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        "author": "Aalok Sathe",
        "author_email": "aalok.sathe@richmond.edu",
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        "classifiers": [
            "Development Status :: 1 - Planning",
            "Intended Audience :: Developers",
            "Intended Audience :: Education",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)",
            "Programming Language :: Python :: 3.6",
            "Topic :: Software Development :: Libraries :: Python Modules"
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        "description": "# cfd-reader\n\n[![pipeline status](https://gitlab.com/aalok-sathe/cfd-reader/badges/master/pipeline.svg)](https://gitlab.com/aalok-sathe/cfd-reader/commits/master)\n\n**A `python3` module to index, pre-process, and supply facial data from the Chicago Face Database (CFD).**\n\nA convenient way to load data from the Chicago Face Database, wrapped in `numpy` arrays, to feed to your neural network.\n\n## installation\nFrom a terminal, run the command:\n\n`[sudo -H] pip3 install cfd-reader`\n\n## usage\n\nIn your Python (3.5+) script or interpreter session, run (suggested syntax):\n\n`import cfd_reader as cfdr`\n\n### load face data\n\n`cfdr.load_data(`*[options]*`)`\n\n**where *options* include**:\n\n- `grayscale=[True, False]`:\n    - `True`: provides 3 channel BGR output\n    - `False`: provides single channel grayscale output\n- `train_proportion=x`:\n    - `x`: real-valued variable between 0 and 1. `x` proportion of all data will be supplied as training data, and 1-x data will be supplied as test data\n- `resize=[False, (x,y)]`:\n    - `False`: keeps images in their original resolution\n    - `(x,y)`: tuple of integers to resize the image to\n\n**returns**:\n\n`numpy` array of shape `(n, x, y, c)` where `n` are the total number of images in that particular set (train/test), `(x,y)` is the 2D image shape, and `c` is the number of channels. In other words, `(x,y,c)` is the image shape.",
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