How to Detect Basketball Game using Deep Learning
In this tutorial, we delve into the world of *computer vision* by creating automatic labeling in Video streaming , and **YOLOv8-based basketball object detection ** using **Deep learning **.
We'll work with game footage from a *YouTube match between Real Madrid and Maccabi Tel-Aviv* to build a model capable of detecting *players, referees**, and the **basketball* itself in real-time.
This tutorial covers the full pipeline, from *automatically labeling data* with *Autodistill and GroundingDINO* to *training a custom YOLOv8 model* and *running live inference* on new game footage. You'll gain hands-on experience with essential tools for AI-based sports analytics, while learning practical deep learning techniques.
Key Concepts Covered:
*Frame extraction from YouTube videos* using `CamGear`
*Automatic annotation* generation with *Autodistill and GroundingDINO*
*Model training* with *YOLOv8* for object detection in sports
*Real-time inference* on new basketball footage
Code for the tutorial : https://ko-fi.com/s/cff94b715a
You can find more computer vision tutorials in my blog page : https://eranfeit.net/blog/
You can find more projects and tutorials in this playlist : • Best Object Detection models
~~~~~~~~~~~~~~~ recommended courses and books ~~~~~~~~~~~~~~~
A perfect course for learning modern Computer Vision with deep dive in TensorFlow , Keras and Pytorch . You can find it here : http://bit.ly/3HeDy1V
I also recommend this book, https://amzn.to/44GnlLW : "Make Your Own Neural Network - An In-depth Visual Introduction For Beginners ".
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00:00 Introduction & Demo
02:18 Installation
04:37 Generate the dataset
13:45 Automatic dataset annotation
28:35 Train a model
34:19 Test the mode
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#EranFeit #objectdetection #yolo
~~~~~~~~~~~~~~ Credits ~~~~~~~~~~~~~
Music by Vincent Rubinetti
Download the music on Bandcamp: https://vincerubinetti.bandcamp.com/a...
Stream the music on Spotify: https://open.spotify.com/album/1dVyjw...