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%!s(int64=8) %!d(string=hai) anos | |
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docker | %!s(int64=8) %!d(string=hai) anos | |
labelme | %!s(int64=8) %!d(string=hai) anos | |
scripts | %!s(int64=8) %!d(string=hai) anos | |
static | %!s(int64=9) %!d(string=hai) anos | |
tests | %!s(int64=8) %!d(string=hai) anos | |
.gitignore | %!s(int64=9) %!d(string=hai) anos | |
.travis.yml | %!s(int64=8) %!d(string=hai) anos | |
LICENSE | %!s(int64=9) %!d(string=hai) anos | |
MANIFEST.in | %!s(int64=9) %!d(string=hai) anos | |
README.md | %!s(int64=8) %!d(string=hai) anos | |
setup.py | %!s(int64=8) %!d(string=hai) anos |
Labelme is a graphical image annotation tool inspired by http://labelme.csail.mit.edu.
It is written in Python and uses Qt for its graphical interface.
On Ubuntu:
sudo apt-get install python-qt4 pyqt4-dev-tools
sudo pip install labelme
On OS X:
brew install qt qt4
pip install labelme
On macOS Sierra:
brew install pyqt5
pip install git+https://github.com/wkentaro/labelme.git@pyqt5
Annotation
Run labelme --help
for detail.
labelme # Open GUI
labelme _static/IMG_6319.jpg # Specify file
labelme _static/IMG_6319.jpg -O _static/IMG_6319.json # Close window after the save
If you are installed docker, you can run:
# Maybe you need http://sourabhbajaj.com/blog/2017/02/07/gui-applications-docker-mac/ on macOS
labelme_on_docker _static/IMG_6319.jpg -O _static/IMG_6319.json
The annotations are saved as a JSON file. The file includes the image itself.
Visualization
To view the json file quickly, you can use utility script:
labelme_draw_json _static/IMG_6319.json
Convert to Dataset
To convert the json to set of image and label, you can run following:
labelme_json_to_dataset _static/IMG_6319.json