code: def __getitem__(self, properties):
      # properites is a tuple, contains (width, height, index)
      img_height = properties[1]
      idx = properties[2]
      if self.ds_width and properties[3] is not None:
          wh_ratio = properties[3]
          img_width = img_height * (
              1 if int(round(wh_ratio)) == 0 else int(round(wh_ratio))
          )
          file_idx = self.wh_ratio_sort[idx]
      else:
          file_idx = self.data_idx_order_list[idx]
          img_width = properties[0]
          wh_ratio = None
  
      data_line = self.data_lines[file_idx]
      try:
          data_line = data_line.decode("utf-8")
          substr = data_line.strip("\n").split(self.delimiter)
          file_name = substr[0]
          file_name = self._try_parse_filename_list(file_name)
          label = substr[1]
          img_path = os.path.join(self.data_dir, file_name)
          data = {"img_path": img_path, "label": label}
          if not os.path.exists(img_path):
              raise Exception("{} does not exist!".format(img_path))
          with open(data["img_path"], "rb") as f:
              img = f.read()
              data["image"] = img
          data["ext_data"] = self.get_ext_data()
          outs = transform(data, self.ops[:-1])
          if outs is not None:
              outs = self.resize_norm_img(outs, img_width, img_height)
              outs = transform(outs, self.ops[-1:])
      except:
          self.logger.error(
              "When parsing line {}, error happened with msg: {}".format(
                  data_line, traceback.format_exc()
              )
          )
          outs = None
      if outs is None:
          # during evaluation, we should fix the idx to get same results for many times of evaluation.
          rnd_idx = (idx + 1) % self.__len__()
          return self.__getitem__(
              [img_width, img_height, rnd_idx, wh_ratio]
          )
      return outs
  
imports: import numpy
  import cv2
  import math
  import os
  import json
  import random
  import traceback
  from paddle.io import Dataset
  from .imaug import transform, create_operators
label_desc: Use image node_id 4 for calling the MultiScaleDataSet obj's underlying member method code with example usage: obj.__getitem__(properties) and returns: outs, self