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        "author": "Joel Laity",
        "author_email": "joel.laity@gmail.com",
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            "License :: OSI Approved :: MIT License",
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            "Programming Language :: Python :: 3.6"
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        "description": "# Tensorshow\n\nTensorshow is a python module for inspecting [TFRecords](https://www.tensorflow.org/api_guides/python/reading_data#file_formats).\n\nTensorshow can convert a TFRecord to a pandas dataframe.\n\n```python\nimport tensorshow\n\n# The column labels of `df` are the features of the tf.train.example protobufs.\ndf = tensorshow.dataframe_from('path/to/tfrecord')\n```\n\nTensorshow can be used as a command line utility. It will convert a tfrecord to an html file on the command line.\n\n```bash\npython tensorshow --tfrecord=/Users/joel/train.tfrecord --html_file=Users/joel/out.html\n```\n\nImages stored as byte strings will be automatically detected and displayed as images rather than text. The `out.html` file looks like this when you open it with a browser.\n\n![TFRecord displayed as a table](http://www.joellaity.com/img/html_tensorshow_example.png)\n\n\nTensorshow can be used in a jupyter notebook to preview a TFRecord. The `head` function will show the first 5 `tf.train.example`s by default and the `random` function will show five random `tf.train.example`s from the tfrecord.\n\n![A preview of a TFRecord in a jupyter notebook](http://www.joellaity.com/img/nb_tensorshow_example.png)\n\n\n",
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        "name": "tensorshow",
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        "summary": "A python module and commaned line tool for inspecting TFRecords.",
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