scikit-image
unknown · United StatesScores
1 product on the map — 1 open.
Openness
5 high confidence- license
- BSD-3-Clause(OSI)
- source
- public(github.com/scikit-image/scikit-image)
- core features withheld
- no — consensus-based community project with a steering council
BSD-3-Clause and built from the public repository. It is a community project run by consensus under a steering council, with nothing for sale.
- https://pypi.org/pypi/scikit-image/json recorded 2026-09-27
PyPI record for scikit-image 0.26.0, uploaded 2025-12-20, source URL github.com/scikit-image/scikit-image.
- https://raw.githubusercontent.com/scikit-image/scikit-image/main/LICENSE.txt recorded 2026-09-27
LICENSE.txt: "Files: *", "Copyright: 2009-2022 the scikit-image team", "License: BSD-3-Clause", with a few files under BSD-2-Clause and MIT.
- https://scikit-image.org/docs/stable/skips/1-governance.html recorded 2026-09-27
SKIP 1, governance: "This is a consensus-based community project. Anyone with an interest in the project can join the community, contribute to the project design, and participate in the decision making process."
- https://ungh.cc/repos/scikit-image/scikit-image/files/main recorded 2026-09-27
Repository tree with no ee, enterprise, commercial or pro directory.
Adoption
5 high confidenceMeasured on monthly PyPI downloads of the scikit-image package.
- https://pypistats.org/api/packages/scikit-image/recent recorded 2026-09-27
last_month 24,072,233 downloads of scikit-image
Capability
1 high confidencescikit-image supplies classical image-processing operations and fits no learned predictor of its own, which places it with OpenCV as a primitives library; OpenCV's scope is broader and extends to running neural networks.
- https://scikit-image.org/docs/stable/api/api.html recorded 2026-09-27
API reference modules color, data, draw, exposure, feature, filters, filters.rank, future, graph, io, measure, metrics, morphology, registration, restoration, segmentation, transform and util.