Royalvice/DocDiff

ACM Multimedia 2023: DocDiff: Document Enhancement via Residual Diffusion Models. Also contains 1597 red seals in Chinese scenes, along with their corresponding binary masks.

41
/ 100
Emerging

This helps professionals working with scanned or digital documents improve their quality. You input a document image that might be blurry, noisy, have watermarks, or old and faded, and it outputs a clearer, enhanced version, often with elements like watermarks or seals removed. It's designed for anyone managing or processing large volumes of documents, such as archivists, legal professionals, or data entry specialists.

338 stars. No commits in the last 6 months.

Use this if you need to quickly clean up and enhance document images for better readability, archiving, or further processing.

Not ideal if you're primarily looking to enhance natural scene photographs or require high-diversity image generation for creative tasks, as it's optimized for document characteristics.

document-management digital-archiving data-entry image-restoration legal-document-processing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 15 / 25

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Stars

338

Forks

32

Language

Python

License

MIT

Last pushed

Aug 22, 2024

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/Royalvice/DocDiff"

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