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用于制作VOC格式数据集的框图工具 2016.11.7

LabelImg

Build Status

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

Demo video

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 and lxml:

$ sudo apt-get install pyqt4-dev-tools
$ sudo pip install lxml
$ make all
$ ./labelImg.py

Mac requires "$ brew install libxml2" when installing lxml

  • Windows

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

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 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

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 specify

Create pre-defined classes

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

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

License

License