Local-first, AI-assisted data labeling — a cross-platform desktop studio for images, video, text & audio.
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Vailabel Studio is an open-source desktop annotation tool in the spirit of LabelMe and Label Studio — but it runs entirely on your machine. Your data lives in a local SQLite database, images are referenced in place (no base64 copies), and everything works offline. On top of that familiar labeling workflow it adds an AI layer: one-click auto-labeling, click-to-segment, and an on-device assistant.
It's built as a native desktop app with Tauri (Rust) + React, so you get a small, fast binary with real filesystem access instead of a browser tab.
- Images — bounding boxes, polygons, keypoints, lines, polylines, circles, and free-draw.
- Video — frame extraction, scene detection, and object labeling across time (FFmpeg pipeline).
- Text — named-entity spans, relations, classification, Q&A, and translation.
- Audio — waveform region labeling, diarization, and transcription.
- Custom — define your own projects with Label-Studio-style JSON configs; a config-driven editor renders the right tools automatically.
- Auto-label — run a YOLO detection model on the current image and review the suggestions.
- Smart Segment — click an object to segment it with SAM (Segment Anything).
- Copilot (experimental) — an offline, on-device vision assistant for label suggestions.
- Local-first — a single SQLite database; fully offline, your data never leaves your machine.
- Reference in place — point at a folder of images; nothing is copied or duplicated.
- Import / export — LabelMe sidecars, JSONL, and dataset exports for model training.
- Cloud storage (optional) — connect S3, Azure Blob, or Google Cloud Storage; credentials stay in your OS keychain.
- Label-Studio-style workspace — a file queue, center canvas with a tool rail, and a docked Classes / Regions / AI / Copilot panel.
Project status: Vailabel Studio is under active development. Core image/text/audio/video labeling and YOLO/SAM assistance are usable today; the on-device Copilot and embedded training runtime are evolving — expect rough edges and breaking changes.
Grab the latest installer for your platform from the Releases page:
| Platform | Installer |
|---|---|
| Windows | .exe (setup) or .msi |
| macOS | .dmg — Apple Silicon (aarch64) and Intel (x64) |
| Linux | .AppImage, .deb, or .rpm |
macOS builds are unsigned for now — if Gatekeeper blocks the app, right-click → Open the first time (or
xattr -dr com.apple.quarantine /Applications/Vailabel\ Studio.app).
- Node.js 20+ and Yarn (Classic / v1)
- Rust (stable toolchain) — install via rustup
- The platform build dependencies for Tauri v2 — see the Tauri prerequisites guide
# install workspace dependencies
yarn install
# run the full desktop app (Tauri + React)
yarn dev # alias: yarn desktop
# run just the React UI in the browser (no Rust backend)
yarn studio
# tests, lint, typecheck
yarn test
yarn lint
yarn typecheck
# build production bundles
yarn build # web + studio frontend
yarn release # native desktop installers (tauri build)This is a Yarn-workspaces monorepo:
apps/
├── studio/ # the Tauri desktop app
│ ├── src/ # React frontend — feature-sliced
│ │ ├── app/ # router (lazy routes), providers, layout shell
│ │ ├── features/ # studio · projects · ai-models · labels · …
│ │ └── shared/ # ui (shadcn-style) · lib · services · ipc · types
│ └── src-tauri/ # Rust backend — Tauri commands + DDD modular crates
│ ├── crates/ # per-domain crates (pure domain + Diesel/SQLite)
│ └── migrations/ # the canonical SQLite schema
└── web/ # marketing / documentation site
- Frontend — React 19 + Vite + TypeScript + Tailwind v4, organized feature-first
(
app/+features/*+shared/*); routes are code-split withReact.lazy. - Desktop shell — Tauri v2; the React UI talks to Rust over a typed IPC bridge.
- Backend — Rust as a DDD modular monolith: each domain is its own crate with a pure core and a typed Diesel repository over a shared SQLite connection. Embedded migrations are the single source of truth for the schema.
Contributions are welcome! Please read CONTRIBUTE.md to get set up, and our Code of Conduct before opening a pull request. Found a security issue? See SECURITY.md — please don't file it as a public issue.
Vailabel Studio is licensed under the Apache License 2.0.