code: def filter_scores_greater_than(box_mask_list, thresh):
      """Filter to keep only boxes and masks with score exceeding a given threshold.
  
      This op keeps the collection of boxes and masks whose corresponding scores are
      greater than the input threshold.
  
      Args:
        box_mask_list: BoxMaskList holding N boxes and masks.  Must contain a
          'scores' field representing detection scores.
        thresh: scalar threshold
  
      Returns:
        a BoxMaskList holding M boxes and masks where M <= N
  
      Raises:
        ValueError: if box_mask_list not a np_box_mask_list.BoxMaskList object or
          if it does not have a scores field
      """
      if not isinstance(box_mask_list, np_box_mask_list.BoxMaskList):
          raise ValueError("box_mask_list must be a BoxMaskList")
      if not box_mask_list.has_field("scores"):
          raise ValueError(
              "input box_mask_list must have 'scores' field"
          )
      scores = box_mask_list.get_field("scores")
      if len(scores.shape) > 2:
          raise ValueError("Scores should have rank 1 or 2")
      if len(scores.shape) == 2 and scores.shape[1] != 1:
          raise ValueError(
              "Scores should have rank 1 or have shape "
              "consistent with [None, 1]"
          )
      high_score_indices = np.reshape(
          np.where(np.greater(scores, thresh)), [-1]
      ).astype(np.int32)
      return gather(box_mask_list, high_score_indices)
  
file_path: SlowFast/ava_evaluation/np_box_mask_list_ops.py
imports: from __future__ import absolute_import, division, print_function, unicode_literals
  import numpy
  from .None import np_box_list_ops, np_box_mask_list, np_mask_ops
label_desc: Use image node_id 12 for calling a global function with example usage: filter_scores_greater_than(box_mask_list, thresh) and returns: gather