Package: cbi-toolbox
CBI ToolboxCBI Toolbox is a collection of algorithms used for computational bioimaging and microscopy.CBI Toolbox is suitable for large scale 3D simulations to reproduce realistic sample sizes and sampling resolution thanks to hardware acceleration (both GPU and multithreading) and optimized implementation of the algorithms.
It is flexible enough to emulate different acquisition geometries, and also contains a set of tools used for quantitative evaluation of imaging methods.
The framework can also be used for experiment design, as geometries can be virtually tested before being implemented on real acquisition devices... image:: docs/cover.svg
:alt: Demo imageCopyright (c) 2020 Idiap Research Institute,http://www.idiap.ch/Written by François Marellifrancois.marelli@idiap.chFor documentation, seehttps://cbi-toolbox.readthedocs.ioInstall instructionsRequirements:Python>=3.7OpenMP>=2MPI (optional, for parallel module)CudaToolkit>=8 (optional, for GPU support)Using pipPip >=10 is highly recommended to ensure the install works.Run pip install:pip install cbi-toolbox[mpi,plots,docs](choose optional packages according to your needs)Install from sources:Clone the project with its submodules:git clone --recursive <url>Run pip install in the root folder:pip install .[mpi,plots,docs](choose optional packages according to your needs)Optional dependenciesThe package provides optional dependencies that can be selected  at will during
the install (in the square brackets):mpi: allows to use thecbi_toolbox.parallel.mpimodule,
requires a functional MPI installationplots: installs tools to visualize 3D objects easilydocs: installs tools used to generate the documentationUsing condaClone the project with its submodules:git clone --recursive <url>Create a new environment unsing the environment.yml file:conda env create -f environment.yml -n <environment name>Run pip install on the root folder:pip install .[mpi,plots,docs](choose optional packages according to your needs)If you already have an MPI implementation installed on your system, it is possible
that conda installs a different one. If you want compatibility with your system MPI,
uninstall the condampi4pyandmpipackages, then installmpi4pyusing pip. It
will automatically use your system's MPI version for compilation.CUDA supportIf nvcc is present on the machine, the installation will automatically attempt
to compile the software with CUDA support. If you have multiple versions of the
CUDA toolkit installed, or if CMake fails to find nvcc automatically, make sure
to set the environment variableCUDAToolkit_ROOTto point to the correct
tookit folder.To debug potential installation errors, usepip install . -vto get verbose
build logs.After install, run the following::import cbi_toolbox.splineradon as spl
spl.is_cuda_available(True)If the output is other thanCUDA support is not installed., the CUDA acceleration
was installed successfully.Citing CBI ToolboxIf you use this package and wish to aknowledge it in an academic publication,
please cite the following paper:Marelli, F. and Liebling, M. *"Optics versus computation: influence of
illumination and reconstruction model accuracy in Focal-plane-scanning optical
projection tomography."* 2021 IEEE 18th International Symposium on Biomedical
Imaging (ISBI). IEEE, 2021.AcknowledgementsThis work was supported by the Swiss National Science Foundation (SNSF), Grants:206021_164022Platform for Reproducible Acquisition, Processing, and Sharing of Dynamic, Multi-Modal Data.(PLATFORM_MMD)200020_179217Computational biomicroscopy: advanced image processing methods to quantify live biological systems(COMPBIO)