# labelme: Image/Video Polygonal Annotation with Python [![PyPI Version](https://img.shields.io/pypi/v/labelme.svg)](https://pypi.python.org/pypi/labelme) [![Python Versions](https://img.shields.io/pypi/pyversions/labelme.svg)](https://pypi.org/project/labelme) [![Travis Build Status](https://travis-ci.org/wkentaro/labelme.svg?branch=master)](https://travis-ci.org/wkentaro/labelme) [![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. Fig 1. Example of annotations for instance segmentation. ## Features - [x] Polygonal annotation - [x] Predefined labels ([#76](https://github.com/wkentaro/labelme/pull/76)) - [x] Auto save mode ([#138](https://github.com/wkentaro/labelme/pull/138)) - [x] Support custom json keys ([#140](https://github.com/wkentaro/labelme/pull/140)) - [x] Undo by Ctrl-Z ([#112](https://github.com/wkentaro/labelme/pull/112), [#143](https://github.com/wkentaro/labelme/pull/143)) - [x] Customize by config file ([#144](https://github.com/wkentaro/labelme/pull/144)) - [x] VOC dataset export ([semantic segmentation](https://github.com/wkentaro/labelme/blob/master/examples/semantic_segmentation), [instance segmentation](https://github.com/wkentaro/labelme/blob/master/examples/instance_segmentation)) - [x] Image level flag annotation ([#166](https://github.com/wkentaro/labelme/pull/166)) - [x] Video annotation ([video annotation](https://github.com/wkentaro/labelme/blob/master/examples/video_annotation)) ## Requirements - Ubuntu / macOS / Windows - Python2 / Python3 - [PyQt4 / PyQt5](http://www.riverbankcomputing.co.uk/software/pyqt/intro) / [PySide2](https://wiki.qt.io/PySide2_GettingStarted) ## Installation There are options: - Platform agonistic installation: [Anaconda](#anaconda), [Docker](#docker) - Platform specific installation: [Ubuntu](#ubuntu), [macOS](#macos), [Windows](#windows) ### Anaconda You need install [Anaconda](https://www.continuum.io/downloads), then run below: ```bash # 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](https://www.docker.com), then run below: ```bash 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 ```bash # 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 ```bash # 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](#anaconda). ```bash # 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](http://www.json.org/) file. ```bash 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)](https://github.com/wkentaro/labelme/blob/master/examples/tutorial) * [Semantic Segmentation Example](https://github.com/wkentaro/labelme/blob/master/examples/semantic_segmentation) * [Instance Segmentation Example](https://github.com/wkentaro/labelme/blob/master/examples/instance_segmentation) * [Video Annotation Example](https://github.com/wkentaro/labelme/blob/master/examples/video_annotation) ## FAQ - **How to convert JSON file to numpy array?** See [examples/tutorial](https://github.com/wkentaro/labelme/blob/master/examples/tutorial#convert-to-dataset). - **How to load label PNG file?** See [examples/tutorial](https://github.com/wkentaro/labelme/blob/master/examples/tutorial#how-to-load-label-png-file). - **How to get annotations for semantic segmentation?** See [examples/semantic_segmentation](https://github.com/wkentaro/labelme/blob/master/examples/semantic_segmentation). - **How to get annotations for instance segmentation?** See [examples/instance_segmentation](https://github.com/wkentaro/labelme/blob/master/examples/instance_segmentation). ## Screencast ## Testing ```bash 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](https://github.com/wkentaro/labelme/releases). ```bash # 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](https://github.com/mpitid/pylabelme), whose development has already stopped.