football AI code is finally open-source
- player detection and tracking
- team clustering
- camera calibration
I still need to work on README; don't judge me on that
code: github.com/roboflow/sports
polish TV is using computer vision to enhance the viewer experience for sports broadcasts:
- FIFA-like radar overlays
- player recognition
- pass distance measurement
- ball speed and trajectory tracking during shots
I can finally map @NBA player's position from the camera perspective onto the court map
it's still a bit shaky... I'll smooth it out later
it's time to detect shooting motions and mark the shot location!
some of the code has already been migrated to: github.com/roboflow/sports
supervision, the open-source library I created a year ago, has crossed 20,000 stars on GitHub this weekend!
thank you to everyone who helped me build this project!
it took us 3,500+ commits, 850+ PRs and 80+ contributors to do it.
repository: github.com/roboflow/super…
supervision, the open-source library I created a year ago, is crossing 25,000 stars on GitHub!
thank you to everyone who helped me build this project!
it took us 4,000+ commits, 1,000+ PRs and 100+ contributors to do it.
repository: github.com/roboflow/super…
supervision, the open-source library I created 2 years ago, is crossing 30,000 stars on GitHub!
thank you to everyone who helped me build this project! it took us 4,000+ commits, 1,000+ PRs and 100+ contributors to do it.
link: github.com/roboflow/super…
I finally solved player recognition
- player and number detection with RF-DETR
- player tracking with SAM2
- team clustering with SigLIP, UMAP and KMeans
- number recognition with SmolVLM2
stay tuned for YT tutorial: youtube.com/c/Roboflow
↓ full breakdown + code
supervision-0.13.0 is out! Now you can effortlessly build advanced video analytics. Trackers, Zones, Annotators, and much more.
GitHub repository: github.com/roboflow/super…
here is the final version of my vehicle speed estimation demo
read the thread below to learn how I built it.
I will cover:
- detection
- tracking
- perspective transformation
- speed calculation
- some bonus ideas
↓
REAL-TIME object detection WITHOUT TRAINING
YOLO-World is a new SOTA open-vocabulary object detector that outperforms previous models in terms of both accuracy and speed. 35.4 AP with 52.0 FPS on V100.
↓ read more