class_docstr: Tracker for SORT/DeepSORT.
  
  Args:
      obj_score_thr (float, optional): Threshold to filter the objects.
          Defaults to 0.3.
      motion (dict): Configuration of motion. Defaults to None.
      reid (dict, optional): Configuration for the ReID model.
          - num_samples (int, optional): Number of samples to calculate the
              feature embeddings of a track. Default to 10.
          - image_scale (tuple, optional): Input scale of the ReID model.
              Default to (256, 128).
          - img_norm_cfg (dict, optional): Configuration to normalize the
              input. Default to None.
          - match_score_thr (float, optional): Similarity threshold for the
              matching process. Default to 2.0.
      match_iou_thr (float, optional): Threshold of the IoU matching process.
          Defaults to 0.7.
      num_tentatives (int, optional): Number of continuous frames to confirm
          a track. Defaults to 3.
class_docstr_tok: ["Tracker","for","SORT\/DeepSORT",".","Args",":","obj_score_thr","(","float",",","optional",")",":","Threshold","to","filter","the","objects",".","Defaults","to","0.3.","motion","(","dict",")",":","Configuration","of","motion",".","Defaults","to","None",".","reid","(","dict",",","optional",")",":","Configuration","for","the","ReID","model",".","-","num_samples","(","int",",","optional",")",":","Number","of","samples","to","calculate","the","feature","embeddings","of","a","track",".","Default","to","10",".","-","image_scale","(","tuple",",","optional",")",":","Input","scale","of","the","ReID","model",".","Default","to","(","256",",","128",")",".","-","img_norm_cfg","(","dict",",","optional",")",":","Configuration","to","normalize","the","input",".","Default","to","None",".","-","match_score_thr","(","float",",","optional",")",":","Similarity","threshold","for","the","matching","process",".","Default","to","2.0.","match_iou_thr","(","float",",","optional",")",":","Threshold","of","the","IoU","matching","process",".","Defaults","to","0.7.","num_tentatives","(","int",",","optional",")",":","Number","of","continuous","frames","to","confirm","a","track",".","Defaults","to","3","."]
code: def __init__(
      self,
      motion: Optional[dict] = None,
      obj_score_thr: float = 0.3,
      reid: dict = dict(
          num_samples=10,
          img_scale=(256, 128),
          img_norm_cfg=None,
          match_score_thr=2.0,
      ),
      match_iou_thr: float = 0.7,
      num_tentatives: int = 3,
      **kwargs,
  ):
      if motmetrics is None:
          raise RuntimeError(
              "motmetrics is not installed,\
                   please install it by: pip install motmetrics"
          )
      super().__init__(**kwargs)
      if motion is not None:
          self.motion = TASK_UTILS.build(motion)
          assert (
              self.motion is not None
          ), "SORT/Deep SORT need KalmanFilter"
      self.obj_score_thr = obj_score_thr
      self.reid = reid
      self.match_iou_thr = match_iou_thr
      self.num_tentatives = num_tentatives
  
file_path: mmdetection/mmdet/models/trackers/sort_tracker.py
imports: from typing import List, Optional, Tuple
  import numpy
  import torch
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.registry import MODELS, TASK_UTILS
  from mmdet.structures import DetDataSample
  from mmdet.structures.bbox import bbox_overlaps, bbox_xyxy_to_cxcyah
  from mmdet.utils import OptConfigType
  from ..utils import imrenormalize
  from .base_tracker import BaseTracker
label_desc: Use image node_id 1 to create a new SORTTracker object from inherited base classes: BaseTracker with example: obj = SORTTracker(motion, obj_score_thr, reid, match_iou_thr, num_tentatives)