Track Football Players with Computer Vision

Piotr Skalski explores the use of computer vision to track football players, revisiting a project initially attempted with basketball players, and documents the process in a Roboflow video and blog post. Utilizing a combination of YOLOv5 and ByteTRACK, Skalski aimed to efficiently track players on the field but encountered challenges with pre-trained models detecting irrelevant objects and failing to reliably track the ball. Consequently, he constructed a custom dataset and trained a new model, introducing additional classes like referee and goalkeeper. Despite initial setbacks, the custom-trained model improved detection accuracy, although class imbalance issues persisted. ByteTRACK was employed for its efficient object tracking capabilities without requiring additional training. The project demonstrates the potential for analyzing player movements, tracking ball trajectories, and identifying key field zones, while Skalski encourages others to experiment with the open-source code and dataset available on Roboflow Universe.