konpatp/diffae
Official implementation of Diffusion Autoencoders
This project helps graphic designers, artists, and researchers working with digital images to create or modify realistic images. You can input existing images and then generate new variations, manipulate specific features like hair color or expressions, or seamlessly blend images. It's designed for anyone needing to generate diverse image content or alter existing images with fine-grained control.
959 stars. No commits in the last 6 months.
Use this if you need to generate high-quality, realistic images or precisely control the modification of specific features within images, such as facial characteristics or scene elements.
Not ideal if you're looking for a simple, one-click photo editor for casual use or if your primary need is for non-image data generation.
Stars
959
Forks
158
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Sep 12, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/konpatp/diffae"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
huggingface/diffusers
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.
bghira/SimpleTuner
A general fine-tuning kit geared toward image/video/audio diffusion models.
mcmonkeyprojects/SwarmUI
SwarmUI (formerly StableSwarmUI), A Modular Stable Diffusion Web-User-Interface, with an...
nateraw/stable-diffusion-videos
Create 🔥 videos with Stable Diffusion by exploring the latent space and morphing between text prompts
TheDesignFounder/DreamLayer
Benchmark diffusion models faster. Automate evals, seeds, and metrics for reproducible results.