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homm committed Jul 2, 2016
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Expand Up @@ -8,17 +8,16 @@ For more information about original Pillow, please
[find out how to contribute](https://github.com/python-pillow/Pillow/blob/master/.github/CONTRIBUTING.md).


## Aims
## What is SIMD


## Status


## Performance
## Benchmarks

Hardware: Intel Core i5 4258U with AVX2.

Software: Ubuntu 14.04 64-bit.
Numbers are megapixels of source image per second. For example if resize of
7712x4352 image is done in 0.5 seconds, the resoult will be 61.7 Mpx/s.

- ImageMagick 6.9.3-8 Q8 x86_64
- Pillow 3.2.0
Expand All @@ -38,6 +37,36 @@ Source | Operation | IM | Pillow | SIMD SSE4 | SIMD AVX2
| Blur 1px | 8.1 | 17.1 | 37.8
| Blur 10px | 2.6 | 17.4 | 39.0
| Blur 100px | 0.3 | 17.2 | 39.0
1920x1280 | Bilinear resize to 16x16 | 41.6 | 196 | 422 | 489
| Bilinear resize to 320x180 | 27.6 | 111 | 196 | 197
| Bilinear resize to 2048x1155| 9.1 | 20.7 | 71.3 | 72.6
| Bicubic resize to 16x16 | 18.9 | 102 | 225 | 263
| Bicubic resize to 320x180 | 14.5 | 66.3 | 154 | 162
| Bicubic resize to 2048x1155 | 6.3 | 16.9 | 49.3 | 54.3
| Lanczos resize to 16x16 | 13.7 | 68.6 | 118 | 167
| Lanczos resize to 320x180 | 9.8 | 44.3 | 102 | 107
| Lanczos resize to 2048x1155 | 4.7 | 14.6 | 36.8 | 40.6
| Blur 1px | 8.7 | 16.2 | 35.7
| Blur 10px | 2.8 | 16.7 | 35.4
| Blur 100px | 0.4 | 16.4 | 36.2


### Methodology

All tests done on Ubuntu 14.04 64-bit runing on
Intel Core i5 4258U with AVX2 CPU.

Following script were using for tests:
https://gist.github.com/homm/f9b8d8a84a57a7e51f9c2a5828e40e63


## Why Pillow is so fast itself

There are no cheats. High-quality resize and blur methods are used for all
benchmakrs. And result is


## Why Pillow-SIMD even faster


## Contributing to Pillow-SIMD
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