semvec/pypi-packages huggingface dataset:
napari-stitcher 0.1.2
Stitch napari image layers in 2-3D+t
License: BSD-3-Clause
Requires Python: >=3.10

[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-stitcher)](https://napari-hub.org/plugins/napari-stitcher)
[![License {{cookiecutter.license}}](https://img.shields.io/pypi/l/napari-stitcher.svg?color=green)](https://github.com/multiview-stitcher/napari-stitcher/raw/main/LICENSE)
[![PyPI](https://img.shields.io/pypi/v/napari-stitcher.svg?color=green)](https://pypi.org/project/napari-stitcher)
[![Python Version](https://img.shields.io/pypi/pyversions/napari-stitcher.svg?color=green)](https://python.org)
[![tests](https://github.com/multiview-stitcher/napari-stitcher/actions/workflows/test_and_deploy.yml/badge.svg)](https://github.com/multiview-stitcher/napari-stitcher/actions)
[![codecov](https://codecov.io/gh/multiview-stitcher/napari-stitcher/branch/main/graph/badge.svg)](https://codecov.io/gh/multiview-stitcher/napari-stitcher)
[![DOI](https://zenodo.org/badge/697999800.svg)](https://zenodo.org/doi/10.5281/zenodo.14176362)


# napari-stitcher

A napari plugin for stitching large multi-positioning datasets in 2/3D+t using [`multiview-stitcher`](https://github.com/multiview-stitcher/multiview-stitcher).

![](docs/images/napari-stitcher-loaded-mosaic-annotated.png)
<small>Image data by Arthur Michaut @ Jérôme Gros Lab @ Institut Pasteur.</small>

#### Quick guide:

1. Directly stitch napari layers: Use napari to load, visualize and [preposition](prearrangement.md) the tiles to be stitched.
2. When working with multi-channel data, stick to the following [naming convention](naming_convention.md): `{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

<small>This demo uses the awesome [`napari-threedee`](https://github.com/napari-threedee/napari-threedee) for prepositioning the tiles. Image data: [BigStitcher](https://imagej.net/plugins/bigstitcher/).</small>

## Documentation

Head over to the [user guide](https://multiview-stitcher.github.io/napari-stitcher/main/) for more details.

## Installation

You can install `napari-stitcher` via `pip`:

```bash
pip install napari-stitcher
```

For more installation options, see the [installation docs](https://multiview-stitcher.github.io/napari-stitcher/main/installation/).

## 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](https://github.com/multiview-stitcher/napari-stitcher/issues) along with a detailed description.