Inspiration

Color analysis consultations have been gaining popularity in recent years. Color analysis allows people to figure out what color clothing/accessories fit them best without having to figure it out themselves. However, color analysis consultations can be quite expensive. Our inspiration for this project was figuring out a way to automate this process so that people can get color analysis done easily and for free.

What it does

This website allows users to quickly get their own color and feature analysis done from the comfort of their own home. They can either insert a photo of themselves or take one through the website. Then, after identifying the colors of facial features like eye color and hair color, the system will choose a color palette best suited for their complexion. Additionally, users can also learn about what types of clothing and hairstyles are best suited for them based on answering a series of questions about their appearance.

How we built it

We built this website using HTML, CSS, and JavaScript. We used GitHub for version control.

Challenges we ran into

We initially wanted to use React.js to structure our website. However, since both of us didn't have that much experience with React, we quickly found it too complex to achieve what we wanted to with our site with the given amount of time. Although we were able to learn the basics, we decided it would be best to simply code with the basic building blocks of web dev. We also ran into merge conflicts throughout the coding process.

Accomplishments that we're proud of

We're very proud that we were able to build a majority of our original project in under 24 hours! We both tried new things with code, and are satisfied with the final product.

What we learned

As stated previously, we learned the basics of React. We also learned about how color analysis works as well as the impact of face shape and body type on attributes like hairstyle, outfits, and color.

What's next for Persona Palette

Right now the website allows users to locate their facial features manually. In the future we hope to use some sort of computer vision tool so that the system can automatically locate facial features from an image. After locating these features we could possibly use k-means clustering to figure out the "average" color of each feature, which can then be passed into the system for color analysis.

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