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A YOLOv5-based object detection model that identifies and tracks the players, the ball, the sideline referees and the goalkeeper separately when provided with a TV broadcast camera feed. Bytetrack is further used to enhance the model's capabilities! ⚽

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Football Players Tracking on a pitch using YOLOv5 + ByteTrack

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A YOLOv5-based object detection model that identifies and tracks the players, the ball, the sideline referees and the goalkeeper separately when provided with a TV broadcast camera feed. Bytetrack is further used to enhance the model's capabilities! ⚽

About

In my project, I utilized Roboflow Universe, an open-source computer vision dataset repository with over 100,000 datasets. We make use of two pretrained models one after another and apply custom annotations on the latter to get our output.

Useful links:

Steps Involved:

  • Setup🛠️
  • Download data🛠️
  • Install YOLOv5🛠️
  • Install ByteTrack and other libs🛠️
  • Custom annotator🛠️
  • Detect ball possession🛠️
  • Full video tracking🛠️
  • Put everything together🛠️

Output!⚽

Sample Video Frame:

Media Player 10-08-2023 22_07_57

Output Video after first petrained model:

Media Player 10-08-2023 22_07_13

Output video after v2 pretrained model:

Media Player 10-08-2023 22_06_55

Frame after applying Bytetrack:

output2

About

A YOLOv5-based object detection model that identifies and tracks the players, the ball, the sideline referees and the goalkeeper separately when provided with a TV broadcast camera feed. Bytetrack is further used to enhance the model's capabilities! ⚽

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