How sumanxhub/presensee works
PresenSee is a webcam-based attendance application. A user registers face samples, trains an LBPH model, then runs recognition to log each recognized person once per day; attendance CSVs can be exported to Excel. The GUI launches these workflows as separate scripts. Recognition, training, and export behavior is supported by sampled source; the README documents the overall capabilities. The generated trainer file is not present in the supplied tree, so its node uses the enclosing models directory.
Main entry points: face_recognition.py Face recognition · gui.py PresenSee GUI · face_register.py Face registration · face_trainer.py Model training
Components 12
User interface
- PresenSee GUI
gui.py
Face workflows
- Face registration
src/core/face_register.py - Haar cascade
models/haarcascade_frontalface_default.xml - User face samples
dataset/users - Model training
src/core/face_trainer.py - LBPH model
models
Attendance records
- Face recognition
src/core/face_recognition.py - Daily CSV logs
attendance
Reporting
- CSV to Excel
src/core/convertToExcel.py - Excel exports
database
Other components
- Operator
- Webcam
Connections 17
- Operator → PresenSee GUI: uses
- PresenSee GUI → Face registration: launches
- PresenSee GUI → Model training: launches
- PresenSee GUI → Face recognition: launches
- PresenSee GUI → CSV to Excel: launches
- Face registration → Webcam: captures from
- Face registration → Haar cascade: detects with
- Face registration → User face samples: writes samples
- Model training → User face samples: reads samples
- Model training → LBPH model: writes model
- Face recognition → Webcam: captures from
- Face recognition → Haar cascade: detects with
- Face recognition → LBPH model: loads model
- Face recognition → User face samples: loads user names
- Face recognition → Daily CSV logs: writes daily logs
- CSV to Excel → Daily CSV logs: reads today's CSV
- CSV to Excel → Excel exports: writes workbook