Face_Attendance_System

Face Attendance System

This project is a Face Attendance System that leverages advanced machine learning algorithms for facial recognition and attendance tracking. It consists of a Python backend using Flask, OpenCV, and machine learning libraries, along with a React frontend for a user-friendly interface.

Project_Demo.mp4

Features

1. Real-time Face Detection and Recognition:

   - Utilizes OpenCV for real-time face detection.

   - Employs a K-Nearest Neighbors (KNN) classifier for face recognition, trained with user-provided images.

2. Automated Attendance Marking:

   - Automatically marks attendance upon recognizing a registered face.

   - Stores attendance data with timestamps in CSV files.

3. User Registration:

   - Allows new users to register by capturing their facial images through a webcam.

   - Automatically trains the recognition model with new user data.

4. Attendance Data Retrieval:

   - Provides endpoints to fetch attendance data for specific dates.

   - Displays attendance data in a tabular format.

5. Cross-Origin Resource Sharing (CORS):

   - CORS enabled for seamless communication between the backend and frontend.

Setup and Installation

1. Clone the Repository:

   git clone https://github.com/Isara-Li/Face_Attendance_System.git

   cd face-attendance-system

2. Backend Setup:

   - Ensure you have Python and pip installed.

   - Install the required packages:

     pip install -r requirements.txt

   - Run the Flask server:

     python app.py

3. Frontend Setup:

   - Navigate to the frontend directory:

     cd frontend

   - Install the required packages:

     npm install

   - Start the React application:

     npm start

4. Access the Application:

   - Open your browser and navigate to http://localhost:3000 to access the frontend.

   - The Flask backend runs on http://127.0.0.1:5000.

Dependencies

• Backend:

  - Flask

  - OpenCV

  - NumPy

  - Pandas

  - scikit-learn

  - joblib

  - Flask-CORS

• Frontend:

  - React

  - React Router

  - Framer Motion

  - React Typing Effect

Contributing

Feel free to fork this repository and submit pull requests. For major changes, please open an issue first to discuss what you would like to change.

License

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

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This project demonstrates the integration of machine learning with web technologies to create a functional and interactive face attendance system. Contributions and feedback are welcome to further enhance its capabilities and features.