labelimgplusplus 2.0.0a0

labelImg++ is an enhanced graphical image annotation tool with Gallery Mode for browsing and labeling images

A modern, enhanced image annotation tool for machine learning

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labelImg++ is a powerful graphical image annotation tool for creating bounding box labels, designed for machine learning and computer vision projects. Forked from the original LabelImg with significant enhancements.

Features

Core Annotation Features

• Multi-format support: PASCAL VOC (XML), YOLO (TXT), CreateML (JSON)

• Bounding box annotation with drag-and-drop interface

• Auto-save mode for uninterrupted workflow

• Predefined class labels with customizable list

• Verification system to mark completed annotations

New in labelImg++ v2.0.0a

Undo/Redo Support

Full undo/redo for all annotation actions. Press Ctrl+Z to undo and Ctrl+Y to redo. Never lose your work again!

Gallery Mode with Annotation Preview

Visual thumbnail gallery showing all images with bounding box overlays directly on thumbnails.

• Colored borders indicate status: Gray (no labels), Blue (has labels), Green (verified)

• Bounding boxes visible on thumbnails for quick review

• Adjustable thumbnail size (40px - 300px)

• Press Ctrl+G to toggle gallery mode

Modern UI with Feather Icons

Clean, modern interface with beautiful Feather icons and improved visual design.

Responsive DPI Scaling

Icons and UI elements scale properly on high-DPI displays (4K, Retina).

Expandable Toolbar

Click the chevron at the bottom of the toolbar to expand/collapse and show full button labels.

Consolidated File Menu

Open File, Open Dir, and Change Save Dir combined into a single dropdown for cleaner toolbar.

Brightness Adjustment

Adjust image brightness on-the-fly to better see annotations on dark or light images.

Installation

From PyPI (Recommended)

pip3 install labelImgPlusPlus
labelImgPlusPlus

With a specific image or directory:

labelImgPlusPlus [IMAGE_PATH] [PRE-DEFINED CLASS FILE] [SAVE_DIR]

Build from Source

Ubuntu/Linux:

sudo apt-get install pyqt5-dev-tools
pip3 install -r requirements/requirements-linux-python3.txt
make qt5py3
python3 labelImg.py

macOS:

pip3 install pyqt5 lxml
make qt5py3
python3 labelImg.py

Windows:

pip install pyqt5 lxml
pyrcc5 -o libs/resources.py resources.qrc
python labelImg.py

Quick Start

1. Open images: Click the file dropdown button or press Ctrl+U to load a directory

2. Create annotations: Press W or click Create RectBox, then drag to draw

3. Label objects: Select a class from the popup dialog

4. Save: Press Ctrl+S to save annotations

5. Navigate: Use D (next) and A (previous) to move between images

6. Review: Press Ctrl+G for gallery mode to review all annotations

Supported Annotation Formats

Format	Extension	Description
PASCAL VOC	.xml	ImageNet format, absolute coordinates
YOLO	.txt	Normalized coordinates (0-1), with classes.txt for class names
CreateML	.json	Apple’s ML format for iOS/macOS

Keyboard Shortcuts

File Operations

Ctrl + O	Open file
Ctrl + U	Open directory
Ctrl + R	Change save directory
Ctrl + S	Save current annotation
Ctrl + Shift + S	Save as

Navigation

D	Next image
A	Previous image
Ctrl + G	Toggle Gallery Mode

Annotation

W	Create bounding box
Ctrl + Z	Undo
Ctrl + Y	Redo
Ctrl + D	Duplicate selected box
Del	Delete selected box
Space	Mark image as verified
Arrow keys	Move selected box

View

Ctrl + +	Zoom in
Ctrl + -	Zoom out
Ctrl + F	Fit window
Ctrl + Shift + F	Fit width

Configuration

Predefined Classes

Edit data/predefined_classes.txt to customize the label options:

dog
cat
person
car
bicycle

Reset Settings

If you encounter issues, reset the settings:

rm ~/.labelImgSettings.pkl

Or use Menu > File > Reset All

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the repository

2. Create your feature branch (git checkout -b feature/amazing-feature)

3. Commit your changes (git commit -m 'Add amazing feature')

4. Push to the branch (git push origin feature/amazing-feature)

5. Open a Pull Request

License

MIT License

Based on LabelImg by Tzutalin.

Acknowledgments

• Original LabelImg by Tzutalin

• Feather Icons for modern iconography

• All contributors and users of labelImg++