Moodify

Link to demo is under try-it-out (should be for google drive).

Inspiration

Music is a big part of students' lives and although we each have our favorite songs, we always feel different every day. Depending on your mood we sometimes wanted to listen to different songs that could make us feel better or match how we felt. That is why we created this website so that we can listen to music that fits the mood that we feel every day.

What it does

Our website recommends the user music based on how they are feeling and what genre they prefer.

How we built it

The website was built using HTML in repl. it. We used the spotify API's searching feature to search genres and used some basic ML using sklearn to find moods of songs and add them to the dictionary. I then returned the dictionaries for API and coded the website to use the API and display the results.

Challenges we ran into

We first made a website on Figma but realized that it would be difficult to convert it into HTML so that we could use it with our API. So we had to recode the entire website using HTML with little time left. Implementing the iframes into the website also was a bit complicated.

Accomplishments that we're proud of

We finished the API and made it work with the rest of our project.

What we learned

We learned how to use the Spotify API and how to integrate it with an HTML website.

What's next for Moodify.

We're going to add better machine learning and maybe a face mood detecting feature. We are also going to improve (a lot) on the speed of this as it takes between 20 seconds to a very very very long time to load the songs. We are also going to improve the UI and the overall user experience, and add more tools to make sure the music is fit for you