ReStyle

Combat fast fashion's carbon footprint with Restyle. Simplify selling, inspire eco-conscious choices, and ensure smooth connections through AI matching for personalized wardrobe perfection

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Inspiration

Globally, over 92 million tons of textile waste are generated annually, contributing to overflowing landfills and environmental degradation. What's more, the fashion industry is responsible for 10% of global carbon emissions, with fast fashion being a significant contributor due to its rapid production cycles and disposal of unsold items. The inspiration behind our project, ReStyle, is rooted in the urgent need to address the environmental impact of fast fashion. Witnessing the alarming levels of clothing waste and carbon emissions prompted our team to develop a solution that empowers individuals to make sustainable choices effortlessly. We believe in reshaping the future of fashion by promoting a circular economy and encouraging responsible consumer behaviour.

What it does

ReStyle is a revolutionary platform that leverages AI matching to transform how people buy and sell pre-loved clothing items. The platform simplifies the selling process for users, incentivizing them to resell rather than contribute to the environmental crisis of clothing ending up in landfills. Our advanced AI matching algorithm analyzes user preferences, creating tailored recommendations for buyers and ensuring a seamless connection between sellers and buyers.

How we built it

We used React Native and Expo to build the front end, creating different screens and components for the clothing matching, camera, and user profile functionality. The backend functionality was made possible using Firebase and the OpenAI API. Each user's style preferences are saved in a Firebase Realtime Database, as are the style descriptions for each piece of clothing, and when a user takes a picture of a piece of clothing, the OpenAI API is called to generate a description for that piece of clothing, and this description is saved to the DB. When the user is on the home page, they will see the top pieces of clothing that match with their style, retrieved from the DB and the matches generated using the OpenAI API.

Challenges we ran into

  • Our entire team was new to the technologies we utilized.
  • This included React Native, Expo, Firebase, OpenAI.

Accomplishments that we're proud of

  • Efficient and even work distribution between all team members
  • A visually aesthetic and accurate and working application!

What we learned

  • React Native
  • Expo
  • Firebase
  • OpenAI

What's next for ReStyle

Continuously refine our AI matching algorithm, incorporating machine learning advancements to provide even more accurate and personalized recommendations for users, enabling users to save clothing that they are interested in.

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