go-resize/README.md

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Resize
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======
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Image resizing for the [Go programming language](http://golang.org) that includes a few interpolation methods.
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[![Build Status](https://travis-ci.org/nfnt/resize.png)](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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Import package with
```go
import "github.com/nfnt/resize"
```
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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.
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```go
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resize.Resize(width, height uint, img image.Image, interp resize.InterpolationFunction) image.Image
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```
The provided interpolation functions are
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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)
- `MitchellNetravali`: [Mitchell-Netravali interpolation](http://dl.acm.org/citation.cfm?id=378514)
- `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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Sample usage:
```go
package main
import (
"github.com/nfnt/resize"
"image/jpeg"
"log"
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"os"
)
func main() {
// open "test.jpg"
file, err := os.Open("test.jpg")
if err != nil {
log.Fatal(err)
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}
// decode jpeg into image.Image
img, err := jpeg.Decode(file)
if err != nil {
log.Fatal(err)
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}
file.Close()
// resize to width 1000 using Lanczos resampling
// and preserve aspect ratio
m := resize.Resize(1000, 0, img, resize.Lanczos3)
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out, err := os.Create("test_resized.jpg")
if err != nil {
log.Fatal(err)
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}
defer out.Close()
// write new image to file
jpeg.Encode(out, m, nil)
}
```
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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 an MIT style license.