PyTorch-StudioGAN
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
Generate images using advanced AI techniques with a library for Generative Adversarial Networks in Python.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeStudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
PyTorch-StudioGAN has 3.5k stars on GitHub. It has been forked 344 times. PyTorch-StudioGAN is written mainly in Python. It has been in active development since 2020. Its main topics are biggan, clean-fid, data-efficient-gan-training, deep-learning.
What is PyTorch-StudioGAN?
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
Is PyTorch-StudioGAN open source?
PyTorch-StudioGAN is an open-source project.
Is PyTorch-StudioGAN free?
Yes. PyTorch-StudioGAN is free and open source — you can use, modify and self-host it.
What language is PyTorch-StudioGAN written in?
PyTorch-StudioGAN is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/postech-cvlab-pytorch-studiogan.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.