lib/core/get_gt_perturbed_proposals.py [100:122]:
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            rows = set()
            unique_sbj_gt_inds = []
            for idx, row in enumerate(sbj_gt_boxes):
                if tuple(row) not in rows:
                    rows.add(tuple(row))
                    unique_sbj_gt_inds.append(idx)
            unique_sbj_gt_boxes = sbj_gt_boxes[unique_sbj_gt_inds, :]

            rows = set()
            unique_obj_gt_inds = []
            for idx, row in enumerate(obj_gt_boxes):
                if tuple(row) not in rows:
                    rows.add(tuple(row))
                    unique_obj_gt_inds.append(idx)
            unique_obj_gt_boxes = obj_gt_boxes[unique_obj_gt_inds, :]

            # use better sampling by default
            im_width = entry['width'] * scale
            im_height = entry['height'] * scale

            _rois_sbj = _augment_gt_boxes_by_perturbation(
                unique_sbj_gt_boxes[:, 1:5], im_width, im_height)
            rois_sbj = np.zeros((_rois_sbj.shape[0], 5), dtype=np.float32)
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lib/roi_data/fast_rcnn_rel.py [122:144]:
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                rows = set()
                unique_sbj_gt_inds = []
                for idx, row in enumerate(sbj_gt_boxes):
                    if tuple(row) not in rows:
                        rows.add(tuple(row))
                        unique_sbj_gt_inds.append(idx)
                unique_sbj_gt_boxes = sbj_gt_boxes[unique_sbj_gt_inds, :]

                rows = set()
                unique_obj_gt_inds = []
                for idx, row in enumerate(obj_gt_boxes):
                    if tuple(row) not in rows:
                        rows.add(tuple(row))
                        unique_obj_gt_inds.append(idx)
                unique_obj_gt_boxes = obj_gt_boxes[unique_obj_gt_inds, :]

                # use better sampling by default
                im_width = entry['width'] * scale
                im_height = entry['height'] * scale

                _rois_sbj = _augment_gt_boxes_by_perturbation(
                    unique_sbj_gt_boxes[:, 1:5], im_width, im_height)
                rois_sbj = np.zeros((_rois_sbj.shape[0], 5), dtype=np.float32)
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