CereStyle

Landing page of our web application

Inspiration

CereStyle was born out of a personal challenge that all of us have faced—struggling to choose clothes that truly complement our looks and define our fashion sense. We often found ourselves unsure of what colors suited us best, leading to a lack of confidence in our wardrobe choices. In one of our classes, we learned about the power of color theory and how it can be used to highlight natural features by selecting the right colors. This sparked the idea to create a solution using AI, blending color theory with technology to solve a real-life problem. CereStyle aims to help thousands of people who face the same challenge we did, guiding them to discover the perfect fashion style that enhances their confidence.

What it does

CereStyle is an AI-powered fashion assistant that leverages color theory to provide personalized clothing recommendations. Users upload a photo of themselves, and the platform analyzes their skin tone and eye color to suggest outfits that enhance their natural features. The app provides tailored suggestions for casual, professional, and special occasions, helping users feel more confident in every setting.

How we built it

We built CereStyle using a combination of front-end and back-end technologies. The image analysis is powered by the Cerebras API, which processes the uploaded photos to identify skin tone, hair color, and eye color. The backend is developed using Node.js, Flask, Python to handle user requests and integrate the AI features, while the front-end is built using React, HTML, CSS, JavaScript providing a sleek, responsive user interface. We also integrated fashion retailer APIs to source real-time clothing recommendations that match the user's profile.

Challenges we ran into

One of the major challenges we encountered was ensuring the accuracy of skin tone detection. Variations in lighting and image quality made it difficult to standardize results across different users. Another challenge was integrating multiple APIs, each with its own set of authentication protocols, data structures, and response times. Additionally, fine-tuning the color theory algorithms to provide recommendations that are both accurate and fashionable required extensive testing and refinement.

Accomplishments that we're proud of

We’re proud of successfully merging AI and color theory into a user-friendly platform that provides real, actionable fashion advice. Overcoming the technical challenges of integrating the Cerebras API and ensuring smooth interaction between multiple APIs was a significant achievement. Most importantly, we’ve created a tool that can genuinely help users feel more confident by understanding their personal style.

What we learned

Throughout this project, we deepened our understanding of color theory and how it relates to fashion. We also gained hands-on experience working with AI-powered image analysis and integrating complex APIs. The project taught us the importance of user experience design, as we needed to make sure the platform was intuitive and accessible for all users. Additionally, balancing technical constraints with fashion-forward recommendations was a key learning experience.

What's next for CereStyle

Looking ahead, we plan to enhance CereStyle by integrating even more advanced AI models to improve the accuracy of our color recommendations. We aim to partner with additional fashion retailers to broaden our range of product suggestions. Moreover, we want to introduce features that promote sustainable fashion by recommending eco-friendly clothing options. Our goal is to keep refining CereStyle to better serve users in their journey to find their unique style.