tensorflow/models · error · ValueError

pool_boxes must have a 'classes' field

Error message

pool_boxes must have a 'classes' field

What it means

Error "pool_boxes must have a 'classes' field" thrown in tensorflow/models.

Source

Thrown at official/vision/utils/object_detection/box_list_ops.py:898

  Returns:
    BoxList of refined boxes.

  Raises:
    ValueError: if
      a) nms_iou_thresh or voting_iou_thresh is not in [0, 1].
      b) pool_boxes is not a BoxList.
      c) pool_boxes does not have a scores and classes field.
  """
  if not 0.0 <= nms_iou_thresh <= 1.0:
    raise ValueError('nms_iou_thresh must be between 0 and 1')
  if not 0.0 <= voting_iou_thresh <= 1.0:
    raise ValueError('voting_iou_thresh must be between 0 and 1')
  if not isinstance(pool_boxes, box_list.BoxList):
    raise ValueError('pool_boxes must be a BoxList')
  if not pool_boxes.has_field('scores'):
    raise ValueError('pool_boxes must have a \'scores\' field')
  if not pool_boxes.has_field('classes'):
    raise ValueError('pool_boxes must have a \'classes\' field')

  refined_boxes = []
  for i in range(num_classes):
    boxes_class = filter_field_value_equals(pool_boxes, 'classes', i)
    refined_boxes_class = refine_boxes(boxes_class, nms_iou_thresh,
                                       nms_max_detections, voting_iou_thresh)
    refined_boxes.append(refined_boxes_class)
  return sort_by_field(concatenate(refined_boxes), 'scores')


def refine_boxes(pool_boxes,
                 nms_iou_thresh,
                 nms_max_detections,
                 voting_iou_thresh=0.5):
  """Refines a pool of boxes using non max suppression and box voting.

  Args:
    pool_boxes: (BoxList) A collection of boxes to be refined. pool_boxes must

View on GitHub (pinned to e006f5f0d5)

Solutions

1. Add a 'classes' field to pool_boxes.
2. Call pool_boxes.add_field('classes', classes) first.

When it happens

Trigger: Thrown at official/vision/utils/object_detection/box_list_ops.py:898 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/e38bfad0730df1eb. Report an issue: GitHub.