基于 PyTorch 的 YOLOv3 系列实现，覆盖训练、验证、推理全流程，并支持导出 ONNX、CoreML、TensorRT 等多种格式，方便做实时目标检测和边缘部署。
[assets]: https://github.com/ultralytics/yolov5/releases [previous]: https://github.com/ultralytics/yolov5/releases/tag/v6.2 [current]: https://github.com/ultralytics/yol
[assets]: https://github.com/ultralytics/yolov5/releases [previous]: https://github.com/ultralytics/yolov5/releases/tag/v6.1 [current]: https://github.com/ultralytics/yol
[assets]: https://github.com/ultralytics/yolov5/releases [previous]: https://github.com/ultralytics/yolov5/releases/tag/v6.0 [current]: https://github.com/ultralytics/yol
[assets]: https://github.com/ultralytics/yolov5/releases [TTA]: https://github.com/ultralytics/yolov5/issues/303 This release incorporates many new features and bug fixes
… YOLOv3 release merges the most recent updates to YOLOv5 featured in the April 11th, 2021 YOLOv5 v5.0 release into this repository. This is part of routine Ultralytics ma
This release implements YOLOv5-P6 models and retrained YOLOv5-P5 models. All model sizes YOLOv5s/m/l/x are now available in both P5 and P6 architectures: YOLOv5-P5 models