tensorflow/models · error · ValueError

anchors must be an BoxList

Error message

anchors must be an BoxList

What it means

Error "anchors must be an BoxList" thrown in tensorflow/models.

Source

Thrown at official/vision/utils/object_detection/target_assigner.py:130

        Matcher.

    Returns:
      cls_targets: a float32 tensor with shape [num_anchors, d_1, d_2 ... d_k],
        where the subshape [d_1, ..., d_k] is compatible with groundtruth_labels
        which has shape [num_gt_boxes, d_1, d_2, ... d_k].
      cls_weights: a float32 tensor with shape [num_anchors]
      reg_targets: a float32 tensor with shape [num_anchors, box_code_dimension]
      reg_weights: a float32 tensor with shape [num_anchors]
      match: a matcher.Match object encoding the match between anchors and
        groundtruth boxes, with rows corresponding to groundtruth boxes
        and columns corresponding to anchors.

    Raises:
      ValueError: if anchors or groundtruth_boxes are not of type
        box_list.BoxList
    """
    if not isinstance(anchors, box_list.BoxList):
      raise ValueError('anchors must be an BoxList')
    if not isinstance(groundtruth_boxes, box_list.BoxList):
      raise ValueError('groundtruth_boxes must be an BoxList')

    if groundtruth_labels is None:
      groundtruth_labels = tf.ones(
          tf.expand_dims(groundtruth_boxes.num_boxes(), 0))
      groundtruth_labels = tf.expand_dims(groundtruth_labels, -1)
    unmatched_shape_assert = shape_utils.assert_shape_equal(
        shape_utils.combined_static_and_dynamic_shape(groundtruth_labels)[1:],
        shape_utils.combined_static_and_dynamic_shape(
            self._unmatched_cls_target))
    labels_and_box_shapes_assert = shape_utils.assert_shape_equal(
        shape_utils.combined_static_and_dynamic_shape(groundtruth_labels)[:1],
        shape_utils.combined_static_and_dynamic_shape(
            groundtruth_boxes.get())[:1])

    if groundtruth_weights is None:
      num_gt_boxes = groundtruth_boxes.num_boxes_static()

View on GitHub (pinned to e006f5f0d5)

Solutions

  1. Pass anchors as a BoxList instance.
  2. Wrap the anchor tensor in box_list.BoxList(anchors).

When it happens

Trigger: Thrown at official/vision/utils/object_detection/target_assigner.py:130 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/edaab38787025f7f. Report an issue: GitHub.