def get_expected_image_size()

in tensorflow_hub/image_util.py [0:0]

• 24 lines of code
• 11 McCabe index (conditional complexity)

def get_expected_image_size(module_or_spec, signature=None, input_name=None):
  """Returns expected [height, width] dimensions of an image input.

  TODO(b/139530454): This does not work yet with TF2.

  Args:
    module_or_spec: a Module or ModuleSpec that accepts image inputs.
    signature: a string with the key of the signature in question.
      If None, the default signature is used.
    input_name: a string with the input name for images. If None, the
      conventional input name `images` for the default signature is used.

  Returns:
    A list if integers `[height, width]`.

  Raises:
    ValueError: If the size information is missing or malformed.
  """
  # First see if an attached ImageModuleInfo provides this information.
  image_module_info = get_image_module_info(module_or_spec)
  if image_module_info:
    size = image_module_info.default_image_size
    if size.height and size.width:
      return [size.height, size.width]

  # Else inspect the input shape in the module signature.
  if input_name is None:
    input_name = "images"
  input_info_dict = module_or_spec.get_input_info_dict(signature)
  try:
    shape = input_info_dict[input_name].get_shape()
  except KeyError:
    raise ValueError("Module is missing input '%s' in signature '%s'." %
                     (input_name, signature or "default"))
  try:
    _, height, width, _ = shape.as_list()
    if not height or not width:
      raise ValueError
  except ValueError:
    raise ValueError(
        "Shape of module input is %s, "
        "expected [batch_size, height, width, num_channels] "
        "with known height and width." % shape)
  return [height, width]