Facial Attendance System

Current attendance systems often face issues like proxy attendance, time consumption, and data manipulation, leading to inaccuracies and inefficiencies. “Facial Attendance Management System Using Python” provides an in-depth analysis of the facial attendance management system, which offers the best statistics and accuracy in identifying individuals, enhancing efficiency, and ensuring secure and reliable attendance tracking. It is an automated solution that utilizes Python and its libraries for marking real-time attendance using facial recognition technology. This approach replaces traditional attendance methods, minimizing human intervention and reducing errors such as proxy, time consumption, and data manipulation. The implementation contains OpenCV for image processing, NumPy, Pandas  for efficient data handlimg & Matplotlib for statistical representation. The system captures facial images of the students, train them, and matches with the database records using  Machine learning. It integrates with MySQL to securely store the images and manage the attendance records. The performance of the proposed model has been compared with several other modelsand the proposed model has shown significant improvement in terms of accuracy over other model.