We feel that presentation is heavily correlated to self-confidence. When we were younger, we never understood the importance of dress, and presentation in general. It hampered my self-esteem and body image, as well as that of my partners. While in our dorm room, we came up with the idea to create fitted - an app we hoped would guide a base of self-conscious men on their path to dressing well, and feeling even better.
What it does
fitted is a comprehensive guide to dressing well, but more so, it's a guide tailored entirely to the individual. We take in metrics such as skin tone, hair length, face structure, and body measurements in order to determine what clothes, glasses, or styles fit the individual best. We developed an algorithm that takes into account all these different factors and determines outfits from a database that would fit you the best, providing links to each individual item in the outfit provided. You tell us about yourself, pick a style you'd like to embody, and we do the rest.
How we built it
Challenges we ran into
We had time constraints preventing us from implementing Google and Facebook API's in login, as well as in porting the algorithm over to the mobile application (the algorithm exists on the web-app, although we are in the process of optimizing it). In an attempt to consolidate our data in a Firebase database, we ran into issues, and decided, in an effort to create a functional MVP, to just host the data locally (something we plan on altering in the future). Also, our designer's laptop stopped working halfway through the night, forcing him to switch to a new one and re-install Sketch.
Accomplishments that we're proud of
This is all of our first hackathon and we're all freshmen, to top it off. So, we're proud we were able to create something functional with a website and mobile implementation. We're also proud we were able to, to some extent, implement a functional algorithm and that we were able to go out and conduct market research. As far as we're concerned, this hackathon has already been a great success, and has set the pace for future hacking adventures.
What we learned
What's next for fitted
Although we're very happy with the progress we've made on fitted here at CalHacks, we definitely think that it has a long way to go. We plan on expanding our dictionary of outfits significantly and modifying the algorithm so it works with individual articles of clothing rather than entire outfits. We also hope to integrate more personalization through allowing users to upload their personal wardrobes, from which we'll make outfits. We also hope to create a marketplace of our own and sell clothes from that - as well as implement machine learning that predicts future purchases and suggests them based on prior clothes purchased by a user and the styles they've made.