diff --git a/_sources/usage.rst.txt b/_sources/usage.rst.txt index 2ee172f..20aa2df 100644 --- a/_sources/usage.rst.txt +++ b/_sources/usage.rst.txt @@ -1,5 +1,5 @@ Using affinder ============== -.. include:: ../.napari/DESCRIPTION.md +.. include:: ../README.md :parser: myst_parser.sphinx_ diff --git a/index.html b/index.html index 015d30a..6496148 100644 --- a/index.html +++ b/index.html @@ -204,47 +204,90 @@

Welcome to affinder’s documentation! -

affinder#

-

License -PyPI -Python Version -tests -codecov

-

Quickly find the affine matrix mapping one image to another using manual correspondence points annotation

-
-

Installation#

-

You can install affinder via pip:

-
pip install affinder
-
-
+
+

Description#

+

This GUI plugin allows you to quickly find the affine matrix mapping +one image to another using manual correspondence points annotation.

+

More simply, this plugin allows you to select corresponding points +on an image, and a second image you wish to transform. It computes +the requisite transformation matrix using Affine Transform, Euclidean Transform, +or Similarity Transform, and performs this transformation on the +moving image, aligning it to the reference image.

+
-
-

Documentation#

-

The affinder documentation is available here: https://jni.github.io/affinder/

+
+

Who is This For?#

+

This is a simple plugin which can be used on any 2D images, provided +they can be loaded as layers into napari. The images need not be the same +file format and this plugin also works with labels layers.

+

No prior understanding of the transformation methods is required, as +they perform in the background based on the reference points selected.

-
-

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.

+
+

How to Guide#

+

You will need a combination of two or more 2D image and/or labels layers +loaded into napari. Once you have installed affinder, you can find it in +the dock widgets menu.

+

Affinder widget in the Plugins->Add Dock Widget menu

+

The first two dropdown boxes will be populated with the layers currently +loaded into napari. Select a layer to use as reference, and another to +transform.

+

Dropdowns allow you to select the reference and moving layers

+

Next, you can select the transformation model to use (affine is selected by default +and is the least rigid transformation of those available). See below for a +description of the different models.

+

Finally, you can optionally select a path to a text file for saving out the +resulting transformation matrix.

+

When you click Start, affinder will add two points layers to napari. +The plugin will also bring your reference image in focus, and its associated points +layer. You can then start adding reference points by clicking on your image.

+

Adding reference points to layer

+

Once three points are added, affinder will switch focus to the moving image, +and you should then proceed to select the corresponding three points.

+

Adding corresponding points to newly focused layer

+

affinder will immediately transform the moving image to align the points you’ve +selected when you add your third corresponding point to your moving image.

+

The moving image is transformed once three points are added

+

From there, you can continue iteratively adding points until you +are happy with the alignment. Affinder will switch focus between +reference and moving image with each point.

+

Click Finish to exit affinder.

+
+

Transformation Models#

+

There are three transformation models available for use with affinder. +They are listed here in order of increasing rigidity in the types of +transforms they will allow. The eponymous Affine Transform is the +least rigid and is the default choice.

+
    +

  • Affine Transform: +the least rigid transformation, it preserves +lines and parallelism, but not necessarily distance and angles. Translation, +scaling, similarity, reflection, rotation and shearing are all valid +affine transformations.

    • +

  • Similarity Transform: +this is a “shape preserving” transformation, producing objects which are +geometrically similar. Translation, rotation, reflection and uniform scaling are +valid similarity transforms. Shearing is not.

    • +

  • Euclidean Transform: +Also known as a rigid transformation, this transform preserves the Euclidean +distance between each pair of points on the image. This includes rotation, +translation and reflection but not scaling or shearing.

    • +
-
-

License#

-

Distributed under the terms of the BSD-3 license, -“affinder” is free and open source software

-
-

Issues#

-

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

-
-

This napari plugin was generated with Cookiecutter using with @napari’s cookiecutter-napari-plugin template.

-
+
+

Getting Help#

+

If you find a bug with affinder, or would like support with using it, please raise an +issue on the GitHub repository.

+
+
+

How to Cite#

+

Many plugins may be used in the course of published (or publishable) research, as well as +during conference talks and other public facing events. If you’d like to be cited in +a particular format, or have a DOI you’d like used, you should provide that information here.

@@ -304,14 +347,14 @@

Indices and tables
  • Welcome to affinder’s documentation!
      -
    • affinder
    • Indices and tables
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