labelme: Image Polygonal Annotation with Python
===============================================
[](https://pypi.python.org/pypi/labelme)
[](https://travis-ci.org/wkentaro/labelme)
[](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.
Requirements
------------
- Ubuntu / macOS / Windows
- Python2 / Python3
- [PyQt4 / 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
# python2
conda create --name=labelme python=2.7
source activate labelme
conda install pyqt
pip install labelme
# python3
conda create --name=labelme python=3.6
source activate labelme
# 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/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 examples/single_image/apc2016_obj3.jpg -O examples/single_image/apc2016_obj3.json
labelme_on_docker examples/semantic_segmentation/data_annotated
```
**Ubuntu**
```bash
# Ubuntu 14.04
sudo apt-get install python-qt4 pyqt4-dev-tools
sudo pip install labelme # python2
sudo apt-get install python3-pyqt5 pyqt5-dev-tools
sudo pip3 install labelme # python3
# Ubuntu 16.04
sudo apt-get install python-pyqt5 pyqt5-dev-tools
sudo pip install labelme # python2
sudo apt-get install python3-pyqt5 pyqt5-dev-tools
sudo pip3 install labelme # python3
```
**macOS**
```bash
# macOS Sierra
brew install pyqt # maybe pyqt5
pip install labelme # both python2/3 should work
```
Usage
-----
Run `labelme --help` for detail.
The annotations are saved as a [JSON](http://www.json.org/) file.
```bash
labelme # just open gui
# single image example
cd examples/single_image
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:
* [Single Image Example](examples/single_image)
* [Semantic Segmentation Example](examples/semantic_segmentation)
* [Instance Segmentation Example](examples/instance_segmentation)
Screencast
----------
Acknowledgement
---------------
This repo is the fork of [mpitid/pylabelme](https://github.com/mpitid/pylabelme),
whose development has already stopped.