lmxyy/sige
[NeurIPS 2022, T-PAMI 2023] Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models
This tool helps creative professionals or researchers who need to quickly make small, localized changes to images generated by AI models like Stable Diffusion or GauGAN. By only processing the edited parts, it drastically speeds up the image generation process, allowing you to iterate on visual ideas much faster. You provide an original image and your desired edits, and it quickly outputs the updated, high-quality image.
268 stars. No commits in the last 6 months. Available on PyPI.
Use this if you are working with AI-generated images and frequently need to make minor local adjustments, such as inpainting or small content changes, and want to reduce the time it takes to see the results.
Not ideal if you are generating entirely new images from scratch or performing extensive, global transformations that affect the entire image, as the efficiency gains are minimal in those scenarios.
Stars
268
Forks
13
Language
Python
License
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Category
Last pushed
Mar 18, 2024
Commits (30d)
0
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