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@clEsperanto

clEsperanto

GPU-accelerated image processing across languages and platforms

About Clesperanto

The clesperanto project is a multi-language and multi-platform framework for GPU-accelerated image processing. It aims in removing language barriers in the scientific image analysis community by proposing a unified interface API for different programming languages and Frameworks, which rely on a common backend library accelerated by GPU.

The project is organised in a set of core-reposiroty dedicated to the low-level functionning of the project, and a set of sattelite repositories corresponding to a different programming language or framework.

Repositories and responsabilities

Clesperanto tries to offer at the same time:

  • a unified API for image processing library for different programming languages and frameworks
  • a complete operation librairy for image processing and analysis accelerated by GPU
  • a compatibility with most known and used hardware and system in used

To achieve this goal, the project is organised in various repository listed below with a brief description:

Repository Description Maintainer Distribution
🚀 opencl-kernels Collection of OpenCL kernels for image processing. SR, RH
🚀 CLIc (backend) Common backend C++ library in charge of computation and GPU interactions, dependend of clij-opencl-kernels. SR
🐍 pyclesperanto Python package for GPU-accelerated image analysis, dependend of CLIc. SR, RH Conda Version
clesperantoj Java library for GPU-accelerated image analysis, dependend of CLIc. SR, RH
clij3 Fiji plugin for GPU image processing in FIJI, dependend of clesperantoJ. RH Fiji update site "clesperanto"
🐍 prototype Initial Pure-Python package for GPU-accelerated image analysis, dependend of pyOpenCL. RH Conda Version

Maintainers:

How we work together

clEsperanto is developed as a community effort in the open because we believe in the open source community. Contributions like feedback, suggestions, code and testing are very welcome. This can be done through github issue, pull requests, or via image.sc forum using the tag clesperanto.

The clesperanto project is maintained and lead as a benevolent dictatorship by Stephane Rigaud and Robert Haase.

Contribution are very welcome. Please read our community guidelines before you start, and do not hesitate to get in touch with us so that we can help you get started. Each repository has its own contribution guidelines, so please check them out before you start and do not hesitate to contact us if you have any question, we are happy to help!

Regular and committed contributors will be welcomed as core contributors and will be thrusted with advanced rights and will be included in the project's decisions making.

Acknowledgements

We acknowledge support by the Deutsche Forschungsgemeinschaft under Germany’s Excellence Strategy (EXC2068) Cluster of Excellence Physics of Life of TU Dresden. This project has been made possible in part by grant number 2021-237734 (GPU-accelerating Fiji and friends using distributed CLIJ, NEUBIAS-style, EOSS4) from the Chan Zuckerberg Initiative DAF, an advised fund of the Silicon Valley Community Foundation.

Pinned

  1. clesperanto.github.io clesperanto.github.io Public

    clEsperanto - GPU-accelerated image processing across languages and platforms

    11 2

  2. clij-opencl-kernels clij-opencl-kernels Public

    C 13 5

  3. pyclesperanto_prototype pyclesperanto_prototype Public

    GPU-accelerated bio-image analysis focusing on 3D+t microscopy image data

    Jupyter Notebook 195 45

  4. CLIc CLIc Public

    GPU-accelerated Image Processing library

    C++ 14 14

Repositories

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