Metadata-Version: 2.1
Name: pyolaf
Version: 0.2.0
Summary: 3D reconstruction framework for light field microscopy
Home-page: https://github.com/lambdaloop/pyolaf
Author: Lili Karashchuk
Author-email: krchtchk@gmail.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Image Recognition
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pyyaml
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: tqdm
Requires-Dist: tifffile
Requires-Dist: scikit-image
Requires-Dist: matplotlib
Provides-Extra: gpu
Requires-Dist: cupy ; extra == 'gpu'

# pyolaf - A Python-based 3D reconstruction framework for light field microscopy

pyolaf is a Python port of the [oLaF](https://gitlab.lrz.de/IP/olaf/) 3D reconstruction framework for light field microscopy (LFM). 

## Overview
  
The light field microscope (LFM) allows for 3D imaging of fluorescent specimens using an array of micro-lenses (MLA) that capture both spatial and directional light field information in a single shot. oLaF is a Matlab framework for 3D reconstruction of LFM data that makes use of advanced algorithms for artifact-free deconvolution and Fourier integral microscopy. 

pyolaf brings these same features to the Python ecosystem, using GPU acceleration and some further code optimizations to **speed up deconvolution by 20x**. 

## Limitations

pyolaf only supports regular grids and single-focus conventional light-field microscopes.
In particular Fourier LFM, hexagonal grids, and multi-focus lenslets are currently not supported.
Pull requests to add these are welcome!

## Copyright

Copyright (c) 2017-2020 Anca Stefanoiu, Josue Page, and Tobias Lasser -- original oLaF code  
Copyright (c) 2023 Lili Karashchuk -- pyolaf

## Citation

When using pyolaf in academic publications, please reference the following citation:

- A. Stefanoiu et. al., "Artifact-free deconvolution in light field microscopy", Opt. Express, 27(22):31644, (2019).

