def _filter_crowd_proposals(roidb, crowd_thresh):
    """Finds proposals that are inside crowd regions and marks them as
    overlap = -1 with each ground-truth rois, which means they will be excluded
    from training.
    """
    for entry in roidb:
        gt_overlaps = entry['gt_overlaps'].toarray()
        crowd_inds = np.where(entry['is_crowd'] == 1)[0]
        non_gt_inds = np.where(entry['gt_classes'] == 0)[0]
        if len(crowd_inds) == 0 or len(non_gt_inds) == 0:
            continue
        crowd_boxes = box_utils.xyxy_to_xywh(entry['boxes'][crowd_inds, :])
        non_gt_boxes = box_utils.xyxy_to_xywh(entry['boxes'][non_gt_inds, :])
        iscrowd_flags = [int(True)] * len(crowd_inds)
        ious = COCOmask.iou(non_gt_boxes, crowd_boxes, iscrowd_flags)
        bad_inds = np.where(ious.max(axis=1) > crowd_thresh)[0]
        gt_overlaps[non_gt_inds[bad_inds], :] = -1
        entry['gt_overlaps'] = scipy.sparse.csr_matrix(gt_overlaps)
Finds proposals that are inside crowd regions and marks them as
    overlap = -1 with each ground-truth rois, which means they will be excluded
    from training.
    
detectron/datasets/json_dataset.py