非常感谢您阅读我的问题
我的数据集大约是9779张图片（.dcm）。有两个标签，一个是1，有5000个训练图像，另一个是0，有4779个图像。
我使用TFrecords来合并和构建数据集。然后将其提供给CNN模型。
writer = tf.python_io.TFRecordWriter("train.tfrecords")
for idx, img_path in enumerate(all_images):#all_images is a list containing all path of all images
img = dm.read_file(img_path)
pixel_bytes = img.PixelData
img_raw = pixel_bytes
if idx < len_all_cancer_images:
example = tf.train.Example(features=tf.train.Features(feature={
"label": tf.train.Feature(int64_list = tf.train.Int64List(value = [1])),
'img_raw': tf.train.Feature(bytes_list = tf.train.BytesList(value = [img_raw]))}))
writer.write(example.SerializeToString())
else:
example = tf.train.Example(features=tf.train.Features(feature={
"label": tf.train.Feature(int64_list = tf.train.Int64List(value=[0])),
'img_raw': tf.train.Feature(bytes_list = tf.train.BytesList(value = [img_raw]))}))
writer.write(example.SerializeToString())
writer.close()
然后我用TFRecordReader读取它
filename = '/Users/wuzhenglin/Python_nice/SAL_LUNG/train.tfrecords'
filename_queue = tf.train.string_input_producer([filename])
reader = tf.TFRecordReader()
_, serialized_example = reader.read(filename_queue)
features = tf.parse_single_example(serialized_example,
features={
'label': tf.FixedLenFeature([], tf.int64),
'img_raw' : tf.FixedLenFeature([], tf.string),
})
print features['img_raw']
print features['label']
img = tf.decode_raw(features['img_raw'], tf.uint8)
img = tf.reshape(img, [512, 512, 1])
img = tf.cast(img, tf.float32) * (1. / 255)
label = tf.cast(features['label'], tf.int32)
然后当我想要阅读我的数据时
img_batch, label_batch = tf.train.shuffle_batch([img, label],
batch_size = 200, capacity = 9779,
min_after_dequeue = 2000)
init = tf.global_variables_initializer()
with tf.Session() as sess:
sess.run(init)
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(coord = coord)
for i in xrange(1):
a, b = sess.run([img_batch, label_batch])
a_ = a[0]
b_ = b[0]
img_1 = tf.reshape(a_[0, :, :, :], [512, 512])
print img_1.shape
print b_.shape
print b_
print '********************'
plt.imshow(sess.run(img_1), cmap='gray')
我想选择一些数据并打印出来，但错误......
首先：
InvalidArgumentError (see above for traceback): Input to reshape is a tensor with 524288 values, but the requested shape has 262144
[[Node: Reshape = Reshape[T=DT_UINT8, Tshape=DT_INT32, _device="/job:localhost/replica:0/task:0/cpu:0"](DecodeRaw, Reshape/shape)]]
第二
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/spyder/utils/site/sitecustomize.py", line 880, in runfile
execfile(filename, namespace)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/spyder/utils/site/sitecustomize.py", line 94, in execfile
builtins.execfile(filename, *where)
File "/Users/wuzhenglin/Python_nice/SAL_LUNG/test.py", line 96, in <module>
read_and_decode()
File "/Users/wuzhenglin/Python_nice/SAL_LUNG/test.py", line 82, in read_and_decode
a, b = sess.run([img_batch, label_batch])
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 767, in run
run_metadata_ptr)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 965, in _run
feed_dict_string, options, run_metadata)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1015, in _do_run
target_list, options, run_metadata)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/client/session.py", line 1035, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.OutOfRangeError: RandomShuffleQueue '_7_shuffle_batch_1/random_shuffle_queue' is closed and has insufficient elements (requested 200, current size 0)
[[Node: shuffle_batch_1 = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](shuffle_batch_1/random_shuffle_queue, shuffle_batch_1/n)]]
Caused by op u'shuffle_batch_1', defined at:
File "<stdin>", line 1, in <module>
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/spyder/utils/site/sitecustomize.py", line 880, in runfile
execfile(filename, namespace)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/spyder/utils/site/sitecustomize.py", line 94, in execfile
builtins.execfile(filename, *where)
File "/Users/wuzhenglin/Python_nice/SAL_LUNG/test.py", line 96, in <module>
read_and_decode()
File "/Users/wuzhenglin/Python_nice/SAL_LUNG/test.py", line 71, in read_and_decode
min_after_dequeue = 2000)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 1165, in shuffle_batch
name=name)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 739, in _shuffle_batch
dequeued = queue.dequeue_many(batch_size, name=name)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/data_flow_ops.py", line 458, in dequeue_many
self._queue_ref, n=n, component_types=self._dtypes, name=name)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/ops/gen_data_flow_ops.py", line 1310, in _queue_dequeue_many_v2
timeout_ms=timeout_ms, name=name)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 763, in apply_op
op_def=op_def)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 2327, in create_op
original_op=self._default_original_op, op_def=op_def)
File "/Users/wuzhenglin/anaconda/lib/python2.7/site-packages/tensorflow/python/framework/ops.py", line 1226, in __init__
self._traceback = _extract_stack()
OutOfRangeError (see above for traceback): RandomShuffleQueue '_7_shuffle_batch_1/random_shuffle_queue' is closed and has insufficient elements (requested 200, current size 0)
[[Node: shuffle_batch_1 = QueueDequeueManyV2[component_types=[DT_FLOAT, DT_INT32], timeout_ms=-1, _device="/job:localhost/replica:0/task:0/cpu:0"](shuffle_batch_1/random_shuffle_queue, shuffle_batch_1/n)]]
一些有用的信息，image.dcm是512 * 512，RGB
真的非常感谢你： - ）
答案 0 :(得分：0)
1个错误InvalidArgumentError (see above for traceback): Input to reshape is a tensor with 524288 values, but the requested shape has 262144表示重塑操作的输入大小为[512,512,2]
# this line causes the error,, you have to confirm that your image size
img = tf.reshape(img, [512, 512, 1])
# should be
img = tf.reshape(img, [512, 512, 2])
# another line with mkstake; here you dont need to use tensorflow reshape; you can use numpy reshape since a[0] is python object
# img_1 = tf.reshape(a_[0, :, :, :], [512, 512])
img_1 = np.reshape(a_[0, :, :, :], [512, 512, 2])
由于第一个错误，第二个错误出现。因此，请确保您没有使用输入图像大小的任何错误。