markov-chain-img v1.0.0

Markov Chain Image

An image processing library that build Markov chains from input images and generate statistically identical output images.

Introduction

A Markov chain is a system that experiences transitions from one state to another, according to certain probabilistic rules. You can find a simple introduction on setosa.io, and a more in-depth definition on brilliant.org.

This module is able to build a Markov chain by analyzing the colors transitions of any input images. After the Markov chain is created, the library can produce beautiful images which have statistically identical color transitions.

Input

Output

Usage

// Create a new object
var mkvChain = new MarkovChainImage();

// Create a new ImageData
var image = new Image(...);
var canvas = document.createElement("canvas");
var context = canvas.getContext("2d");
context.drawImage(image, 0, 0);
var imageData = context.getImageData(0, 0, image.width, image.height);

// Build the Markov chain with ImageData stats
mkvChain.feed(imageData);

// Create a new ImageData
var newImageData = mkvChain.createImageData(image.width, image.height);

API

Instanciation

new MarkovChainImage()

Create a new Object that contains the Markov chain data.

MarkovChainImage.setCompression(n)

Change the compression level used to store colors. Changing this value will reduce the memory requirements.

Default to 1.

Build a Markov chain

MarkovChainImage.feed(ImageData [, async])

Main method to build the Markov chain

If async is set to true, the method will run asynchronously and return a Promise (with no data).

MarkovChainImage.addColorTransition(color 1, color2)

Utility method, add a new color transition to the chain.

Inputs : Object {r, g, b}

Generate images

MarkovChainImage.createImageData(width, height)

Main method to create a new image. Returns a Uint8ClampedArray with pixel color information, that can be used on a Canvas.

MarkovChainImage.getColorTransition(color)

Utility method, return a random color that follow the input color according to the Markov chain transition probability.

Input & Output: Object {r, g, b}

MarkovChainImage.getRandomColor()

Get a random color.

WebWorker

You can use the library as a WebWorker.

var worker = new WebWorker('path/to/markov-chain_img.js');

worker.onmessage(function (e) {
  var newImageData = e.data;
  // do something
});

worker.postMessage(myImageData);

It accepts as message an ImageData and return a Uint8ClampedArray. It runs successively the feed() and createImageData() methods.

Installation

You can install the module with npm

npm install markov-chain-img

You can import the module with a CDN like unpkg

<script type="text/javascript" src="https://unpkg.com/markov-chain-img@latest"></script>

You can clone the repository & include the markov-chain-img.js file in your project:

git clone https://github.com/ogus/markov-chain-img.git

License

This project is licensed under the WTFPL - see LICENSE for more details