A modern, deep learning-based attendance tracking system utilizing facial recognition for automated student/employee check-in. The system consists of a Python/Flask backend handling the computer vision (OpenCV/Face Recognition library) and a web frontend built with HTML, Tailwind CSS, and JavaScript.
- Real-time Face Scanning: Live video feed for instant recognition.
- User Enrollment: Simple interface to add new users by capturing a face sample and associating it with a name.
- Automatic Attendance Marking: Single button click to record attendance for the currently recognized person.
- Attendance Logging: Displays today's attendance record with names and timestamps.
- Data Management: Tools to view, delete individual, or clear all enrolled face data.
- HTML5 / Tailwind CSS: Responsive and modern UI.
- JavaScript (Fetch API): Client-side logic for interacting with the backend API.
- Python (Flask): Web framework to serve the frontend and handle API requests.
- OpenCV: Handles camera stream and image processing.
- Face Recognition (Dlib): Core library for facial encoding and matching.