ITK is an open-source toolkit for multidimensional image analysis

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for jcfr from gravatar.com jcfr Avatar for phcerdan from gravatar.com phcerdan Avatar for tbirdso from gravatar.com tbirdso Avatar for thewtex from gravatar.com thewtex

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Apache Software License (Apache)
  • Author: Insight Software Consortium
  • Tags ITK, InsightToolkit, segmentation, registration, image, imaging
Classifiers

Project description

itk-core

ITK is an open-source, cross-platform library that provides developers with an extensive suite of software tools for image analysis. Developed through extreme programming methodologies, ITK employs leading-edge algorithms for registering and segmenting multidimensional scientific images.

This package contain the toolkit framework used by other modules. There are common base classes for data objects and process objects, basic data structures such as Image, Mesh, QuadEdgeMesh, and SpatialObjects, and common functionality for operations such as finite differences, image adaptors, or image transforms.

ITK - The Insight Toolkit

ITK: The Insight Toolkit

GitHub release PyPI Wheels License DOI Powered by NumFOCUS

C++ Python
Linux Build Status Build Status
macOS Build Status Build Status
Windows Build Status Build Status
Linux (Code coverage) Build Status

Links

About

The Insight Toolkit (ITK) is an open-source, cross-platform toolkit for N-dimensional scientific image processing, segmentation, and registration. Segmentation is the process of identifying and classifying data found in a digitally sampled representation. Typically the sampled representation is an image acquired from such medical instrumentation as CT or MRI scanners. Registration is the task of aligning or developing correspondences between data. For example, in the medical environment, a CT scan may be aligned with a MRI scan in order to combine the information contained in both.

The ITK project uses an open governance model and is fiscally sponsored by NumFOCUS. Consider making a tax-deductible donation to help the project pay for developer time, professional services, travel, workshops, and a variety of other needs.


ITK is distributed in binary Python packages. To install:

pip install itk

or

conda install -c conda-forge itk

The cross-platform, C++ core of the toolkit may be built from source using CMake.

Copyright

NumFOCUS holds the copyright of this software. NumFOCUS is a non-profit entity that promotes the use of open source scientific software for educational and research purposes. NumFOCUS delegates project governance to the Insight Software Consortium Council, an educational consortium dedicated to promoting and maintaining open-source, freely available software for medical image analysis. This includes promoting such software in teaching, research, and commercial applications, and maintaining webpages and user and developer communities. ITK is distributed under a license that enables use for both non-commercial and commercial applications. See LICENSE and NOTICE files for details.

Supporting ITK

ITK is a fiscally sponsored project of NumFOCUS, a non-profit dedicated to supporting the open source scientific computing community. If you want to support ITK's mission to develop and maintain open-source, reproducible scientific image analysis software for education and research, please consider making a donation to support our efforts.

NumFOCUS is 501(c)(3) non-profit charity in the United States; as such, donations to NumFOCUS are tax-deductible as allowed by law. As with any donation, you should consult with your personal tax adviser or the IRS about your particular tax situation.

Professional Services

Kitware provides professional services for ITK, including custom solution creation, collaborative research and development, development support, and training.

Citation

To cite ITK, please reference, as appropriate:

The papers

McCormick M, Liu X, Jomier J, Marion C, Ibanez L. ITK: enabling reproducible research and open science. Front Neuroinform. 2014;8:13. Published 2014 Feb 20. doi:10.3389/fninf.2014.00013

Yoo TS, Ackerman MJ, Lorensen WE, Schroeder W, Chalana V, Aylward S, Metaxas D, Whitaker R. Engineering and Algorithm Design for an Image Processing API: A Technical Report on ITK – The Insight Toolkit. In Proc. of Medicine Meets Virtual Reality, J. Westwood, ed., IOS Press Amsterdam pp 586-592 (2002).

The books

Johnson, McCormick, Ibanez. "The ITK Software Guide: Design and Functionality." Fourth Edition. Published by Kitware, Inc. 2015 ISBN: 9781-930934-28-3.

Johnson, McCormick, Ibanez. "The ITK Software Guide: Introduction and Development Guidelines." Fourth Edition. Published by Kitware, Inc. 2015 ISBN: 9781-930934-27-6.

Specific software version

DOI

Once your work has been published, please create a pull request to add the publication to the ITKBibliography.bib file.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for jcfr from gravatar.com jcfr Avatar for phcerdan from gravatar.com phcerdan Avatar for tbirdso from gravatar.com tbirdso Avatar for thewtex from gravatar.com thewtex

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: Apache Software License (Apache)
  • Author: Insight Software Consortium
  • Tags ITK, InsightToolkit, segmentation, registration, image, imaging
Classifiers

Release history Release notifications | RSS feed

5.4.0

5.4rc4 pre-release

5.4rc3 pre-release

5.4rc2 pre-release

5.4rc1 pre-release

This version

5.3.0

5.3rc4.post4 pre-release

5.3rc4 pre-release

5.2.1.post1

5.2.1

5.2.0.post3

5.2.0

5.1.2

5.1.1.post1

5.1.0.post3

5.1.0

5.0.1

5.0.0.post1

4.13.2.post1

4.12.0.post1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

itk_core-5.3.0-cp311-cp311-win_amd64.whl (36.4 MB view details)

Uploaded CPython 3.11 Windows x86-64

itk_core-5.3.0-cp311-cp311-manylinux_2_28_x86_64.whl (81.2 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.28+ x86-64

itk_core-5.3.0-cp311-cp311-manylinux_2_28_aarch64.whl (73.4 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.28+ ARM64

itk_core-5.3.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (83.8 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

itk_core-5.3.0-cp311-cp311-macosx_11_0_arm64.whl (57.6 MB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

itk_core-5.3.0-cp311-cp311-macosx_10_9_x86_64.whl (71.0 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

itk_core-5.3.0-cp310-cp310-win_amd64.whl (36.4 MB view details)

Uploaded CPython 3.10 Windows x86-64

itk_core-5.3.0-cp310-cp310-manylinux_2_28_x86_64.whl (81.2 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.28+ x86-64

itk_core-5.3.0-cp310-cp310-manylinux_2_28_aarch64.whl (73.4 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.28+ ARM64

itk_core-5.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (83.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

itk_core-5.3.0-cp310-cp310-macosx_11_0_arm64.whl (57.6 MB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

itk_core-5.3.0-cp310-cp310-macosx_10_9_x86_64.whl (71.0 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

itk_core-5.3.0-cp39-cp39-win_amd64.whl (36.4 MB view details)

Uploaded CPython 3.9 Windows x86-64

itk_core-5.3.0-cp39-cp39-manylinux_2_28_x86_64.whl (81.2 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.28+ x86-64

itk_core-5.3.0-cp39-cp39-manylinux_2_28_aarch64.whl (73.4 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.28+ ARM64

itk_core-5.3.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (83.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

itk_core-5.3.0-cp39-cp39-macosx_11_0_arm64.whl (57.6 MB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

itk_core-5.3.0-cp39-cp39-macosx_10_9_x86_64.whl (71.0 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

itk_core-5.3.0-cp38-cp38-win_amd64.whl (36.3 MB view details)

Uploaded CPython 3.8 Windows x86-64

itk_core-5.3.0-cp38-cp38-manylinux_2_28_x86_64.whl (81.2 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.28+ x86-64

itk_core-5.3.0-cp38-cp38-manylinux_2_28_aarch64.whl (73.4 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.28+ ARM64

itk_core-5.3.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (83.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

itk_core-5.3.0-cp38-cp38-macosx_10_9_x86_64.whl (71.1 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

itk_core-5.3.0-cp37-cp37m-win_amd64.whl (36.1 MB view details)

Uploaded CPython 3.7m Windows x86-64

itk_core-5.3.0-cp37-cp37m-manylinux_2_28_x86_64.whl (81.1 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.28+ x86-64

itk_core-5.3.0-cp37-cp37m-manylinux_2_28_aarch64.whl (73.3 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.28+ ARM64

itk_core-5.3.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (83.5 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

itk_core-5.3.0-cp37-cp37m-macosx_10_9_x86_64.whl (71.0 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

File details

Details for the file itk_core-5.3.0-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 cd22229f6945e539141e8829f866bdf0c21567e8f8b9b7621a27032c5f2cfbf8
MD5 2bccdbbb6ba784510d9915fbaaa0a786
BLAKE2b-256 ffa8e2666c5e784c3a509d2c0a6e3a04cf24377d7ab0f08ecea6654b7a6bbeff

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp311-cp311-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp311-cp311-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 7cc25d0923deb9219299cd8c5a7e5bc1d8ed6731497a06cf121409b71c72ae59
MD5 ebf91815cb32f4a14001fb89a4b6e4d5
BLAKE2b-256 fe0022580238b122f4c0d38061764ce94e0f47c9b8c9fc24e4f6ade6a93f4563

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp311-cp311-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp311-cp311-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 2068a7456d22a31ef689099f5a342e591c7a426673c8e84ecaadf92456ddea07
MD5 f3cab5baf40f96ebdb880e204c0cc32e
BLAKE2b-256 ddb525a14bec1eae967d9dd68476c8e6f36726b98af97283480c925d82358fa7

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5a43f1e625409cedf7c9046bfaba0ce02ee86c86263b2615b9e0444acb38a1d8
MD5 14f9bda89f9187d3a3981a3bab74f69e
BLAKE2b-256 c88ec27b81324c573854ea70e79e123ba33ec8c0aac70194ef50c3a7d0eaac9b

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5be7b5ebaaf29cb4a1763b09ec0dbbcc6f84580b2dc234f98167cd2e3f7ea97b
MD5 8ffd804d9458fbae3ed13f8845d7cefc
BLAKE2b-256 e2021c3446e3a7f83f1fbf4014ce7a524baf36527cb0de9e6214a9597fb18e61

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 530ffb9492004cb2eee8b9702e728e62373cf205e01b3612a811cd6b745b1251
MD5 023d8bac6c71f76bb59716a3c725f618
BLAKE2b-256 9d644c3ec6144a41839ad3ca6e842cf15dae0e7225a8bdd505a9553b158b5d8b

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 b7cd730513bbd502e660855f45a9657953eed8c88c666f39a3b622203d14720b
MD5 2cc7755c940c0097e5e29e02ebfde1b7
BLAKE2b-256 cf9488837a1556666115d5665b70bb191742bb56de74fab3b3715064d782a2cd

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp310-cp310-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp310-cp310-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 f51cffaeddb86aa650538955a8aa1a4f6cb8a0f5296b6977412b0bdea10fae99
MD5 5d549001c599e6e09194d08b2d571057
BLAKE2b-256 3e42873546782e228daa476be06fe8075c7b037f818697b9af16b0bfcb8f3a37

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp310-cp310-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp310-cp310-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 c8f26fae88f6e0f0eac6f6800c5e6ec62879e2597a861bed36454954db5e377e
MD5 8a9ce101829b8d69816c36f0d3b55dff
BLAKE2b-256 7811bd86c6acab901f95dee3ec933bf10ee9a1861fe79addb3c6e4f3d127feb7

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 9fa2f4b283af6c67707c4ed2f3b064a2126a60ec7658917fa33d5f2f21e1698d
MD5 994ae7b952684c9e3e9d9c582f520dbe
BLAKE2b-256 93f5c13beb61a4e81192f8d3e93f3ac8458bab6285cb4b67241f05dd59266b5c

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 4b8bb2df8697c3706b12adf4d79dea0be3dab73b8bd200c14a970f1ea6e52bb7
MD5 1d6d0b3fa21dce1c952812847f8119b5
BLAKE2b-256 a69aed52969e20a48b4e1321c87d9e6c125e3ea453c37305a72a81868379e2a3

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 15fd888c5338a0d630ae5ceaa90d0244d4e2040baf08279bb6db284f2774b77c
MD5 79f7578975304e847c5eb802a8c2ef73
BLAKE2b-256 d3b09e7d9487da2413abd9d5c7f39c7e90b4fc11f54b3366f25ef2509591639d

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: itk_core-5.3.0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 36.4 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.2

File hashes

Hashes for itk_core-5.3.0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 bafc7d3472efc4e9d164d979bdcab88c78da8d37f10cc422285e3b219857a98e
MD5 fe54b6f7130e9a9d46bcfdcafba0c4b2
BLAKE2b-256 9b91e269b9d03a69c2a3489937cbc44c72954cbe096321a2efc4e97501aac6ea

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp39-cp39-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp39-cp39-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 c3825d3042c208a91d46884b7af80af00c86b83cdf099833d4e61961c9989aa0
MD5 74468aa2ed4d4f70cc288d5de5bedd4d
BLAKE2b-256 b39c4ed1f4102a9d39adffbae268c7b670deead8dbfaec008432693c17552ddc

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp39-cp39-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp39-cp39-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 7f913621eaf319f670332de39143f0cd7e27266d0172a1d225ed784bec4587fa
MD5 2c25c59d1102608969c6018e84ae87b9
BLAKE2b-256 6861769eb248fe2ab381be458c27c352173bc9b04a0e2b5aa28215fb1d5e94e7

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 e98aea3787d3bc1f49cf5a4988a1ec4a54232830ef42e50f91234ec1485365a9
MD5 f5c8382d59af5cafcf3b38674bbbbf16
BLAKE2b-256 c2756bfa2b53b5188b6c5c5b171cd3bbf465172775ad4938919685d1d3943e78

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 fbdf8fb96e929cd2298d1f3c61398265620050b140410516a9283a1894211564
MD5 29d79c70ea3d18e035a04c02e41b2cf3
BLAKE2b-256 fa492172f43366bc777ac020f9cc55989d903e51e942f7920e9e87fb18adb486

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 48313b935f9cdee3ff9bed24d7e604a97e6971645c7c346d8a9b03d10d53ba28
MD5 647b24f72bda96454763ed33716a433a
BLAKE2b-256 9224643243f59e66888d4fb4cebf158797eef6ff40fda516ab9c5cfc2e876a42

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: itk_core-5.3.0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 36.3 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.2

File hashes

Hashes for itk_core-5.3.0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 a01ce1e2456cdb432fc88eab5a0b0585a77d1e73758bfae2d3f0d6fdd7ecb222
MD5 efd86778427af660b8284d6a4a11445f
BLAKE2b-256 1c606a85264f03e053f334b7fcd8dfd5fa7ed661653319440dd8f41d8c9f0959

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp38-cp38-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp38-cp38-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 10b2236bced382aeef65aed4f36e9fb39c1bed0ccc2d163417700442a4fe355d
MD5 82fd59b6638be604fbd9c9b984a74276
BLAKE2b-256 9adcb664117665f164d93e914b0d959c1aaacf7b9f91f4393d29114ed875b862

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp38-cp38-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp38-cp38-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 34493c3f59ae9ad47202ff41ceea8a81acd36c3702e6b2ce42c56be94a1892fa
MD5 6b85fa51e80d562ce220f5395ea0c41c
BLAKE2b-256 82ad3b119185983d4a7da6d594a352bd32c6ab32b01b58677b584d9bd3c2550c

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 44b55a36e8746e052ef7638458cb088eb0269c1023d1fe0a575580840d25334e
MD5 a765fc88ac9a2b9b14aa7be7ba0d8f96
BLAKE2b-256 2b2cd443dbf29c0811a74c2db203238463297144473bd3b9118f8606746671d1

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 dabcce38cf30daa4c21dd500f96f4be250bde4718fa3c28d1c60094a12fa68f4
MD5 0ab8ffcf0b2e298080f454af3537a2a1
BLAKE2b-256 d3bcbd9340b83c3b7be8d1cb52ea35324fcde770a384c3ca2f56149779c685ae

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: itk_core-5.3.0-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 36.1 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.2

File hashes

Hashes for itk_core-5.3.0-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 1b7cf723ca9c01ab952ba956bcbb8b368984e6585268c5c0c7d431f28def8190
MD5 3fa2a2bcdd8a667e484b7c5f2a988648
BLAKE2b-256 72c56138b4fff63c0aa4a782f8b785bdfb9fd8e57142c8276321c64217c38522

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp37-cp37m-manylinux_2_28_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp37-cp37m-manylinux_2_28_x86_64.whl
Algorithm Hash digest
SHA256 1cf17bc60a7caa648bbe8643f53187ee4cce2e24eef20ad0904a0dd71b718582
MD5 6f1baafdfc4d5503cdcf626553982a03
BLAKE2b-256 274f2b36a6913e1981af94570122db55147f91035b0d85b05d187485c2921d61

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp37-cp37m-manylinux_2_28_aarch64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp37-cp37m-manylinux_2_28_aarch64.whl
Algorithm Hash digest
SHA256 03470278569da50a6cc8adf8a8b89a34b01468009f1291efb78e8dcb694b66f6
MD5 5e7c3ad2fb632fe7bee92def03a2bd26
BLAKE2b-256 3ae970adc66221b0497b5681aa1203b508415a706749b844e9563626bdd68ba1

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f9c77357c383236db6d24de312c0d13b4908a347e3f1eb27ab65995e25b54236
MD5 40809d547b91261ce986296f757ccee3
BLAKE2b-256 dcc781b07f81e240630f06bd41d29d2a3e7d0076913af1a6c8c94e94ebe94d5a

See more details on using hashes here.

Provenance

File details

Details for the file itk_core-5.3.0-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for itk_core-5.3.0-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 ec82117e4a9d57705aabd6ed94c3fd73707c090fdcff9c7dfbdb42b1c4ba66bd
MD5 e8e18afd912dff3ce84123c33af5432a
BLAKE2b-256 e9e6bdafceb8476251ed47628798b4159a77b9922d708a7aa9949992f590866c

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page