title: load images for Auto-enncoder with keras ImageDataGenerator questions
body: <p>dear community.
  I have a dataset folder split into X and Y that are meant to be fed to an Auto-encoder
  The X is the modified version of the Y, which means that the model should learn to turn X into Y
  I loaded X and Y with the following code</p>
  <pre><code>X = []
  for i in tqdm(glob.glob(&quot;data/X/*.jpg&quot;)):
      im = cv2.imread(i)
      im = img_to_array(im)
      X.append(im)
      #X.append(cv2.flip(im, 0))
      #X.append(cv2.flip(im, 1))
      #X.append(cv2.flip(im, -1))
      
  print(len(X))
  X = np.array(X, dtype=&quot;float32&quot;)/255
  Y = []
  for i in tqdm(glob.glob(&quot;data/Y/*.jpg&quot;)):
      im = cv2.imread(i)
      im = img_to_array(im)
      Y.append(im)
      #Y.append(cv2.flip(im, 0))
      #Y.append(cv2.flip(im, 1))
      #Y.append(cv2.flip(im, -1))
  print(len(Y))
  Y = np.array(Y, dtype=&quot;float32&quot;)/255
  </code></pre>
  <p>then I wanted to make some augmentations because I did not have a lot of images so I used  Keras ImageDataGenerator</p>
  <pre><code>from tensorflow.keras.preprocessing.image import ImageDataGenerator
  
  trainGen = ImageDataGenerator(
      vertical_flip=True
  )
  train = trainGen.flow(X, Y, batch_size=8)
  </code></pre>
  <p>my wonders are if the augmentations are also applied top the Y not only the X, if no how to do so please?</p>