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AI Hawk-Eye for Badminton
This open-source computer vision application analyzes badminton games by tracking the shuttlecock and players’ movement. Previously done only in broadcasting studios at high costs.
Good-Badminton is an Open Source AI Hawk-Eye system for Badminton. By using YOLO model to detect shuttlecock and player, RTMPose model to extract skeleton keypoints, then generate annotated video, player heatmap and movement statistics (distance & speed per rally). In just a few days since launch, it has received nearly 400 stars, which is quite remarkable for such a specialist application!
Why a vibe-coder should care
Previously, we had to rely on expensive proprietary software to perform computer vision tasks on sporting events. This would require sports clubs and media production houses to fork out a substantial amount of money. But now, with just a few lines of Python code, we can analyse our own recorded matches at home (and possibly even on CPUs!) This is yet another example of how high quality broadcast applications can be developed in our spare time.
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