- Introduce unique face ID generation and enhance face matching based on proximity and size
- Refactor face ID generation to use centroids and size for better accuracy
- Update tracked face data structure to include centroid, zone, timestamp, and size
- Improve comments for clarity on face tracking and matching processes
- Update zone transition logic to count first detections in entry and exit zones
- Refine conditions for counting entries and exits based on zone transitions
- Improve comments for clarity on zone assignment and transitions
- Add Flask application with MJPEG video streaming
- Implement OpenCV DNN face detection module
- Add zone-based entry/exit tracking with cooldown mechanism
- Create web interface with real-time WebSocket updates
- Add model download script and comprehensive README
- Include OpenCV DNN model files for face detection
