Analyzing coral restoration with machine learning

With hundreds of thousands of monitoring pictures, we have one of the most extensive database on coral restoration in the world. This project’s goal is to extract the information contained within these pictures. We can then analyze this data to understand coral growth and resilience better.

This repository contains all the code we wrote to analyze our coral frames pictures and produce the results for the paper.