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Feature extraction for labeled objects in images using regionprops from scikit-image

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haesleinhuepf/napari-skimage-regionprops

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napari-skimage-regionprops

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A napari plugin for measuring properties of labeled objects based on scikit-image

Features

The user can select categories of features for feature extraction in the user interface. These categories contain measurements from the scikit-image regionprops list of measurements library:

  • size:
    • area
    • bbox_area
    • convex_area
    • equivalent_diameter
  • intensity:
    • max_intensity
    • mean_intensity
    • min_intensity
    • standard_deviation_intensity (extra_properties implementation using numpy)
  • perimeter:
    • perimeter
    • perimeter_crofton
  • shape
    • major_axis_length
    • minor_axis_length
    • orientation
    • solidity
    • eccentricity
    • extent
    • feret_diameter_max
    • local_centroid
  • position:
    • centroid
    • bbox
    • weighted_centroid
  • moments:
    • moments
    • moments_central
    • moments_hu
    • moments_normalized

This napari plugin was generated with Cookiecutter using with @napari's cookiecutter-napari-plugin template.

Installation

You can install napari-skimage-regionprops via pip:

pip install napari-skimage-regionprops

Or if you plan to develop it:

git clone https://github.com/haesleinhuepf/napari-skimage-regionprops
cd napari-skimage-regionprops
pip install -e .

If there is an error message suggesting that git is not installed, run conda install git.

Contributing

Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.

License

Distributed under the terms of the BSD-3 license, "napari-skimage-regionprops" is free and open source software

Issues

If you encounter any problems, please create a thread on image.sc along with a detailed description and tag @haesleinhuepf.

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Feature extraction for labeled objects in images using regionprops from scikit-image

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