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<h1 class="sd-d-none">Pyxu<a class="headerlink" href="#pyxu" title="Link to this heading">#</a></h1>
<h2 style="font-size: 60px; font-weight: bold; display: inline"><span>Pyxu</span></h2>
<h3 style="margin-top: 0; font-weight: bold; text-align: left; ">Modular & Scalable Computational Imaging</h3>
<p>
<strong> Pyxu </strong> (pronounced [piksu], formerly known as Pycsou) is an open-source Python framework allowing
scientists at any level to quickly prototype/deploy <em> hardware accelerated and out-of-core </em> computational
imaging pipelines at scale.
Thanks to its hardware-agnostic <strong>microservice architecture </strong> and its tight integration with the
PyData ecosystem, Pyxu supports a wide range of imaging applications, scales, and computation architectures.
</p>
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</div> <!-- End Hero -->
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</div></section>
<section id="key-features-capabilities">
<h1>Key Features & Capabilities<a class="headerlink" href="#key-features-capabilities" title="Link to this heading">#</a></h1>
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</figure>
<p style="text-align: center;">
<strong> Microservice architecture </strong> <br/>
Loosely coupled software components that are composable via an advanced <em> operator algebra</em>.
</p></div>
</div>
</div>
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<strong> Plug-and-play API </strong> <br/>
Simple interface for beginners with theory-informed automatic hyperparameter selection.
Experts may still fine-tune parameters via a <em> guru </em> interface.
</p></div>
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<strong> Application agnostic </strong> <br/>
Generic software components with wide applicability across imaging modalities.
</p></div>
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<strong> Flexible computation backends </strong> <br/>
The same code executes for multiple array backends, including CPU and GPU, with a unified, easily
maintainable codebase.
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<strong> High-performance computing </strong> <br/>
Just-in-time compilation, batch processing, automatic parallelization, out-of-core computing, and
controllable computation precision.
</p></div>
</div>
</div>
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<p style="text-align: center;">
<strong> Interoperability </strong> <br/>
Pyxu is highly interoperable with the <em>PyData stack</em>, including full-fledged zero-copy wrappers
for <a href="https://jax.readthedocs.io/en/latest/">JAX</a> and <a
href="https://pytorch.org/">PyTorch</a> operators.
</p></div>
</div>
</div>
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<strong> Quality controlled </strong> <br/>
Extensive logical and functional unit testing of software components.
Templated test classes for custom operators.
</p></div>
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<strong> Community driven </strong> <br/>
Pyxu is open source, version controlled, and is available to all on <a
href="https://pypi.org/project/pyxu/">PyPI</a> and <a
href="https://github.com/pyxu-org/pyxu">GitHub</a>.
</p></div>
</div>
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<strong> Extensible </strong> <br/>
Powerful plugin mechanism and community marketplace (<a href="./fair/index.html">Pyxu FAIR</a>) for
discovering and sharing custom operators.
</p></div>
</div>
</div>
</div>
</div>
</section>
<section id="ecosystem">
<h1>Ecosystem<a class="headerlink" href="#ecosystem" title="Link to this heading">#</a></h1>
<p>Pyxu is highly interoperable with the wider scientific Python ecosystem.
It is built on a minimal set of foundational and robust scientific computing librairies from the PyData stack.
Pyxu notably supports multiple array backends –<a class="reference external" href="https://numpy.org/">NumPy</a>, <a class="reference external" href="https://www.dask.org/">Dask</a>, and
optionally <a class="reference external" href="https://cupy.dev/">CuPy</a>–, allowing users to choose array backends that work best for their
application/computation.
Aside from <a class="reference external" href="https://scipy.org/">SciPy</a> and <a class="reference external" href="https://numba.pydata.org/">Numba</a> – which we use for scientific
computing and <a class="reference external" href="https://numba.readthedocs.io/en/stable/user/5minguide.html#how-does-numba-work">JIT-compilation</a>
respectively– these are Pyxu’s <strong>only</strong> dependencies, making the software very easy to ship, install, deploy in
production, and sustain in the long term.</p>
<p>Pyxu is also interoperable with (but does not depend on) major deep learning frameworks such as <a class="reference external" href="https://jax.readthedocs.io/en/latest/">JAX</a> and <a class="reference external" href="https://pytorch.org/">PyTorch</a>, allowing users to benefit from the
latest incursions of deep learning in the field of computational imaging (e.g., PnP methods, unrolled neural networks,
deep generative priors).
Our wrappers can moreover leverage the autograd engine to auto-infer gradients or adjoint operations.</p>
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<p style="text-align: center;">
Foundational package for array computing in Python.
</p></div>
</div>
</div>
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</a>
<p style="text-align: center;">
NumPy-compatible distributed arrays and advanced parallelism for both in and out-of-core computing,
enabling performance at scale.
</p></div>
</div>
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NumPy-compatible array library for GPU-accelerated computing.
</p></div>
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Fundamental algorithms for scientific computing.
</p></div>
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NumPy-aware dynamic compiler using <a href="https://llvm.org/">LLVM</a>.
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Tensors and dynamic neural networks with strong GPU acceleration.
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</a>
<p style="text-align: center;">
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more.
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</section>
<section id="governance-and-team">
<h1>Governance and Team<a class="headerlink" href="#governance-and-team" title="Link to this heading">#</a></h1>
<p>Pyxu is an <strong>open-source project</strong> developed and maintained primarily by members of the <a class="reference external" href="https://imaging.epfl.ch/">EPFL Center for Imaging</a>, but the repository itself is public and external contributions are welcome.
We are committed to keeping the project public and owned by the community through a meritocratic and consensus-based
governance.
Anyone with an interest in the project can join the community, contribute to the project design, and participate in the
decision-making process.</p>
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</a>
</div>
</div>
</div>
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</a>
</div>
</div>
</div>
</div>
</div>
<section id="steering-council">
<h2>Steering Council<a class="headerlink" href="#steering-council" title="Link to this heading">#</a></h2>
<p>The role of Pyxu’s Steering Council is to ensure the long-term sustainability of the project, both technically and as a
community. Pyxu’s Steering Council meets regularly (every two weeks or so) and currently consists of the following
members:</p>
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<a class="reference external image-reference" href="https://github.com/SepandKashani"><img alt="_images/kashani.png" class="align-center" src="_images/kashani.png" style="width: 40%;" />
</a>
<p style="text-align: center;">
<strong> Sepand Kashani </strong> <br/>
Core architect, maintainer
</p></div>
</div>
</div>
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<a class="reference external image-reference" href="https://github.com/joanrue"><img alt="_images/rue_queralt.png" class="align-center" src="_images/rue_queralt.png" style="width: 40%;" />
</a>
<p style="text-align: center;">
<strong> Joan Rué-Queralt </strong> <br/>
Core architect, maintainer
</p></div>
</div>
</div>
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<a class="reference external image-reference" href="https://github.com/matthieumeo"><img alt="_images/simeoni.png" class="align-center" src="_images/simeoni.png" style="width: 40%;" />
</a>
<p style="text-align: center;">
<strong> Matthieu Simeoni </strong> <br/>
Core architect, creator
</p></div>
</div>
</div>
</div>
</div>
</section>
<section id="contributors">
<h2>Contributors<a class="headerlink" href="#contributors" title="Link to this heading">#</a></h2>
<p>In addition to the steering council, you can also check the <a class="reference external" href="https://github.com/pyxu-org/pyxu/graphs/contributors">full list of contributors</a>.</p>
</section>
</section>
<section id="partners-sponsors">
<h1>Partners & Sponsors<a class="headerlink" href="#partners-sponsors" title="Link to this heading">#</a></h1>
<div class="sponsors-inner" style="color: #fff;
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<img width="100" alt="EPFL Slider" src="_static/EPFL_Logo_Digital_BLACK_PROD.png">
</div>
<div class="sponsors-list-item">
<img width="150" alt="Imaging Slider" src="_static/imaging.png">
</div>
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<img width="100" alt="LCAV Slider" src="_static/LCAV_LOGO.png">
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