Today we’re diving into something really cool: fine-tuning YOLO models for soccer detection. We’re going to detect balls, referees, players, and goalkeepers in soccer matches using Ultralytics’ fine-tuning tools. The popular YOLO models you’ll find out there, like Ultralytics YOLOv11, and YOLOX in different sizes, are mostly pre-trained on something called the COCO dataset. What’s […]| Poeticoding
When you decline an offer without providing a “convincing” reason, you risk positioning yourself as stubborn and unagreeable. The post “No” is An Excuse on Its Own appeared first on The Observer.| The Observer
NASCAR Chicago Street Race is reaffirming its commitment to STEAM and the Adler Planetarium with a sponsorship of Adler at Night. The post Adler Planetarium Announces $1 Million Gift for STEAM Youth Engagement Programs from S&C Electric Company Fund appeared first on Adler Planetarium.| Adler Planetarium
YOLOv8 object tracking and counting unveils new dimensions in real-time tacking; explore its mastery in our detailed guide, your key to mastering the tech.| LearnOpenCV – Learn OpenCV, PyTorch, Keras, Tensorflow with code, & tutorials
We have released a new version of Colour - Checker Detection that implements a new machine learning inference method to detect colour rendition charts, specifically the ColorChecker Classic 24 from X-| Colour Science
The YOLO (You Only Look Once) series of models, renowned for its real-time object detection capabilities, owes much of its effectiveness to its specialized loss functions. In this article, we delve into the various YOLO loss function integral to YOLO's evolution, focusing on their implementation in PyTorch. Our aim is to provide a clear, technical| LearnOpenCV – Learn OpenCV, PyTorch, Keras, Tensorflow with code, & tutorials