ultralytics / yolov3

YOLOv3 in PyTorch > ONNX > CoreML > TFLite
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if there are multi detected targets of the same class in output, how are they sorted? #1754

Closed zssure-thu closed 3 years ago

zssure-thu commented 3 years ago

❔Question

if there are multi detected targets of the same class in output, how are they sorted?

Additional context

image As shown in the picture above, it contains two persons, the left one and the right one. And they are recorded in the first two lines in label file XXX.txt, like" 0.481719 0.634028 0.690625 0.713278" and "0.741094 0.524306 0.314750 0.933389". I want to know is there a sorting logic in the label file?

github-actions[bot] commented 3 years ago

👋 Hello @zssure-thu, thank you for your interest in YOLOv3 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution.

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glenn-jocher commented 3 years ago

@zssure-thu there is no default sorting on labels or predictions within an image.

zssure-thu commented 3 years ago

@glenn-jocher > there is no default sorting on labels or predictions within an image Thanks. So if we want to trace the target man, we should do post-processing on labels by ourselves.

glenn-jocher commented 3 years ago

@zssure-thu actually I just remembered, I think the outputs in detect.py at least are sorted by reverse confidence, lowest first. This is to allow the higher confidence boxes to overlay the lower confidence ones if there is a conflict.

zssure-thu commented 3 years ago

@zssure-thu actually I just remembered, I think the outputs in detect.py at least are sorted by reverse confidence, lowest first. This is to allow the higher confidence boxes to overlay the lower confidence ones if there is a conflict.

@glenn-jocher THANKS.

github-actions[bot] commented 3 years ago

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

glenn-jocher commented 11 months ago

@zssure-thu you're welcome! Always happy to help. The YOLO community and Ultralytics team are constantly working to improve the framework.