LabelImg2 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.
Linux/Ubuntu/Mac requires at least Python 2.6 and has been tested with PyQt 4.8.
Python 2 + Qt4
sudo apt-get install pyqt4-dev-tools sudo pip install lxml python labelImg.py python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
Python 3 + Qt5
sudo apt-get install pyqt5-dev-tools sudo pip3 install lxml python3 labelImg.py python3 labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
Download and setup Python 2.6 or later, PyQt4 and install lxml.
Open cmd and go to the labelImg directory
python labelImg.py python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
Download and install Anaconda (Python 3+)
Open the Anaconda Prompt and go to the labelImg directory
conda install pyqt=5 python labelImg.py python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
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 |
Enter | Select a rect box |
Ctrl++ | Zoom in |
Ctrl-- | Zoom out |
↑→↓← | Keyboard arrows to move selected rect box |
Send a pull request
Citation: Chinakook. LabelImg2. Git code (2018). https://github.com/chinakook/labelImg2
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