/sharp

High performance Node.js image processing, the fastest module to resize JPEG, PNG, WebP and TIFF images. Uses the libvips library.

Primary LanguageJavaScriptApache License 2.0Apache-2.0

sharp

sharp logo

npm install sharp

The typical use case for this high speed Node.js module is to convert large images in common formats to smaller, web-friendly JPEG, PNG and WebP images of varying dimensions.

Resizing an image is typically 4x-5x faster than using the quickest ImageMagick and GraphicsMagick settings.

Colour spaces, embedded ICC profiles and alpha transparency channels are all handled correctly. Lanczos resampling ensures quality is not sacrificed for speed.

As well as image resizing, operations such as rotation, extraction, compositing and gamma correction are available.

Most modern 64-bit OS X, Windows and Linux systems running Node versions 6, 8, 10, 11 and 12 do not require any additional install or runtime dependencies.

Examples

const sharp = require('sharp');

Callback

sharp(inputBuffer)
  .resize(320, 240)
  .toFile('output.webp', (err, info) => { ... });

Promise

sharp('input.jpg')
  .rotate()
  .resize(200)
  .toBuffer()
  .then( data => { ... })
  .catch( err => { ... });

Async/await

const semiTransparentRedPng = await sharp({
  create: {
    width: 48,
    height: 48,
    channels: 4,
    background: { r: 255, g: 0, b: 0, alpha: 0.5 }
  }
})
  .png()
  .toBuffer();

Stream

const roundedCorners = Buffer.from(
  '<svg><rect x="0" y="0" width="200" height="200" rx="50" ry="50"/></svg>'
);

const roundedCornerResizer =
  sharp()
    .resize(200, 200)
    .composite([{
      input: roundedCorners,
      blend: 'dest-in'
    }])
    .png();

readableStream
  .pipe(roundedCornerResizer)
  .pipe(writableStream);

Test Coverage

Documentation

Visit sharp.pixelplumbing.com for complete installation instructions, API documentation, benchmark tests and changelog.

Contributing

A guide for contributors covers reporting bugs, requesting features and submitting code changes.

Licensing

Copyright 2013, 2014, 2015, 2016, 2017, 2018, 2019 Lovell Fuller and contributors.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.