Yolov7-pose
Overview
This python package is an 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.
This is a tailored version for use of the SAS Viya DLModelZoo action set.
Installation
To install YOLOv7-Pose, use the following command:
pip install sas-yolov7-pose
Contributing
We welcome your contributions! Please read CONTRIBUTING.md for details on how to submit contributions to this project.
License
This project is licensed under the GNU GENERAL PUBLIC LICENSE 3.0 License.
Additional Resources
- https://github.com/AlexeyAB/darknet
- https://github.com/WongKinYiu/yolor
- https://github.com/WongKinYiu/PyTorch_YOLOv4
- https://github.com/WongKinYiu/ScaledYOLOv4
- https://github.com/Megvii-BaseDetection/YOLOX
- https://github.com/ultralytics/yolov3
- https://github.com/ultralytics/yolov5
- https://github.com/DingXiaoH/RepVGG
- https://github.com/JUGGHM/OREPA_CVPR2022
- https://github.com/TexasInstruments/edgeai-yolov5/tree/yolo-pose
- https://github.com/WongKinYiu/yolov7/tree/pose
3 maintainers
Metadata
3 maintainers
Release files for sas-yolov7-pose 1.0.5
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| File | Size | Uploaded | Provenance | |
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| sas_yolov7_pose-1.0.5.tar.gz | 80.7 kB | Without provenance | Details |
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| sas_yolov7_pose-1.0.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 167.9 kB
Release files / sas_yolov7_pose-1.0.5.tar.gz
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Release files / sas_yolov7_pose-1.0.5-py3-none-any.whl
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