Get class info of Keras' ImageDataGenerator images besides parsing filename

I load hundres of images with ImageGenerator and its flow_from_dirctory-function from lets say two directories (two classes) in the validation directory (and test directory) with names "cats" and "dogs":

validation_generator = test_datagen.flow_from_directory(
        root_dir + '/validate',
        target_size=(img_x, img_y),
        batch_size=batch_size,
        color_mode='grayscale',
        class_mode='input',  # necessarry for autoencoder
        shuffle=False, # must be false otherwise filenames are wrong
        seed = seed)

After using some Keras model generation and fitting I want to debug sample images: I want to take images from the validation_generator and run the model on it. But I have to know in which directory the image was in the first place or with the class it was assigned to.

For plotting I use:

import matplotlib.pyplot as plt
n = 7
x,y = validation_generator.next()
for i in range(0,n):
    image_x = x[i,:,:,0]
    #print(validation_generator.class_indices) # always shows the same
    print(validation_generator.filenames[i]) # only OK if shuffle=false
    plt.imshow(image_x)
    plt.show()

I could only find the possibility to parse validation_generator.filenames[i] and take the directory of it. Is there any other, more elegant, way for that?

There does not seem to be an elegant way for an autoencoder so I post my quirky way:

import matplotlib.pyplot as plt
import os
n = 7
x,y = validation_generator.next()
for i in range(0,n):
    plt.figure(figsize=(2, 2))
    image_x = x[i,:,:,0]
    image_label = os.path.dirname(validation_generator.filenames[i]) # only OK if shuffle=false
    print(image_label)
    plt.imshow(image_x)
    plt.show()