class_docstr: StrongSORT: Make DeepSORT Great Again.
  
  Details can be found at `StrongSORT<https://arxiv.org/abs/2202.13514>`_.
  
  Args:
      detector (dict): Configuration of detector. Defaults to None.
      reid (dict): Configuration of reid. Defaults to None
      tracker (dict): Configuration of tracker. Defaults to None.
      kalman (dict): Configuration of Kalman filter. Defaults to None.
      cmc (dict): Configuration of camera model compensation.
          Defaults to None.
      data_preprocessor (dict or ConfigDict, optional): The pre-process
         config of :class:`TrackDataPreprocessor`.  it usually includes,
          ``pad_size_divisor``, ``pad_value``, ``mean`` and ``std``.
      init_cfg (dict or list[dict]): Configuration of initialization.
          Defaults to None.
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code: def __init__(
      self,
      detector: Optional[dict] = None,
      reid: Optional[dict] = None,
      cmc: Optional[dict] = None,
      tracker: Optional[dict] = None,
      postprocess_model: Optional[dict] = None,
      data_preprocessor: OptConfigType = None,
      init_cfg: OptConfigType = None,
  ):
      super().__init__(
          detector, reid, tracker, data_preprocessor, init_cfg
      )
  
      if cmc is not None:
          self.cmc = TASK_UTILS.build(cmc)
  
      if postprocess_model is not None:
          self.postprocess_model = TASK_UTILS.build(postprocess_model)
  
file_path: mmdetection/mmdet/models/mot/strongsort.py
imports: from typing import Optional
  import numpy
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.registry import MODELS, TASK_UTILS
  from mmdet.structures import TrackSampleList
  from mmdet.utils import OptConfigType
  from .deep_sort import DeepSORT
label_desc: Use image node_id 1 to create a new StrongSORT object from inherited base classes: DeepSORT with example: obj = StrongSORT(detector, reid, cmc, tracker, postprocess_model, data_preprocessor, init_cfg)