shepnerd/inpainting_gmcnn
Image Inpainting via Generative Multi-column Convolutional Neural Networks, NeurIPS2018
This project helps graphic designers, photographers, or image editors seamlessly remove unwanted objects or fill in missing areas in images. You provide an image with a masked or damaged section, and it intelligently reconstructs the missing pixels, outputting a complete, natural-looking image. It's designed for anyone working with visual media who needs to repair or alter images.
436 stars. No commits in the last 6 months.
Use this if you need to realistically "heal" or complete sections of an image, such as removing a photobomber from a landscape or restoring an old, damaged photo.
Not ideal if you need to fill in very large, complex missing areas or if you're working with datasets containing thousands of highly diverse categories, as performance may be unstable.
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436
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Language
Python
License
MIT
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Last pushed
Mar 01, 2022
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