2019-12-08 03:13:45 +00:00
|
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{
|
|
|
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"cells": [
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|
|
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{
|
2021-01-01 22:05:49 +00:00
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"cell_type": "code",
|
|
|
|
|
"execution_count": 17,
|
2019-12-08 03:13:45 +00:00
|
|
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"metadata": {},
|
2021-01-01 22:05:49 +00:00
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"outputs": [],
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|
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|
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"source": [
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|
|
|
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"import cv2\n",
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|
|
"import numpy as np\n",
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|
|
"from matplotlib import pyplot as plt"
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]
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},
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|
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|
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{
|
2019-12-08 03:13:45 +00:00
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"source": [
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"Basic opencv\n",
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|
|
"=================="
|
2021-01-01 22:05:49 +00:00
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|
],
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"cell_type": "markdown",
|
|
|
|
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"metadata": {}
|
2019-12-08 03:13:45 +00:00
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},
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{
|
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"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
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"execution_count": 18,
|
2019-12-08 03:13:45 +00:00
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"metadata": {},
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"outputs": [
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{
|
2021-01-01 22:05:49 +00:00
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|
|
"output_type": "execute_result",
|
2019-12-08 03:13:45 +00:00
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|
|
"data": {
|
|
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|
"text/plain": [
|
2021-01-01 22:05:49 +00:00
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"<matplotlib.image.AxesImage at 0x27d7b92d520>"
|
2019-12-08 03:13:45 +00:00
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|
|
]
|
|
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},
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"metadata": {},
|
2021-01-01 22:05:49 +00:00
|
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|
"execution_count": 18
|
2019-12-08 03:13:45 +00:00
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},
|
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{
|
2021-01-01 22:05:49 +00:00
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"output_type": "display_data",
|
2019-12-08 03:13:45 +00:00
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"data": {
|
2021-01-01 22:05:49 +00:00
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"text/plain": "<Figure size 432x288 with 1 Axes>",
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"image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"251.806921pt\" version=\"1.1\" viewBox=\"0 0 367.157923 251.806921\" width=\"367.157923pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n <cc:Work>\r\n <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n <dc:date>2021-01-01T21:54:50.342494</dc:date>\r\n <dc:format>image/svg+xml</dc:format>\r\n <dc:creator>\r\n <cc:Agent>\r\n <dc:title>Matplotlib v3.3.3, https://matplotlib.org/</dc:title>\r\n </cc:Agent>\r\n </dc:creator>\r\n </cc:Work>\r\n </rdf:RDF>\r\n </metadata>\r\n <defs>\r\n <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\r\n </defs>\r\n <g id=\"figure_1\">\r\n <g id=\"patch_1\">\r\n <path d=\"M 0 251.806921 \r\nL 367.157923 251.806921 \r\nL 367.157923 0 \r\nL 0 0 \r\nz\r\n\" style=\"fill:none;\"/>\r\n </g>\r\n <g id=\"axes_1\">\r\n <g id=\"patch_2\">\r\n <path d=\"M 33.2875 227.928796 \r\nL 359.957923 227.928796 \r\nL 359.957923 10.488796 \r\nL 33.2875 10.488796 \r\nz\r\n\" style=\"fill:#ffffff;\"/>\r\n </g>\r\n <g clip-path=\"url(#p18f04bad81)\">\r\n <image height=\"218\" id=\"imageb22ad99234\" transform=\"scale(1 -1)translate(0 -218)\" width=\"327\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\r\niVBORw0KGgoAAAANSUhEUgAAAUcAAADaCAYAAAA1xoBCAAEAAElEQVR4nDz9x69sa5rmh/0+s/wKv93x91yXN29mua5qW2iIDTUkgADRokRQEKCZAGouQEONNdRI/4JAQZQGlLoFsUvVpJpd1ZXVlWXSXX/vMduHXbH85zSIBGd7sPcGAhGx3ud93Cv+9O/+7+H//H/6P/LY3pBpeP3sJamOuXt/iwmOpMzZ9yPn8xV/9ze/YXU1wfcDKkmQKqLveoZ+IJIpT54u2Gwq2sGxmM6om4betJzNpsRJRN91bHcdAcH5YoqLPfvNjrI4Y7UsyCclkpg3797y8tkFkdC8e39HbwKTOVSPhvIiYVrOeNxveL684G73gGstH189p5yV/Omf/yUfPFkQT+ekacahqbCdI40kbdPyP/5n/4L79zt++tPfJ5YZucqZLnKUFATjsAGGsccOHX4ccX7EBkc/OERQeC/YHxuKSclmv6NrOy6eXfJw98BkmRGEpu8N08WEpm6J84i//O//nLvdG379xdfkk4yAYug7Ll5MqPYtrhG8+miJDvD3/+E/4c//9C8wqWWzfuDZkzPyaYnpB2TqIQSuJpd4H7PZPxJ6w2Q6ReUxXV9RFBOkSGjqI3EWYZ2ja47YpsLYwOWLp0ipqZseFQBjEInC20BTNygEXmtiBZqIgcDqLGaRXdK5juqh4vd/58e8O6zpvt2QX0aIJGeaLxEmgE5QzvAXf/XXRGcRCYJJGtOpiM71lDphqA90XUBnEUhPmRdoqXHBAjDJ50RRyf64RcmOaj+ijELmltoYLi8uAMvXv/yaTz/9lENrWU1Tlq8+56tf/IzV4oLt7S2ry2dsmjuuv7knKQU//fhjvr2+oQ2WQhcodcH5wlC3B2arFbIduN7fEM1TbA1BaCZZQd813L7fUEynzMsJdbvn2FRMi5zldMqhGqn6kSyLiIUnLVOcV+wetuSTDOs7EILgDFqlRHnB5bMX/O2f/TUffXrO/XpDPssJPsY3hr5vSCYFRZqTqJTB7Pjo2af8+vsvaKqRsoiJZIZMCvquoh0aLpYLVBQzuoAZOkCgsxSpBJfnV/jRc3N9w2B6CIo8i9E4RjNirCEuU4gjjvuGiBhnLaMdIcRMCo1rR7JlQTN0JErxuK6QUvB6eYnpD+wGw3S1IkoiNo1FmA7pHR98/JrffPEti6LkULXs+oEkWMo8Yd9b5nFKPvHs90e0iJguply9/IgvvvqSsel48uQcLRVt01JXO9IyZTKdUR9H6rbmYjmjLHLqviVYT98PoBTGDrhGYIaGoihRWUa7C1hZsTpb4qstQxoYB03fjkgMk3LGQ1dzefmcZOwQ/7v//X8Svr3+gl2zZTWfYYIlF4q+g4f2QFmmmEHzuD/w/MmcsWuI05zYxOjZlEN9x2q5ZP+4xw+BfJozBMvu2NEPPbkQaKdBxayeLVCp5HDYIbzHjwIjDPPkjOevn5InUz55+Qn/1f/3/8bl8gnHYweD5cUHS/7u539DlmaUiyVRlPB+c8eqnJFpgQ0SM7bE8wV2eyTuA3ViKaKMznqiWLI6P+O43ZBHM/7o9/8jPv3wd8nzOcJ6xqEn0po0TTHW0TQ1Q90ghQcch0PFbn/AO8+z1y+IkpSb63uu31+zuX0gJIatbxiGDREpOEVeTujbijjSPL/6kG/efsNu6Pnrn/8N5YVnPMDViwn7bYfUmlLFfPjxa4auIdIR87M53755i1aG4CKkt0zPC0brUGLEDTGTxZTBNBRxQeQEdw/31N1InuYsL5fkkynDcWAYjnjXIJVEZxkP+w1x4hEhYpnOMYNAKMHmcc/lk5LZ9IyuX/PdN2+Jo5If/egjVLXmoTY8VBv++PN/RCN7ns1e4ei577e8/eGG+bTkq2/ucGIkmRVEqaTvGmZRgu0GoiQjm8Tsd3vGXhDHCavVFDs4pNbMJjGJVFgvUXGBFfD++jsur5bMioRf/eYr4kmKkjN8X2G6CqKERM1582bNhx9esXrxIRrH22++RUuQuYKmZegd58/PeHi8ZxglTib8zk8+4uaHN2Rpwndv7yknGcQWO0qyMkYKiRCOtuk4X8xxnWB6tuLm9pb7zT0qgjyOSOKULCvABA7bPV54kqJAIlHAKByBkbbtKPOcKCrYb44k85ZcZ9RNoO5rkjwhHhKyIiE/u+Qin3H/w1tCAdIIhDfo+ZT14yOShMsnK/aHPaOtWJTnCAry+RnH3YGhr3DjgBkGVJzh4kBV1wxthwqecjpjsZxj+47jvsKMAeNACEjzCK0UZjy9L8FZhBpYTDMaE7AuEIUZo2kIY0vnA5GM6HvLxdUlcQJSBDxwsTxnt96w2bfEeUw1bqkf97x6+QFd1xHr
|
|
|
|
|
"image/png": "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
|
2019-12-08 03:13:45 +00:00
|
|
|
},
|
|
|
|
|
"metadata": {
|
|
|
|
|
"needs_background": "light"
|
2021-01-01 22:05:49 +00:00
|
|
|
}
|
2019-12-08 03:13:45 +00:00
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"img = cv2.imread('sheep.png')\n",
|
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|
|
|
"\n",
|
|
|
|
|
"plt.imshow(img[:,:,::-1])"
|
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|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"# load images (matlab equiv)"
|
2019-12-08 03:13:45 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 19,
|
2019-12-08 03:13:45 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "execute_result",
|
2019-12-08 03:13:45 +00:00
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"numpy.ndarray"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 19
|
2019-12-08 03:13:45 +00:00
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"type(img)"
|
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|
|
]
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|
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},
|
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{
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"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 20,
|
2019-12-08 03:13:45 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
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|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "execute_result",
|
2019-12-08 03:13:45 +00:00
|
|
|
"data": {
|
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|
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|
"text/plain": [
|
2019-12-08 22:19:30 +00:00
|
|
|
"array([82, 88, 87], dtype=uint8)"
|
2019-12-08 03:13:45 +00:00
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|
]
|
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|
},
|
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"metadata": {},
|
2021-01-01 22:05:49 +00:00
|
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|
"execution_count": 20
|
2019-12-08 03:13:45 +00:00
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|
}
|
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|
|
],
|
|
|
|
|
"source": [
|
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|
|
|
"px = img[100, 100]\n",
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|
|
|
"px"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 21,
|
2019-12-08 03:13:45 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "execute_result",
|
2019-12-08 03:13:45 +00:00
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"<matplotlib.image.AxesImage at 0x27d7c956d00>"
|
2019-12-08 03:13:45 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 21
|
2019-12-08 03:13:45 +00:00
|
|
|
},
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "display_data",
|
2019-12-08 03:13:45 +00:00
|
|
|
"data": {
|
2021-01-01 22:05:49 +00:00
|
|
|
"text/plain": "<Figure size 432x288 with 1 Axes>",
|
|
|
|
|
"image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"251.806921pt\" version=\"1.1\" viewBox=\"0 0 367.157923 251.806921\" width=\"367.157923pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n <cc:Work>\r\n <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n <dc:date>2021-01-01T21:54:51.422495</dc:date>\r\n <dc:format>image/svg+xml</dc:format>\r\n <dc:creator>\r\n <cc:Agent>\r\n <dc:title>Matplotlib v3.3.3, https://matplotlib.org/</dc:title>\r\n </cc:Agent>\r\n </dc:creator>\r\n </cc:Work>\r\n </rdf:RDF>\r\n </metadata>\r\n <defs>\r\n <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\r\n </defs>\r\n <g id=\"figure_1\">\r\n <g id=\"patch_1\">\r\n <path d=\"M 0 251.806921 \r\nL 367.157923 251.806921 \r\nL 367.157923 0 \r\nL 0 0 \r\nz\r\n\" style=\"fill:none;\"/>\r\n </g>\r\n <g id=\"axes_1\">\r\n <g id=\"patch_2\">\r\n <path d=\"M 33.2875 227.928796 \r\nL 359.957923 227.928796 \r\nL 359.957923 10.488796 \r\nL 33.2875 10.488796 \r\nz\r\n\" style=\"fill:#ffffff;\"/>\r\n </g>\r\n <g clip-path=\"url(#pb4be0598a4)\">\r\n <image height=\"218\" id=\"imagefb52dc5c3d\" transform=\"scale(1 -1)translate(0 -218)\" width=\"327\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\r\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
|
|
|
|
|
"image/png": "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
|
2019-12-08 03:13:45 +00:00
|
|
|
},
|
|
|
|
|
"metadata": {
|
|
|
|
|
"needs_background": "light"
|
2021-01-01 22:05:49 +00:00
|
|
|
}
|
2019-12-08 03:13:45 +00:00
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"img[100:300, 100:200] = [255, 0, 0]\n",
|
|
|
|
|
"img[:, :, 2] = 0\n",
|
|
|
|
|
"plt.imshow(img[:,:,::-1])"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"# set pixels red"
|
2019-12-08 03:13:45 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 22,
|
2019-12-08 03:13:45 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"output_type": "stream",
|
2021-01-01 22:05:49 +00:00
|
|
|
"name": "stdout",
|
2019-12-08 03:13:45 +00:00
|
|
|
"text": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"(213, 320, 3)\nuint8\n"
|
2019-12-08 03:13:45 +00:00
|
|
|
]
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"print(img.shape)\n",
|
|
|
|
|
"print(img.dtype)"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 23,
|
2019-12-08 03:13:45 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "execute_result",
|
2019-12-08 03:13:45 +00:00
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"(array([[0, 0, 0, ..., 0, 0, 0],\n",
|
|
|
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
|
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
|
|
|
" ...,\n",
|
|
|
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
|
|
|
" [0, 0, 0, ..., 0, 0, 0],\n",
|
|
|
|
|
" [0, 0, 0, ..., 0, 0, 0]], dtype=uint8),\n",
|
|
|
|
|
" array([[103, 103, 104, ..., 104, 103, 102],\n",
|
|
|
|
|
" [103, 102, 104, ..., 104, 105, 102],\n",
|
|
|
|
|
" [101, 101, 103, ..., 105, 103, 102],\n",
|
|
|
|
|
" ...,\n",
|
|
|
|
|
" [104, 102, 86, ..., 116, 87, 86],\n",
|
|
|
|
|
" [117, 90, 79, ..., 83, 71, 100],\n",
|
|
|
|
|
" [210, 97, 87, ..., 84, 108, 101]], dtype=uint8),\n",
|
|
|
|
|
" array([[ 53, 53, 53, ..., 49, 52, 49],\n",
|
|
|
|
|
" [ 51, 50, 52, ..., 46, 46, 45],\n",
|
|
|
|
|
" [ 50, 48, 52, ..., 49, 49, 47],\n",
|
|
|
|
|
" ...,\n",
|
|
|
|
|
" [ 51, 42, 19, ..., 57, 35, 35],\n",
|
|
|
|
|
" [ 77, 37, 19, ..., 30, 28, 43],\n",
|
|
|
|
|
" [173, 52, 26, ..., 27, 56, 46]], dtype=uint8))"
|
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|
|
|
]
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|
},
|
|
|
|
|
"metadata": {},
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 23
|
2019-12-08 03:13:45 +00:00
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"b, g, r = cv2.split(img)\n",
|
|
|
|
|
"r, g, b"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"# fairly expensive"
|
2019-12-08 03:13:45 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 24,
|
2019-12-08 03:13:45 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"img = cv2.merge((b, g, r))"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 25,
|
2019-12-08 03:13:45 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [],
|
|
|
|
|
"source": [
|
|
|
|
|
"BLUE = [255, 0, 0]\n",
|
|
|
|
|
"constant = cv2.copyMakeBorder(img, 10, 10, 10, 10, cv2.BORDER_CONSTANT, value=BLUE)"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 26,
|
2019-12-08 03:13:45 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "execute_result",
|
2019-12-08 03:13:45 +00:00
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"array([[255]], dtype=uint8)"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 26
|
2019-12-08 03:13:45 +00:00
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"x = np.uint8([250])\n",
|
|
|
|
|
"y = np.uint8([10])\n",
|
|
|
|
|
"cv2.add(x, y)"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "markdown",
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"source": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"# use numpy integers"
|
2019-12-08 03:13:45 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 27,
|
2019-12-08 03:13:45 +00:00
|
|
|
"metadata": {},
|
2019-12-08 22:19:30 +00:00
|
|
|
"outputs": [
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "execute_result",
|
2019-12-08 22:19:30 +00:00
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"<matplotlib.image.AxesImage at 0x27d7c9b6d30>"
|
2019-12-08 22:19:30 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 27
|
2019-12-08 22:19:30 +00:00
|
|
|
},
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "display_data",
|
2019-12-08 22:19:30 +00:00
|
|
|
"data": {
|
2021-01-01 22:05:49 +00:00
|
|
|
"text/plain": "<Figure size 432x288 with 1 Axes>",
|
|
|
|
|
"image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"251.773744pt\" version=\"1.1\" viewBox=\"0 0 257.9275 251.773744\" width=\"257.9275pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n <cc:Work>\r\n <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n <dc:date>2021-01-01T21:54:52.553495</dc:date>\r\n <dc:format>image/svg+xml</dc:format>\r\n <dc:creator>\r\n <cc:Agent>\r\n <dc:title>Matplotlib v3.3.3, https://matplotlib.org/</dc:title>\r\n </cc:Agent>\r\n </dc:creator>\r\n </cc:Work>\r\n </rdf:RDF>\r\n </metadata>\r\n <defs>\r\n <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\r\n </defs>\r\n <g id=\"figure_1\">\r\n <g id=\"patch_1\">\r\n <path d=\"M 0 251.773744 \r\nL 257.9275 251.773744 \r\nL 257.9275 0 \r\nL 0 0 \r\nz\r\n\" style=\"fill:none;\"/>\r\n </g>\r\n <g id=\"axes_1\">\r\n <g id=\"patch_2\">\r\n <path d=\"M 33.2875 227.895619 \r\nL 250.7275 227.895619 \r\nL 250.7275 10.455619 \r\nL 33.2875 10.455619 \r\nz\r\n\" style=\"fill:#ffffff;\"/>\r\n </g>\r\n <g clip-path=\"url(#p07fb0d614e)\">\r\n <image height=\"218\" id=\"imaged35cb42c1f\" transform=\"scale(1 -1)translate(0 -218)\" width=\"218\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\r\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
|
|
|
|
|
"image/png": "iVBORw0KGgoAAAANSUhEUgAAAQEAAAD8CAYAAAB3lxGOAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjMuMywgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/Il7ecAAAACXBIWXMAAAsTAAALEwEAmpwYAADgsUlEQVR4nOz9eawtW34ehn1rVdWeznzu/O6bu183u0k2KZEhlVhTpMhSnESKjUCwgsiKY4R2EgEJECBWHCAJ/JeA2DHgBDAiwYLtwJGTQFFsCLJlxbAsCRIlkRRJNdns8Y13PvdMe95VtVb++L7fWmuffre7ye5HHj7eAs499+xdtWpNv+n7DcvFGPHyenm9vH7nXv63ugMvr5fXy+u39nrJBF5eL6/f4ddLJvDyenn9Dr9eMoGX18vrd/j1kgm8vF5ev8Ovl0zg5fXy+h1+fWJMwDn3x5xzX3XOfcM59+c+qfe8vF5eL6/v73KfRJyAc64C8DUAfwTARwD+EYA/FWP81R/4y15eL6+X1/d1fVKawE8B+EaM8Vsxxg2A/wjAn/iE3vXyenm9vL6Pq/6E2r0P4MPi748A/PQLOzFycbinPxzgrnxfKiuu+M9VHcbucwCiK/4PwF1pNF75j3P5+S3l6Ep/vq1vxWdbfYvffs+VZtOH39a3K8+Wl7s6P3H7vm97xwv6vfXFlTa2/viYB9N4P25OYx7bd2jiY5/beocDvMvrEgIQivtdOfFXO/ddlNs0h47tRD3ycfvMvkt9tfFdGZxzaq98ENvrXI73O63TC7sft5/9TvPqvu0/wPwpTmKMt67e+0kxge96Oed+BsDPAMBgF/ihf06L44HK58kIgRMfQ/EsgOD0mQcqR6K3CfIeCLZJNAlebSNyM7mQG3MAagdsItD1QB8BH9lOWmT9eP0YoScmg22iSN3VfX0PhB4IvninLzYPOA4HoAtA7IHO2nF8Z+3Ypxr5vb3NT+SYo56prOtF22kTaQ6855zUNteR7RkhR90Pl++1cTa1CBVqN3LeOvXHea6J13oiinB16SOum/ru1Edbc++2x1W+J8TcT18Vc11QkQPX0bliLR3nYtjksfQB2PRA27GPldYxAug0J8HldyIArte8OL7fD4C65ppW6nfXbQsmu3rkeeoi56dxeY/ZWpT7ztajtzV2XGNfMAabQ68fu+z7f/Rv4318zPVJMYEHAF4r/n5Vn+WOxfgXAPwFANi55WKIeVBGqCGQ0EsJEyMnoI3svLeF1/+3iF4z2ptk1gL6mDeAEUqImcC9GEpjm8Hl96d27TmnNvVZb8zJbS+ec3kc1scAbjrninHbLoh5HMGI3POhzubCCDsW40NmUvbLbL5yHlN/AtBXuV9G+E4NJUIvCMmpnzb/znOtuj6/J0Y+HwD4kPsTXWYANkceeU4jAFcVTBr5OUgYOACVOhn0rh7cPzGIsZXEELOACXpJbw2XTLRYV9sDLuR9ZX3tqnyPV3+9434Zaag25LU0GA8xUtsTyH0IAWj1oTEtu0qCLues0frY0vX20kim1NR8XxRjbju88PqkmMA/AvCOc+4tkPj/eQD/wxfdHEHO6ipKQCP8PogR6CZbxCjO3NdZ6lVGnNoYfc/NGh25Z41tAivvT8wgcvMESOoVhLTFkpE3rtfmccXn9rcriNPrnX3RTLm5XEmp+jyiWCCfiSvNh/1f/fMAiTpqw7nUXYSYtQp7jTEYe3UfOZlbBFjOkct9jp7MKIJE3hf9VjcQAzdkIlCb/6LNrU2A3OdK7RvTyQuh/okhVfaMiM1VeW2qYg1jMVcBwKrN/QmmicQ8xx78u3Ns05hnb8zIF/3V3PsI1JX6bppcKLRS3R/1Lle82/atA+BNyyg0YtjYdF9VzokxEGNGFdCIQZjm0yWu9+3XJ8IEYoydc+7PAvgbYF/+UozxV178AJLdl9io/u5QSC4RdeeyJLPfSVXTfX3gxigXOkkoZHXde21sL0mHrXnl3277/0W3AbA/dcxqWnq40B5soStJJFdIX2NGADeGD5T6tTrj+qweXjUESxvUg8/5kOfU+ULqFeMApFF4EXDZdpWZYupbwQiSBoHMBEoiS0pJzBMdXdbYEJBV9GJdzATwjutujZWMzqmd8lmHLPVMkzNmkswOZDMjGFG4YuwFMzTT8spU570p7SDtkWKvtmokSICZeWVzanvZx6wJRqgf6psv1in1pZg/52QO2GexWLqKPwNHzSRGmqHVtw0mX58YJhBj/OsA/vr3fL/UPCf7LkRpBJos43I2Id4hYQKmNdjVQwQQiolWW+jzxELv8xXvqUEOamph6Mnxk3pdSE5TQ03aR5elvEmVUvWGzxLKSYpFk6q20QupZ9IloFjokoLtfpf3pmkftvPTOE0aYnuDp99G5HaT5iyZPsXmM7wl2DiRNzCQJZ/1J6neIWtIEVo/Mx/iNnP2ZkaoP8HGEfO4rL8298USbUnRBCzGrFXa2pVS2qFglsgMpGSCpo0aFpT4b8xzYAw79kDb8x1b9BfzfoqgZuE1bx7YIvSrDCBpm8bwqszUalsPu88XjByZwX3c9VsGDF69bLOWE+/S7t5WWysjHhRSBNtc1ce8uYz4nbh4IgYjbHHVBEChEGKa5LQp9L1tpK2NaX0JuW8u5sX1xlCqvOmTlBKR28YtFxCamxi/fUMBxcLbHBQ7NCHqLo/b2kpX+VnBHUrml27V9/Z40sD0spKg7XvTYgwbqXyxDjGDm4lB6L0mRFE8n9p3mUkkhl7MizEHLfnWT2I4MbdfYjbl1Hi9y4gxMfXyndZX02AloNqQ27J+l+aD7W8TDAZKuitzXg7OFb9TO8jahe3bHjJH3DZz+7jrWjCBiNxZ52TniWDMRo9XNghcoQ2UBBXzxBgIZUTqHCW/bZDoM/HC62+fpYdJ1NK2Lrk/YiYy2+ipOy73p7zM5AiOTKmPhURDXljbJLGUJC5LSKPVq1dJpIkxfcy9waSa2c1+W2rZ/G0xByeCtUa0sZO2VTAAp8mw+bCNWOnesh8mqctOOpcxjC3vR/H/5EWKxbiNUIu2SubRIwsTY7ShYJylUEn298fNcZ6StBdDzFiAebNsL5ila3spCQl9Vmndq0LaJOapf8o9bZoORPzWIdNwOt1rJskVnHXruhZMAOCG7I1QNcA6coB9wdlLVdCbzVVwTrPVILXVJ71SG6PQBJKqbai3F/PR5JW+6MTRS8aj1TTC6V1xTzGuUsoVPIeEUW5+kzquUO2QN0p6t92qL607Nvb0eSkiC63B5tKJ2xgo6WoypohMcEboZf+M+SXCLSSQbXqTSk7rkxh0IVVNzU8/sWDaMa+zaROh6E/QC40wYijAWp9daYlJIZuJtvZmPpVjsf4nlbrwkCStCnlMiVnbWBzNSLsxvadgFGnfXVmzqiLgF+tMzGbGJjPB+hiz2Wr7ydYXkcB4V8ypu8rJiutaMAHnshZgu94Yge2QEIBganTk5JhNmhva1hQqAMGLy2oDImQiSwtiTAB509hmTcSALF1KKezs3qu2YsE8oji9tWegUIjZ522mgG0soyjj5qbJ1H57zIUilKW/jacE7Mq5VZ9dhS3/eQI3RWBJ8mr39yKwCrld60tiVOqIzaH1K7nyjVsIKPNAojB7tpToaT62uIzGrg1uBF+aUX0Uk7U+xAwCGoMx5uM0x8ZQAanlMfe75PvGZMxMtPiOtO7GXET4aW8JFykxjLrSkKSVJgZmfXXFehRrZ30yBlMyMZs7j0xHVTFvV69rwQSM6NPCuLzpzVVjPufEGJDvTX7/4tnUtLWNPNm2+mav98VE9qEIrHGZQEtvggXibHkKHE2XTm1XWpASmQe0wIFMoy84vfWvdPsZo+pj7l/lsklR2rY9sj1p3TIGkjSKmCVcXZFBRhTzo76bO7ULuQ/G4Cxyzza5bUrvs+mWNrH6M0BBaDEvQZo+YzYFEyqjBZP97HMffeS6leh+G+ke622dzLSD1gXFi42h6x2lpmYEVBVomjFpw4lsPmGf+YKJGTMp1sO0rgQQX2HO1gfzikTzLhTbx0Hase43Zhp7bHW+3E8e2Qv0out6MAF
|
2019-12-08 22:19:30 +00:00
|
|
|
},
|
|
|
|
|
"metadata": {
|
|
|
|
|
"needs_background": "light"
|
2021-01-01 22:05:49 +00:00
|
|
|
}
|
2019-12-08 22:19:30 +00:00
|
|
|
}
|
|
|
|
|
],
|
2019-12-08 03:13:45 +00:00
|
|
|
"source": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"blended = cv2.addWeighted(img[0:200, 0:200], 0.8, img[0:200, 0:200], 0.2, 0)\n",
|
|
|
|
|
"plt.imshow(blended)"
|
2019-12-08 22:19:30 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 28,
|
2019-12-08 22:19:30 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "execute_result",
|
2019-12-08 22:19:30 +00:00
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"<matplotlib.image.AxesImage at 0x27d7ca0fca0>"
|
2019-12-08 22:19:30 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 28
|
2019-12-08 22:19:30 +00:00
|
|
|
},
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "display_data",
|
2019-12-08 22:19:30 +00:00
|
|
|
"data": {
|
2021-01-01 22:05:49 +00:00
|
|
|
"text/plain": "<Figure size 432x288 with 1 Axes>",
|
|
|
|
|
"image/svg+xml": "<?xml version=\"1.0\" encoding=\"utf-8\" standalone=\"no\"?>\r\n<!DOCTYPE svg PUBLIC \"-//W3C//DTD SVG 1.1//EN\"\r\n \"http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd\">\r\n<!-- Created with matplotlib (https://matplotlib.org/) -->\r\n<svg height=\"251.806921pt\" version=\"1.1\" viewBox=\"0 0 367.157923 251.806921\" width=\"367.157923pt\" xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\">\r\n <metadata>\r\n <rdf:RDF xmlns:cc=\"http://creativecommons.org/ns#\" xmlns:dc=\"http://purl.org/dc/elements/1.1/\" xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\">\r\n <cc:Work>\r\n <dc:type rdf:resource=\"http://purl.org/dc/dcmitype/StillImage\"/>\r\n <dc:date>2021-01-01T21:54:53.215494</dc:date>\r\n <dc:format>image/svg+xml</dc:format>\r\n <dc:creator>\r\n <cc:Agent>\r\n <dc:title>Matplotlib v3.3.3, https://matplotlib.org/</dc:title>\r\n </cc:Agent>\r\n </dc:creator>\r\n </cc:Work>\r\n </rdf:RDF>\r\n </metadata>\r\n <defs>\r\n <style type=\"text/css\">*{stroke-linecap:butt;stroke-linejoin:round;}</style>\r\n </defs>\r\n <g id=\"figure_1\">\r\n <g id=\"patch_1\">\r\n <path d=\"M 0 251.806921 \r\nL 367.157923 251.806921 \r\nL 367.157923 0 \r\nL 0 0 \r\nz\r\n\" style=\"fill:none;\"/>\r\n </g>\r\n <g id=\"axes_1\">\r\n <g id=\"patch_2\">\r\n <path d=\"M 33.2875 227.928796 \r\nL 359.957923 227.928796 \r\nL 359.957923 10.488796 \r\nL 33.2875 10.488796 \r\nz\r\n\" style=\"fill:#ffffff;\"/>\r\n </g>\r\n <g clip-path=\"url(#p8faa9b0714)\">\r\n <image height=\"218\" id=\"image30eaf3f4fa\" transform=\"scale(1 -1)translate(0 -218)\" width=\"327\" x=\"33.2875\" xlink:href=\"data:image/png;base64,\r\niVBORw0KGgoAAAANSUhEUgAAAUcAAADaCAYAAAA1xoBCAAEAAElEQVR4nGT9R69t25kliI1pltv+2OvvMzSPjCAjmZFZWZGFkgpKhVIQqiGpUdUQ1NJPKKipn1Coltr6AVIBEiAJVXKRKSArshjpIoOefPa+d93x2y43jRrjm3NfQgQIko/3nrP3WnN+ZnxjjE/9F//uP4v//H//F6gfAnypsPlIIxTA7LsIFYBxChR7oDtTuPzXLQ5PKpg+wFcawQBFG2APAaFQ2D6zmNwEmDagPzEotwGmD2jPLHypULQR9e0IAGgvCkQNNDcOw8KgPdMY5gpQwOJrj+0Lg2iA+bcBZojoFxrNjUd7bjAsFJqbgP1jjclVgOkjti8NhgXw/J912L6sMMwVXAOUmwjTA6EEin3Eu790KN8WmPzkHoX1mJYDPp7fwaqA1hdwUWMz1NgNFQZvMDgDHzT6wQIAQlAYNxWK+YDxoYI5aOBJh/i+Rlg6QEWgM7DLAW5fQDcOi79uMH3vsfw3bxFWMyBGqEOP9tNTVDctdDti+9kJoIC3/1jj+V85RKvQvD1g99EU/ULDdhG+VPzxpwqIQH0XYYaIYaHgagXbRowzPsNiF+FqBe0iij1QHAK0i9i8sIia/z8UoB0QCkB5oNwGRK0QNRAs/1P7iPZMY1wAegTq64i7nwVU1wbTNxH9qYIvADePUB6IBkAEHv/co1vyHbpGAQDMwM9U7CK/T6UQFeCmCsEAKgBQPHOhBMo1EDVQPfAs+gowHXB4zOdw9ssRdz8uYPcRw0rh8Mzj5Jca3anC5H3E4ZFCuQZOPh8wTg3ufmww/yZAO8DVCqEA+hN+nu5UwQxAc81naNoon0WhOETMvnMYlgb9QqHcRZTbgGGu0a00qk1AceB3C0ZhnPK7TK4DhpmG9hEA/1mwfB77pwpP/uWAu89KTK4ChgXfqe0iikPEMNMYJ0Ao+V43nwCr3wHVlj8zWD6PYs+/czjnvdUOMD1/n6/5DttHEXpUmH4XYQYAAMYJn7UeADPyf4dCoXqIiAbQjn82yjOwXUS30rBtRLTA5NojaoXdEwPb8jO3pxq+5p3Tjudg/X3g9NcR/VKhfogodgFQwDDTKA4BrtEYpgrNfUAwQHeisXsBnPyWP3P3zDDO7COqdcA40RiWfGfljt/bzQB7AJSPMB3PjBn5XEzP5+VqhWoToAJwuNAodxHBKJghojgEAEC/MKgfPLbPDLQH1Gf/u/8qLr4OqB88DucW2kWEgg+jevAY5hpmjKiveuxeNLBdgKs1VASGGX9he6bR3ByDmHZAtfawrUOwGohAtArbZwVCAdQPEYh8gCrwIGw+1vBNhP+kw8X/veIX2EboEdi+VHj0rwe4iUG30vAVMHvr0a0MQgkgALaP6Jca1TpAeR4AV/PLh0KhvVSo7nmAN/+gx88+fYXHzRZjMFiPNaZ2wGmxRxtKvDkscdNOoVVEiAo3myn6hxoICo9e3mFaDvj67RnMdzWaK15s2wKmi4DmoRhnCsWeAW3/LGLxFV/w6f/3FfzlCcx6j/b756iuDoiFga8M7n/UwLbyec8VVl94xBQ0ItCeaehRDvUY0Z9omD4y+ERg+j6g2HmMU43DpcE4B6xcHj3yYvqaicWXDFjDnM8oal7m3RODYcnvc/K7Eb7WuP2xQXEAyoeI5s7j/T800F6hP/dABIqNxvxroF8qnP7Oyc/VcBUT4tioHAzHmUJ9x4TmK4X2TPMdWYVhwYOtAoMjAMy+ZZAb5xGnv4oYpwrB8ufZjn/PF8DyqwEPPyixf8YLvfycgdrVxz+7e6oxeR/z9739qcL8awar5dcOw1wjGCYUN2FgAXjxGDwjujOF6euI6XuHUCq4SvN7TQDtgfou8G5MNaD4WVQAVIwo9jzrvgQmtx7DlH+32EcU+wA30bwPU43+VGFYArNvInzN5KUi39fkPZPY4YlC+cDk36+YFIclk4ptIwOfnP9gIEGcgaBbGXSnPD/1fYAZI5ST5DRh8E3vRXu+l36pYHp+lqj5/5sxQo/8c7YN2D2x8JXK96A7A+o7oL4NGCcK5T6iuR7x8L0SxUESfuDP2nysMXkb4aZMmvbAADhOVT4X1YbFWNQKvlYYJxqu5jtUkd8bESh3EcNMMfkbYP9MoXrgvRkWTJ7aRVQPAcOCwVMFoL73sHuP3fMSuroH3ETB1RpFGxG1wuy7gVXkS4v2XKM9MWgf15i+6fOD8SUPzOFCo9jFnB3LfUC59bC7EVEpHC4L9CcWUfMhp8AI8PDavcfJrzY4+42H3Ss0f9ugXyqsvnQodxH9icLFv3fozizaM42oGRinX29z5vM1L3r1ELB7rtGvFHbPNYpDRHeqcXjE
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"image/png": "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
|
2019-12-08 22:19:30 +00:00
|
|
|
},
|
|
|
|
|
"metadata": {
|
|
|
|
|
"needs_background": "light"
|
2021-01-01 22:05:49 +00:00
|
|
|
}
|
2019-12-08 22:19:30 +00:00
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"img = cv2.imread('sheep.png')\n",
|
2021-01-01 22:05:49 +00:00
|
|
|
"img = cv2.normalize(img.astype('float'), None, alpha=0, beta=1, norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_32F)\n",
|
|
|
|
|
"grayscale = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n",
|
|
|
|
|
"plt.imshow(grayscale)"
|
2019-12-08 22:19:30 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 29,
|
2019-12-08 22:19:30 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "execute_result",
|
2019-12-08 22:19:30 +00:00
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"<matplotlib.image.AxesImage at 0x27d7ca6f9d0>"
|
2019-12-08 22:19:30 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 29
|
2019-12-08 22:19:30 +00:00
|
|
|
},
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "display_data",
|
2019-12-08 22:19:30 +00:00
|
|
|
"data": {
|
2021-01-01 22:05:49 +00:00
|
|
|
"text/plain": "<Figure size 432x288 with 1 Axes>",
|
|
|
|
|
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|
2019-12-08 22:19:30 +00:00
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},
|
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"metadata": {
|
|
|
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"needs_background": "light"
|
2021-01-01 22:05:49 +00:00
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}
|
2019-12-08 22:19:30 +00:00
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}
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],
|
|
|
|
|
"source": [
|
|
|
|
|
"img = cv2.imread('sheep.png')\n",
|
2021-01-01 22:05:49 +00:00
|
|
|
"x = np.concatenate((img, img), axis=1)\n",
|
2019-12-08 22:19:30 +00:00
|
|
|
"plt.imshow(x)"
|
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]
|
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|
},
|
|
|
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{
|
|
|
|
|
"cell_type": "code",
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 30,
|
2019-12-08 22:19:30 +00:00
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "execute_result",
|
2019-12-08 22:19:30 +00:00
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
2021-01-01 22:05:49 +00:00
|
|
|
"<matplotlib.image.AxesImage at 0x27d7b64ed30>"
|
2019-12-08 22:19:30 +00:00
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"metadata": {},
|
2021-01-01 22:05:49 +00:00
|
|
|
"execution_count": 30
|
2019-12-08 22:19:30 +00:00
|
|
|
},
|
|
|
|
|
{
|
2021-01-01 22:05:49 +00:00
|
|
|
"output_type": "display_data",
|
2019-12-08 22:19:30 +00:00
|
|
|
"data": {
|
2021-01-01 22:05:49 +00:00
|
|
|
"text/plain": "<Figure size 432x288 with 1 Axes>",
|
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|
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2019-12-08 22:19:30 +00:00
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},
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"metadata": {
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|
"needs_background": "light"
|
2021-01-01 22:05:49 +00:00
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}
|
2019-12-08 22:19:30 +00:00
|
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|
}
|
|
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|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"img = cv2.imread('sheep.png')\n",
|
2021-01-01 22:05:49 +00:00
|
|
|
"x = np.concatenate((img, img), axis=0)\n",
|
|
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|
|
"plt.imshow(x)"
|
2019-12-08 03:13:45 +00:00
|
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|
]
|
|
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|
|
}
|
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|
|
],
|
|
|
|
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"metadata": {
|
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"kernelspec": {
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"display_name": "Python 3",
|
|
|
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"language": "python",
|
|
|
|
|
"name": "python3"
|
|
|
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},
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"language_info": {
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"codemirror_mode": {
|
|
|
|
|
"name": "ipython",
|
|
|
|
|
"version": 3
|
|
|
|
|
},
|
|
|
|
|
"file_extension": ".py",
|
|
|
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"mimetype": "text/x-python",
|
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"name": "python",
|
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"nbconvert_exporter": "python",
|
|
|
|
|
"pygments_lexer": "ipython3",
|
2021-01-01 22:05:49 +00:00
|
|
|
"version": "3.8.4-final"
|
2019-12-08 03:13:45 +00:00
|
|
|
}
|
|
|
|
|
},
|
|
|
|
|
"nbformat": 4,
|
|
|
|
|
"nbformat_minor": 4
|
2021-01-01 22:05:49 +00:00
|
|
|
}
|
