update doc, package and python versions

README.md

@@ -9,7 +9,7 @@
 
 **Images_Alignment** is an application dedicated to ease the images alignment using affine transformation matrices calculated either from the [pyStackReg](https://github.com/glichtner/pystackreg) or [SIFT](https://scikit-image.org/docs/stable/auto_examples/features_detection/plot_sift.html) algorithm, a combined approach, or from a user driven approach (specifying manually the matching points).
 
-Once the parameters have been set, these ones can be applied automatically to a set of images as a workflow.
+Once the parameters have been set, they can be automatically applied to a set of images as part of a workflow.
 
 <p align="center" width="100%">
     <img align="center" width="75%" src=https://cea-metrocarac.github.io/images_alignment/appli.png> <br>

doc/source/index.rst

@@ -2,6 +2,54 @@ Welcome to the Image_Alignment documentation !
 ==============================================
 
 
+**Images_Alignment** is an application dedicated to ease the images alignment using affine transformation matrices calculated either from the `pyStackReg <https://github.com/glichtner/pystackreg)>`_ or `SIFT <https://scikit-image.org/docs/stable/auto_examples/features_detection/plot_sift.html>`_ algorithm, a combined approach, or from a user driven approach (specifying manually the matching points).
+
+Once the parameters have been set, they can be automatically applied to a set of images as part of a workflow.
+
+**This documentation mainly focuses on using the application in GUI mode.**
+
+For a **scripting mode usage**, please refer to the final section of this documentation.
+
+
+Installation
+------------
+
+Assuming you have a python environment which is activated in a terminal, the application can be installed thanks the ``pip`` command:
+
+```bash
+pip install git+https://github.com/CEA-MetroCarac/images_alignment.git
+```
+
+Once installed, the application can be launched directly from a terminal (with the previous python environment activated), by:
+
+```bash
+images_alignment
+```
+
+Tests execution
+---------------
+
+For developers, the full package including examples and tests can be installed via:
+
+```bash
+git clone https://github.com/CEA-MetroCarac/images_alignment.git
+cd images_alignment
+pip install .
+```
+
+The tests can be executed via the following commands:
+
+```bash
+pip install pytest
+pytest tests
+```
+
+
+
+Image_Alignment documentation
+-----------------------------
+
+
 .. toctree::
    :maxdepth: 1
    :caption: GUI Mode

doc/source/user_guide/application.rst

@@ -6,11 +6,11 @@ The application of the previously defined parameters to a set of images is handl
 This requires the user to have pre-defined a **"results"** folder to store the alignment results. This **"results"** folder will contain two sub-folders: **fixed_images** and **moving_images**, which will contain the processed images.
 
 .. note::
-    Since the user can choose to invert the "Fixed/Moving" roles using the ``INV`` button, each **Fixed** (corresponding to a moving image in the ``INV`` mode) is saved with an extension related to its processing order in the workflow.
+    In the case of a 1-to-N image processing, the ``INV`` mode can not be activated.
 
 .. warning::
-    To facilitate the viewing of the realigned images after processing, the images displayed in the visualization windows are those located in the **"results"** directories. Changing the images in the processed set can be done using the image selection frames. Consequently, the displayed images are no longer the original images.
+    To facilitate the viewing of the realigned images after processing, the images displayed in the visualization windows are those located in the **"results"** directories.
 
-    Any new registration will then apply to these processed images and potentially overwrite them.
+    **Consequently**, any new alignment will then be performed from these already processed images, with the risk to overwrite them when saving.
 
-    To reprocess the original images, it is necessary to uncheck the ``Show results`` checkbox.
+    **To go back to the original images, uncheck the ``Show results`` checkbox.**

doc/source/user_guide/intro.rst

@@ -1,11 +1,7 @@
 Introduction
 ============
 
-**Images_Alignment** is an application dedicated to ease the images alignment using affine transformation matrices calculated either from the `pyStackReg <https://github.com/glichtner/pystackreg)>`_ or `SIFT <https://scikit-image.org/docs/stable/auto_examples/features_detection/plot_sift.html>`_ algorithm, a combined approach, or from a user driven approach (specifying manually the matching points).
 
-**This documentation mainly focuses on using the application in GUI mode.**
-
-For scripting mode usage, please refer to the final section of this documentation.
 
 The application's GUI consists of 4 main panels, described in the following pages.
 

doc/source/user_guide/parameters.rst

@@ -1,6 +1,8 @@
 Files selection / Parameters settings
 -------------------------------------
 
+This section and the the following ones address features belonging to the Panel **1** (as defined in the 'Intro' section).
+
 
 Files selection
 ~~~~~~~~~~~~~~~
@@ -33,7 +35,7 @@ The **alignment** is performed in pairs. By consequence the number of selected i
 Defining ROIs
 ~~~~~~~~~~~~~
 
-In addition to defining ROIs (regions of interest) using the mouse, they can also be specified textually in the dedicated fields, following the convention: **[xmin, xmax, ymin, ymax]**, based on the coordinate system of the image displayed in **Panel 4**.
+In addition to defining ROIs (regions of interest) using the mouse ni the main Figure window (Panel **4**), they can also be specified textually in the related fields, following the convention: **[xmin, xmax, ymin, ymax]**, based on the coordinate system of the image displayed in **Panel 4**.
 
 
 .. figure::  ../_static/roi.png

doc/source/user_guide/processing.rst

@@ -18,11 +18,11 @@ With each registration computation, the matrix corresponding to the **affine tra
      [ -0.63508967   1.16203181  52.11186476]
      [  0.           0.           1.        ]]
 
-The ``INV`` mode allows the roles of "fixed" and "moving" images to be reversed.
+The ``INV`` mode allows the roles of **Fixed** and **Moving** images to be reversed during the registration processing.
 
-After registration, the resulting images can be saved via the ``SAVE IMAGES`` button.
+After registration, each of these images can be saved via the ``SAVE IMAGES`` button.
 
-The alignment parameters (e.g., ROIs, binarization thresholds) can also be saved in .json file using ``SAVE PARAMS`` for later reuse with ``RELOAD PARAMS``.
+The alignment parameters (e.g., ROIs, thresholds, ...) can also be saved in a .json file using ``SAVE PARAMS`` for later reuse with ``RELOAD PARAMS``.
 
 .. note::
     To reduce computation times during the registration processing, high-resolution images are sub-sampled to a size of **512 pixels** per  dimension. This criterion can be adjusted through the ``Max image size`` parameter under the **Registration** section in the ``Options`` tab.

doc/source/user_guide/registration.rst

@@ -6,13 +6,13 @@ Registration algorithms
 StackReg
 ~~~~~~~~
 
-This algorithm is based on a minimization processing based on **cross-correlation** of binarized images (of identical size). Binarization and image resizing are handled automatically within the code. Binarization is performed to achieve, as closely as possible, a 50-50 distribution of True-False (or 0-1) values for the selected regions (either ROIs or entire images). In some cases, users have to adjust this threshold in the ``Options`` tab to better highlight features essential for accurate alignment.
+This algorithm is based on a minimization processing based on **cross-correlation** of binarized images of similar size. Binarization and image resizing are handled automatically within the code. Binarization is performed to achieve, by default and as closely as possible, a 50-50 distribution of True-False (or 0-1) values for the selected regions (either ROIs or entire images). In some cases, users have to adjust this threshold in the ``Options`` tab to better highlight features essential for accurate alignment.
 
 .. figure::  ../_static/stackreg_threshold.png
    :align:   center
    :width:   100%
 
-   Adjustment of the Threshold related to the binarization in the ``Options`` tab.
+   Illustration of adjusting the ``Threshold`` in the ``Options`` tab to reveal features.
 
 
 It is important to note that ``StackReg`` relies on a gradient descent method to minimize misalignment. Therefore, it requires the images to already have significant overlap in their features to function effectively.
@@ -40,7 +40,7 @@ Due to the random sampling process used to match features between images, consec
 SIFT + StackReg
 ~~~~~~~~~~~~~~~
 
-This combined approach leverages the strengths of both methods. ``SIFT`` first performs a coarse alignment, bringing potentially highly misaligned images closer together. Then, ``StackReg`` refines this alignment to achieve possibily a higher level of precision.
+This combined approach leverages the strengths of both methods. ``SIFT`` first performs a primary alignment, bringing potentially highly misaligned images closer together. Then, ``StackReg`` refines this alignment to achieve possibily a higher level of precision.
 
 
 User-Driven

doc/source/user_guide/scripting.rst

@@ -1,13 +1,11 @@
 Scripting
 ---------
 
-Every operation performed through the GUI can also be executed in scripting mode.
-
-Below is a brief illustration of image alignment by adjusting a few parameters::
+Every operation performed through the GUI can also be executed in scripting mode. Here is a brief illustration::
 
     from images_alignment import ImagesAlign
 
-    imgalign = ImagesAlign(fixed_images=['img1.tif'], fnames_moving=['img2_1.tif', 'img2_2.tif', 'img2_3.tif', ...])
+    imgalign = ImagesAlign(fixed_images=['img1.tif'], fnames_moving=['img2_1.tif', 'img2_2.tif', ...])
 
     imgalign.angles = [0, 90]
     imgalign.thresholds = [0.50, 0.65]

doc/source/user_guide/visualization.rst

@@ -17,7 +17,7 @@ Once the images to be processed are selected (see next section), **Panel 2** pro
 
 - Selecting the juxtaposition mode: choosing between horizontal or vertical alignment of the images.
 
-- Displaying the Combined images considering the full frame or their overlapping regions only (Apply Mask to ``True``).
+- Displaying the Combined images considering the full frame or their overlapping regions only (enabling ``Apply Mask``).
 
 
 **Panel 3** as 'thumbnails' allows users to select the type of image (**Fixed image**, **Moving image**,  **Juxtaposed images** or **Combined image**) to view in within **Panel 4**.

pyproject.toml

@@ -4,13 +4,20 @@ build-backend = 'setuptools.build_meta'
 
 [project]
 name = "images_alignment"
-version = "2024.2beta"
+version = "2024.2"
 description = "images alignment application"
 authors = [{ name = "Patrick Quéméré", email = "[email protected]" }]
 readme = "README.md"
+requires-python = ">= 3.8"
 classifiers = [
     "License :: OSI Approved :: GNU General Public License v3",
     "Operating System :: OS Independent",
+    "Programming Language :: Python",
+    "Programming Language :: Python :: 3.8",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
 ]
 dependencies = [
     "numpy",