algorithmic modeling for Rhino



The purpose of the Owl plug-in is to constitute a new data type named Tensor, thanks to which the Grasshopper users will be able to work with so-called "big-data". This will further open up new possibilities to use more sophisticated machine-learning tools, which require big data sets to be effective. 

The core library of the Owl plug-in is open sourced, and provides the developers with methods to read/write and use the Tensor data within the GH (and outside of it).

Additionally the Owl.Accord.GH.gha plug-in is the first extension based on the Owl core, utilizing few of the machine-learning methods sourced from the Accord framework. 

Download at:

Core libraries, open-sourced:

NuGet packages: 

Install-Package Owl.Core

Install-Package Owl.GH.Common 

Some parts of the plug-in depend on the Accord framework:

Members: 87
Latest Activity: Jul 17

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Examples discussion 9 Replies

Placeholder for the examples to come.Continue

Started by Mateusz Zwierzycki. Last reply by MarcGrasshopper Jul 13.

Python & Getting outside of GH 2 Replies

While Owl contains some small-scale methods for machine learning, you might want to use more recent deep-learning methods like the ones available in TensorFlow.The solution is:Get the data from…Continue

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Started by Mateusz Zwierzycki. Last reply by Mateusz Zwierzycki Apr 15.

Developers Developers Developers

Here you can find the Owl core libraries: can easily develop your own plugin based on the…Continue

Started by Mateusz Zwierzycki Apr 14.

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