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dlup

Dlup are the Deep Learning Utilities for Pathology developed at the Netherlands Cancer Institute

https://github.com/nki-ai/dlup

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ✓
    CITATION.cff file
    Found CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Committers with academic emails
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (13.5%) to scientific vocabulary
Last synced: 7 months ago · JSON representation ·

Repository

Dlup are the Deep Learning Utilities for Pathology developed at the Netherlands Cancer Institute

Basic Info
  • Host: GitHub
  • Owner: NKI-AI
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 2.88 MB
Statistics
  • Stars: 27
  • Watchers: 4
  • Forks: 6
  • Open Issues: 2
  • Releases: 36
Created almost 5 years ago · Last pushed about 1 year ago
Metadata Files
Readme Contributing License Citation

README.md

Deep Learning Utilities for Pathology

pypi Tox mypy Pylint Black codecov

Dlup offers a set of utilities to ease the process of running Deep Learning algorithms on Whole Slide Images.

Features

  • Read whole-slide images at any arbitrary resolution by seamlessly interpolating between the pyramidal levels
  • Supports multiple backends, including OpenSlide and VIPS, with the possibility to add custom backends
  • Dataset classes to handle whole-slide images in a tile-by-tile manner compatible with pytorch
  • Annotation classes which can load GeoJSON, V7 Darwin, HALO and ASAP formats and read parts of it (e.g. a tile)
  • 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
  • Command-line utilities to report on the metadata of WSIs, and convert masks to polygons

Check the full documentation for more details on how to use dlup.

Quickstart

The package can be installed using python -m pip install dlup.

Used by

  • ahcore: a pytorch lightning based-library for computational pathology

Citing DLUP

If you use DLUP in your research, please use the following BiBTeX entry:

@software{dlup, author = {Teuwen, J., Romor, L., Pai, A., Schirris, Y., Marcus, E.}, month = {8}, title = {{DLUP: Deep Learning Utilities for Pathology}}, url = {https://github.com/NKI-AI/dlup}, version = {0.7.0}, year = {2024} }

or the following plain bibliography:

Teuwen, J., Romor, L., Pai, A., Schirris, Y., Marcus E. (2024). DLUP: Deep Learning Utilities for Pathology (Version 0.7.0) [Computer software]. https://github.com/NKI-AI/dlup

Contributors

In alphabetic order:

|
Ajey Pai Karkala |
Eric Marcus |
Jonas Teuwen |
Leonardo Romor |
Rolf Harkes |
Yoni Schirris | | :---: | :---: | :---: | :---: | :---: | :---: |

Owner

  • Name: NKI AI for Oncology Lab
  • Login: NKI-AI
  • Kind: organization
  • Location: Netherlands

The AI for Oncology Lab's mission to is to develop AI innovations which improve cancer diagnosis and therapy.

Citation (CITATION.cff) 

cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: "Teuwen"
  given-names: "Jonas"
  orcid: "https://orcid.org/0000-0002-1825-1428"
- family-names: "Romor"
  given-names: "Leonardo"
- family-names: "Pai"
  given-names: "Ajey"
  orcid: "https://orcid.org/0009-0003-3970-9236"
- family-names: "Schirris"
  given-names: "Yoni"
  orcid: "https://orcid.org/0000-0003-0217-8737"
- family-names: "Marcus"
  given-names: "Eric"
  orchid: "https://orcid.org/0000-0002-3375-6248"
title: "DLUP: Deep Learning Utilities for Pathology"
version: 0.7.0
date-released: 2024-08-09
url: "https://github.com/nki-ai/dlup"

GitHub Events

Total
  • Issues event: 6
  • Watch event: 3
  • Issue comment event: 3
  • Push event: 5
Last Year
  • Issues event: 6
  • Watch event: 3
  • Issue comment event: 3
  • Push event: 5

Committers

Last synced: about 3 years ago

All Time
  • Total Commits: 146
  • Total Committers: 10
  • Avg Commits per committer: 14.6
  • Development Distribution Score (DDS): 0.589
Top Committers
Name Email Commits
Jonas Teuwen 2****n@u****m 60
Jonas Teuwen j****n@n****l 57
Ajey Pai K a****e@g****m 7
Jonas Teuwen j****n@g****m 7
Yoni Schirris 3****s@u****m 5
Leonardo Romor l****r@g****m 4
Timo Kootstra 4****a@u****m 3
Andreas 3****y@u****m 1
Mensel123 m****r@h****m 1
Francesco Dal Canton f****k@u****m 1
Committer Domains (Top 20 + Academic)
nki.nl: 1

Issues and Pull Requests

Last synced: 8 months ago

All Time
  • Total issues: 87
  • Total pull requests: 116
  • Average time to close issues: 3 months
  • Average time to close pull requests: about 2 months
  • Total issue authors: 14
  • Total pull request authors: 14
  • Average comments per issue: 1.76
  • Average comments per pull request: 0.79
  • Merged pull requests: 91
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 10
  • Pull requests: 15
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 5 days
  • Issue authors: 3
  • Pull request authors: 4
  • Average comments per issue: 0.7
  • Average comments per pull request: 0.87
  • Merged pull requests: 11
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • jonasteuwen (23)
  • AjeyPaiK (13)
  • YoniSchirris (10)
  • moerlemans (7)
  • BPdeRooij (6)
  • Dafidofff (5)
  • Tkootstra (5)
  • manyids2 (4)
  • VanessaBotha (3)
  • DennisHaijma (2)
  • TangTangFei (1)
  • sinberlin2 (1)
  • lromor (1)
  • rharkes (1)
Pull Request Authors
  • jonasteuwen (96)
  • AjeyPaiK (15)
  • BPdeRooij (4)
  • YoniSchirris (3)
  • moerlemans (3)
  • Tkootstra (3)
  • rharkes (3)
  • EricMarcus-ai (2)
  • Mensel123 (2)
  • Baggsy (2)
  • siemdejong (2)
  • lromor (1)
  • martvanrijthoven (1)
  • Dafidofff (1)
Top Labels
Issue Labels
Stale (51) enhancement (37) bug (37) documentation (2) wontfix (2) help wanted (2) good first issue (1)
Pull Request Labels
python (90) documentation (14) ci (14) Stale (13) bug (8) enhancement (4) docker (1) wontfix (1)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 81 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 1
  • Total versions: 43
  • Total maintainers: 1
pypi.org: dlup

A package for digital pathology image analysis

  • Homepage: https://github.com/NKI-AI/dlup
  • Documentation: https://docs.aiforoncology.nl/dlup/
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  • Latest release: 0.7.0
    published over 1 year ago
  • Versions: 43
  • Dependent Packages: 1
  • Dependent Repositories: 1
  • Downloads: 81 Last month
Rankings
Dependent packages count: 4.8%
Downloads: 5.0%
Average: 11.5%
Stargazers count: 12.7%
Forks count: 13.3%
Dependent repos count: 21.5%
Maintainers (1)
jonasteuwen
Last synced: 8 months ago

Dependencies

setup.py pypi
  • matplotlib *
  • numpy >=1.21
  • openslide-python *
  • pillow *
  • pyvips *
  • requests *
  • scikit-image >=0.19
  • shapely *
  • tifffile >=2022.5.4
  • tifftools *
  • tqdm *
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