napari-stitcher

A napari plugin for stitching large multi-positioning datasets in 2/3D+t using multiview-stitcher.

Image data by Arthur Michaut @ Jérôme Gros Lab @ Institut Pasteur.

Directly stitch napari layers: Use napari to load, visualize and preposition the tiles to be stitched.
When working with multi-channel data, stick to the following naming convention: {tile} :: {channel}.
Load either all or just a subset of the layers into the plugin.
Choose registration options: registration channel, binning and more.
Stitching = registration (refining the positions, optional) + fusion (joining the tiles into a single image).
The registration result is shown in the viewer and the fused channels are added as new layers.

Demo

This demo uses the awesome napari-threedee for prepositioning the tiles. Image data: BigStitcher.

Head over to the user guide for more details.

You can install napari-stitcher via pip:

pip install napari-stitcher

For more installation options, see the installation docs.

Contributions are very welcome. Tests can be run with tox.

Distributed under the terms of the [BSD-3] license, "napari-stitcher" is free and open source software

If you encounter any problems, please file an issue along with a detailed description.

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

napari_stitcher-0.1.4.tar.gz (19.1 MB view details)

Uploaded Apr 13, 2026 Source

If you're not sure about the file name format, learn more about wheel file names.

The dropdown lists show the available interpreters, ABIs, and platforms. Enable javascript to be able to filter the list of wheel files.

Uploaded Apr 13, 2026 Python 3

Details for the file napari_stitcher-0.1.4.tar.gz.

Hashes for napari_stitcher-0.1.4.tar.gz
Algorithm	Hash digest
SHA256	`345cb7d0df77f080e85e155328d1222bd897ae99031ef5a41d2558b6ec31d8d0`
MD5	`21ec5d39e02be36b870382298df3ab48`
BLAKE2b-256	`32975a59d1153af07a3f4edec56354970964c95b1ff4ae7de58b563fb2f1ddf6`

Details for the file napari_stitcher-0.1.4-py3-none-any.whl.

Hashes for napari_stitcher-0.1.4-py3-none-any.whl
Algorithm	Hash digest
SHA256	`8d5e52147d3c9c966e89d3c7d0e5c929861baa98714c3f75be766739362ac37f`
MD5	`3417b0aa04a10481cf2c2a87398ba497`
BLAKE2b-256	`64808ccb969dfe67c8a674c2b2ee1747a459b3414fee10b5c1f6ca53d174bede`