我的代码是从 tfrecord 文件中读取图像

import tensorflow as tf import numpy as np import matplotlib.pyplot as plt data_path='christmas.tfrecords'with tf.Session() as sess:    feature={'image':tf.FixedLenFeature([],tf.string),'label':tf.FixedLenFeature([],tf.int64)}    # 创建文件名列表并传递给队列    filename_queue = tf.train.string_input_producer([data_path], num_epochs=1)    # 定义读取器并读取下一条记录    reader = tf.TFRecordReader()    _, serialized_example = reader.read(filename_queue)    # 解码读取器读取的记录    features = tf.parse_single_example(serialized_example, features=feature)    # 将图像数据从字符串转换回数字    image = tf.decode_raw(features['image'], tf.float32)    # 将标签数据转换为 int32    label = tf.cast(features['label'], tf.int32)    # 将图像数据重塑为原始形状    image = tf.reshape(image, [224, 224, 1])    # 在此处进行任何预处理...    # 通过随机洗牌张量创建批次    images, labels = tf.train.shuffle_batch([image, label], batch_size=10, capacity=30, num_threads=1, min_after_dequeue=10)    init_op = tf.group(tf.global_variables_initializer(), tf.local_variables_initializer())    sess.run(init_op)    # 创建协调器并运行所有 QueueRunner 对象    coord = tf.train.Coordinator()    threads = tf.train.start_queue_runners(coord=coord)    for batch_index in range(5):        img, lbl = sess.run([images, labels])        img = img.astype(np.uint8)        for j in range(6):            plt.subplot(2, 3, j+1)            plt.imshow(img[j, ...])            plt.title('猫' if lbl[j]==0 else '狗')        plt.show()    # 停止线程    coord.request_stop()    # 等待线程停止    coord.join(threads)    sess.close()

错误信息

 Traceback (most recent call last):  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1323, in _do_call    return fn(*args)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1302, in _run_fn    status, run_metadata)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/framework/errors_impl.py", line 473, in __exit__    c_api.TF_GetCode(self.status.status))tensorflow.python.framework.errors_impl.OutOfRangeError: RandomShuffleQueue '_1_shuffle_batch/random_shuffle_queue' 已关闭且元素不足（请求 10，当前大小 0）     [[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]在处理上述异常时，发生了另一个异常：Traceback (most recent call last):  File "read_tfrecords.py", line 35, in <module>    img, lbl = sess.run([images, labels])  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 889, in run    run_metadata_ptr)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1120, in _run    feed_dict_tensor, options, run_metadata)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1317, in _do_run    options, run_metadata)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/client/session.py", line 1336, in _do_call    raise type(e)(node_def, op, message)tensorflow.python.framework.errors_impl.OutOfRangeError: RandomShuffleQueue '_1_shuffle_batch/random_shuffle_queue' 已关闭且元素不足（请求 10，当前大小 0）     [[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]由操作 'shuffle_batch' 引起，定义于：  File "read_tfrecords.py", line 27, in <module>    images, labels = tf.train.shuffle_batch([image, label], batch_size=10, capacity=30, num_threads=1, min_after_dequeue=10)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/training/input.py", line 1225, in shuffle_batch    name=name)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/training/input.py", line 796, in _shuffle_batch    dequeued = queue.dequeue_many(batch_size, name=name)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/ops/data_flow_ops.py", line 464, in dequeue_many    self._queue_ref, n=n, component_types=self._dtypes, name=name)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 2418, in _queue_dequeue_many_v2    component_types=component_types, timeout_ms=timeout_ms, name=name)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper    op_def=op_def)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 2956, in create_op    op_def=op_def)  File "/home/robinreni/Documents/pythonprojects/cnn/lib/python3.6/site-packages/tensorflow/python/framework/ops.py", line 1470, in __init__    self._traceback = self._graph._extract_stack()  # pylint: disable=protected-accessOutOfRangeError（参见上面的回溯）：RandomShuffleQueue '_1_shuffle_batch/random_shuffle_queue' 已关闭且元素不足（请求 10，当前大小 0）     [[Node: shuffle_batch = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](shuffle_batch/random_shuffle_queue, shuffle_batch/n)]]

我将所有图像和标签转换为 tfrecord 文件，并在训练过程中需要将文件转换为原始图像和标签。我尝试从 tfrecords 中读取图像，但出现了 OutOfRange 错误。请问如何修复这个错误？

回答：