{"id":13708560,"url":"https://github.com/nki-ai/dlup","last_synced_at":"2026-01-31T16:10:24.797Z","repository":{"id":38392570,"uuid":"369830396","full_name":"NKI-AI/dlup","owner":"NKI-AI","description":"Dlup are the Deep Learning Utilities for Pathology developed at the Netherlands Cancer 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Deep Learning Utilities for Pathology\n\n[![pypi](https://img.shields.io/pypi/v/dlup.svg)](https://pypi.python.org/pypi/dlup)\n[![Tox](https://github.com/NKI-AI/dlup/actions/workflows/tox.yml/badge.svg)](https://github.com/NKI-AI/dlup/actions/workflows/tox.yml)\n[![mypy](https://github.com/NKI-AI/dlup/actions/workflows/mypy.yml/badge.svg)](https://github.com/NKI-AI/dlup/actions/workflows/mypy.yml)\n[![Pylint](https://github.com/NKI-AI/dlup/actions/workflows/pylint.yml/badge.svg)](https://github.com/NKI-AI/dlup/actions/workflows/pylint.yml)\n[![Black](https://github.com/NKI-AI/dlup/actions/workflows/black.yml/badge.svg)](https://github.com/NKI-AI/dlup/actions/workflows/black.yml)\n[![codecov](https://codecov.io/gh/NKI-AI/dlup/branch/main/graph/badge.svg?token=OIJ7F9G7OO)](https://codecov.io/gh/NKI-AI/dlup)\n\nDlup offers a set of utilities to ease the process of running Deep Learning algorithms on\nWhole Slide Images.\n\n## Features\n\n- Read whole-slide images at any arbitrary resolution by seamlessly interpolating between the pyramidal levels\n- Supports multiple backends, including [OpenSlide](https://openslide.org/) and [fastslide](https://github.com/NKI-AI/fastslide.git), with the possibility to add custom backends\n- Dataset classes to handle whole-slide images in a tile-by-tile manner compatible with pytorch\n- Annotation classes which can load GeoJSON, [V7 Darwin](https://www.v7labs.com/), [HALO](https://indicalab.com/halo/) and [ASAP](https://computationalpathologygroup.github.io/ASAP/) formats and read parts of it (e.g. a tile)\n- Transforms to handle annotations per tile, resulting, together with the dataset classes a dataset consisting of tiles of whole-slide images with corresponding masks as targets, readily useable with a pytorch dataloader\n- Command-line utilities to report on the metadata of WSIs, and convert masks to polygons\n\nCheck the [full documentation](https://docs.aiforoncology.nl/dlup) for more details on how to use dlup.\n\n## Quickstart\n\nThe package can be installed using `python -m pip install dlup`. Preferably use `uv` and `uv pip install dlup`.\n\nIf you wish to install from source, you can run `uv pip install .` You will need the boost package to build from source.\n\n## Used by\n\n- [ahcore](https://github.com/NKI-AI/ahcore.git): a pytorch lightning based-library for computational pathology\n\n## Citing DLUP\n\nIf you use DLUP in your research, please use the following BiBTeX entry:\n\n```\n@software{dlup,\n  author = {Teuwen, J., Romor, L., Pai, A., Schirris, Y., Marcus, E.},\n  month = {8},\n  title = {{DLUP: Deep Learning Utilities for Pathology}},\n  url = {https://github.com/NKI-AI/dlup},\n  version = {0.8.0},\n  year = {2024}\n}\n```\n\nor the following plain bibliography:\n\n```\nTeuwen, J., Romor, L., Pai, A., Schirris, Y., Marcus E. (2024). DLUP: Deep Learning Utilities for Pathology (Version 0.8.0) [Computer software]. https://github.com/NKI-AI/dlup\n```\n\n## Contributors\n\nIn alphabetic order:\n\n| [\u003cimg src=\"https://github.com/AjeyPaiK.png\" width=\"50px;\" style=\"border-radius:50%;\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eAjey Pai Karkala\u003c/b\u003e\u003c/sub\u003e](https://github.com/AjeyPaiK) | [\u003cimg src=\"https://github.com/EricMarcus-ai.png\" width=\"50px;\" style=\"border-radius:50%;\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eEric Marcus\u003c/b\u003e\u003c/sub\u003e](https://github.com/EricMarcus-ai) | [\u003cimg src=\"https://github.com/jonasteuwen.png\" width=\"50px;\" style=\"border-radius:50%;\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eJonas Teuwen\u003c/b\u003e\u003c/sub\u003e](https://github.com/jonasteuwen) | [\u003cimg src=\"https://github.com/lromor.png\" width=\"50px;\" style=\"border-radius:50%;\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eLeonardo Romor\u003c/b\u003e\u003c/sub\u003e](https://github.com/lromor) | [\u003cimg src=\"https://github.com/rharkes.png\" width=\"50px;\" style=\"border-radius:50%;\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eRolf Harkes\u003c/b\u003e\u003c/sub\u003e](https://github.com/rharkes) | [\u003cimg src=\"https://github.com/YoniSchirris.png\" width=\"50px;\" style=\"border-radius:50%;\"/\u003e\u003cbr /\u003e\u003csub\u003e\u003cb\u003eYoni Schirris\u003c/b\u003e\u003c/sub\u003e](https://github.com/YoniSchirris) |\n| :----------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------------------------------------------------------------------: |\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnki-ai%2Fdlup","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fnki-ai%2Fdlup","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fnki-ai%2Fdlup/lists"}