code: def parse_accs_metrics(seq_acc, index_name, verbose=False):
      """
      Parse the evaluation indicators of multiple MOTAccumulator
      """
      mh = mm.metrics.create()
      summary = MCMOTEvaluator.get_summary(
          seq_acc, index_name, METRICS_LIST
      )
      summary.loc["OVERALL", "motp"] = (
          summary["motp"] * summary["num_detections"]
      ).sum() / summary.loc["OVERALL", "num_detections"]
      if verbose:
          strsummary = mm.io.render_summary(
              summary, formatters=mh.formatters, namemap=NAME_MAP
          )
          print(strsummary)
  
      return summary
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import copy
  import sys
  import math
  from collections import defaultdict
  import numpy
  import pandas
  from .metrics import Metric
  from ppdet.utils.logger import setup_logger
label_desc: Use image node_id 1 for calling a global function with example usage: parse_accs_metrics(seq_acc, index_name, verbose) and returns: summary