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 your wardrobe.
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.
We developed the web application using React for the frontend and Flask for the backend. We leveraged machine learning algorithms to generate the personalized outfit recommendations.
The React web app allows the user to interact with their wardrobe inventory database and get their recommended outfits. All of the database functionality is handled with the various routes … All data is submitted to the front-end through forms, sent to the backend through POST/GET requests, and saved to the SQLite database.
- 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
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.
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