class_docstr: PyTorch object detection model operator, detect the region of interests in one image and predict the object classes
  in these regions.
class_docstr_tok: ["PyTorch","object","detection","model","operator",",","detect","the","region","of","interests","in","one","image","and","predict","the","object","classes","in","these","regions","."]
code: def __init__(self, model_name) -> None:
      super().__init__()
      model_func = getattr(torchvision.models.detection, model_name)
      self._model = model_func(pretrained=True)
      self._model.eval()
  
file_path: towhee/tests/unittests/mock_operators/pytorch_object_detection_operator/pytorch_object_detection_operator.py
imports: import numpy
  import torch
  import torchvision
  from typing import NamedTuple, List
  from pathlib import Path
  from towhee.operator import Operator
label_desc: Use image node_id 1 to create a new PyTorchObjectDetectionOperator object from inherited base classes: Operator with example: obj = PyTorchObjectDetectionOperator(model_name)