FGVCAircraft — Torchvision 0.22 documentation (original) (raw)

class torchvision.datasets.FGVCAircraft(root: ~typing.Union[str, ~pathlib.Path], split: str = 'trainval', annotation_level: str = 'variant', transform: ~typing.Optional[~typing.Callable] = None, target_transform: ~typing.Optional[~typing.Callable] = None, download: bool = False, loader: ~typing.Callable[[str], ~typing.Any] = <function default_loader>)[source]¶

FGVC Aircraft Dataset.

The dataset contains 10,000 images of aircraft, with 100 images for each of 100 different aircraft model variants, most of which are airplanes. Aircraft models are organized in a three-levels hierarchy. The three levels, from finer to coarser, are:

• variant, e.g. Boeing 737-700. A variant collapses all the models that are visually
  indistinguishable into one class. The dataset comprises 100 different variants.
• family, e.g. Boeing 737. The dataset comprises 70 different families.
• manufacturer, e.g. Boeing. The dataset comprises 30 different manufacturers.

Parameters:

• root (str or pathlib.Path) – Root directory of the FGVC Aircraft dataset.
• split (string , optional) – The dataset split, supports train, val,trainval and test.
• annotation_level (str, optional) – The annotation level, supports variant,family and manufacturer.
• transform (callable , optional) – A function/transform that takes in a PIL image or torch.Tensor, depends on the given loader, and returns a transformed version. E.g, transforms.RandomCrop
• target_transform (callable , optional) – A function/transform that takes in the target and transforms it.
• download (bool, optional) – If True, downloads the dataset from the internet and puts it in root directory. If dataset is already downloaded, it is not downloaded again.
• loader (callable , optional) – A function to load an image given its path. By default, it uses PIL as its image loader, but users could also pass intorchvision.io.decode_image for decoding image data into tensors directly.

Special-members:

__getitem__(idx: int) → Tuple[Any, Any][source]¶

Parameters:

index (int) – Index

Returns:

Sample and meta data, optionally transformed by the respective transforms.

Return type:

(Any)