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normalize output repp #19
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hello, i also want to add the post-processing into yolov5's detect.py. but i got the poor predictions. |
Hello. I am not familiar with YOLO 4 and 5. |
thank you for sharing! yeah! i uses the coco format (like this: {1: [{'id': 0, 'bbox': [472, 110, 16, 20], 'bbox_center': [480, 120, 16, 20], 'scores': [ 0.37517, 0.0020256, 0.00066277, 0.0032884]}, {'id': 1, 'bbox': [582, 361, 16, 12], 'bbox_center': [590, 367, 16, 12], 'scores':[ 0.49756, 0.0009155, 0.00011327, 0.0051832], ....}. where key (1) is frame index, key-id is index of detected candidate target, key-scores is class confidence(there are 4 classes). and, i only use two adjacent frames,the previous frame data is still original data (no repp operation).
Is there something wrong with me in understanding REPP? |
Hello,
Thanks for sharing this nice repo.
I would like normalize output repp for get map with yolo4 program. how i can do it?
output repp xyxy or xywh?
thanks
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