{
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        "author": "Datos Argentina",
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        "classifiers": [
            "Development Status :: 2 - Pre-Alpha",
            "Intended Audience :: Developers",
            "License :: OSI Approved :: MIT License",
            "Natural Language :: Spanish",
            "Programming Language :: Python :: 2.7"
        ],
        "description": "# Detector Aedes\n\n[![Coverage Status](https://coveralls.io/repos/github/datosgobar/detector-aedes/badge.svg?branch=master)](https://coveralls.io/github/datosgobar/detector-aedes?branch=master)\n[![Build Status](https://travis-ci.org/datosgobar/detector-aedes.svg?branch=master)](https://travis-ci.org/datosgobar/detector-aedes)\n[![PyPI](https://badge.fury.io/py/detector-aedes.svg)](http://badge.fury.io/py/detector-aedes)\n[![Stories in Ready](https://badge.waffle.io/datosgobar/detector-aedes.png?label=ready&title=Ready)](https://waffle.io/datosgobar/detector-aedes)\n[![Documentation Status](https://readthedocs.org/projects/detector-aedes/badge/?version=latest)](http://detector-aedes.readthedocs.io/en/latest/?badge=latest)\n\n\nAlgoritmos de Visi\u00f3n Computacional para analizar im\u00e1genes de Ovisensores.\n\n\n* Licencia: MIT license\n* Documentaci\u00f3n: https://detector-aedes.readthedocs.io\n\n\n## Instalaci\u00f3n\n\nEl paquete se encuentra disponible en pip:\n\n```bash\n$ pip install detector_aedes\n```\n\nLuego buscar la carpeta de instalaci\u00f3n y renombrar el archivo config_sample.yml a config.yml\n\n### Instalacion de Desarrollo\n\nPara instalar en modo desarrollo ir a la carpeta en la que fue clonado el reporsitorio:\n\n```bash\n$ cd path/to/detector-aedes\n```\ny luego instalar los requerimientos con:\n\n```bash\n$ pip install -r requirements.txt\n$ pip install -r requirements_dev.txt\n```\nfinalmente instalar el paquete en modo desarrollo con:\n```bash\n$ pip install -e .\n```\nLuego renombrar el archivo config_sample.yml a config.yml\n\n```bash\n$ mv config_sample.yml config.yml\n```\n\n\n## Uso\n\nEl siguiente es un ejemplo de uso rapido que recorre todas las imagenes de una\ncarpeta y graba la salida a un archivo CSV:\n```Python\nfrom detector_aedes import AedesDetector, FolderInputConnector, FileOutputConnector\nic = FolderInputConnector('/carpeta/que/contenga/imagenes')\nfc = FileOutputConnector('/ruta/a/archivo/de/salida.csv')\nad = AedesDetector(input_connector=ic, output_connector=fc)\nad.process(show_results=False)\n```\nPara una descripcion mas detallada referirse al [Manual de Uso](docs/MANUAL.md)\n\n## Tests\n\nPara correr los tests hace falta instalar las dependencias de desarrollo:\n\n```bash\n$ pip install -r requirements_dev.txt\n```\ny luego correr los tests con:\n\n```bash\n$ nosetests\n```\n\n## Cr\u00e9ditos\n\nAgradecemos al Dr. Nicolas Schweigmann del Grupo de Estudio de Mosquitos de la UBA y al equipo de Epidemiolog\u00eda del GCBA por su ayuda en el desarrollo de este software.\n\n## Contacto\n\nTe invitamos a [crearnos un issue](https://github.com/datosgobar/detector-aedes/issues/new?title=Encontre%20un%20bug%20en%20detector-aedes) en caso de que encuentres alg\u00fan bug o tengas feedback de alguna parte de `detector-aedes`.\n\nPara todo lo dem\u00e1s, pod\u00e9s mandarnos tu comentario o consulta a [datos@modernizacion.gob.ar](mailto:datos@modernizacion.gob.ar).\n\n\nHistory\n===\n\n0.1.0 (2017-06-21)\n------------------\n\n* Primer release en PyPI.\n\n\n",
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