keras ImageDataGenerator 用法

datagen = ImageDataGenerator(
    rotation_range=3,
#     featurewise_std_normalization=True,
    fill_mode='nearest',
    width_shift_range=0.2,
    height_shift_range=0.2,
    horizontal_flip=True
)

train_generator = datagen.flow_from_directory(
        path+'/train',
        target_size=(224, 224),
        batch_size=batch_size,)

I have a custom generator for my multi output model like:

a = np.arange(8).reshape(2, 4)
# print(a)

print(train_generator.filenames)

def generate():
    while 1:
        x,y = train_generator.next()
        yield [x] ,[a,y]