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@@ -68,7 +67,7 @@ <h2>Mentoring orgs for GSoC 2026 have not been announced!</h2>
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<p>Mentors: If you're a sub-org who wants to join, please
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<ahref="https://python-gsoc.org/mentors.html#sub-orgs">read the information for sub-orgs</a>.
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</p>
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</div>
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</div><!-- !pure-u-1 -->
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</div><!-- !warning -->
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<br/>
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</div><!-- !Ideas -->
@@ -81,37 +80,109 @@ <h2>Mentoring orgs for GSoC 2026 have not been announced!</h2>
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<divclass="pure-g">
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<divclass="pure-u-1 pure-u-md-1-2 logo">
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<imgsrc="/logos/borg_256.png" />
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</div>
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</div><!-- !pure-u-1 -->
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<divclass="pure-u-1 pure-u-md-1-2">
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<h2>
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Borg Collective
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</h2>
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</div><!-- !pure-u-1 -->
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</div><!-- !pure-g -->
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<br/>
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We are the Borg Collective and maintain multiple Python-based backup tools that are often used in combination: Borg, Borgmatic and Vorta. The core Borg tool is a deduplicating archiver with compression and encryption. Vorta is a desktop backup client that integrates with Linux and macOS desktops. Borgmatic is a wrapper for server systems that also takes care of database backups and pre-backup commands.
We are the Borg Collective and maintain multiple Python-based backup tools that are often used in combination: Borg, Borgmatic and Vorta. The core Borg tool is a deduplicating archiver with compression and deduplication. Vorta is a desktop backp client that integrtes with Linux and macOS desktops. Borgmatic is a wrapper for server systems that also takes care of database backups and pre-backup commands.
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DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.
FURY offers a rich collection of visualization actors, interactive tools, and animation utilities that make it easy to build dynamic and engaging 2D and 3D scenes. Its growing set of tutorials and examples helps users quickly get started with interactive visualizations, animations, and custom rendering workflows. Features such as real-time interactivity, camera controls, animated transitions, and GPU-accelerated rendering enable efficient exploratory analysis and compelling visual storytelling.
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By shifting to wgpu while maintaining a strong focus on usability, documentation, and interactivity, FURY v2 aims to deliver a more flexible, modern, and powerful visualization framework for the Python ecosystem.
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