lib/roi_data/fast_rcnn_rel.py [315:329]:
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            _sample_rois_pos_neg_for_one_branch(
                unique_all_rois_obj, unique_obj_gt_boxes,
                unique_obj_gt_labels, unique_obj_gt_vecs,
                low_shot_helper, 'obj')
    fg_size_obj = pos_vecs_obj.shape[0]
    pos_starts_obj = np.array([0, 0], dtype=np.int32)
    pos_ends_obj = np.array([fg_size_obj, -1], dtype=np.int32)
    neg_starts_obj = np.array([fg_size_obj, 0], dtype=np.int32)
    neg_ends_obj = np.array([-1, -1], dtype=np.int32)
    obj_pos_labels = all_labels_obj[:fg_size_obj] - 1

    # Now sample rel rois
    rois_per_image = int(cfg.TRAIN.BATCH_SIZE_PER_IM)
    fg_rois_per_image = int(
        np.round(cfg.TRAIN.FG_FRACTION * rois_per_image))
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lib/roi_data/fast_rcnn_rel.py [544:557]:
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        _sample_rois_pos_neg_for_one_branch(
            unique_all_rois_obj, unique_obj_gt_boxes,
            unique_obj_gt_labels, unique_obj_gt_vecs,
            low_shot_helper, 'obj')
    fg_size_obj = pos_vecs_obj.shape[0]
    pos_starts_obj = np.array([0, 0], dtype=np.int32)
    pos_ends_obj = np.array([fg_size_obj, -1], dtype=np.int32)
    neg_starts_obj = np.array([fg_size_obj, 0], dtype=np.int32)
    neg_ends_obj = np.array([-1, -1], dtype=np.int32)
    obj_pos_labels = all_labels_obj[:fg_size_obj] - 1

    rois_per_image = int(cfg.TRAIN.BATCH_SIZE_PER_IM)
    fg_rois_per_image = int(
        np.round(cfg.TRAIN.FG_FRACTION * rois_per_image))
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