code: def evaluate(self, max_dets_per_image=None):
      all_preds, main_process = self.synchronize_between_processes()
      if main_process:
          if max_dets_per_image is None:
              max_dets_per_image = 300
  
          eval_imgs = [lvis_res["image_id"] for lvis_res in all_preds]
  
          gt_subset = LvisEvaluator._make_lvis_subset(
              self.lvis_gt, eval_imgs
          )
  
          for iou_type in self.iou_types:
              print("Evaluating for iou", iou_type)
              if iou_type == "segm":
                  # See:
                  # https://detectron2.readthedocs.io/en/latest/_modules/detectron2/evaluation/lvis_evaluation.html
                  lvis_results = copy.deepcopy(all_preds)
                  for c in lvis_results:
                      c.pop("bbox", None)
              else:
                  lvis_results = all_preds
  
              lvis_results = LVISResults(
                  gt_subset, lvis_results, max_dets=max_dets_per_image
              )
              lvis_eval = LVISEval(gt_subset, lvis_results, iou_type)
              lvis_eval.params.img_ids = list(set(eval_imgs))
              lvis_eval.run()
              self.lvis_eval_per_iou[iou_type] = lvis_eval
      else:
          self.lvis_eval_per_iou = None
  
      if dist.is_initialized():
          dist.barrier()
  
      return self.lvis_eval_per_iou
  
imports: import copy
  import itertools
  import logging
  from typing import List
  import numpy
  import pycocotools.mask
  import torch
  import torch.distributed
  from lvis import LVISEval, LVISResults, LVIS
label_desc: Use image node_id 4 for calling the LvisEvaluator obj's underlying member method code with example usage: obj.evaluate(max_dets_per_image) and returns: self