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 Windows (x64), Linux and ARMv6+ systems do not require the installation of any external runtime dependencies.
Use with OS X is as simple as running
brew install homebrew/science/vips
to install the libvips dependency.
This module supports reading JPEG, PNG, WebP, TIFF, GIF and SVG images.
Output images can be in JPEG, PNG and WebP formats as well as uncompressed raw pixel data.
Streams, Buffer objects and the filesystem can be used for input and output.
A single input Stream can be split into multiple processing pipelines and output Streams.
Only small regions of uncompressed image data are held in memory and processed at a time, taking full advantage of multiple CPU cores and L1/L2/L3 cache.
Everything remains non-blocking thanks to libuv, no child processes are spawned and Promises/A+ are supported.
PNG filtering can be disabled, which for diagrams and line art often produces the same result as pngcrush.
A guide for contributors covers reporting bugs, requesting features and submitting code changes.
This module would never have been possible without the help and code contributions of the following people:
- John Cupitt
- Pierre Inglebert
- Jonathan Ong
- Chanon Sajjamanochai
- Juliano Julio
- Daniel Gasienica
- Julian Walker
- Amit Pitaru
- Brandon Aaron
- Andreas Lind
- Maurus Cuelenaere
- Linus Unnebäck
- Victor Mateevitsi
- Alaric Holloway
- Bernhard K. Weisshuhn
- David A. Carley
- John Tobin
- Kenton Gray
- Felix Bünemann
- Samy Al Zahrani
- Chintan Thakkar
- F. Orlando Galashan
- Kleis Auke Wolthuizen
- Matt Hirsch
- Rahul Nanwani
Copyright 2013, 2014, 2015, 2016 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 http://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.