SODA

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

Bases: NonGeoDataset

SODA-A dataset.

The SODA-A dataset is a high resolution aerial imagery dataset for small object detection.

Dataset features:

• 2513 images

• 872,069 annotations with oriented bounding boxes

• 9 classes

Dataset format:

• Images are three channel .jpg files.

• Annotations are in json files

Classes:

0. Airplane

1. Helicopter

2. Small vehicle

3. Large vehicle

4. Ship

5. Container

6. Storage tank

7. Swimming-pool

8. Windmill

9. Other

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

• https://ieeexplore.ieee.org/document/10168277

Added in version 0.7.

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

Initialize a new instance of SODA-A dataset.

Parameters:

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

• split (Literal['train', 'val', 'test']) – one of “train”, “val”, or “test”

• bbox_orientation (Literal['oriented', 'horizontal']) – one of “oriented” or “horizontal”

• 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 bbox_orientation argument is invalid

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

__len__()

Return the number of samples in the dataset.

__getitem__(index)

Return the sample at the given index.

Parameters:

index (int) – index of the sample to return

Returns:

the sample at the given index

Return type:

dict[str, Any]

__annotate_func__()

The type of the None singleton.

plot(sample, show_titles=True, suptitle=None, box_alpha=0.7)

Plot a sample from the dataset with legend.

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

• box_alpha (float) – alpha value for boxes

Returns:

a matplotlib Figure with the rendered sample

Return type:

Figure