Applying Object Character Recognition and Kubernetes to Twitch
Automagically view the most interesting PlayerUnknown's Battlegrounds streams on Twitch.
Presented by:
eggshell
I have been a Developer Advocate at IBM since 2017. Before that, I was a DevOps Engineer working on OpenStack public clouds for IBM since my graduation from Texas State University in 2015. In my free time, I enjoy playing guitar and going on trips to go snowboarding.
Rotisserie is an open source node.js application which runs on Kubernetes and brings the concept of the red zone in American football and applies it to the popular online battle royale game PLAYERUNKNOWN’S BATTLEGROUNDS. The idea is to always be viewing the most popular PUBG twitch stream with the least amount of people alive in-game, as this is the point where streamers are tense and playing at their highest levels to achieve victory.
We were able to achieve this goal through the use of many open source technologies, including a ton of node.js libraries, Tesseract, Docker, and more. The application is currently live at https://rotisserie.tv, and we are actively looking for external developers in the community who are interested to jump on board.
Our team at IBM is continuously developing the technology to include a machine learning model using Tensorflow, and the front end has recently been overhauled to a nice looking react based dashboard. We have plans for much more, some of which will be detailed in the talk.
- Date:
- 2018 April 29 - 05:30
- Duration:
- 45 min
- Room:
- CC-200
- Conference:
- LinuxFest Northwest 2018
- Language:
- Track:
- Code
- Difficulty:
- Easy
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