Image resizing for the Go programming language with common interpolation methods.
$ go get github.com/kmulvey/resize
It's that easy!
This package needs at least Go 1.1. Import package with
import "github.com/kmulvey/resize"
The resize package provides 2 functions:
resize.Resize
creates a scaled image with new dimensions (width
,height
) using the interpolation functioninterp
. If eitherwidth
orheight
is set to 0, it will be set to an aspect ratio preserving value.resize.Thumbnail
downscales an image preserving its aspect ratio to the maximum dimensions (maxWidth
,maxHeight
). It will return the original image if original sizes are smaller than the provided dimensions.
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)
NearestNeighbor
: Nearest-neighbor interpolationBilinear
: Bilinear interpolationBicubic
: Bicubic interpolationMitchellNetravali
: Mitchell-Netravali interpolationLanczos2
: Lanczos resampling with a=2Lanczos3
: Lanczos resampling with a=3
Which of these methods gives the best results depends on your use case.
Sample usage:
package main
import (
"github.com/kmulvey/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)
}
- Optimized access routines are used for
image.RGBA
,image.NRGBA
,image.RGBA64
,image.NRGBA64
,image.YCbCr
,image.Gray
, andimage.Gray16
types. All other image types are accessed in a generic way that will result in slow processing speed. - JPEG images are stored in
image.YCbCr
. This image format stores data in a way that will decrease processing speed. A resize may be up to 2 times slower than withimage.RGBA
.
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.
![]() Nearest-Neighbor |
![]() Bilinear |
---|---|
![]() Bicubic |
![]() Mitchell-Netravali |
![]() Lanczos2 |
![]() Lanczos3 |
![]() Nearest-Neighbor |
![]() Bilinear |
---|---|
![]() Bicubic |
![]() Mitchell-Netravali |
![]() Lanczos2 |
![]() Lanczos3 |
Copyright (c) 2012 Jan Schlicht janschlicht@gmail.com Resize is released under a MIT style license.