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        "author": "Romain Mormont",
        "author_email": "romain.mormont@gmail.com",
        "bugtrack_url": null,
        "classifiers": [
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved",
            "Operating System :: MacOS",
            "Operating System :: POSIX",
            "Operating System :: Unix",
            "Programming Language :: Python",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Topic :: Scientific/Engineering",
            "Topic :: Software Development"
        ],
        "description": "# SLDC\n\n**_SLDC_** is a framework created for accelerating development of large image analysis workflows. It is especially well \nsuited for solving more or less complex problems of object detection and classification in multi-gigapixel images.\n\nThe framework encapsulates problem-independent logic such as parallelism, memory constraints (due to large image handling) \nwhile providing a concise way of declaring problem-dependent components of the implementer's workflows.\n\n[![Build status](https://travis-ci.org/waliens/sldc.svg?branch=master)](https://travis-ci.org/waliens/sldc)\n[![codecov](https://codecov.io/gh/waliens/sldc/branch/master/graph/badge.svg)](https://codecov.io/gh/waliens/sldc)\n[![PyPI package](https://badge.fury.io/py/sldc.svg)](https://badge.fury.io/py/sldc)\n\n## Documentation\n\nThe algorithm used by the framework as well as some toy examples are presented in the [Wiki](https://github.com/waliens/sldc/wiki).\n\n## Dependencies\n\nThe framework currently works under Python 2.7 and 3.5.\n\nThe required dependencies are the following :\n\n* Numpy (>= 1.10, might work with earlier versions)\n* OpenCV (>= 3.0)\n* Pillow (>= 3.1.1)\n* joblib (>= 0.9.4)\n* Shapely (>= 1.5.13)\n* Scipy (>= 0.18.1)\n\n## Install\n\nSimply: `pip install sldc`\n\n#### On windows\n\nOn Windows, some `.dll` are needed by `shapely` and are not installed by `pip` when you install `sldc`. Therefore, you might have to install\n`shapely` yourself from `conda` (i.e. `conda install shapely`) or from [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#shapely) after having run `pip install sldc`.\n\n## Bindings\n\nThe library is image format agnostic and therefore allows you to integrate it with any existing image format by implementing some interfaces. However, some bindings were implemented for integrating SLDC with: \n\n+ [Cytomine](http://www.cytomine.be/): [`cytomine-sldc` repository](https://github.com/cytomine/Cytomine-python-datamining/tree/master/cytomine-datamining/algorithms/sldc) \n+ [OpenSlide](http://openslide.org/): [`sldc-openslide` repository](https://github.com/waliens/sldc-openslide)\n\n## References\n\nIf you use _SLDC_ in a scientific publication, we would appreciate citations: [Mormont & al., Benelearn, 2016](http://orbi.ulg.ac.be/handle/2268/202624).\n\nThe framework was initially developed in the context of [this master thesis](http://hdl.handle.net/2268.2/1314).\n\n\n",
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