Tropical Cyclone#
- class torchgeo.datasets.TropicalCyclone(root='data', split='train', transforms=None, download=False)[source]#
Bases:
NonGeoDatasetTropical Cyclone Wind Estimation Competition dataset.
A collection of tropical storms in the Atlantic and East Pacific Oceans from 2000 to 2019 with corresponding maximum sustained surface wind speed. This dataset is split into training and test categories for the purpose of a competition. Read more about the competition here: https://www.drivendata.org/competitions/72/predict-wind-speeds/.
If you use this dataset in your research, please cite the following paper:
Note
This dataset requires the following additional library to be installed:
azcopy: to download the dataset from Source Cooperative.
Changed in version 0.4: Class name changed from TropicalCycloneWindEstimation to TropicalCyclone to be consistent with TropicalCycloneDataModule.
- __init__(root='data', split='train', transforms=None, download=False)[source]#
Initialize a new TropicalCyclone instance.
- Parameters:
root (str | PathLike[str]) – root directory where dataset can be found
split (str) – one of “train” or “test”
transforms (Callable[[dict[str, Any]], dict[str, Any]] | None) – a function/transform that takes input sample and its target as entry and returns a transformed version
download (bool) – if True, download dataset and store it in the root directory
- Raises:
AssertionError – if
splitargument is invalidDatasetNotFoundError – If dataset is not found and download is False.
- __len__()[source]#
Return the number of data points in the dataset.
- Returns:
length of the dataset
- Return type: