(image_list, crop_height, crop_width)
return outputs
Performs central crops of the given image list.

  Args:
    image_list: a list of image tensors of the same dimension but possibly
      varying channel.
    crop_height: the height of the image following the crop.
    crop_width: the width of the image following the crop.

  Returns:
    the list of cropped images.
Performs central crops of the given image list.
Performs central crops of the given image list .
def _central_crop(image_list, crop_height, crop_width):
  """Performs central crops of the given image list.

  Args:
    image_list: a list of image tensors of the same dimension but possibly
      varying channel.
    crop_height: the height of the image following the crop.
    crop_width: the width of the image following the crop.

  Returns:
    the list of cropped images.
  """
  outputs = []
  for image in image_list:
    image_height = tf.shape(image)[0]
    image_width = tf.shape(image)[1]

    offset_height = (image_height - crop_height) / 2
    offset_width = (image_width - crop_width) / 2

    outputs.append(_crop(image, offset_height, offset_width,
                         crop_height, crop_width))
  return outputs
def _central_crop ( image_list , crop_height , crop_width ) : outputs = [ ] for image in image_list : image_height = tf . shape ( image ) [ 0 ] image_width = tf . shape ( image ) [ 1 ] offset_height = ( image_height - crop_height ) / 2 offset_width = ( image_width - crop_width ) / 2 outputs . append ( _crop ( image , offset_height , offset_width , crop_height , crop_width ) ) return outputs