Have you ever wondered how an image can be recreated by evolutionary principles? Genetic algorithms (GA) provide a fascinating way to approach this challenge. They simulate the process of natural selection by evolving a population of potential solutions over successive generations. In this project, I revisited an open-source contribution I made years ago, where I attempted to replicate user-uploaded images using a genetic algorithm. Although the original pull request was not accepted due to some unnoticed broken code, my fascination with the concept never faded. Inspired to refine it, I rebuilt and enhanced the implementation. Here’s the full story of how it works. What is a Genetic Algorithm? A genetic algorithm is an optimization technique inspired by natural evolution. It works by: Initialization: Generating an initial population of potential solutions. Evaluate Fitness: Measure how closely each solution resembles the target. Selection: Choose the best candidates to...