Inspiration
The idea for AI-closet was born out of the desire to simplify and enhance the online shopping experience. We noticed that people often struggle to visualize how clothing items will look on them, especially when shopping online. With advancements in AI and virtual try-on technology, we saw an opportunity to create a tool that brings the fitting room experience to users' fingertips. AI-closet aims to make fashion more accessible and enjoyable by allowing users to try on outfits digitally before making a purchase.
What it does
AI-closet allows users to virtually try on clothing by uploading a photo of themselves and selecting items from a digital wardrobe. The app uses AI-powered image processing to blend the selected outfit with the user's photo, generating a realistic preview. This feature helps users explore different styles, make better purchasing decisions, and reduces the likelihood of returns, making online shopping more efficient and satisfying.
How we built it
We built AI-closet using React Native for cross-platform compatibility, allowing us to deploy on both iOS and Android. For the virtual try-on feature, we integrated with the HeyBeauty Try-On API, which handles image processing and returns the combined try-on image. We used Expo to manage image selection and permissions, and Axios for API communication. The user interface was designed with accessibility in mind, using React Native's styling capabilities to ensure a smooth and cohesive experience for users across different devices.
Challenges we ran into
One of the main challenges was ensuring that the try-on images appeared natural and proportional. Initially, the returned images did not align well with the user's photo, resulting in distorted previews. We experimented with different scaling options and API configurations to resolve this. Another challenge was handling high-resolution images, which required efficient memory management to prevent the app from lagging or crashing. Additionally, we had to balance functionality and simplicity to keep the interface accessible for all users.
Accomplishments that we're proud of
We’re proud of creating a working virtual try-on feature that is both functional and user-friendly. The app allows users to see themselves in various outfits in real time, which we believe enhances their shopping experience. We're also proud of the design, which maintains a clean, intuitive look and is accessible to users of all ages and technical backgrounds. Completing this project within a short timeframe and overcoming technical challenges was a rewarding accomplishment for our team.
What we learned
This project taught us a lot about integrating third-party APIs, particularly those involving image processing and AI. We gained experience in handling and optimizing images in React Native, as well as in designing for usability and accessibility. We also learned the importance of efficient memory management and the value of collaboration in tackling unexpected challenges. The project reinforced our understanding of how to build cross-platform mobile applications that are both performant and user-centered.
What's next for AI-closet
In the future, we plan to enhance the try-on experience by improving the accuracy and realism of the AI-generated images. We aim to expand the app's wardrobe to include more clothing items and styles, making it a comprehensive tool for fashion exploration. Additionally, we want to implement features like personalized outfit recommendations and size suggestions based on user data. Our ultimate goal is for AI-closet to become a go-to virtual shopping assistant, helping users confidently and conveniently explore fashion from anywhere.
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