# LabelImg

[![Build Status](https://travis-ci.org/tzutalin/labelImg.png)](https://travis-ci.org/tzutalin/labelImg)

LabelImg is a graphical image annotation tool.

It is written in Python and uses Qt for its graphical interface.

Annotations are saved as XML files in PASCAL VOC format, the format used by [ImageNet](http://www.image-net.org/).

![](demo/demo3.jpg)

[Watch a demo video by author tzutalin](https://youtu.be/p0nR2YsCY_U)

## Get it

### Download prebuilt binaries

* Windows
 * [Download LabelImg 1.2.1 for Windows](https://raw.githubusercontent.com/tzutalin/LabelImg/gh-pages/windows/windows_v1.2.1.zip)
 * [Download LabelImg 1.2 for Windows](https://raw.githubusercontent.com/tzutalin/LabelImg/gh-pages/windows/windows_v1.2.zip)
* Linux
 * [Download LabelImg 1.2.1 for Linux](https://raw.githubusercontent.com/tzutalin/LabelImg/gh-pages/linux/linux_v1.2.1.zip)
 * [Download LabelImg 1.2 for Linux](https://raw.githubusercontent.com/tzutalin/LabelImg/gh-pages/linux/linux_v1.2.zip)
* OS X
 * Binaries for OS X are not yet available. Help would be appreciated. At present it must be [built from source](#os-x).

### Build from source

Linux/Ubuntu/Mac requires at least [Python 2.6](http://www.python.org/getit/) and has been tested with [PyQt
4.8](http://www.riverbankcomputing.co.uk/software/pyqt/intro).

#### Ubuntu Linux

    sudo apt-get install pyqt4-dev-tools
    sudo pip install lxml
    make all
    ./labelImg.py

#### OS X

    brew install qt qt4
    brew install libxml2
    make all
    ./labelImg.py

#### Windows

Download and setup [Python 2.6 or later](https://www.python.org/downloads/windows/), [PyQt4](https://www.riverbankcomputing.com/software/pyqt/download) and [install lxml](http://lxml.de/installation.html).

Open cmd and go to [labelImg]

    pyrcc4 -o resources.py resources.qrc
    python labelImg.py


## Usage

### Steps

1. Build and launch using the instructions above.
2. Click 'Change default saved annotation folder' in Menu/File
3. Click 'Open Dir'
4. Click 'Create RectBox'

The annotation will be saved to the folder you specify.

### Create pre-defined classes

You can edit the [data/predefined_classes.txt](https://github.com/tzutalin/labelImg/blob/master/data/predefined_classes.txt) to load pre-defined classes

### Hotkeys

|          |                                          |
|----------|------------------------------------------|
| Ctrl + r | Change the default annotation target dir |
| Ctrl + s | Save                                     |
| w        | Create a bounding box                    |
| d        | Next image                               |
| a        | Previous image                           |

### How to contribute
Send a pull request

### License
[License](LICENSE.md)

### Related
1. [ImageNet Utils](https://github.com/tzutalin/ImageNet_Utils) to download image, create a label text for machine learning, etc