class_docstr: This class represents a bounding box detection in a single image.
  
  Args:
      tlwh (Tensor): Bounding box in format `(top left x, top left y,
          width, height)`.
      score (Tensor): Bounding box confidence score.
      feature (Tensor): A feature vector that describes the object 
          contained in this image.
      cls_id (Tensor): Bounding box category id.
code: def __init__(self, tlwh, score, feature, cls_id):
      self.tlwh = np.asarray(tlwh, dtype=np.float32)
      self.score = float(score)
      self.feature = np.asarray(feature, dtype=np.float32)
      self.cls_id = int(cls_id)
  
imports: import os
  import cv2
  import time
  import numpy
  from .visualization import plot_tracking_dict, plot_tracking
label_desc: Use image node_id 1 to create a new Detection object from inherited base classes: object with example: obj = Detection(tlwh, score, feature, cls_id)