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πŸŽ₯ Face Recognition Surveillance System πŸ•΅οΈβ€β™‚οΈ

**A Face Recognition System, designed for real-time surveillance and locating missing persons or items **

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✨ Key Features

  • Real-time face recognition using ML Model.
  • Surveillance and monitoring for missing persons or items during mass gatherings.
  • Easy-to-use web interface built with React and Tailwind CSS.
  • Robust backend API using Flask and Python.

πŸš€ Demo

🎬 Check out a live demo here or watch a preview below:

Demo

πŸ› οΈ Technologies Used

Frontend:

  • React βš›οΈ for building the user interface
  • Tailwind CSS πŸ’¨ for responsive and attractive styling
  • Axios for API calls to the backend

Backend:

  • Flask 🐍 for building the API
  • face_recognition library for facial detection and recognition
  • OpenCV for handling image and video processing
  • Python as the main backend language

Deployment:

  • Docker 🐳 for containerization of Backend

πŸ“ Project Structure

face-recognition-system/
β”‚
β”œβ”€β”€ frontend/
β”‚   β”œβ”€β”€ public/
β”‚   β”œβ”€β”€ src/
β”‚   β”‚   β”œβ”€β”€ components/
β”‚   β”‚   β”œβ”€β”€ pages/
β”‚   β”‚   β”œβ”€β”€ App.tsx
β”‚   β”‚   └── Home.tsx
β”‚   β”‚   └── Main.tsx
β”‚   β”‚   └── navbar.tsx
β”‚   β”‚   └── NotFound.tsx
β”‚   β”‚   └── ReportForm.tsx
β”‚   β”‚   └── SearchMissing.tsx
β”‚   β”‚   └── Survillance.tsx
β”‚   β”œβ”€β”€ tailwind.config.js
β”‚   └── package.json
β”‚
β”œβ”€β”€ backend/
    β”œβ”€β”€ app.py
    β”œβ”€β”€ models/
    β”œβ”€β”€ static/Images
    └── requirements.tx

⚑ Quick Start

  1. Clone the repository:

    git clone git@github.com:kartik-212004/hackathon-iiit.git
    cd hackathon-iiit
  2. Backend Setup:

    • Navigate to the backend folder and set up a virtual environment:
      cd backend
      python3 -m venv venv
      source venv/bin/activate  # On Linux/macOS
      .\venv\Scripts\activate  # On Windows
    • Install dependencies:
      pip install -r requirements.txt
  3. Frontend Setup:

    • Navigate to the frontend folder and install dependencies:
      cd frontend
      npm install
      npm run dev
  4. Run the Application:

    • Start the Flask backend server:
      cd backend
      python app.py
    • Start the React frontend development server:
      cd frontend
      npm start

🐳 Docker Setup (Optional)

You can also run the entire system using Docker for seamless deployment:

  1. Build and run the Docker containers:

    cd backend
    docker build -t flask-backend .
    docker run -p 5000:5000 flask-backend
  2. Visit http://localhost:3000 for the frontend and http://172.17.0.2:5000/ for the backend.

πŸ“· Screenshots

Example Image

Example Image Example Image

Face Recognition in Action

Face Detection

🧠 How It Works

  1. Face Registration: Known persons’ images are uploaded and stored in the system for future recognition.
  2. Real-time Face Detection: The system captures video feeds or images to detect faces.

πŸ—οΈ Future Improvements

  • Real-time video stream integration for live surveillance.
  • Alert System: Notify authorities when a person is identified.

🀝 Contributions

Contributions are always welcome! Feel free to:

  1. Fork the repo.
  2. Create a feature branch.
  3. Submit a pull request with a detailed description of the changes.

πŸ‘¨β€πŸ’» Team-

πŸ“„ License

This project is licensed under the MIT License.

⭐ If you like this project, don’t forget to star the repository!

πŸ™Œ Acknowledgements

  • Special thanks to the open-source community for amazing resources.
  • Inspiration from real-world applications of AI in surveillance systems .