📘 CNN-Image-Classification-System

A modern and highly accurate Cat vs Dog Image Classification System built using:

• Transfer Learning (97% accuracy)
• TensorFlow / Keras
• Flask Backend API
• HTML + CSS + JavaScript Frontend

This version provides a full UI where users can upload an image and instantly get predictions — no Postman required.

🚀 Features

• 🧠 Transfer Learning Model (97% test accuracy)
• 🖼️ Upload image directly from browser
• ⚡ Real-time prediction using Flask API
• 🎨 Clean and simple web frontend
• 🔥 Automatically loads and preprocesses images
• 📦 Easy to deploy anywhere (local / cloud / VPS)
  
  

📁 Project Structure

/project
│── models
|   |── transfer_learning_model.keras
│── notebooks
|   |── transfer_learning.ipynb
│── templates
|   |── index.html
│── static
|   |── style.css
│── img
|   |── home.png
|   |── prediction.png
│── main.py
│── requirements.txt
│── README.md
│── License

🧰 Technologies Used

• Backend

  • Python
  • Flask
  • TensorFlow / Keras
  • NumPy
  • Pillow (PIL)

• Fronend

  • HTML5
  • HTML5
  • JavaScript

• ML Model

  • Transfer Learning using: Xception
    
    

⚙️ Installation & Setup

1. Clone the repository:

   git clone https://github.com/YourUsername/CNN-Image-Classification-System.git
   cd CNN-Image-Classification-System

2. Create virtual environment (optional but recommended):

   python -m venv venv
   venv\Scripts\activate   # For Windows
   # OR
   source venv/bin/activate  # For macOS/Linux

3. Install dependencies:

   pip install -r requirements.txt

4. Run the Flask server:

   python main.py

   Server will start at:
   👉 http://127.0.0.1:5000
   
   

🖼️ Using the Web Interface

1. Open your browser → http://127.0.0.1:5000
2. Click Choose Image
3. Select a .jpg, .jpeg, or .png
4. Click Predict
5. You will see:

  {
    "prediction": "dog",
    "confidence": 0.9123
  }

or

  {
  "prediction": "cat",
  "confidence": 0.7344
  }

📸 Screenshots

Home Screen

Prediction

📄 Requirements

The requirements.txt file includes all necessary packages:

• flask
• tensorflow
• numpy
• pillow
  
  

🤝 Contribution

Pull requests are welcome! For major changes, please open an issue first to discuss what you'd like to improve.

📜 License

This project is licensed under the MIT License – see the LICENSE file for details.