code: def update(self, predictions=None):
      # Get the tracked boxes from this frame in an array
      for obj in predictions:
          new_row = [
              self.frame_number,
              obj.id,
              obj.estimate[0, 0],
              obj.estimate[0, 1],
              obj.estimate[1, 0] - obj.estimate[0, 0],
              obj.estimate[1, 1] - obj.estimate[0, 1],
              -1,
              -1,
              -1,
              -1,
          ]
          if np.shape(self.matrix_predictions)[0] == 0:
              self.matrix_predictions = new_row
          else:
              self.matrix_predictions = np.vstack(
                  (self.matrix_predictions, new_row)
              )
      self.frame_number += 1
      # Advance in progress bar
      try:
          next(self.progress_bar_iter)
      except StopIteration:
          self.matrixes_predictions.append(self.matrix_predictions)
          return
  
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 3 for calling the Accumulators obj's underlying member method code with example usage: obj.update(predictions) without return types