code: def get_recall_value(true_ids, result_ids):
      """
      Use the intersection length
      true_ids: neighbors taken from the dataset
      result_ids: ids returned by query
      """
      sum_radio = 0.0
      for index, item in enumerate(result_ids):
          # tmp = set(item).intersection(set(flat_id_list[index]))
  
          # Get the value of true_ids and the returned value to do the intersection
          tmp = set(true_ids[index]).intersection(set(item))
  
          # Add up each ratio
          sum_radio = sum_radio + len(tmp) / len(item)
          # logger.debug(sum_radio)
  
      # Calculate the average ratio and take three digits after the decimal point
      return round(sum_radio / len(result_ids), 3)
  
imports: import os
  import logging
  import numpy
  import sklearn.preprocessing
  import h5py
  import random
  from itertools import product
  from pymilvus import DataType
  from milvus_benchmark import config
label_desc: Use image node_id 14 for calling a global function with example usage: get_recall_value(true_ids, result_ids) and returns: round