labelme: Image Polygonal Annotation with Python
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.
Features
- Image polygon annotation for segmentation. (tutorial)
- Image flag annotation for classification or cleaning. (#166)
- Video annotation. (video annotation)
- GUI customization (predefined labels / flags, auto-saving, label validation, etc). (#144)
- Exporting VOC-like dataset for semantic/instance segmentation. (semantic segmentation, instance segmentation)
Requirements
- Ubuntu / macOS / Windows
- Python2 / Python3
- PyQt4 / PyQt5 / PySide2
Installation
There are options:
- Platform agonistic installation: Anaconda, Docker
- Platform specific installation: Ubuntu, macOS, Windows
Anaconda
You need install Anaconda, then run below:
# 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
Docker
You need install docker, then run below:
wget https://raw.githubusercontent.com/wkentaro/labelme/master/labelme/cli/on_docker.py -O labelme_on_docker
chmod u+x labelme_on_docker
# Maybe you need http://sourabhbajaj.com/blog/2017/02/07/gui-applications-docker-mac/ on macOS
./labelme_on_docker examples/tutorial/apc2016_obj3.jpg -O examples/tutorial/apc2016_obj3.json
./labelme_on_docker examples/semantic_segmentation/data_annotated
Ubuntu
# 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
macOS
# macOS Sierra
brew install pyqt # maybe pyqt5
pip install labelme # both python2/3 should work
# or install standalone executable / app
brew install wkentaro/labelme/labelme
brew cask install wkentaro/labelme/labelme
Windows
Firstly, follow instruction in Anaconda.
# Pillow 5 causes dll load error on Windows.
# https://github.com/wkentaro/labelme/pull/174
conda install pillow=4.0.0
Usage
Run labelme --help
for detail.
The annotations are saved as a JSON file.
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
For more advanced usage, please refer to the examples:
- Tutorial (Single Image Example)
- Semantic Segmentation Example
- Instance Segmentation Example
- Video Annotation Example
FAQ
- How to convert JSON file to numpy array? See examples/tutorial.
- How to load label PNG file? See examples/tutorial.
- How to get annotations for semantic segmentation? See examples/semantic_segmentation.
- How to get annotations for instance segmentation? See examples/instance_segmentation.
Screencast
Testing
pip install hacking pytest pytest-qt
flake8 .
pytest -v tests
How to build standalone executable
Below shows how to build the standalone executable on macOS, Linux and Windows.
Also, there are pre-built executables in
the release section.
# Setup conda
conda create --name labelme python=3.6
conda activate labelme
# Build the standalone executable
pip install .
pip install pyinstaller
pyinstaller labelme.spec
dist/labelme --version
Acknowledgement
This repo is the fork of mpitid/pylabelme, whose development has already stopped.