class_docstr: Support MMDET object detection models.
  Refer to https://github.com/open-mmlab/mmdetection
code: def _update_classes(self, classes: Optional[list] = None):
      if classes:
          self.num_classes = len(classes)
          self.classes = classes
          update_mmdet_config(
              key="num_classes",
              value=self.num_classes,
              config=self.config,
          )
      else:
          self.num_classes = lookup_mmdet_config(
              key="num_classes", config=self.config
          )
          if not self.num_classes:
              self.num_classes = 1
              warnings.warn(
                  f"num_classes is not provided and is set to default value {self.num_classes} and this may cause error. Please provide sample_data_path in predictor's initialization."
              )
          self.classes = None
      self.id2label = dict(
          zip(range(self.num_classes), range(self.num_classes))
      )
  
imports: import logging
  import os
  import time
  import warnings
  from typing import Optional
  import torch
  from torch import nn
  from ..constants import BBOX, BBOX_FORMATS, COLUMN, IMAGE, IMAGE_VALID_NUM, LABEL, XYXY
  from .utils import freeze_model_layers, lookup_mmdet_config, update_mmdet_config
label_desc: Use image node_id 3 for calling the MMDetAutoModelForObjectDetection obj's underlying member method code with example usage: obj._update_classes(classes) without return types