162 lines
3.0 KiB
Plaintext
162 lines
3.0 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "imperial-battlefield",
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"metadata": {},
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"source": [
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"# Tensorflow"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 22,
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"id": "genetic-candle",
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"metadata": {},
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"outputs": [],
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"source": [
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"import tensorflow as tf\n",
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"import cv2 as cv\n",
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"import numpy as np"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"id": "liquid-butterfly",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"TensorShape([2, 2, 9])"
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]
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},
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"execution_count": 23,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"subject = tf.constant([\n",
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" [[1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]], \n",
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" [[1, 2, 3, 4, 5, 6, 7, 8, 9], [1, 2, 3, 4, 5, 6, 7, 8, 9]]\n",
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"])\n",
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"subject.shape"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 30,
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"id": "diagnostic-connection",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"(213, 320, 3)\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"(1, 213, 320, 3)"
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]
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},
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"execution_count": 30,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"im = cv.imread('sheep.png')\n",
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"print(im.shape)\n",
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"im = im / 255\n",
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"im = np.expand_dims(im, 0)\n",
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"im.shape"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 52,
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"id": "extraordinary-beads",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"TensorShape([1, 213, 320, 6])"
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]
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},
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"execution_count": 52,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"layer = tf.keras.layers.Conv2D(6, 1)\n",
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"result = layer(im)\n",
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"result.shape"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 56,
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"id": "changing-eligibility",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"TensorShape([1, 213, 320, 10])"
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]
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},
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"execution_count": 56,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"seq = tf.keras.Sequential(\n",
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" layers=[tf.keras.layers.Conv2D(6, 1),\n",
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" tf.keras.layers.Conv2D(10, 1)]\n",
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")\n",
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"\n",
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"seq.compile()\n",
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"res = seq(im)\n",
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"res.shape"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "statewide-steal",
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"metadata": {},
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"outputs": [],
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"source": []
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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",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.4"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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