I was inspired by the people who struggle with
What it does
This app is a way for either the youth or young adult demographic to manage and mitigate their stress. The web app is available anywhere with internet which vastly increases the accessibility. Using high level machine learning the web app understands facial expression and responds to it (although this feature was partly built during the hackathon).
How I built it
We build it using a django back end, standard html, css, and js front end, google app engine to deploy, and the google vision API for handling the facial expression machine learning.
Challenges I ran into
Some challenges that we faced were some integration issues with the Google vision API. To put it into context, our project offered a facial recognition feature where it would detect whether a person appeared sad, happy, or any other range of emotions that the API had. It was everyone's first time attempting a project that utilities that API. Overall, while the challenge was very tough, it proved to be a very good learning experience, and definitely a tool we will use again in the future.
Accomplishments that I'm proud of
Getting the Vision API as well as the Google App Engine to work. While not necessarily a difficult task in their own respective goals, integrating this with a python web framework (Django) which has various different formatted for handling web requests.
What I learned
Aside from the obvious technical skills gained during this project (Django, Google Vision API, Google App Engine, etc) but more so we learned how to effectively wok together as a team. We were able to successfully coordinate all of our requests with each other so that the site worked well. Specifically, I would work on taking an image and determine facial expression using Google Vision while another teammate would work on receiving that image and properly "fitting" it for me to use.
What's next for Chill Calm
We hope to flesh the nuances of the project and really make its key features stand out. Furthermore, we hope to expand a lot more of features to take advantage of the many APIs available out there. Specifically the data processing module from Google Cloud which can better help us understand the trends of anxiety within certain demographics.