00364999 +I0410 14:08:17.575860 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5100.caffemodel +I0410 14:08:17.864403 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5100.solverstate +I0410 14:08:18.064077 18606 solver.cpp:330] Iteration 5100, Testing net (#0) +I0410 14:08:18.064097 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:08:20.505532 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:22.521235 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:08:22.521278 18606 solver.cpp:397] Test net output #1: loss = 5.28654 (* 1 = 5.28654 loss) +I0410 14:08:22.604465 18606 solver.cpp:218] Iteration 5100 (1.27234 iter/s, 9.43143s/12 iters), loss = 5.26694 +I0410 14:08:22.604535 18606 solver.cpp:237] Train net output #0: loss = 5.26694 (* 1 = 5.26694 loss) +I0410 14:08:22.604550 18606 sgd_solver.cpp:105] Iteration 5100, lr = 0.00364132 +I0410 14:08:26.680573 18606 solver.cpp:218] Iteration 5112 (2.94417 iter/s, 4.07586s/12 iters), loss = 5.26539 +I0410 14:08:26.680670 18606 solver.cpp:237] Train net output #0: loss = 5.26539 (* 1 = 5.26539 loss) +I0410 14:08:26.680681 18606 sgd_solver.cpp:105] Iteration 5112, lr = 0.00363268 +I0410 14:08:31.462242 18606 solver.cpp:218] Iteration 5124 (2.50975 iter/s, 4.78135s/12 iters), loss = 5.27378 +I0410 14:08:31.462306 18606 solver.cpp:237] Train net output #0: loss = 5.27378 (* 1 = 5.27378 loss) +I0410 14:08:31.462317 18606 sgd_solver.cpp:105] Iteration 5124, lr = 0.00362405 +I0410 14:08:36.451797 18606 solver.cpp:218] Iteration 5136 (2.40516 iter/s, 4.98927s/12 iters), loss = 5.26579 +I0410 14:08:36.451853 18606 solver.cpp:237] Train net output #0: loss = 5.26579 (* 1 = 5.26579 loss) +I0410 14:08:36.451865 18606 sgd_solver.cpp:105] Iteration 5136, lr = 0.00361545 +I0410 14:08:41.351267 18606 solver.cpp:218] Iteration 5148 (2.44938 iter/s, 4.89919s/12 iters), loss = 5.26168 +I0410 14:08:41.351326 18606 solver.cpp:237] Train net output #0: loss = 5.26168 (* 1 = 5.26168 loss) +I0410 14:08:41.351339 18606 sgd_solver.cpp:105] Iteration 5148, lr = 0.00360687 +I0410 14:08:45.295231 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:08:46.201937 18606 solver.cpp:218] Iteration 5160 (2.47403 iter/s, 4.85039s/12 iters), loss = 5.25489 +I0410 14:08:46.202013 18606 solver.cpp:237] Train net output #0: loss = 5.25489 (* 1 = 5.25489 loss) +I0410 14:08:46.202025 18606 sgd_solver.cpp:105] Iteration 5160, lr = 0.0035983 +I0410 14:08:51.079649 18606 solver.cpp:218] Iteration 5172 (2.46032 iter/s, 4.87741s/12 iters), loss = 5.273 +I0410 14:08:51.079707 18606 solver.cpp:237] Train net output #0: loss = 5.273 (* 1 = 5.273 loss) +I0410 14:08:51.079720 18606 sgd_solver.cpp:105] Iteration 5172, lr = 0.00358976 +I0410 14:08:55.944145 18606 solver.cpp:218] Iteration 5184 (2.46699 iter/s, 4.86422s/12 iters), loss = 5.27071 +I0410 14:08:55.944196 18606 solver.cpp:237] Train net output #0: loss = 5.27071 (* 1 = 5.27071 loss) +I0410 14:08:55.944208 18606 sgd_solver.cpp:105] Iteration 5184, lr = 0.00358124 +I0410 14:09:00.865070 18606 solver.cpp:218] Iteration 5196 (2.4387 iter/s, 4.92066s/12 iters), loss = 5.30847 +I0410 14:09:00.865154 18606 solver.cpp:237] Train net output #0: loss = 5.30847 (* 1 = 5.30847 loss) +I0410 14:09:00.865166 18606 sgd_solver.cpp:105] Iteration 5196, lr = 0.00357273 +I0410 14:09:02.913489 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5202.caffemodel +I0410 14:09:04.369163 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5202.solverstate +I0410 14:09:04.628702 18606 solver.cpp:330] Iteration 5202, Testing net (#0) +I0410 14:09:04.628733 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:09:06.895867 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:09:08.955072 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:09:08.955106 18606 solver.cpp:397] Test net output #1: loss = 5.2867 (* 1 = 5.2867 loss) +I0410 14:09:10.792918 18606 solver.cpp:218] Iteration 5208 (1.20878 iter/s, 9.92733s/12 iters), loss = 5.27451 +I0410 14:09:10.792973 18606 solver.cpp:237] Train net output #0: loss = 5.27451 (* 1 = 5.27451 loss) +I0410 14:09:10.792984 18606 sgd_solver.cpp:105] Iteration 5208, lr = 0.00356425 +I0410 14:09:15.651332 18606 solver.cpp:218] Iteration 5220 (2.47008 iter/s, 4.85814s/12 iters), loss = 5.27472 +I0410 14:09:15.651381 18606 solver.cpp:237] Train net output #0: loss = 5.27472 (* 1 = 5.27472 loss) +I0410 14:09:15.651389 18606 sgd_solver.cpp:105] Iteration 5220, lr = 0.00355579 +I0410 14:09:20.520761 18606 solver.cpp:218] Iteration 5232 (2.46449 iter/s, 4.86916s/12 iters), loss = 5.27979 +I0410 14:09:20.520812 18606 solver.cpp:237] Train net output #0: loss = 5.27979 (* 1 = 5.27979 loss) +I0410 14:09:20.520823 18606 sgd_solver.cpp:105] Iteration 5232, lr = 0.00354735 +I0410 14:09:25.377719 18606 solver.cpp:218] Iteration 5244 (2.47082 iter/s, 4.85668s/12 iters), loss = 5.27143 +I0410 14:09:25.377776 18606 solver.cpp:237] Train net output #0: loss = 5.27143 (* 1 = 5.27143 loss) +I0410 14:09:25.377789 18606 sgd_solver.cpp:105] Iteration 5244, lr = 0.00353892 +I0410 14:09:30.330896 18606 solver.cpp:218] Iteration 5256 (2.42283 iter/s, 4.9529s/12 iters), loss = 5.26013 +I0410 14:09:30.330952 18606 solver.cpp:237] Train net output #0: loss = 5.26013 (* 1 = 5.26013 loss) +I0410 14:09:30.330965 18606 sgd_solver.cpp:105] Iteration 5256, lr = 0.00353052 +I0410 14:09:31.596568 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:09:35.258083 18606 solver.cpp:218] Iteration 5268 (2.43561 iter/s, 4.9269s/12 iters), loss = 5.27785 +I0410 14:09:35.258144 18606 solver.cpp:237] Train net output #0: loss = 5.27785 (* 1 = 5.27785 loss) +I0410 14:09:35.258163 18606 sgd_solver.cpp:105] Iteration 5268, lr = 0.00352214 +I0410 14:09:40.162961 18606 solver.cpp:218] Iteration 5280 (2.44669 iter/s, 4.90459s/12 iters), loss = 5.26878 +I0410 14:09:40.163013 18606 solver.cpp:237] Train net output #0: loss = 5.26878 (* 1 = 5.26878 loss) +I0410 14:09:40.163025 18606 sgd_solver.cpp:105] Iteration 5280, lr = 0.00351378 +I0410 14:09:45.026932 18606 solver.cpp:218] Iteration 5292 (2.46726 iter/s, 4.8637s/12 iters), loss = 5.28071 +I0410 14:09:45.026990 18606 solver.cpp:237] Train net output #0: loss = 5.28071 (* 1 = 5.28071 loss) +I0410 14:09:45.027002 18606 sgd_solver.cpp:105] Iteration 5292, lr = 0.00350544 +I0410 14:09:49.428865 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5304.caffemodel +I0410 14:09:49.746109 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5304.solverstate +I0410 14:09:49.953225 18606 solver.cpp:330] Iteration 5304, Testing net (#0) +I0410 14:09:49.953246 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:09:52.405592 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:09:54.561673 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:09:54.561715 18606 solver.cpp:397] Test net output #1: loss = 5.28647 (* 1 = 5.28647 loss) +I0410 14:09:54.644810 18606 solver.cpp:218] Iteration 5304 (1.24774 iter/s, 9.61739s/12 iters), loss = 5.27277 +I0410 14:09:54.644881 18606 solver.cpp:237] Train net output #0: loss = 5.27277 (* 1 = 5.27277 loss) +I0410 14:09:54.644896 18606 sgd_solver.cpp:105] Iteration 5304, lr = 0.00349711 +I0410 14:09:59.001164 18606 solver.cpp:218] Iteration 5316 (2.75477 iter/s, 4.35608s/12 iters), loss = 5.27214 +I0410 14:09:59.001214 18606 solver.cpp:237] Train net output #0: loss = 5.27214 (* 1 = 5.27214 loss) +I0410 14:09:59.001224 18606 sgd_solver.cpp:105] Iteration 5316, lr = 0.00348881 +I0410 14:10:03.882092 18606 solver.cpp:218] Iteration 5328 (2.45868 iter/s, 4.88066s/12 iters), loss = 5.25837 +I0410 14:10:03.882205 18606 solver.cpp:237] Train net output #0: loss = 5.25837 (* 1 = 5.25837 loss) +I0410 14:10:03.882218 18606 sgd_solver.cpp:105] Iteration 5328, lr = 0.00348053 +I0410 14:10:08.826267 18606 solver.cpp:218] Iteration 5340 (2.42726 iter/s, 4.94384s/12 iters), loss = 5.29928 +I0410 14:10:08.826319 18606 solver.cpp:237] Train net output #0: loss = 5.29928 (* 1 = 5.29928 loss) +I0410 14:10:08.826330 18606 sgd_solver.cpp:105] Iteration 5340, lr = 0.00347226 +I0410 14:10:13.618104 18606 solver.cpp:218] Iteration 5352 (2.5044 iter/s, 4.79157s/12 iters), loss = 5.2757 +I0410 14:10:13.618158 18606 solver.cpp:237] Train net output #0: loss = 5.2757 (* 1 = 5.2757 loss) +I0410 14:10:13.618171 18606 sgd_solver.cpp:105] Iteration 5352, lr = 0.00346402 +I0410 14:10:16.892119 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:10:18.417153 18606 solver.cpp:218] Iteration 5364 (2.50064 iter/s, 4.79878s/12 iters), loss = 5.27661 +I0410 14:10:18.417207 18606 solver.cpp:237] Train net output #0: loss = 5.27661 (* 1 = 5.27661 loss) +I0410 14:10:18.417218 18606 sgd_solver.cpp:105] Iteration 5364, lr = 0.0034558 +I0410 14:10:23.264961 18606 solver.cpp:218] Iteration 5376 (2.47549 iter/s, 4.84753s/12 iters), loss = 5.26417 +I0410 14:10:23.265023 18606 solver.cpp:237] Train net output #0: loss = 5.26417 (* 1 = 5.26417 loss) +I0410 14:10:23.265035 18606 sgd_solver.cpp:105] Iteration 5376, lr = 0.00344759 +I0410 14:10:28.427907 18606 solver.cpp:218] Iteration 5388 (2.32438 iter/s, 5.16266s/12 iters), loss = 5.2681 +I0410 14:10:28.427956 18606 solver.cpp:237] Train net output #0: loss = 5.2681 (* 1 = 5.2681 loss) +I0410 14:10:28.427966 18606 sgd_solver.cpp:105] Iteration 5388, lr = 0.00343941 +I0410 14:10:33.199200 18606 solver.cpp:218] Iteration 5400 (2.51518 iter/s, 4.77103s/12 iters), loss = 5.2694 +I0410 14:10:33.199247 18606 solver.cpp:237] Train net output #0: loss = 5.2694 (* 1 = 5.2694 loss) +I0410 14:10:33.199256 18606 sgd_solver.cpp:105] Iteration 5400, lr = 0.00343124 +I0410 14:10:35.181666 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5406.caffemodel +I0410 14:10:36.007827 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5406.solverstate +I0410 14:10:36.443799 18606 solver.cpp:330] Iteration 5406, Testing net (#0) +I0410 14:10:36.443826 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:10:38.657094 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:10:40.780498 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:10:40.780546 18606 solver.cpp:397] Test net output #1: loss = 5.28658 (* 1 = 5.28658 loss) +I0410 14:10:42.534358 18606 solver.cpp:218] Iteration 5412 (1.28553 iter/s, 9.33471s/12 iters), loss = 5.26319 +I0410 14:10:42.534397 18606 solver.cpp:237] Train net output #0: loss = 5.26319 (* 1 = 5.26319 loss) +I0410 14:10:42.534407 18606 sgd_solver.cpp:105] Iteration 5412, lr = 0.00342309 +I0410 14:10:47.328783 18606 solver.cpp:218] Iteration 5424 (2.50304 iter/s, 4.79416s/12 iters), loss = 5.28161 +I0410 14:10:47.328843 18606 solver.cpp:237] Train net output #0: loss = 5.28161 (* 1 = 5.28161 loss) +I0410 14:10:47.328856 18606 sgd_solver.cpp:105] Iteration 5424, lr = 0.00341497 +I0410 14:10:52.145973 18606 solver.cpp:218] Iteration 5436 (2.49123 iter/s, 4.8169s/12 iters), loss = 5.26608 +I0410 14:10:52.146034 18606 solver.cpp:237] Train net output #0: loss = 5.26608 (* 1 = 5.26608 loss) +I0410 14:10:52.146045 18606 sgd_solver.cpp:105] Iteration 5436, lr = 0.00340686 +I0410 14:10:56.966616 18606 solver.cpp:218] Iteration 5448 (2.48944 iter/s, 4.82036s/12 iters), loss = 5.27647 +I0410 14:10:56.966670 18606 solver.cpp:237] Train net output #0: loss = 5.27647 (* 1 = 5.27647 loss) +I0410 14:10:56.966681 18606 sgd_solver.cpp:105] Iteration 5448, lr = 0.00339877 +I0410 14:11:01.804482 18606 solver.cpp:218] Iteration 5460 (2.48057 iter/s, 4.8376s/12 iters), loss = 5.28095 +I0410 14:11:01.804531 18606 solver.cpp:237] Train net output #0: loss = 5.28095 (* 1 = 5.28095 loss) +I0410 14:11:01.804540 18606 sgd_solver.cpp:105] Iteration 5460, lr = 0.0033907 +I0410 14:11:02.371476 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:11:06.659054 18606 solver.cpp:218] Iteration 5472 (2.47204 iter/s, 4.8543s/12 iters), loss = 5.27825 +I0410 14:11:06.659188 18606 solver.cpp:237] Train net output #0: loss = 5.27825 (* 1 = 5.27825 loss) +I0410 14:11:06.659198 18606 sgd_solver.cpp:105] Iteration 5472, lr = 0.00338265 +I0410 14:11:11.505152 18606 solver.cpp:218] Iteration 5484 (2.4764 iter/s, 4.84574s/12 iters), loss = 5.27338 +I0410 14:11:11.505206 18606 solver.cpp:237] Train net output #0: loss = 5.27338 (* 1 = 5.27338 loss) +I0410 14:11:11.505218 18606 sgd_solver.cpp:105] Iteration 5484, lr = 0.00337462 +I0410 14:11:16.309969 18606 solver.cpp:218] Iteration 5496 (2.49764 iter/s, 4.80453s/12 iters), loss = 5.29275 +I0410 14:11:16.310022 18606 solver.cpp:237] Train net output #0: loss = 5.29275 (* 1 = 5.29275 loss) +I0410 14:11:16.310034 18606 sgd_solver.cpp:105] Iteration 5496, lr = 0.00336661 +I0410 14:11:20.728022 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5508.caffemodel +I0410 14:11:21.040446 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5508.solverstate +I0410 14:11:21.247809 18606 solver.cpp:330] Iteration 5508, Testing net (#0) +I0410 14:11:21.247838 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:11:23.416785 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:11:25.596614 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:11:25.596666 18606 solver.cpp:397] Test net output #1: loss = 5.28751 (* 1 = 5.28751 loss) +I0410 14:11:25.678936 18606 solver.cpp:218] Iteration 5508 (1.28089 iter/s, 9.3685s/12 iters), loss = 5.27542 +I0410 14:11:25.678987 18606 solver.cpp:237] Train net output #0: loss = 5.27542 (* 1 = 5.27542 loss) +I0410 14:11:25.678999 18606 sgd_solver.cpp:105] Iteration 5508, lr = 0.00335861 +I0410 14:11:29.932080 18606 solver.cpp:218] Iteration 5520 (2.8216 iter/s, 4.2529s/12 iters), loss = 5.27176 +I0410 14:11:29.932119 18606 solver.cpp:237] Train net output #0: loss = 5.27176 (* 1 = 5.27176 loss) +I0410 14:11:29.932129 18606 sgd_solver.cpp:105] Iteration 5520, lr = 0.00335064 +I0410 14:11:30.676751 18606 blocking_queue.cpp:49] Waiting for data +I0410 14:11:35.303225 18606 solver.cpp:218] Iteration 5532 (2.23428 iter/s, 5.37086s/12 iters), loss = 5.28679 +I0410 14:11:35.303280 18606 solver.cpp:237] Train net output #0: loss = 5.28679 (* 1 = 5.28679 loss) +I0410 14:11:35.303290 18606 sgd_solver.cpp:105] Iteration 5532, lr = 0.00334268 +I0410 14:11:40.116153 18606 solver.cpp:218] Iteration 5544 (2.49343 iter/s, 4.81265s/12 iters), loss = 5.2587 +I0410 14:11:40.116286 18606 solver.cpp:237] Train net output #0: loss = 5.2587 (* 1 = 5.2587 loss) +I0410 14:11:40.116302 18606 sgd_solver.cpp:105] Iteration 5544, lr = 0.00333475 +I0410 14:11:44.940609 18606 solver.cpp:218] Iteration 5556 (2.48751 iter/s, 4.82411s/12 iters), loss = 5.26942 +I0410 14:11:44.940654 18606 solver.cpp:237] Train net output #0: loss = 5.26942 (* 1 = 5.26942 loss) +I0410 14:11:44.940663 18606 sgd_solver.cpp:105] Iteration 5556, lr = 0.00332683 +I0410 14:11:47.541388 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:11:49.750900 18606 solver.cpp:218] Iteration 5568 (2.49479 iter/s, 4.81003s/12 iters), loss = 5.27499 +I0410 14:11:49.750960 18606 solver.cpp:237] Train net output #0: loss = 5.27499 (* 1 = 5.27499 loss) +I0410 14:11:49.750977 18606 sgd_solver.cpp:105] Iteration 5568, lr = 0.00331893 +I0410 14:11:54.562153 18606 solver.cpp:218] Iteration 5580 (2.4943 iter/s, 4.81098s/12 iters), loss = 5.25914 +I0410 14:11:54.562207 18606 solver.cpp:237] Train net output #0: loss = 5.25914 (* 1 = 5.25914 loss) +I0410 14:11:54.562217 18606 sgd_solver.cpp:105] Iteration 5580, lr = 0.00331105 +I0410 14:11:59.596202 18606 solver.cpp:218] Iteration 5592 (2.3839 iter/s, 5.03377s/12 iters), loss = 5.27104 +I0410 14:11:59.596247 18606 solver.cpp:237] Train net output #0: loss = 5.27104 (* 1 = 5.27104 loss) +I0410 14:11:59.596256 18606 sgd_solver.cpp:105] Iteration 5592, lr = 0.00330319 +I0410 14:12:04.461194 18606 solver.cpp:218] Iteration 5604 (2.46674 iter/s, 4.86472s/12 iters), loss = 5.26302 +I0410 14:12:04.461244 18606 solver.cpp:237] Train net output #0: loss = 5.26302 (* 1 = 5.26302 loss) +I0410 14:12:04.461256 18606 sgd_solver.cpp:105] Iteration 5604, lr = 0.00329535 +I0410 14:12:06.463054 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5610.caffemodel +I0410 14:12:06.767870 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5610.solverstate +I0410 14:12:06.969218 18606 solver.cpp:330] Iteration 5610, Testing net (#0) +I0410 14:12:06.969236 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:12:09.157711 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:11.364478 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:12:11.364655 18606 solver.cpp:397] Test net output #1: loss = 5.28688 (* 1 = 5.28688 loss) +I0410 14:12:13.235530 18606 solver.cpp:218] Iteration 5616 (1.36769 iter/s, 8.7739s/12 iters), loss = 5.29456 +I0410 14:12:13.235587 18606 solver.cpp:237] Train net output #0: loss = 5.29456 (* 1 = 5.29456 loss) +I0410 14:12:13.235601 18606 sgd_solver.cpp:105] Iteration 5616, lr = 0.00328752 +I0410 14:12:18.117832 18606 solver.cpp:218] Iteration 5628 (2.458 iter/s, 4.88202s/12 iters), loss = 5.27476 +I0410 14:12:18.117885 18606 solver.cpp:237] Train net output #0: loss = 5.27476 (* 1 = 5.27476 loss) +I0410 14:12:18.117897 18606 sgd_solver.cpp:105] Iteration 5628, lr = 0.00327972 +I0410 14:12:23.531421 18606 solver.cpp:218] Iteration 5640 (2.21677 iter/s, 5.41329s/12 iters), loss = 5.26332 +I0410 14:12:23.531479 18606 solver.cpp:237] Train net output #0: loss = 5.26332 (* 1 = 5.26332 loss) +I0410 14:12:23.531491 18606 sgd_solver.cpp:105] Iteration 5640, lr = 0.00327193 +I0410 14:12:28.583969 18606 solver.cpp:218] Iteration 5652 (2.37518 iter/s, 5.05225s/12 iters), loss = 5.26757 +I0410 14:12:28.584024 18606 solver.cpp:237] Train net output #0: loss = 5.26757 (* 1 = 5.26757 loss) +I0410 14:12:28.584036 18606 sgd_solver.cpp:105] Iteration 5652, lr = 0.00326416 +I0410 14:12:33.251344 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:33.410856 18606 solver.cpp:218] Iteration 5664 (2.48621 iter/s, 4.82662s/12 iters), loss = 5.25239 +I0410 14:12:33.410910 18606 solver.cpp:237] Train net output #0: loss = 5.25239 (* 1 = 5.25239 loss) +I0410 14:12:33.410921 18606 sgd_solver.cpp:105] Iteration 5664, lr = 0.00325641 +I0410 14:12:38.342687 18606 solver.cpp:218] Iteration 5676 (2.43331 iter/s, 4.93155s/12 iters), loss = 5.2636 +I0410 14:12:38.342736 18606 solver.cpp:237] Train net output #0: loss = 5.2636 (* 1 = 5.2636 loss) +I0410 14:12:38.342746 18606 sgd_solver.cpp:105] Iteration 5676, lr = 0.00324868 +I0410 14:12:43.208998 18606 solver.cpp:218] Iteration 5688 (2.46607 iter/s, 4.86604s/12 iters), loss = 5.29615 +I0410 14:12:43.209105 18606 solver.cpp:237] Train net output #0: loss = 5.29615 (* 1 = 5.29615 loss) +I0410 14:12:43.209116 18606 sgd_solver.cpp:105] Iteration 5688, lr = 0.00324097 +I0410 14:12:48.028218 18606 solver.cpp:218] Iteration 5700 (2.4902 iter/s, 4.81889s/12 iters), loss = 5.28626 +I0410 14:12:48.028266 18606 solver.cpp:237] Train net output #0: loss = 5.28626 (* 1 = 5.28626 loss) +I0410 14:12:48.028276 18606 sgd_solver.cpp:105] Iteration 5700, lr = 0.00323328 +I0410 14:12:52.413301 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5712.caffemodel +I0410 14:12:52.840662 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5712.solverstate +I0410 14:12:53.058212 18606 solver.cpp:330] Iteration 5712, Testing net (#0) +I0410 14:12:53.058239 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:12:55.225198 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:12:57.464390 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:12:57.464428 18606 solver.cpp:397] Test net output #1: loss = 5.28686 (* 1 = 5.28686 loss) +I0410 14:12:57.547559 18606 solver.cpp:218] Iteration 5712 (1.26065 iter/s, 9.51887s/12 iters), loss = 5.27863 +I0410 14:12:57.547605 18606 solver.cpp:237] Train net output #0: loss = 5.27863 (* 1 = 5.27863 loss) +I0410 14:12:57.547613 18606 sgd_solver.cpp:105] Iteration 5712, lr = 0.0032256 +I0410 14:13:01.855170 18606 solver.cpp:218] Iteration 5724 (2.78592 iter/s, 4.30737s/12 iters), loss = 5.26579 +I0410 14:13:01.855211 18606 solver.cpp:237] Train net output #0: loss = 5.26579 (* 1 = 5.26579 loss) +I0410 14:13:01.855221 18606 sgd_solver.cpp:105] Iteration 5724, lr = 0.00321794 +I0410 14:13:06.824302 18606 solver.cpp:218] Iteration 5736 (2.41504 iter/s, 4.96886s/12 iters), loss = 5.24601 +I0410 14:13:06.824365 18606 solver.cpp:237] Train net output #0: loss = 5.24601 (* 1 = 5.24601 loss) +I0410 14:13:06.824378 18606 sgd_solver.cpp:105] Iteration 5736, lr = 0.0032103 +I0410 14:13:11.645021 18606 solver.cpp:218] Iteration 5748 (2.4894 iter/s, 4.82043s/12 iters), loss = 5.28072 +I0410 14:13:11.645079 18606 solver.cpp:237] Train net output #0: loss = 5.28072 (* 1 = 5.28072 loss) +I0410 14:13:11.645092 18606 sgd_solver.cpp:105] Iteration 5748, lr = 0.00320268 +I0410 14:13:16.560770 18606 solver.cpp:218] Iteration 5760 (2.44127 iter/s, 4.91547s/12 iters), loss = 5.26418 +I0410 14:13:16.560936 18606 solver.cpp:237] Train net output #0: loss = 5.26418 (* 1 = 5.26418 loss) +I0410 14:13:16.560950 18606 sgd_solver.cpp:105] Iteration 5760, lr = 0.00319508 +I0410 14:13:18.484045 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:21.459812 18606 solver.cpp:218] Iteration 5772 (2.44965 iter/s, 4.89866s/12 iters), loss = 5.29394 +I0410 14:13:21.459867 18606 solver.cpp:237] Train net output #0: loss = 5.29394 (* 1 = 5.29394 loss) +I0410 14:13:21.459879 18606 sgd_solver.cpp:105] Iteration 5772, lr = 0.00318749 +I0410 14:13:26.386536 18606 solver.cpp:218] Iteration 5784 (2.43583 iter/s, 4.92644s/12 iters), loss = 5.26921 +I0410 14:13:26.386582 18606 solver.cpp:237] Train net output #0: loss = 5.26921 (* 1 = 5.26921 loss) +I0410 14:13:26.386592 18606 sgd_solver.cpp:105] Iteration 5784, lr = 0.00317992 +I0410 14:13:31.304817 18606 solver.cpp:218] Iteration 5796 (2.44001 iter/s, 4.918s/12 iters), loss = 5.26692 +I0410 14:13:31.304881 18606 solver.cpp:237] Train net output #0: loss = 5.26692 (* 1 = 5.26692 loss) +I0410 14:13:31.304894 18606 sgd_solver.cpp:105] Iteration 5796, lr = 0.00317237 +I0410 14:13:36.153946 18606 solver.cpp:218] Iteration 5808 (2.47481 iter/s, 4.84885s/12 iters), loss = 5.26497 +I0410 14:13:36.154003 18606 solver.cpp:237] Train net output #0: loss = 5.26497 (* 1 = 5.26497 loss) +I0410 14:13:36.154013 18606 sgd_solver.cpp:105] Iteration 5808, lr = 0.00316484 +I0410 14:13:38.207839 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5814.caffemodel +I0410 14:13:38.639030 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5814.solverstate +I0410 14:13:38.843195 18606 solver.cpp:330] Iteration 5814, Testing net (#0) +I0410 14:13:38.843220 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:13:40.936308 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:13:43.405737 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:13:43.405791 18606 solver.cpp:397] Test net output #1: loss = 5.28677 (* 1 = 5.28677 loss) +I0410 14:13:45.322602 18606 solver.cpp:218] Iteration 5820 (1.30887 iter/s, 9.16819s/12 iters), loss = 5.27549 +I0410 14:13:45.322654 18606 solver.cpp:237] Train net output #0: loss = 5.27549 (* 1 = 5.27549 loss) +I0410 14:13:45.322664 18606 sgd_solver.cpp:105] Iteration 5820, lr = 0.00315733 +I0410 14:13:50.119510 18606 solver.cpp:218] Iteration 5832 (2.50175 iter/s, 4.79664s/12 iters), loss = 5.27391 +I0410 14:13:50.119632 18606 solver.cpp:237] Train net output #0: loss = 5.27391 (* 1 = 5.27391 loss) +I0410 14:13:50.119644 18606 sgd_solver.cpp:105] Iteration 5832, lr = 0.00314983 +I0410 14:13:54.931375 18606 solver.cpp:218] Iteration 5844 (2.49401 iter/s, 4.81153s/12 iters), loss = 5.2646 +I0410 14:13:54.931433 18606 solver.cpp:237] Train net output #0: loss = 5.2646 (* 1 = 5.2646 loss) +I0410 14:13:54.931447 18606 sgd_solver.cpp:105] Iteration 5844, lr = 0.00314235 +I0410 14:13:59.807703 18606 solver.cpp:218] Iteration 5856 (2.46101 iter/s, 4.87605s/12 iters), loss = 5.26131 +I0410 14:13:59.807754 18606 solver.cpp:237] Train net output #0: loss = 5.26131 (* 1 = 5.26131 loss) +I0410 14:13:59.807765 18606 sgd_solver.cpp:105] Iteration 5856, lr = 0.00313489 +I0410 14:14:03.978732 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:14:04.758424 18606 solver.cpp:218] Iteration 5868 (2.42402 iter/s, 4.95045s/12 iters), loss = 5.25619 +I0410 14:14:04.758466 18606 solver.cpp:237] Train net output #0: loss = 5.25619 (* 1 = 5.25619 loss) +I0410 14:14:04.758476 18606 sgd_solver.cpp:105] Iteration 5868, lr = 0.00312745 +I0410 14:14:09.595238 18606 solver.cpp:218] Iteration 5880 (2.48111 iter/s, 4.83654s/12 iters), loss = 5.27724 +I0410 14:14:09.595301 18606 solver.cpp:237] Train net output #0: loss = 5.27724 (* 1 = 5.27724 loss) +I0410 14:14:09.595315 18606 sgd_solver.cpp:105] Iteration 5880, lr = 0.00312002 +I0410 14:14:14.372790 18606 solver.cpp:218] Iteration 5892 (2.51189 iter/s, 4.77727s/12 iters), loss = 5.2702 +I0410 14:14:14.372840 18606 solver.cpp:237] Train net output #0: loss = 5.2702 (* 1 = 5.2702 loss) +I0410 14:14:14.372851 18606 sgd_solver.cpp:105] Iteration 5892, lr = 0.00311262 +I0410 14:14:19.286720 18606 solver.cpp:218] Iteration 5904 (2.44217 iter/s, 4.91366s/12 iters), loss = 5.30341 +I0410 14:14:19.286770 18606 solver.cpp:237] Train net output #0: loss = 5.30341 (* 1 = 5.30341 loss) +I0410 14:14:19.286780 18606 sgd_solver.cpp:105] Iteration 5904, lr = 0.00310523 +I0410 14:14:23.699501 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_5916.caffemodel +I0410 14:14:24.031630 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_5916.solverstate +I0410 14:14:24.247866 18606 solver.cpp:330] Iteration 5916, Testing net (#0) +I0410 14:14:24.247885 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:14:26.341157 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:14:28.784627 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:14:28.784678 18606 solver.cpp:397] Test net output #1: loss = 5.28682 (* 1 = 5.28682 loss) +I0410 14:14:28.868000 18606 solver.cpp:218] Iteration 5916 (1.2525 iter/s, 9.5808s/12 iters), loss = 5.26609 +I0410 14:14:28.868053 18606 solver.cpp:237] Train net output #0: loss = 5.26609 (* 1 = 5.26609 loss) +I0410 14:14:28.868065 18606 sgd_solver.cpp:105] Iteration 5916, lr = 0.00309785 +I0410 14:14:32.945164 18606 solver.cpp:218] Iteration 5928 (2.9434 iter/s, 4.07692s/12 iters), loss = 5.27107 +I0410 14:14:32.945209 18606 solver.cpp:237] Train net output #0: loss = 5.27107 (* 1 = 5.27107 loss) +I0410 14:14:32.945219 18606 sgd_solver.cpp:105] Iteration 5928, lr = 0.0030905 +I0410 14:14:37.755585 18606 solver.cpp:218] Iteration 5940 (2.49472 iter/s, 4.81016s/12 iters), loss = 5.28097 +I0410 14:14:37.755627 18606 solver.cpp:237] Train net output #0: loss = 5.28097 (* 1 = 5.28097 loss) +I0410 14:14:37.755635 18606 sgd_solver.cpp:105] Iteration 5940, lr = 0.00308316 +I0410 14:14:42.542171 18606 solver.cpp:218] Iteration 5952 (2.50714 iter/s, 4.78632s/12 iters), loss = 5.27458 +I0410 14:14:42.542223 18606 solver.cpp:237] Train net output #0: loss = 5.27458 (* 1 = 5.27458 loss) +I0410 14:14:42.542235 18606 sgd_solver.cpp:105] Iteration 5952, lr = 0.00307584 +I0410 14:14:47.557369 18606 solver.cpp:218] Iteration 5964 (2.39286 iter/s, 5.01492s/12 iters), loss = 5.25839 +I0410 14:14:47.557418 18606 solver.cpp:237] Train net output #0: loss = 5.25839 (* 1 = 5.25839 loss) +I0410 14:14:47.557428 18606 sgd_solver.cpp:105] Iteration 5964, lr = 0.00306854 +I0410 14:14:48.918598 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:14:52.472872 18606 solver.cpp:218] Iteration 5976 (2.44139 iter/s, 4.91523s/12 iters), loss = 5.27648 +I0410 14:14:52.472914 18606 solver.cpp:237] Train net output #0: loss = 5.27648 (* 1 = 5.27648 loss) +I0410 14:14:52.472924 18606 sgd_solver.cpp:105] Iteration 5976, lr = 0.00306125 +I0410 14:14:57.293213 18606 solver.cpp:218] Iteration 5988 (2.48958 iter/s, 4.82008s/12 iters), loss = 5.2638 +I0410 14:14:57.293344 18606 solver.cpp:237] Train net output #0: loss = 5.2638 (* 1 = 5.2638 loss) +I0410 14:14:57.293354 18606 sgd_solver.cpp:105] Iteration 5988, lr = 0.00305398 +I0410 14:15:02.118278 18606 solver.cpp:218] Iteration 6000 (2.48719 iter/s, 4.82472s/12 iters), loss = 5.28045 +I0410 14:15:02.118320 18606 solver.cpp:237] Train net output #0: loss = 5.28045 (* 1 = 5.28045 loss) +I0410 14:15:02.118330 18606 sgd_solver.cpp:105] Iteration 6000, lr = 0.00304673 +I0410 14:15:06.943420 18606 solver.cpp:218] Iteration 6012 (2.48711 iter/s, 4.82488s/12 iters), loss = 5.26814 +I0410 14:15:06.943481 18606 solver.cpp:237] Train net output #0: loss = 5.26814 (* 1 = 5.26814 loss) +I0410 14:15:06.943495 18606 sgd_solver.cpp:105] Iteration 6012, lr = 0.0030395 +I0410 14:15:08.945430 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6018.caffemodel +I0410 14:15:09.258366 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6018.solverstate +I0410 14:15:09.466022 18606 solver.cpp:330] Iteration 6018, Testing net (#0) +I0410 14:15:09.466049 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:15:11.483726 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:13.871227 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:15:13.871275 18606 solver.cpp:397] Test net output #1: loss = 5.28686 (* 1 = 5.28686 loss) +I0410 14:15:15.749620 18606 solver.cpp:218] Iteration 6024 (1.36275 iter/s, 8.80575s/12 iters), loss = 5.26749 +I0410 14:15:15.749660 18606 solver.cpp:237] Train net output #0: loss = 5.26749 (* 1 = 5.26749 loss) +I0410 14:15:15.749667 18606 sgd_solver.cpp:105] Iteration 6024, lr = 0.00303228 +I0410 14:15:20.608562 18606 solver.cpp:218] Iteration 6036 (2.46981 iter/s, 4.85868s/12 iters), loss = 5.2607 +I0410 14:15:20.608608 18606 solver.cpp:237] Train net output #0: loss = 5.2607 (* 1 = 5.2607 loss) +I0410 14:15:20.608618 18606 sgd_solver.cpp:105] Iteration 6036, lr = 0.00302508 +I0410 14:15:25.521006 18606 solver.cpp:218] Iteration 6048 (2.44291 iter/s, 4.91217s/12 iters), loss = 5.30268 +I0410 14:15:25.521060 18606 solver.cpp:237] Train net output #0: loss = 5.30268 (* 1 = 5.30268 loss) +I0410 14:15:25.521073 18606 sgd_solver.cpp:105] Iteration 6048, lr = 0.0030179 +I0410 14:15:30.358203 18606 solver.cpp:218] Iteration 6060 (2.48091 iter/s, 4.83693s/12 iters), loss = 5.27756 +I0410 14:15:30.358294 18606 solver.cpp:237] Train net output #0: loss = 5.27756 (* 1 = 5.27756 loss) +I0410 14:15:30.358305 18606 sgd_solver.cpp:105] Iteration 6060, lr = 0.00301074 +I0410 14:15:33.662904 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:35.221904 18606 solver.cpp:218] Iteration 6072 (2.46742 iter/s, 4.86338s/12 iters), loss = 5.27396 +I0410 14:15:35.221976 18606 solver.cpp:237] Train net output #0: loss = 5.27396 (* 1 = 5.27396 loss) +I0410 14:15:35.221988 18606 sgd_solver.cpp:105] Iteration 6072, lr = 0.00300359 +I0410 14:15:40.073585 18606 solver.cpp:218] Iteration 6084 (2.47351 iter/s, 4.85141s/12 iters), loss = 5.26017 +I0410 14:15:40.073637 18606 solver.cpp:237] Train net output #0: loss = 5.26017 (* 1 = 5.26017 loss) +I0410 14:15:40.073647 18606 sgd_solver.cpp:105] Iteration 6084, lr = 0.00299646 +I0410 14:15:45.128301 18606 solver.cpp:218] Iteration 6096 (2.37415 iter/s, 5.05444s/12 iters), loss = 5.26121 +I0410 14:15:45.128351 18606 solver.cpp:237] Train net output #0: loss = 5.26121 (* 1 = 5.26121 loss) +I0410 14:15:45.128360 18606 sgd_solver.cpp:105] Iteration 6096, lr = 0.00298934 +I0410 14:15:50.028594 18606 solver.cpp:218] Iteration 6108 (2.44897 iter/s, 4.90002s/12 iters), loss = 5.2744 +I0410 14:15:50.028640 18606 solver.cpp:237] Train net output #0: loss = 5.2744 (* 1 = 5.2744 loss) +I0410 14:15:50.028651 18606 sgd_solver.cpp:105] Iteration 6108, lr = 0.00298225 +I0410 14:15:54.430259 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6120.caffemodel +I0410 14:15:54.749049 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6120.solverstate +I0410 14:15:54.965543 18606 solver.cpp:330] Iteration 6120, Testing net (#0) +I0410 14:15:54.965564 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:15:57.026083 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:15:59.445247 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:15:59.445297 18606 solver.cpp:397] Test net output #1: loss = 5.28678 (* 1 = 5.28678 loss) +I0410 14:15:59.526506 18606 solver.cpp:218] Iteration 6120 (1.2635 iter/s, 9.49744s/12 iters), loss = 5.26508 +I0410 14:15:59.526585 18606 solver.cpp:237] Train net output #0: loss = 5.26508 (* 1 = 5.26508 loss) +I0410 14:15:59.526602 18606 sgd_solver.cpp:105] Iteration 6120, lr = 0.00297517 +I0410 14:16:03.651469 18606 solver.cpp:218] Iteration 6132 (2.90931 iter/s, 4.12469s/12 iters), loss = 5.27623 +I0410 14:16:03.651612 18606 solver.cpp:237] Train net output #0: loss = 5.27623 (* 1 = 5.27623 loss) +I0410 14:16:03.651624 18606 sgd_solver.cpp:105] Iteration 6132, lr = 0.0029681 +I0410 14:16:08.526007 18606 solver.cpp:218] Iteration 6144 (2.46196 iter/s, 4.87417s/12 iters), loss = 5.26829 +I0410 14:16:08.526072 18606 solver.cpp:237] Train net output #0: loss = 5.26829 (* 1 = 5.26829 loss) +I0410 14:16:08.526085 18606 sgd_solver.cpp:105] Iteration 6144, lr = 0.00296105 +I0410 14:16:13.310883 18606 solver.cpp:218] Iteration 6156 (2.50805 iter/s, 4.78459s/12 iters), loss = 5.27734 +I0410 14:16:13.310935 18606 solver.cpp:237] Train net output #0: loss = 5.27734 (* 1 = 5.27734 loss) +I0410 14:16:13.310945 18606 sgd_solver.cpp:105] Iteration 6156, lr = 0.00295402 +I0410 14:16:18.131881 18606 solver.cpp:218] Iteration 6168 (2.48925 iter/s, 4.82072s/12 iters), loss = 5.28978 +I0410 14:16:18.131934 18606 solver.cpp:237] Train net output #0: loss = 5.28978 (* 1 = 5.28978 loss) +I0410 14:16:18.131947 18606 sgd_solver.cpp:105] Iteration 6168, lr = 0.00294701 +I0410 14:16:18.698813 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:16:22.928088 18606 solver.cpp:218] Iteration 6180 (2.50212 iter/s, 4.79594s/12 iters), loss = 5.28236 +I0410 14:16:22.928139 18606 solver.cpp:237] Train net output #0: loss = 5.28236 (* 1 = 5.28236 loss) +I0410 14:16:22.928150 18606 sgd_solver.cpp:105] Iteration 6180, lr = 0.00294001 +I0410 14:16:27.746431 18606 solver.cpp:218] Iteration 6192 (2.49062 iter/s, 4.81808s/12 iters), loss = 5.27028 +I0410 14:16:27.746477 18606 solver.cpp:237] Train net output #0: loss = 5.27028 (* 1 = 5.27028 loss) +I0410 14:16:27.746487 18606 sgd_solver.cpp:105] Iteration 6192, lr = 0.00293303 +I0410 14:16:32.718829 18606 solver.cpp:218] Iteration 6204 (2.41346 iter/s, 4.97212s/12 iters), loss = 5.28807 +I0410 14:16:32.718879 18606 solver.cpp:237] Train net output #0: loss = 5.28807 (* 1 = 5.28807 loss) +I0410 14:16:32.718889 18606 sgd_solver.cpp:105] Iteration 6204, lr = 0.00292607 +I0410 14:16:37.663851 18606 solver.cpp:218] Iteration 6216 (2.42682 iter/s, 4.94474s/12 iters), loss = 5.27869 +I0410 14:16:37.663971 18606 solver.cpp:237] Train net output #0: loss = 5.27869 (* 1 = 5.27869 loss) +I0410 14:16:37.663985 18606 sgd_solver.cpp:105] Iteration 6216, lr = 0.00291912 +I0410 14:16:39.627892 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6222.caffemodel +I0410 14:16:40.004349 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6222.solverstate +I0410 14:16:40.221585 18606 solver.cpp:330] Iteration 6222, Testing net (#0) +I0410 14:16:40.221614 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:16:42.150281 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:16:43.058531 18606 blocking_queue.cpp:49] Waiting for data +I0410 14:16:44.586686 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:16:44.586730 18606 solver.cpp:397] Test net output #1: loss = 5.28659 (* 1 = 5.28659 loss) +I0410 14:16:46.428620 18606 solver.cpp:218] Iteration 6228 (1.3692 iter/s, 8.76426s/12 iters), loss = 5.27599 +I0410 14:16:46.428665 18606 solver.cpp:237] Train net output #0: loss = 5.27599 (* 1 = 5.27599 loss) +I0410 14:16:46.428674 18606 sgd_solver.cpp:105] Iteration 6228, lr = 0.00291219 +I0410 14:16:51.194311 18606 solver.cpp:218] Iteration 6240 (2.51814 iter/s, 4.76542s/12 iters), loss = 5.28051 +I0410 14:16:51.194372 18606 solver.cpp:237] Train net output #0: loss = 5.28051 (* 1 = 5.28051 loss) +I0410 14:16:51.194384 18606 sgd_solver.cpp:105] Iteration 6240, lr = 0.00290528 +I0410 14:16:56.060418 18606 solver.cpp:218] Iteration 6252 (2.46618 iter/s, 4.86583s/12 iters), loss = 5.26049 +I0410 14:16:56.060472 18606 solver.cpp:237] Train net output #0: loss = 5.26049 (* 1 = 5.26049 loss) +I0410 14:16:56.060482 18606 sgd_solver.cpp:105] Iteration 6252, lr = 0.00289838 +I0410 14:17:00.891330 18606 solver.cpp:218] Iteration 6264 (2.48415 iter/s, 4.83063s/12 iters), loss = 5.26478 +I0410 14:17:00.891393 18606 solver.cpp:237] Train net output #0: loss = 5.26478 (* 1 = 5.26478 loss) +I0410 14:17:00.891407 18606 sgd_solver.cpp:105] Iteration 6264, lr = 0.0028915 +I0410 14:17:03.637398 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:17:05.801021 18606 solver.cpp:218] Iteration 6276 (2.44429 iter/s, 4.9094s/12 iters), loss = 5.27825 +I0410 14:17:05.801077 18606 solver.cpp:237] Train net output #0: loss = 5.27825 (* 1 = 5.27825 loss) +I0410 14:17:05.801090 18606 sgd_solver.cpp:105] Iteration 6276, lr = 0.00288463 +I0410 14:17:10.626241 18606 solver.cpp:218] Iteration 6288 (2.48708 iter/s, 4.82494s/12 iters), loss = 5.25672 +I0410 14:17:10.628345 18606 solver.cpp:237] Train net output #0: loss = 5.25672 (* 1 = 5.25672 loss) +I0410 14:17:10.628357 18606 sgd_solver.cpp:105] Iteration 6288, lr = 0.00287779 +I0410 14:17:15.422228 18606 solver.cpp:218] Iteration 6300 (2.5033 iter/s, 4.79366s/12 iters), loss = 5.27175 +I0410 14:17:15.422287 18606 solver.cpp:237] Train net output #0: loss = 5.27175 (* 1 = 5.27175 loss) +I0410 14:17:15.422299 18606 sgd_solver.cpp:105] Iteration 6300, lr = 0.00287095 +I0410 14:17:20.247684 18606 solver.cpp:218] Iteration 6312 (2.48696 iter/s, 4.82518s/12 iters), loss = 5.2608 +I0410 14:17:20.247743 18606 solver.cpp:237] Train net output #0: loss = 5.2608 (* 1 = 5.2608 loss) +I0410 14:17:20.247756 18606 sgd_solver.cpp:105] Iteration 6312, lr = 0.00286414 +I0410 14:17:24.841351 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6324.caffemodel +I0410 14:17:25.175529 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6324.solverstate +I0410 14:17:25.394007 18606 solver.cpp:330] Iteration 6324, Testing net (#0) +I0410 14:17:25.394033 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:17:27.239471 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:17:29.710734 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:17:29.710783 18606 solver.cpp:397] Test net output #1: loss = 5.28673 (* 1 = 5.28673 loss) +I0410 14:17:29.793594 18606 solver.cpp:218] Iteration 6324 (1.25715 iter/s, 9.54543s/12 iters), loss = 5.30023 +I0410 14:17:29.793644 18606 solver.cpp:237] Train net output #0: loss = 5.30023 (* 1 = 5.30023 loss) +I0410 14:17:29.793655 18606 sgd_solver.cpp:105] Iteration 6324, lr = 0.00285734 +I0410 14:17:33.889364 18606 solver.cpp:218] Iteration 6336 (2.93002 iter/s, 4.09553s/12 iters), loss = 5.27071 +I0410 14:17:33.889415 18606 solver.cpp:237] Train net output #0: loss = 5.27071 (* 1 = 5.27071 loss) +I0410 14:17:33.889426 18606 sgd_solver.cpp:105] Iteration 6336, lr = 0.00285055 +I0410 14:17:38.701447 18606 solver.cpp:218] Iteration 6348 (2.49386 iter/s, 4.81182s/12 iters), loss = 5.26082 +I0410 14:17:38.701483 18606 solver.cpp:237] Train net output #0: loss = 5.26082 (* 1 = 5.26082 loss) +I0410 14:17:38.701491 18606 sgd_solver.cpp:105] Iteration 6348, lr = 0.00284379 +I0410 14:17:43.490765 18606 solver.cpp:218] Iteration 6360 (2.50571 iter/s, 4.78906s/12 iters), loss = 5.27076 +I0410 14:17:43.490909 18606 solver.cpp:237] Train net output #0: loss = 5.27076 (* 1 = 5.27076 loss) +I0410 14:17:43.490923 18606 sgd_solver.cpp:105] Iteration 6360, lr = 0.00283703 +I0410 14:17:48.288197 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:17:48.418970 18606 solver.cpp:218] Iteration 6372 (2.43515 iter/s, 4.92784s/12 iters), loss = 5.25195 +I0410 14:17:48.419013 18606 solver.cpp:237] Train net output #0: loss = 5.25195 (* 1 = 5.25195 loss) +I0410 14:17:48.419023 18606 sgd_solver.cpp:105] Iteration 6372, lr = 0.0028303 +I0410 14:17:53.252856 18606 solver.cpp:218] Iteration 6384 (2.48261 iter/s, 4.83362s/12 iters), loss = 5.26746 +I0410 14:17:53.252898 18606 solver.cpp:237] Train net output #0: loss = 5.26746 (* 1 = 5.26746 loss) +I0410 14:17:53.252908 18606 sgd_solver.cpp:105] Iteration 6384, lr = 0.00282358 +I0410 14:17:58.097843 18606 solver.cpp:218] Iteration 6396 (2.47692 iter/s, 4.84473s/12 iters), loss = 5.29437 +I0410 14:17:58.097894 18606 solver.cpp:237] Train net output #0: loss = 5.29437 (* 1 = 5.29437 loss) +I0410 14:17:58.097908 18606 sgd_solver.cpp:105] Iteration 6396, lr = 0.00281687 +I0410 14:18:02.919298 18606 solver.cpp:218] Iteration 6408 (2.48902 iter/s, 4.82118s/12 iters), loss = 5.28551 +I0410 14:18:02.919354 18606 solver.cpp:237] Train net output #0: loss = 5.28551 (* 1 = 5.28551 loss) +I0410 14:18:02.919366 18606 sgd_solver.cpp:105] Iteration 6408, lr = 0.00281019 +I0410 14:18:07.709403 18606 solver.cpp:218] Iteration 6420 (2.50531 iter/s, 4.78983s/12 iters), loss = 5.27843 +I0410 14:18:07.709455 18606 solver.cpp:237] Train net output #0: loss = 5.27843 (* 1 = 5.27843 loss) +I0410 14:18:07.709467 18606 sgd_solver.cpp:105] Iteration 6420, lr = 0.00280351 +I0410 14:18:09.675045 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6426.caffemodel +I0410 14:18:10.329300 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6426.solverstate +I0410 14:18:10.538285 18606 solver.cpp:330] Iteration 6426, Testing net (#0) +I0410 14:18:10.538306 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:18:12.464666 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:14.983409 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:18:14.983500 18606 solver.cpp:397] Test net output #1: loss = 5.28669 (* 1 = 5.28669 loss) +I0410 14:18:16.822515 18606 solver.cpp:218] Iteration 6432 (1.31685 iter/s, 9.11266s/12 iters), loss = 5.27258 +I0410 14:18:16.822571 18606 solver.cpp:237] Train net output #0: loss = 5.27258 (* 1 = 5.27258 loss) +I0410 14:18:16.822583 18606 sgd_solver.cpp:105] Iteration 6432, lr = 0.00279686 +I0410 14:18:21.638154 18606 solver.cpp:218] Iteration 6444 (2.49203 iter/s, 4.81536s/12 iters), loss = 5.24543 +I0410 14:18:21.638211 18606 solver.cpp:237] Train net output #0: loss = 5.24543 (* 1 = 5.24543 loss) +I0410 14:18:21.638223 18606 sgd_solver.cpp:105] Iteration 6444, lr = 0.00279022 +I0410 14:18:26.445904 18606 solver.cpp:218] Iteration 6456 (2.49611 iter/s, 4.80747s/12 iters), loss = 5.27351 +I0410 14:18:26.445951 18606 solver.cpp:237] Train net output #0: loss = 5.27351 (* 1 = 5.27351 loss) +I0410 14:18:26.445986 18606 sgd_solver.cpp:105] Iteration 6456, lr = 0.00278359 +I0410 14:18:31.281411 18606 solver.cpp:218] Iteration 6468 (2.48178 iter/s, 4.83524s/12 iters), loss = 5.26675 +I0410 14:18:31.281451 18606 solver.cpp:237] Train net output #0: loss = 5.26675 (* 1 = 5.26675 loss) +I0410 14:18:31.281459 18606 sgd_solver.cpp:105] Iteration 6468, lr = 0.00277698 +I0410 14:18:33.204650 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:18:36.258296 18606 solver.cpp:218] Iteration 6480 (2.41128 iter/s, 4.97661s/12 iters), loss = 5.29009 +I0410 14:18:36.258342 18606 solver.cpp:237] Train net output #0: loss = 5.29009 (* 1 = 5.29009 loss) +I0410 14:18:36.258352 18606 sgd_solver.cpp:105] Iteration 6480, lr = 0.00277039 +I0410 14:18:41.092566 18606 solver.cpp:218] Iteration 6492 (2.48241 iter/s, 4.834s/12 iters), loss = 5.27015 +I0410 14:18:41.092608 18606 solver.cpp:237] Train net output #0: loss = 5.27015 (* 1 = 5.27015 loss) +I0410 14:18:41.092619 18606 sgd_solver.cpp:105] Iteration 6492, lr = 0.00276381 +I0410 14:18:45.928966 18606 solver.cpp:218] Iteration 6504 (2.48132 iter/s, 4.83613s/12 iters), loss = 5.27201 +I0410 14:18:45.929129 18606 solver.cpp:237] Train net output #0: loss = 5.27201 (* 1 = 5.27201 loss) +I0410 14:18:45.929144 18606 sgd_solver.cpp:105] Iteration 6504, lr = 0.00275725 +I0410 14:18:50.727105 18606 solver.cpp:218] Iteration 6516 (2.50117 iter/s, 4.79776s/12 iters), loss = 5.26436 +I0410 14:18:50.727149 18606 solver.cpp:237] Train net output #0: loss = 5.26436 (* 1 = 5.26436 loss) +I0410 14:18:50.727159 18606 sgd_solver.cpp:105] Iteration 6516, lr = 0.00275071 +I0410 14:18:55.154825 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6528.caffemodel +I0410 14:18:55.529613 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6528.solverstate +I0410 14:18:55.898505 18606 solver.cpp:330] Iteration 6528, Testing net (#0) +I0410 14:18:55.898531 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:18:57.689580 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:19:00.249146 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:19:00.249200 18606 solver.cpp:397] Test net output #1: loss = 5.28676 (* 1 = 5.28676 loss) +I0410 14:19:00.331533 18606 solver.cpp:218] Iteration 6528 (1.24949 iter/s, 9.60396s/12 iters), loss = 5.2725 +I0410 14:19:00.331583 18606 solver.cpp:237] Train net output #0: loss = 5.2725 (* 1 = 5.2725 loss) +I0410 14:19:00.331593 18606 sgd_solver.cpp:105] Iteration 6528, lr = 0.00274418 +I0410 14:19:04.511019 18606 solver.cpp:218] Iteration 6540 (2.87133 iter/s, 4.17924s/12 iters), loss = 5.2734 +I0410 14:19:04.511062 18606 solver.cpp:237] Train net output #0: loss = 5.2734 (* 1 = 5.2734 loss) +I0410 14:19:04.511072 18606 sgd_solver.cpp:105] Iteration 6540, lr = 0.00273766 +I0410 14:19:09.390213 18606 solver.cpp:218] Iteration 6552 (2.45956 iter/s, 4.87892s/12 iters), loss = 5.26883 +I0410 14:19:09.390264 18606 solver.cpp:237] Train net output #0: loss = 5.26883 (* 1 = 5.26883 loss) +I0410 14:19:09.390276 18606 sgd_solver.cpp:105] Iteration 6552, lr = 0.00273116 +I0410 14:19:14.196934 18606 solver.cpp:218] Iteration 6564 (2.49665 iter/s, 4.80645s/12 iters), loss = 5.26049 +I0410 14:19:14.196991 18606 solver.cpp:237] Train net output #0: loss = 5.26049 (* 1 = 5.26049 loss) +I0410 14:19:14.197003 18606 sgd_solver.cpp:105] Iteration 6564, lr = 0.00272468 +I0410 14:19:18.280817 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:19:19.045423 18606 solver.cpp:218] Iteration 6576 (2.47514 iter/s, 4.84821s/12 iters), loss = 5.25845 +I0410 14:19:19.045486 18606 solver.cpp:237] Train net output #0: loss = 5.25845 (* 1 = 5.25845 loss) +I0410 14:19:19.045500 18606 sgd_solver.cpp:105] Iteration 6576, lr = 0.00271821 +I0410 14:19:23.974717 18606 solver.cpp:218] Iteration 6588 (2.43457 iter/s, 4.92901s/12 iters), loss = 5.28243 +I0410 14:19:23.974766 18606 solver.cpp:237] Train net output #0: loss = 5.28243 (* 1 = 5.28243 loss) +I0410 14:19:23.974774 18606 sgd_solver.cpp:105] Iteration 6588, lr = 0.00271175 +I0410 14:19:28.793066 18606 solver.cpp:218] Iteration 6600 (2.49062 iter/s, 4.81808s/12 iters), loss = 5.27331 +I0410 14:19:28.793115 18606 solver.cpp:237] Train net output #0: loss = 5.27331 (* 1 = 5.27331 loss) +I0410 14:19:28.793126 18606 sgd_solver.cpp:105] Iteration 6600, lr = 0.00270532 +I0410 14:19:33.626616 18606 solver.cpp:218] Iteration 6612 (2.48279 iter/s, 4.83328s/12 iters), loss = 5.30222 +I0410 14:19:33.626664 18606 solver.cpp:237] Train net output #0: loss = 5.30222 (* 1 = 5.30222 loss) +I0410 14:19:33.626673 18606 sgd_solver.cpp:105] Iteration 6612, lr = 0.00269889 +I0410 14:19:38.596695 18606 solver.cpp:218] Iteration 6624 (2.41458 iter/s, 4.9698s/12 iters), loss = 5.27022 +I0410 14:19:38.596745 18606 solver.cpp:237] Train net output #0: loss = 5.27022 (* 1 = 5.27022 loss) +I0410 14:19:38.596755 18606 sgd_solver.cpp:105] Iteration 6624, lr = 0.00269248 +I0410 14:19:40.589784 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6630.caffemodel +I0410 14:19:41.038887 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6630.solverstate +I0410 14:19:41.424118 18606 solver.cpp:330] Iteration 6630, Testing net (#0) +I0410 14:19:41.424147 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:19:43.240835 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:19:45.837289 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:19:45.837321 18606 solver.cpp:397] Test net output #1: loss = 5.28684 (* 1 = 5.28684 loss) +I0410 14:19:47.670444 18606 solver.cpp:218] Iteration 6636 (1.32256 iter/s, 9.0733s/12 iters), loss = 5.27364 +I0410 14:19:47.670495 18606 solver.cpp:237] Train net output #0: loss = 5.27364 (* 1 = 5.27364 loss) +I0410 14:19:47.670507 18606 sgd_solver.cpp:105] Iteration 6636, lr = 0.00268609 +I0410 14:19:52.578330 18606 solver.cpp:218] Iteration 6648 (2.44518 iter/s, 4.90761s/12 iters), loss = 5.27698 +I0410 14:19:52.578493 18606 solver.cpp:237] Train net output #0: loss = 5.27698 (* 1 = 5.27698 loss) +I0410 14:19:52.578508 18606 sgd_solver.cpp:105] Iteration 6648, lr = 0.00267971 +I0410 14:19:57.457202 18606 solver.cpp:218] Iteration 6660 (2.45978 iter/s, 4.87849s/12 iters), loss = 5.2797 +I0410 14:19:57.457257 18606 solver.cpp:237] Train net output #0: loss = 5.2797 (* 1 = 5.2797 loss) +I0410 14:19:57.457268 18606 sgd_solver.cpp:105] Iteration 6660, lr = 0.00267335 +I0410 14:20:02.375727 18606 solver.cpp:218] Iteration 6672 (2.4399 iter/s, 4.91824s/12 iters), loss = 5.26447 +I0410 14:20:02.375789 18606 solver.cpp:237] Train net output #0: loss = 5.26447 (* 1 = 5.26447 loss) +I0410 14:20:02.375802 18606 sgd_solver.cpp:105] Iteration 6672, lr = 0.00266701 +I0410 14:20:03.668233 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:07.187707 18606 solver.cpp:218] Iteration 6684 (2.49392 iter/s, 4.8117s/12 iters), loss = 5.27455 +I0410 14:20:07.187765 18606 solver.cpp:237] Train net output #0: loss = 5.27455 (* 1 = 5.27455 loss) +I0410 14:20:07.187777 18606 sgd_solver.cpp:105] Iteration 6684, lr = 0.00266067 +I0410 14:20:12.007431 18606 solver.cpp:218] Iteration 6696 (2.48991 iter/s, 4.81944s/12 iters), loss = 5.2685 +I0410 14:20:12.007490 18606 solver.cpp:237] Train net output #0: loss = 5.2685 (* 1 = 5.2685 loss) +I0410 14:20:12.007503 18606 sgd_solver.cpp:105] Iteration 6696, lr = 0.00265436 +I0410 14:20:16.876617 18606 solver.cpp:218] Iteration 6708 (2.46462 iter/s, 4.86891s/12 iters), loss = 5.27455 +I0410 14:20:16.876672 18606 solver.cpp:237] Train net output #0: loss = 5.27455 (* 1 = 5.27455 loss) +I0410 14:20:16.876683 18606 sgd_solver.cpp:105] Iteration 6708, lr = 0.00264805 +I0410 14:20:21.748523 18606 solver.cpp:218] Iteration 6720 (2.46324 iter/s, 4.87163s/12 iters), loss = 5.27193 +I0410 14:20:21.748574 18606 solver.cpp:237] Train net output #0: loss = 5.27193 (* 1 = 5.27193 loss) +I0410 14:20:21.748586 18606 sgd_solver.cpp:105] Iteration 6720, lr = 0.00264177 +I0410 14:20:26.249953 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6732.caffemodel +I0410 14:20:26.654130 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6732.solverstate +I0410 14:20:27.266858 18606 solver.cpp:330] Iteration 6732, Testing net (#0) +I0410 14:20:27.266887 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:20:29.055249 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:31.686641 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:20:31.686692 18606 solver.cpp:397] Test net output #1: loss = 5.28659 (* 1 = 5.28659 loss) +I0410 14:20:31.769697 18606 solver.cpp:218] Iteration 6732 (1.19752 iter/s, 10.0207s/12 iters), loss = 5.27126 +I0410 14:20:31.769757 18606 solver.cpp:237] Train net output #0: loss = 5.27126 (* 1 = 5.27126 loss) +I0410 14:20:31.769768 18606 sgd_solver.cpp:105] Iteration 6732, lr = 0.0026355 +I0410 14:20:35.928725 18606 solver.cpp:218] Iteration 6744 (2.88546 iter/s, 4.15878s/12 iters), loss = 5.26009 +I0410 14:20:35.928771 18606 solver.cpp:237] Train net output #0: loss = 5.26009 (* 1 = 5.26009 loss) +I0410 14:20:35.928781 18606 sgd_solver.cpp:105] Iteration 6744, lr = 0.00262924 +I0410 14:20:40.816664 18606 solver.cpp:218] Iteration 6756 (2.45516 iter/s, 4.88766s/12 iters), loss = 5.29122 +I0410 14:20:40.816717 18606 solver.cpp:237] Train net output #0: loss = 5.29122 (* 1 = 5.29122 loss) +I0410 14:20:40.816730 18606 sgd_solver.cpp:105] Iteration 6756, lr = 0.002623 +I0410 14:20:45.666055 18606 solver.cpp:218] Iteration 6768 (2.47468 iter/s, 4.84912s/12 iters), loss = 5.273 +I0410 14:20:45.666100 18606 solver.cpp:237] Train net output #0: loss = 5.273 (* 1 = 5.273 loss) +I0410 14:20:45.666108 18606 sgd_solver.cpp:105] Iteration 6768, lr = 0.00261677 +I0410 14:20:49.047870 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:20:50.493847 18606 solver.cpp:218] Iteration 6780 (2.48575 iter/s, 4.82752s/12 iters), loss = 5.2753 +I0410 14:20:50.493898 18606 solver.cpp:237] Train net output #0: loss = 5.2753 (* 1 = 5.2753 loss) +I0410 14:20:50.493911 18606 sgd_solver.cpp:105] Iteration 6780, lr = 0.00261056 +I0410 14:20:55.351359 18606 solver.cpp:218] Iteration 6792 (2.47054 iter/s, 4.85724s/12 iters), loss = 5.26074 +I0410 14:20:55.351403 18606 solver.cpp:237] Train net output #0: loss = 5.26074 (* 1 = 5.26074 loss) +I0410 14:20:55.351414 18606 sgd_solver.cpp:105] Iteration 6792, lr = 0.00260436 +I0410 14:21:00.245617 18606 solver.cpp:218] Iteration 6804 (2.45199 iter/s, 4.89398s/12 iters), loss = 5.26654 +I0410 14:21:00.245776 18606 solver.cpp:237] Train net output #0: loss = 5.26654 (* 1 = 5.26654 loss) +I0410 14:21:00.245790 18606 sgd_solver.cpp:105] Iteration 6804, lr = 0.00259817 +I0410 14:21:05.129878 18606 solver.cpp:218] Iteration 6816 (2.45706 iter/s, 4.88388s/12 iters), loss = 5.27842 +I0410 14:21:05.129940 18606 solver.cpp:237] Train net output #0: loss = 5.27842 (* 1 = 5.27842 loss) +I0410 14:21:05.129978 18606 sgd_solver.cpp:105] Iteration 6816, lr = 0.00259201 +I0410 14:21:10.067108 18606 solver.cpp:218] Iteration 6828 (2.43065 iter/s, 4.93695s/12 iters), loss = 5.26548 +I0410 14:21:10.067159 18606 solver.cpp:237] Train net output #0: loss = 5.26548 (* 1 = 5.26548 loss) +I0410 14:21:10.067170 18606 sgd_solver.cpp:105] Iteration 6828, lr = 0.00258585 +I0410 14:21:12.073052 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6834.caffemodel +I0410 14:21:12.382383 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6834.solverstate +I0410 14:21:12.598975 18606 solver.cpp:330] Iteration 6834, Testing net (#0) +I0410 14:21:12.598994 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:21:14.364948 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:17.027607 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:21:17.027645 18606 solver.cpp:397] Test net output #1: loss = 5.28735 (* 1 = 5.28735 loss) +I0410 14:21:18.784186 18606 solver.cpp:218] Iteration 6840 (1.37668 iter/s, 8.71663s/12 iters), loss = 5.27667 +I0410 14:21:18.784242 18606 solver.cpp:237] Train net output #0: loss = 5.27667 (* 1 = 5.27667 loss) +I0410 14:21:18.784255 18606 sgd_solver.cpp:105] Iteration 6840, lr = 0.00257971 +I0410 14:21:23.678932 18606 solver.cpp:218] Iteration 6852 (2.45175 iter/s, 4.89446s/12 iters), loss = 5.27476 +I0410 14:21:23.678988 18606 solver.cpp:237] Train net output #0: loss = 5.27476 (* 1 = 5.27476 loss) +I0410 14:21:23.678999 18606 sgd_solver.cpp:105] Iteration 6852, lr = 0.00257359 +I0410 14:21:28.586438 18606 solver.cpp:218] Iteration 6864 (2.44537 iter/s, 4.90723s/12 iters), loss = 5.27614 +I0410 14:21:28.586493 18606 solver.cpp:237] Train net output #0: loss = 5.27614 (* 1 = 5.27614 loss) +I0410 14:21:28.586504 18606 sgd_solver.cpp:105] Iteration 6864, lr = 0.00256748 +I0410 14:21:33.555133 18606 solver.cpp:218] Iteration 6876 (2.41526 iter/s, 4.96841s/12 iters), loss = 5.28349 +I0410 14:21:33.555254 18606 solver.cpp:237] Train net output #0: loss = 5.28349 (* 1 = 5.28349 loss) +I0410 14:21:33.555264 18606 sgd_solver.cpp:105] Iteration 6876, lr = 0.00256138 +I0410 14:21:34.152547 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:21:38.466317 18606 solver.cpp:218] Iteration 6888 (2.44357 iter/s, 4.91084s/12 iters), loss = 5.28228 +I0410 14:21:38.466365 18606 solver.cpp:237] Train net output #0: loss = 5.28228 (* 1 = 5.28228 loss) +I0410 14:21:38.466377 18606 sgd_solver.cpp:105] Iteration 6888, lr = 0.0025553 +I0410 14:21:43.310122 18606 solver.cpp:218] Iteration 6900 (2.47753 iter/s, 4.84353s/12 iters), loss = 5.26852 +I0410 14:21:43.310170 18606 solver.cpp:237] Train net output #0: loss = 5.26852 (* 1 = 5.26852 loss) +I0410 14:21:43.310180 18606 sgd_solver.cpp:105] Iteration 6900, lr = 0.00254923 +I0410 14:21:48.137635 18606 solver.cpp:218] Iteration 6912 (2.48589 iter/s, 4.82724s/12 iters), loss = 5.2873 +I0410 14:21:48.137682 18606 solver.cpp:237] Train net output #0: loss = 5.2873 (* 1 = 5.2873 loss) +I0410 14:21:48.137691 18606 sgd_solver.cpp:105] Iteration 6912, lr = 0.00254318 +I0410 14:21:53.015727 18606 solver.cpp:218] Iteration 6924 (2.46012 iter/s, 4.87782s/12 iters), loss = 5.28232 +I0410 14:21:53.015787 18606 solver.cpp:237] Train net output #0: loss = 5.28232 (* 1 = 5.28232 loss) +I0410 14:21:53.015800 18606 sgd_solver.cpp:105] Iteration 6924, lr = 0.00253714 +I0410 14:21:57.479758 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_6936.caffemodel +I0410 14:21:57.793068 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_6936.solverstate +I0410 14:21:58.007447 18606 solver.cpp:330] Iteration 6936, Testing net (#0) +I0410 14:21:58.007473 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:21:58.254441 18606 blocking_queue.cpp:49] Waiting for data +I0410 14:21:59.707283 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:22:02.414254 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:22:02.414300 18606 solver.cpp:397] Test net output #1: loss = 5.28707 (* 1 = 5.28707 loss) +I0410 14:22:02.495750 18606 solver.cpp:218] Iteration 6936 (1.26588 iter/s, 9.47954s/12 iters), loss = 5.28442 +I0410 14:22:02.495798 18606 solver.cpp:237] Train net output #0: loss = 5.28442 (* 1 = 5.28442 loss) +I0410 14:22:02.495810 18606 sgd_solver.cpp:105] Iteration 6936, lr = 0.00253112 +I0410 14:22:06.554046 18606 solver.cpp:218] Iteration 6948 (2.95708 iter/s, 4.05806s/12 iters), loss = 5.27656 +I0410 14:22:06.554157 18606 solver.cpp:237] Train net output #0: loss = 5.27656 (* 1 = 5.27656 loss) +I0410 14:22:06.554169 18606 sgd_solver.cpp:105] Iteration 6948, lr = 0.00252511 +I0410 14:22:11.341478 18606 solver.cpp:218] Iteration 6960 (2.50673 iter/s, 4.78711s/12 iters), loss = 5.26529 +I0410 14:22:11.341531 18606 solver.cpp:237] Train net output #0: loss = 5.26529 (* 1 = 5.26529 loss) +I0410 14:22:11.341542 18606 sgd_solver.cpp:105] Iteration 6960, lr = 0.00251911 +I0410 14:22:16.135701 18606 solver.cpp:218] Iteration 6972 (2.50316 iter/s, 4.79395s/12 iters), loss = 5.26723 +I0410 14:22:16.135762 18606 solver.cpp:237] Train net output #0: loss = 5.26723 (* 1 = 5.26723 loss) +I0410 14:22:16.135774 18606 sgd_solver.cpp:105] Iteration 6972, lr = 0.00251313 +I0410 14:22:18.765792 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:22:20.910118 18606 solver.cpp:218] Iteration 6984 (2.51354 iter/s, 4.77413s/12 iters), loss = 5.27282 +I0410 14:22:20.910176 18606 solver.cpp:237] Train net output #0: loss = 5.27282 (* 1 = 5.27282 loss) +I0410 14:22:20.910189 18606 sgd_solver.cpp:105] Iteration 6984, lr = 0.00250717 +I0410 14:22:25.706652 18606 solver.cpp:218] Iteration 6996 (2.50195 iter/s, 4.79626s/12 iters), loss = 5.25826 +I0410 14:22:25.706717 18606 solver.cpp:237] Train net output #0: loss = 5.25826 (* 1 = 5.25826 loss) +I0410 14:22:25.706729 18606 sgd_solver.cpp:105] Iteration 6996, lr = 0.00250121 +I0410 14:22:30.470268 18606 solver.cpp:218] Iteration 7008 (2.51924 iter/s, 4.76333s/12 iters), loss = 5.25921 +I0410 14:22:30.470325 18606 solver.cpp:237] Train net output #0: loss = 5.25921 (* 1 = 5.25921 loss) +I0410 14:22:30.470337 18606 sgd_solver.cpp:105] Iteration 7008, lr = 0.00249528 +I0410 14:22:35.250716 18606 solver.cpp:218] Iteration 7020 (2.51037 iter/s, 4.78017s/12 iters), loss = 5.26022 +I0410 14:22:35.250775 18606 solver.cpp:237] Train net output #0: loss = 5.26022 (* 1 = 5.26022 loss) +I0410 14:22:35.250787 18606 sgd_solver.cpp:105] Iteration 7020, lr = 0.00248935 +I0410 14:22:40.029665 18606 solver.cpp:218] Iteration 7032 (2.51116 iter/s, 4.77867s/12 iters), loss = 5.30342 +I0410 14:22:40.032295 18606 solver.cpp:237] Train net output #0: loss = 5.30342 (* 1 = 5.30342 loss) +I0410 14:22:40.032310 18606 sgd_solver.cpp:105] Iteration 7032, lr = 0.00248344 +I0410 14:22:41.975559 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7038.caffemodel +I0410 14:22:42.367782 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7038.solverstate +I0410 14:22:42.601119 18606 solver.cpp:330] Iteration 7038, Testing net (#0) +I0410 14:22:42.601140 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:22:44.267836 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:22:46.982566 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:22:46.982617 18606 solver.cpp:397] Test net output #1: loss = 5.28679 (* 1 = 5.28679 loss) +I0410 14:22:48.740762 18606 solver.cpp:218] Iteration 7044 (1.37803 iter/s, 8.70809s/12 iters), loss = 5.27098 +I0410 14:22:48.740804 18606 solver.cpp:237] Train net output #0: loss = 5.27098 (* 1 = 5.27098 loss) +I0410 14:22:48.740813 18606 sgd_solver.cpp:105] Iteration 7044, lr = 0.00247755 +I0410 14:22:53.547389 18606 solver.cpp:218] Iteration 7056 (2.49669 iter/s, 4.80636s/12 iters), loss = 5.26943 +I0410 14:22:53.547439 18606 solver.cpp:237] Train net output #0: loss = 5.26943 (* 1 = 5.26943 loss) +I0410 14:22:53.547453 18606 sgd_solver.cpp:105] Iteration 7056, lr = 0.00247166 +I0410 14:22:58.356297 18606 solver.cpp:218] Iteration 7068 (2.49551 iter/s, 4.80864s/12 iters), loss = 5.26873 +I0410 14:22:58.356348 18606 solver.cpp:237] Train net output #0: loss = 5.26873 (* 1 = 5.26873 loss) +I0410 14:22:58.356359 18606 sgd_solver.cpp:105] Iteration 7068, lr = 0.0024658 +I0410 14:23:03.138263 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:03.237985 18606 solver.cpp:218] Iteration 7080 (2.45831 iter/s, 4.8814s/12 iters), loss = 5.24135 +I0410 14:23:03.238044 18606 solver.cpp:237] Train net output #0: loss = 5.24135 (* 1 = 5.24135 loss) +I0410 14:23:03.238056 18606 sgd_solver.cpp:105] Iteration 7080, lr = 0.00245994 +I0410 14:23:08.279772 18606 solver.cpp:218] Iteration 7092 (2.38024 iter/s, 5.0415s/12 iters), loss = 5.26716 +I0410 14:23:08.279815 18606 solver.cpp:237] Train net output #0: loss = 5.26716 (* 1 = 5.26716 loss) +I0410 14:23:08.279824 18606 sgd_solver.cpp:105] Iteration 7092, lr = 0.0024541 +I0410 14:23:13.150310 18606 solver.cpp:218] Iteration 7104 (2.46393 iter/s, 4.87027s/12 iters), loss = 5.29424 +I0410 14:23:13.150403 18606 solver.cpp:237] Train net output #0: loss = 5.29424 (* 1 = 5.29424 loss) +I0410 14:23:13.150414 18606 sgd_solver.cpp:105] Iteration 7104, lr = 0.00244827 +I0410 14:23:17.967550 18606 solver.cpp:218] Iteration 7116 (2.49122 iter/s, 4.81692s/12 iters), loss = 5.27772 +I0410 14:23:17.967610 18606 solver.cpp:237] Train net output #0: loss = 5.27772 (* 1 = 5.27772 loss) +I0410 14:23:17.967624 18606 sgd_solver.cpp:105] Iteration 7116, lr = 0.00244246 +I0410 14:23:22.792954 18606 solver.cpp:218] Iteration 7128 (2.48698 iter/s, 4.82512s/12 iters), loss = 5.27685 +I0410 14:23:22.793010 18606 solver.cpp:237] Train net output #0: loss = 5.27685 (* 1 = 5.27685 loss) +I0410 14:23:22.793022 18606 sgd_solver.cpp:105] Iteration 7128, lr = 0.00243666 +I0410 14:23:27.189795 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7140.caffemodel +I0410 14:23:27.498929 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7140.solverstate +I0410 14:23:27.700867 18606 solver.cpp:330] Iteration 7140, Testing net (#0) +I0410 14:23:27.700894 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:23:29.396139 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:32.250145 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:23:32.250195 18606 solver.cpp:397] Test net output #1: loss = 5.28698 (* 1 = 5.28698 loss) +I0410 14:23:32.333492 18606 solver.cpp:218] Iteration 7140 (1.25785 iter/s, 9.54006s/12 iters), loss = 5.26334 +I0410 14:23:32.333535 18606 solver.cpp:237] Train net output #0: loss = 5.26334 (* 1 = 5.26334 loss) +I0410 14:23:32.333545 18606 sgd_solver.cpp:105] Iteration 7140, lr = 0.00243088 +I0410 14:23:36.427209 18606 solver.cpp:218] Iteration 7152 (2.93149 iter/s, 4.09348s/12 iters), loss = 5.24802 +I0410 14:23:36.427265 18606 solver.cpp:237] Train net output #0: loss = 5.24802 (* 1 = 5.24802 loss) +I0410 14:23:36.427278 18606 sgd_solver.cpp:105] Iteration 7152, lr = 0.00242511 +I0410 14:23:41.328378 18606 solver.cpp:218] Iteration 7164 (2.44853 iter/s, 4.90089s/12 iters), loss = 5.27235 +I0410 14:23:41.328424 18606 solver.cpp:237] Train net output #0: loss = 5.27235 (* 1 = 5.27235 loss) +I0410 14:23:41.328434 18606 sgd_solver.cpp:105] Iteration 7164, lr = 0.00241935 +I0410 14:23:46.236187 18606 solver.cpp:218] Iteration 7176 (2.44522 iter/s, 4.90754s/12 iters), loss = 5.2573 +I0410 14:23:46.236366 18606 solver.cpp:237] Train net output #0: loss = 5.2573 (* 1 = 5.2573 loss) +I0410 14:23:46.236379 18606 sgd_solver.cpp:105] Iteration 7176, lr = 0.0024136 +I0410 14:23:48.420222 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:23:51.282069 18606 solver.cpp:218] Iteration 7188 (2.37837 iter/s, 5.04547s/12 iters), loss = 5.27629 +I0410 14:23:51.282138 18606 solver.cpp:237] Train net output #0: loss = 5.27629 (* 1 = 5.27629 loss) +I0410 14:23:51.282156 18606 sgd_solver.cpp:105] Iteration 7188, lr = 0.00240787 +I0410 14:23:56.140115 18606 solver.cpp:218] Iteration 7200 (2.47028 iter/s, 4.85776s/12 iters), loss = 5.27149 +I0410 14:23:56.140172 18606 solver.cpp:237] Train net output #0: loss = 5.27149 (* 1 = 5.27149 loss) +I0410 14:23:56.140184 18606 sgd_solver.cpp:105] Iteration 7200, lr = 0.00240216 +I0410 14:24:01.067221 18606 solver.cpp:218] Iteration 7212 (2.43564 iter/s, 4.92683s/12 iters), loss = 5.27909 +I0410 14:24:01.067268 18606 solver.cpp:237] Train net output #0: loss = 5.27909 (* 1 = 5.27909 loss) +I0410 14:24:01.067278 18606 sgd_solver.cpp:105] Iteration 7212, lr = 0.00239645 +I0410 14:24:05.882616 18606 solver.cpp:218] Iteration 7224 (2.49215 iter/s, 4.81512s/12 iters), loss = 5.26577 +I0410 14:24:05.882669 18606 solver.cpp:237] Train net output #0: loss = 5.26577 (* 1 = 5.26577 loss) +I0410 14:24:05.882683 18606 sgd_solver.cpp:105] Iteration 7224, lr = 0.00239076 +I0410 14:24:10.741338 18606 solver.cpp:218] Iteration 7236 (2.46993 iter/s, 4.85844s/12 iters), loss = 5.27255 +I0410 14:24:10.741387 18606 solver.cpp:237] Train net output #0: loss = 5.27255 (* 1 = 5.27255 loss) +I0410 14:24:10.741397 18606 sgd_solver.cpp:105] Iteration 7236, lr = 0.00238509 +I0410 14:24:12.727128 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7242.caffemodel +I0410 14:24:13.052892 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7242.solverstate +I0410 14:24:13.272559 18606 solver.cpp:330] Iteration 7242, Testing net (#0) +I0410 14:24:13.272594 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:24:14.863332 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:17.712658 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:24:17.712831 18606 solver.cpp:397] Test net output #1: loss = 5.28661 (* 1 = 5.28661 loss) +I0410 14:24:19.500944 18606 solver.cpp:218] Iteration 7248 (1.36999 iter/s, 8.75917s/12 iters), loss = 5.27308 +I0410 14:24:19.500985 18606 solver.cpp:237] Train net output #0: loss = 5.27308 (* 1 = 5.27308 loss) +I0410 14:24:19.500995 18606 sgd_solver.cpp:105] Iteration 7248, lr = 0.00237942 +I0410 14:24:24.358803 18606 solver.cpp:218] Iteration 7260 (2.47036 iter/s, 4.85759s/12 iters), loss = 5.2727 +I0410 14:24:24.358861 18606 solver.cpp:237] Train net output #0: loss = 5.2727 (* 1 = 5.2727 loss) +I0410 14:24:24.358873 18606 sgd_solver.cpp:105] Iteration 7260, lr = 0.00237378 +I0410 14:24:29.235191 18606 solver.cpp:218] Iteration 7272 (2.46098 iter/s, 4.8761s/12 iters), loss = 5.25423 +I0410 14:24:29.235249 18606 solver.cpp:237] Train net output #0: loss = 5.25423 (* 1 = 5.25423 loss) +I0410 14:24:29.235260 18606 sgd_solver.cpp:105] Iteration 7272, lr = 0.00236814 +I0410 14:24:33.406982 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:24:34.136936 18606 solver.cpp:218] Iteration 7284 (2.44825 iter/s, 4.90146s/12 iters), loss = 5.25606 +I0410 14:24:34.136989 18606 solver.cpp:237] Train net output #0: loss = 5.25606 (* 1 = 5.25606 loss) +I0410 14:24:34.137001 18606 sgd_solver.cpp:105] Iteration 7284, lr = 0.00236252 +I0410 14:24:39.187232 18606 solver.cpp:218] Iteration 7296 (2.37623 iter/s, 5.05001s/12 iters), loss = 5.28159 +I0410 14:24:39.187283 18606 solver.cpp:237] Train net output #0: loss = 5.28159 (* 1 = 5.28159 loss) +I0410 14:24:39.187294 18606 sgd_solver.cpp:105] Iteration 7296, lr = 0.00235691 +I0410 14:24:44.020396 18606 solver.cpp:218] Iteration 7308 (2.48299 iter/s, 4.83289s/12 iters), loss = 5.28184 +I0410 14:24:44.020452 18606 solver.cpp:237] Train net output #0: loss = 5.28184 (* 1 = 5.28184 loss) +I0410 14:24:44.020464 18606 sgd_solver.cpp:105] Iteration 7308, lr = 0.00235131 +I0410 14:24:48.851516 18606 solver.cpp:218] Iteration 7320 (2.48401 iter/s, 4.83089s/12 iters), loss = 5.29499 +I0410 14:24:48.851636 18606 solver.cpp:237] Train net output #0: loss = 5.29499 (* 1 = 5.29499 loss) +I0410 14:24:48.851647 18606 sgd_solver.cpp:105] Iteration 7320, lr = 0.00234573 +I0410 14:24:53.654662 18606 solver.cpp:218] Iteration 7332 (2.49851 iter/s, 4.80287s/12 iters), loss = 5.26941 +I0410 14:24:53.654709 18606 solver.cpp:237] Train net output #0: loss = 5.26941 (* 1 = 5.26941 loss) +I0410 14:24:53.654721 18606 sgd_solver.cpp:105] Iteration 7332, lr = 0.00234016 +I0410 14:24:58.023933 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7344.caffemodel +I0410 14:24:58.352779 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7344.solverstate +I0410 14:24:58.571204 18606 solver.cpp:330] Iteration 7344, Testing net (#0) +I0410 14:24:58.571233 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:25:00.205051 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:25:03.068862 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:25:03.068913 18606 solver.cpp:397] Test net output #1: loss = 5.28748 (* 1 = 5.28748 loss) +I0410 14:25:03.151952 18606 solver.cpp:218] Iteration 7344 (1.26357 iter/s, 9.49693s/12 iters), loss = 5.27596 +I0410 14:25:03.152009 18606 solver.cpp:237] Train net output #0: loss = 5.27596 (* 1 = 5.27596 loss) +I0410 14:25:03.152019 18606 sgd_solver.cpp:105] Iteration 7344, lr = 0.0023346 +I0410 14:25:07.210884 18606 solver.cpp:218] Iteration 7356 (2.95659 iter/s, 4.05873s/12 iters), loss = 5.28369 +I0410 14:25:07.210938 18606 solver.cpp:237] Train net output #0: loss = 5.28369 (* 1 = 5.28369 loss) +I0410 14:25:07.210950 18606 sgd_solver.cpp:105] Iteration 7356, lr = 0.00232906 +I0410 14:25:12.016130 18606 solver.cpp:218] Iteration 7368 (2.49738 iter/s, 4.80503s/12 iters), loss = 5.2762 +I0410 14:25:12.016178 18606 solver.cpp:237] Train net output #0: loss = 5.2762 (* 1 = 5.2762 loss) +I0410 14:25:12.016187 18606 sgd_solver.cpp:105] Iteration 7368, lr = 0.00232353 +I0410 14:25:16.865902 18606 solver.cpp:218] Iteration 7380 (2.47445 iter/s, 4.84956s/12 iters), loss = 5.26404 +I0410 14:25:16.865981 18606 solver.cpp:237] Train net output #0: loss = 5.26404 (* 1 = 5.26404 loss) +I0410 14:25:16.865994 18606 sgd_solver.cpp:105] Iteration 7380, lr = 0.00231802 +I0410 14:25:18.212088 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:25:21.976325 18606 solver.cpp:218] Iteration 7392 (2.34825 iter/s, 5.11019s/12 iters), loss = 5.27187 +I0410 14:25:21.976488 18606 solver.cpp:237] Train net output #0: loss = 5.27187 (* 1 = 5.27187 loss) +I0410 14:25:21.976503 18606 sgd_solver.cpp:105] Iteration 7392, lr = 0.00231251 +I0410 14:25:26.871699 18606 solver.cpp:218] Iteration 7404 (2.45146 iter/s, 4.89504s/12 iters), loss = 5.26986 +I0410 14:25:26.871752 18606 solver.cpp:237] Train net output #0: loss = 5.26986 (* 1 = 5.26986 loss) +I0410 14:25:26.871763 18606 sgd_solver.cpp:105] Iteration 7404, lr = 0.00230702 +I0410 14:25:31.674108 18606 solver.cpp:218] Iteration 7416 (2.49886 iter/s, 4.80219s/12 iters), loss = 5.26551 +I0410 14:25:31.674149 18606 solver.cpp:237] Train net output #0: loss = 5.26551 (* 1 = 5.26551 loss) +I0410 14:25:31.674158 18606 sgd_solver.cpp:105] Iteration 7416, lr = 0.00230154 +I0410 14:25:36.535491 18606 solver.cpp:218] Iteration 7428 (2.46854 iter/s, 4.86117s/12 iters), loss = 5.27755 +I0410 14:25:36.535542 18606 solver.cpp:237] Train net output #0: loss = 5.27755 (* 1 = 5.27755 loss) +I0410 14:25:36.535554 18606 sgd_solver.cpp:105] Iteration 7428, lr = 0.00229608 +I0410 14:25:41.395356 18606 solver.cpp:218] Iteration 7440 (2.46931 iter/s, 4.85965s/12 iters), loss = 5.25554 +I0410 14:25:41.395395 18606 solver.cpp:237] Train net output #0: loss = 5.25554 (* 1 = 5.25554 loss) +I0410 14:25:41.395403 18606 sgd_solver.cpp:105] Iteration 7440, lr = 0.00229063 +I0410 14:25:43.338330 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7446.caffemodel +I0410 14:25:43.670588 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7446.solverstate +I0410 14:25:43.889617 18606 solver.cpp:330] Iteration 7446, Testing net (#0) +I0410 14:25:43.889644 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:25:45.426044 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:25:48.403201 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:25:48.403246 18606 solver.cpp:397] Test net output #1: loss = 5.28682 (* 1 = 5.28682 loss) +I0410 14:25:50.286799 18606 solver.cpp:218] Iteration 7452 (1.34966 iter/s, 8.89111s/12 iters), loss = 5.26389 +I0410 14:25:50.286849 18606 solver.cpp:237] Train net output #0: loss = 5.26389 (* 1 = 5.26389 loss) +I0410 14:25:50.286861 18606 sgd_solver.cpp:105] Iteration 7452, lr = 0.00228519 +I0410 14:25:55.127038 18606 solver.cpp:218] Iteration 7464 (2.47933 iter/s, 4.84002s/12 iters), loss = 5.2867 +I0410 14:25:55.127156 18606 solver.cpp:237] Train net output #0: loss = 5.2867 (* 1 = 5.2867 loss) +I0410 14:25:55.127167 18606 sgd_solver.cpp:105] Iteration 7464, lr = 0.00227976 +I0410 14:26:00.132299 18606 solver.cpp:218] Iteration 7476 (2.39762 iter/s, 5.00497s/12 iters), loss = 5.27609 +I0410 14:26:00.132347 18606 solver.cpp:237] Train net output #0: loss = 5.27609 (* 1 = 5.27609 loss) +I0410 14:26:00.132356 18606 sgd_solver.cpp:105] Iteration 7476, lr = 0.00227435 +I0410 14:26:03.535017 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:04.957267 18606 solver.cpp:218] Iteration 7488 (2.48718 iter/s, 4.82475s/12 iters), loss = 5.26834 +I0410 14:26:04.957324 18606 solver.cpp:237] Train net output #0: loss = 5.26834 (* 1 = 5.26834 loss) +I0410 14:26:04.957337 18606 sgd_solver.cpp:105] Iteration 7488, lr = 0.00226895 +I0410 14:26:09.771425 18606 solver.cpp:218] Iteration 7500 (2.49277 iter/s, 4.81393s/12 iters), loss = 5.2596 +I0410 14:26:09.771478 18606 solver.cpp:237] Train net output #0: loss = 5.2596 (* 1 = 5.2596 loss) +I0410 14:26:09.771489 18606 sgd_solver.cpp:105] Iteration 7500, lr = 0.00226357 +I0410 14:26:14.904176 18606 solver.cpp:218] Iteration 7512 (2.33804 iter/s, 5.13251s/12 iters), loss = 5.26066 +I0410 14:26:14.904234 18606 solver.cpp:237] Train net output #0: loss = 5.26066 (* 1 = 5.26066 loss) +I0410 14:26:14.904247 18606 sgd_solver.cpp:105] Iteration 7512, lr = 0.00225819 +I0410 14:26:19.787199 18606 solver.cpp:218] Iteration 7524 (2.45761 iter/s, 4.88279s/12 iters), loss = 5.27071 +I0410 14:26:19.787245 18606 solver.cpp:237] Train net output #0: loss = 5.27071 (* 1 = 5.27071 loss) +I0410 14:26:19.787254 18606 sgd_solver.cpp:105] Iteration 7524, lr = 0.00225283 +I0410 14:26:24.631202 18606 solver.cpp:218] Iteration 7536 (2.4774 iter/s, 4.84378s/12 iters), loss = 5.26135 +I0410 14:26:24.631247 18606 solver.cpp:237] Train net output #0: loss = 5.26135 (* 1 = 5.26135 loss) +I0410 14:26:24.631255 18606 sgd_solver.cpp:105] Iteration 7536, lr = 0.00224748 +I0410 14:26:28.990587 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7548.caffemodel +I0410 14:26:29.305428 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7548.solverstate +I0410 14:26:29.520444 18606 solver.cpp:330] Iteration 7548, Testing net (#0) +I0410 14:26:29.520469 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:26:31.024261 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:34.024233 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:26:34.024264 18606 solver.cpp:397] Test net output #1: loss = 5.28695 (* 1 = 5.28695 loss) +I0410 14:26:34.109455 18606 solver.cpp:218] Iteration 7548 (1.26611 iter/s, 9.47788s/12 iters), loss = 5.27902 +I0410 14:26:34.109500 18606 solver.cpp:237] Train net output #0: loss = 5.27902 (* 1 = 5.27902 loss) +I0410 14:26:34.109509 18606 sgd_solver.cpp:105] Iteration 7548, lr = 0.00224215 +I0410 14:26:38.240684 18606 solver.cpp:218] Iteration 7560 (2.90484 iter/s, 4.13103s/12 iters), loss = 5.27084 +I0410 14:26:38.240731 18606 solver.cpp:237] Train net output #0: loss = 5.27084 (* 1 = 5.27084 loss) +I0410 14:26:38.240739 18606 sgd_solver.cpp:105] Iteration 7560, lr = 0.00223682 +I0410 14:26:43.113593 18606 solver.cpp:218] Iteration 7572 (2.46271 iter/s, 4.87269s/12 iters), loss = 5.28071 +I0410 14:26:43.113641 18606 solver.cpp:237] Train net output #0: loss = 5.28071 (* 1 = 5.28071 loss) +I0410 14:26:43.113649 18606 sgd_solver.cpp:105] Iteration 7572, lr = 0.00223151 +I0410 14:26:48.122958 18606 solver.cpp:218] Iteration 7584 (2.39563 iter/s, 5.00913s/12 iters), loss = 5.28915 +I0410 14:26:48.123019 18606 solver.cpp:237] Train net output #0: loss = 5.28915 (* 1 = 5.28915 loss) +I0410 14:26:48.123032 18606 sgd_solver.cpp:105] Iteration 7584, lr = 0.00222621 +I0410 14:26:48.762907 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:26:53.087659 18606 solver.cpp:218] Iteration 7596 (2.41718 iter/s, 4.96446s/12 iters), loss = 5.27819 +I0410 14:26:53.087719 18606 solver.cpp:237] Train net output #0: loss = 5.27819 (* 1 = 5.27819 loss) +I0410 14:26:53.087731 18606 sgd_solver.cpp:105] Iteration 7596, lr = 0.00222093 +I0410 14:26:58.110080 18606 solver.cpp:218] Iteration 7608 (2.3894 iter/s, 5.02218s/12 iters), loss = 5.26317 +I0410 14:26:58.110131 18606 solver.cpp:237] Train net output #0: loss = 5.26317 (* 1 = 5.26317 loss) +I0410 14:26:58.110141 18606 sgd_solver.cpp:105] Iteration 7608, lr = 0.00221565 +I0410 14:27:02.962160 18606 solver.cpp:218] Iteration 7620 (2.47328 iter/s, 4.85185s/12 iters), loss = 5.27776 +I0410 14:27:02.962267 18606 solver.cpp:237] Train net output #0: loss = 5.27776 (* 1 = 5.27776 loss) +I0410 14:27:02.962280 18606 sgd_solver.cpp:105] Iteration 7620, lr = 0.00221039 +I0410 14:27:03.707746 18606 blocking_queue.cpp:49] Waiting for data +I0410 14:27:07.823983 18606 solver.cpp:218] Iteration 7632 (2.46835 iter/s, 4.86155s/12 iters), loss = 5.28032 +I0410 14:27:07.824016 18606 solver.cpp:237] Train net output #0: loss = 5.28032 (* 1 = 5.28032 loss) +I0410 14:27:07.824024 18606 sgd_solver.cpp:105] Iteration 7632, lr = 0.00220515 +I0410 14:27:12.753895 18606 solver.cpp:218] Iteration 7644 (2.43423 iter/s, 4.9297s/12 iters), loss = 5.28449 +I0410 14:27:12.753940 18606 solver.cpp:237] Train net output #0: loss = 5.28449 (* 1 = 5.28449 loss) +I0410 14:27:12.753949 18606 sgd_solver.cpp:105] Iteration 7644, lr = 0.00219991 +I0410 14:27:14.724545 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7650.caffemodel +I0410 14:27:15.038059 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7650.solverstate +I0410 14:27:15.257227 18606 solver.cpp:330] Iteration 7650, Testing net (#0) +I0410 14:27:15.257256 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:27:16.806941 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:27:19.799355 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:27:19.799386 18606 solver.cpp:397] Test net output #1: loss = 5.2871 (* 1 = 5.2871 loss) +I0410 14:27:21.595916 18606 solver.cpp:218] Iteration 7656 (1.35721 iter/s, 8.84166s/12 iters), loss = 5.27164 +I0410 14:27:21.595963 18606 solver.cpp:237] Train net output #0: loss = 5.27164 (* 1 = 5.27164 loss) +I0410 14:27:21.595971 18606 sgd_solver.cpp:105] Iteration 7656, lr = 0.00219469 +I0410 14:27:26.402951 18606 solver.cpp:218] Iteration 7668 (2.49646 iter/s, 4.80681s/12 iters), loss = 5.26806 +I0410 14:27:26.403007 18606 solver.cpp:237] Train net output #0: loss = 5.26806 (* 1 = 5.26806 loss) +I0410 14:27:26.403019 18606 sgd_solver.cpp:105] Iteration 7668, lr = 0.00218948 +I0410 14:27:31.221698 18606 solver.cpp:218] Iteration 7680 (2.4904 iter/s, 4.81851s/12 iters), loss = 5.26361 +I0410 14:27:31.221753 18606 solver.cpp:237] Train net output #0: loss = 5.26361 (* 1 = 5.26361 loss) +I0410 14:27:31.221765 18606 sgd_solver.cpp:105] Iteration 7680, lr = 0.00218428 +I0410 14:27:33.890236 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:27:36.000730 18606 solver.cpp:218] Iteration 7692 (2.51109 iter/s, 4.7788s/12 iters), loss = 5.27218 +I0410 14:27:36.000775 18606 solver.cpp:237] Train net output #0: loss = 5.27218 (* 1 = 5.27218 loss) +I0410 14:27:36.000784 18606 sgd_solver.cpp:105] Iteration 7692, lr = 0.00217909 +I0410 14:27:41.101537 18606 solver.cpp:218] Iteration 7704 (2.35268 iter/s, 5.10057s/12 iters), loss = 5.25213 +I0410 14:27:41.101580 18606 solver.cpp:237] Train net output #0: loss = 5.25213 (* 1 = 5.25213 loss) +I0410 14:27:41.101591 18606 sgd_solver.cpp:105] Iteration 7704, lr = 0.00217392 +I0410 14:27:45.992316 18606 solver.cpp:218] Iteration 7716 (2.45371 iter/s, 4.89055s/12 iters), loss = 5.25366 +I0410 14:27:45.992368 18606 solver.cpp:237] Train net output #0: loss = 5.25366 (* 1 = 5.25366 loss) +I0410 14:27:45.992379 18606 sgd_solver.cpp:105] Iteration 7716, lr = 0.00216876 +I0410 14:27:50.864387 18606 solver.cpp:218] Iteration 7728 (2.46313 iter/s, 4.87184s/12 iters), loss = 5.25646 +I0410 14:27:50.864424 18606 solver.cpp:237] Train net output #0: loss = 5.25646 (* 1 = 5.25646 loss) +I0410 14:27:50.864434 18606 sgd_solver.cpp:105] Iteration 7728, lr = 0.00216361 +I0410 14:27:55.719327 18606 solver.cpp:218] Iteration 7740 (2.47182 iter/s, 4.85472s/12 iters), loss = 5.29855 +I0410 14:27:55.719367 18606 solver.cpp:237] Train net output #0: loss = 5.29855 (* 1 = 5.29855 loss) +I0410 14:27:55.719377 18606 sgd_solver.cpp:105] Iteration 7740, lr = 0.00215847 +I0410 14:28:00.160375 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7752.caffemodel +I0410 14:28:00.474467 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7752.solverstate +I0410 14:28:00.688951 18606 solver.cpp:330] Iteration 7752, Testing net (#0) +I0410 14:28:00.688973 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:28:01.965950 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:04.992955 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:28:04.993081 18606 solver.cpp:397] Test net output #1: loss = 5.28674 (* 1 = 5.28674 loss) +I0410 14:28:05.076118 18606 solver.cpp:218] Iteration 7752 (1.28254 iter/s, 9.35641s/12 iters), loss = 5.26838 +I0410 14:28:05.076169 18606 solver.cpp:237] Train net output #0: loss = 5.26838 (* 1 = 5.26838 loss) +I0410 14:28:05.076180 18606 sgd_solver.cpp:105] Iteration 7752, lr = 0.00215335 +I0410 14:28:09.082618 18606 solver.cpp:218] Iteration 7764 (2.99528 iter/s, 4.0063s/12 iters), loss = 5.274 +I0410 14:28:09.082670 18606 solver.cpp:237] Train net output #0: loss = 5.274 (* 1 = 5.274 loss) +I0410 14:28:09.082684 18606 sgd_solver.cpp:105] Iteration 7764, lr = 0.00214823 +I0410 14:28:13.941555 18606 solver.cpp:218] Iteration 7776 (2.46979 iter/s, 4.8587s/12 iters), loss = 5.27012 +I0410 14:28:13.941604 18606 solver.cpp:237] Train net output #0: loss = 5.27012 (* 1 = 5.27012 loss) +I0410 14:28:13.941613 18606 sgd_solver.cpp:105] Iteration 7776, lr = 0.00214313 +I0410 14:28:18.817034 18606 solver.cpp:218] Iteration 7788 (2.46142 iter/s, 4.87524s/12 iters), loss = 5.24613 +I0410 14:28:18.817081 18606 solver.cpp:237] Train net output #0: loss = 5.24613 (* 1 = 5.24613 loss) +I0410 14:28:18.817090 18606 sgd_solver.cpp:105] Iteration 7788, lr = 0.00213805 +I0410 14:28:18.828275 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:23.702591 18606 solver.cpp:218] Iteration 7800 (2.45634 iter/s, 4.88531s/12 iters), loss = 5.269 +I0410 14:28:23.702647 18606 solver.cpp:237] Train net output #0: loss = 5.269 (* 1 = 5.269 loss) +I0410 14:28:23.702659 18606 sgd_solver.cpp:105] Iteration 7800, lr = 0.00213297 +I0410 14:28:28.587584 18606 solver.cpp:218] Iteration 7812 (2.45662 iter/s, 4.88475s/12 iters), loss = 5.29587 +I0410 14:28:28.587639 18606 solver.cpp:237] Train net output #0: loss = 5.29587 (* 1 = 5.29587 loss) +I0410 14:28:28.587651 18606 sgd_solver.cpp:105] Iteration 7812, lr = 0.00212791 +I0410 14:28:33.474712 18606 solver.cpp:218] Iteration 7824 (2.45555 iter/s, 4.88689s/12 iters), loss = 5.27214 +I0410 14:28:33.474768 18606 solver.cpp:237] Train net output #0: loss = 5.27214 (* 1 = 5.27214 loss) +I0410 14:28:33.474781 18606 sgd_solver.cpp:105] Iteration 7824, lr = 0.00212285 +I0410 14:28:38.304019 18606 solver.cpp:218] Iteration 7836 (2.48495 iter/s, 4.82907s/12 iters), loss = 5.2759 +I0410 14:28:38.304167 18606 solver.cpp:237] Train net output #0: loss = 5.2759 (* 1 = 5.2759 loss) +I0410 14:28:38.304179 18606 sgd_solver.cpp:105] Iteration 7836, lr = 0.00211781 +I0410 14:28:43.150761 18606 solver.cpp:218] Iteration 7848 (2.47606 iter/s, 4.84642s/12 iters), loss = 5.2578 +I0410 14:28:43.150806 18606 solver.cpp:237] Train net output #0: loss = 5.2578 (* 1 = 5.2578 loss) +I0410 14:28:43.150815 18606 sgd_solver.cpp:105] Iteration 7848, lr = 0.00211279 +I0410 14:28:45.109911 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7854.caffemodel +I0410 14:28:45.438299 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7854.solverstate +I0410 14:28:45.656054 18606 solver.cpp:330] Iteration 7854, Testing net (#0) +I0410 14:28:45.656081 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:28:46.954828 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:28:50.014370 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:28:50.014420 18606 solver.cpp:397] Test net output #1: loss = 5.28662 (* 1 = 5.28662 loss) +I0410 14:28:51.833346 18606 solver.cpp:218] Iteration 7860 (1.38214 iter/s, 8.68222s/12 iters), loss = 5.24125 +I0410 14:28:51.833397 18606 solver.cpp:237] Train net output #0: loss = 5.24125 (* 1 = 5.24125 loss) +I0410 14:28:51.833406 18606 sgd_solver.cpp:105] Iteration 7860, lr = 0.00210777 +I0410 14:28:56.726756 18606 solver.cpp:218] Iteration 7872 (2.4524 iter/s, 4.89317s/12 iters), loss = 5.26486 +I0410 14:28:56.726801 18606 solver.cpp:237] Train net output #0: loss = 5.26486 (* 1 = 5.26486 loss) +I0410 14:28:56.726811 18606 sgd_solver.cpp:105] Iteration 7872, lr = 0.00210277 +I0410 14:29:01.660303 18606 solver.cpp:218] Iteration 7884 (2.43245 iter/s, 4.9333s/12 iters), loss = 5.25794 +I0410 14:29:01.660377 18606 solver.cpp:237] Train net output #0: loss = 5.25794 (* 1 = 5.25794 loss) +I0410 14:29:01.660393 18606 sgd_solver.cpp:105] Iteration 7884, lr = 0.00209777 +I0410 14:29:03.746592 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:29:06.498277 18606 solver.cpp:218] Iteration 7896 (2.48051 iter/s, 4.83772s/12 iters), loss = 5.27768 +I0410 14:29:06.498332 18606 solver.cpp:237] Train net output #0: loss = 5.27768 (* 1 = 5.27768 loss) +I0410 14:29:06.498344 18606 sgd_solver.cpp:105] Iteration 7896, lr = 0.00209279 +I0410 14:29:11.402606 18606 solver.cpp:218] Iteration 7908 (2.44694 iter/s, 4.90409s/12 iters), loss = 5.26977 +I0410 14:29:11.402777 18606 solver.cpp:237] Train net output #0: loss = 5.26977 (* 1 = 5.26977 loss) +I0410 14:29:11.402791 18606 sgd_solver.cpp:105] Iteration 7908, lr = 0.00208782 +I0410 14:29:16.287134 18606 solver.cpp:218] Iteration 7920 (2.45691 iter/s, 4.88418s/12 iters), loss = 5.28327 +I0410 14:29:16.287184 18606 solver.cpp:237] Train net output #0: loss = 5.28327 (* 1 = 5.28327 loss) +I0410 14:29:16.287196 18606 sgd_solver.cpp:105] Iteration 7920, lr = 0.00208287 +I0410 14:29:21.135583 18606 solver.cpp:218] Iteration 7932 (2.47514 iter/s, 4.84821s/12 iters), loss = 5.26236 +I0410 14:29:21.135639 18606 solver.cpp:237] Train net output #0: loss = 5.26236 (* 1 = 5.26236 loss) +I0410 14:29:21.135653 18606 sgd_solver.cpp:105] Iteration 7932, lr = 0.00207792 +I0410 14:29:26.023356 18606 solver.cpp:218] Iteration 7944 (2.45523 iter/s, 4.88753s/12 iters), loss = 5.26735 +I0410 14:29:26.023404 18606 solver.cpp:237] Train net output #0: loss = 5.26735 (* 1 = 5.26735 loss) +I0410 14:29:26.023414 18606 sgd_solver.cpp:105] Iteration 7944, lr = 0.00207299 +I0410 14:29:30.504676 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_7956.caffemodel +I0410 14:29:31.798257 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_7956.solverstate +I0410 14:29:32.569855 18606 solver.cpp:330] Iteration 7956, Testing net (#0) +I0410 14:29:32.569886 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:29:33.908551 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:29:37.010736 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:29:37.010772 18606 solver.cpp:397] Test net output #1: loss = 5.28712 (* 1 = 5.28712 loss) +I0410 14:29:37.093444 18606 solver.cpp:218] Iteration 7956 (1.08405 iter/s, 11.0696s/12 iters), loss = 5.27794 +I0410 14:29:37.093492 18606 solver.cpp:237] Train net output #0: loss = 5.27794 (* 1 = 5.27794 loss) +I0410 14:29:37.093500 18606 sgd_solver.cpp:105] Iteration 7956, lr = 0.00206807 +I0410 14:29:41.278322 18606 solver.cpp:218] Iteration 7968 (2.86761 iter/s, 4.18466s/12 iters), loss = 5.27433 +I0410 14:29:41.278373 18606 solver.cpp:237] Train net output #0: loss = 5.27433 (* 1 = 5.27433 loss) +I0410 14:29:41.278383 18606 sgd_solver.cpp:105] Iteration 7968, lr = 0.00206316 +I0410 14:29:46.187767 18606 solver.cpp:218] Iteration 7980 (2.44439 iter/s, 4.9092s/12 iters), loss = 5.2544 +I0410 14:29:46.187922 18606 solver.cpp:237] Train net output #0: loss = 5.2544 (* 1 = 5.2544 loss) +I0410 14:29:46.187938 18606 sgd_solver.cpp:105] Iteration 7980, lr = 0.00205826 +I0410 14:29:50.395736 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:29:51.095053 18606 solver.cpp:218] Iteration 7992 (2.44551 iter/s, 4.90695s/12 iters), loss = 5.2547 +I0410 14:29:51.095096 18606 solver.cpp:237] Train net output #0: loss = 5.2547 (* 1 = 5.2547 loss) +I0410 14:29:51.095105 18606 sgd_solver.cpp:105] Iteration 7992, lr = 0.00205337 +I0410 14:29:56.097321 18606 solver.cpp:218] Iteration 8004 (2.39903 iter/s, 5.00203s/12 iters), loss = 5.27962 +I0410 14:29:56.097368 18606 solver.cpp:237] Train net output #0: loss = 5.27962 (* 1 = 5.27962 loss) +I0410 14:29:56.097378 18606 sgd_solver.cpp:105] Iteration 8004, lr = 0.0020485 +I0410 14:30:00.922662 18606 solver.cpp:218] Iteration 8016 (2.48699 iter/s, 4.82511s/12 iters), loss = 5.27729 +I0410 14:30:00.922708 18606 solver.cpp:237] Train net output #0: loss = 5.27729 (* 1 = 5.27729 loss) +I0410 14:30:00.922715 18606 sgd_solver.cpp:105] Iteration 8016, lr = 0.00204363 +I0410 14:30:05.739651 18606 solver.cpp:218] Iteration 8028 (2.4913 iter/s, 4.81676s/12 iters), loss = 5.29278 +I0410 14:30:05.739706 18606 solver.cpp:237] Train net output #0: loss = 5.29278 (* 1 = 5.29278 loss) +I0410 14:30:05.739717 18606 sgd_solver.cpp:105] Iteration 8028, lr = 0.00203878 +I0410 14:30:10.742463 18606 solver.cpp:218] Iteration 8040 (2.39877 iter/s, 5.00256s/12 iters), loss = 5.26431 +I0410 14:30:10.742519 18606 solver.cpp:237] Train net output #0: loss = 5.26431 (* 1 = 5.26431 loss) +I0410 14:30:10.742533 18606 sgd_solver.cpp:105] Iteration 8040, lr = 0.00203394 +I0410 14:30:15.531168 18606 solver.cpp:218] Iteration 8052 (2.50602 iter/s, 4.78847s/12 iters), loss = 5.28092 +I0410 14:30:15.531219 18606 solver.cpp:237] Train net output #0: loss = 5.28092 (* 1 = 5.28092 loss) +I0410 14:30:15.531229 18606 sgd_solver.cpp:105] Iteration 8052, lr = 0.00202911 +I0410 14:30:17.498728 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8058.caffemodel +I0410 14:30:17.827330 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8058.solverstate +I0410 14:30:18.044147 18606 solver.cpp:330] Iteration 8058, Testing net (#0) +I0410 14:30:18.044173 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:30:19.450073 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:30:22.656337 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:30:22.656373 18606 solver.cpp:397] Test net output #1: loss = 5.28702 (* 1 = 5.28702 loss) +I0410 14:30:24.519150 18606 solver.cpp:218] Iteration 8064 (1.33517 iter/s, 8.98759s/12 iters), loss = 5.27877 +I0410 14:30:24.519198 18606 solver.cpp:237] Train net output #0: loss = 5.27877 (* 1 = 5.27877 loss) +I0410 14:30:24.519208 18606 sgd_solver.cpp:105] Iteration 8064, lr = 0.00202429 +I0410 14:30:29.327603 18606 solver.cpp:218] Iteration 8076 (2.49573 iter/s, 4.80821s/12 iters), loss = 5.27796 +I0410 14:30:29.327667 18606 solver.cpp:237] Train net output #0: loss = 5.27796 (* 1 = 5.27796 loss) +I0410 14:30:29.327683 18606 sgd_solver.cpp:105] Iteration 8076, lr = 0.00201949 +I0410 14:30:34.182334 18606 solver.cpp:218] Iteration 8088 (2.47194 iter/s, 4.85448s/12 iters), loss = 5.26266 +I0410 14:30:34.182379 18606 solver.cpp:237] Train net output #0: loss = 5.26266 (* 1 = 5.26266 loss) +I0410 14:30:34.182389 18606 sgd_solver.cpp:105] Iteration 8088, lr = 0.00201469 +I0410 14:30:35.551996 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:30:39.003415 18606 solver.cpp:218] Iteration 8100 (2.48919 iter/s, 4.82085s/12 iters), loss = 5.26138 +I0410 14:30:39.003460 18606 solver.cpp:237] Train net output #0: loss = 5.26138 (* 1 = 5.26138 loss) +I0410 14:30:39.003469 18606 sgd_solver.cpp:105] Iteration 8100, lr = 0.00200991 +I0410 14:30:43.974117 18606 solver.cpp:218] Iteration 8112 (2.41426 iter/s, 4.97046s/12 iters), loss = 5.26519 +I0410 14:30:43.974162 18606 solver.cpp:237] Train net output #0: loss = 5.26519 (* 1 = 5.26519 loss) +I0410 14:30:43.974174 18606 sgd_solver.cpp:105] Iteration 8112, lr = 0.00200514 +I0410 14:30:48.949599 18606 solver.cpp:218] Iteration 8124 (2.41194 iter/s, 4.97524s/12 iters), loss = 5.27073 +I0410 14:30:48.949719 18606 solver.cpp:237] Train net output #0: loss = 5.27073 (* 1 = 5.27073 loss) +I0410 14:30:48.949733 18606 sgd_solver.cpp:105] Iteration 8124, lr = 0.00200038 +I0410 14:30:53.832226 18606 solver.cpp:218] Iteration 8136 (2.45785 iter/s, 4.88232s/12 iters), loss = 5.28466 +I0410 14:30:53.832281 18606 solver.cpp:237] Train net output #0: loss = 5.28466 (* 1 = 5.28466 loss) +I0410 14:30:53.832293 18606 sgd_solver.cpp:105] Iteration 8136, lr = 0.00199563 +I0410 14:30:58.759809 18606 solver.cpp:218] Iteration 8148 (2.43539 iter/s, 4.92734s/12 iters), loss = 5.24975 +I0410 14:30:58.759856 18606 solver.cpp:237] Train net output #0: loss = 5.24975 (* 1 = 5.24975 loss) +I0410 14:30:58.759865 18606 sgd_solver.cpp:105] Iteration 8148, lr = 0.00199089 +I0410 14:31:03.199347 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8160.caffemodel +I0410 14:31:03.532158 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8160.solverstate +I0410 14:31:03.750360 18606 solver.cpp:330] Iteration 8160, Testing net (#0) +I0410 14:31:03.750391 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:31:04.981465 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:08.158324 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:31:08.158368 18606 solver.cpp:397] Test net output #1: loss = 5.28678 (* 1 = 5.28678 loss) +I0410 14:31:08.241349 18606 solver.cpp:218] Iteration 8160 (1.26567 iter/s, 9.48113s/12 iters), loss = 5.26429 +I0410 14:31:08.241400 18606 solver.cpp:237] Train net output #0: loss = 5.26429 (* 1 = 5.26429 loss) +I0410 14:31:08.241410 18606 sgd_solver.cpp:105] Iteration 8160, lr = 0.00198616 +I0410 14:31:12.341831 18606 solver.cpp:218] Iteration 8172 (2.92664 iter/s, 4.10026s/12 iters), loss = 5.28387 +I0410 14:31:12.341889 18606 solver.cpp:237] Train net output #0: loss = 5.28387 (* 1 = 5.28387 loss) +I0410 14:31:12.341902 18606 sgd_solver.cpp:105] Iteration 8172, lr = 0.00198145 +I0410 14:31:17.211539 18606 solver.cpp:218] Iteration 8184 (2.46434 iter/s, 4.86946s/12 iters), loss = 5.27247 +I0410 14:31:17.211588 18606 solver.cpp:237] Train net output #0: loss = 5.27247 (* 1 = 5.27247 loss) +I0410 14:31:17.211599 18606 sgd_solver.cpp:105] Iteration 8184, lr = 0.00197674 +I0410 14:31:20.701035 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:22.116516 18606 solver.cpp:218] Iteration 8196 (2.44662 iter/s, 4.90473s/12 iters), loss = 5.27242 +I0410 14:31:22.116565 18606 solver.cpp:237] Train net output #0: loss = 5.27242 (* 1 = 5.27242 loss) +I0410 14:31:22.116576 18606 sgd_solver.cpp:105] Iteration 8196, lr = 0.00197205 +I0410 14:31:27.009755 18606 solver.cpp:218] Iteration 8208 (2.45249 iter/s, 4.89299s/12 iters), loss = 5.25876 +I0410 14:31:27.009809 18606 solver.cpp:237] Train net output #0: loss = 5.25876 (* 1 = 5.25876 loss) +I0410 14:31:27.009821 18606 sgd_solver.cpp:105] Iteration 8208, lr = 0.00196737 +I0410 14:31:31.854689 18606 solver.cpp:218] Iteration 8220 (2.47694 iter/s, 4.84469s/12 iters), loss = 5.26345 +I0410 14:31:31.854743 18606 solver.cpp:237] Train net output #0: loss = 5.26345 (* 1 = 5.26345 loss) +I0410 14:31:31.854754 18606 sgd_solver.cpp:105] Iteration 8220, lr = 0.0019627 +I0410 14:31:36.690254 18606 solver.cpp:218] Iteration 8232 (2.48174 iter/s, 4.83532s/12 iters), loss = 5.26868 +I0410 14:31:36.690310 18606 solver.cpp:237] Train net output #0: loss = 5.26868 (* 1 = 5.26868 loss) +I0410 14:31:36.690320 18606 sgd_solver.cpp:105] Iteration 8232, lr = 0.00195804 +I0410 14:31:41.618144 18606 solver.cpp:218] Iteration 8244 (2.43524 iter/s, 4.92764s/12 iters), loss = 5.25444 +I0410 14:31:41.618193 18606 solver.cpp:237] Train net output #0: loss = 5.25444 (* 1 = 5.25444 loss) +I0410 14:31:41.618203 18606 sgd_solver.cpp:105] Iteration 8244, lr = 0.00195339 +I0410 14:31:46.424727 18606 solver.cpp:218] Iteration 8256 (2.4967 iter/s, 4.80634s/12 iters), loss = 5.27287 +I0410 14:31:46.424782 18606 solver.cpp:237] Train net output #0: loss = 5.27287 (* 1 = 5.27287 loss) +I0410 14:31:46.424794 18606 sgd_solver.cpp:105] Iteration 8256, lr = 0.00194875 +I0410 14:31:48.395395 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8262.caffemodel +I0410 14:31:48.975453 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8262.solverstate +I0410 14:31:49.193768 18606 solver.cpp:330] Iteration 8262, Testing net (#0) +I0410 14:31:49.193795 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:31:50.506862 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:31:53.846462 18606 solver.cpp:397] Test net output #0: accuracy = 0.00612745 +I0410 14:31:53.846592 18606 solver.cpp:397] Test net output #1: loss = 5.2869 (* 1 = 5.2869 loss) +I0410 14:31:55.720628 18606 solver.cpp:218] Iteration 8268 (1.29095 iter/s, 9.29548s/12 iters), loss = 5.27975 +I0410 14:31:55.720680 18606 solver.cpp:237] Train net output #0: loss = 5.27975 (* 1 = 5.27975 loss) +I0410 14:31:55.720691 18606 sgd_solver.cpp:105] Iteration 8268, lr = 0.00194412 +I0410 14:32:00.536726 18606 solver.cpp:218] Iteration 8280 (2.49177 iter/s, 4.81586s/12 iters), loss = 5.28413 +I0410 14:32:00.536765 18606 solver.cpp:237] Train net output #0: loss = 5.28413 (* 1 = 5.28413 loss) +I0410 14:32:00.536773 18606 sgd_solver.cpp:105] Iteration 8280, lr = 0.00193951 +I0410 14:32:05.400930 18606 solver.cpp:218] Iteration 8292 (2.46712 iter/s, 4.86397s/12 iters), loss = 5.29138 +I0410 14:32:05.400981 18606 solver.cpp:237] Train net output #0: loss = 5.29138 (* 1 = 5.29138 loss) +I0410 14:32:05.400992 18606 sgd_solver.cpp:105] Iteration 8292, lr = 0.0019349 +I0410 14:32:06.077474 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:32:10.266034 18606 solver.cpp:218] Iteration 8304 (2.46667 iter/s, 4.86485s/12 iters), loss = 5.27859 +I0410 14:32:10.266081 18606 solver.cpp:237] Train net output #0: loss = 5.27859 (* 1 = 5.27859 loss) +I0410 14:32:10.266089 18606 sgd_solver.cpp:105] Iteration 8304, lr = 0.00193031 +I0410 14:32:11.433857 18606 blocking_queue.cpp:49] Waiting for data +I0410 14:32:15.199115 18606 solver.cpp:218] Iteration 8316 (2.43268 iter/s, 4.93283s/12 iters), loss = 5.27063 +I0410 14:32:15.199178 18606 solver.cpp:237] Train net output #0: loss = 5.27063 (* 1 = 5.27063 loss) +I0410 14:32:15.199191 18606 sgd_solver.cpp:105] Iteration 8316, lr = 0.00192573 +I0410 14:32:20.226233 18606 solver.cpp:218] Iteration 8328 (2.38718 iter/s, 5.02686s/12 iters), loss = 5.28075 +I0410 14:32:20.226274 18606 solver.cpp:237] Train net output #0: loss = 5.28075 (* 1 = 5.28075 loss) +I0410 14:32:20.226284 18606 sgd_solver.cpp:105] Iteration 8328, lr = 0.00192115 +I0410 14:32:25.046705 18606 solver.cpp:218] Iteration 8340 (2.48951 iter/s, 4.82023s/12 iters), loss = 5.27351 +I0410 14:32:25.058035 18606 solver.cpp:237] Train net output #0: loss = 5.27351 (* 1 = 5.27351 loss) +I0410 14:32:25.058049 18606 sgd_solver.cpp:105] Iteration 8340, lr = 0.00191659 +I0410 14:32:29.867841 18606 solver.cpp:218] Iteration 8352 (2.495 iter/s, 4.80962s/12 iters), loss = 5.28995 +I0410 14:32:29.867882 18606 solver.cpp:237] Train net output #0: loss = 5.28995 (* 1 = 5.28995 loss) +I0410 14:32:29.867892 18606 sgd_solver.cpp:105] Iteration 8352, lr = 0.00191204 +I0410 14:32:34.315814 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8364.caffemodel +I0410 14:32:36.744832 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8364.solverstate +I0410 14:32:37.532042 18606 solver.cpp:330] Iteration 8364, Testing net (#0) +I0410 14:32:37.532063 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:32:38.806499 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:32:42.095176 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:32:42.095227 18606 solver.cpp:397] Test net output #1: loss = 5.28661 (* 1 = 5.28661 loss) +I0410 14:32:42.178336 18606 solver.cpp:218] Iteration 8364 (0.97482 iter/s, 12.31s/12 iters), loss = 5.26598 +I0410 14:32:42.178393 18606 solver.cpp:237] Train net output #0: loss = 5.26598 (* 1 = 5.26598 loss) +I0410 14:32:42.178406 18606 sgd_solver.cpp:105] Iteration 8364, lr = 0.0019075 +I0410 14:32:46.258193 18606 solver.cpp:218] Iteration 8376 (2.94144 iter/s, 4.07963s/12 iters), loss = 5.26579 +I0410 14:32:46.258246 18606 solver.cpp:237] Train net output #0: loss = 5.26579 (* 1 = 5.26579 loss) +I0410 14:32:46.258258 18606 sgd_solver.cpp:105] Iteration 8376, lr = 0.00190297 +I0410 14:32:51.147536 18606 solver.cpp:218] Iteration 8388 (2.45444 iter/s, 4.88909s/12 iters), loss = 5.25903 +I0410 14:32:51.147589 18606 solver.cpp:237] Train net output #0: loss = 5.25903 (* 1 = 5.25903 loss) +I0410 14:32:51.147603 18606 sgd_solver.cpp:105] Iteration 8388, lr = 0.00189846 +I0410 14:32:53.962148 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:32:56.089864 18606 solver.cpp:218] Iteration 8400 (2.42813 iter/s, 4.94208s/12 iters), loss = 5.26444 +I0410 14:32:56.090021 18606 solver.cpp:237] Train net output #0: loss = 5.26444 (* 1 = 5.26444 loss) +I0410 14:32:56.090030 18606 sgd_solver.cpp:105] Iteration 8400, lr = 0.00189395 +I0410 14:33:00.917217 18606 solver.cpp:218] Iteration 8412 (2.48601 iter/s, 4.82701s/12 iters), loss = 5.24889 +I0410 14:33:00.917258 18606 solver.cpp:237] Train net output #0: loss = 5.24889 (* 1 = 5.24889 loss) +I0410 14:33:00.917268 18606 sgd_solver.cpp:105] Iteration 8412, lr = 0.00188945 +I0410 14:33:05.823361 18606 solver.cpp:218] Iteration 8424 (2.44603 iter/s, 4.90591s/12 iters), loss = 5.25428 +I0410 14:33:05.823396 18606 solver.cpp:237] Train net output #0: loss = 5.25428 (* 1 = 5.25428 loss) +I0410 14:33:05.823405 18606 sgd_solver.cpp:105] Iteration 8424, lr = 0.00188497 +I0410 14:33:10.667881 18606 solver.cpp:218] Iteration 8436 (2.47715 iter/s, 4.84428s/12 iters), loss = 5.25682 +I0410 14:33:10.667929 18606 solver.cpp:237] Train net output #0: loss = 5.25682 (* 1 = 5.25682 loss) +I0410 14:33:10.667938 18606 sgd_solver.cpp:105] Iteration 8436, lr = 0.00188049 +I0410 14:33:15.498474 18606 solver.cpp:218] Iteration 8448 (2.48429 iter/s, 4.83034s/12 iters), loss = 5.29487 +I0410 14:33:15.498533 18606 solver.cpp:237] Train net output #0: loss = 5.29487 (* 1 = 5.29487 loss) +I0410 14:33:15.498545 18606 sgd_solver.cpp:105] Iteration 8448, lr = 0.00187603 +I0410 14:33:20.286024 18606 solver.cpp:218] Iteration 8460 (2.50663 iter/s, 4.7873s/12 iters), loss = 5.27424 +I0410 14:33:20.286077 18606 solver.cpp:237] Train net output #0: loss = 5.27424 (* 1 = 5.27424 loss) +I0410 14:33:20.286089 18606 sgd_solver.cpp:105] Iteration 8460, lr = 0.00187157 +I0410 14:33:22.264000 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8466.caffemodel +I0410 14:33:22.586820 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8466.solverstate +I0410 14:33:22.788681 18606 solver.cpp:330] Iteration 8466, Testing net (#0) +I0410 14:33:22.788702 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:33:23.795806 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:33:27.082547 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:33:27.082654 18606 solver.cpp:397] Test net output #1: loss = 5.28661 (* 1 = 5.28661 loss) +I0410 14:33:28.975420 18606 solver.cpp:218] Iteration 8472 (1.38106 iter/s, 8.689s/12 iters), loss = 5.27384 +I0410 14:33:28.975461 18606 solver.cpp:237] Train net output #0: loss = 5.27384 (* 1 = 5.27384 loss) +I0410 14:33:28.975469 18606 sgd_solver.cpp:105] Iteration 8472, lr = 0.00186713 +I0410 14:33:33.910698 18606 solver.cpp:218] Iteration 8484 (2.4316 iter/s, 4.93503s/12 iters), loss = 5.2718 +I0410 14:33:33.910753 18606 solver.cpp:237] Train net output #0: loss = 5.2718 (* 1 = 5.2718 loss) +I0410 14:33:33.910766 18606 sgd_solver.cpp:105] Iteration 8484, lr = 0.0018627 +I0410 14:33:38.800182 18606 solver.cpp:218] Iteration 8496 (2.45437 iter/s, 4.88923s/12 iters), loss = 5.25446 +I0410 14:33:38.800230 18606 solver.cpp:237] Train net output #0: loss = 5.25446 (* 1 = 5.25446 loss) +I0410 14:33:38.800243 18606 sgd_solver.cpp:105] Iteration 8496, lr = 0.00185827 +I0410 14:33:38.851267 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:33:43.687407 18606 solver.cpp:218] Iteration 8508 (2.45551 iter/s, 4.88698s/12 iters), loss = 5.27944 +I0410 14:33:43.687469 18606 solver.cpp:237] Train net output #0: loss = 5.27944 (* 1 = 5.27944 loss) +I0410 14:33:43.687480 18606 sgd_solver.cpp:105] Iteration 8508, lr = 0.00185386 +I0410 14:33:48.566468 18606 solver.cpp:218] Iteration 8520 (2.45962 iter/s, 4.8788s/12 iters), loss = 5.29444 +I0410 14:33:48.566519 18606 solver.cpp:237] Train net output #0: loss = 5.29444 (* 1 = 5.29444 loss) +I0410 14:33:48.566531 18606 sgd_solver.cpp:105] Iteration 8520, lr = 0.00184946 +I0410 14:33:53.427089 18606 solver.cpp:218] Iteration 8532 (2.46895 iter/s, 4.86037s/12 iters), loss = 5.2693 +I0410 14:33:53.427130 18606 solver.cpp:237] Train net output #0: loss = 5.2693 (* 1 = 5.2693 loss) +I0410 14:33:53.427140 18606 sgd_solver.cpp:105] Iteration 8532, lr = 0.00184507 +I0410 14:33:58.257612 18606 solver.cpp:218] Iteration 8544 (2.48433 iter/s, 4.83029s/12 iters), loss = 5.27213 +I0410 14:33:58.257751 18606 solver.cpp:237] Train net output #0: loss = 5.27213 (* 1 = 5.27213 loss) +I0410 14:33:58.257761 18606 sgd_solver.cpp:105] Iteration 8544, lr = 0.00184069 +I0410 14:34:03.268057 18606 solver.cpp:218] Iteration 8556 (2.39516 iter/s, 5.0101s/12 iters), loss = 5.25646 +I0410 14:34:03.268107 18606 solver.cpp:237] Train net output #0: loss = 5.25646 (* 1 = 5.25646 loss) +I0410 14:34:03.268118 18606 sgd_solver.cpp:105] Iteration 8556, lr = 0.00183632 +I0410 14:34:07.681479 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8568.caffemodel +I0410 14:34:08.023303 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8568.solverstate +I0410 14:34:08.306356 18606 solver.cpp:330] Iteration 8568, Testing net (#0) +I0410 14:34:08.306375 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:34:09.376823 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:12.876699 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:34:12.876750 18606 solver.cpp:397] Test net output #1: loss = 5.28669 (* 1 = 5.28669 loss) +I0410 14:34:12.959389 18606 solver.cpp:218] Iteration 8568 (1.23827 iter/s, 9.6909s/12 iters), loss = 5.24604 +I0410 14:34:12.959439 18606 solver.cpp:237] Train net output #0: loss = 5.24604 (* 1 = 5.24604 loss) +I0410 14:34:12.959451 18606 sgd_solver.cpp:105] Iteration 8568, lr = 0.00183196 +I0410 14:34:17.090029 18606 solver.cpp:218] Iteration 8580 (2.90528 iter/s, 4.13042s/12 iters), loss = 5.26303 +I0410 14:34:17.090075 18606 solver.cpp:237] Train net output #0: loss = 5.26303 (* 1 = 5.26303 loss) +I0410 14:34:17.090085 18606 sgd_solver.cpp:105] Iteration 8580, lr = 0.00182761 +I0410 14:34:21.929991 18606 solver.cpp:218] Iteration 8592 (2.47949 iter/s, 4.83971s/12 iters), loss = 5.25403 +I0410 14:34:21.930048 18606 solver.cpp:237] Train net output #0: loss = 5.25403 (* 1 = 5.25403 loss) +I0410 14:34:21.930061 18606 sgd_solver.cpp:105] Iteration 8592, lr = 0.00182327 +I0410 14:34:24.045011 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:26.791963 18606 solver.cpp:218] Iteration 8604 (2.46826 iter/s, 4.86171s/12 iters), loss = 5.27128 +I0410 14:34:26.792007 18606 solver.cpp:237] Train net output #0: loss = 5.27128 (* 1 = 5.27128 loss) +I0410 14:34:26.792017 18606 sgd_solver.cpp:105] Iteration 8604, lr = 0.00181894 +I0410 14:34:31.708726 18606 solver.cpp:218] Iteration 8616 (2.44075 iter/s, 4.91652s/12 iters), loss = 5.26632 +I0410 14:34:31.708815 18606 solver.cpp:237] Train net output #0: loss = 5.26632 (* 1 = 5.26632 loss) +I0410 14:34:31.708824 18606 sgd_solver.cpp:105] Iteration 8616, lr = 0.00181462 +I0410 14:34:36.557224 18606 solver.cpp:218] Iteration 8628 (2.47514 iter/s, 4.84821s/12 iters), loss = 5.28366 +I0410 14:34:36.557282 18606 solver.cpp:237] Train net output #0: loss = 5.28366 (* 1 = 5.28366 loss) +I0410 14:34:36.557297 18606 sgd_solver.cpp:105] Iteration 8628, lr = 0.00181031 +I0410 14:34:41.310245 18606 solver.cpp:218] Iteration 8640 (2.52485 iter/s, 4.75277s/12 iters), loss = 5.26515 +I0410 14:34:41.310297 18606 solver.cpp:237] Train net output #0: loss = 5.26515 (* 1 = 5.26515 loss) +I0410 14:34:41.310308 18606 sgd_solver.cpp:105] Iteration 8640, lr = 0.00180602 +I0410 14:34:46.171831 18606 solver.cpp:218] Iteration 8652 (2.46846 iter/s, 4.86133s/12 iters), loss = 5.26561 +I0410 14:34:46.171880 18606 solver.cpp:237] Train net output #0: loss = 5.26561 (* 1 = 5.26561 loss) +I0410 14:34:46.171890 18606 sgd_solver.cpp:105] Iteration 8652, lr = 0.00180173 +I0410 14:34:51.077682 18606 solver.cpp:218] Iteration 8664 (2.44618 iter/s, 4.9056s/12 iters), loss = 5.276 +I0410 14:34:51.077740 18606 solver.cpp:237] Train net output #0: loss = 5.276 (* 1 = 5.276 loss) +I0410 14:34:51.077752 18606 sgd_solver.cpp:105] Iteration 8664, lr = 0.00179745 +I0410 14:34:53.107733 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8670.caffemodel +I0410 14:34:53.428043 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8670.solverstate +I0410 14:34:53.630787 18606 solver.cpp:330] Iteration 8670, Testing net (#0) +I0410 14:34:53.630817 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:34:54.656903 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:34:58.067625 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:34:58.067669 18606 solver.cpp:397] Test net output #1: loss = 5.28701 (* 1 = 5.28701 loss) +I0410 14:34:59.956830 18606 solver.cpp:218] Iteration 8676 (1.35154 iter/s, 8.87874s/12 iters), loss = 5.27632 +I0410 14:34:59.956861 18606 solver.cpp:237] Train net output #0: loss = 5.27632 (* 1 = 5.27632 loss) +I0410 14:34:59.956869 18606 sgd_solver.cpp:105] Iteration 8676, lr = 0.00179318 +I0410 14:35:04.851135 18606 solver.cpp:218] Iteration 8688 (2.45195 iter/s, 4.89406s/12 iters), loss = 5.26383 +I0410 14:35:04.851285 18606 solver.cpp:237] Train net output #0: loss = 5.26383 (* 1 = 5.26383 loss) +I0410 14:35:04.851298 18606 sgd_solver.cpp:105] Iteration 8688, lr = 0.00178893 +I0410 14:35:09.087119 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:35:09.755376 18606 solver.cpp:218] Iteration 8700 (2.44704 iter/s, 4.90389s/12 iters), loss = 5.26372 +I0410 14:35:09.755434 18606 solver.cpp:237] Train net output #0: loss = 5.26372 (* 1 = 5.26372 loss) +I0410 14:35:09.755450 18606 sgd_solver.cpp:105] Iteration 8700, lr = 0.00178468 +I0410 14:35:14.676520 18606 solver.cpp:218] Iteration 8712 (2.43859 iter/s, 4.92088s/12 iters), loss = 5.28168 +I0410 14:35:14.676578 18606 solver.cpp:237] Train net output #0: loss = 5.28168 (* 1 = 5.28168 loss) +I0410 14:35:14.676589 18606 sgd_solver.cpp:105] Iteration 8712, lr = 0.00178044 +I0410 14:35:19.572129 18606 solver.cpp:218] Iteration 8724 (2.45131 iter/s, 4.89534s/12 iters), loss = 5.27902 +I0410 14:35:19.572191 18606 solver.cpp:237] Train net output #0: loss = 5.27902 (* 1 = 5.27902 loss) +I0410 14:35:19.572206 18606 sgd_solver.cpp:105] Iteration 8724, lr = 0.00177621 +I0410 14:35:24.421258 18606 solver.cpp:218] Iteration 8736 (2.4748 iter/s, 4.84887s/12 iters), loss = 5.29435 +I0410 14:35:24.421306 18606 solver.cpp:237] Train net output #0: loss = 5.29435 (* 1 = 5.29435 loss) +I0410 14:35:24.421316 18606 sgd_solver.cpp:105] Iteration 8736, lr = 0.001772 +I0410 14:35:29.274364 18606 solver.cpp:218] Iteration 8748 (2.47277 iter/s, 4.85286s/12 iters), loss = 5.26882 +I0410 14:35:29.274408 18606 solver.cpp:237] Train net output #0: loss = 5.26882 (* 1 = 5.26882 loss) +I0410 14:35:29.274418 18606 sgd_solver.cpp:105] Iteration 8748, lr = 0.00176779 +I0410 14:35:34.135891 18606 solver.cpp:218] Iteration 8760 (2.46849 iter/s, 4.86128s/12 iters), loss = 5.2745 +I0410 14:35:34.135941 18606 solver.cpp:237] Train net output #0: loss = 5.2745 (* 1 = 5.2745 loss) +I0410 14:35:34.135951 18606 sgd_solver.cpp:105] Iteration 8760, lr = 0.00176359 +I0410 14:35:38.581552 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8772.caffemodel +I0410 14:35:39.196710 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8772.solverstate +I0410 14:35:39.409158 18606 solver.cpp:330] Iteration 8772, Testing net (#0) +I0410 14:35:39.409188 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:35:40.417248 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:35:43.918491 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:35:43.918542 18606 solver.cpp:397] Test net output #1: loss = 5.28707 (* 1 = 5.28707 loss) +I0410 14:35:44.001890 18606 solver.cpp:218] Iteration 8772 (1.21635 iter/s, 9.86556s/12 iters), loss = 5.27853 +I0410 14:35:44.001940 18606 solver.cpp:237] Train net output #0: loss = 5.27853 (* 1 = 5.27853 loss) +I0410 14:35:44.001951 18606 sgd_solver.cpp:105] Iteration 8772, lr = 0.00175941 +I0410 14:35:48.100443 18606 solver.cpp:218] Iteration 8784 (2.92802 iter/s, 4.09833s/12 iters), loss = 5.27631 +I0410 14:35:48.100484 18606 solver.cpp:237] Train net output #0: loss = 5.27631 (* 1 = 5.27631 loss) +I0410 14:35:48.100493 18606 sgd_solver.cpp:105] Iteration 8784, lr = 0.00175523 +I0410 14:35:52.914391 18606 solver.cpp:218] Iteration 8796 (2.49288 iter/s, 4.8137s/12 iters), loss = 5.25657 +I0410 14:35:52.914448 18606 solver.cpp:237] Train net output #0: loss = 5.25657 (* 1 = 5.25657 loss) +I0410 14:35:52.914463 18606 sgd_solver.cpp:105] Iteration 8796, lr = 0.00175106 +I0410 14:35:54.333395 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:35:57.760829 18606 solver.cpp:218] Iteration 8808 (2.47618 iter/s, 4.84618s/12 iters), loss = 5.26257 +I0410 14:35:57.760879 18606 solver.cpp:237] Train net output #0: loss = 5.26257 (* 1 = 5.26257 loss) +I0410 14:35:57.760887 18606 sgd_solver.cpp:105] Iteration 8808, lr = 0.0017469 +I0410 14:36:02.598593 18606 solver.cpp:218] Iteration 8820 (2.48061 iter/s, 4.83752s/12 iters), loss = 5.26773 +I0410 14:36:02.598634 18606 solver.cpp:237] Train net output #0: loss = 5.26773 (* 1 = 5.26773 loss) +I0410 14:36:02.598642 18606 sgd_solver.cpp:105] Iteration 8820, lr = 0.00174276 +I0410 14:36:07.388486 18606 solver.cpp:218] Iteration 8832 (2.5054 iter/s, 4.78965s/12 iters), loss = 5.26488 +I0410 14:36:07.388543 18606 solver.cpp:237] Train net output #0: loss = 5.26488 (* 1 = 5.26488 loss) +I0410 14:36:07.388556 18606 sgd_solver.cpp:105] Iteration 8832, lr = 0.00173862 +I0410 14:36:12.245183 18606 solver.cpp:218] Iteration 8844 (2.47095 iter/s, 4.85643s/12 iters), loss = 5.29729 +I0410 14:36:12.245306 18606 solver.cpp:237] Train net output #0: loss = 5.29729 (* 1 = 5.29729 loss) +I0410 14:36:12.245317 18606 sgd_solver.cpp:105] Iteration 8844, lr = 0.00173449 +I0410 14:36:17.058385 18606 solver.cpp:218] Iteration 8856 (2.49331 iter/s, 4.81288s/12 iters), loss = 5.25523 +I0410 14:36:17.058441 18606 solver.cpp:237] Train net output #0: loss = 5.25523 (* 1 = 5.25523 loss) +I0410 14:36:17.058454 18606 sgd_solver.cpp:105] Iteration 8856, lr = 0.00173037 +I0410 14:36:21.900720 18606 solver.cpp:218] Iteration 8868 (2.47828 iter/s, 4.84207s/12 iters), loss = 5.26039 +I0410 14:36:21.900772 18606 solver.cpp:237] Train net output #0: loss = 5.26039 (* 1 = 5.26039 loss) +I0410 14:36:21.900784 18606 sgd_solver.cpp:105] Iteration 8868, lr = 0.00172626 +I0410 14:36:23.850616 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8874.caffemodel +I0410 14:36:24.155354 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8874.solverstate +I0410 14:36:24.371567 18606 solver.cpp:330] Iteration 8874, Testing net (#0) +I0410 14:36:24.371593 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:36:25.470470 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:36:29.033587 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:36:29.033625 18606 solver.cpp:397] Test net output #1: loss = 5.28687 (* 1 = 5.28687 loss) +I0410 14:36:30.923722 18606 solver.cpp:218] Iteration 8880 (1.33 iter/s, 9.02259s/12 iters), loss = 5.28044 +I0410 14:36:30.923765 18606 solver.cpp:237] Train net output #0: loss = 5.28044 (* 1 = 5.28044 loss) +I0410 14:36:30.923775 18606 sgd_solver.cpp:105] Iteration 8880, lr = 0.00172217 +I0410 14:36:35.809298 18606 solver.cpp:218] Iteration 8892 (2.45634 iter/s, 4.88533s/12 iters), loss = 5.27903 +I0410 14:36:35.809352 18606 solver.cpp:237] Train net output #0: loss = 5.27903 (* 1 = 5.27903 loss) +I0410 14:36:35.809363 18606 sgd_solver.cpp:105] Iteration 8892, lr = 0.00171808 +I0410 14:36:39.376109 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:36:40.730206 18606 solver.cpp:218] Iteration 8904 (2.4387 iter/s, 4.92065s/12 iters), loss = 5.27467 +I0410 14:36:40.730260 18606 solver.cpp:237] Train net output #0: loss = 5.27467 (* 1 = 5.27467 loss) +I0410 14:36:40.730273 18606 sgd_solver.cpp:105] Iteration 8904, lr = 0.001714 +I0410 14:36:45.559901 18606 solver.cpp:218] Iteration 8916 (2.48476 iter/s, 4.82944s/12 iters), loss = 5.26564 +I0410 14:36:45.560039 18606 solver.cpp:237] Train net output #0: loss = 5.26564 (* 1 = 5.26564 loss) +I0410 14:36:45.560050 18606 sgd_solver.cpp:105] Iteration 8916, lr = 0.00170993 +I0410 14:36:50.343932 18606 solver.cpp:218] Iteration 8928 (2.50852 iter/s, 4.78369s/12 iters), loss = 5.26252 +I0410 14:36:50.343971 18606 solver.cpp:237] Train net output #0: loss = 5.26252 (* 1 = 5.26252 loss) +I0410 14:36:50.343978 18606 sgd_solver.cpp:105] Iteration 8928, lr = 0.00170587 +I0410 14:36:55.102774 18606 solver.cpp:218] Iteration 8940 (2.52175 iter/s, 4.7586s/12 iters), loss = 5.26684 +I0410 14:36:55.102823 18606 solver.cpp:237] Train net output #0: loss = 5.26684 (* 1 = 5.26684 loss) +I0410 14:36:55.102831 18606 sgd_solver.cpp:105] Iteration 8940, lr = 0.00170182 +I0410 14:37:00.185729 18606 solver.cpp:218] Iteration 8952 (2.36096 iter/s, 5.08269s/12 iters), loss = 5.25743 +I0410 14:37:00.185786 18606 solver.cpp:237] Train net output #0: loss = 5.25743 (* 1 = 5.25743 loss) +I0410 14:37:00.185796 18606 sgd_solver.cpp:105] Iteration 8952, lr = 0.00169778 +I0410 14:37:05.106178 18606 solver.cpp:218] Iteration 8964 (2.43893 iter/s, 4.92019s/12 iters), loss = 5.27857 +I0410 14:37:05.106230 18606 solver.cpp:237] Train net output #0: loss = 5.27857 (* 1 = 5.27857 loss) +I0410 14:37:05.106242 18606 sgd_solver.cpp:105] Iteration 8964, lr = 0.00169375 +I0410 14:37:09.626322 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_8976.caffemodel +I0410 14:37:09.923830 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_8976.solverstate +I0410 14:37:10.136871 18606 solver.cpp:330] Iteration 8976, Testing net (#0) +I0410 14:37:10.136893 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:37:11.037259 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:14.632324 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:37:14.632369 18606 solver.cpp:397] Test net output #1: loss = 5.28694 (* 1 = 5.28694 loss) +I0410 14:37:14.715425 18606 solver.cpp:218] Iteration 8976 (1.24885 iter/s, 9.60881s/12 iters), loss = 5.2773 +I0410 14:37:14.715473 18606 solver.cpp:237] Train net output #0: loss = 5.2773 (* 1 = 5.2773 loss) +I0410 14:37:14.715484 18606 sgd_solver.cpp:105] Iteration 8976, lr = 0.00168973 +I0410 14:37:18.873461 18606 solver.cpp:218] Iteration 8988 (2.88613 iter/s, 4.15781s/12 iters), loss = 5.28213 +I0410 14:37:18.873582 18606 solver.cpp:237] Train net output #0: loss = 5.28213 (* 1 = 5.28213 loss) +I0410 14:37:18.873594 18606 sgd_solver.cpp:105] Iteration 8988, lr = 0.00168571 +I0410 14:37:20.435382 18606 blocking_queue.cpp:49] Waiting for data +I0410 14:37:23.670055 18606 solver.cpp:218] Iteration 9000 (2.50194 iter/s, 4.79627s/12 iters), loss = 5.28719 +I0410 14:37:23.670109 18606 solver.cpp:237] Train net output #0: loss = 5.28719 (* 1 = 5.28719 loss) +I0410 14:37:23.670120 18606 sgd_solver.cpp:105] Iteration 9000, lr = 0.00168171 +I0410 14:37:24.382526 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:28.526808 18606 solver.cpp:218] Iteration 9012 (2.47092 iter/s, 4.85649s/12 iters), loss = 5.2857 +I0410 14:37:28.526865 18606 solver.cpp:237] Train net output #0: loss = 5.2857 (* 1 = 5.2857 loss) +I0410 14:37:28.526877 18606 sgd_solver.cpp:105] Iteration 9012, lr = 0.00167772 +I0410 14:37:33.330047 18606 solver.cpp:218] Iteration 9024 (2.49845 iter/s, 4.80298s/12 iters), loss = 5.26474 +I0410 14:37:33.330092 18606 solver.cpp:237] Train net output #0: loss = 5.26474 (* 1 = 5.26474 loss) +I0410 14:37:33.330101 18606 sgd_solver.cpp:105] Iteration 9024, lr = 0.00167374 +I0410 14:37:38.188203 18606 solver.cpp:218] Iteration 9036 (2.4702 iter/s, 4.8579s/12 iters), loss = 5.27339 +I0410 14:37:38.188266 18606 solver.cpp:237] Train net output #0: loss = 5.27339 (* 1 = 5.27339 loss) +I0410 14:37:38.188279 18606 sgd_solver.cpp:105] Iteration 9036, lr = 0.00166976 +I0410 14:37:43.084925 18606 solver.cpp:218] Iteration 9048 (2.45075 iter/s, 4.89645s/12 iters), loss = 5.27308 +I0410 14:37:43.084976 18606 solver.cpp:237] Train net output #0: loss = 5.27308 (* 1 = 5.27308 loss) +I0410 14:37:43.084990 18606 sgd_solver.cpp:105] Iteration 9048, lr = 0.0016658 +I0410 14:37:47.974720 18606 solver.cpp:218] Iteration 9060 (2.45422 iter/s, 4.88954s/12 iters), loss = 5.2915 +I0410 14:37:47.974768 18606 solver.cpp:237] Train net output #0: loss = 5.2915 (* 1 = 5.2915 loss) +I0410 14:37:47.974777 18606 sgd_solver.cpp:105] Iteration 9060, lr = 0.00166184 +I0410 14:37:52.800388 18606 solver.cpp:218] Iteration 9072 (2.48683 iter/s, 4.82541s/12 iters), loss = 5.26737 +I0410 14:37:52.800535 18606 solver.cpp:237] Train net output #0: loss = 5.26737 (* 1 = 5.26737 loss) +I0410 14:37:52.800546 18606 sgd_solver.cpp:105] Iteration 9072, lr = 0.0016579 +I0410 14:37:54.790261 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9078.caffemodel +I0410 14:37:55.113376 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9078.solverstate +I0410 14:37:55.319635 18606 solver.cpp:330] Iteration 9078, Testing net (#0) +I0410 14:37:55.319662 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:37:56.192905 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:37:59.873164 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:37:59.873211 18606 solver.cpp:397] Test net output #1: loss = 5.28713 (* 1 = 5.28713 loss) +I0410 14:38:01.662763 18606 solver.cpp:218] Iteration 9084 (1.35412 iter/s, 8.86187s/12 iters), loss = 5.25903 +I0410 14:38:01.662809 18606 solver.cpp:237] Train net output #0: loss = 5.25903 (* 1 = 5.25903 loss) +I0410 14:38:01.662820 18606 sgd_solver.cpp:105] Iteration 9084, lr = 0.00165396 +I0410 14:38:06.479903 18606 solver.cpp:218] Iteration 9096 (2.49124 iter/s, 4.81688s/12 iters), loss = 5.26481 +I0410 14:38:06.479959 18606 solver.cpp:237] Train net output #0: loss = 5.26481 (* 1 = 5.26481 loss) +I0410 14:38:06.479972 18606 sgd_solver.cpp:105] Iteration 9096, lr = 0.00165003 +I0410 14:38:09.521284 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:38:11.502686 18606 solver.cpp:218] Iteration 9108 (2.38924 iter/s, 5.02252s/12 iters), loss = 5.26098 +I0410 14:38:11.502738 18606 solver.cpp:237] Train net output #0: loss = 5.26098 (* 1 = 5.26098 loss) +I0410 14:38:11.502749 18606 sgd_solver.cpp:105] Iteration 9108, lr = 0.00164612 +I0410 14:38:16.346894 18606 solver.cpp:218] Iteration 9120 (2.47732 iter/s, 4.84395s/12 iters), loss = 5.24977 +I0410 14:38:16.346949 18606 solver.cpp:237] Train net output #0: loss = 5.24977 (* 1 = 5.24977 loss) +I0410 14:38:16.346962 18606 sgd_solver.cpp:105] Iteration 9120, lr = 0.00164221 +I0410 14:38:21.147418 18606 solver.cpp:218] Iteration 9132 (2.49986 iter/s, 4.80026s/12 iters), loss = 5.24904 +I0410 14:38:21.147467 18606 solver.cpp:237] Train net output #0: loss = 5.24904 (* 1 = 5.24904 loss) +I0410 14:38:21.147478 18606 sgd_solver.cpp:105] Iteration 9132, lr = 0.00163831 +I0410 14:38:25.962659 18606 solver.cpp:218] Iteration 9144 (2.49222 iter/s, 4.81499s/12 iters), loss = 5.2588 +I0410 14:38:25.962788 18606 solver.cpp:237] Train net output #0: loss = 5.2588 (* 1 = 5.2588 loss) +I0410 14:38:25.962802 18606 sgd_solver.cpp:105] Iteration 9144, lr = 0.00163442 +I0410 14:38:30.810623 18606 solver.cpp:218] Iteration 9156 (2.47544 iter/s, 4.84763s/12 iters), loss = 5.2868 +I0410 14:38:30.810678 18606 solver.cpp:237] Train net output #0: loss = 5.2868 (* 1 = 5.2868 loss) +I0410 14:38:30.810690 18606 sgd_solver.cpp:105] Iteration 9156, lr = 0.00163054 +I0410 14:38:35.744762 18606 solver.cpp:218] Iteration 9168 (2.43217 iter/s, 4.93387s/12 iters), loss = 5.2712 +I0410 14:38:35.744819 18606 solver.cpp:237] Train net output #0: loss = 5.2712 (* 1 = 5.2712 loss) +I0410 14:38:35.744832 18606 sgd_solver.cpp:105] Iteration 9168, lr = 0.00162667 +I0410 14:38:40.134681 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9180.caffemodel +I0410 14:38:41.316921 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9180.solverstate +I0410 14:38:41.889742 18606 solver.cpp:330] Iteration 9180, Testing net (#0) +I0410 14:38:41.889773 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:38:42.750692 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:38:46.517418 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:38:46.517468 18606 solver.cpp:397] Test net output #1: loss = 5.28741 (* 1 = 5.28741 loss) +I0410 14:38:46.600509 18606 solver.cpp:218] Iteration 9180 (1.10546 iter/s, 10.8552s/12 iters), loss = 5.27408 +I0410 14:38:46.600565 18606 solver.cpp:237] Train net output #0: loss = 5.27408 (* 1 = 5.27408 loss) +I0410 14:38:46.600579 18606 sgd_solver.cpp:105] Iteration 9180, lr = 0.00162281 +I0410 14:38:50.776664 18606 solver.cpp:218] Iteration 9192 (2.87362 iter/s, 4.17592s/12 iters), loss = 5.27456 +I0410 14:38:50.776722 18606 solver.cpp:237] Train net output #0: loss = 5.27456 (* 1 = 5.27456 loss) +I0410 14:38:50.776734 18606 sgd_solver.cpp:105] Iteration 9192, lr = 0.00161895 +I0410 14:38:55.684630 18606 solver.cpp:218] Iteration 9204 (2.44514 iter/s, 4.9077s/12 iters), loss = 5.26609 +I0410 14:38:55.684689 18606 solver.cpp:237] Train net output #0: loss = 5.26609 (* 1 = 5.26609 loss) +I0410 14:38:55.684701 18606 sgd_solver.cpp:105] Iteration 9204, lr = 0.00161511 +I0410 14:38:55.767992 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:39:00.594305 18606 solver.cpp:218] Iteration 9216 (2.44429 iter/s, 4.9094s/12 iters), loss = 5.27657 +I0410 14:39:00.594441 18606 solver.cpp:237] Train net output #0: loss = 5.27657 (* 1 = 5.27657 loss) +I0410 14:39:00.594455 18606 sgd_solver.cpp:105] Iteration 9216, lr = 0.00161128 +I0410 14:39:05.493597 18606 solver.cpp:218] Iteration 9228 (2.4495 iter/s, 4.89895s/12 iters), loss = 5.28558 +I0410 14:39:05.493651 18606 solver.cpp:237] Train net output #0: loss = 5.28558 (* 1 = 5.28558 loss) +I0410 14:39:05.493664 18606 sgd_solver.cpp:105] Iteration 9228, lr = 0.00160745 +I0410 14:39:10.397445 18606 solver.cpp:218] Iteration 9240 (2.44719 iter/s, 4.90359s/12 iters), loss = 5.26124 +I0410 14:39:10.397497 18606 solver.cpp:237] Train net output #0: loss = 5.26124 (* 1 = 5.26124 loss) +I0410 14:39:10.397509 18606 sgd_solver.cpp:105] Iteration 9240, lr = 0.00160363 +I0410 14:39:15.195456 18606 solver.cpp:218] Iteration 9252 (2.50117 iter/s, 4.79775s/12 iters), loss = 5.2751 +I0410 14:39:15.195513 18606 solver.cpp:237] Train net output #0: loss = 5.2751 (* 1 = 5.2751 loss) +I0410 14:39:15.195524 18606 sgd_solver.cpp:105] Iteration 9252, lr = 0.00159983 +I0410 14:39:20.002452 18606 solver.cpp:218] Iteration 9264 (2.4965 iter/s, 4.80673s/12 iters), loss = 5.26057 +I0410 14:39:20.002516 18606 solver.cpp:237] Train net output #0: loss = 5.26057 (* 1 = 5.26057 loss) +I0410 14:39:20.002528 18606 sgd_solver.cpp:105] Iteration 9264, lr = 0.00159603 +I0410 14:39:24.784512 18606 solver.cpp:218] Iteration 9276 (2.50952 iter/s, 4.78179s/12 iters), loss = 5.24909 +I0410 14:39:24.784576 18606 solver.cpp:237] Train net output #0: loss = 5.24909 (* 1 = 5.24909 loss) +I0410 14:39:24.784588 18606 sgd_solver.cpp:105] Iteration 9276, lr = 0.00159224 +I0410 14:39:26.722353 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9282.caffemodel +I0410 14:39:27.655640 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9282.solverstate +I0410 14:39:28.085861 18606 solver.cpp:330] Iteration 9282, Testing net (#0) +I0410 14:39:28.085888 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:39:28.902964 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:39:32.525593 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:39:32.525789 18606 solver.cpp:397] Test net output #1: loss = 5.28694 (* 1 = 5.28694 loss) +I0410 14:39:34.340989 18606 solver.cpp:218] Iteration 9288 (1.25575 iter/s, 9.55602s/12 iters), loss = 5.26528 +I0410 14:39:34.341046 18606 solver.cpp:237] Train net output #0: loss = 5.26528 (* 1 = 5.26528 loss) +I0410 14:39:34.341058 18606 sgd_solver.cpp:105] Iteration 9288, lr = 0.00158846 +I0410 14:39:39.169996 18606 solver.cpp:218] Iteration 9300 (2.48512 iter/s, 4.82873s/12 iters), loss = 5.2519 +I0410 14:39:39.170051 18606 solver.cpp:237] Train net output #0: loss = 5.2519 (* 1 = 5.2519 loss) +I0410 14:39:39.170063 18606 sgd_solver.cpp:105] Iteration 9300, lr = 0.00158469 +I0410 14:39:41.272330 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:39:43.988004 18606 solver.cpp:218] Iteration 9312 (2.49079 iter/s, 4.81774s/12 iters), loss = 5.27378 +I0410 14:39:43.988055 18606 solver.cpp:237] Train net output #0: loss = 5.27378 (* 1 = 5.27378 loss) +I0410 14:39:43.988067 18606 sgd_solver.cpp:105] Iteration 9312, lr = 0.00158092 +I0410 14:39:48.803339 18606 solver.cpp:218] Iteration 9324 (2.49217 iter/s, 4.81508s/12 iters), loss = 5.27766 +I0410 14:39:48.803393 18606 solver.cpp:237] Train net output #0: loss = 5.27766 (* 1 = 5.27766 loss) +I0410 14:39:48.803406 18606 sgd_solver.cpp:105] Iteration 9324, lr = 0.00157717 +I0410 14:39:53.589232 18606 solver.cpp:218] Iteration 9336 (2.5075 iter/s, 4.78564s/12 iters), loss = 5.28664 +I0410 14:39:53.589282 18606 solver.cpp:237] Train net output #0: loss = 5.28664 (* 1 = 5.28664 loss) +I0410 14:39:53.589294 18606 sgd_solver.cpp:105] Iteration 9336, lr = 0.00157343 +I0410 14:39:58.392323 18606 solver.cpp:218] Iteration 9348 (2.49853 iter/s, 4.80283s/12 iters), loss = 5.27194 +I0410 14:39:58.392375 18606 solver.cpp:237] Train net output #0: loss = 5.27194 (* 1 = 5.27194 loss) +I0410 14:39:58.392386 18606 sgd_solver.cpp:105] Iteration 9348, lr = 0.00156969 +I0410 14:40:03.236167 18606 solver.cpp:218] Iteration 9360 (2.4775 iter/s, 4.84359s/12 iters), loss = 5.26898 +I0410 14:40:03.236255 18606 solver.cpp:237] Train net output #0: loss = 5.26898 (* 1 = 5.26898 loss) +I0410 14:40:03.236268 18606 sgd_solver.cpp:105] Iteration 9360, lr = 0.00156596 +I0410 14:40:08.080849 18606 solver.cpp:218] Iteration 9372 (2.4771 iter/s, 4.84438s/12 iters), loss = 5.27257 +I0410 14:40:08.080907 18606 solver.cpp:237] Train net output #0: loss = 5.27257 (* 1 = 5.27257 loss) +I0410 14:40:08.080920 18606 sgd_solver.cpp:105] Iteration 9372, lr = 0.00156225 +I0410 14:40:12.457706 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9384.caffemodel +I0410 14:40:12.747756 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9384.solverstate +I0410 14:40:12.948335 18606 solver.cpp:330] Iteration 9384, Testing net (#0) +I0410 14:40:12.948354 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:40:13.698848 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:17.356762 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:40:17.356812 18606 solver.cpp:397] Test net output #1: loss = 5.28699 (* 1 = 5.28699 loss) +I0410 14:40:17.439621 18606 solver.cpp:218] Iteration 9384 (1.28228 iter/s, 9.35833s/12 iters), loss = 5.27619 +I0410 14:40:17.439683 18606 solver.cpp:237] Train net output #0: loss = 5.27619 (* 1 = 5.27619 loss) +I0410 14:40:17.439697 18606 sgd_solver.cpp:105] Iteration 9384, lr = 0.00155854 +I0410 14:40:21.572508 18606 solver.cpp:218] Iteration 9396 (2.90371 iter/s, 4.13264s/12 iters), loss = 5.26735 +I0410 14:40:21.572568 18606 solver.cpp:237] Train net output #0: loss = 5.26735 (* 1 = 5.26735 loss) +I0410 14:40:21.572582 18606 sgd_solver.cpp:105] Iteration 9396, lr = 0.00155484 +I0410 14:40:25.788375 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:40:26.413692 18606 solver.cpp:218] Iteration 9408 (2.47887 iter/s, 4.84091s/12 iters), loss = 5.26999 +I0410 14:40:26.413753 18606 solver.cpp:237] Train net output #0: loss = 5.26999 (* 1 = 5.26999 loss) +I0410 14:40:26.413766 18606 sgd_solver.cpp:105] Iteration 9408, lr = 0.00155114 +I0410 14:40:31.259341 18606 solver.cpp:218] Iteration 9420 (2.47659 iter/s, 4.84538s/12 iters), loss = 5.27512 +I0410 14:40:31.259402 18606 solver.cpp:237] Train net output #0: loss = 5.27512 (* 1 = 5.27512 loss) +I0410 14:40:31.259414 18606 sgd_solver.cpp:105] Iteration 9420, lr = 0.00154746 +I0410 14:40:36.139367 18606 solver.cpp:218] Iteration 9432 (2.45914 iter/s, 4.87976s/12 iters), loss = 5.28248 +I0410 14:40:36.139530 18606 solver.cpp:237] Train net output #0: loss = 5.28248 (* 1 = 5.28248 loss) +I0410 14:40:36.139545 18606 sgd_solver.cpp:105] Iteration 9432, lr = 0.00154379 +I0410 14:40:41.006778 18606 solver.cpp:218] Iteration 9444 (2.46556 iter/s, 4.86705s/12 iters), loss = 5.28434 +I0410 14:40:41.006824 18606 solver.cpp:237] Train net output #0: loss = 5.28434 (* 1 = 5.28434 loss) +I0410 14:40:41.006834 18606 sgd_solver.cpp:105] Iteration 9444, lr = 0.00154012 +I0410 14:40:45.854270 18606 solver.cpp:218] Iteration 9456 (2.47564 iter/s, 4.84723s/12 iters), loss = 5.2664 +I0410 14:40:45.854327 18606 solver.cpp:237] Train net output #0: loss = 5.2664 (* 1 = 5.2664 loss) +I0410 14:40:45.854339 18606 sgd_solver.cpp:105] Iteration 9456, lr = 0.00153647 +I0410 14:40:50.669803 18606 solver.cpp:218] Iteration 9468 (2.49207 iter/s, 4.81527s/12 iters), loss = 5.28047 +I0410 14:40:50.669853 18606 solver.cpp:237] Train net output #0: loss = 5.28047 (* 1 = 5.28047 loss) +I0410 14:40:50.669864 18606 sgd_solver.cpp:105] Iteration 9468, lr = 0.00153282 +I0410 14:40:55.489851 18606 solver.cpp:218] Iteration 9480 (2.48973 iter/s, 4.8198s/12 iters), loss = 5.27523 +I0410 14:40:55.489897 18606 solver.cpp:237] Train net output #0: loss = 5.27523 (* 1 = 5.27523 loss) +I0410 14:40:55.489907 18606 sgd_solver.cpp:105] Iteration 9480, lr = 0.00152918 +I0410 14:40:57.466714 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9486.caffemodel +I0410 14:40:57.819658 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9486.solverstate +I0410 14:40:58.033432 18606 solver.cpp:330] Iteration 9486, Testing net (#0) +I0410 14:40:58.033449 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:40:58.726552 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:02.438659 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:41:02.438701 18606 solver.cpp:397] Test net output #1: loss = 5.28646 (* 1 = 5.28646 loss) +I0410 14:41:04.259604 18606 solver.cpp:218] Iteration 9492 (1.3684 iter/s, 8.76934s/12 iters), loss = 5.26922 +I0410 14:41:04.259660 18606 solver.cpp:237] Train net output #0: loss = 5.26922 (* 1 = 5.26922 loss) +I0410 14:41:04.259671 18606 sgd_solver.cpp:105] Iteration 9492, lr = 0.00152555 +I0410 14:41:09.077505 18606 solver.cpp:218] Iteration 9504 (2.49085 iter/s, 4.81763s/12 iters), loss = 5.2608 +I0410 14:41:09.077618 18606 solver.cpp:237] Train net output #0: loss = 5.2608 (* 1 = 5.2608 loss) +I0410 14:41:09.077631 18606 sgd_solver.cpp:105] Iteration 9504, lr = 0.00152193 +I0410 14:41:10.485790 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:13.814097 18606 solver.cpp:218] Iteration 9516 (2.53364 iter/s, 4.73627s/12 iters), loss = 5.26172 +I0410 14:41:13.814167 18606 solver.cpp:237] Train net output #0: loss = 5.26172 (* 1 = 5.26172 loss) +I0410 14:41:13.814182 18606 sgd_solver.cpp:105] Iteration 9516, lr = 0.00151831 +I0410 14:41:18.590164 18606 solver.cpp:218] Iteration 9528 (2.51267 iter/s, 4.7758s/12 iters), loss = 5.26334 +I0410 14:41:18.590212 18606 solver.cpp:237] Train net output #0: loss = 5.26334 (* 1 = 5.26334 loss) +I0410 14:41:18.590222 18606 sgd_solver.cpp:105] Iteration 9528, lr = 0.00151471 +I0410 14:41:23.526196 18606 solver.cpp:218] Iteration 9540 (2.43123 iter/s, 4.93577s/12 iters), loss = 5.24667 +I0410 14:41:23.526238 18606 solver.cpp:237] Train net output #0: loss = 5.24667 (* 1 = 5.24667 loss) +I0410 14:41:23.526247 18606 sgd_solver.cpp:105] Iteration 9540, lr = 0.00151111 +I0410 14:41:28.355842 18606 solver.cpp:218] Iteration 9552 (2.48478 iter/s, 4.82939s/12 iters), loss = 5.29952 +I0410 14:41:28.355906 18606 solver.cpp:237] Train net output #0: loss = 5.29952 (* 1 = 5.29952 loss) +I0410 14:41:28.355918 18606 sgd_solver.cpp:105] Iteration 9552, lr = 0.00150752 +I0410 14:41:33.866652 18606 solver.cpp:218] Iteration 9564 (2.17765 iter/s, 5.51052s/12 iters), loss = 5.25523 +I0410 14:41:33.866690 18606 solver.cpp:237] Train net output #0: loss = 5.25523 (* 1 = 5.25523 loss) +I0410 14:41:33.866700 18606 sgd_solver.cpp:105] Iteration 9564, lr = 0.00150395 +I0410 14:41:38.762981 18606 solver.cpp:218] Iteration 9576 (2.45094 iter/s, 4.89607s/12 iters), loss = 5.2617 +I0410 14:41:38.763036 18606 solver.cpp:237] Train net output #0: loss = 5.2617 (* 1 = 5.2617 loss) +I0410 14:41:38.763046 18606 sgd_solver.cpp:105] Iteration 9576, lr = 0.00150037 +I0410 14:41:43.246316 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9588.caffemodel +I0410 14:41:43.691432 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9588.solverstate +I0410 14:41:44.044092 18606 solver.cpp:330] Iteration 9588, Testing net (#0) +I0410 14:41:44.044123 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:41:44.737457 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:48.503779 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:41:48.503829 18606 solver.cpp:397] Test net output #1: loss = 5.28675 (* 1 = 5.28675 loss) +I0410 14:41:48.587124 18606 solver.cpp:218] Iteration 9588 (1.22154 iter/s, 9.82367s/12 iters), loss = 5.2754 +I0410 14:41:48.587193 18606 solver.cpp:237] Train net output #0: loss = 5.2754 (* 1 = 5.2754 loss) +I0410 14:41:48.587208 18606 sgd_solver.cpp:105] Iteration 9588, lr = 0.00149681 +I0410 14:41:52.824594 18606 solver.cpp:218] Iteration 9600 (2.83204 iter/s, 4.23723s/12 iters), loss = 5.27531 +I0410 14:41:52.824636 18606 solver.cpp:237] Train net output #0: loss = 5.27531 (* 1 = 5.27531 loss) +I0410 14:41:52.824645 18606 sgd_solver.cpp:105] Iteration 9600, lr = 0.00149326 +I0410 14:41:56.366477 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:41:57.719905 18606 solver.cpp:218] Iteration 9612 (2.45145 iter/s, 4.89506s/12 iters), loss = 5.27151 +I0410 14:41:57.719960 18606 solver.cpp:237] Train net output #0: loss = 5.27151 (* 1 = 5.27151 loss) +I0410 14:41:57.719972 18606 sgd_solver.cpp:105] Iteration 9612, lr = 0.00148971 +I0410 14:42:02.632966 18606 solver.cpp:218] Iteration 9624 (2.4426 iter/s, 4.91279s/12 iters), loss = 5.26714 +I0410 14:42:02.633023 18606 solver.cpp:237] Train net output #0: loss = 5.26714 (* 1 = 5.26714 loss) +I0410 14:42:02.633038 18606 sgd_solver.cpp:105] Iteration 9624, lr = 0.00148618 +I0410 14:42:07.500032 18606 solver.cpp:218] Iteration 9636 (2.46569 iter/s, 4.8668s/12 iters), loss = 5.25592 +I0410 14:42:07.500090 18606 solver.cpp:237] Train net output #0: loss = 5.25592 (* 1 = 5.25592 loss) +I0410 14:42:07.500103 18606 sgd_solver.cpp:105] Iteration 9636, lr = 0.00148265 +I0410 14:42:12.351953 18606 solver.cpp:218] Iteration 9648 (2.47338 iter/s, 4.85165s/12 iters), loss = 5.2666 +I0410 14:42:12.351997 18606 solver.cpp:237] Train net output #0: loss = 5.2666 (* 1 = 5.2666 loss) +I0410 14:42:12.352007 18606 sgd_solver.cpp:105] Iteration 9648, lr = 0.00147913 +I0410 14:42:17.257949 18606 solver.cpp:218] Iteration 9660 (2.44612 iter/s, 4.90574s/12 iters), loss = 5.25419 +I0410 14:42:17.258266 18606 solver.cpp:237] Train net output #0: loss = 5.25419 (* 1 = 5.25419 loss) +I0410 14:42:17.258280 18606 sgd_solver.cpp:105] Iteration 9660, lr = 0.00147562 +I0410 14:42:22.324357 18606 solver.cpp:218] Iteration 9672 (2.36879 iter/s, 5.06587s/12 iters), loss = 5.27051 +I0410 14:42:22.324415 18606 solver.cpp:237] Train net output #0: loss = 5.27051 (* 1 = 5.27051 loss) +I0410 14:42:22.324429 18606 sgd_solver.cpp:105] Iteration 9672, lr = 0.00147211 +I0410 14:42:27.182010 18606 solver.cpp:218] Iteration 9684 (2.47047 iter/s, 4.85738s/12 iters), loss = 5.28905 +I0410 14:42:27.182070 18606 solver.cpp:237] Train net output #0: loss = 5.28905 (* 1 = 5.28905 loss) +I0410 14:42:27.182083 18606 sgd_solver.cpp:105] Iteration 9684, lr = 0.00146862 +I0410 14:42:29.149649 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9690.caffemodel +I0410 14:42:29.498610 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9690.solverstate +I0410 14:42:29.714547 18606 solver.cpp:330] Iteration 9690, Testing net (#0) +I0410 14:42:29.714566 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:42:30.275943 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:42:32.808842 18606 blocking_queue.cpp:49] Waiting for data +I0410 14:42:34.165793 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:42:34.165841 18606 solver.cpp:397] Test net output #1: loss = 5.28695 (* 1 = 5.28695 loss) +I0410 14:42:35.908547 18606 solver.cpp:218] Iteration 9696 (1.37518 iter/s, 8.72611s/12 iters), loss = 5.28696 +I0410 14:42:35.908604 18606 solver.cpp:237] Train net output #0: loss = 5.28696 (* 1 = 5.28696 loss) +I0410 14:42:35.908617 18606 sgd_solver.cpp:105] Iteration 9696, lr = 0.00146513 +I0410 14:42:40.708297 18606 solver.cpp:218] Iteration 9708 (2.50027 iter/s, 4.79948s/12 iters), loss = 5.28801 +I0410 14:42:40.708364 18606 solver.cpp:237] Train net output #0: loss = 5.28801 (* 1 = 5.28801 loss) +I0410 14:42:40.708376 18606 sgd_solver.cpp:105] Iteration 9708, lr = 0.00146165 +I0410 14:42:41.424788 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:42:45.615420 18606 solver.cpp:218] Iteration 9720 (2.44556 iter/s, 4.90685s/12 iters), loss = 5.28914 +I0410 14:42:45.615463 18606 solver.cpp:237] Train net output #0: loss = 5.28914 (* 1 = 5.28914 loss) +I0410 14:42:45.615471 18606 sgd_solver.cpp:105] Iteration 9720, lr = 0.00145818 +I0410 14:42:50.719691 18606 solver.cpp:218] Iteration 9732 (2.3511 iter/s, 5.104s/12 iters), loss = 5.26225 +I0410 14:42:50.719859 18606 solver.cpp:237] Train net output #0: loss = 5.26225 (* 1 = 5.26225 loss) +I0410 14:42:50.719873 18606 sgd_solver.cpp:105] Iteration 9732, lr = 0.00145472 +I0410 14:42:55.645648 18606 solver.cpp:218] Iteration 9744 (2.43626 iter/s, 4.92558s/12 iters), loss = 5.2682 +I0410 14:42:55.645696 18606 solver.cpp:237] Train net output #0: loss = 5.2682 (* 1 = 5.2682 loss) +I0410 14:42:55.645705 18606 sgd_solver.cpp:105] Iteration 9744, lr = 0.00145127 +I0410 14:43:00.470695 18606 solver.cpp:218] Iteration 9756 (2.48715 iter/s, 4.82479s/12 iters), loss = 5.27418 +I0410 14:43:00.470741 18606 solver.cpp:237] Train net output #0: loss = 5.27418 (* 1 = 5.27418 loss) +I0410 14:43:00.470750 18606 sgd_solver.cpp:105] Iteration 9756, lr = 0.00144782 +I0410 14:43:05.306035 18606 solver.cpp:218] Iteration 9768 (2.48186 iter/s, 4.83508s/12 iters), loss = 5.28814 +I0410 14:43:05.306089 18606 solver.cpp:237] Train net output #0: loss = 5.28814 (* 1 = 5.28814 loss) +I0410 14:43:05.306100 18606 sgd_solver.cpp:105] Iteration 9768, lr = 0.00144438 +I0410 14:43:10.074985 18606 solver.cpp:218] Iteration 9780 (2.51642 iter/s, 4.76869s/12 iters), loss = 5.2709 +I0410 14:43:10.075035 18606 solver.cpp:237] Train net output #0: loss = 5.2709 (* 1 = 5.2709 loss) +I0410 14:43:10.075047 18606 sgd_solver.cpp:105] Iteration 9780, lr = 0.00144095 +I0410 14:43:14.844563 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9792.caffemodel +I0410 14:43:15.154974 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9792.solverstate +I0410 14:43:15.357342 18606 solver.cpp:330] Iteration 9792, Testing net (#0) +I0410 14:43:15.357362 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:43:16.003763 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:43:19.833856 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:43:19.833901 18606 solver.cpp:397] Test net output #1: loss = 5.28672 (* 1 = 5.28672 loss) +I0410 14:43:19.916857 18606 solver.cpp:218] Iteration 9792 (1.21934 iter/s, 9.84141s/12 iters), loss = 5.2519 +I0410 14:43:19.916908 18606 solver.cpp:237] Train net output #0: loss = 5.2519 (* 1 = 5.2519 loss) +I0410 14:43:19.916918 18606 sgd_solver.cpp:105] Iteration 9792, lr = 0.00143753 +I0410 14:43:24.163828 18606 solver.cpp:218] Iteration 9804 (2.8257 iter/s, 4.24673s/12 iters), loss = 5.27284 +I0410 14:43:24.163959 18606 solver.cpp:237] Train net output #0: loss = 5.27284 (* 1 = 5.27284 loss) +I0410 14:43:24.163973 18606 sgd_solver.cpp:105] Iteration 9804, lr = 0.00143412 +I0410 14:43:27.023586 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:43:28.983841 18606 solver.cpp:218] Iteration 9816 (2.48979 iter/s, 4.81968s/12 iters), loss = 5.26638 +I0410 14:43:28.983887 18606 solver.cpp:237] Train net output #0: loss = 5.26638 (* 1 = 5.26638 loss) +I0410 14:43:28.983898 18606 sgd_solver.cpp:105] Iteration 9816, lr = 0.00143072 +I0410 14:43:33.823899 18606 solver.cpp:218] Iteration 9828 (2.47944 iter/s, 4.8398s/12 iters), loss = 5.25323 +I0410 14:43:33.823952 18606 solver.cpp:237] Train net output #0: loss = 5.25323 (* 1 = 5.25323 loss) +I0410 14:43:33.823966 18606 sgd_solver.cpp:105] Iteration 9828, lr = 0.00142732 +I0410 14:43:38.664674 18606 solver.cpp:218] Iteration 9840 (2.47908 iter/s, 4.84051s/12 iters), loss = 5.24908 +I0410 14:43:38.664731 18606 solver.cpp:237] Train net output #0: loss = 5.24908 (* 1 = 5.24908 loss) +I0410 14:43:38.664744 18606 sgd_solver.cpp:105] Iteration 9840, lr = 0.00142393 +I0410 14:43:43.445374 18606 solver.cpp:218] Iteration 9852 (2.51023 iter/s, 4.78044s/12 iters), loss = 5.26702 +I0410 14:43:43.445410 18606 solver.cpp:237] Train net output #0: loss = 5.26702 (* 1 = 5.26702 loss) +I0410 14:43:43.445417 18606 sgd_solver.cpp:105] Iteration 9852, lr = 0.00142055 +I0410 14:43:48.274632 18606 solver.cpp:218] Iteration 9864 (2.48498 iter/s, 4.82901s/12 iters), loss = 5.28992 +I0410 14:43:48.274682 18606 solver.cpp:237] Train net output #0: loss = 5.28992 (* 1 = 5.28992 loss) +I0410 14:43:48.274691 18606 sgd_solver.cpp:105] Iteration 9864, lr = 0.00141718 +I0410 14:43:53.124430 18606 solver.cpp:218] Iteration 9876 (2.47446 iter/s, 4.84953s/12 iters), loss = 5.27175 +I0410 14:43:53.124487 18606 solver.cpp:237] Train net output #0: loss = 5.27175 (* 1 = 5.27175 loss) +I0410 14:43:53.124500 18606 sgd_solver.cpp:105] Iteration 9876, lr = 0.00141381 +I0410 14:43:57.922662 18606 solver.cpp:218] Iteration 9888 (2.50106 iter/s, 4.79797s/12 iters), loss = 5.27498 +I0410 14:43:57.922772 18606 solver.cpp:237] Train net output #0: loss = 5.27498 (* 1 = 5.27498 loss) +I0410 14:43:57.922783 18606 sgd_solver.cpp:105] Iteration 9888, lr = 0.00141045 +I0410 14:43:59.888773 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9894.caffemodel +I0410 14:44:00.185231 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9894.solverstate +I0410 14:44:00.403820 18606 solver.cpp:330] Iteration 9894, Testing net (#0) +I0410 14:44:00.403851 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:44:00.978271 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:04.873889 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:44:04.873935 18606 solver.cpp:397] Test net output #1: loss = 5.28706 (* 1 = 5.28706 loss) +I0410 14:44:06.680490 18606 solver.cpp:218] Iteration 9900 (1.37028 iter/s, 8.75735s/12 iters), loss = 5.27323 +I0410 14:44:06.680548 18606 solver.cpp:237] Train net output #0: loss = 5.27323 (* 1 = 5.27323 loss) +I0410 14:44:06.680562 18606 sgd_solver.cpp:105] Iteration 9900, lr = 0.00140711 +I0410 14:44:11.586750 18606 solver.cpp:218] Iteration 9912 (2.44599 iter/s, 4.90599s/12 iters), loss = 5.25792 +I0410 14:44:11.586817 18606 solver.cpp:237] Train net output #0: loss = 5.25792 (* 1 = 5.25792 loss) +I0410 14:44:11.586829 18606 sgd_solver.cpp:105] Iteration 9912, lr = 0.00140377 +I0410 14:44:11.685933 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:16.433832 18606 solver.cpp:218] Iteration 9924 (2.47586 iter/s, 4.84681s/12 iters), loss = 5.27072 +I0410 14:44:16.433887 18606 solver.cpp:237] Train net output #0: loss = 5.27072 (* 1 = 5.27072 loss) +I0410 14:44:16.433899 18606 sgd_solver.cpp:105] Iteration 9924, lr = 0.00140043 +I0410 14:44:21.278825 18606 solver.cpp:218] Iteration 9936 (2.47692 iter/s, 4.84473s/12 iters), loss = 5.28874 +I0410 14:44:21.278867 18606 solver.cpp:237] Train net output #0: loss = 5.28874 (* 1 = 5.28874 loss) +I0410 14:44:21.278874 18606 sgd_solver.cpp:105] Iteration 9936, lr = 0.00139711 +I0410 14:44:26.262732 18606 solver.cpp:218] Iteration 9948 (2.40788 iter/s, 4.98365s/12 iters), loss = 5.26094 +I0410 14:44:26.262785 18606 solver.cpp:237] Train net output #0: loss = 5.26094 (* 1 = 5.26094 loss) +I0410 14:44:26.262799 18606 sgd_solver.cpp:105] Iteration 9948, lr = 0.00139379 +I0410 14:44:31.317164 18606 solver.cpp:218] Iteration 9960 (2.37428 iter/s, 5.05416s/12 iters), loss = 5.26921 +I0410 14:44:31.317312 18606 solver.cpp:237] Train net output #0: loss = 5.26921 (* 1 = 5.26921 loss) +I0410 14:44:31.317327 18606 sgd_solver.cpp:105] Iteration 9960, lr = 0.00139048 +I0410 14:44:36.239707 18606 solver.cpp:218] Iteration 9972 (2.43794 iter/s, 4.92218s/12 iters), loss = 5.26029 +I0410 14:44:36.239764 18606 solver.cpp:237] Train net output #0: loss = 5.26029 (* 1 = 5.26029 loss) +I0410 14:44:36.239778 18606 sgd_solver.cpp:105] Iteration 9972, lr = 0.00138718 +I0410 14:44:41.218606 18606 solver.cpp:218] Iteration 9984 (2.41031 iter/s, 4.97862s/12 iters), loss = 5.24684 +I0410 14:44:41.218662 18606 solver.cpp:237] Train net output #0: loss = 5.24684 (* 1 = 5.24684 loss) +I0410 14:44:41.218673 18606 sgd_solver.cpp:105] Iteration 9984, lr = 0.00138389 +I0410 14:44:45.627400 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_9996.caffemodel +I0410 14:44:46.502239 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_9996.solverstate +I0410 14:44:47.488729 18606 solver.cpp:330] Iteration 9996, Testing net (#0) +I0410 14:44:47.488760 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:44:48.053797 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:44:51.998631 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:44:51.998669 18606 solver.cpp:397] Test net output #1: loss = 5.28751 (* 1 = 5.28751 loss) +I0410 14:44:52.079151 18606 solver.cpp:218] Iteration 9996 (1.10497 iter/s, 10.86s/12 iters), loss = 5.27081 +I0410 14:44:52.079193 18606 solver.cpp:237] Train net output #0: loss = 5.27081 (* 1 = 5.27081 loss) +I0410 14:44:52.079203 18606 sgd_solver.cpp:105] Iteration 9996, lr = 0.0013806 +I0410 14:44:56.459944 18606 solver.cpp:218] Iteration 10008 (2.73938 iter/s, 4.38055s/12 iters), loss = 5.24463 +I0410 14:44:56.459995 18606 solver.cpp:237] Train net output #0: loss = 5.24463 (* 1 = 5.24463 loss) +I0410 14:44:56.460009 18606 sgd_solver.cpp:105] Iteration 10008, lr = 0.00137732 +I0410 14:44:58.633816 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:45:01.276156 18606 solver.cpp:218] Iteration 10020 (2.49172 iter/s, 4.81596s/12 iters), loss = 5.26792 +I0410 14:45:01.276206 18606 solver.cpp:237] Train net output #0: loss = 5.26792 (* 1 = 5.26792 loss) +I0410 14:45:01.276219 18606 sgd_solver.cpp:105] Iteration 10020, lr = 0.00137405 +I0410 14:45:06.193828 18606 solver.cpp:218] Iteration 10032 (2.44031 iter/s, 4.91741s/12 iters), loss = 5.27592 +I0410 14:45:06.195443 18606 solver.cpp:237] Train net output #0: loss = 5.27592 (* 1 = 5.27592 loss) +I0410 14:45:06.195457 18606 sgd_solver.cpp:105] Iteration 10032, lr = 0.00137079 +I0410 14:45:11.032318 18606 solver.cpp:218] Iteration 10044 (2.48105 iter/s, 4.83667s/12 iters), loss = 5.28372 +I0410 14:45:11.032361 18606 solver.cpp:237] Train net output #0: loss = 5.28372 (* 1 = 5.28372 loss) +I0410 14:45:11.032371 18606 sgd_solver.cpp:105] Iteration 10044, lr = 0.00136754 +I0410 14:45:15.869455 18606 solver.cpp:218] Iteration 10056 (2.48094 iter/s, 4.83688s/12 iters), loss = 5.27484 +I0410 14:45:15.869508 18606 solver.cpp:237] Train net output #0: loss = 5.27484 (* 1 = 5.27484 loss) +I0410 14:45:15.869519 18606 sgd_solver.cpp:105] Iteration 10056, lr = 0.00136429 +I0410 14:45:20.741991 18606 solver.cpp:218] Iteration 10068 (2.46293 iter/s, 4.87225s/12 iters), loss = 5.27273 +I0410 14:45:20.742038 18606 solver.cpp:237] Train net output #0: loss = 5.27273 (* 1 = 5.27273 loss) +I0410 14:45:20.742046 18606 sgd_solver.cpp:105] Iteration 10068, lr = 0.00136105 +I0410 14:45:25.585355 18606 solver.cpp:218] Iteration 10080 (2.47775 iter/s, 4.84311s/12 iters), loss = 5.26235 +I0410 14:45:25.585398 18606 solver.cpp:237] Train net output #0: loss = 5.26235 (* 1 = 5.26235 loss) +I0410 14:45:25.585407 18606 sgd_solver.cpp:105] Iteration 10080, lr = 0.00135782 +I0410 14:45:30.547355 18606 solver.cpp:218] Iteration 10092 (2.41851 iter/s, 4.96174s/12 iters), loss = 5.27629 +I0410 14:45:30.547401 18606 solver.cpp:237] Train net output #0: loss = 5.27629 (* 1 = 5.27629 loss) +I0410 14:45:30.547410 18606 sgd_solver.cpp:105] Iteration 10092, lr = 0.0013546 +I0410 14:45:32.484161 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10098.caffemodel +I0410 14:45:32.806130 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10098.solverstate +I0410 14:45:33.019099 18606 solver.cpp:330] Iteration 10098, Testing net (#0) +I0410 14:45:33.019120 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:45:33.437436 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:45:37.442986 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:45:37.443125 18606 solver.cpp:397] Test net output #1: loss = 5.28715 (* 1 = 5.28715 loss) +I0410 14:45:39.259793 18606 solver.cpp:218] Iteration 10104 (1.37741 iter/s, 8.71202s/12 iters), loss = 5.27132 +I0410 14:45:39.259850 18606 solver.cpp:237] Train net output #0: loss = 5.27132 (* 1 = 5.27132 loss) +I0410 14:45:39.259863 18606 sgd_solver.cpp:105] Iteration 10104, lr = 0.00135138 +I0410 14:45:43.509893 18610 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:45:44.106019 18606 solver.cpp:218] Iteration 10116 (2.47629 iter/s, 4.84596s/12 iters), loss = 5.25845 +I0410 14:45:44.106072 18606 solver.cpp:237] Train net output #0: loss = 5.25845 (* 1 = 5.25845 loss) +I0410 14:45:44.106084 18606 sgd_solver.cpp:105] Iteration 10116, lr = 0.00134817 +I0410 14:45:48.890290 18606 solver.cpp:218] Iteration 10128 (2.50836 iter/s, 4.78401s/12 iters), loss = 5.27415 +I0410 14:45:48.890333 18606 solver.cpp:237] Train net output #0: loss = 5.27415 (* 1 = 5.27415 loss) +I0410 14:45:48.890342 18606 sgd_solver.cpp:105] Iteration 10128, lr = 0.00134497 +I0410 14:45:53.754304 18606 solver.cpp:218] Iteration 10140 (2.46723 iter/s, 4.86376s/12 iters), loss = 5.28228 +I0410 14:45:53.754348 18606 solver.cpp:237] Train net output #0: loss = 5.28228 (* 1 = 5.28228 loss) +I0410 14:45:53.754359 18606 sgd_solver.cpp:105] Iteration 10140, lr = 0.00134178 +I0410 14:45:58.746632 18606 solver.cpp:218] Iteration 10152 (2.40382 iter/s, 4.99206s/12 iters), loss = 5.27595 +I0410 14:45:58.746686 18606 solver.cpp:237] Train net output #0: loss = 5.27595 (* 1 = 5.27595 loss) +I0410 14:45:58.746698 18606 sgd_solver.cpp:105] Iteration 10152, lr = 0.00133859 +I0410 14:46:03.625676 18606 solver.cpp:218] Iteration 10164 (2.45963 iter/s, 4.87878s/12 iters), loss = 5.26367 +I0410 14:46:03.625733 18606 solver.cpp:237] Train net output #0: loss = 5.26367 (* 1 = 5.26367 loss) +I0410 14:46:03.625746 18606 sgd_solver.cpp:105] Iteration 10164, lr = 0.00133541 +I0410 14:46:08.459496 18606 solver.cpp:218] Iteration 10176 (2.48264 iter/s, 4.83356s/12 iters), loss = 5.27805 +I0410 14:46:08.459594 18606 solver.cpp:237] Train net output #0: loss = 5.27805 (* 1 = 5.27805 loss) +I0410 14:46:08.459604 18606 sgd_solver.cpp:105] Iteration 10176, lr = 0.00133224 +I0410 14:46:13.358700 18606 solver.cpp:218] Iteration 10188 (2.44953 iter/s, 4.89889s/12 iters), loss = 5.27595 +I0410 14:46:13.358736 18606 solver.cpp:237] Train net output #0: loss = 5.27595 (* 1 = 5.27595 loss) +I0410 14:46:13.358743 18606 sgd_solver.cpp:105] Iteration 10188, lr = 0.00132908 +I0410 14:46:17.751695 18606 solver.cpp:447] Snapshotting to binary proto file snapshot_iter_10200.caffemodel +I0410 14:46:18.068476 18606 sgd_solver.cpp:273] Snapshotting solver state to binary proto file snapshot_iter_10200.solverstate +I0410 14:46:18.308171 18606 solver.cpp:310] Iteration 10200, loss = 5.2626 +I0410 14:46:18.308197 18606 solver.cpp:330] Iteration 10200, Testing net (#0) +I0410 14:46:18.308202 18606 net.cpp:676] Ignoring source layer train-data +I0410 14:46:18.648090 18611 data_layer.cpp:73] Restarting data prefetching from start. +I0410 14:46:22.595371 18606 solver.cpp:397] Test net output #0: accuracy = 0.00551471 +I0410 14:46:22.595418 18606 solver.cpp:397] Test net output #1: loss = 5.28649 (* 1 = 5.28649 loss) +I0410 14:46:22.595429 18606 solver.cpp:315] Optimization Done. +I0410 14:46:22.595436 18606 caffe.cpp:259] Optimization Done. diff --git a/cars/architecture-investigations/fc/4-layers/256/conf.csv b/cars/architecture-investigations/fc/4-layers/256/conf.csv new file mode 100644 index 0000000..e1b505f --- /dev/null +++ b/cars/architecture-investigations/fc/4-layers/256/conf.csv @@ -0,0 +1,197 @@ +,AM General Hummer SUV 2000,Acura RL Sedan 2012,Acura TL Sedan 2012,Acura TL Type-S 2008,Acura TSX Sedan 2012,Acura Integra Type R 2001,Acura ZDX Hatchback 2012,Aston Martin V8 Vantage Convertible 2012,Aston Martin V8 Vantage Coupe 2012,Aston Martin Virage Convertible 2012,Aston Martin Virage Coupe 2012,Audi RS 4 Convertible 2008,Audi A5 Coupe 2012,Audi TTS Coupe 2012,Audi R8 Coupe 2012,Audi V8 Sedan 1994,Audi 100 Sedan 1994,Audi 100 Wagon 1994,Audi TT Hatchback 2011,Audi S6 Sedan 2011,Audi S5 Convertible 2012,Audi S5 Coupe 2012,Audi S4 Sedan 2012,Audi S4 Sedan 2007,Audi TT RS Coupe 2012,BMW ActiveHybrid 5 Sedan 2012,BMW 1 Series Convertible 2012,BMW 1 Series Coupe 2012,BMW 3 Series Sedan 2012,BMW 3 Series Wagon 2012,BMW 6 Series Convertible 2007,BMW X5 SUV 2007,BMW X6 SUV 2012,BMW M3 Coupe 2012,BMW M5 Sedan 2010,BMW M6 Convertible 2010,BMW X3 SUV 2012,BMW Z4 Convertible 2012,Bentley Continental Supersports Conv. Convertible 2012,Bentley Arnage Sedan 2009,Bentley Mulsanne Sedan 2011,Bentley Continental GT Coupe 2012,Bentley Continental GT Coupe 2007,Bentley Continental Flying Spur Sedan 2007,Bugatti Veyron 16.4 Convertible 2009,Bugatti Veyron 16.4 Coupe 2009,Buick Regal GS 2012,Buick Rainier SUV 2007,Buick Verano Sedan 2012,Buick Enclave SUV 2012,Cadillac CTS-V Sedan 2012,Cadillac SRX SUV 2012,Cadillac Escalade EXT Crew Cab 2007,Chevrolet Silverado 1500 Hybrid Crew Cab 2012,Chevrolet Corvette Convertible 2012,Chevrolet Corvette ZR1 2012,Chevrolet Corvette Ron Fellows Edition Z06 2007,Chevrolet Traverse SUV 2012,Chevrolet Camaro Convertible 2012,Chevrolet HHR SS 2010,Chevrolet Impala Sedan 2007,Chevrolet Tahoe Hybrid SUV 2012,Chevrolet Sonic Sedan 2012,Chevrolet Express Cargo Van 2007,Chevrolet Avalanche Crew Cab 2012,Chevrolet Cobalt SS 2010,Chevrolet Malibu Hybrid Sedan 2010,Chevrolet TrailBlazer SS 2009,Chevrolet Silverado 2500HD Regular Cab 2012,Chevrolet Silverado 1500 Classic Extended Cab 2007,Chevrolet Express Van 2007,Chevrolet Monte Carlo Coupe 2007,Chevrolet Malibu Sedan 2007,Chevrolet Silverado 1500 Extended Cab 2012,Chevrolet Silverado 1500 Regular Cab 2012,Chrysler Aspen SUV 2009,Chrysler Sebring Convertible 2010,Chrysler Town and Country Minivan 2012,Chrysler 300 SRT-8 2010,Chrysler Crossfire Convertible 2008,Chrysler PT Cruiser Convertible 2008,Daewoo Nubira Wagon 2002,Dodge Caliber Wagon 2012,Dodge Caliber Wagon 2007,Dodge Caravan Minivan 1997,Dodge Ram Pickup 3500 Crew Cab 2010,Dodge Ram Pickup 3500 Quad Cab 2009,Dodge Sprinter Cargo Van 2009,Dodge Journey SUV 2012,Dodge Dakota Crew Cab 2010,Dodge Dakota Club Cab 2007,Dodge Magnum Wagon 2008,Dodge Challenger SRT8 2011,Dodge Durango SUV 2012,Dodge Durango SUV 2007,Dodge Charger Sedan 2012,Dodge Charger SRT-8 2009,Eagle Talon Hatchback 1998,FIAT 500 Abarth 2012,FIAT 500 Convertible 2012,Ferrari FF Coupe 2012,Ferrari California Convertible 2012,Ferrari 458 Italia Convertible 2012,Ferrari 458 Italia Coupe 2012,Fisker Karma Sedan 2012,Ford F-450 Super Duty Crew Cab 2012,Ford Mustang Convertible 2007,Ford Freestar Minivan 2007,Ford Expedition EL SUV 2009,Ford Edge SUV 2012,Ford Ranger SuperCab 2011,Ford GT Coupe 2006,Ford F-150 Regular Cab 2012,Ford F-150 Regular Cab 2007,Ford Focus Sedan 2007,Ford E-Series Wagon Van 2012,Ford Fiesta Sedan 2012,GMC Terrain SUV 2012,GMC Savana Van 2012,GMC Yukon Hybrid SUV 2012,GMC Acadia SUV 2012,GMC Canyon Extended Cab 2012,Geo Metro Convertible 1993,HUMMER H3T Crew Cab 2010,HUMMER H2 SUT Crew Cab 2009,Honda Odyssey Minivan 2012,Honda Odyssey Minivan 2007,Honda Accord Coupe 2012,Honda Accord Sedan 2012,Hyundai Veloster Hatchback 2012,Hyundai Santa Fe SUV 2012,Hyundai Tucson SUV 2012,Hyundai Veracruz SUV 2012,Hyundai Sonata Hybrid Sedan 2012,Hyundai Elantra Sedan 2007,Hyundai Accent Sedan 2012,Hyundai Genesis Sedan 2012,Hyundai Sonata Sedan 2012,Hyundai Elantra Touring Hatchback 2012,Hyundai Azera Sedan 2012,Infiniti G Coupe IPL 2012,Infiniti QX56 SUV 2011,Isuzu Ascender SUV 2008,Jaguar XK XKR 2012,Jeep Patriot SUV 2012,Jeep Wrangler SUV 2012,Jeep Liberty SUV 2012,Jeep Grand Cherokee SUV 2012,Jeep Compass SUV 2012,Lamborghini Reventon Coupe 2008,Lamborghini Aventador Coupe 2012,Lamborghini Gallardo LP 570-4 Superleggera 2012,Lamborghini Diablo Coupe 2001,Land Rover Range Rover SUV 2012,Land Rover LR2 SUV 2012,Lincoln Town Car Sedan 2011,MINI Cooper Roadster Convertible 2012,Maybach Landaulet Convertible 2012,Mazda Tribute SUV 2011,McLaren MP4-12C Coupe 2012,Mercedes-Benz 300-Class Convertible 1993,Mercedes-Benz C-Class Sedan 2012,Mercedes-Benz SL-Class Coupe 2009,Mercedes-Benz E-Class Sedan 2012,Mercedes-Benz S-Class Sedan 2012,Mercedes-Benz Sprinter Van 2012,Mitsubishi Lancer Sedan 2012,Nissan Leaf Hatchback 2012,Nissan NV Passenger Van 2012,Nissan Juke Hatchback 2012,Nissan 240SX Coupe 1998,Plymouth Neon Coupe 1999,Porsche Panamera Sedan 2012,Ram C/V Cargo Van Minivan 2012,Rolls-Royce Phantom Drophead Coupe Convertible 2012,Rolls-Royce Ghost Sedan 2012,Rolls-Royce Phantom Sedan 2012,Scion xD Hatchback 2012,Spyker C8 Convertible 2009,Spyker C8 Coupe 2009,Suzuki Aerio Sedan 2007,Suzuki Kizashi Sedan 2012,Suzuki SX4 Hatchback 2012,Suzuki SX4 Sedan 2012,Tesla Model S Sedan 2012,Toyota Sequoia SUV 2012,Toyota Camry Sedan 2012,Toyota Corolla Sedan 2012,Toyota 4Runner SUV 2012,Volkswagen Golf Hatchback 2012,Volkswagen Golf Hatchback 1991,Volkswagen Beetle Hatchback 2012,Volvo C30 Hatchback 2012,Volvo 240 Sedan 1993,Volvo XC90 SUV 2007,smart fortwo Convertible 2012,Per-class accuracy +AM General Hummer SUV 2000,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura RL Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura TL Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura TL Type-S 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura TSX Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura Integra Type R 2001,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Acura ZDX Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Aston Martin V8 Vantage Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Aston Martin V8 Vantage Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Aston Martin Virage Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Aston Martin Virage Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Audi RS 4 Convertible 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Audi A5 Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Audi TTS Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Audi R8 Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Audi V8 Sedan 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2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +BMW X6 SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +BMW M3 Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +BMW M5 Sedan 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +BMW M6 Convertible 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Continental Supersports Conv. Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Arnage Sedan 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Mulsanne Sedan 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Continental GT Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Continental GT Coupe 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bentley Continental Flying Spur Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bugatti Veyron 16.4 Convertible 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Bugatti Veyron 16.4 Coupe 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Buick Regal GS 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Buick Rainier SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Buick Verano Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Buick Enclave SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Cadillac CTS-V Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Cadillac SRX SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Cadillac Escalade EXT Crew Cab 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Silverado 1500 Hybrid Crew Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Corvette Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Corvette ZR1 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Corvette Ron Fellows Edition Z06 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Traverse SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Camaro Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet HHR SS 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Impala Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Tahoe Hybrid SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Sonic Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Express Cargo Van 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,3,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Avalanche Crew Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Cobalt SS 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Malibu Hybrid Sedan 2010,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet TrailBlazer SS 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Silverado 2500HD Regular Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Silverado 1500 Classic Extended Cab 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Express Van 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Monte Carlo Coupe 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Malibu Sedan 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Silverado 1500 Extended Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Chevrolet Silverado 1500 Regular Cab 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2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Ford E-Series Wagon Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Ford Fiesta Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +GMC Terrain SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +GMC Savana Van 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +GMC Canyon Extended Cab 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Geo Metro Convertible 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2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Infiniti QX56 SUV 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,5,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Isuzu Ascender SUV 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Jaguar XK XKR 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Jeep Patriot SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Jeep Wrangler SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Jeep Liberty SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Jeep Grand Cherokee SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Jeep Compass SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Lamborghini Reventon Coupe 2008,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Lamborghini Aventador Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Lamborghini Gallardo LP 570-4 Superleggera 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Lamborghini Diablo Coupe 2001,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Land Rover Range Rover SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Land Rover LR2 SUV 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Lincoln Town Car Sedan 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +MINI Cooper Roadster Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Maybach Landaulet Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mazda Tribute SUV 2011,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +McLaren MP4-12C Coupe 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,10,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mercedes-Benz 300-Class Convertible 1993,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mercedes-Benz C-Class Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,9,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mercedes-Benz SL-Class Coupe 2009,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mercedes-Benz E-Class Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mercedes-Benz S-Class Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mercedes-Benz Sprinter Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Mitsubishi Lancer Sedan 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Nissan Leaf Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Nissan NV Passenger Van 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Nissan Juke Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,16,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Nissan 240SX Coupe 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1991,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,7,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Volkswagen Beetle Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,11,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Volvo C30 Hatchback 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,6,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Volvo 240 Sedan 1993,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,12,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +Volvo XC90 SUV 2007,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,8,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% +smart fortwo Convertible 2012,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,13,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0.0% diff --git a/cars/architecture-investigations/fc/4-layers/256/deploy.prototxt b/cars/architecture-investigations/fc/4-layers/256/deploy.prototxt new file mode 100644 index 0000000..de5a18b --- /dev/null +++ b/cars/architecture-investigations/fc/4-layers/256/deploy.prototxt @@ -0,0 +1,421 @@ +input: "data" +input_shape { + dim: 1 + dim: 3 + dim: 227 + dim: 227 +} +layer { + name: "conv1" + type: "Convolution" + bottom: "data" + top: "conv1" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu1" + type: "ReLU" + bottom: "conv1" + top: "conv1" +} +layer { + name: "norm1" + type: "LRN" + bottom: "conv1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool1" + type: "Pooling" + bottom: "norm1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv2" + type: "Convolution" + bottom: "pool1" + top: "conv2" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu2" + type: "ReLU" + bottom: "conv2" + top: "conv2" +} +layer { + name: "norm2" + type: "LRN" + bottom: "conv2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool2" + type: "Pooling" + bottom: "norm2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv3" + type: "Convolution" + bottom: "pool2" + top: "conv3" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu3" + type: "ReLU" + bottom: "conv3" + top: "conv3" +} +layer { + name: "conv4" + type: "Convolution" + bottom: "conv3" + top: "conv4" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu4" + type: "ReLU" + bottom: "conv4" + top: "conv4" +} +layer { + name: "conv5" + type: "Convolution" + bottom: "conv4" + top: "conv5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu5" + type: "ReLU" + bottom: "conv5" + top: "conv5" +} +layer { + name: "pool5" + type: "Pooling" + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "fc6" + type: "InnerProduct" + bottom: "pool5" + top: "fc6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu6" + type: "ReLU" + bottom: "fc6" + top: "fc6" +} +layer { + name: "drop6" + type: "Dropout" + bottom: "fc6" + top: "fc6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7" + type: "InnerProduct" + bottom: "fc6" + top: "fc7" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7" + type: "ReLU" + bottom: "fc7" + top: "fc7" +} +layer { + name: "drop7" + type: "Dropout" + bottom: "fc7" + top: "fc7" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7.5" + type: "InnerProduct" + bottom: "fc7" + top: "fc7.5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7.5" + type: "ReLU" + bottom: "fc7.5" + top: "fc7.5" +} +layer { + name: "drop7.5" + type: "Dropout" + bottom: "fc7.5" + top: "fc7.5" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7.6" + type: "InnerProduct" + bottom: "fc7.5" + top: "fc7.6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7.6" + type: "ReLU" + bottom: "fc7.6" + top: "fc7.6" +} +layer { + name: "drop7.6" + type: "Dropout" + bottom: "fc7.6" + top: "fc7.6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc8" + type: "InnerProduct" + bottom: "fc7.6" + top: "fc8" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 196 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "softmax" + type: "Softmax" + bottom: "fc8" + top: "softmax" +} diff --git a/cars/architecture-investigations/fc/4-layers/256/large.png b/cars/architecture-investigations/fc/4-layers/256/large.png new file mode 100644 index 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100644 index 0000000..8fce122 --- /dev/null +++ b/cars/architecture-investigations/fc/4-layers/256/original.prototxt @@ -0,0 +1,468 @@ +name: "AlexNet" +layer { + name: "train-data" + type: "Data" + top: "data" + top: "label" + include { + stage: "train" + } + transform_param { + mirror: true + crop_size: 227 + } + data_param { + batch_size: 128 + } +} +layer { + name: "val-data" + type: "Data" + top: "data" + top: "label" + include { + stage: "val" + } + transform_param { + crop_size: 227 + } + data_param { + batch_size: 32 + } +} +layer { + name: "conv1" + type: "Convolution" + bottom: "data" + top: "conv1" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 96 + kernel_size: 11 + stride: 4 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu1" + type: "ReLU" + bottom: "conv1" + top: "conv1" +} +layer { + name: "norm1" + type: "LRN" + bottom: "conv1" + top: "norm1" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool1" + type: "Pooling" + bottom: "norm1" + top: "pool1" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv2" + type: "Convolution" + bottom: "pool1" + top: "conv2" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 2 + kernel_size: 5 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu2" + type: "ReLU" + bottom: "conv2" + top: "conv2" +} +layer { + name: "norm2" + type: "LRN" + bottom: "conv2" + top: "norm2" + lrn_param { + local_size: 5 + alpha: 9.99999974738e-05 + beta: 0.75 + } +} +layer { + name: "pool2" + type: "Pooling" + bottom: "norm2" + top: "pool2" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "conv3" + type: "Convolution" + bottom: "pool2" + top: "conv3" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "relu3" + type: "ReLU" + bottom: "conv3" + top: "conv3" +} +layer { + name: "conv4" + type: "Convolution" + bottom: "conv3" + top: "conv4" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 384 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu4" + type: "ReLU" + bottom: "conv4" + top: "conv4" +} +layer { + name: "conv5" + type: "Convolution" + bottom: "conv4" + top: "conv5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + convolution_param { + num_output: 256 + pad: 1 + kernel_size: 3 + group: 2 + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu5" + type: "ReLU" + bottom: "conv5" + top: "conv5" +} +layer { + name: "pool5" + type: "Pooling" + bottom: "conv5" + top: "pool5" + pooling_param { + pool: MAX + kernel_size: 3 + stride: 2 + } +} +layer { + name: "fc6" + type: "InnerProduct" + bottom: "pool5" + top: "fc6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu6" + type: "ReLU" + bottom: "fc6" + top: "fc6" +} +layer { + name: "drop6" + type: "Dropout" + bottom: "fc6" + top: "fc6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7" + type: "InnerProduct" + bottom: "fc6" + top: "fc7" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7" + type: "ReLU" + bottom: "fc7" + top: "fc7" +} +layer { + name: "drop7" + type: "Dropout" + bottom: "fc7" + top: "fc7" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7.5" + type: "InnerProduct" + bottom: "fc7" + top: "fc7.5" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7.5" + type: "ReLU" + bottom: "fc7.5" + top: "fc7.5" +} +layer { + name: "drop7.5" + type: "Dropout" + bottom: "fc7.5" + top: "fc7.5" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc7.6" + type: "InnerProduct" + bottom: "fc7.5" + top: "fc7.6" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + num_output: 256 + weight_filler { + type: "gaussian" + std: 0.00499999988824 + } + bias_filler { + type: "constant" + value: 0.10000000149 + } + } +} +layer { + name: "relu7.6" + type: "ReLU" + bottom: "fc7.6" + top: "fc7.6" +} +layer { + name: "drop7.6" + type: "Dropout" + bottom: "fc7.6" + top: "fc7.6" + dropout_param { + dropout_ratio: 0.5 + } +} +layer { + name: "fc8" + type: "InnerProduct" + bottom: "fc7.6" + top: "fc8" + param { + lr_mult: 1.0 + decay_mult: 1.0 + } + param { + lr_mult: 2.0 + decay_mult: 0.0 + } + inner_product_param { + weight_filler { + type: "gaussian" + std: 0.00999999977648 + } + bias_filler { + type: "constant" + value: 0.0 + } + } +} +layer { + name: "accuracy" + type: "Accuracy" + bottom: "fc8" + bottom: "label" + top: "accuracy" + include { + stage: "val" + } +} +layer { + name: "loss" + type: "SoftmaxWithLoss" + bottom: "fc8" + bottom: "label" + top: "loss" + exclude { + stage: "deploy" + } +} +layer { + name: "softmax" + type: "Softmax" + bottom: "fc8" + top: "softmax" + include { + stage: "deploy" + } +} diff --git a/cars/architecture-investigations/fc/4-layers/256/pred.csv b/cars/architecture-investigations/fc/4-layers/256/pred.csv new file mode 100644 index 0000000..1e087d0 --- /dev/null +++ b/cars/architecture-investigations/fc/4-layers/256/pred.csv @@ -0,0 +1,1619 @@ +1 /scratch/Teaching/cars/car_ims/012117.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +2 /scratch/Teaching/cars/car_ims/008738.jpg Ford Mustang Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +3 /scratch/Teaching/cars/car_ims/015794.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +4 /scratch/Teaching/cars/car_ims/004173.jpg Cadillac SRX SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +5 /scratch/Teaching/cars/car_ims/005889.jpg Chevrolet Malibu Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +6 /scratch/Teaching/cars/car_ims/001393.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +7 /scratch/Teaching/cars/car_ims/001507.jpg Audi TT Hatchback 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +8 /scratch/Teaching/cars/car_ims/002597.jpg BMW X5 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +9 /scratch/Teaching/cars/car_ims/000071.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +10 /scratch/Teaching/cars/car_ims/008059.jpg FIAT 500 Abarth 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +11 /scratch/Teaching/cars/car_ims/001659.jpg Audi S5 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +12 /scratch/Teaching/cars/car_ims/004557.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +13 /scratch/Teaching/cars/car_ims/004311.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +14 /scratch/Teaching/cars/car_ims/006145.jpg Chrysler Aspen SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +15 /scratch/Teaching/cars/car_ims/012832.jpg Lincoln Town Car Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +16 /scratch/Teaching/cars/car_ims/006057.jpg Chevrolet Silverado 1500 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +17 /scratch/Teaching/cars/car_ims/005195.jpg Chevrolet Avalanche Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +18 /scratch/Teaching/cars/car_ims/013970.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +19 /scratch/Teaching/cars/car_ims/000910.jpg Audi RS 4 Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +20 /scratch/Teaching/cars/car_ims/008161.jpg FIAT 500 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +21 /scratch/Teaching/cars/car_ims/001019.jpg Audi A5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +22 /scratch/Teaching/cars/car_ims/002588.jpg BMW X5 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +23 /scratch/Teaching/cars/car_ims/004884.jpg Chevrolet Impala Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +24 /scratch/Teaching/cars/car_ims/001972.jpg Audi S4 Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +25 /scratch/Teaching/cars/car_ims/001030.jpg Audi A5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +26 /scratch/Teaching/cars/car_ims/002376.jpg BMW 3 Series Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +27 /scratch/Teaching/cars/car_ims/009940.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +28 /scratch/Teaching/cars/car_ims/012396.jpg Lamborghini Aventador Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +29 /scratch/Teaching/cars/car_ims/006287.jpg Chrysler Town and Country Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +30 /scratch/Teaching/cars/car_ims/006286.jpg Chrysler Town and Country Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +31 /scratch/Teaching/cars/car_ims/001090.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +32 /scratch/Teaching/cars/car_ims/003162.jpg Bentley Continental Supersports Conv. Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +33 /scratch/Teaching/cars/car_ims/009978.jpg GMC Canyon Extended Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +34 /scratch/Teaching/cars/car_ims/013824.jpg Nissan Leaf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +35 /scratch/Teaching/cars/car_ims/003698.jpg Bugatti Veyron 16.4 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +36 /scratch/Teaching/cars/car_ims/007674.jpg Dodge Durango SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +37 /scratch/Teaching/cars/car_ims/012705.jpg Land Rover LR2 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +38 /scratch/Teaching/cars/car_ims/007644.jpg Dodge Durango SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +39 /scratch/Teaching/cars/car_ims/007457.jpg Dodge Dakota Club Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +40 /scratch/Teaching/cars/car_ims/005424.jpg Chevrolet Malibu Hybrid Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +41 /scratch/Teaching/cars/car_ims/003712.jpg Bugatti Veyron 16.4 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +42 /scratch/Teaching/cars/car_ims/007814.jpg Dodge Charger Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +43 /scratch/Teaching/cars/car_ims/015765.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +44 /scratch/Teaching/cars/car_ims/012091.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +45 /scratch/Teaching/cars/car_ims/015546.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +46 /scratch/Teaching/cars/car_ims/012984.jpg Maybach Landaulet Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +47 /scratch/Teaching/cars/car_ims/007744.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +48 /scratch/Teaching/cars/car_ims/001459.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +49 /scratch/Teaching/cars/car_ims/004803.jpg Chevrolet Camaro Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +50 /scratch/Teaching/cars/car_ims/013803.jpg Nissan Leaf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +51 /scratch/Teaching/cars/car_ims/009797.jpg GMC Yukon Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +52 /scratch/Teaching/cars/car_ims/014728.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +53 /scratch/Teaching/cars/car_ims/007389.jpg Dodge Dakota Club Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +54 /scratch/Teaching/cars/car_ims/011599.jpg Infiniti G Coupe IPL 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +55 /scratch/Teaching/cars/car_ims/006305.jpg Chrysler Town and Country Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +56 /scratch/Teaching/cars/car_ims/010055.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +57 /scratch/Teaching/cars/car_ims/014172.jpg Plymouth Neon Coupe 1999 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +58 /scratch/Teaching/cars/car_ims/004832.jpg Chevrolet HHR SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +59 /scratch/Teaching/cars/car_ims/001935.jpg Audi S4 Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +60 /scratch/Teaching/cars/car_ims/014928.jpg Suzuki Kizashi Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +61 /scratch/Teaching/cars/car_ims/008224.jpg Ferrari FF Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +62 /scratch/Teaching/cars/car_ims/005419.jpg Chevrolet Malibu Hybrid Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +63 /scratch/Teaching/cars/car_ims/000617.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +64 /scratch/Teaching/cars/car_ims/004587.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +65 /scratch/Teaching/cars/car_ims/014717.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +66 /scratch/Teaching/cars/car_ims/014933.jpg Suzuki Kizashi Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +67 /scratch/Teaching/cars/car_ims/015065.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +68 /scratch/Teaching/cars/car_ims/002362.jpg BMW 3 Series Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +69 /scratch/Teaching/cars/car_ims/001718.jpg Audi S5 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +70 /scratch/Teaching/cars/car_ims/007698.jpg Dodge Durango SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +71 /scratch/Teaching/cars/car_ims/006352.jpg Chrysler 300 SRT-8 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +72 /scratch/Teaching/cars/car_ims/008545.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +73 /scratch/Teaching/cars/car_ims/000555.jpg Acura ZDX Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +74 /scratch/Teaching/cars/car_ims/010155.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +75 /scratch/Teaching/cars/car_ims/006070.jpg Chevrolet Silverado 1500 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +76 /scratch/Teaching/cars/car_ims/010758.jpg Hyundai Santa Fe SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +77 /scratch/Teaching/cars/car_ims/014203.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +78 /scratch/Teaching/cars/car_ims/006788.jpg Dodge Caliber Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +79 /scratch/Teaching/cars/car_ims/005775.jpg Chevrolet Monte Carlo Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +80 /scratch/Teaching/cars/car_ims/013231.jpg Mercedes-Benz 300-Class Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +81 /scratch/Teaching/cars/car_ims/006212.jpg Chrysler Sebring Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +82 /scratch/Teaching/cars/car_ims/003269.jpg Bentley Mulsanne Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +83 /scratch/Teaching/cars/car_ims/000569.jpg Acura ZDX Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +84 /scratch/Teaching/cars/car_ims/013843.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +85 /scratch/Teaching/cars/car_ims/002828.jpg BMW M5 Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +86 /scratch/Teaching/cars/car_ims/015020.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +87 /scratch/Teaching/cars/car_ims/007528.jpg Dodge Magnum Wagon 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +88 /scratch/Teaching/cars/car_ims/001985.jpg Audi TT RS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +89 /scratch/Teaching/cars/car_ims/002403.jpg BMW 3 Series Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +90 /scratch/Teaching/cars/car_ims/014148.jpg Plymouth Neon Coupe 1999 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +91 /scratch/Teaching/cars/car_ims/004645.jpg Chevrolet Traverse SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +92 /scratch/Teaching/cars/car_ims/007318.jpg Dodge Dakota Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +93 /scratch/Teaching/cars/car_ims/001070.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +94 /scratch/Teaching/cars/car_ims/004489.jpg Chevrolet Corvette ZR1 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +95 /scratch/Teaching/cars/car_ims/013414.jpg Mercedes-Benz E-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +96 /scratch/Teaching/cars/car_ims/008628.jpg Ford F-450 Super Duty Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +97 /scratch/Teaching/cars/car_ims/012921.jpg MINI Cooper Roadster Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +98 /scratch/Teaching/cars/car_ims/005304.jpg Chevrolet Cobalt SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +99 /scratch/Teaching/cars/car_ims/000951.jpg Audi RS 4 Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +100 /scratch/Teaching/cars/car_ims/006517.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +101 /scratch/Teaching/cars/car_ims/007067.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +102 /scratch/Teaching/cars/car_ims/013445.jpg Mercedes-Benz E-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +103 /scratch/Teaching/cars/car_ims/005331.jpg Chevrolet Cobalt SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +104 /scratch/Teaching/cars/car_ims/005569.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +105 /scratch/Teaching/cars/car_ims/011571.jpg Infiniti G Coupe IPL 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +106 /scratch/Teaching/cars/car_ims/015756.jpg Volkswagen Golf Hatchback 1991 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +107 /scratch/Teaching/cars/car_ims/001231.jpg Audi V8 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +108 /scratch/Teaching/cars/car_ims/004435.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +109 /scratch/Teaching/cars/car_ims/006110.jpg Chrysler Aspen SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +110 /scratch/Teaching/cars/car_ims/012879.jpg MINI Cooper Roadster Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +111 /scratch/Teaching/cars/car_ims/015062.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +112 /scratch/Teaching/cars/car_ims/009405.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +113 /scratch/Teaching/cars/car_ims/012882.jpg MINI Cooper Roadster Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +114 /scratch/Teaching/cars/car_ims/010887.jpg Hyundai Tucson SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +115 /scratch/Teaching/cars/car_ims/000441.jpg Acura Integra Type R 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +116 /scratch/Teaching/cars/car_ims/010536.jpg Honda Accord Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +117 /scratch/Teaching/cars/car_ims/013656.jpg Mercedes-Benz Sprinter Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +118 /scratch/Teaching/cars/car_ims/009218.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +119 /scratch/Teaching/cars/car_ims/015198.jpg Tesla Model S Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +120 /scratch/Teaching/cars/car_ims/008421.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +121 /scratch/Teaching/cars/car_ims/013496.jpg Mercedes-Benz S-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +122 /scratch/Teaching/cars/car_ims/009437.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +123 /scratch/Teaching/cars/car_ims/012516.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +124 /scratch/Teaching/cars/car_ims/015679.jpg Volkswagen Golf Hatchback 1991 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +125 /scratch/Teaching/cars/car_ims/002639.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +126 /scratch/Teaching/cars/car_ims/008918.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +127 /scratch/Teaching/cars/car_ims/004135.jpg Cadillac SRX SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +128 /scratch/Teaching/cars/car_ims/008676.jpg Ford Mustang Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +129 /scratch/Teaching/cars/car_ims/014637.jpg Scion xD Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +130 /scratch/Teaching/cars/car_ims/005759.jpg Chevrolet Monte Carlo Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +131 /scratch/Teaching/cars/car_ims/001181.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +132 /scratch/Teaching/cars/car_ims/016126.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +133 /scratch/Teaching/cars/car_ims/016061.jpg Volvo XC90 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +134 /scratch/Teaching/cars/car_ims/004335.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +135 /scratch/Teaching/cars/car_ims/006750.jpg Dodge Caliber Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +136 /scratch/Teaching/cars/car_ims/000446.jpg Acura Integra Type R 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +137 /scratch/Teaching/cars/car_ims/010470.jpg Honda Odyssey Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +138 /scratch/Teaching/cars/car_ims/002896.jpg BMW M6 Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +139 /scratch/Teaching/cars/car_ims/002910.jpg BMW M6 Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +140 /scratch/Teaching/cars/car_ims/014739.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +141 /scratch/Teaching/cars/car_ims/011972.jpg Jeep Wrangler SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +142 /scratch/Teaching/cars/car_ims/015837.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +143 /scratch/Teaching/cars/car_ims/012094.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +144 /scratch/Teaching/cars/car_ims/007379.jpg Dodge Dakota Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +145 /scratch/Teaching/cars/car_ims/012130.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +146 /scratch/Teaching/cars/car_ims/003988.jpg Buick Enclave SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +147 /scratch/Teaching/cars/car_ims/009771.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +148 /scratch/Teaching/cars/car_ims/007198.jpg Dodge Sprinter Cargo Van 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +149 /scratch/Teaching/cars/car_ims/015552.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +150 /scratch/Teaching/cars/car_ims/010126.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +151 /scratch/Teaching/cars/car_ims/006590.jpg Chrysler PT Cruiser Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +152 /scratch/Teaching/cars/car_ims/001275.jpg Audi V8 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +153 /scratch/Teaching/cars/car_ims/006732.jpg Dodge Caliber Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +154 /scratch/Teaching/cars/car_ims/006313.jpg Chrysler Town and Country Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +155 /scratch/Teaching/cars/car_ims/006413.jpg Chrysler 300 SRT-8 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +156 /scratch/Teaching/cars/car_ims/002546.jpg BMW X5 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +157 /scratch/Teaching/cars/car_ims/003794.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +158 /scratch/Teaching/cars/car_ims/004370.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +159 /scratch/Teaching/cars/car_ims/012547.jpg Lamborghini Diablo Coupe 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +160 /scratch/Teaching/cars/car_ims/003093.jpg BMW Z4 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +161 /scratch/Teaching/cars/car_ims/011134.jpg Hyundai Elantra Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +162 /scratch/Teaching/cars/car_ims/000466.jpg Acura Integra Type R 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +163 /scratch/Teaching/cars/car_ims/004251.jpg Cadillac Escalade EXT Crew Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +164 /scratch/Teaching/cars/car_ims/012043.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +165 /scratch/Teaching/cars/car_ims/013956.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +166 /scratch/Teaching/cars/car_ims/011227.jpg Hyundai Genesis Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +167 /scratch/Teaching/cars/car_ims/009636.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +168 /scratch/Teaching/cars/car_ims/001345.jpg Audi 100 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +169 /scratch/Teaching/cars/car_ims/006159.jpg Chrysler Aspen SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +170 /scratch/Teaching/cars/car_ims/014729.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +171 /scratch/Teaching/cars/car_ims/003356.jpg Bentley Continental GT Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +172 /scratch/Teaching/cars/car_ims/000255.jpg Acura TL Type-S 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +173 /scratch/Teaching/cars/car_ims/001575.jpg Audi S6 Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +174 /scratch/Teaching/cars/car_ims/003495.jpg Bentley Continental Flying Spur Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +175 /scratch/Teaching/cars/car_ims/015738.jpg Volkswagen Golf Hatchback 1991 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +176 /scratch/Teaching/cars/car_ims/011241.jpg Hyundai Genesis Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +177 /scratch/Teaching/cars/car_ims/007077.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +178 /scratch/Teaching/cars/car_ims/008495.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +179 /scratch/Teaching/cars/car_ims/010613.jpg Honda Accord Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +180 /scratch/Teaching/cars/car_ims/006821.jpg Dodge Caliber Wagon 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +181 /scratch/Teaching/cars/car_ims/003406.jpg Bentley Continental GT Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +182 /scratch/Teaching/cars/car_ims/000523.jpg Acura ZDX Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +183 /scratch/Teaching/cars/car_ims/010431.jpg Honda Odyssey Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +184 /scratch/Teaching/cars/car_ims/002193.jpg BMW 1 Series Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +185 /scratch/Teaching/cars/car_ims/002106.jpg BMW ActiveHybrid 5 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +186 /scratch/Teaching/cars/car_ims/009326.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +187 /scratch/Teaching/cars/car_ims/004448.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +188 /scratch/Teaching/cars/car_ims/013876.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +189 /scratch/Teaching/cars/car_ims/009358.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +190 /scratch/Teaching/cars/car_ims/014404.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +191 /scratch/Teaching/cars/car_ims/009561.jpg Ford Fiesta Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +192 /scratch/Teaching/cars/car_ims/011623.jpg Infiniti QX56 SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +193 /scratch/Teaching/cars/car_ims/009392.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +194 /scratch/Teaching/cars/car_ims/008462.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +195 /scratch/Teaching/cars/car_ims/005643.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +196 /scratch/Teaching/cars/car_ims/016142.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +197 /scratch/Teaching/cars/car_ims/013939.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +198 /scratch/Teaching/cars/car_ims/010662.jpg Honda Accord Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +199 /scratch/Teaching/cars/car_ims/011023.jpg Hyundai Sonata Hybrid Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +200 /scratch/Teaching/cars/car_ims/005575.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +201 /scratch/Teaching/cars/car_ims/002201.jpg BMW 1 Series Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +202 /scratch/Teaching/cars/car_ims/004506.jpg Chevrolet Corvette ZR1 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +203 /scratch/Teaching/cars/car_ims/010099.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +204 /scratch/Teaching/cars/car_ims/014813.jpg Spyker C8 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +205 /scratch/Teaching/cars/car_ims/005180.jpg Chevrolet Express Cargo Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +206 /scratch/Teaching/cars/car_ims/015822.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +207 /scratch/Teaching/cars/car_ims/008501.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +208 /scratch/Teaching/cars/car_ims/003132.jpg Bentley Continental Supersports Conv. Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +209 /scratch/Teaching/cars/car_ims/004268.jpg Cadillac Escalade EXT Crew Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +210 /scratch/Teaching/cars/car_ims/014799.jpg Spyker C8 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +211 /scratch/Teaching/cars/car_ims/009257.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +212 /scratch/Teaching/cars/car_ims/005514.jpg Chevrolet TrailBlazer SS 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +213 /scratch/Teaching/cars/car_ims/000813.jpg Aston Martin Virage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +214 /scratch/Teaching/cars/car_ims/015343.jpg Toyota Camry Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +215 /scratch/Teaching/cars/car_ims/014452.jpg Rolls-Royce Ghost Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +216 /scratch/Teaching/cars/car_ims/005861.jpg Chevrolet Malibu Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +217 /scratch/Teaching/cars/car_ims/003121.jpg Bentley Continental Supersports Conv. Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +218 /scratch/Teaching/cars/car_ims/003017.jpg BMW X3 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +219 /scratch/Teaching/cars/car_ims/014597.jpg Scion xD Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +220 /scratch/Teaching/cars/car_ims/011717.jpg Isuzu Ascender SUV 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +221 /scratch/Teaching/cars/car_ims/009772.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +222 /scratch/Teaching/cars/car_ims/003355.jpg Bentley Continental GT Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +223 /scratch/Teaching/cars/car_ims/008636.jpg Ford F-450 Super Duty Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +224 /scratch/Teaching/cars/car_ims/016134.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +225 /scratch/Teaching/cars/car_ims/006048.jpg Chevrolet Silverado 1500 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +226 /scratch/Teaching/cars/car_ims/001833.jpg Audi S4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +227 /scratch/Teaching/cars/car_ims/007571.jpg Dodge Challenger SRT8 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +228 /scratch/Teaching/cars/car_ims/001141.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +229 /scratch/Teaching/cars/car_ims/006985.jpg Dodge Ram Pickup 3500 Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +230 /scratch/Teaching/cars/car_ims/001795.jpg Audi S5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +231 /scratch/Teaching/cars/car_ims/013009.jpg Mazda Tribute SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +232 /scratch/Teaching/cars/car_ims/001230.jpg Audi V8 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +233 /scratch/Teaching/cars/car_ims/014300.jpg Ram C/V Cargo Van Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +234 /scratch/Teaching/cars/car_ims/014169.jpg Plymouth Neon Coupe 1999 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +235 /scratch/Teaching/cars/car_ims/013258.jpg Mercedes-Benz C-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +236 /scratch/Teaching/cars/car_ims/015661.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +237 /scratch/Teaching/cars/car_ims/011790.jpg Jaguar XK XKR 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +238 /scratch/Teaching/cars/car_ims/007625.jpg Dodge Durango SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +239 /scratch/Teaching/cars/car_ims/000226.jpg Acura TL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +240 /scratch/Teaching/cars/car_ims/011515.jpg Hyundai Azera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +241 /scratch/Teaching/cars/car_ims/002699.jpg BMW M3 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +242 /scratch/Teaching/cars/car_ims/012239.jpg Jeep Compass SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +243 /scratch/Teaching/cars/car_ims/010522.jpg Honda Accord Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +244 /scratch/Teaching/cars/car_ims/007178.jpg Dodge Sprinter Cargo Van 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +245 /scratch/Teaching/cars/car_ims/016121.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +246 /scratch/Teaching/cars/car_ims/014422.jpg Rolls-Royce Ghost Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +247 /scratch/Teaching/cars/car_ims/005261.jpg Chevrolet Avalanche Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +248 /scratch/Teaching/cars/car_ims/000853.jpg Aston Martin Virage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +249 /scratch/Teaching/cars/car_ims/001391.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +250 /scratch/Teaching/cars/car_ims/009933.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +251 /scratch/Teaching/cars/car_ims/015495.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +252 /scratch/Teaching/cars/car_ims/002817.jpg BMW M5 Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +253 /scratch/Teaching/cars/car_ims/012192.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +254 /scratch/Teaching/cars/car_ims/014214.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +255 /scratch/Teaching/cars/car_ims/008646.jpg Ford F-450 Super Duty Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +256 /scratch/Teaching/cars/car_ims/012906.jpg MINI Cooper Roadster Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +257 /scratch/Teaching/cars/car_ims/009128.jpg Ford GT Coupe 2006 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +258 /scratch/Teaching/cars/car_ims/007474.jpg Dodge Magnum Wagon 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +259 /scratch/Teaching/cars/car_ims/014815.jpg Spyker C8 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +260 /scratch/Teaching/cars/car_ims/011980.jpg Jeep Wrangler SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +261 /scratch/Teaching/cars/car_ims/003373.jpg Bentley Continental GT Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +262 /scratch/Teaching/cars/car_ims/006316.jpg Chrysler Town and Country Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +263 /scratch/Teaching/cars/car_ims/014191.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +264 /scratch/Teaching/cars/car_ims/015602.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +265 /scratch/Teaching/cars/car_ims/009702.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +266 /scratch/Teaching/cars/car_ims/007788.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +267 /scratch/Teaching/cars/car_ims/011684.jpg Isuzu Ascender SUV 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +268 /scratch/Teaching/cars/car_ims/014740.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +269 /scratch/Teaching/cars/car_ims/003392.jpg Bentley Continental GT Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +270 /scratch/Teaching/cars/car_ims/002205.jpg BMW 1 Series Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +271 /scratch/Teaching/cars/car_ims/012049.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +272 /scratch/Teaching/cars/car_ims/008724.jpg Ford Mustang Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +273 /scratch/Teaching/cars/car_ims/008524.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +274 /scratch/Teaching/cars/car_ims/015516.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +275 /scratch/Teaching/cars/car_ims/004373.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +276 /scratch/Teaching/cars/car_ims/008948.jpg Ford Edge SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +277 /scratch/Teaching/cars/car_ims/011319.jpg Hyundai Sonata Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +278 /scratch/Teaching/cars/car_ims/016185.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +279 /scratch/Teaching/cars/car_ims/009506.jpg Ford E-Series Wagon Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +280 /scratch/Teaching/cars/car_ims/010110.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +281 /scratch/Teaching/cars/car_ims/015510.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +282 /scratch/Teaching/cars/car_ims/008054.jpg Eagle Talon Hatchback 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +283 /scratch/Teaching/cars/car_ims/005535.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +284 /scratch/Teaching/cars/car_ims/009341.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +285 /scratch/Teaching/cars/car_ims/014486.jpg Rolls-Royce Ghost Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +286 /scratch/Teaching/cars/car_ims/007525.jpg Dodge Magnum Wagon 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +287 /scratch/Teaching/cars/car_ims/004555.jpg Chevrolet Corvette ZR1 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +288 /scratch/Teaching/cars/car_ims/012913.jpg MINI Cooper Roadster Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +289 /scratch/Teaching/cars/car_ims/009843.jpg GMC Yukon Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +290 /scratch/Teaching/cars/car_ims/008907.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +291 /scratch/Teaching/cars/car_ims/001105.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +292 /scratch/Teaching/cars/car_ims/013839.jpg Nissan Leaf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +293 /scratch/Teaching/cars/car_ims/005266.jpg Chevrolet Avalanche Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +294 /scratch/Teaching/cars/car_ims/007367.jpg Dodge Dakota Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +295 /scratch/Teaching/cars/car_ims/011359.jpg Hyundai Sonata Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +296 /scratch/Teaching/cars/car_ims/014464.jpg Rolls-Royce Ghost Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +297 /scratch/Teaching/cars/car_ims/006729.jpg Dodge Caliber Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +298 /scratch/Teaching/cars/car_ims/006580.jpg Chrysler PT Cruiser Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +299 /scratch/Teaching/cars/car_ims/006265.jpg Chrysler Sebring Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +300 /scratch/Teaching/cars/car_ims/015297.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +301 /scratch/Teaching/cars/car_ims/011484.jpg Hyundai Azera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +302 /scratch/Teaching/cars/car_ims/003613.jpg Bugatti Veyron 16.4 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +303 /scratch/Teaching/cars/car_ims/002787.jpg BMW M3 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +304 /scratch/Teaching/cars/car_ims/000912.jpg Audi RS 4 Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +305 /scratch/Teaching/cars/car_ims/013209.jpg Mercedes-Benz 300-Class Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +306 /scratch/Teaching/cars/car_ims/006547.jpg Chrysler PT Cruiser Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +307 /scratch/Teaching/cars/car_ims/002290.jpg BMW 3 Series Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +308 /scratch/Teaching/cars/car_ims/013562.jpg Mercedes-Benz S-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +309 /scratch/Teaching/cars/car_ims/016027.jpg Volvo XC90 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +310 /scratch/Teaching/cars/car_ims/008859.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +311 /scratch/Teaching/cars/car_ims/003480.jpg Bentley Continental GT Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +312 /scratch/Teaching/cars/car_ims/005221.jpg Chevrolet Avalanche Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +313 /scratch/Teaching/cars/car_ims/001094.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +314 /scratch/Teaching/cars/car_ims/005591.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +315 /scratch/Teaching/cars/car_ims/013904.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +316 /scratch/Teaching/cars/car_ims/006434.jpg Chrysler 300 SRT-8 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +317 /scratch/Teaching/cars/car_ims/003946.jpg Buick Verano Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +318 /scratch/Teaching/cars/car_ims/005945.jpg Chevrolet Silverado 1500 Extended Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +319 /scratch/Teaching/cars/car_ims/006819.jpg Dodge Caliber Wagon 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +320 /scratch/Teaching/cars/car_ims/010120.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +321 /scratch/Teaching/cars/car_ims/004932.jpg Chevrolet Impala Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +322 /scratch/Teaching/cars/car_ims/000277.jpg Acura TL Type-S 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +323 /scratch/Teaching/cars/car_ims/007678.jpg Dodge Durango SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +324 /scratch/Teaching/cars/car_ims/008349.jpg Ferrari 458 Italia Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +325 /scratch/Teaching/cars/car_ims/003694.jpg Bugatti Veyron 16.4 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +326 /scratch/Teaching/cars/car_ims/010035.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +327 /scratch/Teaching/cars/car_ims/015965.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +328 /scratch/Teaching/cars/car_ims/002291.jpg BMW 3 Series Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +329 /scratch/Teaching/cars/car_ims/014383.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +330 /scratch/Teaching/cars/car_ims/001160.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +331 /scratch/Teaching/cars/car_ims/000145.jpg Acura RL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +332 /scratch/Teaching/cars/car_ims/012308.jpg Lamborghini Reventon Coupe 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +333 /scratch/Teaching/cars/car_ims/012830.jpg Lincoln Town Car Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +334 /scratch/Teaching/cars/car_ims/014310.jpg Ram C/V Cargo Van Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +335 /scratch/Teaching/cars/car_ims/008263.jpg Ferrari California Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +336 /scratch/Teaching/cars/car_ims/005342.jpg Chevrolet Cobalt SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +337 /scratch/Teaching/cars/car_ims/008726.jpg Ford Mustang Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +338 /scratch/Teaching/cars/car_ims/008665.jpg Ford F-450 Super Duty Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +339 /scratch/Teaching/cars/car_ims/002664.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +340 /scratch/Teaching/cars/car_ims/000024.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +341 /scratch/Teaching/cars/car_ims/015973.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +342 /scratch/Teaching/cars/car_ims/014127.jpg Plymouth Neon Coupe 1999 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +343 /scratch/Teaching/cars/car_ims/007476.jpg Dodge Magnum Wagon 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +344 /scratch/Teaching/cars/car_ims/015381.jpg Toyota Camry Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +345 /scratch/Teaching/cars/car_ims/007769.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +346 /scratch/Teaching/cars/car_ims/009388.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +347 /scratch/Teaching/cars/car_ims/014738.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +348 /scratch/Teaching/cars/car_ims/006310.jpg Chrysler Town and Country Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +349 /scratch/Teaching/cars/car_ims/016167.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +350 /scratch/Teaching/cars/car_ims/015279.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +351 /scratch/Teaching/cars/car_ims/015944.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +352 /scratch/Teaching/cars/car_ims/015578.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +353 /scratch/Teaching/cars/car_ims/009330.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +354 /scratch/Teaching/cars/car_ims/003812.jpg Buick Rainier SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +355 /scratch/Teaching/cars/car_ims/003823.jpg Buick Rainier SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +356 /scratch/Teaching/cars/car_ims/003564.jpg Bentley Continental Flying Spur Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +357 /scratch/Teaching/cars/car_ims/012659.jpg Land Rover Range Rover SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +358 /scratch/Teaching/cars/car_ims/015287.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +359 /scratch/Teaching/cars/car_ims/009173.jpg Ford GT Coupe 2006 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +360 /scratch/Teaching/cars/car_ims/013266.jpg Mercedes-Benz C-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +361 /scratch/Teaching/cars/car_ims/004553.jpg Chevrolet Corvette ZR1 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +362 /scratch/Teaching/cars/car_ims/009374.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +363 /scratch/Teaching/cars/car_ims/015096.jpg Suzuki SX4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +364 /scratch/Teaching/cars/car_ims/008828.jpg Ford Freestar Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +365 /scratch/Teaching/cars/car_ims/013404.jpg Mercedes-Benz SL-Class Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +366 /scratch/Teaching/cars/car_ims/010800.jpg Hyundai Santa Fe SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +367 /scratch/Teaching/cars/car_ims/014414.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +368 /scratch/Teaching/cars/car_ims/002266.jpg BMW 1 Series Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +369 /scratch/Teaching/cars/car_ims/009733.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +370 /scratch/Teaching/cars/car_ims/003846.jpg Buick Rainier SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +371 /scratch/Teaching/cars/car_ims/014244.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +372 /scratch/Teaching/cars/car_ims/005903.jpg Chevrolet Malibu Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +373 /scratch/Teaching/cars/car_ims/000029.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +374 /scratch/Teaching/cars/car_ims/014423.jpg Rolls-Royce Ghost Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +375 /scratch/Teaching/cars/car_ims/011224.jpg Hyundai Genesis Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +376 /scratch/Teaching/cars/car_ims/001451.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +377 /scratch/Teaching/cars/car_ims/011438.jpg Hyundai Elantra Touring Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +378 /scratch/Teaching/cars/car_ims/001650.jpg Audi S5 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +379 /scratch/Teaching/cars/car_ims/007592.jpg Dodge Challenger SRT8 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +380 /scratch/Teaching/cars/car_ims/002115.jpg BMW ActiveHybrid 5 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +381 /scratch/Teaching/cars/car_ims/011727.jpg Isuzu Ascender SUV 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +382 /scratch/Teaching/cars/car_ims/013469.jpg Mercedes-Benz E-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +383 /scratch/Teaching/cars/car_ims/001052.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +384 /scratch/Teaching/cars/car_ims/009676.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +385 /scratch/Teaching/cars/car_ims/011540.jpg Hyundai Azera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +386 /scratch/Teaching/cars/car_ims/004615.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +387 /scratch/Teaching/cars/car_ims/009898.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +388 /scratch/Teaching/cars/car_ims/001026.jpg Audi A5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +389 /scratch/Teaching/cars/car_ims/012162.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +390 /scratch/Teaching/cars/car_ims/011125.jpg Hyundai Elantra Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +391 /scratch/Teaching/cars/car_ims/015324.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +392 /scratch/Teaching/cars/car_ims/004953.jpg Chevrolet Impala Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +393 /scratch/Teaching/cars/car_ims/011876.jpg Jeep Patriot SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +394 /scratch/Teaching/cars/car_ims/007754.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +395 /scratch/Teaching/cars/car_ims/008589.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +396 /scratch/Teaching/cars/car_ims/008551.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +397 /scratch/Teaching/cars/car_ims/010555.jpg Honda Accord Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +398 /scratch/Teaching/cars/car_ims/009647.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +399 /scratch/Teaching/cars/car_ims/012971.jpg Maybach Landaulet Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +400 /scratch/Teaching/cars/car_ims/013113.jpg McLaren MP4-12C Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +401 /scratch/Teaching/cars/car_ims/006956.jpg Dodge Caravan Minivan 1997 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +402 /scratch/Teaching/cars/car_ims/010404.jpg Honda Odyssey Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +403 /scratch/Teaching/cars/car_ims/013135.jpg McLaren MP4-12C Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +404 /scratch/Teaching/cars/car_ims/011991.jpg Jeep Wrangler SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +405 /scratch/Teaching/cars/car_ims/002250.jpg BMW 1 Series Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +406 /scratch/Teaching/cars/car_ims/013497.jpg Mercedes-Benz S-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +407 /scratch/Teaching/cars/car_ims/011077.jpg Hyundai Elantra Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +408 /scratch/Teaching/cars/car_ims/015949.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +409 /scratch/Teaching/cars/car_ims/003900.jpg Buick Verano Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +410 /scratch/Teaching/cars/car_ims/009294.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +411 /scratch/Teaching/cars/car_ims/013363.jpg Mercedes-Benz SL-Class Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +412 /scratch/Teaching/cars/car_ims/005909.jpg Chevrolet Malibu Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +413 /scratch/Teaching/cars/car_ims/012223.jpg Jeep Compass SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +414 /scratch/Teaching/cars/car_ims/001412.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +415 /scratch/Teaching/cars/car_ims/012399.jpg Lamborghini Aventador Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +416 /scratch/Teaching/cars/car_ims/007952.jpg Dodge Charger SRT-8 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +417 /scratch/Teaching/cars/car_ims/009266.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +418 /scratch/Teaching/cars/car_ims/009440.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +419 /scratch/Teaching/cars/car_ims/013751.jpg Mitsubishi Lancer Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +420 /scratch/Teaching/cars/car_ims/013403.jpg Mercedes-Benz SL-Class Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +421 /scratch/Teaching/cars/car_ims/005810.jpg Chevrolet Monte Carlo Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +422 /scratch/Teaching/cars/car_ims/000698.jpg Aston Martin V8 Vantage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +423 /scratch/Teaching/cars/car_ims/002327.jpg BMW 3 Series Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +424 /scratch/Teaching/cars/car_ims/005186.jpg Chevrolet Express Cargo Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +425 /scratch/Teaching/cars/car_ims/002812.jpg BMW M5 Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +426 /scratch/Teaching/cars/car_ims/014385.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +427 /scratch/Teaching/cars/car_ims/009864.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +428 /scratch/Teaching/cars/car_ims/005652.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +429 /scratch/Teaching/cars/car_ims/009984.jpg GMC Canyon Extended Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +430 /scratch/Teaching/cars/car_ims/014469.jpg Rolls-Royce Ghost Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +431 /scratch/Teaching/cars/car_ims/005406.jpg Chevrolet Malibu Hybrid Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +432 /scratch/Teaching/cars/car_ims/003969.jpg Buick Enclave SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +433 /scratch/Teaching/cars/car_ims/012313.jpg Lamborghini Reventon Coupe 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +434 /scratch/Teaching/cars/car_ims/014768.jpg Spyker C8 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +435 /scratch/Teaching/cars/car_ims/002802.jpg BMW M5 Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +436 /scratch/Teaching/cars/car_ims/013139.jpg McLaren MP4-12C Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +437 /scratch/Teaching/cars/car_ims/004653.jpg Chevrolet Traverse SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +438 /scratch/Teaching/cars/car_ims/004806.jpg Chevrolet Camaro Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +439 /scratch/Teaching/cars/car_ims/007292.jpg Dodge Journey SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +440 /scratch/Teaching/cars/car_ims/003526.jpg Bentley Continental Flying Spur Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +441 /scratch/Teaching/cars/car_ims/012011.jpg Jeep Wrangler SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +442 /scratch/Teaching/cars/car_ims/012291.jpg Lamborghini Reventon Coupe 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +443 /scratch/Teaching/cars/car_ims/013933.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +444 /scratch/Teaching/cars/car_ims/007158.jpg Dodge Sprinter Cargo Van 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +445 /scratch/Teaching/cars/car_ims/010652.jpg Honda Accord Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +446 /scratch/Teaching/cars/car_ims/000416.jpg Acura Integra Type R 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +447 /scratch/Teaching/cars/car_ims/014945.jpg Suzuki Kizashi Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +448 /scratch/Teaching/cars/car_ims/005530.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +449 /scratch/Teaching/cars/car_ims/001845.jpg Audi S4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +450 /scratch/Teaching/cars/car_ims/004226.jpg Cadillac Escalade EXT Crew Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +451 /scratch/Teaching/cars/car_ims/002516.jpg BMW 6 Series Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +452 /scratch/Teaching/cars/car_ims/011648.jpg Infiniti QX56 SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +453 /scratch/Teaching/cars/car_ims/005093.jpg Chevrolet Sonic Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +454 /scratch/Teaching/cars/car_ims/008321.jpg Ferrari California Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +455 /scratch/Teaching/cars/car_ims/014458.jpg Rolls-Royce Ghost Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +456 /scratch/Teaching/cars/car_ims/011027.jpg Hyundai Sonata Hybrid Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +457 /scratch/Teaching/cars/car_ims/010038.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +458 /scratch/Teaching/cars/car_ims/009238.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +459 /scratch/Teaching/cars/car_ims/002093.jpg BMW ActiveHybrid 5 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +460 /scratch/Teaching/cars/car_ims/007336.jpg Dodge Dakota Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +461 /scratch/Teaching/cars/car_ims/011947.jpg Jeep Wrangler SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +462 /scratch/Teaching/cars/car_ims/003886.jpg Buick Rainier SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +463 /scratch/Teaching/cars/car_ims/013212.jpg Mercedes-Benz 300-Class Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +464 /scratch/Teaching/cars/car_ims/006447.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +465 /scratch/Teaching/cars/car_ims/014069.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +466 /scratch/Teaching/cars/car_ims/001355.jpg Audi 100 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +467 /scratch/Teaching/cars/car_ims/012077.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +468 /scratch/Teaching/cars/car_ims/005632.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +469 /scratch/Teaching/cars/car_ims/000453.jpg Acura Integra Type R 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +470 /scratch/Teaching/cars/car_ims/015438.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +471 /scratch/Teaching/cars/car_ims/011934.jpg Jeep Patriot SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +472 /scratch/Teaching/cars/car_ims/007109.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +473 /scratch/Teaching/cars/car_ims/001523.jpg Audi TT Hatchback 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +474 /scratch/Teaching/cars/car_ims/012994.jpg Mazda Tribute SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +475 /scratch/Teaching/cars/car_ims/005420.jpg Chevrolet Malibu Hybrid Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +476 /scratch/Teaching/cars/car_ims/003607.jpg Bugatti Veyron 16.4 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +477 /scratch/Teaching/cars/car_ims/014653.jpg Scion xD Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +478 /scratch/Teaching/cars/car_ims/002912.jpg BMW M6 Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +479 /scratch/Teaching/cars/car_ims/011037.jpg Hyundai Sonata Hybrid Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +480 /scratch/Teaching/cars/car_ims/013104.jpg McLaren MP4-12C Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +481 /scratch/Teaching/cars/car_ims/003769.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +482 /scratch/Teaching/cars/car_ims/006031.jpg Chevrolet Silverado 1500 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +483 /scratch/Teaching/cars/car_ims/002655.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +484 /scratch/Teaching/cars/car_ims/014170.jpg Plymouth Neon Coupe 1999 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +485 /scratch/Teaching/cars/car_ims/006724.jpg Dodge Caliber Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +486 /scratch/Teaching/cars/car_ims/002363.jpg BMW 3 Series Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +487 /scratch/Teaching/cars/car_ims/000128.jpg Acura RL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +488 /scratch/Teaching/cars/car_ims/000984.jpg Audi A5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +489 /scratch/Teaching/cars/car_ims/007998.jpg Eagle Talon Hatchback 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +490 /scratch/Teaching/cars/car_ims/013245.jpg Mercedes-Benz C-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +491 /scratch/Teaching/cars/car_ims/009214.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +492 /scratch/Teaching/cars/car_ims/013574.jpg Mercedes-Benz S-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +493 /scratch/Teaching/cars/car_ims/015307.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +494 /scratch/Teaching/cars/car_ims/015848.jpg Volvo C30 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +495 /scratch/Teaching/cars/car_ims/010136.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +496 /scratch/Teaching/cars/car_ims/003459.jpg Bentley Continental GT Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +497 /scratch/Teaching/cars/car_ims/015818.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +498 /scratch/Teaching/cars/car_ims/007766.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +499 /scratch/Teaching/cars/car_ims/003391.jpg Bentley Continental GT Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +500 /scratch/Teaching/cars/car_ims/007805.jpg Dodge Charger Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +501 /scratch/Teaching/cars/car_ims/002965.jpg BMW X3 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +502 /scratch/Teaching/cars/car_ims/007262.jpg Dodge Journey SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +503 /scratch/Teaching/cars/car_ims/005585.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +504 /scratch/Teaching/cars/car_ims/015036.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +505 /scratch/Teaching/cars/car_ims/000892.jpg Audi RS 4 Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +506 /scratch/Teaching/cars/car_ims/002195.jpg BMW 1 Series Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +507 /scratch/Teaching/cars/car_ims/000546.jpg Acura ZDX Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +508 /scratch/Teaching/cars/car_ims/001117.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +509 /scratch/Teaching/cars/car_ims/014807.jpg Spyker C8 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +510 /scratch/Teaching/cars/car_ims/012191.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +511 /scratch/Teaching/cars/car_ims/007101.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +512 /scratch/Teaching/cars/car_ims/011872.jpg Jeep Patriot SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +513 /scratch/Teaching/cars/car_ims/015234.jpg Tesla Model S Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +514 /scratch/Teaching/cars/car_ims/014883.jpg Suzuki Aerio Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +515 /scratch/Teaching/cars/car_ims/009194.jpg Ford GT Coupe 2006 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +516 /scratch/Teaching/cars/car_ims/016080.jpg Volvo XC90 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +517 /scratch/Teaching/cars/car_ims/008820.jpg Ford Freestar Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +518 /scratch/Teaching/cars/car_ims/008045.jpg Eagle Talon Hatchback 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +519 /scratch/Teaching/cars/car_ims/003819.jpg Buick Rainier SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +520 /scratch/Teaching/cars/car_ims/001680.jpg Audi S5 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +521 /scratch/Teaching/cars/car_ims/012267.jpg Jeep Compass SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +522 /scratch/Teaching/cars/car_ims/008598.jpg Ford F-450 Super Duty Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +523 /scratch/Teaching/cars/car_ims/000229.jpg Acura TL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +524 /scratch/Teaching/cars/car_ims/012148.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +525 /scratch/Teaching/cars/car_ims/000342.jpg Acura TSX Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +526 /scratch/Teaching/cars/car_ims/001909.jpg Audi S4 Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +527 /scratch/Teaching/cars/car_ims/012118.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +528 /scratch/Teaching/cars/car_ims/007485.jpg Dodge Magnum Wagon 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +529 /scratch/Teaching/cars/car_ims/009914.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +530 /scratch/Teaching/cars/car_ims/015487.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +531 /scratch/Teaching/cars/car_ims/015946.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +532 /scratch/Teaching/cars/car_ims/008766.jpg Ford Freestar Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +533 /scratch/Teaching/cars/car_ims/012625.jpg Land Rover Range Rover SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +534 /scratch/Teaching/cars/car_ims/013688.jpg Mitsubishi Lancer Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +535 /scratch/Teaching/cars/car_ims/013807.jpg Nissan Leaf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +536 /scratch/Teaching/cars/car_ims/013924.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +537 /scratch/Teaching/cars/car_ims/008198.jpg Ferrari FF Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +538 /scratch/Teaching/cars/car_ims/006493.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +539 /scratch/Teaching/cars/car_ims/003322.jpg Bentley Mulsanne Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +540 /scratch/Teaching/cars/car_ims/015298.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +541 /scratch/Teaching/cars/car_ims/004771.jpg Chevrolet Camaro Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +542 /scratch/Teaching/cars/car_ims/011062.jpg Hyundai Sonata Hybrid Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +543 /scratch/Teaching/cars/car_ims/012742.jpg Land Rover LR2 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +544 /scratch/Teaching/cars/car_ims/015518.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +545 /scratch/Teaching/cars/car_ims/013472.jpg Mercedes-Benz E-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +546 /scratch/Teaching/cars/car_ims/003839.jpg Buick Rainier SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +547 /scratch/Teaching/cars/car_ims/007108.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +548 /scratch/Teaching/cars/car_ims/007273.jpg Dodge Journey SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +549 /scratch/Teaching/cars/car_ims/004666.jpg Chevrolet Traverse SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +550 /scratch/Teaching/cars/car_ims/010722.jpg Hyundai Veloster Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +551 /scratch/Teaching/cars/car_ims/000919.jpg Audi RS 4 Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +552 /scratch/Teaching/cars/car_ims/003108.jpg BMW Z4 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +553 /scratch/Teaching/cars/car_ims/006228.jpg Chrysler Sebring Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +554 /scratch/Teaching/cars/car_ims/015713.jpg Volkswagen Golf Hatchback 1991 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +555 /scratch/Teaching/cars/car_ims/003552.jpg Bentley Continental Flying Spur Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +556 /scratch/Teaching/cars/car_ims/005717.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +557 /scratch/Teaching/cars/car_ims/009534.jpg Ford E-Series Wagon Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +558 /scratch/Teaching/cars/car_ims/003906.jpg Buick Verano Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +559 /scratch/Teaching/cars/car_ims/015003.jpg Suzuki Kizashi Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +560 /scratch/Teaching/cars/car_ims/002850.jpg BMW M5 Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +561 /scratch/Teaching/cars/car_ims/003100.jpg BMW Z4 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +562 /scratch/Teaching/cars/car_ims/014344.jpg Ram C/V Cargo Van Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +563 /scratch/Teaching/cars/car_ims/004836.jpg Chevrolet HHR SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +564 /scratch/Teaching/cars/car_ims/016180.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +565 /scratch/Teaching/cars/car_ims/009217.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +566 /scratch/Teaching/cars/car_ims/008334.jpg Ferrari California Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +567 /scratch/Teaching/cars/car_ims/015474.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +568 /scratch/Teaching/cars/car_ims/016106.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +569 /scratch/Teaching/cars/car_ims/004993.jpg Chevrolet Tahoe Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +570 /scratch/Teaching/cars/car_ims/000765.jpg Aston Martin Virage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +571 /scratch/Teaching/cars/car_ims/009609.jpg Ford Fiesta Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +572 /scratch/Teaching/cars/car_ims/006166.jpg Chrysler Aspen SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +573 /scratch/Teaching/cars/car_ims/009438.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +574 /scratch/Teaching/cars/car_ims/008504.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +575 /scratch/Teaching/cars/car_ims/002457.jpg BMW 6 Series Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +576 /scratch/Teaching/cars/car_ims/013755.jpg Mitsubishi Lancer Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +577 /scratch/Teaching/cars/car_ims/001706.jpg Audi S5 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +578 /scratch/Teaching/cars/car_ims/000395.jpg Acura TSX Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +579 /scratch/Teaching/cars/car_ims/014349.jpg Ram C/V Cargo Van Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +580 /scratch/Teaching/cars/car_ims/004627.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +581 /scratch/Teaching/cars/car_ims/008247.jpg Ferrari FF Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +582 /scratch/Teaching/cars/car_ims/013470.jpg Mercedes-Benz E-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +583 /scratch/Teaching/cars/car_ims/015022.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +584 /scratch/Teaching/cars/car_ims/008559.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +585 /scratch/Teaching/cars/car_ims/003568.jpg Bentley Continental Flying Spur Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +586 /scratch/Teaching/cars/car_ims/002865.jpg BMW M5 Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +587 /scratch/Teaching/cars/car_ims/005797.jpg Chevrolet Monte Carlo Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +588 /scratch/Teaching/cars/car_ims/015378.jpg Toyota Camry Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +589 /scratch/Teaching/cars/car_ims/004432.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +590 /scratch/Teaching/cars/car_ims/001529.jpg Audi TT Hatchback 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +591 /scratch/Teaching/cars/car_ims/008896.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +592 /scratch/Teaching/cars/car_ims/014448.jpg Rolls-Royce Ghost Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +593 /scratch/Teaching/cars/car_ims/004929.jpg Chevrolet Impala Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +594 /scratch/Teaching/cars/car_ims/005217.jpg Chevrolet Avalanche Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +595 /scratch/Teaching/cars/car_ims/015873.jpg Volvo C30 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +596 /scratch/Teaching/cars/car_ims/000758.jpg Aston Martin Virage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +597 /scratch/Teaching/cars/car_ims/002913.jpg BMW M6 Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +598 /scratch/Teaching/cars/car_ims/012741.jpg Land Rover LR2 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +599 /scratch/Teaching/cars/car_ims/002523.jpg BMW 6 Series Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +600 /scratch/Teaching/cars/car_ims/007048.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +601 /scratch/Teaching/cars/car_ims/006641.jpg Daewoo Nubira Wagon 2002 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +602 /scratch/Teaching/cars/car_ims/015522.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +603 /scratch/Teaching/cars/car_ims/004214.jpg Cadillac SRX SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +604 /scratch/Teaching/cars/car_ims/016144.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +605 /scratch/Teaching/cars/car_ims/001971.jpg Audi S4 Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +606 /scratch/Teaching/cars/car_ims/009309.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +607 /scratch/Teaching/cars/car_ims/000893.jpg Audi RS 4 Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +608 /scratch/Teaching/cars/car_ims/005124.jpg Chevrolet Sonic Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +609 /scratch/Teaching/cars/car_ims/006393.jpg Chrysler 300 SRT-8 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +610 /scratch/Teaching/cars/car_ims/000591.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +611 /scratch/Teaching/cars/car_ims/010263.jpg HUMMER H3T Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +612 /scratch/Teaching/cars/car_ims/006805.jpg Dodge Caliber Wagon 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +613 /scratch/Teaching/cars/car_ims/013816.jpg Nissan Leaf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +614 /scratch/Teaching/cars/car_ims/000652.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +615 /scratch/Teaching/cars/car_ims/005034.jpg Chevrolet Tahoe Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +616 /scratch/Teaching/cars/car_ims/004339.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +617 /scratch/Teaching/cars/car_ims/013997.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +618 /scratch/Teaching/cars/car_ims/004603.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +619 /scratch/Teaching/cars/car_ims/010145.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +620 /scratch/Teaching/cars/car_ims/002622.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +621 /scratch/Teaching/cars/car_ims/006477.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +622 /scratch/Teaching/cars/car_ims/011090.jpg Hyundai Elantra Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +623 /scratch/Teaching/cars/car_ims/007581.jpg Dodge Challenger SRT8 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +624 /scratch/Teaching/cars/car_ims/009268.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +625 /scratch/Teaching/cars/car_ims/006895.jpg Dodge Caravan Minivan 1997 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +626 /scratch/Teaching/cars/car_ims/010704.jpg Hyundai Veloster Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +627 /scratch/Teaching/cars/car_ims/006608.jpg Chrysler PT Cruiser Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +628 /scratch/Teaching/cars/car_ims/004696.jpg Chevrolet Traverse SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +629 /scratch/Teaching/cars/car_ims/009757.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +630 /scratch/Teaching/cars/car_ims/003003.jpg BMW X3 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +631 /scratch/Teaching/cars/car_ims/014395.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +632 /scratch/Teaching/cars/car_ims/002554.jpg BMW X5 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +633 /scratch/Teaching/cars/car_ims/013908.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +634 /scratch/Teaching/cars/car_ims/014579.jpg Rolls-Royce Phantom Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +635 /scratch/Teaching/cars/car_ims/014999.jpg Suzuki Kizashi Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +636 /scratch/Teaching/cars/car_ims/008716.jpg Ford Mustang Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +637 /scratch/Teaching/cars/car_ims/004416.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +638 /scratch/Teaching/cars/car_ims/002442.jpg BMW 3 Series Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +639 /scratch/Teaching/cars/car_ims/003992.jpg Buick Enclave SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +640 /scratch/Teaching/cars/car_ims/006082.jpg Chevrolet Silverado 1500 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +641 /scratch/Teaching/cars/car_ims/011625.jpg Infiniti QX56 SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +642 /scratch/Teaching/cars/car_ims/006980.jpg Dodge Ram Pickup 3500 Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +643 /scratch/Teaching/cars/car_ims/008322.jpg Ferrari California Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +644 /scratch/Teaching/cars/car_ims/009348.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +645 /scratch/Teaching/cars/car_ims/011815.jpg Jaguar XK XKR 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +646 /scratch/Teaching/cars/car_ims/004434.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +647 /scratch/Teaching/cars/car_ims/010411.jpg Honda Odyssey Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +648 /scratch/Teaching/cars/car_ims/003908.jpg Buick Verano Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +649 /scratch/Teaching/cars/car_ims/015223.jpg Tesla Model S Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +650 /scratch/Teaching/cars/car_ims/011392.jpg Hyundai Elantra Touring Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +651 /scratch/Teaching/cars/car_ims/015246.jpg Tesla Model S Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +652 /scratch/Teaching/cars/car_ims/000143.jpg Acura RL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +653 /scratch/Teaching/cars/car_ims/009657.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +654 /scratch/Teaching/cars/car_ims/009563.jpg Ford Fiesta Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +655 /scratch/Teaching/cars/car_ims/004966.jpg Chevrolet Impala Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +656 /scratch/Teaching/cars/car_ims/014411.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +657 /scratch/Teaching/cars/car_ims/004441.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +658 /scratch/Teaching/cars/car_ims/011300.jpg Hyundai Sonata Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +659 /scratch/Teaching/cars/car_ims/002102.jpg BMW ActiveHybrid 5 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +660 /scratch/Teaching/cars/car_ims/008892.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +661 /scratch/Teaching/cars/car_ims/000600.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +662 /scratch/Teaching/cars/car_ims/004782.jpg Chevrolet Camaro Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +663 /scratch/Teaching/cars/car_ims/012429.jpg Lamborghini Aventador Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +664 /scratch/Teaching/cars/car_ims/007575.jpg Dodge Challenger SRT8 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +665 /scratch/Teaching/cars/car_ims/006747.jpg Dodge Caliber Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +666 /scratch/Teaching/cars/car_ims/011650.jpg Infiniti QX56 SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +667 /scratch/Teaching/cars/car_ims/010408.jpg Honda Odyssey Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +668 /scratch/Teaching/cars/car_ims/002225.jpg BMW 1 Series Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +669 /scratch/Teaching/cars/car_ims/012883.jpg MINI Cooper Roadster Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +670 /scratch/Teaching/cars/car_ims/013917.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +671 /scratch/Teaching/cars/car_ims/009827.jpg GMC Yukon Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +672 /scratch/Teaching/cars/car_ims/014721.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +673 /scratch/Teaching/cars/car_ims/001746.jpg Audi S5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +674 /scratch/Teaching/cars/car_ims/015475.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +675 /scratch/Teaching/cars/car_ims/013396.jpg Mercedes-Benz SL-Class Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +676 /scratch/Teaching/cars/car_ims/004427.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +677 /scratch/Teaching/cars/car_ims/010890.jpg Hyundai Tucson SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +678 /scratch/Teaching/cars/car_ims/013957.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +679 /scratch/Teaching/cars/car_ims/012211.jpg Jeep Compass SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +680 /scratch/Teaching/cars/car_ims/014328.jpg Ram C/V Cargo Van Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +681 /scratch/Teaching/cars/car_ims/001464.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +682 /scratch/Teaching/cars/car_ims/010220.jpg HUMMER H3T Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +683 /scratch/Teaching/cars/car_ims/009050.jpg Ford Ranger SuperCab 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +684 /scratch/Teaching/cars/car_ims/008465.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +685 /scratch/Teaching/cars/car_ims/010568.jpg Honda Accord Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +686 /scratch/Teaching/cars/car_ims/002226.jpg BMW 1 Series Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +687 /scratch/Teaching/cars/car_ims/005122.jpg Chevrolet Sonic Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +688 /scratch/Teaching/cars/car_ims/007993.jpg Eagle Talon Hatchback 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +689 /scratch/Teaching/cars/car_ims/016051.jpg Volvo XC90 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +690 /scratch/Teaching/cars/car_ims/000033.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +691 /scratch/Teaching/cars/car_ims/015077.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +692 /scratch/Teaching/cars/car_ims/011526.jpg Hyundai Azera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +693 /scratch/Teaching/cars/car_ims/015147.jpg Suzuki SX4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +694 /scratch/Teaching/cars/car_ims/014145.jpg Plymouth Neon Coupe 1999 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +695 /scratch/Teaching/cars/car_ims/007728.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +696 /scratch/Teaching/cars/car_ims/014074.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +697 /scratch/Teaching/cars/car_ims/015644.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +698 /scratch/Teaching/cars/car_ims/014953.jpg Suzuki Kizashi Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +699 /scratch/Teaching/cars/car_ims/000732.jpg Aston Martin V8 Vantage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +700 /scratch/Teaching/cars/car_ims/012590.jpg Lamborghini Diablo Coupe 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +701 /scratch/Teaching/cars/car_ims/008074.jpg FIAT 500 Abarth 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +702 /scratch/Teaching/cars/car_ims/014033.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +703 /scratch/Teaching/cars/car_ims/014859.jpg Suzuki Aerio Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +704 /scratch/Teaching/cars/car_ims/008489.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +705 /scratch/Teaching/cars/car_ims/002980.jpg BMW X3 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +706 /scratch/Teaching/cars/car_ims/010980.jpg Hyundai Veracruz SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +707 /scratch/Teaching/cars/car_ims/011681.jpg Isuzu Ascender SUV 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +708 /scratch/Teaching/cars/car_ims/014655.jpg Scion xD Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +709 /scratch/Teaching/cars/car_ims/014848.jpg Suzuki Aerio Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +710 /scratch/Teaching/cars/car_ims/001427.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +711 /scratch/Teaching/cars/car_ims/011775.jpg Jaguar XK XKR 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +712 /scratch/Teaching/cars/car_ims/000818.jpg Aston Martin Virage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +713 /scratch/Teaching/cars/car_ims/000009.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +714 /scratch/Teaching/cars/car_ims/013636.jpg Mercedes-Benz Sprinter Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +715 /scratch/Teaching/cars/car_ims/008656.jpg Ford F-450 Super Duty Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +716 /scratch/Teaching/cars/car_ims/011167.jpg Hyundai Accent Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +717 /scratch/Teaching/cars/car_ims/012951.jpg Maybach Landaulet Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +718 /scratch/Teaching/cars/car_ims/010140.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +719 /scratch/Teaching/cars/car_ims/013084.jpg McLaren MP4-12C Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +720 /scratch/Teaching/cars/car_ims/007168.jpg Dodge Sprinter Cargo Van 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +721 /scratch/Teaching/cars/car_ims/013590.jpg Mercedes-Benz Sprinter Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +722 /scratch/Teaching/cars/car_ims/015424.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +723 /scratch/Teaching/cars/car_ims/012976.jpg Maybach Landaulet Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +724 /scratch/Teaching/cars/car_ims/006812.jpg Dodge Caliber Wagon 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +725 /scratch/Teaching/cars/car_ims/000349.jpg Acura TSX Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +726 /scratch/Teaching/cars/car_ims/013355.jpg Mercedes-Benz SL-Class Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +727 /scratch/Teaching/cars/car_ims/001618.jpg Audi S6 Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +728 /scratch/Teaching/cars/car_ims/001863.jpg Audi S4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +729 /scratch/Teaching/cars/car_ims/015511.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +730 /scratch/Teaching/cars/car_ims/008480.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +731 /scratch/Teaching/cars/car_ims/002609.jpg BMW X5 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +732 /scratch/Teaching/cars/car_ims/003279.jpg Bentley Mulsanne Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +733 /scratch/Teaching/cars/car_ims/010913.jpg Hyundai Tucson SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +734 /scratch/Teaching/cars/car_ims/004762.jpg Chevrolet Camaro Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +735 /scratch/Teaching/cars/car_ims/009327.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +736 /scratch/Teaching/cars/car_ims/003600.jpg Bugatti Veyron 16.4 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +737 /scratch/Teaching/cars/car_ims/003857.jpg Buick Rainier SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +738 /scratch/Teaching/cars/car_ims/014370.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +739 /scratch/Teaching/cars/car_ims/002307.jpg BMW 3 Series Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +740 /scratch/Teaching/cars/car_ims/015777.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +741 /scratch/Teaching/cars/car_ims/001337.jpg Audi 100 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +742 /scratch/Teaching/cars/car_ims/007051.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +743 /scratch/Teaching/cars/car_ims/013230.jpg Mercedes-Benz 300-Class Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +744 /scratch/Teaching/cars/car_ims/007872.jpg Dodge Charger Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +745 /scratch/Teaching/cars/car_ims/006685.jpg Daewoo Nubira Wagon 2002 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +746 /scratch/Teaching/cars/car_ims/015192.jpg Tesla Model S Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +747 /scratch/Teaching/cars/car_ims/013967.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +748 /scratch/Teaching/cars/car_ims/002079.jpg BMW ActiveHybrid 5 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +749 /scratch/Teaching/cars/car_ims/016002.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +750 /scratch/Teaching/cars/car_ims/007936.jpg Dodge Charger SRT-8 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +751 /scratch/Teaching/cars/car_ims/010130.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +752 /scratch/Teaching/cars/car_ims/003523.jpg Bentley Continental Flying Spur Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +753 /scratch/Teaching/cars/car_ims/015824.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +754 /scratch/Teaching/cars/car_ims/008826.jpg Ford Freestar Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +755 /scratch/Teaching/cars/car_ims/001420.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +756 /scratch/Teaching/cars/car_ims/013730.jpg Mitsubishi Lancer Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +757 /scratch/Teaching/cars/car_ims/004698.jpg Chevrolet Traverse SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +758 /scratch/Teaching/cars/car_ims/003921.jpg Buick Verano Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +759 /scratch/Teaching/cars/car_ims/002297.jpg BMW 3 Series Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +760 /scratch/Teaching/cars/car_ims/008484.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +761 /scratch/Teaching/cars/car_ims/014198.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +762 /scratch/Teaching/cars/car_ims/010816.jpg Hyundai Santa Fe SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +763 /scratch/Teaching/cars/car_ims/007710.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +764 /scratch/Teaching/cars/car_ims/006589.jpg Chrysler PT Cruiser Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +765 /scratch/Teaching/cars/car_ims/008316.jpg Ferrari California Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +766 /scratch/Teaching/cars/car_ims/006133.jpg Chrysler Aspen SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +767 /scratch/Teaching/cars/car_ims/002056.jpg BMW ActiveHybrid 5 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +768 /scratch/Teaching/cars/car_ims/012823.jpg Lincoln Town Car Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +769 /scratch/Teaching/cars/car_ims/001121.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +770 /scratch/Teaching/cars/car_ims/013075.jpg McLaren MP4-12C Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +771 /scratch/Teaching/cars/car_ims/012908.jpg MINI Cooper Roadster Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +772 /scratch/Teaching/cars/car_ims/005847.jpg Chevrolet Malibu Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +773 /scratch/Teaching/cars/car_ims/012960.jpg Maybach Landaulet Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +774 /scratch/Teaching/cars/car_ims/000627.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +775 /scratch/Teaching/cars/car_ims/005723.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +776 /scratch/Teaching/cars/car_ims/011465.jpg Hyundai Azera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +777 /scratch/Teaching/cars/car_ims/004650.jpg Chevrolet Traverse SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +778 /scratch/Teaching/cars/car_ims/014580.jpg Rolls-Royce Phantom Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +779 /scratch/Teaching/cars/car_ims/006959.jpg Dodge Caravan Minivan 1997 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +780 /scratch/Teaching/cars/car_ims/000632.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +781 /scratch/Teaching/cars/car_ims/003032.jpg BMW Z4 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +782 /scratch/Teaching/cars/car_ims/006364.jpg Chrysler 300 SRT-8 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +783 /scratch/Teaching/cars/car_ims/007496.jpg Dodge Magnum Wagon 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +784 /scratch/Teaching/cars/car_ims/008279.jpg Ferrari California Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +785 /scratch/Teaching/cars/car_ims/008861.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +786 /scratch/Teaching/cars/car_ims/010412.jpg Honda Odyssey Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +787 /scratch/Teaching/cars/car_ims/001203.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +788 /scratch/Teaching/cars/car_ims/003807.jpg Buick Rainier SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +789 /scratch/Teaching/cars/car_ims/008503.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +790 /scratch/Teaching/cars/car_ims/012426.jpg Lamborghini Aventador Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +791 /scratch/Teaching/cars/car_ims/001176.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +792 /scratch/Teaching/cars/car_ims/002185.jpg BMW 1 Series Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +793 /scratch/Teaching/cars/car_ims/003826.jpg Buick Rainier SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +794 /scratch/Teaching/cars/car_ims/010670.jpg Honda Accord Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +795 /scratch/Teaching/cars/car_ims/007448.jpg Dodge Dakota Club Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +796 /scratch/Teaching/cars/car_ims/000723.jpg Aston Martin V8 Vantage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +797 /scratch/Teaching/cars/car_ims/009184.jpg Ford GT Coupe 2006 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +798 /scratch/Teaching/cars/car_ims/000066.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +799 /scratch/Teaching/cars/car_ims/012992.jpg Mazda Tribute SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +800 /scratch/Teaching/cars/car_ims/013728.jpg Mitsubishi Lancer Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +801 /scratch/Teaching/cars/car_ims/009624.jpg Ford Fiesta Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +802 /scratch/Teaching/cars/car_ims/008594.jpg Ford F-450 Super Duty Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +803 /scratch/Teaching/cars/car_ims/005287.jpg Chevrolet Cobalt SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +804 /scratch/Teaching/cars/car_ims/000508.jpg Acura ZDX Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +805 /scratch/Teaching/cars/car_ims/005798.jpg Chevrolet Monte Carlo Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +806 /scratch/Teaching/cars/car_ims/013129.jpg McLaren MP4-12C Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +807 /scratch/Teaching/cars/car_ims/008759.jpg Ford Mustang Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +808 /scratch/Teaching/cars/car_ims/010445.jpg Honda Odyssey Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +809 /scratch/Teaching/cars/car_ims/005005.jpg Chevrolet Tahoe Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +810 /scratch/Teaching/cars/car_ims/015755.jpg Volkswagen Golf Hatchback 1991 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +811 /scratch/Teaching/cars/car_ims/005182.jpg Chevrolet Express Cargo Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +812 /scratch/Teaching/cars/car_ims/003909.jpg Buick Verano Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +813 /scratch/Teaching/cars/car_ims/004818.jpg Chevrolet HHR SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +814 /scratch/Teaching/cars/car_ims/005640.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +815 /scratch/Teaching/cars/car_ims/011143.jpg Hyundai Elantra Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +816 /scratch/Teaching/cars/car_ims/009085.jpg Ford Ranger SuperCab 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +817 /scratch/Teaching/cars/car_ims/011897.jpg Jeep Patriot SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +818 /scratch/Teaching/cars/car_ims/013878.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +819 /scratch/Teaching/cars/car_ims/008951.jpg Ford Edge SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +820 /scratch/Teaching/cars/car_ims/005235.jpg Chevrolet Avalanche Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +821 /scratch/Teaching/cars/car_ims/009642.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +822 /scratch/Teaching/cars/car_ims/015583.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +823 /scratch/Teaching/cars/car_ims/007324.jpg Dodge Dakota Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +824 /scratch/Teaching/cars/car_ims/004568.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +825 /scratch/Teaching/cars/car_ims/009680.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +826 /scratch/Teaching/cars/car_ims/002483.jpg BMW 6 Series Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +827 /scratch/Teaching/cars/car_ims/012401.jpg Lamborghini Aventador Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +828 /scratch/Teaching/cars/car_ims/015111.jpg Suzuki SX4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +829 /scratch/Teaching/cars/car_ims/006490.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +830 /scratch/Teaching/cars/car_ims/009972.jpg GMC Canyon Extended Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +831 /scratch/Teaching/cars/car_ims/015504.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +832 /scratch/Teaching/cars/car_ims/000020.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +833 /scratch/Teaching/cars/car_ims/013888.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +834 /scratch/Teaching/cars/car_ims/014080.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +835 /scratch/Teaching/cars/car_ims/006105.jpg Chrysler Aspen SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +836 /scratch/Teaching/cars/car_ims/000567.jpg Acura ZDX Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +837 /scratch/Teaching/cars/car_ims/004196.jpg Cadillac SRX SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +838 /scratch/Teaching/cars/car_ims/009663.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +839 /scratch/Teaching/cars/car_ims/001143.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +840 /scratch/Teaching/cars/car_ims/009447.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +841 /scratch/Teaching/cars/car_ims/015480.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +842 /scratch/Teaching/cars/car_ims/010121.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +843 /scratch/Teaching/cars/car_ims/007070.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +844 /scratch/Teaching/cars/car_ims/004134.jpg Cadillac SRX SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +845 /scratch/Teaching/cars/car_ims/013374.jpg Mercedes-Benz SL-Class Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +846 /scratch/Teaching/cars/car_ims/001167.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +847 /scratch/Teaching/cars/car_ims/006421.jpg Chrysler 300 SRT-8 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +848 /scratch/Teaching/cars/car_ims/002925.jpg BMW M6 Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +849 /scratch/Teaching/cars/car_ims/009373.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +850 /scratch/Teaching/cars/car_ims/003176.jpg Bentley Continental Supersports Conv. Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +851 /scratch/Teaching/cars/car_ims/007264.jpg Dodge Journey SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +852 /scratch/Teaching/cars/car_ims/015908.jpg Volvo C30 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +853 /scratch/Teaching/cars/car_ims/014023.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +854 /scratch/Teaching/cars/car_ims/015655.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +855 /scratch/Teaching/cars/car_ims/007139.jpg Dodge Sprinter Cargo Van 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +856 /scratch/Teaching/cars/car_ims/006712.jpg Dodge Caliber Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +857 /scratch/Teaching/cars/car_ims/006965.jpg Dodge Ram Pickup 3500 Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +858 /scratch/Teaching/cars/car_ims/008228.jpg Ferrari FF Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +859 /scratch/Teaching/cars/car_ims/001966.jpg Audi S4 Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +860 /scratch/Teaching/cars/car_ims/000398.jpg Acura TSX Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +861 /scratch/Teaching/cars/car_ims/010351.jpg HUMMER H2 SUT Crew Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +862 /scratch/Teaching/cars/car_ims/012458.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +863 /scratch/Teaching/cars/car_ims/011103.jpg Hyundai Elantra Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +864 /scratch/Teaching/cars/car_ims/004419.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +865 /scratch/Teaching/cars/car_ims/006967.jpg Dodge Ram Pickup 3500 Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +866 /scratch/Teaching/cars/car_ims/004018.jpg Buick Enclave SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +867 /scratch/Teaching/cars/car_ims/012576.jpg Lamborghini Diablo Coupe 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +868 /scratch/Teaching/cars/car_ims/013596.jpg Mercedes-Benz Sprinter Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +869 /scratch/Teaching/cars/car_ims/011106.jpg Hyundai Elantra Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +870 /scratch/Teaching/cars/car_ims/002486.jpg BMW 6 Series Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +871 /scratch/Teaching/cars/car_ims/011343.jpg Hyundai Sonata Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +872 /scratch/Teaching/cars/car_ims/011861.jpg Jeep Patriot SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +873 /scratch/Teaching/cars/car_ims/012238.jpg Jeep Compass SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +874 /scratch/Teaching/cars/car_ims/005355.jpg Chevrolet Cobalt SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +875 /scratch/Teaching/cars/car_ims/003970.jpg Buick Enclave SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +876 /scratch/Teaching/cars/car_ims/003067.jpg BMW Z4 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +877 /scratch/Teaching/cars/car_ims/009449.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +878 /scratch/Teaching/cars/car_ims/004934.jpg Chevrolet Impala Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +879 /scratch/Teaching/cars/car_ims/004901.jpg Chevrolet Impala Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +880 /scratch/Teaching/cars/car_ims/001385.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +881 /scratch/Teaching/cars/car_ims/005731.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +882 /scratch/Teaching/cars/car_ims/014791.jpg Spyker C8 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +883 /scratch/Teaching/cars/car_ims/006018.jpg Chevrolet Silverado 1500 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +884 /scratch/Teaching/cars/car_ims/000789.jpg Aston Martin Virage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +885 /scratch/Teaching/cars/car_ims/001233.jpg Audi V8 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +886 /scratch/Teaching/cars/car_ims/014230.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +887 /scratch/Teaching/cars/car_ims/007378.jpg Dodge Dakota Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +888 /scratch/Teaching/cars/car_ims/007154.jpg Dodge Sprinter Cargo Van 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +889 /scratch/Teaching/cars/car_ims/009739.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +890 /scratch/Teaching/cars/car_ims/014264.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +891 /scratch/Teaching/cars/car_ims/012998.jpg Mazda Tribute SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +892 /scratch/Teaching/cars/car_ims/015916.jpg Volvo C30 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +893 /scratch/Teaching/cars/car_ims/001148.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +894 /scratch/Teaching/cars/car_ims/007607.jpg Dodge Challenger SRT8 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +895 /scratch/Teaching/cars/car_ims/009813.jpg GMC Yukon Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +896 /scratch/Teaching/cars/car_ims/004076.jpg Cadillac CTS-V Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +897 /scratch/Teaching/cars/car_ims/003788.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +898 /scratch/Teaching/cars/car_ims/014521.jpg Rolls-Royce Phantom Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +899 /scratch/Teaching/cars/car_ims/009619.jpg Ford Fiesta Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +900 /scratch/Teaching/cars/car_ims/009020.jpg Ford Edge SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +901 /scratch/Teaching/cars/car_ims/005526.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +902 /scratch/Teaching/cars/car_ims/008575.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +903 /scratch/Teaching/cars/car_ims/007366.jpg Dodge Dakota Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +904 /scratch/Teaching/cars/car_ims/006213.jpg Chrysler Sebring Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +905 /scratch/Teaching/cars/car_ims/010402.jpg Honda Odyssey Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +906 /scratch/Teaching/cars/car_ims/015604.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +907 /scratch/Teaching/cars/car_ims/007699.jpg Dodge Durango SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +908 /scratch/Teaching/cars/car_ims/009072.jpg Ford Ranger SuperCab 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +909 /scratch/Teaching/cars/car_ims/008015.jpg Eagle Talon Hatchback 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +910 /scratch/Teaching/cars/car_ims/009026.jpg Ford Ranger SuperCab 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +911 /scratch/Teaching/cars/car_ims/004421.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +912 /scratch/Teaching/cars/car_ims/008106.jpg FIAT 500 Abarth 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +913 /scratch/Teaching/cars/car_ims/003418.jpg Bentley Continental GT Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +914 /scratch/Teaching/cars/car_ims/005333.jpg Chevrolet Cobalt SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +915 /scratch/Teaching/cars/car_ims/000917.jpg Audi RS 4 Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +916 /scratch/Teaching/cars/car_ims/004408.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +917 /scratch/Teaching/cars/car_ims/012045.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +918 /scratch/Teaching/cars/car_ims/009074.jpg Ford Ranger SuperCab 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +919 /scratch/Teaching/cars/car_ims/006203.jpg Chrysler Sebring Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +920 /scratch/Teaching/cars/car_ims/011446.jpg Hyundai Elantra Touring Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +921 /scratch/Teaching/cars/car_ims/009880.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +922 /scratch/Teaching/cars/car_ims/013039.jpg Mazda Tribute SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +923 /scratch/Teaching/cars/car_ims/008658.jpg Ford F-450 Super Duty Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +924 /scratch/Teaching/cars/car_ims/009235.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +925 /scratch/Teaching/cars/car_ims/007739.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +926 /scratch/Teaching/cars/car_ims/002147.jpg BMW 1 Series Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +927 /scratch/Teaching/cars/car_ims/016030.jpg Volvo XC90 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +928 /scratch/Teaching/cars/car_ims/003296.jpg Bentley Mulsanne Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +929 /scratch/Teaching/cars/car_ims/010208.jpg HUMMER H3T Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +930 /scratch/Teaching/cars/car_ims/005686.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +931 /scratch/Teaching/cars/car_ims/001115.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +932 /scratch/Teaching/cars/car_ims/012283.jpg Jeep Compass SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +933 /scratch/Teaching/cars/car_ims/012179.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +934 /scratch/Teaching/cars/car_ims/012403.jpg Lamborghini Aventador Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +935 /scratch/Teaching/cars/car_ims/003556.jpg Bentley Continental Flying Spur Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +936 /scratch/Teaching/cars/car_ims/000637.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +937 /scratch/Teaching/cars/car_ims/008797.jpg Ford Freestar Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +938 /scratch/Teaching/cars/car_ims/007510.jpg Dodge Magnum Wagon 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +939 /scratch/Teaching/cars/car_ims/011048.jpg Hyundai Sonata Hybrid Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +940 /scratch/Teaching/cars/car_ims/000228.jpg Acura TL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +941 /scratch/Teaching/cars/car_ims/007213.jpg Dodge Sprinter Cargo Van 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +942 /scratch/Teaching/cars/car_ims/006041.jpg Chevrolet Silverado 1500 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +943 /scratch/Teaching/cars/car_ims/010693.jpg Hyundai Veloster Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +944 /scratch/Teaching/cars/car_ims/013371.jpg Mercedes-Benz SL-Class Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +945 /scratch/Teaching/cars/car_ims/002175.jpg BMW 1 Series Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +946 /scratch/Teaching/cars/car_ims/013290.jpg Mercedes-Benz C-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +947 /scratch/Teaching/cars/car_ims/003560.jpg Bentley Continental Flying Spur Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +948 /scratch/Teaching/cars/car_ims/010817.jpg Hyundai Santa Fe SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +949 /scratch/Teaching/cars/car_ims/004769.jpg Chevrolet Camaro Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +950 /scratch/Teaching/cars/car_ims/014713.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +951 /scratch/Teaching/cars/car_ims/001087.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +952 /scratch/Teaching/cars/car_ims/008190.jpg Ferrari FF Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +953 /scratch/Teaching/cars/car_ims/002508.jpg BMW 6 Series Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +954 /scratch/Teaching/cars/car_ims/006276.jpg Chrysler Town and Country Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +955 /scratch/Teaching/cars/car_ims/008633.jpg Ford F-450 Super Duty Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +956 /scratch/Teaching/cars/car_ims/009557.jpg Ford Fiesta Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +957 /scratch/Teaching/cars/car_ims/006446.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +958 /scratch/Teaching/cars/car_ims/010714.jpg Hyundai Veloster Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +959 /scratch/Teaching/cars/car_ims/013880.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +960 /scratch/Teaching/cars/car_ims/016170.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +961 /scratch/Teaching/cars/car_ims/004672.jpg Chevrolet Traverse SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +962 /scratch/Teaching/cars/car_ims/001197.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +963 /scratch/Teaching/cars/car_ims/012142.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +964 /scratch/Teaching/cars/car_ims/001506.jpg Audi TT Hatchback 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +965 /scratch/Teaching/cars/car_ims/007421.jpg Dodge Dakota Club Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +966 /scratch/Teaching/cars/car_ims/012202.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +967 /scratch/Teaching/cars/car_ims/002656.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +968 /scratch/Teaching/cars/car_ims/013926.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +969 /scratch/Teaching/cars/car_ims/013382.jpg Mercedes-Benz SL-Class Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +970 /scratch/Teaching/cars/car_ims/003445.jpg Bentley Continental GT Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +971 /scratch/Teaching/cars/car_ims/003412.jpg Bentley Continental GT Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +972 /scratch/Teaching/cars/car_ims/009981.jpg GMC Canyon Extended Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +973 /scratch/Teaching/cars/car_ims/000490.jpg Acura Integra Type R 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +974 /scratch/Teaching/cars/car_ims/004062.jpg Cadillac CTS-V Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +975 /scratch/Teaching/cars/car_ims/007422.jpg Dodge Dakota Club Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +976 /scratch/Teaching/cars/car_ims/002178.jpg BMW 1 Series Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +977 /scratch/Teaching/cars/car_ims/004266.jpg Cadillac Escalade EXT Crew Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +978 /scratch/Teaching/cars/car_ims/015188.jpg Tesla Model S Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +979 /scratch/Teaching/cars/car_ims/002002.jpg Audi TT RS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +980 /scratch/Teaching/cars/car_ims/008840.jpg Ford Freestar Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +981 /scratch/Teaching/cars/car_ims/004274.jpg Cadillac Escalade EXT Crew Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +982 /scratch/Teaching/cars/car_ims/008583.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +983 /scratch/Teaching/cars/car_ims/012221.jpg Jeep Compass SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +984 /scratch/Teaching/cars/car_ims/015598.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +985 /scratch/Teaching/cars/car_ims/002822.jpg BMW M5 Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +986 /scratch/Teaching/cars/car_ims/006494.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +987 /scratch/Teaching/cars/car_ims/014565.jpg Rolls-Royce Phantom Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +988 /scratch/Teaching/cars/car_ims/002923.jpg BMW M6 Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +989 /scratch/Teaching/cars/car_ims/003244.jpg Bentley Arnage Sedan 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +990 /scratch/Teaching/cars/car_ims/006647.jpg Daewoo Nubira Wagon 2002 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +991 /scratch/Teaching/cars/car_ims/001498.jpg Audi TT Hatchback 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +992 /scratch/Teaching/cars/car_ims/000974.jpg Audi A5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +993 /scratch/Teaching/cars/car_ims/009660.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +994 /scratch/Teaching/cars/car_ims/010604.jpg Honda Accord Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +995 /scratch/Teaching/cars/car_ims/007023.jpg Dodge Ram Pickup 3500 Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +996 /scratch/Teaching/cars/car_ims/014533.jpg Rolls-Royce Phantom Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +997 /scratch/Teaching/cars/car_ims/016011.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +998 /scratch/Teaching/cars/car_ims/007080.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +999 /scratch/Teaching/cars/car_ims/011700.jpg Isuzu Ascender SUV 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1000 /scratch/Teaching/cars/car_ims/005453.jpg Chevrolet TrailBlazer SS 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1001 /scratch/Teaching/cars/car_ims/004598.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1002 /scratch/Teaching/cars/car_ims/008155.jpg FIAT 500 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1003 /scratch/Teaching/cars/car_ims/012847.jpg Lincoln Town Car Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1004 /scratch/Teaching/cars/car_ims/012355.jpg Lamborghini Reventon Coupe 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1005 /scratch/Teaching/cars/car_ims/000141.jpg Acura RL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1006 /scratch/Teaching/cars/car_ims/014822.jpg Spyker C8 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1007 /scratch/Teaching/cars/car_ims/007071.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1008 /scratch/Teaching/cars/car_ims/005872.jpg Chevrolet Malibu Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1009 /scratch/Teaching/cars/car_ims/008052.jpg Eagle Talon Hatchback 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1010 /scratch/Teaching/cars/car_ims/010944.jpg Hyundai Veracruz SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1011 /scratch/Teaching/cars/car_ims/000392.jpg Acura TSX Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1012 /scratch/Teaching/cars/car_ims/002633.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1013 /scratch/Teaching/cars/car_ims/003169.jpg Bentley Continental Supersports Conv. Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1014 /scratch/Teaching/cars/car_ims/004231.jpg Cadillac Escalade EXT Crew Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1015 /scratch/Teaching/cars/car_ims/005814.jpg Chevrolet Monte Carlo Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1016 /scratch/Teaching/cars/car_ims/002179.jpg BMW 1 Series Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1017 /scratch/Teaching/cars/car_ims/002834.jpg BMW M5 Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1018 /scratch/Teaching/cars/car_ims/015390.jpg Toyota Camry Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1019 /scratch/Teaching/cars/car_ims/009812.jpg GMC Yukon Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1020 /scratch/Teaching/cars/car_ims/003228.jpg Bentley Arnage Sedan 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1021 /scratch/Teaching/cars/car_ims/011527.jpg Hyundai Azera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1022 /scratch/Teaching/cars/car_ims/015630.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1023 /scratch/Teaching/cars/car_ims/010264.jpg HUMMER H3T Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1024 /scratch/Teaching/cars/car_ims/009295.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1025 /scratch/Teaching/cars/car_ims/013922.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1026 /scratch/Teaching/cars/car_ims/013465.jpg Mercedes-Benz E-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1027 /scratch/Teaching/cars/car_ims/009411.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1028 /scratch/Teaching/cars/car_ims/007733.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1029 /scratch/Teaching/cars/car_ims/011307.jpg Hyundai Sonata Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1030 /scratch/Teaching/cars/car_ims/004403.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1031 /scratch/Teaching/cars/car_ims/000219.jpg Acura TL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1032 /scratch/Teaching/cars/car_ims/010368.jpg Honda Odyssey Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1033 /scratch/Teaching/cars/car_ims/011290.jpg Hyundai Genesis Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1034 /scratch/Teaching/cars/car_ims/003115.jpg Bentley Continental Supersports Conv. Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1035 /scratch/Teaching/cars/car_ims/000002.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1036 /scratch/Teaching/cars/car_ims/009463.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1037 /scratch/Teaching/cars/car_ims/008366.jpg Ferrari 458 Italia Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1038 /scratch/Teaching/cars/car_ims/007368.jpg Dodge Dakota Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1039 /scratch/Teaching/cars/car_ims/014075.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1040 /scratch/Teaching/cars/car_ims/015807.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1041 /scratch/Teaching/cars/car_ims/012874.jpg MINI Cooper Roadster Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1042 /scratch/Teaching/cars/car_ims/005741.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1043 /scratch/Teaching/cars/car_ims/006241.jpg Chrysler Sebring Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1044 /scratch/Teaching/cars/car_ims/016097.jpg Volvo XC90 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1045 /scratch/Teaching/cars/car_ims/006340.jpg Chrysler Town and Country Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1046 /scratch/Teaching/cars/car_ims/014079.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1047 /scratch/Teaching/cars/car_ims/009567.jpg Ford Fiesta Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1048 /scratch/Teaching/cars/car_ims/015538.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1049 /scratch/Teaching/cars/car_ims/013973.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1050 /scratch/Teaching/cars/car_ims/012102.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1051 /scratch/Teaching/cars/car_ims/008870.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1052 /scratch/Teaching/cars/car_ims/004459.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1053 /scratch/Teaching/cars/car_ims/005611.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1054 /scratch/Teaching/cars/car_ims/016149.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1055 /scratch/Teaching/cars/car_ims/012076.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1056 /scratch/Teaching/cars/car_ims/012761.jpg Land Rover LR2 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1057 /scratch/Teaching/cars/car_ims/003792.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1058 /scratch/Teaching/cars/car_ims/014273.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1059 /scratch/Teaching/cars/car_ims/007323.jpg Dodge Dakota Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1060 /scratch/Teaching/cars/car_ims/004675.jpg Chevrolet Traverse SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1061 /scratch/Teaching/cars/car_ims/008262.jpg Ferrari California Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1062 /scratch/Teaching/cars/car_ims/006998.jpg Dodge Ram Pickup 3500 Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1063 /scratch/Teaching/cars/car_ims/008120.jpg FIAT 500 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1064 /scratch/Teaching/cars/car_ims/009140.jpg Ford GT Coupe 2006 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1065 /scratch/Teaching/cars/car_ims/007690.jpg Dodge Durango SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1066 /scratch/Teaching/cars/car_ims/001313.jpg Audi 100 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1067 /scratch/Teaching/cars/car_ims/008110.jpg FIAT 500 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1068 /scratch/Teaching/cars/car_ims/000989.jpg Audi A5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1069 /scratch/Teaching/cars/car_ims/007554.jpg Dodge Challenger SRT8 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1070 /scratch/Teaching/cars/car_ims/013859.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1071 /scratch/Teaching/cars/car_ims/011773.jpg Jaguar XK XKR 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1072 /scratch/Teaching/cars/car_ims/015588.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1073 /scratch/Teaching/cars/car_ims/000592.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1074 /scratch/Teaching/cars/car_ims/014017.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1075 /scratch/Teaching/cars/car_ims/007508.jpg Dodge Magnum Wagon 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1076 /scratch/Teaching/cars/car_ims/014750.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1077 /scratch/Teaching/cars/car_ims/009180.jpg Ford GT Coupe 2006 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1078 /scratch/Teaching/cars/car_ims/000686.jpg Aston Martin V8 Vantage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1079 /scratch/Teaching/cars/car_ims/004701.jpg Chevrolet Traverse SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1080 /scratch/Teaching/cars/car_ims/011950.jpg Jeep Wrangler SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1081 /scratch/Teaching/cars/car_ims/015611.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1082 /scratch/Teaching/cars/car_ims/004995.jpg Chevrolet Tahoe Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1083 /scratch/Teaching/cars/car_ims/003748.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1084 /scratch/Teaching/cars/car_ims/015992.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1085 /scratch/Teaching/cars/car_ims/008030.jpg Eagle Talon Hatchback 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1086 /scratch/Teaching/cars/car_ims/002055.jpg BMW ActiveHybrid 5 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1087 /scratch/Teaching/cars/car_ims/015999.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1088 /scratch/Teaching/cars/car_ims/009576.jpg Ford Fiesta Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1089 /scratch/Teaching/cars/car_ims/015026.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1090 /scratch/Teaching/cars/car_ims/001039.jpg Audi A5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1091 /scratch/Teaching/cars/car_ims/013301.jpg Mercedes-Benz C-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1092 /scratch/Teaching/cars/car_ims/008407.jpg Ferrari 458 Italia Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1093 /scratch/Teaching/cars/car_ims/000568.jpg Acura ZDX Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1094 /scratch/Teaching/cars/car_ims/010012.jpg GMC Canyon Extended Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1095 /scratch/Teaching/cars/car_ims/013059.jpg McLaren MP4-12C Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1096 /scratch/Teaching/cars/car_ims/009753.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1097 /scratch/Teaching/cars/car_ims/010563.jpg Honda Accord Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1098 /scratch/Teaching/cars/car_ims/004714.jpg Chevrolet Traverse SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1099 /scratch/Teaching/cars/car_ims/002407.jpg BMW 3 Series Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1100 /scratch/Teaching/cars/car_ims/015130.jpg Suzuki SX4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1101 /scratch/Teaching/cars/car_ims/008515.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1102 /scratch/Teaching/cars/car_ims/012610.jpg Land Rover Range Rover SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1103 /scratch/Teaching/cars/car_ims/004795.jpg Chevrolet Camaro Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1104 /scratch/Teaching/cars/car_ims/006544.jpg Chrysler PT Cruiser Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1105 /scratch/Teaching/cars/car_ims/001975.jpg Audi S4 Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1106 /scratch/Teaching/cars/car_ims/000017.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1107 /scratch/Teaching/cars/car_ims/012250.jpg Jeep Compass SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1108 /scratch/Teaching/cars/car_ims/009230.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1109 /scratch/Teaching/cars/car_ims/009058.jpg Ford Ranger SuperCab 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1110 /scratch/Teaching/cars/car_ims/015778.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1111 /scratch/Teaching/cars/car_ims/005742.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1112 /scratch/Teaching/cars/car_ims/005803.jpg Chevrolet Monte Carlo Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1113 /scratch/Teaching/cars/car_ims/004059.jpg Cadillac CTS-V Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1114 /scratch/Teaching/cars/car_ims/010921.jpg Hyundai Tucson SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1115 /scratch/Teaching/cars/car_ims/001738.jpg Audi S5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1116 /scratch/Teaching/cars/car_ims/015727.jpg Volkswagen Golf Hatchback 1991 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1117 /scratch/Teaching/cars/car_ims/011005.jpg Hyundai Veracruz SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1118 /scratch/Teaching/cars/car_ims/012806.jpg Lincoln Town Car Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1119 /scratch/Teaching/cars/car_ims/011874.jpg Jeep Patriot SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1120 /scratch/Teaching/cars/car_ims/013938.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1121 /scratch/Teaching/cars/car_ims/001564.jpg Audi S6 Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1122 /scratch/Teaching/cars/car_ims/008698.jpg Ford Mustang Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1123 /scratch/Teaching/cars/car_ims/005863.jpg Chevrolet Malibu Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1124 /scratch/Teaching/cars/car_ims/000378.jpg Acura TSX Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1125 /scratch/Teaching/cars/car_ims/006093.jpg Chevrolet Silverado 1500 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1126 /scratch/Teaching/cars/car_ims/015490.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1127 /scratch/Teaching/cars/car_ims/015847.jpg Volvo C30 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1128 /scratch/Teaching/cars/car_ims/005267.jpg Chevrolet Avalanche Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1129 /scratch/Teaching/cars/car_ims/014061.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1130 /scratch/Teaching/cars/car_ims/003691.jpg Bugatti Veyron 16.4 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1131 /scratch/Teaching/cars/car_ims/009509.jpg Ford E-Series Wagon Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1132 /scratch/Teaching/cars/car_ims/006354.jpg Chrysler 300 SRT-8 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1133 /scratch/Teaching/cars/car_ims/007736.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1134 /scratch/Teaching/cars/car_ims/010883.jpg Hyundai Tucson SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1135 /scratch/Teaching/cars/car_ims/014271.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1136 /scratch/Teaching/cars/car_ims/002762.jpg BMW M3 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1137 /scratch/Teaching/cars/car_ims/011888.jpg Jeep Patriot SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1138 /scratch/Teaching/cars/car_ims/000751.jpg Aston Martin Virage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1139 /scratch/Teaching/cars/car_ims/007403.jpg Dodge Dakota Club Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1140 /scratch/Teaching/cars/car_ims/009025.jpg Ford Ranger SuperCab 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1141 /scratch/Teaching/cars/car_ims/013509.jpg Mercedes-Benz S-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1142 /scratch/Teaching/cars/car_ims/001054.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1143 /scratch/Teaching/cars/car_ims/014942.jpg Suzuki Kizashi Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1144 /scratch/Teaching/cars/car_ims/008194.jpg Ferrari FF Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1145 /scratch/Teaching/cars/car_ims/006466.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1146 /scratch/Teaching/cars/car_ims/013641.jpg Mercedes-Benz Sprinter Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1147 /scratch/Teaching/cars/car_ims/013204.jpg Mercedes-Benz 300-Class Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1148 /scratch/Teaching/cars/car_ims/000208.jpg Acura TL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1149 /scratch/Teaching/cars/car_ims/015286.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1150 /scratch/Teaching/cars/car_ims/009923.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1151 /scratch/Teaching/cars/car_ims/003545.jpg Bentley Continental Flying Spur Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1152 /scratch/Teaching/cars/car_ims/009202.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1153 /scratch/Teaching/cars/car_ims/009857.jpg GMC Yukon Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1154 /scratch/Teaching/cars/car_ims/015306.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1155 /scratch/Teaching/cars/car_ims/010908.jpg Hyundai Tucson SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1156 /scratch/Teaching/cars/car_ims/011179.jpg Hyundai Accent Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1157 /scratch/Teaching/cars/car_ims/003435.jpg Bentley Continental GT Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1158 /scratch/Teaching/cars/car_ims/009602.jpg Ford Fiesta Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1159 /scratch/Teaching/cars/car_ims/013038.jpg Mazda Tribute SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1160 /scratch/Teaching/cars/car_ims/005572.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1161 /scratch/Teaching/cars/car_ims/000093.jpg Acura RL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1162 /scratch/Teaching/cars/car_ims/006588.jpg Chrysler PT Cruiser Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1163 /scratch/Teaching/cars/car_ims/004105.jpg Cadillac CTS-V Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1164 /scratch/Teaching/cars/car_ims/015664.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1165 /scratch/Teaching/cars/car_ims/013306.jpg Mercedes-Benz C-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1166 /scratch/Teaching/cars/car_ims/002824.jpg BMW M5 Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1167 /scratch/Teaching/cars/car_ims/004726.jpg Chevrolet Camaro Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1168 /scratch/Teaching/cars/car_ims/007118.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1169 /scratch/Teaching/cars/car_ims/014786.jpg Spyker C8 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1170 /scratch/Teaching/cars/car_ims/013280.jpg Mercedes-Benz C-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1171 /scratch/Teaching/cars/car_ims/010762.jpg Hyundai Santa Fe SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1172 /scratch/Teaching/cars/car_ims/015885.jpg Volvo C30 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1173 /scratch/Teaching/cars/car_ims/010409.jpg Honda Odyssey Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1174 /scratch/Teaching/cars/car_ims/012344.jpg Lamborghini Reventon Coupe 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1175 /scratch/Teaching/cars/car_ims/001648.jpg Audi S5 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1176 /scratch/Teaching/cars/car_ims/005555.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1177 /scratch/Teaching/cars/car_ims/006375.jpg Chrysler 300 SRT-8 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1178 /scratch/Teaching/cars/car_ims/015238.jpg Tesla Model S Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1179 /scratch/Teaching/cars/car_ims/004215.jpg Cadillac SRX SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1180 /scratch/Teaching/cars/car_ims/001301.jpg Audi 100 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1181 /scratch/Teaching/cars/car_ims/012479.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1182 /scratch/Teaching/cars/car_ims/011568.jpg Infiniti G Coupe IPL 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1183 /scratch/Teaching/cars/car_ims/010848.jpg Hyundai Tucson SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1184 /scratch/Teaching/cars/car_ims/014995.jpg Suzuki Kizashi Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1185 /scratch/Teaching/cars/car_ims/011881.jpg Jeep Patriot SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1186 /scratch/Teaching/cars/car_ims/011410.jpg Hyundai Elantra Touring Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1187 /scratch/Teaching/cars/car_ims/010039.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1188 /scratch/Teaching/cars/car_ims/013224.jpg Mercedes-Benz 300-Class Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1189 /scratch/Teaching/cars/car_ims/003997.jpg Buick Enclave SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1190 /scratch/Teaching/cars/car_ims/015619.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1191 /scratch/Teaching/cars/car_ims/004153.jpg Cadillac SRX SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1192 /scratch/Teaching/cars/car_ims/010746.jpg Hyundai Veloster Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1193 /scratch/Teaching/cars/car_ims/001152.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1194 /scratch/Teaching/cars/car_ims/013711.jpg Mitsubishi Lancer Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1195 /scratch/Teaching/cars/car_ims/012074.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1196 /scratch/Teaching/cars/car_ims/006280.jpg Chrysler Town and Country Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1197 /scratch/Teaching/cars/car_ims/005720.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1198 /scratch/Teaching/cars/car_ims/012588.jpg Lamborghini Diablo Coupe 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1199 /scratch/Teaching/cars/car_ims/005327.jpg Chevrolet Cobalt SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1200 /scratch/Teaching/cars/car_ims/014640.jpg Scion xD Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1201 /scratch/Teaching/cars/car_ims/004163.jpg Cadillac SRX SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1202 /scratch/Teaching/cars/car_ims/000148.jpg Acura RL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1203 /scratch/Teaching/cars/car_ims/006869.jpg Dodge Caliber Wagon 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1204 /scratch/Teaching/cars/car_ims/001861.jpg Audi S4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1205 /scratch/Teaching/cars/car_ims/008282.jpg Ferrari California Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1206 /scratch/Teaching/cars/car_ims/000155.jpg Acura TL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1207 /scratch/Teaching/cars/car_ims/004388.jpg Chevrolet Corvette Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1208 /scratch/Teaching/cars/car_ims/006706.jpg Daewoo Nubira Wagon 2002 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1209 /scratch/Teaching/cars/car_ims/005698.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1210 /scratch/Teaching/cars/car_ims/005502.jpg Chevrolet TrailBlazer SS 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1211 /scratch/Teaching/cars/car_ims/002873.jpg BMW M6 Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1212 /scratch/Teaching/cars/car_ims/000206.jpg Acura TL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1213 /scratch/Teaching/cars/car_ims/000956.jpg Audi RS 4 Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1214 /scratch/Teaching/cars/car_ims/005301.jpg Chevrolet Cobalt SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1215 /scratch/Teaching/cars/car_ims/009658.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1216 /scratch/Teaching/cars/car_ims/001969.jpg Audi S4 Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1217 /scratch/Teaching/cars/car_ims/003042.jpg BMW Z4 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1218 /scratch/Teaching/cars/car_ims/014243.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1219 /scratch/Teaching/cars/car_ims/005431.jpg Chevrolet Malibu Hybrid Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1220 /scratch/Teaching/cars/car_ims/002433.jpg BMW 3 Series Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1221 /scratch/Teaching/cars/car_ims/006663.jpg Daewoo Nubira Wagon 2002 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1222 /scratch/Teaching/cars/car_ims/007433.jpg Dodge Dakota Club Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1223 /scratch/Teaching/cars/car_ims/011964.jpg Jeep Wrangler SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1224 /scratch/Teaching/cars/car_ims/012047.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1225 /scratch/Teaching/cars/car_ims/008226.jpg Ferrari FF Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1226 /scratch/Teaching/cars/car_ims/001270.jpg Audi V8 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1227 /scratch/Teaching/cars/car_ims/004621.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1228 /scratch/Teaching/cars/car_ims/000674.jpg Aston Martin V8 Vantage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1229 /scratch/Teaching/cars/car_ims/000047.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1230 /scratch/Teaching/cars/car_ims/007641.jpg Dodge Durango SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1231 /scratch/Teaching/cars/car_ims/004064.jpg Cadillac CTS-V Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1232 /scratch/Teaching/cars/car_ims/011299.jpg Hyundai Sonata Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1233 /scratch/Teaching/cars/car_ims/006658.jpg Daewoo Nubira Wagon 2002 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1234 /scratch/Teaching/cars/car_ims/002584.jpg BMW X5 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1235 /scratch/Teaching/cars/car_ims/003177.jpg Bentley Continental Supersports Conv. Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1236 /scratch/Teaching/cars/car_ims/011552.jpg Infiniti G Coupe IPL 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1237 /scratch/Teaching/cars/car_ims/003529.jpg Bentley Continental Flying Spur Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1238 /scratch/Teaching/cars/car_ims/016015.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1239 /scratch/Teaching/cars/car_ims/009160.jpg Ford GT Coupe 2006 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1240 /scratch/Teaching/cars/car_ims/007978.jpg Eagle Talon Hatchback 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1241 /scratch/Teaching/cars/car_ims/004731.jpg Chevrolet Camaro Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1242 /scratch/Teaching/cars/car_ims/004773.jpg Chevrolet Camaro Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1243 /scratch/Teaching/cars/car_ims/008087.jpg FIAT 500 Abarth 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1244 /scratch/Teaching/cars/car_ims/004574.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1245 /scratch/Teaching/cars/car_ims/008917.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1246 /scratch/Teaching/cars/car_ims/010032.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1247 /scratch/Teaching/cars/car_ims/009014.jpg Ford Edge SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1248 /scratch/Teaching/cars/car_ims/002645.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1249 /scratch/Teaching/cars/car_ims/008094.jpg FIAT 500 Abarth 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1250 /scratch/Teaching/cars/car_ims/009876.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1251 /scratch/Teaching/cars/car_ims/003933.jpg Buick Verano Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1252 /scratch/Teaching/cars/car_ims/001216.jpg Audi V8 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1253 /scratch/Teaching/cars/car_ims/006426.jpg Chrysler 300 SRT-8 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1254 /scratch/Teaching/cars/car_ims/003740.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1255 /scratch/Teaching/cars/car_ims/000430.jpg Acura Integra Type R 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1256 /scratch/Teaching/cars/car_ims/014909.jpg Suzuki Aerio Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1257 /scratch/Teaching/cars/car_ims/014372.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1258 /scratch/Teaching/cars/car_ims/001836.jpg Audi S4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1259 /scratch/Teaching/cars/car_ims/010997.jpg Hyundai Veracruz SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1260 /scratch/Teaching/cars/car_ims/004286.jpg Cadillac Escalade EXT Crew Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1261 /scratch/Teaching/cars/car_ims/007124.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1262 /scratch/Teaching/cars/car_ims/007215.jpg Dodge Journey SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1263 /scratch/Teaching/cars/car_ims/010212.jpg HUMMER H3T Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1264 /scratch/Teaching/cars/car_ims/001513.jpg Audi TT Hatchback 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1265 /scratch/Teaching/cars/car_ims/001712.jpg Audi S5 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1266 /scratch/Teaching/cars/car_ims/002494.jpg BMW 6 Series Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1267 /scratch/Teaching/cars/car_ims/008811.jpg Ford Freestar Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1268 /scratch/Teaching/cars/car_ims/010732.jpg Hyundai Veloster Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1269 /scratch/Teaching/cars/car_ims/012382.jpg Lamborghini Aventador Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1270 /scratch/Teaching/cars/car_ims/010739.jpg Hyundai Veloster Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1271 /scratch/Teaching/cars/car_ims/008547.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1272 /scratch/Teaching/cars/car_ims/003323.jpg Bentley Mulsanne Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1273 /scratch/Teaching/cars/car_ims/016077.jpg Volvo XC90 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1274 /scratch/Teaching/cars/car_ims/000085.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1275 /scratch/Teaching/cars/car_ims/005924.jpg Chevrolet Malibu Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1276 /scratch/Teaching/cars/car_ims/003140.jpg Bentley Continental Supersports Conv. Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1277 /scratch/Teaching/cars/car_ims/002722.jpg BMW M3 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1278 /scratch/Teaching/cars/car_ims/013259.jpg Mercedes-Benz C-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1279 /scratch/Teaching/cars/car_ims/011274.jpg Hyundai Genesis Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1280 /scratch/Teaching/cars/car_ims/008990.jpg Ford Edge SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1281 /scratch/Teaching/cars/car_ims/003079.jpg BMW Z4 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1282 /scratch/Teaching/cars/car_ims/006904.jpg Dodge Caravan Minivan 1997 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1283 /scratch/Teaching/cars/car_ims/012720.jpg Land Rover LR2 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1284 /scratch/Teaching/cars/car_ims/012469.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1285 /scratch/Teaching/cars/car_ims/006501.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1286 /scratch/Teaching/cars/car_ims/009232.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1287 /scratch/Teaching/cars/car_ims/001116.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1288 /scratch/Teaching/cars/car_ims/012692.jpg Land Rover LR2 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1289 /scratch/Teaching/cars/car_ims/002661.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1290 /scratch/Teaching/cars/car_ims/014596.jpg Scion xD Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1291 /scratch/Teaching/cars/car_ims/008508.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1292 /scratch/Teaching/cars/car_ims/004323.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1293 /scratch/Teaching/cars/car_ims/014085.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1294 /scratch/Teaching/cars/car_ims/010191.jpg HUMMER H3T Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1295 /scratch/Teaching/cars/car_ims/009119.jpg Ford GT Coupe 2006 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1296 /scratch/Teaching/cars/car_ims/002119.jpg BMW ActiveHybrid 5 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1297 /scratch/Teaching/cars/car_ims/001378.jpg Audi 100 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1298 /scratch/Teaching/cars/car_ims/014277.jpg Ram C/V Cargo Van Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1299 /scratch/Teaching/cars/car_ims/001048.jpg Audi TTS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1300 /scratch/Teaching/cars/car_ims/011379.jpg Hyundai Elantra Touring Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1301 /scratch/Teaching/cars/car_ims/000289.jpg Acura TL Type-S 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1302 /scratch/Teaching/cars/car_ims/008798.jpg Ford Freestar Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1303 /scratch/Teaching/cars/car_ims/012540.jpg Lamborghini Diablo Coupe 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1304 /scratch/Teaching/cars/car_ims/007703.jpg Dodge Durango SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1305 /scratch/Teaching/cars/car_ims/012505.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1306 /scratch/Teaching/cars/car_ims/015699.jpg Volkswagen Golf Hatchback 1991 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1307 /scratch/Teaching/cars/car_ims/001763.jpg Audi S5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1308 /scratch/Teaching/cars/car_ims/013750.jpg Mitsubishi Lancer Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1309 /scratch/Teaching/cars/car_ims/002060.jpg BMW ActiveHybrid 5 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1310 /scratch/Teaching/cars/car_ims/008410.jpg Ferrari 458 Italia Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1311 /scratch/Teaching/cars/car_ims/009147.jpg Ford GT Coupe 2006 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1312 /scratch/Teaching/cars/car_ims/011104.jpg Hyundai Elantra Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1313 /scratch/Teaching/cars/car_ims/000769.jpg Aston Martin Virage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1314 /scratch/Teaching/cars/car_ims/014094.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1315 /scratch/Teaching/cars/car_ims/011535.jpg Hyundai Azera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1316 /scratch/Teaching/cars/car_ims/015564.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1317 /scratch/Teaching/cars/car_ims/014217.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1318 /scratch/Teaching/cars/car_ims/008660.jpg Ford F-450 Super Duty Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1319 /scratch/Teaching/cars/car_ims/011270.jpg Hyundai Genesis Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1320 /scratch/Teaching/cars/car_ims/013974.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1321 /scratch/Teaching/cars/car_ims/007285.jpg Dodge Journey SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1322 /scratch/Teaching/cars/car_ims/005881.jpg Chevrolet Malibu Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1323 /scratch/Teaching/cars/car_ims/002050.jpg Audi TT RS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1324 /scratch/Teaching/cars/car_ims/000887.jpg Audi RS 4 Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1325 /scratch/Teaching/cars/car_ims/014762.jpg Spyker C8 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1326 /scratch/Teaching/cars/car_ims/000494.jpg Acura ZDX Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1327 /scratch/Teaching/cars/car_ims/006450.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1328 /scratch/Teaching/cars/car_ims/010301.jpg HUMMER H2 SUT Crew Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1329 /scratch/Teaching/cars/car_ims/013990.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1330 /scratch/Teaching/cars/car_ims/004935.jpg Chevrolet Impala Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1331 /scratch/Teaching/cars/car_ims/013528.jpg Mercedes-Benz S-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1332 /scratch/Teaching/cars/car_ims/007439.jpg Dodge Dakota Club Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1333 /scratch/Teaching/cars/car_ims/008494.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1334 /scratch/Teaching/cars/car_ims/008964.jpg Ford Edge SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1335 /scratch/Teaching/cars/car_ims/000062.jpg AM General Hummer SUV 2000 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1336 /scratch/Teaching/cars/car_ims/003985.jpg Buick Enclave SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1337 /scratch/Teaching/cars/car_ims/009512.jpg Ford E-Series Wagon Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1338 /scratch/Teaching/cars/car_ims/015320.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1339 /scratch/Teaching/cars/car_ims/002971.jpg BMW X3 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1340 /scratch/Teaching/cars/car_ims/003780.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1341 /scratch/Teaching/cars/car_ims/011908.jpg Jeep Patriot SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1342 /scratch/Teaching/cars/car_ims/009296.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1343 /scratch/Teaching/cars/car_ims/014367.jpg Rolls-Royce Phantom Drophead Coupe Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1344 /scratch/Teaching/cars/car_ims/012525.jpg Lamborghini Diablo Coupe 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1345 /scratch/Teaching/cars/car_ims/003869.jpg Buick Rainier SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1346 /scratch/Teaching/cars/car_ims/012241.jpg Jeep Compass SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1347 /scratch/Teaching/cars/car_ims/003232.jpg Bentley Arnage Sedan 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1348 /scratch/Teaching/cars/car_ims/006218.jpg Chrysler Sebring Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1349 /scratch/Teaching/cars/car_ims/011792.jpg Jaguar XK XKR 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1350 /scratch/Teaching/cars/car_ims/004319.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1351 /scratch/Teaching/cars/car_ims/012092.jpg Jeep Liberty SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1352 /scratch/Teaching/cars/car_ims/015334.jpg Toyota Camry Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1353 /scratch/Teaching/cars/car_ims/010831.jpg Hyundai Santa Fe SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1354 /scratch/Teaching/cars/car_ims/009879.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1355 /scratch/Teaching/cars/car_ims/014688.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1356 /scratch/Teaching/cars/car_ims/008883.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1357 /scratch/Teaching/cars/car_ims/003755.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1358 /scratch/Teaching/cars/car_ims/013132.jpg McLaren MP4-12C Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1359 /scratch/Teaching/cars/car_ims/005564.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1360 /scratch/Teaching/cars/car_ims/015454.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1361 /scratch/Teaching/cars/car_ims/006504.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1362 /scratch/Teaching/cars/car_ims/004983.jpg Chevrolet Tahoe Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1363 /scratch/Teaching/cars/car_ims/012376.jpg Lamborghini Aventador Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1364 /scratch/Teaching/cars/car_ims/014072.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1365 /scratch/Teaching/cars/car_ims/014702.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1366 /scratch/Teaching/cars/car_ims/002465.jpg BMW 6 Series Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1367 /scratch/Teaching/cars/car_ims/003962.jpg Buick Verano Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1368 /scratch/Teaching/cars/car_ims/009088.jpg Ford Ranger SuperCab 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1369 /scratch/Teaching/cars/car_ims/011008.jpg Hyundai Veracruz SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1370 /scratch/Teaching/cars/car_ims/000220.jpg Acura TL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1371 /scratch/Teaching/cars/car_ims/002755.jpg BMW M3 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1372 /scratch/Teaching/cars/car_ims/008438.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1373 /scratch/Teaching/cars/car_ims/014284.jpg Ram C/V Cargo Van Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1374 /scratch/Teaching/cars/car_ims/015029.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1375 /scratch/Teaching/cars/car_ims/002875.jpg BMW M6 Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1376 /scratch/Teaching/cars/car_ims/010491.jpg Honda Odyssey Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1377 /scratch/Teaching/cars/car_ims/001402.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1378 /scratch/Teaching/cars/car_ims/012673.jpg Land Rover Range Rover SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1379 /scratch/Teaching/cars/car_ims/009875.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1380 /scratch/Teaching/cars/car_ims/001290.jpg Audi V8 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1381 /scratch/Teaching/cars/car_ims/002698.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1382 /scratch/Teaching/cars/car_ims/000107.jpg Acura RL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1383 /scratch/Teaching/cars/car_ims/002390.jpg BMW 3 Series Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1384 /scratch/Teaching/cars/car_ims/009104.jpg Ford Ranger SuperCab 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1385 /scratch/Teaching/cars/car_ims/015276.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1386 /scratch/Teaching/cars/car_ims/005523.jpg Chevrolet Silverado 2500HD Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1387 /scratch/Teaching/cars/car_ims/011279.jpg Hyundai Genesis Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1388 /scratch/Teaching/cars/car_ims/004537.jpg Chevrolet Corvette ZR1 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1389 /scratch/Teaching/cars/car_ims/003789.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1390 /scratch/Teaching/cars/car_ims/014512.jpg Rolls-Royce Phantom Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1391 /scratch/Teaching/cars/car_ims/015459.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1392 /scratch/Teaching/cars/car_ims/008952.jpg Ford Edge SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1393 /scratch/Teaching/cars/car_ims/011166.jpg Hyundai Accent Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1394 /scratch/Teaching/cars/car_ims/007727.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1395 /scratch/Teaching/cars/car_ims/005110.jpg Chevrolet Sonic Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1396 /scratch/Teaching/cars/car_ims/012339.jpg Lamborghini Reventon Coupe 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1397 /scratch/Teaching/cars/car_ims/006699.jpg Daewoo Nubira Wagon 2002 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1398 /scratch/Teaching/cars/car_ims/008420.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1399 /scratch/Teaching/cars/car_ims/010390.jpg Honda Odyssey Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1400 /scratch/Teaching/cars/car_ims/014792.jpg Spyker C8 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1401 /scratch/Teaching/cars/car_ims/000454.jpg Acura Integra Type R 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1402 /scratch/Teaching/cars/car_ims/010181.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1403 /scratch/Teaching/cars/car_ims/005233.jpg Chevrolet Avalanche Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1404 /scratch/Teaching/cars/car_ims/015663.jpg Volkswagen Golf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1405 /scratch/Teaching/cars/car_ims/008991.jpg Ford Edge SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1406 /scratch/Teaching/cars/car_ims/001612.jpg Audi S6 Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1407 /scratch/Teaching/cars/car_ims/001454.jpg Audi 100 Wagon 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1408 /scratch/Teaching/cars/car_ims/010958.jpg Hyundai Veracruz SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1409 /scratch/Teaching/cars/car_ims/001015.jpg Audi A5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1410 /scratch/Teaching/cars/car_ims/007609.jpg Dodge Challenger SRT8 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1411 /scratch/Teaching/cars/car_ims/014554.jpg Rolls-Royce Phantom Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1412 /scratch/Teaching/cars/car_ims/015356.jpg Toyota Camry Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1413 /scratch/Teaching/cars/car_ims/011019.jpg Hyundai Sonata Hybrid Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1414 /scratch/Teaching/cars/car_ims/012852.jpg Lincoln Town Car Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1415 /scratch/Teaching/cars/car_ims/005882.jpg Chevrolet Malibu Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1416 /scratch/Teaching/cars/car_ims/002331.jpg BMW 3 Series Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1417 /scratch/Teaching/cars/car_ims/008134.jpg FIAT 500 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1418 /scratch/Teaching/cars/car_ims/012487.jpg Lamborghini Gallardo LP 570-4 Superleggera 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1419 /scratch/Teaching/cars/car_ims/005011.jpg Chevrolet Tahoe Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1420 /scratch/Teaching/cars/car_ims/004372.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1421 /scratch/Teaching/cars/car_ims/000857.jpg Aston Martin Virage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1422 /scratch/Teaching/cars/car_ims/001844.jpg Audi S4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1423 /scratch/Teaching/cars/car_ims/009420.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1424 /scratch/Teaching/cars/car_ims/003218.jpg Bentley Arnage Sedan 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1425 /scratch/Teaching/cars/car_ims/009866.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1426 /scratch/Teaching/cars/car_ims/009886.jpg GMC Acadia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1427 /scratch/Teaching/cars/car_ims/003624.jpg Bugatti Veyron 16.4 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1428 /scratch/Teaching/cars/car_ims/008311.jpg Ferrari California Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1429 /scratch/Teaching/cars/car_ims/014188.jpg Porsche Panamera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1430 /scratch/Teaching/cars/car_ims/008213.jpg Ferrari FF Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1431 /scratch/Teaching/cars/car_ims/011930.jpg Jeep Patriot SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1432 /scratch/Teaching/cars/car_ims/006592.jpg Chrysler PT Cruiser Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1433 /scratch/Teaching/cars/car_ims/002670.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1434 /scratch/Teaching/cars/car_ims/012748.jpg Land Rover LR2 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1435 /scratch/Teaching/cars/car_ims/014923.jpg Suzuki Kizashi Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1436 /scratch/Teaching/cars/car_ims/004479.jpg Chevrolet Corvette ZR1 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1437 /scratch/Teaching/cars/car_ims/011339.jpg Hyundai Sonata Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1438 /scratch/Teaching/cars/car_ims/012004.jpg Jeep Wrangler SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1439 /scratch/Teaching/cars/car_ims/015148.jpg Suzuki SX4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1440 /scratch/Teaching/cars/car_ims/002682.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1441 /scratch/Teaching/cars/car_ims/012905.jpg MINI Cooper Roadster Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1442 /scratch/Teaching/cars/car_ims/009970.jpg GMC Canyon Extended Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1443 /scratch/Teaching/cars/car_ims/006480.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1444 /scratch/Teaching/cars/car_ims/000325.jpg Acura TSX Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1445 /scratch/Teaching/cars/car_ims/000405.jpg Acura Integra Type R 2001 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1446 /scratch/Teaching/cars/car_ims/014665.jpg Scion xD Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1447 /scratch/Teaching/cars/car_ims/006913.jpg Dodge Caravan Minivan 1997 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1448 /scratch/Teaching/cars/car_ims/013848.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1449 /scratch/Teaching/cars/car_ims/012668.jpg Land Rover Range Rover SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1450 /scratch/Teaching/cars/car_ims/015840.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1451 /scratch/Teaching/cars/car_ims/008207.jpg Ferrari FF Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1452 /scratch/Teaching/cars/car_ims/009360.jpg Ford F-150 Regular Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1453 /scratch/Teaching/cars/car_ims/003473.jpg Bentley Continental GT Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1454 /scratch/Teaching/cars/car_ims/003444.jpg Bentley Continental GT Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1455 /scratch/Teaching/cars/car_ims/004542.jpg Chevrolet Corvette ZR1 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1456 /scratch/Teaching/cars/car_ims/013201.jpg Mercedes-Benz 300-Class Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1457 /scratch/Teaching/cars/car_ims/014143.jpg Plymouth Neon Coupe 1999 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1458 /scratch/Teaching/cars/car_ims/016125.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1459 /scratch/Teaching/cars/car_ims/015945.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1460 /scratch/Teaching/cars/car_ims/011783.jpg Jaguar XK XKR 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1461 /scratch/Teaching/cars/car_ims/007800.jpg Dodge Charger Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1462 /scratch/Teaching/cars/car_ims/002900.jpg BMW M6 Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1463 /scratch/Teaching/cars/car_ims/007606.jpg Dodge Challenger SRT8 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1464 /scratch/Teaching/cars/car_ims/012979.jpg Maybach Landaulet Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1465 /scratch/Teaching/cars/car_ims/009732.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1466 /scratch/Teaching/cars/car_ims/011633.jpg Infiniti QX56 SUV 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1467 /scratch/Teaching/cars/car_ims/013761.jpg Nissan Leaf Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1468 /scratch/Teaching/cars/car_ims/004228.jpg Cadillac Escalade EXT Crew Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1469 /scratch/Teaching/cars/car_ims/011529.jpg Hyundai Azera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1470 /scratch/Teaching/cars/car_ims/011960.jpg Jeep Wrangler SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1471 /scratch/Teaching/cars/car_ims/015080.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1472 /scratch/Teaching/cars/car_ims/015270.jpg Toyota Sequoia SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1473 /scratch/Teaching/cars/car_ims/006000.jpg Chevrolet Silverado 1500 Extended Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1474 /scratch/Teaching/cars/car_ims/006961.jpg Dodge Caravan Minivan 1997 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1475 /scratch/Teaching/cars/car_ims/013612.jpg Mercedes-Benz Sprinter Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1476 /scratch/Teaching/cars/car_ims/010690.jpg Hyundai Veloster Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1477 /scratch/Teaching/cars/car_ims/009412.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1478 /scratch/Teaching/cars/car_ims/015218.jpg Tesla Model S Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1479 /scratch/Teaching/cars/car_ims/008775.jpg Ford Freestar Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1480 /scratch/Teaching/cars/car_ims/015101.jpg Suzuki SX4 Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1481 /scratch/Teaching/cars/car_ims/000576.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1482 /scratch/Teaching/cars/car_ims/012289.jpg Lamborghini Reventon Coupe 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1483 /scratch/Teaching/cars/car_ims/009430.jpg Ford Focus Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1484 /scratch/Teaching/cars/car_ims/016136.jpg smart fortwo Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1485 /scratch/Teaching/cars/car_ims/011715.jpg Isuzu Ascender SUV 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1486 /scratch/Teaching/cars/car_ims/014341.jpg Ram C/V Cargo Van Minivan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1487 /scratch/Teaching/cars/car_ims/011329.jpg Hyundai Sonata Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1488 /scratch/Teaching/cars/car_ims/001727.jpg Audi S5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1489 /scratch/Teaching/cars/car_ims/009223.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1490 /scratch/Teaching/cars/car_ims/011174.jpg Hyundai Accent Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1491 /scratch/Teaching/cars/car_ims/006627.jpg Daewoo Nubira Wagon 2002 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1492 /scratch/Teaching/cars/car_ims/013292.jpg Mercedes-Benz C-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1493 /scratch/Teaching/cars/car_ims/008722.jpg Ford Mustang Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1494 /scratch/Teaching/cars/car_ims/004986.jpg Chevrolet Tahoe Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1495 /scratch/Teaching/cars/car_ims/007960.jpg Dodge Charger SRT-8 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1496 /scratch/Teaching/cars/car_ims/016023.jpg Volvo XC90 SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1497 /scratch/Teaching/cars/car_ims/011732.jpg Isuzu Ascender SUV 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1498 /scratch/Teaching/cars/car_ims/006880.jpg Dodge Caravan Minivan 1997 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1499 /scratch/Teaching/cars/car_ims/010117.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1500 /scratch/Teaching/cars/car_ims/015476.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1501 /scratch/Teaching/cars/car_ims/000812.jpg Aston Martin Virage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1502 /scratch/Teaching/cars/car_ims/006900.jpg Dodge Caravan Minivan 1997 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1503 /scratch/Teaching/cars/car_ims/003161.jpg Bentley Continental Supersports Conv. Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1504 /scratch/Teaching/cars/car_ims/006498.jpg Chrysler Crossfire Convertible 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1505 /scratch/Teaching/cars/car_ims/013583.jpg Mercedes-Benz Sprinter Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1506 /scratch/Teaching/cars/car_ims/009838.jpg GMC Yukon Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1507 /scratch/Teaching/cars/car_ims/015092.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1508 /scratch/Teaching/cars/car_ims/007177.jpg Dodge Sprinter Cargo Van 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1509 /scratch/Teaching/cars/car_ims/007289.jpg Dodge Journey SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1510 /scratch/Teaching/cars/car_ims/007647.jpg Dodge Durango SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1511 /scratch/Teaching/cars/car_ims/015449.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1512 /scratch/Teaching/cars/car_ims/004145.jpg Cadillac SRX SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1513 /scratch/Teaching/cars/car_ims/015083.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1514 /scratch/Teaching/cars/car_ims/001774.jpg Audi S5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1515 /scratch/Teaching/cars/car_ims/010206.jpg HUMMER H3T Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1516 /scratch/Teaching/cars/car_ims/008923.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1517 /scratch/Teaching/cars/car_ims/002014.jpg Audi TT RS Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1518 /scratch/Teaching/cars/car_ims/011188.jpg Hyundai Accent Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1519 /scratch/Teaching/cars/car_ims/015046.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1520 /scratch/Teaching/cars/car_ims/008104.jpg FIAT 500 Abarth 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1521 /scratch/Teaching/cars/car_ims/010880.jpg Hyundai Tucson SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1522 /scratch/Teaching/cars/car_ims/014073.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1523 /scratch/Teaching/cars/car_ims/000739.jpg Aston Martin V8 Vantage Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1524 /scratch/Teaching/cars/car_ims/007972.jpg Eagle Talon Hatchback 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1525 /scratch/Teaching/cars/car_ims/001931.jpg Audi S4 Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1526 /scratch/Teaching/cars/car_ims/011269.jpg Hyundai Genesis Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1527 /scratch/Teaching/cars/car_ims/014691.jpg Spyker C8 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1528 /scratch/Teaching/cars/car_ims/008526.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1529 /scratch/Teaching/cars/car_ims/014456.jpg Rolls-Royce Ghost Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1530 /scratch/Teaching/cars/car_ims/001760.jpg Audi S5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1531 /scratch/Teaching/cars/car_ims/011603.jpg Infiniti G Coupe IPL 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1532 /scratch/Teaching/cars/car_ims/000210.jpg Acura TL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1533 /scratch/Teaching/cars/car_ims/015090.jpg Suzuki SX4 Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1534 /scratch/Teaching/cars/car_ims/005019.jpg Chevrolet Tahoe Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1535 /scratch/Teaching/cars/car_ims/007715.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1536 /scratch/Teaching/cars/car_ims/005418.jpg Chevrolet Malibu Hybrid Sedan 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1537 /scratch/Teaching/cars/car_ims/012690.jpg Land Rover Range Rover SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1538 /scratch/Teaching/cars/car_ims/007134.jpg Dodge Ram Pickup 3500 Quad Cab 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1539 /scratch/Teaching/cars/car_ims/013235.jpg Mercedes-Benz 300-Class Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1540 /scratch/Teaching/cars/car_ims/008464.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1541 /scratch/Teaching/cars/car_ims/012425.jpg Lamborghini Aventador Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1542 /scratch/Teaching/cars/car_ims/006779.jpg Dodge Caliber Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1543 /scratch/Teaching/cars/car_ims/009242.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1544 /scratch/Teaching/cars/car_ims/000614.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1545 /scratch/Teaching/cars/car_ims/010172.jpg Geo Metro Convertible 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1546 /scratch/Teaching/cars/car_ims/002685.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1547 /scratch/Teaching/cars/car_ims/006255.jpg Chrysler Sebring Convertible 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1548 /scratch/Teaching/cars/car_ims/010701.jpg Hyundai Veloster Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1549 /scratch/Teaching/cars/car_ims/008937.jpg Ford Expedition EL SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1550 /scratch/Teaching/cars/car_ims/011221.jpg Hyundai Genesis Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1551 /scratch/Teaching/cars/car_ims/000611.jpg Aston Martin V8 Vantage Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1552 /scratch/Teaching/cars/car_ims/009229.jpg Ford F-150 Regular Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1553 /scratch/Teaching/cars/car_ims/013895.jpg Nissan NV Passenger Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1554 /scratch/Teaching/cars/car_ims/001569.jpg Audi S6 Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1555 /scratch/Teaching/cars/car_ims/006173.jpg Chrysler Aspen SUV 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1556 /scratch/Teaching/cars/car_ims/001960.jpg Audi S4 Sedan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1557 /scratch/Teaching/cars/car_ims/013514.jpg Mercedes-Benz S-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1558 /scratch/Teaching/cars/car_ims/003636.jpg Bugatti Veyron 16.4 Convertible 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1559 /scratch/Teaching/cars/car_ims/013698.jpg Mitsubishi Lancer Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1560 /scratch/Teaching/cars/car_ims/009760.jpg GMC Savana Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1561 /scratch/Teaching/cars/car_ims/008162.jpg FIAT 500 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1562 /scratch/Teaching/cars/car_ims/014001.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1563 /scratch/Teaching/cars/car_ims/011483.jpg Hyundai Azera Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1564 /scratch/Teaching/cars/car_ims/011017.jpg Hyundai Sonata Hybrid Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1565 /scratch/Teaching/cars/car_ims/012165.jpg Jeep Grand Cherokee SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1566 /scratch/Teaching/cars/car_ims/001027.jpg Audi A5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1567 /scratch/Teaching/cars/car_ims/001665.jpg Audi S5 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1568 /scratch/Teaching/cars/car_ims/005675.jpg Chevrolet Silverado 1500 Classic Extended Cab 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1569 /scratch/Teaching/cars/car_ims/015576.jpg Toyota 4Runner SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1570 /scratch/Teaching/cars/car_ims/013128.jpg McLaren MP4-12C Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1571 /scratch/Teaching/cars/car_ims/007383.jpg Dodge Dakota Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1572 /scratch/Teaching/cars/car_ims/006760.jpg Dodge Caliber Wagon 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1573 /scratch/Teaching/cars/car_ims/005733.jpg Chevrolet Express Van 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1574 /scratch/Teaching/cars/car_ims/003803.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1575 /scratch/Teaching/cars/car_ims/008956.jpg Ford Edge SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1576 /scratch/Teaching/cars/car_ims/014087.jpg Nissan 240SX Coupe 1998 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1577 /scratch/Teaching/cars/car_ims/008802.jpg Ford Freestar Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1578 /scratch/Teaching/cars/car_ims/013409.jpg Mercedes-Benz E-Class Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1579 /scratch/Teaching/cars/car_ims/004847.jpg Chevrolet HHR SS 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1580 /scratch/Teaching/cars/car_ims/003903.jpg Buick Verano Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1581 /scratch/Teaching/cars/car_ims/009008.jpg Ford Edge SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1582 /scratch/Teaching/cars/car_ims/001253.jpg Audi V8 Sedan 1994 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1583 /scratch/Teaching/cars/car_ims/008715.jpg Ford Mustang Convertible 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1584 /scratch/Teaching/cars/car_ims/004985.jpg Chevrolet Tahoe Hybrid SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1585 /scratch/Teaching/cars/car_ims/015428.jpg Toyota Corolla Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1586 /scratch/Teaching/cars/car_ims/001193.jpg Audi R8 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1587 /scratch/Teaching/cars/car_ims/007763.jpg Dodge Durango SUV 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1588 /scratch/Teaching/cars/car_ims/010777.jpg Hyundai Santa Fe SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1589 /scratch/Teaching/cars/car_ims/001538.jpg Audi TT Hatchback 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1590 /scratch/Teaching/cars/car_ims/013652.jpg Mercedes-Benz Sprinter Van 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1591 /scratch/Teaching/cars/car_ims/008561.jpg Fisker Karma Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1592 /scratch/Teaching/cars/car_ims/014119.jpg Plymouth Neon Coupe 1999 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1593 /scratch/Teaching/cars/car_ims/009661.jpg GMC Terrain SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1594 /scratch/Teaching/cars/car_ims/003797.jpg Buick Regal GS 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1595 /scratch/Teaching/cars/car_ims/004624.jpg Chevrolet Corvette Ron Fellows Edition Z06 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1596 /scratch/Teaching/cars/car_ims/012206.jpg Jeep Compass SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1597 /scratch/Teaching/cars/car_ims/000959.jpg Audi A5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1598 /scratch/Teaching/cars/car_ims/001742.jpg Audi S5 Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1599 /scratch/Teaching/cars/car_ims/010453.jpg Honda Odyssey Minivan 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1600 /scratch/Teaching/cars/car_ims/014991.jpg Suzuki Kizashi Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1601 /scratch/Teaching/cars/car_ims/006866.jpg Dodge Caliber Wagon 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1602 /scratch/Teaching/cars/car_ims/002615.jpg BMW X6 SUV 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1603 /scratch/Teaching/cars/car_ims/014002.jpg Nissan Juke Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1604 /scratch/Teaching/cars/car_ims/010528.jpg Honda Accord Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1605 /scratch/Teaching/cars/car_ims/015780.jpg Volkswagen Beetle Hatchback 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1606 /scratch/Teaching/cars/car_ims/000119.jpg Acura RL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1607 /scratch/Teaching/cars/car_ims/000214.jpg Acura TL Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1608 /scratch/Teaching/cars/car_ims/005466.jpg Chevrolet TrailBlazer SS 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1609 /scratch/Teaching/cars/car_ims/011729.jpg Isuzu Ascender SUV 2008 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1610 /scratch/Teaching/cars/car_ims/015370.jpg Toyota Camry Sedan 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1611 /scratch/Teaching/cars/car_ims/011835.jpg Jaguar XK XKR 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1612 /scratch/Teaching/cars/car_ims/003714.jpg Bugatti Veyron 16.4 Coupe 2009 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1613 /scratch/Teaching/cars/car_ims/008459.jpg Ferrari 458 Italia Coupe 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1614 /scratch/Teaching/cars/car_ims/015939.jpg Volvo 240 Sedan 1993 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1615 /scratch/Teaching/cars/car_ims/007031.jpg Dodge Ram Pickup 3500 Crew Cab 2010 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1616 /scratch/Teaching/cars/car_ims/005796.jpg Chevrolet Monte Carlo Coupe 2007 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1617 /scratch/Teaching/cars/car_ims/012842.jpg Lincoln Town Car Sedan 2011 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1618 /scratch/Teaching/cars/car_ims/004377.jpg Chevrolet Silverado 1500 Hybrid Crew Cab 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% +1619 /scratch/Teaching/cars/car_ims/003059.jpg BMW Z4 Convertible 2012 GMC Savana Van 2012 0.88% Chrysler 300 SRT-8 2010 0.65% Chrysler PT Cruiser Convertible 2008 0.61% HUMMER H2 SUT Crew Cab 2009 0.61% Bugatti Veyron 16.4 Coupe 2009 0.6% \ No newline at end of file diff --git a/cars/architecture-investigations/fc/4-layers/256/small.png b/cars/architecture-investigations/fc/4-layers/256/small.png new file mode 100644 index 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    196 rows × 196 columns

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Hummer SUV 2000 0 ... \n", + "Acura RL Sedan 2012 0 ... \n", + "Acura TL Sedan 2012 0 ... \n", + "Acura TL Type-S 2008 0 ... \n", + "Acura TSX Sedan 2012 0 ... \n", + "... ... ... \n", + "Volkswagen Beetle Hatchback 2012 0 ... \n", + "Volvo C30 Hatchback 2012 0 ... \n", + "Volvo 240 Sedan 1993 0 ... \n", + "Volvo XC90 SUV 2007 0 ... \n", + "smart fortwo Convertible 2012 0 ... \n", + "\n", + " Toyota Camry Sedan 2012 \\\n", + "AM General Hummer SUV 2000 0 \n", + "Acura RL Sedan 2012 0 \n", + "Acura TL Sedan 2012 0 \n", + "Acura TL Type-S 2008 0 \n", + "Acura TSX Sedan 2012 0 \n", + "... ... \n", + "Volkswagen Beetle Hatchback 2012 0 \n", + "Volvo C30 Hatchback 2012 0 \n", + "Volvo 240 Sedan 1993 0 \n", + "Volvo XC90 SUV 2007 0 \n", + "smart fortwo Convertible 2012 0 \n", + "\n", + " Toyota Corolla Sedan 2012 \\\n", + "AM General Hummer SUV 2000 0 \n", + "Acura RL Sedan 2012 0 \n", + "Acura TL Sedan 2012 0 \n", + "Acura TL Type-S 2008 0 \n", + "Acura TSX Sedan 2012 0 \n", + "... ... \n", 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Volkswagen Golf Hatchback 1991 \\\n", + "AM General Hummer SUV 2000 0 \n", + "Acura RL Sedan 2012 0 \n", + "Acura TL Sedan 2012 0 \n", + "Acura TL Type-S 2008 0 \n", + "Acura TSX Sedan 2012 0 \n", + "... ... \n", + "Volkswagen Beetle Hatchback 2012 0 \n", + "Volvo C30 Hatchback 2012 0 \n", + "Volvo 240 Sedan 1993 0 \n", + "Volvo XC90 SUV 2007 0 \n", + "smart fortwo Convertible 2012 0 \n", + "\n", + " Volkswagen Beetle Hatchback 2012 \\\n", + "AM General Hummer SUV 2000 0 \n", + "Acura RL Sedan 2012 0 \n", + "Acura TL Sedan 2012 0 \n", + "Acura TL Type-S 2008 0 \n", + "Acura TSX Sedan 2012 0 \n", + "... ... \n", + "Volkswagen Beetle Hatchback 2012 5 \n", + "Volvo C30 Hatchback 2012 1 \n", + "Volvo 240 Sedan 1993 0 \n", + "Volvo XC90 SUV 2007 0 \n", + "smart fortwo Convertible 2012 0 \n", + "\n", + " Volvo C30 Hatchback 2012 \\\n", + "AM General Hummer SUV 2000 0 \n", + "Acura RL Sedan 2012 0 \n", + "Acura TL Sedan 2012 0 \n", + "Acura TL Type-S 2008 0 \n", + "Acura TSX Sedan 2012 0 \n", + "... ... \n", + "Volkswagen Beetle Hatchback 2012 0 \n", + "Volvo C30 Hatchback 2012 4 \n", + "Volvo 240 Sedan 1993 0 \n", + "Volvo XC90 SUV 2007 0 \n", + "smart fortwo Convertible 2012 0 \n", + "\n", + " Volvo 240 Sedan 1993 Volvo XC90 SUV 2007 \\\n", + "AM General Hummer SUV 2000 0 0 \n", + "Acura RL Sedan 2012 0 0 \n", + "Acura TL Sedan 2012 0 0 \n", + "Acura TL Type-S 2008 0 0 \n", + "Acura TSX Sedan 2012 0 0 \n", + "... ... ... \n", + "Volkswagen Beetle Hatchback 2012 0 0 \n", + "Volvo C30 Hatchback 2012 0 0 \n", + "Volvo 240 Sedan 1993 10 0 \n", + "Volvo XC90 SUV 2007 0 7 \n", + "smart fortwo Convertible 2012 0 0 \n", + "\n", + " smart fortwo Convertible 2012 \n", + "AM General Hummer SUV 2000 1 \n", + "Acura RL Sedan 2012 0 \n", + "Acura TL Sedan 2012 0 \n", + "Acura TL Type-S 2008 0 \n", + "Acura TSX Sedan 2012 0 \n", + "... ... \n", + "Volkswagen Beetle Hatchback 2012 0 \n", + "Volvo C30 Hatchback 2012 0 \n", + "Volvo 240 Sedan 1993 0 \n", + "Volvo XC90 SUV 2007 0 \n", + "smart fortwo Convertible 2012 10 \n", + "\n", + "[196 rows x 196 columns]" + ] + }, + "execution_count": 3, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "frame" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "af1f4956", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "
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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12, 10)\n", + "# , dpi=400\n", + " )\n", + "\n", + "plt.matshow(frame)\n", + "\n", + "plt.title('Confusion matrix')\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "cde63a06", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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    " + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12, 10)\n", + "# , dpi=400\n", + " )\n", + "sns.heatmap(frame, xticklabels=False, yticklabels=False)\n", + "\n", + "plt.title('Confusion matrix')\n", + "plt.show()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.2" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/pyproject.toml b/pyproject.toml index 286602e..0b23182 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -10,6 +10,7 @@ numpy = "^1.20.2" matplotlib = "^3.4.1" jupyterlab = "^3.0.12" pandas = "^1.2.3" +seaborn = "^0.11.1" [tool.poetry.dev-dependencies] diff --git a/report/report.lyx b/report/report.lyx index 334fa39..87fef3b 100644 --- a/report/report.lyx +++ b/report/report.lyx @@ -330,19 +330,6 @@ Epochs/learning rate/momentum? Network Architectures \end_layout -\begin_layout Standard -\begin_inset Flex TODO Note (inline) -status open - -\begin_layout Plain Layout -LeNet?/AlexNet/GoogLeNet/VGGNet -\end_layout - -\end_inset - - -\end_layout - \begin_layout Subsubsection Convolutional Layers \end_layout

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    AM General Hummer SUV 2000Acura RL Sedan 2012Acura TL Sedan 2012Acura TL Type-S 2008Acura TSX Sedan 2012Acura Integra Type R 2001Acura ZDX Hatchback 2012Aston Martin V8 Vantage Convertible 2012Aston Martin V8 Vantage Coupe 2012Aston Martin Virage Convertible 2012...Toyota Camry Sedan 2012Toyota Corolla Sedan 2012Toyota 4Runner SUV 2012Volkswagen Golf Hatchback 2012Volkswagen Golf Hatchback 1991Volkswagen Beetle Hatchback 2012Volvo C30 Hatchback 2012Volvo 240 Sedan 1993Volvo XC90 SUV 2007smart fortwo Convertible 2012
    AM General Hummer SUV 20006000000000...0000000001
    Acura RL Sedan 20120210200000...0000000000
    Acura TL Sedan 20120130200000...0000000000
    Acura TL Type-S 20080003000000...0000000000
    Acura TSX Sedan 20120100500000...0000000000
    ..................................................................
    Volkswagen Beetle Hatchback 20120000000000...0000050000
    Volvo C30 Hatchback 20120000000000...0000014000
    Volvo 240 Sedan 19930000000000...00000001000
    Volvo XC90 SUV 20070000000000...0000000070
    smart fortwo Convertible 20120000000000...00000000010
    \n", + "