Metadata-Version: 2.1
Name: napari-pystackreg
Version: 0.1.1
Summary: Robust image registration for napari
Home-page: https://github.com/glichtner/napari-pystackreg
Author: Gregor Lichtner
Author-email: gregor.lichtner@med.uni-greifswald.de
License: Apache-2.0
Project-URL: Bug Tracker, https://github.com/glichtner/napari-pystackreg/issues
Project-URL: Documentation, https://github.com/glichtner/napari-pystackreg#README.md
Project-URL: Source Code, https://github.com/glichtner/napari-pystackreg
Project-URL: User Support, https://github.com/glichtner/napari-pystackreg/issues
Classifier: Development Status :: 4 - Beta
Classifier: Framework :: napari
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Software Development :: Testing
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Provides-Extra: testing
License-File: LICENSE

# napari-pystackreg

[![License](https://img.shields.io/pypi/l/napari-pystackreg.svg?color=green)](https://github.com/glichtner/napari-pystackreg/raw/main/LICENSE)
[![PyPI](https://img.shields.io/pypi/v/napari-pystackreg.svg?color=green)](https://pypi.org/project/napari-pystackreg)
[![Python Version](https://img.shields.io/pypi/pyversions/napari-pystackreg.svg?color=green)](https://python.org)
[![tests](https://github.com/glichtner/napari-pystackreg/workflows/tests/badge.svg)](https://github.com/glichtner/napari-pystackreg/actions)
[![codecov](https://codecov.io/gh/glichtner/napari-pystackreg/branch/main/graph/badge.svg)](https://codecov.io/gh/glichtner/napari-pystackreg)
[![napari hub](https://img.shields.io/endpoint?url=https://api.napari-hub.org/shields/napari-pystackreg)](https://napari-hub.org/plugins/napari-pystackreg)

Robust image registration for napari.

Summary
-------
napari-pystackreg offers the image registration capabilities of the python package
[pystackreg](https://github.com/glichtner/pystackreg) for napari.

Description
-----------
pyStackReg is used to align (register) one or more images to a common reference image, as is required usually in
time-resolved fluorescence or wide-field microscopy.
It is directly ported from the source code of the ImageJ plugin ``TurboReg`` and provides additionally the
functionality of the ImageJ plugin ``StackReg``, both of which were written by Philippe Thevenaz/EPFL
(available at http://bigwww.epfl.ch/thevenaz/turboreg/).

pyStackReg provides the following five types of distortion:

- translation
- rigid body (translation + rotation)
- scaled rotation (translation + rotation + scaling)
- affine (translation + rotation + scaling + shearing)
- bilinear (non-linear transformation; does not preserve straight lines)

pyStackReg supports the full functionality of StackReg plus some additional options, e.g., using different reference
images and having access to the actual transformation matrices (please see the examples below). Note that pyStackReg
uses the high quality (i.e. high accuracy) mode of TurboReg that uses cubic spline interpolation for transformation.

Please note: The bilinear transformation cannot be propagated, as a combination of bilinear transformations does not
generally result in a bilinear transformation. Therefore, stack registration/transform functions won't work with
bilinear transformation when using "previous" image as reference image. You can either use another reference (
"first" or "mean" for first or mean image, respectively), or try to register/transform each image of the stack
separately to its respective previous image (and use the already transformed previous image as reference for the
next image).



----------------------------------

This [napari] plugin was generated with [Cookiecutter] using [@napari]'s [cookiecutter-napari-plugin] template.


## Installation

You can install `napari-pystackreg` via [pip]:

    pip install napari-pystackreg



To install latest development version :

    pip install git+https://github.com/glichtner/napari-pystackreg.git


## Contributing

Contributions are very welcome. Tests can be run with [tox], please ensure
the coverage at least stays the same before you submit a pull request.

## License

Distributed under the terms of the [Apache Software License 2.0] license,
"napari-pystackreg" is free and open source software

## Issues

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

[napari]: https://github.com/napari/napari
[Cookiecutter]: https://github.com/audreyr/cookiecutter
[@napari]: https://github.com/napari
[MIT]: http://opensource.org/licenses/MIT
[BSD-3]: http://opensource.org/licenses/BSD-3-Clause
[GNU GPL v3.0]: http://www.gnu.org/licenses/gpl-3.0.txt
[GNU LGPL v3.0]: http://www.gnu.org/licenses/lgpl-3.0.txt
[Apache Software License 2.0]: http://www.apache.org/licenses/LICENSE-2.0
[Mozilla Public License 2.0]: https://www.mozilla.org/media/MPL/2.0/index.txt
[cookiecutter-napari-plugin]: https://github.com/napari/cookiecutter-napari-plugin

[file an issue]: https://github.com/glichtner/napari-pystackreg/issues

[napari]: https://github.com/napari/napari
[tox]: https://tox.readthedocs.io/en/latest/
[pip]: https://pypi.org/project/pip/
[PyPI]: https://pypi.org/
