code: def print_class_histogram(roidbs):
      
      dataset = DetectionDataset()
      hist_bins = np.arange(dataset.num_classes + 1)
  
      # Histogram of ground-truth objects
      gt_hist = np.zeros((dataset.num_classes,), dtype=np.int)
      for entry in roidbs:
          # filter crowd?
          gt_inds = np.where(
              (entry['class'] > 0) & (entry['is_crowd'] == 0))[0]
          gt_classes = entry['class'][gt_inds]
          gt_hist += np.histogram(gt_classes, bins=hist_bins)[0]
      data = [[dataset.class_names[i], v] for i, v in enumerate(gt_hist)]
      data.append(['total', sum(x[1] for x in data)])
      # the first line is BG
      table = tabulate(data[1:], headers=['class', '#box'], tablefmt='pipe')
      logger.info("Ground-Truth Boxes:\n" + colored(table, 'cyan'))
docs: Args:
          roidbs (list[dict]): the same format as the output of `load_training_roidbs`.