def sort_by_field(boxlist, field, order=SortOrder.descend, scope=None):
  """Sort boxes and associated fields according to a scalar field.

  A common use case is reordering the boxes according to descending scores.

  Args:
    boxlist: BoxList holding N boxes.
    field: A BoxList field for sorting and reordering the BoxList.
    order: (Optional) descend or ascend. Default is descend.
    scope: name scope.

  Returns:
    sorted_boxlist: A sorted BoxList with the field in the specified order.

  Raises:
    ValueError: if specified field does not exist
    ValueError: if the order is not either descend or ascend
  """
  with tf.name_scope(scope, 'SortByField'):
    if order != SortOrder.descend and order != SortOrder.ascend:
      raise ValueError('Invalid sort order')

    field_to_sort = boxlist.get_field(field)
    if len(field_to_sort.shape.as_list()) != 1:
      raise ValueError('Field should have rank 1')

    num_boxes = boxlist.num_boxes()
    num_entries = tf.size(field_to_sort)
    length_assert = tf.Assert(
        tf.equal(num_boxes, num_entries),
        ['Incorrect field size: actual vs expected.', num_entries, num_boxes])

    with tf.control_dependencies([length_assert]):
      _, sorted_indices = tf.nn.top_k(field_to_sort, num_boxes, sorted=True)

    if order == SortOrder.ascend:
      sorted_indices = tf.reverse_v2(sorted_indices, [0])

    return gather(boxlist, sorted_indices)
Sort boxes and associated fields according to a scalar field.

  A common use case is reordering the boxes according to descending scores.

  Args:
    boxlist: BoxList holding N boxes.
    field: A BoxList field for sorting and reordering the BoxList.
    order: (Optional) descend or ascend. Default is descend.
    scope: name scope.

  Returns:
    sorted_boxlist: A sorted BoxList with the field in the specified order.

  Raises:
    ValueError: if specified field does not exist
    ValueError: if the order is not either descend or ascend
  
inference_api/src/main/object_detection/core/box_list_ops.py