code: def __init__(self, tlwh, score, cls_id, buff_size=30, temp_feat=None):
      # wait activate
      self._tlwh = np.asarray(tlwh, dtype=np.float32)
      self.score = score
      self.cls_id = cls_id
      self.track_len = 0
  
      self.kalman_filter = None
      self.mean, self.covariance = None, None
      self.is_activated = False
  
      self.use_reid = True if temp_feat is not None else False
      if self.use_reid:
          self.smooth_feat = None
          self.update_features(temp_feat)
          self.features = deque([], maxlen=buff_size)
          self.alpha = 0.9
  
imports: import numpy
  from collections import defaultdict
  from collections import deque, OrderedDict
  from ..matching import jde_matching
  from ppdet.core.workspace import register, serializable
  import warnings
label_desc: Use image node_id 1 to create a new STrack object from inherited base classes: BaseTrack with example: obj = STrack(tlwh, score, cls_id, buff_size, temp_feat)