AutoShade

Describe the picture. Keep the RAW.

AI decides what to change — a deterministic Rust engine does it.
An editable, Lightroom-ready recipe instead of AI pixels.

Download v1.15.0  ·  Website  ·  Manual  ·  Showcase  ·  In depth

_{Straight conversion → generated target → recovered recipe on the 61 MP RAW → same recipe after AI denoise. Bottom row: 1:1 crops.}

Two AI paths, kept apart in the app, the command line and this page:

• AI generation & reverse-fit — an image model paints the picture you describe from your own frame (reimagine), and the reverse fit recovers that look as an editable recipe on the full RAW (match). The generated pixels are only ever a target.
• AI analysis & auto develop — a vision model looks at the photo and proposes the recipe directly (analyze, auto), guided by your reference library or a typed direction; AI adjust sends the develop you are looking at with a request ("darken the sky a little") and gets the complete adjusted recipe back, with any part it names selected by a content mask cut locally.

_{Reverse-fit. Prompt: “a clearer afternoon, a little more contrast, a slightly deeper blue sky.” The recipe renders the look on the 9504 × 6336 RAW; the generated frame carries neither the detail nor the resolution.}

_{One RAW, four looks. Straight conversion, then moody, golden and vivid — only the direction text changes.}

_{ISO 2500 star field, 1:1. Top: Lightroom, Denoise off / 50. Bottom: AutoShade, off / its own denoiser at 71 %. Clean colour, natural grain, faint stars intact.}

_{Every number and prompt → Showcase}

Six techniques you will not find in another RAW developer. Each is written up in full — equations, figures, refused training runs — in AutoShade in depth.

• One engine, three front ends — desktop app, CLI and loopback web UI share one Rust library and one per-user develop store.
• Local first — eight Python sidecars (masks, two denoisers, correspondence, descriptions, embeddings, depth for the lens blur, faces) run on your machine; pixels leave it only for an AI operation you ask for.
• Non-destructive — your photo library stays read-only; generated pixels always land on their own labelled card.

_{Diagram generated from autoshade.architecture.json · zoom it online · full design in ARCHITECTURE.md}

_{The full table — 20+ rows with conditions and sources — is in AutoShade in depth; scripts/check_docs.py re-derives the pinned claims.}

All on the v1.15.0 release page. Python 3 is needed only for the local AI sidecars; model weights download on first use.

Desktop app — it starts on a mode page (Landscape, Portraits, Normal; see Choosing a mode); then open a photo (Ctrl+O), move a slider, export with Ctrl+Shift+E. The original is never touched. Normal is a short one-click panel for phone and jpg photos (Normal mode).

CLI

# manual develop
autoshade apply photo.ARW recipe.json -o developed.tif

# AI develop, end to end
autoshade auto photo.ARW --guidance "natural color; protect highlights" -o developed.tif

# describe a look, then recover it as an editable recipe on the RAW
autoshade reimagine photo.ARW --prompt "a clearer afternoon, deeper blue sky"
autoshade match photo.ARW out/photo.reimagine.png --render

Upgrades, silent installs and every command: User manual.

cargo build --release                                   # CLI
cargo build --release --features gui --bin autoshade-gui  # desktop app

.cr2 · Canon EOS 40D	.cr3 · Canon EOS R6	.nef · Nikon D700
.arw · Sony α7 III	.orf · Olympus E-M5	.rw2 · Panasonic DMC-GX85
.pef · Pentax K-5	.dng · Ricoh GR II	.raf · Fujifilm X-S10 — X-Trans, approximate

_{Nine real CC0 files, fully decoded and neutral-rendered — not embedded previews.}

Camera RAW — 24 extensions

arw, dng, raw, raf, nef, cr2, cr3, orf, rw2, pef, srw, 3fr,
fff, iiq, mef, mos, erf, kdc, dcr, dcs, crw, nrw, mrw, ari

Decoded by rawler 0.7.2, which carries 725 camera models. No embedded preview: 12 of the 24 formats store none. They are orf, srw, nrw, mef, mos, kdc, dcr, dcs, erf, iiq, crw, and ari; AutoShade renders its own neutral version instead.

Baked rasters — 8 extensions: jpg jpeg png tif tiff bmp webp gif, with ICC conversion.

Rust (rustc/cargo 1.94, edition 2024) · rawler · image · qcms · rayon · egui/eframe · tiny_http — Python sidecars on PyTorch.

RAW decode, 24 formats, 725 bodies · deterministic f32 develop engine · hand-rolled XMP layer (no XML crate) for byte-exact Lightroom merges. The current battery is 1747 library (1732 pass + 15 #[ignore]d forensic probes) / 25 CLI / 289 GUI / 2+2 contract tests. Per-subsystem notes: In depth → Implementation · equations and provenance: TECH_STACK.md.

• Release gates at v1.15.0 cover the CLI, desktop GUI, sidecar contracts, format fixtures and the deterministic renderer.
• Not in scope: bit-exact Adobe rendering (parity is measured, not identical), an exact X-Trans demosaic, a notarised macOS build, a Linux desktop app.
• Honest markers: AI masks are local re-creations, not Adobe's pixels; linear masks are not pixel-closed (radial closes 41/41 to ≤ 1 px); the macOS app is CI-verified but has no reported interactive users yet.
• Release ledger and rulings: ROADMAP.md.

MIT — see LICENSE. Showcase photographs © 2026 skymanbp, all rights reserved (not MIT).