ilastik-napari 0.2.1

ilastik plugin for napari

ilastik-napari

Napari plugin for interactive pixel classification. Designed to be similar to the pixel classification workflow in classic ilastik.

Installation

Currently, this plugin requires you to use a conda environment. If you haven't used conda before, please read conda user guide.

Instad of the default miniconda installation, we highly recommend to use mambaforge. It has better default settings, and the mamba command, which is an (almost) drop-in replacement for conda.

After installing mambaforge, create a new environment with this plugin installed:

mamba create -y -c ilastik-forge -n my-napari-env napari-ilastik

Finally, launch napari in the new environment.

conda activate my-napari-env
napari

Napari Hub and pip

You can also install this plugin via Napari Hub or pip. However, in this case you must do that inside a conda environment with the fastfilters package installed:

mamba create -y -c ilastik-forge -n my-napari-env fastfilters
conda activate my-napari-env
pip install ilastik-napari

Usage

As a prerequisite, make sure you understand the napari basics.

1. Open your image, or use a sample in File - Open Sample.

   

2. Activate the plugin in the Plugins menu.

   

3. In layer list, create a new Labels layer.

   

4. In layers control, switch to the paint action.

   

5. Draw your background labels.

   

6. Switch to a new label.

   

7. Draw your foreground labels.

   

8. Select output types you need, and click Run.

   

9. The plugin will create one layer for each output type, which you save as normal napari layers.

   

Development

Create a development environment:

mamba create -y -n ilastik-napari-dev -c ilastik-forge fastfilters setuptools-scm conda-build anaconda-client
conda activate napari-ilastik-dev
pip install -e .

Build conda package:

conda activate napari-ilastik-dev
mamba build -c ilastik-forge conda-recipe
anaconda upload /path/to/the/new/package.tar.bz2

Build wheel and sdist packages:

conda activate napari-ilastik-dev
pip install build twine
python -m build
python -m twine upload --repository testpypi dist/*