ColorSea
AI-powered color analysis using computer vision and face recognition to find palettes that actually work for you.
Overview
ColorSea analyzes your features using computer vision — skin tone, face shape, etc. — and suggests color palettes that complement you. The idea came from noticing how many people struggle with choosing colors that suit them, whether for clothes, accessories, or even room decor.
Challenge
Color analysis is surprisingly subjective and culturally nuanced. Getting the computer vision pipeline to work reliably across different lighting conditions, skin tones, and camera qualities was harder than expected.
Approach
I used MediaPipe for face detection and landmark recognition, OpenCV for the image processing pipeline, and scikit-image for color extraction. The backend is FastAPI serving a Next.js frontend. PostgreSQL stores user profiles and palette history.
Outcome
The accuracy improved a lot once I started accounting for ambient lighting in the analysis. People seem to find it most useful for the seasonal color analysis feature — it tells you whether you're a "warm autumn" or "cool winter" type and gives you specific hex codes to work with.