Imager for JavaScript

• Source
• NPM
• Example
• Documentation

Features

Brute Force Image Optimization

Optimizes the compression using ML based metrics in a trial ’n error sorta manner.

This is a tool that can competitively optimize (e.g.) extremely noisy, high resolution images; at the expense of increased encoding time and CPU overhead. This is a tradeoff that should be suitable for over 90% of online content, where site performance matters.

It's pretty easy too.

$ npm install --save imager-io

Using the JavaScript non-blocking API:

const {ImageBuffer} = require("imager-io");
ImageBuffer
	.open("source-image.jpeg")
	.then(buffer => buffer.opt())
	.then(buffer => buffer.save("result.jpeg"))
	.then(() => console.log("done"));

Compression Benchmarks

source        : ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 39.00M (4 images)
kraken.io     : ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 24M
jpegmini.com  : ▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 16M
compression.ai: ▇▇▇▇▇▇▇▇ 8.90M
imager        : ▇▇▇▇ 4.20M

Supported Input Image Formats

| Format | Decoding | | ------ | -------- | | PNG | All supported color types | | JPEG | Baseline and progressive | | GIF | Yes | | BMP | Yes | | ICO | Yes | | TIFF | Baseline(no fax support) + LZW + PackBits | | WebP | Lossy(Luma channel only) | | PNM | PBM, PGM, PPM, standard PAM |

Essentially supports any image decodable by image-rs.

Supported Output Image Formats

These are your optimization targets (for lack of a better name). It’s a bit higher level, since e.g. rate control is automatically handled.

| Format | Encoding | | ------ | -------- | | JPEG | progressive |

Webpack

It’s possible and pretty easy to use Webpack and Imager already, here is an example.

Feedback, Requests, Bugs, Confusion & Performance Issues

Just use the GitHub issue tracker for this project.

Other Miscellaneous

Articles

• Modern Image Optimization for 2020 - Issues, Solutions, and Open Source Solutions

Copyright 2019 Colbyn Wadman