import tensorflow as tf
import cv2

filename = "train.tfrecords"
filename_queue = tf.train.string_input_producer([filename])

reader = tf.TFRecordReader()
_, serialized_example = reader.read(filename_queue)   #返回文件名和文件
features = tf.parse_single_example(serialized_example,
    features={
        'label': tf.FixedLenFeature([], tf.int64),
        'image' : tf.FixedLenFeature([], tf.string),
    })

img = tf.decode_raw(features['image'], tf.uint8)
img = tf.reshape(img, [300, 300,3])
#notice shape應(yīng)該保持一致

img = tf.cast(img, tf.float32) * (1. / 128) - 0.5
label = tf.cast(features['label'], tf.int32)

///////////////////////////////////////////
函數(shù)封裝
///////////////////////////////////////////
import tensorflow as tf
import cv2
def read_decode(filename):
    #filename = "train.tfrecords"
    filename_queue = tf.train.string_input_producer([filename])

    reader = tf.TFRecordReader()
    _, serialized_example = reader.read(filename_queue)   #返回文件名和文件
    features = tf.parse_single_example(serialized_example,
        features={
            'label': tf.FixedLenFeature([], tf.int64),
            'image' : tf.FixedLenFeature([], tf.string),
        })

    img = tf.decode_raw(features['image'], tf.uint8)
    img = tf.reshape(img, [500, 500,3])

    img = tf.cast(img, tf.float32) * (1. / 128) - 0.5
    label = tf.cast(features['label'], tf.int32)
    return img,label
//////////////////////////////////////////////////
使用案例
//////////////////////////////////////////////////
import tensorflow as tf
import cv2
import aaa

filename = "train.tfrecords"
img,label = aaa.read_decode(filename)

img_batch,label_batch = tf.train.shuffle_batch([img,label],batch_size=1,
                                               capacity=10,
                                               min_after_dequeue=1)

init = tf.global_variables_initializer()
sess = tf.Session()
sess.run(init)
threads = tf.train.start_queue_runners(sess=sess)
for _ in range(10):
    val = sess.run(img_batch)
    label = sess.run(label_batch)
    val.resize((500,500,3))
    cv2.imshow("cool",val)
    print(label)
////////////////////////////////////////////////////////////

1