mirror of https://github.com/WongKinYiu/yolov7.git
46 lines
1.8 KiB
Markdown
46 lines
1.8 KiB
Markdown
# Official YOLOv7
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Implementation of paper - [YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors](https://arxiv.org/abs/2207.02696)
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Instance segmentaion code is partially based on [BlendMask](https://arxiv.org/abs/2001.00309).
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## Testing
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[yolov7-mask.pt](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-mask.pt)
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[[scripts]](./tools/instance.ipynb)
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<div align="center">
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<a href="./">
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<img src="./figure/horses_instance.png" width="79%"/>
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</a>
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</div>
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## Citation
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```
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@article{wang2022yolov7,
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title={{YOLOv7}: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors},
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author={Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark},
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journal={arXiv preprint arXiv:2207.02696},
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year={2022}
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}
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```
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## Acknowledgements
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<details><summary> <b>Expand</b> </summary>
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* [https://github.com/AlexeyAB/darknet](https://github.com/AlexeyAB/darknet)
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* [https://github.com/WongKinYiu/yolor](https://github.com/WongKinYiu/yolor)
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* [https://github.com/WongKinYiu/PyTorch_YOLOv4](https://github.com/WongKinYiu/PyTorch_YOLOv4)
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* [https://github.com/WongKinYiu/ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4)
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* [https://github.com/Megvii-BaseDetection/YOLOX](https://github.com/Megvii-BaseDetection/YOLOX)
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* [https://github.com/ultralytics/yolov3](https://github.com/ultralytics/yolov3)
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* [https://github.com/ultralytics/yolov5](https://github.com/ultralytics/yolov5)
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* [https://github.com/DingXiaoH/RepVGG](https://github.com/DingXiaoH/RepVGG)
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* [https://github.com/JUGGHM/OREPA_CVPR2022](https://github.com/JUGGHM/OREPA_CVPR2022)
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* [https://github.com/TexasInstruments/edgeai-yolov5/tree/yolo-pose](https://github.com/TexasInstruments/edgeai-yolov5/tree/yolo-pose)
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</details>
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