Skip to main content

A Python toolkit for Histopathology Image Analysis

Project description

HistomicsTK is a Python package for the analysis of digital pathology images. It can function as a stand-alone library, or as a Digital Slide Archive plugin that allows users to invoke image analysis jobs through HistomicsUI. The functionality offered by HistomicsTK can be extended using slicer cli web which allows developers to integrate their image analysis algorithms into DSA for dissemination through HistomicsUI.

Whole-slide imaging captures the histologic details of tissues in large multiresolution images. Improvements in imaging technology, decreases in storage costs, and regulatory approval of digital pathology for primary diagnosis have resulted in an explosion of whole-slide imaging data. Digitization enables the application of computational image analysis and machine learning algorithms to characterize the contents of these images, and to understand the relationships between histology, clinical outcomes, and molecular data from genomic platforms. Compared to the related areas of radiology and genomics, open-source tools for the management, visualization, and analysis of digital pathology has lagged. To address this we have developed HistomicsTK in coordination with the Digital Slide Archive (DSA), a platform for managing and sharing digital pathology images in a centralized web-accessible server, and HistomicsUI, a specialized user interface for annotation and markup of whole-slide images and for running image analysis tools and for scalable visualizing of dense outputs from image analysis algorithms. HistomicsTK aims to serve the needs of both pathologists/biologists interested in using state-of-the-art algorithms to analyze their data, and algorithm researchers interested in developing new/improved algorithms and disseminate them for wider use by the community.

HistomicsTK can be used in two ways:

  • As a pure Python package: enables application of image analysis algorithms to data independent of the Digital Slide Archive (DSA). HistomicsTK provides a collection of fundamental algorithms for tasks such as color normalization, color deconvolution, nuclei segmentation, and feature extraction. Read more about these capabilities here: api-docs and examples for more information.

    Installation instructions on Linux:

    To install HistomicsTK using PyPI:

    $ python -m pip install histomicstk --find-links https://girder.github.io/large_image_wheels

    To install HistomicsTK from source:

    $ git clone https://github.com/DigitalSlideArchive/HistomicsTK/
    $ cd HistomicsTK/
    $ python -m pip install setuptools-scm "Cython>=0.25.2" "scikit-build>=0.8.1" "cmake>=0.6.0" "numpy>=1.12.1"
    $ python -m pip install -e .

    HistomicsTK uses the large_image library to read content from whole-slide and microscopy image formats. Depending on your exact system, installing the necessary libraries to support these formats can be complex. There are some non-official prebuilt libraries available for Linux that can be included as part of the installation by specifying pip install histomicstk --find-links https://girder.github.io/large_image_wheels. Note that if you previously installed HistomicsTK or large_image without these, you may need to add --force-reinstall --no-cache-dir to the pip install command to force it to use the find-links option.

    The system version of various libraries are used if the --find-links option is not specified. You will need to use your package manager to install appropriate libraries (on Ubuntu, for instance, you’ll need libopenslide-dev and libtiff-dev).

    To install from source on Windows:

    1- Run the following:

    $ pip install large-image
    $ pip install cmake
    $ git clone https://github.com/DigitalSlideArchive/HistomicsTK/
    $ cd HistomicsTK/
    $ python -m pip install setuptools-scm "Cython>=0.25.2" "scikit-build>=0.8.1" "cmake>=0.6.0" "numpy>=1.12.1"

    2- Run pip install libtiff

    3- Run pip install large-image-source-tiff to install typical tile sources. You may need other sources, which would require other libraries.

    4- Install Visual Studio 15 2017 Community Version

    5- Install C++ build tools. Under Tools > Get Tools and Features … > Desktop Development with C++, ensure that the first 8 boxes are checked.

    6- Run this:

    $ python -m pip install -e .
    $ pip install girder-client

    To install from source on OSX:

    Note: This needs to be confirmed and expanded by an OSX user. There are probably assumptions made about available libraries.

    Use homebrew to install libtiff and openslide or other libraries depending on your desired tile sources.

    Run:

    $ python -m pip install histomicstk large-image-source-tiff large-image-source-openslide
  • As a image-processing task library for HistomicsUI and the Digital Slide Archive: This allows end users to apply containerized analysis modules/pipelines over the web. See the Digital Slide Archive for installation instructions.

Refer to our website for more information.

Previous Versions

The HistomicsTK repository used to contain almost all of the Digital Slide Archive and HistomicsUI, and now container primarily code for image analysis algorithms and processing of annotation data. The deployment and installation code and instructions for DSA have moved to the Digital Slide Archive repository. The user interface and annotation functionality has moved to the HistomicsUI repository.

The deployment and UI code will eventually be removed from the master branch of this repository; any new development on those topics should be done in those locations.

Funding

This work is funded by the NIH grant U24-CA194362-01.

See Also

DSA/HistomicsTK project website: Demos | Success stories

Source repositories: Digital Slide Archive | HistomicsUI | large_image | slicer_cli_web

Discussion: GitHub Discussion | Discourse forum

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

histomicstk-1.3.2.dev10.tar.gz (207.0 kB view details)

Uploaded Source

Built Distributions

histomicstk-1.3.2.dev10-cp312-cp312-win_amd64.whl (551.0 kB view details)

Uploaded CPython 3.12 Windows x86-64

histomicstk-1.3.2.dev10-cp312-cp312-musllinux_1_1_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.12 musllinux: musl 1.1+ x86-64

histomicstk-1.3.2.dev10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (631.2 kB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

histomicstk-1.3.2.dev10-cp312-cp312-macosx_11_0_arm64.whl (578.5 kB view details)

Uploaded CPython 3.12 macOS 11.0+ ARM64

histomicstk-1.3.2.dev10-cp312-cp312-macosx_10_12_x86_64.whl (575.0 kB view details)

Uploaded CPython 3.12 macOS 10.12+ x86-64

histomicstk-1.3.2.dev10-cp311-cp311-win_amd64.whl (549.6 kB view details)

Uploaded CPython 3.11 Windows x86-64

histomicstk-1.3.2.dev10-cp311-cp311-musllinux_1_1_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

histomicstk-1.3.2.dev10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (642.1 kB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

histomicstk-1.3.2.dev10-cp311-cp311-macosx_11_0_arm64.whl (575.6 kB view details)

Uploaded CPython 3.11 macOS 11.0+ ARM64

histomicstk-1.3.2.dev10-cp311-cp311-macosx_10_12_x86_64.whl (570.8 kB view details)

Uploaded CPython 3.11 macOS 10.12+ x86-64

histomicstk-1.3.2.dev10-cp310-cp310-win_amd64.whl (549.6 kB view details)

Uploaded CPython 3.10 Windows x86-64

histomicstk-1.3.2.dev10-cp310-cp310-musllinux_1_1_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

histomicstk-1.3.2.dev10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (643.5 kB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

histomicstk-1.3.2.dev10-cp310-cp310-macosx_11_0_arm64.whl (576.4 kB view details)

Uploaded CPython 3.10 macOS 11.0+ ARM64

histomicstk-1.3.2.dev10-cp310-cp310-macosx_10_12_x86_64.whl (572.0 kB view details)

Uploaded CPython 3.10 macOS 10.12+ x86-64

histomicstk-1.3.2.dev10-cp39-cp39-win_amd64.whl (551.4 kB view details)

Uploaded CPython 3.9 Windows x86-64

histomicstk-1.3.2.dev10-cp39-cp39-musllinux_1_1_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

histomicstk-1.3.2.dev10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (644.9 kB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

histomicstk-1.3.2.dev10-cp39-cp39-macosx_11_0_arm64.whl (578.0 kB view details)

Uploaded CPython 3.9 macOS 11.0+ ARM64

histomicstk-1.3.2.dev10-cp39-cp39-macosx_10_12_x86_64.whl (573.7 kB view details)

Uploaded CPython 3.9 macOS 10.12+ x86-64

histomicstk-1.3.2.dev10-cp38-cp38-win_amd64.whl (551.8 kB view details)

Uploaded CPython 3.8 Windows x86-64

histomicstk-1.3.2.dev10-cp38-cp38-musllinux_1_1_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

histomicstk-1.3.2.dev10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (646.0 kB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

histomicstk-1.3.2.dev10-cp38-cp38-macosx_11_0_arm64.whl (576.3 kB view details)

Uploaded CPython 3.8 macOS 11.0+ ARM64

histomicstk-1.3.2.dev10-cp38-cp38-macosx_10_12_x86_64.whl (572.1 kB view details)

Uploaded CPython 3.8 macOS 10.12+ x86-64

File details

Details for the file histomicstk-1.3.2.dev10.tar.gz.

File metadata

  • Download URL: histomicstk-1.3.2.dev10.tar.gz
  • Upload date:
  • Size: 207.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.7

File hashes

Hashes for histomicstk-1.3.2.dev10.tar.gz
Algorithm Hash digest
SHA256 d6190766aca838463762445286c86f16059404b4933f3280679e21b985b98d52
MD5 8407b51cdd08132a8684dc939a3e7bfb
BLAKE2b-256 3867b00e838dddf81951f592654debc8ff6ead8d8e6d4fe0d779504ccf652a08

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 31af6785b37955ab397f36de8986b47e8d5fd62398788969f9c7925f649ccaeb
MD5 5b2841e87bc3e56b01ca9f720bec7435
BLAKE2b-256 3b882d5293f4917c9df0831dcbacd5909a43768f2e6e6f7481911824dcd9562c

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp312-cp312-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp312-cp312-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 a76f95891779e5d5af872c6f29a51c26ec367863e8b702c099e867aa4818c7e9
MD5 fc4493bab268d329d13652ab6a2167c7
BLAKE2b-256 ef47a5800a667904c3ab84c8079877a49631f6c8d77ed267de0b465947933d62

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fc5d963f0b43bc4a28958032d77beeb7db63f814e8558730fb8e2f2ff2738120
MD5 c432cc1d75f2312fa7066757c709854c
BLAKE2b-256 7effd441b6f00c17ffffff9f8cc5fc8845b2b97bd0bcfd80730afccd37224e5e

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 98433fd464c7e3e3af07aaf164140541c0654b8ea28e0f4400b269bde5cf9d25
MD5 08dc03833b2438433873089c6124219b
BLAKE2b-256 4e5107eb16035cd92231bdea02cdee396bfbd1aef5ed9245c8d7b882e876e73f

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp312-cp312-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp312-cp312-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 5051ca8bc23fd9ef455e8e58443dbf4b9f98e46b36a6237374fb14bc9abd0be9
MD5 4df3c2e35eee4218115d223ba8fb0c54
BLAKE2b-256 722d55fb9936c1455ee8d2792e43ef41259ba5d42efc5d25b1b081a6b66ea98e

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 e01d1dfe7bcfe7fe89ed0d4c2d0a8c010d7111b0e7847e0f6fa22f6ff35ca402
MD5 e3fdc700a15e0779e315e9b83053b8d0
BLAKE2b-256 d20b9be3857ce149fc74fb3d63a2cd23aaa124d764a6f0abcbe45905b707afbf

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 c15f4d988cf9a47e6c774e35714547287b34e51b864423ade692b482ca1640c6
MD5 ebda4a20b1d72d9f14a172a7213e6016
BLAKE2b-256 18826512bf8aebd5d547c39b478a3289d515fc92170f2b95a749bcba18732a4c

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 d9ac8426dba58bd3651f1ae910f1b1d92a9ca7c895747bc498c99a4a38cc3470
MD5 f8c595ed0e98612fb6eaa0562e35bbe8
BLAKE2b-256 5762672dacd87924583d7a05471322a66f679027a9ec57cb636c6aaba2a83b4d

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5a0cb5e39d0512fa0cd3d67a2f5fab2b006d0ccd4f190b0ff9816d7abe4139e0
MD5 a3d8908a15ecbf911aeb270555e1cfac
BLAKE2b-256 da9a8dd4478c306e3a739b382849ba4e17c593990645ad3e8b18e4c3de3cf6a4

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp311-cp311-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp311-cp311-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 9beec9bafb386fb2bebcc5e79a38e461cb7f28cdfe63312a3ae15141bec82669
MD5 283b09b6ae9fcd9248f61e5724b7dbb9
BLAKE2b-256 a4ef584e763e11ed82c051a0c8183fc8f70d4b4c3afc9c5de94ea622573ae80d

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 ec3d1e23579558f07aa8fc120d1226e429f3abe6071ed84a40877bf111e3d4ad
MD5 cb3232cd0eab94119ce740661b964eaf
BLAKE2b-256 2074fb44b90b7573206b78c78baf2c1e2b217a5365bfd79051f3b53a5b2519c3

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 0de91211dc8071029134b1573ad595ec2458682300360a7256bbc73a3d7aba7d
MD5 ea57cf8164763ab4ff66541503f91797
BLAKE2b-256 b6a445338eb89d24f67138a4de1a7a87ab9558b41feba65938e59b28f333ea48

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6693084254716e8f999084c84bd518f8f38d41c2eb3582b5e665ec43f236c0e8
MD5 d0d370069cb796232cf3b1e52bbd321f
BLAKE2b-256 f46cf400096b955a352a7579000631bd18530ed5fcb7b0133703990d66c67c97

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 0997e75e8cbfc8d29a036d0b2ffb2aa15d3c5e740b19b5a8f25ce506fcf46194
MD5 54579b57d5f176c165118ffe6366f504
BLAKE2b-256 f26cd0a55e1f068f26fad4394d4afaaa25056e92066d88e0e11870894f00d966

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp310-cp310-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp310-cp310-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 8ef0f5fdced48e3ecd1797e8896220bd509681851100bd8ea1421c9f2d92e70f
MD5 f53f8b42496e020c03ce3db7b64cd76d
BLAKE2b-256 c4a64fb4893092c616baad81f0133f99d319d3793dc1dbd86c0fa035b361ed08

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp39-cp39-win_amd64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 f8a20eb96125ef2e09307c632500ed7468f14924f3cdeac14ea22838e3112567
MD5 3feeeb081b703a2a02001fa80bcfd646
BLAKE2b-256 a917de861ee55bb829a798bab4c0758a57ce03338a7de7bb980eb15911353056

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 5563ba50717b0147375971125efde7d983c87b9c9e6fa084bbb4854560b9a5a4
MD5 189d801ed5a854cdc7fe6d9ba403524f
BLAKE2b-256 f9e2216935fca9ba0d77ba6aca7f747df4ca34f3abe741f95a8fba0a25bacbc9

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 537e766b8c7ebd886117561cae4f3e153e1fd97c10d4c4ae7ec87db67d80105d
MD5 22eb9bd9bd7833c64890b852cf2fe71d
BLAKE2b-256 ea780b464546254153e35d60451251211e3d0c7369a452dde5815d7bd029e35c

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 479b1b1dcb5a5e392b16bdd8b2abb955de754f0cdf4b339e0147c606d8dc4267
MD5 ed393850b436ed1aa50b93382bdf0448
BLAKE2b-256 c63ce780f7cc4ecda2c167b61270b9d435ed5dd82b95b0f1b29c531470df7909

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp39-cp39-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp39-cp39-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 c3ffd7b2b8b6ac1f98b50f0d71607485205e4cc0b5414cf8f7b7b638f5e7102b
MD5 b5c73b32105e88298226c891a1c02a62
BLAKE2b-256 e84e380ad1bce84396a7588aefabdce1f750cdd65d3744a95dee210a46b09e49

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp38-cp38-win_amd64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 f38ce24577ad5d71cf6089e4f30568e8fc8286bc87a78697069b2d8c75d6617b
MD5 dfa2d05bc6b3331dcc531fd3462dea9c
BLAKE2b-256 b6a8d5b23aeba00c3d45e0ccd4bbc78458eadbce4139fdc21134136237fa8aff

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 eec351919bc1664a4843a9472d2c68e3fa6b3115e1eb9eddd27a2de9927c716f
MD5 14c272f2c0d8b0ec87979177bebebba0
BLAKE2b-256 76eba7100d2beb7aa14cf0190a36c51868b6bcab72595ba4e70c690674ca0de4

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 65ce5a2b74879a1b4f11df7909074d1c6dfc5104a62754395b87964bd011dc29
MD5 83eb00dce7c13dfb79c5944844cafe18
BLAKE2b-256 0eadd440320e4e919273c691d9ec909fb44c04e373ecc4198078548ffb8ec203

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 edbfb3d3c517bfd215bd25e28331f3956313ab1f7b1e7d3e940cd3c5e360663f
MD5 0affc33b3ea7408306895794d60c0744
BLAKE2b-256 f3b92d47f8f720830ca267867d31700deda024a7f518b86512085ffefb48bf7b

See more details on using hashes here.

Provenance

File details

Details for the file histomicstk-1.3.2.dev10-cp38-cp38-macosx_10_12_x86_64.whl.

File metadata

File hashes

Hashes for histomicstk-1.3.2.dev10-cp38-cp38-macosx_10_12_x86_64.whl
Algorithm Hash digest
SHA256 d0d20c946b00a91477d18d874faffbf6b216ca4dd565b8932e3b370a7b1864bf
MD5 2e505be41aba654530e35e6735d355de
BLAKE2b-256 4a4f01866c6cdb96efcc63fb3352ace1ff0a6df03ef07a4769b10dbefb48e432

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