SDeconv

SDeconv is a python framework to develop scientific image deconvolution algorithms. This library has been developed for microscopy 2D and 3D images, but can be use to any image deconvolution application.

System Requirements

Software Requirements

OS Requirements

The SDeconv development version is tested on Windows 10, MacOS and Linux operating systems. The developmental version of the package has been tested on the following systems:

• Linux: 20.04.4
• Mac OSX: Mac OS Catalina 10.15.7
• Windows: 10

install

Library installation from PyPI

1. Install an Anaconda distribution of Python -- Choose Python 3.9 and your operating system. Note you might need to use an anaconda prompt if you did not add anaconda to the path.
2. Open an anaconda prompt / command prompt with conda for python 3 in the path
3. Create a new environment with conda create --name sdeconv python=3.9.
4. To activate this new environment, run conda activate sdeconv
5. To install the SDeconvlibrary, run python -m pip install sdeconv.

if you need to update to a new release, use:

python -m pip install sdeconv --upgrade

Library installation from source

This installation is for developers or people who want the last features in the main branch.

1. Install an Anaconda distribution of Python -- Choose Python 3.9 and your operating system. Note you might need to use an anaconda prompt if you did not add anaconda to the path.
2. Open an anaconda prompt / command prompt with conda for python 3 in the path
3. Create a new environment with conda create --name sdeconv python=3.9.
4. To activate this new environment, run conda activate sdeconv
5. Pull the source code from git with `git pull https://github.com/sylvainprigent/sdeconv.git
6. Then install the SDeconv library from you local dir with: python -m pip install -e ./sdeconv.

Use SDeconv with napari

The SDeconv library is embedded in a napari plugin that allows using SDeconv with a graphical interface. Please refer to the SDeconv napari plugin documentation to install and use it.

SDeconv documentation

The full documentation with tutorial and docstring is available here