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        "description": "Description\n===========\n\n.. image:: https://travis-ci.org/mittagessen/kraken.svg?branch=master\n    :target: https://travis-ci.org/mittagessen/kraken\n\nkraken is a fork of ocropus intended to rectify a number of issues while\npreserving (mostly) functional equivalence. Its main features are:\n\n  - Script detection and multiscript recognition support\n  - `Right-to-Left <https://en.wikipedia.org/wiki/Right-to-left>`_, `BiDi\n    <https://en.wikipedia.org/wiki/Bi-directional_text>`_, and Top-to-Bottom\n    script support\n  - `ALTO <https://www.loc.gov/standards/alto/>`_, abbyXML, and hOCR output\n  - Word bounding boxes and character cuts\n  - `Public repository <https://github.com/mittagessen/kraken-models>`_ of model files\n  - Dynamic recognition model architectures and GPU acceleration\n  - Clean public API \n\nInstallation\n============\n\nWhen using a recent version of pip all dependencies will be installed from\nbinary wheel packages, so installing build-essential or your distributions\nequivalent is often unnecessary. kraken only runs on **Linux or Mac OS X**.\nWindows is not supported.\n\nInstall the latest 1.0 release through `conda <https://anaconda.org>`_:\n\n::\n\n  $ wget https://raw.githubusercontent.com/mittagessen/kraken/master/environment.yml\n  $ conda env create -f environment.yml\n\nor:\n\n::\n\n  $ wget https://raw.githubusercontent.com/mittagessen/kraken/master/environment_cuda.yml\n  $ conda env create -f environment_cuda.yml\n\nfor CUDA acceleration with the appropriate hardware.\n\nIt is also possible to install the same version from pypi:\n\n::\n\n  $ pip install kraken\n\nFinally you'll have to scrounge up a model to do the actual recognition of\ncharacters. To download the default model for printed English text and place it\nin the kraken directory for the current user:\n\n::\n\n  $ kraken get default\n\nA list of libre models available in the central repository can be retrieved by\nrunning:\n\n::\n\n  $ kraken list\n\nQuickstart\n==========\n\nRecognizing text on an image using the default parameters including the\nprerequisite steps of binarization and page segmentation:\n\n::\n\n  $ kraken -i image.tif image.txt binarize segment ocr\n\nTo binarize a single image using the nlbin algorithm:\n\n::\n\n  $ kraken -i image.tif bw.png binarize\n\nTo segment a binarized image into reading-order sorted lines:\n\n::\n\n  $ kraken -i bw.png lines.json segment\n\nTo OCR a binarized image using the default RNN and the previously generated\npage segmentation:\n\n::\n\n  $ kraken -i bw.png image.txt ocr --lines lines.json\n\nAll subcommands and options are documented. Use the ``help`` option to get more\ninformation.\n\nDocumentation\n=============\n\nHave a look at the `docs <http://kraken.re>`_\n\nFunding\n=======\n\nkraken is developed at `Universit\u00e9 PSL <http://www.psl.eu>`_.\n\n\n\n",
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