Corel_cnn.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import keras \n",
    "from keras import layers\n",
    "from keras import models\n",
    "import numpy as np\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_1\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "conv2d_1 (Conv2D)            (None, 81, 81, 8)         104       \n",
      "_________________________________________________________________\n",
      "conv2d_2 (Conv2D)            (None, 80, 80, 16)        528       \n",
      "_________________________________________________________________\n",
      "dropout_1 (Dropout)          (None, 80, 80, 16)        0         \n",
      "_________________________________________________________________\n",
      "conv2d_3 (Conv2D)            (None, 79, 79, 32)        2080      \n",
      "_________________________________________________________________\n",
      "conv2d_4 (Conv2D)            (None, 78, 78, 64)        8256      \n",
      "_________________________________________________________________\n",
      "dropout_2 (Dropout)          (None, 78, 78, 64)        0         \n",
      "_________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2 (None, 39, 39, 64)        0         \n",
      "_________________________________________________________________\n",
      "flatten_1 (Flatten)          (None, 97344)             0         \n",
      "_________________________________________________________________\n",
      "dense4 (Dense)               (None, 300)               29203500  \n",
      "_________________________________________________________________\n",
      "dropout_3 (Dropout)          (None, 300)               0         \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 100)               30100     \n",
      "=================================================================\n",
      "Total params: 29,244,568\n",
      "Trainable params: 29,244,568\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "None\n"
     ]
    }
   ],
   "source": [
    "model =models.Sequential()\n",
    "model.add(layers.Conv2D(8, kernel_size=2, padding='valid', strides=1, activation='relu', input_shape=(82, 82, 3)))\n",
    "model.add(layers.Conv2D(16, kernel_size=2, padding='valid', strides=1, activation='relu'))\n",
    "model.add(layers.Dropout(0.25))\n",
    "model.add(layers.Conv2D(32, kernel_size=2, padding='valid', strides=1, activation='relu'))\n",
    "model.add(layers.Conv2D(64, kernel_size=2, padding='valid', strides=1, activation='relu'))\n",
    "model.add(layers.Dropout(0.5))\n",
    "model.add(layers.MaxPool2D((2, 2)))\n",
    "\n",
    "model.add(layers.Flatten())\n",
    "model.add(layers.Dense(300, activation='relu', name='dense4'))\n",
    "model.add(layers.Dropout(0.25))\n",
    "model.add(layers.Dense(100, activation='softmax'))\n",
    "\n",
    "print(model.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ImageAugmentation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_data = keras.preprocessing.image.ImageDataGenerator(rescale = 1./255,\n",
    "                                    featurewise_center=True, \n",
    "                                    samplewise_center=True, \n",
    "                                    featurewise_std_normalization=True, \n",
    "                                    samplewise_std_normalization=True, \n",
    "                                    zca_whitening=False, zca_epsilon=1e-06, \n",
    "                                    rotation_range=40, width_shift_range=0.0,\n",
    "                                    height_shift_range=0.0, brightness_range=(0.2, 0.2),\n",
    "                                    shear_range=0.2, zoom_range=0.2, \n",
    "                                    channel_shift_range=0.0, fill_mode='nearest', \n",
    "                                    cval=0.0, horizontal_flip=True, vertical_flip=True,\n",
    "                                    data_format=None, validation_split=0.0, dtype=None)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test and Train"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 1000 images belonging to 100 classes.\n",
      "Found 8900 images belonging to 100 classes.\n"
     ]
    }
   ],
   "source": [
    "test = train_data.flow_from_directory(r\"C:\\Users\\SUPERMAN\\Desktop\\hand\\image_Sep\\test\\\\\",\n",
    "                                     target_size=(82, 82), classes = [str(x) for x in range(100)],\n",
    "                                     class_mode='categorical', batch_size=64, seed=1)\n",
    "train = train_data.flow_from_directory(r\"C:\\Users\\SUPERMAN\\Desktop\\hand\\image_Sep\\train\\\\\",\n",
    "                                     target_size=(82, 82), classes = [str(x) for x in range(100)],\n",
    "                                     class_mode='categorical', batch_size=64, seed=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class_ = test.classes"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Function for Metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras import backend as K\n",
    "\n",
    "def recall_m(y_true, y_pred):\n",
    "        true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n",
    "        possible_positives = K.sum(K.round(K.clip(y_true, 0, 1)))\n",
    "        recall = true_positives / (possible_positives + K.epsilon())\n",
    "        return recall\n",
    "\n",
    "def precision_m(y_true, y_pred):\n",
    "        true_positives = K.sum(K.round(K.clip(y_true * y_pred, 0, 1)))\n",
    "        predicted_positives = K.sum(K.round(K.clip(y_pred, 0, 1)))\n",
    "        precision = true_positives / (predicted_positives + K.epsilon())\n",
    "        return precision\n",
    "\n",
    "def f1_m(y_true, y_pred):\n",
    "    precision = precision_m(y_true, y_pred)\n",
    "    recall = recall_m(y_true, y_pred)\n",
    "    return 2*((precision*recall)/(precision+recall+K.epsilon()))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Compiler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(optimizer = 'sgd',\n",
    "              loss = 'categorical_crossentropy',\n",
    "              metrics=['accuracy', recall_m, precision_m, f1_m])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Fitting "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUPERMAN\\Anaconda3\\lib\\site-packages\\keras_preprocessing\\image\\image_data_generator.py:716: UserWarning: This ImageDataGenerator specifies `featurewise_center`, but it hasn't been fit on any training data. Fit it first by calling `.fit(numpy_data)`.\n",
      "  warnings.warn('This ImageDataGenerator specifies '\n",
      "C:\\Users\\SUPERMAN\\Anaconda3\\lib\\site-packages\\keras_preprocessing\\image\\image_data_generator.py:724: UserWarning: This ImageDataGenerator specifies `featurewise_std_normalization`, but it hasn't been fit on any training data. Fit it first by calling `.fit(numpy_data)`.\n",
      "  warnings.warn('This ImageDataGenerator specifies '\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "156/156 [==============================] - 165s 1s/step - loss: 4.5388 - accuracy: 0.0285 - recall_m: 0.0000e+00 - precision_m: 0.0000e+00 - f1_m: 0.0000e+00 - val_loss: 4.3553 - val_accuracy: 0.0710 - val_recall_m: 0.0000e+00 - val_precision_m: 0.0000e+00 - val_f1_m: 0.0000e+00\n",
      "Epoch 2/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 4.1952 - accuracy: 0.0782 - recall_m: 0.0036 - precision_m: 0.1624 - f1_m: 0.0070 - val_loss: 4.0438 - val_accuracy: 0.1222 - val_recall_m: 0.0000e+00 - val_precision_m: 0.0000e+00 - val_f1_m: 0.0000e+00\n",
      "Epoch 3/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 3.8437 - accuracy: 0.1264 - recall_m: 0.0161 - precision_m: 0.5139 - f1_m: 0.0310 - val_loss: 3.8148 - val_accuracy: 0.1820 - val_recall_m: 0.0000e+00 - val_precision_m: 0.0000e+00 - val_f1_m: 0.0000e+00\n",
      "Epoch 4/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 3.5656 - accuracy: 0.1758 - recall_m: 0.0356 - precision_m: 0.6578 - f1_m: 0.0666 - val_loss: 3.6395 - val_accuracy: 0.2098 - val_recall_m: 1.9531e-04 - val_precision_m: 0.0125 - val_f1_m: 3.8462e-04\n",
      "Epoch 5/100\n",
      "156/156 [==============================] - 107s 689ms/step - loss: 3.3656 - accuracy: 0.2090 - recall_m: 0.0539 - precision_m: 0.6918 - f1_m: 0.0984 - val_loss: 3.7415 - val_accuracy: 0.2500 - val_recall_m: 0.0023 - val_precision_m: 0.1375 - val_f1_m: 0.0046\n",
      "Epoch 6/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 3.1385 - accuracy: 0.2463 - recall_m: 0.0702 - precision_m: 0.6923 - f1_m: 0.1252 - val_loss: 3.3811 - val_accuracy: 0.2852 - val_recall_m: 0.0086 - val_precision_m: 0.4125 - val_f1_m: 0.0168\n",
      "Epoch 7/100\n",
      "156/156 [==============================] - 108s 695ms/step - loss: 2.9879 - accuracy: 0.2779 - recall_m: 0.0964 - precision_m: 0.7129 - f1_m: 0.1671 - val_loss: 3.3860 - val_accuracy: 0.3176 - val_recall_m: 0.0228 - val_precision_m: 0.6741 - val_f1_m: 0.0435\n",
      "Epoch 8/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 2.8525 - accuracy: 0.2997 - recall_m: 0.1132 - precision_m: 0.7173 - f1_m: 0.1934 - val_loss: 3.0083 - val_accuracy: 0.3302 - val_recall_m: 0.0268 - val_precision_m: 0.7715 - val_f1_m: 0.0513\n",
      "Epoch 9/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 2.7095 - accuracy: 0.3273 - recall_m: 0.1332 - precision_m: 0.7221 - f1_m: 0.2229 - val_loss: 3.1300 - val_accuracy: 0.3550 - val_recall_m: 0.0405 - val_precision_m: 0.8335 - val_f1_m: 0.0765\n",
      "Epoch 10/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 2.6018 - accuracy: 0.3498 - recall_m: 0.1554 - precision_m: 0.7335 - f1_m: 0.2543 - val_loss: 3.0440 - val_accuracy: 0.3818 - val_recall_m: 0.0486 - val_precision_m: 0.9138 - val_f1_m: 0.0915\n",
      "Epoch 11/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 2.5098 - accuracy: 0.3779 - recall_m: 0.1749 - precision_m: 0.7491 - f1_m: 0.2808 - val_loss: 2.6172 - val_accuracy: 0.3622 - val_recall_m: 0.0636 - val_precision_m: 0.8227 - val_f1_m: 0.1166\n",
      "Epoch 12/100\n",
      "156/156 [==============================] - 111s 714ms/step - loss: 2.4753 - accuracy: 0.3892 - recall_m: 0.1847 - precision_m: 0.7386 - f1_m: 0.2921 - val_loss: 2.6249 - val_accuracy: 0.4120 - val_recall_m: 0.0623 - val_precision_m: 0.9155 - val_f1_m: 0.1156\n",
      "Epoch 13/100\n",
      "156/156 [==============================] - 114s 731ms/step - loss: 2.3267 - accuracy: 0.4097 - recall_m: 0.2059 - precision_m: 0.7367 - f1_m: 0.3194 - val_loss: 2.8376 - val_accuracy: 0.4214 - val_recall_m: 0.0611 - val_precision_m: 0.9332 - val_f1_m: 0.1128\n",
      "Epoch 14/100\n",
      "156/156 [==============================] - 111s 711ms/step - loss: 2.3256 - accuracy: 0.4119 - recall_m: 0.2084 - precision_m: 0.7430 - f1_m: 0.3226 - val_loss: 2.6287 - val_accuracy: 0.4036 - val_recall_m: 0.0722 - val_precision_m: 0.9329 - val_f1_m: 0.1316\n",
      "Epoch 15/100\n",
      "156/156 [==============================] - 108s 694ms/step - loss: 2.1688 - accuracy: 0.4425 - recall_m: 0.2481 - precision_m: 0.7681 - f1_m: 0.3728 - val_loss: 2.5859 - val_accuracy: 0.4436 - val_recall_m: 0.0779 - val_precision_m: 0.9524 - val_f1_m: 0.1422\n",
      "Epoch 16/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 2.1265 - accuracy: 0.4600 - recall_m: 0.2607 - precision_m: 0.7552 - f1_m: 0.3850 - val_loss: 2.2392 - val_accuracy: 0.4430 - val_recall_m: 0.0932 - val_precision_m: 0.9175 - val_f1_m: 0.1671\n",
      "Epoch 17/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 2.0474 - accuracy: 0.4713 - recall_m: 0.2782 - precision_m: 0.7523 - f1_m: 0.4039 - val_loss: 2.3260 - val_accuracy: 0.4354 - val_recall_m: 0.0744 - val_precision_m: 0.9547 - val_f1_m: 0.1363\n",
      "Epoch 18/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 2.0032 - accuracy: 0.4860 - recall_m: 0.2900 - precision_m: 0.7620 - f1_m: 0.4171 - val_loss: 2.4461 - val_accuracy: 0.4362 - val_recall_m: 0.1132 - val_precision_m: 0.9186 - val_f1_m: 0.1992\n",
      "Epoch 19/100\n",
      "156/156 [==============================] - 108s 689ms/step - loss: 1.9671 - accuracy: 0.4893 - recall_m: 0.3021 - precision_m: 0.7615 - f1_m: 0.4306 - val_loss: 2.5842 - val_accuracy: 0.4716 - val_recall_m: 0.1168 - val_precision_m: 0.9109 - val_f1_m: 0.2050\n",
      "Epoch 20/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 1.8986 - accuracy: 0.5050 - recall_m: 0.3194 - precision_m: 0.7714 - f1_m: 0.4492 - val_loss: 2.3002 - val_accuracy: 0.4610 - val_recall_m: 0.0980 - val_precision_m: 0.9225 - val_f1_m: 0.1754\n",
      "Epoch 21/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 1.8574 - accuracy: 0.5098 - recall_m: 0.3288 - precision_m: 0.7689 - f1_m: 0.4582 - val_loss: 2.2475 - val_accuracy: 0.4824 - val_recall_m: 0.1254 - val_precision_m: 0.9215 - val_f1_m: 0.2187\n",
      "Epoch 22/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 1.8065 - accuracy: 0.5217 - recall_m: 0.3475 - precision_m: 0.7749 - f1_m: 0.4779 - val_loss: 1.9687 - val_accuracy: 0.4926 - val_recall_m: 0.1359 - val_precision_m: 0.9290 - val_f1_m: 0.2345\n",
      "Epoch 23/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 1.7890 - accuracy: 0.5269 - recall_m: 0.3513 - precision_m: 0.7693 - f1_m: 0.4800 - val_loss: 2.5773 - val_accuracy: 0.3830 - val_recall_m: 0.0658 - val_precision_m: 0.7212 - val_f1_m: 0.1191\n",
      "Epoch 24/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 1.7811 - accuracy: 0.5275 - recall_m: 0.3422 - precision_m: 0.7759 - f1_m: 0.4725 - val_loss: 2.1832 - val_accuracy: 0.4956 - val_recall_m: 0.1356 - val_precision_m: 0.9448 - val_f1_m: 0.2351\n",
      "Epoch 25/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 1.7088 - accuracy: 0.5383 - recall_m: 0.3685 - precision_m: 0.7775 - f1_m: 0.4981 - val_loss: 2.4996 - val_accuracy: 0.5034 - val_recall_m: 0.1500 - val_precision_m: 0.9223 - val_f1_m: 0.2562\n",
      "Epoch 26/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 1.6304 - accuracy: 0.5661 - recall_m: 0.4045 - precision_m: 0.7955 - f1_m: 0.5341 - val_loss: 1.9165 - val_accuracy: 0.5044 - val_recall_m: 0.1655 - val_precision_m: 0.9413 - val_f1_m: 0.2785\n",
      "Epoch 27/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 1.6367 - accuracy: 0.5596 - recall_m: 0.3953 - precision_m: 0.7853 - f1_m: 0.5243 - val_loss: 1.8851 - val_accuracy: 0.4918 - val_recall_m: 0.1682 - val_precision_m: 0.9046 - val_f1_m: 0.2818\n",
      "Epoch 28/100\n",
      "156/156 [==============================] - 107s 688ms/step - loss: 1.6020 - accuracy: 0.5760 - recall_m: 0.4089 - precision_m: 0.7903 - f1_m: 0.5364 - val_loss: 2.3406 - val_accuracy: 0.5048 - val_recall_m: 0.1820 - val_precision_m: 0.9113 - val_f1_m: 0.3004\n",
      "Epoch 29/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 1.5467 - accuracy: 0.5851 - recall_m: 0.4276 - precision_m: 0.7921 - f1_m: 0.5537 - val_loss: 1.9122 - val_accuracy: 0.4982 - val_recall_m: 0.1646 - val_precision_m: 0.9378 - val_f1_m: 0.2777\n",
      "Epoch 30/100\n",
      "156/156 [==============================] - 109s 697ms/step - loss: 1.5428 - accuracy: 0.5804 - recall_m: 0.4254 - precision_m: 0.7984 - f1_m: 0.5533 - val_loss: 1.9216 - val_accuracy: 0.5204 - val_recall_m: 0.1895 - val_precision_m: 0.9214 - val_f1_m: 0.3120\n",
      "Epoch 31/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "156/156 [==============================] - 108s 691ms/step - loss: 1.4933 - accuracy: 0.5921 - recall_m: 0.4394 - precision_m: 0.7975 - f1_m: 0.5651 - val_loss: 2.1501 - val_accuracy: 0.5054 - val_recall_m: 0.1841 - val_precision_m: 0.9246 - val_f1_m: 0.3046\n",
      "Epoch 32/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 1.4871 - accuracy: 0.5918 - recall_m: 0.4398 - precision_m: 0.8002 - f1_m: 0.5662 - val_loss: 1.8458 - val_accuracy: 0.5042 - val_recall_m: 0.2059 - val_precision_m: 0.9152 - val_f1_m: 0.3339\n",
      "Epoch 33/100\n",
      "156/156 [==============================] - 109s 696ms/step - loss: 1.4517 - accuracy: 0.6031 - recall_m: 0.4571 - precision_m: 0.8094 - f1_m: 0.5825 - val_loss: 1.7563 - val_accuracy: 0.5364 - val_recall_m: 0.2112 - val_precision_m: 0.9170 - val_f1_m: 0.3407\n",
      "Epoch 34/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 1.4326 - accuracy: 0.6031 - recall_m: 0.4649 - precision_m: 0.8010 - f1_m: 0.5867 - val_loss: 2.2320 - val_accuracy: 0.5318 - val_recall_m: 0.1934 - val_precision_m: 0.9234 - val_f1_m: 0.3172\n",
      "Epoch 35/100\n",
      "156/156 [==============================] - 109s 697ms/step - loss: 1.4065 - accuracy: 0.6157 - recall_m: 0.4736 - precision_m: 0.8068 - f1_m: 0.5948 - val_loss: 1.9991 - val_accuracy: 0.5262 - val_recall_m: 0.2106 - val_precision_m: 0.9290 - val_f1_m: 0.3415\n",
      "Epoch 36/100\n",
      "156/156 [==============================] - 108s 695ms/step - loss: 1.3790 - accuracy: 0.6173 - recall_m: 0.4821 - precision_m: 0.8149 - f1_m: 0.6043 - val_loss: 1.5758 - val_accuracy: 0.5468 - val_recall_m: 0.2475 - val_precision_m: 0.9216 - val_f1_m: 0.3878\n",
      "Epoch 37/100\n",
      "156/156 [==============================] - 108s 695ms/step - loss: 1.4309 - accuracy: 0.6080 - recall_m: 0.4635 - precision_m: 0.8020 - f1_m: 0.5853 - val_loss: 2.3180 - val_accuracy: 0.5388 - val_recall_m: 0.2205 - val_precision_m: 0.9314 - val_f1_m: 0.3537\n",
      "Epoch 38/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 1.3359 - accuracy: 0.6270 - recall_m: 0.4914 - precision_m: 0.8099 - f1_m: 0.6100 - val_loss: 1.7221 - val_accuracy: 0.5482 - val_recall_m: 0.2550 - val_precision_m: 0.9108 - val_f1_m: 0.3958\n",
      "Epoch 39/100\n",
      "156/156 [==============================] - 108s 690ms/step - loss: 1.3414 - accuracy: 0.6268 - recall_m: 0.4934 - precision_m: 0.8082 - f1_m: 0.6109 - val_loss: 2.0821 - val_accuracy: 0.5520 - val_recall_m: 0.2508 - val_precision_m: 0.9220 - val_f1_m: 0.3912\n",
      "Epoch 40/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 1.2864 - accuracy: 0.6458 - recall_m: 0.5128 - precision_m: 0.8201 - f1_m: 0.6295 - val_loss: 2.0408 - val_accuracy: 0.4726 - val_recall_m: 0.2303 - val_precision_m: 0.8126 - val_f1_m: 0.3563\n",
      "Epoch 41/100\n",
      "156/156 [==============================] - 108s 695ms/step - loss: 1.2501 - accuracy: 0.6478 - recall_m: 0.5175 - precision_m: 0.8201 - f1_m: 0.6332 - val_loss: 1.7924 - val_accuracy: 0.5472 - val_recall_m: 0.2600 - val_precision_m: 0.8985 - val_f1_m: 0.4011\n",
      "Epoch 42/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 1.2925 - accuracy: 0.6415 - recall_m: 0.5112 - precision_m: 0.8143 - f1_m: 0.6264 - val_loss: 1.7867 - val_accuracy: 0.5558 - val_recall_m: 0.2504 - val_precision_m: 0.9085 - val_f1_m: 0.3900\n",
      "Epoch 43/100\n",
      "156/156 [==============================] - 108s 690ms/step - loss: 1.2231 - accuracy: 0.6559 - recall_m: 0.5330 - precision_m: 0.8182 - f1_m: 0.6437 - val_loss: 2.0697 - val_accuracy: 0.5274 - val_recall_m: 0.2574 - val_precision_m: 0.8971 - val_f1_m: 0.3979\n",
      "Epoch 44/100\n",
      "156/156 [==============================] - 108s 694ms/step - loss: 1.2444 - accuracy: 0.6539 - recall_m: 0.5244 - precision_m: 0.8207 - f1_m: 0.6383 - val_loss: 1.6115 - val_accuracy: 0.5354 - val_recall_m: 0.2504 - val_precision_m: 0.8850 - val_f1_m: 0.3869\n",
      "Epoch 45/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 1.1895 - accuracy: 0.6610 - recall_m: 0.5379 - precision_m: 0.8220 - f1_m: 0.6487 - val_loss: 1.5081 - val_accuracy: 0.5558 - val_recall_m: 0.2798 - val_precision_m: 0.8844 - val_f1_m: 0.4221\n",
      "Epoch 46/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 1.1701 - accuracy: 0.6716 - recall_m: 0.5546 - precision_m: 0.8268 - f1_m: 0.6626 - val_loss: 1.7522 - val_accuracy: 0.5748 - val_recall_m: 0.2917 - val_precision_m: 0.9122 - val_f1_m: 0.4396\n",
      "Epoch 47/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 1.1515 - accuracy: 0.6760 - recall_m: 0.5575 - precision_m: 0.8268 - f1_m: 0.6645 - val_loss: 1.8139 - val_accuracy: 0.5572 - val_recall_m: 0.2680 - val_precision_m: 0.8925 - val_f1_m: 0.4096\n",
      "Epoch 48/100\n",
      "156/156 [==============================] - 108s 689ms/step - loss: 1.1505 - accuracy: 0.6714 - recall_m: 0.5535 - precision_m: 0.8260 - f1_m: 0.6613 - val_loss: 2.1455 - val_accuracy: 0.5682 - val_recall_m: 0.3004 - val_precision_m: 0.8758 - val_f1_m: 0.4444\n",
      "Epoch 49/100\n",
      "156/156 [==============================] - 109s 696ms/step - loss: 1.1105 - accuracy: 0.6827 - recall_m: 0.5684 - precision_m: 0.8382 - f1_m: 0.6761 - val_loss: 2.0350 - val_accuracy: 0.5676 - val_recall_m: 0.2816 - val_precision_m: 0.8991 - val_f1_m: 0.4274\n",
      "Epoch 50/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 1.1302 - accuracy: 0.6862 - recall_m: 0.5640 - precision_m: 0.8323 - f1_m: 0.6703 - val_loss: 1.8095 - val_accuracy: 0.5646 - val_recall_m: 0.3211 - val_precision_m: 0.8749 - val_f1_m: 0.4667\n",
      "Epoch 51/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 1.1053 - accuracy: 0.6866 - recall_m: 0.5709 - precision_m: 0.8244 - f1_m: 0.6733 - val_loss: 1.5381 - val_accuracy: 0.5676 - val_recall_m: 0.3012 - val_precision_m: 0.8915 - val_f1_m: 0.4475\n",
      "Epoch 52/100\n",
      "156/156 [==============================] - 108s 689ms/step - loss: 1.0820 - accuracy: 0.6920 - recall_m: 0.5772 - precision_m: 0.8296 - f1_m: 0.6786 - val_loss: 2.0084 - val_accuracy: 0.5702 - val_recall_m: 0.3044 - val_precision_m: 0.8869 - val_f1_m: 0.4507\n",
      "Epoch 53/100\n",
      "156/156 [==============================] - 108s 690ms/step - loss: 1.0735 - accuracy: 0.6989 - recall_m: 0.5850 - precision_m: 0.8358 - f1_m: 0.6868 - val_loss: 1.4882 - val_accuracy: 0.5568 - val_recall_m: 0.3034 - val_precision_m: 0.8851 - val_f1_m: 0.4496\n",
      "Epoch 54/100\n",
      "156/156 [==============================] - 110s 708ms/step - loss: 1.0455 - accuracy: 0.7049 - recall_m: 0.5973 - precision_m: 0.8402 - f1_m: 0.6969 - val_loss: 1.4364 - val_accuracy: 0.5724 - val_recall_m: 0.3215 - val_precision_m: 0.8832 - val_f1_m: 0.4690\n",
      "Epoch 55/100\n",
      "156/156 [==============================] - 109s 699ms/step - loss: 1.0198 - accuracy: 0.7086 - recall_m: 0.6020 - precision_m: 0.8414 - f1_m: 0.7005 - val_loss: 1.5437 - val_accuracy: 0.5742 - val_recall_m: 0.3286 - val_precision_m: 0.8828 - val_f1_m: 0.4762\n",
      "Epoch 56/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 1.0077 - accuracy: 0.7109 - recall_m: 0.6090 - precision_m: 0.8395 - f1_m: 0.7049 - val_loss: 1.4395 - val_accuracy: 0.5736 - val_recall_m: 0.3227 - val_precision_m: 0.8705 - val_f1_m: 0.4685\n",
      "Epoch 57/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 1.0067 - accuracy: 0.7116 - recall_m: 0.6072 - precision_m: 0.8368 - f1_m: 0.7025 - val_loss: 1.5261 - val_accuracy: 0.5754 - val_recall_m: 0.3185 - val_precision_m: 0.8870 - val_f1_m: 0.4666\n",
      "Epoch 58/100\n",
      "156/156 [==============================] - 109s 696ms/step - loss: 1.0007 - accuracy: 0.7095 - recall_m: 0.6044 - precision_m: 0.8350 - f1_m: 0.7003 - val_loss: 1.1272 - val_accuracy: 0.5850 - val_recall_m: 0.3407 - val_precision_m: 0.8823 - val_f1_m: 0.4894\n",
      "Epoch 59/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 1.0173 - accuracy: 0.7115 - recall_m: 0.6046 - precision_m: 0.8425 - f1_m: 0.7022 - val_loss: 1.3470 - val_accuracy: 0.5788 - val_recall_m: 0.3488 - val_precision_m: 0.8542 - val_f1_m: 0.4929\n",
      "Epoch 60/100\n",
      "156/156 [==============================] - 108s 694ms/step - loss: 0.9772 - accuracy: 0.7210 - recall_m: 0.6196 - precision_m: 0.8431 - f1_m: 0.7129 - val_loss: 1.8627 - val_accuracy: 0.5640 - val_recall_m: 0.3146 - val_precision_m: 0.8582 - val_f1_m: 0.4583\n",
      "Epoch 61/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 0.9628 - accuracy: 0.7237 - recall_m: 0.6217 - precision_m: 0.8443 - f1_m: 0.7150 - val_loss: 1.5686 - val_accuracy: 0.5716 - val_recall_m: 0.3205 - val_precision_m: 0.8763 - val_f1_m: 0.4668\n",
      "Epoch 62/100\n",
      "156/156 [==============================] - 108s 695ms/step - loss: 0.9622 - accuracy: 0.7212 - recall_m: 0.6221 - precision_m: 0.8453 - f1_m: 0.7154 - val_loss: 1.8124 - val_accuracy: 0.5932 - val_recall_m: 0.3553 - val_precision_m: 0.8838 - val_f1_m: 0.5049\n",
      "Epoch 63/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 0.9327 - accuracy: 0.7287 - recall_m: 0.6326 - precision_m: 0.8438 - f1_m: 0.7220 - val_loss: 2.1004 - val_accuracy: 0.5948 - val_recall_m: 0.3679 - val_precision_m: 0.8619 - val_f1_m: 0.5127\n",
      "Epoch 64/100\n",
      "156/156 [==============================] - 108s 690ms/step - loss: 0.9056 - accuracy: 0.7346 - recall_m: 0.6409 - precision_m: 0.8450 - f1_m: 0.7279 - val_loss: 1.4893 - val_accuracy: 0.5688 - val_recall_m: 0.3450 - val_precision_m: 0.8424 - val_f1_m: 0.4869\n",
      "Epoch 65/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 0.9017 - accuracy: 0.7351 - recall_m: 0.6446 - precision_m: 0.8471 - f1_m: 0.7311 - val_loss: 1.7939 - val_accuracy: 0.5736 - val_recall_m: 0.3427 - val_precision_m: 0.8490 - val_f1_m: 0.4860\n",
      "Epoch 66/100\n",
      "156/156 [==============================] - 107s 688ms/step - loss: 0.8786 - accuracy: 0.7429 - recall_m: 0.6571 - precision_m: 0.8522 - f1_m: 0.7411 - val_loss: 1.3850 - val_accuracy: 0.5908 - val_recall_m: 0.3657 - val_precision_m: 0.8703 - val_f1_m: 0.5125\n",
      "Epoch 67/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 0.8532 - accuracy: 0.7460 - recall_m: 0.6613 - precision_m: 0.8511 - f1_m: 0.7431 - val_loss: 1.8046 - val_accuracy: 0.5868 - val_recall_m: 0.3723 - val_precision_m: 0.8595 - val_f1_m: 0.5179\n",
      "Epoch 68/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.8334 - accuracy: 0.7528 - recall_m: 0.6741 - precision_m: 0.8593 - f1_m: 0.7546 - val_loss: 1.9680 - val_accuracy: 0.5946 - val_recall_m: 0.3751 - val_precision_m: 0.8648 - val_f1_m: 0.5209\n",
      "Epoch 69/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.8428 - accuracy: 0.7486 - recall_m: 0.6638 - precision_m: 0.8566 - f1_m: 0.7468 - val_loss: 1.7325 - val_accuracy: 0.5762 - val_recall_m: 0.3902 - val_precision_m: 0.8368 - val_f1_m: 0.5294\n",
      "Epoch 70/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 0.8502 - accuracy: 0.7480 - recall_m: 0.6655 - precision_m: 0.8501 - f1_m: 0.7457 - val_loss: 1.2306 - val_accuracy: 0.5854 - val_recall_m: 0.3693 - val_precision_m: 0.8578 - val_f1_m: 0.5140\n",
      "Epoch 71/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.8702 - accuracy: 0.7440 - recall_m: 0.6549 - precision_m: 0.8469 - f1_m: 0.7378 - val_loss: 1.7819 - val_accuracy: 0.5726 - val_recall_m: 0.3811 - val_precision_m: 0.8353 - val_f1_m: 0.5209\n",
      "Epoch 72/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.8641 - accuracy: 0.7433 - recall_m: 0.6592 - precision_m: 0.8443 - f1_m: 0.7393 - val_loss: 1.4244 - val_accuracy: 0.5882 - val_recall_m: 0.3805 - val_precision_m: 0.8658 - val_f1_m: 0.5268\n",
      "Epoch 73/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.8092 - accuracy: 0.7588 - recall_m: 0.6782 - precision_m: 0.8585 - f1_m: 0.7570 - val_loss: 1.2769 - val_accuracy: 0.5830 - val_recall_m: 0.4014 - val_precision_m: 0.8179 - val_f1_m: 0.5367\n",
      "Epoch 74/100\n",
      "156/156 [==============================] - 107s 688ms/step - loss: 0.8374 - accuracy: 0.7504 - recall_m: 0.6699 - precision_m: 0.8541 - f1_m: 0.7501 - val_loss: 1.6372 - val_accuracy: 0.5818 - val_recall_m: 0.3719 - val_precision_m: 0.8409 - val_f1_m: 0.5136\n",
      "Epoch 75/100\n",
      "156/156 [==============================] - 108s 694ms/step - loss: 0.7724 - accuracy: 0.7629 - recall_m: 0.6845 - precision_m: 0.8611 - f1_m: 0.7618 - val_loss: 1.7822 - val_accuracy: 0.6064 - val_recall_m: 0.4051 - val_precision_m: 0.8680 - val_f1_m: 0.5501\n",
      "Epoch 76/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.7933 - accuracy: 0.7641 - recall_m: 0.6833 - precision_m: 0.8566 - f1_m: 0.7592 - val_loss: 1.7297 - val_accuracy: 0.5910 - val_recall_m: 0.3796 - val_precision_m: 0.8523 - val_f1_m: 0.5233\n",
      "Epoch 77/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 0.7682 - accuracy: 0.7702 - recall_m: 0.6919 - precision_m: 0.8642 - f1_m: 0.7678 - val_loss: 1.6735 - val_accuracy: 0.5806 - val_recall_m: 0.3932 - val_precision_m: 0.8164 - val_f1_m: 0.5287\n",
      "Epoch 78/100\n",
      "156/156 [==============================] - 107s 687ms/step - loss: 0.7817 - accuracy: 0.7643 - recall_m: 0.6867 - precision_m: 0.8529 - f1_m: 0.7600 - val_loss: 1.7384 - val_accuracy: 0.5954 - val_recall_m: 0.3892 - val_precision_m: 0.8546 - val_f1_m: 0.5325\n",
      "Epoch 79/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 0.7471 - accuracy: 0.7770 - recall_m: 0.6998 - precision_m: 0.8611 - f1_m: 0.7713 - val_loss: 1.8965 - val_accuracy: 0.5972 - val_recall_m: 0.4094 - val_precision_m: 0.8343 - val_f1_m: 0.5474\n",
      "Epoch 80/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.7400 - accuracy: 0.7749 - recall_m: 0.7006 - precision_m: 0.8633 - f1_m: 0.7728 - val_loss: 1.7818 - val_accuracy: 0.5844 - val_recall_m: 0.4021 - val_precision_m: 0.8199 - val_f1_m: 0.5379\n",
      "Epoch 81/100\n",
      "156/156 [==============================] - 108s 695ms/step - loss: 0.7318 - accuracy: 0.7805 - recall_m: 0.7087 - precision_m: 0.8714 - f1_m: 0.7809 - val_loss: 1.9551 - val_accuracy: 0.5888 - val_recall_m: 0.4090 - val_precision_m: 0.8345 - val_f1_m: 0.5466\n",
      "Epoch 82/100\n",
      "156/156 [==============================] - 107s 688ms/step - loss: 0.7657 - accuracy: 0.7745 - recall_m: 0.6981 - precision_m: 0.8566 - f1_m: 0.7684 - val_loss: 1.5684 - val_accuracy: 0.5804 - val_recall_m: 0.3980 - val_precision_m: 0.8288 - val_f1_m: 0.5361\n",
      "Epoch 83/100\n",
      "156/156 [==============================] - 108s 695ms/step - loss: 0.7299 - accuracy: 0.7763 - recall_m: 0.7030 - precision_m: 0.8641 - f1_m: 0.7746 - val_loss: 1.8907 - val_accuracy: 0.5932 - val_recall_m: 0.4218 - val_precision_m: 0.8341 - val_f1_m: 0.5585\n",
      "Epoch 84/100\n",
      "156/156 [==============================] - 108s 690ms/step - loss: 0.6975 - accuracy: 0.7912 - recall_m: 0.7284 - precision_m: 0.8711 - f1_m: 0.7926 - val_loss: 1.5124 - val_accuracy: 0.5882 - val_recall_m: 0.4163 - val_precision_m: 0.8334 - val_f1_m: 0.5526\n",
      "Epoch 85/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.7286 - accuracy: 0.7814 - recall_m: 0.7153 - precision_m: 0.8688 - f1_m: 0.7839 - val_loss: 1.8073 - val_accuracy: 0.5910 - val_recall_m: 0.4013 - val_precision_m: 0.8392 - val_f1_m: 0.5413\n",
      "Epoch 86/100\n",
      "156/156 [==============================] - 109s 696ms/step - loss: 0.7079 - accuracy: 0.7877 - recall_m: 0.7198 - precision_m: 0.8768 - f1_m: 0.7899 - val_loss: 1.2317 - val_accuracy: 0.5888 - val_recall_m: 0.4156 - val_precision_m: 0.8222 - val_f1_m: 0.5503\n",
      "Epoch 87/100\n",
      "156/156 [==============================] - 108s 690ms/step - loss: 0.7148 - accuracy: 0.7840 - recall_m: 0.7169 - precision_m: 0.8669 - f1_m: 0.7839 - val_loss: 1.7741 - val_accuracy: 0.5842 - val_recall_m: 0.3883 - val_precision_m: 0.8273 - val_f1_m: 0.5267\n",
      "Epoch 88/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 0.6780 - accuracy: 0.7962 - recall_m: 0.7289 - precision_m: 0.8758 - f1_m: 0.7950 - val_loss: 1.8078 - val_accuracy: 0.6106 - val_recall_m: 0.4352 - val_precision_m: 0.8297 - val_f1_m: 0.5693\n",
      "Epoch 89/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.6760 - accuracy: 0.7944 - recall_m: 0.7340 - precision_m: 0.8751 - f1_m: 0.7977 - val_loss: 1.6529 - val_accuracy: 0.5970 - val_recall_m: 0.4142 - val_precision_m: 0.8349 - val_f1_m: 0.5517\n",
      "Epoch 90/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.6408 - accuracy: 0.8073 - recall_m: 0.7377 - precision_m: 0.8767 - f1_m: 0.8006 - val_loss: 1.7462 - val_accuracy: 0.5994 - val_recall_m: 0.4429 - val_precision_m: 0.8120 - val_f1_m: 0.5714\n",
      "Epoch 91/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "156/156 [==============================] - 108s 689ms/step - loss: 0.6476 - accuracy: 0.8027 - recall_m: 0.7416 - precision_m: 0.8770 - f1_m: 0.8030 - val_loss: 1.6742 - val_accuracy: 0.5958 - val_recall_m: 0.4288 - val_precision_m: 0.8276 - val_f1_m: 0.5631\n",
      "Epoch 92/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 0.6275 - accuracy: 0.8056 - recall_m: 0.7426 - precision_m: 0.8777 - f1_m: 0.8037 - val_loss: 1.3676 - val_accuracy: 0.5954 - val_recall_m: 0.4280 - val_precision_m: 0.8051 - val_f1_m: 0.5572\n",
      "Epoch 93/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 0.6226 - accuracy: 0.8101 - recall_m: 0.7550 - precision_m: 0.8816 - f1_m: 0.8129 - val_loss: 1.3895 - val_accuracy: 0.6056 - val_recall_m: 0.4581 - val_precision_m: 0.8247 - val_f1_m: 0.5878\n",
      "Epoch 94/100\n",
      "156/156 [==============================] - 108s 692ms/step - loss: 0.6980 - accuracy: 0.7932 - recall_m: 0.7278 - precision_m: 0.8673 - f1_m: 0.7907 - val_loss: 1.8155 - val_accuracy: 0.5934 - val_recall_m: 0.4332 - val_precision_m: 0.8070 - val_f1_m: 0.5622\n",
      "Epoch 95/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.6606 - accuracy: 0.8035 - recall_m: 0.7437 - precision_m: 0.8751 - f1_m: 0.8034 - val_loss: 1.7612 - val_accuracy: 0.5814 - val_recall_m: 0.3973 - val_precision_m: 0.8477 - val_f1_m: 0.5393\n",
      "Epoch 96/100\n",
      "156/156 [==============================] - 108s 691ms/step - loss: 0.6613 - accuracy: 0.8033 - recall_m: 0.7383 - precision_m: 0.8783 - f1_m: 0.8016 - val_loss: 1.2800 - val_accuracy: 0.6056 - val_recall_m: 0.4462 - val_precision_m: 0.8328 - val_f1_m: 0.5792\n",
      "Epoch 97/100\n",
      "156/156 [==============================] - 107s 689ms/step - loss: 0.6119 - accuracy: 0.8100 - recall_m: 0.7570 - precision_m: 0.8862 - f1_m: 0.8159 - val_loss: 1.8885 - val_accuracy: 0.6042 - val_recall_m: 0.4280 - val_precision_m: 0.8160 - val_f1_m: 0.5595\n",
      "Epoch 98/100\n",
      "156/156 [==============================] - 108s 694ms/step - loss: 0.6117 - accuracy: 0.8133 - recall_m: 0.7560 - precision_m: 0.8839 - f1_m: 0.8144 - val_loss: 1.7777 - val_accuracy: 0.6032 - val_recall_m: 0.4466 - val_precision_m: 0.8209 - val_f1_m: 0.5767\n",
      "Epoch 99/100\n",
      "156/156 [==============================] - 108s 689ms/step - loss: 0.6017 - accuracy: 0.8180 - recall_m: 0.7641 - precision_m: 0.8848 - f1_m: 0.8196 - val_loss: 1.6508 - val_accuracy: 0.5980 - val_recall_m: 0.4432 - val_precision_m: 0.8281 - val_f1_m: 0.5754\n",
      "Epoch 100/100\n",
      "156/156 [==============================] - 108s 693ms/step - loss: 0.6075 - accuracy: 0.8149 - recall_m: 0.7603 - precision_m: 0.8776 - f1_m: 0.8143 - val_loss: 1.6953 - val_accuracy: 0.6042 - val_recall_m: 0.4447 - val_precision_m: 0.8178 - val_f1_m: 0.5736\n"
     ]
    }
   ],
   "source": [
    "history = model.fit_generator(train, steps_per_epoch=10000//64,\n",
    "                    epochs=100, validation_data=test,\n",
    "                    validation_steps=80, verbose=1, )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['val_loss', 'val_accuracy', 'val_recall_m', 'val_precision_m', 'val_f1_m', 'loss', 'accuracy', 'recall_m', 'precision_m', 'f1_m'])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "history.history.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>val_loss</th>\n",
       "      <th>val_accuracy</th>\n",
       "      <th>val_recall_m</th>\n",
       "      <th>val_precision_m</th>\n",
       "      <th>val_f1_m</th>\n",
       "      <th>loss</th>\n",
       "      <th>accuracy</th>\n",
       "      <th>recall_m</th>\n",
       "      <th>precision_m</th>\n",
       "      <th>f1_m</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>4.355263</td>\n",
       "      <td>0.0710</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.538037</td>\n",
       "      <td>0.028517</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>4.043817</td>\n",
       "      <td>0.1222</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.192393</td>\n",
       "      <td>0.078194</td>\n",
       "      <td>0.003606</td>\n",
       "      <td>0.162393</td>\n",
       "      <td>0.007029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>3.814821</td>\n",
       "      <td>0.1820</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.842703</td>\n",
       "      <td>0.126360</td>\n",
       "      <td>0.016126</td>\n",
       "      <td>0.513889</td>\n",
       "      <td>0.030993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>3.639455</td>\n",
       "      <td>0.2098</td>\n",
       "      <td>0.000195</td>\n",
       "      <td>0.0125</td>\n",
       "      <td>0.000385</td>\n",
       "      <td>3.570682</td>\n",
       "      <td>0.175836</td>\n",
       "      <td>0.035557</td>\n",
       "      <td>0.657828</td>\n",
       "      <td>0.066635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>3.741517</td>\n",
       "      <td>0.2500</td>\n",
       "      <td>0.002344</td>\n",
       "      <td>0.1375</td>\n",
       "      <td>0.004604</td>\n",
       "      <td>3.368065</td>\n",
       "      <td>0.209043</td>\n",
       "      <td>0.053886</td>\n",
       "      <td>0.691776</td>\n",
       "      <td>0.098404</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   val_loss  val_accuracy  val_recall_m  val_precision_m  val_f1_m      loss  \\\n",
       "0  4.355263        0.0710      0.000000           0.0000  0.000000  4.538037   \n",
       "1  4.043817        0.1222      0.000000           0.0000  0.000000  4.192393   \n",
       "2  3.814821        0.1820      0.000000           0.0000  0.000000  3.842703   \n",
       "3  3.639455        0.2098      0.000195           0.0125  0.000385  3.570682   \n",
       "4  3.741517        0.2500      0.002344           0.1375  0.004604  3.368065   \n",
       "\n",
       "   accuracy  recall_m  precision_m      f1_m  \n",
       "0  0.028517  0.000000     0.000000  0.000000  \n",
       "1  0.078194  0.003606     0.162393  0.007029  \n",
       "2  0.126360  0.016126     0.513889  0.030993  \n",
       "3  0.175836  0.035557     0.657828  0.066635  \n",
       "4  0.209043  0.053886     0.691776  0.098404  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_csv = pd.DataFrame(data=history.history)\n",
    "data_csv.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Saving CSV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_csv.to_csv(\"metris.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Accuracy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "dict_keys(['val_loss', 'val_accuracy', 'val_recall_m', 'val_precision_m', 'val_f1_m', 'loss', 'accuracy', 'recall_m', 'precision_m', 'f1_m'])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "print(history.history.keys())\n",
    "# summarize history for accuracy\n",
    "plt.plot(history.history['accuracy'])\n",
    "plt.plot(history.history['val_accuracy'])\n",
    "plt.title('model accuracy')\n",
    "plt.ylabel('accuracy')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'test'], loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['loss'])\n",
    "plt.plot(history.history['val_loss'])\n",
    "plt.title('model loss')\n",
    "plt.ylabel('loss')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'test'], loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Recall"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['recall_m'])\n",
    "plt.plot(history.history['val_recall_m'])\n",
    "plt.title('model recall')\n",
    "plt.ylabel('recall')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'test'], loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Precision"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['precision_m'])\n",
    "plt.plot(history.history['val_precision_m'])\n",
    "plt.title('model precision')\n",
    "plt.ylabel('recision')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'test'], loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F1_Score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['f1_m'])\n",
    "plt.plot(history.history['val_f1_m'])\n",
    "plt.title('model f1_score')\n",
    "plt.ylabel('f1')\n",
    "plt.xlabel('epoch')\n",
    "plt.legend(['train', 'test'], loc='upper left')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Predicting"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SUPERMAN\\Anaconda3\\lib\\site-packages\\keras_preprocessing\\image\\image_data_generator.py:716: UserWarning: This ImageDataGenerator specifies `featurewise_center`, but it hasn't been fit on any training data. Fit it first by calling `.fit(numpy_data)`.\n",
      "  warnings.warn('This ImageDataGenerator specifies '\n",
      "C:\\Users\\SUPERMAN\\Anaconda3\\lib\\site-packages\\keras_preprocessing\\image\\image_data_generator.py:724: UserWarning: This ImageDataGenerator specifies `featurewise_std_normalization`, but it hasn't been fit on any training data. Fit it first by calling `.fit(numpy_data)`.\n",
      "  warnings.warn('This ImageDataGenerator specifies '\n"
     ]
    }
   ],
   "source": [
    "y_pred = model.predict(test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.014"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from sklearn.metrics import accuracy_score\n",
    "accuracy_score(y_pred, t)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_pred = np.argmax(y_pred, axis=-1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Confusion matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Confusion Matrix\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2560x2560 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn.metrics import confusion_matrix\n",
    "import seaborn as sns\n",
    "from matplotlib.pyplot import figure\n",
    "figure(num=None, figsize=(32, 32), dpi=80, facecolor='w', edgecolor='k')\n",
    "\n",
    "print('Confusion Matrix')\n",
    "#print(sns.heatmap(confusion_matrix(class_, y_pred), fmt='.2f', annot=True))\n",
    "img = sns.heatmap(confusion_matrix(class_, y_pred), fmt='.2f', annot=True)\n",
    "img.figure.savefig(\"confusion_matrix.jpg\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}