# Annotex 🚀
**AI-Powered Annotation Tool for Computer Vision Datasets**
[](https://www.python.org/downloads/)
<!-- [](https://opensource.org/licenses/MIT) -->
<!-- [](https://badge.fury.io/py/annotex) -->
<!-- [](https://pepy.tech/project/annotex) -->
Annotex is a professional-grade annotation tool designed for creating high-quality computer vision datasets. With AI-powered assistance and an intuitive interface, it streamlines the annotation process for machine learning practitioners.
## ✨ Features
### 🎯 **Professional Annotation Tools**
- **Rectangle Annotation** - Precise bounding box creation
- **AI-Assisted Annotation** - Auto-annotation with pre-trained YOLO models
- **Batch Processing** - Process multiple images simultaneously
### 🔧 **Advanced Workflow**
- **Project Management** - Save/load projects (.anno format)
- **Class Management** - Dynamic class creation with custom colors
- **Export Formats** - YOLO11, YOLOv8, compatible
- **Quality Control** - Confidence scoring and validation
### 🚀 **Performance Optimized**
- **Memory Efficient** - Handles large datasets smoothly
- **Real-time Preview** - Instant annotation feedback
- **Keyboard Shortcuts** - Professional workflow acceleration
## 📦 Installation
### Quick Install
```bash
pip install annotex
```
## 🚀 Quick Start
### Launch Annotex
```bash
# Start the GUI
annotex
# Or
python -m annotex.main
# Load a project
annotex --project my_project.anno
# Load images from directory
annotex --images /path/to/images
```
### Basic Workflow
1. **Load Images** - Import your image dataset
2. **Create Classes** - Define annotation classes
3. **Annotate** - Create bounding boxes manually or with AI
4. **Export** - Generate YOLO-format dataset
## 📚 Documentation
### Keyboard Shortcuts
| Category | Shortcut | Action |
|----------|----------|--------|
| **Navigation** | `Left Arrow` | Previous image |
| | `Right Arrow` | Next image |
| | `Home` | First image |
| | `End` | Last image |
| | `Ctrl + +` | Zoom in |
| | `Ctrl + -` | Zoom out |
| | `Ctrl + 0` | Zoom fit |
| | `Ctrl + R` | Reset view |
| **File Operations** | `Ctrl + N` | New project |
| | `Ctrl + O` | Open project |
| | `Ctrl + S` | Save current |
| | `Ctrl + Shift + S` | Save project |
| | `Ctrl + I` | Load images |
| | `Ctrl + E` | Export dataset |
| **Editing** | `Ctrl + Z` | Undo |
| | `Ctrl + C` | Copy annotation |
| | `Ctrl + V` | Paste annotation |
| | `Delete` | Delete selected |
| | `Ctrl + Shift + C` | Clear all |
| | `R` | Rectangle tool |
| **Tools & Classes** | `1-9` | Select class by number |
| | `F1` | Show shortcuts |
| | `Middle Click + Drag` | Pan image |
| | `Mouse Wheel` | Zoom in/out |
| | `Right Click` | Context menu |
## 🎨 Interface Overview
### Main Components
- **Tools Panel** - Annotation tools and class management
- **Image Viewer** - Zoomable canvas with annotation overlay
- **Image List** - Project image management
- **Export Panel** - Dataset export configuration
### Advanced Features
- **Semi-Automated Annotation** - Pre-trained AI model integration
- **Batch Processing** - Multi-image operations
- **Quality Metrics** - Annotation statistics and validation
- **Custom Export** - Flexible dataset formats (Currently:only YOLO formats)
## 🤖 AI Integration
### Supported Models
- **YOLO11** - Proven performance
- **Custom Models** - Load your own trained models
### Auto-Annotation Workflow
```bash
1. Load pre-trained model (.pt file)
2. Set confidence threshold
3. Run individual or batch annotation
4. Review and refine results
5. Export final dataset
Possible Usage: Pre-train your AI model on a small dataset and use that model to annotate the rest of the dataset.
```
## 🏗️ Roadmap
### Version 2.2 (Coming Soon)
- [ ] Polygon annotation tool
- [ ] Point annotation support
- [ ] Brush/segmentation tool
- [ ] COCO format export
- [ ] Pascal VOC format support
### Version 2.3 (Planned)
<!-- - [ ] Cloud storage integration -->
- [ ] Team collaboration features
- [ ] Advanced AI suggestions
<!-- - [ ] Mobile app companion -->
## 📞 Support
- 📧 **Email**: randikamk.96@gmail.com
## 🌟 Acknowledgments
- [Ultralytics](https://ultralytics.com/) for YOLO implementation
- [OpenCV](https://opencv.org/) for computer vision tools
- [Tkinter](https://docs.python.org/3/library/tkinter.html) for GUI framework
---
**⭐ Star us on GitHub if Annotex helps your projects!**
Made by [Randika](https://github.com/RandikaKM)
Raw data
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"description": "# Annotex \ud83d\ude80\r\n\r\n**AI-Powered Annotation Tool for Computer Vision Datasets**\r\n\r\n[](https://www.python.org/downloads/)\r\n<!-- [](https://opensource.org/licenses/MIT) -->\r\n<!-- [](https://badge.fury.io/py/annotex) -->\r\n<!-- [](https://pepy.tech/project/annotex) -->\r\n\r\nAnnotex is a professional-grade annotation tool designed for creating high-quality computer vision datasets. With AI-powered assistance and an intuitive interface, it streamlines the annotation process for machine learning practitioners.\r\n\r\n\r\n\r\n## \u2728 Features\r\n\r\n### \ud83c\udfaf **Professional Annotation Tools**\r\n- **Rectangle Annotation** - Precise bounding box creation\r\n- **AI-Assisted Annotation** - Auto-annotation with pre-trained YOLO models\r\n- **Batch Processing** - Process multiple images simultaneously\r\n\r\n### \ud83d\udd27 **Advanced Workflow**\r\n- **Project Management** - Save/load projects (.anno format)\r\n- **Class Management** - Dynamic class creation with custom colors\r\n- **Export Formats** - YOLO11, YOLOv8, compatible\r\n- **Quality Control** - Confidence scoring and validation\r\n\r\n### \ud83d\ude80 **Performance Optimized**\r\n- **Memory Efficient** - Handles large datasets smoothly\r\n- **Real-time Preview** - Instant annotation feedback\r\n- **Keyboard Shortcuts** - Professional workflow acceleration\r\n\r\n## \ud83d\udce6 Installation\r\n\r\n### Quick Install\r\n```bash\r\npip install annotex\r\n```\r\n\r\n## \ud83d\ude80 Quick Start\r\n\r\n### Launch Annotex\r\n```bash\r\n# Start the GUI\r\nannotex\r\n\r\n# Or\r\npython -m annotex.main\r\n\r\n# Load a project\r\nannotex --project my_project.anno\r\n\r\n# Load images from directory\r\nannotex --images /path/to/images\r\n```\r\n\r\n### Basic Workflow\r\n1. **Load Images** - Import your image dataset\r\n2. **Create Classes** - Define annotation classes\r\n3. **Annotate** - Create bounding boxes manually or with AI\r\n4. **Export** - Generate YOLO-format dataset\r\n\r\n## \ud83d\udcda Documentation\r\n\r\n### Keyboard Shortcuts\r\n\r\n| Category | Shortcut | Action |\r\n|----------|----------|--------|\r\n| **Navigation** | `Left Arrow` | Previous image |\r\n| | `Right Arrow` | Next image |\r\n| | `Home` | First image |\r\n| | `End` | Last image |\r\n| | `Ctrl + +` | Zoom in |\r\n| | `Ctrl + -` | Zoom out |\r\n| | `Ctrl + 0` | Zoom fit |\r\n| | `Ctrl + R` | Reset view |\r\n| **File Operations** | `Ctrl + N` | New project |\r\n| | `Ctrl + O` | Open project |\r\n| | `Ctrl + S` | Save current |\r\n| | `Ctrl + Shift + S` | Save project |\r\n| | `Ctrl + I` | Load images |\r\n| | `Ctrl + E` | Export dataset |\r\n| **Editing** | `Ctrl + Z` | Undo |\r\n| | `Ctrl + C` | Copy annotation |\r\n| | `Ctrl + V` | Paste annotation |\r\n| | `Delete` | Delete selected |\r\n| | `Ctrl + Shift + C` | Clear all |\r\n| | `R` | Rectangle tool |\r\n| **Tools & Classes** | `1-9` | Select class by number |\r\n| | `F1` | Show shortcuts |\r\n| | `Middle Click + Drag` | Pan image |\r\n| | `Mouse Wheel` | Zoom in/out |\r\n| | `Right Click` | Context menu |\r\n\r\n## \ud83c\udfa8 Interface Overview\r\n\r\n### Main Components\r\n- **Tools Panel** - Annotation tools and class management\r\n- **Image Viewer** - Zoomable canvas with annotation overlay\r\n- **Image List** - Project image management\r\n- **Export Panel** - Dataset export configuration\r\n\r\n### Advanced Features\r\n- **Semi-Automated Annotation** - Pre-trained AI model integration\r\n- **Batch Processing** - Multi-image operations\r\n- **Quality Metrics** - Annotation statistics and validation\r\n- **Custom Export** - Flexible dataset formats (Currently:only YOLO formats)\r\n\r\n## \ud83e\udd16 AI Integration\r\n\r\n### Supported Models\r\n- **YOLO11** - Proven performance\r\n- **Custom Models** - Load your own trained models\r\n\r\n### Auto-Annotation Workflow\r\n```bash\r\n1. 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