code: def load_bin_cv(path, image_size):
      bins, issame_list = pickle.load(
          open(path, "rb"), encoding="bytes"
      )
      data_list = []
      for flip in [0, 1]:
          data = flow.empty(
              len(issame_list) * 2, 3, image_size[0], image_size[1]
          )
          data_list.append(data)
      for i in range(len(issame_list) * 2):
          _bin = bins[i]
          img_ori = cv.imdecode(_bin, cv.IMREAD_COLOR)[:, :, ::-1]
  
          for flip in [0, 1]:
              img = img_ori.copy()
              if flip == 1:
                  img = cv.flip(img, 1)
              img = np.array(img).transpose((2, 0, 1))
              img = (img - 127.5) * 0.00784313725
              data_list[flip][i] = flow.tensor(img, dtype=flow.float)
  
          if i % 1000 == 0:
              logging.info("loading bin:%d", i)
      logging.info(data_list[0].shape)
      return data_list, issame_list
  
imports: import datetime
  import os
  import pickle
  import numpy
  import sklearn
  import oneflow
  from scipy import interpolate
  from sklearn.decomposition import PCA
  from sklearn.model_selection import KFold
  import cv2
  import logging
label_desc: Use image node_id 6 for calling a global function with example usage: load_bin_cv(path, image_size) and returns: data_list,  issame_list