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    "info": {
        "author": "D.",
        "author_email": "dtk@gmx.de",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Science/Research",
            "License :: Other/Proprietary License",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering"
        ],
        "description": "About\n=====\n\nCPBD is a perceptual-based no-reference objective image sharpness metric\nbased on the cumulative probability of blur detection `developed at the\nImage, Video and Usability Laboratory of Arizona State\nUniversity <https://ivulab.asu.edu/Quality/CPBD>`__.\n\n    [The metric] is based on the study of human blur perception for\n    varying contrast values. The metric utilizes a probabilistic model\n    to estimate the probability of detecting blur at each edge in the\n    image, and then the information is pooled by computing the\n    cumulative probability of blur detection (CPBD).\n\nThis software is a Python port of the `reference MATLAB\nimplementation <http://lina.faculty.asu.edu/Software/CPBDM/CPBDM_Release_v1.0.zip>`__.\nTo approximate the behaviour of MATLAB's proprietary implementation of\nthe Sobel operator, it uses an implementation `inspired by GNU\nOctave <https://sourceforge.net/p/octave/image/ci/default/tree/inst/edge.m#l196>`__.\n\nReferences\n==========\n\nCPBD is described in detail in the following papers:\n\n-  `N. D. Narvekar and L. J. Karam, \"A No-Reference Image Blur Metric\n   Based on the Cumulative Probability of Blur Detection (CPBD),\" in\n   IEEE Transactions on Image Processing, vol. 20, no. 9, pp. 2678-2683,\n   Sept.\n   2011. <http://ieeexplore.ieee.org/abstract/document/5739529/>`__\n-  `N. D. Narvekar and L. J. Karam, \"An Improved No-Reference Sharpness\n   Metric Based on the Probability of Blur Detection,\" International\n   Workshop on Video Processing and Quality Metrics for Consumer\n   Electronics (VPQM), January 2010, http://www.vpqm.org\n   (pdf) <http://events.engineering.asu.edu/vpqm/vpqm10/Proceedings_VPQM2010/vpqm_p27.pdf>`__\n-  `N. D. Narvekar and L. J. Karam, \"A no-reference perceptual image\n   sharpness metric based on a cumulative probability of blur\n   detection,\" 2009 International Workshop on Quality of Multimedia\n   Experience, San Diego, CA, 2009, pp.\n   87-91. <http://ieeexplore.ieee.org/abstract/document/5246972/>`__\n\nCredits\n=======\n\nIf you publish research results using this code, I kindly ask you to\nreference the papers of the original authors of the metric as stated in\nthe previous section as well as their reference implementation in your\nbibliography. See also the copyright statement of the reference\nimplementation in the `license\nfile <https://raw.githubusercontent.com/0x64746b/python-cpbd/master/LICENSE.txt>`__.\nThank you!\n\nInstallation\n============\n\n::\n\n    $ pip install cpbd\n\nUsage\n=====\n\n::\n\n    In [1]: import cpbd\n\n    In [2]: from scipy import ndimage\n\n    In [3]: input_image = ndimage.imread('/tmp/LIVE_Images_GBlur/img4.bmp', mode='L')\n\n    In [4]: cpbd.compute(input_image)\n    Out[4]: 0.75343203230148048\n\nDevelopment\n===========\n\n::\n\n    $ git clone git@github.com:0x64746b/python-cpbd.git\n    Cloning into 'python-cpbd'...\n    $ cd python-cpbd\n    $ pip install -U '.[dev]'\n\nTo quickly run the tests with the invocation interpreter:\n\n::\n\n    $ python setup.py test\n\nTo test the library under different interpreters:\n\n::\n\n    $ tox\n\nPerformance\n===========\n\nThe following graph visualizes the accuracy of this port in comparison\nwith the reference implementation when tested on the\n`images <http://lina.faculty.asu.edu/Software/CPBDM/LIVE_Images_GBlur.zip>`__\nof the `LIVE\ndatabase <http://live.ece.utexas.edu/research/quality/subjective.htm>`__:\n\n.. image:: https://raw.githubusercontent.com/0x64746b/python-cpbd/master/tests/data/performance_LIVE.png\n   :alt: Performance on LIVE database",
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        "keywords": "sharpness,metric,blur,cumulative probability,no-reference,objective,perceptual",
        "license": "Other/Proprietary License",
        "maintainer": "",
        "maintainer_email": "",
        "name": "cpbd",
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        "summary": "Calculate the sharpness of an image with the CPBD metric",
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