tensorflow/models · error · ValueError

The masks must have the same dimensions.

Error message

The masks must have the same dimensions.

What it means

Error "The masks must have the same dimensions." thrown in tensorflow/models.

Source

Thrown at official/projects/waste_identification_ml/data_generation/utils.py:206

def _calculate_intersection_score(
    elem1: dict[str, Any], elem2: dict[str, Any]
) -> float:
  """Calculates the intersection score for two masks.

  Args:
    elem1: The first element.
    elem2: The second element.

  Returns:
    The intersection score calculated as the ratio of the intersection
    area to the area of the smaller mask.
  """

  # Check if the masks have the same dimensions.
  if elem1['segmentation'].shape != elem2['segmentation'].shape:
    raise ValueError('The masks must have the same dimensions.')

  min_elem = elem1 if elem1['area'] < elem2['area'] else elem2
  intersection = np.logical_and(elem1['segmentation'], elem2['segmentation'])
  score = np.sum(intersection) / np.sum(min_elem['segmentation'])
  return score


def filter_nested_similar_masks(
    elements: list[dict[str, Any]]
) -> list[dict[str, Any]]:
  """Filters out nested masks from a list of elements.

  Args:
    elements: A list of dictionaries representing elements.

  Returns:
    A list of dictionaries representing elements with nested masks filtered out.
  """

View on GitHub (pinned to e006f5f0d5)

When it happens

Trigger: Thrown at official/projects/waste_identification_ml/data_generation/utils.py:206 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/9451cefbb6d1417f. Report an issue: GitHub.