code: def __getitem__(self, idx):
      each_line = self.lines[idx]
      name_lmk_score = each_line.strip().split(" ")
      name = os.path.join(self.root, name_lmk_score[0])
      img = cv2.cvtColor(cv2.imread(name), cv2.COLOR_BGR2RGB)
      landmark5 = np.array(
          [float(x) for x in name_lmk_score[1:-1]], dtype=np.float32
      ).reshape((5, 2))
      st = skimage.transform.SimilarityTransform()
      st.estimate(landmark5, SRC)
      img = cv2.warpAffine(
          img, st.params[0:2, :], (112, 112), borderValue=0.0
      )
      img_1 = np.expand_dims(img, 0)
      img_2 = np.expand_dims(np.fliplr(img), 0)
      output = np.concatenate((img_1, img_2), axis=0).astype(np.float32)
      output = np.transpose(output, (0, 3, 1, 2))
      output = mx.nd.array(output)
      return output
  
imports: import argparse
  import os
  import pickle
  import timeit
  import cv2
  import mxnet
  import numpy
  import pandas
  import prettytable
  import skimage.transform
  from sklearn.metrics import roc_curve
  from sklearn.preprocessing import normalize
  import insightface
  from insightface.model_zoo import ArcFaceONNX
label_desc: Use image node_id 3 for calling the AlignedDataSet obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: output