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MindYOLO implements state-of-the-art YOLO series algorithms based on MindSpore.The following is the correspondingmindyolo versions and supportedmindspore versions.

SeeBenchmark Results.

• YOLOv11
• YOLOv10
• YOLOv9
• YOLOv8
• YOLOv7
• YOLOX
• YOLOv5
• YOLOv4
• YOLOv3

SeeINSTALLATION for details.

SeeGETTING STARTED for details.

Seeexamples

⚠️ The current version is based on thestatic shape of GRAPH.The dynamic shape of verision will be supported later. Please look forward to it.

We appreciate all contributions including issues and PRs to make MindYOLO better.

Please refer toCONTRIBUTING.md for the contributing guideline.

MindYOLO is released under theApache License 2.0.

MindYOLO is an open source project that welcome any contribution and feedback. We wish that the toolbox and benchmark could support the growing research community, reimplement existing methods, and develop their own new real-time object detection methods by providing a flexible and standardized toolkit.

If you find this project useful in your research, please consider cite:

@misc{MindSpore Object Detection YOLO 2023,    title={{MindSpore Object Detection YOLO}:MindSpore Object Detection YOLO Toolbox and Benchmark},    author={MindSpore YOLO Contributors},    howpublished = {\url{https://github.com/mindspore-lab/mindyolo}},    year={2023}}