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{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "German Traffic Sign Recognition Benchmark GTSRB\n",
    "===============================================\n",
    "## Episode 2 : First convolutions\n",
    "\n",
    "---\n",
    "CNN with Tensorflow and Keras  \n",
    "pjluc 2019 - CNRS/DEVLOG - Formation Deep Learning\n",
    "\n",
    "## 1/ Import and init "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Deepmod/pwk by pjluc 2019\n",
      "  Version            : 0.1.0\n",
      "  Run time           : Friday 27 December 2019, 22:52:24\n",
      "  Matplotlib style   : deepmods/talk.mplstyle\n",
      "  TensorFlow version :  1.14.0\n",
      "  Keras version      :  2.2.4-tf\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "from tensorflow.keras.callbacks import TensorBoard\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pyplot as plt\n",
    "import time\n",
    "\n",
    "import deepmods.pwk as ooo\n",
    "\n",
    "ooo.init()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 2/ Reload dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 15.6 ms, sys: 297 ms, total: 312 ms\n",
      "Wall time: 321 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "img_rows, img_cols = 25,25\n",
    "\n",
    "x_train = np.load('./data/x_train_v2.npy')\n",
    "x_train = x_train.reshape( x_train.shape[0], img_rows, img_cols, 1)\n",
    "y_train = np.load('./data/y_train_v2.npy')\n",
    "\n",
    "x_test = np.load('./data/x_test_v2.npy')\n",
    "x_test = x_test.reshape( x_test.shape[0], img_rows, img_cols, 1)\n",
    "y_test = np.load('./data/y_test_v2.npy')\n",
    "\n",
    "input_shape = (img_rows, img_cols, 1)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 3/ Have a look to the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_train :  (39209, 25, 25, 1)\n",
      "y_train :  (39209,)\n",
      "x_test  :  (12630, 25, 25, 1)\n",
      "y_test  :  (12630,)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x482.4 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x291.6 with 36 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"x_train : \",x_train.shape)\n",
    "print(\"y_train : \",y_train.shape)\n",
    "print(\"x_test  : \",x_test.shape)\n",
    "print(\"y_test  : \",y_test.shape)\n",
    "\n",
    "ooo.plot_images(x_train.reshape(-1,img_rows,img_cols),y_train, range(6),  columns=3, x_size=4, y_size=3)\n",
    "ooo.plot_images(x_train.reshape(-1,img_rows,img_cols),y_train, range(36), columns=12, x_size=1, y_size=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 4/ Create model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch_size  =  64\n",
    "num_classes =  43\n",
    "epochs      =  5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_3\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_8 (Conv2D)            (None, 23, 23, 48)        480       \n",
      "_________________________________________________________________\n",
      "max_pooling2d_7 (MaxPooling2 (None, 11, 11, 48)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_9 (Conv2D)            (None, 9, 9, 96)          41568     \n",
      "_________________________________________________________________\n",
      "max_pooling2d_8 (MaxPooling2 (None, 4, 4, 96)          0         \n",
      "_________________________________________________________________\n",
      "flatten_2 (Flatten)          (None, 1536)              0         \n",
      "_________________________________________________________________\n",
      "dense_8 (Dense)              (None, 1536)              2360832   \n",
      "_________________________________________________________________\n",
      "dense_9 (Dense)              (None, 500)               768500    \n",
      "_________________________________________________________________\n",
      "dense_10 (Dense)             (None, 500)               250500    \n",
      "_________________________________________________________________\n",
      "dense_11 (Dense)             (None, 43)                21543     \n",
      "=================================================================\n",
      "Total params: 3,443,423\n",
      "Trainable params: 3,443,423\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = keras.models.Sequential()\n",
    "model.add( keras.layers.Conv2D(48, (3, 3), activation='relu', input_shape=(img_rows, img_cols, 1))) # 25->24\n",
    "model.add( keras.layers.MaxPooling2D((2, 2))) # 12\n",
    "model.add( keras.layers.Conv2D(96, (3, 3), activation='relu')) #11\n",
    "model.add( keras.layers.MaxPooling2D((2, 2)))\n",
    "model.add( keras.layers.Flatten()) \n",
    "model.add( keras.layers.Dense(1536, activation='relu')) # 576\n",
    "model.add( keras.layers.Dense(500, activation='relu'))\n",
    "model.add( keras.layers.Dense(500, activation='relu'))\n",
    "model.add( keras.layers.Dense(43, activation='softmax'))\n",
    "model.summary()\n",
    "\n",
    "model.compile(optimizer='adam',\n",
    "              loss='sparse_categorical_crossentropy',\n",
    "              metrics=['accuracy'])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 39209 samples, validate on 12630 samples\n",
      "Epoch 1/5\n",
      "39209/39209 [==============================] - 14s 358us/sample - loss: 0.7138 - acc: 0.7917 - val_loss: 0.3566 - val_acc: 0.9112\n",
      "Epoch 2/5\n",
      "39209/39209 [==============================] - 14s 354us/sample - loss: 0.0920 - acc: 0.9726 - val_loss: 0.3150 - val_acc: 0.9205\n",
      "Epoch 3/5\n",
      "39209/39209 [==============================] - 15s 386us/sample - loss: 0.0529 - acc: 0.9843 - val_loss: 0.2792 - val_acc: 0.9305\n",
      "Epoch 4/5\n",
      "39209/39209 [==============================] - 16s 405us/sample - loss: 0.0350 - acc: 0.9889 - val_loss: 0.2860 - val_acc: 0.9306\n",
      "Epoch 5/5\n",
      "39209/39209 [==============================] - 16s 397us/sample - loss: 0.0330 - acc: 0.9897 - val_loss: 0.2647 - val_acc: 0.9339\n",
      "CPU times: user 5min 42s, sys: 17.3 s, total: 6min\n",
      "Wall time: 1min 15s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "\n",
    "history = model.fit(  x_train, y_train,\n",
    "                      batch_size=batch_size,\n",
    "                      epochs=epochs,\n",
    "                      verbose=1,\n",
    "                      validation_data=(x_test, y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "12630/12630 [==============================] - 2s 155us/sample - loss: 0.2647 - acc: 0.9339\n",
      "Test loss      : 0.2647\n",
      "Test accuracy  : 0.9339\n"
     ]
    }
   ],
   "source": [
    "score = model.evaluate(x_test, y_test, verbose=1)\n",
    "\n",
    "print('Test loss      : {:5.4f}'.format(score[0]))\n",
    "print('Test accuracy  : {:5.4f}'.format(score[1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}