StyleGAN 2 Truncation

StyleGAN 2 trained on images of landscapes, with varying levels of truncation.
At the beginning, all images have been fully truncated, showing the "average" landscape of all generated landscapes. When ψ = 1, no truncation is applied, showing full diversity across the distribution of images. When ψ = 1.5, generated images can reach beyond its own distribution, lowering image quality significantly, but increasing diversity beyond what is even in the real distribution.
Code: github.com/man...
Research Paper: Analyzing and Improving the Image Quality of StyleGAN
StyleGAN, Tensorflow 2.0, Truncation, Landscapes

[@Gadreth]

Looking foward for more tutorials of how to use this software
I really want to use it

[@Zarkaltair]

It was really cool, please explain how to use a pre-trained network?

[@ArtHiteca]

Hello. Thank you very much for your videos and implementations of StyleGAN 2 Tensorflow 2 on github. Could you tell us more about what computer equipment you use for training? How long did it take you? How do you collect data for training?

[@Matchue624]

Hey, thanks for the support! I'm using a single computer with a GTX 1060. To train a full StyleGAN 2 model for 256x256 images it takes about 3-5 days, but longer if you have more data and want to train longer. For my landscapes dataset I've been using a scraper to scrape them off the internet.

[@ArtHiteca]

@@Matchue624 Thank you very much for your response. Please continue to make video tutorials and demonstrations, it is very inspiring)

[@biaohe5141]

Great, just wondering is it possible to run on a machine without GPU?
If I just want to inference.

[@ArtHiteca]

Tutorial, please)