transferLearningCancerDetection.ipynb

{"cells":[{"cell_type":"code","execution_count":null,"id":"WkHSY8r9-SWS","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":371,"status":"ok","timestamp":1650980887188,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"WkHSY8r9-SWS","outputId":"a401b658-e2b9-4c53-a7eb-773e51490241"},"outputs":[],"source":["# ! pip install keras_sequential_ascii\n","# !pip install scikit-plot\n","# from google.colab import drive                    # drive\n","# drive.mount(\"/content/drive\")                                                     # drive\n","# import os\n","# os.chdir(\"/content/drive/My Drive/assignments/north_umbrea/archive\")              # drive, set path"]},{"cell_type":"code","execution_count":1,"id":"8d4d0c33","metadata":{"executionInfo":{"elapsed":4700,"status":"ok","timestamp":1650980891882,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"8d4d0c33"},"outputs":[],"source":["import os\n","import numpy as np\n","import tensorflow as tf \n","import tensorflow_hub as hub \n","from sklearn.utils import shuffle \n","from matplotlib import pyplot as plt \n","from tensorflow.keras import Sequential \n","from sklearn.model_selection import train_test_split\n","from scikitplot.metrics import plot_confusion_matrix\n","from sklearn.metrics import roc_curve, auc, classification_report\n","from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Rescaling, RandomFlip, RandomRotation, RandomZoom, Dropout, Resizing"]},{"cell_type":"code","execution_count":2,"id":"3tv3jICdMiCe","metadata":{"executionInfo":{"elapsed":8,"status":"ok","timestamp":1650980891882,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"3tv3jICdMiCe"},"outputs":[],"source":["path = os.getcwd()                                                                  # local\n","path = path+'\\\\'+\"archive\"                                                          # local\n","os.chdir(path)                                                                      # local "]},{"cell_type":"code","execution_count":3,"id":"b080a79c","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":7,"status":"ok","timestamp":1650980891882,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"b080a79c","outputId":"7e027f09-2ec0-417d-e92d-b7a0b669cb17"},"outputs":[{"name":"stdout","output_type":"stream","text":["shape of X :  (5547, 50, 50, 3) \n","\n","Input image shape :  (50, 50, 3) \n","\n","Total number of samples :  (5547,) \n","\n","class distribution \n",":  [[   0 2759]\n"," [   1 2788]]\n"]}],"source":["X = np.load(\"X.npy\")\n","Y = np.load(\"Y.npy\")\n","print('shape of X : ',X.shape,'\\n') \n","print('Input image shape : ',X[0].shape,'\\n')\n","print('Total number of samples : ',Y.shape,'\\n')\n","print('class distribution \\n: ',np.array(np.unique(Y, return_counts=True)).T)"]},{"cell_type":"markdown","id":"IonBphsCzPBF","metadata":{"id":"IonBphsCzPBF"},"source":["*   The dataset consists of two '.npy' formated files with 5547 sample images of specimens with or without breast cancer. This data set is obtained from [kaggle](https://www.kaggle.com/datasets/simjeg/lymphoma-subtype-classification-fl-vs-cll?datasetId=1260&sortBy=voteCount). \n","*   Kaggle obtained this data set from Andrew Janowczyk who explained the detailed image processing methods [here](http://www.andrewjanowczyk.com/use-case-6-invasive-ductal-carcinoma-idc-segmentation/) to obtain 50*50*3 shaped images from the original [larger data set](http://andrewjanowczyk.com/wp-static/IDC_regular_ps50_idx5.zip) \n","*   The X.npy file is of shape (5547, 50, 50, 3) which is a collection of RGB images with 50*50 resolution and 5547 samples\n","\n","*   The 'Y.npy' file consists of image lables as ones and zeros indicating if a corresponding image in X is cancerous or not \n","\n","*   label value = 0 : no invasive ductal carcinoma, label value = 1 :  invasive ductal carcinoma"]},{"cell_type":"markdown","id":"_CDsSN13AGwx","metadata":{"id":"_CDsSN13AGwx"},"source":["**A look at some of the images along with their labels on X-axis**"]},{"cell_type":"code","execution_count":4,"id":"H2yMxOgjpHIJ","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":483},"executionInfo":{"elapsed":3491,"status":"ok","timestamp":1650980895368,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"H2yMxOgjpHIJ","outputId":"11580622-2628-4df1-8bd5-9d877d730eae"},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 864x576 with 25 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["plt.figure(figsize=(12,8))\n","for imageNum in range(25):\n","    plt.subplot(5,5,imageNum+1)\n","    plt.xticks([])  # Disable xticks\n","    plt.imshow(X[2745+imageNum]) \n","    plt.xlabel(Y[2745+imageNum])\n","plt.show()"]},{"cell_type":"markdown","id":"VTairSKE1rOd","metadata":{"id":"VTairSKE1rOd"},"source":["looking at the above figures we see that cancerous samples are distinctly coloured from the non-cancerous onoes.  "]},{"cell_type":"markdown","id":"MpMfkbJcDwJv","metadata":{"id":"MpMfkbJcDwJv"},"source":["## **Preprocessing**\n","*    Images generally have rgb values in range 0 to 255 as so in this case. We rescale these values between 0 and 1. Neural networks are trained on smaller values of initial weights and for faster training larger values to the input variables are not preferred. we normalize the pixel values. \n","*    we can increase the number of samples in the images by transformations like random flipping, random zooming and random rotations as these transformations do not effect the classification labels. Moreover training with such augumented data makes our model more robust as real images are generally taken without predefined such parameters. Thus over model picks up better patterns while learnng as it is exposed to the fact that images are invariant under such transformations. "]},{"cell_type":"code","execution_count":5,"id":"U2-Z02l9Dmdi","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":13,"status":"ok","timestamp":1650980895369,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"U2-Z02l9Dmdi","outputId":"1e30b3d4-7e20-4412-ba46-35c65b57c959"},"outputs":[{"name":"stdout","output_type":"stream","text":["Max value of a pixel value:  255\n"]}],"source":["print('Max value of a pixel value: ',X.max())"]},{"cell_type":"markdown","id":"3c2R01jq2DJL","metadata":{"id":"3c2R01jq2DJL"},"source":["we need to divide the pixel values by 255 for rescaling the pixel values. Also in the data set all the sample images above the 2760 numpy arry index are positively labeled and below it are negatively labeled. For a good train test split we first shuffle the image and label arrays together"]},{"cell_type":"code","execution_count":6,"id":"BtxReENhsoBQ","metadata":{"executionInfo":{"elapsed":11,"status":"ok","timestamp":1650980895370,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"BtxReENhsoBQ"},"outputs":[],"source":["x, y = shuffle(X, Y, random_state=11)"]},{"cell_type":"markdown","id":"1f639ce1","metadata":{"id":"1f639ce1"},"source":["Next we split the dataset in to training and testing components where 70% data goes for training and rest for testing"]},{"cell_type":"code","execution_count":7,"id":"6drAqcd0wEkS","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":815,"status":"ok","timestamp":1650980896175,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"6drAqcd0wEkS","outputId":"dbd6af76-d281-4b5c-8aa8-943490d265ea"},"outputs":[{"name":"stdout","output_type":"stream","text":["number of non cancerous images in training data:  3882.0\n","number of cancerous images in training data:  3882.0\n"]}],"source":["X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.3, random_state=3, shuffle=True)\n","X_train = tf.convert_to_tensor(X_train, np.float32)                   # numpy to tensor\n","y_train = tf.convert_to_tensor(y_train, np.float32) \n","X_test = tf.convert_to_tensor(X_test, np.float32)\n","y_test = tf.convert_to_tensor(y_test, np.float32)\n","y_train = tf.keras.utils.to_categorical(y_train, num_classes = 2)       # one-hot representation\n","y_test = tf.keras.utils.to_categorical(y_test, num_classes = 2) \n","distribution = np.array(np.unique(y_train, return_counts=True)).T\n","print('number of non cancerous images in training data: ',distribution[0][1])\n","print('number of cancerous images in training data: ',distribution[1][1])"]},{"cell_type":"markdown","id":"yBom01s5D81U","metadata":{"id":"yBom01s5D81U"},"source":["*    The classes are nearly balanced. \n","*    Lets define a deep neural network model with a series of convolutional layers. \n","*    Inorder to minimize the information loss from an image during convolutions we use zero padding to retain the image size.\n","*    first two layers are preprocessing layers\n","*    next 4 layers are pairs of convolutional layers followed by maxpooling\n","*    kernal size = (3,3)\n","*    Then the layers are flattened and passed to another hidden layer of 512 units with 40% dropout rate to reduce overfitting.\n","*    Finally a dense layer for classification output at the bottom of the pipeline"]},{"cell_type":"code","execution_count":8,"id":"53a9ad2a","metadata":{"executionInfo":{"elapsed":19,"status":"ok","timestamp":1650980896176,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"53a9ad2a"},"outputs":[],"source":["IMG_SIZE = 50    \n","resize_and_rescale = Sequential([ Resizing(IMG_SIZE, IMG_SIZE), Rescaling(1.0/255) ]) \n","data_augmentation = Sequential([ RandomFlip(\"horizontal_and_vertical\"), RandomRotation(0.2), RandomZoom(0.1)]) \n","model = Sequential([\n","  resize_and_rescale,\n","  data_augmentation,\n","  Conv2D(32, (3,3), activation='relu', padding='same'), MaxPooling2D(2, 2),\n","  Conv2D(64, (3,3), activation='relu', padding='same'), MaxPooling2D(2,2),\n","  Conv2D(128, (3,3), activation='relu', padding='same'), MaxPooling2D(2,2),\n","  Conv2D(128, (3,3), activation='relu', padding='same'), MaxPooling2D(2,2),\n","  Flatten(),\n","  Dropout(0.4),                    \n","  Dense(512, activation='relu'),\n","  Dense(2, activation='softmax')\n","]) "]},{"cell_type":"code","execution_count":10,"id":"a241osbKAFdS","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":20,"status":"ok","timestamp":1650980896178,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"a241osbKAFdS","outputId":"028f1ee5-7741-40fc-9231-25afee747947"},"outputs":[{"name":"stdout","output_type":"stream","text":["Model: \"sequential_2\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," sequential (Sequential)     (None, 50, 50, 3)         0         \n","                                                                 \n"," sequential_1 (Sequential)   (None, 50, 50, 3)         0         \n","                                                                 \n"," conv2d (Conv2D)             (None, 50, 50, 32)        896       \n","                                                                 \n"," max_pooling2d (MaxPooling2D  (None, 25, 25, 32)       0         \n"," )                                                               \n","                                                                 \n"," conv2d_1 (Conv2D)           (None, 25, 25, 64)        18496     \n","                                                                 \n"," max_pooling2d_1 (MaxPooling  (None, 12, 12, 64)       0         \n"," 2D)                                                             \n","                                                                 \n"," conv2d_2 (Conv2D)           (None, 12, 12, 128)       73856     \n","                                                                 \n"," max_pooling2d_2 (MaxPooling  (None, 6, 6, 128)        0         \n"," 2D)                                                             \n","                                                                 \n"," conv2d_3 (Conv2D)           (None, 6, 6, 128)         147584    \n","                                                                 \n"," max_pooling2d_3 (MaxPooling  (None, 3, 3, 128)        0         \n"," 2D)                                                             \n","                                                                 \n"," flatten (Flatten)           (None, 1152)              0         \n","                                                                 \n"," dropout (Dropout)           (None, 1152)              0         \n","                                                                 \n"," dense (Dense)               (None, 512)               590336    \n","                                                                 \n"," dense_1 (Dense)             (None, 2)                 1026      \n","                                                                 \n","=================================================================\n","Total params: 832,194\n","Trainable params: 832,194\n","Non-trainable params: 0\n","_________________________________________________________________\n"]}],"source":["model.compile( loss=tf.keras.losses.CategoricalCrossentropy () , metrics=['accuracy']) \n","model.build([None, IMG_SIZE, IMG_SIZE, 3])  \n","model.summary() "]},{"cell_type":"code","execution_count":11,"id":"SOHoRlxx0pdP","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":11,"status":"ok","timestamp":1650980896179,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"SOHoRlxx0pdP","outputId":"1b96bc0c-49a1-4298-b4a7-f05bd88d09a7"},"outputs":[{"name":"stdout","output_type":"stream","text":["           OPERATION           DATA DIMENSIONS   WEIGHTS(N)   WEIGHTS(%)\n","\n","               Input   #####     50   50    3\n","          Sequential   ????? -------------------         0     0.0%\n","                       #####     50   50    3\n","          Sequential   ????? -------------------         0     0.0%\n","                       #####     50   50    3\n","              Conv2D    \\|/  -------------------       896     0.1%\n","                relu   #####     50   50   32\n","        MaxPooling2D   Y max -------------------         0     0.0%\n","                       #####     25   25   32\n","              Conv2D    \\|/  -------------------     18496     2.2%\n","                relu   #####     25   25   64\n","        MaxPooling2D   Y max -------------------         0     0.0%\n","                       #####     12   12   64\n","              Conv2D    \\|/  -------------------     73856     8.9%\n","                relu   #####     12   12  128\n","        MaxPooling2D   Y max -------------------         0     0.0%\n","                       #####      6    6  128\n","              Conv2D    \\|/  -------------------    147584    17.7%\n","                relu   #####      6    6  128\n","        MaxPooling2D   Y max -------------------         0     0.0%\n","                       #####      3    3  128\n","             Flatten   ||||| -------------------         0     0.0%\n","                       #####        1152\n","             Dropout    | || -------------------         0     0.0%\n","                       #####        1152\n","               Dense   XXXXX -------------------    590336    70.9%\n","                relu   #####         512\n","               Dense   XXXXX -------------------      1026     0.1%\n","             softmax   #####           2\n"]}],"source":["from keras_sequential_ascii import keras2ascii \n","keras2ascii(model)"]},{"cell_type":"code","execution_count":12,"id":"P5PkDw2mAFjF","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":263444,"status":"ok","timestamp":1650981159615,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"P5PkDw2mAFjF","outputId":"66d4b79e-78b5-4be4-8dd8-5ed98193ca97"},"outputs":[{"name":"stdout","output_type":"stream","text":["Epoch 1/100\n","104/104 [==============================] - 13s 114ms/step - loss: 0.7266 - accuracy: 0.5790 - val_loss: 0.6464 - val_accuracy: 0.6346\n","Epoch 2/100\n","104/104 [==============================] - 13s 127ms/step - loss: 0.6335 - accuracy: 0.6766 - val_loss: 0.9411 - val_accuracy: 0.5129\n","Epoch 3/100\n","104/104 [==============================] - 11s 110ms/step - loss: 0.6129 - accuracy: 0.6893 - val_loss: 0.8879 - val_accuracy: 0.5249\n","Epoch 4/100\n","104/104 [==============================] - 12s 113ms/step - loss: 0.5859 - accuracy: 0.7090 - val_loss: 0.9480 - val_accuracy: 0.5798\n","Epoch 5/100\n","104/104 [==============================] - 11s 106ms/step - loss: 0.5804 - accuracy: 0.7060 - val_loss: 0.5599 - val_accuracy: 0.6998\n","Epoch 6/100\n","104/104 [==============================] - 11s 109ms/step - loss: 0.5714 - accuracy: 0.7169 - val_loss: 0.6169 - val_accuracy: 0.6587\n","Epoch 7/100\n","104/104 [==============================] - 12s 111ms/step - loss: 0.5566 - accuracy: 0.7266 - val_loss: 0.8642 - val_accuracy: 0.5094\n","Epoch 8/100\n","104/104 [==============================] - 14s 137ms/step - loss: 0.5489 - accuracy: 0.7405 - val_loss: 0.5529 - val_accuracy: 0.7238\n","Epoch 9/100\n","104/104 [==============================] - 14s 132ms/step - loss: 0.5531 - accuracy: 0.7360 - val_loss: 0.5789 - val_accuracy: 0.6844\n","Epoch 10/100\n","104/104 [==============================] - 15s 146ms/step - loss: 0.5439 - accuracy: 0.7342 - val_loss: 0.5324 - val_accuracy: 0.7599\n","Epoch 11/100\n","104/104 [==============================] - 16s 152ms/step - loss: 0.5425 - accuracy: 0.7366 - val_loss: 0.8455 - val_accuracy: 0.5592\n","Epoch 12/100\n","104/104 [==============================] - 13s 129ms/step - loss: 0.5438 - accuracy: 0.7342 - val_loss: 0.5364 - val_accuracy: 0.7444\n","Epoch 13/100\n","104/104 [==============================] - 14s 133ms/step - loss: 0.5340 - accuracy: 0.7390 - val_loss: 1.0529 - val_accuracy: 0.5420\n","Epoch 14/100\n","104/104 [==============================] - 15s 143ms/step - loss: 0.5355 - accuracy: 0.7408 - val_loss: 0.6005 - val_accuracy: 0.6810\n","Epoch 15/100\n","104/104 [==============================] - 15s 141ms/step - loss: 0.5837 - accuracy: 0.7393 - val_loss: 0.5049 - val_accuracy: 0.7702\n","Epoch 16/100\n","104/104 [==============================] - 16s 150ms/step - loss: 0.5129 - accuracy: 0.7533 - val_loss: 0.5477 - val_accuracy: 0.7513\n","Epoch 17/100\n","104/104 [==============================] - 15s 141ms/step - loss: 0.5208 - accuracy: 0.7536 - val_loss: 0.9826 - val_accuracy: 0.5986\n","Epoch 18/100\n","104/104 [==============================] - 15s 141ms/step - loss: 0.5166 - accuracy: 0.7514 - val_loss: 0.9951 - val_accuracy: 0.6398\n","Epoch 19/100\n","104/104 [==============================] - 13s 130ms/step - loss: 0.5175 - accuracy: 0.7602 - val_loss: 0.9528 - val_accuracy: 0.5352\n","Epoch 20/100\n","104/104 [==============================] - 13s 129ms/step - loss: 0.5226 - accuracy: 0.7520 - val_loss: 0.6487 - val_accuracy: 0.6244\n","Epoch 21/100\n","104/104 [==============================] - 13s 129ms/step - loss: 0.5126 - accuracy: 0.7584 - val_loss: 0.6688 - val_accuracy: 0.6106\n","Epoch 22/100\n","104/104 [==============================] - 14s 135ms/step - loss: 0.5089 - accuracy: 0.7551 - val_loss: 0.6259 - val_accuracy: 0.6998\n","Epoch 23/100\n","104/104 [==============================] - 16s 152ms/step - loss: 0.5122 - accuracy: 0.7551 - val_loss: 1.4659 - val_accuracy: 0.6141\n","Epoch 24/100\n","104/104 [==============================] - 13s 129ms/step - loss: 0.5070 - accuracy: 0.7575 - val_loss: 0.7914 - val_accuracy: 0.5729\n","Epoch 25/100\n","104/104 [==============================] - 13s 129ms/step - loss: 0.4980 - accuracy: 0.7654 - val_loss: 0.4905 - val_accuracy: 0.7856\n","Epoch 26/100\n","104/104 [==============================] - 14s 138ms/step - loss: 0.5046 - accuracy: 0.7696 - val_loss: 0.5452 - val_accuracy: 0.7204\n","Epoch 27/100\n","104/104 [==============================] - 14s 137ms/step - loss: 0.5001 - accuracy: 0.7672 - val_loss: 0.6074 - val_accuracy: 0.7136\n","Epoch 28/100\n","104/104 [==============================] - 16s 149ms/step - loss: 0.4947 - accuracy: 0.7699 - val_loss: 0.6007 - val_accuracy: 0.6913\n","Epoch 29/100\n","104/104 [==============================] - 15s 147ms/step - loss: 0.4918 - accuracy: 0.7727 - val_loss: 0.8474 - val_accuracy: 0.6621\n","Epoch 30/100\n","104/104 [==============================] - 14s 137ms/step - loss: 0.4976 - accuracy: 0.7739 - val_loss: 0.5989 - val_accuracy: 0.6913\n","Epoch 31/100\n","104/104 [==============================] - 14s 137ms/step - loss: 0.4859 - accuracy: 0.7760 - val_loss: 1.8897 - val_accuracy: 0.6810\n","Epoch 32/100\n","104/104 [==============================] - 14s 136ms/step - loss: 0.5097 - accuracy: 0.7693 - val_loss: 0.6438 - val_accuracy: 0.6123\n","Epoch 33/100\n","104/104 [==============================] - 15s 145ms/step - loss: 0.4894 - accuracy: 0.7736 - val_loss: 0.6662 - val_accuracy: 0.6381\n","Epoch 34/100\n","104/104 [==============================] - 15s 144ms/step - loss: 0.6409 - accuracy: 0.7748 - val_loss: 0.5137 - val_accuracy: 0.7564\n","Epoch 35/100\n","104/104 [==============================] - 16s 157ms/step - loss: 0.4832 - accuracy: 0.7775 - val_loss: 0.5514 - val_accuracy: 0.7324\n","Epoch 36/100\n","104/104 [==============================] - 14s 138ms/step - loss: 0.4859 - accuracy: 0.7790 - val_loss: 0.6790 - val_accuracy: 0.6604\n","Epoch 37/100\n","104/104 [==============================] - 16s 149ms/step - loss: 0.4965 - accuracy: 0.7836 - val_loss: 1.1031 - val_accuracy: 0.5472\n","Epoch 38/100\n","104/104 [==============================] - 14s 132ms/step - loss: 0.5113 - accuracy: 0.7818 - val_loss: 0.5759 - val_accuracy: 0.7581\n","Epoch 39/100\n","104/104 [==============================] - 15s 145ms/step - loss: 0.4825 - accuracy: 0.7821 - val_loss: 0.5045 - val_accuracy: 0.7787\n","Epoch 40/100\n","104/104 [==============================] - 15s 147ms/step - loss: 0.4963 - accuracy: 0.7751 - val_loss: 0.5395 - val_accuracy: 0.7479\n","Epoch 41/100\n","104/104 [==============================] - 15s 147ms/step - loss: 0.4727 - accuracy: 0.7836 - val_loss: 0.5705 - val_accuracy: 0.7496\n","Epoch 42/100\n","104/104 [==============================] - 14s 137ms/step - loss: 0.4900 - accuracy: 0.7799 - val_loss: 0.5955 - val_accuracy: 0.7307\n","Epoch 43/100\n","104/104 [==============================] - 15s 148ms/step - loss: 0.4795 - accuracy: 0.7839 - val_loss: 0.5687 - val_accuracy: 0.7427\n","Epoch 44/100\n","104/104 [==============================] - 16s 151ms/step - loss: 0.4805 - accuracy: 0.7805 - val_loss: 4.9808 - val_accuracy: 0.6141\n","Epoch 45/100\n","104/104 [==============================] - 16s 153ms/step - loss: 0.4741 - accuracy: 0.7787 - val_loss: 0.8260 - val_accuracy: 0.6089\n","Epoch 46/100\n","104/104 [==============================] - 15s 147ms/step - loss: 0.4829 - accuracy: 0.7742 - val_loss: 0.5361 - val_accuracy: 0.7393\n","Epoch 47/100\n","104/104 [==============================] - 14s 133ms/step - loss: 0.4681 - accuracy: 0.7893 - val_loss: 1.8488 - val_accuracy: 0.6861\n","Epoch 48/100\n","104/104 [==============================] - 15s 143ms/step - loss: 0.4785 - accuracy: 0.7845 - val_loss: 0.5835 - val_accuracy: 0.7496\n","Epoch 49/100\n","104/104 [==============================] - 14s 135ms/step - loss: 0.5137 - accuracy: 0.7802 - val_loss: 0.6523 - val_accuracy: 0.7084\n","Epoch 50/100\n","104/104 [==============================] - 14s 135ms/step - loss: 0.5115 - accuracy: 0.7802 - val_loss: 0.5377 - val_accuracy: 0.7633\n","Epoch 51/100\n","104/104 [==============================] - 14s 133ms/step - loss: 0.4770 - accuracy: 0.7842 - val_loss: 0.5204 - val_accuracy: 0.7496\n","Epoch 52/100\n","104/104 [==============================] - 15s 144ms/step - loss: 0.4690 - accuracy: 0.7851 - val_loss: 0.6374 - val_accuracy: 0.6913\n","Epoch 53/100\n","104/104 [==============================] - 15s 142ms/step - loss: 0.4762 - accuracy: 0.7936 - val_loss: 0.5059 - val_accuracy: 0.7907\n","Epoch 54/100\n","104/104 [==============================] - 15s 145ms/step - loss: 0.4794 - accuracy: 0.7821 - val_loss: 0.9650 - val_accuracy: 0.6072\n","Epoch 55/100\n","104/104 [==============================] - 15s 143ms/step - loss: 0.4850 - accuracy: 0.7811 - val_loss: 0.7587 - val_accuracy: 0.6449\n","Epoch 56/100\n","104/104 [==============================] - 15s 140ms/step - loss: 0.4726 - accuracy: 0.7845 - val_loss: 0.5012 - val_accuracy: 0.7822\n","Epoch 57/100\n","104/104 [==============================] - 14s 139ms/step - loss: 0.4734 - accuracy: 0.7869 - val_loss: 0.7037 - val_accuracy: 0.6913\n","Epoch 58/100\n","104/104 [==============================] - 15s 149ms/step - loss: 0.5041 - accuracy: 0.7924 - val_loss: 0.5168 - val_accuracy: 0.7822\n","Epoch 59/100\n","104/104 [==============================] - 15s 144ms/step - loss: 0.4687 - accuracy: 0.7918 - val_loss: 0.5378 - val_accuracy: 0.7410\n","Epoch 60/100\n","104/104 [==============================] - 15s 140ms/step - loss: 0.4858 - accuracy: 0.7854 - val_loss: 0.7686 - val_accuracy: 0.6415\n","Epoch 61/100\n","104/104 [==============================] - 15s 140ms/step - loss: 0.4663 - accuracy: 0.7939 - val_loss: 0.5033 - val_accuracy: 0.7667\n","Epoch 62/100\n","104/104 [==============================] - 14s 134ms/step - loss: 0.5016 - accuracy: 0.7802 - val_loss: 0.5592 - val_accuracy: 0.7358\n","Epoch 63/100\n","104/104 [==============================] - 16s 152ms/step - loss: 0.4653 - accuracy: 0.7942 - val_loss: 0.5014 - val_accuracy: 0.7650\n","Epoch 64/100\n","104/104 [==============================] - 16s 151ms/step - loss: 0.4757 - accuracy: 0.7818 - val_loss: 0.5219 - val_accuracy: 0.7787\n","Epoch 65/100\n","104/104 [==============================] - 16s 154ms/step - loss: 0.4688 - accuracy: 0.7902 - val_loss: 0.8192 - val_accuracy: 0.6106\n","Epoch 66/100\n","104/104 [==============================] - 15s 145ms/step - loss: 0.4703 - accuracy: 0.7908 - val_loss: 0.6159 - val_accuracy: 0.7393\n","Epoch 67/100\n","104/104 [==============================] - 15s 147ms/step - loss: 0.4704 - accuracy: 0.7908 - val_loss: 0.9558 - val_accuracy: 0.5660\n","Epoch 68/100\n","104/104 [==============================] - 16s 156ms/step - loss: 0.5394 - accuracy: 0.7854 - val_loss: 0.6362 - val_accuracy: 0.6192\n","Epoch 69/100\n","104/104 [==============================] - 13s 128ms/step - loss: 0.4807 - accuracy: 0.7839 - val_loss: 0.6029 - val_accuracy: 0.7547\n","Epoch 70/100\n","104/104 [==============================] - 16s 157ms/step - loss: 0.4684 - accuracy: 0.7887 - val_loss: 0.5794 - val_accuracy: 0.7667\n","Epoch 71/100\n","104/104 [==============================] - 15s 149ms/step - loss: 0.4678 - accuracy: 0.7908 - val_loss: 0.5063 - val_accuracy: 0.7736\n","Epoch 72/100\n","104/104 [==============================] - 12s 120ms/step - loss: 0.4707 - accuracy: 0.7824 - val_loss: 0.5782 - val_accuracy: 0.7084\n","Epoch 73/100\n","104/104 [==============================] - 14s 132ms/step - loss: 0.4764 - accuracy: 0.7869 - val_loss: 0.6676 - val_accuracy: 0.7461\n","Epoch 74/100\n","104/104 [==============================] - 15s 146ms/step - loss: 0.4612 - accuracy: 0.7911 - val_loss: 0.7116 - val_accuracy: 0.6810\n","Epoch 75/100\n","104/104 [==============================] - 16s 158ms/step - loss: 0.4626 - accuracy: 0.8021 - val_loss: 0.5414 - val_accuracy: 0.7324\n","Epoch 76/100\n","104/104 [==============================] - 17s 164ms/step - loss: 0.4591 - accuracy: 0.7927 - val_loss: 0.6202 - val_accuracy: 0.7667\n","Epoch 77/100\n","104/104 [==============================] - 14s 133ms/step - loss: 0.4632 - accuracy: 0.7939 - val_loss: 0.5249 - val_accuracy: 0.7770\n","Epoch 78/100\n","104/104 [==============================] - 14s 132ms/step - loss: 0.4593 - accuracy: 0.7981 - val_loss: 1.0298 - val_accuracy: 0.6741\n","Epoch 79/100\n","104/104 [==============================] - 15s 147ms/step - loss: 0.4658 - accuracy: 0.7933 - val_loss: 0.5685 - val_accuracy: 0.7564\n","Epoch 80/100\n","104/104 [==============================] - 15s 142ms/step - loss: 0.4704 - accuracy: 0.7896 - val_loss: 0.5301 - val_accuracy: 0.7479\n","Epoch 81/100\n","104/104 [==============================] - 16s 152ms/step - loss: 0.4667 - accuracy: 0.7942 - val_loss: 1.1869 - val_accuracy: 0.6861\n","Epoch 82/100\n","104/104 [==============================] - 15s 142ms/step - loss: 0.4660 - accuracy: 0.7908 - val_loss: 0.5473 - val_accuracy: 0.7410\n","Epoch 83/100\n","104/104 [==============================] - 14s 137ms/step - loss: 0.4648 - accuracy: 0.7875 - val_loss: 0.5573 - val_accuracy: 0.7513\n","Epoch 84/100\n","104/104 [==============================] - 14s 131ms/step - loss: 0.4788 - accuracy: 0.7839 - val_loss: 0.4955 - val_accuracy: 0.7770\n","Epoch 85/100\n","104/104 [==============================] - 14s 134ms/step - loss: 0.4742 - accuracy: 0.7890 - val_loss: 0.5617 - val_accuracy: 0.7376\n","Epoch 86/100\n","104/104 [==============================] - 15s 141ms/step - loss: 0.4936 - accuracy: 0.7869 - val_loss: 0.6293 - val_accuracy: 0.7719\n","Epoch 87/100\n","104/104 [==============================] - 15s 145ms/step - loss: 0.5271 - accuracy: 0.7905 - val_loss: 0.5232 - val_accuracy: 0.7736\n","Epoch 88/100\n","104/104 [==============================] - 15s 148ms/step - loss: 0.4555 - accuracy: 0.7939 - val_loss: 0.7179 - val_accuracy: 0.6278\n","Epoch 89/100\n","104/104 [==============================] - 14s 138ms/step - loss: 0.4692 - accuracy: 0.7902 - val_loss: 0.4964 - val_accuracy: 0.7873\n","Epoch 90/100\n","104/104 [==============================] - 15s 147ms/step - loss: 0.4711 - accuracy: 0.7890 - val_loss: 0.5159 - val_accuracy: 0.7753\n","Epoch 91/100\n","104/104 [==============================] - 15s 141ms/step - loss: 0.4582 - accuracy: 0.7893 - val_loss: 0.6270 - val_accuracy: 0.7633\n","Epoch 92/100\n","104/104 [==============================] - 14s 133ms/step - loss: 0.4628 - accuracy: 0.7924 - val_loss: 0.6573 - val_accuracy: 0.7496\n","Epoch 93/100\n","104/104 [==============================] - 15s 144ms/step - loss: 0.4756 - accuracy: 0.7821 - val_loss: 0.5954 - val_accuracy: 0.6792\n","Epoch 94/100\n","104/104 [==============================] - 15s 144ms/step - loss: 0.4564 - accuracy: 0.7942 - val_loss: 0.8175 - val_accuracy: 0.7273\n","Epoch 95/100\n","104/104 [==============================] - 15s 148ms/step - loss: 0.5172 - accuracy: 0.7924 - val_loss: 0.7353 - val_accuracy: 0.6278\n","Epoch 96/100\n","104/104 [==============================] - 15s 141ms/step - loss: 0.4729 - accuracy: 0.7930 - val_loss: 1.4960 - val_accuracy: 0.5283\n","Epoch 97/100\n","104/104 [==============================] - 16s 157ms/step - loss: 0.4840 - accuracy: 0.7872 - val_loss: 0.5500 - val_accuracy: 0.7015\n","Epoch 98/100\n","104/104 [==============================] - 14s 138ms/step - loss: 0.4614 - accuracy: 0.7927 - val_loss: 0.7277 - val_accuracy: 0.7118\n","Epoch 99/100\n","104/104 [==============================] - 15s 141ms/step - loss: 0.4880 - accuracy: 0.7911 - val_loss: 0.6535 - val_accuracy: 0.7427\n","Epoch 100/100\n","104/104 [==============================] - 15s 144ms/step - loss: 0.4684 - accuracy: 0.7887 - val_loss: 0.4944 - val_accuracy: 0.7667\n"]}],"source":["num_epoches = 100\n","result = model.fit(X_train, y_train, epochs = num_epoches, validation_split = 0.15)"]},{"cell_type":"markdown","id":"7fd06f82","metadata":{"id":"7fd06f82"},"source":["#### Model evaluation"]},{"cell_type":"code","execution_count":13,"id":"c21f8fb2","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":2034,"status":"ok","timestamp":1650981161625,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"c21f8fb2","outputId":"bb37a76c-1c96-4b2e-90ef-d328b18dee79"},"outputs":[{"name":"stdout","output_type":"stream","text":["53/53 [==============================] - 2s 29ms/step - loss: 0.4957 - accuracy: 0.7748\n","Average training accuracy =  0.7717368882894516\n","Average validation accuracy =  0.6951629507541657\n","Average testing accuracy =  0.7747747898101807\n"]}],"source":["test_loss, test_accuracy = model.evaluate(X_test, y_test)\n","print('Average training accuracy = ',np.mean(result.history['accuracy'])) \n","print('Average validation accuracy = ',np.mean(result.history['val_accuracy']))\n","print('Average testing accuracy = ', test_accuracy)  "]},{"cell_type":"code","execution_count":14,"id":"qp35ZKHAlLm_","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":513},"executionInfo":{"elapsed":42,"status":"ok","timestamp":1650981161625,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"qp35ZKHAlLm_","outputId":"600bb7f4-cdb7-4f5a-af7e-7223184b82fb"},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1584x576 with 2 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["Accuracy, loss, ValidationAcccuracy, validationLoss = result.history['accuracy'], result.history['loss'], result.history['val_accuracy'], result.history['val_loss']\n","\n","plt.figure(figsize=(22, 8))\n","plt.subplot(1, 2, 1)\n","plt.title('Validation Accuracy and Training Accuracy')\n","plt.plot(range(num_epoches), Accuracy, label='Training Accuracy')\n","plt.plot(range(num_epoches), ValidationAcccuracy, label='Validation Accuracy')\n","plt.xlabel('num of epochs')\n","plt.ylabel('Accuracy')\n","plt.legend()\n","\n","\n","plt.subplot(1, 2, 2)\n","plt.title('Validation Loss and Training Loss')\n","plt.plot(range(num_epoches), loss, label='Training Loss')\n","plt.plot(range(num_epoches), validationLoss, label='Validation Loss')\n","plt.xlabel('num of epochs')\n","plt.ylabel('Accuracy')\n","plt.legend()\n","\n","plt.show()"]},{"cell_type":"code","execution_count":15,"id":"5103ddd9","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":35,"status":"ok","timestamp":1650981161627,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"5103ddd9","outputId":"2e47b975-8105-48de-b0fb-33e0aa55c0d6"},"outputs":[{"name":"stdout","output_type":"stream","text":["              precision    recall  f1-score   support\n","\n","           0       0.82      0.69      0.75       811\n","           1       0.74      0.86      0.80       854\n","\n","    accuracy                           0.77      1665\n","   macro avg       0.78      0.77      0.77      1665\n","weighted avg       0.78      0.77      0.77      1665\n","\n"]}],"source":["y_pred = model.predict(X_test)\n","y_pred_int = np.argmax(y_pred, axis=1)\n","y_test_int = np.argmax(y_test, axis=1) \n","print(classification_report(y_test_int,y_pred_int))"]},{"cell_type":"code","execution_count":16,"id":"af2bde08","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":312},"executionInfo":{"elapsed":22,"status":"ok","timestamp":1650981162583,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"af2bde08","outputId":"1fedc67f-4923-430a-e164-84dac55dcb21"},"outputs":[{"data":{"text/plain":["<AxesSubplot:title={'center':'Normalized Confusion Matrix'}, xlabel='Predicted label', ylabel='True label'>"]},"execution_count":16,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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","text/plain":["<Figure size 432x288 with 2 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["plot_confusion_matrix(y_test_int, y_pred_int, normalize=True)"]},{"cell_type":"code","execution_count":17,"id":"018966f6","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":312},"executionInfo":{"elapsed":19,"status":"ok","timestamp":1650981162585,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"018966f6","outputId":"cd52a9de-9a56-41ec-9f71-6f632530f199"},"outputs":[{"data":{"text/plain":["Text(0.5, 1.0, 'ROC curve')"]},"execution_count":17,"metadata":{},"output_type":"execute_result"},{"data":{"image/png":"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","text/plain":["<Figure size 432x288 with 1 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["fp, tp, thr = roc_curve(y_test_int, y_pred_int)\n","auc_val = auc(fp, tp)\n","plt.plot(fp, tp, label='(auc = {:.3f})'.format(auc_val))\n","plt.ylabel('True positive rate') \n","plt.xlabel('False positive rate') \n","plt.legend() \n","plt.title('ROC curve') "]},{"cell_type":"code","execution_count":18,"id":"dS1ZN5-3UnFk","metadata":{"executionInfo":{"elapsed":14,"status":"ok","timestamp":1650981162586,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"dS1ZN5-3UnFk"},"outputs":[],"source":["model.save('model1.h5')"]},{"cell_type":"markdown","id":"0ac80e1b","metadata":{"id":"0ac80e1b"},"source":["## Using pre-trained mobilenet model"]},{"cell_type":"markdown","id":"02da1ba0","metadata":{"id":"02da1ba0"},"source":["*    Mobile net expects the image size to be in 224/224/3 shape where as the images in the data set are 50/50/3 shaped. To account for this we add image resizing layer in the pipeline along with the rescaling layer.\n","*    Also we set the offset value after normalization in accordance with the requirements of mobilenet."]},{"cell_type":"code","execution_count":19,"id":"SrqdpVpnkrih","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":3309,"status":"ok","timestamp":1650981165882,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"SrqdpVpnkrih","outputId":"e2e5cc88-ffac-41f0-8940-a971a74ee146"},"outputs":[{"name":"stdout","output_type":"stream","text":["Model: \"mobilenetv2_1.00_224\"\n","__________________________________________________________________________________________________\n"," Layer (type)                   Output Shape         Param #     Connected to                     \n","==================================================================================================\n"," input_1 (InputLayer)           [(None, 224, 224, 3  0           []                               \n","                                )]                                                                \n","                                                                                                  \n"," Conv1 (Conv2D)                 (None, 112, 112, 32  864         ['input_1[0][0]']                \n","                                )                                                                 \n","                                                                                                  \n"," bn_Conv1 (BatchNormalization)  (None, 112, 112, 32  128         ['Conv1[0][0]']                  \n","                                )                                                                 \n","                                                                                                  \n"," Conv1_relu (ReLU)              (None, 112, 112, 32  0           ['bn_Conv1[0][0]']               \n","                                )                                                                 \n","                                                                                                  \n"," expanded_conv_depthwise (Depth  (None, 112, 112, 32  288        ['Conv1_relu[0][0]']             \n"," wiseConv2D)                    )                                                                 \n","                                                                                                  \n"," expanded_conv_depthwise_BN (Ba  (None, 112, 112, 32  128        ['expanded_conv_depthwise[0][0]']\n"," tchNormalization)              )                                                                 \n","                                                                                                  \n"," expanded_conv_depthwise_relu (  (None, 112, 112, 32  0          ['expanded_conv_depthwise_BN[0][0\n"," ReLU)                          )                                ]']                              \n","                                                                                                  \n"," expanded_conv_project (Conv2D)  (None, 112, 112, 16  512        ['expanded_conv_depthwise_relu[0]\n","                                )                                [0]']                            \n","                                                                                                  \n"," expanded_conv_project_BN (Batc  (None, 112, 112, 16  64         ['expanded_conv_project[0][0]']  \n"," hNormalization)                )                                                                 \n","                                                                                                  \n"," block_1_expand (Conv2D)        (None, 112, 112, 96  1536        ['expanded_conv_project_BN[0][0]'\n","                                )                                ]                                \n","                                                                                                  \n"," block_1_expand_BN (BatchNormal  (None, 112, 112, 96  384        ['block_1_expand[0][0]']         \n"," ization)                       )                                                                 \n","                                                                                                  \n"," block_1_expand_relu (ReLU)     (None, 112, 112, 96  0           ['block_1_expand_BN[0][0]']      \n","                                )                                                                 \n","                                                                                                  \n"," block_1_pad (ZeroPadding2D)    (None, 113, 113, 96  0           ['block_1_expand_relu[0][0]']    \n","                                )                                                                 \n","                                                                                                  \n"," block_1_depthwise (DepthwiseCo  (None, 56, 56, 96)  864         ['block_1_pad[0][0]']            \n"," nv2D)                                                                                            \n","                                                                                                  \n"," block_1_depthwise_BN (BatchNor  (None, 56, 56, 96)  384         ['block_1_depthwise[0][0]']      \n"," malization)                                                                                      \n","                                                                                                  \n"," block_1_depthwise_relu (ReLU)  (None, 56, 56, 96)   0           ['block_1_depthwise_BN[0][0]']   \n","                                                                                                  \n"," block_1_project (Conv2D)       (None, 56, 56, 24)   2304        ['block_1_depthwise_relu[0][0]'] \n","                                                                                                  \n"," block_1_project_BN (BatchNorma  (None, 56, 56, 24)  96          ['block_1_project[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_2_expand (Conv2D)        (None, 56, 56, 144)  3456        ['block_1_project_BN[0][0]']     \n","                                                                                                  \n"," block_2_expand_BN (BatchNormal  (None, 56, 56, 144)  576        ['block_2_expand[0][0]']         \n"," ization)                                                                                         \n","                                                                                                  \n"," block_2_expand_relu (ReLU)     (None, 56, 56, 144)  0           ['block_2_expand_BN[0][0]']      \n","                                                                                                  \n"," block_2_depthwise (DepthwiseCo  (None, 56, 56, 144)  1296       ['block_2_expand_relu[0][0]']    \n"," nv2D)                                                                                            \n","                                                                                                  \n"," block_2_depthwise_BN (BatchNor  (None, 56, 56, 144)  576        ['block_2_depthwise[0][0]']      \n"," malization)                                                                                      \n","                                                                                                  \n"," block_2_depthwise_relu (ReLU)  (None, 56, 56, 144)  0           ['block_2_depthwise_BN[0][0]']   \n","                                                                                                  \n"," block_2_project (Conv2D)       (None, 56, 56, 24)   3456        ['block_2_depthwise_relu[0][0]'] \n","                                                                                                  \n"," block_2_project_BN (BatchNorma  (None, 56, 56, 24)  96          ['block_2_project[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_2_add (Add)              (None, 56, 56, 24)   0           ['block_1_project_BN[0][0]',     \n","                                                                  'block_2_project_BN[0][0]']     \n","                                                                                                  \n"," block_3_expand (Conv2D)        (None, 56, 56, 144)  3456        ['block_2_add[0][0]']            \n","                                                                                                  \n"," block_3_expand_BN (BatchNormal  (None, 56, 56, 144)  576        ['block_3_expand[0][0]']         \n"," ization)                                                                                         \n","                                                                                                  \n"," block_3_expand_relu (ReLU)     (None, 56, 56, 144)  0           ['block_3_expand_BN[0][0]']      \n","                                                                                                  \n"," block_3_pad (ZeroPadding2D)    (None, 57, 57, 144)  0           ['block_3_expand_relu[0][0]']    \n","                                                                                                  \n"," block_3_depthwise (DepthwiseCo  (None, 28, 28, 144)  1296       ['block_3_pad[0][0]']            \n"," nv2D)                                                                                            \n","                                                                                                  \n"," block_3_depthwise_BN (BatchNor  (None, 28, 28, 144)  576        ['block_3_depthwise[0][0]']      \n"," malization)                                                                                      \n","                                                                                                  \n"," block_3_depthwise_relu (ReLU)  (None, 28, 28, 144)  0           ['block_3_depthwise_BN[0][0]']   \n","                                                                                                  \n"," block_3_project (Conv2D)       (None, 28, 28, 32)   4608        ['block_3_depthwise_relu[0][0]'] \n","                                                                                                  \n"," block_3_project_BN (BatchNorma  (None, 28, 28, 32)  128         ['block_3_project[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_4_expand (Conv2D)        (None, 28, 28, 192)  6144        ['block_3_project_BN[0][0]']     \n","                                                                                                  \n"," block_4_expand_BN (BatchNormal  (None, 28, 28, 192)  768        ['block_4_expand[0][0]']         \n"," ization)                                                                                         \n","                                                                                                  \n"," block_4_expand_relu (ReLU)     (None, 28, 28, 192)  0           ['block_4_expand_BN[0][0]']      \n","                                                                                                  \n"," block_4_depthwise (DepthwiseCo  (None, 28, 28, 192)  1728       ['block_4_expand_relu[0][0]']    \n"," nv2D)                                                                                            \n","                                                                                                  \n"," block_4_depthwise_BN (BatchNor  (None, 28, 28, 192)  768        ['block_4_depthwise[0][0]']      \n"," malization)                                                                                      \n","                                                                                                  \n"," block_4_depthwise_relu (ReLU)  (None, 28, 28, 192)  0           ['block_4_depthwise_BN[0][0]']   \n","                                                                                                  \n"," block_4_project (Conv2D)       (None, 28, 28, 32)   6144        ['block_4_depthwise_relu[0][0]'] \n","                                                                                                  \n"," block_4_project_BN (BatchNorma  (None, 28, 28, 32)  128         ['block_4_project[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_4_add (Add)              (None, 28, 28, 32)   0           ['block_3_project_BN[0][0]',     \n","                                                                  'block_4_project_BN[0][0]']     \n","                                                                                                  \n"," block_5_expand (Conv2D)        (None, 28, 28, 192)  6144        ['block_4_add[0][0]']            \n","                                                                                                  \n"," block_5_expand_BN (BatchNormal  (None, 28, 28, 192)  768        ['block_5_expand[0][0]']         \n"," ization)                                                                                         \n","                                                                                                  \n"," block_5_expand_relu (ReLU)     (None, 28, 28, 192)  0           ['block_5_expand_BN[0][0]']      \n","                                                                                                  \n"," block_5_depthwise (DepthwiseCo  (None, 28, 28, 192)  1728       ['block_5_expand_relu[0][0]']    \n"," nv2D)                                                                                            \n","                                                                                                  \n"," block_5_depthwise_BN (BatchNor  (None, 28, 28, 192)  768        ['block_5_depthwise[0][0]']      \n"," malization)                                                                                      \n","                                                                                                  \n"," block_5_depthwise_relu (ReLU)  (None, 28, 28, 192)  0           ['block_5_depthwise_BN[0][0]']   \n","                                                                                                  \n"," block_5_project (Conv2D)       (None, 28, 28, 32)   6144        ['block_5_depthwise_relu[0][0]'] \n","                                                                                                  \n"," block_5_project_BN (BatchNorma  (None, 28, 28, 32)  128         ['block_5_project[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_5_add (Add)              (None, 28, 28, 32)   0           ['block_4_add[0][0]',            \n","                                                                  'block_5_project_BN[0][0]']     \n","                                                                                                  \n"," block_6_expand (Conv2D)        (None, 28, 28, 192)  6144        ['block_5_add[0][0]']            \n","                                                                                                  \n"," block_6_expand_BN (BatchNormal  (None, 28, 28, 192)  768        ['block_6_expand[0][0]']         \n"," ization)                                                                                         \n","                                                                                                  \n"," block_6_expand_relu (ReLU)     (None, 28, 28, 192)  0           ['block_6_expand_BN[0][0]']      \n","                                                                                                  \n"," block_6_pad (ZeroPadding2D)    (None, 29, 29, 192)  0           ['block_6_expand_relu[0][0]']    \n","                                                                                                  \n"," block_6_depthwise (DepthwiseCo  (None, 14, 14, 192)  1728       ['block_6_pad[0][0]']            \n"," nv2D)                                                                                            \n","                                                                                                  \n"," block_6_depthwise_BN (BatchNor  (None, 14, 14, 192)  768        ['block_6_depthwise[0][0]']      \n"," malization)                                                                                      \n","                                                                                                  \n"," block_6_depthwise_relu (ReLU)  (None, 14, 14, 192)  0           ['block_6_depthwise_BN[0][0]']   \n","                                                                                                  \n"," block_6_project (Conv2D)       (None, 14, 14, 64)   12288       ['block_6_depthwise_relu[0][0]'] \n","                                                                                                  \n"," block_6_project_BN (BatchNorma  (None, 14, 14, 64)  256         ['block_6_project[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_7_expand (Conv2D)        (None, 14, 14, 384)  24576       ['block_6_project_BN[0][0]']     \n","                                                                                                  \n"," block_7_expand_BN (BatchNormal  (None, 14, 14, 384)  1536       ['block_7_expand[0][0]']         \n"," ization)                                                                                         \n","                                                                                                  \n"," block_7_expand_relu (ReLU)     (None, 14, 14, 384)  0           ['block_7_expand_BN[0][0]']      \n","                                                                                                  \n"," block_7_depthwise (DepthwiseCo  (None, 14, 14, 384)  3456       ['block_7_expand_relu[0][0]']    \n"," nv2D)                                                                                            \n","                                                                                                  \n"," block_7_depthwise_BN (BatchNor  (None, 14, 14, 384)  1536       ['block_7_depthwise[0][0]']      \n"," malization)                                                                                      \n","                                                                                                  \n"," block_7_depthwise_relu (ReLU)  (None, 14, 14, 384)  0           ['block_7_depthwise_BN[0][0]']   \n","                                                                                                  \n"," block_7_project (Conv2D)       (None, 14, 14, 64)   24576       ['block_7_depthwise_relu[0][0]'] \n","                                                                                                  \n"," block_7_project_BN (BatchNorma  (None, 14, 14, 64)  256         ['block_7_project[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_7_add (Add)              (None, 14, 14, 64)   0           ['block_6_project_BN[0][0]',     \n","                                                                  'block_7_project_BN[0][0]']     \n","                                                                                                  \n"," block_8_expand (Conv2D)        (None, 14, 14, 384)  24576       ['block_7_add[0][0]']            \n","                                                                                                  \n"," block_8_expand_BN (BatchNormal  (None, 14, 14, 384)  1536       ['block_8_expand[0][0]']         \n"," ization)                                                                                         \n","                                                                                                  \n"," block_8_expand_relu (ReLU)     (None, 14, 14, 384)  0           ['block_8_expand_BN[0][0]']      \n","                                                                                                  \n"," block_8_depthwise (DepthwiseCo  (None, 14, 14, 384)  3456       ['block_8_expand_relu[0][0]']    \n"," nv2D)                                                                                            \n","                                                                                                  \n"," block_8_depthwise_BN (BatchNor  (None, 14, 14, 384)  1536       ['block_8_depthwise[0][0]']      \n"," malization)                                                                                      \n","                                                                                                  \n"," block_8_depthwise_relu (ReLU)  (None, 14, 14, 384)  0           ['block_8_depthwise_BN[0][0]']   \n","                                                                                                  \n"," block_8_project (Conv2D)       (None, 14, 14, 64)   24576       ['block_8_depthwise_relu[0][0]'] \n","                                                                                                  \n"," block_8_project_BN (BatchNorma  (None, 14, 14, 64)  256         ['block_8_project[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_8_add (Add)              (None, 14, 14, 64)   0           ['block_7_add[0][0]',            \n","                                                                  'block_8_project_BN[0][0]']     \n","                                                                                                  \n"," block_9_expand (Conv2D)        (None, 14, 14, 384)  24576       ['block_8_add[0][0]']            \n","                                                                                                  \n"," block_9_expand_BN (BatchNormal  (None, 14, 14, 384)  1536       ['block_9_expand[0][0]']         \n"," ization)                                                                                         \n","                                                                                                  \n"," block_9_expand_relu (ReLU)     (None, 14, 14, 384)  0           ['block_9_expand_BN[0][0]']      \n","                                                                                                  \n"," block_9_depthwise (DepthwiseCo  (None, 14, 14, 384)  3456       ['block_9_expand_relu[0][0]']    \n"," nv2D)                                                                                            \n","                                                                                                  \n"," block_9_depthwise_BN (BatchNor  (None, 14, 14, 384)  1536       ['block_9_depthwise[0][0]']      \n"," malization)                                                                                      \n","                                                                                                  \n"," block_9_depthwise_relu (ReLU)  (None, 14, 14, 384)  0           ['block_9_depthwise_BN[0][0]']   \n","                                                                                                  \n"," block_9_project (Conv2D)       (None, 14, 14, 64)   24576       ['block_9_depthwise_relu[0][0]'] \n","                                                                                                  \n"," block_9_project_BN (BatchNorma  (None, 14, 14, 64)  256         ['block_9_project[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_9_add (Add)              (None, 14, 14, 64)   0           ['block_8_add[0][0]',            \n","                                                                  'block_9_project_BN[0][0]']     \n","                                                                                                  \n"," block_10_expand (Conv2D)       (None, 14, 14, 384)  24576       ['block_9_add[0][0]']            \n","                                                                                                  \n"," block_10_expand_BN (BatchNorma  (None, 14, 14, 384)  1536       ['block_10_expand[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_10_expand_relu (ReLU)    (None, 14, 14, 384)  0           ['block_10_expand_BN[0][0]']     \n","                                                                                                  \n"," block_10_depthwise (DepthwiseC  (None, 14, 14, 384)  3456       ['block_10_expand_relu[0][0]']   \n"," onv2D)                                                                                           \n","                                                                                                  \n"," block_10_depthwise_BN (BatchNo  (None, 14, 14, 384)  1536       ['block_10_depthwise[0][0]']     \n"," rmalization)                                                                                     \n","                                                                                                  \n"," block_10_depthwise_relu (ReLU)  (None, 14, 14, 384)  0          ['block_10_depthwise_BN[0][0]']  \n","                                                                                                  \n"," block_10_project (Conv2D)      (None, 14, 14, 96)   36864       ['block_10_depthwise_relu[0][0]']\n","                                                                                                  \n"," block_10_project_BN (BatchNorm  (None, 14, 14, 96)  384         ['block_10_project[0][0]']       \n"," alization)                                                                                       \n","                                                                                                  \n"," block_11_expand (Conv2D)       (None, 14, 14, 576)  55296       ['block_10_project_BN[0][0]']    \n","                                                                                                  \n"," block_11_expand_BN (BatchNorma  (None, 14, 14, 576)  2304       ['block_11_expand[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_11_expand_relu (ReLU)    (None, 14, 14, 576)  0           ['block_11_expand_BN[0][0]']     \n","                                                                                                  \n"," block_11_depthwise (DepthwiseC  (None, 14, 14, 576)  5184       ['block_11_expand_relu[0][0]']   \n"," onv2D)                                                                                           \n","                                                                                                  \n"," block_11_depthwise_BN (BatchNo  (None, 14, 14, 576)  2304       ['block_11_depthwise[0][0]']     \n"," rmalization)                                                                                     \n","                                                                                                  \n"," block_11_depthwise_relu (ReLU)  (None, 14, 14, 576)  0          ['block_11_depthwise_BN[0][0]']  \n","                                                                                                  \n"," block_11_project (Conv2D)      (None, 14, 14, 96)   55296       ['block_11_depthwise_relu[0][0]']\n","                                                                                                  \n"," block_11_project_BN (BatchNorm  (None, 14, 14, 96)  384         ['block_11_project[0][0]']       \n"," alization)                                                                                       \n","                                                                                                  \n"," block_11_add (Add)             (None, 14, 14, 96)   0           ['block_10_project_BN[0][0]',    \n","                                                                  'block_11_project_BN[0][0]']    \n","                                                                                                  \n"," block_12_expand (Conv2D)       (None, 14, 14, 576)  55296       ['block_11_add[0][0]']           \n","                                                                                                  \n"," block_12_expand_BN (BatchNorma  (None, 14, 14, 576)  2304       ['block_12_expand[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_12_expand_relu (ReLU)    (None, 14, 14, 576)  0           ['block_12_expand_BN[0][0]']     \n","                                                                                                  \n"," block_12_depthwise (DepthwiseC  (None, 14, 14, 576)  5184       ['block_12_expand_relu[0][0]']   \n"," onv2D)                                                                                           \n","                                                                                                  \n"," block_12_depthwise_BN (BatchNo  (None, 14, 14, 576)  2304       ['block_12_depthwise[0][0]']     \n"," rmalization)                                                                                     \n","                                                                                                  \n"," block_12_depthwise_relu (ReLU)  (None, 14, 14, 576)  0          ['block_12_depthwise_BN[0][0]']  \n","                                                                                                  \n"," block_12_project (Conv2D)      (None, 14, 14, 96)   55296       ['block_12_depthwise_relu[0][0]']\n","                                                                                                  \n"," block_12_project_BN (BatchNorm  (None, 14, 14, 96)  384         ['block_12_project[0][0]']       \n"," alization)                                                                                       \n","                                                                                                  \n"," block_12_add (Add)             (None, 14, 14, 96)   0           ['block_11_add[0][0]',           \n","                                                                  'block_12_project_BN[0][0]']    \n","                                                                                                  \n"," block_13_expand (Conv2D)       (None, 14, 14, 576)  55296       ['block_12_add[0][0]']           \n","                                                                                                  \n"," block_13_expand_BN (BatchNorma  (None, 14, 14, 576)  2304       ['block_13_expand[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_13_expand_relu (ReLU)    (None, 14, 14, 576)  0           ['block_13_expand_BN[0][0]']     \n","                                                                                                  \n"," block_13_pad (ZeroPadding2D)   (None, 15, 15, 576)  0           ['block_13_expand_relu[0][0]']   \n","                                                                                                  \n"," block_13_depthwise (DepthwiseC  (None, 7, 7, 576)   5184        ['block_13_pad[0][0]']           \n"," onv2D)                                                                                           \n","                                                                                                  \n"," block_13_depthwise_BN (BatchNo  (None, 7, 7, 576)   2304        ['block_13_depthwise[0][0]']     \n"," rmalization)                                                                                     \n","                                                                                                  \n"," block_13_depthwise_relu (ReLU)  (None, 7, 7, 576)   0           ['block_13_depthwise_BN[0][0]']  \n","                                                                                                  \n"," block_13_project (Conv2D)      (None, 7, 7, 160)    92160       ['block_13_depthwise_relu[0][0]']\n","                                                                                                  \n"," block_13_project_BN (BatchNorm  (None, 7, 7, 160)   640         ['block_13_project[0][0]']       \n"," alization)                                                                                       \n","                                                                                                  \n"," block_14_expand (Conv2D)       (None, 7, 7, 960)    153600      ['block_13_project_BN[0][0]']    \n","                                                                                                  \n"," block_14_expand_BN (BatchNorma  (None, 7, 7, 960)   3840        ['block_14_expand[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_14_expand_relu (ReLU)    (None, 7, 7, 960)    0           ['block_14_expand_BN[0][0]']     \n","                                                                                                  \n"," block_14_depthwise (DepthwiseC  (None, 7, 7, 960)   8640        ['block_14_expand_relu[0][0]']   \n"," onv2D)                                                                                           \n","                                                                                                  \n"," block_14_depthwise_BN (BatchNo  (None, 7, 7, 960)   3840        ['block_14_depthwise[0][0]']     \n"," rmalization)                                                                                     \n","                                                                                                  \n"," block_14_depthwise_relu (ReLU)  (None, 7, 7, 960)   0           ['block_14_depthwise_BN[0][0]']  \n","                                                                                                  \n"," block_14_project (Conv2D)      (None, 7, 7, 160)    153600      ['block_14_depthwise_relu[0][0]']\n","                                                                                                  \n"," block_14_project_BN (BatchNorm  (None, 7, 7, 160)   640         ['block_14_project[0][0]']       \n"," alization)                                                                                       \n","                                                                                                  \n"," block_14_add (Add)             (None, 7, 7, 160)    0           ['block_13_project_BN[0][0]',    \n","                                                                  'block_14_project_BN[0][0]']    \n","                                                                                                  \n"," block_15_expand (Conv2D)       (None, 7, 7, 960)    153600      ['block_14_add[0][0]']           \n","                                                                                                  \n"," block_15_expand_BN (BatchNorma  (None, 7, 7, 960)   3840        ['block_15_expand[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_15_expand_relu (ReLU)    (None, 7, 7, 960)    0           ['block_15_expand_BN[0][0]']     \n","                                                                                                  \n"," block_15_depthwise (DepthwiseC  (None, 7, 7, 960)   8640        ['block_15_expand_relu[0][0]']   \n"," onv2D)                                                                                           \n","                                                                                                  \n"," block_15_depthwise_BN (BatchNo  (None, 7, 7, 960)   3840        ['block_15_depthwise[0][0]']     \n"," rmalization)                                                                                     \n","                                                                                                  \n"," block_15_depthwise_relu (ReLU)  (None, 7, 7, 960)   0           ['block_15_depthwise_BN[0][0]']  \n","                                                                                                  \n"," block_15_project (Conv2D)      (None, 7, 7, 160)    153600      ['block_15_depthwise_relu[0][0]']\n","                                                                                                  \n"," block_15_project_BN (BatchNorm  (None, 7, 7, 160)   640         ['block_15_project[0][0]']       \n"," alization)                                                                                       \n","                                                                                                  \n"," block_15_add (Add)             (None, 7, 7, 160)    0           ['block_14_add[0][0]',           \n","                                                                  'block_15_project_BN[0][0]']    \n","                                                                                                  \n"," block_16_expand (Conv2D)       (None, 7, 7, 960)    153600      ['block_15_add[0][0]']           \n","                                                                                                  \n"," block_16_expand_BN (BatchNorma  (None, 7, 7, 960)   3840        ['block_16_expand[0][0]']        \n"," lization)                                                                                        \n","                                                                                                  \n"," block_16_expand_relu (ReLU)    (None, 7, 7, 960)    0           ['block_16_expand_BN[0][0]']     \n","                                                                                                  \n"," block_16_depthwise (DepthwiseC  (None, 7, 7, 960)   8640        ['block_16_expand_relu[0][0]']   \n"," onv2D)                                                                                           \n","                                                                                                  \n"," block_16_depthwise_BN (BatchNo  (None, 7, 7, 960)   3840        ['block_16_depthwise[0][0]']     \n"," rmalization)                                                                                     \n","                                                                                                  \n"," block_16_depthwise_relu (ReLU)  (None, 7, 7, 960)   0           ['block_16_depthwise_BN[0][0]']  \n","                                                                                                  \n"," block_16_project (Conv2D)      (None, 7, 7, 320)    307200      ['block_16_depthwise_relu[0][0]']\n","                                                                                                  \n"," block_16_project_BN (BatchNorm  (None, 7, 7, 320)   1280        ['block_16_project[0][0]']       \n"," alization)                                                                                       \n","                                                                                                  \n"," Conv_1 (Conv2D)                (None, 7, 7, 1280)   409600      ['block_16_project_BN[0][0]']    \n","                                                                                                  \n"," Conv_1_bn (BatchNormalization)  (None, 7, 7, 1280)  5120        ['Conv_1[0][0]']                 \n","                                                                                                  \n"," out_relu (ReLU)                (None, 7, 7, 1280)   0           ['Conv_1_bn[0][0]']              \n","                                                                                                  \n","==================================================================================================\n","Total params: 2,257,984\n","Trainable params: 0\n","Non-trainable params: 2,257,984\n","__________________________________________________________________________________________________\n","None\n","Number of layers in the MobileNet model:  154\n"]}],"source":["IMG_SIZE = 224                                                                                  \n","resize_and_rescale = Sequential([ Resizing(IMG_SIZE, IMG_SIZE), Rescaling(1.0/255, offset=-1) ]) \n","data_augmentation = Sequential([ RandomFlip(\"horizontal_and_vertical\"), RandomRotation(0.2), RandomZoom(0.1)]) \n","# Top layer of the pretrained model is removed\n","base = tf.keras.applications.MobileNetV2(input_shape=(IMG_SIZE,IMG_SIZE) + (3,), include_top=False, weights='imagenet')  #pretrained on 1.4M images and 1000 classes\n","base.trainable = False \n","print(base.summary()) \n","print(\"Number of layers in the MobileNet model: \", len(base.layers)) \n","Transfermodel = Sequential([ resize_and_rescale,  data_augmentation, base, Flatten(), Dense(2, activation='softmax')])   "]},{"cell_type":"code","execution_count":null,"id":"fb3e156b","metadata":{"executionInfo":{"elapsed":12,"status":"ok","timestamp":1650981165884,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"fb3e156b"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":20,"id":"a4b14c6e","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":627009,"status":"ok","timestamp":1650981792886,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"a4b14c6e","outputId":"ae74303d-fd71-498a-c9c0-cdc12ebc8fad"},"outputs":[{"name":"stdout","output_type":"stream","text":["Num of trainable parameters 2\n","Model: \"sequential_5\"\n","_________________________________________________________________\n"," Layer (type)                Output Shape              Param #   \n","=================================================================\n"," sequential_3 (Sequential)   (None, 224, 224, 3)       0         \n","                                                                 \n"," sequential_4 (Sequential)   (None, 224, 224, 3)       0         \n","                                                                 \n"," mobilenetv2_1.00_224 (Funct  (None, 7, 7, 1280)       2257984   \n"," ional)                                                          \n","                                                                 \n"," flatten_1 (Flatten)         (None, 62720)             0         \n","                                                                 \n"," dense_2 (Dense)             (None, 2)                 125442    \n","                                                                 \n","=================================================================\n","Total params: 2,383,426\n","Trainable params: 125,442\n","Non-trainable params: 2,257,984\n","_________________________________________________________________\n","None\n","Epoch 1/50\n","104/104 [==============================] - 146s 1s/step - loss: 6.7848 - accuracy: 0.6599 - val_loss: 5.2131 - val_accuracy: 0.6981\n","Epoch 2/50\n","104/104 [==============================] - 138s 1s/step - loss: 5.2066 - accuracy: 0.6951 - val_loss: 9.6038 - val_accuracy: 0.6209\n","Epoch 3/50\n","104/104 [==============================] - 148s 1s/step - loss: 5.5181 - accuracy: 0.7069 - val_loss: 3.8830 - val_accuracy: 0.6998\n","Epoch 4/50\n","104/104 [==============================] - 148s 1s/step - loss: 5.5090 - accuracy: 0.7084 - val_loss: 12.4543 - val_accuracy: 0.5317\n","Epoch 5/50\n","104/104 [==============================] - 154s 1s/step - loss: 5.2232 - accuracy: 0.7145 - val_loss: 4.4521 - val_accuracy: 0.7393\n","Epoch 6/50\n","104/104 [==============================] - 155s 1s/step - loss: 5.0065 - accuracy: 0.7126 - val_loss: 22.0478 - val_accuracy: 0.5077\n","Epoch 7/50\n","104/104 [==============================] - 157s 2s/step - loss: 5.6135 - accuracy: 0.7202 - val_loss: 7.4416 - val_accuracy: 0.6604\n","Epoch 8/50\n","104/104 [==============================] - 155s 1s/step - loss: 5.3503 - accuracy: 0.7139 - val_loss: 5.1060 - val_accuracy: 0.7101\n","Epoch 9/50\n","104/104 [==============================] - 158s 2s/step - loss: 4.7613 - accuracy: 0.7302 - val_loss: 3.7444 - val_accuracy: 0.7393\n","Epoch 10/50\n","104/104 [==============================] - 155s 1s/step - loss: 5.2352 - accuracy: 0.7223 - val_loss: 4.1095 - val_accuracy: 0.7290\n","Epoch 11/50\n","104/104 [==============================] - 151s 1s/step - loss: 5.1556 - accuracy: 0.7329 - val_loss: 6.1671 - val_accuracy: 0.7033\n","Epoch 12/50\n","104/104 [==============================] - 147s 1s/step - loss: 4.8318 - accuracy: 0.7436 - val_loss: 3.4654 - val_accuracy: 0.7444\n","Epoch 13/50\n","104/104 [==============================] - 152s 1s/step - loss: 4.9833 - accuracy: 0.7402 - val_loss: 4.8260 - val_accuracy: 0.7204\n","Epoch 14/50\n","104/104 [==============================] - 150s 1s/step - loss: 4.8606 - accuracy: 0.7408 - val_loss: 9.7036 - val_accuracy: 0.6278\n","Epoch 15/50\n","104/104 [==============================] - 150s 1s/step - loss: 4.7759 - accuracy: 0.7457 - val_loss: 7.3639 - val_accuracy: 0.6741\n","Epoch 16/50\n","104/104 [==============================] - 146s 1s/step - loss: 4.8670 - accuracy: 0.7369 - val_loss: 8.6330 - val_accuracy: 0.6535\n","Epoch 17/50\n","104/104 [==============================] - 148s 1s/step - loss: 4.7846 - accuracy: 0.7527 - val_loss: 4.8058 - val_accuracy: 0.7238\n","Epoch 18/50\n","104/104 [==============================] - 149s 1s/step - loss: 4.7428 - accuracy: 0.7472 - val_loss: 10.1682 - val_accuracy: 0.5969\n","Epoch 19/50\n","104/104 [==============================] - 146s 1s/step - loss: 4.5682 - accuracy: 0.7481 - val_loss: 5.1352 - val_accuracy: 0.7101\n","Epoch 20/50\n","104/104 [==============================] - 142s 1s/step - loss: 4.9414 - accuracy: 0.7490 - val_loss: 4.0374 - val_accuracy: 0.7479\n","Epoch 21/50\n","104/104 [==============================] - 158s 2s/step - loss: 4.7247 - accuracy: 0.7530 - val_loss: 5.1357 - val_accuracy: 0.7290\n","Epoch 22/50\n","104/104 [==============================] - 166s 2s/step - loss: 4.8500 - accuracy: 0.7405 - val_loss: 5.4529 - val_accuracy: 0.7101\n","Epoch 23/50\n","104/104 [==============================] - 170s 2s/step - loss: 4.7400 - accuracy: 0.7442 - val_loss: 9.4555 - val_accuracy: 0.6484\n","Epoch 24/50\n","104/104 [==============================] - 151s 1s/step - loss: 5.0562 - accuracy: 0.7460 - val_loss: 4.4209 - val_accuracy: 0.7358\n","Epoch 25/50\n","104/104 [==============================] - 104s 1s/step - loss: 4.6395 - accuracy: 0.7511 - val_loss: 8.0595 - val_accuracy: 0.6724\n","Epoch 26/50\n","104/104 [==============================] - 91s 875ms/step - loss: 4.6856 - accuracy: 0.7648 - val_loss: 14.9466 - val_accuracy: 0.5866\n","Epoch 27/50\n","104/104 [==============================] - 91s 874ms/step - loss: 4.3990 - accuracy: 0.7645 - val_loss: 4.9804 - val_accuracy: 0.7204\n","Epoch 28/50\n","104/104 [==============================] - 104s 997ms/step - loss: 4.3958 - accuracy: 0.7684 - val_loss: 17.8468 - val_accuracy: 0.5557\n","Epoch 29/50\n","104/104 [==============================] - 106s 1s/step - loss: 5.0082 - accuracy: 0.7478 - val_loss: 8.0259 - val_accuracy: 0.6758\n","Epoch 30/50\n","104/104 [==============================] - 106s 1s/step - loss: 4.8115 - accuracy: 0.7624 - val_loss: 4.2752 - val_accuracy: 0.7599\n","Epoch 31/50\n","104/104 [==============================] - 102s 985ms/step - loss: 4.5049 - accuracy: 0.7530 - val_loss: 6.4197 - val_accuracy: 0.7015\n","Epoch 32/50\n","104/104 [==============================] - 94s 908ms/step - loss: 4.8342 - accuracy: 0.7505 - val_loss: 5.1017 - val_accuracy: 0.7393\n","Epoch 33/50\n","104/104 [==============================] - 93s 895ms/step - loss: 4.7057 - accuracy: 0.7627 - val_loss: 6.9258 - val_accuracy: 0.6930\n","Epoch 34/50\n","104/104 [==============================] - 93s 892ms/step - loss: 4.5047 - accuracy: 0.7636 - val_loss: 8.8178 - val_accuracy: 0.6346\n","Epoch 35/50\n","104/104 [==============================] - 93s 896ms/step - loss: 5.2761 - accuracy: 0.7478 - val_loss: 17.1605 - val_accuracy: 0.5832\n","Epoch 36/50\n","104/104 [==============================] - 92s 882ms/step - loss: 4.6632 - accuracy: 0.7630 - val_loss: 6.5560 - val_accuracy: 0.7290\n","Epoch 37/50\n","104/104 [==============================] - 95s 917ms/step - loss: 4.4433 - accuracy: 0.7790 - val_loss: 4.9267 - val_accuracy: 0.7358\n","Epoch 38/50\n","104/104 [==============================] - 93s 892ms/step - loss: 4.6668 - accuracy: 0.7654 - val_loss: 4.8924 - val_accuracy: 0.7358\n","Epoch 39/50\n","104/104 [==============================] - 91s 878ms/step - loss: 4.2652 - accuracy: 0.7739 - val_loss: 4.5864 - val_accuracy: 0.7341\n","Epoch 40/50\n","104/104 [==============================] - 92s 890ms/step - loss: 4.2022 - accuracy: 0.7781 - val_loss: 4.9336 - val_accuracy: 0.7444\n","Epoch 41/50\n","104/104 [==============================] - 89s 853ms/step - loss: 4.4565 - accuracy: 0.7596 - val_loss: 5.8847 - val_accuracy: 0.7084\n","Epoch 42/50\n","104/104 [==============================] - 88s 845ms/step - loss: 4.5283 - accuracy: 0.7754 - val_loss: 17.5880 - val_accuracy: 0.5609\n","Epoch 43/50\n","104/104 [==============================] - 208s 2s/step - loss: 4.6960 - accuracy: 0.7614 - val_loss: 5.9852 - val_accuracy: 0.6981\n","Epoch 44/50\n","104/104 [==============================] - 101s 977ms/step - loss: 4.5928 - accuracy: 0.7717 - val_loss: 5.0886 - val_accuracy: 0.7616\n","Epoch 45/50\n","104/104 [==============================] - 95s 919ms/step - loss: 4.2043 - accuracy: 0.7769 - val_loss: 13.9696 - val_accuracy: 0.6089\n","Epoch 46/50\n","104/104 [==============================] - 103s 993ms/step - loss: 4.4440 - accuracy: 0.7681 - val_loss: 19.1572 - val_accuracy: 0.5746\n","Epoch 47/50\n","104/104 [==============================] - 98s 946ms/step - loss: 4.3460 - accuracy: 0.7702 - val_loss: 8.4486 - val_accuracy: 0.6827\n","Epoch 48/50\n","104/104 [==============================] - 93s 896ms/step - loss: 4.2866 - accuracy: 0.7760 - val_loss: 6.4491 - val_accuracy: 0.7204\n","Epoch 49/50\n","104/104 [==============================] - 94s 902ms/step - loss: 4.2394 - accuracy: 0.7766 - val_loss: 8.9452 - val_accuracy: 0.6690\n","Epoch 50/50\n","104/104 [==============================] - 106s 1s/step - loss: 4.3209 - accuracy: 0.7751 - val_loss: 6.0471 - val_accuracy: 0.7136\n"]}],"source":["Transfermodel.build([None, 224, 224, 3])  \n","print('Num of trainable parameters',len(Transfermodel.trainable_variables))\n","Transfermodel.compile( loss=tf.keras.losses.CategoricalCrossentropy () , metrics=['accuracy']) \n","print(Transfermodel.summary() )\n","num_epoches = 50\n","result2 = Transfermodel.fit(X_train, y_train, epochs = num_epoches, validation_split = 0.15) "]},{"cell_type":"code","execution_count":21,"id":"54f88940","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5061,"status":"ok","timestamp":1650981797941,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"54f88940","outputId":"7b9f4c8b-e9fc-44bd-cb62-c8463e636857"},"outputs":[{"name":"stdout","output_type":"stream","text":["53/53 [==============================] - 40s 747ms/step - loss: 5.5561 - accuracy: 0.7423\n","Average training accuracy =  0.7717368882894516\n","Average validation accuracy =  0.6951629507541657\n","Average testing accuracy =  0.7423423528671265\n"]}],"source":["test_loss, test_accuracy = Transfermodel.evaluate(X_test, y_test) \n","print('Average training accuracy = ',np.mean(result.history['accuracy']))\n","print('Average validation accuracy = ',np.mean(result.history['val_accuracy']))\n","print('Average testing accuracy = ', test_accuracy)  "]},{"cell_type":"code","execution_count":22,"id":"NcbLJBYvHVao","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":513},"executionInfo":{"elapsed":1369,"status":"ok","timestamp":1650981799306,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"NcbLJBYvHVao","outputId":"b3d94191-86e2-4ab5-82bd-ddb11da7fed2"},"outputs":[{"data":{"image/png":"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","text/plain":["<Figure size 1584x576 with 2 Axes>"]},"metadata":{"needs_background":"light"},"output_type":"display_data"}],"source":["Accuracy, loss, ValidationAcccuracy, validationLoss = result2.history['accuracy'], result2.history['loss'], result2.history['val_accuracy'], result2.history['val_loss']\n","\n","plt.figure(figsize=(22, 8))\n","plt.subplot(1, 2, 1)\n","plt.title('Validation Accuracy and Training Accuracy')\n","plt.plot(range(num_epoches), Accuracy, label='Training Accuracy')\n","plt.plot(range(num_epoches), ValidationAcccuracy, label='Validation Accuracy')\n","plt.xlabel('num of epochs')\n","plt.ylabel('Accuracy')\n","plt.legend()\n","\n","\n","plt.subplot(1, 2, 2)\n","plt.title('Validation Loss and Training Loss')\n","plt.plot(range(num_epoches), loss, label='Training Loss')\n","plt.plot(range(num_epoches), validationLoss, label='Validation Loss')\n","plt.xlabel('num of epochs')\n","plt.ylabel('Accuracy')\n","plt.legend()\n","\n","plt.show()"]},{"cell_type":"code","execution_count":23,"id":"DrBbVM8WHn9J","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":469},"executionInfo":{"elapsed":4635,"status":"ok","timestamp":1650981803934,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"DrBbVM8WHn9J","outputId":"301720f7-8450-4035-b393-9484813ab51a"},"outputs":[],"source":["y_pred = Transfermodel.predict(X_test)\n","y_pred_int = np.argmax(y_pred, axis=1)\n","y_test_int = np.argmax(y_test, axis=1) \n","print(classification_report(y_test_int,y_pred_int))\n","plot_confusion_matrix(y_test_int, y_pred_int, normalize=True)"]},{"cell_type":"code","execution_count":null,"id":"lWrlWe72MhN7","metadata":{"id":"lWrlWe72MhN7"},"outputs":[],"source":["fp, tp, thr = roc_curve(y_test_int, y_pred_int)\n","auc_val = auc(fp, tp)\n","plt.plot(fp, tp, label='(auc = {:.3f})'.format(auc_val))\n","plt.ylabel('True positive rate') \n","plt.xlabel('False positive rate') \n","plt.legend() \n","\n","plt.title('ROC curve') "]},{"cell_type":"markdown","id":"d3bee523","metadata":{"id":"d3bee523"},"source":["### Fine tuning"]},{"cell_type":"code","execution_count":null,"id":"23bb9288","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":628,"status":"ok","timestamp":1650981804550,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"23bb9288","outputId":"d3758f26-103f-4d25-8b34-e9cf88176b16"},"outputs":[],"source":["print(\"Number of layers in the MobileNet model: \",len(base.layers))\n","print(\"Freezing first 130 layers\") \n","base.trainable = True\n","for layer in base.layers[:130]:\n","  layer.trainable = False\n","\n","Transfermodel.compile( loss=tf.keras.losses.CategoricalCrossentropy () , metrics=['accuracy'])  # try implementing smaller learning rate here\n","Transfermodel.summary() "]},{"cell_type":"code","execution_count":null,"id":"24945aae","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":147164,"status":"ok","timestamp":1650981951710,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"24945aae","outputId":"f62fdeda-827d-4506-8f64-8af69c123057"},"outputs":[],"source":["tune_epoch = 10\n","result2 = Transfermodel.fit(X_train, y_train, epochs = num_epoches+tune_epoch,initial_epoch=num_epoches, validation_split = 0.15) "]},{"cell_type":"code","execution_count":null,"id":"WHO6Q9V9krlY","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":513},"executionInfo":{"elapsed":18,"status":"ok","timestamp":1650981951711,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"WHO6Q9V9krlY","outputId":"dbd0dd82-34b1-40d6-a7f4-9c46b2934a11"},"outputs":[],"source":["Accuracy, loss, ValidationAcccuracy, validationLoss = result2.history['accuracy'], result2.history['loss'], result2.history['val_accuracy'], result2.history['val_loss']\n","\n","plt.figure(figsize=(22, 8))\n","plt.subplot(1, 2, 1)\n","plt.title('Validation Accuracy and Training Accuracy')\n","plt.plot(range(tune_epoch), Accuracy, label='Training Accuracy')\n","plt.plot(range(tune_epoch), ValidationAcccuracy, label = 'Validation Accuracy')\n","plt.xlabel('num of epochs')\n","plt.ylabel('Accuracy')\n","plt.legend()\n","\n","plt.subplot(1, 2, 2)\n","plt.title('Validation Loss and Training Loss')\n","plt.plot(range(tune_epoch), loss, label='Training Loss')\n","plt.plot(range(tune_epoch), validationLoss, label='Validation Loss')\n","plt.xlabel('num of epochs')\n","plt.ylabel('Accuracy')\n","plt.legend()\n","plt.show()"]},{"cell_type":"code","execution_count":null,"id":"c3452822","metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5345,"status":"ok","timestamp":1650981957050,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"c3452822","outputId":"1754e741-a61b-493d-ba34-22ecc2cd0f85"},"outputs":[],"source":["y_pred = Transfermodel.predict(X_test)\n","y_pred_int = np.argmax(y_pred, axis=1)\n","y_test_int = np.argmax(y_test, axis=1) \n","print(classification_report(y_test_int,y_pred_int)) "]},{"cell_type":"code","execution_count":null,"id":"IkE9OcmAkr1T","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":312},"executionInfo":{"elapsed":19,"status":"ok","timestamp":1650981957051,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"IkE9OcmAkr1T","outputId":"5d286282-6e1e-48de-a84b-f511006b4e59"},"outputs":[],"source":["plot_confusion_matrix(y_test_int, y_pred_int, normalize=True)"]},{"cell_type":"code","execution_count":null,"id":"SMlGhrGQ1bRQ","metadata":{"colab":{"base_uri":"https://localhost:8080/","height":312},"executionInfo":{"elapsed":800,"status":"ok","timestamp":1650981957844,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"SMlGhrGQ1bRQ","outputId":"14f8f4cc-5e5a-4671-8013-43b4e0383611"},"outputs":[],"source":["fp, tp, thr = roc_curve(y_test_int, y_pred_int)\n","auc_val = auc(fp, tp)\n","plt.plot(fp, tp, label='(auc = {:.3f})'.format(auc_val))\n","plt.xlabel('False positive rate')\n","plt.ylabel('True positive rate')\n","plt.title('ROC curve')\n","plt.legend()"]},{"cell_type":"code","execution_count":null,"id":"pKMHmRGdWDD0","metadata":{"executionInfo":{"elapsed":660,"status":"ok","timestamp":1650981958500,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"pKMHmRGdWDD0"},"outputs":[],"source":["Transfermodel.save('model2.h5')"]},{"cell_type":"code","execution_count":null,"id":"83863fdd","metadata":{"executionInfo":{"elapsed":12,"status":"ok","timestamp":1650981958500,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"83863fdd"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"id":"e370c9af","metadata":{"executionInfo":{"elapsed":12,"status":"ok","timestamp":1650981958501,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"e370c9af"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"id":"a59df1f8","metadata":{"executionInfo":{"elapsed":9,"status":"ok","timestamp":1650981958501,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"a59df1f8"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"id":"bf776816","metadata":{"executionInfo":{"elapsed":9,"status":"ok","timestamp":1650981958501,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"bf776816"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"id":"a9b13b18","metadata":{"executionInfo":{"elapsed":9,"status":"ok","timestamp":1650981958502,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"a9b13b18"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"id":"1d7f3e67","metadata":{"executionInfo":{"elapsed":10,"status":"ok","timestamp":1650981958503,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"1d7f3e67"},"outputs":[],"source":[]},{"cell_type":"code","execution_count":null,"id":"a66f2175","metadata":{"executionInfo":{"elapsed":10,"status":"ok","timestamp":1650981958503,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"a66f2175"},"outputs":[],"source":["# Transfermodel = Sequential([\n","#     resize_and_rescale,\n","#     data_augmentation,\n","#     hub.KerasLayer(\"https://tfhub.dev/google/tf2-preview/mobilenet_v2/feature_vector/4\", output_shape=[1280], trainable=False),\n","#     Flatten(),\n","#     Dense(2,  activation='softmax')\n","#     ]) "]},{"cell_type":"code","execution_count":null,"id":"f5da1403","metadata":{"executionInfo":{"elapsed":9,"status":"ok","timestamp":1650981958503,"user":{"displayName":"Vishwanath reddy","userId":"11133494476273499334"},"user_tz":-330},"id":"f5da1403"},"outputs":[],"source":[]}],"metadata":{"colab":{"collapsed_sections":[],"name":"final.ipynb","provenance":[]},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.10.2"}},"nbformat":4,"nbformat_minor":5}