Problem and solution
Problem
Manual classroom attendance can allow proxy sign-ins and makes attendance records harder to manage.
Solution
A Python and OpenCV desktop system that recognizes registered faces, records attendance, and manages student data.
Technical approach
- Face detection and recognition with OpenCV and deep learning
- Attendance history, dashboards, and Excel or CSV export
- Unknown-face notifications and face database management
Implementation details
An automated facial-recognition attendance system built with Python and OpenCV to address proxy attendance in classrooms. It uses OpenCV and deep learning for face detection and recognition, with a face database for storing and managing student profiles. Attendance is recorded automatically when students enter the classroom. The system provides attendance history and statistics, student record management, Excel or CSV data export, alerts for unknown faces or recognition failures, and a dashboard with attendance statistics and charts. It was developed with Python 3.x, OpenCV, NumPy, Pandas, Tkinter, SQLite/MySQL, and the Face Recognition library, using face-detection and recognition models, database management, and a GUI application framework.