For an all-in-one Python file that can run detection, segmentation, and pose estimation with various YOLO models (such as YOLOv5, YOLOv7, YOLOv8, and YOLOv11), you should choose a name that clearly reflects the functionality and the models used, while being concise. includes detection, segmentation, and pose estimation) using different YOLO models.
## recommended conda env python=3.10
## pip install ultralytics -U
$ python yolo_multi_model.py --source 0 1 vid1.mp4 vid2.mp4 --track --count
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- 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/ultralytics/ultralytics
