Optica 2023 pulibcation : Quantitative hyperspectral microscopy using encoded illumination and neural networks with physics priors

This code generates the figures in the article and allow to study the data used.

Authors: S Crombez,N Ducros

Contact: [email protected], CREATIS Laboratory, University of Lyon, France.

Install the dependencies

1. We recommend creating a virtual (e.g., conda) environment first.

   # conda install
   conda create --name new-env
   conda activate new-env
   conda install spyder
   conda install -c conda-forge matplotlib
   conda install -c conda-forge jupyterlab
   conda install -c anaconda scikit-image
   conda install -c anaconda h5py 
   conda install pytorch torchvision torchaudio cudatoolkit=11.6 -c pytorch -c conda-forge

   Alternatively, you can clone an existing environment with conda create --name new-env --clone existing-env

2. Clone the spyrit package, and install the version in the towards_v2_fadoua branch

   git clone https://github.com/openspyrit/spyrit.git
   cd spyrit
   git checkout towards_v2
   pip install -e .

3. Clone the spas package:

   git clone https://github.com/openspyrit/spas.git
   cd spas
   pip install -e .

Get the notebooks and the data

1. Get source code and navigate to the /2023_Optica/ folder

   git clone https://github.com/openspyrit/spyrit-examples.git
   cd spyrit-examples/2023_Opyica/ 

2. Download the models from this link A Changer