medical-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.
- DICOM image annotation, includes single-frame and multi-frame images
- Image annotation for polygon, rectangle, circle, line and point. (tutorial)
- Image flag annotation for classification and cleaning.
- Video annotation. (video annotation)
- GUI customization (predefined labels / flags, auto-saving, label validation, etc).
- Exporting VOC-format dataset for semantic/instance segmentation. (semantic segmentation, instance segmentation)
- Exporting COCO-format dataset for instance segmentation. (instance segmentation)
Install standalone executable/app from: https://github.com/hustyichi/medical-labelme/releases
Below shows how to build the standalone executable on macOS, Linux and Windows.
# Setup conda
conda create --name medical-labelme python=3.9
conda activate medical-labelme
# Build the standalone executable
pip install .
pip install 'matplotlib<3.3'
pip install pyinstaller
pyinstaller labelme.spec
dist/labelme --version
Make sure below test passes on your environment.
See .github/workflows/ci.yml
for more detail.
pip install -r requirements-dev.txt
flake8 .
black --line-length 79 --check labelme/
MPLBACKEND='agg' pytest -vsx tests/
This repo is the fork of wkentaro/labelme.