从凯拉斯的发电机那里得到X戥u测试,Y戥u测试?

更新(22/06/2018):阅读OP提供的答案以简洁有效的解决方案。读我的来了解发生了什么。

在python中,可以使用以下命令获取所有生成器数据:

data = [x for x in generator]

但是, ImageDataGenerators 不终止,因此上述方法将不起作用。但在这种情况下,我们可以使用相同的方法进行一些修改:

data = []     # store all the generated data batches
labels = []   # store all the generated label batches
max_iter = 100  # maximum number of iterations, in each iteration one batch is generated; the proper value depends on batch size and size of whole data
i = 0
for d, l in validation_generator:
    data.append(d)
    labels.append(l)
    i += 1
    if i == max_iter:
        break

现在我们有两个张量批列表。我们需要重塑它们,使其成为两个张量,一个用于数据(即 X 一个用于标签(即 y ):

data = np.array(data)
data = np.reshape(data, (data.shape[0]*data.shape[1],) + data.shape[2:])

labels = np.array(labels)
labels = np.reshape(labels, (labels.shape[0]*labels.shape[1],) + labels.shape[2:])

Python2.7和Python3.*解决方案:

from platform import python_version_tuple

if python_version_tuple()[0] == '3':
    xrange = range
    izip = zip
    imap = map
else:
    from itertools import izip, imap

import numpy as np

# ..
# other code as in question
# ..

x, y = izip(*(validation_seq[i] for i in xrange(len(validation_seq))))
x_val, y_val = np.vstack(x), np.vstack(y)

或支持 class_mode='binary' 然后:

from keras.utils import to_categorical

x_val = np.vstack(x)
y_val = np.vstack(imap(to_categorical, y))[:,0] if class_mode == 'binary' else y

完整的可运行代码: https://gist.github.com/AlecTaylor/7f6cc03ed6c3dd84548a039e2e0fd006