Skip to main content

A phenotyping pipeline for python

Project description


Project status Windows build Linux build OSX build Coverage Style
Project Status: Active Build status soon to come none Coverage Status Code style

Author: Moritz Lürig
License: LGPL
Homepage www.phenopype.org
Publication https://doi.org/10.1111/2041-210x.13771


What is phenopype?

phenopype is a high throughput phenotyping pipeline for Python to support ecologists and evolutionary biologists in extracting high dimensional phenotypic data from digital images. The package aims at facilitating rapid, signal processing based analysis of biological images containing phenotypic information.

Why phenopype

phenopype is aiming to augment, rather than replace the utility of existing CV libraries for scientists measuring phenotypes. Put differently, phenopype does not intend to be an exhaustive library of granular image processing functions, like OpenCV, scikit-image or ImageJ, but instead, it is a set of wrappers and convenient management tools to allow biologists to get their data fast without having to fiddle with too much code.

Main features

(For a complete list check the API reference)

  • image analysis workflow:
    • preprocessing (automatic reference detection, colour and size correction, morphology operations)
    • segmentation (thresholding, watershed, contour-filtering, foreground-background subtraction)
    • measurement (pixel intensities, landmarks, shape features, texture features)
    • visualization and export
    • video analysis module for object tracking
  • project management tools to organize images and data (automatic creation of project directory tree)
  • customizable analysis-templates that allow anyone to reproduce all collected data with only a few lines of code (suitable for repositories like Dryad or OSF).


Quickstart

https://www.phenopype.org/docs/quickstart/

Documentation

https://www.phenopype.org/docs/

Vignette gallery

https://www.phenopype.org/gallery/

Contributions and feedback

phenopype development is ongoing and contributions towards making it more broadly applicable and user-friendly are most welcome. This can be in the form of feature requests (e.g. more functions from the OpenCV library) or by reporting bugs via the issue tracker. You can also get in touch with me directly if you would like to contribute code - in that case, please have a look at the API.

How to cite phenopype

Lürig, M. D. (2021). phenopype : A phenotyping pipeline for Python. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210x.13771

@ARTICLE{Lurig2021,
  title     = "phenopype : A phenotyping pipeline for Python",
  author    = "L{\"u}rig, Moritz D",
  journal   = "Methods in Ecology and Evolution",
  publisher = "Wiley",
  month     =  dec,
  year      =  2021,
  copyright = "http://creativecommons.org/licenses/by-nc/4.0/",
  language  = "en",
  doi       = "10.1111/2041-210x.13771"
}

Project details


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 Distribution

phenopype-3.1.0-py3-none-any.whl (73.7 kB view details)

Uploaded Python 3

File details

Details for the file phenopype-3.1.0-py3-none-any.whl.

File metadata

  • Download URL: phenopype-3.1.0-py3-none-any.whl
  • Upload date:
  • Size: 73.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.8.2 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.7.11

File hashes

Hashes for phenopype-3.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 d1afe31f7c459917922396d1d607450f9b21afa679ba7553642fad3b01927a56
MD5 ee0dba2ab16799331b69b350a441dda2
BLAKE2b-256 55abc0b9c7ec966ef0d0cb7055c04cf06fd8c26dd2cf448c1c1ddca612a15b36

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