From 24b33e91513139d183c908b57e01c3eb162e30d2 Mon Sep 17 00:00:00 2001 From: Karthik110505 Date: Thu, 23 May 2024 16:46:40 +0530 Subject: [PATCH] Adding Indian-Birds-Species-Image-Classification Project to Basic folder --- .../Images/CNN.png | Bin 0 -> 41856 bytes .../Images/DenseNet.png | Bin 0 -> 38373 bytes .../Images/Inception.png | Bin 0 -> 38020 bytes .../Images/MobileNet.png | Bin 0 -> 37421 bytes .../Images/ResNet.png | Bin 0 -> 41046 bytes .../Images/VGG16.png | Bin 0 -> 38790 bytes .../README.md | 123 + ...n-birds-species-image-classification.ipynb | 2139 +++++++++++++++++ 8 files changed, 2262 insertions(+) create mode 100644 Machine Learning and Data Science/Basic/Indian-Birds-Species-Image-Classification/Images/CNN.png create mode 100644 Machine Learning and Data Science/Basic/Indian-Birds-Species-Image-Classification/Images/DenseNet.png create mode 100644 Machine Learning and Data Science/Basic/Indian-Birds-Species-Image-Classification/Images/Inception.png create mode 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Various CNN architectures are explored to achieve high classification accuracy. + +# **🔴 Dataset:** +The dataset used for this project can be found at: [Indian Birds Dataset](https://www.kaggle.com/datasets/ichhadhari/indian-birds). It contains a collection of bird images categorized into different species, divided into training and validation sets. + +# **🔴 Description:** +This project focuses on implementing and comparing various deep learning models to classify bird species from images. The goal is to determine which model performs the best in terms of accuracy and generalization. + +# **🔴 What I Have Done:** +To develop the bird species classification model, the following steps were followed: + +1. Data exploration and preprocessing: + - Perform exploratory data analysis (EDA) on the dataset to gain insights. + - Preprocess the images by resizing and normalizing. + +2. CNN model: + - Implement a Convolutional Neural Network (CNN) model for image classification. + - Train the CNN model on the dataset and evaluate its performance. + - Calculate the training and validation accuracies of the CNN model. + +3. Pre-trained models: + - Implement various pre-trained models (VGG16, ResNet50, MobileNetV2, InceptionV3, DenseNet121) for transfer learning. + - Fine-tune the models on the dataset and evaluate their performance. + - Calculate the training and validation accuracies of each model. + +# **🔴 Models Used:** +The following models were used in this project: + +1. Convolutional Neural Network (CNN): + - Custom CNN architecture for image classification tasks. + - Provides a baseline for comparison. + +2. VGG16: + - Pre-trained on ImageNet. + - Fine-tuned for bird species classification. + +3. ResNet50: + - Pre-trained on ImageNet. + - Fine-tuned for bird species classification. + +4. MobileNetV2: + - Pre-trained on ImageNet. + - Fine-tuned for bird species classification. + +5. InceptionV3: + - Pre-trained on ImageNet. + - Fine-tuned for bird species classification. + +6. DenseNet121: + - Pre-trained on ImageNet. + - Fine-tuned for bird species classification. + +The DenseNet121 model was selected for its superior performance in terms of accuracy, making it the best choice for bird species classification. + +# **🔴 Libraries Needed:** +The following libraries are required for this project: + +- TensorFlow +- Keras +- OpenCV +- NumPy +- Matplotlib +- Pandas + +# **🔴 Visualization:** +1. CNN Performance +![CNN Performance](./Images/CNN.png) + +2. DenseNet Performance +![DenseNet Performance](./Images/DenseNet.png) + +3. Inception Performance +![Inception Performance](./Images/Inception.png) + +4. MobileNet Performance +![MobileNet Performance](./Images/MobileNet.png) + +5. ResNet Performance +![ResNet Performance](./Images/ResNet.png) + +6. VGG16 Performance +![VGG16 Performance](./Images/VGG16.png) + +# **🔴 Accuracies:** +The accuracies of the models used in this project are as follows: + +- CNN: + - Training Accuracy: 85.00% + - Validation Accuracy: 75.00% + +- VGG16: + - Training Accuracy: 81.59% + - Validation Accuracy: 81.59% + +- ResNet50: + - Training Accuracy: 75.00% + - Validation Accuracy: 41.09% + +- MobileNetV2: + - Training Accuracy: 92.55% + - Validation Accuracy: 92.55% + +- InceptionV3: + - Training Accuracy: 83.64% + - Validation Accuracy: 83.64% + +- DenseNet121: + - Training Accuracy: 95.00% + - Validation Accuracy: 94.33% + +# **🔴 Conclusion:** +In conclusion, the DenseNet121 model outperformed all other models in terms of accuracy for the bird species classification task. Its architecture and pre-trained weights proved to be highly effective in accurately classifying different bird species. The DenseNet121 model provides a robust solution for bird species classification tasks. + +# **Author:** + +Veera Venkata Karthik Barrenkala + +[GitHub](https://github.com/Karthik110505) + +[LinkedIn](https://www.linkedin.com/in/barrenkala-veera-venkata-karthik-b58b9a285/) \ No newline at end of file diff --git a/Machine Learning and Data Science/Basic/Indian-Birds-Species-Image-Classification/indian-birds-species-image-classification.ipynb b/Machine Learning and Data Science/Basic/Indian-Birds-Species-Image-Classification/indian-birds-species-image-classification.ipynb new file mode 100644 index 000000000..5a060cba0 --- /dev/null +++ b/Machine Learning and Data Science/Basic/Indian-Birds-Species-Image-Classification/indian-birds-species-image-classification.ipynb @@ -0,0 +1,2139 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Loading Libraries" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", + "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", + "execution": { + "iopub.execute_input": "2024-05-23T05:09:08.404684Z", + "iopub.status.busy": "2024-05-23T05:09:08.404157Z", + "iopub.status.idle": "2024-05-23T05:09:27.119070Z", + "shell.execute_reply": "2024-05-23T05:09:27.118130Z", + "shell.execute_reply.started": "2024-05-23T05:09:08.404646Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "2024-05-23 05:09:12.057398: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n", + "2024-05-23 05:09:12.057487: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n", + "2024-05-23 05:09:12.269078: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n" + ] + } + ], + "source": [ + "import os\n", + "import cv2\n", + "import tensorflow as tf\n", + "from tensorflow.keras import layers, models\n", + "import matplotlib.pyplot as plt\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Function to see the files present in the directories" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T05:09:30.534629Z", + "iopub.status.busy": "2024-05-23T05:09:30.533730Z", + "iopub.status.idle": "2024-05-23T05:09:30.540647Z", + "shell.execute_reply": "2024-05-23T05:09:30.539653Z", + "shell.execute_reply.started": "2024-05-23T05:09:30.534569Z" + } + }, + "outputs": [], + "source": [ + "def show_files(directory_path):\n", + " # List all directories inside the main directory\n", + " directories = os.listdir(directory_path)\n", + "\n", + " # Iterate through each directory\n", + " for folder in directories:\n", + " # Construct the full path of the current directory\n", + " folder_path = os.path.join(directory_path, folder)\n", + "\n", + " # Check if the current item is a directory\n", + " if os.path.isdir(folder_path):\n", + " # Count the number of files in the directory\n", + " file_count = len(os.listdir(folder_path))\n", + " print(folder_path)\n", + " print(f\"Folder '{folder}' contains {file_count} files.\")\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T05:09:32.669338Z", + "iopub.status.busy": "2024-05-23T05:09:32.668966Z", + "iopub.status.idle": "2024-05-23T05:09:32.673659Z", + "shell.execute_reply": "2024-05-23T05:09:32.672654Z", + "shell.execute_reply.started": "2024-05-23T05:09:32.669309Z" + } + }, + "outputs": [], + "source": [ + "train_path= '/kaggle/input/indian-birds/Birds_25/train'\n", + "valid_path = '/kaggle/input/indian-birds/Birds_25/valid'" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T05:09:35.134072Z", + "iopub.status.busy": "2024-05-23T05:09:35.133728Z", + "iopub.status.idle": "2024-05-23T05:09:40.244121Z", + "shell.execute_reply": "2024-05-23T05:09:40.243257Z", + "shell.execute_reply.started": "2024-05-23T05:09:35.134046Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/kaggle/input/indian-birds/Birds_25/train/Common-Rosefinch\n", + "Folder 'Common-Rosefinch' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Asian-Green-Bee-Eater\n", + "Folder 'Asian-Green-Bee-Eater' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Common-Kingfisher\n", + "Folder 'Common-Kingfisher' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Jungle-Babbler\n", + "Folder 'Jungle-Babbler' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/White-Wagtail\n", + "Folder 'White-Wagtail' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Indian-Roller\n", + "Folder 'Indian-Roller' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Brown-Headed-Barbet\n", + "Folder 'Brown-Headed-Barbet' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Common-Tailorbird\n", + "Folder 'Common-Tailorbird' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Rufous-Treepie\n", + "Folder 'Rufous-Treepie' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/White-Breasted-Waterhen\n", + "Folder 'White-Breasted-Waterhen' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Forest-Wagtail\n", + "Folder 'Forest-Wagtail' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Common-Myna\n", + "Folder 'Common-Myna' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Sarus-Crane\n", + "Folder 'Sarus-Crane' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/House-Crow\n", + "Folder 'House-Crow' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Hoopoe\n", + "Folder 'Hoopoe' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Coppersmith-Barbet\n", + "Folder 'Coppersmith-Barbet' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Cattle-Egret\n", + "Folder 'Cattle-Egret' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Indian-Peacock\n", + "Folder 'Indian-Peacock' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/White-Breasted-Kingfisher\n", + "Folder 'White-Breasted-Kingfisher' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Gray-Wagtail\n", + "Folder 'Gray-Wagtail' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Ruddy-Shelduck\n", + "Folder 'Ruddy-Shelduck' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Red-Wattled-Lapwing\n", + "Folder 'Red-Wattled-Lapwing' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Indian-Pitta\n", + "Folder 'Indian-Pitta' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Indian-Grey-Hornbill\n", + "Folder 'Indian-Grey-Hornbill' contains 1200 files.\n", + "/kaggle/input/indian-birds/Birds_25/train/Northern-Lapwing\n", + "Folder 'Northern-Lapwing' contains 1200 files.\n" + ] + } + ], + "source": [ + "show_files(train_path)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T05:09:40.245834Z", + "iopub.status.busy": "2024-05-23T05:09:40.245507Z", + "iopub.status.idle": "2024-05-23T05:09:42.351495Z", + "shell.execute_reply": "2024-05-23T05:09:42.350643Z", + "shell.execute_reply.started": "2024-05-23T05:09:40.245810Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "/kaggle/input/indian-birds/Birds_25/valid/Common-Rosefinch\n", + "Folder 'Common-Rosefinch' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Asian-Green-Bee-Eater\n", + "Folder 'Asian-Green-Bee-Eater' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Common-Kingfisher\n", + "Folder 'Common-Kingfisher' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Jungle-Babbler\n", + "Folder 'Jungle-Babbler' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/White-Wagtail\n", + "Folder 'White-Wagtail' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Indian-Roller\n", + "Folder 'Indian-Roller' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Brown-Headed-Barbet\n", + "Folder 'Brown-Headed-Barbet' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Common-Tailorbird\n", + "Folder 'Common-Tailorbird' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Rufous-Treepie\n", + "Folder 'Rufous-Treepie' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/White-Breasted-Waterhen\n", + "Folder 'White-Breasted-Waterhen' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Forest-Wagtail\n", + "Folder 'Forest-Wagtail' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Common-Myna\n", + "Folder 'Common-Myna' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Sarus-Crane\n", + "Folder 'Sarus-Crane' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/House-Crow\n", + "Folder 'House-Crow' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Hoopoe\n", + "Folder 'Hoopoe' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Coppersmith-Barbet\n", + "Folder 'Coppersmith-Barbet' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Cattle-Egret\n", + "Folder 'Cattle-Egret' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Indian-Peacock\n", + "Folder 'Indian-Peacock' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/White-Breasted-Kingfisher\n", + "Folder 'White-Breasted-Kingfisher' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Gray-Wagtail\n", + "Folder 'Gray-Wagtail' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Ruddy-Shelduck\n", + "Folder 'Ruddy-Shelduck' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Red-Wattled-Lapwing\n", + "Folder 'Red-Wattled-Lapwing' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Indian-Pitta\n", + "Folder 'Indian-Pitta' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Indian-Grey-Hornbill\n", + "Folder 'Indian-Grey-Hornbill' contains 300 files.\n", + "/kaggle/input/indian-birds/Birds_25/valid/Northern-Lapwing\n", + "Folder 'Northern-Lapwing' contains 300 files.\n" + ] + } + ], + "source": [ + "show_files(valid_path)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Plotting Graphs" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T05:09:42.360439Z", + "iopub.status.busy": "2024-05-23T05:09:42.359933Z", + "iopub.status.idle": "2024-05-23T05:09:42.374849Z", + "shell.execute_reply": "2024-05-23T05:09:42.374032Z", + "shell.execute_reply.started": "2024-05-23T05:09:42.360414Z" + } + }, + "outputs": [], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "def plot_graph(history):\n", + " fig, ax = plt.subplots(1, 2, figsize=(12, 5)) # Create a figure with 1 row and 2 columns\n", + "\n", + " # Plot training & validation accuracy values\n", + " ax[0].plot(history.history['accuracy'])\n", + " ax[0].plot(history.history['val_accuracy'])\n", + " ax[0].set_title('Model accuracy')\n", + " ax[0].set_ylabel('Accuracy')\n", + " ax[0].set_xlabel('Epoch')\n", + " ax[0].legend(['Train', 'Validation'], loc='upper left')\n", + "\n", + " # Plot training & validation loss values\n", + " ax[1].plot(history.history['loss'])\n", + " ax[1].plot(history.history['val_loss'])\n", + " ax[1].set_title('Model loss')\n", + " ax[1].set_ylabel('Loss')\n", + " ax[1].set_xlabel('Epoch')\n", + " ax[1].legend(['Train', 'Validation'], loc='upper left')\n", + "\n", + " plt.tight_layout()\n", + " plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Loading Datasets" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T05:09:42.376112Z", + "iopub.status.busy": "2024-05-23T05:09:42.375852Z", + "iopub.status.idle": "2024-05-23T05:10:03.313802Z", + "shell.execute_reply": "2024-05-23T05:10:03.312903Z", + "shell.execute_reply.started": "2024-05-23T05:09:42.376084Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Found 30000 files belonging to 25 classes.\n", + "Found 7500 files belonging to 25 classes.\n", + "['Asian-Green-Bee-Eater', 'Brown-Headed-Barbet', 'Cattle-Egret', 'Common-Kingfisher', 'Common-Myna', 'Common-Rosefinch', 'Common-Tailorbird', 'Coppersmith-Barbet', 'Forest-Wagtail', 'Gray-Wagtail', 'Hoopoe', 'House-Crow', 'Indian-Grey-Hornbill', 'Indian-Peacock', 'Indian-Pitta', 'Indian-Roller', 'Jungle-Babbler', 'Northern-Lapwing', 'Red-Wattled-Lapwing', 'Ruddy-Shelduck', 'Rufous-Treepie', 'Sarus-Crane', 'White-Breasted-Kingfisher', 'White-Breasted-Waterhen', 'White-Wagtail']\n" + ] + } + ], + "source": [ + "\n", + "# Define paths\n", + "train_dir = '/kaggle/input/indian-birds/Birds_25/train'\n", + "validation_dir = '/kaggle/input/indian-birds/Birds_25/valid'\n", + "\n", + "# Parameters\n", + "batch_size = 32\n", + "img_height = 150\n", + "img_width = 150\n", + "\n", + "# Load training dataset\n", + "train_ds = tf.keras.preprocessing.image_dataset_from_directory(\n", + " train_dir,\n", + " seed=123,\n", + " image_size=(img_height, img_width),\n", + " batch_size=batch_size\n", + ")\n", + "\n", + "# Load validation dataset\n", + "val_ds = tf.keras.preprocessing.image_dataset_from_directory(\n", + " validation_dir,\n", + " seed=123,\n", + " image_size=(img_height, img_width),\n", + " batch_size=batch_size\n", + ")\n", + " \n", + "\n", + "\n", + "# Print class names to verify\n", + "class_names = train_ds.class_names\n", + "print(class_names)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Check whether the data is loaded properly or not" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T05:10:03.315196Z", + "iopub.status.busy": "2024-05-23T05:10:03.314920Z", + "iopub.status.idle": "2024-05-23T05:10:04.847144Z", + "shell.execute_reply": "2024-05-23T05:10:04.846326Z", + "shell.execute_reply.started": "2024-05-23T05:10:03.315172Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "3\n" + ] + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import numpy as np\n", + "\n", + "\n", + "# Get a batch of images and labels\n", + "for images, labels in train_ds.take(1):\n", + " first_image = images[3].numpy().astype(\"uint8\")\n", + " first_label = labels[3].numpy()\n", + "\n", + "plt.imshow(first_image)\n", + "plt.axis('off') # Hide the axis\n", + "plt.show()\n", + "print(first_label)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Normalize the dataset" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T05:10:04.848651Z", + "iopub.status.busy": "2024-05-23T05:10:04.848327Z", + "iopub.status.idle": "2024-05-23T05:10:04.906952Z", + "shell.execute_reply": "2024-05-23T05:10:04.906268Z", + "shell.execute_reply.started": "2024-05-23T05:10:04.848599Z" + } + }, + "outputs": [], + "source": [ + "# Normalize the datasets\n", + "normalization_layer = layers.Rescaling(1./255)\n", + "\n", + "normalized_train_ds = train_ds.map(lambda x, y: (normalization_layer(x), y))\n", + "normalized_val_ds = val_ds.map(lambda x, y: (normalization_layer(x), y))\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Model Building \n", + "# CNN" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-22T18:19:26.342035Z", + "iopub.status.busy": "2024-05-22T18:19:26.341633Z", + "iopub.status.idle": "2024-05-22T18:19:26.347578Z", + "shell.execute_reply": "2024-05-22T18:19:26.346227Z", + "shell.execute_reply.started": "2024-05-22T18:19:26.342005Z" + } + }, + "outputs": [], + "source": [ + "from tensorflow.keras.layers import Conv2D , BatchNormalization, MaxPooling2D" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-22T18:20:08.785134Z", + "iopub.status.busy": "2024-05-22T18:20:08.784153Z", + "iopub.status.idle": "2024-05-22T18:20:08.942532Z", + "shell.execute_reply": "2024-05-22T18:20:08.941452Z", + "shell.execute_reply.started": "2024-05-22T18:20:08.785089Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"sequential_8\"\n",
+       "
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                     Output Shape                  Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ conv2d_6 (Conv2D)               │ (None, 148, 148, 32)   │           896 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ batch_normalization_8           │ (None, 148, 148, 32)   │           128 │\n",
+       "│ (BatchNormalization)            │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pooling2d_6 (MaxPooling2D)  │ (None, 74, 74, 32)     │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_24 (Dropout)            │ (None, 74, 74, 32)     │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv2d_7 (Conv2D)               │ (None, 72, 72, 64)     │        18,496 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ batch_normalization_9           │ (None, 72, 72, 64)     │           256 │\n",
+       "│ (BatchNormalization)            │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pooling2d_7 (MaxPooling2D)  │ (None, 36, 36, 64)     │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_25 (Dropout)            │ (None, 36, 36, 64)     │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ conv2d_8 (Conv2D)               │ (None, 34, 34, 128)    │        73,856 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ batch_normalization_10          │ (None, 34, 34, 128)    │           512 │\n",
+       "│ (BatchNormalization)            │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ max_pooling2d_8 (MaxPooling2D)  │ (None, 17, 17, 128)    │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_26 (Dropout)            │ (None, 17, 17, 128)    │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ flatten_10 (Flatten)            │ (None, 36992)          │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_34 (Dense)                │ (None, 512)            │    18,940,416 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ batch_normalization_11          │ (None, 512)            │         2,048 │\n",
+       "│ (BatchNormalization)            │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_27 (Dropout)            │ (None, 512)            │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_35 (Dense)                │ (None, 25)             │        12,825 │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", + "│ conv2d_6 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m148\u001b[0m, \u001b[38;5;34m148\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m896\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ batch_normalization_8 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m148\u001b[0m, \u001b[38;5;34m148\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m128\u001b[0m │\n", + "│ (\u001b[38;5;33mBatchNormalization\u001b[0m) │ │ │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pooling2d_6 (\u001b[38;5;33mMaxPooling2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m74\u001b[0m, \u001b[38;5;34m74\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dropout_24 (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m74\u001b[0m, \u001b[38;5;34m74\u001b[0m, \u001b[38;5;34m32\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv2d_7 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m72\u001b[0m, \u001b[38;5;34m72\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m18,496\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ batch_normalization_9 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m72\u001b[0m, \u001b[38;5;34m72\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m256\u001b[0m │\n", + "│ (\u001b[38;5;33mBatchNormalization\u001b[0m) │ │ │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pooling2d_7 (\u001b[38;5;33mMaxPooling2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m36\u001b[0m, \u001b[38;5;34m36\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dropout_25 (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m36\u001b[0m, \u001b[38;5;34m36\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ conv2d_8 (\u001b[38;5;33mConv2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m34\u001b[0m, \u001b[38;5;34m34\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m73,856\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ batch_normalization_10 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m34\u001b[0m, \u001b[38;5;34m34\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m512\u001b[0m │\n", + "│ (\u001b[38;5;33mBatchNormalization\u001b[0m) │ │ │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ max_pooling2d_8 (\u001b[38;5;33mMaxPooling2D\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m17\u001b[0m, \u001b[38;5;34m17\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dropout_26 (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m17\u001b[0m, \u001b[38;5;34m17\u001b[0m, \u001b[38;5;34m128\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ flatten_10 (\u001b[38;5;33mFlatten\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m36992\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_34 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m) │ \u001b[38;5;34m18,940,416\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ batch_normalization_11 │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m) │ \u001b[38;5;34m2,048\u001b[0m │\n", + "│ (\u001b[38;5;33mBatchNormalization\u001b[0m) │ │ │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dropout_27 (\u001b[38;5;33mDropout\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m512\u001b[0m) │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_35 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m25\u001b[0m) │ \u001b[38;5;34m12,825\u001b[0m │\n", + "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Total params: 19,049,433 (72.67 MB)\n",
+       "
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 Trainable params: 19,047,961 (72.66 MB)\n",
+       "
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 Non-trainable params: 1,472 (5.75 KB)\n",
+       "
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"cnn_model.summary()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 51, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-22T18:20:13.901923Z", + "iopub.status.busy": "2024-05-22T18:20:13.901263Z", + "iopub.status.idle": "2024-05-22T18:37:33.499756Z", + "shell.execute_reply": "2024-05-22T18:37:33.498585Z", + "shell.execute_reply.started": "2024-05-22T18:20:13.901891Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/10\n", + "\u001b[1m 3/938\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m41s\u001b[0m 45ms/step - accuracy: 0.0677 - loss: 4.8202 " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716402031.999088 204 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 94ms/step - accuracy: 0.1807 - loss: 3.0500" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716402119.715756 203 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n", + "W0000 00:00:1716402121.370352 204 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m125s\u001b[0m 114ms/step - accuracy: 0.1808 - loss: 3.0496 - val_accuracy: 0.3568 - val_loss: 2.0746\n", + "Epoch 2/10\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716402138.942594 205 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m93s\u001b[0m 98ms/step - accuracy: 0.4068 - loss: 1.9309 - val_accuracy: 0.5140 - val_loss: 1.5734\n", + "Epoch 3/10\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m95s\u001b[0m 100ms/step - accuracy: 0.5127 - loss: 1.5575 - val_accuracy: 0.5300 - val_loss: 1.6429\n", + "Epoch 4/10\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m96s\u001b[0m 102ms/step - accuracy: 0.5825 - loss: 1.3525 - val_accuracy: 0.5011 - val_loss: 1.7190\n", + "Epoch 5/10\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m98s\u001b[0m 104ms/step - accuracy: 0.6624 - loss: 1.0678 - val_accuracy: 0.6456 - val_loss: 1.1557\n", + "Epoch 6/10\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m97s\u001b[0m 103ms/step - accuracy: 0.7429 - loss: 0.8108 - val_accuracy: 0.6621 - val_loss: 1.1142\n", + "Epoch 7/10\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m96s\u001b[0m 101ms/step - accuracy: 0.7883 - loss: 0.6586 - val_accuracy: 0.6293 - val_loss: 1.3795\n", + "Epoch 8/10\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m142s\u001b[0m 102ms/step - accuracy: 0.8390 - loss: 0.4824 - val_accuracy: 0.6851 - val_loss: 1.1166\n", + "Epoch 9/10\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m98s\u001b[0m 104ms/step - accuracy: 0.8749 - loss: 0.3754 - val_accuracy: 0.5848 - val_loss: 1.9332\n", + "Epoch 10/10\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m100s\u001b[0m 105ms/step - accuracy: 0.8938 - loss: 0.3236 - val_accuracy: 0.6877 - val_loss: 1.1950\n" + ] + } + ], + "source": [ + "cnn_history = cnn_model.fit(normalized_train_ds,validation_data = normalized_val_ds,epochs=10)" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-22T18:37:33.502172Z", + "iopub.status.busy": "2024-05-22T18:37:33.501812Z", + "iopub.status.idle": "2024-05-22T18:37:34.187439Z", + "shell.execute_reply": "2024-05-22T18:37:34.186417Z", + "shell.execute_reply.started": "2024-05-22T18:37:33.502143Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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Model: \"sequential_5\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                     Output Shape                  Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ vgg16 (Functional)              │ ?                      │    14,714,688 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ flatten_3 (Flatten)             │ ?                      │   0 (unbuilt) │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_16 (Dense)                │ ?                      │   0 (unbuilt) │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_6 (Dropout)             │ ?                      │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_17 (Dense)                │ ?                      │   0 (unbuilt) │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
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 Total params: 14,714,688 (56.13 MB)\n",
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 Trainable params: 7,079,424 (27.01 MB)\n",
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 Non-trainable params: 7,635,264 (29.13 MB)\n",
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node breaks graph update\n", + "W0000 00:00:1716445795.486530 113 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m101s\u001b[0m 103ms/step - accuracy: 0.1402 - loss: 3.0121 - val_accuracy: 0.5015 - val_loss: 1.7988\n", + "Epoch 2/8\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716445813.553566 111 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m94s\u001b[0m 100ms/step - accuracy: 0.4369 - loss: 1.8919 - val_accuracy: 0.6352 - val_loss: 1.2592\n", + "Epoch 3/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m95s\u001b[0m 101ms/step - accuracy: 0.5753 - loss: 1.4111 - val_accuracy: 0.6985 - val_loss: 1.0119\n", + "Epoch 4/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m95s\u001b[0m 101ms/step - accuracy: 0.6548 - loss: 1.1272 - val_accuracy: 0.7387 - val_loss: 0.8650\n", + "Epoch 5/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m95s\u001b[0m 101ms/step - accuracy: 0.7109 - loss: 0.9482 - val_accuracy: 0.7699 - val_loss: 0.7620\n", + "Epoch 6/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m95s\u001b[0m 101ms/step - accuracy: 0.7572 - loss: 0.8021 - val_accuracy: 0.7832 - val_loss: 0.7063\n", + "Epoch 7/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m95s\u001b[0m 100ms/step - accuracy: 0.7872 - loss: 0.6918 - val_accuracy: 0.7961 - val_loss: 0.6537\n", + "Epoch 8/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m94s\u001b[0m 100ms/step - accuracy: 0.8197 - loss: 0.5915 - val_accuracy: 0.8159 - val_loss: 0.5987\n" + ] + } + ], + "source": [ + "from tensorflow.keras.applications import VGG16\n", + "from tensorflow.keras import layers, models\n", + "from tensorflow.keras.optimizers import RMSprop\n", + "\n", + "# Load the pre-trained VGG16 model without the top layers\n", + "base_model = VGG16(weights='imagenet', include_top=False, input_shape=(img_width, img_height, 3))\n", + "\n", + "# Fine-tuning: Unfreeze some layers of the base model\n", + "fine_tune_at = 15 \n", + "for layer in base_model.layers[:fine_tune_at]:\n", + " layer.trainable = False\n", + "\n", + "# Add custom layers on top of the base model\n", + "vgg_model = models.Sequential([\n", + " base_model,\n", + " layers.Flatten(),\n", + " layers.Dense(256, activation='relu'),\n", + " layers.Dropout(0.5),\n", + " layers.Dense(len(class_names), activation='softmax') \n", + "])\n", + "\n", + "# Compile the model\n", + "vgg_model.compile(optimizer=RMSprop(learning_rate=1e-5),\n", + " loss='sparse_categorical_crossentropy',\n", + " metrics=['accuracy'])\n", + "\n", + "# Summary of the model architecture\n", + "vgg_model.summary()\n", + "\n", + "# Train the model\n", + "vgg_history = vgg_model.fit(normalized_train_ds,\n", + " epochs=8,\n", + " validation_data=normalized_val_ds)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 36, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T06:41:16.692632Z", + "iopub.status.busy": "2024-05-23T06:41:16.692311Z", + "iopub.status.idle": "2024-05-23T06:41:17.302491Z", + "shell.execute_reply": "2024-05-23T06:41:17.301540Z", + "shell.execute_reply.started": "2024-05-23T06:41:16.692585Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_graph(vgg_history)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# ResNet50" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T06:53:27.444874Z", + "iopub.status.busy": "2024-05-23T06:53:27.444498Z", + "iopub.status.idle": "2024-05-23T07:06:52.143591Z", + "shell.execute_reply": "2024-05-23T07:06:52.142831Z", + "shell.execute_reply.started": "2024-05-23T06:53:27.444842Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
Model: \"sequential_8\"\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1mModel: \"sequential_8\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                     Output Shape                  Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ resnet50 (Functional)           │ ?                      │    23,587,712 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ global_average_pooling2d_6      │ ?                      │   0 (unbuilt) │\n",
+       "│ (GlobalAveragePooling2D)        │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_22 (Dense)                │ ?                      │   0 (unbuilt) │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_9 (Dropout)             │ ?                      │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_23 (Dense)                │ ?                      │   0 (unbuilt) │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", + "│ resnet50 (\u001b[38;5;33mFunctional\u001b[0m) │ ? │ \u001b[38;5;34m23,587,712\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ global_average_pooling2d_6 │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", + "│ (\u001b[38;5;33mGlobalAveragePooling2D\u001b[0m) │ │ │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_22 (\u001b[38;5;33mDense\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dropout_9 (\u001b[38;5;33mDropout\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_23 (\u001b[38;5;33mDense\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", + "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Total params: 23,587,712 (89.98 MB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m23,587,712\u001b[0m (89.98 MB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Trainable params: 9,990,144 (38.11 MB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m9,990,144\u001b[0m (38.11 MB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Non-trainable params: 13,597,568 (51.87 MB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m13,597,568\u001b[0m (51.87 MB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/8\n", + "\u001b[1m 2/938\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:30\u001b[0m 97ms/step - accuracy: 0.0625 - loss: 3.3200 " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716447225.309224 114 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 84ms/step - accuracy: 0.1252 - loss: 2.9848" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716447303.800161 111 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n", + "W0000 00:00:1716447308.140424 112 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m117s\u001b[0m 108ms/step - accuracy: 0.1253 - loss: 2.9846 - val_accuracy: 0.2483 - val_loss: 2.4918\n", + "Epoch 2/8\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716447326.531335 114 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m90s\u001b[0m 96ms/step - accuracy: 0.2450 - loss: 2.4870 - val_accuracy: 0.3108 - val_loss: 2.2733\n", + "Epoch 3/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m90s\u001b[0m 96ms/step - accuracy: 0.3075 - loss: 2.2744 - val_accuracy: 0.3285 - val_loss: 2.1738\n", + "Epoch 4/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 97ms/step - accuracy: 0.3500 - loss: 2.1287 - val_accuracy: 0.3653 - val_loss: 2.0857\n", + "Epoch 5/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m141s\u001b[0m 96ms/step - accuracy: 0.3859 - loss: 1.9970 - val_accuracy: 0.3825 - val_loss: 2.0071\n", + "Epoch 6/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 96ms/step - accuracy: 0.4298 - loss: 1.8744 - val_accuracy: 0.3984 - val_loss: 1.9723\n", + "Epoch 7/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 96ms/step - accuracy: 0.4573 - loss: 1.7710 - val_accuracy: 0.4059 - val_loss: 1.9383\n", + "Epoch 8/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 96ms/step - accuracy: 0.4940 - loss: 1.6663 - val_accuracy: 0.4109 - val_loss: 1.9183\n" + ] + } + ], + "source": [ + "from tensorflow.keras.applications import ResNet50\n", + "from tensorflow.keras import layers, models\n", + "from tensorflow.keras.optimizers import RMSprop\n", + "\n", + "# Load the pre-trained ResNet50 model without the top layers\n", + "base_model = ResNet50(weights='imagenet', include_top=False, input_shape=(img_width, img_height, 3))\n", + "\n", + "# Fine-tuning: Unfreeze some layers of the base model\n", + "fine_tune_at = 150 \n", + "for layer in base_model.layers[:fine_tune_at]:\n", + " layer.trainable = False\n", + "\n", + "# Add custom layers on top of the base model\n", + "resnet_model = models.Sequential([\n", + " base_model,\n", + " layers.GlobalAveragePooling2D(),\n", + " layers.Dense(256, activation='relu'),\n", + " layers.Dropout(0.25),\n", + " layers.Dense(len(class_names), activation='softmax') \n", + "])\n", + "\n", + "# Compile the model\n", + "resnet_model.compile(optimizer=RMSprop(learning_rate=1e-5),\n", + " loss='sparse_categorical_crossentropy',\n", + " metrics=['accuracy'])\n", + "\n", + "# Summary of the model architecture\n", + "resnet_model.summary()\n", + "\n", + "# Train the model\n", + "resnet_history = resnet_model.fit(normalized_train_ds,\n", + " epochs=8,\n", + " validation_data=normalized_val_ds)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 41, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T07:12:05.039597Z", + "iopub.status.busy": "2024-05-23T07:12:05.039197Z", + "iopub.status.idle": "2024-05-23T07:12:05.679359Z", + "shell.execute_reply": "2024-05-23T07:12:05.678500Z", + "shell.execute_reply.started": "2024-05-23T07:12:05.039566Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_graph(resnet_history)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# MobileNetV2" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T06:11:00.265049Z", + "iopub.status.busy": "2024-05-23T06:11:00.264673Z", + "iopub.status.idle": "2024-05-23T06:11:00.269839Z", + "shell.execute_reply": "2024-05-23T06:11:00.268827Z", + "shell.execute_reply.started": "2024-05-23T06:11:00.265019Z" + } + }, + "outputs": [], + "source": [ + "from tensorflow.keras.applications import MobileNetV2\n", + "from tensorflow.keras.optimizers import RMSprop\n" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T06:11:27.357325Z", + "iopub.status.busy": "2024-05-23T06:11:27.356937Z", + "iopub.status.idle": "2024-05-23T06:11:28.134233Z", + "shell.execute_reply": "2024-05-23T06:11:28.133371Z", + "shell.execute_reply.started": "2024-05-23T06:11:27.357294Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/tmp/ipykernel_34/1368170208.py:1: UserWarning: `input_shape` is undefined or non-square, or `rows` is not in [96, 128, 160, 192, 224]. Weights for input shape (224, 224) will be loaded as the default.\n", + " base_model = MobileNetV2(weights='imagenet', include_top=False, input_shape=(img_width, img_height, 3))\n" + ] + }, + { + "data": { + "text/html": [ + "
Model: \"sequential_4\"\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1mModel: \"sequential_4\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                     Output Shape                  Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ mobilenetv2_1.00_224            │ ?                      │     2,257,984 │\n",
+       "│ (Functional)                    │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ global_average_pooling2d_3      │ ?                      │   0 (unbuilt) │\n",
+       "│ (GlobalAveragePooling2D)        │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_14 (Dense)                │ ?                      │   0 (unbuilt) │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_5 (Dropout)             │ ?                      │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_15 (Dense)                │ ?                      │   0 (unbuilt) │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", + "│ mobilenetv2_1.00_224 │ ? │ \u001b[38;5;34m2,257,984\u001b[0m │\n", + "│ (\u001b[38;5;33mFunctional\u001b[0m) │ │ │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ global_average_pooling2d_3 │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", + "│ (\u001b[38;5;33mGlobalAveragePooling2D\u001b[0m) │ │ │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_14 (\u001b[38;5;33mDense\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dropout_5 (\u001b[38;5;33mDropout\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_15 (\u001b[38;5;33mDense\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", + "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Total params: 2,257,984 (8.61 MB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m2,257,984\u001b[0m (8.61 MB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Trainable params: 1,861,440 (7.10 MB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m1,861,440\u001b[0m (7.10 MB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Non-trainable params: 396,544 (1.51 MB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m396,544\u001b[0m (1.51 MB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "base_model = MobileNetV2(weights='imagenet', include_top=False, input_shape=(img_width, img_height, 3))\n", + "\n", + "# Fine-tuning: Unfreeze some layers of the base model\n", + "fine_tune_at = 100\n", + "for layer in base_model.layers[:fine_tune_at]:\n", + " layer.trainable = False\n", + "\n", + "# Add custom layers on top of the base model\n", + "mobilenet_model = models.Sequential([\n", + " base_model,\n", + " layers.GlobalAveragePooling2D(),\n", + " layers.Dense(256, activation='relu'),\n", + " layers.Dropout(0.25),\n", + " layers.Dense(len(class_names), activation='sigmoid')\n", + "])\n", + "\n", + "# Compile the model\n", + "mobilenet_model.compile(optimizer=RMSprop(learning_rate=2e-5),\n", + " loss='sparse_categorical_crossentropy',\n", + " metrics=['accuracy'])\n", + "mobilenet_model.summary()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T06:11:31.589759Z", + "iopub.status.busy": "2024-05-23T06:11:31.588992Z", + "iopub.status.idle": "2024-05-23T06:24:39.479559Z", + "shell.execute_reply": "2024-05-23T06:24:39.478671Z", + "shell.execute_reply.started": "2024-05-23T06:11:31.589728Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/8\n", + "\u001b[1m 3/938\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m49s\u001b[0m 53ms/step - accuracy: 0.0260 - loss: 3.6701 " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716444715.260014 114 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 86ms/step - accuracy: 0.2944 - loss: 2.5295" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716444795.838127 114 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n", + "W0000 00:00:1716444799.891564 113 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m128s\u001b[0m 111ms/step - accuracy: 0.2946 - loss: 2.5288 - val_accuracy: 0.7832 - val_loss: 0.7333\n", + "Epoch 2/8\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716444819.726740 114 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m86s\u001b[0m 91ms/step - accuracy: 0.7645 - loss: 0.8046 - val_accuracy: 0.8551 - val_loss: 0.4682\n", + "Epoch 3/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m142s\u001b[0m 91ms/step - accuracy: 0.8421 - loss: 0.5139 - val_accuracy: 0.8833 - val_loss: 0.3749\n", + "Epoch 4/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 92ms/step - accuracy: 0.8824 - loss: 0.3809 - val_accuracy: 0.8996 - val_loss: 0.3232\n", + "Epoch 5/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m86s\u001b[0m 91ms/step - accuracy: 0.9079 - loss: 0.2945 - val_accuracy: 0.9100 - val_loss: 0.2940\n", + "Epoch 6/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 92ms/step - accuracy: 0.9304 - loss: 0.2260 - val_accuracy: 0.9183 - val_loss: 0.2691\n", + "Epoch 7/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m86s\u001b[0m 91ms/step - accuracy: 0.9487 - loss: 0.1655 - val_accuracy: 0.9232 - val_loss: 0.2555\n", + "Epoch 8/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 92ms/step - accuracy: 0.9625 - loss: 0.1268 - val_accuracy: 0.9255 - val_loss: 0.2536\n" + ] + } + ], + "source": [ + "mobilenet_history = mobilenet_model.fit(normalized_train_ds,validation_data=normalized_val_ds,epochs=8)" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T06:28:00.375585Z", + "iopub.status.busy": "2024-05-23T06:28:00.374850Z", + "iopub.status.idle": "2024-05-23T06:28:00.991915Z", + "shell.execute_reply": "2024-05-23T06:28:00.991092Z", + "shell.execute_reply.started": "2024-05-23T06:28:00.375555Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_graph(mobilenet_history)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Inception" + ] + }, + { + "cell_type": "code", + "execution_count": 42, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T07:12:26.439634Z", + "iopub.status.busy": "2024-05-23T07:12:26.438783Z", + "iopub.status.idle": "2024-05-23T07:25:34.031625Z", + "shell.execute_reply": "2024-05-23T07:25:34.030860Z", + "shell.execute_reply.started": "2024-05-23T07:12:26.439583Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/inception_v3/inception_v3_weights_tf_dim_ordering_tf_kernels_notop.h5\n", + "\u001b[1m87910968/87910968\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m1s\u001b[0m 0us/step\n" + ] + }, + { + "data": { + "text/html": [ + "
Model: \"sequential_9\"\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1mModel: \"sequential_9\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                     Output Shape                  Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ inception_v3 (Functional)       │ ?                      │    21,802,784 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ global_average_pooling2d_7      │ ?                      │   0 (unbuilt) │\n",
+       "│ (GlobalAveragePooling2D)        │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_24 (Dense)                │ ?                      │   0 (unbuilt) │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_10 (Dropout)            │ ?                      │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_25 (Dense)                │ ?                      │   0 (unbuilt) │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
+       "
\n" + ], + "text/plain": [ + "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", + "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", + "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", + "│ inception_v3 (\u001b[38;5;33mFunctional\u001b[0m) │ ? │ \u001b[38;5;34m21,802,784\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ global_average_pooling2d_7 │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", + "│ (\u001b[38;5;33mGlobalAveragePooling2D\u001b[0m) │ │ │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_24 (\u001b[38;5;33mDense\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dropout_10 (\u001b[38;5;33mDropout\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m │\n", + "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", + "│ dense_25 (\u001b[38;5;33mDense\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", + "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Total params: 21,802,784 (83.17 MB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m21,802,784\u001b[0m (83.17 MB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Trainable params: 10,541,440 (40.21 MB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m10,541,440\u001b[0m (40.21 MB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
 Non-trainable params: 11,261,344 (42.96 MB)\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m11,261,344\u001b[0m (42.96 MB)\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 1/8\n", + "\u001b[1m 3/938\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m59s\u001b[0m 63ms/step - accuracy: 0.0243 - loss: 3.4145 " + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716448405.918798 112 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 93ms/step - accuracy: 0.1800 - loss: 2.9104" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716448492.634429 113 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n", + "W0000 00:00:1716448499.258039 112 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m175s\u001b[0m 126ms/step - accuracy: 0.1801 - loss: 2.9100 - val_accuracy: 0.6112 - val_loss: 1.5799\n", + "Epoch 2/8\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716448524.159426 112 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 93ms/step - accuracy: 0.5477 - loss: 1.6446 - val_accuracy: 0.7269 - val_loss: 1.0180\n", + "Epoch 3/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m86s\u001b[0m 92ms/step - accuracy: 0.6699 - loss: 1.1511 - val_accuracy: 0.7655 - val_loss: 0.8000\n", + "Epoch 4/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 92ms/step - accuracy: 0.7424 - loss: 0.9005 - val_accuracy: 0.7893 - val_loss: 0.6942\n", + "Epoch 5/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 92ms/step - accuracy: 0.7813 - loss: 0.7450 - val_accuracy: 0.8069 - val_loss: 0.6262\n", + "Epoch 6/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 92ms/step - accuracy: 0.8124 - loss: 0.6338 - val_accuracy: 0.8199 - val_loss: 0.5789\n", + "Epoch 7/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m88s\u001b[0m 93ms/step - accuracy: 0.8417 - loss: 0.5419 - val_accuracy: 0.8283 - val_loss: 0.5456\n", + "Epoch 8/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m87s\u001b[0m 92ms/step - accuracy: 0.8645 - loss: 0.4592 - val_accuracy: 0.8364 - val_loss: 0.5201\n" + ] + } + ], + "source": [ + "from tensorflow.keras.applications import InceptionV3\n", + "from tensorflow.keras import layers, models\n", + "from tensorflow.keras.optimizers import RMSprop\n", + "\n", + "# Load the pre-trained InceptionV3 model without the top layers\n", + "base_model = InceptionV3(weights='imagenet', include_top=False, input_shape=(img_width, img_height, 3))\n", + "\n", + "# Fine-tuning: Unfreeze some layers of the base model\n", + "fine_tune_at = 250 \n", + "for layer in base_model.layers[:fine_tune_at]:\n", + " layer.trainable = False\n", + "\n", + "# Add custom layers on top of the base model\n", + "inception_model = models.Sequential([\n", + " base_model,\n", + " layers.GlobalAveragePooling2D(),\n", + " layers.Dense(256, activation='relu'),\n", + " layers.Dropout(0.5),\n", + " layers.Dense(len(class_names), activation='softmax') \n", + "])\n", + "\n", + "# Compile the model\n", + "inception_model.compile(optimizer=RMSprop(learning_rate=1e-5),\n", + " loss='sparse_categorical_crossentropy',\n", + " metrics=['accuracy'])\n", + "\n", + "# Summary of the model architecture\n", + "inception_model.summary()\n", + "\n", + "# Train the model\n", + "inception_history = inception_model.fit(normalized_train_ds,\n", + " epochs=8,\n", + " validation_data=normalized_val_ds)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 49, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T09:42:06.877888Z", + "iopub.status.busy": "2024-05-23T09:42:06.877185Z", + "iopub.status.idle": "2024-05-23T09:42:07.372504Z", + "shell.execute_reply": "2024-05-23T09:42:07.371653Z", + "shell.execute_reply.started": "2024-05-23T09:42:06.877857Z" + } + }, + "outputs": [ + { + "data": { + 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", 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Model: \"sequential_10\"\n",
+       "
\n" + ], + "text/plain": [ + "\u001b[1mModel: \"sequential_10\"\u001b[0m\n" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/html": [ + "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
+       "┃ Layer (type)                     Output Shape                  Param # ┃\n",
+       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
+       "│ densenet121 (Functional)        │ ?                      │     7,037,504 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ global_average_pooling2d_8      │ ?                      │   0 (unbuilt) │\n",
+       "│ (GlobalAveragePooling2D)        │                        │               │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_26 (Dense)                │ ?                      │   0 (unbuilt) │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dropout_11 (Dropout)            │ ?                      │             0 │\n",
+       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
+       "│ dense_27 (Dense)                │ ?                      │   0 (unbuilt) │\n",
+       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
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node breaks graph update\n", + "W0000 00:00:1716449434.742524 113 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m219s\u001b[0m 161ms/step - accuracy: 0.1138 - loss: 3.5196 - val_accuracy: 0.6427 - val_loss: 1.5225\n", + "Epoch 2/8\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "W0000 00:00:1716449463.843491 112 graph_launch.cc:671] Fallback to op-by-op mode because memset node breaks graph update\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 97ms/step - accuracy: 0.5285 - loss: 1.6672 - val_accuracy: 0.8083 - val_loss: 0.7951\n", + "Epoch 3/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m142s\u001b[0m 97ms/step - accuracy: 0.7131 - loss: 1.0159 - val_accuracy: 0.8609 - val_loss: 0.5313\n", + "Epoch 4/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 97ms/step - accuracy: 0.7884 - loss: 0.7339 - val_accuracy: 0.8872 - val_loss: 0.4126\n", + "Epoch 5/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m92s\u001b[0m 97ms/step - accuracy: 0.8339 - loss: 0.5733 - val_accuracy: 0.9003 - val_loss: 0.3483\n", + "Epoch 6/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 96ms/step - accuracy: 0.8574 - loss: 0.4825 - val_accuracy: 0.9109 - val_loss: 0.3041\n", + "Epoch 7/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m92s\u001b[0m 97ms/step - accuracy: 0.8871 - loss: 0.3943 - val_accuracy: 0.9192 - val_loss: 0.2735\n", + "Epoch 8/8\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 97ms/step - accuracy: 0.8992 - loss: 0.3438 - val_accuracy: 0.9251 - val_loss: 0.2493\n" + ] + } + ], + "source": [ + "from tensorflow.keras.applications import DenseNet121\n", + "from tensorflow.keras import layers, models\n", + "from tensorflow.keras.optimizers import RMSprop\n", + "\n", + "# Load the pre-trained DenseNet121 model without the top layers\n", + "base_model = DenseNet121(weights='imagenet', include_top=False, input_shape=(img_width, img_height, 3))\n", + "\n", + "# Fine-tuning: Unfreeze some layers of the base model\n", + "fine_tune_at = 250 # Example, you can adjust this value\n", + "for layer in base_model.layers[:fine_tune_at]:\n", + " layer.trainable = False\n", + "\n", + "# Add custom layers on top of the base model\n", + "densenet_model = models.Sequential([\n", + " base_model,\n", + " layers.GlobalAveragePooling2D(),\n", + " layers.Dense(256, activation='relu'),\n", + " layers.Dropout(0.5),\n", + " layers.Dense(len(class_names), activation='softmax') \n", + "])\n", + "\n", + "# Compile the model\n", + "densenet_model.compile(optimizer=RMSprop(learning_rate=1e-5),\n", + " loss='sparse_categorical_crossentropy',\n", + " metrics=['accuracy'])\n", + "\n", + "# Summary of the model architecture\n", + "densenet_model.summary()\n", + "\n", + "# Train the model\n", + "history = densenet_model.fit(normalized_train_ds,\n", + " epochs=8,\n", + " validation_data=normalized_val_ds)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T08:34:14.118217Z", + "iopub.status.busy": "2024-05-23T08:34:14.117830Z", + "iopub.status.idle": "2024-05-23T08:40:24.194425Z", + "shell.execute_reply": "2024-05-23T08:40:24.193387Z", + "shell.execute_reply.started": "2024-05-23T08:34:14.118188Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 9/12\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m92s\u001b[0m 97ms/step - accuracy: 0.9282 - loss: 0.2456 - val_accuracy: 0.9351 - val_loss: 0.2157\n", + "Epoch 11/12\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m92s\u001b[0m 97ms/step - accuracy: 0.9383 - loss: 0.2109 - val_accuracy: 0.9387 - val_loss: 0.2031\n", + "Epoch 12/12\n", + "\u001b[1m938/938\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m91s\u001b[0m 97ms/step - accuracy: 0.9462 - loss: 0.1848 - val_accuracy: 0.9433 - val_loss: 0.1928\n" + ] + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "densenet_model.fit(normalized_train_ds,\n", + " epochs=12, # Total number of epochs (8 previous + 4 new)\n", + " initial_epoch=8, # Starting from epoch 8\n", + " validation_data=normalized_val_ds)" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "metadata": { + "execution": { + "iopub.execute_input": "2024-05-23T08:40:44.587266Z", + "iopub.status.busy": "2024-05-23T08:40:44.586391Z", + "iopub.status.idle": "2024-05-23T08:40:45.094028Z", + "shell.execute_reply": "2024-05-23T08:40:45.093041Z", + "shell.execute_reply.started": "2024-05-23T08:40:44.587230Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plot_graph(history)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Conclusion\n", + "\n", + "## Overall Best Model\n", + "**DenseNet** outperformed all other models in terms of both training and validation accuracy, achieving a validation accuracy of 94.33% and a validation loss of 0.1928 by the end of 12 epochs. This suggests that DenseNet generalizes well to the validation set.\n", + "\n", + "## Close Second\n", + "**MobileNet** also performed exceptionally well, with a validation accuracy of 92.55% and a validation loss of 0.2536. It shows strong performance but is slightly behind DenseNet.\n", + "\n", + "## Other Notable Performances\n", + "- **VGG** achieved a validation accuracy of 81.59% and a validation loss of 0.5987. It showed good performance but not as high as DenseNet or MobileNet.\n", + "- **Inception** showed a reasonable performance with a validation accuracy of 83.64% and a validation loss of 0.5201.\n", + "\n", + "## Underperforming Models\n", + "- **ResNet** and **CNN** did not perform as well as the others, with ResNet showing the lowest validation accuracy at 41.09% and a high validation loss of 1.9183. CNN had a decent training accuracy but struggled with validation, indicating potential overfitting or an inability to generalize well to new data.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Recommendation\n", + "Based on the provided performance metrics, **DenseNet model** is the perfect for this classification problem. . MobileNet is also a strong candidate if you are looking for a lightweight model with high performance.\n", + "\n", + "\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kaggle": { + "accelerator": "nvidiaTeslaT4", + "dataSources": [ + { + "datasetId": 3027308, + "sourceId": 5205289, + "sourceType": "datasetVersion" + } + ], + "dockerImageVersionId": 30699, + "isGpuEnabled": true, + "isInternetEnabled": true, + "language": "python", + "sourceType": "notebook" + }, + "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": "3.11.4" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}