Robust, Distributed, and Parallel Processing for Enormous Images Using SuperVisor, Node, Flow, Nx, and evision.
Susumu Yamazaki (ZACKY) is currently an Associate Professor at the University of Kitakyushu. One of his current research interests focuses on system and social implementation using Elixir, Phoenix, Nerves, and Nx, and the satellite image processing system by them. He is a creator of the Pelemay series. He is also a co-organizer of ElixirConf JP.
What do you use when you process enormous images? Of course, Python, Numpy, and OpenCV will be helpful for it, but don’t you want to speed it up by processing it in a distributed and parallel way? Elixir can do it:
- You can replace Numpy and OpenCV with Nx and evision.
- Node and Flow can make the processing distributed and parallel.
- Supervisor makes it robust for crashing due to consuming much memory.
This presentation will introduce satellite image processing for an information provision system of sediment disasters as an example case study shown at ElixirConf US 2020.