EverWatch

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

Bases: NonGeoDataset

EverWatch Bird Detection dataset.

The EverWatch Bird Detection dataset contains high-resolution aerial images of birds in the Everglades National Park. Seven bird species haven been annotated and classified.

Dataset features:

• 5128 training images with 50491 annotations

• 197 test images with 4113 annotations

• seven different bird species

Dataset format:

• images are three-channel pngs

• annotations are csv file

Dataset Classes:

0. White Ibis (Eudocimus albus)

1. Great Egret (Ardea alba)

2. Great Blue Heron (Ardea herodias)

3. Snowy Egret (Egretta thula)

4. Wood Stork (Mycteria americana)

5. Roseate Spoonbill (Platalea ajaja)

6. Anhinga (Anhinga anhinga)

7. Unknown White (only present in test split)

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

• https://doi.org/10.5281/zenodo.11165946

Added in version 0.7.

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

Initialize a new EverWatch dataset instance.

Parameters:

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

• split (str) – one of {‘train’, ‘val’, ‘test’} to specify the dataset split

• 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:

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

• AssertionError – If split argument is invalid.

__len__()

Return the number of samples in the dataset.

Returns:

length of the dataset

Return type:

int

__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]

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

Plot a sample from the dataset.

Parameters:

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

• 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