code: def eval_image(image, height, width, scope=None):
    
    with tf.name_scope(values=[image, height, width], name=scope,
                       default_name='eval_image'):
      # Crop the central region of the image with an area containing 87.5% of
      # the original image.
      image = tf.image.central_crop(image, central_fraction=0.875)
  
      # Resize the image to the original height and width.
      image = tf.expand_dims(image, 0)
      image = tf.image.resize_bilinear(image, [height, width],
                                       align_corners=False)
      image = tf.squeeze(image, [0])
      return image
docs: Prepare one image for evaluation.
  
    Args:
      image: 3-D float Tensor
      height: integer
      width: integer
      scope: Optional scope for name_scope.
    Returns:
      3-D float Tensor of prepared image.