code: def read_results(
      filename,
      data_type,
      is_gt=False,
      is_ignore=False,
      multi_class=False,
      union=False,
  ):
      if data_type in ["mcmot", "lab"]:
          if multi_class:
              if union:
                  # The results are evaluated by union all the categories.
                  # Track IDs between different categories cannot be duplicate.
                  read_fun = read_mcmot_results_union
              else:
                  # The results are evaluated separately by category.
                  read_fun = read_mcmot_results
          else:
              raise ValueError(
                  "multi_class: {}, MCMOT should have cls_id.".format(
                      multi_class
                  )
              )
      else:
          raise ValueError("Unknown data type: {}".format(data_type))
  
      return read_fun(filename, is_gt, is_ignore)
  
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 5 for calling a global function with example usage: read_results(filename, data_type, is_gt, is_ignore, multi_class, union) and returns: read_fun