What it does
napari displays multidimensional images and overlays points, polygons or segmentation data for annotation and analysis.
napari lets you keep an image and its derived data together on screen: display the source, overlay labels or points, then inspect and edit the annotations through different slices. Saving those layers depends on a writer that supports the data and requested file format; the label-layer API can choose a suitable installed plug-in or use one you specify. Check that route before starting a large annotation job. The display also has scientific consequences: its guide recommends nearest-neighbour interpolation for many scientific uses because it does not mix adjacent data points. Switching a very large dataset to 3D can trigger computation that runs out of memory.
Strengths
- Overlay images with derived annotations
- Standalone and Python installation routes
Best for
- Inspecting scientific images and segmentation data
Sources
- napari: a fast, interactive viewer for multi-dimensional images in Python — napari (Oct 26, 2026)
- napari Labels save API (Oct 26, 2026)
- napari layers and rendering (Oct 26, 2026)