转自下面的
https://blog.csdn.net/happyhorizion/article/details/77894055
https://blog.csdn.net/sinat_29957455/article/details/83316173
tfrecord数据文件是一种将图像数据和标签统一存储的二进制文件,能更好的利用内存,在tensorflow中快速的复制,移动,读取,存储等。
把样本写入tfrecord示例
tfrecords_filename = './train.tfrecords'
writer = tf.python_io.TFRecordWriter(tfrecords_filename) # 创建.tfrecord文件,准备写入
for i in range(100):
img_raw = np.random.random_integers(0,255,size=(7,30)) # 创建7*30,取值在0-255之间随机数组
img_raw = img_raw.tostring()
example = tf.train.Example(features=tf.train.Features(
feature={
'label': tf.train.Feature(int64_list = tf.train.Int64List(value=[i])),
'img_raw':tf.train.Feature(bytes_list = tf.train.BytesList(value=[img_raw]))
}))
writer.write(example.SerializeToString())
writer.close()