YOLOv8 ๐ 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 and neck architectures, and offers optimized accuracy -speed tradeoff, making it ideal for diverse applications.
NEW - YOLOv8 ๐ in PyTorch > ONNX > CoreML > TFLite - YOLOv8/README.zh-CN.md at main RhineAI/YOLOv8
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 further boost performance and flexibility. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection, image segmentation and image ...
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 performance and flexibility. YOLOv8 is designed to be fast, accurate, and easy to use, making it an excellent choice for a wide range of object detection and tracking, instance segmentation, image classification ...
:fire: Official YOLOv8ๆจกๅ่ฎญ็ปๅ้จ็ฝฒ. Contribute to DataXujing/YOLOv8 development by creating an account on GitHub.