code: def compute_dists(kp_source, kp_target, trans):
      """
      compute distance between points that are matches
      """
      kp_target_t = kp_target.dot(trans[:3, :3].T) + trans[:3, 3]
      dist = np.linalg.norm(kp_source - kp_target_t, axis=1)
      return dist
  
file_path: torch-points3d/scripts/test_registration_scripts/descriptor_matcher.py
imports: import pandas
  import hydra
  import numpy
  from sklearn.neighbors import KDTree
  import os
  import os.path
  from omegaconf import OmegaConf
  import sys
  import matplotlib.pyplot
label_desc: Use image node_id 3 for calling a global function with example usage: compute_dists(kp_source, kp_target, trans) and returns: dist