A simple image-level annotation tool supporting multi-channel images for napari.

Overview

napari-labelimg4classification

License PyPI Python Version tests codecov napari hub

A simple image-level annotation tool supporting multi-channel images for napari.


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

Usage

Start the labeling tool from the menu Utilities > label tool for classification.
First, click on the Choose directory button to open the folder selection window, and select the folder that contains the images you want to label and annotate.
It will automatically list and display the images of tif, png, jpg, and bmp formats. If you want to view the channels of a multi-channel image separately, check the split channels checkbox.

Initially, all channels will be opened in grayscale, but the pseudo-color and contrast adjustments you specified will be carried over when you open the next image.
Thanks to napari, you can freely merge channels and turn them on and off.
Label classes can be added, and can be removed by typing the same name as an already added class.

It will automatically save the labels.csv file with the image path and label, and the class.txt file with the class of the label.

If labels.csv and class.txt are already in the folder, they will be loaded and reflected automatically.

Installation

You can install napari-labelimg4classification via pip:

pip install napari-labelimg4classification

To install latest development version :

pip install git+https://github.com/hiroalchem/napari-labelimg4classification.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 MIT license, "napari-labelimg4classification" is free and open source software

Issues

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

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