A modern, web-based tool for creating and editing YOLO format image annotations with an intuitive interface. All data processing happens in your browser - no images or annotations are uploaded to any server.
Visit the live demo at https://yololabellingtool.com
Try out the tool's features directly in your browser without installing anything. The demo includes sample images to help you get started.
- 🎨 Interactive bounding box creation and editing
- 📁 Multi-image support with responsive thumbnail navigation
- 🎯 Robust class management with color-coded labels
- 💾 Export to YOLO format with classes.txt
- 🔄 Import existing YOLO annotations
- 🎨 Customizable class colors using Tailwind CSS color palette
- 🔒 Privacy-focused: All data stays in your browser
- 📱 [WIP]Responsive design for various screen sizes
- Clone the repository
- Install dependencies:
npm install- Start the development server:
npm run dev- Open your browser and navigate to
http://localhost:3000
- Click "Upload Images & Annotations" to select your images
- Use the "Draw Box" tool to create bounding boxes
- Select a class from the Classes panel
- Draw boxes around objects in your images
- Use the Edit mode to adjust box positions and sizes
- Navigate between images using the thumbnail panel or Previous/Next buttons
- Click "Edit" in the Classes panel
- Add new classes using the "Add Class" button
- Customize class names and colors
- Click "Done" to save changes
- Click "Export Dataset" to download your annotations
- The export will include:
- All images
- YOLO format annotation files (.txt)
- classes.txt file
Each annotation file contains one line per object in the format:
<class_id> <x_center> <y_center> <width> <height>
All values are normalized between 0 and 1.
Contains one class name per line, where the line number corresponds to the class ID in the annotation files.
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.