code: def create_accumulator(self, input_path, information_file=None):
      # Check that motmetrics is installed here, so we don't have to process
      # the whole dataset before failing out if we don't.
      mm.metrics
  
      file_name = os.path.split(input_path)[1]
  
      self.frame_number = 1
      # Save the path of this video in a list
      self.paths = np.hstack((self.paths, input_path))
      # Initialize a matrix where we will save our predictions for this video (in the MOTChallenge format)
      self.matrix_predictions = []
  
      # Initialize progress bar
      if information_file is None:
          seqinfo_path = os.path.join(input_path, "seqinfo.ini")
          information_file = InformationFile(file_path=seqinfo_path)
      length = information_file.search(variable_name="seqLength")
      self.progress_bar_iter = track(
          range(length - 1), description=file_name, transient=False
      )
  
imports: import os
  import numpy
  from rich import print
  from rich.progress import track
  from norfair import Detection
  from collections import OrderedDict
label_desc: Use image node_id 2 for calling the Accumulators obj's underlying member method code with example usage: obj.create_accumulator(input_path, information_file) without return types