code: def rescaled_keypoints_vote(detected_pose, tracked_pose):
      distances = np.linalg.norm(
          detected_pose.points - tracked_pose.estimate, axis=1
      )
  
      match_num = np.count_nonzero(
          (
              distances
              < KEYPOINT_DIST_SCALE_FACTOR
              * np.linalg.norm(
                  tracked_pose.estimate[11] - tracked_pose.estimate[15]
              )
          )
          * (detected_pose.scores > DETECTION_THRESHOLD)
          * (tracked_pose.last_detection.scores > DETECTION_THRESHOLD)
      )
      return 1 / (1 + match_num)
  
file_path: norfair/demos/profiling/src/utils.py
imports: import json
  import cv2
  import numpy
  import PIL.Image
  import torch
  import torch2trt
  import torchvision.transforms
  import trt_pose.coco
  import trt_pose.models
  from torch2trt import TRTModule
  from trt_pose.parse_objects import ParseObjects
  from norfair import Detection
  from norfair.distances import create_keypoints_voting_distance, create_normalized_mean_euclidean_distance
  from norfair.filter import FilterPyKalmanFilterFactory, NoFilterFactory, OptimizedKalmanFilterFactory
label_desc: Use image node_id 5 for calling a global function with example usage: rescaled_keypoints_vote(detected_pose, tracked_pose) and returns: unknown