LabelImg

LabelImg is a graphical image annotation tool. The source mainly comes from labelme.

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

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

Dependencies

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:

$ sudo apt-get install pyqt4-dev-tools

$ make all

$ ./labelImg.py

Windows

Need to download and setup Python 2.6 or later and PyQt4. You can also try to download the whole neccessary executable files from my drive and install them.

Open cmd and go to $labelImg,

$ pyrcc4 -o resources.py resources.qrc

$ python labelImg.py

Usage

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 a 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

Create pre-defined classes

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

General steps from scratch

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 specifiy

Hotkeys

Ctrl + r : Change the defult target dir which saving annotation files
Ctrl + n : Create a bounding box
Ctrl + s : Save
n : Next image
p : Previous image

How to contribute

Send a pull request and help me write setup.py to build executable file for all platforms.