code: def convert_mean(binaryproto_fname, output=None):
      
      mean_blob = caffe_parser.caffe_pb2.BlobProto()
      with open(binaryproto_fname, 'rb') as f:
          mean_blob.ParseFromString(f.read())
  
      img_mean_np = np.array(mean_blob.data)
      img_mean_np = img_mean_np.reshape(
          mean_blob.channels, mean_blob.height, mean_blob.width
      )
      # swap channels from Caffe BGR to RGB
      img_mean_np[[0, 2], :, :] = img_mean_np[[2, 0], :, :]
      nd = mx.nd.array(img_mean_np)
      if output is not None:
          mx.nd.save(output, {"mean_image": nd})
      return nd
docs: Convert caffe mean
  
      Parameters
      ----------
      binaryproto_fname : str
          Filename of the mean
      output : str, optional
          Save the mean into mxnet's format
  
      Returns
      -------
      NDArray
          Mean in ndarray