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napari-orientationpy

Analyze greylevel orientations in 2D and 3D in Napari. This plugin is based on the Orientationpy project.

Installation

Python installation

You can install napari-orientationpy as a Python package via pip:

pip install napari-orientationpy

Executable installer

Alternatively, you can download, unzip, and execute the latest installer from the Releases page to install napari-orientationpy as a standalone app. The first time you run the app, it'll take some time to install the project on your computer (this is only on the first run).

Usage

To get started, open an image in the Napari viewer and start napari-orientationpy from the Plugins menu:

Plugins > Orientation measurement (Napari Orientationpy)
  1. Select the structural scale parameter sigma. This value control represents the scale at which the image gradients are computed. Try different values of sigma to understand what works best for your images. A reasonable guess would be the order in size, in pixels, of the structures that you are interested in. For example, if you are imaging fibers that appear to be about 4 pixels wide, try to set a value of sigma=4.

  1. If you are analyzing a 3D image, select fiber or membrane mode. In fiber mode, the orientation normals follow fibrous structures. In membrane mode, the orientations are normal to the surface of membranous structures.

  2. Decide which outputs you'd like to visualize.

  • The color-coded orientation is a pixel-wise representation of 3D orientations as colors (similar colors = similar orientations).
  • The orientation vectors get rendered in a Vectors layer in Napari. They are sampled on a regular grid defined by the Spacing (X), Spacing (Y) and Spacing (Z) values (for 2D images, the Z value is ignored).
  • You can also output the local orientation gradient (misorientation).
  1. Compute orientation. This button will trigger the orientation computation only when necessary (i.e. when the value of sigma, the mode or the image have changed). If you only adjust the orientation vectors parameters, clicking the compute button will update the results very fast.
  2. Save orientation (CSV). This will save the orientation measurements as a CSV table with columns X, Y, Z, theta, phi, for all the pixels in the image.

Sample images

We provide a few sample images to test our plugin. You can open them from:

File > Open Sample > Napari Orientationpy

Contributing

Contributions are very welcome.

License

This software is distributed under the terms of the BSD-3 license.

Issues

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

Acknowledgements

This project uses the PyApp software for creating a runtime installer.

Metadata

Release files for napari-orientationpy 0.1.1

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Source distribution for napari-orientationpy 0.1.1
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