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\n\n[](https://pypi.org/project/digipathos)\n[](https://travis-ci.org/bresan/digipathos_plant_pathology)\n[](https://codecov.io/gh/bresan/digipathos_plant_pathology)\n[](https://github.com/bresan/digipathos_plant_pathology/blob/master/LICENSE.md)\n[](https://www.codacy.com/app/bresan/digipathos_plant_pathology?utm_source=github.com&utm_medium=referral&utm_content=bresan/digipathos_plant_pathology&utm_campaign=Badge_Grade)\n\n# Overview\n\nThis project is aimed to serve as a wrapper for the Digipathos dataset, in order to list and download public data from plant pathologies provided by Embrapa (Brazilian Agricultural Research Corporation).\n\nExample of pictures:\n\n![](\"docs/figs/fig.png\")
![](\"docs/figs/fig2.png\")
![](\"docs/figs/fig3.png\")
\n\n\n\n\n# Installation\n\nThe installation is pretty simple if you have a virtualenv already installed on your machine. If you don't please rely to [VirtualEnv official documentation](https://virtualenv.pypa.io/en/latest/).\n\n```bash\npip install digipathos\n```\n\n# Documentation\n\nBesides the docstrings, major details about the documentation can be found [here](https://digipathos.readthedocs.io/en/latest/).\n\n# Testing\n\nThis project is inteded to suit most of the existent needs, so for this reason, testability is a major concern. Most of the code is heavily tested, along with [Travis](https://travis-ci.org/bresan/digipathos_plant_pathology) as Continuous Integration tool to run all the unit tests once there is a new commit.\n\n# Usage\n\nYou can use Digipathos in two different ways: via terminal or programatically.\n\n## CLI (Command-Line Interface)\n\nThis mode is highly recommended for those who are looking to explore a little bit the dataset. Here you can do the same operations from the programmatic mode, but with the advantage of being able to see all the data that is being retrieved.\n\n\n```bash\ndigipathos\n```\n\nAnd then you're gonna be greeted by our dataset browser :-)\n\n![](\"docs/figs/browser.png\")
\n\nAn example listing all the datasets:\n\n![](\"docs/figs/datasets.png\")
\n\n\n## Programmatically\n\n\n```python\ndata_loader = DataLoader()\n\n# list all the datasets\ndatasets = data_loader.get_datasets()\n\n# now lets give a look at the crops\ncrops = data_loader.get_crops()\n\n# how about getting all the datasets from a crop?\ndatasets_from_crop = data_loader.get_datasets_from_crop('Pineapple')\n\n# now let's download a random dataset\ndataset_id = random.choice(list(datasets.keys()))\ndata_loader.download_dataset(dataset_id=dataset_id)\n\n# download all from a given crop\ndata_loader.download_datasets_from_crop('Pineapple')\n\n# download all the datasets\ndata_loader.download_all_datasets()\n```\n\nPretty simple, huh?\n\nA working example can be found [here as a Python script](https://github.com/bresan/digipathos_plant_pathology/blob/master/example/example.py).\n\n\n# Troubleshooting\n\nIn case of any issue with the project, or for further questions, do not hesitate to open an issue here on GitHub.\n\n# Contributions\n\nContributions are really welcome, so feel free to open a pull request :-)\n\n\n",
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