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https://github.com/fawick/speedtest-resize

Compare various Image resize algorithms for the Go language
https://github.com/fawick/speedtest-resize

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Compare various Image resize algorithms for the Go language

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speedtest-resize

================



Compare various Image resize algorithms for the Go language



I am writing a web gallery called gonagall in Go

(https://github.com/fawick/gonagall). For that, I need a efficient solution for

scaling and resizing a lot of images (mostly JPGs) to generate thumbnails and

bandwidth-friendly sized copies from high-resolution original photo files.



In this project I compare the speed of a few selected image resizing algorithms

with each other as well as with ImageMagick and GraphicsMagick. The competitors

are



- https://github.com/nfnt/resize, Pure golang image resizing, more precisely

  only Nearest-Neighbor interpolation that comes with that Go package.

- https://github.com/disintegration/gift Again, I use one of the fastest

  algorithms of the package. Here, it's called 'Box'

- https://github.com/disintegration/imaging Again, I use one of the fastest

  algorithms of the package. Here, it's called 'Box'

- https://github.com/anthonynsimon/bild A collection of parallel image

  processing algorithms in pure Go ('NearestNeighbor' algorithm)

- [ImageMagick convert](http://www.imagemagick.org/script/convert.php) with the options `-resize 150x150>`

- [ImageMagick convert](http://www.imagemagick.org/script/convert.php) with the

  options `-define "jpeg:size=300x300 -thumbnail 150x150>`. `-thumbnail` is

considered to be faster than resize, and the `-define` will reduce the size (in

terms of memory footprint) of the original image on reading.

- [GraphicsMagick convert](http://www.graphicsmagick.org/convert.html) with the

  options `-define "jpeg:size=300x300 -thumbnail 150x150>`.

- https://github.com/gographics/imagick Go wrapper for the MagickWand API,

  again the Box algorithm is used for the sake of comparing the results.

- https://github.com/lazywei/go-opencv Go binding for OpenCV, using the fastest

  algorithm.

- https://github.com/bamiaux/rez, pure go resizer, using bilinear interpolation

  in these tests

- https://github.com/DAddYE/vips, bindings for libvips

  (http://www.vips.ecs.soton.ac.uk/index.php?title=Libvips)

- https://github.com/daddye/trez, an image resizer build on top of OpenCV and

  jpeg-turbo

- https://camlistore.org/pkg/images/fastjpeg, package fastjpeg uses djpeg(1),

  from the Independent JPEG Group's (www.ijg.org) jpeg package, to quickly

  down-sample images on load

- External command `vipsthumbnail` with parameters `-s 150`

  (https://github.com/libvips/libvips)

- External command `epeg` with parameters `-m 150`

  (https://github.com/mattes/epeg)



### Installation



To run the tests `go get` the source and compile/run it:



    $ go get -u github.com/fawick/speedtest-resize -tags all

    $ cd $GOPATH/src/speedtest-resize

    $ go run main.go 



Alternatively, call the go command (or the compiled binary) from the image

folder without supplying a parameter



    $ cd 

    $ go run $GOPATH/src/speedtest-resize/main.go



A the package requires different 3rdparty libraries to be installed, you can

use build tags to control what libraries to use. The following build tags are

available:



| Tag         | Description                                             |

| ----------- | ------------------------------------------------------- |

| `opencv`    | Include `lazywei/go-opencv` in the tests.               |

| `imagick`   | Include `gographics/imagick` in the tests.              |

| `vips`      | Include `DAddYE/vips in the tests`.                     |

| `fastjpeg`  | Include `camlistore/fastjpeg in the tests`.             |

| `all`       | An alias for `opencv imagick fastjpeg vips`.            |

| `nopure`    | Don't include the Pure Golang packages                  |

| `noexec`    | Don't run the tests that execute other programs.        |



The default `go get` without any tags will try the packages that are pure go

and the external programs but not use any non-Go library.



### Benchmark



Im my test scenario all of these tools/packages are unleashed on a directory

containing JPG photo files, all of which have a resolution of 5616x3744 pixels

(aspect ratio 2:1, both landscape and portrait).



For each tool/package and for all files, the total time for loading the

original file, scaling the image to a thumbnail of 150x100 pixels, and writing

it to a new JPG file is measured. In the end, the total runtime for processing

the 10 first files and the average time per file is printed for each

tool/package.



The scenario is run on a Intel(R) Pentium(R) Dual T2390 @ 1.86GHz running

Ubuntu 14.04. Here are the results:



| Table                 | Time (avg.) | Size (avg.) | Pure Go |

|-----------------------|------------:|------------:|:-------:|

| vipsthumbnail         |      0.120s |      0.065% |         |

| ImageMagick_thumbnail |      0.326s |      0.242% |         |

| vips                  |      0.339s |      0.100% |         |

| magickwand_box        |      1.148s |      0.538% |         |

| ImageMagick_resize    |      2.316s |      0.626% |         |

| rez_bilinear          |      2.913s |      0.053% |    X    |

| Nfnt_NearestNeighbor  |      3.498s |      0.057% |    X    |

| imaging_box           |      4.734s |      0.057% |    X    |

| gift_box              |      4.746s |      0.057% |    X    |



--------



Yet another scenario ran by [lazywei](https://github.com/lazywei), 2.5GHz Intel Core i5, Mac OS X 10.9.1:



| Tables               | Average time per file  |

| -------------------- | ----------------------:|

| magickwand_box       |  155.371531ms          |

| imaging_Box          |  463.459339ms          |

| Nfnt_NearestNeighbor |  1.436507946s          |

| OpenCv               |   97.353041ms          |



--------



Yet another scenario ran by [bamiaux](https://github.com/bamiaux), 3.3GHz Intel Core i5, win 7:



| Tables               | Average time per file  |

| -------------------- | ----------------------:|

| rez_bilinear         |  148ms                 |

| imaging_Box          |  243ms                 |

| Nfnt_NearestNeighbor |  233ms                 |



--------



A new scenario ran by [nono](https://github.com/nono), 3.4GHz Intel Core i7, Ubuntu 16.10:



| Table                          | Time (file avg.) | Size (file avg.) | Pure Go |

|--------------------------------|-----------------:|-----------------:|:-------:|

| ImageMagick_thumbnail          |           0.057s |           0.361% |         |

| vips                           |           0.070s |           0.260% |         |

| epeg                           |           0.079s |           0.207% |         |

| fastjpeg                       |           0.082s |           0.186% |         |

| opencv                         |           0.110s |           0.597% |         |

| vipsthumbnail                  |           0.115s |           0.441% |         |

| GraphicsMagick_thumbnail       |           0.172s |           0.427% |         |

| magickwand_box                 |           0.190s |           0.575% |         |

| T-REZ                          |           0.204s |           0.323% |         |

| rez_bilinear                   |           0.349s |           0.140% |    X    |

| x_image_draw                   |           0.370s |           0.160% |    X    |

| imaging_box                    |           0.439s |           0.146% |    X    |

| gift_box                       |           0.440s |           0.146% |    X    |

| Nfnt_NearestNeighbor           |           0.447s |           0.146% |    X    |

| bild_resize                    |           0.515s |           0.206% |    X    |

| ImageMagick_resize             |           0.568s |           0.542% |         |



--------



So, what is to learn from that? While all of the currently existing

pure-Go-language solutions do a pretty good job in generating good-looking

thumbnails, they are much slower than the veteran dedicated image processing

toolboxes. That is hardly surprising, given that both ImageMagick and

GraphicsMagick have been around for decades and have been optimized to work as

efficient as possible. Go and its image processing packages are still the new

kids on the block, and while they work pretty neat for the occasional tweak of

an image or two, I rather not use them as the default image processor in

[gonagall](http://github.com/fawick/gonagall) yet.



I was surprised to find that GraphicsMagick was slower than ImageMagick in my

test scenario, as I expected it to be exactly the other way around with

GraphicsMagick's fancy multi-processor algorithms.



While the imagick Wrapper is written in Go, it uses CGO bindings of the C

MagickWand API. It outperforms the pure-Go approaches (five times faster than

http://github.com/disintegration/imaging) but it still slower than calling

ImageMagick in an external process. Of the above 1.13 seconds, only around 275

millisecs were used for resizing and saving an individual file, while over 850

ms were used by simply loading the file. I wonder how much optimization can

still be done in the imagick loading routines.



Holy cow! `vipsthumbnail` __is__ blazing fast.