How sarkarroni748-cpu/face_recognition_model- works
This is a webcam-based face-recognition attendance application. At startup, it loads enrolled faces from the picture folder and prepares an attendance session; during capture, a background recognition worker identifies faces, and the main loop displays labels. Attendance is managed through MySQL, and detected names can be spoken. The recognition-to-attendance-marking connection is omitted because that call is not visible in the sampled excerpt.
Main entry points: face_ricognition.py Capture and display loop · db_manager.py Attendance manager
Components 13
Capture and display
- Capture and display loop
face_ricognition.py
Face recognition
- Load known faces
face_ricognition.py - Recognition worker
face_ricognition.py - FaceAnalysis model
face_ricognition.py - Current face labels
face_ricognition.py
Attendance records
- Attendance manager
db_manager.py - MySQL database
Voice feedback
- Speech functions
face_ricognition.py
Other components
- Operator
- Webcam
- Enrolled face images
- Text-to-speech engine
- Audio output
Connections 15
- Operator → Capture and display loop: starts
- Webcam → Capture and display loop: video frames
- Capture and display loop → Load known faces: loads enrollment
- Enrolled face images → Load known faces: image files
- Load known faces → FaceAnalysis model: extracts embeddings
- Capture and display loop → Attendance manager: initializes and syncs
- Attendance manager → MySQL database: creates and updates
- Capture and display loop → Attendance manager: starts session
- Capture and display loop → Recognition worker: dispatches frames
- Recognition worker → FaceAnalysis model: detects and embeds
- Recognition worker → Current face labels: writes results
- Capture and display loop → Current face labels: reads labels
- Capture and display loop → Speech functions: speaks detected names
- Speech functions → Text-to-speech engine: sends text
- Text-to-speech engine → Audio output: produces audio