https://github.com/debaq/annotix

Open-source desktop platform for ML dataset annotation, training, and collaboration — Images, Video, Time Series, Tabular
https://github.com/debaq/annotix
annotation computer-vision dataset deep-learning desktop-app image-annotation machine-learning object-detection p2p react rust tauri time-series video-annotation yolo
Last synced: 2 months ago
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Open-source desktop platform for ML dataset annotation, training, and collaboration — Images, Video, Time Series, Tabular
Host: GitHub
URL: https://github.com/debaq/annotix
Owner: Debaq
Created: 2025-11-29T01:07:49.000Z (7 months ago)
Default Branch: main
Last Pushed: 2026-04-25T18:16:27.000Z (2 months ago)
Last Synced: 2026-04-25T18:31:39.491Z (2 months ago)
Topics: annotation, computer-vision, dataset, deep-learning, desktop-app, image-annotation, machine-learning, object-detection, p2p, react, rust, tauri, time-series, video-annotation, yolo
Language: TypeScript
Homepage: https://www.preprints.org/manuscript/202604.0919
Size: 5.1 MB
Stars: 2
Watchers: 0
Forks: 0
Open Issues: 2
Metadata Files:
- Readme: README.md
- Roadmap: docs/roadmap-perf-js-rust.md
- Zenodo: .zenodo.json
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README

          


  



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](https://www.preprints.org/manuscript/202604.0919) (April 2026)

>

> Universidad Austral de Chile, Campus Puerto Montt — [TecMedHub](https://github.com/tecmedhub)

If you use Annotix in your research, please [cite the paper](#citation).

---

## 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) | :white_check_mark: Stable | BBox, OBB, Mask, Polygon, Keypoints, Landmarks, Pan |

| **Video annotation** | :white_check_mark: Stable | Tracks, keyframes, interpolation, bake |

| **Time series annotation** | :white_check_mark: Stable | 5 annotation types, Chart.js canvas |

| **Tabular ML** | :white_check_mark: Stable | scikit-learn integration, column selector |

| **ONNX inference** | :white_check_mark: Stable | Auto-detects YOLOv5-v12, DETR, SSD, classification |

| **Export** (11 formats) | :white_check_mark: Stable | YOLO, COCO, VOC, CSV, U-Net, TIX, etc. |

| **Import** (8 formats) | :white_check_mark: Stable | Auto-detection with confidence scoring |

| **Local ML training** (19 backends) | :white_check_mark: Stable | Isolated Python env, GPU auto-detection |

| **Cloud training** (7 providers) | :white_check_mark: Stable | Vertex AI, Kaggle, Lightning AI, HuggingFace, Saturn Cloud, Colab Enterprise |

| **Browser automation** (Colab free) | :white_check_mark: Stable | T4 GPU, real-time progress |

| **Keyboard shortcuts** | :white_check_mark: Stable | Fully customizable, conflict detection |

| **i18n** (10 languages) | :white_check_mark: Stable | Lazy loading, English fallback |

| **P2P collaboration** | :construction: Beta | Works but no auto-reconnection on network drop; last-write-wins conflict resolution; video frames excluded from sync |

| **Audio annotation** | :construction: In progress | Classification, speech recognition, sound event detection, TTS recording exist; waveform UI partially wired |

| **Audio export** | :construction: In progress | HuggingFace ASR, LJSpeech, CSV formats implemented; import not yet available |

| **Network sharing** (serve) | :construction: In development | HTTP server to share projects via browser; web annotation UI built; not yet released |

| **LLM chat via browser** | :construction: Beta | Kimi, Qwen, DeepSeek, HuggingChat; generic runner works, provider-specific modules are stubs |

| **macOS build** | :warning: Not tested | No CI for macOS; should build from source but untested |

:white_check_mark: = production-ready  ·  :construction: = usable but incomplete  ·  :warning: = known limitation

---

## Download

Pre-built binaries for the latest release:

| Platform | Download |

|----------|----------|

| **Windows** (x64) | [`.exe` installer](https://github.com/Debaq/Annotix/releases/latest/download/Annotix_2.4.4_x64-setup.exe)  \|  [`.msi`](https://github.com/Debaq/Annotix/releases/latest/download/Annotix_2.4.4_x64_en-US.msi) |

| **Linux** (x64) | [`.AppImage`](https://github.com/Debaq/Annotix/releases/latest/download/Annotix_2.4.4_amd64.AppImage) |

| **macOS** | Build from source (see [Getting Started](#getting-started)) |

> All releases: [github.com/Debaq/Annotix/releases](https://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](https://iroh.computer/) (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](https://nodejs.org/) >= 18

- [Rust](https://rustup.rs/) >= 1.89

- [Tauri 2 prerequisites](https://v2.tauri.app/start/prerequisites/) for your platform

### Build & Run

```bash

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:

```bibtex

@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](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](https://github.com/tecmedhub), Universidad Austral de Chile, Campus Puerto Montt.
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