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AI Hawk-Eye for Badminton Courts
An open-source computer vision system that tracks shuttlecock trajectories and player movement in badminton matches — the kind of analysis that used to be locked inside expensive broadcast studios.
Good-Badminton is an open-source AI Hawk-Eye system for badminton. It uses YOLO models to detect the shuttlecock and players, RTMPose to build skeleton keypoints, and then generates annotated video, player heatmaps, and movement statistics including distance and speed per rally. The project hit nearly 400 stars within days of its release — a rare result for a tool this sport-specific.
Why a vibe-coder should care
Computer vision for live sports used to require expensive proprietary systems that clubs and media companies pay heavily to license. This project packages the same core functionality — trajectory tracking, player speed, court heatmaps — into a Python script you can run on your own match recordings, even on a CPU. It's a strong example of how broadcast-grade tools are turning into weekend-scale projects.
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