conda create -n label python=3.7 -y conda activate label pip install pyqt5 python roLabelImg.py
roLabelImg is a graphical image annotation tool can label ROTATED rectangle regions, which is rewrite from 'labelImg'.
The original version 'labelImg''s link is here<https://github.com/tzutalin/labelImg>.
It is written in Python and uses Qt for its graphical interface.
Watch a demo by author cgvict
Annotations are saved as XML files almost like PASCAL VOC format, the format used by ImageNet.
<annotation verified="yes">
<folder>hsrc</folder>
<filename>100000001</filename>
<path>/Users/haoyou/Library/Mobile Documents/com~apple~CloudDocs/OneDrive/hsrc/100000001.bmp</path>
<source>
<database>Unknown</database>
</source>
<size>
<width>1166</width>
<height>753</height>
<depth>3</depth>
</size>
<segmented>0</segmented>
<object>
<type>bndbox</type>
<name>ship</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<bndbox>
<xmin>178</xmin>
<ymin>246</ymin>
<xmax>974</xmax>
<ymax>504</ymax>
</bndbox>
</object>
<object>
<type>robndbox</type>
<name>ship</name>
<pose>Unspecified</pose>
<truncated>0</truncated>
<difficult>0</difficult>
<robndbox>
<cx>580.7887</cx>
<cy>343.2913</cy>
<w>775.0449</w>
<h>170.2159</h>
<angle>2.889813</angle>
</robndbox>
</object>
</annotation>
- Windows & Linux
- OS X. Binaries for OS X are not yet available. Help would be appreciated. At present, it must be built from source.
Linux/Ubuntu/Mac requires at least Python 2.6 and has been tested with PyQt 4.8.
sudo apt-get install pyqt4-dev-tools sudo pip install lxml make all ./roLabelImg.py ./roLabelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
brew install qt qt4 brew install libxml2 make all ./roLabelImg.py ./roLabelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
Download and setup Python 2.6 or later, PyQt4 and install lxml.
Open cmd and go to roLabelImg directory
pyrcc4 -o resources.py resources.qrc python roLabelImg.py python roLabelImg.py [IMAGE_PATH] [PRE-DEFINED CLASS FILE]
docker pull tzutalin/py2qt4 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
You can pull the image which has all of the installed and required dependencies.
- Build and launch using the instructions above.
- Click 'Change default saved annotation folder' in Menu/File
- Click 'Open Dir'
- Click 'Create RectBox'
- Click and release left mouse to select a region to annotate the rect box
- 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.
You can edit the data/predefined_classes.txt to load pre-defined classes
| 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 |
| e | Create a Rotated rect box |
| d | Next image |
| a | Previous image |
| r | Hidden/Show Rotated Rect boxes |
| n | Hidden/Show Normal Rect boxes |
| del | Delete the selected rect box |
| Ctrl++ | Zoom in |
| Ctrl-- | Zoom out |
| ↑→↓← | Keyboard arrows to move selected rect box |
| zxcv | Keyboard to rotate selected rect box |
Send a pull request
- ImageNet Utils to download image, create a label text for machine learning, etc
- Docker hub to run it