Football Players Tracking with YOLOv5 + ByteTRACK Tutorial

This page summarizes the projects mentioned and recommended in the original post on /r/computervision

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  • notebooks

    Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.

  • YouTube video: https://youtu.be/QCG8QMhga9k Jupyter notebook: https://github.com/roboflow-ai/notebooks/blob/main/notebooks/how-to-track-football-players.ipynb

  • yolov5

    YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

  • I love this! TF.js is big! And to answer your question - sure, we can run that model in the browser. This is the YOLOv5 model it can be converted from PyTorch to TF.js with this script: https://github.com/ultralytics/yolov5/blob/master/export.py And then run it with my NPM package https://github.com/SkalskiP/yolov5js. ML in Java Script is the future! The problem is I don't know anything about any good tracker implemented in JS.

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  • yolov5js

    Effortless YOLOv5 javascript deployment

  • I love this! TF.js is big! And to answer your question - sure, we can run that model in the browser. This is the YOLOv5 model it can be converted from PyTorch to TF.js with this script: https://github.com/ultralytics/yolov5/blob/master/export.py And then run it with my NPM package https://github.com/SkalskiP/yolov5js. ML in Java Script is the future! The problem is I don't know anything about any good tracker implemented in JS.

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