YOLO Label VS - andaoai/yolo-label-vs GitHub Wiki
YOLO Label VS - Plugin Wiki
Introduction
YOLO Label VS is an extension designed for Visual Studio Code that enables quick browsing and editing of YOLO dataset annotations. Through YAML configuration files, it allows you to efficiently view and modify YOLO-formatted labels directly within VS Code, simplifying the management of computer vision datasets.
Key Features
Dataset Browsing
- Quick View: Instantly load and display YOLO-annotated images through YAML configuration files
- Smooth Navigation: Quickly move forward or backward through image collections using shortcuts (A/D)
- Image Search: Rapidly locate specific images within your dataset
Annotation Management
- Real-time Editing: Modify existing annotations directly in VS Code
- Visual Preview: Intuitively display bounding boxes, segmentation areas, and label information
- Multi-mode Support: Support for both Box and Segmentation annotation modes
User Interface
- Interactive Controls: Various function buttons including navigation, mode selector, label display controls, etc.
- Zoom and Pan: Support for image zooming and panning for detailed inspection
- Label List: Display all label information for the current image
Technical Features
- Lightweight Design: Fast response, optimized for handling large datasets
- YAML Integration: Direct support for YAML configuration files
- React Technology Stack: Modern user interface built with React
- Native VS Code Integration: Seamlessly integrates into the VS Code development environment
System Requirements
- Visual Studio Code 1.85.0 or higher
- Image files in your workspace
- YAML configuration files for YOLO format annotations
Installation
- Open VS Code
- Press
Ctrl+P
to open the Quick Open dialog - Type
ext install andaoai.yolo-labeling-vs
- Press Enter to install
Alternatively, install directly from the VS Code Marketplace.
Usage Guide
Basic Operations
- Open a folder containing YAML configuration files and corresponding images
- Right-click on a YAML file in the explorer
- Select "Open YOLO Labeling Panel"
- Use the panel toolbar or shortcuts to browse and edit annotations
Keyboard Shortcuts
Global Shortcuts
Ctrl+Y
: Open YOLO Labeling Panel
In Labeling Panel
D
: Next imageA
: Previous imageCtrl+S
: Save labelsCtrl+Wheel
: Zoom in/out centered on mouse positionAlt+Drag
: Pan the image when zoomed inWheel
: Scroll vertically when zoomed inShift+Wheel
: Scroll horizontally when zoomed inRight-click
: Cancel polygon drawing (in segmentation mode)
Search Functionality
Down Arrow
: Move down through search resultsUp Arrow
: Move up through search resultsEnter
: Select the highlighted search resultEscape
: Close search results panel
Annotation Modes
Box Mode
- Suitable for object detection tasks
- Support for adding, editing, and deleting rectangular bounding boxes
Segmentation Mode
- Suitable for instance segmentation tasks
- Support for adding, editing, and deleting polygon areas
Version History
0.0.4 (2024-05-10)
- Simplified keyboard shortcuts for better usability
- Changed main shortcut from
Ctrl+Shift+Y
toCtrl+Y
for easier access - Removed
Ctrl+Right
andCtrl+Left
shortcuts - Improved UI by hiding scrollbar in label list
- Reduced extension package size
0.0.3 (2024-05-01)
- Added demo GIF showing extension functionality
- Added Chinese documentation
- Provided detailed packaging and publishing guides in both English and Chinese
- Improved documentation organization
0.0.1 (2024-04-30)
- Initial release
- Basic image labeling functionality
- YOLO format support
- Keyboard shortcuts support
- Configuration file support
Frequently Asked Questions
Q: What types of YOLO annotation formats does this plugin support?
A: The plugin supports standard YOLO format annotations, including both bounding box (bbox) and segmentation annotations.
Q: Can I process multiple datasets in the same workspace?
A: Yes, you can process different datasets by opening different YAML configuration files.
Q: How do I report issues or request new features?
A: Please submit issues or feature requests on our GitHub repository.
Contribution and Support
We welcome community contributions! If you're interested in improving YOLO Label VS, please feel free to submit a Pull Request.
If you encounter any problems or have any suggestions, please visit our GitHub repository to submit an issue.
License
This project is licensed under the MIT License - see the LICENSE file for details.