I am trying to train an autoencoder for image inpainting where the input images are the corrupted ones, and the output images are the ground truth.
The dataset used is organized as:
/Dataset
/corrupted
img1.jpg
img2.jpg
.
.
/groundTruth
img1.jpg
img2.jpg
.
.
The number of images used is relatively large. How can I feed the data to the model using Keras image data generators? I checked flow_from_directory method but couldn't find a proper class_mode to use (each image in the 'corrupted' folder maps to the one with the same name in 'groundTruth' folder)