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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Cool experiments at the intersection of Computer Vision and Sports ⚽🏃
| Date | Stars |
|---|---|
| 2026-07-24 | 552 |
| 2026-07-25 | 552 |
| 2026-07-28 | 551 |
| 2026-07-30 | 551 |
| 2026-07-31 | 551 |
| 2026-08-06 | 551 |
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# ⚽ Football Players Tracking with YOLOv5 + ByteTrack [](https://www.youtube.com/watch?v=QCG8QMhga9k) [](https://blog.roboflow.com/track-football-players/) [](https://github.com/roboflow-ai/notebooks/blob/main/notebooks/how-to-track-football-players.ipynb) I have long been fascinated by the use of Computer Vision in sports. After all, it is a combination of two things I love. Almost three years ago, I wrote a post on my personal blog in which I tried — at that time, still using YOLOv3 — to [detect and classify basketball players on the court](https://towardsdatascience.com/chess-rolls-or-basketball-lets-create-a-custom-object-detection-model-ef53028eac7d). FIFA World Cup 2022 has motivated me to revisit this idea. This time I used a combination of [YOLOv5](https://github.com/ultralytics/yolov5) and [ByteTrack](https://github.com/ifzhang/ByteTrack) to track football players on the field. This blog post accompanies the Roboflow video where I talk through how to track players on a football field. https://user-images.githubusercontent.com/26109316/207858600-ee862b22-0353-440b-ad85-caa0c4777904.mp4 # 🤸 3D Football Players Pose Estimation with YOLOv7 [](https://www.youtube.com/watch?v=AWjKfjDGiYE) [](https://github.com/SkalskiP/sport/tree/master/football-players-pose-estimation) I was watching a FIFA 2022 World Cup match the other day, and one of the things that caught my eye was VAR - Video Assistant Referee, or to be more precise, the part of it responsible for analyzing whether a player was on the offside. I did a little [research](https://www.youtube.com/watch?v=WycjDx6giVE) and found that the system performs pose estimation on multiple cameras at once. I decided to check how difficult it would be to reproduce it at home using two cameras and [YOLOv7](https://github.com/WongKinYiu/yolov7). https://user-images.githubusercontent.com/26109316/207677038-20f951a6-e469-4b3f-a934-66e036fcff69.mp4 # 👕 Assigning Football Players to Teams by Uniform Color with GPT-4V [](https://github.com/SkalskiP/sport/tree/master/football-analysis-with-gpt4-vision) This project explores the use of [GPT-4V](https://openai.com/research/gpt-4v-system-card) in sports analytics, specifically in the context of football. Its primary aim was to evaluate whether GPT-4V could effectively distinguish and assign players to teams based on the color of their uniforms. This was achieved through the implementation of several advanced vision prompting techniques. https://github.com/SkalskiP/sports/assets/26109316/b354b38d-1a12-477d-9283-45059ce12467
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Piotr Skalski · @roboflow
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:3eae362d1223b016, topic:computer-vision, topic:object-detection, desc:computer vision
matched fp:3eae362d1223b016, topic:deep-learning, topic:pytorch