WongKinYiu / yolov7

Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
GNU General Public License v3.0
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yolov7-Pose compared with edgeai-yolov5 #309

Open StochasticGame opened 2 years ago

StochasticGame commented 2 years ago

I put your recently submitted YOLOv7 pose detection model into my own modified edgeai-yolov5 project and used the inference prediction in the detect.py script, and the inference results were very good, but I had the problem of the key point going out of the target detection frame when using the model in edgeai-yolov5 for inference, I would like to know I would like to know how your yolov7-pose was trained, or how you avoided the keypoint out-of-bounds problem(yolov7-pose:Figure 1;edgeai-yolov5-pose:Figure 2) Figure 1 Figure 1 Figure 2 Figure 2

edgeai-yolov5/issues:https://github.com/TexasInstruments/edgeai-yolov5/issues/16

WongKinYiu commented 2 years ago

I do not do anything to avoid it. Just put yolor pose to edgeai-yolov5 pose code, and use same training script to train yolov7 pose.