TrueReviews

Inspiration

We were inspired by the movie theater and the hume ai table. seeing the emotion scores updating in real time instantly lit a fire to explore the new technology.

What it does

TrueReviews uses hume to analyze peoples reactions when watching movies and based on the emotions and reactions we create a movie review with a rating. this is then stored with postgres and sql. The reviews are then used to give people movie recommendations

How we built it

we take videos of reactions to movies and split into 15 second segments. Send this to hume and get the reactions and emotions from the viewer and create a top three emotions list. Then using postgresql db we store these reactions. This is then used to create a movie rating system and movie recommendations.

Challenges we ran into

Some issues we ran into is the wifi was slow and so my api requests with hume took too long and the timeout of 300ms according to some code on hume's github would stop my job before the predictions can be created. wifi made it so that queries were not able to download 10,000 videos.

Accomplishments that we're proud of

attended a lot of the workshops and learned a lot of new skills

What we learned

We need to commit to making a project right away and move swiftly with brainstorming, decision making, and execution.

What's next for TrueReviews

create more features and connect hume to postgresql db to the user.

Built With

• bash
• cockroachdb
• hume
• postgresql
• python
• sql