code: def agg_prediction(result: PredictionResult, thresh):
      coord_list = []
      res = result.to_coco_annotations()
      for ann in res:
          current_bbox = ann["bbox"]
          x = current_bbox[0]
          y = current_bbox[1]
          w = current_bbox[2]
          h = current_bbox[3]
  
          coord_list.append((x, y, w, h))
      cnts = sorted(
          coord_list,
          key=cmp_to_key(lambda a, b: bbox_sort(a, b, thresh)),
      )
      for pred in range(len(res) - 1):
          res[pred]["image_id"] = cnts.index(tuple(res[pred]["bbox"]))
  
      return res
  
imports: import logging
  import os
  import time
  from typing import List, Optional
  from sahi.utils.import_utils import is_available
  from functools import cmp_to_key
  import numpy
  from tqdm import tqdm
  from sahi.auto_model import AutoDetectionModel
  from sahi.models.base import DetectionModel
  from sahi.postprocess.combine import GreedyNMMPostprocess, LSNMSPostprocess, NMMPostprocess, NMSPostprocess, PostprocessPredictions
  from sahi.prediction import ObjectPrediction, PredictionResult
  from sahi.slicing import slice_image
  from sahi.utils.coco import Coco, CocoImage
  from sahi.utils.cv import IMAGE_EXTENSIONS, VIDEO_EXTENSIONS, crop_object_predictions, cv2, get_video_reader, read_image_as_pil, visualize_object_predictions
  from sahi.utils.file import Path, increment_path, list_files, save_json, save_pickle
  from sahi.utils.import_utils import check_requirements
label_desc: Use image node_id 4 for calling a global function with example usage: agg_prediction(result, thresh) and returns: res