khanhvu207/vqgan
An unofficial PyTorch implementation of VQGAN
This project provides an implementation of VQGAN, a method for generating high-resolution images from a dataset of existing images. You input a collection of images, and it learns to create new, similar images based on the patterns it observes. This is useful for researchers and practitioners in generative AI who want to experiment with or apply advanced image synthesis techniques.
No commits in the last 6 months.
Use this if you are an AI researcher or machine learning engineer looking to train models to generate synthetic images.
Not ideal if you need an out-of-the-box solution for image generation without deep technical involvement, as it requires dataset preparation and command-line execution.
Stars
11
Forks
—
Language
HTML
License
—
Category
Last pushed
Oct 08, 2023
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/khanhvu207/vqgan"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
jxhe/vae-lagging-encoder
PyTorch implementation of "Lagging Inference Networks and Posterior Collapse in Variational...
chaitanya100100/VAE-for-Image-Generation
Implemented Variational Autoencoder generative model in Keras for image generation and its...
taldatech/soft-intro-vae-pytorch
[CVPR 2021 Oral] Official PyTorch implementation of Soft-IntroVAE from the paper "Soft-IntroVAE:...
lavinal712/AutoencoderKL
Train Your VAE: A VAE Training and Finetuning Script for SD/FLUX
Rayhane-mamah/Efficient-VDVAE
Official Pytorch and JAX implementation of "Efficient-VDVAE: Less is more"