video_data_utils.py 文件源码

def decoderFn(num_samples=1, modality='rgb'):
  class decoder_func(slim.data_decoder.DataDecoder):
    @staticmethod
    def list_items():
      return ['image', 'label']

    @staticmethod
    def decode(data, items):
      with tf.name_scope('decode_video'):
        if modality == 'rgb':
          data.set_shape((num_samples,))
        elif modality.startswith('flow'):
          optical_flow_frames = int(modality[4:])
          data.set_shape((num_samples, 2 * optical_flow_frames))
        elif modality.startswith('rgb+flow'):
          optical_flow_frames = int(modality[-2:])
          data.set_shape((num_samples, 1 + 2 * optical_flow_frames))
        else:
          logging.error('Unknown modality %s\n' % modality)
        image_buffer = [_decode_from_string(el, modality) for
                        el in tf.unpack(data)]
        # image_buffer = tf.pack(image_buffer)
        return image_buffer
  return decoder_func