ozanciga/diffusion-for-beginners
denoising diffusion models, as simple as possible
This project helps image generators and digital artists efficiently produce high-quality images from text descriptions. It provides various denoising techniques (diffusion schedulers) that take a text prompt and an initial random noise image, then refine it into a clear, detailed final image. This tool is for researchers, engineers, and artists who work with generative AI models and need to experiment with different methods for faster or higher-quality image generation.
173 stars. No commits in the last 6 months.
Use this if you are a researcher or engineer looking to understand and implement different diffusion model sampling techniques with clear, simplified code.
Not ideal if you are an end-user simply looking to generate images without diving into the underlying algorithmic implementations.
Stars
173
Forks
10
Language
Python
License
MIT
Category
Last pushed
Nov 08, 2022
Commits (30d)
0
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