VolleyVision and fast-volleyball-tracking-inference

Maintenance 2/25
Adoption 10/25
Maturity 16/25
Community 22/25
Maintenance 10/25
Adoption 8/25
Maturity 7/25
Community 11/25
Stars: 289
Forks: 57
Downloads:
Commits (30d): 0
Language: Python
License: AGPL-3.0
Stars: 44
Forks: 5
Downloads:
Commits (30d): 0
Language: Python
License:
Stale 6m No Package No Dependents
No License No Package No Dependents

About VolleyVision

shukkkur/VolleyVision

Applying Deep Learning Approaches to Volleyball Data

This project helps volleyball coaches and analysts automatically extract key information from game footage. By analyzing video, it identifies the volleyball, players, and the court, then recognizes specific actions like serves, spikes, or blocks. The output can be used to understand game flow and individual player performance, making it useful for scouting, training, and strategic planning.

volleyball-coaching sports-analytics player-performance game-footage-analysis scouting

About fast-volleyball-tracking-inference

asigatchov/fast-volleyball-tracking-inference

Fast Volleyball Tracking Inference: Real-time volleyball ball detection and tracking at 100 FPS on CPU (Intel i5-10400F). Powered by an optimized ONNX model, outputs ball coordinates to CSV, with optional video visualization. Ideal for sports analytics and computer vision research.

This tool automates the analysis of volleyball game footage. It takes a raw video file of a volleyball match and identifies the ball's movement throughout. The output includes detailed ball coordinates, rally breakdowns, and automatically generated vertical video clips (reels) optimized for social media, ideal for sports analysts, coaches, or content creators.

volleyball-analytics sports-coaching video-highlights match-analysis social-media-content

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