Skip to main content

A tool for segmentation of grayscale evolution from 4D tomograhphy data (or other images)

Project description

evoSegment

This is a tool to segment microstructural evolution from 4D tomography data (or other image data).The method is based on k-means clustering of a 2D histogram built from the intensities in a reference state and in an evolved state.

Installation

The easiest is to install the package from PyPI using python3 - m pip install evosegment

It is also possible to clone the repository, build and install a local wheel. Something like this might work:

 cd evoSegment
 python3 -m build
 python3 -m pip install -e .

Using this approach will install the package in an editable way so that any changes you make to the code are reflected without reinstalling.

Usage

Have a look at the example.ipynb!

License

This software is licensed under the GNU General Public Licence v3.0 or later.

Support

Send an email to johan.hektor@mau.se or open an issue on gitlab if you have any questions.

Project details


Download files

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

Source Distribution

evosegment-0.0.2.tar.gz (4.3 MB view details)

Uploaded Source

Built Distribution

evosegment-0.0.2-py3-none-any.whl (4.4 MB view details)

Uploaded Python 3

File details

Details for the file evosegment-0.0.2.tar.gz.

File metadata

  • Download URL: evosegment-0.0.2.tar.gz
  • Upload date:
  • Size: 4.3 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for evosegment-0.0.2.tar.gz
Algorithm Hash digest
SHA256 19df011023cdb4f0852db4c45586c620d0420c965459750407bd57fb7d9ad8f1
MD5 9d796b32f0336fbe9c775ba7f733b323
BLAKE2b-256 da815c8ae7eed8e6aaf4d0b40d944339faa521638b064226d5aeeef111007477

See more details on using hashes here.

File details

Details for the file evosegment-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: evosegment-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 4.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.12

File hashes

Hashes for evosegment-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 ce009d8a3fc621d26f035a6447a7d092326edcb9c174cdb6eedf02951ca1c012
MD5 026ee3c256307d8c57b8d7659cff3dff
BLAKE2b-256 a06b9a2c69cd49ce62781f24949bb32de7361d178902c10b1bd061c0b9ffa45b

See more details on using hashes here.

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