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.github/FUNDING.yml

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# These are supported funding model platforms
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github: # Replace with up to 4 GitHub Sponsors-enabled usernames e.g., [user1, user2]
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patreon: rndteam
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open_collective: # Replace with a single Open Collective username
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ko_fi: # Replace with a single Ko-fi username
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tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel
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community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry
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liberapay: # Replace with a single Liberapay username
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issuehunt: # Replace with a single IssueHunt username
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otechie: # Replace with a single Otechie username
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custom: # Replace with up to 4 custom sponsorship URLs e.g., ['link1', 'link2']

README.rst

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see `examples on GitHub <https://github.com/rnd-team-dev/plotoptix/tree/master/examples>`__
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for practical code samples.
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PlotOptiX is based on `NVIDIA OptiX 7 <https://developer.nvidia.com/optix>`_ framework. It is a set of CUDA shaders by `R&D Team <https://rnd.team>`_ wrapped in RnD.SharpOptiX C#/C++ libraries with a Python API. PlotOptiX makes use of RTX-capable GPU's.
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PlotOptiX is based on `NVIDIA OptiX 7.1 <https://developer.nvidia.com/optix>`_ framework. It is a set of CUDA shaders by `R&D Team <https://rnd.team>`_ wrapped in RnD.SharpOptiX C#/C++ libraries with a Python API. PlotOptiX makes use of RTX-capable GPU's.
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.. image:: https://plotoptix.rnd.team/images/screenshots.jpg
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:alt: PlotOptiX screenshots, scatter and line plots ray tracing
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- spherical and parallelogram light sources, light emission in volumes
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- environmental light, environment maps, and ambient occlusion
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- post-processing: tonal correction curves, levels adjustment, apply mask/overlay, AI denoiser
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- GPU acceleration using RT Cores and everything else what comes with `OptiX 7 <https://developer.nvidia.com/optix>`__
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- GPU acceleration using RT Cores and everything else what comes with `OptiX 7.1 <https://developer.nvidia.com/optix>`__
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- callbacks at the scene initialization, start and end of each frame raytracing, end of progressive accumulation
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- 8/16/32bps(hdr) image output to `numpy <http://www.numpy.org>`__ array, or save to popular image file formats
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- hardware accelerated video output to MP4 file format using `NVENC 9.0 <https://developer.nvidia.com/nvidia-video-codec-sdk>`__

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