code: def _load_bboxes(csv_path, csv_positions, prefix):
    
    logging.info('Loading CSVs %s from positions %s with prefix %s',
                 csv_path, csv_positions, prefix)
    boxes = collections.defaultdict(list)
    with tf.io.gfile.GFile(csv_path) as csv_f:
      if csv_positions[0] > 0:
        csv_f.seek(csv_positions[0])
      else:
        csv_f.readline()  # Drop headers
      reader = csv.reader(csv_f)
      for (image_id, source, label, confidence, xmin, xmax, ymin, ymax,
           is_occluded, is_truncated, is_group_of, is_depiction, is_inside,
          ) in reader:
        if prefix and image_id[0] != prefix:
          break
        csv_positions[0] = csv_f.tell()
        image_id = int(image_id, 16)
        del confidence  # always 1 in bounding boxes.
        current_row = _Bbox(
            label, source, tfds.features.BBox(
                float(ymin), float(xmin), float(ymax), float(xmax)),
            int(is_occluded), int(is_truncated),
            int(is_group_of), int(is_depiction), int(is_inside))
        boxes[image_id].append(current_row)
    return dict(boxes)
docs: Returns bounded boxes listed within given CSV file.