{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"gpu","dataSources":[{"sourceId":3362,"databundleVersionId":31148,"sourceType":"competition"}],"dockerImageVersionId":30919,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n    for filename in filenames:\n        print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:00.024624Z","iopub.execute_input":"2025-03-25T13:37:00.024965Z","iopub.status.idle":"2025-03-25T13:37:00.405783Z","shell.execute_reply.started":"2025-03-25T13:37:00.024938Z","shell.execute_reply":"2025-03-25T13:37:00.404745Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<h1 style=\"text-align:center; color:#6A5ACD; font-weight:bold; font-size:38px;\">Image Classification With TensorFlow</h1>\n","metadata":{}},{"cell_type":"markdown","source":"<div style=\"text-align: center;\">\n    <img src=\"https://www.shutterstock.com/image-photo/portrait-adorable-labrador-puppy-scottish-600nw-2379672403.jpg\" alt=\"Centered Image\">\n</div>","metadata":{}},{"cell_type":"markdown","source":"# 🐶🐱 Dogs vs. Cats Dataset  \n\n## 📌 Introduction  \nThe **Dogs vs. Cats** dataset is a well-known dataset from Kaggle, designed for binary image classification. It consists of images of **dogs** and **cats**, making it ideal for training deep learning models, especially **Convolutional Neural Networks (CNNs)**.  \n\n---\n\n## 📂 Dataset Details  \n- **Total Images**: 25,000  \n- **Categories**:  \n  - 🐶 `dog`  \n  - 🐱 `cat`  \n- **Image Format**: `.jpg`  \n- **Image Size**: Varies (not uniform)  \n- **Labels**:  \n  - The filenames contain the class labels (e.g., `dog.1.jpg`, `cat.2.jpg`).  \n  - No separate label file; labels are inferred from filenames.  \n\n---\n\n## 📊 Data Organization  \nThe dataset is typically divided into:  \n- **Training Set**: Used for model training.  \n- **Validation/Test Set**: Used to assess model performance.  \n\n---\n\n## 🛠️ How to Use the Dataset  \n\n✔️ **Image Classification Tasks**: Build models to classify images as dogs or cats.  \n✔️ **Deep Learning (CNNs & Transfer Learning)**: Train **Convolutional Neural Networks (CNNs)** or apply **pre-trained models** like VGG16, ResNet, or EfficientNet for improved accuracy.  \n✔️ **Data Augmentation & Preprocessing**: Apply techniques like **resizing, normalization, flipping, and rotation** to enhance model generalization.  \n\n---\n\n## 🔗 Dataset Link  \n📥 **[Download from Kaggle](https://www.kaggle.com/competitions/dogs-vs-cats/data)**  \n\n---\n\n💡 *This dataset is perfect for image classification projects and deep learning experiments!* 🚀  \n","metadata":{}},{"cell_type":"markdown","source":"<h1 style=\"text-align:left; color:#6A5ACD; font-weight:bold; font-size:28px; font-family:Arial, sans-serif;\">Import Libraries</h1>","metadata":{}},{"cell_type":"code","source":"import numpy as np\nimport random\nimport pandas as pd\nimport matplotlib.pyplot as plt\nimport seaborn as sns\nfrom PIL import Image\nimport os, shutil\nfrom pathlib import Path\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.metrics import confusion_matrix\n\nimport tensorflow as tf\nfrom tensorflow import keras \nfrom tensorflow.keras import layers\nfrom tensorflow.keras.utils import image_dataset_from_directory\nfrom tensorflow.keras.preprocessing.image import load_img, img_to_array\n\n\nSEED = 42\nrandom.seed(SEED)\nnp.random.seed(SEED)\ntf.random.set_seed(SEED)\ntf.keras.utils.set_random_seed(SEED)\n\n\n#Remove Warnings\nimport warnings\nwarnings.filterwarnings('ignore')","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T16:22:04.171776Z","iopub.execute_input":"2025-03-25T16:22:04.172155Z","iopub.status.idle":"2025-03-25T16:22:04.206853Z","shell.execute_reply.started":"2025-03-25T16:22:04.172117Z","shell.execute_reply":"2025-03-25T16:22:04.205718Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<a id=\"1\"></a>\n# <div style=\"text-align:center; border-radius:25px 70px; padding:9px; color:white; margin:0; font-size:150%; font-family:Pacifico; background-color:#6A5ACD; overflow:hidden\"><b>Reading The Data</b></div>","metadata":{}},{"cell_type":"markdown","source":"## Unzipping the Dogs vs. Cats Dataset","metadata":{}},{"cell_type":"code","source":"!unzip -q \"/kaggle/input/dogs-vs-cats/train.zip\"","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:14.354175Z","iopub.execute_input":"2025-03-25T13:37:14.354787Z","iopub.status.idle":"2025-03-25T13:37:27.874102Z","shell.execute_reply.started":"2025-03-25T13:37:14.354756Z","shell.execute_reply":"2025-03-25T13:37:27.872994Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"!unzip -q \"/kaggle/input/dogs-vs-cats/test1.zip\"","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:27.875675Z","iopub.execute_input":"2025-03-25T13:37:27.876029Z","iopub.status.idle":"2025-03-25T13:37:34.448095Z","shell.execute_reply.started":"2025-03-25T13:37:27.875984Z","shell.execute_reply":"2025-03-25T13:37:34.446985Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Prepare Data","metadata":{}},{"cell_type":"code","source":"def prepare_data(train_path, val_size=0.15, test_size=0.15, random_state=42):\n\n    train_filenames = os.listdir(train_path)\n    train_categories = [1 if filename.split(\".\")[0] == 'dog' else 0 for filename in train_filenames]\n\n    df = pd.DataFrame({\n        'filename': train_filenames,\n        'category': train_categories\n    })\n\n    \n    train_df, temp_df = train_test_split(df, test_size=(val_size + test_size), stratify=df[\"category\"], random_state=random_state)\n\n    val_ratio = val_size / (val_size + test_size)  \n    val_df, test_df = train_test_split(temp_df, test_size=(1 - val_ratio), stratify=temp_df[\"category\"], random_state=random_state)\n\n    return train_df, val_df, test_df","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:34.449547Z","iopub.execute_input":"2025-03-25T13:37:34.449991Z","iopub.status.idle":"2025-03-25T13:37:34.456569Z","shell.execute_reply.started":"2025-03-25T13:37:34.449942Z","shell.execute_reply":"2025-03-25T13:37:34.455520Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train_path = \"/kaggle/working/train\"\ntrain_df, val_df, test_df = prepare_data(train_path)\nprint(f\"Total Training Images: {len(train_df)}\")\nprint(f\"Total Validation Images: {len(val_df)}\")\nprint(f\"Total Test Images: {len(test_df)}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:34.457825Z","iopub.execute_input":"2025-03-25T13:37:34.458100Z","iopub.status.idle":"2025-03-25T13:37:34.544677Z","shell.execute_reply.started":"2025-03-25T13:37:34.458076Z","shell.execute_reply":"2025-03-25T13:37:34.543800Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"train_df.head()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:34.545556Z","iopub.execute_input":"2025-03-25T13:37:34.545861Z","iopub.status.idle":"2025-03-25T13:37:34.567478Z","shell.execute_reply.started":"2025-03-25T13:37:34.545834Z","shell.execute_reply":"2025-03-25T13:37:34.566653Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"val_df.head()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:34.570346Z","iopub.execute_input":"2025-03-25T13:37:34.570615Z","iopub.status.idle":"2025-03-25T13:37:34.578874Z","shell.execute_reply.started":"2025-03-25T13:37:34.570591Z","shell.execute_reply":"2025-03-25T13:37:34.578024Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"test_df.head()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:34.580729Z","iopub.execute_input":"2025-03-25T13:37:34.581102Z","iopub.status.idle":"2025-03-25T13:37:34.600927Z","shell.execute_reply.started":"2025-03-25T13:37:34.581062Z","shell.execute_reply":"2025-03-25T13:37:34.599911Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Subsampled Dataset Directory Structure","metadata":{}},{"cell_type":"markdown","source":"The dataset is organized into **three main directories**: `train`, `validation`, and `test`, each containing images of cats and dogs.","metadata":{}},{"cell_type":"markdown","source":"![image.png](attachment:e1023c24-60e6-4ce8-9e8c-1346bdbebd3b.png)","metadata":{},"attachments":{"e1023c24-60e6-4ce8-9e8c-1346bdbebd3b.png":{"image/png":"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"}}},{"cell_type":"code","source":"def subsampled_dataset(df, source_path, base_dir, dataset_type):\n    dogs_dir = os.path.join(base_dir, dataset_type, \"dogs\")\n    cats_dir = os.path.join(base_dir, dataset_type, \"cats\")\n    os.makedirs(dogs_dir, exist_ok=True)\n    os.makedirs(cats_dir, exist_ok=True)\n    source_path = Path(source_path)\n\n    for category, num, folder in [(\"cat\", 0, cats_dir), (\"dog\", 1, dogs_dir)]:\n        for i, filename in enumerate(df[df[\"category\"] == num][\"filename\"]):\n            src = source_path / filename\n            dst = os.path.join(folder, f\"{category}{i}.jpg\") \n            shutil.copyfile(src, dst)\n\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:34.601964Z","iopub.execute_input":"2025-03-25T13:37:34.602235Z","iopub.status.idle":"2025-03-25T13:37:34.618673Z","shell.execute_reply.started":"2025-03-25T13:37:34.602213Z","shell.execute_reply":"2025-03-25T13:37:34.617822Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"base_dir = \"cats_vs_dogs\"\nsubsampled_dataset(train_df, train_path, base_dir, \"train\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:34.619845Z","iopub.execute_input":"2025-03-25T13:37:34.620079Z","iopub.status.idle":"2025-03-25T13:37:36.856121Z","shell.execute_reply.started":"2025-03-25T13:37:34.620057Z","shell.execute_reply":"2025-03-25T13:37:36.855109Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"subsampled_dataset(val_df, train_path, base_dir, \"validation\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:36.857201Z","iopub.execute_input":"2025-03-25T13:37:36.857505Z","iopub.status.idle":"2025-03-25T13:37:37.368079Z","shell.execute_reply.started":"2025-03-25T13:37:36.857481Z","shell.execute_reply":"2025-03-25T13:37:37.367187Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"subsampled_dataset(test_df, train_path, base_dir, \"test\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:37.368971Z","iopub.execute_input":"2025-03-25T13:37:37.369238Z","iopub.status.idle":"2025-03-25T13:37:37.870634Z","shell.execute_reply.started":"2025-03-25T13:37:37.369215Z","shell.execute_reply":"2025-03-25T13:37:37.869486Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"cats = len(os.listdir(\"/kaggle/working/cats_vs_dogs/train/cats\"))\ndogs = len(os.listdir(\"/kaggle/working/cats_vs_dogs/train/dogs\"))\ncats+dogs","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:37.871641Z","iopub.execute_input":"2025-03-25T13:37:37.871955Z","iopub.status.idle":"2025-03-25T13:37:37.888685Z","shell.execute_reply.started":"2025-03-25T13:37:37.871931Z","shell.execute_reply":"2025-03-25T13:37:37.887795Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"The number of training samples is **17,500**, so the total count of dogs and cats after subsampling is **17,500**.","metadata":{}},{"cell_type":"markdown","source":"## Show Sample From Train Data","metadata":{}},{"cell_type":"code","source":"def display_images(df, image_path, num_images=6):\n\n    sample_data = df.sample(n=num_images).reset_index(drop=True)\n\n    fig, axes = plt.subplots(1, num_images, figsize=(15, 5))\n    \n    for i, ax in enumerate(axes):\n        filename = sample_data.loc[i, \"filename\"]\n        img = Image.open(os.path.join(image_path, filename))\n\n        img = img.resize((128, 128))\n        \n        label = \"Dog\" if sample_data.loc[i, \"category\"] == 1 else \"Cat\"\n\n        ax.imshow(img)\n        ax.set_title(label, fontsize=20)\n        ax.axis(\"off\")\n\n    plt.tight_layout()\n    plt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:37.889798Z","iopub.execute_input":"2025-03-25T13:37:37.890136Z","iopub.status.idle":"2025-03-25T13:37:37.896079Z","shell.execute_reply.started":"2025-03-25T13:37:37.890101Z","shell.execute_reply":"2025-03-25T13:37:37.895184Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"display_images(train_df, train_path)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:37.896903Z","iopub.execute_input":"2025-03-25T13:37:37.897122Z","iopub.status.idle":"2025-03-25T13:37:38.727849Z","shell.execute_reply.started":"2025-03-25T13:37:37.897102Z","shell.execute_reply":"2025-03-25T13:37:38.726733Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<a id=\"1\"></a>\n# <div style=\"text-align:center; border-radius:25px 70px; padding:9px; color:white; margin:0; font-size:150%; font-family:Pacifico; background-color:#6A5ACD; overflow:hidden\"><b>Data Preprocessing</b></div>","metadata":{}},{"cell_type":"markdown","source":"## 📌 Preparing Image Data for a Deep Learning Model  \n\nBefore feeding data into a model, we need to **preprocess** it into floating-point tensors. Our dataset consists of **JPEG images**, so we must follow these steps:  \n\n### ✅ Steps to Prepare Image Data:\n1️⃣ **Read the image files** from disk.  \n2️⃣ **Decode JPEG images** into RGB pixel grids.  \n3️⃣ **Convert images** into floating-point tensors.  \n4️⃣ **Resize** images to a uniform shape (e.g., **180 × 180**).  \n5️⃣ **Batch** the images for efficient training (e.g., **batch size = 32**).  \n\n### ⚡ Using `image_dataset_from_directory()`\nKeras provides a **convenient function** called `image_dataset_from_directory()`, which automates these steps. It:  \n🔹 Scans subdirectories and assigns labels automatically.  \n🔹 Indexes and loads images efficiently.  \n🔹 Decodes and resizes images.  \n🔹 Packs images into shuffled batches, returning a **tf.data.Dataset**.  \n\nWith this approach, we can **seamlessly load and preprocess images** for deep learning models! 🚀  \n","metadata":{}},{"cell_type":"code","source":"new_base_dir = Path(base_dir)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:38.728939Z","iopub.execute_input":"2025-03-25T13:37:38.729302Z","iopub.status.idle":"2025-03-25T13:37:38.733717Z","shell.execute_reply.started":"2025-03-25T13:37:38.729259Z","shell.execute_reply":"2025-03-25T13:37:38.732868Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"#Training\ntrain_dataset = image_dataset_from_directory(\n    new_base_dir / \"train\",\n    image_size=(180, 180),\n    batch_size=32,\n    shuffle=True,\n    seed=42\n)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:38.734744Z","iopub.execute_input":"2025-03-25T13:37:38.735101Z","iopub.status.idle":"2025-03-25T13:37:42.922252Z","shell.execute_reply.started":"2025-03-25T13:37:38.735037Z","shell.execute_reply":"2025-03-25T13:37:42.921460Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"#Validation\nvalidation_dataset = image_dataset_from_directory(\n    new_base_dir / \"validation\",\n    image_size=(180, 180),\n    batch_size=32,\n    shuffle=True,\n    seed=42\n)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:42.923071Z","iopub.execute_input":"2025-03-25T13:37:42.923299Z","iopub.status.idle":"2025-03-25T13:37:43.212835Z","shell.execute_reply.started":"2025-03-25T13:37:42.923280Z","shell.execute_reply":"2025-03-25T13:37:43.211780Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"#Test\ntest_dataset = image_dataset_from_directory(\n    new_base_dir / \"test\",\n    image_size=(180, 180),\n    batch_size=32,\n    shuffle=True,\n    seed=42\n)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:43.213924Z","iopub.execute_input":"2025-03-25T13:37:43.214266Z","iopub.status.idle":"2025-03-25T13:37:43.489035Z","shell.execute_reply.started":"2025-03-25T13:37:43.214228Z","shell.execute_reply":"2025-03-25T13:37:43.487996Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"for data_batch, labels_batch in train_dataset:\n    print(\"data batch shape:\", data_batch.shape)   \n    print(\"labels batch shape:\", labels_batch.shape)\n    break\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:43.490033Z","iopub.execute_input":"2025-03-25T13:37:43.490321Z","iopub.status.idle":"2025-03-25T13:37:43.617445Z","shell.execute_reply.started":"2025-03-25T13:37:43.490285Z","shell.execute_reply":"2025-03-25T13:37:43.616407Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<a id=\"1\"></a>\n# <div style=\"text-align:center; border-radius:25px 70px; padding:9px; color:white; margin:0; font-size:150%; font-family:Pacifico; background-color:#6A5ACD; overflow:hidden\"><b>Building Model</b></div>","metadata":{}},{"cell_type":"markdown","source":"## Convolutional Neural Network (CNN) Architecture\n\nThe following diagram represents the architecture of our Convolutional Neural Network (CNN) used for image classification.\n\n![image.png](attachment:7c6b2247-a943-4350-918e-03256b196181.png)\n\n### **Architecture Breakdown:**\n1. **Input Layer**  \n   - The input is an image (e.g., a dog or cat) that enters the network.\n\n2. **Feature Extractors**  \n   - The CNN consists of multiple convolutional layers followed by pooling layers:\n     - **Layer 1**: Convolution (Conv) + Pooling\n     - **Layer 2**: Convolution (Conv) + Pooling\n     - **Layer 3**: Convolution (Conv) + Pooling\n     - **Layer 4**: Convolution (Conv) + Pooling\n     - **Layer 5**: Convolution (Conv) (No pooling)\n   - These layers extract meaningful features from the input image.\n\n3. **Classifier**  \n   - The extracted features are passed through a fully connected (dense) layer:\n     - **Flatten**: Converts the feature maps into a 1D array.\n     - **Dense**: Fully connected layer to learn complex patterns.\n\n4. **Output Layer**  \n   - A final layer provides the probability of the image belonging to a specific class (e.g., dog or cat).\n\nThis CNN is designed for efficient image classification by learning hierarchical features from raw image pixels. 🚀\n","metadata":{},"attachments":{"7c6b2247-a943-4350-918e-03256b196181.png":{"image/png":"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"}}},{"cell_type":"code","source":"inputs = keras.Input(shape=(180, 180, 3))  \nx = layers.Rescaling(1./255)(inputs)     \n\n# Conv Block 1\nx = layers.Conv2D(filters=32, kernel_size=3, activation=\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\n\n# Conv Block 2\nx = layers.Conv2D(filters=64, kernel_size=3, activation=\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\n\n# Conv Block 3\nx = layers.Conv2D(filters=128, kernel_size=3, activation=\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\n\n# Conv Block 4\nx = layers.Conv2D(filters=256, kernel_size=3, activation=\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\n\n# Conv Block 5\nx = layers.Conv2D(filters=256, kernel_size=3, activation=\"relu\")(x)\n\n# Flatten and Dense Layers\nx = layers.Flatten()(x)\noutputs = layers.Dense(1, activation=\"sigmoid\")(x)\nmodel = keras.Model(inputs=inputs, outputs=outputs)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:43.618524Z","iopub.execute_input":"2025-03-25T13:37:43.618850Z","iopub.status.idle":"2025-03-25T13:37:44.815542Z","shell.execute_reply.started":"2025-03-25T13:37:43.618820Z","shell.execute_reply":"2025-03-25T13:37:44.814671Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"model.compile(loss=\"binary_crossentropy\",\n      optimizer=\"rmsprop\",\n      metrics=[\"accuracy\"])","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:44.820576Z","iopub.execute_input":"2025-03-25T13:37:44.820874Z","iopub.status.idle":"2025-03-25T13:37:44.834454Z","shell.execute_reply.started":"2025-03-25T13:37:44.820851Z","shell.execute_reply":"2025-03-25T13:37:44.833607Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"callbacks = [\nkeras.callbacks.ModelCheckpoint(\n filepath=\"convnet_from_scratch.keras\",\n save_best_only=True,\n monitor=\"val_loss\")\n ]","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:44.836763Z","iopub.execute_input":"2025-03-25T13:37:44.837063Z","iopub.status.idle":"2025-03-25T13:37:44.843857Z","shell.execute_reply.started":"2025-03-25T13:37:44.837039Z","shell.execute_reply":"2025-03-25T13:37:44.842784Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"history = model.fit(\n    train_dataset,\n    epochs=30,\n    validation_data=validation_dataset,\n    callbacks=callbacks)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:37:44.844612Z","iopub.execute_input":"2025-03-25T13:37:44.844925Z","iopub.status.idle":"2025-03-25T13:44:43.041584Z","shell.execute_reply.started":"2025-03-25T13:37:44.844902Z","shell.execute_reply":"2025-03-25T13:44:43.040756Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"model.summary()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:44:43.042612Z","iopub.execute_input":"2025-03-25T13:44:43.042918Z","iopub.status.idle":"2025-03-25T13:44:43.069869Z","shell.execute_reply.started":"2025-03-25T13:44:43.042893Z","shell.execute_reply":"2025-03-25T13:44:43.068970Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Displaying curves of loss and accuracy during training","metadata":{}},{"cell_type":"code","source":"accuracy = history.history[\"accuracy\"]\nval_accuracy = history.history[\"val_accuracy\"]\nloss = history.history[\"loss\"]\nval_loss = history.history[\"val_loss\"]\nepochs = range(1, len(accuracy) + 1)\nplt.plot(epochs, accuracy, \"bo\", label=\"Training accuracy\")\nplt.plot(epochs, val_accuracy, \"b\", label=\"Validation accuracy\")\nplt.title(\"Training and validation accuracy\")\nplt.legend()\nplt.figure()\nplt.plot(epochs, loss, \"bo\", label=\"Training loss\")\nplt.plot(epochs, val_loss, \"b\", label=\"Validation loss\")\nplt.title(\"Training and validation loss\")\nplt.legend()\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:44:43.070788Z","iopub.execute_input":"2025-03-25T13:44:43.071031Z","iopub.status.idle":"2025-03-25T13:44:43.521121Z","shell.execute_reply.started":"2025-03-25T13:44:43.071011Z","shell.execute_reply":"2025-03-25T13:44:43.520129Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"##  Evaluating the model on the test set","metadata":{}},{"cell_type":"code","source":"test_model = keras.models.load_model(\"convnet_from_scratch.keras\")\ntest_loss, test_acc = test_model.evaluate(test_dataset) \nprint(f\"Test accuracy: {test_acc:.3f}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:44:43.522127Z","iopub.execute_input":"2025-03-25T13:44:43.522463Z","iopub.status.idle":"2025-03-25T13:44:46.809846Z","shell.execute_reply.started":"2025-03-25T13:44:43.522437Z","shell.execute_reply":"2025-03-25T13:44:46.809048Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## 📈 Training vs Validation Accuracy\n\nThe plot shows **training and validation accuracy** over **30 epochs**. \n\n#### 🔍 Observations:\n- **Training accuracy** (dots) quickly reaches **98%**.\n- **Validation accuracy** (line) improves but fluctuates around **90%**.\n- A **gap** between them suggests **overfitting**.\n\n### ⚠️ Possible Issues:\n- The model may be **memorizing** training data.\n- Fluctuations in validation accuracy indicate a need for **regularization**.\n\n### ✅ Next Steps:\n- Use **dropout** or **L2 regularization**.\n- Apply **data augmentation** for more diversity.\n- Implement **early stopping** to prevent overfitting.\n\nThis helps improve model generalization. 🚀\n","metadata":{}},{"cell_type":"markdown","source":"## Regularization with dropout","metadata":{}},{"cell_type":"code","source":"# Define the model with regularization\ninputs = keras.Input(shape=(180, 180, 3))\nx = layers.Rescaling(1./255)(inputs)\n\n# Conv Block 1\nx = layers.Conv2D(filters=32, kernel_size=3, activation=None)(x)  \nx = layers.BatchNormalization()(x)  # Batch normalization\nx = layers.Activation(\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\nx = layers.Dropout(0.3)(x) # Dropout\n\n# Conv Block 2\nx = layers.Conv2D(filters=64, kernel_size=3, activation=None)(x)\nx = layers.BatchNormalization()(x)\nx = layers.Activation(\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\nx = layers.Dropout(0.4)(x)\n\n# Conv Block 3\nx = layers.Conv2D(filters=128, kernel_size=3, activation=None)(x)\nx = layers.BatchNormalization()(x)\nx = layers.Activation(\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\nx = layers.Dropout(0.4)(x)\n\n# Conv Block 4\nx = layers.Conv2D(filters=256, kernel_size=3, activation=None)(x)\nx = layers.BatchNormalization()(x)\nx = layers.Activation(\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\nx = layers.Dropout(0.4)(x)\n\n# Conv Block 5\nx = layers.Conv2D(filters=256, kernel_size=3, activation=None)(x)\nx = layers.BatchNormalization()(x)\nx = layers.Activation(\"relu\")(x)\n\n# Flatten and Dense Layers\nx = layers.Flatten()(x)\nx = layers.Dropout(0.5)(x)  \noutputs = layers.Dense(1, activation=\"sigmoid\")(x)\n\nmodel1 = keras.Model(inputs=inputs, outputs=outputs)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:44:46.810722Z","iopub.execute_input":"2025-03-25T13:44:46.811010Z","iopub.status.idle":"2025-03-25T13:44:46.933016Z","shell.execute_reply.started":"2025-03-25T13:44:46.810986Z","shell.execute_reply":"2025-03-25T13:44:46.931806Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"model1.compile(loss=\"binary_crossentropy\",\n      optimizer=\"rmsprop\",\n      metrics=[\"accuracy\"])","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:44:46.934170Z","iopub.execute_input":"2025-03-25T13:44:46.934545Z","iopub.status.idle":"2025-03-25T13:44:46.943324Z","shell.execute_reply.started":"2025-03-25T13:44:46.934507Z","shell.execute_reply":"2025-03-25T13:44:46.942313Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"callbacks = [\nkeras.callbacks.ModelCheckpoint(\n filepath=\"convnet_from_scratch1.keras\",\n save_best_only=True,\n monitor=\"val_loss\")\n ]","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:44:46.944412Z","iopub.execute_input":"2025-03-25T13:44:46.944808Z","iopub.status.idle":"2025-03-25T13:44:46.959349Z","shell.execute_reply.started":"2025-03-25T13:44:46.944771Z","shell.execute_reply":"2025-03-25T13:44:46.958365Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"history = model1.fit(\n    train_dataset,\n    epochs=30,\n    validation_data=validation_dataset,\n    callbacks=callbacks)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:44:46.960287Z","iopub.execute_input":"2025-03-25T13:44:46.960568Z","iopub.status.idle":"2025-03-25T13:52:55.910118Z","shell.execute_reply.started":"2025-03-25T13:44:46.960543Z","shell.execute_reply":"2025-03-25T13:52:55.909340Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Displaying curves of loss and accuracy with dropout during training","metadata":{}},{"cell_type":"code","source":"accuracy = history.history[\"accuracy\"]\nval_accuracy = history.history[\"val_accuracy\"]\nloss = history.history[\"loss\"]\nval_loss = history.history[\"val_loss\"]\nepochs = range(1, len(accuracy) + 1)\nplt.plot(epochs, accuracy, \"bo\", label=\"Training accuracy\")\nplt.plot(epochs, val_accuracy, \"b\", label=\"Validation accuracy\")\nplt.title(\"Training and validation accuracy\")\nplt.legend()\nplt.figure()\nplt.plot(epochs, loss, \"bo\", label=\"Training loss\")\nplt.plot(epochs, val_loss, \"b\", label=\"Validation loss\")\nplt.title(\"Training and validation loss\")\nplt.legend()\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:52:55.911068Z","iopub.execute_input":"2025-03-25T13:52:55.911300Z","iopub.status.idle":"2025-03-25T13:52:56.368404Z","shell.execute_reply.started":"2025-03-25T13:52:55.911280Z","shell.execute_reply":"2025-03-25T13:52:56.367341Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"##  Evaluating the model with dropout on the test set","metadata":{}},{"cell_type":"code","source":"def plot_confusion_matrix(model, test_dataset, class_names=[\"cat\", \"dog\"]):\n    y_true = []\n    y_pred = []\n    \n    for images, labels in test_dataset:\n        preds = model.predict(images, verbose=0)\n        # Convert probabilities to binary predictions (threshold = 0.5)\n        preds_binary = (preds > 0.5).astype(int).flatten()\n        y_true.extend(labels.numpy())\n        y_pred.extend(preds_binary)\n    \n    # Convert to numpy arrays\n    y_true = np.array(y_true)\n    y_pred = np.array(y_pred)\n    \n    # Compute confusion matrix\n    cm = confusion_matrix(y_true, y_pred)\n    \n    # Plot confusion matrix\n    plt.figure(figsize=(8, 6))\n    sns.heatmap(cm, annot=True, fmt=\"d\", cmap=\"Blues\", \n                xticklabels=class_names, yticklabels=class_names)\n    plt.title(\"Confusion Matrix\")\n    plt.xlabel(\"Predicted Label\")\n    plt.ylabel(\"True Label\")\n    plt.show()\n    \n    tn, fp, fn, tp = cm.ravel()\n    print(f\"True Negatives (cat as cat): {tn}\")\n    print(f\"False Positives (cat as dog): {fp}\")\n    print(f\"False Negatives (dog as cat): {fn}\")\n    print(f\"True Positives (dog as dog): {tp}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:48:08.603644Z","iopub.execute_input":"2025-03-25T15:48:08.604053Z","iopub.status.idle":"2025-03-25T15:48:08.611206Z","shell.execute_reply.started":"2025-03-25T15:48:08.604024Z","shell.execute_reply":"2025-03-25T15:48:08.610051Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"test_model = keras.models.load_model(\"convnet_from_scratch1.keras\")\ntest_loss, test_acc = test_model.evaluate(test_dataset) \nprint(f\"Test accuracy: {test_acc:.3f}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:52:56.369425Z","iopub.execute_input":"2025-03-25T13:52:56.369792Z","iopub.status.idle":"2025-03-25T13:53:00.021028Z","shell.execute_reply.started":"2025-03-25T13:52:56.369758Z","shell.execute_reply":"2025-03-25T13:53:00.020014Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plot_confusion_matrix(keras.models.load_model(\"convnet_from_scratch1.keras\"), test_dataset)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:50:41.901293Z","iopub.execute_input":"2025-03-25T15:50:41.902079Z","iopub.status.idle":"2025-03-25T15:50:53.262205Z","shell.execute_reply.started":"2025-03-25T15:50:41.902043Z","shell.execute_reply":"2025-03-25T15:50:53.261271Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"def display_predictions(model, test_dataset, class_names=[\"cat\", \"dog\"], num_images=6):\n\n    images, labels = next(iter(test_dataset))\n    \n    # Predict probabilities\n    preds = model.predict(images, verbose=0)\n    preds_binary = (preds > 0.5).astype(int).flatten()\n    \n    # Convert to numpy arrays\n    images = images.numpy()\n    labels = labels.numpy()\n    \n    # Set up the plot\n    plt.figure(figsize=(15, 10))\n    for i in range(min(num_images, len(images))):\n        plt.subplot(2, 3, i + 1)  # 2 rows, 3 columns\n        plt.imshow(images[i].astype(\"uint8\"))  # Assuming images are normalized\n        actual_label = class_names[labels[i]]\n        pred_label = class_names[preds_binary[i]]\n        # Set title color: green if correct, red if wrong\n        title_color = \"green\" if actual_label == pred_label else \"red\"\n        plt.title(f\"Actual: {actual_label}\\nPred: {pred_label}\", color=title_color, fontsize=12)\n        plt.axis(\"off\")\n    plt.tight_layout()\n    plt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:52:44.146756Z","iopub.execute_input":"2025-03-25T15:52:44.147195Z","iopub.status.idle":"2025-03-25T15:52:44.154136Z","shell.execute_reply.started":"2025-03-25T15:52:44.147161Z","shell.execute_reply":"2025-03-25T15:52:44.153059Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"display_predictions(keras.models.load_model(\"convnet_from_scratch1.keras\"), test_dataset)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:53:08.799053Z","iopub.execute_input":"2025-03-25T15:53:08.799420Z","iopub.status.idle":"2025-03-25T15:53:10.878838Z","shell.execute_reply.started":"2025-03-25T15:53:08.799388Z","shell.execute_reply":"2025-03-25T15:53:10.877706Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## CNN Model Training Summary (with Dropout)  \n\n- **Training Accuracy** reaches **~95%**, while **Validation Accuracy** fluctuates between **90-92%**, with a **Test Accuracy** of **92%**.  \n- **Dropout (0.3, 0.4, 0.5)** effectively mitigates overfitting, though some generalization challenges persist.  \n- **Possible Improvements**:  \n  - Data Augmentation (if not already applied)  \n  - Early Stopping to prevent overtraining  \n  - Hyperparameter tuning for better generalization\n\n🚀 **Conclusion**: The model delivers strong performance, but further refinements can enhance its stability and generalization. By optimizing key aspects such as data augmentation, early stopping, and hyperparameter tuning, we can push its accuracy and reliability even further!  \n","metadata":{}},{"cell_type":"markdown","source":"<a id=\"1\"></a>\n# <div style=\"text-align:center; border-radius:25px 70px; padding:9px; color:white; margin:0; font-size:150%; font-family:Pacifico; background-color:#6A5ACD; overflow:hidden\"><b>Data Augmentation</b></div>","metadata":{}},{"cell_type":"markdown","source":"## Data Augmentation Layers Overview  \n\nKeras provides several **data augmentation** layers to enhance model generalization:  \n\n- **`RandomFlip(\"horizontal\")`**: Randomly flips images horizontally (50% probability).  \n- **`RandomRotation(0.1)`**: Rotates images within a range of **±10%** of a full circle (**±36°**).  \n- **`RandomZoom(0.2)`**: Randomly zooms images in or out by **±20%**.  \n\nThese augmentations help improve model robustness and **prevent overfitting**.  ","metadata":{}},{"cell_type":"code","source":"data_augmentation = keras.Sequential(\n    [\n     layers.RandomFlip(\"horizontal\"),\n     layers.RandomRotation(0.1),\n     layers.RandomZoom(0.2),\n    ])","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:53:00.022203Z","iopub.execute_input":"2025-03-25T13:53:00.022588Z","iopub.status.idle":"2025-03-25T13:53:00.036957Z","shell.execute_reply.started":"2025-03-25T13:53:00.022549Z","shell.execute_reply":"2025-03-25T13:53:00.035966Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"### Data Augmentation and Dropout in Model Training  \n\n- **Data Augmentation** ensures the model never sees the exact same input twice, but since it only remixes existing data, it may not fully eliminate overfitting.   \n- **Inference Behavior**:  \n  - Like Dropout, data augmentation layers are **inactive** during inference.  \n  - During evaluation (`predict()` or `evaluate()`), the model behaves as if data augmentation and Dropout were never applied.  \n\n📌 **Key Takeaway**: Data augmentation and Dropout help improve generalization, but additional techniques may still be needed to prevent overfitting entirely.\n","metadata":{}},{"cell_type":"markdown","source":"## Displaying some randomly augmented training images","metadata":{}},{"cell_type":"code","source":"plt.figure(figsize=(15, 15)) \nfor images, _ in train_dataset.take(1):   \n    for i in range(9):\n       augmented_images = data_augmentation(images)  \n       ax = plt.subplot(3, 3, i + 1)\n       plt.imshow(augmented_images[0].numpy().astype(\"uint8\"))   \n       plt.axis(\"off\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:53:00.037825Z","iopub.execute_input":"2025-03-25T13:53:00.038164Z","iopub.status.idle":"2025-03-25T13:53:02.659598Z","shell.execute_reply.started":"2025-03-25T13:53:00.038135Z","shell.execute_reply":"2025-03-25T13:53:02.658266Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"# Define the model with regularization\ninputs = keras.Input(shape=(180, 180, 3))\nx = data_augmentation(inputs)\nx = layers.Rescaling(1./255)(x)\n\n# Conv Block 1\nx = layers.Conv2D(filters=32, kernel_size=3, activation=None)(x)  \nx = layers.BatchNormalization()(x)  # Batch normalization\nx = layers.Activation(\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\nx = layers.Dropout(0.3)(x) # Dropout\n\n# Conv Block 2\nx = layers.Conv2D(filters=64, kernel_size=3, activation=None)(x)\nx = layers.BatchNormalization()(x)\nx = layers.Activation(\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\nx = layers.Dropout(0.4)(x)\n\n# Conv Block 3\nx = layers.Conv2D(filters=128, kernel_size=3, activation=None)(x)\nx = layers.BatchNormalization()(x)\nx = layers.Activation(\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\nx = layers.Dropout(0.4)(x)\n\n# Conv Block 4\nx = layers.Conv2D(filters=256, kernel_size=3, activation=None)(x)\nx = layers.BatchNormalization()(x)\nx = layers.Activation(\"relu\")(x)\nx = layers.MaxPooling2D(pool_size=2)(x)\nx = layers.Dropout(0.4)(x)\n\n# Conv Block 5\nx = layers.Conv2D(filters=256, kernel_size=3, activation=None)(x)\nx = layers.BatchNormalization()(x)\nx = layers.Activation(\"relu\")(x)\n\n# Flatten and Dense Layers\nx = layers.Flatten()(x)\nx = layers.Dropout(0.5)(x)  \noutputs = layers.Dense(1, activation=\"sigmoid\")(x)\n\nmodel2 = keras.Model(inputs=inputs, outputs=outputs)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:53:02.661097Z","iopub.execute_input":"2025-03-25T13:53:02.661523Z","iopub.status.idle":"2025-03-25T13:53:02.800051Z","shell.execute_reply.started":"2025-03-25T13:53:02.661485Z","shell.execute_reply":"2025-03-25T13:53:02.798989Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"model2.compile(loss=\"binary_crossentropy\",\n      optimizer=\"rmsprop\",\n      metrics=[\"accuracy\"])","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:53:02.801109Z","iopub.execute_input":"2025-03-25T13:53:02.801345Z","iopub.status.idle":"2025-03-25T13:53:02.809410Z","shell.execute_reply.started":"2025-03-25T13:53:02.801324Z","shell.execute_reply":"2025-03-25T13:53:02.808578Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"callbacks = [\n    keras.callbacks.ModelCheckpoint(\n    filepath=\"convnet_from_scratch_with_augmentation.keras\",\n    save_best_only=True,\n     monitor=\"val_loss\")\n  ]","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:53:02.810418Z","iopub.execute_input":"2025-03-25T13:53:02.810738Z","iopub.status.idle":"2025-03-25T13:53:02.825296Z","shell.execute_reply.started":"2025-03-25T13:53:02.810683Z","shell.execute_reply":"2025-03-25T13:53:02.824475Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Training the Model with Data Augmentation & Dropout  \n\n- **Approach**: Utilize **data augmentation** and **dropout** to improve generalization.  \n- **Expectation**: Overfitting is expected to occur much later in training.  \n- **Training Strategy**: Increase the number of **epochs to 100** (3x the usual) to allow the model to learn effectively before overfitting.  \n\n🚀 **Goal**: Achieve better model performance with improved generalization!","metadata":{}},{"cell_type":"code","source":"history = model2.fit(\n    train_dataset,\n    epochs=100,\n    validation_data=validation_dataset,\n    callbacks=callbacks)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T13:53:02.826128Z","iopub.execute_input":"2025-03-25T13:53:02.826418Z","iopub.status.idle":"2025-03-25T14:46:43.185413Z","shell.execute_reply.started":"2025-03-25T13:53:02.826393Z","shell.execute_reply":"2025-03-25T14:46:43.184605Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"accuracy = history.history[\"accuracy\"]\nval_accuracy = history.history[\"val_accuracy\"]\nloss = history.history[\"loss\"]\nval_loss = history.history[\"val_loss\"]\nepochs = range(1, len(accuracy) + 1)\nplt.plot(epochs, accuracy, \"bo\", label=\"Training accuracy\")\nplt.plot(epochs, val_accuracy, \"b\", label=\"Validation accuracy\")\nplt.title(\"Training and validation accuracy\")\nplt.legend()\nplt.figure()\nplt.plot(epochs, loss, \"bo\", label=\"Training loss\")\nplt.plot(epochs, val_loss, \"b\", label=\"Validation loss\")\nplt.title(\"Training and validation loss\")\nplt.legend()\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T14:46:43.186750Z","iopub.execute_input":"2025-03-25T14:46:43.187002Z","iopub.status.idle":"2025-03-25T14:46:43.635059Z","shell.execute_reply.started":"2025-03-25T14:46:43.186979Z","shell.execute_reply":"2025-03-25T14:46:43.634084Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"test_model = keras.models.load_model(\"convnet_from_scratch_with_augmentation.keras\")\ntest_loss, test_acc = test_model.evaluate(test_dataset)\nprint(f\"Test accuracy: {test_acc:.3f}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T14:46:43.636239Z","iopub.execute_input":"2025-03-25T14:46:43.636606Z","iopub.status.idle":"2025-03-25T14:46:46.704996Z","shell.execute_reply.started":"2025-03-25T14:46:43.636569Z","shell.execute_reply":"2025-03-25T14:46:46.704122Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plot_confusion_matrix(keras.models.load_model(\"convnet_from_scratch_with_augmentation.keras\"), test_dataset)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:54:34.847461Z","iopub.execute_input":"2025-03-25T15:54:34.847856Z","iopub.status.idle":"2025-03-25T15:54:44.849765Z","shell.execute_reply.started":"2025-03-25T15:54:34.847825Z","shell.execute_reply":"2025-03-25T15:54:44.848568Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"display_predictions(keras.models.load_model(\"convnet_from_scratch_with_augmentation.keras\"), test_dataset)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:55:10.045140Z","iopub.execute_input":"2025-03-25T15:55:10.045483Z","iopub.status.idle":"2025-03-25T15:55:11.827393Z","shell.execute_reply.started":"2025-03-25T15:55:10.045458Z","shell.execute_reply":"2025-03-25T15:55:11.826120Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## CNN Model Training Summary (with Data Augmentation)  \n\n- **Strong Performance**: The model achieves **95.1% test accuracy**, showing effective learning.  \n- **Data Augmentation Effect**: Likely helped improve generalization, preventing overfitting.  \n\n### Next Step: Transfer Learning  \nTo further enhance performance, we will apply **transfer learning** by fine-tuning a **pretrained CNN**, leveraging powerful feature extraction from large datasets while allowing the model to adapt to our specific task and further improve accuracy.  \n","metadata":{}},{"cell_type":"markdown","source":"<a id=\"1\"></a>\n# <div style=\"text-align:center; border-radius:25px 70px; padding:9px; color:white; margin:0; font-size:150%; font-family:Pacifico; background-color:#6A5ACD; overflow:hidden\"><b>Transfer Learning</b></div>","metadata":{}},{"cell_type":"markdown","source":"## Using Pretrained Models for Small Image Datasets  \n\n- **Pretrained Models**: Previously trained on large datasets (e.g., ImageNet).  \n- **Benefit**: Leverages learned features for different tasks, even with different classes.  \n- **Example**: ImageNet-trained model repurposed for **cats vs. dogs** classification.  \n- **Chosen Model**: **VGG16** (developed in 2014, simple and effective).  \n- **Two Approaches**:  \n  1. **Feature Extraction**  \n  2. **Fine-Tuning**  \n\n🚀 **Next Step**: Implement **Feature Extraction** and **Fine-Tuning**!","metadata":{}},{"cell_type":"markdown","source":"![image.png](attachment:cd52727f-d94d-4bb2-800a-b51321b1decd.png)","metadata":{},"attachments":{"cd52727f-d94d-4bb2-800a-b51321b1decd.png":{"image/png":"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"}}},{"cell_type":"markdown","source":"## Feature Extraction With Data Augmentation","metadata":{}},{"cell_type":"markdown","source":"### The model consists of three main stages:  \n\n1. **Data Augmentation Stage**  \n   - Applies random transformations to input images to improve generalization.  \n\n2. **Frozen Convolutional Base**  \n   - Uses a pretrained CNN (e.g., VGG16) with **frozen weights** to extract meaningful features.  \n   - The **top classification layer is removed** and replaced with a new classifier.  \n\n3. **Dense Classifier**  \n   - A fully connected layer that maps extracted features to final class predictions (**Dog or Cat**).  \n\n---\n\n- The **convolutional base is frozen** to prevent its weights from being updated during training.  \n- Freezing prevents large weight updates from destroying learned representations.  \n- In Keras, we remove the top layer by setting `include_top = False`.  \n- We then **add a new classification layer** specific to our task (**Dog or Cat**).  \n- To freeze a layer, we set `trainable = False`.  \n","metadata":{}},{"cell_type":"code","source":"conv_base  = keras.applications.vgg16.VGG16(\n    weights=\"imagenet\",\n    include_top=False,\n    input_shape=(180, 180, 3))","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T14:46:46.706039Z","iopub.execute_input":"2025-03-25T14:46:46.706339Z","iopub.status.idle":"2025-03-25T14:46:47.375107Z","shell.execute_reply.started":"2025-03-25T14:46:46.706313Z","shell.execute_reply":"2025-03-25T14:46:47.374312Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"conv_base.summary()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T14:46:47.376033Z","iopub.execute_input":"2025-03-25T14:46:47.376307Z","iopub.status.idle":"2025-03-25T14:46:47.405513Z","shell.execute_reply.started":"2025-03-25T14:46:47.376282Z","shell.execute_reply":"2025-03-25T14:46:47.404812Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":" conv_base.trainable = False","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T14:46:47.406479Z","iopub.execute_input":"2025-03-25T14:46:47.406862Z","iopub.status.idle":"2025-03-25T14:46:47.411414Z","shell.execute_reply.started":"2025-03-25T14:46:47.406826Z","shell.execute_reply":"2025-03-25T14:46:47.410391Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"inputs = keras.Input(shape=(180, 180, 3))\nx = data_augmentation(inputs)          \nx = keras.applications.vgg16.preprocess_input(x)   \nx = conv_base(x)\nx = layers.Flatten()(x)\nx = layers.Dense(256)(x)\nx = layers.Dropout(0.5)(x)\noutputs = layers.Dense(1, activation=\"sigmoid\")(x)\n\nmodel3 = keras.Model(inputs, outputs)\n","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T14:46:47.412341Z","iopub.execute_input":"2025-03-25T14:46:47.412609Z","iopub.status.idle":"2025-03-25T14:46:47.458030Z","shell.execute_reply.started":"2025-03-25T14:46:47.412585Z","shell.execute_reply":"2025-03-25T14:46:47.457263Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"model3.compile(loss=\"binary_crossentropy\",\n      optimizer=\"rmsprop\",\n      metrics=[\"accuracy\"])","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T14:46:47.458910Z","iopub.execute_input":"2025-03-25T14:46:47.459152Z","iopub.status.idle":"2025-03-25T14:46:47.466792Z","shell.execute_reply.started":"2025-03-25T14:46:47.459131Z","shell.execute_reply":"2025-03-25T14:46:47.466015Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"callbacks = [\n    keras.callbacks.ModelCheckpoint(\n    filepath=\"feature_extraction_with_data_augmentation.keras\",\n    save_best_only=True,\n    monitor=\"val_loss\")\n ]","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T14:46:47.467581Z","iopub.execute_input":"2025-03-25T14:46:47.467848Z","iopub.status.idle":"2025-03-25T14:46:47.481507Z","shell.execute_reply.started":"2025-03-25T14:46:47.467825Z","shell.execute_reply":"2025-03-25T14:46:47.480420Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"history = model3.fit(\n    train_dataset,\n    epochs=50,\n    validation_data=validation_dataset,\n    callbacks=callbacks)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T14:46:47.482479Z","iopub.execute_input":"2025-03-25T14:46:47.482798Z","iopub.status.idle":"2025-03-25T15:20:33.883640Z","shell.execute_reply.started":"2025-03-25T14:46:47.482767Z","shell.execute_reply":"2025-03-25T15:20:33.882825Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"accuracy = history.history[\"accuracy\"]\nval_accuracy = history.history[\"val_accuracy\"]\nloss = history.history[\"loss\"]\nval_loss = history.history[\"val_loss\"]\nepochs = range(1, len(accuracy) + 1)\nplt.plot(epochs, accuracy, \"bo\", label=\"Training accuracy\")\nplt.plot(epochs, val_accuracy, \"b\", label=\"Validation accuracy\")\nplt.title(\"Training and validation accuracy\")\nplt.legend()\nplt.figure()\nplt.plot(epochs, loss, \"bo\", label=\"Training loss\")\nplt.plot(epochs, val_loss, \"b\", label=\"Validation loss\")\nplt.title(\"Training and validation loss\")\nplt.legend()\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:20:33.884844Z","iopub.execute_input":"2025-03-25T15:20:33.885217Z","iopub.status.idle":"2025-03-25T15:20:34.332830Z","shell.execute_reply.started":"2025-03-25T15:20:33.885180Z","shell.execute_reply":"2025-03-25T15:20:34.331591Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"test_model = keras.models.load_model(\"feature_extraction_with_data_augmentation.keras\")\ntest_loss, test_acc = test_model.evaluate(test_dataset)\nprint(f\"Test accuracy: {test_acc:.3f}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:20:34.334058Z","iopub.execute_input":"2025-03-25T15:20:34.334479Z","iopub.status.idle":"2025-03-25T15:20:42.097979Z","shell.execute_reply.started":"2025-03-25T15:20:34.334427Z","shell.execute_reply":"2025-03-25T15:20:42.096971Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plot_confusion_matrix(keras.models.load_model(\"feature_extraction_with_data_augmentation.keras\"), test_dataset)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:55:57.470496Z","iopub.execute_input":"2025-03-25T15:55:57.470887Z","iopub.status.idle":"2025-03-25T15:56:12.791469Z","shell.execute_reply.started":"2025-03-25T15:55:57.470855Z","shell.execute_reply":"2025-03-25T15:56:12.790413Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"display_predictions(keras.models.load_model(\"feature_extraction_with_data_augmentation.keras\"), test_dataset)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:56:26.603063Z","iopub.execute_input":"2025-03-25T15:56:26.603452Z","iopub.status.idle":"2025-03-25T15:56:28.687637Z","shell.execute_reply.started":"2025-03-25T15:56:26.603421Z","shell.execute_reply":"2025-03-25T15:56:28.686510Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"## Fine-Tuning","metadata":{}},{"cell_type":"markdown","source":"### Fine-Tuning Process  \n\n1. **Add Custom Network**  \n   - Place a new classification head on top of a pretrained base network.  \n\n2. **Freeze the Base Network**  \n   - Prevents weight updates to retain learned features.  \n\n3. **Train the Custom Layers**  \n   - Only the newly added layers are trained initially.  \n\n4. **Unfreeze Some Base Layers**  \n   - Fine-tune higher layers while keeping lower layers frozen.  \n   - Avoid unfreezing **batch normalization** layers (not present in VGG16).  \n\n5. **Joint Training**  \n   - Train both the unfrozen base layers and the custom classifier together.  \n\nWe already completed the first three steps during feature extraction. Now, let's proceed with step 4:  \nwe’ll unfreeze the `conv_base` and then selectively freeze individual layers inside it.\n\n### Why Not Fine-Tune the Entire Model?  \n- **Lower layers** learn **generic features** (edges, textures) → already useful.  \n- **Higher layers** learn **task-specific features** → benefit most from fine-tuning.  \n- Fine-tuning too many layers **increases overfitting risk** (15M+ parameters in VGG16).\n\n### Fine-Tuning Strategy  \n\n- **Focus on fine-tuning the top 2-3 layers** to adapt high-level features for the new task.  \n- **Keep lower layers frozen** to retain foundational patterns like edges and textures.  \n- **Balances adaptation and generalization**, minimizing overfitting while improving performance.\n\n### Fine-Tuning the Model  \n\n- We begin **fine-tuning** using the **RMSprop optimizer** with a **very low learning rate**.  \n- A low learning rate helps **limit modifications** to the representations of the fine-tuned layers.  \n- **Large updates** may negatively impact learned features, so careful tuning is essential.  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"}}},{"cell_type":"code","source":"conv_base.trainable = True\nfor layer in conv_base.layers[:-8]:\n    layer.trainable = False","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:59:00.927141Z","iopub.execute_input":"2025-03-25T15:59:00.927528Z","iopub.status.idle":"2025-03-25T15:59:00.931977Z","shell.execute_reply.started":"2025-03-25T15:59:00.927492Z","shell.execute_reply":"2025-03-25T15:59:00.930927Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"model3.compile(loss=\"binary_crossentropy\",\n      optimizer=keras.optimizers.RMSprop(learning_rate=1e-5),\n      metrics=[\"accuracy\"])","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:59:02.514683Z","iopub.execute_input":"2025-03-25T15:59:02.515050Z","iopub.status.idle":"2025-03-25T15:59:02.524349Z","shell.execute_reply.started":"2025-03-25T15:59:02.515022Z","shell.execute_reply":"2025-03-25T15:59:02.523326Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"callbacks = [\n    keras.callbacks.ModelCheckpoint(\n    filepath=\"fine_tuning.keras\",\n    save_best_only=True,\n    monitor=\"val_loss\")\n ]","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:59:02.770660Z","iopub.execute_input":"2025-03-25T15:59:02.771072Z","iopub.status.idle":"2025-03-25T15:59:02.775221Z","shell.execute_reply.started":"2025-03-25T15:59:02.771038Z","shell.execute_reply":"2025-03-25T15:59:02.774178Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"history = model3.fit(\n    train_dataset,\n    epochs=30,\n    validation_data=validation_dataset,\n    callbacks=callbacks)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:59:04.763352Z","iopub.execute_input":"2025-03-25T15:59:04.763672Z","iopub.status.idle":"2025-03-25T16:22:04.170047Z","shell.execute_reply.started":"2025-03-25T15:59:04.763645Z","shell.execute_reply":"2025-03-25T16:22:04.168978Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"accuracy = history.history[\"accuracy\"]\nval_accuracy = history.history[\"val_accuracy\"]\nloss = history.history[\"loss\"]\nval_loss = history.history[\"val_loss\"]\nepochs = range(1, len(accuracy) + 1)\nplt.plot(epochs, accuracy, \"bo\", label=\"Training accuracy\")\nplt.plot(epochs, val_accuracy, \"b\", label=\"Validation accuracy\")\nplt.title(\"Training and validation accuracy\")\nplt.legend()\nplt.figure()\nplt.plot(epochs, loss, \"bo\", label=\"Training loss\")\nplt.plot(epochs, val_loss, \"b\", label=\"Validation loss\")\nplt.title(\"Training and validation loss\")\nplt.legend()\nplt.show()","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T15:46:26.727583Z","iopub.execute_input":"2025-03-25T15:46:26.728015Z","iopub.status.idle":"2025-03-25T15:46:27.183806Z","shell.execute_reply.started":"2025-03-25T15:46:26.727985Z","shell.execute_reply":"2025-03-25T15:46:27.182510Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"model = keras.models.load_model(\"fine_tuning.keras\")\ntest_loss, test_acc = model.evaluate(test_dataset) \nprint(f\"Test accuracy: {test_acc:.3f}\")","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T16:22:11.295653Z","iopub.execute_input":"2025-03-25T16:22:11.296118Z","iopub.status.idle":"2025-03-25T16:22:19.318116Z","shell.execute_reply.started":"2025-03-25T16:22:11.296079Z","shell.execute_reply":"2025-03-25T16:22:19.317237Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"plot_confusion_matrix(keras.models.load_model(\"fine_tuning.keras\"), test_dataset)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T16:22:27.523179Z","iopub.execute_input":"2025-03-25T16:22:27.523519Z","iopub.status.idle":"2025-03-25T16:22:42.781738Z","shell.execute_reply.started":"2025-03-25T16:22:27.523490Z","shell.execute_reply":"2025-03-25T16:22:42.780668Z"}},"outputs":[],"execution_count":null},{"cell_type":"code","source":"display_predictions(keras.models.load_model(\"fine_tuning.keras\"), test_dataset)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T16:22:42.783209Z","iopub.execute_input":"2025-03-25T16:22:42.783624Z","iopub.status.idle":"2025-03-25T16:22:44.953186Z","shell.execute_reply.started":"2025-03-25T16:22:42.783584Z","shell.execute_reply":"2025-03-25T16:22:44.951946Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<a id=\"1\"></a>\n# <div style=\"text-align:center; border-radius:25px 70px; padding:9px; color:white; margin:0; font-size:150%; font-family:Pacifico; background-color:#6A5ACD; overflow:hidden\"><b>Submission</b></div>","metadata":{}},{"cell_type":"code","source":"model = keras.models.load_model(\"fine_tuning.keras\")\ntest_dir = \"/kaggle/working/test1\"\n\ndef load_test_images(test_dir, image_size=(180, 180)):\n    image_ids = []\n    images = []\n    for filename in sorted(os.listdir(test_dir)):\n        if filename.endswith(\".jpg\"):\n            img_path = os.path.join(test_dir, filename)\n            img = load_img(img_path, target_size=image_size)\n            img_array = img_to_array(img) / 255.0\n            images.append(img_array)\n            image_ids.append(int(filename.split(\".\")[0]))\n    return np.array(images), image_ids\n\ntest_images, test_ids = load_test_images(test_dir)\npredictions = model.predict(test_images, batch_size=32, verbose=1)\npredictions = (predictions > 0.5).astype(int).flatten()\n\nsubmission_df = pd.DataFrame({\"id\": test_ids, \"label\": predictions})\nsubmission_df = submission_df.sort_values(by=\"id\")\nsubmission_df.to_csv(\"/kaggle/working/submission.csv\", index=False)","metadata":{"trusted":true,"execution":{"iopub.status.busy":"2025-03-25T16:25:45.359153Z","iopub.execute_input":"2025-03-25T16:25:45.359613Z","iopub.status.idle":"2025-03-25T16:26:43.610496Z","shell.execute_reply.started":"2025-03-25T16:25:45.359578Z","shell.execute_reply":"2025-03-25T16:26:43.609661Z"}},"outputs":[],"execution_count":null},{"cell_type":"markdown","source":"<a id=\"1\"></a>\n# <div style=\"text-align:center; border-radius:25px 70px; padding:9px; color:white; margin:0; font-size:150%; font-family:Pacifico; background-color:#6A5ACD; overflow:hidden\"><b>Conclusion</b></div>","metadata":{}},{"cell_type":"markdown","source":"## 📌 **Final Conclusion: CNN Model Performance & Optimization**   \n\n### 🔹 Baseline Model (No Dropout)  \n- **Training Accuracy:** 100%  \n- **Validation Accuracy:** ~90% (with fluctuations)  \n- **Issue:** Overfitting due to lack of regularization  \n\n### 🔹 Model with Dropout  \n- **Training Accuracy:** ~95%  \n- **Validation Accuracy:** 90-92%  \n- **Test Accuracy:** 92%  \n- **Effect of Dropout (0.3, 0.4, 0.5):** Reduced overfitting, but generalization challenges remain.  \n\n### 🔹 Data Augmentation  \n- **Test Accuracy:** **95.1%**  \n- **Impact:** Improved generalization, better than previous models.  \n\n### 🔹 Transfer Learning (Feature Extraction)  \n- **Test Accuracy:** **98.2%**  \n- **Impact:** Significant performance boost using pretrained networks.  \n\n### 🔹 Fine-Tuned Model  \n- **Test Accuracy:** **98.7%**  \n- **Impact:** Fine-tuning improved feature learning, **boosting accuracy further**. \n---\n## 🔍 **Key Learnings & Observations:** \n- **Data Augmentation & Dropout** helped improve generalization and reduced overfitting.  \n- **Transfer Learning** significantly boosts accuracy.  \n- **Fine-Tuning** significantly **enhanced accuracy and stability**\n---\n# **🏆 Conclusion:**  \nThe model has achieved **excellent accuracy (98.7%)** after fine-tuning. While generalization has improved, further refinements in **regularization, hyperparameter tuning, and model ensembling** could enhance stability.  \n\nOverall, this CNN delivers **high performance and strong generalization**, making it a **solid foundation for further AI applications.** 🚀\n\n---\n## 🙌 Thank You for Checking Out This Notebook!  \nIf you found it helpful, please **leave feedback or an upvote**! 🚀  \n","metadata":{}}]}