Innovogue

Inspiration

We've all been there - staring at our closet, unsure of what to wear and feeling overwhelmed by our choices. Tired of this daily struggle, we were inspired to design a solution that simplifies the process of finding the perfect outfit. Our application uses cutting-edge machine learning technologies to provide personalized outfit recommendations based on your wardrobe and the occasion, making it easier than ever to get dressed for any event.

What it does

Innovogue revolutionizes the way you choose your outfits by leveraging the power of cutting-edge machine learning algorithms. Our innovative web application provides users with personalized recommendations based on the occasion and the clothing items they have in their wardrobe.

How we built it

We developed the web application using React for the frontend and Flask for the backend. We leveraged machine learning algorithms to generate personalized outfit recommendations.

The React web app allows the user to interact with their wardrobe inventory database and get their recommended outfits. All data is submitted to the frontend through forms, sent to the backend through POST/GET requests, and saved to the SQLite database. The images are large files which are stored in an Amazon S3 bucket pointing to the SQLite database.

Challenges we ran into

Finding a suitable dataset to use for our purposes
Cleaning and setting up the data to be used for training
Implementing the upload picture feature on the application

Accomplishments that we're proud of

We’re proud of being able to integrate the React frontend with the Flask backend. After many hours spent debugging issues with JWT and React props, we persisted and were able to create a seamless integration between the frontend and backend.