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# This package is no longer being updated! Please look for alternatives if that bothers you.
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Resize
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======
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Image resizing for the [Go programming language ](http://golang.org ) with common interpolation methods.
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[![Build Status ](https://travis-ci.org/nfnt/resize.svg )](https://travis-ci.org/nfnt/resize)
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Installation
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------------
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```bash
$ go get github.com/nfnt/resize
```
It's that easy!
Usage
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-----
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This package needs at least Go 1.1. Import package with
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```go
import "github.com/nfnt/resize"
```
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The resize package provides 2 functions:
* `resize.Resize` creates a scaled image with new dimensions (`width`, `height` ) using the interpolation function `interp` .
If either `width` or `height` 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.
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```go
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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
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```
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The provided interpolation functions are (from fast to slow execution time)
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- `NearestNeighbor` : [Nearest-neighbor interpolation ](http://en.wikipedia.org/wiki/Nearest-neighbor_interpolation )
- `Bilinear` : [Bilinear interpolation ](http://en.wikipedia.org/wiki/Bilinear_interpolation )
- `Bicubic` : [Bicubic interpolation ](http://en.wikipedia.org/wiki/Bicubic_interpolation )
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- `MitchellNetravali` : [Mitchell-Netravali interpolation ](http://dl.acm.org/citation.cfm?id=378514 )
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- `Lanczos2` : [Lanczos resampling ](http://en.wikipedia.org/wiki/Lanczos_resampling ) with a=2
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- `Lanczos3` : [Lanczos resampling ](http://en.wikipedia.org/wiki/Lanczos_resampling ) with a=3
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Which of these methods gives the best results depends on your use case.
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Sample usage:
```go
package main
import (
"github.com/nfnt/resize"
"image/jpeg"
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"log"
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"os"
)
func main() {
// open "test.jpg"
file, err := os.Open("test.jpg")
if err != nil {
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log.Fatal(err)
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}
// decode jpeg into image.Image
img, err := jpeg.Decode(file)
if err != nil {
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log.Fatal(err)
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}
file.Close()
// resize to width 1000 using Lanczos resampling
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// and preserve aspect ratio
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m := resize.Resize(1000, 0, img, resize.Lanczos3)
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out, err := os.Create("test_resized.jpg")
if err != nil {
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log.Fatal(err)
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}
defer out.Close()
// write new image to file
jpeg.Encode(out, m, nil)
}
```
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Caveats
-------
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* Optimized access routines are used for `image.RGBA` , `image.NRGBA` , `image.RGBA64` , `image.NRGBA64` , `image.YCbCr` , `image.Gray` , and `image.Gray16` types. All other image types are accessed in a generic way that will result in slow processing speed.
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* 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 with `image.RGBA` .
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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 ](http://nfnt.github.com/img/rings_lg_orig.png )
< table >
< tr >
< th > < img src = "http://nfnt.github.com/img/rings_300_NearestNeighbor.png" / > < br > Nearest-Neighbor< / th >
< th > < img src = "http://nfnt.github.com/img/rings_300_Bilinear.png" / > < br > Bilinear< / th >
< / tr >
< tr >
< th > < img src = "http://nfnt.github.com/img/rings_300_Bicubic.png" / > < br > Bicubic< / th >
< th > < img src = "http://nfnt.github.com/img/rings_300_MitchellNetravali.png" / > < br > Mitchell-Netravali< / th >
< / tr >
< tr >
< th > < img src = "http://nfnt.github.com/img/rings_300_Lanczos2.png" / > < br > Lanczos2< / th >
< th > < img src = "http://nfnt.github.com/img/rings_300_Lanczos3.png" / > < br > Lanczos3< / th >
< / tr >
< / table >
### Real-Life sample
Original image
![Original ](http://nfnt.github.com/img/IMG_3694_720.jpg )
< table >
< tr >
< th > < img src = "http://nfnt.github.com/img/IMG_3694_300_NearestNeighbor.png" / > < br > Nearest-Neighbor< / th >
< th > < img src = "http://nfnt.github.com/img/IMG_3694_300_Bilinear.png" / > < br > Bilinear< / th >
< / tr >
< tr >
< th > < img src = "http://nfnt.github.com/img/IMG_3694_300_Bicubic.png" / > < br > Bicubic< / th >
< th > < img src = "http://nfnt.github.com/img/IMG_3694_300_MitchellNetravali.png" / > < br > Mitchell-Netravali< / th >
< / tr >
< tr >
< th > < img src = "http://nfnt.github.com/img/IMG_3694_300_Lanczos2.png" / > < br > Lanczos2< / th >
< th > < img src = "http://nfnt.github.com/img/IMG_3694_300_Lanczos3.png" / > < br > Lanczos3< / th >
< / tr >
< / table >
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License
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-------
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Copyright (c) 2012 Jan Schlicht < janschlicht @ gmail . com >
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Resize is released under a MIT style license.