class_docstr: Tracker for Quasi-Dense Tracking.
  
  Args:
      init_score_thr (float): The cls_score threshold to
          initialize a new tracklet. Defaults to 0.8.
      obj_score_thr (float): The cls_score threshold to
          update a tracked tracklet. Defaults to 0.5.
      match_score_thr (float): The match threshold. Defaults to 0.5.
      memo_tracklet_frames (int): The most frames in a tracklet memory.
          Defaults to 10.
      memo_backdrop_frames (int): The most frames in the backdrops.
          Defaults to 1.
      memo_momentum (float): The momentum value for embeds updating.
          Defaults to 0.8.
      nms_conf_thr (float): The nms threshold for confidence.
          Defaults to 0.5.
      nms_backdrop_iou_thr (float): The nms threshold for backdrop IoU.
          Defaults to 0.3.
      nms_class_iou_thr (float): The nms threshold for class IoU.
          Defaults to 0.7.
      with_cats (bool): Whether to track with the same category.
          Defaults to True.
      match_metric (str): The match metric. Defaults to 'bisoftmax'.
docstr: Reset the buffer of the tracker.
docstr_tok: ["Reset","the","buffer","of","the","tracker","."]
code: def reset(self):
      """Reset the buffer of the tracker."""
      self.num_tracks = 0
      self.tracks = dict()
      self.backdrops = []
  
file_path: mmdetection/mmdet/models/trackers/quasi_dense_tracker.py
imports: from typing import List, Tuple
  import torch
  import torch.nn.functional
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.registry import MODELS
  from mmdet.structures import TrackDataSample
  from mmdet.structures.bbox import bbox_overlaps
  from .base_tracker import BaseTracker
label_desc: Use image node_id 2 for calling the QuasiDenseTracker obj's underlying member method code with example usage: obj.reset() without return types