mirror of
https://github.com/go-gitea/gitea.git
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150 lines
4.7 KiB
Markdown
150 lines
4.7 KiB
Markdown
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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
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$ go get github.com/nfnt/resize
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```
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It's that easy!
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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
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import "github.com/nfnt/resize"
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```
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The resize package provides 2 functions:
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* `resize.Resize` creates a scaled image with new dimensions (`width`, `height`) using the interpolation function `interp`.
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If either `width` or `height` is set to 0, it will be set to an aspect ratio preserving value.
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* `resize.Thumbnail` downscales an image preserving its aspect ratio to the maximum dimensions (`maxWidth`, `maxHeight`).
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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
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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)
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- `Bilinear`: [Bilinear interpolation](http://en.wikipedia.org/wiki/Bilinear_interpolation)
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- `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:
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```go
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package main
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import (
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"github.com/nfnt/resize"
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"image/jpeg"
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"log"
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"os"
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)
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func main() {
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// open "test.jpg"
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file, err := os.Open("test.jpg")
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if err != nil {
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log.Fatal(err)
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}
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// decode jpeg into image.Image
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img, err := jpeg.Decode(file)
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if err != nil {
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log.Fatal(err)
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}
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file.Close()
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// 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")
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if err != nil {
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log.Fatal(err)
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}
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defer out.Close()
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// write new image to file
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jpeg.Encode(out, m, nil)
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}
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```
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Caveats
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-------
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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
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-------
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Downsizing is not as simple as it might look like. Images have to be filtered before they are scaled down, otherwise aliasing might occur.
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Filtering is highly subjective: Applying too much will blur the whole image, too little will make aliasing become apparent.
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Resize tries to provide sane defaults that should suffice in most cases.
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### Artificial sample
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Original image
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![Rings](http://nfnt.github.com/img/rings_lg_orig.png)
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<table>
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<tr>
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<th><img src="http://nfnt.github.com/img/rings_300_NearestNeighbor.png" /><br>Nearest-Neighbor</th>
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<th><img src="http://nfnt.github.com/img/rings_300_Bilinear.png" /><br>Bilinear</th>
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</tr>
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<tr>
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<th><img src="http://nfnt.github.com/img/rings_300_Bicubic.png" /><br>Bicubic</th>
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<th><img src="http://nfnt.github.com/img/rings_300_MitchellNetravali.png" /><br>Mitchell-Netravali</th>
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</tr>
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<tr>
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<th><img src="http://nfnt.github.com/img/rings_300_Lanczos2.png" /><br>Lanczos2</th>
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<th><img src="http://nfnt.github.com/img/rings_300_Lanczos3.png" /><br>Lanczos3</th>
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</tr>
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</table>
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### Real-Life sample
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Original image
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![Original](http://nfnt.github.com/img/IMG_3694_720.jpg)
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<table>
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<tr>
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<th><img src="http://nfnt.github.com/img/IMG_3694_300_NearestNeighbor.png" /><br>Nearest-Neighbor</th>
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<th><img src="http://nfnt.github.com/img/IMG_3694_300_Bilinear.png" /><br>Bilinear</th>
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</tr>
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<tr>
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<th><img src="http://nfnt.github.com/img/IMG_3694_300_Bicubic.png" /><br>Bicubic</th>
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<th><img src="http://nfnt.github.com/img/IMG_3694_300_MitchellNetravali.png" /><br>Mitchell-Netravali</th>
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</tr>
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<tr>
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<th><img src="http://nfnt.github.com/img/IMG_3694_300_Lanczos2.png" /><br>Lanczos2</th>
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<th><img src="http://nfnt.github.com/img/IMG_3694_300_Lanczos3.png" /><br>Lanczos3</th>
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</tr>
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</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.
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