# cykooz.resizer
```cykooz.resizer``` is package with the optimized version of image resizing
based on Rust's crate [fast_image_resize](https://crates.io/crates/fast_image_resize).
[CHANGELOG](https://github.com/Cykooz/cykooz.resizer/blob/main/CHANGES.md)
## Installation
```shell
python3 -m pip install cykooz.resizer
```
Or with automatically installing Pillow:
```shell
python3 -m pip install cykooz.resizer[pillow]
```
## Information
Supported pixel types and available optimisations:
| Format | Description | SSE4.1 | AVX2 | Neon |
|:------:|:--------------------------------------------------------------|:------:|:----:|:----:|
| U8 | One `u8` component per pixel (e.g. L) | + | + | + |
| U8x2 | Two `u8` components per pixel (e.g. LA) | + | + | + |
| U8x3 | Three `u8` components per pixel (e.g. RGB) | + | + | + |
| U8x4 | Four `u8` components per pixel (e.g. RGBA, RGBx, CMYK) | + | + | + |
| U16 | One `u16` components per pixel (e.g. L16) | + | + | + |
| U16x2 | Two `u16` components per pixel (e.g. LA16) | + | + | + |
| U16x3 | Three `u16` components per pixel (e.g. RGB16) | + | + | + |
| U16x4 | Four `u16` components per pixel (e.g. RGBA16, RGBx16, CMYK16) | + | + | + |
| I32 | One `i32` component per pixel | - | - | - |
| F32 | One `f32` component per pixel | + | + | - |
| F32x2 | Two `f32` components per pixel (e.g. LA32F) | + | + | - |
| F32x3 | Three `f32` components per pixel (e.g. RGB32F) | + | + | - |
| F32x4 | Four `f32` components per pixel (e.g. RGBA32F) | + | + | - |
Implemented resize algorithms:
- Nearest - is nearest-neighbor interpolation, replacing every pixel with the
nearest pixel in the output; for upscaling this means multiple pixels of the
same color will be present.
- Convolution with different filters:
- box
- bilinear
- catmull_rom
- mitchell
- gaussian
- lanczos3
- Super sampling - is resizing an image in two steps.
The first step uses the "nearest" algorithm. The second step uses "convolution"
with configurable filter.
## Usage Examples
### Resize Pillow's image
```python
from PIL import Image
from cykooz.resizer import FilterType, ResizeAlg, Resizer, ResizeOptions
resizer = Resizer()
dst_size = (255, 170)
dst_image = Image.new('RGBA', dst_size)
for i in range(1, 10):
image = Image.open('nasa_%d-4928x3279.png' % i)
resizer.resize_pil(image, dst_image)
dst_image.save('nasa_%d-255x170.png' % i)
# Resize using a bilinear filter and ignoring an alpha channel.
image = Image.open('nasa-4928x3279.png')
resizer.resize_pil(
image,
dst_image,
ResizeOptions(
resize_alg=ResizeAlg.convolution(FilterType.bilinear),
use_alpha=False,
)
)
```
### Resize raw image with an alpha channel
```python
from cykooz.resizer import ImageData, PixelType, Resizer
def resize_raw(width: int, height: int, pixels: bytes):
src_image = ImageData(
width,
height,
PixelType.U8x4,
pixels,
)
resizer = Resizer()
dst_image = ImageData(255, 170, PixelType.U8x4)
# By default, Resizer multiplies and divides by alpha channel
# images with `U8x2`, `U8x4`, `U16x2` and `U16x4` pixels.
resizer.resize(src_image, dst_image)
return dst_image
```
### Change used CPU-extensions
```python
from cykooz.resizer import Resizer, CpuExtensions
resizer = Resizer()
resizer.cpu_extensions = CpuExtensions.sse4_1
...
```
### Resize with using thread-pool
```python
from cykooz.resizer import Resizer, ResizeOptions, ResizerThreadPool
...
thread_pool = ResizerThreadPool(num_threads=6)
resizer = Resizer()
resizer.resize(
src_image,
dst_image,
ResizeOptions(thread_pool=thread_pool),
)
...
```
## Benchmarks
Environment:
- CPU: AMD Ryzen 9 5950X
- RAM: DDR4 4000 MHz
- Ubuntu 24.04 (linux 6.8.0)
- Python 3.12
- Rust 1.83.0
- cykooz.resizer = "3.1" (single-threaded mode)
Other Python libraries used to compare of resizing speed:
- Pillow = "11.0.0" (https://pypi.org/project/Pillow/)
Resize algorithms:
- Nearest
- Convolution with Bilinear filter
- Convolution with Lanczos3 filter
### Resize RGBA image 4928x3279 => 852x567
- Source image [nasa-4928x3279.png](https://github.com/Cykooz/cykooz.resizer/blob/main/tests/data/nasa-4928x3279.png)
| Package (time in ms) | nearest | bilinear | lanczos3 |
|:------------------------|--------:|---------:|---------:|
| Pillow | 0.89 | 107.21 | 203.67 |
| cykooz.resizer | 0.20 | 26.09 | 50.47 |
| cykooz.resizer - sse4_1 | 0.20 | 12.12 | 24.91 |
| cykooz.resizer - avx2 | 0.20 | 8.53 | 22.10 |
### Resize grayscale (U8) image 4928x3279 => 852x567
- Source image [nasa-4928x3279.png](https://github.com/Cykooz/cykooz.resizer/blob/main/tests/data/nasa-4928x3279.png)
has converted into grayscale image with one byte per pixel.
| Package (time in ms) | nearest | bilinear | lanczos3 |
|:------------------------|--------:|---------:|---------:|
| Pillow | 0.23 | 21.41 | 51.15 |
| cykooz.resizer | 0.17 | 5.30 | 12.17 |
| cykooz.resizer - sse4_1 | 0.17 | 2.11 | 5.84 |
| cykooz.resizer - avx2 | 0.17 | 1.86 | 4.58 |
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"description": "# cykooz.resizer\n\n```cykooz.resizer``` is package with the optimized version of image resizing\nbased on Rust's crate [fast_image_resize](https://crates.io/crates/fast_image_resize).\n\n[CHANGELOG](https://github.com/Cykooz/cykooz.resizer/blob/main/CHANGES.md)\n\n## Installation\n\n```shell\npython3 -m pip install cykooz.resizer\n```\n\nOr with automatically installing Pillow:\n\n```shell\npython3 -m pip install cykooz.resizer[pillow]\n```\n\n## Information\n\nSupported pixel types and available optimisations:\n\n| Format | Description | SSE4.1 | AVX2 | Neon |\n|:------:|:--------------------------------------------------------------|:------:|:----:|:----:|\n| U8 | One `u8` component per pixel (e.g. L) | + | + | + |\n| U8x2 | Two `u8` components per pixel (e.g. LA) | + | + | + |\n| U8x3 | Three `u8` components per pixel (e.g. RGB) | + | + | + |\n| U8x4 | Four `u8` components per pixel (e.g. RGBA, RGBx, CMYK) | + | + | + |\n| U16 | One `u16` components per pixel (e.g. L16) | + | + | + |\n| U16x2 | Two `u16` components per pixel (e.g. LA16) | + | + | + |\n| U16x3 | Three `u16` components per pixel (e.g. RGB16) | + | + | + |\n| U16x4 | Four `u16` components per pixel (e.g. RGBA16, RGBx16, CMYK16) | + | + | + |\n| I32 | One `i32` component per pixel | - | - | - |\n| F32 | One `f32` component per pixel | + | + | - |\n| F32x2 | Two `f32` components per pixel (e.g. LA32F) | + | + | - |\n| F32x3 | Three `f32` components per pixel (e.g. RGB32F) | + | + | - |\n| F32x4 | Four `f32` components per pixel (e.g. RGBA32F) | + | + | - |\n\nImplemented resize algorithms:\n\n- Nearest - is nearest-neighbor interpolation, replacing every pixel with the\n nearest pixel in the output; for upscaling this means multiple pixels of the\n same color will be present.\n- Convolution with different filters:\n - box\n - bilinear\n - catmull_rom\n - mitchell\n - gaussian\n - lanczos3\n- Super sampling - is resizing an image in two steps.\n The first step uses the \"nearest\" algorithm. The second step uses \"convolution\"\n with configurable filter.\n\n## Usage Examples\n\n### Resize Pillow's image\n\n```python\nfrom PIL import Image\n\nfrom cykooz.resizer import FilterType, ResizeAlg, Resizer, ResizeOptions\n\n\nresizer = Resizer()\ndst_size = (255, 170)\ndst_image = Image.new('RGBA', dst_size)\n\nfor i in range(1, 10):\n image = Image.open('nasa_%d-4928x3279.png' % i)\n resizer.resize_pil(image, dst_image)\n dst_image.save('nasa_%d-255x170.png' % i)\n\n# Resize using a bilinear filter and ignoring an alpha channel.\nimage = Image.open('nasa-4928x3279.png')\nresizer.resize_pil(\n image,\n dst_image,\n ResizeOptions(\n resize_alg=ResizeAlg.convolution(FilterType.bilinear),\n use_alpha=False,\n )\n)\n```\n\n### Resize raw image with an alpha channel\n\n```python\nfrom cykooz.resizer import ImageData, PixelType, Resizer\n\n\ndef resize_raw(width: int, height: int, pixels: bytes):\n src_image = ImageData(\n width,\n height,\n PixelType.U8x4,\n pixels,\n )\n resizer = Resizer()\n dst_image = ImageData(255, 170, PixelType.U8x4)\n # By default, Resizer multiplies and divides by alpha channel\n # images with `U8x2`, `U8x4`, `U16x2` and `U16x4` pixels.\n resizer.resize(src_image, dst_image)\n return dst_image\n```\n\n### Change used CPU-extensions\n\n```python\nfrom cykooz.resizer import Resizer, CpuExtensions\n\n\nresizer = Resizer()\nresizer.cpu_extensions = CpuExtensions.sse4_1\n...\n```\n\n### Resize with using thread-pool\n\n```python\nfrom cykooz.resizer import Resizer, ResizeOptions, ResizerThreadPool\n\n\n...\nthread_pool = ResizerThreadPool(num_threads=6)\nresizer = Resizer()\nresizer.resize(\n src_image,\n dst_image,\n ResizeOptions(thread_pool=thread_pool),\n)\n...\n```\n\n## Benchmarks\n\nEnvironment:\n\n- CPU: AMD Ryzen 9 5950X\n- RAM: DDR4 4000 MHz\n- Ubuntu 24.04 (linux 6.8.0)\n- Python 3.12\n- Rust 1.83.0\n- cykooz.resizer = \"3.1\" (single-threaded mode)\n\nOther Python libraries used to compare of resizing speed:\n\n- Pillow = \"11.0.0\" (https://pypi.org/project/Pillow/)\n\nResize algorithms:\n\n- Nearest\n- Convolution with Bilinear filter\n- Convolution with Lanczos3 filter\n\n### Resize RGBA image 4928x3279 => 852x567\n\n- Source image [nasa-4928x3279.png](https://github.com/Cykooz/cykooz.resizer/blob/main/tests/data/nasa-4928x3279.png)\n\n| Package (time in ms) | nearest | bilinear | lanczos3 |\n|:------------------------|--------:|---------:|---------:|\n| Pillow | 0.89 | 107.21 | 203.67 |\n| cykooz.resizer | 0.20 | 26.09 | 50.47 |\n| cykooz.resizer - sse4_1 | 0.20 | 12.12 | 24.91 |\n| cykooz.resizer - avx2 | 0.20 | 8.53 | 22.10 |\n\n### Resize grayscale (U8) image 4928x3279 => 852x567\n\n- Source image [nasa-4928x3279.png](https://github.com/Cykooz/cykooz.resizer/blob/main/tests/data/nasa-4928x3279.png)\n has converted into grayscale image with one byte per pixel.\n\n| Package (time in ms) | nearest | bilinear | lanczos3 |\n|:------------------------|--------:|---------:|---------:|\n| Pillow | 0.23 | 21.41 | 51.15 |\n| cykooz.resizer | 0.17 | 5.30 | 12.17 |\n| cykooz.resizer - sse4_1 | 0.17 | 2.11 | 5.84 |\n| cykooz.resizer - avx2 | 0.17 | 1.86 | 4.58 |\n\n",
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