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Case Notes

Image Color Palette Generator

A web based tool that extracts dominant color palettes from uploaded images using K-Means clustering with a Flask interface

PythonFlaskscikit-learnNumPyPillowHTML/CSSJavaScript
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Overview

This project is a web application that analyzes uploaded images and extracts their dominant color palettes using the K-means clustering algorithm. Built with a Python/Flask backend and a clean, responsive frontend, it gives designers and developers instant access to hex codes and RGB values from any image.

Features

  • K-means machine learning algorithm for accurate dominant color extraction
  • Customizable output of 2-10 colors per image
  • One-click hex code copying to clipboard
  • Visual percentage display showing how much of each color appears in the image
  • Responsive design that works across desktop, tablet, and mobile
  • Clean modern UI with smooth animations

What I Learned

This project helped deepen my understanding of how machine learning algorithms like K-Means can be applied to real-world problems outside of traditional data science contexts. Integrating scikit-learn with a Flask web interface also reinforced how to structure a Python application that bridges a backend algorithm with a user-facing frontend.