Sometime in late 2015/early 2016, I was involved in a “Snack Watcher” project at the Jonah Group. This was a fun exercise involving a sweet office tradition.
|HARDWARE USED||Raspberry Pi 2. One for development, and another for deployment. Spare monitors, for shielding the camera from glare.|
|SOFTWARE USED||A whole bunch of Python libraries! OpenCV and SimpleCV for image recognition. Orange machine learning tools. Flask and Jinja were used for displaying data to the web. A Hubot gave our team automatic updates via Slack.|
When people wanted to share snacks, they would place it on a certain snack table, so fellow devs can enjoy some treats. The project’s premise was to install a camera over the snack table, and automatically alert our colleagues whenever a snack was deployed.
When the call went out for people to work on it, I eagerly joined the SnackWatcher team. I worked on the user-facing parts of the system. First, I set up a Slack bot to let our colleagues know when there are new snacks. This bot periodically checked the table status (using the handy SnackWatcher API). I also implemented a webpage using Flask, a Python static site generator.