Installation#
SCIP can be installed from the PyPi repository, or from source.
We recommend installing SCIP in a conda environment using mambaforge.
Prerequisites#
If you want to use GPU-accelerated Cellpose segmentation, make sure to install a compatible cudatoolkit. The version you need depends on which GPU model you want to use.
If you want to run SCIP on a dask-mpi cluster, an MPI implementation must be available. We recommend installing mpich.
mamba install -c conda-forge mpich-mpicc
PyPi#
SCIP can be installed from the PyPi repository. The base installation can be installed as follows:
pip install scip
There are also optional dependencies: * mpi: Add support for running SCIP using a dask-mpi cluster, * cellpose: Add support for cellpose functionality, * czi: Add support for reading Carl Zeiss Image files, and * dev: Installing extra package related to development.
These can be installed using pip’s bracket notation:
pip install scip[mpi]
pip install scip[cellpose]
pip install scip[cellpose,mpi,czi]
From source#
To install SCIP from source:
Download the latest release from Github, or clone the repository.
Optionally extract the release.
Enter the repository directory.
Run
pip install .
if you only need default functionality.(Optional) Run
pip install .[extra]
for extra functionality (refer to the list above for available extras)