(image, output_height, output_width, is_training)
return image
Preprocesses the given image.

  Args:
    image: A `Tensor` representing an image of arbitrary size.
    output_height: The height of the image after preprocessing.
    output_width: The width of the image after preprocessing.
    is_training: `True` if we're preprocessing the image for training and
      `False` otherwise.

  Returns:
    A preprocessed image.
Preprocesses the given image.
Preprocesses the given image .
def preprocess_image(image, output_height, output_width, is_training):
  """Preprocesses the given image.

  Args:
    image: A `Tensor` representing an image of arbitrary size.
    output_height: The height of the image after preprocessing.
    output_width: The width of the image after preprocessing.
    is_training: `True` if we're preprocessing the image for training and
      `False` otherwise.

  Returns:
    A preprocessed image.
  """
  image = tf.to_float(image)
  image = tf.image.resize_image_with_crop_or_pad(
      image, output_width, output_height)
  image = tf.subtract(image, 128.0)
  image = tf.div(image, 128.0)
  return image
def preprocess_image ( image , output_height , output_width , is_training ) : image = tf . to_float ( image ) image = tf . image . resize_image_with_crop_or_pad ( image , output_width , output_height ) image = tf . subtract ( image , 128.0 ) image = tf . div ( image , 128.0 ) return image