tensorflow/models · error · ValueError

Scores should have rank 1 or 2

Error message

Scores should have rank 1 or 2

What it means

Error "Scores should have rank 1 or 2" thrown in tensorflow/models.

Source

Thrown at official/vision/utils/object_detection/box_list_ops.py:720

      representing detection scores.
    thresh: scalar threshold
    scope: name scope.

  Returns:
    a BoxList holding M boxes where M <= N

  Raises:
    ValueError: if boxlist not a BoxList object or if it does not
      have a scores field
  """
  with tf.name_scope(scope or 'FilterGreaterThan'):
    if not isinstance(boxlist, box_list.BoxList):
      raise ValueError('boxlist must be a BoxList')
    if not boxlist.has_field('scores'):
      raise ValueError('input boxlist must have \'scores\' field')
    scores = boxlist.get_field('scores')
    if len(scores.shape.as_list()) > 2:
      raise ValueError('Scores should have rank 1 or 2')
    if len(scores.shape.as_list()) == 2 and scores.shape.as_list()[1] != 1:
      raise ValueError('Scores should have rank 1 or have shape '
                       'consistent with [None, 1]')
    high_score_indices = tf.cast(
        tf.reshape(tf.where(tf.greater(scores, thresh)), [-1]), tf.int32)
    return gather(boxlist, high_score_indices)


def non_max_suppression(boxlist, thresh, max_output_size, scope=None):
  """Non maximum suppression.

  This op greedily selects a subset of detection bounding boxes, pruning
  away boxes that have high IOU (intersection over union) overlap (> thresh)
  with already selected boxes.  Note that this only works for a single class ---
  to apply NMS to multi-class predictions, use MultiClassNonMaxSuppression.

  Args:
    boxlist: BoxList holding N boxes.  Must contain a 'scores' field

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Pass scores as a rank-1 or rank-2 tensor.
2. Reshape the scores tensor to [N] or [N, 1].

When it happens

Trigger: Thrown at official/vision/utils/object_detection/box_list_ops.py:720 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/1538d2787f9b428c. Report an issue: GitHub.