code: def get_sizes_and_spacings_after_cropping(self):
      sizes = []
      spacings = []
      for c in self.patient_identifiers:
          properties = self.load_properties_of_cropped(c)
          sizes.append(properties["size_after_cropping"])
          spacings.append(properties["original_spacing"])
      return sizes, spacings
  
file_path: PaddleSeg/contrib/MedicalSeg/tools/preprocess_utils/dataset_analyzer.py
imports: import json
  import os
  import pickle
  import numpy
  from skimage.morphology import label
  from collections import OrderedDict
  from multiprocessing import Pool
  from .path_utils import join_paths
label_desc: Use image node_id 5 for calling the DatasetAnalyzer obj's underlying member method code with example usage: obj.get_sizes_and_spacings_after_cropping() and returns: sizes,  spacings