Question

Tensorflow 1.3 Windows 7，Python 3.6

我遇到了这个错误：

#more testing tfrecords

我看一下类似的帖子：

OutOfRangeError (see above for traceback): RandomShuffleQueue '_5_shuffle_batch_1/random_shuffle_queue' is closed and has insufficient elements

OutOfRangeError (see above for traceback): FIFOQueue '_1_batch/fifo_queue' is closed and has insufficient elements (requested 32, current size 0)

OutOfRangeError: RandomShuffleQueue '_2_shuffle_batch/random_shuffle_queue' is closed and has insufficient elements (requested 1, current size 0)

尝试了列出的解决方案（除了注释一，我不明白）

这是我的代码：

import matplotlib.pyplot as plt
import numpy as np
from scipy.misc import imread, imresize
import os
import tensorflow as tf
import numpy
import cv2


#Gather image paths

DIR = r'C:\Users\Moondra\Desktop\DATA\IMAGE_2'

images = [os.path.join(DIR, image) for image in os.listdir(DIR)]

# len(images) is 41




def _bytes_feature(value):
    return tf.train.Feature(bytes_list=tf.train.BytesList(value=[value]))

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

tfrecords_filename = 'testing_2.tfrecords'

writer = tf.python_io.TFRecordWriter(tfrecords_filename)

for image in images:
    img = cv2.imread(image)
    img = cv2.resize(img, (300, 300), interpolation=cv2.INTER_CUBIC)
    img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    img = img.astype(np.float32)


    feature ={'train/image': _bytes_feature(tf.compat.as_bytes(img.tostring()))}



    example = tf.train.Example(features=tf.train.Features(feature=feature))
    writer.write(example.SerializeToString())

writer.close()

创建TFREcords

#absolute path
tfrecords_filename = r'C:\Users\Moondra\Desktop\Transfer Learning Tutorials\testing_2.tfrecords'


with tf.Session() as sess:
    feature = {'train/image': tf.FixedLenFeature([],tf.string)
               }

    filename_queue = tf.train.string_input_producer([tfrecords_filename],num_epochs=1)
    reader = tf.TFRecordReader()
    _, serialized_example = reader.read(filename_queue)

    features = tf.parse_single_example(serialized_example, features=feature)
    image = tf.decode_raw(features['train/image'], tf.float32)
    image = tf.reshape(image, [299, 299, 3])

    images = tf.train.shuffle_batch([image], batch_size=3, capacity=12, num_threads=1, min_after_dequeue=10)

    init_op = tf.group(tf.global_variables_initializer(), tf.local_variables_initializer())
    sess.run(init_op)
    coord = tf.train.Coordinator()
    threads = tf.train.start_queue_runners(coord=coord)

    for batch_index in range(2):
        img  = sess.run([images])
        print(img.shape)
        img = img.astype(np.uint8)
        for j in range(6):
            plt.subplot(2, 3, j+1)
            plt.imshow(img[j, ...])
            plt.show()
    coord.request_stop()
    coord.join(threads)
    sess.close()

将TFREcords加载到批次中

{{1}}

如果需要，我已将图像作为zip文件上传到我的github：

https://github.com/moondra2017/Testing_Cat_classifier_Tensorflow

标记为IMAGE_2.7z

谢谢。

Answer 1

我有类似的问题，它是由num_epochs = 1参数引起的（我增加到我的实际纪元数）。

请参阅此帖子：TensorFlow random_shuffle_queue is closed and has insufficient elements

Answer 2

弄清楚错误。

我保存的尺寸为[300,300]

我试图加载的尺寸是[299,299]

#Image = tf.reshape(image, [299, 299, 3])

Answer 3

我之前也有同样的问题，但是很多答案都不好，最终我发现答案是，如果要使用num_epochs，我们应该在[tf.Session（）作为sess：]之前生成队列。

OutOfRangeError（参见上面的回溯）：RandomShuffleQueue'_1_shuffle_batch / random_shuffle_queue'已关闭

创建TFREcords

将TFREcords加载到批次中

3 个答案: