{"id":25895574,"url":"https://github.com/diamondlightsource/httomolibgpu","last_synced_at":"2025-03-02T22:32:03.352Z","repository":{"id":64333303,"uuid":"569698017","full_name":"DiamondLightSource/httomolibgpu","owner":"DiamondLightSource","description":"A library of GPU-enabled data processing and reconstruction methods for tomography","archived":false,"fork":false,"pushed_at":"2024-05-23T08:17:57.000Z","size":48541,"stargazers_count":4,"open_issues_count":6,"forks_count":4,"subscribers_count":5,"default_branch":"main","last_synced_at":"2024-05-23T08:57:49.455Z","etag":null,"topics":["cupy","data-science","filters","gpu-acceleration","image-processing","tomography"],"latest_commit_sha":null,"homepage":"https://diamondlightsource.github.io/httomolibgpu/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/DiamondLightSource.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-11-23T12:16:56.000Z","updated_at":"2024-05-28T12:18:42.831Z","dependencies_parsed_at":"2024-05-23T09:05:02.414Z","dependency_job_id":null,"html_url":"https://github.com/DiamondLightSource/httomolibgpu","commit_stats":null,"previous_names":[],"tags_count":6,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DiamondLightSource%2Fhttomolibgpu","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DiamondLightSource%2Fhttomolibgpu/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DiamondLightSource%2Fhttomolibgpu/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/DiamondLightSource%2Fhttomolibgpu/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/DiamondLightSource","download_url":"https://codeload.github.com/DiamondLightSource/httomolibgpu/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":241582515,"owners_count":19985845,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cupy","data-science","filters","gpu-acceleration","image-processing","tomography"],"created_at":"2025-03-02T22:32:02.857Z","updated_at":"2025-03-02T22:32:03.341Z","avatar_url":"https://github.com/DiamondLightSource.png","language":"Python","readme":"HTTomolibGPU is a library of GPU accelerated methods for tomography\n--------------------------------------------------------------------\n\n**HTTomolibGPU** is a collection of image processing methods in Python for computed tomography.\nThe methods are GPU-accelerated with the open-source Python library `CuPy \u003chttps://cupy.dev/\u003e`_. Most of the\nmethods migrated from `TomoPy \u003chttps://tomopy.readthedocs.io/en/stable/\u003e`_ and `Savu \u003chttps://savu.readthedocs.io/en/latest/\u003e`_ software packages.\nSome of the methods also have been optimised to ensure higher computational efficiency, before ported to CuPy.\n\nThe purpose of HTTomolibGPU\n===========================\n\nAlthough **HTTomolibGPU** can be used as a stand-alone library, it has been specifically developed to work together with the \n`HTTomo \u003chttps://diamondlightsource.github.io/httomo/\u003e`_ package as\nits backend for data processing. HTTomo is a user interface (UI) written in Python for fast big tomographic data processing using\nMPI protocols or as well serially.\n\nInstall HTTomolibGPU as a PyPi package\n=========================================================\n.. code-block:: console\n\n   $ pip install httomolibgpu\n\nInstall HTTomolibGPU as a pre-built conda Python package\n=========================================================\n.. code-block:: console\n\n   $ conda create --name httomolibgpu # create a fresh conda environment\n   $ conda activate httomolibgpu # activate the environment\n   $ conda install -c httomo httomolibgpu -c conda-forge # for linux users\n\nSetup the development environment:\n==================================\n\n.. code-block:: console\n\n   $ git clone git@github.com:DiamondLightSource/httomolibgpu.git # clone the repo\n   $ conda env create --name httomolibgpu --file conda/environment.yml # install dependencies\n   $ conda activate httomolibgpu # activate the environment\n   $ pip install -e .[dev] # editable/development mode\n\nBuild HTTomolibGPU as a conda Python package\n============================================\n\n.. code-block:: console\n\n   $ conda build conda/recipe/ -c conda-forge -c httomo\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdiamondlightsource%2Fhttomolibgpu","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdiamondlightsource%2Fhttomolibgpu","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdiamondlightsource%2Fhttomolibgpu/lists"}