import tensorflow as tf
from tensorflow.examples.tutorials.mnist import input_data
import numpy as np

def _int64_feature(value):
    return tf.train.Feature(int64_list = tf.train.Int64List(value=[value]))

def _bytes_feature(value):
    return tf.train.Feature(bytes_list = tf.train.BytesList(value=[value]))
if __name__ == '__main__':
    mnist = input_data.read_data_sets("./mnist/MNIST_data", dtype=tf.uint8, one_hot=True)
    images = mnist.train.images
    labels = mnist.train.labels
    pixels = images.shape[1]
    num_examples = mnist.train.num_examples
    filename = "output.tfrecords"
    writer = tf.python_io.TFRecordWriter(filename)
    for index in range(num_examples):
        image_raw = images[index].tostring()
        example = tf.train.Example(features=tf.train.Features(feature={
            'pixels': _int64_feature(pixels),
            'label': _int64_feature(np.argmax(labels[index])),
            'image_raw': _bytes_feature(image_raw)
        }))
        writer.write(example.SerializeToString())
    writer.close()


