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    "info": {
        "author": "Akbar Gumbira",
        "author_email": "akbar.gumbira@bukalapak.com",
        "bugtrack_url": null,
        "classifiers": [
            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License v3 (GPLv3)",
            "Operating System :: OS Independent",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering",
            "Topic :: Scientific/Engineering :: Image Recognition"
        ],
        "description": "# PyBRISQUE\nAn implementation of BRISQUE (Blind/Referenceless Image Spatial Quality \nEvaluator) in Python from the paper: [\"No-Reference Image Quality Assessment \nin the Spatial Domain\"](https://ieeexplore.ieee.org/document/6272356/).\n\n\n## Installation\nThe package is in PyPI so you can install it simply by this command:\n\n```pip install --process-dependency-links pybrisque```\n\n## Usage\nInitialize once:\n```\nbrisq = BRISQUE()\n```\nand get the BRISQUE feature or score many times:\n```\nbrisq.get_feature('/path')\nbrisq.get_score('/image_path')\n```\n\n\n## Limitations\nThis implementation is heavily adopted from the original Matlab \nimplementation in [here](https://github.com/dsoellinger/blind_image_quality_toolbox/tree/master/%2Bbrisque). There is one catch though, the bicubic interpolation when resizing image in \nMatlab and OpenCV is a bit different as explained in [here](https://stackoverflow.com/questions/26823140/imresize-trying-to-understand-the-bicubic-interpolation). For now, it uses ```nearest``` interpolation \nwhich gives the most similar output with the original implementation.\n\nComparing with Matlab original implementation on reference images of TID 2008: \n\n![Comparison](examples/comparison.png)\n \nAnd the absolute differences' stat is as follows: \n```\n{'min': 0.17222238726479588,\n 'max': 16.544924728934404,\n 'mean': 3.9994322498322754,\n 'std': 3.0715344507521416}\n```",
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        "license": "GPL",
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        "name": "pybrisque",
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        "summary": "A package for BRISQUE metric calculation.",
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