LabelImg
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 byImageNet.
- Windows & Linux
- macOS. Binaries for macOS are not yet available. Help would be appreciated. At present, it must be built from source.
Linux/Ubuntu/Mac requires at least Python 2.6and has been tested with PyQt 4.8.
Python 2 + Qt4
sudo apt-getinstall pyqt4-dev-tools
sudo pip installlxml
make qt4py2
python labelImg.py
python labelImg.py[IMAGE_PATH] [PRE-DEFINED CLASS FILE]
Python 3 + Qt5
sudo apt-getinstall pyqt5-dev-tools
sudo pip3 installlxml
make qt5py3
python3labelImg.py
python3labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
Python 2 + Qt4
brew install qtqt4
brew installlibxml2
make qt4py2
python labelImg.py
python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASSFILE]
Download and setup Python 2.6 orlater, PyQt4and install lxml.
Open cmd and go to labelImgdirectory
pyrcc4 -oresources.py resources.qrc
python labelImg.py
python labelImg.py[IMAGE_PATH] [PRE-DEFINED CLASS FILE]
pip installlabelImg
labelImg
labelImg[IMAGE_PATH] [PRE-DEFINED CLASS FILE]
I tested pip on Ubuntu 14.04 and 16.04. However, I didn't test pip on macOSand Windows
docker run -it \
--user $(id -u) \
-eDISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER"\
--volume="/etc/group:/etc/group:ro"\
--volume="/etc/passwd:/etc/passwd:ro"\
--volume="/etc/shadow:/etc/shadow:ro"\
--volume="/etc/sudoers.d:/etc/sudoers.d:ro"\
-v /tmp/.X11-unix:/tmp/.X11-unix\
tzutalin/py2qt4
makeqt4py2;./labelImg.py
You can pull the image which has all of the installed and requireddependencies. Watch a demo video
- 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.txtto 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 |
↑→↓← |
Keyboard arrows to move selected rect box |
Send a pull request
Citation: Tzutalin. LabelImg. Git code (2015). https://github.com/tzutalin/labelImg
- ImageNet Utils to download image, create a label text for machine learning, etc
- Use Docker to run labelImg
- Generating the PASCAL VOC TFRecord files