text: import tensorflow as tf
  import numpy as np
  from keras.utils import to_categorical
  import sys
  
  
  def tfrecord2array(path_res):
      imgs = []
      lbls = []
      # print('tfrecords_files to be transformed:', path_res)
      reader = tf.TFRecordReader()
  
      filename_queue = tf.train.string_input_producer([path_res], num_epochs=1)
  
      # 从 TFRecord 读取内容并保存到 serialized_example 中
      _, serialized_example = reader.read(filename_queue)
      # 读取 serialized_example 的格式
      features = tf.parse_single_example(
          serialized_example,
          features={
              'image_raw': tf.FixedLenFeature([], tf.string),
              'label': tf.FixedLenFeature([], tf.int64),
          })
  
      # 解析从 serialized_example 读取到的内容
      labels = tf.cast(features['label'], tf.int64)
      images = tf.decode_raw(features['image_raw'], tf.uint8)
  
      # print('Extracting {} has just started.'.format(path_res))
      with tf.Session() as sess:
          # 启动多线程
          sess.run(tf.local_variables_initializer())
          coord = tf.train.Coordinator()
          threads = tf.train.start_queue_runners(sess=sess, coord=coord)
          while not coord.should_stop():
              try:
                  label, img = sess.run([labels, images])
              except tf.errors.OutOfRangeError:
                  print("Turn to next folder.")
                  break
              img = (img > 0).astype(np.uint8).reshape(-1)
              imgs.append(img)
              lbls.append(label)
              clock_lines = ['-', '\\', '|', '/']
  
              sys.stdout.write(
                  ''.join((str(np.array(lbls).shape[0]),
                           "-th sample in ",
                           path_res.split('/')[-2],
                           clock_lines[np.array(lbls).shape[0]//100 % 4],
                           '\r')))
              sys.stdout.flush()
  
          coord.request_stop()
          coord.join(threads)
      return to_categorical(np.array(lbls), num_classes=68), np.array(imgs)
  
  
  def main():
      imgs, labels = tfrecord2array(
          r"./data_tfrecords/integers_tfrecords/test.tfrecords")
      print("imgs.shape:", imgs.shape)
      print("labels.shape:", labels.shape)
  
  
  if __name__ == '__main__':
      main()
  