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napari-stitcher

napari-stitcher

Stitch napari image layers in 2-3D+t

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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.

Quick guide:

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

Demo

https://github.com/user-attachments/assets/8773e49f-af18-4ff3-ab2f-2a5f1b1cadf2

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

Documentation

Head over to the user guide for more details.

Installation

You can install napari-stitcher via pip:

pip install napari-stitcher

For more installation options, see the installation docs.

Contributing

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

License

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

Issues

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

Version:

  • 0.1.1

Last updated:

  • 02 April 2025

First released:

  • 18 October 2024

License:

Supported data:

  • Information not submitted

Open extension:

Save extension:

Save layers:

GitHub activity:

  • Stars: 16
  • Forks: 5
  • Issues + PRs: 5

Python versions supported:

Operating system:

Requirements:

  • dask
  • magicgui
  • multiscale_spatial_image
  • multiview-stitcher>=0.1.19
  • napari
  • numpy>=1.18
  • qtpy
  • spatial_image
  • tifffile>=2022.7.28
  • tqdm
  • xarray