This is an implementation of an autoencoder to downscale images and generate mipmaps.
The architecture of the autoencoder can be seen in this diagram:
The saved weights are in weights/weights_perceptual_ssim_nadam_500_0.0002_0.9_0.999_1587746299.670421
Run the test file image_downscaling/conv_autoencoder_test.py after setting the right folder where you have images.
Download the train dataset in the root folder of the repository from here: https://drive.google.com/file/d/1bZMm92vCFVYYxJW0G06CtSX0IXhlJxEg/view?usp=sharing
Run image_downscaling/conv_autoencoder_main.py after tweaking the parameters as you wish.