UCSB-NLP-Chang/CoPaint
Implementation of paper 'Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models'
This tool helps you flawlessly fill in missing or damaged parts of an image, making it look complete and natural. You provide a partially visible image and a mask indicating the missing areas, and it intelligently generates the missing content, ensuring it blends seamlessly with the existing parts. This is ideal for graphic designers, photo retouchers, or anyone needing to restore or complete images with high visual quality.
No commits in the last 6 months.
Use this if you need to precisely fill in holes or remove unwanted objects from images, ensuring the added content matches the surrounding context without visible seams or inconsistencies.
Not ideal if you're looking for a simple, quick fix for minor imperfections or require real-time image processing for live feeds.
Stars
77
Forks
8
Language
Python
License
—
Category
Last pushed
Apr 03, 2024
Commits (30d)
0
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