Read_tfrecord.py

Read_tfrecord.py

 

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import os
# import modulus
import tensorflow as tf
import numpy as np
import scipy.misc

tf_file = './train.tfrecords'

def extract_tfrecords_features(tfrecords_file):
    """Extract features in a tfrecords file for parsing a series of tfrecords files."""
    tfrecords_iterator = tf.python_io.tf_record_iterator(tfrecords_file)

    for record in tfrecords_iterator:
        example = tf.train.Example()
        example.ParseFromString(record)
        features = example.features.feature

        image = features['image'].bytes_list.value
        #print(image)

        image1 = tf.decode_raw(features['image'].bytes_list.value[0], tf.uint8)
        with tf.Session() as sess:
            image1 = tf.convert_to_tensor(image1.eval())
            print(image1)
            print(sess.run(image1))

            arr = sess.run(image1).reshape(1920,1080,3)
            arr0 = arr[:,:,0]
            arr1 = arr[:,:,1]
            arr2 = arr[:,:,2]
            print(arr)
            print(arr0)
            print(arr1)
            print(arr2)
            scipy.misc.imsave('0.png',arr0)
            scipy.misc.imsave('1.png',arr1)
            scipy.misc.imsave('2.png',arr2)
            #print(sess.run(image1).reshape(3,1920,1080))

        break

        x1 = features['node_id'].int64_list.value
        #print(x1)

if __name__ == '__main__':
    print('start...')
    extract_tfrecords_features(tf_file)