cybertimon/rapidraw

A beautiful, non-destructive, and GPU-accelerated RAW image editor built with performance in mind.

View on GitHub ↗Jump to charts ↓

Summary Information

Updated 59 minutes ago
Added to GitGenius on September 6th, 2026
Created on June 13th, 2025
Open Issues & Pull Requests: 408 (+0)
GitHub issues: Enabled
Number of forks: 538
Total Stargazers: 9,900 (+3)
Total Subscribers: 68 (+0)

Repository Insights (GitGenius)

Most active contributors

Sign in to see contributor activity.

Related repositories by overlapping contributors

No overlapping-contributor repos identified yet.

Charts & Analytics

Fetching additional details & charts...

Issue Activity (beta)

Issue API getrepoissuespagesummary failed: 429 Rate limit exceeded. Please try again later.

Detailed Description

RapidRAW is a GPU-accelerated RAW image editor that provides non-destructive editing with a focus on performance and visual simplicity.

The tool addresses the need for a lightweight, fast alternative to heavyweight RAW editors by leveraging GPU acceleration through WGSL shaders and Rust for performance-critical operations. It delivers editing capabilities in a package under 20MB while maintaining a clean, beautiful interface. The non-destructive workflow means adjustments are applied as layers that can be modified or removed without altering the original image data.

RapidRAW suits photographers who prioritize speed and workflow simplicity over the exhaustive feature sets of mature alternatives. It runs on Windows, macOS, Linux, and Android, making it accessible across platforms. The README acknowledges that the tool is still in active development and not yet as polished as Darktable, RawTherapee, or Adobe Lightroom, with the current focus on building a fast, enjoyable core editing experience rather than feature parity. Photographers should expect occasional bugs but will benefit from a streamlined interface and responsive performance.

Development activity shows consistent, focused iteration on core editing features. Recent work includes perspective correction with guided assistance, edge-aware filtering for AI masks, improved sharpening, a retouch tool for skin smoothing, and refinements to the crop panel and transform workflow. The project demonstrates active maintenance of infrastructure elements such as Wayland and Nvidia compatibility workarounds, EXIF metadata handling, and thumbnail caching optimization. UI improvements span both desktop and mobile platforms, indicating ongoing attention to the user experience across all supported systems.