Annotation Tool for Object Segmentation.
Project description
labelme: Image Annotation Tool with Python
==========================================
[![PyPI Version](https://img.shields.io/pypi/v/labelme.svg)](https://pypi.python.org/pypi/labelme)
[![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 <http://labelme.csail.mit.edu>.
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
----------
<img src="https://github.com/wkentaro/labelme/raw/master/static/screencast.gif" width="70%"/>
==========================================
[![PyPI Version](https://img.shields.io/pypi/v/labelme.svg)](https://pypi.python.org/pypi/labelme)
[![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 <http://labelme.csail.mit.edu>.
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
----------
<img src="https://github.com/wkentaro/labelme/raw/master/static/screencast.gif" width="70%"/>
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