Advanced Face Recognition Attendance System
This project offers a cutting-edge solution for attendance tracking, combining the power of Django and deep learning to deliver a secure and accurate experience. Leveraging MTCNN (Multi-Task Cascaded Convolutional Networks) for face detection and the InceptionResnetV1 model for face encoding, the system automatically recognizes faces in real-time and logs attendance seamlessly.
Key Features:
Real-Time Face Recognition: Utilizes MTCNN and InceptionResnetV1 for precise face detection and encoding.
Multi-Camera Support: Configurable to work with both IP and local cameras for enhanced flexibility.
Automated Attendance Logging: Automatically records check-ins and check-outs, reducing manual intervention.
Admin Dashboard: Provides easy access to student databases, attendance records, and customizable settings.
Alert Sound on Successful Recognition: Plays a sound via Pygame when a face is successfully recognized.
Secure Login and Access: Ensures data security by restricting admin access for viewing, editing, and authorizing users.
This advanced system is perfect for institutions and businesses aiming to streamline their attendance processes while boosting security with biometric verification.
