{ "info": { "author": "lospooky", "author_email": "my.accounts@gmx.se", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved :: MIT License", "Programming Language :: Python :: 2.7", "Topic :: Multimedia :: Graphics" ], "description": "#Pyblur\r\n##Python image blurring routines.\r\nPyblur is a collection of simple image blurring routines.
\r\nIt supports Gaussian, Disk, Box, and Linear Motion Blur Kernels as well as the Point Spread Functions\r\nused in [Convolutional Neural Networks for Direct Text Deblurring](http://www.fit.vutbr.cz/~ihradis/CNN-Deblur/).
\r\nFunctions receive a PIL image as input, and return another as output.
\r\nKernel sizes can either be specified as input, or randomized.
\r\nFinally, there's a RandomizedBlur function that applies a random type of blurring kernel with a random width/strength.\r\n\r\npypi: [https://pypi.python.org/pypi?:action=display&name=pyblur&version=0.2.3](https://pypi.python.org/pypi?:action=display&name=pyblur&version=0.2.3)\r\n\r\n\r\n\r\n##Installation\r\n>From Pip: `pip install pyblur`
\r\nOr alternatively `git clone` this repo and run locally\r\n\r\n##Usage\r\n from pyblur import *\r\n\r\n###Gaussian Blur\r\nBlurs image using a Gaussian Kernel\r\n\r\n blurred = GaussianBlur(img, bandwidth)\r\n\r\nRandomized kernel bandwidth (between 0.5 and 3.5)\r\n\r\n blurred = GaussianBlur_random(img)\r\n\r\n###Defocus (Disk) Blur\r\nBlurs image using a Disk Kernel\r\n\r\n\tblurred = DefocusBlur(img, kernelsize)\r\n\r\nRandomized kernel size (between 3 and 9)\r\n\r\n\tblurred = DefocusBlur_random(img)\r\n\r\n\r\n###Box Blur\r\nBlurs image using a Box Kernel\r\n\r\n\tblurred = BoxBlur(img, kernelsize)\r\n\r\nRandomized kernel size (between 3 and 9)\r\n\r\n\tblurred = BoxBlur_random(img)\r\n\r\n\r\n###Linear Motion Blur\r\nBlurs image using a Line Kernel\r\n\r\n\tblurred = LinearMotionBlur(img, dim, angle, linetype)\r\n\r\n####Parameters\r\n* `dim` Kernel Size: {3,5,7,9}
\r\n* `angle` Angle of the line of motion. Will be floored to the closest one available for the given kernel size.
\r\n* `linetype = {left, right, full}` Controls whether the blur kernel will be applied in full or only the left/right halves of it.
\r\n\r\nRandomized kernel size, angle, and line type\r\n\r\n\tblurred = LinearMotionBlur_random(img)\r\n\r\n### PSF Blur\r\nBlurs image using one of the Point Spread Functions (Kernels) used in:
\r\n[Convolutional Neural Networks for Direct Text Deblurring](http://www.fit.vutbr.cz/~ihradis/CNN-Deblur/)\r\n\r\n\tblurred = PsfBlur(img, psfid)\r\n\r\n####Parameters\r\n* `psfid` Id of the Point Spread Function to apply [0, 99]
\r\n\r\n\r\nRandomized kernel size, angle, and line type\r\n\r\n\tblurred = PsfBlur_random(img)\r\n\r\n\r\n###Random Blur\r\nRandomly applies one of the supported blur types, with a randomized bandwidth/strenght.\r\n\r\n\tblurred = RandomizedBlur(img)\r\n\r\n", "description_content_type": null, "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "http://github.com/lospooky/pyblur", "keywords": "blur", "license": "MIT", "maintainer": "", "maintainer_email": "", "name": "pyblur", "package_url": "https://pypi.org/project/pyblur/", "platform": "", "project_url": "https://pypi.org/project/pyblur/", "project_urls": { "Homepage": "http://github.com/lospooky/pyblur" }, "release_url": "https://pypi.org/project/pyblur/0.2.3/", "requires_dist": [ "numpy", "pillow", "scikit-image", "scipy" ], "requires_python": "", "summary": "Image blurring routines", "version": "0.2.3" }, "last_serial": 2552352, "releases": { "0.1": [ { 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