code: def scaled_euclidean(
      detection: "Detection", tracked_object: "TrackedObject"
  ) -> float:
      """
      Average euclidean distance between the points in detection and estimates in tracked_object, rescaled by the object diagonal
      See `np.linalg.norm`.
      """
      obj_estimate = tracked_object.estimate
      diagonal = np.linalg.norm(obj_estimate[1] - obj_estimate[8])
      return (
          np.linalg.norm(detection.points - obj_estimate, axis=1).mean()
          / diagonal
      )
  
file_path: norfair/demos/3d_track/src/utils.py
imports: import cv2
  import numpy
  from norfair import Palette
label_desc: Use image node_id 2 for calling a global function with example usage: scaled_euclidean(detection, tracked_object) and returns: unknown