feat: Filter out low-confidence bounding box detections #3154
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fixes issue with len(keepers). Since keepers is a tuple with indices, it's len() is not indicative of the number of bboxes that should be kept. This is resolved by using Any()
… reproducibility. instead of a default filtering threshold of 0.25, the filtering is made optional and by default all bboxes are kept.
Low-confidence bounding boxes are removed when min_bbox_score parameter is provided. Default behavior remains unchanged.
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Revised version of PR #3118 by @tlancaster6
Feature
Filter out low-confidence bounding box detections during top-down pose estimation to reduce false-positives.
Function
get_inference_runnersin deeplabcut.pose_estimation_pytorch now accepts an optional argumentmin_bbox_score. Low-confidence bounding boxes are removed when min_bbox_score parameter is provided. Default behavior remains unchanged (i.e. all bounding boxes are kept).