YOLOv8 🚀 in PyTorch > ONNX > CoreML > TFLite. Contribute to Pertical/YOLOv8 development by creating an account on GitHub.

YOLOv8 is designed to improve real-time object detection performance with advanced features. Unlike earlier versions, YOLOv8 incorporates an anchor-free split Ultralytics head, state-of-the-art backbone …

Ultralytics creates cutting-edge, state-of-the-art (SOTA) YOLO models built on years of foundational research in computer vision and AI. Constantly updated for performance and flexibility, our models …

Ultralytics YOLOv8, developed by Ultralytics, is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to …

NEW - YOLOv8 🚀 in PyTorch > ONNX > CoreML > TFLite - YOLOv8/README.zh-CN.md at main · RhineAI/YOLOv8

Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost …

Ultralytics YOLOv8 is a cutting-edge, state-of-the-art (SOTA) model that builds upon the success of previous YOLO versions and introduces new features and improvements to further boost …

YOLOv8. Contribute to haermosi/yolov8 development by creating an account on GitHub.

:fire: Official YOLOv8模型训练和部署. Contribute to DataXujing/YOLOv8 development by creating an account on GitHub.

YOLOv8 OBB Models: The introduction of Oriented Bounding Box models in YOLOv8 marks a significant step in object detection, especially for angled or rotated objects, enhancing accuracy and …