【发布时间】：2017-08-19 19:43:13
【问题描述】：
我想使用批处理从文件夹中读取图像。但是解码后，当我使用tf.train.batch时可能会出现一些问题。这是代码。
def get_batch(image, label, batch_size, capacity):
image = tf.cast(image, tf.string)
label = tf.cast(label, tf.int32)
input_queue = tf.train.slice_input_producer([image, label])
label = input_queue[1]
image_contents = tf.read_file(input_queue[0])
image = tf.image.decode_jpeg(image_contents, channels=3)
image = tf.image.per_image_whitening(image)
image_batch, label_batch = tf.train.batch([image, label],
batch_size = batch_size,
num_threads = 8,
capacity = capacity)
label_batch = tf.reshape(label_batch, [batch_size])
image_batch = tf.cast(image_batch, tf.float32)
return image_batch, label_batch
错误说我没有定义一些张量形状。我不知道该怎么做。也许我没有以正确的方式使用解码。这是错误。
Traceback (most recent call last):
File "input_data.py", line 118, in <module>
image_batch, label_batch = get_batch(image_list, label_list, BATCH_SIZE, CAPACITY)
File "input_data.py", line 90, in get_batch
capacity = capacity)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/training/input.py", line 538, in batch
capacity=capacity, dtypes=types, shapes=shapes, shared_name=shared_name)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/data_flow_ops.py", line 453, in __init__
shapes = _as_shape_list(shapes, dtypes)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/data_flow_ops.py", line 71, in _as_shape_list
raise ValueError("All shapes must be fully defined: %s" % shapes)
ValueError: All shapes must be fully defined: [TensorShape([Dimension(None), Dimension(None), Dimension(3)]), TensorShape([])]
【问题讨论】：
标签： python tensorflow