docstr: given a fragment, compute FPFH descriptor for keypoints
docstr_tok: ["given","a","fragment",",","compute","FPFH","descriptor","for","keypoints"]
code: def __init__(
      self, radius=0.3, max_nn=128, radius_normal=0.3, max_nn_normal=17
  ):
      """
      given a fragment, compute FPFH descriptor for keypoints
      """
      self.kdtree = open3d.geometry.KDTreeSearchParamHybrid(
          radius, max_nn
      )
      self.kdtree_normal = open3d.geometry.KDTreeSearchParamHybrid(
          radius_normal, max_nn_normal
      )
  
file_path: torch-points3d/scripts/test_registration_scripts/fpfh.py
imports: import open3d
  import torch
  import numpy
  import hydra
  import os
  import os.path
  import sys
  import json
  from omegaconf import OmegaConf
  from test_registration_scripts.save_feature import save
label_desc: Use image node_id 1 to create a new FPFH object from inherited base classes: object with example: obj = FPFH(radius, max_nn, radius_normal, max_nn_normal)