RMOTR: Machine Learning power . Extracting dominant colors from images with clustering.

A couple of days ago we were thinking about simple Machine Learning applications to present to our students. One of our main goals is to demonstrate how simple it can be to apply machine learning techniques to resolve every day problems and that you don’t need a PhD to use libraries like scikit-learn or Keras.

Our friend Matias (https://twitter.com/yosoymatias) devised a simple clustering app to extract colors from images: using K-Means, an unsupervised clustering method, we can identify “dominant” colors and create a simple color palette.

The result is exactly what we were looking for. A really simple and fun application that any Python programmer can understand: [LIVE DEMO]https://colors.rmotr.com/

There’s a step by step explanation in this Jupyter Notebook.

We created the webapp (and the API) using Flask and deployed it with AWS Lambdas (using the amazing Zappa project).

And the source code is hosted here: https://github.com/rmotr/color-extractor-service

Are you interested in learning Data Science? Check our LIVE online course: http://rmotr.com/python-data-science-projects/

Machine Learning power 💪. Extracting dominant colors from images with clustering. was originally published in rmotr.com on Medium, where people are continuing the conversation by highlighting and responding to this story.