code: def __init__(
      self,
      executor: Callable = people_detection_executor,
      model_name: str = "faster_rcnn_R_50_C4",
      threshold=0.7,
  ):
      self.inputs = ["loaded_image"]
      self.outputs = ["bbox_coordinates"]
      self.executor = executor
  
      # Configure detectron2
      self.cfg = get_cfg()
      self.model_config = det_models[model_name]
      self.cfg.merge_from_file(
          model_zoo.get_config_file(self.model_config)
      )
      self.cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url(
          self.model_config
      )
      self.cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = threshold
  
      if not torch.cuda.is_available():
          self.cfg.MODEL.DEVICE = "cpu"
  
      self.predictor = DefaultPredictor(self.cfg)
  
imports: from collections import OrderedDict
  from typing import Callable
  import cv2
  import torch
  from hook import HookBase
label_desc: Use image node_id 1 to create a new Detectron2PeopleDetectionHook object from inherited base classes: HookBase with example: obj = Detectron2PeopleDetectionHook(executor, model_name, threshold)