RESNET 50.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "dc9898ca",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow.keras.layers import Input, Flatten, Dense\n",
    "from tensorflow.keras.models import Model\n",
    "from tensorflow.keras.applications.resnet50 import ResNet50, preprocess_input\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c5dac487",
   "metadata": {},
   "outputs": [],
   "source": [
    "config = tf.compat.v1.ConfigProto()\n",
    "config.gpu_options.per_process_gpu_memory_fraction = 0.5\n",
    "config.gpu_options.allow_growth = True\n",
    "session = tf.compat.v1.InteractiveSession(config=config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a730b475",
   "metadata": {},
   "outputs": [],
   "source": [
    "IMAGE_SIZE = (224, 224)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c5fa01ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 1924 files belonging to 2 classes.\n"
     ]
    }
   ],
   "source": [
    "train_ds=tf.keras.preprocessing.image_dataset_from_directory(\n",
    "    r'C:\\Users\\dushy\\Downloads\\archive (14)\\data\\train',\n",
    "    labels=\"inferred\",\n",
    "    label_mode=\"binary\",\n",
    "    class_names=None,\n",
    "    color_mode=\"rgb\",\n",
    "    batch_size=32,\n",
    "    image_size=(224, 224),\n",
    "    shuffle=True,\n",
    "    seed=24,\n",
    "    validation_split=None,\n",
    "    subset=None,\n",
    "    interpolation=\"bilinear\",\n",
    "    follow_links=True,\n",
    "    crop_to_aspect_ratio=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "52022962",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 1348 images belonging to 2 classes.\n",
      "Found 576 images belonging to 2 classes.\n"
     ]
    }
   ],
   "source": [
    "\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "# create generator\n",
    "datagen = ImageDataGenerator(rescale = 1./255,\n",
    "                             shear_range = 0.2,\n",
    "                             zoom_range = 0.2,\n",
    "                             horizontal_flip = True,\n",
    "                             vertical_flip=True,\n",
    "                             rotation_range=30,\n",
    "                             validation_split=0.3,\n",
    "                             fill_mode='nearest'\n",
    "                             )\n",
    "# prepare an iterators for each dataset\n",
    "train_it = datagen.flow_from_directory(r'C:\\Users\\dushy\\Downloads\\archive (14)\\data\\train', \n",
    "                                       class_mode='categorical',\n",
    "                                       classes=['infected', 'notinfected'],\n",
    "                                       target_size=(224, 224),\n",
    "                                       batch_size=100,\n",
    "                                       subset='training',\n",
    "                                       seed=24)\n",
    "# prepare an iterators for each dataset\n",
    "val_it = datagen.flow_from_directory(r'C:\\Users\\dushy\\Downloads\\archive (14)\\data\\train', \n",
    "                                       class_mode='categorical',\n",
    "                                       classes=['infected', 'notinfected'],\n",
    "                                       target_size=(224, 224),\n",
    "                                       batch_size=100,\n",
    "                                       subset='validation',\n",
    "                                       seed=24)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4c5f6c06",
   "metadata": {},
   "outputs": [],
   "source": [
    "base_model = ResNet50(input_shape=(224, 224, 3), weights='imagenet', include_top=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "5383d209",
   "metadata": {},
   "outputs": [],
   "source": [
    "x = base_model.output\n",
    "x = Flatten()(x)\n",
    "predictions = Dense(len(train_it.class_indices), activation='softmax')(x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "cfc69085",
   "metadata": {},
   "outputs": [],
   "source": [
    "model = Model(inputs=base_model.input, outputs=predictions)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "5d6b2186",
   "metadata": {},
   "outputs": [],
   "source": [
    "for layer in base_model.layers:\n",
    "    layer.trainable = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "d93f8f16",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(\n",
    "    loss='categorical_crossentropy',\n",
    "    optimizer='adam',\n",
    "    metrics=['accuracy']\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "bc0dfb7e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "14/14 [==============================] - 123s 9s/step - loss: 2.6538 - accuracy: 0.5549 - val_loss: 0.1644 - val_accuracy: 0.9566\n",
      "Epoch 2/10\n",
      "14/14 [==============================] - 121s 9s/step - loss: 0.3375 - accuracy: 0.8828 - val_loss: 0.1529 - val_accuracy: 0.9323\n",
      "Epoch 3/10\n",
      "14/14 [==============================] - 124s 9s/step - loss: 0.1480 - accuracy: 0.9466 - val_loss: 0.1126 - val_accuracy: 0.9670\n",
      "Epoch 4/10\n",
      "14/14 [==============================] - 118s 9s/step - loss: 0.1046 - accuracy: 0.9659 - val_loss: 0.0756 - val_accuracy: 0.9740\n",
      "Epoch 5/10\n",
      "14/14 [==============================] - 110s 8s/step - loss: 0.0950 - accuracy: 0.9740 - val_loss: 0.0782 - val_accuracy: 0.9757\n",
      "Epoch 6/10\n",
      "14/14 [==============================] - 111s 8s/step - loss: 0.0766 - accuracy: 0.9755 - val_loss: 0.0748 - val_accuracy: 0.9792\n",
      "Epoch 7/10\n",
      "14/14 [==============================] - 111s 8s/step - loss: 0.0931 - accuracy: 0.9711 - val_loss: 0.0993 - val_accuracy: 0.9601\n",
      "Epoch 8/10\n",
      "14/14 [==============================] - 113s 8s/step - loss: 0.0936 - accuracy: 0.9674 - val_loss: 0.0846 - val_accuracy: 0.9809\n",
      "Epoch 9/10\n",
      "14/14 [==============================] - 113s 8s/step - loss: 0.0730 - accuracy: 0.9785 - val_loss: 0.0698 - val_accuracy: 0.9757\n",
      "Epoch 10/10\n",
      "14/14 [==============================] - 112s 8s/step - loss: 0.0712 - accuracy: 0.9800 - val_loss: 0.0502 - val_accuracy: 0.9913\n"
     ]
    }
   ],
   "source": [
    "history = model.fit(\n",
    "    train_it,\n",
    "    validation_data=val_it,\n",
    "    epochs=10,\n",
    "    steps_per_epoch=len(train_it),\n",
    "    validation_steps=len(val_it)\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "189305dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model_1\"\n",
      "__________________________________________________________________________________________________\n",
      " Layer (type)                   Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      " input_2 (InputLayer)           [(None, 224, 224, 3  0           []                               \n",
      "                                )]                                                                \n",
      "                                                                                                  \n",
      " conv1_pad (ZeroPadding2D)      (None, 230, 230, 3)  0           ['input_2[0][0]']                \n",
      "                                                                                                  \n",
      " conv1_conv (Conv2D)            (None, 112, 112, 64  9472        ['conv1_pad[0][0]']              \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv1_bn (BatchNormalization)  (None, 112, 112, 64  256         ['conv1_conv[0][0]']             \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv1_relu (Activation)        (None, 112, 112, 64  0           ['conv1_bn[0][0]']               \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " pool1_pad (ZeroPadding2D)      (None, 114, 114, 64  0           ['conv1_relu[0][0]']             \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " pool1_pool (MaxPooling2D)      (None, 56, 56, 64)   0           ['pool1_pad[0][0]']              \n",
      "                                                                                                  \n",
      " conv2_block1_1_conv (Conv2D)   (None, 56, 56, 64)   4160        ['pool1_pool[0][0]']             \n",
      "                                                                                                  \n",
      " conv2_block1_1_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block1_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv2_block1_1_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block1_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block1_2_conv (Conv2D)   (None, 56, 56, 64)   36928       ['conv2_block1_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv2_block1_2_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block1_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv2_block1_2_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block1_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block1_0_conv (Conv2D)   (None, 56, 56, 256)  16640       ['pool1_pool[0][0]']             \n",
      "                                                                                                  \n",
      " conv2_block1_3_conv (Conv2D)   (None, 56, 56, 256)  16640       ['conv2_block1_2_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv2_block1_0_bn (BatchNormal  (None, 56, 56, 256)  1024       ['conv2_block1_0_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv2_block1_3_bn (BatchNormal  (None, 56, 56, 256)  1024       ['conv2_block1_3_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv2_block1_add (Add)         (None, 56, 56, 256)  0           ['conv2_block1_0_bn[0][0]',      \n",
      "                                                                  'conv2_block1_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv2_block1_out (Activation)  (None, 56, 56, 256)  0           ['conv2_block1_add[0][0]']       \n",
      "                                                                                                  \n",
      " conv2_block2_1_conv (Conv2D)   (None, 56, 56, 64)   16448       ['conv2_block1_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv2_block2_1_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block2_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv2_block2_1_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block2_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block2_2_conv (Conv2D)   (None, 56, 56, 64)   36928       ['conv2_block2_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv2_block2_2_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block2_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv2_block2_2_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block2_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block2_3_conv (Conv2D)   (None, 56, 56, 256)  16640       ['conv2_block2_2_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv2_block2_3_bn (BatchNormal  (None, 56, 56, 256)  1024       ['conv2_block2_3_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv2_block2_add (Add)         (None, 56, 56, 256)  0           ['conv2_block1_out[0][0]',       \n",
      "                                                                  'conv2_block2_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv2_block2_out (Activation)  (None, 56, 56, 256)  0           ['conv2_block2_add[0][0]']       \n",
      "                                                                                                  \n",
      " conv2_block3_1_conv (Conv2D)   (None, 56, 56, 64)   16448       ['conv2_block2_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv2_block3_1_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block3_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv2_block3_1_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block3_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block3_2_conv (Conv2D)   (None, 56, 56, 64)   36928       ['conv2_block3_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv2_block3_2_bn (BatchNormal  (None, 56, 56, 64)  256         ['conv2_block3_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv2_block3_2_relu (Activatio  (None, 56, 56, 64)  0           ['conv2_block3_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block3_3_conv (Conv2D)   (None, 56, 56, 256)  16640       ['conv2_block3_2_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv2_block3_3_bn (BatchNormal  (None, 56, 56, 256)  1024       ['conv2_block3_3_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv2_block3_add (Add)         (None, 56, 56, 256)  0           ['conv2_block2_out[0][0]',       \n",
      "                                                                  'conv2_block3_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv2_block3_out (Activation)  (None, 56, 56, 256)  0           ['conv2_block3_add[0][0]']       \n",
      "                                                                                                  \n",
      " conv3_block1_1_conv (Conv2D)   (None, 28, 28, 128)  32896       ['conv2_block3_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv3_block1_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block1_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block1_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block1_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block1_2_conv (Conv2D)   (None, 28, 28, 128)  147584      ['conv3_block1_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv3_block1_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block1_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block1_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block1_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block1_0_conv (Conv2D)   (None, 28, 28, 512)  131584      ['conv2_block3_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv3_block1_3_conv (Conv2D)   (None, 28, 28, 512)  66048       ['conv3_block1_2_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv3_block1_0_bn (BatchNormal  (None, 28, 28, 512)  2048       ['conv3_block1_0_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block1_3_bn (BatchNormal  (None, 28, 28, 512)  2048       ['conv3_block1_3_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block1_add (Add)         (None, 28, 28, 512)  0           ['conv3_block1_0_bn[0][0]',      \n",
      "                                                                  'conv3_block1_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv3_block1_out (Activation)  (None, 28, 28, 512)  0           ['conv3_block1_add[0][0]']       \n",
      "                                                                                                  \n",
      " conv3_block2_1_conv (Conv2D)   (None, 28, 28, 128)  65664       ['conv3_block1_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv3_block2_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block2_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block2_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block2_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block2_2_conv (Conv2D)   (None, 28, 28, 128)  147584      ['conv3_block2_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv3_block2_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block2_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block2_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block2_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block2_3_conv (Conv2D)   (None, 28, 28, 512)  66048       ['conv3_block2_2_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv3_block2_3_bn (BatchNormal  (None, 28, 28, 512)  2048       ['conv3_block2_3_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block2_add (Add)         (None, 28, 28, 512)  0           ['conv3_block1_out[0][0]',       \n",
      "                                                                  'conv3_block2_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv3_block2_out (Activation)  (None, 28, 28, 512)  0           ['conv3_block2_add[0][0]']       \n",
      "                                                                                                  \n",
      " conv3_block3_1_conv (Conv2D)   (None, 28, 28, 128)  65664       ['conv3_block2_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv3_block3_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block3_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block3_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block3_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block3_2_conv (Conv2D)   (None, 28, 28, 128)  147584      ['conv3_block3_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv3_block3_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block3_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block3_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block3_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block3_3_conv (Conv2D)   (None, 28, 28, 512)  66048       ['conv3_block3_2_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv3_block3_3_bn (BatchNormal  (None, 28, 28, 512)  2048       ['conv3_block3_3_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block3_add (Add)         (None, 28, 28, 512)  0           ['conv3_block2_out[0][0]',       \n",
      "                                                                  'conv3_block3_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv3_block3_out (Activation)  (None, 28, 28, 512)  0           ['conv3_block3_add[0][0]']       \n",
      "                                                                                                  \n",
      " conv3_block4_1_conv (Conv2D)   (None, 28, 28, 128)  65664       ['conv3_block3_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv3_block4_1_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block4_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block4_1_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block4_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block4_2_conv (Conv2D)   (None, 28, 28, 128)  147584      ['conv3_block4_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv3_block4_2_bn (BatchNormal  (None, 28, 28, 128)  512        ['conv3_block4_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block4_2_relu (Activatio  (None, 28, 28, 128)  0          ['conv3_block4_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block4_3_conv (Conv2D)   (None, 28, 28, 512)  66048       ['conv3_block4_2_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv3_block4_3_bn (BatchNormal  (None, 28, 28, 512)  2048       ['conv3_block4_3_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv3_block4_add (Add)         (None, 28, 28, 512)  0           ['conv3_block3_out[0][0]',       \n",
      "                                                                  'conv3_block4_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv3_block4_out (Activation)  (None, 28, 28, 512)  0           ['conv3_block4_add[0][0]']       \n",
      "                                                                                                  \n",
      " conv4_block1_1_conv (Conv2D)   (None, 14, 14, 256)  131328      ['conv3_block4_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv4_block1_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block1_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block1_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block1_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block1_2_conv (Conv2D)   (None, 14, 14, 256)  590080      ['conv4_block1_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv4_block1_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block1_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block1_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block1_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block1_0_conv (Conv2D)   (None, 14, 14, 1024  525312      ['conv3_block4_out[0][0]']       \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block1_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block1_2_relu[0][0]']    \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block1_0_bn (BatchNormal  (None, 14, 14, 1024  4096       ['conv4_block1_0_conv[0][0]']    \n",
      " ization)                       )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block1_3_bn (BatchNormal  (None, 14, 14, 1024  4096       ['conv4_block1_3_conv[0][0]']    \n",
      " ization)                       )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block1_add (Add)         (None, 14, 14, 1024  0           ['conv4_block1_0_bn[0][0]',      \n",
      "                                )                                 'conv4_block1_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv4_block1_out (Activation)  (None, 14, 14, 1024  0           ['conv4_block1_add[0][0]']       \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block2_1_conv (Conv2D)   (None, 14, 14, 256)  262400      ['conv4_block1_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv4_block2_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block2_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block2_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block2_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block2_2_conv (Conv2D)   (None, 14, 14, 256)  590080      ['conv4_block2_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv4_block2_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block2_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block2_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block2_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block2_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block2_2_relu[0][0]']    \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block2_3_bn (BatchNormal  (None, 14, 14, 1024  4096       ['conv4_block2_3_conv[0][0]']    \n",
      " ization)                       )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block2_add (Add)         (None, 14, 14, 1024  0           ['conv4_block1_out[0][0]',       \n",
      "                                )                                 'conv4_block2_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv4_block2_out (Activation)  (None, 14, 14, 1024  0           ['conv4_block2_add[0][0]']       \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block3_1_conv (Conv2D)   (None, 14, 14, 256)  262400      ['conv4_block2_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv4_block3_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block3_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block3_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block3_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block3_2_conv (Conv2D)   (None, 14, 14, 256)  590080      ['conv4_block3_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv4_block3_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block3_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block3_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block3_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block3_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block3_2_relu[0][0]']    \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block3_3_bn (BatchNormal  (None, 14, 14, 1024  4096       ['conv4_block3_3_conv[0][0]']    \n",
      " ization)                       )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block3_add (Add)         (None, 14, 14, 1024  0           ['conv4_block2_out[0][0]',       \n",
      "                                )                                 'conv4_block3_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv4_block3_out (Activation)  (None, 14, 14, 1024  0           ['conv4_block3_add[0][0]']       \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block4_1_conv (Conv2D)   (None, 14, 14, 256)  262400      ['conv4_block3_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv4_block4_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block4_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block4_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block4_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block4_2_conv (Conv2D)   (None, 14, 14, 256)  590080      ['conv4_block4_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv4_block4_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block4_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block4_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block4_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block4_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block4_2_relu[0][0]']    \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block4_3_bn (BatchNormal  (None, 14, 14, 1024  4096       ['conv4_block4_3_conv[0][0]']    \n",
      " ization)                       )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block4_add (Add)         (None, 14, 14, 1024  0           ['conv4_block3_out[0][0]',       \n",
      "                                )                                 'conv4_block4_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv4_block4_out (Activation)  (None, 14, 14, 1024  0           ['conv4_block4_add[0][0]']       \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block5_1_conv (Conv2D)   (None, 14, 14, 256)  262400      ['conv4_block4_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv4_block5_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block5_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block5_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block5_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block5_2_conv (Conv2D)   (None, 14, 14, 256)  590080      ['conv4_block5_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv4_block5_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block5_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block5_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block5_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block5_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block5_2_relu[0][0]']    \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block5_3_bn (BatchNormal  (None, 14, 14, 1024  4096       ['conv4_block5_3_conv[0][0]']    \n",
      " ization)                       )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block5_add (Add)         (None, 14, 14, 1024  0           ['conv4_block4_out[0][0]',       \n",
      "                                )                                 'conv4_block5_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv4_block5_out (Activation)  (None, 14, 14, 1024  0           ['conv4_block5_add[0][0]']       \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block6_1_conv (Conv2D)   (None, 14, 14, 256)  262400      ['conv4_block5_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv4_block6_1_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block6_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block6_1_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block6_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block6_2_conv (Conv2D)   (None, 14, 14, 256)  590080      ['conv4_block6_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv4_block6_2_bn (BatchNormal  (None, 14, 14, 256)  1024       ['conv4_block6_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv4_block6_2_relu (Activatio  (None, 14, 14, 256)  0          ['conv4_block6_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block6_3_conv (Conv2D)   (None, 14, 14, 1024  263168      ['conv4_block6_2_relu[0][0]']    \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block6_3_bn (BatchNormal  (None, 14, 14, 1024  4096       ['conv4_block6_3_conv[0][0]']    \n",
      " ization)                       )                                                                 \n",
      "                                                                                                  \n",
      " conv4_block6_add (Add)         (None, 14, 14, 1024  0           ['conv4_block5_out[0][0]',       \n",
      "                                )                                 'conv4_block6_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv4_block6_out (Activation)  (None, 14, 14, 1024  0           ['conv4_block6_add[0][0]']       \n",
      "                                )                                                                 \n",
      "                                                                                                  \n",
      " conv5_block1_1_conv (Conv2D)   (None, 7, 7, 512)    524800      ['conv4_block6_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv5_block1_1_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block1_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv5_block1_1_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block1_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block1_2_conv (Conv2D)   (None, 7, 7, 512)    2359808     ['conv5_block1_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv5_block1_2_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block1_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv5_block1_2_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block1_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block1_0_conv (Conv2D)   (None, 7, 7, 2048)   2099200     ['conv4_block6_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv5_block1_3_conv (Conv2D)   (None, 7, 7, 2048)   1050624     ['conv5_block1_2_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv5_block1_0_bn (BatchNormal  (None, 7, 7, 2048)  8192        ['conv5_block1_0_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv5_block1_3_bn (BatchNormal  (None, 7, 7, 2048)  8192        ['conv5_block1_3_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv5_block1_add (Add)         (None, 7, 7, 2048)   0           ['conv5_block1_0_bn[0][0]',      \n",
      "                                                                  'conv5_block1_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv5_block1_out (Activation)  (None, 7, 7, 2048)   0           ['conv5_block1_add[0][0]']       \n",
      "                                                                                                  \n",
      " conv5_block2_1_conv (Conv2D)   (None, 7, 7, 512)    1049088     ['conv5_block1_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv5_block2_1_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block2_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv5_block2_1_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block2_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block2_2_conv (Conv2D)   (None, 7, 7, 512)    2359808     ['conv5_block2_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv5_block2_2_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block2_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv5_block2_2_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block2_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block2_3_conv (Conv2D)   (None, 7, 7, 2048)   1050624     ['conv5_block2_2_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv5_block2_3_bn (BatchNormal  (None, 7, 7, 2048)  8192        ['conv5_block2_3_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv5_block2_add (Add)         (None, 7, 7, 2048)   0           ['conv5_block1_out[0][0]',       \n",
      "                                                                  'conv5_block2_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv5_block2_out (Activation)  (None, 7, 7, 2048)   0           ['conv5_block2_add[0][0]']       \n",
      "                                                                                                  \n",
      " conv5_block3_1_conv (Conv2D)   (None, 7, 7, 512)    1049088     ['conv5_block2_out[0][0]']       \n",
      "                                                                                                  \n",
      " conv5_block3_1_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block3_1_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv5_block3_1_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block3_1_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block3_2_conv (Conv2D)   (None, 7, 7, 512)    2359808     ['conv5_block3_1_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv5_block3_2_bn (BatchNormal  (None, 7, 7, 512)   2048        ['conv5_block3_2_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv5_block3_2_relu (Activatio  (None, 7, 7, 512)   0           ['conv5_block3_2_bn[0][0]']      \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block3_3_conv (Conv2D)   (None, 7, 7, 2048)   1050624     ['conv5_block3_2_relu[0][0]']    \n",
      "                                                                                                  \n",
      " conv5_block3_3_bn (BatchNormal  (None, 7, 7, 2048)  8192        ['conv5_block3_3_conv[0][0]']    \n",
      " ization)                                                                                         \n",
      "                                                                                                  \n",
      " conv5_block3_add (Add)         (None, 7, 7, 2048)   0           ['conv5_block2_out[0][0]',       \n",
      "                                                                  'conv5_block3_3_bn[0][0]']      \n",
      "                                                                                                  \n",
      " conv5_block3_out (Activation)  (None, 7, 7, 2048)   0           ['conv5_block3_add[0][0]']       \n",
      "                                                                                                  \n",
      " flatten_2 (Flatten)            (None, 100352)       0           ['conv5_block3_out[0][0]']       \n",
      "                                                                                                  \n",
      " dense_1 (Dense)                (None, 2)            200706      ['flatten_2[0][0]']              \n",
      "                                                                                                  \n",
      "==================================================================================================\n",
      "Total params: 23,788,418\n",
      "Trainable params: 200,706\n",
      "Non-trainable params: 23,587,712\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "e25a626c",
   "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"
    },
    {
     "data": {
      "image/png": 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sSYudqzqnfS7s493Xlnu56fFi2v1BHvnaQs6elhfW44tIdNFJ0ROVkAATz3C+LroP9q91wr3hUyj6BkxYNCQv++rGA3z36XWMzvSw6uZFTBuVPiSvIyKxQYE+UMYcvbnsELHW8vA7u/j5a5+wcFIOK76+kNx0jWQRkeNToA8z7f4gP/7rJp4uruALc8fxiyvmaCSLiPSLAn0YqWv28a0nS3h/VzXf+ew0vnvhqbpYSET6TYE+TJRXN7N85ceU1zTzwJVzuXzh+EiXJCJRRoE+DJSU1XDT4yUEreWJG87gjCknfhGSiMQfBXqEvbhuH99/dgPjsjw8tvx0Jufp9mAiMjgK9Aix1vLg33fywBvbOb1gBH/4+kLNUS4iJ0SBHgFt/gA/en4jz5fu40vz87n/8tNIdmski4icGAX6SeZtauebT5Tw8Z4a/u3CU7n9s9M0kkVEwkKBfhLtOdzEN1auYZ+3hd9cPY9l8/IjXZKIxJB+3fPMGLPUGPOJMWanMeauHrbnGGNeMMZsMMZ8bIyZHf5So9tHu6v50kPvUdfi4y83naEwF5Gw6zPQjTEu4PfAxUAhcI0xprDbbncD66y1c4DrgN+Eu9Bo9nxpJV/7j48YkZbEC98+m6KCEZEuSURiUH9a6KcDO621u6217cAqYFm3fQqB1QDW2m1AgTFmdFgrjULWWn71xnb+7Zn1FE0awQvfWsykXA1LFJGh0Z9AzwcqOi1XhtZ1th74MoAx5nRgEhDXlzq2+gLcsWodv129gysXjufP3zidrNTwzZEuItJdf06K9jQEo/sk6vcDvzHGrAM2AmsB/zEHMuZm4GaAiRNP7N6aw1l1Yxvf/M8Sisu8/GDpdL71makaySIiQ64/gV4JdL5Fznhgf+cdrLX1wHIA4yTXntAX3fZbAawA5wYXgyt5eNt5qJFvrFzDp/Wt/P7aBVw6Z2ykSxKRONGfQF8DnGKMmQzsA64Gru28gzEmG2gO9bHfCLwbCvm48v7Ow9zyRAlJ7gSeuvlMFkzMiXRJIhJH+gx0a63fGHMb8DrgAh611m42xtwS2v4IMBN43BgTALYANwxhzcPSM8UV3P38RibnpfHo9YuYMCI10iWJSJzp14VF1tpXgVe7rXuk0+MPgFPCW1p0CAYtv/zvT3jo7V2ce0oeD167gKwUnfwUkZNPV4qegFZfgP/xzHr+a+MBrjl9Iv9r2SwSXf26VktEJOwU6INU09TODX9ew7qKWv7nJTO58dzJGskiIhGlQB+kh97ayaZ9dTz81YUsnT0m0uWIiPRvLhc51poyL/Mn5ijMRWTYUKAPQkt7gM376lg4ScMSRWT4UKAPwobKWvxBy0KNMxeRYUSBPggl5V4AFqiFLiLDiAJ9EEr2epkyMo0RugeoiAwjCvQBstZSUu5Vd4uIDDsK9AHafbiJ2mafToiKyLCjQB+gkjKn/7yoQIEuIsOLAn2ASvZ6yUpJZEpeeqRLERHpQoE+QCXlXhZMzCYhQZf5i8jwokAfgNrmdnYeatRNnkVkWFKgD0DpkfHnGuEiIsOQAn0ASsq8uBIMcydkRboUEZFjKNAHoKTMS+HYTFKTNEmliAw/CvR+8gWCrKuo1fhzERm2FOj9tPVAPa2+oAJdRIYtBXo/HbmgSIEuIsOVAr2fSsq8jMvyMC47JdKliIj0SIHeTyVlXk2XKyLDmgK9H/bXtnCgrlXdLSIyrCnQ+6FjQq5JukJURIYvBXo/lJR5SUl0MWNsRqRLERHplQK9H0rKvMydkEWiS2+XiAxfSqg+NLf72XKgXv3nIjLsKdD7sL6ijkDQqv9cRIY9BXofSspqAJg/MTuyhYiI9EGB3oeSMi/TRqWTnZoU6VJERI5LgX4cwaCltLyWIvWfi0gUUKAfx66qRupafLpCVESiggL9ODQhl4hEEwX6cZSUeclJTWRKXlqkSxER6ZMC/ThKyrwsnJSDMSbSpYiI9EmB3ouapnZ2H25S/7mIRA0Fei9Kj/SfT1Sgi0h06FegG2OWGmM+McbsNMbc1cP2LGPMy8aY9caYzcaY5eEv9eQqKffiTjDMnZAd6VJERPqlz0A3xriA3wMXA4XANcaYwm673QpssdbOBZYADxhjovpKnJK9XmblZ+FJdEW6FBGRfulPC/10YKe1dre1th1YBSzrto8FMoxz9jAdqAH8Ya30JGr3B1lfWavuFhGJKv0J9HygotNyZWhdZw8CM4H9wEbgDmttsPuBjDE3G2OKjTHFVVVVgyx56G05UE+bP0hRgQJdRKJHfwK9pzF7ttvyvwDrgHHAPOBBY0zmMU+ydoW1tshaWzRy5MgBlnryFO91JuTSBUUiEk36E+iVwIROy+NxWuKdLQeet46dwB5gRnhKPPlKy73kZ6cwOtMT6VJERPqtP4G+BjjFGDM5dKLzauClbvuUAxcAGGNGA9OB3eEs9GSx1nZcUCQiEk3cfe1grfUbY24DXgdcwKPW2s3GmFtC2x8B7gVWGmM24nTR/NBae3gI6x4y+2pb+LS+Tf3nIhJ1+gx0AGvtq8Cr3dY90unxfuCi8JYWGUcm5FqgES4iEmV0pWg3JWVeUpNczBiTEelSREQGRIHeTUmZl/kTs3G79NaISHRRanXS2OZn64F6XVAkIlFJgd7J+opaghbNsCgiUUmB3klJmRdjYL5a6CIShRTonZSUeTl1VAZZKYmRLkVEZMAU6CHBoKW03KvuFhGJWgr0kB2HGmlo9esKURGJWgr0kCMXFBUp0EUkSinQQ4rLashNS2JSbmqkSxERGRQFekhpmdN/7tyjQ0Qk+ijQgcONbeytblZ3i4hENQU6R/vPdUJURKKZAh2nuyXRZZidnxXpUkREBk2BjtNCn52fhSfRFelSREQGLe4Dvc0fYMO+OvWfi0jUi/tA37SvnnZ/UP3nIhL14j7QS4/coUiBLiJRLu4DvaTMy8QRqYzK8ES6FBGRExLXgW6tpbjMq+4WEYkJcR3oFTUtHG5sU3eLiMSEuA70kvIaAN1yTkRiQnwHepmX9GQ308dkRLoUEZETFteBXrzXy/yJ2bgSNCGXiES/uA30hlYfn3zawAJ1t4hIjIjbQF9XUYu1UFSgQBeR2BC3gV6814sxMG9CdqRLEREJi7gN9NJyL9NHZ5DhSYx0KSIiYRGXgR4IWtaW16q7RURiSlwG+icHG2hs8+sKURGJKXEZ6CXloTsUTRwR4UpERMInLgO9tMxLXnoyE0akRLoUEZGwictALynzUjQpB2N0QZGIxI64C/RDDa2U1zSr/1xEYk7cBbpuaCEisSruAr2kzEuSO4HZ+ZmRLkVEJKz6FejGmKXGmE+MMTuNMXf1sP37xph1oa9NxpiAMWZYDiEpLvMyJz+LZLcr0qWIiIRVn4FujHEBvwcuBgqBa4wxhZ33sdb+wlo7z1o7D/gR8I61tmYI6j0hrb4Am/bVqf9cRGJSf1ropwM7rbW7rbXtwCpg2XH2vwZ4KhzFhdumfXX4Alb95yISk/oT6PlARaflytC6YxhjUoGlwHO9bL/ZGFNsjCmuqqoaaK0nrCR0QlQtdBGJRf0J9J4Ga9te9v0C8F5v3S3W2hXW2iJrbdHIkSP7W2PYFJd5KchNJS89+aS/tojIUOtPoFcCEzotjwf297Lv1QzT7hZrLaVlXnW3iEjM6k+grwFOMcZMNsYk4YT2S913MsZkAZ8BXgxvieFRVt1MdVM7RZOG5eAbEZET5u5rB2ut3xhzG/A64AIetdZuNsbcEtr+SGjXLwH/ba1tGrJqT0Cx+s9FJMb1GegA1tpXgVe7rXuk2/JKYGW4Cgu3kjIvGR43p4xKj3QpIiJDIm6uFC0t87JgYg4JCZqQS0RiU1wEel2Lj+2HGtTdIiIxLS4CfW25F2vVfy4isS0uAr20zEuCgbkTsiNdiojIkImLQC8p9zJzbCbpyf06BywiEpViPtD9gSBry2vV3SIiMS/mA33bwQaa2wMKdBGJeTEf6KXluqBIROJDzAd68V4vozOTyc9OiXQpIiJDKuYDvaTMy8JJORijC4pEJLbFdKAfrGtlX20LCyaqu0VEYl9MB/qR/vOiAs2wKCKxL6YDvXivl2R3AoVjMyNdiojIkIvpQC8p9zJ3fDZJ7pj+MUVEgBgO9FZfgM376lhYoP5zEYkPMRvo6ytq8QctC3VCVETiRMwGeknohKjuISoi8SJmA720zMuUkWmMSEuKdCkiIidFTAa6tda5oEjdLSISR2Iy0HcfbsLb7NP8LSISV2Iy0EvKNCGXiMSfmAz00jIvWSmJTB2ZHulSREROmpgM9OIyLwsmZpOQoAm5RCR+xFyg1za3s/NQo7pbRCTuxFygry2vBWDhJE3IJSLxJeYCvbisBleCYe6ErEiXIiJyUsVcoJeUeSkcm0lqkjvSpYiInFQxFei+QJD1FXXqPxeRuBRTgb7tQAMtvoACXUTiUkwFenFZDaALikQkPsVUoJeUeRmb5WFcdkqkSxEROeliKtBLy7xqnYtI3IqZoSD7a1vYX9fKTQp0kV75fD4qKytpbW2NdCnSB4/Hw/jx40lMTOz3c2Im0DUhl0jfKisrycjIoKCgAGM0NcZwZa2lurqayspKJk+e3O/nxUyXS0mZl5REFzPHZka6FJFhq7W1ldzcXIX5MGeMITc3d8CfpGIm0EvLvcydkEWiK2Z+JJEhoTCPDoP5d+pX+hljlhpjPjHG7DTG3NXLPkuMMeuMMZuNMe8MuJIT0NzuZ/P+enW3iEhc6zPQjTEu4PfAxUAhcI0xprDbPtnAQ8Bl1tpZwJXhL7V36yvqCAStAl1kmKutreWhhx4a1HMvueQSamtrw1tQjOlPC/10YKe1dre1th1YBSzrts+1wPPW2nIAa+2h8JZ5fKXlzgnRBbqHqMiwdrxADwQCx33uq6++SnZ29hBUdWKstQSDwUiXAfRvlEs+UNFpuRI4o9s+pwKJxpi3gQzgN9bax7sfyBhzM3AzwMSJEwdTb4+K99YwbVQ62alJYTumSKy75+XNbNlfH9ZjFo7L5CdfmNXr9rvuuotdu3Yxb948LrzwQi699FLuuecexo4dy7p169iyZQtf/OIXqaiooLW1lTvuuIObb74ZgIKCAoqLi2lsbOTiiy/mnHPO4f333yc/P58XX3yRlJSuFxS+/PLL3HfffbS3t5Obm8uTTz7J6NGjaWxs5Pbbb6e4uBhjDD/5yU+4/PLLee2117j77rsJBALk5eWxevVqfvrTn5Kens73vvc9AGbPns0rr7wCwMUXX8z555/PBx98wF//+lfuv/9+1qxZQ0tLC1dccQX33HMPAGvWrOGOO+6gqamJ5ORkVq9ezSWXXMLvfvc75s2bB8DixYt5+OGHmTNnzgm9//0J9J565m0Px1kIXACkAB8YYz601m7v8iRrVwArAIqKirofY1CCQUtpeS1LZ40Jx+FEZAjdf//9bNq0iXXr1gHw9ttv8/HHH7Np06aO4XmPPvooI0aMoKWlhUWLFnH55ZeTm5vb5Tg7duzgqaee4o9//CNf+cpXeO655/ja177WZZ9zzjmHDz/8EGMMf/rTn/j5z3/OAw88wL333ktWVhYbN24EwOv1UlVVxU033cS7777L5MmTqamp6fNn+eSTT3jsscc6PnH87Gc/Y8SIEQQCAS644AI2bNjAjBkzuOqqq3j66adZtGgR9fX1pKSkcOONN7Jy5Up+/etfs337dtra2k44zKF/gV4JTOi0PB7Y38M+h621TUCTMeZdYC6wnSG2+3AjdS0+Fhaou0VkII7Xkj6ZTj/99C5jrX/729/ywgsvAFBRUcGOHTuOCfTJkyd3tG4XLlzI3r17jzluZWUlV111FQcOHKC9vb3jNd58801WrVrVsV9OTg4vv/wy5513Xsc+I0b0fYOcSZMmceaZZ3YsP/PMM6xYsQK/38+BAwfYsmULxhjGjh3LokWLAMjMdIZVX3nlldx777384he/4NFHH+X666/v8/X6oz996GuAU4wxk40xScDVwEvd9nkRONcY4zbGpOJ0yWwNS4V9KN6rC4pEollaWlrH47fffps333yTDz74gPXr1zN//vwex2InJyd3PHa5XPj9/mP2uf3227ntttvYuHEjf/jDHzqOY609ZkhgT+sA3G53l/7xzrV0rnvPnj388pe/ZPXq1WzYsIFLL72U1tbWXo+bmprKhRdeyIsvvsgzzzzDtdde2+N7M1B9Brq11g/cBryOE9LPWGs3G2NuMcbcEtpnK/AasAH4GPiTtXZTWCrsQ0mZl+zURKbkpfW9s4hEVEZGBg0NDb1ur6urIycnh9TUVLZt28aHH3446Neqq6sjPz8fgD//+c8d6y+66CIefPDBjmWv18tZZ53FO++8w549ewA6ulwKCgooLS0FoLS0tGN7d/X19aSlpZGVlcWnn37K3/72NwBmzJjB/v37WbNmDQANDQ0df3xuvPFGvvOd77Bo0aJ+fSLoj36NQ7fWvmqtPdVaO9Va+7PQukestY902ucX1tpCa+1sa+2vw1JdP5SUe1k4MUcXS4hEgdzcXBYvXszs2bP5/ve/f8z2pUuX4vf7mTNnDj/+8Y+7dGkM1E9/+lOuvPJKzj33XPLy8jrW//u//zter5fZs2czd+5c3nrrLUaOHMmKFSv48pe/zNy5c7nqqqsAuPzyy6mpqWHevHk8/PDDnHrqqT2+1ty5c5k/fz6zZs3iG9/4BosXLwYgKSmJp59+mttvv525c+dy4YUXdrTyFy5cSGZmJsuXLx/0z9idsTYs5yYHrKioyBYXF5/QMWqa2llw7xv8YOl0vr1kWpgqE4ldW7duZebMmZEuQ4D9+/ezZMkStm3bRkJCz23rnv69jDEl1tqinvaP6uvkS49MyKXx5yISRR5//HHOOOMMfvazn/Ua5oMR1bMtlpR7cScY5ozPjnQpIiL9dt1113HdddeF/bhR3UIvKfMyKz+LlCRXpEsREYm4qA30dn+Q9RW16m4REQmJ2kDfcqCeNn9Q489FREKiNtB1hyIRka6iNtBLy7zkZ6cwJssT6VJEZAilp6dHuoSoEZWBbq2luKxGrXMRGXI9TSswXEXlsMV9tS18Wt+mQBc5EX+7Cw5uDO8xx5wGF9/f6+Yf/vCHTJo0iW9/+9uAczVnRkYG3/zmN1m2bBlerxefz8d9993HsmXdb7vQVW/T7PY0DW5vU+amp6fT2NgIwLPPPssrr7zCypUruf766xkxYgRr165lwYIFXHXVVdx55520tLSQkpLCY489xvTp0wkEAvzwhz/k9ddfxxjDTTfdRGFhIQ8++GDHBGNvvPEGDz/8MM8//3w43uHjispAV/+5SHS6+uqrufPOOzsC/ZlnnuG1117D4/HwwgsvkJmZyeHDhznzzDO57LLLjjulR0/T7AaDwR6nwe1pyty+bN++nTfffBOXy0V9fT3vvvsubrebN998k7vvvpvnnnuOFStWsGfPHtauXYvb7aampoacnBxuvfVWqqqqGDlyJI899lhYL+8/nqgN9NQkFzPGZES6FJHodZyW9FCZP38+hw4dYv/+/VRVVZGTk8PEiRPx+XzcfffdvPvuuyQkJLBv3z4+/fRTxozp/T4HPU2zW1VV1eM0uD1NmduXK6+8EpfLucalrq6Of/3Xf2XHjh0YY/D5fB3HveWWW3C73V1e7+tf/zpPPPEEy5cv54MPPuDxx4+538+QiNpAnzchG7crKk8BiMS1K664gmeffZaDBw9y9dVXA/Dkk09SVVVFSUkJiYmJFBQU9Dht7hGdp9lNTU1lyZIlx52utrf1ndd1f73O0+P++Mc/5vzzz+eFF15g7969LFmy5LjHXb58OV/4whfweDxceeWVHYE/1KIuEZva/Gw9UE+RultEotLVV1/NqlWrePbZZ7niiisApwU8atQoEhMTeeuttygrKzvuMXqbZre3aXB7mjIXYPTo0WzdupVgMNjR2u/t9Y5Mxbty5cqO9RdddBGPPPJIx4nTI683btw4xo0bx3333Re2m1f0R9QF+vqKWoIWFijQRaLSrFmzaGhoID8/n7FjxwLw1a9+leLiYoqKinjyySeZMWPGcY/R2zS7vU2D29OUueDcEu/zn/88n/3sZztq6ckPfvADfvSjH7F48eIuN7O+8cYbmThxInPmzGHu3Ln85S9/6dj21a9+lQkTJlBYWDi4N2oQom763OK9NTz09i7+31XzyEpJHILKRGKXps89eW677Tbmz5/PDTfcMOhjDHT63KjrQy8qGMGj14fn7h4iIkNh4cKFpKWl8cADD5zU1426QBcRGe5KSkoi8rpR14cuIicmUt2sMjCD+XdSoIvEEY/HQ3V1tUJ9mLPWUl1djcczsLmq1OUiEkfGjx9PZWUlVVVVkS5F+uDxeBg/fvyAnqNAF4kjiYmJHVdRSuxRl4uISIxQoIuIxAgFuohIjIjYlaLGmCrg+BM29C4POBzGcqKd3o+u9H4cpfeiq1h4PyZZa0f2tCFigX4ijDHFvV36Go/0fnSl9+MovRddxfr7oS4XEZEYoUAXEYkR0RroKyJdwDCj96MrvR9H6b3oKqbfj6jsQxcRkWNFawtdRES6UaCLiMSIqAt0Y8xSY8wnxpidxpi7Il1PJBljJhhj3jLGbDXGbDbG3BHpmiLNGOMyxqw1xrwS6VoizRiTbYx51hizLfR/5KxI1xQpxpjvhn5HNhljnjLGDGwawygRVYFujHEBvwcuBgqBa4wxJ++GfcOPH/gf1tqZwJnArXH+fgDcAWyNdBHDxG+A16y1M4C5xOn7YozJB74DFFlrZwMu4OrIVjU0oirQgdOBndba3dbadmAVsCzCNUWMtfaAtbY09LgB5xc2P7JVRY4xZjxwKfCnSNcSacaYTOA84D8ArLXt1traiBYVWW4gxRjjBlKB/RGuZ0hEW6DnAxWdliuJ4wDrzBhTAMwHPopwKZH0a+AHQDDCdQwHU4Aq4LFQF9SfjDFpkS4qEqy1+4BfAuXAAaDOWvvfka1qaERboJse1sX9uEtjTDrwHHCntbY+0vVEgjHm88Aha21kbuY4/LiBBcDD1tr5QBMQl+ecjDE5OJ/kJwPjgDRjzNciW9XQiLZArwQmdFoeT4x+dOovY0wiTpg/aa19PtL1RNBi4DJjzF6crrjPGmOeiGxJEVUJVFprj3xiexYn4OPR54A91toqa60PeB44O8I1DYloC/Q1wCnGmMnGmCScExsvRbimiDHGGJw+0q3W2l9Fup5Istb+yFo73lpbgPP/4u/W2phshfWHtfYgUGGMmR5adQGwJYIlRVI5cKYxJjX0O3MBMXqCOKpuQWet9RtjbgNexzlT/ai1dnOEy4qkxcDXgY3GmHWhdXdba1+NXEkyjNwOPBlq/OwGlke4noiw1n5kjHkWKMUZGbaWGJ0CQJf+i4jEiGjrchERkV4o0EVEYoQCXUQkRijQRURihAJdRCRGKNBFRGKEAl1EJEb8f3C+IHoWkmYcAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(history.history['loss'], label='train loss')\n",
    "plt.plot(history.history['val_loss'], label='val loss')\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "plt.plot(history.history['accuracy'], label='train accuracy')\n",
    "plt.plot(history.history['val_accuracy'], label='val accuracy')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "dae38ed2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "14/14 [==============================] - 77s 5s/step - loss: 0.0573 - accuracy: 0.9844\n",
      "Model has a loss of 0.06 and accuracy 98.44%\n"
     ]
    }
   ],
   "source": [
    "model_loss_train, model_train_acc = model.evaluate(train_it)\n",
    "print(\"Model has a loss of %.2f and accuracy %.2f%%\" % (model_loss_train, model_train_acc*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "a3a391eb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6/6 [==============================] - 35s 6s/step - loss: 0.0617 - accuracy: 0.9792\n",
      "Model has a loss of 0.06 and accuracy 97.92%\n"
     ]
    }
   ],
   "source": [
    "model_loss, model_acc = model.evaluate(val_it)\n",
    "print(\"Model has a loss of %.2f and accuracy %.2f%%\" % (model_loss, model_acc*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "8688bac7",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.save('model_resnet50.h5')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}