utils.py 文件源码

def ReadInput(self,num_epochs=None, val=False,test=False):
  if val:
    filenames = tf.gfile.Glob(self.data_dir+'/surfing_val.tfrecords')
  elif test:
    filenames = tf.gfile.Glob(self.data_dir+'/surfing_test.tfrecords')
  else:
    filenames = tf.gfile.Glob(self.data_dir+'/surfing.tfrecords')
  filename_queue = tf.train.string_input_producer(filenames,num_epochs=num_epochs, shuffle=True)
  reader = tf.TFRecordReader()
  _, example = reader.read(filename_queue)
  feature_sepc = {
      self.features: tf.FixedLenSequenceFeature(
          shape=[self.image_width * self.image_width * self.c_dim], dtype=tf.float32)}
  _, features = tf.parse_single_sequence_example(
      example, sequence_features=feature_sepc)
  moving_objs = tf.reshape(
      features[self.features], [self.video_len, self.image_width, self.image_width, self.c_dim])
  examples = tf.train.shuffle_batch(
        [moving_objs],
        batch_size=self.batch_size,
        num_threads=self.batch_size,
        capacity=self.batch_size * 100,
        min_after_dequeue=self.batch_size * 4)
  return examples