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grunt-contrib-imagemin Build Status: Linux Build Status: Windows

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)

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

progressive (jpg)

Lossless conversion to progressive.

interlaced (gif)

Interlace gif for progressive rendering.

svgoPlugins (svg)

Type: Array

Customize which SVGO plugins to use. More here.

use

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

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

concurrency

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

License

MIT © Sindre Sorhus