HTTomolibGPU is a library of GPU accelerated methods for tomography

HTTomolibGPU is a collection of image processing methods in Python for computed tomography. The methods are GPU-accelerated with the open-source Python library CuPy <https://cupy.dev/>. Most of the methods migrated from TomoPy <https://tomopy.readthedocs.io/en/stable/> and Savu <https://savu.readthedocs.io/en/latest/>_ software packages. Some of the methods also have been optimised to ensure higher computational efficiency, before ported to CuPy.

The purpose of HTTomolibGPU

HTTomolibGPU can be used as a stand-alone library, see Examples section in Documentation <https://diamondlightsource.github.io/httomolibgpu/>. However, it has been specifically developed to work together with the HTTomo <https://diamondlightsource.github.io/httomo/> package as its backend for data processing. HTTomo is a user interface (UI) written in Python for fast big tomographic data processing using MPI protocols.

Install HTTomolibGPU as a pre-built conda Python package

.. code-block:: console

$ conda create --name httomolibgpu # create a fresh conda environment $ conda activate httomolibgpu # activate the environment $ conda install -c httomo httomolibgpu -c astra-toolbox -c rapidsai -c conda-forge # for linux users $ conda install -c httomo httomolibgpu -c astra-toolbox -c jplumail -c conda-forge # for windows users

Setup the development environment:

.. code-block:: console

$ git clone git@github.com:DiamondLightSource/httomolibgpu.git # clone the repo $ conda env create --name httomolibgpu --file conda/environment.yml # install dependencies $ conda activate httomolibgpu # activate the environment $ pip install -e .[dev] # editable/development mode

Build HTTomolibGPU as a conda Python package

.. code-block:: console

$ conda build conda/recipe/ -c conda-forge -c httomo -c astra-toolbox -c rapidsai