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        "author": "Horia Coman",
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            "Development Status :: 4 - Beta",
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            "Operating System :: POSIX",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.6",
            "Programming Language :: Python :: 2.7",
            "Topic :: Multimedia :: Graphics",
            "Topic :: Multimedia :: Video",
            "Topic :: Scientific/Engineering :: Image Recognition",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# SDHash [![Build Status](https://travis-ci.org/horia141/sdhash.svg?branch=master)](https://travis-ci.org/horia141/sdhash)\n\nA Python library for computing hashes of images which ignore perceptual differences.\n\n## Usage\n\n```python\nimport sdhash\nfrom PIL import Image\n\ni1 = Image.open('test1.png')\ni2 = Image.open('test1_noise.png')\ni3 = Image.open('test2.png')\n\nsdhash.test_duplicate(i1, i2) # True\nsdhash.test_duplicate(i1, i3) # False\nsdhash.hash_image(i1) # [ an md5 output ]\n```\n\n## Background\n\nSuppose you want to test that two images are identical. The naive approach of simply comparing the byte-array representation of the two is not good.\n\n## Algorithm\n\n## Installation ##\n\nThe Python image library and NumPy/SciPy etc.\n\nInstallation is simple, via `pip`:\n\n```bash\npip install sdhash\n```\n\n## TODO\n\nResistance to rotation, mirroring etc.\nTunable knobs (for similarity detection etc.)",
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