tensorflow/models · error · ValueError

Input must be of size [height, width, C>0]

Error message

Input must be of size [height, width, C>0]

What it means

Error "Input must be of size [height, width, C>0]" thrown in tensorflow/models.

Source

Thrown at official/legacy/image_classification/preprocessing.py:62

  Note that the rank of `image` must be known.

  Args:
    image_bytes: a tensor of size [height, width, C].
    means: a C-vector of values to subtract from each channel.
    num_channels: number of color channels in the image that will be distorted.
    dtype: the dtype to convert the images to. Set to `None` to skip conversion.

  Returns:
    the centered image.

  Raises:
    ValueError: If the rank of `image` is unknown, if `image` has a rank other
      than three or if the number of channels in `image` doesn't match the
      number of values in `means`.
  """
  if image_bytes.get_shape().ndims != 3:
    raise ValueError('Input must be of size [height, width, C>0]')

  if len(means) != num_channels:
    raise ValueError('len(means) must match the number of channels')

  # We have a 1-D tensor of means; convert to 3-D.
  # Note(b/130245863): we explicitly call `broadcast` instead of simply
  # expanding dimensions for better performance.
  means = tf.broadcast_to(means, tf.shape(image_bytes))
  if dtype is not None:
    means = tf.cast(means, dtype=dtype)

  return image_bytes - means


def standardize_image(
    image_bytes: tf.Tensor,
    stddev: Tuple[float, ...],
    num_channels: int = 3,

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/legacy/image_classification/preprocessing.py:62 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of tensorflow/models@e006f5f0d5 (2026-08-24). Data as JSON: /api/errors/254c66631675cc85. Report an issue: GitHub.