Multi-dimensional image viewer for python

napari is a fast, interactive, multi-dimensional image viewer for Python. It’s designed for browsing, annotating, and analyzing large multi-dimensional images. It’s built on top of Qt (for the GUI), vispy (for performant GPU-based rendering), and the scientific Python stack (numpyscipy). It includes critical viewer features out-of-the-box, such as support for large multi-dimensional data, and layering and annotation. By integrating closely with the Python ecosystem, napari can be easily coupled to leading machine learning and image analysis tools (e.g. scikit-imagescikit-learnTensorFlowPyTorch), enabling more user-friendly automated analysis.

napari is developed in the open! Currently the project is in an alpha stage, and there will still likely be breaking changes with each release. You can follow progress on its GitHub repository, test new versions as being released, and contribute ideas and code.


Check out the scripts in napari examples folder to see some of the functionality developed! napari supports six main different layer types, ImageLabelsPointsVectors, Shapes, and Surface, each corresponding to a different data type, visualization, and interactivity. You can add multiple layers of different types into the viewer and then start working with them, adjusting their properties.

All layer types support n-dimensional data and the viewer provides the ability to quickly browse and visualize either 2D or 3D slices of the data.

napari also supports bidirectional communication between the viewer and the Python kernel, which is especially useful when launching from jupyter notebooks or when using our built-in console. Using the console allows you to interactively load and save data from the viewer and control all the features of the viewer programmatically.

You can extend napari using custom shortcuts, key bindings, and mouse functions.

For more information about the developers plans for napari you can read their mission and values statement, which includes more details on their vision for supporting a plugin ecosystem around napari.

napari logo was apparently inspired by a NASA 2006 image of Tabuaeran atollKiribati in Pacific ocean

Github page, Project Homepage

Installation Info, Installation Guide

Getting Started Guide, Tutorials, How-to guides

In-depth explanations,


Community Resources, API reference, Dev Resources, Glossary

Release Notes, Roadmaps

napari-hub: a service of the Chan Zuckerberg Initiative in collaboration with napari seeking to solve many of the challenges and needs in finding analysis solutions to bioimaging problems. You can explore how the hub is being built in the open (including research studies, design prototypes and technical specs) by visiting its GitHub repository.

Reference Publications


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