face-recognition

Class Attendance System using Facial Recognition

This project is a class attendance system that utilizes facial recognition technology to identify and verify students based on their facial features. The system automatically marks attendance for students as they enter the classroom, streamlining the attendance-taking process for teachers and reducing manual effort.

Features

• Facial Recognition: The system uses state-of-the-art facial recognition algorithms to accurately identify students.
• Automatic Attendance: Upon detection and verification, the system automatically marks attendance for recognized students.
• Efficient and Secure: Attendance records are stored securely, ensuring data privacy and integrity.
• User-Friendly Interface: The system provides a user-friendly interface for teachers to manage attendance records and view attendance statistics.

Technologies Used

• Python: Programming language used for the backend logic and implementation.
• OpenCV: Library used for image processing and facial recognition.
• face_recognition: Python library built on top of dlib's state-of-the-art face recognition algorithms.
• SQLite: Lightweight relational database used for storing attendance records.

How to Use

1. Installation: Clone the repository to your local machine and install the required dependencies using pip install -r requirements.txt.

2. Database Setup: Create a SQLite database to store attendance records.

3. Configuration: Configure the system parameters such as the database path and attendance threshold.

4. Run the System: Execute the main script to start the class attendance system.

5. Attendance Monitoring: Access the attendance records and statistics through the provided interface.

Contributors

• Tanmay Toshniwal(@tanmaytoshniwal09): Lead Developer,Database Administrator

License

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