Scripting Automation for Tamashii

Information

• Publication Type: Bachelor Thesis
• Workgroup(s)/Project(s):
  • Advanced Computational Design
• Date: September 2023
• Date (Start): October 2022
• Date (End): September 2023
• Matrikelnummer: e12020638
• First Supervisor:
  • Michael Wimmer
  • David Hahn
  • Lukas Lipp

Abstract

We extend the Tamashii scientific rendering framework with an interface to the Python scripting language to automate the process of documenting and comparing results of different approaches, simplifying the development of experimental code, and seamlessly integrating with existing libraries. The framework is a research platform enabling the implementation of various graphics processing unit (GPU) driven (differentiable) rendering tasks and is currently under development by the institute for computer graphics at TU Wien. Tamashii offers a large set of premade functionality common to these workflows that can be leveraged by researchers to create their own custom implementations. The focus of this thesis is the integration of the Python programming language into the framework in a way that benefits all projects utilizing Tamashii in their research. With this addition the steps of loading scenes, configuring the rendering process and exporting the generated data can now be controlled using scripting. Furthermore, with the ability to employ Python directly, access to the whole ecosystem of third party software and libraries opens up, which includes many prevalent projects for optimization and machine learning algorithms. In this thesis we identify the required features and properties of such an interface, explain the design process, give technical details on the realization and finally evaluate the result by demonstrating its use.

Additional Files and Images

Weblinks

No further information available.

BibTeX

@bachelorsthesis{Preymann-2022-pytamashii,
  title =      "Scripting Automation for Tamashii",
  author =     "Matthias Preymann",
  year =       "2023",
  abstract =   "We extend the Tamashii scientific rendering framework with
               an interface to the Python scripting language to automate
               the process of documenting and comparing results of
               different approaches, simplifying the development of
               experimental code, and seamlessly integrating with existing
               libraries. The framework is a research platform enabling the
               implementation of various graphics processing unit (GPU)
               driven (differentiable) rendering tasks and is currently
               under development by the institute for computer graphics at
               TU Wien. Tamashii offers a large set of premade
               functionality common to these workflows that can be
               leveraged by researchers to create their own custom
               implementations. The focus of this thesis is the integration
               of the Python programming language into the framework in a
               way that benefits all projects utilizing Tamashii in their
               research. With this addition the steps of loading scenes,
               configuring the rendering process and exporting the
               generated data can now be controlled using scripting.
               Furthermore, with the ability to employ Python directly,
               access to the whole ecosystem of third party software and
               libraries opens up, which includes many prevalent projects
               for optimization and machine learning algorithms. In this
               thesis we identify the required features and properties of
               such an interface, explain the design process, give
               technical details on the realization and finally evaluate
               the result by demonstrating its use.",
  month =      sep,
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  school =     "Research Unit of Computer Graphics, Institute of Visual
               Computing and Human-Centered Technology, Faculty of
               Informatics, TU Wien ",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2023/Preymann-2022-pytamashii/",
}