deepmancer/diffusion-gan-vae-pytorch
A PyTorch implementation of various deep generative models, including Diffusion (DDPM), GAN, cGAN, and VAE.
This is a collection of code examples for creating new images based on existing ones. It allows you to take a dataset of images and generate brand new, similar-looking images, potentially controlling their characteristics. This is useful for researchers or students exploring advanced image generation techniques.
No commits in the last 6 months.
Use this if you are a researcher or student in machine learning and want to understand or experiment with different deep learning models that generate new images from scratch.
Not ideal if you need a user-friendly application to generate images without any coding or deep learning knowledge.
Stars
13
Forks
2
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Dec 09, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/deepmancer/diffusion-gan-vae-pytorch"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
quantgirluk/aleatory
📦 Python library for Stochastic Processes Simulation and Visualisation
blei-lab/treeffuser
Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression...
TuftsBCB/RegDiffusion
Diffusion model for gene regulatory network inference.
yuanchenyang/smalldiffusion
Simple and readable code for training and sampling from diffusion models
chairc/Integrated-Design-Diffusion-Model
IDDM (Industrial, landscape, animate, latent diffusion), support LDM, DDPM, DDIM, PLMS, webui...