proposal_target_layer.py 文件源码

def _get_bbox_regression_labels(bbox_target_data, num_classes):
  """Bounding-box regression targets (bbox_target_data) are stored in a
  compact form N x (class, tx, ty, tw, th)

  This function expands those targets into the 4-of-4*K representation used
  by the network (i.e. only one class has non-zero targets).

  Returns:
      bbox_target (ndarray): N x 4K blob of regression targets
      bbox_inside_weights (ndarray): N x 4K blob of loss weights
  """

  clss = bbox_target_data[:, 0]
  bbox_targets = np.zeros((clss.size, 4 * num_classes), dtype=np.float32)
  bbox_inside_weights = np.zeros(bbox_targets.shape, dtype=np.float32)
  inds = np.where(clss > 0)[0]
  for ind in inds:
    cls = clss[ind]
    start = int(4 * cls)
    end = start + 4
    bbox_targets[ind, start:end] = bbox_target_data[ind, 1:]
    bbox_inside_weights[ind, start:end] = cfg.TRAIN.BBOX_INSIDE_WEIGHTS
  return bbox_targets, bbox_inside_weights