RefereAI MLX turns ordinary match footage into local, inspectable sports intelligence: sport classification, object overlays, frame logs, summaries, and a human review loop.
Video enters from a phone, upload, or stream. YOLO26 MLX runs locally, RefereAI observers add sports context, and the result lands in a review console where mistakes can be corrected.
Use a phone camera, a saved match clip, or a public broadcast segment.
Run YOLO26 MLX on Apple Silicon with no external inference API.
Layer sport classification, ball/player evidence, timing, and overlay rules.
Inspect overlays, mark wrong sport or bad overlay, and preserve demo-worthy runs.
Full-width clips for recording the demo: public broadcast or public sample footage, raw links, overlay links, and summary JSON. No private personal footage is used on the public site.
All public demo assets are 720p where source allows. Volleyball clips are 12 seconds; tennis and badminton use checked-in public sample footage.
Clone the repo, bootstrap the MLX model, start the local server, then open the app on your Mac or phone.
git clone https://github.com/jravinder/refereai-mlx cd refereai-mlx bash scripts/bootstrap.sh .venv/bin/refereai serve --port 8765
Track players, teams, referees, spectators, and off-court context with less flicker.
Use scoreboard OCR and rally state so the score changes only when play actually resolves.
Blend official corner phones and guest phones into one private venue view.
Share a private link with viewer-specific overlays, commentary, and replay controls.
Open an issue, inspect the code, or contact Ravi. The project is public so the build can be reviewed end to end.