FAIR1M

class torchgeo.datasets.FAIR1M(root='data', split='train', transforms=None, download=False, checksum=False)

Bases: NonGeoDataset

FAIR1M dataset.

The FAIR1M dataset is a dataset for remote sensing fine-grained oriented object detection.

Dataset features:

• 15,000+ images with 0.3-0.8 m per pixel resolution (1,000-10,000 px)

• 1 million object instances

• 5 object categories, 37 object sub-categories

• three spectral bands - RGB

• images taken by Gaofen satellites and Google Earth

Dataset format:

• images are three-channel tiffs

• labels are xml files with PASCAL VOC like annotations

Dataset classes:

0. Passenger Ship

1. Motorboat

2. Fishing Boat

3. Tugboat

4. other-ship

5. Engineering Ship

6. Liquid Cargo Ship

7. Dry Cargo Ship

8. Warship

9. Small Car

10. Bus

11. Cargo Truck

12. Dump Truck

13. other-vehicle

14. Van

15. Trailer

16. Tractor

17. Excavator

18. Truck Tractor

19. Boeing737

20. Boeing747

21. Boeing777

22. Boeing787

23. ARJ21

24. C919

25. A220

26. A321

27. A330

28. A350

29. other-airplane

30. Baseball Field

31. Basketball Court

32. Football Field

33. Tennis Court

34. Roundabout

35. Intersection

36. Bridge

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

• https://doi.org/10.1016/j.isprsjprs.2021.12.004

Added in version 0.2.

__init__(root='data', split='train', transforms=None, download=False, checksum=False)

Initialize a new FAIR1M dataset instance.

Parameters:

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

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

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

Raises:

• AssertionError – if split argument is invalid

• DatasetNotFoundError – If dataset is not found.

Changed in version 0.5: Added split and download parameters.

__getitem__(index)

Return an index within the dataset.

Parameters:

index (int) – index to return

Returns:

data and label at that index

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 string to use as a suptitle

Returns:

a matplotlib Figure with the rendered sample

Return type:

Figure

__annotate_func__()

The type of the None singleton.