LabelImg is a graphical image annotation tool.

It is written in Python and uses Qt for its graphical interface.

The annotation file will be saved as an XML file. The annotation format is PASCAL VOC format, and the format is the same as ImageNet

Linux/Ubuntu/Mac requires at least Python 2.6 and has been tested with PyQt 4.8.

In order to build the resource and assets, you need to install pyqt4-dev-tools and lxml:

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

Need to download and setup Python 2.6 or later and PyQt4. Also, you need to install lxml.

Open cmd and go to [labelImg]

pyrcc4 -o resources.py resources.qrc
python labelImg.py

http://tzutalin.github.io/labelImg/. However, there are only prebuilt binaries for Windows and Linux because I don't have Mac OS to do that. If someone can help me to write a script to build binary for Mac OS, I will appreciate that.

After cloning the code, you should run $ make all to generate the resource file.

You can then start annotating by running $ ./labelImg.py. For usage instructions you can see Here

At the moment annotations are saved as an XML file. The format is PASCAL VOC format, and the format is the same as ImageNet

You can also see ImageNet Utils to download image, create a label text for machine learning, etc

• Build and launch: $ make all; python labelImg.py

• Click 'Change default saved annotation folder' in Menu/File

• Click 'Open Dir'

• Click 'Create RectBox'

The annotation will be saved to the folder you specify

You can edit the data/predefined_classes.txt to load pre-defined classes

• Ctrl + r : Change the defult target dir which saving annotation files

• Ctrl + s : Save

• w : Create a bounding box

• d : Next image

• a : Previous image

Send a pull request

License