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        "author": "Declan Crew",
        "author_email": "dcrew@dstl.gov.uk",
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        "description": "# Noisify\n\nNoisify is a simple light weight library for augmenting and modifying data by adding realistic noise.\n\n## Introduction\n\nAdd some human noise (typos, things in the wrong boxes etc.)\n\n    >>> from noisify.recipes import human_error\n    >>> test_data = {'this': 1.0, 'is': 2, 'a': 'test!'}\n    >>> human_noise = human_error(5)\n    >>> print(list(human_noise(test_data)))\n    [{'a': 'tset!', 'this': 2, 'is': 1.0}]\n    >>> print(list(human_noise(test_data)))\n    [{'a': 0.0, 'this': 'test!', 'is': 2}]\n\nAdd some machine noise (gaussian noise, data collection interruptions etc.)\n\n    >>> from noisify.recipes import machine_error\n    >>> machine_noise = machine_error(5)\n    >>> print(list(machine_noise(test_data)))\n    [{'this': 1.12786393038729, 'is': 2.1387080616716307, 'a': 'test!'}]\n\nIf you want both, just add them together\n\n    >>> combined_noise = machine_error(5) + human_error(5)\n    >>> print(list(combined_noise(test_data)))\n    [{'this': 1.23854334573554, 'is': 20.77848220943227, 'a': 'tst!'}]\n\nAdd noise to numpy arrays\n\n    >>> import numpy as np\n    >>> test_array = np.arange(10)\n    >>> print(test_array)\n    [0 1 2 3 4 5 6 7 8 9]\n    >>> print(list(combined_noise(test_array)))\n    [[0.09172393 2.52539794 1.38823741 2.85571154 2.85571154 6.37596668\n                      4.7135771  7.28358719 6.83600156 9.40973018]]\n\nRead an image\n\n    >>> from PIL import Image\n    >>> test_image = Image.open(noisify.jpg)\n    >>> test_image.show()\n\n\n\nAnd now with noise\n\n    >>> from noisify.recipes import human_error, machine_error\n    >>> combined_noise = machine_error(5) + human_error(5)\n    >>> for out_image in combined_noise(test_image):\n    ...     out_image.show()\n\n\n*Noisify* allows you to build flexible data augmentation pipelines for arbitrary objects.\nAll pipelines are built from simple high level objects, plugged together like lego.\nUse noisify to stress test application interfaces, verify data cleaning pipelines, and to make your ML algorithms more\nrobust to real world conditions.\n\n## Installation\n\n#### Prerequisites\nNoisify relies on Python 3.5+\n\n#### Installation from pipy\n    $ pip install noisify\n\n## Additional Information\n\nFull documentation is available at TODO ReadTheDocs Link.\n## Licence\n\nDstl (c) Crown Copyright 2019\n\nNoisify is released under the MIT licence\n\n\n",
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