Computer Vision AI Tagger
In Action
The Problem
Tennis coaches and players record hours of match footage but spend even more time manually reviewing it. Identifying key moments—ball placement, rally patterns, shot types—requires tedious frame-by-frame analysis that most players simply don't have time for.
The Insight
By applying YOLOv8 object detection to match video, we can automatically track ball position, detect bounces, and classify shot types in real-time. The breakthrough was training on high-resolution (1080p+) footage and curating datasets to focus on active play—filtering out serves, ball tosses, and between-point dead time.
The Result
The system achieves 81% recall on tennis ball detection and processes full matches in minutes, not hours. Players get timestamped highlight reels and shot-by-shot breakdowns without touching a single frame manually.