This project applies computer vision and deep learning to basketball video analysis. It detects and tracks players and basketballs using YOLOv4, extracts body pose keypoints via OpenPose, and computes shooting metrics. Users can upload videos for automated analysis or call the REST API programmatically. The system processes video frames to identify shot attempts and evaluate shooter form.