image_read_utils.py 文件源码

def _read_from_disk_temporal(
    fpath, nframes, num_samples=25,
    optical_flow_frames=10, start_frame=0,
    file_prefix='', file_zero_padding=4, file_index=1,
    dataset_dir='', step=None):
    duration = nframes
    if step is None:
      if num_samples == 1:
          step = tf.random_uniform([1], 0, nframes-optical_flow_frames-1, dtype='int32')[0]
      else:
          step = tf.cast((duration-tf.constant(optical_flow_frames)) /
                         (tf.constant(num_samples)), 'int32')
    allimgs = []
    with tf.variable_scope('read_flow_video'):
        for i in range(num_samples):
            if num_samples == 1:
                i = 1  # so that the random step value can be used
            with tf.variable_scope('read_flow_image'):
              flow_img = []
              for j in range(optical_flow_frames):
                with tf.variable_scope('read_flow_channels'):
                  for dr in ['x', 'y']:
                    prefix = file_prefix + '_' if file_prefix else ''
                    impath = tf.string_join([
                        tf.constant(dataset_dir + '/'),
                        fpath, tf.constant('/'),
                        prefix, '%s_' % dr,
                        tf.as_string(start_frame + i * step + file_index + j,
                          width=file_zero_padding, fill='0'),
                        tf.constant('.jpg')])
                    img_str = tf.read_file(impath)
                    flow_img.append(img_str)
              allimgs.append(flow_img)
    return allimgs