pyblur 1.1.0

Image blurring routines

pyblur

Image blurring library for Python. Provides Gaussian, defocus (disk), box, linear motion, and point-spread-function (PSF) blur kernels, plus a randomized dispatcher that picks one at random.

All functions accept a PIL.Image.Image and return a new PIL.Image.Image of the same size. Both grayscale (L) and RGB images are supported. Every blur type exposes a deterministic variant (explicit parameters) and a random variant (parameters sampled automatically).

PSF kernels are taken from Convolutional Neural Networks for Direct Text Deblurring.

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Installation

pip install pyblur

Requirements: Python ≥ 3.10, numpy, pillow, scikit-image, scipy.

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Quick start

from PIL import Image
import pyblur

img = Image.open("photo.png")   # L or RGB

# Pick a specific blur
blurred = pyblur.gaussian_blur(img, bandwidth=1.5)

# Or let pyblur choose everything at random
blurred = pyblur.randomized_blur(img)

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API reference

gaussian_blur(img, bandwidth)

Supports any PIL image mode (delegates to PIL internally).

Parameter	Type	Description
bandwidth	float > 0	Standard deviation of the Gaussian kernel

blurred = pyblur.gaussian_blur(img, bandwidth=1.5)
blurred = pyblur.gaussian_blur_random(img)   # bandwidth ∈ {0.5, 1.0, …, 3.5}

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defocus_blur(img, dim)

Simulates a circular (disk) aperture blur. Supports L and RGB images.

Parameter	Type	Description
dim	int	Kernel size — one of 3, 5, 7, 9

blurred = pyblur.defocus_blur(img, dim=5)
blurred = pyblur.defocus_blur_random(img)

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box_blur(img, dim)

Uniform box (average) blur. Supports L and RGB images.

Parameter	Type	Description
dim	int	Kernel size — one of 3, 5, 7, 9

blurred = pyblur.box_blur(img, dim=7)
blurred = pyblur.box_blur_random(img)

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linear_motion_blur(img, dim, angle, linetype)

Simulates camera or subject motion along a straight line. Supports L and RGB images.

Parameter	Type	Description
dim	int	Kernel size — one of 3, 5, 7, 9
angle	float	Motion direction in degrees; snapped to the nearest valid angle for the kernel size
linetype	str	"full" — symmetric; "right" / "left" — half-kernel

blurred = pyblur.linear_motion_blur(img, dim=5, angle=45.0, linetype="full")
blurred = pyblur.linear_motion_blur_random(img)

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psf_blur(img, psfid)

Applies one of 100 real-world point-spread-function kernels captured from camera hardware. Supports L and RGB images.

Parameter	Type	Description
psfid	int	Kernel index — 0 to 99

blurred = pyblur.psf_blur(img, psfid=42)
blurred = pyblur.psf_blur_random(img)

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randomized_blur(img)

Randomly selects one of the five blur types above and samples its parameters uniformly. Useful for data augmentation pipelines where you want diverse blur without manual configuration.

blurred = pyblur.randomized_blur(img)

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Maintenance

This project is maintained on a best-effort, irregular basis. Issues and PRs are welcome but response times are not guaranteed.

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Migrating from v0.2

All public functions were renamed to snake_case in v1.0.0 The old PascalCase names (GaussianBlur, BoxBlur, etc.) were removed in v1.0.

v0.2	v1.0+
GaussianBlur(img, bw)	gaussian_blur(img, bandwidth=bw)
GaussianBlur_random(img)	gaussian_blur_random(img)
DefocusBlur(img, dim)	defocus_blur(img, dim)
DefocusBlur_random(img)	defocus_blur_random(img)
BoxBlur(img, dim)	box_blur(img, dim)
BoxBlur_random(img)	box_blur_random(img)
LinearMotionBlur(img, dim, angle, linetype)	linear_motion_blur(img, dim, angle, linetype)
LinearMotionBlur_random(img)	linear_motion_blur_random(img)
PsfBlur(img, psfid)	psf_blur(img, psfid)
PsfBlur_random(img)	psf_blur_random(img)
RandomizedBlur(img)	randomized_blur(img)