我无法从 keras 运行简单的数据生成器代码

import os
import keras as K
from keras.preprocessing.image import ImageDataGenerator

def save_images_from_generator(maximal_nb_of_images, generator):
    nb_of_images_processed = 0
    for x, _ in generator:
        nb_of_images += x.shape[0]
        if nb_of_images <= maximal_nb_of_images:
            for image_nb in range(x.shape[0]):
                your_custom_save(x[image_nb]) # your custom function for saving images
        else:
            break

Gen=ImageDataGenerator(featurewise_center=True,
    samplewise_center=False,
    featurewise_std_normalization=False,
    samplewise_std_normalization=False,
    zca_whitening=True,
    rotation_range=90,
    width_shift_range=0.2,
    height_shift_range=0.1,
    shear_range=0.5,
    zoom_range=0.2,
    channel_shift_range=0.1,
    fill_mode='nearest',
    cval=0.,
    horizontal_flip=True,
    vertical_flip=True,
    rescale=None,
    preprocessing_function=None)


if __name__ == '__main__':
    save_images_from_generator(40,Gen.flow_from_directory('C:\\Users\\aanilil\\PycharmProjects\\untitled\\images_input', target_size=(150, 150),class_mode=None,save_prefix='augm',save_to_dir='C:\\Users\\aanilil\\PycharmProjects\\untitled\\im_output\\'))

Output

Using TensorFlow backend.
Found 0 images belonging to 0 classes.
Found 0 images belonging to 0 classes.
Found 0 images belonging to 0 classes.
Found 0 images belonging to 0 classes.
Found 0 images belonging to 0 classes.
Traceback (most recent call last):
  File "C:\Program Files (x86)\JetBrains\PyCharm Community Edition 2016.3.2\helpers\pydev\pydevd.py", line 1578, in <module>
    globals = debugger.run(setup['file'], None, None, is_module)
  File "C:\Program Files (x86)\JetBrains\PyCharm Community Edition 2016.3.2\helpers\pydev\pydevd.py", line 1015, in run
    pydev_imports.execfile(file, globals, locals)  # execute the script
  File "C:\Program Files (x86)\JetBrains\PyCharm Community Edition 2016.3.2\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile
    exec(compile(contents+"\n", file, 'exec'), glob, loc)
  File "C:/Users/aanilil/PycharmProjects/untitled/generate_data_from_folder.py", line 35, in <module>
    save_images_from_generator(40,Gen.flow_from_directory('C:\\Users\\aanilil\\PycharmProjects\\untitled\\images_input', target_size=(150, 150),class_mode=None,save_prefix='augm',save_to_dir='C:\\Users\\aanilil\\PycharmProjects\\untitled\\im_output\\'))
  File "C:/Users/aanilil/PycharmProjects/untitled/generate_data_from_folder.py", line 7, in save_images_from_generator
    for x, _ in generator:
  File "C:\ProgramData\Anaconda3\envs\tensorflow\lib\site-packages\keras\preprocessing\image.py", line 727, in __next__
    return self.next(*args, **kwargs)
  File "C:\ProgramData\Anaconda3\envs\tensorflow\lib\site-packages\keras\preprocessing\image.py", line 950, in next
    index_array, current_index, current_batch_size = next(self.index_generator)
  File "C:\ProgramData\Anaconda3\envs\tensorflow\lib\site-packages\keras\preprocessing\image.py", line 710, in _flow_index
    current_index = (self.batch_index * batch_size) % n
ZeroDivisionError: integer division or modulo by zero

当我做一个 os. listdir 我得到这样的输出

os.listdir('C:\\Users\\aanilil\\PycharmProjects\\untitled\\images_input') 
['download (1).png', 'download.jpg', 'download.png', 'images.jpg']

因此输入文件夹中有图像，但它仍然会抛出与找不到文件相关的错误

Keras 假设图像存储在文件夹树中，每个类都有一个单独的子文件夹，如下所示：

• some/path/
  • class1/
    • 图片1.jpg
    • 图片2.jpg
  • class2/
    • 图片3.jpg
    • etc
  • etc

因此，在您的情况下，解决方案是在 'C:\Users\aanilil\PycharmProjects\untitled\images_input' 下创建一个子文件夹并将图像移动到那里。当然，如果您的目标是，您将需要多个类子文件夹来训练分类器。