grunt-contrib-imagemin
Minify images using imagemin
Install
npm install --save-dev grunt-contrib-imagemin
Usage
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
optimizationLevel (png)
- 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 trial
- 8 trials
- 16 trials
- 24 trials
- 48 trials
- 120 trials
- 240 trials
progressive (jpg)
- Type:
boolean
- Default:
true
Lossless conversion to progressive.
interlaced (gif)
- Type:
boolean
- Default:
true
Interlace gif for progressive rendering.
svgoPlugins (svg)
Type: Array
Customize which SVGO plugins to use. More here.
use
- 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.
concurrency
- Type:
number
- Default:
os.cpus().length
Control the maximum number of image optimizations that may be performed in parallel.
License
MIT © Sindre Sorhus