https://github.com/bigtuo/yolov7-pose-bytetrack-stgcn
YOLOv7-POSE was used for key point detection, Bytetrack for tracking, and Stgan for fall and other behavior recognition
Science Score: 10.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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○codemeta.json file
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○.zenodo.json file
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○DOI references
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✓Academic publication links
Links to: arxiv.org -
○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (7.5%) to scientific vocabulary
Repository
YOLOv7-POSE was used for key point detection, Bytetrack for tracking, and Stgan for fall and other behavior recognition
Basic Info
- Host: GitHub
- Owner: Bigtuo
- License: other
- Language: Python
- Default Branch: main
- Size: 63.5 MB
Statistics
- Stars: 42
- Watchers: 1
- Forks: 5
- Open Issues: 7
- Releases: 0
Metadata Files
README.md
YOLOv7-Pose-Bytetrack-STGCN
YOLOv7-POSE was used for key point detection, Bytetrack for tracking, and STGCN for fall and other behavior recognition.
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Key point detection, run the command below:
python detect.py --weights "yolov7-w6-pose.pt" --kpt-label --view-img
Key point detection+Bytetrack, run the command below:
python detect_track.py --weights "yolov7-w6-pose.pt" --kpt-label --view-img
Key point detection+Bytetrack+STGCN, run the command below:
python detect_track_stgcn.py --weights "yolov7-w6-pose.pt" --kpt-label --view-img
YOLO-Pose: [https://github.com/Bigtuo/YOLO-POSE-Bytetrack-STGCN]
yolov7-pose
Implementation of "YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors"
Pose estimation implimentation is based on YOLO-Pose.
Dataset preparison
[Keypoints Labels of MS COCO 2017]
Training
shell
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
Deploy
TensorRT:https://github.com/nanmi/yolov7-pose
Testing
shell
python test.py --data data/coco_kpts.yaml --img 960 --conf 0.001 --iou 0.65 --weights yolov7-w6-pose.pt --kpt-label
Citation
@article{wang2022yolov7,
title={{YOLOv7}: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors},
author={Wang, Chien-Yao and Bochkovskiy, Alexey and Liao, Hong-Yuan Mark},
journal={arXiv preprint arXiv:2207.02696},
year={2022}
}
Acknowledgements
Expand
* [https://github.com/AlexeyAB/darknet](https://github.com/AlexeyAB/darknet) * [https://github.com/WongKinYiu/yolor](https://github.com/WongKinYiu/yolor) * [https://github.com/WongKinYiu/PyTorch_YOLOv4](https://github.com/WongKinYiu/PyTorch_YOLOv4) * [https://github.com/WongKinYiu/ScaledYOLOv4](https://github.com/WongKinYiu/ScaledYOLOv4) * [https://github.com/Megvii-BaseDetection/YOLOX](https://github.com/Megvii-BaseDetection/YOLOX) * [https://github.com/ultralytics/yolov3](https://github.com/ultralytics/yolov3) * [https://github.com/ultralytics/yolov5](https://github.com/ultralytics/yolov5) * [https://github.com/DingXiaoH/RepVGG](https://github.com/DingXiaoH/RepVGG) * [https://github.com/JUGGHM/OREPA_CVPR2022](https://github.com/JUGGHM/OREPA_CVPR2022) * [https://github.com/TexasInstruments/edgeai-yolov5/tree/yolo-pose](https://github.com/TexasInstruments/edgeai-yolov5/tree/yolo-pose)Owner
- Login: Bigtuo
- Kind: user
- Repositories: 4
- Profile: https://github.com/Bigtuo
GitHub Events
Total
- Issues event: 3
- Watch event: 20
- Fork event: 2
Last Year
- Issues event: 3
- Watch event: 20
- Fork event: 2
Dependencies
- gcr.io/google-appengine/python latest build
- Pillow *
- PyYAML >=5.3.1
- matplotlib >=3.2.2
- numpy >=1.18.5
- onnxruntime ==1.10.0
- opencv-python >=4.1.2
- pandas *
- pycocotools >=2.0
- scipy >=1.4.1
- seaborn >=0.11.0
- tensorboard >=2.4.1
- thop *
- torch >=1.7.0
- torchvision >=0.8.1
- tqdm >=4.41.0
- Flask ==1.0.2
- gunicorn ==19.9.0
- pip ==18.1