mirror of https://github.com/WongKinYiu/yolov7.git
56 lines
2.3 KiB
Markdown
56 lines
2.3 KiB
Markdown
# yolov7-pose
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Implementation of "YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors"
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Pose estimation implimentation is based on [YOLO-Pose](https://arxiv.org/abs/2204.06806).
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## Dataset preparison
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[[Keypoints Labels of MS COCO 2017]](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/coco2017labels-keypoints.zip)
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## Training
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[yolov7-w6-person.pt](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-w6-person.pt)
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``` shell
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python -m torch.distributed.launch --nproc_per_node 8 --master_port 9527 train.py --data data/coco_kpts.yaml --cfg cfg/yolov7-w6-pose.yaml --weights weights/yolov7-w6-person.pt --batch-size 128 --img 960 --kpt-label --sync-bn --device 0,1,2,3,4,5,6,7 --name yolov7-w6-pose --hyp data/hyp.pose.yaml
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```
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## Deploy
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TensorRT:[https://github.com/nanmi/yolov7-pose](https://github.com/nanmi/yolov7-pose)
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## Testing
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[yolov7-w6-pose.pt](https://github.com/WongKinYiu/yolov7/releases/download/v0.1/yolov7-w6-pose.pt)
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``` shell
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python test.py --data data/coco_kpts.yaml --img 960 --conf 0.001 --iou 0.65 --weights yolov7-w6-pose.pt --kpt-label
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```
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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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