vqgan-clip
Image generation tool
A toolkit for generating and editing images based on learned semantic representations of visual features.
350 stars
9 watching
40 forks
Language: Jupyter Notebook
last commit: over 2 years ago Related projects:
| Repository | Description | Stars |
|---|---|---|
 mingyuliutw/cogan | An implementation of a Generative Adversarial Network (GAN) designed to generate diverse types of images from single input images | 285 |
 pixray/pixray | An image generation system built around CLIP and GAN techniques. | 1,027 |
 google-research/xmcgan_image_generation | This implementation enables text-to-image generation by leveraging cross-modal contrastive learning. | 98 |
 eps696/aphantasia | A text-to-image tool using CLIP and FFT/DWT parameters to generate detailed images from user-provided text prompts. | 776 |
 casualganpapers/make-a-scene | PyTorch implementation of a scene-based text-to-image generation system with human priors using Generative Adversarial Networks and semantic segmentation | 334 |
 ypxie/hdgan | A PyTorch implementation of an adversarial network for generating high-definition images from text descriptions. | 150 |
 soumith/dcgan.torch | A PyTorch implementation of a deep generative model that can be used to generate images from a dataset. | 1,458 |
 noelyahan/mergi | A Go library and command-line tool for manipulating images | 233 |
 wuhuikai/gp-gan | A software framework for generating high-resolution image blends by combining source and destination images using a deep generative model. | 461 |
 junyanz/bicyclegan | A PyTorch implementation of an image-to-image translation model that generates new images from paired training data. | 1,486 |
 eladhoffer/captiongen | A PyTorch-based tool for generating captions from images | 128 |
 reedscot/icml2016 | Generates synthetic images from text descriptions using a Generative Adversarial Network (GAN) | 913 |
 paulkinlan/simple-image | Provides tools and functionality to embed images in a rich text editor | 11 |
 pbaylies/stylegan2 | Implementation of a generative adversarial network for generating images with conditional variations. | 315 |
 mattya/chainer-dcgan | Generates images using a Deep Convolutional Generative Adversarial Network (DCGAN) algorithm | 935 |