LabelImg is a graphical image annotation tool.
It is written in Python and uses Qt for its graphical interface.
Annotations are saved as XML files in PASCAL VOC format, the format used by ImageNet.
Watch a demo video by author tzutalin
- Windows
- Download LabelImg 1.2.2 for Windows
- Download LabelImg 1.2.1 for Windows
- Download LabelImg 1.2 for Windows
- Linux
- Download LabelImg 1.2.2 for Linux
- Download LabelImg 1.2.1 for Linux
- Download LabelImg 1.2 for Linux
- OS X
- Binaries for OS X are not yet available. Help would be appreciated. At present it must be built from source.
Linux/Ubuntu/Mac requires at least Python 2.6 and has been tested with PyQt 4.8.
sudo apt-get install pyqt4-dev-tools
sudo pip install lxml
make all
./labelImg.py
brew install qt qt4
brew install libxml2
make all
./labelImg.py
Download and setup Python 2.6 or later, PyQt4 and install lxml.
Open cmd and go to [labelImg]
pyrcc4 -o resources.py resources.qrc
python labelImg.py
- Build and launch using the instructions above.
- Click 'Change default saved annotation folder' in Menu/File
- Click 'Open Dir'
- Click 'Create RectBox'
- Click and release left mouse to select a region to annotate the rect box
- You can use right mouse to drag the rect box to copy or move it
The annotation will be saved to the folder you specify.
You can refer to the below hotkeys to speed up your workflow.
You can edit the data/predefined_classes.txt to load pre-defined classes
Ctrl + u | Load all of the images from a directory |
Ctrl + r | Change the default annotation target dir |
Ctrl + s | Save |
Ctrl + d | Copy the current label and rect box |
Space | Flag the current image as verified |
w | Create a rect box |
d | Next image |
a | Previous image |
del | Delete the selected rect box |
Ctrl++ | Zoom in |
Ctrl-- | Zoom out |
Send a pull request
- ImageNet Utils to download image, create a label text for machine learning, etc