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README.md
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README.md
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# Pillow-SIMD
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Pillow-SIMD is "following" Pillow (which is a PIL's fork itself).
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"Following" here means than Pillow-SIMD versions are 100% compatible
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Pillow-SIMD is "following" [Pillow][original-docs].
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Pillow-SIMD versions are 100% compatible
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drop-in replacements for Pillow of the same version.
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For example, `Pillow-SIMD 3.2.0.post3` is a drop-in replacement for
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`Pillow 3.2.0`, and `Pillow-SIMD 3.3.3.post0` — for `Pillow 3.3.3`.
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@ -53,71 +53,17 @@ The following image operations are currently SIMD-accelerated:
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See [CHANGES](CHANGES.SIMD.rst) for more information.
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## Benchmarks
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In order for you to clearly assess the productivity of implementing SIMD computing into Pillow image processing,
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we ran a number of benchmarks. The respective results can be found in the table below (the more — the better).
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The numbers represent processing rates in megapixels per second (Mpx/s).
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For instance, the rate at which a 2560x1600 RGB image is processed in 0.5 seconds equals to 8.2 Mpx/s.
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Here is the list of libraries and their versions we've been up to during the benchmarks:
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- Skia 53
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- ImageMagick 6.9.3-8 Q8 x86_64
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- Pillow 3.4.1
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- Pillow-SIMD 3.4.1.post1
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Operation | Filter | IM | Pillow| SIMD SSE4| SIMD AVX2| Skia 53
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------------------------|---------|------|-------|----------|----------|--------
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**Resize to 16x16** | Bilinear| 41.37| 317.28| 1282.85| 1601.85| 809.49
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| Bicubic | 20.58| 174.85| 712.95| 900.65| 453.10
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| Lanczos | 14.17| 117.58| 438.60| 544.89| 292.57
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**Resize to 320x180** | Bilinear| 29.46| 195.21| 863.40| 1057.81| 592.76
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| Bicubic | 15.75| 118.79| 503.75| 504.76| 327.68
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| Lanczos | 10.80| 79.59| 312.05| 384.92| 196.92
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**Resize to 1920x1200** | Bilinear| 17.80| 68.39| 215.15| 268.29| 192.30
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| Bicubic | 9.99| 49.23| 170.41| 210.62| 112.84
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| Lanczos | 6.95| 37.71| 130.00| 162.57| 104.76
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**Resize to 7712x4352** | Bilinear| 2.54| 8.38| 22.81| 29.17| 20.58
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| Bicubic | 1.60| 6.57| 18.23| 23.94| 16.52
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| Lanczos | 1.09| 5.20| 14.90| 20.40| 12.05
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**Blur** | 1px | 6.60| 16.94| 35.16| |
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| 10px | 2.28| 16.94| 35.47| |
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| 100px | 0.34| 16.93| 35.53| |
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### A brief conclusion
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Tons of tests can be found on the [Pillow Performance][pillow-perf-page] page.
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There are benchmarks against different versions of Pillow and Pillow-SIMD
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as well as ImageMagick, Skia, OpenCV and IPP.
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The results show that Pillow is always faster than ImageMagick,
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Pillow-SIMD, in turn, is even faster than the original Pillow by the factor of 4-5.
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Pillow-SIMD, in turn, is even faster than the original Pillow by the factor of 4-6.
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In general, Pillow-SIMD with AVX2 is always **16 to 40 times faster** than
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ImageMagick and outperforms Skia, the high-speed graphics library used in Chromium.
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### Methodology
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All rates were measured using the following setup: Ubuntu 14.04 64-bit,
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single-thread AVX2-enabled Intel i5 4258U CPU.
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ImageMagick performance was measured with the `convert` command-line tool
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followed by `-verbose` and `-bench` arguments.
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Such approach was used because there's usually a need in testing
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the latest software versions and command-line is the easiest way to do that.
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All the routines involved with the testing procedure produced identic results.
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Resizing filters compliance:
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- PIL.Image.BILINEAR == Triangle
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- PIL.Image.BICUBIC == Catrom
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- PIL.Image.LANCZOS == Lanczos
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In ImageMagick, Gaussian blur operation invokes two parameters:
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the first is called 'radius' and the second is called 'sigma'.
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In fact, in order for the blur operation to be Gaussian, there should be no additional parameters.
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When the radius value is too small the blur procedure ceases to be Gaussian and
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if the value is excessively big the operation gets slowed down with zero benefits in exchange.
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For the benchmarking purposes, the radius was set to `sigma × 2.5`.
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Following script was used for the benchmarking procedure:
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https://gist.github.com/homm/f9b8d8a84a57a7e51f9c2a5828e40e63
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## Why Pillow itself is so fast
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@ -125,6 +71,7 @@ No cheats involved. We've used identical high-quality resize and blur methods fo
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Outcomes produced by different libraries are in almost pixel-perfect agreement.
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The difference in measured rates is only provided with the performance of every involved algorithm.
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## Why Pillow-SIMD is even faster
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Because of the SIMD computing, of course. But there's more to it:
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@ -159,6 +106,7 @@ $ pip uninstall pillow
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$ CC="cc -mavx2" pip install -U --force-reinstall pillow-simd
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```
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## Contributing to Pillow-SIMD
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Please be aware that Pillow-SIMD and Pillow are two separate projects.
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@ -166,10 +114,13 @@ Please submit bugs and improvements not related to SIMD to the [original Pillow]
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All bugfixes to the original Pillow will then be transferred to the next Pillow-SIMD version automatically.
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[original-docs]: http://pillow.readthedocs.io/
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[original-homepage]: https://python-pillow.org/
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[original-docs]: https://pillow.readthedocs.io/
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[original-issues]: https://github.com/python-pillow/Pillow/issues/new
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[original-changelog]: https://github.com/python-pillow/Pillow/blob/master/CHANGES.rst
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[original-contribute]: https://github.com/python-pillow/Pillow/blob/master/.github/CONTRIBUTING.md
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[gaussian-blur-changes]: http://pillow.readthedocs.io/en/3.2.x/releasenotes/2.7.0.html#gaussian-blur-and-unsharp-mask
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[gaussian-blur-changes]: https://pillow.readthedocs.io/en/3.2.x/releasenotes/2.7.0.html#gaussian-blur-and-unsharp-mask
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[pillow-perf-page]: https://python-pillow.org/pillow-perf/
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[pillow-perf-repo]: https://github.com/python-pillow/pillow-perf
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[uploadcare.com]: https://uploadcare.com/?utm_source=github&utm_medium=description&utm_campaign=pillow-simd
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[uploadcare.logo]: https://ucarecdn.com/dc4b8363-e89f-402f-8ea8-ce606664069c/-/preview/
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