napari

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 (numpy, scipy).

We're developing napari in the open! You can follow progress on [our project roadmap](https://github.com/napari/napari (opens in a new tab)), test out new versions as we release them, and contribute ideas and code.

If you want to refer to our documentation, please go to napari.org (opens in a new tab). If you want to contribute to it, please refer to the contributing section below.

We're working on tutorials (opens in a new tab), but you can also quickly get started by looking below.

try it out now!

Install uv (opens in a new tab) to try napari. Then launch the program in a terminal window with the command: In the File menu, select Open Sample and select a sample image to get started.

simple example

This example uses a data sample from the scikit-image library, but you can pass your own dataset as an array to imshow. From inside an IPython shell, you can open up an interactive viewer by calling

To use napari from inside a script, use napari.run():

features

Check out the scripts in our [examples folder](examples) to see some of the functionality we're developing!

napari supports six main different layer types, Image, Labels, Points, Vectors, 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.