Learn and reproduce a photographer's Lightroom editing style
Project description
Lureva
Lureva is an experimental tool for learning a photographer's Lightroom editing style from paired RAW and edited examples.
The initial goal is straightforward: given a RAW image, predict adjustments that reproduce the photographer's editing decisions and emit either:
- a DNG containing the resulting edit metadata, or
- the original RAW file with an accompanying XMP sidecar.
The project is Python-first. A minimal Rust crate is published under the same name to reserve the namespace and leave room for native components later.
Python
uv sync
uv run lureva
Expected output:
Hello from Lureva 0.1.0!
Rust
cargo run
Expected output:
Hello from Lureva 0.1.0!
Status
Early development. No editing or prediction functionality has been implemented yet.
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