class_docstr: This class wraps an object detection model and performs pre-processing and post-processing.
class_docstr_tok: ["This","class","wraps","an","object","detection","model","and","performs","pre-processing","and","post-processing","."]
docstr: Construct an Object Detector object.
  
  Args:
      model: an object detection model.
      pre_processor: a pre-processing module
      post_processor: a post-processing module.
docstr_tok: ["Construct","an","Object","Detector","object",".","Args",":","model",":","an","object","detection","model",".","pre_processor",":","a","pre-processing","module","post_processor",":","a","post-processing","module","."]
code: def __init__(
      self, model: Module, pre_processor: Module, post_processor: Module
  ) -> None:
      """Construct an Object Detector object.
  
      Args:
          model: an object detection model.
          pre_processor: a pre-processing module
          post_processor: a post-processing module.
      """
      super().__init__()
      self.model = model.eval()
      self.pre_processor = pre_processor.eval()
      self.post_processor = post_processor.eval()
  
imports: from __future__ import annotations
  from dataclasses import dataclass
  from enum import Enum
  from typing import Optional
  import torch
  from kornia.core import Module, Tensor, concatenate
  from kornia.core.check import KORNIA_CHECK_SHAPE
  from kornia.image.base import ImageSize
label_desc: Use image node_id 1 to create a new ObjectDetector object from inherited base classes: Module with example: obj = ObjectDetector(model, pre_processor, post_processor)