Inspiration
Our inspiration was to work on a machine learning project while being able to help make the world a better place. We believe mental health is a significant health aspect that often gets overlooked. We wanted to create something that helped manage/track emotions to help people understand their feelings better.
What it does
It uses a camera to help see the emotions you are expressing and stores that data in a database for tracking.
How we built it
Currently, it uses OpenCV to help track faces, and in addition, it uses a deep learning framework to help recognize emotions. We used Flask as the web framework to give the app a UI to make it easier to use. We also used MongoDB to store the emotional history.
Challenges we ran into
Mostly everything we used in this project was new to us, so we ran into a lot of debugging problems when trying to implement things. Challenges include routing to the proper pages, not being able to recognize faces, database CRUD operations not functioning properly, etc.
Accomplishments that we're proud of
We are proud that we got to build something that we didn't have much experience in, and building something we had a passion for. It was fun learning and being able to build.
What we learned
We learned a lot about facial recognition as well as web frameworks.
What's next for EmotionTracker
We are linking our emotion tracker with Spotify to help create playlists that can help improve your mood. We will include personalized content, such that the suggested songs will most likely be songs you already have listened to in your history.
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