ResNet50 - Covid detection.ipynb

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the necessary libraries**"],"metadata":{"id":"ITd0d8uFFsgs"}},{"cell_type":"code","execution_count":1,"metadata":{"id":"eZoBk_hUh8xi","executionInfo":{"status":"ok","timestamp":1652897300093,"user_tz":-330,"elapsed":2674,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}}},"outputs":[],"source":["import os\n","import numpy as np\n","import tensorflow as tf\n","from keras.models import Model\n","from keras.preprocessing.image import ImageDataGenerator\n","from keras.callbacks import ModelCheckpoint, EarlyStopping\n","from keras.layers import Dense, Dropout, Flatten\n","from keras.models import Sequential\n","from pathlib import Path\n","from sklearn.metrics import precision_score\n","from sklearn.metrics import recall_score\n","from sklearn.metrics import f1_score\n","from sklearn.metrics import confusion_matrix\n","\n","# Display\n","from IPython.display import Image, display\n","import matplotlib.pyplot as plt\n","import matplotlib.cm as cm"]},{"cell_type":"code","source":["import numpy as np\n","import keras\n","from keras.applications.imagenet_utils import decode_predictions\n","import skimage.io \n","import skimage.segmentation\n","import copy\n","import sklearn\n","import sklearn.metrics\n","from sklearn.linear_model import LinearRegression\n","import warnings\n","\n","print('Notebook running: keras ', keras.__version__)\n","np.random.seed(222)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"kV6geJD8bJHC","executionInfo":{"status":"ok","timestamp":1652898440895,"user_tz":-330,"elapsed":1942,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"5a0ab879-3d74-4f28-b13d-1fd970df22f4"},"execution_count":9,"outputs":[{"output_type":"stream","name":"stdout","text":["Notebook running: keras  2.8.0\n"]}]},{"cell_type":"markdown","source":["**Rescaling the pixels**"],"metadata":{"id":"N4B8PH7tGafM"}},{"cell_type":"code","source":["BATCH_SIZE = 64\n","\n","train_generator = ImageDataGenerator(\n","                    rescale=1./255,\n","                    validation_split=0.15)\n","\n","test_generator = ImageDataGenerator(rescale=1./255)"],"metadata":{"id":"1Gm9dQGfkToK","executionInfo":{"status":"ok","timestamp":1652897303567,"user_tz":-330,"elapsed":12,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}}},"execution_count":2,"outputs":[]},{"cell_type":"markdown","source":["**Splitting the data into training,testing and validation**"],"metadata":{"id":"1CVimN08G7aH"}},{"cell_type":"code","source":["train_data_dir = \"/content/drive/MyDrive/CovidCV/train\"\n","test_data_dir = \"/content/drive/MyDrive/CovidCV/test\"\n","\n","traingen = train_generator.flow_from_directory(train_data_dir,\n","                                               target_size=(150, 150),\n","                                               classes=['covid','normal'],\n","                                               class_mode='binary',\n","                                               subset='training',\n","                                               batch_size=BATCH_SIZE, \n","                                               shuffle=True,\n","                                               seed=42)\n","\n","validgen = train_generator.flow_from_directory(train_data_dir,\n","                                               target_size=(150, 150),\n","                                               classes=['covid','normal'],\n","                                               class_mode='binary',\n","                                               subset='validation',\n","                                               batch_size=BATCH_SIZE,\n","                                               shuffle=True,\n","                                               seed=42)\n","\n","testgen = test_generator.flow_from_directory(test_data_dir,\n","                                             target_size=(150, 150),\n","                                             class_mode=None,\n","                                             shuffle=False,\n","                                             seed=42)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"FAtK94-EkXoo","executionInfo":{"status":"ok","timestamp":1652897331220,"user_tz":-330,"elapsed":23122,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"c1fa8ee8-97c1-404d-c754-5a5f182d43f6"},"execution_count":3,"outputs":[{"output_type":"stream","name":"stdout","text":["Found 7028 images belonging to 2 classes.\n","Found 1239 images belonging to 2 classes.\n","Found 2000 images belonging to 2 classes.\n"]}]},{"cell_type":"markdown","source":["**Resizing the image**"],"metadata":{"id":"9PJxQgoiHWwo"}},{"cell_type":"code","source":["input_shape = (150, 150, 3)\n","optim_1 = tf.keras.optimizers.Adam(learning_rate=0.0001)\n","n_classes=2\n","\n","n_steps = traingen.samples // BATCH_SIZE\n","n_val_steps = validgen.samples // BATCH_SIZE\n","n_epochs = 50"],"metadata":{"id":"YzURlSsjkqPe","executionInfo":{"status":"ok","timestamp":1652897340637,"user_tz":-330,"elapsed":1056,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}}},"execution_count":4,"outputs":[]},{"cell_type":"markdown","source":["**Setting up the model**"],"metadata":{"id":"LQZx-C_1HPAi"}},{"cell_type":"code","source":["pre_trained_model =  tf.keras.applications.ResNet50(input_shape = (150, 150, 3), include_top = False, weights = 'imagenet')\n","for layer in pre_trained_model.layers:\n","      layer.trainable=False"],"metadata":{"id":"Ydm25PMOkvrt","executionInfo":{"status":"ok","timestamp":1652897351931,"user_tz":-330,"elapsed":6896,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"colab":{"base_uri":"https://localhost:8080/"},"outputId":"445e165c-0ea2-420a-b0fd-b3229ba0543a"},"execution_count":5,"outputs":[{"output_type":"stream","name":"stdout","text":["Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n","94773248/94765736 [==============================] - 1s 0us/step\n","94781440/94765736 [==============================] - 1s 0us/step\n"]}]},{"cell_type":"code","source":["pre_trained_model.summary()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"Xs1FSCsmryko","executionInfo":{"status":"ok","timestamp":1651308493798,"user_tz":-330,"elapsed":2368,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"4d4cb7ce-63af-459f-d092-403f9dc840a6"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Model: \"resnet50\"\n","__________________________________________________________________________________________________\n"," Layer (type)                   Output Shape         Param #     Connected to                     \n","==================================================================================================\n"," input_1 (InputLayer)           [(None, 150, 150, 3  0           []                               \n","                                )]                                                                \n","                                                                                                  \n"," conv1_pad (ZeroPadding2D)      (None, 156, 156, 3)  0           ['input_1[0][0]']                \n","                                                                                                  \n"," conv1_conv (Conv2D)            (None, 75, 75, 64)   9472        ['conv1_pad[0][0]']              \n","                                                                                                  \n"," conv1_bn (BatchNormalization)  (None, 75, 75, 64)   256         ['conv1_conv[0][0]']             \n","                                                                                                  \n"," conv1_relu (Activation)        (None, 75, 75, 64)   0           ['conv1_bn[0][0]']               \n","                                                                                                  \n"," pool1_pad (ZeroPadding2D)      (None, 77, 77, 64)   0           ['conv1_relu[0][0]']             \n","                                                                                                  \n"," pool1_pool (MaxPooling2D)      (None, 38, 38, 64)   0           ['pool1_pad[0][0]']              \n","                                                                                                  \n"," conv2_block1_1_conv (Conv2D)   (None, 38, 38, 64)   4160        ['pool1_pool[0][0]']             \n","                                                                                                  \n"," conv2_block1_1_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block1_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block1_1_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block1_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block1_2_conv (Conv2D)   (None, 38, 38, 64)   36928       ['conv2_block1_1_relu[0][0]']    \n","                                                                                                  \n"," conv2_block1_2_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block1_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block1_2_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block1_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block1_0_conv (Conv2D)   (None, 38, 38, 256)  16640       ['pool1_pool[0][0]']             \n","                                                                                                  \n"," conv2_block1_3_conv (Conv2D)   (None, 38, 38, 256)  16640       ['conv2_block1_2_relu[0][0]']    \n","                                                                                                  \n"," conv2_block1_0_bn (BatchNormal  (None, 38, 38, 256)  1024       ['conv2_block1_0_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block1_3_bn (BatchNormal  (None, 38, 38, 256)  1024       ['conv2_block1_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block1_add (Add)         (None, 38, 38, 256)  0           ['conv2_block1_0_bn[0][0]',      \n","                                                                  'conv2_block1_3_bn[0][0]']      \n","                                                                                                  \n"," conv2_block1_out (Activation)  (None, 38, 38, 256)  0           ['conv2_block1_add[0][0]']       \n","                                                                                                  \n"," conv2_block2_1_conv (Conv2D)   (None, 38, 38, 64)   16448       ['conv2_block1_out[0][0]']       \n","                                                                                                  \n"," conv2_block2_1_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block2_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block2_1_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block2_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block2_2_conv (Conv2D)   (None, 38, 38, 64)   36928       ['conv2_block2_1_relu[0][0]']    \n","                                                                                                  \n"," conv2_block2_2_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block2_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block2_2_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block2_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block2_3_conv (Conv2D)   (None, 38, 38, 256)  16640       ['conv2_block2_2_relu[0][0]']    \n","                                                                                                  \n"," conv2_block2_3_bn (BatchNormal  (None, 38, 38, 256)  1024       ['conv2_block2_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block2_add (Add)         (None, 38, 38, 256)  0           ['conv2_block1_out[0][0]',       \n","                                                                  'conv2_block2_3_bn[0][0]']      \n","                                                                                                  \n"," conv2_block2_out (Activation)  (None, 38, 38, 256)  0           ['conv2_block2_add[0][0]']       \n","                                                                                                  \n"," conv2_block3_1_conv (Conv2D)   (None, 38, 38, 64)   16448       ['conv2_block2_out[0][0]']       \n","                                                                                                  \n"," conv2_block3_1_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block3_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block3_1_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block3_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block3_2_conv (Conv2D)   (None, 38, 38, 64)   36928       ['conv2_block3_1_relu[0][0]']    \n","                                                                                                  \n"," conv2_block3_2_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block3_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block3_2_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block3_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block3_3_conv (Conv2D)   (None, 38, 38, 256)  16640       ['conv2_block3_2_relu[0][0]']    \n","                                                                                                  \n"," conv2_block3_3_bn (BatchNormal  (None, 38, 38, 256)  1024       ['conv2_block3_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block3_add (Add)         (None, 38, 38, 256)  0           ['conv2_block2_out[0][0]',       \n","                                                                  'conv2_block3_3_bn[0][0]']      \n","                                                                                                  \n"," conv2_block3_out (Activation)  (None, 38, 38, 256)  0           ['conv2_block3_add[0][0]']       \n","                                                                                                  \n"," conv3_block1_1_conv (Conv2D)   (None, 19, 19, 128)  32896       ['conv2_block3_out[0][0]']       \n","                                                                                                  \n"," conv3_block1_1_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block1_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block1_1_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block1_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block1_2_conv (Conv2D)   (None, 19, 19, 128)  147584      ['conv3_block1_1_relu[0][0]']    \n","                                                                                                  \n"," conv3_block1_2_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block1_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block1_2_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block1_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block1_0_conv (Conv2D)   (None, 19, 19, 512)  131584      ['conv2_block3_out[0][0]']       \n","                                                                                                  \n"," conv3_block1_3_conv (Conv2D)   (None, 19, 19, 512)  66048       ['conv3_block1_2_relu[0][0]']    \n","                                                                                                  \n"," conv3_block1_0_bn (BatchNormal  (None, 19, 19, 512)  2048       ['conv3_block1_0_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block1_3_bn (BatchNormal  (None, 19, 19, 512)  2048       ['conv3_block1_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block1_add (Add)         (None, 19, 19, 512)  0           ['conv3_block1_0_bn[0][0]',      \n","                                                                  'conv3_block1_3_bn[0][0]']      \n","                                                                                                  \n"," conv3_block1_out (Activation)  (None, 19, 19, 512)  0           ['conv3_block1_add[0][0]']       \n","                                                                                                  \n"," conv3_block2_1_conv (Conv2D)   (None, 19, 19, 128)  65664       ['conv3_block1_out[0][0]']       \n","                                                                                                  \n"," conv3_block2_1_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block2_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block2_1_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block2_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block2_2_conv (Conv2D)   (None, 19, 19, 128)  147584      ['conv3_block2_1_relu[0][0]']    \n","                                                                                                  \n"," conv3_block2_2_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block2_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block2_2_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block2_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block2_3_conv (Conv2D)   (None, 19, 19, 512)  66048       ['conv3_block2_2_relu[0][0]']    \n","                                                                                                  \n"," conv3_block2_3_bn (BatchNormal  (None, 19, 19, 512)  2048       ['conv3_block2_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block2_add (Add)         (None, 19, 19, 512)  0           ['conv3_block1_out[0][0]',       \n","                                                                  'conv3_block2_3_bn[0][0]']      \n","                                                                                                  \n"," conv3_block2_out (Activation)  (None, 19, 19, 512)  0           ['conv3_block2_add[0][0]']       \n","                                                                                                  \n"," conv3_block3_1_conv (Conv2D)   (None, 19, 19, 128)  65664       ['conv3_block2_out[0][0]']       \n","                                                                                                  \n"," conv3_block3_1_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block3_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block3_1_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block3_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block3_2_conv (Conv2D)   (None, 19, 19, 128)  147584      ['conv3_block3_1_relu[0][0]']    \n","                                                                                                  \n"," conv3_block3_2_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block3_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block3_2_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block3_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block3_3_conv (Conv2D)   (None, 19, 19, 512)  66048       ['conv3_block3_2_relu[0][0]']    \n","                                                                                                  \n"," conv3_block3_3_bn (BatchNormal  (None, 19, 19, 512)  2048       ['conv3_block3_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block3_add (Add)         (None, 19, 19, 512)  0           ['conv3_block2_out[0][0]',       \n","                                                                  'conv3_block3_3_bn[0][0]']      \n","                                                                                                  \n"," conv3_block3_out (Activation)  (None, 19, 19, 512)  0           ['conv3_block3_add[0][0]']       \n","                                                                                                  \n"," conv3_block4_1_conv (Conv2D)   (None, 19, 19, 128)  65664       ['conv3_block3_out[0][0]']       \n","                                                                                                  \n"," conv3_block4_1_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block4_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block4_1_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block4_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block4_2_conv (Conv2D)   (None, 19, 19, 128)  147584      ['conv3_block4_1_relu[0][0]']    \n","                                                                                                  \n"," conv3_block4_2_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block4_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block4_2_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block4_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block4_3_conv (Conv2D)   (None, 19, 19, 512)  66048       ['conv3_block4_2_relu[0][0]']    \n","                                                                                                  \n"," conv3_block4_3_bn (BatchNormal  (None, 19, 19, 512)  2048       ['conv3_block4_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block4_add (Add)         (None, 19, 19, 512)  0           ['conv3_block3_out[0][0]',       \n","                                                                  'conv3_block4_3_bn[0][0]']      \n","                                                                                                  \n"," conv3_block4_out (Activation)  (None, 19, 19, 512)  0           ['conv3_block4_add[0][0]']       \n","                                                                                                  \n"," conv4_block1_1_conv (Conv2D)   (None, 10, 10, 256)  131328      ['conv3_block4_out[0][0]']       \n","                                                                                                  \n"," conv4_block1_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block1_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block1_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block1_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block1_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block1_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block1_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block1_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block1_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block1_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block1_0_conv (Conv2D)   (None, 10, 10, 1024  525312      ['conv3_block4_out[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block1_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block1_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block1_0_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block1_0_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block1_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block1_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block1_add (Add)         (None, 10, 10, 1024  0           ['conv4_block1_0_bn[0][0]',      \n","                                )                                 'conv4_block1_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block1_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block1_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block2_1_conv (Conv2D)   (None, 10, 10, 256)  262400      ['conv4_block1_out[0][0]']       \n","                                                                                                  \n"," conv4_block2_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block2_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block2_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block2_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block2_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block2_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block2_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block2_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block2_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block2_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block2_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block2_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block2_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block2_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block2_add (Add)         (None, 10, 10, 1024  0           ['conv4_block1_out[0][0]',       \n","                                )                                 'conv4_block2_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block2_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block2_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block3_1_conv (Conv2D)   (None, 10, 10, 256)  262400      ['conv4_block2_out[0][0]']       \n","                                                                                                  \n"," conv4_block3_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block3_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block3_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block3_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block3_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block3_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block3_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block3_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block3_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block3_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block3_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block3_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block3_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block3_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block3_add (Add)         (None, 10, 10, 1024  0           ['conv4_block2_out[0][0]',       \n","                                )                                 'conv4_block3_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block3_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block3_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block4_1_conv (Conv2D)   (None, 10, 10, 256)  262400      ['conv4_block3_out[0][0]']       \n","                                                                                                  \n"," conv4_block4_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block4_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block4_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block4_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block4_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block4_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block4_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block4_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block4_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block4_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block4_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block4_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block4_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block4_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block4_add (Add)         (None, 10, 10, 1024  0           ['conv4_block3_out[0][0]',       \n","                                )                                 'conv4_block4_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block4_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block4_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block5_1_conv (Conv2D)   (None, 10, 10, 256)  262400      ['conv4_block4_out[0][0]']       \n","                                                                                                  \n"," conv4_block5_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block5_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block5_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block5_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block5_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block5_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block5_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block5_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block5_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block5_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block5_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block5_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block5_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block5_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block5_add (Add)         (None, 10, 10, 1024  0           ['conv4_block4_out[0][0]',       \n","                                )                                 'conv4_block5_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block5_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block5_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block6_1_conv (Conv2D)   (None, 10, 10, 256)  262400      ['conv4_block5_out[0][0]']       \n","                                                                                                  \n"," conv4_block6_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block6_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block6_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block6_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block6_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block6_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block6_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block6_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block6_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block6_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block6_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block6_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block6_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block6_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block6_add (Add)         (None, 10, 10, 1024  0           ['conv4_block5_out[0][0]',       \n","                                )                                 'conv4_block6_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block6_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block6_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv5_block1_1_conv (Conv2D)   (None, 5, 5, 512)    524800      ['conv4_block6_out[0][0]']       \n","                                                                                                  \n"," conv5_block1_1_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block1_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block1_1_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block1_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block1_2_conv (Conv2D)   (None, 5, 5, 512)    2359808     ['conv5_block1_1_relu[0][0]']    \n","                                                                                                  \n"," conv5_block1_2_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block1_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block1_2_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block1_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block1_0_conv (Conv2D)   (None, 5, 5, 2048)   2099200     ['conv4_block6_out[0][0]']       \n","                                                                                                  \n"," conv5_block1_3_conv (Conv2D)   (None, 5, 5, 2048)   1050624     ['conv5_block1_2_relu[0][0]']    \n","                                                                                                  \n"," conv5_block1_0_bn (BatchNormal  (None, 5, 5, 2048)  8192        ['conv5_block1_0_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block1_3_bn (BatchNormal  (None, 5, 5, 2048)  8192        ['conv5_block1_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block1_add (Add)         (None, 5, 5, 2048)   0           ['conv5_block1_0_bn[0][0]',      \n","                                                                  'conv5_block1_3_bn[0][0]']      \n","                                                                                                  \n"," conv5_block1_out (Activation)  (None, 5, 5, 2048)   0           ['conv5_block1_add[0][0]']       \n","                                                                                                  \n"," conv5_block2_1_conv (Conv2D)   (None, 5, 5, 512)    1049088     ['conv5_block1_out[0][0]']       \n","                                                                                                  \n"," conv5_block2_1_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block2_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block2_1_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block2_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block2_2_conv (Conv2D)   (None, 5, 5, 512)    2359808     ['conv5_block2_1_relu[0][0]']    \n","                                                                                                  \n"," conv5_block2_2_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block2_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block2_2_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block2_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block2_3_conv (Conv2D)   (None, 5, 5, 2048)   1050624     ['conv5_block2_2_relu[0][0]']    \n","                                                                                                  \n"," conv5_block2_3_bn (BatchNormal  (None, 5, 5, 2048)  8192        ['conv5_block2_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block2_add (Add)         (None, 5, 5, 2048)   0           ['conv5_block1_out[0][0]',       \n","                                                                  'conv5_block2_3_bn[0][0]']      \n","                                                                                                  \n"," conv5_block2_out (Activation)  (None, 5, 5, 2048)   0           ['conv5_block2_add[0][0]']       \n","                                                                                                  \n"," conv5_block3_1_conv (Conv2D)   (None, 5, 5, 512)    1049088     ['conv5_block2_out[0][0]']       \n","                                                                                                  \n"," conv5_block3_1_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block3_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block3_1_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block3_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block3_2_conv (Conv2D)   (None, 5, 5, 512)    2359808     ['conv5_block3_1_relu[0][0]']    \n","                                                                                                  \n"," conv5_block3_2_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block3_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block3_2_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block3_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block3_3_conv (Conv2D)   (None, 5, 5, 2048)   1050624     ['conv5_block3_2_relu[0][0]']    \n","                                                                                                  \n"," conv5_block3_3_bn (BatchNormal  (None, 5, 5, 2048)  8192        ['conv5_block3_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block3_add (Add)         (None, 5, 5, 2048)   0           ['conv5_block2_out[0][0]',       \n","                                                                  'conv5_block3_3_bn[0][0]']      \n","                                                                                                  \n"," conv5_block3_out (Activation)  (None, 5, 5, 2048)   0           ['conv5_block3_add[0][0]']       \n","                                                                                                  \n","==================================================================================================\n","Total params: 23,587,712\n","Trainable params: 0\n","Non-trainable params: 23,587,712\n","__________________________________________________________________________________________________\n"]}]},{"cell_type":"code","source":["x = Flatten()(pre_trained_model.output)\n","x = Dense(1024, activation='relu')(x)\n","x = Dropout(0.2)(x)  \n","x = Dense(n_classes, activation='sigmoid')(x)    \n","\n","model = Model( pre_trained_model.input, x) \n","\n","model.compile(optimizer = optim_1, \n","              loss = tf.keras.losses.sparse_categorical_crossentropy, \n","              metrics = ['accuracy'])\n"],"metadata":{"id":"bJlomhL1n75L","executionInfo":{"status":"ok","timestamp":1652897356675,"user_tz":-330,"elapsed":558,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}}},"execution_count":6,"outputs":[]},{"cell_type":"code","source":["model.summary()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"LYgF_bRJoHoH","executionInfo":{"status":"ok","timestamp":1651302788431,"user_tz":-330,"elapsed":2787,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"fcc3d2f1-bf3b-4614-a493-0ff7144435b7"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Model: \"model\"\n","__________________________________________________________________________________________________\n"," Layer (type)                   Output Shape         Param #     Connected to                     \n","==================================================================================================\n"," input_1 (InputLayer)           [(None, 150, 150, 3  0           []                               \n","                                )]                                                                \n","                                                                                                  \n"," conv1_pad (ZeroPadding2D)      (None, 156, 156, 3)  0           ['input_1[0][0]']                \n","                                                                                                  \n"," conv1_conv (Conv2D)            (None, 75, 75, 64)   9472        ['conv1_pad[0][0]']              \n","                                                                                                  \n"," conv1_bn (BatchNormalization)  (None, 75, 75, 64)   256         ['conv1_conv[0][0]']             \n","                                                                                                  \n"," conv1_relu (Activation)        (None, 75, 75, 64)   0           ['conv1_bn[0][0]']               \n","                                                                                                  \n"," pool1_pad (ZeroPadding2D)      (None, 77, 77, 64)   0           ['conv1_relu[0][0]']             \n","                                                                                                  \n"," pool1_pool (MaxPooling2D)      (None, 38, 38, 64)   0           ['pool1_pad[0][0]']              \n","                                                                                                  \n"," conv2_block1_1_conv (Conv2D)   (None, 38, 38, 64)   4160        ['pool1_pool[0][0]']             \n","                                                                                                  \n"," conv2_block1_1_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block1_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block1_1_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block1_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block1_2_conv (Conv2D)   (None, 38, 38, 64)   36928       ['conv2_block1_1_relu[0][0]']    \n","                                                                                                  \n"," conv2_block1_2_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block1_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block1_2_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block1_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block1_0_conv (Conv2D)   (None, 38, 38, 256)  16640       ['pool1_pool[0][0]']             \n","                                                                                                  \n"," conv2_block1_3_conv (Conv2D)   (None, 38, 38, 256)  16640       ['conv2_block1_2_relu[0][0]']    \n","                                                                                                  \n"," conv2_block1_0_bn (BatchNormal  (None, 38, 38, 256)  1024       ['conv2_block1_0_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block1_3_bn (BatchNormal  (None, 38, 38, 256)  1024       ['conv2_block1_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block1_add (Add)         (None, 38, 38, 256)  0           ['conv2_block1_0_bn[0][0]',      \n","                                                                  'conv2_block1_3_bn[0][0]']      \n","                                                                                                  \n"," conv2_block1_out (Activation)  (None, 38, 38, 256)  0           ['conv2_block1_add[0][0]']       \n","                                                                                                  \n"," conv2_block2_1_conv (Conv2D)   (None, 38, 38, 64)   16448       ['conv2_block1_out[0][0]']       \n","                                                                                                  \n"," conv2_block2_1_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block2_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block2_1_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block2_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block2_2_conv (Conv2D)   (None, 38, 38, 64)   36928       ['conv2_block2_1_relu[0][0]']    \n","                                                                                                  \n"," conv2_block2_2_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block2_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block2_2_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block2_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block2_3_conv (Conv2D)   (None, 38, 38, 256)  16640       ['conv2_block2_2_relu[0][0]']    \n","                                                                                                  \n"," conv2_block2_3_bn (BatchNormal  (None, 38, 38, 256)  1024       ['conv2_block2_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block2_add (Add)         (None, 38, 38, 256)  0           ['conv2_block1_out[0][0]',       \n","                                                                  'conv2_block2_3_bn[0][0]']      \n","                                                                                                  \n"," conv2_block2_out (Activation)  (None, 38, 38, 256)  0           ['conv2_block2_add[0][0]']       \n","                                                                                                  \n"," conv2_block3_1_conv (Conv2D)   (None, 38, 38, 64)   16448       ['conv2_block2_out[0][0]']       \n","                                                                                                  \n"," conv2_block3_1_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block3_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block3_1_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block3_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block3_2_conv (Conv2D)   (None, 38, 38, 64)   36928       ['conv2_block3_1_relu[0][0]']    \n","                                                                                                  \n"," conv2_block3_2_bn (BatchNormal  (None, 38, 38, 64)  256         ['conv2_block3_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block3_2_relu (Activatio  (None, 38, 38, 64)  0           ['conv2_block3_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv2_block3_3_conv (Conv2D)   (None, 38, 38, 256)  16640       ['conv2_block3_2_relu[0][0]']    \n","                                                                                                  \n"," conv2_block3_3_bn (BatchNormal  (None, 38, 38, 256)  1024       ['conv2_block3_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv2_block3_add (Add)         (None, 38, 38, 256)  0           ['conv2_block2_out[0][0]',       \n","                                                                  'conv2_block3_3_bn[0][0]']      \n","                                                                                                  \n"," conv2_block3_out (Activation)  (None, 38, 38, 256)  0           ['conv2_block3_add[0][0]']       \n","                                                                                                  \n"," conv3_block1_1_conv (Conv2D)   (None, 19, 19, 128)  32896       ['conv2_block3_out[0][0]']       \n","                                                                                                  \n"," conv3_block1_1_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block1_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block1_1_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block1_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block1_2_conv (Conv2D)   (None, 19, 19, 128)  147584      ['conv3_block1_1_relu[0][0]']    \n","                                                                                                  \n"," conv3_block1_2_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block1_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block1_2_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block1_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block1_0_conv (Conv2D)   (None, 19, 19, 512)  131584      ['conv2_block3_out[0][0]']       \n","                                                                                                  \n"," conv3_block1_3_conv (Conv2D)   (None, 19, 19, 512)  66048       ['conv3_block1_2_relu[0][0]']    \n","                                                                                                  \n"," conv3_block1_0_bn (BatchNormal  (None, 19, 19, 512)  2048       ['conv3_block1_0_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block1_3_bn (BatchNormal  (None, 19, 19, 512)  2048       ['conv3_block1_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block1_add (Add)         (None, 19, 19, 512)  0           ['conv3_block1_0_bn[0][0]',      \n","                                                                  'conv3_block1_3_bn[0][0]']      \n","                                                                                                  \n"," conv3_block1_out (Activation)  (None, 19, 19, 512)  0           ['conv3_block1_add[0][0]']       \n","                                                                                                  \n"," conv3_block2_1_conv (Conv2D)   (None, 19, 19, 128)  65664       ['conv3_block1_out[0][0]']       \n","                                                                                                  \n"," conv3_block2_1_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block2_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block2_1_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block2_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block2_2_conv (Conv2D)   (None, 19, 19, 128)  147584      ['conv3_block2_1_relu[0][0]']    \n","                                                                                                  \n"," conv3_block2_2_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block2_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block2_2_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block2_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block2_3_conv (Conv2D)   (None, 19, 19, 512)  66048       ['conv3_block2_2_relu[0][0]']    \n","                                                                                                  \n"," conv3_block2_3_bn (BatchNormal  (None, 19, 19, 512)  2048       ['conv3_block2_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block2_add (Add)         (None, 19, 19, 512)  0           ['conv3_block1_out[0][0]',       \n","                                                                  'conv3_block2_3_bn[0][0]']      \n","                                                                                                  \n"," conv3_block2_out (Activation)  (None, 19, 19, 512)  0           ['conv3_block2_add[0][0]']       \n","                                                                                                  \n"," conv3_block3_1_conv (Conv2D)   (None, 19, 19, 128)  65664       ['conv3_block2_out[0][0]']       \n","                                                                                                  \n"," conv3_block3_1_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block3_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block3_1_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block3_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block3_2_conv (Conv2D)   (None, 19, 19, 128)  147584      ['conv3_block3_1_relu[0][0]']    \n","                                                                                                  \n"," conv3_block3_2_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block3_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block3_2_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block3_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block3_3_conv (Conv2D)   (None, 19, 19, 512)  66048       ['conv3_block3_2_relu[0][0]']    \n","                                                                                                  \n"," conv3_block3_3_bn (BatchNormal  (None, 19, 19, 512)  2048       ['conv3_block3_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block3_add (Add)         (None, 19, 19, 512)  0           ['conv3_block2_out[0][0]',       \n","                                                                  'conv3_block3_3_bn[0][0]']      \n","                                                                                                  \n"," conv3_block3_out (Activation)  (None, 19, 19, 512)  0           ['conv3_block3_add[0][0]']       \n","                                                                                                  \n"," conv3_block4_1_conv (Conv2D)   (None, 19, 19, 128)  65664       ['conv3_block3_out[0][0]']       \n","                                                                                                  \n"," conv3_block4_1_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block4_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block4_1_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block4_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block4_2_conv (Conv2D)   (None, 19, 19, 128)  147584      ['conv3_block4_1_relu[0][0]']    \n","                                                                                                  \n"," conv3_block4_2_bn (BatchNormal  (None, 19, 19, 128)  512        ['conv3_block4_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block4_2_relu (Activatio  (None, 19, 19, 128)  0          ['conv3_block4_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv3_block4_3_conv (Conv2D)   (None, 19, 19, 512)  66048       ['conv3_block4_2_relu[0][0]']    \n","                                                                                                  \n"," conv3_block4_3_bn (BatchNormal  (None, 19, 19, 512)  2048       ['conv3_block4_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv3_block4_add (Add)         (None, 19, 19, 512)  0           ['conv3_block3_out[0][0]',       \n","                                                                  'conv3_block4_3_bn[0][0]']      \n","                                                                                                  \n"," conv3_block4_out (Activation)  (None, 19, 19, 512)  0           ['conv3_block4_add[0][0]']       \n","                                                                                                  \n"," conv4_block1_1_conv (Conv2D)   (None, 10, 10, 256)  131328      ['conv3_block4_out[0][0]']       \n","                                                                                                  \n"," conv4_block1_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block1_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block1_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block1_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block1_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block1_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block1_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block1_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block1_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block1_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block1_0_conv (Conv2D)   (None, 10, 10, 1024  525312      ['conv3_block4_out[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block1_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block1_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block1_0_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block1_0_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block1_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block1_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block1_add (Add)         (None, 10, 10, 1024  0           ['conv4_block1_0_bn[0][0]',      \n","                                )                                 'conv4_block1_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block1_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block1_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block2_1_conv (Conv2D)   (None, 10, 10, 256)  262400      ['conv4_block1_out[0][0]']       \n","                                                                                                  \n"," conv4_block2_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block2_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block2_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block2_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block2_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block2_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block2_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block2_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block2_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block2_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block2_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block2_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block2_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block2_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block2_add (Add)         (None, 10, 10, 1024  0           ['conv4_block1_out[0][0]',       \n","                                )                                 'conv4_block2_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block2_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block2_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block3_1_conv (Conv2D)   (None, 10, 10, 256)  262400      ['conv4_block2_out[0][0]']       \n","                                                                                                  \n"," conv4_block3_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block3_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block3_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block3_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block3_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block3_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block3_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block3_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block3_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block3_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block3_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block3_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block3_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block3_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block3_add (Add)         (None, 10, 10, 1024  0           ['conv4_block2_out[0][0]',       \n","                                )                                 'conv4_block3_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block3_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block3_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block4_1_conv (Conv2D)   (None, 10, 10, 256)  262400      ['conv4_block3_out[0][0]']       \n","                                                                                                  \n"," conv4_block4_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block4_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block4_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block4_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block4_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block4_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block4_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block4_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block4_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block4_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block4_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block4_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block4_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block4_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block4_add (Add)         (None, 10, 10, 1024  0           ['conv4_block3_out[0][0]',       \n","                                )                                 'conv4_block4_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block4_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block4_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block5_1_conv (Conv2D)   (None, 10, 10, 256)  262400      ['conv4_block4_out[0][0]']       \n","                                                                                                  \n"," conv4_block5_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block5_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block5_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block5_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block5_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block5_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block5_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block5_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block5_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block5_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block5_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block5_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block5_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block5_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block5_add (Add)         (None, 10, 10, 1024  0           ['conv4_block4_out[0][0]',       \n","                                )                                 'conv4_block5_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block5_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block5_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block6_1_conv (Conv2D)   (None, 10, 10, 256)  262400      ['conv4_block5_out[0][0]']       \n","                                                                                                  \n"," conv4_block6_1_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block6_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block6_1_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block6_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block6_2_conv (Conv2D)   (None, 10, 10, 256)  590080      ['conv4_block6_1_relu[0][0]']    \n","                                                                                                  \n"," conv4_block6_2_bn (BatchNormal  (None, 10, 10, 256)  1024       ['conv4_block6_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv4_block6_2_relu (Activatio  (None, 10, 10, 256)  0          ['conv4_block6_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv4_block6_3_conv (Conv2D)   (None, 10, 10, 1024  263168      ['conv4_block6_2_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," conv4_block6_3_bn (BatchNormal  (None, 10, 10, 1024  4096       ['conv4_block6_3_conv[0][0]']    \n"," ization)                       )                                                                 \n","                                                                                                  \n"," conv4_block6_add (Add)         (None, 10, 10, 1024  0           ['conv4_block5_out[0][0]',       \n","                                )                                 'conv4_block6_3_bn[0][0]']      \n","                                                                                                  \n"," conv4_block6_out (Activation)  (None, 10, 10, 1024  0           ['conv4_block6_add[0][0]']       \n","                                )                                                                 \n","                                                                                                  \n"," conv5_block1_1_conv (Conv2D)   (None, 5, 5, 512)    524800      ['conv4_block6_out[0][0]']       \n","                                                                                                  \n"," conv5_block1_1_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block1_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block1_1_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block1_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block1_2_conv (Conv2D)   (None, 5, 5, 512)    2359808     ['conv5_block1_1_relu[0][0]']    \n","                                                                                                  \n"," conv5_block1_2_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block1_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block1_2_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block1_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block1_0_conv (Conv2D)   (None, 5, 5, 2048)   2099200     ['conv4_block6_out[0][0]']       \n","                                                                                                  \n"," conv5_block1_3_conv (Conv2D)   (None, 5, 5, 2048)   1050624     ['conv5_block1_2_relu[0][0]']    \n","                                                                                                  \n"," conv5_block1_0_bn (BatchNormal  (None, 5, 5, 2048)  8192        ['conv5_block1_0_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block1_3_bn (BatchNormal  (None, 5, 5, 2048)  8192        ['conv5_block1_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block1_add (Add)         (None, 5, 5, 2048)   0           ['conv5_block1_0_bn[0][0]',      \n","                                                                  'conv5_block1_3_bn[0][0]']      \n","                                                                                                  \n"," conv5_block1_out (Activation)  (None, 5, 5, 2048)   0           ['conv5_block1_add[0][0]']       \n","                                                                                                  \n"," conv5_block2_1_conv (Conv2D)   (None, 5, 5, 512)    1049088     ['conv5_block1_out[0][0]']       \n","                                                                                                  \n"," conv5_block2_1_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block2_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block2_1_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block2_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block2_2_conv (Conv2D)   (None, 5, 5, 512)    2359808     ['conv5_block2_1_relu[0][0]']    \n","                                                                                                  \n"," conv5_block2_2_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block2_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block2_2_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block2_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block2_3_conv (Conv2D)   (None, 5, 5, 2048)   1050624     ['conv5_block2_2_relu[0][0]']    \n","                                                                                                  \n"," conv5_block2_3_bn (BatchNormal  (None, 5, 5, 2048)  8192        ['conv5_block2_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block2_add (Add)         (None, 5, 5, 2048)   0           ['conv5_block1_out[0][0]',       \n","                                                                  'conv5_block2_3_bn[0][0]']      \n","                                                                                                  \n"," conv5_block2_out (Activation)  (None, 5, 5, 2048)   0           ['conv5_block2_add[0][0]']       \n","                                                                                                  \n"," conv5_block3_1_conv (Conv2D)   (None, 5, 5, 512)    1049088     ['conv5_block2_out[0][0]']       \n","                                                                                                  \n"," conv5_block3_1_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block3_1_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block3_1_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block3_1_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block3_2_conv (Conv2D)   (None, 5, 5, 512)    2359808     ['conv5_block3_1_relu[0][0]']    \n","                                                                                                  \n"," conv5_block3_2_bn (BatchNormal  (None, 5, 5, 512)   2048        ['conv5_block3_2_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block3_2_relu (Activatio  (None, 5, 5, 512)   0           ['conv5_block3_2_bn[0][0]']      \n"," n)                                                                                               \n","                                                                                                  \n"," conv5_block3_3_conv (Conv2D)   (None, 5, 5, 2048)   1050624     ['conv5_block3_2_relu[0][0]']    \n","                                                                                                  \n"," conv5_block3_3_bn (BatchNormal  (None, 5, 5, 2048)  8192        ['conv5_block3_3_conv[0][0]']    \n"," ization)                                                                                         \n","                                                                                                  \n"," conv5_block3_add (Add)         (None, 5, 5, 2048)   0           ['conv5_block2_out[0][0]',       \n","                                                                  'conv5_block3_3_bn[0][0]']      \n","                                                                                                  \n"," conv5_block3_out (Activation)  (None, 5, 5, 2048)   0           ['conv5_block3_add[0][0]']       \n","                                                                                                  \n"," flatten (Flatten)              (None, 51200)        0           ['conv5_block3_out[0][0]']       \n","                                                                                                  \n"," dense (Dense)                  (None, 1024)         52429824    ['flatten[0][0]']                \n","                                                                                                  \n"," dropout (Dropout)              (None, 1024)         0           ['dense[0][0]']                  \n","                                                                                                  \n"," dense_1 (Dense)                (None, 2)            2050        ['dropout[0][0]']                \n","                                                                                                  \n","==================================================================================================\n","Total params: 76,019,586\n","Trainable params: 52,431,874\n","Non-trainable params: 23,587,712\n","__________________________________________________________________________________________________\n"]}]},{"cell_type":"code","source":["tl_checkpoint_1 = ModelCheckpoint(filepath='/content/drive/MyDrive/CovidCV/resnet_50.hdf5',\n","                                  save_best_only=True,\n","                                  verbose=1)\n","\n","early_stop = EarlyStopping(monitor='val_accuracy',\n","                           patience=20,\n","                           restore_best_weights=True,\n","                           mode='min')"],"metadata":{"id":"lZXa0lk0rus4"},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":["**Training the model**"],"metadata":{"id":"4QJjnscZHjEe"}},{"cell_type":"code","source":["history = model.fit(traingen,\n","                    batch_size=BATCH_SIZE,\n","                    epochs=n_epochs,\n","                    validation_data=validgen,\n","                    steps_per_epoch=n_steps,\n","                    validation_steps=n_val_steps,\n","                    callbacks=[tl_checkpoint_1, early_stop])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"V6xbOJeJsVLk","executionInfo":{"status":"ok","timestamp":1646848823996,"user_tz":-330,"elapsed":2305208,"user":{"displayName":"Akash VS","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"00889159785818876835"}},"outputId":"38b78a40-10b1-48e2-d402-4329502f224c"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Epoch 1/50\n","109/109 [==============================] - ETA: 0s - loss: 0.7592 - accuracy: 0.6570\n","Epoch 1: val_loss improved from inf to 0.49028, saving model to /content/drive/MyDrive/CovidCV/resnet_50.hdf5\n","109/109 [==============================] - 997s 9s/step - loss: 0.7592 - accuracy: 0.6570 - val_loss: 0.4903 - val_accuracy: 0.7780\n","Epoch 2/50\n","109/109 [==============================] - ETA: 0s - loss: 0.4874 - accuracy: 0.7622\n","Epoch 2: val_loss improved from 0.49028 to 0.44454, saving model to /content/drive/MyDrive/CovidCV/resnet_50.hdf5\n","109/109 [==============================] - 55s 503ms/step - loss: 0.4874 - accuracy: 0.7622 - val_loss: 0.4445 - val_accuracy: 0.7788\n","Epoch 3/50\n","109/109 [==============================] - ETA: 0s - loss: 0.3936 - accuracy: 0.8254\n","Epoch 3: val_loss improved from 0.44454 to 0.39015, saving model to /content/drive/MyDrive/CovidCV/resnet_50.hdf5\n","109/109 [==============================] - 53s 482ms/step - loss: 0.3936 - accuracy: 0.8254 - val_loss: 0.3901 - val_accuracy: 0.8100\n","Epoch 4/50\n","109/109 [==============================] - ETA: 0s - loss: 0.3660 - accuracy: 0.8418\n","Epoch 4: val_loss improved from 0.39015 to 0.38221, saving model to /content/drive/MyDrive/CovidCV/resnet_50.hdf5\n","109/109 [==============================] - 53s 489ms/step - loss: 0.3660 - accuracy: 0.8418 - val_loss: 0.3822 - val_accuracy: 0.8158\n","Epoch 5/50\n","109/109 [==============================] - ETA: 0s - loss: 0.3264 - accuracy: 0.8702\n","Epoch 5: val_loss did not improve from 0.38221\n","109/109 [==============================] - 46s 418ms/step - loss: 0.3264 - accuracy: 0.8702 - val_loss: 0.4010 - val_accuracy: 0.8183\n","Epoch 6/50\n","109/109 [==============================] - ETA: 0s - loss: 0.3139 - accuracy: 0.8702\n","Epoch 6: val_loss did not improve from 0.38221\n","109/109 [==============================] - 46s 419ms/step - loss: 0.3139 - accuracy: 0.8702 - val_loss: 0.4590 - val_accuracy: 0.8174\n","Epoch 7/50\n","109/109 [==============================] - ETA: 0s - loss: 0.3147 - accuracy: 0.8649\n","Epoch 7: val_loss did not improve from 0.38221\n","109/109 [==============================] - 46s 422ms/step - loss: 0.3147 - accuracy: 0.8649 - val_loss: 0.4410 - val_accuracy: 0.8158\n","Epoch 8/50\n","109/109 [==============================] - ETA: 0s - loss: 0.2777 - accuracy: 0.8896\n","Epoch 8: val_loss improved from 0.38221 to 0.36919, saving model to /content/drive/MyDrive/CovidCV/resnet_50.hdf5\n","109/109 [==============================] - 53s 483ms/step - loss: 0.2777 - accuracy: 0.8896 - val_loss: 0.3692 - val_accuracy: 0.8322\n","Epoch 9/50\n","109/109 [==============================] - ETA: 0s - loss: 0.2583 - accuracy: 0.9028\n","Epoch 9: val_loss improved from 0.36919 to 0.36855, saving model to /content/drive/MyDrive/CovidCV/resnet_50.hdf5\n","109/109 [==============================] - 53s 491ms/step - loss: 0.2583 - accuracy: 0.9028 - val_loss: 0.3685 - val_accuracy: 0.8363\n","Epoch 10/50\n","109/109 [==============================] - ETA: 0s - loss: 0.2498 - accuracy: 0.9025\n","Epoch 10: val_loss improved from 0.36855 to 0.36574, saving model to /content/drive/MyDrive/CovidCV/resnet_50.hdf5\n","109/109 [==============================] - 53s 489ms/step - loss: 0.2498 - accuracy: 0.9025 - val_loss: 0.3657 - val_accuracy: 0.8347\n","Epoch 11/50\n","109/109 [==============================] - ETA: 0s - loss: 0.2256 - accuracy: 0.9207\n","Epoch 11: val_loss did not improve from 0.36574\n","109/109 [==============================] - 46s 418ms/step - loss: 0.2256 - accuracy: 0.9207 - val_loss: 0.3999 - val_accuracy: 0.8322\n","Epoch 12/50\n","109/109 [==============================] - ETA: 0s - loss: 0.2344 - accuracy: 0.9077\n","Epoch 12: val_loss improved from 0.36574 to 0.33636, saving model to /content/drive/MyDrive/CovidCV/resnet_50.hdf5\n","109/109 [==============================] - 52s 475ms/step - loss: 0.2344 - accuracy: 0.9077 - val_loss: 0.3364 - val_accuracy: 0.8536\n","Epoch 13/50\n","109/109 [==============================] - ETA: 0s - loss: 0.2264 - accuracy: 0.9147\n","Epoch 13: val_loss did not improve from 0.33636\n","109/109 [==============================] - 47s 432ms/step - loss: 0.2264 - accuracy: 0.9147 - val_loss: 0.4762 - val_accuracy: 0.8224\n","Epoch 14/50\n","109/109 [==============================] - ETA: 0s - loss: 0.2196 - accuracy: 0.9138\n","Epoch 14: val_loss did not improve from 0.33636\n","109/109 [==============================] - 46s 419ms/step - loss: 0.2196 - accuracy: 0.9138 - val_loss: 0.3906 - val_accuracy: 0.8396\n","Epoch 15/50\n","109/109 [==============================] - ETA: 0s - loss: 0.2247 - accuracy: 0.9062\n","Epoch 15: val_loss did not improve from 0.33636\n","109/109 [==============================] - 46s 419ms/step - loss: 0.2247 - accuracy: 0.9062 - val_loss: 0.4228 - val_accuracy: 0.8363\n","Epoch 16/50\n","109/109 [==============================] - ETA: 0s - loss: 0.2029 - accuracy: 0.9207\n","Epoch 16: val_loss did not improve from 0.33636\n","109/109 [==============================] - 45s 417ms/step - loss: 0.2029 - accuracy: 0.9207 - val_loss: 0.4158 - val_accuracy: 0.8347\n","Epoch 17/50\n","109/109 [==============================] - ETA: 0s - loss: 0.2121 - accuracy: 0.9174\n","Epoch 17: val_loss did not improve from 0.33636\n","109/109 [==============================] - 46s 418ms/step - loss: 0.2121 - accuracy: 0.9174 - val_loss: 0.4273 - val_accuracy: 0.8355\n","Epoch 18/50\n","109/109 [==============================] - ETA: 0s - loss: 0.1871 - accuracy: 0.9286\n","Epoch 18: val_loss did not improve from 0.33636\n","109/109 [==============================] - 45s 416ms/step - loss: 0.1871 - accuracy: 0.9286 - val_loss: 0.5012 - val_accuracy: 0.8298\n","Epoch 19/50\n","109/109 [==============================] - ETA: 0s - loss: 0.1758 - accuracy: 0.9360\n","Epoch 19: val_loss did not improve from 0.33636\n","109/109 [==============================] - 46s 419ms/step - loss: 0.1758 - accuracy: 0.9360 - val_loss: 0.4380 - val_accuracy: 0.8380\n","Epoch 20/50\n","109/109 [==============================] - ETA: 0s - loss: 0.1723 - accuracy: 0.9348\n","Epoch 20: val_loss did not improve from 0.33636\n","109/109 [==============================] - 45s 415ms/step - loss: 0.1723 - accuracy: 0.9348 - val_loss: 0.4527 - val_accuracy: 0.8347\n","Epoch 21/50\n","109/109 [==============================] - ETA: 0s - loss: 0.1636 - accuracy: 0.9421\n","Epoch 21: val_loss did not improve from 0.33636\n","109/109 [==============================] - 46s 421ms/step - loss: 0.1636 - accuracy: 0.9421 - val_loss: 0.4468 - val_accuracy: 0.8322\n"]}]},{"cell_type":"markdown","source":["**Result**"],"metadata":{"id":"FPZ0xHH9Ho9e"}},{"cell_type":"code","source":["import matplotlib.pyplot as plt\n","acc = history.history['accuracy']\n","val_acc = history.history['val_accuracy']\n","loss = history.history['loss']\n","val_loss = history.history['val_loss']\n","\n","epochs = range(len(acc))\n","\n","plt.plot(epochs, acc, 'bo', label='Training accuracy')\n","plt.plot(epochs, val_acc, 'b', label='Validation accuracy')\n","plt.title('Training and validation accuracy')\n","\n","plt.figure()\n","\n","plt.plot(epochs, loss, 'bo', label='Training Loss')\n","plt.plot(epochs, val_loss, 'b', label='Validation Loss')\n","plt.title('Training and validation loss')\n","plt.legend()\n","\n","plt.show()"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":545},"id":"JzzBQYX03xLo","executionInfo":{"status":"ok","timestamp":1646849391966,"user_tz":-330,"elapsed":1349,"user":{"displayName":"Akash VS","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"00889159785818876835"}},"outputId":"450ead1a-e6d8-43b3-a2d3-dd491cfd3014"},"execution_count":null,"outputs":[{"output_type":"display_data","data":{"image/png":"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\n","text/plain":["<Figure 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\n","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":["**Accuracy**"],"metadata":{"id":"3ge9EB3vHxet"}},{"cell_type":"code","source":["acc = history.history['accuracy'][-1]\n","loss = history.history['loss'][-1]\n","print('Training Accuracy:',acc);\n","print('Training loss:',loss)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"UIjBJOvT37jq","executionInfo":{"status":"ok","timestamp":1646849482501,"user_tz":-330,"elapsed":355,"user":{"displayName":"Akash VS","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"00889159785818876835"}},"outputId":"560f6ffd-ab25-451d-d669-d58844c748c6"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Training Accuracy: 0.942130982875824\n","Training loss: 0.16357126832008362\n"]}]},{"cell_type":"markdown","source":["**Loading the weights of the saved model for prediction**"],"metadata":{"id":"i15lHWrZH8Fs"}},{"cell_type":"code","source":["model.load_weights('/content/drive/MyDrive/CovidCV/resnet_50.hdf5')\n","preds_ft = model.predict(testgen)\n","pred_classes_ft = np.argmax(preds_ft, axis=1)"],"metadata":{"id":"jTd27DyJK0Ia","executionInfo":{"status":"ok","timestamp":1652898055395,"user_tz":-330,"elapsed":689343,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}}},"execution_count":7,"outputs":[]},{"cell_type":"code","source":["true_classes = testgen.classes\n","print(true_classes)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"4fyjlMwu4PJ4","executionInfo":{"status":"ok","timestamp":1652898231825,"user_tz":-330,"elapsed":929,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"1e3eeebe-344b-4f3a-bf2a-e17fa2c32752"},"execution_count":8,"outputs":[{"output_type":"stream","name":"stdout","text":["[0 0 0 ... 1 1 1]\n"]}]},{"cell_type":"code","source":["from sklearn.metrics import accuracy_score\n","\n","acc_ft = accuracy_score(true_classes, pred_classes_ft)\n","print(\"Test Accuracy: {:.2f}%\".format(acc_ft * 100))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"z2jv4ff76sBN","executionInfo":{"status":"ok","timestamp":1648315687854,"user_tz":-330,"elapsed":937,"user":{"displayName":"Akash VS","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"00889159785818876835"}},"outputId":"d188cdb4-842d-4bc1-a965-c543d9a4c294"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Test Accuracy: 88.70%\n"]}]},{"cell_type":"markdown","source":["**Evaluation metrics**"],"metadata":{"id":"ctin7D4U6UcC"}},{"cell_type":"code","source":["# precision tp / (tp + fp)\n","precision = precision_score(true_classes, pred_classes_ft)\n","print(\"Precision: {:.2f}%\".format(precision))\n","\n","# recall: tp / (tp + fn)\n","recall = recall_score(true_classes, pred_classes_ft)\n","print(\"Recall: {:.2f}%\".format(recall))\n","\n","# f1: 2 tp / (2 tp + fp + fn)\n","f1 = f1_score(true_classes, pred_classes_ft)\n","print(\"F1 score: {:.2f}%\".format(f1))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"s4JL4cNO2LuV","executionInfo":{"status":"ok","timestamp":1648392638396,"user_tz":-330,"elapsed":334,"user":{"displayName":"Akash VS","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"00889159785818876835"}},"outputId":"a9cdf4f3-9936-4be3-d9b0-db729b16ac27"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Precision: 0.93%\n","Recall: 0.83%\n","F1 score: 0.88%\n"]}]},{"cell_type":"code","source":["# confusion matrix\n","matrix = confusion_matrix(true_classes, pred_classes_ft)\n","print(matrix)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"3cCuL-s627Wm","executionInfo":{"status":"ok","timestamp":1648392687515,"user_tz":-330,"elapsed":347,"user":{"displayName":"Akash VS","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"00889159785818876835"}},"outputId":"28cf3e56-ecac-4fc4-cb7f-a06b88e6531b"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["[[939  61]\n"," [165 835]]\n"]}]},{"cell_type":"markdown","source":["**Test a sample image**"],"metadata":{"id":"hLlMWOaMvWPy"}},{"cell_type":"code","source":["from keras.preprocessing import image\n","\n","img = image.load_img(\"/content/drive/MyDrive/CovidCV/test/normal/lfkdkdjdj (37).jpg\",target_size=(150,150))\n","img = np.asarray(img).astype(\"float32\")\n","img = np.expand_dims(img, axis=0)\n","output = model.predict(img)\n","print(output)\n","\n","if output[0][0] > output[0][1]:\n","    print(\"Image is predicted as covid\")\n","else:\n","    print(\"Image is predicted as normal\")\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"oeXgAsnnvbbp","executionInfo":{"status":"ok","timestamp":1651312004173,"user_tz":-330,"elapsed":1374,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"a7073483-4658-4cfd-bffa-5ae6bcb19fcf"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["[[1.0000000e+00 1.8241679e-11]]\n","Image is predicted as covid\n"]}]},{"cell_type":"markdown","source":["## **EXPLAINABLE AI**"],"metadata":{"id":"SWsLMxZkZXSs"}},{"cell_type":"markdown","source":["###**IMPLEMENTATION OF LIME**"],"metadata":{"id":"Ve01JjiYZxpB"}},{"cell_type":"code","source":["!pip install lime"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"2vSFeFhsg-7a","executionInfo":{"status":"ok","timestamp":1652898539042,"user_tz":-330,"elapsed":5119,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"04b204b0-d083-4ab6-d282-47a0e8cfdb79"},"execution_count":10,"outputs":[{"output_type":"stream","name":"stdout","text":["Collecting lime\n","  Downloading lime-0.2.0.1.tar.gz (275 kB)\n","\u001b[?25l\r\u001b[K     |█▏                              | 10 kB 31.8 MB/s eta 0:00:01\r\u001b[K     |██▍                             | 20 kB 38.8 MB/s eta 0:00:01\r\u001b[K     |███▋                            | 30 kB 35.9 MB/s eta 0:00:01\r\u001b[K     |████▊                           | 40 kB 26.7 MB/s eta 0:00:01\r\u001b[K     |██████                          | 51 kB 28.8 MB/s eta 0:00:01\r\u001b[K     |███████▏                        | 61 kB 32.4 MB/s eta 0:00:01\r\u001b[K     |████████▎                       | 71 kB 25.6 MB/s eta 0:00:01\r\u001b[K     |█████████▌                      | 81 kB 27.0 MB/s eta 0:00:01\r\u001b[K     |██████████▊                     | 92 kB 29.2 MB/s eta 0:00:01\r\u001b[K     |███████████▉                    | 102 kB 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/usr/local/lib/python3.7/dist-packages (from lime) (0.18.3)\n","Requirement already satisfied: imageio>=2.3.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.12->lime) (2.4.1)\n","Requirement already satisfied: PyWavelets>=1.1.1 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.12->lime) (1.3.0)\n","Requirement already satisfied: networkx>=2.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.12->lime) (2.6.3)\n","Requirement already satisfied: tifffile>=2019.7.26 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.12->lime) (2021.11.2)\n","Requirement already satisfied: pillow!=7.1.0,!=7.1.1,>=4.3.0 in /usr/local/lib/python3.7/dist-packages (from scikit-image>=0.12->lime) (7.1.2)\n","Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->lime) (2.8.2)\n","Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->lime) (3.0.9)\n","Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib->lime) (0.11.0)\n","Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib->lime) (1.4.2)\n","Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from kiwisolver>=1.0.1->matplotlib->lime) (4.2.0)\n","Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.1->matplotlib->lime) (1.15.0)\n","Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from scikit-learn>=0.18->lime) (3.1.0)\n","Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.7/dist-packages (from scikit-learn>=0.18->lime) (1.1.0)\n","Building wheels for collected packages: lime\n","  Building wheel for lime (setup.py) ... \u001b[?25l\u001b[?25hdone\n","  Created wheel for lime: filename=lime-0.2.0.1-py3-none-any.whl size=283857 sha256=e960422cbd6df4bee3585f5c296d38aff29831349e71e871359c4a93ddd6ad62\n","  Stored in directory: /root/.cache/pip/wheels/ca/cb/e5/ac701e12d365a08917bf4c6171c0961bc880a8181359c66aa7\n","Successfully built lime\n","Installing collected packages: lime\n","Successfully installed lime-0.2.0.1\n"]}]},{"cell_type":"markdown","source":["**Testing a covid sample image**"],"metadata":{"id":"Oebtwocjt1A2"}},{"cell_type":"code","source":["img = testgen[10][10]\n","img = np.expand_dims(img, axis=0)\n","output = model.predict(img)\n","print(output)\n","\n","if output[0][0] > output[0][1]:\n","    print(\"Image is predicted as covid\")\n","else:\n","    print(\"Image is predicted as normal\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"cnQS_uBut5rL","executionInfo":{"status":"ok","timestamp":1652899647155,"user_tz":-330,"elapsed":802,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"7ced22de-ce07-4822-90c5-77a7833642ad"},"execution_count":47,"outputs":[{"output_type":"stream","name":"stdout","text":["[[0.71956253 0.18923515]]\n","Image is predicted as covid\n"]}]},{"cell_type":"code","source":["plt.imshow(testgen[10][10])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":286},"id":"F-LseOQK1dK9","executionInfo":{"status":"ok","timestamp":1652899651230,"user_tz":-330,"elapsed":112,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"7d374252-b96d-4fe4-ac35-4dea11debf16"},"execution_count":48,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.image.AxesImage at 0x7f9b29398cd0>"]},"metadata":{},"execution_count":48},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":["**Calculating superpixels**"],"metadata":{"id":"Krd9X9NgK3uy"}},{"cell_type":"code","source":["Xi = img[0].astype(\"double\")\n","superpixels = skimage.segmentation.quickshift(Xi, kernel_size=4,max_dist=200, ratio=0.2)\n","num_superpixels = np.unique(superpixels).shape[0]\n","num_superpixels"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"gyDtYLynTYpr","executionInfo":{"status":"ok","timestamp":1652899655859,"user_tz":-330,"elapsed":547,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"a8e2f0a4-df5d-4a67-9091-d7133e872b5e"},"execution_count":49,"outputs":[{"output_type":"execute_result","data":{"text/plain":["21"]},"metadata":{},"execution_count":49}]},{"cell_type":"code","source":["skimage.io.imshow(skimage.segmentation.mark_boundaries(Xi/2+0.5, superpixels))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":314},"id":"abWq9bs1TeWE","executionInfo":{"status":"ok","timestamp":1652899662650,"user_tz":-330,"elapsed":1657,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"7473cbe2-9e3b-4311-e53d-15409fe80881"},"execution_count":50,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.image.AxesImage at 0x7f9b294ed110>"]},"metadata":{},"execution_count":50},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["num_perturb = 150\n","perturbations = np.random.binomial(1, 0.5, size=(num_perturb, num_superpixels))\n","perturbations[0] #Show example of perturbation"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"awIGcBXrTnR1","executionInfo":{"status":"ok","timestamp":1652899666549,"user_tz":-330,"elapsed":700,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"63fc4a26-5c37-4ef1-fbc7-9347dfefcd1a"},"execution_count":51,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0])"]},"metadata":{},"execution_count":51}]},{"cell_type":"code","source":["def perturb_image(img,perturbation,segments):\n","  active_pixels = np.where(perturbation == 1)[0]\n","  mask = np.zeros(segments.shape)\n","  for active in active_pixels:\n","      mask[segments == active] = 1 \n","  perturbed_image = copy.deepcopy(img)\n","  perturbed_image = perturbed_image*mask[:,:,np.newaxis]\n","  return perturbed_image"],"metadata":{"id":"t913U4HcTtS5","executionInfo":{"status":"ok","timestamp":1652899669517,"user_tz":-330,"elapsed":2,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}}},"execution_count":52,"outputs":[]},{"cell_type":"markdown","source":["**Visualizing perturbed images**"],"metadata":{"id":"qAM2F3WgLFCl"}},{"cell_type":"code","source":["skimage.io.imshow(perturb_image(Xi/2+0.5,perturbations[0],superpixels))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":314},"id":"Ho5llRC7T1CI","executionInfo":{"status":"ok","timestamp":1652899672697,"user_tz":-330,"elapsed":6,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"93231625-16d9-412d-8371-82968b9f5d5c"},"execution_count":53,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.image.AxesImage at 0x7f9c7be512d0>"]},"metadata":{},"execution_count":53},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["predictions = []\n","for pert in perturbations:\n","  perturbed_img = perturb_image(Xi,pert,superpixels)\n","  pred = model.predict(perturbed_img[np.newaxis,:,:,:])\n","  predictions.append(pred)\n","\n","predictions = np.array(predictions)\n","predictions.shape"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"FQyRbW-iT5zB","executionInfo":{"status":"ok","timestamp":1652899711761,"user_tz":-330,"elapsed":8916,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"f7b5e708-a00d-46ac-c92b-ae8a41304411"},"execution_count":55,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(150, 1, 2)"]},"metadata":{},"execution_count":55}]},{"cell_type":"markdown","source":["**Calculating distances using cosine metric**"],"metadata":{"id":"AIlBeifrKxHX"}},{"cell_type":"code","source":["original_image = np.ones(num_superpixels)[np.newaxis,:] #Perturbation with all superpixels enabled \n","distances = sklearn.metrics.pairwise_distances(perturbations,original_image, metric='cosine').ravel()\n","distances.shape"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"wzwlksEPUHOc","executionInfo":{"status":"ok","timestamp":1652899715351,"user_tz":-330,"elapsed":529,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"1227ee09-d58d-40a5-88da-5bb27e64db36"},"execution_count":56,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(150,)"]},"metadata":{},"execution_count":56}]},{"cell_type":"markdown","source":["**Mapping distance values to weights**"],"metadata":{"id":"KoeHlM9hKtF3"}},{"cell_type":"code","source":["kernel_width = 0.25\n","weights = np.sqrt(np.exp(-(distances**2)/kernel_width**2)) #Kernel function\n","weights.shape"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"2MqimUQBUMQE","executionInfo":{"status":"ok","timestamp":1652899718536,"user_tz":-330,"elapsed":4,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"2356fb56-614e-4ad8-dca5-019ac8ba842e"},"execution_count":57,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(150,)"]},"metadata":{},"execution_count":57}]},{"cell_type":"code","source":["class_to_explain = 0\n","simpler_model = LinearRegression()\n","simpler_model.fit(X=perturbations, y=predictions[:,:,class_to_explain], sample_weight=weights)\n","coeff = simpler_model.coef_[0]\n","coeff"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"PqPnsxffUP3t","executionInfo":{"status":"ok","timestamp":1652899723365,"user_tz":-330,"elapsed":8,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"092a4321-f81f-4dab-8cd5-ef554accdb9d"},"execution_count":58,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([ 0.24450415,  0.07896672, -0.07402024,  0.24886618,  0.0559503 ,\n","       -0.04778802,  0.0477696 , -0.09155641, -0.00361992,  0.09514559,\n","       -0.13996805,  0.06598704,  0.02786102,  0.03675631,  0.03710897,\n","        0.00379032, -0.01578316,  0.05896718, -0.04816111,  0.02486546,\n","        0.01528517])"]},"metadata":{},"execution_count":58}]},{"cell_type":"code","source":["num_top_features = 4\n","top_features = np.argsort(coeff)[-num_top_features:] \n","top_features"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"PjT-Df5tUWG1","executionInfo":{"status":"ok","timestamp":1652899727422,"user_tz":-330,"elapsed":542,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"3bcca994-0357-4b6a-ff91-e4622c22804e"},"execution_count":59,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([1, 9, 0, 3])"]},"metadata":{},"execution_count":59}]},{"cell_type":"code","source":["from skimage.segmentation import mark_boundaries\n","import matplotlib.pyplot as plt\n","from lime import lime_image\n","\n","explainer = lime_image.LimeImageExplainer()\n","explanation = explainer.explain_instance(Xi, model.predict)\n","temp_1, mask_1 = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=True, num_features=4, hide_rest=True)\n","temp_2, mask_2 = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=False, num_features=2, hide_rest=False)\n","\n","fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,15))\n","ax1.imshow(mark_boundaries(temp_1, mask_1))\n","ax2.imshow(mark_boundaries(temp_2, mask_2))\n","ax1.axis('off')\n","ax2.axis('off')"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":460,"referenced_widgets":["e347740342f64d0fba591fcb5e18e6a7","69f609b0ecd541358673ff57b1aee13b","36a3e1925e9848a48f3b41b7cbda9e13","dac4622e368949ff9a231dde3bdf2ba2","7f7819e75333453bb568559c98089615","cb78e036158a4c7c8854d9fe486953e5","2ac0246f3f4c4b8caddc0e04fe3f88de","590b427c8b4040d1b8bbb6737df68a76","74a3f25d3b404aa786823b0761936d63","3f3a477de5bb44409d5ff60e08ed7fb5","38d608f3ce934637a7d0e0c005d8bb53"]},"id":"lpkDY6fYcVEC","executionInfo":{"status":"ok","timestamp":1652899747042,"user_tz":-330,"elapsed":11830,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"cc62af4e-ebf5-4252-cc2a-9404f2b6bf7e"},"execution_count":60,"outputs":[{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/1000 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"e347740342f64d0fba591fcb5e18e6a7"}},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["(-0.5, 149.5, 149.5, -0.5)"]},"metadata":{},"execution_count":60},{"output_type":"display_data","data":{"text/plain":["<Figure size 1080x1080 with 2 Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":["**Testing a normal sample image**"],"metadata":{"id":"rL1_bc9Lt6Rc"}},{"cell_type":"code","source":["img = testgen[60][5]\n","img = np.expand_dims(img, axis=0)\n","output = model.predict(img)\n","print(output)\n","\n","if output[0][0] > output[0][1]:\n","    print(\"Image is predicted as covid\")\n","else:\n","    print(\"Image is predicted as normal\")\n"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"lRP_MMAat_xN","executionInfo":{"status":"ok","timestamp":1652898632569,"user_tz":-330,"elapsed":552,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"13edff4a-02a5-4d47-c1eb-86c8b9b03fa1"},"execution_count":24,"outputs":[{"output_type":"stream","name":"stdout","text":["[[0.45813707 0.49711955]]\n","Image is predicted as normal\n"]}]},{"cell_type":"code","source":["plt.imshow(testgen[60][5])"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":286},"id":"oXQp9l01HvK-","executionInfo":{"status":"ok","timestamp":1652898637295,"user_tz":-330,"elapsed":1963,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"d9029d81-ff38-4d67-eb56-cee1d0e74ff1"},"execution_count":25,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.image.AxesImage at 0x7f9b2949fe50>"]},"metadata":{},"execution_count":25},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":["**Calculating superpixels**"],"metadata":{"id":"vNa4VVv_H0q9"}},{"cell_type":"code","source":["Xi = img[0].astype(\"double\")\n","superpixels = skimage.segmentation.quickshift(Xi, kernel_size=4,max_dist=200, ratio=0.2)\n","num_superpixels = np.unique(superpixels).shape[0]\n","num_superpixels"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"OdLhhNMIXWw_","executionInfo":{"status":"ok","timestamp":1652898641887,"user_tz":-330,"elapsed":5,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"1a5a67cc-ba7f-4fa7-cf3a-fe09999d3884"},"execution_count":26,"outputs":[{"output_type":"execute_result","data":{"text/plain":["17"]},"metadata":{},"execution_count":26}]},{"cell_type":"code","source":["skimage.io.imshow(skimage.segmentation.mark_boundaries(Xi/2+0.5, superpixels))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":314},"id":"_s1w7g9rXcHC","executionInfo":{"status":"ok","timestamp":1652898644888,"user_tz":-330,"elapsed":6,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"e05dc2ed-8531-4c68-a7f4-01fa45523d20"},"execution_count":27,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.image.AxesImage at 0x7f9b292e7b10>"]},"metadata":{},"execution_count":27},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["num_perturb = 150\n","perturbations = np.random.binomial(1, 0.5, size=(num_perturb, num_superpixels))\n","perturbations[0] #Show example of perturbation"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"fMZ95UMmXkCu","executionInfo":{"status":"ok","timestamp":1652898649368,"user_tz":-330,"elapsed":1024,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"a7a19c68-d08d-4445-9713-8a1be3e6017a"},"execution_count":28,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([0, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 0, 0, 1, 0, 1, 1])"]},"metadata":{},"execution_count":28}]},{"cell_type":"code","source":["def perturb_image(img,perturbation,segments):\n","  active_pixels = np.where(perturbation == 1)[0]\n","  mask = np.zeros(segments.shape)\n","  for active in active_pixels:\n","      mask[segments == active] = 1 \n","  perturbed_image = copy.deepcopy(img)\n","  perturbed_image = perturbed_image*mask[:,:,np.newaxis]\n","  return perturbed_image"],"metadata":{"id":"l38TCU2_XpUM","executionInfo":{"status":"ok","timestamp":1652898652758,"user_tz":-330,"elapsed":4,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}}},"execution_count":29,"outputs":[]},{"cell_type":"markdown","source":["**Visualizing perturbed images**"],"metadata":{"id":"IglIrCOIH7-D"}},{"cell_type":"code","source":["skimage.io.imshow(perturb_image(Xi/2+0.5,perturbations[3],superpixels))"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":314},"id":"LsyFxWzBX4Ey","executionInfo":{"status":"ok","timestamp":1652898656677,"user_tz":-330,"elapsed":834,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"c5ed94bf-b3a3-4458-d4fa-18c8cb2c54c8"},"execution_count":30,"outputs":[{"output_type":"execute_result","data":{"text/plain":["<matplotlib.image.AxesImage at 0x7f9b291da210>"]},"metadata":{},"execution_count":30},{"output_type":"display_data","data":{"text/plain":["<Figure size 432x288 with 1 Axes>"],"image/png":"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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"code","source":["predictions = []\n","for pert in perturbations:\n","  perturbed_img = perturb_image(Xi,pert,superpixels)\n","  pred = model.predict(perturbed_img[np.newaxis,:,:,:])\n","  predictions.append(pred)\n","\n","predictions = np.array(predictions)\n","predictions.shape"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"WMKIL2E-YCk8","executionInfo":{"status":"ok","timestamp":1652898669529,"user_tz":-330,"elapsed":8898,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"4134db14-1039-4c46-8fb4-34c0a5d0cabc"},"execution_count":31,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(150, 1, 2)"]},"metadata":{},"execution_count":31}]},{"cell_type":"markdown","source":["**Calculating distances using cosine metric**"],"metadata":{"id":"68brRoYFINHs"}},{"cell_type":"code","source":["original_image = np.ones(num_superpixels)[np.newaxis,:] #Perturbation with all superpixels enabled \n","distances = sklearn.metrics.pairwise_distances(perturbations,original_image, metric='cosine').ravel()\n","distances.shape"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"M8eZTmmLYOiJ","executionInfo":{"status":"ok","timestamp":1652898672945,"user_tz":-330,"elapsed":858,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"a647d898-e9ea-4b3c-dcc3-dfb8b7f2485d"},"execution_count":32,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(150,)"]},"metadata":{},"execution_count":32}]},{"cell_type":"markdown","source":["**Mapping distance values to weights**"],"metadata":{"id":"VWApJZGEIS2z"}},{"cell_type":"code","source":["kernel_width = 0.25\n","weights = np.sqrt(np.exp(-(distances**2)/kernel_width**2)) #Kernel function\n","weights.shape"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"GH_SLOFVYXQj","executionInfo":{"status":"ok","timestamp":1652898675780,"user_tz":-330,"elapsed":4,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"5f5ed695-1b2f-4ebf-f7d2-7a89b93f7d66"},"execution_count":33,"outputs":[{"output_type":"execute_result","data":{"text/plain":["(150,)"]},"metadata":{},"execution_count":33}]},{"cell_type":"code","source":["class_to_explain = 1\n","simpler_model = LinearRegression()\n","simpler_model.fit(X=perturbations, y=predictions[:,:,class_to_explain], sample_weight=weights)\n","coeff = simpler_model.coef_[0]\n","coeff"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"nL8tZrHCYbQg","executionInfo":{"status":"ok","timestamp":1652898678444,"user_tz":-330,"elapsed":7,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"388139a7-d87b-4910-ec66-49f1772a7412"},"execution_count":34,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([-0.05538153, -0.05124718, -0.00795117,  0.06664561, -0.0306482 ,\n","       -0.02790758, -0.02577775,  0.02034795,  0.15096707, -0.0908085 ,\n","       -0.04474152, -0.0044102 , -0.19806814, -0.07270281,  0.13742464,\n","       -0.00415267,  0.05373173])"]},"metadata":{},"execution_count":34}]},{"cell_type":"code","source":["num_top_features = 4\n","top_features = np.argsort(coeff)[-num_top_features:] \n","top_features"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"bsRtBebvYeO4","executionInfo":{"status":"ok","timestamp":1652898681671,"user_tz":-330,"elapsed":6,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"82ad7eb8-7af0-494b-8d75-64c5d6b94904"},"execution_count":35,"outputs":[{"output_type":"execute_result","data":{"text/plain":["array([16,  3, 14,  8])"]},"metadata":{},"execution_count":35}]},{"cell_type":"code","source":["from lime import lime_image\n","from skimage.segmentation import mark_boundaries\n","import matplotlib.pyplot as plt\n","\n","explainer = lime_image.LimeImageExplainer()\n","explanation = explainer.explain_instance(Xi, model.predict)\n","temp_1, mask_1 = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=True, num_features=2, hide_rest=True)\n","temp_2, mask_2 = explanation.get_image_and_mask(explanation.top_labels[0], positive_only=False, num_features=5, hide_rest=False)\n","\n","fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(15,15))\n","ax1.imshow(mark_boundaries(temp_1, mask_1))\n","ax2.imshow(mark_boundaries(temp_2, mask_2))\n","ax1.axis('off')\n","ax2.axis('off')"],"metadata":{"id":"Hvl9xYcQzNRA","colab":{"base_uri":"https://localhost:8080/","height":460,"referenced_widgets":["f88d21b952fc4b809bae53029bcec9a3","18b152eadb634e45a4f19a68f280f007","e785f62312b347b6af7032ca1a0c49a5","78445191c53347be800ccd9b1dc8871f","27bd9c896e794ffaa66c40de82ed0753","7334571e4ea849378338a7eae3f05d20","0e6a0a370bdc40c5bfe20c92335f9623","7d8598d272ed43fabda502d807e48a04","15cdf3939fa64c1fb3adf9ce4b485666","eaca31973159414bb77628d084d4b071","1e88563ec5944c369dbb5abe823951b3"]},"executionInfo":{"status":"ok","timestamp":1652898857161,"user_tz":-330,"elapsed":14234,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"outputId":"888f0c0e-237d-4bce-a9a0-7f59442689e0"},"execution_count":37,"outputs":[{"output_type":"display_data","data":{"text/plain":["  0%|          | 0/1000 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"f88d21b952fc4b809bae53029bcec9a3"}},"metadata":{}},{"output_type":"execute_result","data":{"text/plain":["(-0.5, 149.5, 149.5, -0.5)"]},"metadata":{},"execution_count":37},{"output_type":"display_data","data":{"text/plain":["<Figure size 1080x1080 with 2 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\n"},"metadata":{"needs_background":"light"}}]},{"cell_type":"markdown","source":["###**IMPLEMENTATION OF GRADCAM**"],"metadata":{"id":"B6cLVg-Kty_k"}},{"cell_type":"code","source":["import numpy as np\n","import tensorflow as tf\n","from tensorflow import keras\n","\n","# Display\n","from IPython.display import Image, display\n","import matplotlib.pyplot as plt\n","import matplotlib.cm as cm\n","import cv2\n","\n","last_conv_layer_name = \"conv5_block3_out\"\n","\n","def get_img_array(img_path, size):\n","    img = keras.preprocessing.image.load_img(img_path, target_size=size)\n","    array = keras.preprocessing.image.img_to_array(img)\n","    array = np.expand_dims(array, axis=0)\n","    return array\n","\n","\n","def make_gradcam_heatmap(img_array, model, last_conv_layer_name, pred_index=None):\n","    grad_model = tf.keras.models.Model(\n","        [model.inputs], [model.get_layer(last_conv_layer_name).output, model.output]\n","    )\n","    with tf.GradientTape() as tape:\n","        last_conv_layer_output, preds = grad_model(img_array)\n","        if pred_index is None:\n","            pred_index = tf.argmax(preds[0])\n","        class_channel = preds[:, pred_index]\n","    grads = tape.gradient(class_channel, last_conv_layer_output)\n","    pooled_grads = tf.reduce_mean(grads, axis=(0, 1, 2))\n","    last_conv_layer_output = last_conv_layer_output[0]\n","    heatmap = last_conv_layer_output @ pooled_grads[..., tf.newaxis]\n","    heatmap = tf.squeeze(heatmap)\n","    heatmap = tf.maximum(heatmap, 0) / tf.math.reduce_max(heatmap)\n","    return heatmap.numpy()"],"metadata":{"id":"Gc6rwJMDzxNl","executionInfo":{"status":"ok","timestamp":1652899379706,"user_tz":-330,"elapsed":1060,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}}},"execution_count":41,"outputs":[]},{"cell_type":"code","source":["def save_and_display_gradcam(img, heatmap, cam_path=\"/content/drive/MyDrive/CovidCV/GradCAM result/cam.jpg\", alpha=0.8):\n","    img = np.uint8(255 * img)\n","    heatmap = np.uint8(255 * heatmap)\n","    jet = cm.get_cmap(\"jet\")\n","    jet_colors = jet(np.arange(256))[:, :3]\n","    jet_heatmap = jet_colors[heatmap]\n","    jet_heatmap = keras.preprocessing.image.array_to_img(jet_heatmap)\n","    jet_heatmap = jet_heatmap.resize((img.shape[1], img.shape[0]))\n","    jet_heatmap = keras.preprocessing.image.img_to_array(jet_heatmap)\n","    superimposed_img = jet_heatmap * alpha + img\n","    superimposed_img = keras.preprocessing.image.array_to_img(superimposed_img)\n","    superimposed_img.save(cam_path)\n","    display(Image(cam_path))\n","    return superimposed_img"],"metadata":{"id":"7MgEFs503XzV","executionInfo":{"status":"ok","timestamp":1652899423540,"user_tz":-330,"elapsed":953,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}}},"execution_count":42,"outputs":[]},{"cell_type":"markdown","source":["**Testing a Covid sample Image**"],"metadata":{"id":"yYRePHCgt8e9"}},{"cell_type":"code","source":["img = testgen[60][5]\n","img = np.expand_dims(img, axis=0)\n","heatmap = make_gradcam_heatmap(img, model, 'conv5_block3_out')\n","heatmap = cv2.resize(heatmap, (150, 150))\n","img = testgen[10][10]\n","img = cv2.resize(img, (250,250))\n","superimposed_img = save_and_display_gradcam(img, heatmap)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":267},"id":"5ZfKLxNTR5x0","outputId":"e367690f-9634-4601-a042-3926845de0de","executionInfo":{"status":"ok","timestamp":1652899457235,"user_tz":-330,"elapsed":4341,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}}},"execution_count":43,"outputs":[{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.Image object>"],"image/jpeg":"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\n"},"metadata":{}}]},{"cell_type":"markdown","source":["**Testing a normal sample Image**"],"metadata":{"id":"5uT6rD8ZuCR8"}},{"cell_type":"code","source":["img = testgen[12][7]\n","img = np.expand_dims(img, axis=0)\n","heatmap = make_gradcam_heatmap(img, model, 'conv5_block3_out')\n","heatmap = cv2.resize(heatmap, (150, 150))\n","img = testgen[60][5]\n","img = cv2.resize(img, (250,250))\n","print(img.shape)\n","superimposed_img = save_and_display_gradcam(img, heatmap)"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":284},"outputId":"d19a7453-6f06-4872-8e73-7a2b6a1e70ad","executionInfo":{"status":"ok","timestamp":1652896316093,"user_tz":-330,"elapsed":1164,"user":{"displayName":"Akash VS","userId":"00889159785818876835"}},"id":"N5ku2REzjICq"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["(250, 250, 3)\n"]},{"output_type":"display_data","data":{"text/plain":["<IPython.core.display.Image object>"],"image/jpeg":"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\n"},"metadata":{}}]}]}