INGEST
Import XMP folders or Lightroom catalogs as the source material for a style pack.
[ What RedLnx Actually Does ]
RedLnx is a local Rust + ONNX desktop app for photographers. It ingests real edits, filters obvious bad sources, adapts to your style, and writes local XMP outputs without a cloud handoff.
FILTER
Skip neutral sources, duplicate or derived sources, and Adobe AI / Adaptive Color poison markers before training.
PROFILE
Build an adaptive local style model from real edits you already trust instead of starting from a generic preset.
OUTPUT
Write local XMP sidecars for one style or multiple styles in dedicated output folders.
[ How It Works ]
The pipeline is concrete: train from real edits, inspect the develop deltas, then process a batch with one look or several.
Train
Import XMP folders or Lightroom catalogs. RedLnx builds a local style profile from your real edits and filters obvious poisoned or neutral sources before training.
Preview
Inspect before/after slider deltas on sample photos, compare style behavior, and choose a representative cover image for the style pack.
Batch
Write local XMP sidecars for one style or multiple styles, fully offline, with dedicated output folders per style.
[ Screenshots ]
Two real interface views. Click either card to open the full screenshot.
[ How RedLnx Runs ]
CAPABILITY STACK IMPACT
Native Desktop Runtime Rust desktop app with local storage and predictable offline execution. Training, preview, and batch output stay on your own machine.
Adaptive Local Inference Local ONNX inference with automatic Windows fallback: CUDA, then DirectML, then CPU. Acceleration uses what is available without turning the workflow into a cloud dependency.
Lightroom-Oriented Pipeline Train from edits, preview the develop deltas, and write local XMP sidecars. RedLnx automates develop settings without pretending to replace Lightroom's renderer.
No Hidden Network Path No telemetry, no cloud queue, no photo upload path. Your catalog, edits, and client work stay local.
[ LOCAL / PRIVACY / LICENSING ]
No subscriptions. No cloud queue. No hidden upload path.
RedLnx is a native Rust desktop app with local storage and predictable offline execution. Once installed, training, inference, preview, and batch output stay on your hardware.
The workflow is Lightroom-oriented and XMP-based. RedLnx automates develop settings locally; Lightroom still handles final rendering.
The project is AGPLv3, open source, and free to download, with no telemetry, tracker scripts, subscriptions, or locked feature tiers.
[ FAQ ]
What does RedLnx output?
RedLnx writes local XMP sidecars for Lightroom-oriented workflows. It automates develop settings; it is not a final raw renderer by itself.
What can I train on?
You can train from XMP folders or Lightroom catalogs. RedLnx profiles your existing edits and builds a local adaptive style model.
Does RedLnx filter bad training data?
Yes. RedLnx already skips neutral sources, duplicate or derived sources, and Adobe AI / Adaptive Color poison markers before training.
Can I process the same batch with multiple looks?
Yes. RedLnx can write separate outputs for multiple styles in dedicated folders.
Do I need a GPU?
No. CPU works too. On Windows, RedLnx can use CUDA when the NVIDIA runtime is ready, otherwise DirectML or CPU fallback. GPU acceleration helps some parts of the pipeline more than others.
Does it work offline?
Yes. Training, inference, preview, and batch output are local once the app is installed.
What affects training quality?
Training quality depends on the quality and consistency of the source edits. Cleaner source work produces a stronger style model.
Is there a subscription or paywall?
No. RedLnx is AGPLv3, open source, and free to download. There is no subscription tier or locked feature set.
[ DOWNLOAD / RELEASES ]
Releases ship the desktop app and the local runtime flow. On Windows, auto mode prefers CUDA when the NVIDIA runtime looks compatible, otherwise it falls back to DirectML, then CPU.
CPU is supported too. Acceleration helps some parts of the pipeline more than others, and training quality still depends on the consistency of the source edits.
[ Support The Project ]
RedLnx stays free, local, and subscription-free. If it saves you time, support development so the desktop app, docs, and releases keep moving.
[ Support The Project ]