Sometime in late 2015/early 2016, I worked on a neat project while working at the Jonah Group. When we wanted to share snacks, they would place it on a 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.
- Raspberry Pi 2. One for development, and another for deployment
- Spare monitors, for shielding the camera from glare
- OpenCV and SimpleCV for image recognition.
- Orange machine learning tools.
- Flask and Jinja were used for displaying data to the web.
- Hubot gave our team automatic updates via Slack.
Upon joining 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.
It worked! Even if it was easily confused by what we put on the table, it worked!
Back to Code.