EarthEmbeddings#

class torchgeo.datasets.EarthEmbeddings(root='data', transforms=None)[source]#

Bases: NonGeoDataset

EarthEmbeddings dataset.

EarthEmbeddings are pre-computed embeddings of uniformly sampled MajorTOM-Core-S2L2A imagery using SatCLIP, FarSLIP, DINOv2, SigLIP models. These embeddings power the EarthEmbeddingExplorer application, which allows users to search for satellite images using text queries, image uploads, or geographic locations.

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

  • A tutorial paper to be uploaded to arXiv soon.

Added in version 0.9.

__init__(root='data', transforms=None)[source]#

Initialize a new EarthEmbeddings instance.

Parameters:

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

  • 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.

Raises:

DatasetNotFoundError – If dataset is not found.

__len__()[source]#

Return the number of data points in the dataset.

Returns:

Length of the dataset.

Return type:

int

__getitem__(index)[source]#

Return an index within the dataset.

Parameters:

index (int) – Index to return.

Returns:

Data and label at that index.

Return type:

dict[str, Any]

plot(sample, show_titles=True)[source]#

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.

Returns:

A matplotlib Figure with the rendered sample.

Return type:

Figure