ui/README.md

ui/

Live OpenCV demo and inference pipelines used by the app.

Files: pipeline.py (FaceMesh, MLP, XGBoost, Hybrid pipelines), live_demo.py (webcam window with mesh + focus label).

Pipelines: FaceMesh = rule-based head/eye; MLP = 10 features → PyTorch MLP (checkpoints/mlp_best.pt + scaler); XGBoost = same 10 features → xgboost_face_orientation_best.json. Hybrid combines ML/XGB with geometric scores.

Run demo:

python ui/live_demo.py
python ui/live_demo.py --xgb

m = cycle mesh, p = switch pipeline, q = quit. Same pipelines back the FastAPI WebSocket video in main.py.