grunt-contrib-imagemin  

> Minify images using imagemin

Install

``sh
npm install --save-dev grunt-contrib-imagemin
`

Usage

`js
const mozjpeg = require('imagemin-mozjpeg');

grunt.initConfig({
imagemin: {
static: {
options: {
optimizationLevel: 3,
svgoPlugins: [{removeViewBox: false}],
use: [mozjpeg()] // Example plugin usage
},
files: {
'dist/img.png': 'src/img.png',
'dist/img.jpg': 'src/img.jpg',
'dist/img.gif': 'src/img.gif'
}
},
dynamic: {
files: [{
expand: true,
cwd: 'src/',
src: ['*/.{png,jpg,gif}'],
dest: 'dist/'
}]
}
}
});

grunt.loadNpmTasks('grunt-contrib-imagemin');
grunt.registerTask('default', ['imagemin']);
`

Options

$3

* Type: number
* Default: 3

Select optimization level between 0 and 7.

> The optimization level 0 enables a set of optimization operations that require minimal effort. There will be no changes to image attributes like bit depth or color type, and no recompression of existing IDAT datastreams. The optimization level 1 enables a single IDAT compression trial. The trial chosen is what OptiPNG thinks it’s probably the most effective. The optimization levels 2 and higher enable multiple IDAT compression trials; the higher the level, the more trials.

Level and trials:

1. 1 trial
2. 8 trials
3. 16 trials
4. 24 trials
5. 48 trials
6. 120 trials
7. 240 trials

$3

* Type: boolean
* Default: true

Lossless conversion to progressive.

$3

* Type: boolean
* Default: true

Interlace gif for progressive rendering.

$3

Type: Array

Customize which SVGO plugins to use. More here.

$3

* Type: Array
* Default: [imagemin.gifsicle(), imagemin.jpegtran(), imagemin.optipng(), imagemin.svgo()]

Plugins to use with imagemin. It comes bundled with the following lossless optimizers:

- gifsicle — Compress GIF images
- jpegtran — Compress JPEG images
- optipng — Compress PNG images
- svgo — Compress SVG images

These are bundled for convenience and most users will not need anything else.

$3

* Type: number
* Default: os.cpus().length`

Control the maximum number of image optimizations that may be performed in parallel.

License

MIT © Sindre Sorhus