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PhotoTour

class torchvision.datasets.PhotoTour(root: str, name: str, train: bool = True, transform: Optional[Callable] = None, download: bool = False)[source]

Multi-view Stereo Correspondence Dataset.

Note

We only provide the newer version of the dataset, since the authors state that it

is more suitable for training descriptors based on difference of Gaussian, or Harris corners, as the patches are centred on real interest point detections, rather than being projections of 3D points as is the case in the old dataset.

The original dataset is available under http://phototour.cs.washington.edu/patches/default.htm.

Parameters:
  • root (string) – Root directory where images are.

  • name (string) – Name of the dataset to load.

  • transform (callable, optional) – A function/transform that takes in a PIL image and returns a transformed version.

  • 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.

Special-members:

__getitem__(index: int) Union[Tensor, Tuple[Any, Any, Tensor]][source]
Parameters:

index (int) – Index

Returns:

(data1, data2, matches)

Return type:

tuple

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