tensorflow/models · error · ValueError

The image has spatial dimensions %s but the mask has dimensi

Error message

The image has spatial dimensions %s but the mask has dimensions %s

What it means

Error "The image has spatial dimensions %s but the mask has dimensions %s" thrown in tensorflow/models.

Source

Thrown at official/vision/utils/object_detection/visualization_utils.py:669

  Args:
    image: uint8 numpy array with shape (img_height, img_height, 3)
    mask: a uint8 numpy array of shape (img_height, img_height) with values
      between either 0 or 1.
    color: color to draw the keypoints with. Default is red.
    alpha: transparency value between 0 and 1. (default: 0.4)

  Raises:
    ValueError: On incorrect data type for image or masks.
  """
  if image.dtype != np.uint8:
    raise ValueError('`image` not of type np.uint8')
  if mask.dtype != np.uint8:
    raise ValueError('`mask` not of type np.uint8')
  if np.any(np.logical_and(mask != 1, mask != 0)):
    raise ValueError('`mask` elements should be in [0, 1]')
  if image.shape[:2] != mask.shape:
    raise ValueError('The image has spatial dimensions %s but the mask has '
                     'dimensions %s' % (image.shape[:2], mask.shape))
  rgb = ImageColor.getrgb(color)
  pil_image = Image.fromarray(image)

  solid_color = np.expand_dims(
      np.ones_like(mask), axis=2) * np.reshape(list(rgb), [1, 1, 3])
  pil_solid_color = Image.fromarray(np.uint8(solid_color)).convert('RGBA')
  pil_mask = Image.fromarray(np.uint8(255.0 * alpha * mask)).convert('L')
  pil_image = Image.composite(pil_solid_color, pil_image, pil_mask)
  np.copyto(image, np.array(pil_image.convert('RGB')))


def visualize_boxes_and_labels_on_image_array(
    image,
    boxes,
    classes,
    scores,
    category_index,

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Resize the mask to the image's spatial dimensions before overlaying.
2. Ensure mask and image share the same height and width.

When it happens

Trigger: Thrown at official/vision/utils/object_detection/visualization_utils.py:669 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/bdfa4449a51a54d7. Report an issue: GitHub.