Inspiration
Every inspiration aims to solve a problem. You wake up and put together an outfit, but your indecisiveness gets in the way. When you finally is able to put together a stylistic outfit, you leave your house and realize it's actually freezing cold. We want to build an app that can solve these problems.
What it does
You can use our app to scan your current clothing pieces, which our app will store. Using the stored wardrobe data, it combines it with current weather, your style, and event of the day and returns realistic advice.
How we built it
With a backend Python with Flask as the center of our program, we integrate it with a weather api, an openai api, our trained machine learning clothes classifier, and our database local storage to output a frontend user interface build using HTML, CSS, and JavaScript.
Challenges we ran into
Training the models to recognize clothes Image generation with Dall-E often produces incorrect results Python library reliability
What's next for QlosUnid
Recommendation based on likings - We hope that in the future, QlosUnid will be able to offer recommendations from online shopping platforms to add to your collection. Outfit planning & Tracking - Users can log in and keep track of their outfit, which allows them to plan ahead as well to add variety to their style. Sharing Ideas & Trading - There can never be too much inspiration. People will be able to share their outfit ideas, which may lead to buying and selling from one another.
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