RapidRAW: A beautiful, non-destructive, and GPU-accelerated RAW image editor

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

RapidRAW is a modern, high-performance alternative to Adobe Lightroom. It delivers a feature-rich, beautiful editing experience in a lightweight package (under 30MB) for Windows, macOS, and Linux.

I developed this project as a personal challenge at the age of 18. My goal was to create a high-performance tool for my own photography workflow while deepening my understanding of both React and Rust, with the support from Google Gemini.

Have fun!

Recent Changes

• 2025-07-08: Ability to toggle the visibility of individual adjustments sections
• 2025-07-08: Fixed top-left zoom bug, corrected scale behavior in crop panel, keep default original aspect ratio.
• 2025-07-08: Added image rating filter and redesigned the metadata panel with improved layout, clearer sections, and an embedded GPS map.
• 2025-07-07: Improved generative AI features and updated AI Roadmap
• 2025-07-06: Initial generative AI integration with ComfyUI - for more details, checkout the AI Roadmap
• 2025-07-05: Ability to overwrite preset with current settings
• 2025-07-04: High speed and precise cache to significantly accelerate large image editing
• 2025-07-04: Greatly improved shader with better dehaze, more accurate curves etc.
• 2025-07-04: Predefined 90° clockwise rotation and ability to flip images
• 2025-07-03: Switched from rawloader to rawler to support a wider range of RAW formats
• 2025-07-02: AI-powered foreground / background masking
• 2025-06-30: AI-powered subject masking
• 2025-06-30: Precompiled Linux builds
• 2025-06-29: New 5:4 aspect ratio, new low contrast grey theme and more cameras support (DJI Mavic lineup)
• 2025-06-28: Release cleanup, CI/CD improvements and minor fixes
• 2025-06-27: Initial release. For more information about the earlier progress, look at the Initial Development Log

Table of Contents

• Key Features
• Demo & Screenshots
• The Idea
• Current Priorities
• AI Roadmap
• Initial Development Log
• Getting Started
• Contributing
• Special Thanks
• Support the Project
• License & Philosophy

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GPU-Accelerated Processing: All image adjustments are processed on the GPU using a custom WGSL shader for rapid feedback. Masking: Instantly create precise masks with AI subject and foreground detection. Combine with traditional Brush, Linear, and Radial masks for great control. Generative Edits: Remove objects or add new elements with text prompts. Each edit creates a non-destructive patch layer, powered by an optional ComfyUI backend. Full RAW Support: Supports a wide range of RAW camera formats thanks to rawler. Non-Destructive Workflow: All edits are stored in a .rrdata sidecar file, leaving your original images untouched. 32-bit Precision: Ensures high-quality adjustments without banding or data loss. Professional Grade Adjustments Tonal Controls: Exposure, Contrast, Highlights, Shadows, Whites, and Blacks. Tone Curves: Full control over Luma, Red, Green, and Blue channels. Color Grading: Temperature, Tint, Vibrance, Saturation, and a full HSL color mixer. Detail Enhancement: Sharpening, Clarity, Structure, and Noise Reduction. Effects: Dehaze, Vignette, and realistic Film Grain simulation. Transform Tools: Crop with aspect ratio locking, Rotate, and Flip.

Image Library: Effortlessly sort, rate, and manage your entire photo collection for a streamlined and efficient workflow. Folder Management: Integrated folder tree, create, rename, and delete folders directly within the app. File Operations: Copy, move, and duplicate images and their associated edits. Filmstrip View: Quickly navigate between all the images in your current folder while editing. Batch Operations: Save significant time by applying a consistent set of adjustments or exporting entire batches of images simultaneously. EXIF Data Viewer: Gain insights by inspecting the complete metadata from your camera, including shutter speed, aperture, ISO, and lens information. Preset System: Create, save, import, and export your favorite looks. Copy & Paste Settings: Quickly transfer adjustments between images. Undo/Redo History: A robust history system for every edit. Customizable UI: Resizable panels and multiple beautiful UI themes with smooth animations. Exporting: Control file format (JPEG, PNG, TIFF), quality, and resizing options on export.

Here's RapidRAW in action.

The main editor interface in action.

If you like the theme images and want to see more of my own images, checkout my Instagram: @timonkaech.photography

As a photography enthusiast, I often found existing software to be sluggish and resource-heavy on my machine. Born from the desire for a more responsive and streamlined photo editing experience, I set out to build my own. The goal was to create a tool that was not only fast but also helped me learn the details of digital image processing and camera technology.

I set an ambitious goal to rapidly build a functional, feature-rich application from an empty folder. This personal challenge pushed me to learn quickly and focus intensely on the core architecture and user experience.

The foundation is built on Rust for its safety and performance, and Tauri for its ability to create lightweight, cross-platform desktop apps with a web frontend. The entire image processing pipeline is offloaded to the GPU via WGPU and a custom WGSL shader, ensuring that even on complex edits with multiple masks, the UI remains fluid.

I am immensely grateful for Google's Gemini suite of AI models. As an 18-year-old without a formal background in advanced mathematics or image science, the AI Studio's free tier was an invaluable assistant, helping me research and implement concepts like the Menon demosaicing algorithm.

While the core functionality is in place, I'm actively working on improving several key areas. Here's a transparent look at the current focus:

Task Priority Difficulty Status

Refactoring the frontend (reduce prop drilling in React components)	Medium	Medium	[ ]
Allow 45°+ rotation for images (e.g. predefined 90° clockwise )	Medium	Low	[X]
Improving the dehaze tool for more natural results	Low	Medium	[X]
Optimize image transport (replace Base64 for better performance)	Low	Medium	[ ]
Add AI-generated masks using Segment Anything	High	Medium	[X]
Implement a simple MVP of the ComfyUI based AI Roadmap	Low	High	[X]
Sign macOS builds using a registered developer account	Medium	Low	[ ]
Switch to a better rawloader (e.g. rawler)	High	Medium	[X]
Improve speed on older systems (e.g. Pascal GPUs)	Medium	High	[ ]
Auto white balance detection and exposure correction	Medium	Medium	[ ]

RapidRAW features a two-tier approach to AI to provide both speed and power. It distinguishes between lightweight, integrated tools and heavy, optional generative features.

1. Built-in AI Masking: The core application includes lightweight, fast and open source AI models (SAM from Meta) for intelligent masking (e.g., Subject and Foreground selection). These tools run locally, are always available, and are designed to accelerate your standard editing workflow.

2. Optional Generative AI: For computationally intensive tasks like inpainting (Generative Replace), RapidRAW connects to an external ComfyUI backend. This keeps the main application small and fast, while offloading heavy processing to a dedicated, user-run server.

The Built-in AI Masking is fully functional for all users.

The Optional Generative AI features, however, currently require a manual setup of a ComfyUI backend. The official, easy-to-use Docker container is not yet provided.

This means the generative tools are considered a developer preview and are not ready for general, out-of-the-box use.

Click to see the Generative AI features in action

Generative Replace powered by a local ComfyUI backend.

The initial work on generative AI focused on building a connection to the ComfyUI backend and implementing the first key features.

• Modular Backend: RapidRAW connects to a local ComfyUI server, which acts as the inference engine.
• Generative Replace (Inpainting): Users can paint a mask over an area of the image (or use the AI masking tool to create a precise selection) and provide a text prompt to fill that area with generated content.
• Non-Destructive Patches: Each generative edit is stored as a separate "patch" layer. These can be toggled, re-ordered, or deleted at any time, consistent with RapidRAW's non-destructive philosophy.

The Technical Approach for Generative AI
The integration is designed as follows:

1. Optional Backend: Users who want generative features can run an official, pre-configured Docker container which launches a ComfyUI server with all necessary models and custom nodes.
2. Automatic Detection: RapidRAW automatically detects if the local ComfyUI server is running and enables the generative AI tools in the UI.
3. Workflow-Based Execution: When a user triggers a generative action (e.g., "Generative Replace"), RapidRAW sends the source image, mask, and text prompt to the ComfyUI server along with a specific, predefined workflow JSON.
4. Backend Processing: The Docker container handles all the heavy processing on the GPU, executing the Stable Diffusion workflow.
5. Seamless Integration: The resulting image (the generated patch) is sent back to RapidRAW and composited into the editor as a patch onto the source image.

This approach ensures that RapidRAW's core experience remains fast and lightweight, while providing an extensible path for optional, powerful AI features.

This project began as an intensive sprint to build the core functionality. Here's a summary of the initial progress and key milestones:

Click to expand the day-by-day development log

• Day 1: June 13th, 2025 - Project inception, basic Tauri setup, and initial brightness/contrast shader implementation.
• Day 2: June 14th - Core architecture refactor, full library support (folder tree, image list), and optimized image loading. Implemented histogram and curve editor support. Added UI themes.
• Day 3: June 15th - Implemented a working crop tool, preset system, and context menus. Enabled auto-saving of edits to sidecar files and auto-thumbnail generation. Refined color adjustments.
• Day 4: June 16th - Initial prototype for local adjustments with masking. Added mask support to presets. Bug-free image preview switching.
• Day 5: June 17th - Major UI overhaul. Created the filmstrip and resizable panel layout. Fixed mask scaling issues and improved the library/welcome screen.
• Day 6: June 18th - Performance tuning. Reduced GPU calls for adjustments, leading to a much smoother cropping and editing experience. Implemented saving of panel UI state.
• Day 7: June 19th - Enhanced library functionality. Added multi-selection and the ability to copy/paste adjustments across multiple images.
• Day 8: June 20th - Implemented initial RAW file support and an EXIF metadata viewer.
• Day 9: June 21st - Added advanced detail adjustments (Clarity, Sharpening, Dehaze, etc.) and film grain. Developed a linear RAW processing pipeline.
• Day 10: June 22nd - Implemented layer stacking for smooth preview transitions. Built a robust export panel with batch export capabilities. Added import/export for presets.
• Day 11: June 23rd - Added full undo/redo functionality integrated with a custom history hook. Improved context menus and completed the settings panel.
• Day 12: June 24th - Implemented image rotation and fixed all mask scaling/alignment issues related to cropping and rotation.
• Day 13: June 25th - Rewrote the mask system to be bitmap-based. Implemented brush and linear gradient tools, with semi-transparent visualization.
• Day 14: June 26th-27th - Final polish. Added universal keyboard shortcuts, full adjustment support for masks, theme management, and final UI/UX improvements. This ReadMe.

You have two options to run RapidRAW:

1. Download the Latest Release (Recommended)

Grab the pre-built installer or application bundle for your operating system from the Releases page.

2. Build from Source

If you want to build the project yourself, you'll need to have Rust and Node.js installed.

Contributions are welcome and highly appreciated! Whether it's reporting a bug, suggesting a feature, or submitting a pull request, your help makes this project better. Please feel free to open an issue to discuss your ideas.

A huge thank you to the following projects and tools that were very important in the development of RapidRAW:

• Google AI Studio: For providing amazing assistance in researching, implementing image processing algorithms and giving an overall speed boost.
• rawler: For the excellent Rust crate that provides the foundation for RAW file processing in this project.

As an 18-year-old developer balancing this project with an apprenticeship, your support means the world. If you find RapidRAW useful or exciting, please consider donating to help me dedicate more time to its development and cover any associated costs.

• Ko-fi: Donate on Ko-fi
• Crypto:
  • BTC: 36yHjo2dkBwQ63p3YwtqoYAohoZhhUTkCJ (min. 0.0001 because of broker)
  • ETH: 0x597e6bdb97f3d0f1602b5efc8f3b7beb21eaf74a (min. 0.005 because of broker)
  • SOL: CkXM3C777S8iJX9h3MGSfwGxb85Yx7GHmynQUFSbZXUL (min. 0.01 because of broker)

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). I chose this license to ensure that RapidRAW and any of its derivatives will always remain open-source and free for the community. It protects the project from being used in closed-source commercial software, ensuring that improvements benefit everyone.

See the LICENSE file for more details.