# mindyolo **Repository Path**: mindspore-lab/mindyolo ## Basic Information - **Project Name**: mindyolo - **Description**: MindYOLO is MindSpore Lab's software system that implements state-of-the-art YOLO series algorithms, support list and benchmark. - **Primary Language**: Unknown - **License**: Apache-2.0 - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 20 - **Forks**: 7 - **Created**: 2023-01-10 - **Last Updated**: 2025-09-24 ## Categories & Tags **Categories**: cv **Tags**: None ## README # MindSpore YOLO

docs GitHub PRs Welcome

MindSpore YOLO implements state-of-the-art YOLO series algorithms based on MindSpore. The following is the corresponding `mindyolo` versions and supported `mindspore` versions. | mindyolo | mindspore | | :------: | :---------: | | master | master | | 0.5 | 2.5.0 | | 0.4 | 2.3.0/2.3.1 | | 0.3 | 2.2.10 | | 0.2 | 2.0 | | 0.1 | 1.8 | ## Benchmark and Model Zoo See [Benchmark Results](benchmark_results.md). ## supported model list - [x] [YOLOv11](configs/yolov11) - [x] [YOLOv10](configs/yolov10) - [x] [YOLOv9](configs/yolov9) - [x] [YOLOv8](configs/yolov8) - [x] [YOLOv7](configs/yolov7) - [x] [YOLOX](configs/yolox) - [x] [YOLOv5](configs/yolov5) - [x] [YOLOv4](configs/yolov4) - [x] [YOLOv3](configs/yolov3) ## Installation See [INSTALLATION](docs/en/installation.md) for details. ## Getting Started See [GETTING STARTED](GETTING_STARTED.md) for details. ## Custom dataset examples See [examples](examples) ## Notes ⚠️ The current version is based on the [static shape of GRAPH](https://mindspore.cn/docs/en/r2.0/note/static_graph_syntax_support.html). The dynamic shape of verision will be supported later. Please look forward to it. ### How to Contribute We appreciate all contributions including issues and PRs to make MindSpore YOLO better. Please refer to [CONTRIBUTING.md](CONTRIBUTING.md) for the contributing guideline. ### License MindSpore YOLO is released under the [Apache License 2.0](LICENSE.md). ### Acknowledgement MindSpore YOLO 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. ### Citation If you find this project useful in your research, please consider cite: ```latex @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} } ```