This is a three-part workshop that takes you begins with an introduction to napari, its interface and its layers using a simple image analysis exercise. We then look at extending napari's functionality with custom event handlers, keybindings and widgets. Finally, we look at how your new custom functionality can be packaged into a pip-installable napari plugin.
Use the installation guide to prepare your environment and install napari and its required dependencies.
In this section we introduce napari's interface, opening and exploring images and other napari layer types, and the bi-directional interactions between the napari viewer and a Jupyter notebook. The napari application document will walk you through the basics.
The next step is interactive image analysis. Follow through the interactive analysis notebook to learn how to use napari, a Jupyter notebook and scikit-image to perform an image segmentation.
We explore three easy ways to add custom functionality to napari to support interactive analysis:
- Event handlers are functions that are executed when different viewer and layer events occur
- Keybinding/mouse handlers are custom functions that are executed when you press a key sequence or click the mouse
- Widgets are custom GUI elements like checkboxes, dropdown menus, buttons and sliders, that you can add to the viewer with simple Python code
Follow through the event handlers and widget notebook to learn how to use these different elements to customize your analysis.
Now that you've learned how to use napari and built our own custom elements, you might want to share them with your coworkers or with the napari community at large! This section walks you through packaging your functionality into a pip-installable napari plugin. Follow through the Creating a napari plugin document to learn how to declare and install a plugin.