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Object detection models usually generate multiple detections per object. Duplicates are removed in a post-processing step called Non-Maximum Suppression (NMS). The Pytorch code that performs this post-processing is called here in the RegionProposalNetwork class. The filtering loop you've mentioned performs the NMS and applies the score_thresh threshold (...


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I might be able to help with the theory, but the coding... it is a non standard API such as Tensorflow or Pytorch (it might be custom code for what I can tell). The key element here is that the bouding boxes are removed only if they hold a prediciton for the same class that the box that is overlapping with (but with less confidence, that is why it gets ...


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