library for interacting with QuPath
PAQUO: PAthological QUpath Obsession
paquo's goal is to provide a pythonic interface to important features of
QuPath, and to make creating and working with QuPath projects intuitive for
We strive to make your lives as easy as possible: If
paquo is not pythonic,
unintuitive, slow or if its documentation is confusing, it's a bug in
paquo. Feel free to report any issues or feature requests in the issue
Development happens on github :octocat:
You can find
paquo's documentation at
paquo's stable releases can be installed via
pip install paquo
conda install -c conda-forge paquo
After installing, paquo requires a QuPath installation to run. To get QuPath follow the installation instructions. If you choose the default installation paths paquo should autodetect your QuPath.
Or you can run the following command to download a specific version of QuPath
to a location on your machine. Follow the printed instructions to configure
paquo to use that version. Currently, paquo supports every version of QuPath from
0.2.0 to the most recent. (We even support older
0.2.0-mX versions but no guarantees).
> paquo get_qupath --install-path "/some/path/on/your/machine" 0.4.3 # downloading: https://github.com/qupath/qupath/releases/download/v0.4.3/QuPath-0.4.3-Linux.tar.xz # progress ................... OK # extracting: [...]/QuPath-0.4.3-Linux.tar.xz # available at: /some/path/on/your/machine/QuPath-0.4.3 # # use via environment variable: # $ export PAQUO_QUPATH_DIR=/some/path/on/your/machine/QuPath-0.4.3 # # use via .paquo.toml config file: # qupath_dir="/some/path/on/your/machine/QuPath-0.4.3" /some/path/on/your/machine/QuPath-0.4.3
- Install conda and git
- Clone paquo
git clone https://github.com/bayer-science-for-a-better-life/paquo.git
conda env create -f environment.devenv.yaml
- Activate the environment
conda activate paquo
Note that in this environment
paquo is already installed in development mode,
so go ahead and hack.
- Please follow pep-8 conventions but:
- We allow 120 character long lines (try anyway to keep them short)
- Please use numpy docstrings.
- When contributing code, please try to use Pull Requests.
- tests go hand in hand with modules on
testspackages at the same level. We use
You can setup your IDE to help you adhering to these guidelines.
(Santi is happy to help you setting up pycharm in 5 minutes)
Build with love by Andreas Poehlmann and Santi Villalba from the Machine Learning Research group at Bayer. In collaboration with the Pathology Lab 2 and the Mechanistic and Toxicologic Pathology group.
paquo: copyright 2020 Bayer AG, licensed under GPL-3.0
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.