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| # This package is no longer being updated! Please look for alternatives if that bothers you. | ||
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| Resize | ||
| Canvas | ||
| ====== | ||
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| Image resizing for the [Go programming language](http://golang.org) with common interpolation methods. | ||
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| [](https://travis-ci.org/nfnt/resize) | ||
| Image resizing for the [Go](http://golang.org) with common interpolation methods. | ||
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| Installation | ||
| ------------ | ||
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| ```bash | ||
| $ go get github.com/nfnt/resize | ||
| $ go get github.com/leon3103/canvas | ||
| ``` | ||
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| It's that easy! | ||
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| Usage | ||
| Using Canvas | ||
| ----- | ||
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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" | ||
| import "github.com/leon3103/canvas" | ||
| ``` | ||
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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`. | ||
| 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 | ||
| 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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| 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) | ||
| - `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 | ||
| - `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 | ||
| package main | ||
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| import ( | ||
| "github.com/nfnt/resize" | ||
| "image/jpeg" | ||
| "log" | ||
| "os" | ||
| ) | ||
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| 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) | ||
| } | ||
| file.Close() | ||
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| // 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) | ||
| } | ||
| defer out.Close() | ||
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| // 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. | ||
| * 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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| 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. | ||
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| ### Artificial sample | ||
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| Original image | ||
|  | ||
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| <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> | ||
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| ### Real-Life sample | ||
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| Original image | ||
|  | ||
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| <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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| Copyright (c) 2012 Jan Schlicht <janschlicht@gmail.com> | ||
| Resize is released under a MIT style license. | ||
| Copyright (c) 2020 Leon Wolf <leonwolf.oldb+canvas@gmail.com> | ||
| canvas is released under MIT license. |