|Train Your GAN With 1/10th of the Data! NVIDIA ADA Explained
With this new training method developed by NVIDIA, you can train a powerful generative model with one-tenth of the images! Making possible many applications that do not have access to so many images!
|GitHub – NVlabs/stylegan2-ada: StyleGAN2 with adaptive discriminator augmentation (ADA) – Official TensorFlow implementation
For optimal results, the target image should be cropped and aligned similar to the original FFHQ dataset. The above command saves the projection target out/target.png, result out/proj.png, latent vector out/dlatents.npz, and progression video out/proj.mp4.You can render the resulting latent vector by specifying –dlatents for python generate.py: