tqch/ddpm-torch

Unofficial PyTorch Implementation of Denoising Diffusion Probabilistic Models (DDPM)

45
/ 100
Emerging

This tool helps researchers and artists create new, realistic images from scratch, or understand the underlying structure of image generation. You provide a dataset of existing images (like MNIST, CIFAR10, or CelebA), and it learns to generate similar, novel images. It's designed for anyone experimenting with generative AI for image synthesis or data augmentation.

231 stars. No commits in the last 6 months.

Use this if you need to generate high-quality, diverse synthetic images from a given dataset for creative projects, research, or expanding training data.

Not ideal if you are looking for an out-of-the-box solution to modify existing images or perform specific image-to-image translations, as its primary focus is on generating new images.

Image Generation Creative AI Synthetic Data Generative Art Machine Learning Research
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 19 / 25

How are scores calculated?

Stars

231

Forks

39

Language

Python

License

MIT

Last pushed

Aug 07, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/tqch/ddpm-torch"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.