ui/README.md

ui/

Live camera demo and real-time inference pipeline.

1. Files

File	Description
pipeline.py	Inference pipelines: FaceMeshPipeline, MLPPipeline, XGBoostPipeline
live_demo.py	OpenCV webcam window with mesh overlay and focus classification

2. Pipelines

Pipeline	Features	Model	Source
FaceMeshPipeline	Head pose + eye geometry	Rule-based fusion	models/head_pose.py, models/eye_scorer.py
MLPPipeline	10 selected features	PyTorch MLP	checkpoints/model_best.joblib
XGBoostPipeline	10 selected features	XGBoost	models/xgboost/checkpoints/face_orientation_best.json

3. Running

# default mode (cycles through available pipelines)
python ui/live_demo.py

# start directly in XGBoost mode
python ui/live_demo.py --xgb

Controls

Key	Action
m	Cycle mesh overlay (full → contours → off)
p	Switch pipeline (FaceMesh → MLP → XGBoost)
q	Quit

4. Integration

The same pipelines are used by the FastAPI backend (main.py) for WebSocket-based video inference in the React app.