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restoration and quality assessment"],"sub_categories":[],"readme":".. -*- mode: rst -*-\n\n|Travis|_ |PyPi|_\n\n.. |Travis| image:: https://travis-ci.com/ocampor/image-quality.svg?branch=master\n.. _Travis: https://travis-ci.com/ocampor/image-quality\n\n.. |PyPi| image:: https://img.shields.io/pypi/dm/image-quality?color=blue   :alt: PyPI - Downloads\n.. _PyPi: https://pypi.org/project/image-quality/\n\nImage Quality\n=============\n\nDescription\n-----------\n\nImage quality is an open source software library for Automatic Image\nQuality Assessment (IQA).\n\nDependencies\n------------\n\n-  Python 3.8\n-  (Development) Docker\n\nInstallation\n------------\n\nThe package is public and is hosted in PyPi repository. To install it in\nyour machine run\n\n::\n\n   pip install image-quality\n\nExample\n-------\n\nAfter installing ``image-quality`` package, you can test that it was\nsuccessfully installed running the following commands in a python\nterminal.\n\n::\n\n   \u003e\u003e\u003e import imquality.brisque as brisque\n   \u003e\u003e\u003e import PIL.Image\n\n   \u003e\u003e\u003e path = 'path/to/image'\n   \u003e\u003e\u003e img = PIL.Image.open(path)\n   \u003e\u003e\u003e brisque.score(img)\n   4.9541572815704455\n\n\nDevelopment\n-----------\n\nIn case of adding a new tensorflow dataset or modifying the location of a zip file, it is\nnecessary to update the url checksums. You can find the instructions in the following\n`tensorflow documentation \u003chttps://www.tensorflow.org/datasets/add_dataset#1_adjust_the_checksums_directory\u003e`_.\n\nThe steps to create the url checksums are the following:\n\n1. Take the file with the dataset configuration (e.g. live_iqa.py) an place it in the ``tensorflow_datasets``\nfolder. The folder is commonly placed in ``${HOME}/.local/lib/python3.8/site-packages`` if you\ninstall the python packages using the ``user`` flag.\n\n2. Modify the ``__init__.py`` of the ``tensorflow_datasets`` to import your new dataset.\nFor example ``from .image.live_iqa import LiveIQA`` at the top of the file.\n\n3. In your terminal run the commands:\n::\n\n   touch url_checksums/live_iqa.txt\n   python -m tensorflow_datasets.scripts.download_and_prepare  \\\n      --register_checksums  \\\n      --datasets=live_iqa\n\n4. The file ``live_iqa.txt`` is going to contain the checksum. Now you can copy and paste it to your\nproject's ``url_checksums`` folder.\n\nSponsor\n-------\n\n.. image:: https://github.com/antonreshetov/mysigmail/raw/master/jetbrains.svg?sanitize=true\n   :target: \u003chttps://www.jetbrains.com/?from=mysigmail\u003e_\n\nMaintainer\n----------\n\n- `Ricardo Ocampo \u003chttps://ocampor.com\u003e`_\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Focampor%2Fimage-quality","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Focampor%2Fimage-quality","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Focampor%2Fimage-quality/lists"}