labelme: Image Annotation Tool with Python ========================================== [![PyPI Version](https://img.shields.io/pypi/v/labelme.svg)](https://pypi.python.org/pypi/labelme) [![Travis Build Status](https://travis-ci.org/wkentaro/labelme.svg?branch=master)](https://travis-ci.org/wkentaro/labelme) [![Appveyor Build status](https://ci.appveyor.com/api/projects/status/epxf9b6c47cw373y/branch/master?svg=true)](https://ci.appveyor.com/project/wkentaro/labelme/branch/master) [![Docker Build Status](https://img.shields.io/docker/build/wkentaro/labelme.svg)](https://hub.docker.com/r/wkentaro/labelme) Labelme is a graphical image annotation tool inspired by . It is written in Python and uses Qt for its graphical interface. Dependencies ------------ - [PyQt4 or PyQt5](http://www.riverbankcomputing.co.uk/software/pyqt/intro) Installation ------------ There are options: - Platform agonistic installation: Anaconda, Docker - Platform specific installation: Ubuntu, macOS **Anaconda** You need install [Anaconda](https://www.continuum.io/downloads), then run below: ```bash conda create --name=labelme python=2.7 source activate labelme conda install pyqt pip install labelme ``` **Docker** You need install [docker](https://www.docker.com), then run below: ```bash wget https://raw.githubusercontent.com/wkentaro/labelme/master/scripts/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 static/apc2016_obj3.jpg -O static/apc2016_obj3.json ``` **Ubuntu** ```bash sudo apt-get install python-qt4 pyqt4-dev-tools sudo pip install labelme ``` **macOS** ```bash brew install qt qt4 || brew install pyqt # qt4 is deprecated pip install labelme ``` Usage ----- **Annotation** Run `labelme --help` for detail. ```bash labelme # Open GUI labelme static/apc2016_obj3.jpg # Specify file labelme static/apc2016_obj3.jpg -O static/apc2016_obj3.json # Close window after the save ``` The annotations are saved as a [JSON](http://www.json.org/) file. The file includes the image itself. **Visualization** To view the json file quickly, you can use utility script: ```bash labelme_draw_json static/apc2016_obj3.json ``` **Convert to Dataset** To convert the json to set of image and label, you can run following: ```bash labelme_json_to_dataset static/apc2016_obj3.json ``` Sample ------ - [Original Image](https://github.com/wkentaro/labelme/blob/master/static/apc2016_obj3.jpg) - [Screenshot](https://github.com/wkentaro/labelme/blob/master/static/apc2016_obj3_screenshot.jpg) - [Generated Json File](https://github.com/wkentaro/labelme/blob/master/static/apc2016_obj3.json) - [Visualized Json File](https://github.com/wkentaro/labelme/blob/master/static/apc2016_obj3_draw_json.jpg) Screencast ----------