https://github.com/anopara/genetic-drawing

A genetic algorithm toy project for drawing
https://github.com/anopara/genetic-drawing

Last synced: about 1 month ago
JSON representation

A genetic algorithm toy project for drawing

• Host: GitHub
• URL: https://github.com/anopara/genetic-drawing
• Owner: anopara
• License: mit
• Created: 2020-06-05T11:13:14.000Z (about 4 years ago)
• Default Branch: master
• Last Pushed: 2020-06-26T07:34:08.000Z (almost 4 years ago)
• Last Synced: 2024-02-04T18:37:53.960Z (5 months ago)
• Language: Python
• Size: 6.31 MB
• Stars: 2,160
• Watchers: 49
• Forks: 232
• Open Issues: 10
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Lists

• awesome-list - genetic-drawing
• awesome-cg-vfx-pipeline - Genetic Drawing - Python library to generate a stylised rendering from an image. (Digital Content Creation Software (DCCs) / Tools)
• my-awesome-starred - anopara/genetic-drawing - A genetic algorithm toy project for drawing (Python)
• awesome - anopara/genetic-drawing - A genetic algorithm toy project for drawing (Python)
• awesome-cg-vfx-pipeline - Genetic Drawing - Python library to generate a stylised rendering from an image (Digital Content Creation Software (DCCs) / Tools)

README

        
# Genetic Drawing

This is a toy project I did around 2017 for imitating a drawing process given a target image (inspired by many examples of genetic drawing on the internet, and this was my take on it, mostly as an exercise). 

Due to a popular request, it is now opensource 🙂

Examples of generated images:

![](imgs/img1.gif) 

It also supports user-created sampling masks, in case you'd like to specify regions where more brushstrokes are needed (for ex, to allocate more finer details)



## Python

you would need the following python 3 libraries:

* opencv 3.4.1

* numpy 1.16.2

* matplotlib 3.0.3

* and Jupyter Notebook

To start, open the GeneticDrawing.ipynb and run the example code