napari skimage

napari-skimage

A plugin to apply scikit-image operations

Workflow step:
Image annotation
Image segmentation

License BSD-3 PyPI Python Version tests codecov napari hub

napari-skimage gives easy access to scikit-image functions in napari. The main goal of the plugin is to allow new users of napari, especially without coding experience, to easily explore basic image processing, in a similar way to what is possible in Fiji.

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

Philosophy

The plugin is still in early development and does not cover all functions of scikit-image. If you are interested in a specific function, please open an issue or a pull request. scikit-image functions are turned into interactive widgets mostly via magicgui, a tool that allows to create GUIs from functions in a simple way (in particular not requiring Qt knowledge). The code avoids on purpose complex approaches, e.g. to automate the creation of widgets, in order to keep the code simple and easy to understand for beginners.

Installation

You can install napari-skimage via pip:

pip install napari-skimage

To install latest development version :

pip install git+https://github.com/guiwitz/napari-skimage.git

Usage

The plugin function can be accessed under Plugins -> napari-skimage. Each function will appear as a widget on the right of the napari window. Some functions such as Gaussian Filter give access to a single operation and its options. Some functions such as Thresholding give access to variants of the same operation via a dropdown menu. Currently the plugin does not support multi-channel processing and will consider those as stacks. At the moment, the plugin offers access to the following operation types.

Filtering

A set of classical filters: Gaussian, Prewitt, Laplace etc. as well as rank filters such as median, minimum, maximum etc.

Gaussian filter

Thresholding

A set of thresholding methods: Otsu, Li, Yen etc. Thresholding

Binary morphological operations

A set of binary morphology operations: binary erosion, binary dilation etc. Binary morphological operations

Morphological operations

A set of morphological operations: erosion, dilation, opening, closing etc. Morphological operations

Restoration

A set of restoration operations such as rolling ball, or non-local means denoising. Restoration

Mathematics

In addition the plugin provides a set of simple mathematical operators to:

  • operate on single images e.g. square, square root, log etc.
  • operate on two images e.g. add, subtract, multiply etc. Mathematics

Code structure

Each set of functions is grouped in a separate module. For example all filtering operations are grouped in src/napari_skimge/skimage_filter_widget.py. A set of test in src/_tests/test_basic_widgets.py simply check that each widget can be created and generated an output of the correct size using the default settings.

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" is free and open source software

Issues

If you encounter any problems, please file an issue along with a detailed description.

Version:

  • 0.2.0

Last updated:

  • 11 June 2024

First released:

  • 29 May 2024

License:

Supported data:

  • Information not submitted

Plugin type:

GitHub activity:

  • Stars: 14
  • Forks: 1
  • Issues + PRs: 0

Python versions supported:

Operating system:

Requirements:

  • numpy
  • magicgui
  • qtpy
  • scikit-image