Annotix

Open-source desktop platform for ML dataset annotation, training, and collaboration
Images · Video · Time Series · Tabular Data

Download • Read the Paper • Build from Source • Cite

Paper

Annotix: An Open-Source Desktop Platform for Comprehensive Machine Learning Dataset Annotation

Published on Preprints.org (April 2026)

Universidad Austral de Chile, Campus Puerto Montt — TecMedHub

If you use Annotix in your research, please cite the paper.

Why Annotix?

Most annotation tools focus on a single data type or require cloud accounts. Annotix is different:

	Annotix	Cloud tools (CVAT, Label Studio)	Desktop tools (labelImg, LabelMe)
Runs fully offline	Yes	No	Yes
Images + Video + Time Series + Tabular	Yes	Partial	No
Integrated ML training (19 backends)	Yes	No	No
P2P collaboration (no server)	Yes	Server required	No
Free GPU training (Colab automation)	Yes	No	No
Export to 11 formats	Yes	Yes	Limited
Cross-platform native app	Yes	Browser	Partial

Status

Last updated: April 2026 — v2.4.4

Feature	Status	Notes
Image annotation (7 tools)	✅ Stable	BBox, OBB, Mask, Polygon, Keypoints, Landmarks, Pan
Video annotation	✅ Stable	Tracks, keyframes, interpolation, bake
Time series annotation	✅ Stable	5 annotation types, Chart.js canvas
Tabular ML	✅ Stable	scikit-learn integration, column selector
ONNX inference	✅ Stable	Auto-detects YOLOv5-v12, DETR, SSD, classification
Export (11 formats)	✅ Stable	YOLO, COCO, VOC, CSV, U-Net, TIX, etc.
Import (8 formats)	✅ Stable	Auto-detection with confidence scoring
Local ML training (19 backends)	✅ Stable	Isolated Python env, GPU auto-detection
Cloud training (7 providers)	✅ Stable	Vertex AI, Kaggle, Lightning AI, HuggingFace, Saturn Cloud, Colab Enterprise
Browser automation (Colab free)	✅ Stable	T4 GPU, real-time progress
Keyboard shortcuts	✅ Stable	Fully customizable, conflict detection
i18n (10 languages)	✅ Stable	Lazy loading, English fallback
P2P collaboration	🚧 Beta	Works but no auto-reconnection on network drop; last-write-wins conflict resolution; video frames excluded from sync
Audio annotation	🚧 In progress	Classification, speech recognition, sound event detection, TTS recording exist; waveform UI partially wired
Audio export	🚧 In progress	HuggingFace ASR, LJSpeech, CSV formats implemented; import not yet available
Network sharing (serve)	🚧 In development	HTTP server to share projects via browser; web annotation UI built; not yet released
LLM chat via browser	🚧 Beta	Kimi, Qwen, DeepSeek, HuggingChat; generic runner works, provider-specific modules are stubs
macOS build	⚠️ Not tested	No CI for macOS; should build from source but untested

✅ = production-ready · 🚧 = usable but incomplete · ⚠️ = known limitation

Download

Pre-built binaries for the latest release:

Platform	Download
Windows (x64)	`.exe` installer \| `.msi`
Linux (x64)	`.AppImage`
macOS	Build from source (see Getting Started)

All releases: github.com/Debaq/Annotix/releases

Features at a Glance

Annotation Tools

7 tools on a high-performance Konva canvas:

Tool	Key	Description
BBox	`B`	Rectangular bounding box with drag & resize
OBB	`O`	Oriented bounding box with free rotation
Mask	`M`	Freehand painting with configurable brush and eraser
Polygon	`P`	Point-by-point polygon with auto-close
Keypoints	`K`	Skeleton presets (COCO, face, hand, MediaPipe)
Landmarks	`L`	Named reference points with labels
Pan	`H`	Canvas navigation

Plus: mouse wheel zoom, image rotation, label/grid toggles, quick class selection (1-0, Q-P for up to 20 classes), undo/redo with 100-step history.

Project Types

Images — Object detection, oriented detection, semantic/instance segmentation, keypoints, landmarks, single & multi-label classification
Video — Frame extraction (FFmpeg), tracks with keyframes, linear interpolation, bake to per-frame annotations
Time Series — Univariate & multivariate CSV, 5 annotation types (point, range, classification, event, anomaly)
Tabular — Built-in editor with column selection and scikit-learn training

Integrated ML Training (19 Backends)

Train models directly from the app with real-time metrics charts.

Full backend list

Object Detection

Backend	Models
YOLO (Ultralytics)	YOLOv8, v9, v10, v11, v12
RT-DETR (Ultralytics)	RT-DETR-l, RT-DETR-x
RF-DETR (Roboflow)	RF-DETR-base, RF-DETR-large
MMDetection (OpenMMLab)	30+ architectures (Faster R-CNN, DINO, Co-DETR, etc.)

Semantic Segmentation

Backend	Models
SMP	U-Net, DeepLabV3+, FPN, PSPNet, etc.
HuggingFace Segmentation	SegFormer, Mask2Former, etc.
MMSegmentation	Full OpenMMLab catalog

Instance Segmentation

Backend	Models
Detectron2 (Meta)	Mask R-CNN, Cascade R-CNN, etc.

Keypoints & Pose

Backend	Models
MMPose	HRNet, ViTPose, RTMPose, etc.

Oriented Object Detection (OBB)

Backend	Models
MMRotate	Oriented R-CNN, RoI Transformer, etc.

Image Classification

Backend	Models
timm	700+ models (ResNet, EfficientNet, ViT, ConvNeXt, etc.)
HuggingFace Classification	ViT, BEiT, DeiT, Swin, etc.

Time Series

Backend	Task
tsai	Classification, regression, forecasting
PyTorch Forecasting	TFT, N-BEATS, etc.
PyOD	Anomaly detection
tslearn	Temporal clustering
PyPOTS	Missing value imputation
STUMPY	Matrix Profile (motif/pattern discovery)

Tabular

Backend	Task
scikit-learn	RandomForest, SVM, kNN, GradientBoosting, etc.

4 execution modes:

Mode	Description
Local	Isolated Python env via micromamba, GPU auto-detection (CUDA / MPS)
Download Package	ZIP with script + data for external execution
Cloud	Vertex AI, Kaggle, Lightning AI, HuggingFace, Saturn Cloud
Browser Automation	Free T4 GPU on Google Colab via CDP automation

6 training presets: small_objects, industrial, traffic, edge_mobile, medical, aerial.

Model export: PyTorch .pt, ONNX, TorchScript, TFLite, CoreML, TensorRT.

P2P Collaboration

Real-time collaborative annotation powered by Iroh (QUIC). No central server.

Host or join with a session code
Roles: LeadResearcher (full control) / Annotator / DataCurator (configurable permissions)
Image locking with 3-min TTL, batch assignment, CRDT sync
Peer list with online status

Browser Automation

Train on Google Colab for free (T4 GPU) via Chrome DevTools Protocol:

Auto-detects Chromium browsers, uploads dataset, runs training
Real-time progress with pause / resume / cancel

Query LLMs without API keys through the user's browser: Kimi, Qwen, DeepSeek, HuggingChat.

Export & Import

11 export formats: YOLO Detection, YOLO Segmentation, COCO JSON, Pascal VOC, CSV (Detection/Classification/Keypoints/Landmarks), Folders by Class, U-Net Masks, TIX (native).

8 import formats with automatic detection: YOLO, COCO, Pascal VOC, CSV (4 variants), U-Net Masks, Folders by Class, TIX.

Keyboard Shortcuts

All shortcuts are fully customizable from Settings with per-context conflict detection.

Default shortcuts

Image Tools

Shortcut	Action
`B`	Bounding Box
`O`	OBB
`M`	Mask
`P`	Polygon
`K`	Keypoints
`L`	Landmarks
`H`	Pan
`[` / `]`	Decrease / Increase brush size
`E`	Toggle eraser
`A` / `D`	Rotate image
`Enter`	Confirm
`Esc`	Cancel

Navigation

Shortcut	Action
`Left` / `Right`	Previous / Next image
`Ctrl++` / `Ctrl+-`	Zoom in / out
`Ctrl+0`	Zoom to fit

General

Shortcut	Action
`Ctrl+S`	Save
`Ctrl+Z` / `Ctrl+Y`	Undo / Redo
`Del`	Delete selection

Quick Class Selection

Keys	Classes
`1` - `0`	Classes 1 to 10
`Q` - `P`	Classes 11 to 20

Video

Shortcut	Action
`T`	New track
`Left` / `Right`	Previous / Next frame

Time Series

Shortcut	Action
`V`	Select
`P`	Point
`R`	Range
`E`	Event
`A`	Anomaly

Languages

10 languages with lazy loading and English fallback:

de Deutsch · en English · es Espanol · fr Francais · it Italiano · ja Japanese · ko Korean · pt Portugues · ru Russian · zh Chinese

Architecture

+-----------------------------------------------------+
|                    Frontend                           |
|   React 19 + TypeScript + Tailwind + shadcn/ui       |
|   Konva (canvas) . Chart.js (metrics) . i18next      |
|   Zustand (state) . React Router 7                   |
+-----------------------------------------------------+
|                  Tauri 2 IPC                          |
|             137+ registered commands                  |
+-----------------------------------------------------+
|                  Backend (Rust)                       |
|   +------------+ +-----------+ +-----------------+   |
|   |   Store    | | Commands  | | Export/Import   |   |
|   | (JSON+RAM) | | (16 mod)  | | (11+8 formats) |   |
|   +------------+ +-----------+ +-----------------+   |
|   +------------+ +-----------+ +-----------------+   |
|   |  Training  | | Browser   | | P2P (Iroh)      |   |
|   | (19 backs) | | Automat.  | | QUIC mesh       |   |
|   +------------+ +-----------+ +-----------------+   |
+-----------------------------------------------------+
|               External Integrations                   |
|   Python (micromamba) . FFmpeg . Chromium CDP         |
|   Cloud APIs . Iroh P2P network                      |
+-----------------------------------------------------+

Storage

All data stored as JSON + raw assets on disk. No database.

~/.local/share/annotix/config.json        -> global configuration
{projects_dir}/{uuid}/project.json        -> project (metadata + classes + annotations)
{projects_dir}/{uuid}/images/             -> original images
{projects_dir}/{uuid}/thumbnails/         -> generated thumbnails
{projects_dir}/{uuid}/videos/             -> video files
{projects_dir}/{uuid}/models/             -> trained models

In-memory cache with dirty-flag tracking, atomic writes (.tmp + rename).

Tech Stack

Frontend

Technology	Version	Purpose
React	19	UI framework
TypeScript	5.7	Static typing
Vite	6	Bundler and dev server
Tailwind CSS	3.4	Utility-first styling
shadcn/ui	—	Component library (Radix UI)
Zustand	5	Global state with persistence
React Router	7	SPA routing
Konva	10	2D annotation canvas
Chart.js	4	Metrics visualization
i18next	24	Internationalization

Backend (Rust)

Crate	Version	Purpose
tauri	2	Desktop application framework
serde / serde_json	1	JSON serialization
image	0.25	Image processing
ffmpeg-the-third	4	Video frame extraction
zip	2	Export/import packaging
quick-xml	0.37	Pascal VOC XML
csv	1.3	CSV import/export
reqwest	0.12	HTTP client (cloud providers)
headless_chrome	1.0	Browser automation (CDP)
iroh	0.96	P2P networking (QUIC)
tokio	1	Async runtime
blake3	1	Hashing

Python (via micromamba)

Package	Purpose
ultralytics	YOLO, RT-DETR
rfdetr	RF-DETR
mmdet, mmseg, mmpose, mmrotate	OpenMMLab suite
segmentation-models-pytorch	Semantic segmentation
timm	Classification (700+ models)
detectron2	Instance segmentation
tsai, pytorch-forecasting	Time series deep learning
pyod, tslearn, pypots, stumpy	Time series classical ML
scikit-learn	Tabular ML

System Requirements

OS: Windows 10+, macOS 12+, Linux (glibc 2.31+)
RAM: 4 GB minimum, 8 GB recommended
Disk: ~500 MB for the app + space for datasets
GPU (optional): NVIDIA with CUDA or Apple Silicon with MPS for accelerated training
FFmpeg: required for video annotation (bundled in release builds)
Chromium browser (optional): for browser automation (Chrome, Brave, Edge)

Getting Started

Prerequisites

Node.js >= 18
Rust >= 1.89
Tauri 2 prerequisites for your platform

Build & Run

git clone https://github.com/Debaq/Annotix.git
cd Annotix
npm install
npm run tauri:dev       # development (hot-reload)
npm run tauri:build     # production build

Scripts

Script	Description
`npm run dev`	Frontend only (Vite dev server)
`npm run build`	Build frontend (TypeScript check + Vite)
`npm run tauri:dev`	Full dev (frontend + Rust backend)
`npm run tauri:build`	Production build with installers
`npm run lint`	ESLint with zero warnings policy

Project Structure

annotix/
├── src/                         # React frontend
│   ├── App.tsx                  # Router and providers
│   ├── lib/
│   │   ├── db.ts                # Type definitions (mirrors Rust structs)
│   │   ├── tauriDb.ts           # Centralized Tauri invoke bridge
│   │   └── i18n.ts              # i18next configuration
│   ├── components/ui/           # shadcn/ui components
│   └── features/
│       ├── canvas/              # Annotation canvas (7 tools)
│       ├── video/               # Video annotation
│       ├── timeseries/          # Time series annotation
│       ├── tabular/             # Tabular data editor
│       ├── training/            # ML training panel
│       ├── export/              # 11 export formats
│       ├── import/              # 8 import formats
│       ├── inference/           # Model inference
│       ├── p2p/                 # P2P collaboration
│       ├── browser-automation/  # Chrome automation
│       └── settings/            # App settings
├── src-tauri/                   # Rust backend
│   └── src/
│       ├── lib.rs               # 137+ Tauri command registrations
│       ├── store/               # Storage layer (state, IO, cache)
│       ├── commands/            # 16 command modules
│       ├── export/              # Export format modules
│       ├── import/              # Import + auto-detector
│       ├── training/            # Multi-backend ML pipeline
│       ├── browser_automation/  # Headless Chrome
│       ├── p2p/                 # Iroh P2P networking
│       └── inference/           # ONNX inference
└── public/locales/              # 10 language files

Citation

If you use Annotix in your research, please cite:

@article{annotix2026,
  title     = {Annotix: An Open-Source Desktop Platform for Comprehensive Machine Learning Dataset Annotation},
  year      = {2026},
  publisher = {Preprints.org},
  url       = {https://www.preprints.org/manuscript/202604.0919}
}

Full paper: https://www.preprints.org/manuscript/202604.0919

Contributing

Contributions are welcome. Please open an issue first to discuss what you'd like to change.

License

MIT License — TecMedHub, Universidad Austral de Chile, Campus Puerto Montt.

Name		Name	Last commit message	Last commit date
Latest commit History 203 Commits
.github/workflows		.github/workflows
docs		docs
public		public
scripts		scripts
src-tauri		src-tauri
src		src
wiki		wiki
.env.example		.env.example
.gitignore		.gitignore
.zenodo.json		.zenodo.json
ARCHITECTURE.md		ARCHITECTURE.md
README.md		README.md
VERSION		VERSION
annotix.sh		annotix.sh
build.json		build.json
check-translations.ts		check-translations.ts
components.json		components.json
eslint.config.js		eslint.config.js
index.html		index.html
package.json		package.json
pnpm-lock.yaml		pnpm-lock.yaml
postcss.config.js		postcss.config.js
releases.json		releases.json
tailwind.config.js		tailwind.config.js
tsconfig.json		tsconfig.json
tsconfig.node.json		tsconfig.node.json
vite.config.ts		vite.config.ts

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Annotix

Paper

Why Annotix?

Status

Download

Features at a Glance

Annotation Tools

Project Types

Integrated ML Training (19 Backends)

Object Detection

Semantic Segmentation

Instance Segmentation

Keypoints & Pose

Oriented Object Detection (OBB)

Image Classification

Time Series

Tabular

P2P Collaboration

Browser Automation

Export & Import

Keyboard Shortcuts

Image Tools

Navigation

General

Quick Class Selection

Video

Time Series

Languages

Architecture

Storage

Tech Stack

System Requirements

Getting Started

Prerequisites

Build & Run

Scripts

Project Structure

Citation

Contributing

License

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