@bazzite/nuxt-optimized-images

:sunrise: :rocket: Nuxt Optimized Images

Automatically optimizes images used in Nuxt.js projects (JPEG, PNG, SVG, WebP and GIF).

This module is inspired by the work of Cyril Wanner in next-optimized-images.

Read this in other languages: English, Español

Features

Image sizes can often get reduced up to 60%, but this is not the only thing @bazzite/nuxt-optimized-images does:

• Reduces image size by optimizing images during build.
• Improves loading speed by providing progressive images (for formats that support it).
• JPEG/PNG images can be converted to WebP on the fly for an even smaller size.
• Can resize images or generate low-quality image placeholders (lqip) and extract the dominant colors of it.
• Provides query params for file-specific handling/settings.
• And supports these features already included in Nuxt.js:
  • Content hash to the file name so images can get cached on CDN level and in the browser for a long time.
  • Inlined small images to save HTTP requests and additional roundtrips.
  • Same URLs fo unchanged images over multiple builds for long time caching.

Installation

:warning: node >= 10 and nuxt >= 2 are required.

npm install --save-dev @bazzite/nuxt-optimized-images

or

yarn add --dev @bazzite/nuxt-optimized-images

Add @bazzite/nuxt-optimized-images to buildModules section of nuxt.config.js:

:warning: If you are using Nuxt < 2.9.0, use modules instead.

{
  buildModules: [
    '@bazzite/nuxt-optimized-images',
  ],

  optimizedImages: {
    optimizeImages: true
  }
}

See the configuration section for all available options.

:warning: Images won't get optimized out of the box. You have to install the optimization packages you really need in addition to this module. This doesn't force you to download big optimization libraries you don't even use. Please check out the table of all optional optimization packages.

Optimization Packages

You have to install the optimization packages you need in your project in addition to this module. Then, @bazzite/nuxt-optimized-images detects all the supported packages and uses them.

So you only have to install these packages with npm, there is no additional step needed after that.

The following optimization packages are available and supported:

Optimization Package	Description	Project Link
imagemin-mozjpeg	Optimizes JPEG images	Link
imagemin-pngquant	Optimizes PNG images	Link
imagemin-optipng	Alternative for optimizing PNG images	Link
imagemin-gifsicle	Optimizes GIF images	Link
imagemin-svgo	Optimizes SVG images and icons	Link
webp-loader	Optimizes WebP images and can convert JPEG/PNG images to WebP on the fly (WebP resource query)	Link
lqip-loader	Generates low quality image placeholders and can extract the dominant colors of an image (lqip resource query)	Link
responsive-loader	Can resize images on the fly and create multiple versions of it for a srcSet. Important: You need to additionally install either jimp (node implementation, slower) or sharp (binary, faster)	Link
sqip-loader	Loads images and exports tiny SQIP previews as image/svg+xml URL-encoded data	Link

Example: If you have JPG, PNG, and SVG images in your project, you would then need to run

npm install --save-dev imagemin-mozjpeg imagemin-pngquant imagemin-svgo

# or

yarn add --dev imagemin-mozjpeg imagemin-pngquant imagemin-svgo

To install all optional packages, run:

npm install --save-dev imagemin-mozjpeg imagemin-pngquant imagemin-gifsicle imagemin-svgo  webp-loader lqip-loader responsive-loader sqip-loader sharp

# or

yarn add --dev imagemin-mozjpeg imagemin-pngquant imagemin-gifsicle imagemin-svgo  webp-loader lqip-loader responsive-loader sqip-loader sharp

:warning: Please note that by default, images are only optimized for production builds, not development builds. However, this can get changed with the optimizeImagesInDev config.

Documentation & Support

• 📄 If you want extra details of how to configure and use this project, the full documentation is available at https://www.bazzite.com/docs/nuxt-optimized-images/.
• 🐞 For Bug reports or Feature requests, use the Issues section.
• 💬 For questions, go to https://spectrum.chat/bazzite/open-source.
• 🚀 You may also want to follow the company supporting this project on Twitter.

Professional Support

This project is sponsored by Bazzite. If you require Professional Assistance on your project(s), please contact us at https://www.bazzite.com/contact.

Code of Conduct

Everyone participating in this project is expected to agree to abide by the Code of Conduct.

License

Code released under the MIT License.