CaBuAr

class torchgeo.datasets.CaBuAr(root='data', split='train', bands=('B01', 'B02', 'B03', 'B04', 'B05', 'B06', 'B07', 'B08', 'B8A', 'B09', 'B11', 'B12'), transforms=None, download=False, checksum=False)

Bases: NonGeoDataset

CaBuAr dataset.

CaBuAr is a dataset for Change detection for Burned area Delineation and part of the splits are used for the ChaBuD ECML-PKDD 2023 Discovery Challenge.

Dataset features:

• Sentinel-2 multispectral imagery

• binary masks of burned areas

• 12 multispectral bands

• 424 pairs of pre and post images with 20 m per pixel resolution (512x512 px)

Dataset format:

• single hdf5 dataset containing images and masks

Dataset classes:

0. no change

1. burned area

If you use this dataset in your research, please cite the following paper:

• https://doi.org/10.1109/MGRS.2023.3292467

Note

This dataset requires the following additional library to be installed:

• h5py to load the dataset

Added in version 0.6.

__init__(root='data', split='train', bands=('B01', 'B02', 'B03', 'B04', 'B05', 'B06', 'B07', 'B08', 'B8A', 'B09', 'B11', 'B12'), transforms=None, download=False, checksum=False)

Initialize a new CaBuAr dataset instance.

Parameters:

• root (str | PathLike[str]) – root directory where dataset can be found

• split (str) – one of “train”, “val”, “test”

• bands (tuple[str, ...]) – the subset of bands to load

• 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

• checksum (bool) – if True, check the MD5 of the downloaded files (may be slow)

Raises:

• AssertionError – If split or bands arguments are invalid.

• DatasetNotFoundError – If dataset is not found and download is False.

• DependencyNotFoundError – If h5py is not installed.

__getitem__(index)

Return an index within the dataset.

Changed in version 0.8: Now returns a single T x C x H x W image.

Parameters:

index (int) – index to return

Returns:

sample containing image and mask

Return type:

dict[str, Any]

__len__()

Return the number of data points in the dataset.

Returns:

length of the dataset

Return type:

int

plot(sample, show_titles=True, suptitle=None)

Plot a sample from the dataset.

Parameters:

• sample (dict[str, Any]) – a sample returned by __getitem__()

• show_titles (bool) – flag indicating whether to show titles above each panel

• suptitle (str | None) – optional suptitle to use for figure

Returns:

a matplotlib Figure with the rendered sample

Return type:

Figure

__annotate_func__()

The type of the None singleton.