TFrecords读、写图片文件

参考：https://blog.csdn.net/u014802590/article/details/68495238

参考：https://www.2cto.com/kf/201709/680575.html

1、读取图片文件并写为TFRecords文件

import tensorflow as tf
from PIL import Image
import os
file_path='C:/Users/1/Desktop/123/'
file_name=os.listdir(file_path)
writer=tf.python_io.TFRecordWriter('C:/Users/1/Desktop/fuck.tfrecords')
for name in file_name:
    img_path=file_path+name
    img=Image.open(img_path)
    img=img.resize((10,10))
    img_raw=img.tobytes()
    print(index)
    example=tf.train.Example(features=tf.train.Features(feature={'label':tf.train.Feature(int64_list=tf.train.Int64List(value=[index])),'img_raw':tf.train.Feature(bytes_list=tf.train.BytesList(value=[img_raw]))}))
    imgg=example.SerializeToString()
    writer.write(imgg)
writer.close()

2、读取图片文件对应的tfrecords文件：

import scipy.misc as misc
import matplotlib.pyplot as plt
filename=tf.train.match_filenames_once('C:/Users/1/Desktop/fuck.*frecords')
files=tf.train.string_input_producer(filename,shuffle=False)
reader=tf.TFRecordReader()
_,seri=reader.read(files)
feature=tf.parse_single_example(seri,features={'label':tf.FixedLenFeature([],tf.int64),'img_raw':tf.FixedLenFeature([],tf.string)})
img=feature['img_raw']
img=tf.decode_raw(img,tf.uint8)
img=tf.reshape(img,[256,256,3])     
img=tf.cast(img,tf.float32)
with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    sess.run(tf.local_variables_initializer())
    coord=tf.train.Coordinator()
    threads=tf.train.start_queue_runners(sess=sess,coord=coord)
    img=sess.run(img)
    plt.imshow(img)             
    plt.show()           #plot.show(）展示的是黑白图
    misc.imsave('C:/Users/1/Desktop/1111.jpg', img)     #使用scipy.misc.imsave来保存np.array数组格式的图片，保存好的图片为彩色图片
    coord.request_stop()
    coord.join(threads)