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This 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).
Example of pictures:
The installation is pretty simple if you have a virtualenv already installed on your machine. If you don't please rely to VirtualEnv official documentation.
pip install digipathos
Besides the docstrings, major details about the documentation can be found here.
This 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 as Continuous Integration tool to run all the unit tests once there is a new commit.
You can use Digipathos in two different ways: via terminal or programatically.
CLI (Command-Line Interface)
This 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.
And then you're gonna be greeted by our dataset browser :-)
An example listing all the datasets:
data_loader = DataLoader() # list all the datasets datasets = data_loader.get_datasets() # now lets give a look at the crops crops = data_loader.get_crops() # how about getting all the datasets from a crop? datasets_from_crop = data_loader.get_datasets_from_crop('Pineapple') # now let's download a random dataset dataset_id = random.choice(list(datasets.keys())) data_loader.download_dataset(dataset_id=dataset_id) # download all from a given crop data_loader.download_datasets_from_crop('Pineapple') # download all the datasets data_loader.download_all_datasets()
Pretty simple, huh?
A working example can be found here as a Python script.
In case of any issue with the project, or for further questions, do not hesitate to open an issue here on GitHub.
Contributions are really welcome, so feel free to open a pull request :-)
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