Document_digitization_for_blind.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "64ac61ff-e49f-47eb-b4bb-bf5d8f7248b5",
   "metadata": {
    "tags": []
   },
   "source": [
    "Necessary libraries: TensorFlow, NumPy, Matplotlib, scikit-learn, Pillow, and pandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1669adca-e9d9-403a-b4b7-3a37f8e4ac16",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: tensorflow in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (2.15.1)\n",
      "Requirement already satisfied: numpy in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (1.26.4)\n",
      "Requirement already satisfied: matplotlib in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (3.8.3)\n",
      "Requirement already satisfied: scikit-learn in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (1.4.1.post1)\n",
      "Requirement already satisfied: pillow in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (10.2.0)\n",
      "Requirement already satisfied: pandas in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (1.5.3)\n",
      "Requirement already satisfied: absl-py>=1.0.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (2.1.0)\n",
      "Requirement already satisfied: astunparse>=1.6.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (1.6.3)\n",
      "Requirement already satisfied: flatbuffers>=23.5.26 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (24.3.25)\n",
      "Requirement already satisfied: gast!=0.5.0,!=0.5.1,!=0.5.2,>=0.2.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (0.5.4)\n",
      "Requirement already satisfied: google-pasta>=0.1.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (0.2.0)\n",
      "Requirement already satisfied: h5py>=2.9.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (3.10.0)\n",
      "Requirement already satisfied: libclang>=13.0.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (18.1.1)\n",
      "Requirement already satisfied: ml-dtypes~=0.3.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (0.3.2)\n",
      "Requirement already satisfied: opt-einsum>=2.3.2 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (3.3.0)\n",
      "Requirement already satisfied: packaging in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (21.3)\n",
      "Requirement already satisfied: protobuf!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0dev,>=3.20.3 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (4.25.3)\n",
      "Requirement already satisfied: setuptools in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (69.2.0)\n",
      "Requirement already satisfied: six>=1.12.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (1.16.0)\n",
      "Requirement already satisfied: termcolor>=1.1.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (2.4.0)\n",
      "Requirement already satisfied: typing-extensions>=3.6.6 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (4.10.0)\n",
      "Requirement already satisfied: wrapt<1.15,>=1.11.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (1.14.1)\n",
      "Requirement already satisfied: tensorflow-io-gcs-filesystem>=0.23.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (0.36.0)\n",
      "Requirement already satisfied: grpcio<2.0,>=1.24.3 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (1.62.1)\n",
      "Requirement already satisfied: tensorboard<2.16,>=2.15 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (2.15.2)\n",
      "Requirement already satisfied: tensorflow-estimator<2.16,>=2.15.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (2.15.0)\n",
      "Requirement already satisfied: keras<2.16,>=2.15.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorflow) (2.15.0)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from matplotlib) (1.2.0)\n",
      "Requirement already satisfied: cycler>=0.10 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from matplotlib) (0.12.1)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from matplotlib) (4.50.0)\n",
      "Requirement already satisfied: kiwisolver>=1.3.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from matplotlib) (1.4.5)\n",
      "Requirement already satisfied: pyparsing>=2.3.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from matplotlib) (3.1.2)\n",
      "Requirement already satisfied: python-dateutil>=2.7 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from matplotlib) (2.9.0)\n",
      "Requirement already satisfied: scipy>=1.6.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from scikit-learn) (1.12.0)\n",
      "Requirement already satisfied: joblib>=1.2.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from scikit-learn) (1.3.2)\n",
      "Requirement already satisfied: threadpoolctl>=2.0.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from scikit-learn) (3.4.0)\n",
      "Requirement already satisfied: pytz>=2020.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from pandas) (2024.1)\n",
      "Requirement already satisfied: wheel<1.0,>=0.23.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from astunparse>=1.6.0->tensorflow) (0.43.0)\n",
      "Requirement already satisfied: google-auth<3,>=1.6.3 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorboard<2.16,>=2.15->tensorflow) (2.29.0)\n",
      "Requirement already satisfied: google-auth-oauthlib<2,>=0.5 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorboard<2.16,>=2.15->tensorflow) (1.2.0)\n",
      "Requirement already satisfied: markdown>=2.6.8 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorboard<2.16,>=2.15->tensorflow) (3.6)\n",
      "Requirement already satisfied: requests<3,>=2.21.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorboard<2.16,>=2.15->tensorflow) (2.31.0)\n",
      "Requirement already satisfied: tensorboard-data-server<0.8.0,>=0.7.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorboard<2.16,>=2.15->tensorflow) (0.7.2)\n",
      "Requirement already satisfied: werkzeug>=1.0.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from tensorboard<2.16,>=2.15->tensorflow) (3.0.1)\n",
      "Requirement already satisfied: cachetools<6.0,>=2.0.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from google-auth<3,>=1.6.3->tensorboard<2.16,>=2.15->tensorflow) (5.3.3)\n",
      "Requirement already satisfied: pyasn1-modules>=0.2.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from google-auth<3,>=1.6.3->tensorboard<2.16,>=2.15->tensorflow) (0.4.0)\n",
      "Requirement already satisfied: rsa<5,>=3.1.4 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from google-auth<3,>=1.6.3->tensorboard<2.16,>=2.15->tensorflow) (4.7.2)\n",
      "Requirement already satisfied: requests-oauthlib>=0.7.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from google-auth-oauthlib<2,>=0.5->tensorboard<2.16,>=2.15->tensorflow) (2.0.0)\n",
      "Requirement already satisfied: charset-normalizer<4,>=2 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from requests<3,>=2.21.0->tensorboard<2.16,>=2.15->tensorflow) (3.3.2)\n",
      "Requirement already satisfied: idna<4,>=2.5 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from requests<3,>=2.21.0->tensorboard<2.16,>=2.15->tensorflow) (3.6)\n",
      "Requirement already satisfied: urllib3<3,>=1.21.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from requests<3,>=2.21.0->tensorboard<2.16,>=2.15->tensorflow) (2.2.1)\n",
      "Requirement already satisfied: certifi>=2017.4.17 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from requests<3,>=2.21.0->tensorboard<2.16,>=2.15->tensorflow) (2024.2.2)\n",
      "Requirement already satisfied: MarkupSafe>=2.1.1 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from werkzeug>=1.0.1->tensorboard<2.16,>=2.15->tensorflow) (2.1.5)\n",
      "Requirement already satisfied: pyasn1<0.7.0,>=0.4.6 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard<2.16,>=2.15->tensorflow) (0.5.1)\n",
      "Requirement already satisfied: oauthlib>=3.0.0 in /home/ec2-user/anaconda3/envs/tensorflow2_p310/lib/python3.10/site-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<2,>=0.5->tensorboard<2.16,>=2.15->tensorflow) (3.2.2)\n"
     ]
    }
   ],
   "source": [
    "!pip install tensorflow numpy matplotlib scikit-learn pillow pandas"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d36869a7-e33d-4c34-bf76-49efc0d45650",
   "metadata": {
    "tags": []
   },
   "source": [
    "imports the os module for interacting with the operating system and ImageDataGenerator from TensorFlow Keras for augmenting image data for training the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "bdea2a05-8dd7-45a0-8853-d3740aa9368e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1262097d-1a09-42a9-b524-6c22d5c15dd2",
   "metadata": {
    "tags": []
   },
   "source": [
    "Defines the directories where the training and testing images are stored."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "962bab38-7a6e-4bec-ad85-3807361fe0fa",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "train_dir = 'images/training'\n",
    "test_dir = 'images/testing'"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0a622b63-8cb7-4c2a-ba2c-441622c8178a",
   "metadata": {
    "tags": []
   },
   "source": [
    "creates an ImageDataGenerator object for the training data with various augmentations such as rescaling, rotation, shifting, shearing, zooming, and flipping."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "bd178319-c3cb-42fb-94c1-ea2c9effb301",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "train_datagen = ImageDataGenerator(\n",
    "    rescale=1./255,\n",
    "    rotation_range=20,\n",
    "    width_shift_range=0.2,\n",
    "    height_shift_range=0.2,\n",
    "    shear_range=0.2,\n",
    "    zoom_range=0.2,\n",
    "    horizontal_flip=True,\n",
    "    fill_mode='nearest'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2ece0cb1-dc5a-47bb-a679-3355d5f1b3e6",
   "metadata": {
    "tags": []
   },
   "source": [
    "creates an ImageDataGenerator object for the test data, rescaling the pixel values to the range [0, 1]."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "05ed4d83-0e31-4ac2-8816-e8ebfa6cee0e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "test_datagen = ImageDataGenerator(rescale=1./255)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e60a6dc8-7ffe-4ade-b975-ab884d479a21",
   "metadata": {
    "tags": []
   },
   "source": [
    "creates a data generator for the training images, specifying the directory, target size, batch size, and class mode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "1e4bf1e2-9b3f-4ce2-b967-482ed06ee753",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 2367 images belonging to 3 classes.\n"
     ]
    }
   ],
   "source": [
    "train_generator = train_datagen.flow_from_directory(\n",
    "    train_dir,\n",
    "    target_size=(224, 224),\n",
    "    batch_size=32,\n",
    "    class_mode='binary'\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cfef0547-8b3b-4b2c-8437-c3a515eebac0",
   "metadata": {
    "tags": []
   },
   "source": [
    "A data generator for the test images, specifying the directory, target size, batch size, and class mode."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "5ddbb391-007e-4ce2-98ea-6f42c98f2bee",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 591 images belonging to 3 classes.\n"
     ]
    }
   ],
   "source": [
    "test_generator = test_datagen.flow_from_directory(\n",
    "    test_dir,\n",
    "    target_size=(224, 224),\n",
    "    batch_size=32,\n",
    "    class_mode='binary'\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "683d142d-f73e-4ede-8019-e0145ed51904",
   "metadata": {
    "tags": []
   },
   "source": [
    "Imports necessary classes from TensorFlow Keras to build a sequential model with convolutional, pooling, flattening, dense, and dropout layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7377e6bc-9f85-4068-bc4a-ed820cae182a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Dropout"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d0b10cfb-7a2f-46ed-9f92-72250b5341cd",
   "metadata": {
    "tags": []
   },
   "source": [
    "def create_baseline_model: Defines a new function named create_baseline_model.\n",
    "input_shape=(224, 224, 3): The function takes an optional parameter input_shape, which defaults to (224, 224, 3). This represents the shape of the input images (224x224 pixels with 3 color channels - RGB).\n",
    "Sequential(): Creates a new Sequential model, which is a linear stack of layers.\n",
    "Conv2D(32, (3, 3), activation='relu', input_shape=input_shape): Adds a 2D convolutional layer with 32 filters, a 3x3 kernel, ReLU activation, and the specified input shape. This layer detects features in the input image.\n",
    "MaxPooling2D((2, 2)): Adds a max-pooling layer with a 2x2 pool size. This reduces the spatial dimensions of the feature maps, which helps in reducing computation and controlling overfitting.\n",
    "Conv2D(64, (3, 3), activation='relu'): Adds another 2D convolutional layer with 64 filters and ReLU activation.\n",
    "MaxPooling2D((2, 2)): Adds another max-pooling layer with a 2x2 pool size.\n",
    "Conv2D(128, (3, 3), activation='relu'): Adds a third 2D convolutional layer with 128 filters and ReLU activation.\n",
    "MaxPooling2D((2, 2)): Adds another max-pooling layer with a 2x2 pool size.\n",
    "Flatten(): Flattens the 3D feature maps to a 1D vector, preparing it for the dense (fully connected) layers.\n",
    "Dense(128, activation='relu'): Adds a dense layer with 128 units and ReLU activation. This layer learns high-level features.\n",
    "Dropout(0.5): Adds a dropout layer with a 50% dropout rate. This helps in reducing overfitting by randomly setting half of the inputs to zero during training.\n",
    "Dense(1, activation='sigmoid'): Adds a dense layer with 1 unit and sigmoid activation. This is the output layer for binary classification, outputting a probability between 0 and 1.\n",
    "optimizer='adam': Uses the Adam optimizer, which is an adaptive learning rate optimization algorithm.\n",
    "loss='binary_crossentropy': Uses binary cross-entropy as the loss function, which is appropriate for binary classification tasks.\n",
    "metrics=['accuracy']: Specifies that accuracy should be tracked as a metric during training.\n",
    "Returns the compiled model.\n",
    "create_baseline_model(): Calls the function to create the baseline model.\n",
    "baseline_model.summary(): Prints a summary of the model architecture, showing the layers, output shapes, and the number of parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "03b280a1-9344-4060-8efc-566950a42154",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential_3\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " conv2d_9 (Conv2D)           (None, 222, 222, 32)      896       \n",
      "                                                                 \n",
      " max_pooling2d_9 (MaxPoolin  (None, 111, 111, 32)      0         \n",
      " g2D)                                                            \n",
      "                                                                 \n",
      " conv2d_10 (Conv2D)          (None, 109, 109, 64)      18496     \n",
      "                                                                 \n",
      " max_pooling2d_10 (MaxPooli  (None, 54, 54, 64)        0         \n",
      " ng2D)                                                           \n",
      "                                                                 \n",
      " conv2d_11 (Conv2D)          (None, 52, 52, 128)       73856     \n",
      "                                                                 \n",
      " max_pooling2d_11 (MaxPooli  (None, 26, 26, 128)       0         \n",
      " ng2D)                                                           \n",
      "                                                                 \n",
      " flatten_3 (Flatten)         (None, 86528)             0         \n",
      "                                                                 \n",
      " dense_6 (Dense)             (None, 128)               11075712  \n",
      "                                                                 \n",
      " dropout_3 (Dropout)         (None, 128)               0         \n",
      "                                                                 \n",
      " dense_7 (Dense)             (None, 1)                 129       \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 11169089 (42.61 MB)\n",
      "Trainable params: 11169089 (42.61 MB)\n",
      "Non-trainable params: 0 (0.00 Byte)\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "def create_baseline_model(input_shape=(224, 224, 3)):\n",
    "    model = Sequential([\n",
    "        Conv2D(32, (3, 3), activation='relu', input_shape=input_shape),\n",
    "        MaxPooling2D((2, 2)),\n",
    "        Conv2D(64, (3, 3), activation='relu'),\n",
    "        MaxPooling2D((2, 2)),\n",
    "        Conv2D(128, (3, 3), activation='relu'),\n",
    "        MaxPooling2D((2, 2)),\n",
    "        Flatten(),\n",
    "        Dense(128, activation='relu'),\n",
    "        Dropout(0.5),\n",
    "        Dense(1, activation='sigmoid')\n",
    "    ])\n",
    "    model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])\n",
    "    return model\n",
    "\n",
    "baseline_model = create_baseline_model()\n",
    "baseline_model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "add10179-e911-45ae-83bf-a824d530b1bd",
   "metadata": {
    "tags": []
   },
   "source": [
    "trains the baseline model using the training data generator and validates it using the test data generator for 3 epochs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "af30be2c-26d5-4daf-af02-c1ceb0f8bc48",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/3\n",
      "74/74 [==============================] - 280s 4s/step - loss: -14898040.0000 - accuracy: 0.4795 - val_loss: -116103712.0000 - val_accuracy: 0.4873\n",
      "Epoch 2/3\n",
      "74/74 [==============================] - 280s 4s/step - loss: -2652317440.0000 - accuracy: 0.4808 - val_loss: -10312916992.0000 - val_accuracy: 0.4873\n",
      "Epoch 3/3\n",
      "74/74 [==============================] - 304s 4s/step - loss: -50339033088.0000 - accuracy: 0.4808 - val_loss: -133815517184.0000 - val_accuracy: 0.4873\n"
     ]
    }
   ],
   "source": [
    "history_baseline = baseline_model.fit(train_generator, validation_data=test_generator, epochs=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e290082a-0779-4632-8e6f-97acc876f69b",
   "metadata": {
    "tags": []
   },
   "source": [
    " imports the numpy library, which is used for numerical operations. It then creates ensemble predictions by averaging the predictions from the baseline, ResNet50, and EfficientNet models and rounding them to the nearest integer."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "af4e3dbd-8912-48cf-ab3a-dafb610e0e8b",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from tensorflow.keras.applications import ResNet50\n",
    "from tensorflow.keras.models import Model\n",
    "from tensorflow.keras.layers import GlobalAveragePooling2D, Dense"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "99cbf9dc-063d-4c4b-ba13-1bf833a9ece5",
   "metadata": {
    "tags": []
   },
   "source": [
    "This function creates a fine-tuned ResNet50 model for binary classification. It removes the top layers of the pre-trained ResNet50, adds global average pooling, dense, and dropout layers, and compiles the model with the Adam optimizer and binary cross-entropy loss. The base ResNet50 layers are frozen to prevent retraining."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "1d1d0319-6920-47ba-854c-659d318840ab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
      "94765736/94765736 [==============================] - 1s 0us/step\n",
      "Model: \"model\"\n",
      "__________________________________________________________________________________________________\n",
      " Layer (type)                Output Shape                 Param #   Connected to                  \n",
      "==================================================================================================\n",
      " input_1 (InputLayer)        [(None, 224, 224, 3)]        0         []                            \n",
      "                                                                                                  \n",
      " conv1_pad (ZeroPadding2D)   (None, 230, 230, 3)          0         ['input_1[0][0]']             \n",
      "                                                                                                  \n",
      " conv1_conv (Conv2D)         (None, 112, 112, 64)         9472      ['conv1_pad[0][0]']           \n",
      "                                                                                                  \n",
      " conv1_bn (BatchNormalizati  (None, 112, 112, 64)         256       ['conv1_conv[0][0]']          \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv1_relu (Activation)     (None, 112, 112, 64)         0         ['conv1_bn[0][0]']            \n",
      "                                                                                                  \n",
      " pool1_pad (ZeroPadding2D)   (None, 114, 114, 64)         0         ['conv1_relu[0][0]']          \n",
      "                                                                                                  \n",
      " pool1_pool (MaxPooling2D)   (None, 56, 56, 64)           0         ['pool1_pad[0][0]']           \n",
      "                                                                                                  \n",
      " conv2_block1_1_conv (Conv2  (None, 56, 56, 64)           4160      ['pool1_pool[0][0]']          \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block1_1_bn (BatchNo  (None, 56, 56, 64)           256       ['conv2_block1_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv2_block1_1_relu (Activ  (None, 56, 56, 64)           0         ['conv2_block1_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv2_block1_2_conv (Conv2  (None, 56, 56, 64)           36928     ['conv2_block1_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block1_2_bn (BatchNo  (None, 56, 56, 64)           256       ['conv2_block1_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv2_block1_2_relu (Activ  (None, 56, 56, 64)           0         ['conv2_block1_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv2_block1_0_conv (Conv2  (None, 56, 56, 256)          16640     ['pool1_pool[0][0]']          \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block1_3_conv (Conv2  (None, 56, 56, 256)          16640     ['conv2_block1_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block1_0_bn (BatchNo  (None, 56, 56, 256)          1024      ['conv2_block1_0_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv2_block1_3_bn (BatchNo  (None, 56, 56, 256)          1024      ['conv2_block1_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv2_block1_add (Add)      (None, 56, 56, 256)          0         ['conv2_block1_0_bn[0][0]',   \n",
      "                                                                     'conv2_block1_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv2_block1_out (Activati  (None, 56, 56, 256)          0         ['conv2_block1_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv2_block2_1_conv (Conv2  (None, 56, 56, 64)           16448     ['conv2_block1_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block2_1_bn (BatchNo  (None, 56, 56, 64)           256       ['conv2_block2_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv2_block2_1_relu (Activ  (None, 56, 56, 64)           0         ['conv2_block2_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv2_block2_2_conv (Conv2  (None, 56, 56, 64)           36928     ['conv2_block2_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block2_2_bn (BatchNo  (None, 56, 56, 64)           256       ['conv2_block2_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv2_block2_2_relu (Activ  (None, 56, 56, 64)           0         ['conv2_block2_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv2_block2_3_conv (Conv2  (None, 56, 56, 256)          16640     ['conv2_block2_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block2_3_bn (BatchNo  (None, 56, 56, 256)          1024      ['conv2_block2_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv2_block2_add (Add)      (None, 56, 56, 256)          0         ['conv2_block1_out[0][0]',    \n",
      "                                                                     'conv2_block2_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv2_block2_out (Activati  (None, 56, 56, 256)          0         ['conv2_block2_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv2_block3_1_conv (Conv2  (None, 56, 56, 64)           16448     ['conv2_block2_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block3_1_bn (BatchNo  (None, 56, 56, 64)           256       ['conv2_block3_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv2_block3_1_relu (Activ  (None, 56, 56, 64)           0         ['conv2_block3_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv2_block3_2_conv (Conv2  (None, 56, 56, 64)           36928     ['conv2_block3_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block3_2_bn (BatchNo  (None, 56, 56, 64)           256       ['conv2_block3_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv2_block3_2_relu (Activ  (None, 56, 56, 64)           0         ['conv2_block3_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv2_block3_3_conv (Conv2  (None, 56, 56, 256)          16640     ['conv2_block3_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv2_block3_3_bn (BatchNo  (None, 56, 56, 256)          1024      ['conv2_block3_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv2_block3_add (Add)      (None, 56, 56, 256)          0         ['conv2_block2_out[0][0]',    \n",
      "                                                                     'conv2_block3_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv2_block3_out (Activati  (None, 56, 56, 256)          0         ['conv2_block3_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv3_block1_1_conv (Conv2  (None, 28, 28, 128)          32896     ['conv2_block3_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block1_1_bn (BatchNo  (None, 28, 28, 128)          512       ['conv3_block1_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block1_1_relu (Activ  (None, 28, 28, 128)          0         ['conv3_block1_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv3_block1_2_conv (Conv2  (None, 28, 28, 128)          147584    ['conv3_block1_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block1_2_bn (BatchNo  (None, 28, 28, 128)          512       ['conv3_block1_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block1_2_relu (Activ  (None, 28, 28, 128)          0         ['conv3_block1_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv3_block1_0_conv (Conv2  (None, 28, 28, 512)          131584    ['conv2_block3_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block1_3_conv (Conv2  (None, 28, 28, 512)          66048     ['conv3_block1_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block1_0_bn (BatchNo  (None, 28, 28, 512)          2048      ['conv3_block1_0_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block1_3_bn (BatchNo  (None, 28, 28, 512)          2048      ['conv3_block1_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block1_add (Add)      (None, 28, 28, 512)          0         ['conv3_block1_0_bn[0][0]',   \n",
      "                                                                     'conv3_block1_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv3_block1_out (Activati  (None, 28, 28, 512)          0         ['conv3_block1_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv3_block2_1_conv (Conv2  (None, 28, 28, 128)          65664     ['conv3_block1_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block2_1_bn (BatchNo  (None, 28, 28, 128)          512       ['conv3_block2_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block2_1_relu (Activ  (None, 28, 28, 128)          0         ['conv3_block2_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv3_block2_2_conv (Conv2  (None, 28, 28, 128)          147584    ['conv3_block2_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block2_2_bn (BatchNo  (None, 28, 28, 128)          512       ['conv3_block2_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block2_2_relu (Activ  (None, 28, 28, 128)          0         ['conv3_block2_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv3_block2_3_conv (Conv2  (None, 28, 28, 512)          66048     ['conv3_block2_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block2_3_bn (BatchNo  (None, 28, 28, 512)          2048      ['conv3_block2_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block2_add (Add)      (None, 28, 28, 512)          0         ['conv3_block1_out[0][0]',    \n",
      "                                                                     'conv3_block2_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv3_block2_out (Activati  (None, 28, 28, 512)          0         ['conv3_block2_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv3_block3_1_conv (Conv2  (None, 28, 28, 128)          65664     ['conv3_block2_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block3_1_bn (BatchNo  (None, 28, 28, 128)          512       ['conv3_block3_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block3_1_relu (Activ  (None, 28, 28, 128)          0         ['conv3_block3_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv3_block3_2_conv (Conv2  (None, 28, 28, 128)          147584    ['conv3_block3_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block3_2_bn (BatchNo  (None, 28, 28, 128)          512       ['conv3_block3_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block3_2_relu (Activ  (None, 28, 28, 128)          0         ['conv3_block3_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv3_block3_3_conv (Conv2  (None, 28, 28, 512)          66048     ['conv3_block3_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block3_3_bn (BatchNo  (None, 28, 28, 512)          2048      ['conv3_block3_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block3_add (Add)      (None, 28, 28, 512)          0         ['conv3_block2_out[0][0]',    \n",
      "                                                                     'conv3_block3_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv3_block3_out (Activati  (None, 28, 28, 512)          0         ['conv3_block3_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv3_block4_1_conv (Conv2  (None, 28, 28, 128)          65664     ['conv3_block3_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block4_1_bn (BatchNo  (None, 28, 28, 128)          512       ['conv3_block4_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block4_1_relu (Activ  (None, 28, 28, 128)          0         ['conv3_block4_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv3_block4_2_conv (Conv2  (None, 28, 28, 128)          147584    ['conv3_block4_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block4_2_bn (BatchNo  (None, 28, 28, 128)          512       ['conv3_block4_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block4_2_relu (Activ  (None, 28, 28, 128)          0         ['conv3_block4_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv3_block4_3_conv (Conv2  (None, 28, 28, 512)          66048     ['conv3_block4_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv3_block4_3_bn (BatchNo  (None, 28, 28, 512)          2048      ['conv3_block4_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv3_block4_add (Add)      (None, 28, 28, 512)          0         ['conv3_block3_out[0][0]',    \n",
      "                                                                     'conv3_block4_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv3_block4_out (Activati  (None, 28, 28, 512)          0         ['conv3_block4_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv4_block1_1_conv (Conv2  (None, 14, 14, 256)          131328    ['conv3_block4_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block1_1_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block1_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block1_1_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block1_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block1_2_conv (Conv2  (None, 14, 14, 256)          590080    ['conv4_block1_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block1_2_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block1_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block1_2_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block1_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block1_0_conv (Conv2  (None, 14, 14, 1024)         525312    ['conv3_block4_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block1_3_conv (Conv2  (None, 14, 14, 1024)         263168    ['conv4_block1_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block1_0_bn (BatchNo  (None, 14, 14, 1024)         4096      ['conv4_block1_0_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block1_3_bn (BatchNo  (None, 14, 14, 1024)         4096      ['conv4_block1_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block1_add (Add)      (None, 14, 14, 1024)         0         ['conv4_block1_0_bn[0][0]',   \n",
      "                                                                     'conv4_block1_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv4_block1_out (Activati  (None, 14, 14, 1024)         0         ['conv4_block1_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv4_block2_1_conv (Conv2  (None, 14, 14, 256)          262400    ['conv4_block1_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block2_1_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block2_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block2_1_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block2_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block2_2_conv (Conv2  (None, 14, 14, 256)          590080    ['conv4_block2_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block2_2_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block2_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block2_2_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block2_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block2_3_conv (Conv2  (None, 14, 14, 1024)         263168    ['conv4_block2_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block2_3_bn (BatchNo  (None, 14, 14, 1024)         4096      ['conv4_block2_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block2_add (Add)      (None, 14, 14, 1024)         0         ['conv4_block1_out[0][0]',    \n",
      "                                                                     'conv4_block2_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv4_block2_out (Activati  (None, 14, 14, 1024)         0         ['conv4_block2_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv4_block3_1_conv (Conv2  (None, 14, 14, 256)          262400    ['conv4_block2_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block3_1_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block3_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block3_1_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block3_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block3_2_conv (Conv2  (None, 14, 14, 256)          590080    ['conv4_block3_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block3_2_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block3_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block3_2_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block3_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block3_3_conv (Conv2  (None, 14, 14, 1024)         263168    ['conv4_block3_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block3_3_bn (BatchNo  (None, 14, 14, 1024)         4096      ['conv4_block3_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block3_add (Add)      (None, 14, 14, 1024)         0         ['conv4_block2_out[0][0]',    \n",
      "                                                                     'conv4_block3_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv4_block3_out (Activati  (None, 14, 14, 1024)         0         ['conv4_block3_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv4_block4_1_conv (Conv2  (None, 14, 14, 256)          262400    ['conv4_block3_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block4_1_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block4_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block4_1_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block4_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block4_2_conv (Conv2  (None, 14, 14, 256)          590080    ['conv4_block4_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block4_2_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block4_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block4_2_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block4_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block4_3_conv (Conv2  (None, 14, 14, 1024)         263168    ['conv4_block4_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block4_3_bn (BatchNo  (None, 14, 14, 1024)         4096      ['conv4_block4_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block4_add (Add)      (None, 14, 14, 1024)         0         ['conv4_block3_out[0][0]',    \n",
      "                                                                     'conv4_block4_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv4_block4_out (Activati  (None, 14, 14, 1024)         0         ['conv4_block4_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv4_block5_1_conv (Conv2  (None, 14, 14, 256)          262400    ['conv4_block4_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block5_1_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block5_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block5_1_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block5_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block5_2_conv (Conv2  (None, 14, 14, 256)          590080    ['conv4_block5_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block5_2_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block5_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block5_2_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block5_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block5_3_conv (Conv2  (None, 14, 14, 1024)         263168    ['conv4_block5_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block5_3_bn (BatchNo  (None, 14, 14, 1024)         4096      ['conv4_block5_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block5_add (Add)      (None, 14, 14, 1024)         0         ['conv4_block4_out[0][0]',    \n",
      "                                                                     'conv4_block5_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv4_block5_out (Activati  (None, 14, 14, 1024)         0         ['conv4_block5_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv4_block6_1_conv (Conv2  (None, 14, 14, 256)          262400    ['conv4_block5_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block6_1_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block6_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block6_1_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block6_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block6_2_conv (Conv2  (None, 14, 14, 256)          590080    ['conv4_block6_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block6_2_bn (BatchNo  (None, 14, 14, 256)          1024      ['conv4_block6_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block6_2_relu (Activ  (None, 14, 14, 256)          0         ['conv4_block6_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv4_block6_3_conv (Conv2  (None, 14, 14, 1024)         263168    ['conv4_block6_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv4_block6_3_bn (BatchNo  (None, 14, 14, 1024)         4096      ['conv4_block6_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv4_block6_add (Add)      (None, 14, 14, 1024)         0         ['conv4_block5_out[0][0]',    \n",
      "                                                                     'conv4_block6_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv4_block6_out (Activati  (None, 14, 14, 1024)         0         ['conv4_block6_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv5_block1_1_conv (Conv2  (None, 7, 7, 512)            524800    ['conv4_block6_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block1_1_bn (BatchNo  (None, 7, 7, 512)            2048      ['conv5_block1_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv5_block1_1_relu (Activ  (None, 7, 7, 512)            0         ['conv5_block1_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv5_block1_2_conv (Conv2  (None, 7, 7, 512)            2359808   ['conv5_block1_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block1_2_bn (BatchNo  (None, 7, 7, 512)            2048      ['conv5_block1_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv5_block1_2_relu (Activ  (None, 7, 7, 512)            0         ['conv5_block1_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv5_block1_0_conv (Conv2  (None, 7, 7, 2048)           2099200   ['conv4_block6_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block1_3_conv (Conv2  (None, 7, 7, 2048)           1050624   ['conv5_block1_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block1_0_bn (BatchNo  (None, 7, 7, 2048)           8192      ['conv5_block1_0_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv5_block1_3_bn (BatchNo  (None, 7, 7, 2048)           8192      ['conv5_block1_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv5_block1_add (Add)      (None, 7, 7, 2048)           0         ['conv5_block1_0_bn[0][0]',   \n",
      "                                                                     'conv5_block1_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv5_block1_out (Activati  (None, 7, 7, 2048)           0         ['conv5_block1_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv5_block2_1_conv (Conv2  (None, 7, 7, 512)            1049088   ['conv5_block1_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block2_1_bn (BatchNo  (None, 7, 7, 512)            2048      ['conv5_block2_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv5_block2_1_relu (Activ  (None, 7, 7, 512)            0         ['conv5_block2_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv5_block2_2_conv (Conv2  (None, 7, 7, 512)            2359808   ['conv5_block2_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block2_2_bn (BatchNo  (None, 7, 7, 512)            2048      ['conv5_block2_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv5_block2_2_relu (Activ  (None, 7, 7, 512)            0         ['conv5_block2_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv5_block2_3_conv (Conv2  (None, 7, 7, 2048)           1050624   ['conv5_block2_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block2_3_bn (BatchNo  (None, 7, 7, 2048)           8192      ['conv5_block2_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv5_block2_add (Add)      (None, 7, 7, 2048)           0         ['conv5_block1_out[0][0]',    \n",
      "                                                                     'conv5_block2_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv5_block2_out (Activati  (None, 7, 7, 2048)           0         ['conv5_block2_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " conv5_block3_1_conv (Conv2  (None, 7, 7, 512)            1049088   ['conv5_block2_out[0][0]']    \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block3_1_bn (BatchNo  (None, 7, 7, 512)            2048      ['conv5_block3_1_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv5_block3_1_relu (Activ  (None, 7, 7, 512)            0         ['conv5_block3_1_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv5_block3_2_conv (Conv2  (None, 7, 7, 512)            2359808   ['conv5_block3_1_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block3_2_bn (BatchNo  (None, 7, 7, 512)            2048      ['conv5_block3_2_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv5_block3_2_relu (Activ  (None, 7, 7, 512)            0         ['conv5_block3_2_bn[0][0]']   \n",
      " ation)                                                                                           \n",
      "                                                                                                  \n",
      " conv5_block3_3_conv (Conv2  (None, 7, 7, 2048)           1050624   ['conv5_block3_2_relu[0][0]'] \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " conv5_block3_3_bn (BatchNo  (None, 7, 7, 2048)           8192      ['conv5_block3_3_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " conv5_block3_add (Add)      (None, 7, 7, 2048)           0         ['conv5_block2_out[0][0]',    \n",
      "                                                                     'conv5_block3_3_bn[0][0]']   \n",
      "                                                                                                  \n",
      " conv5_block3_out (Activati  (None, 7, 7, 2048)           0         ['conv5_block3_add[0][0]']    \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " global_average_pooling2d (  (None, 2048)                 0         ['conv5_block3_out[0][0]']    \n",
      " GlobalAveragePooling2D)                                                                          \n",
      "                                                                                                  \n",
      " dense_8 (Dense)             (None, 128)                  262272    ['global_average_pooling2d[0][\n",
      "                                                                    0]']                          \n",
      "                                                                                                  \n",
      " dropout_4 (Dropout)         (None, 128)                  0         ['dense_8[0][0]']             \n",
      "                                                                                                  \n",
      " dense_9 (Dense)             (None, 1)                    129       ['dropout_4[0][0]']           \n",
      "                                                                                                  \n",
      "==================================================================================================\n",
      "Total params: 23850113 (90.98 MB)\n",
      "Trainable params: 262401 (1.00 MB)\n",
      "Non-trainable params: 23587712 (89.98 MB)\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "def create_resnet50_model(input_shape=(224, 224, 3)):\n",
    "    base_model = ResNet50(weights='imagenet', include_top=False, input_shape=input_shape)\n",
    "    x = base_model.output\n",
    "    x = GlobalAveragePooling2D()(x)\n",
    "    x = Dense(128, activation='relu')(x)\n",
    "    x = Dropout(0.5)(x)\n",
    "    predictions = Dense(1, activation='sigmoid')(x)\n",
    "    model = Model(inputs=base_model.input, outputs=predictions)\n",
    "\n",
    "    # Freeze the base model layers\n",
    "    for layer in base_model.layers:\n",
    "        layer.trainable = False\n",
    "\n",
    "    model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])\n",
    "    return model\n",
    "\n",
    "resnet50_model = create_resnet50_model()\n",
    "resnet50_model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d66e95e0-2d71-4e95-bca6-ab1cc895d0bf",
   "metadata": {
    "tags": []
   },
   "source": [
    "This block trains the fine-tuned ResNet50 model using the training data generator and validates it using the test data generator for 3 epochs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "cd951348-1eee-4460-a093-4259d9c73d03",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/3\n",
      "74/74 [==============================] - 470s 6s/step - loss: -32.8188 - accuracy: 0.4778 - val_loss: -78.0321 - val_accuracy: 0.4873\n",
      "Epoch 2/3\n",
      "74/74 [==============================] - 473s 6s/step - loss: -159.7166 - accuracy: 0.4808 - val_loss: -257.5944 - val_accuracy: 0.4873\n",
      "Epoch 3/3\n",
      "74/74 [==============================] - 470s 6s/step - loss: -400.7887 - accuracy: 0.4808 - val_loss: -557.3835 - val_accuracy: 0.4873\n"
     ]
    }
   ],
   "source": [
    "history_resnet50 = resnet50_model.fit(train_generator, validation_data=test_generator, epochs=3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0dd83601-5dde-4c41-acad-4654b47b0cc1",
   "metadata": {
    "tags": []
   },
   "source": [
    "This block imports ReduceLROnPlateau and EarlyStopping callbacks from TensorFlow Keras. These callbacks help in adjusting the learning rate and stopping the training early if the performance does not improve.\n",
    "def fine_tune_resnet50_model(model, unfreeze_layers=10):: Defines a function named fine_tune_resnet50_model that takes a model and the number of layers to unfreeze as inputs.\n",
    "for layer in model.layers[-unfreeze_layers:]: layer.trainable = True: Unfreezes the last unfreeze_layers layers of the model, allowing them to be trained.\n",
    "model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy']): Compiles the model with the Adam optimizer, binary cross-entropy loss function, and accuracy metric.\n",
    "return model: Returns the fine-tuned model.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "bd1c4c09-2d14-47c2-ba97-51d0b0cbc6d3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from tensorflow.keras.callbacks import ReduceLROnPlateau, EarlyStopping\n",
    "\n",
    "# Fine-tuning ResNet-50 model\n",
    "def fine_tune_resnet50_model(model, unfreeze_layers=10):\n",
    "    # Unfreeze the last `unfreeze_layers` layers of the base model\n",
    "    for layer in model.layers[-unfreeze_layers:]:\n",
    "        layer.trainable = True\n",
    "\n",
    "    model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])\n",
    "    return model\n",
    "\n",
    "fine_tuned_resnet50_model = fine_tune_resnet50_model(resnet50_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "517534e3-42e4-4431-b087-725d90e0b0b6",
   "metadata": {
    "tags": []
   },
   "source": [
    "ReduceLROnPlateau Callback\n",
    "\n",
    "reduce_lr = ReduceLROnPlateau(monitor='val_loss', factor=0.2, patience=3, min_lr=1e-6):\n",
    "monitor='val_loss': This parameter specifies that the callback should monitor the validation loss during training.\n",
    "factor=0.2: When triggered, the learning rate will be reduced by a factor of 0.2.\n",
    "patience=3: The callback will wait for 3 epochs with no improvement in the monitored quantity (validation loss) before reducing the learning rate.\n",
    "min_lr=1e-6: The learning rate will not be reduced below this minimum threshold.\n",
    "EarlyStopping Callback\n",
    "\n",
    "early_stopping = EarlyStopping(monitor='val_loss', patience=5, restore_best_weights=True):\n",
    "monitor='val_loss': This parameter specifies that the callback should monitor the validation loss during training.\n",
    "patience=5: The callback will wait for 5 epochs with no improvement in the monitored quantity (validation loss) before stopping the training.\n",
    "restore_best_weights=True: Once training is stopped, the model weights will be restored to the state of the best epoch (i.e., the epoch with the lowest validation loss).\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "e57d8e84-4074-485f-b337-9d09a2da2f21",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "reduce_lr = ReduceLROnPlateau(monitor='val_loss', factor=0.2, patience=3, min_lr=1e-6)\n",
    "early_stopping = EarlyStopping(monitor='val_loss', patience=5, restore_best_weights=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "13223001-921b-4a59-85e4-05c132ea6f7c",
   "metadata": {
    "tags": []
   },
   "source": [
    "1. Training the Model\n",
    "\n",
    "history_fine_tuned_resnet50: This variable stores the history of the training process, including loss and accuracy metrics for each epoch.\n",
    "fine_tuned_resnet50_model.fit(): This method trains the fine-tuned ResNet-50 model.\n",
    "2. Parameters\n",
    "\n",
    "train_generator: This parameter is the training data generator that provides batches of augmented training images.\n",
    "validation_data=test_generator: This parameter specifies the validation data generator that provides batches of augmented validation images.\n",
    "epochs=5: This parameter sets the number of epochs to 5, meaning the model will be trained for 5 complete passes over the entire training dataset.\n",
    "callbacks=[reduce_lr, early_stopping]: This parameter specifies a list of callbacks to be used during training. In this case, the callbacks are reduce_lr and early_stopping.\n",
    "3. Callbacks\n",
    "\n",
    "ReduceLROnPlateau: This callback monitors the validation loss and reduces the learning rate by a factor of 0.2 if there is no improvement for 3 consecutive epochs, with a minimum learning rate of 0.1×10 ^−6\n",
    "EarlyStopping: This callback monitors the validation loss and stops the training if there is no improvement for 5 consecutive epochs. It also restores the model weights to those of the epoch with the best validation loss."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "5289390e-0233-43c7-a737-3921a02f9c1d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/5\n",
      "74/74 [==============================] - 472s 6s/step - loss: -1473.1949 - accuracy: 0.4808 - val_loss: -1346.3750 - val_accuracy: 0.4873 - lr: 0.0010\n",
      "Epoch 2/5\n",
      "74/74 [==============================] - 473s 6s/step - loss: -2872.3188 - accuracy: 0.4808 - val_loss: -1919.8953 - val_accuracy: 0.4873 - lr: 0.0010\n",
      "Epoch 3/5\n",
      "74/74 [==============================] - 523s 7s/step - loss: -5120.5146 - accuracy: 0.4808 - val_loss: -4106.7607 - val_accuracy: 0.4873 - lr: 0.0010\n",
      "Epoch 4/5\n",
      "74/74 [==============================] - 474s 6s/step - loss: -8677.0537 - accuracy: 0.4808 - val_loss: -8183.1777 - val_accuracy: 0.4873 - lr: 0.0010\n",
      "Epoch 5/5\n",
      "74/74 [==============================] - 495s 7s/step - loss: -14018.0137 - accuracy: 0.4808 - val_loss: -17359.7539 - val_accuracy: 0.4873 - lr: 0.0010\n"
     ]
    }
   ],
   "source": [
    "history_fine_tuned_resnet50 = fine_tuned_resnet50_model.fit(\n",
    "    train_generator,\n",
    "    validation_data=test_generator,\n",
    "    epochs=5,\n",
    "    callbacks=[reduce_lr, early_stopping]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "77aaec6f-2bfe-4c04-914d-ccf6755d86bb",
   "metadata": {
    "tags": []
   },
   "source": [
    "from tensorflow.keras.applications import EfficientNetB0: This line imports the EfficientNetB0 class from the tensorflow.keras.applications module. EfficientNetB0 is a pre-trained convolutional neural network model available in TensorFlow Keras that is designed for image classification tasks."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "02ff55a1-3b5d-4663-8a7d-d524afaa2af7",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from tensorflow.keras.applications import EfficientNetB0"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb63c844-9bdc-4cd6-ac0f-4e685869b6e7",
   "metadata": {
    "tags": []
   },
   "source": [
    "Function Definition\n",
    "\n",
    "def create_efficientnet_model(input_shape=(224, 224, 3)):: Defines a function named create_efficientnet_model that takes an optional parameter input_shape, which defaults to (224, 224, 3). This represents the shape of the input images (224x224 pixels with 3 color channels - RGB).\n",
    "Base Model\n",
    "\n",
    "base_model = EfficientNetB0(weights='imagenet', include_top=False, input_shape=input_shape): Loads the EfficientNetB0 model with weights pre-trained on ImageNet and removes the top layers (fully connected layers). This allows for customization of the classification layers.\n",
    "Adding Custom Layers\n",
    "\n",
    "x = base_model.output: Retrieves the output of the base EfficientNetB0 model.\n",
    "x = GlobalAveragePooling2D()(x): Adds a global average pooling layer to reduce the spatial dimensions of the feature maps.\n",
    "x = Dense(128, activation='relu')(x): Adds a dense layer with 128 units and ReLU activation to learn complex features.\n",
    "x = Dropout(0.5)(x): Adds a dropout layer with a 50% dropout rate to prevent overfitting.\n",
    "predictions = Dense(1, activation='sigmoid')(x): Adds a dense layer with 1 unit and sigmoid activation for binary classification.\n",
    "Model Compilation\n",
    "\n",
    "model = Model(inputs=base_model.input, outputs=predictions): Creates a new model that includes both the base EfficientNetB0 layers and the custom classification layers.\n",
    "for layer in base_model.layers: layer.trainable = False: Freezes the base EfficientNetB0 layers to prevent them from being retrained during the initial training phase.\n",
    "model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy']): Compiles the model with the Adam optimizer, binary cross-entropy loss function, and accuracy metric.\n",
    "Model Summary\n",
    "\n",
    "efficientnet_model.summary(): Prints a summary of the model architecture, showing the layers, output shapes, and the number of parameters."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "c44997b8-dd15-4a9b-ad8d-1c8ef74a4f7f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Downloading data from https://storage.googleapis.com/keras-applications/efficientnetb0_notop.h5\n",
      "16705208/16705208 [==============================] - 0s 0us/step\n",
      "Model: \"model_1\"\n",
      "__________________________________________________________________________________________________\n",
      " Layer (type)                Output Shape                 Param #   Connected to                  \n",
      "==================================================================================================\n",
      " input_2 (InputLayer)        [(None, 224, 224, 3)]        0         []                            \n",
      "                                                                                                  \n",
      " rescaling (Rescaling)       (None, 224, 224, 3)          0         ['input_2[0][0]']             \n",
      "                                                                                                  \n",
      " normalization (Normalizati  (None, 224, 224, 3)          7         ['rescaling[0][0]']           \n",
      " on)                                                                                              \n",
      "                                                                                                  \n",
      " rescaling_1 (Rescaling)     (None, 224, 224, 3)          0         ['normalization[0][0]']       \n",
      "                                                                                                  \n",
      " stem_conv_pad (ZeroPadding  (None, 225, 225, 3)          0         ['rescaling_1[0][0]']         \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " stem_conv (Conv2D)          (None, 112, 112, 32)         864       ['stem_conv_pad[0][0]']       \n",
      "                                                                                                  \n",
      " stem_bn (BatchNormalizatio  (None, 112, 112, 32)         128       ['stem_conv[0][0]']           \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " stem_activation (Activatio  (None, 112, 112, 32)         0         ['stem_bn[0][0]']             \n",
      " n)                                                                                               \n",
      "                                                                                                  \n",
      " block1a_dwconv (DepthwiseC  (None, 112, 112, 32)         288       ['stem_activation[0][0]']     \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block1a_bn (BatchNormaliza  (None, 112, 112, 32)         128       ['block1a_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block1a_activation (Activa  (None, 112, 112, 32)         0         ['block1a_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block1a_se_squeeze (Global  (None, 32)                   0         ['block1a_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block1a_se_reshape (Reshap  (None, 1, 1, 32)             0         ['block1a_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block1a_se_reduce (Conv2D)  (None, 1, 1, 8)              264       ['block1a_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block1a_se_expand (Conv2D)  (None, 1, 1, 32)             288       ['block1a_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block1a_se_excite (Multipl  (None, 112, 112, 32)         0         ['block1a_activation[0][0]',  \n",
      " y)                                                                  'block1a_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block1a_project_conv (Conv  (None, 112, 112, 16)         512       ['block1a_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block1a_project_bn (BatchN  (None, 112, 112, 16)         64        ['block1a_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block2a_expand_conv (Conv2  (None, 112, 112, 96)         1536      ['block1a_project_bn[0][0]']  \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block2a_expand_bn (BatchNo  (None, 112, 112, 96)         384       ['block2a_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block2a_expand_activation   (None, 112, 112, 96)         0         ['block2a_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block2a_dwconv_pad (ZeroPa  (None, 113, 113, 96)         0         ['block2a_expand_activation[0]\n",
      " dding2D)                                                           [0]']                         \n",
      "                                                                                                  \n",
      " block2a_dwconv (DepthwiseC  (None, 56, 56, 96)           864       ['block2a_dwconv_pad[0][0]']  \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block2a_bn (BatchNormaliza  (None, 56, 56, 96)           384       ['block2a_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block2a_activation (Activa  (None, 56, 56, 96)           0         ['block2a_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block2a_se_squeeze (Global  (None, 96)                   0         ['block2a_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block2a_se_reshape (Reshap  (None, 1, 1, 96)             0         ['block2a_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block2a_se_reduce (Conv2D)  (None, 1, 1, 4)              388       ['block2a_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block2a_se_expand (Conv2D)  (None, 1, 1, 96)             480       ['block2a_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block2a_se_excite (Multipl  (None, 56, 56, 96)           0         ['block2a_activation[0][0]',  \n",
      " y)                                                                  'block2a_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block2a_project_conv (Conv  (None, 56, 56, 24)           2304      ['block2a_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block2a_project_bn (BatchN  (None, 56, 56, 24)           96        ['block2a_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block2b_expand_conv (Conv2  (None, 56, 56, 144)          3456      ['block2a_project_bn[0][0]']  \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block2b_expand_bn (BatchNo  (None, 56, 56, 144)          576       ['block2b_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block2b_expand_activation   (None, 56, 56, 144)          0         ['block2b_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block2b_dwconv (DepthwiseC  (None, 56, 56, 144)          1296      ['block2b_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block2b_bn (BatchNormaliza  (None, 56, 56, 144)          576       ['block2b_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block2b_activation (Activa  (None, 56, 56, 144)          0         ['block2b_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block2b_se_squeeze (Global  (None, 144)                  0         ['block2b_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block2b_se_reshape (Reshap  (None, 1, 1, 144)            0         ['block2b_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block2b_se_reduce (Conv2D)  (None, 1, 1, 6)              870       ['block2b_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block2b_se_expand (Conv2D)  (None, 1, 1, 144)            1008      ['block2b_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block2b_se_excite (Multipl  (None, 56, 56, 144)          0         ['block2b_activation[0][0]',  \n",
      " y)                                                                  'block2b_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block2b_project_conv (Conv  (None, 56, 56, 24)           3456      ['block2b_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block2b_project_bn (BatchN  (None, 56, 56, 24)           96        ['block2b_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block2b_drop (Dropout)      (None, 56, 56, 24)           0         ['block2b_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block2b_add (Add)           (None, 56, 56, 24)           0         ['block2b_drop[0][0]',        \n",
      "                                                                     'block2a_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block3a_expand_conv (Conv2  (None, 56, 56, 144)          3456      ['block2b_add[0][0]']         \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block3a_expand_bn (BatchNo  (None, 56, 56, 144)          576       ['block3a_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block3a_expand_activation   (None, 56, 56, 144)          0         ['block3a_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block3a_dwconv_pad (ZeroPa  (None, 59, 59, 144)          0         ['block3a_expand_activation[0]\n",
      " dding2D)                                                           [0]']                         \n",
      "                                                                                                  \n",
      " block3a_dwconv (DepthwiseC  (None, 28, 28, 144)          3600      ['block3a_dwconv_pad[0][0]']  \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block3a_bn (BatchNormaliza  (None, 28, 28, 144)          576       ['block3a_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block3a_activation (Activa  (None, 28, 28, 144)          0         ['block3a_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block3a_se_squeeze (Global  (None, 144)                  0         ['block3a_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block3a_se_reshape (Reshap  (None, 1, 1, 144)            0         ['block3a_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block3a_se_reduce (Conv2D)  (None, 1, 1, 6)              870       ['block3a_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block3a_se_expand (Conv2D)  (None, 1, 1, 144)            1008      ['block3a_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block3a_se_excite (Multipl  (None, 28, 28, 144)          0         ['block3a_activation[0][0]',  \n",
      " y)                                                                  'block3a_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block3a_project_conv (Conv  (None, 28, 28, 40)           5760      ['block3a_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block3a_project_bn (BatchN  (None, 28, 28, 40)           160       ['block3a_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block3b_expand_conv (Conv2  (None, 28, 28, 240)          9600      ['block3a_project_bn[0][0]']  \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block3b_expand_bn (BatchNo  (None, 28, 28, 240)          960       ['block3b_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block3b_expand_activation   (None, 28, 28, 240)          0         ['block3b_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block3b_dwconv (DepthwiseC  (None, 28, 28, 240)          6000      ['block3b_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block3b_bn (BatchNormaliza  (None, 28, 28, 240)          960       ['block3b_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block3b_activation (Activa  (None, 28, 28, 240)          0         ['block3b_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block3b_se_squeeze (Global  (None, 240)                  0         ['block3b_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block3b_se_reshape (Reshap  (None, 1, 1, 240)            0         ['block3b_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block3b_se_reduce (Conv2D)  (None, 1, 1, 10)             2410      ['block3b_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block3b_se_expand (Conv2D)  (None, 1, 1, 240)            2640      ['block3b_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block3b_se_excite (Multipl  (None, 28, 28, 240)          0         ['block3b_activation[0][0]',  \n",
      " y)                                                                  'block3b_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block3b_project_conv (Conv  (None, 28, 28, 40)           9600      ['block3b_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block3b_project_bn (BatchN  (None, 28, 28, 40)           160       ['block3b_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block3b_drop (Dropout)      (None, 28, 28, 40)           0         ['block3b_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block3b_add (Add)           (None, 28, 28, 40)           0         ['block3b_drop[0][0]',        \n",
      "                                                                     'block3a_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block4a_expand_conv (Conv2  (None, 28, 28, 240)          9600      ['block3b_add[0][0]']         \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block4a_expand_bn (BatchNo  (None, 28, 28, 240)          960       ['block4a_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block4a_expand_activation   (None, 28, 28, 240)          0         ['block4a_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block4a_dwconv_pad (ZeroPa  (None, 29, 29, 240)          0         ['block4a_expand_activation[0]\n",
      " dding2D)                                                           [0]']                         \n",
      "                                                                                                  \n",
      " block4a_dwconv (DepthwiseC  (None, 14, 14, 240)          2160      ['block4a_dwconv_pad[0][0]']  \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block4a_bn (BatchNormaliza  (None, 14, 14, 240)          960       ['block4a_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block4a_activation (Activa  (None, 14, 14, 240)          0         ['block4a_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block4a_se_squeeze (Global  (None, 240)                  0         ['block4a_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block4a_se_reshape (Reshap  (None, 1, 1, 240)            0         ['block4a_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block4a_se_reduce (Conv2D)  (None, 1, 1, 10)             2410      ['block4a_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block4a_se_expand (Conv2D)  (None, 1, 1, 240)            2640      ['block4a_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block4a_se_excite (Multipl  (None, 14, 14, 240)          0         ['block4a_activation[0][0]',  \n",
      " y)                                                                  'block4a_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block4a_project_conv (Conv  (None, 14, 14, 80)           19200     ['block4a_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block4a_project_bn (BatchN  (None, 14, 14, 80)           320       ['block4a_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block4b_expand_conv (Conv2  (None, 14, 14, 480)          38400     ['block4a_project_bn[0][0]']  \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block4b_expand_bn (BatchNo  (None, 14, 14, 480)          1920      ['block4b_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block4b_expand_activation   (None, 14, 14, 480)          0         ['block4b_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block4b_dwconv (DepthwiseC  (None, 14, 14, 480)          4320      ['block4b_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block4b_bn (BatchNormaliza  (None, 14, 14, 480)          1920      ['block4b_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block4b_activation (Activa  (None, 14, 14, 480)          0         ['block4b_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block4b_se_squeeze (Global  (None, 480)                  0         ['block4b_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block4b_se_reshape (Reshap  (None, 1, 1, 480)            0         ['block4b_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block4b_se_reduce (Conv2D)  (None, 1, 1, 20)             9620      ['block4b_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block4b_se_expand (Conv2D)  (None, 1, 1, 480)            10080     ['block4b_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block4b_se_excite (Multipl  (None, 14, 14, 480)          0         ['block4b_activation[0][0]',  \n",
      " y)                                                                  'block4b_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block4b_project_conv (Conv  (None, 14, 14, 80)           38400     ['block4b_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block4b_project_bn (BatchN  (None, 14, 14, 80)           320       ['block4b_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block4b_drop (Dropout)      (None, 14, 14, 80)           0         ['block4b_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block4b_add (Add)           (None, 14, 14, 80)           0         ['block4b_drop[0][0]',        \n",
      "                                                                     'block4a_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block4c_expand_conv (Conv2  (None, 14, 14, 480)          38400     ['block4b_add[0][0]']         \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block4c_expand_bn (BatchNo  (None, 14, 14, 480)          1920      ['block4c_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block4c_expand_activation   (None, 14, 14, 480)          0         ['block4c_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block4c_dwconv (DepthwiseC  (None, 14, 14, 480)          4320      ['block4c_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block4c_bn (BatchNormaliza  (None, 14, 14, 480)          1920      ['block4c_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block4c_activation (Activa  (None, 14, 14, 480)          0         ['block4c_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block4c_se_squeeze (Global  (None, 480)                  0         ['block4c_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block4c_se_reshape (Reshap  (None, 1, 1, 480)            0         ['block4c_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block4c_se_reduce (Conv2D)  (None, 1, 1, 20)             9620      ['block4c_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block4c_se_expand (Conv2D)  (None, 1, 1, 480)            10080     ['block4c_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block4c_se_excite (Multipl  (None, 14, 14, 480)          0         ['block4c_activation[0][0]',  \n",
      " y)                                                                  'block4c_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block4c_project_conv (Conv  (None, 14, 14, 80)           38400     ['block4c_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block4c_project_bn (BatchN  (None, 14, 14, 80)           320       ['block4c_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block4c_drop (Dropout)      (None, 14, 14, 80)           0         ['block4c_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block4c_add (Add)           (None, 14, 14, 80)           0         ['block4c_drop[0][0]',        \n",
      "                                                                     'block4b_add[0][0]']         \n",
      "                                                                                                  \n",
      " block5a_expand_conv (Conv2  (None, 14, 14, 480)          38400     ['block4c_add[0][0]']         \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block5a_expand_bn (BatchNo  (None, 14, 14, 480)          1920      ['block5a_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block5a_expand_activation   (None, 14, 14, 480)          0         ['block5a_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block5a_dwconv (DepthwiseC  (None, 14, 14, 480)          12000     ['block5a_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block5a_bn (BatchNormaliza  (None, 14, 14, 480)          1920      ['block5a_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block5a_activation (Activa  (None, 14, 14, 480)          0         ['block5a_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block5a_se_squeeze (Global  (None, 480)                  0         ['block5a_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block5a_se_reshape (Reshap  (None, 1, 1, 480)            0         ['block5a_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block5a_se_reduce (Conv2D)  (None, 1, 1, 20)             9620      ['block5a_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block5a_se_expand (Conv2D)  (None, 1, 1, 480)            10080     ['block5a_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block5a_se_excite (Multipl  (None, 14, 14, 480)          0         ['block5a_activation[0][0]',  \n",
      " y)                                                                  'block5a_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block5a_project_conv (Conv  (None, 14, 14, 112)          53760     ['block5a_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block5a_project_bn (BatchN  (None, 14, 14, 112)          448       ['block5a_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block5b_expand_conv (Conv2  (None, 14, 14, 672)          75264     ['block5a_project_bn[0][0]']  \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block5b_expand_bn (BatchNo  (None, 14, 14, 672)          2688      ['block5b_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block5b_expand_activation   (None, 14, 14, 672)          0         ['block5b_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block5b_dwconv (DepthwiseC  (None, 14, 14, 672)          16800     ['block5b_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block5b_bn (BatchNormaliza  (None, 14, 14, 672)          2688      ['block5b_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block5b_activation (Activa  (None, 14, 14, 672)          0         ['block5b_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block5b_se_squeeze (Global  (None, 672)                  0         ['block5b_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block5b_se_reshape (Reshap  (None, 1, 1, 672)            0         ['block5b_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block5b_se_reduce (Conv2D)  (None, 1, 1, 28)             18844     ['block5b_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block5b_se_expand (Conv2D)  (None, 1, 1, 672)            19488     ['block5b_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block5b_se_excite (Multipl  (None, 14, 14, 672)          0         ['block5b_activation[0][0]',  \n",
      " y)                                                                  'block5b_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block5b_project_conv (Conv  (None, 14, 14, 112)          75264     ['block5b_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block5b_project_bn (BatchN  (None, 14, 14, 112)          448       ['block5b_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block5b_drop (Dropout)      (None, 14, 14, 112)          0         ['block5b_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block5b_add (Add)           (None, 14, 14, 112)          0         ['block5b_drop[0][0]',        \n",
      "                                                                     'block5a_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block5c_expand_conv (Conv2  (None, 14, 14, 672)          75264     ['block5b_add[0][0]']         \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block5c_expand_bn (BatchNo  (None, 14, 14, 672)          2688      ['block5c_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block5c_expand_activation   (None, 14, 14, 672)          0         ['block5c_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block5c_dwconv (DepthwiseC  (None, 14, 14, 672)          16800     ['block5c_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block5c_bn (BatchNormaliza  (None, 14, 14, 672)          2688      ['block5c_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block5c_activation (Activa  (None, 14, 14, 672)          0         ['block5c_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block5c_se_squeeze (Global  (None, 672)                  0         ['block5c_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block5c_se_reshape (Reshap  (None, 1, 1, 672)            0         ['block5c_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block5c_se_reduce (Conv2D)  (None, 1, 1, 28)             18844     ['block5c_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block5c_se_expand (Conv2D)  (None, 1, 1, 672)            19488     ['block5c_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block5c_se_excite (Multipl  (None, 14, 14, 672)          0         ['block5c_activation[0][0]',  \n",
      " y)                                                                  'block5c_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block5c_project_conv (Conv  (None, 14, 14, 112)          75264     ['block5c_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block5c_project_bn (BatchN  (None, 14, 14, 112)          448       ['block5c_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block5c_drop (Dropout)      (None, 14, 14, 112)          0         ['block5c_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block5c_add (Add)           (None, 14, 14, 112)          0         ['block5c_drop[0][0]',        \n",
      "                                                                     'block5b_add[0][0]']         \n",
      "                                                                                                  \n",
      " block6a_expand_conv (Conv2  (None, 14, 14, 672)          75264     ['block5c_add[0][0]']         \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block6a_expand_bn (BatchNo  (None, 14, 14, 672)          2688      ['block6a_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block6a_expand_activation   (None, 14, 14, 672)          0         ['block6a_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block6a_dwconv_pad (ZeroPa  (None, 17, 17, 672)          0         ['block6a_expand_activation[0]\n",
      " dding2D)                                                           [0]']                         \n",
      "                                                                                                  \n",
      " block6a_dwconv (DepthwiseC  (None, 7, 7, 672)            16800     ['block6a_dwconv_pad[0][0]']  \n",
      " onv2D)                                                                                           \n",
      "                                                                                                  \n",
      " block6a_bn (BatchNormaliza  (None, 7, 7, 672)            2688      ['block6a_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block6a_activation (Activa  (None, 7, 7, 672)            0         ['block6a_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block6a_se_squeeze (Global  (None, 672)                  0         ['block6a_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block6a_se_reshape (Reshap  (None, 1, 1, 672)            0         ['block6a_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block6a_se_reduce (Conv2D)  (None, 1, 1, 28)             18844     ['block6a_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block6a_se_expand (Conv2D)  (None, 1, 1, 672)            19488     ['block6a_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block6a_se_excite (Multipl  (None, 7, 7, 672)            0         ['block6a_activation[0][0]',  \n",
      " y)                                                                  'block6a_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block6a_project_conv (Conv  (None, 7, 7, 192)            129024    ['block6a_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block6a_project_bn (BatchN  (None, 7, 7, 192)            768       ['block6a_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block6b_expand_conv (Conv2  (None, 7, 7, 1152)           221184    ['block6a_project_bn[0][0]']  \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block6b_expand_bn (BatchNo  (None, 7, 7, 1152)           4608      ['block6b_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block6b_expand_activation   (None, 7, 7, 1152)           0         ['block6b_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block6b_dwconv (DepthwiseC  (None, 7, 7, 1152)           28800     ['block6b_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block6b_bn (BatchNormaliza  (None, 7, 7, 1152)           4608      ['block6b_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block6b_activation (Activa  (None, 7, 7, 1152)           0         ['block6b_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block6b_se_squeeze (Global  (None, 1152)                 0         ['block6b_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block6b_se_reshape (Reshap  (None, 1, 1, 1152)           0         ['block6b_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block6b_se_reduce (Conv2D)  (None, 1, 1, 48)             55344     ['block6b_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block6b_se_expand (Conv2D)  (None, 1, 1, 1152)           56448     ['block6b_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block6b_se_excite (Multipl  (None, 7, 7, 1152)           0         ['block6b_activation[0][0]',  \n",
      " y)                                                                  'block6b_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block6b_project_conv (Conv  (None, 7, 7, 192)            221184    ['block6b_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block6b_project_bn (BatchN  (None, 7, 7, 192)            768       ['block6b_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block6b_drop (Dropout)      (None, 7, 7, 192)            0         ['block6b_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block6b_add (Add)           (None, 7, 7, 192)            0         ['block6b_drop[0][0]',        \n",
      "                                                                     'block6a_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block6c_expand_conv (Conv2  (None, 7, 7, 1152)           221184    ['block6b_add[0][0]']         \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block6c_expand_bn (BatchNo  (None, 7, 7, 1152)           4608      ['block6c_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block6c_expand_activation   (None, 7, 7, 1152)           0         ['block6c_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block6c_dwconv (DepthwiseC  (None, 7, 7, 1152)           28800     ['block6c_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block6c_bn (BatchNormaliza  (None, 7, 7, 1152)           4608      ['block6c_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block6c_activation (Activa  (None, 7, 7, 1152)           0         ['block6c_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block6c_se_squeeze (Global  (None, 1152)                 0         ['block6c_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block6c_se_reshape (Reshap  (None, 1, 1, 1152)           0         ['block6c_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block6c_se_reduce (Conv2D)  (None, 1, 1, 48)             55344     ['block6c_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block6c_se_expand (Conv2D)  (None, 1, 1, 1152)           56448     ['block6c_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block6c_se_excite (Multipl  (None, 7, 7, 1152)           0         ['block6c_activation[0][0]',  \n",
      " y)                                                                  'block6c_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block6c_project_conv (Conv  (None, 7, 7, 192)            221184    ['block6c_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block6c_project_bn (BatchN  (None, 7, 7, 192)            768       ['block6c_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block6c_drop (Dropout)      (None, 7, 7, 192)            0         ['block6c_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block6c_add (Add)           (None, 7, 7, 192)            0         ['block6c_drop[0][0]',        \n",
      "                                                                     'block6b_add[0][0]']         \n",
      "                                                                                                  \n",
      " block6d_expand_conv (Conv2  (None, 7, 7, 1152)           221184    ['block6c_add[0][0]']         \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block6d_expand_bn (BatchNo  (None, 7, 7, 1152)           4608      ['block6d_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block6d_expand_activation   (None, 7, 7, 1152)           0         ['block6d_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block6d_dwconv (DepthwiseC  (None, 7, 7, 1152)           28800     ['block6d_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block6d_bn (BatchNormaliza  (None, 7, 7, 1152)           4608      ['block6d_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block6d_activation (Activa  (None, 7, 7, 1152)           0         ['block6d_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block6d_se_squeeze (Global  (None, 1152)                 0         ['block6d_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block6d_se_reshape (Reshap  (None, 1, 1, 1152)           0         ['block6d_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block6d_se_reduce (Conv2D)  (None, 1, 1, 48)             55344     ['block6d_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block6d_se_expand (Conv2D)  (None, 1, 1, 1152)           56448     ['block6d_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block6d_se_excite (Multipl  (None, 7, 7, 1152)           0         ['block6d_activation[0][0]',  \n",
      " y)                                                                  'block6d_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block6d_project_conv (Conv  (None, 7, 7, 192)            221184    ['block6d_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block6d_project_bn (BatchN  (None, 7, 7, 192)            768       ['block6d_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " block6d_drop (Dropout)      (None, 7, 7, 192)            0         ['block6d_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " block6d_add (Add)           (None, 7, 7, 192)            0         ['block6d_drop[0][0]',        \n",
      "                                                                     'block6c_add[0][0]']         \n",
      "                                                                                                  \n",
      " block7a_expand_conv (Conv2  (None, 7, 7, 1152)           221184    ['block6d_add[0][0]']         \n",
      " D)                                                                                               \n",
      "                                                                                                  \n",
      " block7a_expand_bn (BatchNo  (None, 7, 7, 1152)           4608      ['block7a_expand_conv[0][0]'] \n",
      " rmalization)                                                                                     \n",
      "                                                                                                  \n",
      " block7a_expand_activation   (None, 7, 7, 1152)           0         ['block7a_expand_bn[0][0]']   \n",
      " (Activation)                                                                                     \n",
      "                                                                                                  \n",
      " block7a_dwconv (DepthwiseC  (None, 7, 7, 1152)           10368     ['block7a_expand_activation[0]\n",
      " onv2D)                                                             [0]']                         \n",
      "                                                                                                  \n",
      " block7a_bn (BatchNormaliza  (None, 7, 7, 1152)           4608      ['block7a_dwconv[0][0]']      \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block7a_activation (Activa  (None, 7, 7, 1152)           0         ['block7a_bn[0][0]']          \n",
      " tion)                                                                                            \n",
      "                                                                                                  \n",
      " block7a_se_squeeze (Global  (None, 1152)                 0         ['block7a_activation[0][0]']  \n",
      " AveragePooling2D)                                                                                \n",
      "                                                                                                  \n",
      " block7a_se_reshape (Reshap  (None, 1, 1, 1152)           0         ['block7a_se_squeeze[0][0]']  \n",
      " e)                                                                                               \n",
      "                                                                                                  \n",
      " block7a_se_reduce (Conv2D)  (None, 1, 1, 48)             55344     ['block7a_se_reshape[0][0]']  \n",
      "                                                                                                  \n",
      " block7a_se_expand (Conv2D)  (None, 1, 1, 1152)           56448     ['block7a_se_reduce[0][0]']   \n",
      "                                                                                                  \n",
      " block7a_se_excite (Multipl  (None, 7, 7, 1152)           0         ['block7a_activation[0][0]',  \n",
      " y)                                                                  'block7a_se_expand[0][0]']   \n",
      "                                                                                                  \n",
      " block7a_project_conv (Conv  (None, 7, 7, 320)            368640    ['block7a_se_excite[0][0]']   \n",
      " 2D)                                                                                              \n",
      "                                                                                                  \n",
      " block7a_project_bn (BatchN  (None, 7, 7, 320)            1280      ['block7a_project_conv[0][0]']\n",
      " ormalization)                                                                                    \n",
      "                                                                                                  \n",
      " top_conv (Conv2D)           (None, 7, 7, 1280)           409600    ['block7a_project_bn[0][0]']  \n",
      "                                                                                                  \n",
      " top_bn (BatchNormalization  (None, 7, 7, 1280)           5120      ['top_conv[0][0]']            \n",
      " )                                                                                                \n",
      "                                                                                                  \n",
      " top_activation (Activation  (None, 7, 7, 1280)           0         ['top_bn[0][0]']              \n",
      " )                                                                                                \n",
      "                                                                                                  \n",
      " global_average_pooling2d_1  (None, 1280)                 0         ['top_activation[0][0]']      \n",
      "  (GlobalAveragePooling2D)                                                                        \n",
      "                                                                                                  \n",
      " dense_10 (Dense)            (None, 128)                  163968    ['global_average_pooling2d_1[0\n",
      "                                                                    ][0]']                        \n",
      "                                                                                                  \n",
      " dropout_5 (Dropout)         (None, 128)                  0         ['dense_10[0][0]']            \n",
      "                                                                                                  \n",
      " dense_11 (Dense)            (None, 1)                    129       ['dropout_5[0][0]']           \n",
      "                                                                                                  \n",
      "==================================================================================================\n",
      "Total params: 4213668 (16.07 MB)\n",
      "Trainable params: 164097 (641.00 KB)\n",
      "Non-trainable params: 4049571 (15.45 MB)\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "def create_efficientnet_model(input_shape=(224, 224, 3)):\n",
    "    base_model = EfficientNetB0(weights='imagenet', include_top=False, input_shape=input_shape)\n",
    "    x = base_model.output\n",
    "    x = GlobalAveragePooling2D()(x)\n",
    "    x = Dense(128, activation='relu')(x)\n",
    "    x = Dropout(0.5)(x)\n",
    "    predictions = Dense(1, activation='sigmoid')(x)\n",
    "    model = Model(inputs=base_model.input, outputs=predictions)\n",
    "\n",
    "    # Freeze the base model layers\n",
    "    for layer in base_model.layers:\n",
    "        layer.trainable = False\n",
    "\n",
    "    model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])\n",
    "    return model\n",
    "\n",
    "efficientnet_model = create_efficientnet_model()\n",
    "efficientnet_model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "382d596a-ea78-44cb-9113-25dc3b5ded2a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "9eb4cfba-d04d-4639-8a2e-a4bdfa4a0515",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/3\n",
      "74/74 [==============================] - 277s 4s/step - loss: -28.9342 - accuracy: 0.4782 - val_loss: -74.2481 - val_accuracy: 0.4873\n",
      "Epoch 2/3\n",
      "74/74 [==============================] - 260s 4s/step - loss: -156.1465 - accuracy: 0.4808 - val_loss: -265.5513 - val_accuracy: 0.4873\n",
      "Epoch 3/3\n",
      "74/74 [==============================] - 303s 4s/step - loss: -411.2669 - accuracy: 0.4808 - val_loss: -588.5508 - val_accuracy: 0.4873\n"
     ]
    }
   ],
   "source": [
    "history_efficientnet = efficientnet_model.fit(train_generator, validation_data=test_generator, epochs=3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "131152c8-3955-4876-a60d-1753f894460a",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "f0b5667b-6e5f-4dc4-9ef9-504aee5a0505",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "from sklearn.metrics import f1_score"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "93a23a90-d0d0-4439-83b7-0711400bc580",
   "metadata": {
    "tags": []
   },
   "source": [
    "import Accuracy metrics\n",
    "Function Definition:\n",
    "def get_predictions(model, data_generator):: Defines a function named get_predictions that takes two parameters:\n",
    "model: The trained machine learning model.\n",
    "data_generator: The data generator providing the input data for predictions.\n",
    "Making Predictions\n",
    "\n",
    "predictions = model.predict(data_generator): Uses the model to predict the output for the data provided by the data_generator. The predict method returns an array of probabilities.\n",
    "Thresholding Predictions\n",
    "\n",
    "return (predictions > 0.5).astype(int): Converts the predicted probabilities into binary class labels. If the probability is greater than 0.5, the prediction is classified as 1 (positive class); otherwise, it is classified as 0 (negative class). The astype(int) method ensures that the resulting array contains integer values.\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "3cd1e86e-f51a-4214-88a2-868e86b781c3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_predictions(model, data_generator):\n",
    "    predictions = model.predict(data_generator)\n",
    "    return (predictions > 0.5).astype(int)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "bd309faa-d937-487d-adbd-fb811c1e4df8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19/19 [==============================] - 22s 1s/step\n",
      "19/19 [==============================] - 85s 4s/step\n",
      "19/19 [==============================] - 51s 3s/step\n"
     ]
    }
   ],
   "source": [
    "baseline_preds = get_predictions(baseline_model, test_generator)\n",
    "resnet50_preds = get_predictions(fine_tuned_resnet50_model, test_generator)\n",
    "efficientnet_preds = get_predictions(efficientnet_model, test_generator)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ce18d844-fa80-4769-93af-51b6cb2d0a87",
   "metadata": {
    "tags": []
   },
   "source": [
    "Creating Ensemble Predictions\n",
    "\n",
    "ensemble_preds = np.round((baseline_preds + resnet50_preds + efficientnet_preds) / 3):\n",
    "baseline_preds, resnet50_preds, efficientnet_preds: These variables store the binary predictions (0 or 1) from the baseline model, the fine-tuned ResNet50 model, and the EfficientNet model, respectively.\n",
    "(baseline_preds + resnet50_preds + efficientnet_preds) / 3: This expression calculates the average of the predictions from the three models. Since the predictions are binary (0 or 1), this average will be a value between 0 and 1.\n",
    "np.round(...): The np.round function rounds the averaged predictions to the nearest integer (0 or 1). This step converts the averaged values back to binary predictions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "b32476e0-047a-4fb2-923f-c6fb205d6568",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "ensemble_preds = np.round((baseline_preds + resnet50_preds + efficientnet_preds) / 3)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eff0d6d9-0a8c-4213-99d1-3aa994034e8a",
   "metadata": {
    "tags": []
   },
   "source": [
    "Retrieving Test Labels\n",
    "\n",
    "test_labels = test_generator.classes: This line retrieves the true class labels for the test dataset from the test_generator. The classes attribute of the data generator returns an array of integer class labels corresponding to the images in the test set.\n",
    "Calculating the F1 Score\n",
    "\n",
    "f1 = f1_score(test_labels, ensemble_preds): This line calculates the F1 score for the ensemble model's predictions. The f1_score function from scikit-learn is used for this purpose. It takes two arguments:\n",
    "test_labels: The true class labels for the test dataset.\n",
    "ensemble_preds: The predicted class labels from the ensemble model.\n",
    "The F1 score is a measure of a model's accuracy on a dataset and is the harmonic mean of precision and recall. It is especially useful for imbalanced datasets.\n",
    "\n",
    "Printing the F1 Score\n",
    "\n",
    "print(f'Ensemble Model F1 Score: {f1}'): This line prints the F1 score of the ensemble model, formatted as a string. The f before the string denotes an f-string, which allows for embedding expressions inside string literals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "46fccf50-d1c2-4821-9526-80a819d7ef78",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ensemble Model F1 Score: 0.6552901023890785\n"
     ]
    }
   ],
   "source": [
    "test_labels = test_generator.classes\n",
    "f1 = f1_score(test_labels, ensemble_preds)\n",
    "print(f'Ensemble Model F1 Score: {f1}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e3df4f34-b943-46cf-851b-c371c84632b3",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}