Near-Real-Time Computational Astrophotography with AstroComPYute | 2024-07-21

Contemporary astrophotography processing typically involves being locked into a specific processing software suite and includes a high amount of manual user actions and user-guided tradecraft. In contrast with this, Dan Champion presents and discusses a Python-based scripted astrophotography processing approach based on a new library called AstroComPYute. By scripting an end-to-end processing workflow we can easily rerun the processing to reproduce results and experiment with processing variations (and share workflows with peers!). Furthermore, AstroComPYute enables the user to access powerful astrophotography and astronomy specific stand-alone tools like ASTAP and Starnet++ in a unified python workflow. By using GPU acceleration facilitated by a-CUDA compatible GPU and Python GPU acceleration tools (cupy) we can even fully process images typically faster than the data arrives. Dan will discuss the AstroComPYute approach and strategy, provide processing examples, and have a live demo of the processing. Finally, we will deep-dive into how AstroComPYute can perform automated gradient removals powered by openly available all-sky survey data.

A resident of Las Vegas, Nevada, Daniel's background and professional experience includes a Mathematics graduate degree and careers in scientific imaging and measurement within the biotechnology and government sectors. Daniel has astrophotography experience spanning 25 years that began with film and early DSLR's and Photoshop processing. Daniel now leverages his scientific computing background for astrophotography by pursuing an automated and near-real-time astrophotography processing solution utilizing Python open-source tools called AstroComPYute.

GitHub link: https://github.com/Daniel-Champion/As...

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