Labelme-使用Python的图像多边形批注(多边形、矩形、圆、直线、点和图像级标志批注)

# python2
conda create --name=labelme python=2.7
source activate labelme
# conda install -c conda-forge pyside2
conda install pyqt
pip install labelme
# if you'd like to use the latest version. run below: # pip install git+https://github.com/wkentaro/labelme.git # python3
conda create --name=labelme python=3.6
source activate labelme
# conda install -c conda-forge pyside2 # conda install pyqt # pip install pyqt5  # pyqt5 can be installed via pip on python3
pip install labelme
# or you can install everything by conda command # conda install labelme -c conda-forge

# on macOS
socat TCP-LISTEN:6000,reuseaddr,fork UNIX-CLIENT:\"$DISPLAY\" &
docker run -it -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=docker.for.mac.host.internal:0 -v $(pwd):/root/workdir wkentaro/labelme

# on Linux
xhost +
docker run -it -v /tmp/.X11-unix:/tmp/.X11-unix -e DISPLAY=:0 -v $(pwd):/root/workdir wkentaro/labelme

# Ubuntu 14.04 / Ubuntu 16.04 # Python2 # sudo apt-get install python-qt4  # PyQt4
sudo apt-get install python-pyqt5  # PyQt5
sudo pip install labelme
# Python3
sudo apt-get install python3-pyqt5  # PyQt5
sudo pip3 install labelme

# or install standalone executable from: # https://github.com/wkentaro/labelme/releases

sudo apt-get install labelme

# macOS Sierra
brew install pyqt  # maybe pyqt5
pip install labelme  # both python2/3 should work # or install standalone executable/app from: # https://github.com/wkentaro/labelme/releases

# python3
conda create --name=labelme python=3.6
conda activate labelme
pip install labelme

labelme  # just open gui # tutorial (single image example) cd examples/tutorial
labelme apc2016_obj3.jpg  # specify image file
labelme apc2016_obj3.jpg -O apc2016_obj3.json  # close window after the save
labelme apc2016_obj3.jpg --nodata  # not include image data but relative image path in JSON file
labelme apc2016_obj3.jpg \
  --labels highland_6539_self_stick_notes,mead_index_cards,kong_air_dog_squeakair_tennis_ball  # specify label list # semantic segmentation example cd examples/semantic_segmentation
labelme data_annotated/  # Open directory to annotate all images in it
labelme data_annotated/ --labels labels.txt  # specify label list with a file

pip install hacking pytest pytest-qt
flake8 .
pytest -v tests

git clone https://github.com/wkentaro/labelme.git
cd labelme

# Install anaconda3 and labelme
curl -L https://github.com/wkentaro/dotfiles/raw/master/local/bin/install_anaconda3.sh | bash -s . source .anaconda3/bin/activate
pip install -e .

# Setup conda
conda create --name labelme python==3.6.0
conda activate labelme

# Build the standalone executable
pip install .
pip install pyinstaller
pyinstaller labelme.spec
dist/labelme --version

pip install black hacking pytest pytest-qt

flake8 .
black --line-length 79 --check labelme/
MPLBACKEND='agg' pytest tests/ -m 'not gpu'

@misc{labelme2016,
  author =       {Kentaro Wada},
  title =        {{labelme: Image Polygonal Annotation with Python}},
  howpublished = {\url{https://github.com/wkentaro/labelme}},
  year =         {2016}
}