resize

Resize

Image resizing for the Go programming language with common interpolation methods.

Build Status

Installation

$ go get github.com/nfnt/resize

It’s that easy!

Usage

This package needs at least Go 1.1. Import package with

import "github.com/nfnt/resize"

The resize package provides 2 functions:

resize.Resize(width, height uint, img image.Image, interp resize.InterpolationFunction) image.Image
resize.Thumbnail(maxWidth, maxHeight uint, img image.Image, interp resize.InterpolationFunction) image.Image

The provided interpolation functions are (from fast to slow execution time)

Which of these methods gives the best results depends on your use case.

Sample usage:

package main

import (
	"github.com/nfnt/resize"
	"image/jpeg"
	"log"
	"os"
)

func main() {
	// open "test.jpg"
	file, err := os.Open("test.jpg")
	if err != nil {
		log.Fatal(err)
	}

	// decode jpeg into image.Image
	img, err := jpeg.Decode(file)
	if err != nil {
		log.Fatal(err)
	}
	file.Close()

	// resize to width 1000 using Lanczos resampling
	// and preserve aspect ratio
	m := resize.Resize(1000, 0, img, resize.Lanczos3)

	out, err := os.Create("test_resized.jpg")
	if err != nil {
		log.Fatal(err)
	}
	defer out.Close()

	// write new image to file
	jpeg.Encode(out, m, nil)
}

Caveats

Downsizing Samples

Downsizing is not as simple as it might look like. Images have to be filtered before they are scaled down, otherwise aliasing might occur.
Filtering is highly subjective: Applying too much will blur the whole image, too little will make aliasing become apparent.
Resize tries to provide sane defaults that should suffice in most cases.

Artificial sample

Original image
Rings


Nearest-Neighbor

Bilinear

Bicubic

Mitchell-Netravali

Lanczos2

Lanczos3

Real-Life sample

Original image
Original


Nearest-Neighbor

Bilinear

Bicubic

Mitchell-Netravali

Lanczos2

Lanczos3

License

Copyright © 2012 Jan Schlicht janschlicht@gmail.com
Resize is released under a MIT style license.

Fork allmark on GitHub