Machine Learning with napari plugins

In this lecture, we will explore how to apply different machine learning algorithms to images using napari plugins. We will do supervised machine learning with napari-apoc plugin and unsupervised machine learning with napari-clusters-plotter plugin. Finally, we will go slightly off-topic to analyze FLIM data with the napari-flim-phasor-plotter plugin.

For this, we will need to create 2 new environments. Please follow the instructions below.

First environemnt: devbio-napari

Open a terminal and type (or copy the line below):

mamba create --name devbio-napari-env python=3.9 devbio-napari pyqt -c conda-forge -c pytorch

Hit ENTER to answer yes when asked to install packages. Activate your environment with:

mamba activate devbio-napari

Second environment: napari-flim-phasor-env

Open a terminal and type (or copy the line below):

mamba create -n napari-flim-phasor-env python=3.9 napari==0.4.17 napari-clusters-plotter git pyqt devbio-napari

Hit ENTER to answer yes when asked to install packages.

Activate your environment with:

mamba activate napari-flim-phasor-env

Then install napari-flim-phasor-plotter with pip:

pip install napari-flim-phasor-plotter