indices

napari-indices

Calculer les indices de végétation

License BSD-3 PyPI Python Version tests codecov napari hub

Calculer les indices de végétation


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

Emmanuella OKAFOR (L3 PA CMI-PSI_Université d'Angers) developed this plugin during her internship with a french team called ImHorPHen (lead by David ROUSSEAU). This plugin realises vegetation indexes computation with hyperspectral images. For the momment, there are five vegetation indexes : NDVI, TCARI, NPCI, SGI, NDGI.

Installation

You can install napari-indices via pip:

pip install napari-indices

To install latest development version :

pip install git+https://github.com/Emmanulla0/napari-indices.git

Plugin description

Using this plugin requires importing the bands of a hyperspectral image into a tif file, in our case, 160 bands. You must launch it by accessing the Plugins > napari-indices> Vegetation indices menu.

Capture d'écran 2023-05-29 124720

Then select the vegetation index to be calculated and the different bands to be used, then click the Run button to start the calculation. This results in the images corresponding to the calculated indices.

etape_2

The areas of interest to be analysed must then be defined. To do this, click the Shapes button on the Napari interface and choose the add rectangle shape from the menu that appears. Using the mouse, it is then possible to draw a rectangle on each of the two areas to be analyzed, for example a tree sheet and a green sheet of paper.

etape_3

To perform the Fisher ratio calculation and display the histogram, it is necessary to go back to the Plugins > napari-indices > ExempleQWidget menu and click the **Click me! **. This action opens a new window displaying the best vegetation index to use, its corresponding Fisher ratio and the histogram of the two selected regions on the image of the vegetation index concerned. A video explaining the plugin is available at: https://uabox.univ-angers.fr/index.php/s/LqB0qs11n3jxZVJ.

Histogram

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-indices" is free and open source software

Issues

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

Version:

  • 0.0.2

Last updated:

  • 31 May 2023

First released:

  • 30 May 2023

License:

Supported data:

  • Information not submitted

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GitHub activity:

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

Python versions supported:

Operating system:

Requirements:

  • numpy
  • magicgui
  • qtpy
  • spectral
  • matplotlib
  • tifffile