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。
用 TensorRT 网络定义 API 手写实现 YOLO、ResNet、Swin Transformer 等主流深度学习模型，并附 C++ 推理代码，方便直接部署到 NVIDIA GPU。
…h, 2021 YOLOv5 v6.0 release into this Ultralytics YOLOv3 repository. This is part of Ultralytics YOLOv3 maintenance and takes place on every major YOLOv5 release. Full de
…is a high-performance anchor-free YOLO, exceeding yolov3~v5. Support deployment of MegEngine, ONNX, TensorRT, openvino and ncnn. Document [website](https://yolox.readthed
This 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 Ultralytic
…from v9.0 release. Branch Notice The [ultralytics/yolov3](https://github.com/ultralytics/yolov3) repository is now divided into two branches: [Master branch](https://gith
…ajor update to the https://github.com/ultralytics/yolov3 repository that brings forward-compatibility with YOLOv5, and incorporates numerous bug fixes, feature additions
…ble version of the https://github.com/ultralytics/yolov3 repository. This release is backwards-compatible with darknet .cfg files for model configuration. All pytorch ( .