{ "info": { "author": "scloudyy", "author_email": "onecloud.shen@gmail.com", "bugtrack_url": null, "classifiers": [], "description": "=========\ndefogging\n=========\n\n\n.. image:: https://img.shields.io/pypi/v/defogging.svg\n :target: https://pypi.python.org/pypi/defogging/\n\n.. image:: https://img.shields.io/travis/scloudyy/Defogging.svg\n :target: https://travis-ci.org/scloudyy/Defogging\n\nImplement a robust and efficient defogging method with Python\n\n\nFeatures\n--------\n\n* Defogging a single foggy image\n\ninstall\n-------\n\nUse ``pip`` to install: ::\n\n $ pip install defogging\n\nOr you can install from source: ::\n\n $ git clone git@github.com:scloudyy/Defogging.git\n $ cd Defogging\n $ python setup.py build\n $ pip install .\n\nUsage\n-----\n\nUse ``defogging`` through command line: ::\n\n $ defogging your_img.bmp\n\nthe result will be saved as ``your_img_defogging.bmp``\n\nAnd you can also use ``defogging`` in your own code:\n\n.. code-block:: python\n\n from defogging import Defog\n\n in_name = \"foggy.bmp\"\n out_name = \"defogged.bmp\"\n\n df = Defog()\n df.read_img(in_name)\n df.defog()\n df.save_img(out_name)\n\nyou can directly input a foggy object in the form of ``numpy.array`` :\n\n.. code-block:: python\n\n df.read_array(your_array, range)\n\nwhere ``range`` indicates the value range of your array.The range has two options:\nthe first is ``1``, which means the value range of your array is [0,1],\nand the second is ``255``, which means the value range is [0,255]\n\nIf you want to process the defogged object further, you can also get defogged array:\n\n.. code-block:: python\n\n dst = df.get_array(range)\n\nalso, ``range`` indicates the value range of returned array, either ``1`` or ``255``.\nIf you choose ``1``, the range will lie in [0,1], and the type of it is ``float``.\nOr if you choose ``255``, the range will be [0,255], and the type will be ``uint8``.\n\n", "description_content_type": null, "docs_url": null, "download_url": 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