manutdzou / labelImg

:metal: LabelImg is a graphical image annotation tool and label object bounding boxes in images

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.

Watch a demo video

Installation

Download prebuilt binaries

• Windows & Linux
• macOS. Binaries for macOS are not yet available. Help would be appreciated. At present, it must be built from source.

Build from source

Linux/Ubuntu/Mac requires at least Python 2.6 and has been tested with PyQt 4.8.

Ubuntu Linux

Python 2 + Qt4

sudo apt-get install pyqt4-dev-tools
sudo pip install lxml
make qt4py2
python labelImg.py
python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]

Python 3 + Qt5

sudo apt-get install pyqt5-dev-tools
sudo pip3 install lxml
make qt5py3
python3 labelImg.py
python3 labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]

macOS ^^^^ Python 2 + Qt4

brew install qt qt4
brew install libxml2
make qt4py2
python labelImg.py
python  labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]

Python 3 + Qt5 (Works on macOS High Sierra)

brew install qt  # will install qt-5.x.x
brew install libxml2
make qt5py3
python labelImg.py
python  labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]

Windows

Download and setup Python 2.6 or later, PyQt4 and install lxml.

Open cmd and go to labelImg directory

pyrcc4 -o resources.py resources.qrc
python labelImg.py
python labelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]

Get from PyPI

pip install labelImg
labelImg
labelImg [IMAGE_PATH] [PRE-DEFINED CLASS FILE]

I tested pip on Ubuntu 14.04 and 16.04. However, I didn't test pip on macOS and Windows

Use Docker

docker run -it \
--user $(id -u) \
-e DISPLAY=unix$DISPLAY \
--workdir=$(pwd) \
--volume="/home/$USER:/home/$USER" \
--volume="/etc/group:/etc/group:ro" \
--volume="/etc/passwd:/etc/passwd:ro" \
--volume="/etc/shadow:/etc/shadow:ro" \
--volume="/etc/sudoers.d:/etc/sudoers.d:ro" \
-v /tmp/.X11-unix:/tmp/.X11-unix \
tzutalin/py2qt4

make qt4py2;./labelImg.py

You can pull the image which has all of the installed and required dependencies. Watch a demo video

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'
5. Click and release left mouse to select a region to annotate the rect box
6. You can use right mouse to drag the rect box to copy or move it

The annotation will be saved to the folder you specify.

You can refer to the below hotkeys to speed up your workflow.

Create pre-defined classes

You can edit the data/predefined_classes.txt to load pre-defined classes

Hotkeys

Ctrl + u	Load all of the images from a directory
Ctrl + r	Change the default annotation target dir
Ctrl + s	Save
Ctrl + d	Copy the current label and rect box
Space	Flag the current image as verified
w	Create a rect box
d	Next image
a	Previous image
del	Delete the selected rect box
Ctrl++	Zoom in
Ctrl--	Zoom out
↑→↓←	Keyboard arrows to move selected rect box

How to contribute

Send a pull request

License

Free software: MIT license

Citation: Tzutalin. LabelImg. Git code (2015). https://github.com/tzutalin/labelImg

Related

1. ImageNet Utils to download image, create a label text for machine learning, etc
2. Use Docker to run labelImg
3. Generating the PASCAL VOC TFRecord files