LoveDA

class torchgeo.datasets.LoveDA(root='data', split='train', scene=['urban', 'rural'], transforms=None, download=False, checksum=False)

Bases: NonGeoDataset

LoveDA dataset.

The LoveDA datataset is a semantic segmentation dataset.

Dataset features:

• 2713 urban scene and 3274 rural scene HSR images, spatial resolution of 0.3m

• image source is Google Earth platform

• total of 166768 annotated objects from Nanjing, Changzhou and Wuhan cities

• dataset comes with predefined train, validation, and test set

• dataset differentiates between ‘rural’ and ‘urban’ images

Dataset format:

• images are three-channel pngs with dimension 1024x1024

• segmentation masks are single-channel pngs

Dataset classes:

1. background

2. building

3. road

4. water

5. barren

6. forest

7. agriculture

No-data regions assigned with 0 and should be ignored.

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

• https://arxiv.org/abs/2110.08733

Added in version 0.2.

__init__(root='data', split='train', scene=['urban', 'rural'], transforms=None, download=False, checksum=False)

Initialize a new LoveDA dataset instance.

Parameters:

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

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

• scene (Sequence[str]) – specify whether to load only ‘urban’, only ‘rural’ or both

• 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 scene arguments are invalid

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

__getitem__(index)

Return an index within the dataset.

Parameters:

index (int) – index to return

Returns:

image and mask at that index with image of dimension 3x1024x1024 and mask of dimension 1024x1024

Return type:

dict[str, Any]

__len__()

Return the number of datapoints in the dataset.

Returns:

length of dataset

Return type:

int

plot(sample, suptitle=None)

Plot a sample from the dataset.

Parameters:

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

• 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.