A fast image resizer

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Project description

cykooz.resizer

cykooz.resizer is package with the optimized version of image resizing based on Rust's crate fast_image_resize.

Installation

python3 -m pip install cykooz.resizer

Or with automatically installing Pillow:

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	-	-	-

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
- 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

from PIL import Image

from cykooz.resizer import FilterType, ResizeAlg, Resizer


resizer = Resizer(ResizeAlg.convolution(FilterType.lanczos3))
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 raw image with an alpha channel

from cykooz.resizer import AlphaMulDiv, FilterType, ImageData, PixelType, ResizeAlg, Resizer

def resize_raw(width: int, height: int, pixels: bytes):
    src_image = ImageData(
        width,
        height,
        PixelType.U8x4,
        pixels,
    )
    alpha_mul_div = AlphaMulDiv()
    resizer = Resizer(ResizeAlg.convolution(FilterType.lanczos3))
    dst_image = ImageData(255, 170, PixelType.U8x4)
    alpha_mul_div.multiply_alpha_inplace(src_image)
    resizer.resize(src_image, dst_image)
    alpha_mul_div.divide_alpha_inplace(dst_image)    
    return dst_image

Change used CPU-extensions

from cykooz.resizer import FilterType, ResizeAlg, Resizer, CpuExtensions


resizer = Resizer(ResizeAlg.convolution(FilterType.lanczos3))
resizer.cpu_extensions = CpuExtensions.sse4_1
...

Benchmarks

Environment:

CPU: AMD Ryzen 9 5950X
RAM: DDR4 3800 MHz
Ubuntu 22.04 (linux 6.5.0)
Python 3.10
Rust 1.75.0
cykooz.resizer = "2.2"

Other Python libraries used to compare of resizing speed:

Pillow = "10.2.0" (https://pypi-hypernode.com/project/Pillow/)

Resize algorithms:

Nearest
Convolution with Bilinear filter
Convolution with Lanczos3 filter

Resize RGBA image 4928x3279 => 852x567

Source image nasa-4928x3279.png

Package (time in ms)	nearest	bilinear	lanczos3
Pillow	0.88	105.27	200.80
cykooz.resizer	0.20	29.64	58.83
cykooz.resizer - sse4_1	0.20	14.83	27.87
cykooz.resizer - avx2	0.20	10.44	21.34

Resize grayscale (U8) image 4928x3279 => 852x567

Source image nasa-4928x3279.png has converted into grayscale image with one byte per pixel.

Package (time in ms)	nearest	bilinear	lanczos3
Pillow U8	0.27	23.78	61.23
cykooz.resizer U8	0.17	5.29	11.44
cykooz.resizer U8 - sse4_1	0.17	2.30	5.90
cykooz.resizer U8 - avx2	0.17	1.85	4.17

Project details

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Release history Release notifications | RSS feed

3.0.0

May 15, 2024

2.2.1

Feb 15, 2024

This version

2.2.0

Feb 8, 2024

2.1.2

Oct 27, 2022

2.1.1

Jul 18, 2022

2.1

Jul 7, 2022

2.0

Mar 23, 2022

1.1

Oct 27, 2021

1.0

Oct 8, 2021

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cykooz.resizer 2.2.0

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cykooz.resizer

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Resize Pillow's image

Resize raw image with an alpha channel

Change used CPU-extensions

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Resize RGBA image 4928x3279 => 852x567

Resize grayscale (U8) image 4928x3279 => 852x567

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