torch_geometric.datasets.MedShapeNet

class MedShapeNet(root: str, size: int = 100, transform: Optional[Callable] = None, pre_transform: Optional[Callable] = None, pre_filter: Optional[Callable] = None, force_reload: bool = False)[source]

Bases: InMemoryDataset

The MedShapeNet datasets from the “MedShapeNet – A Large-Scale Dataset of 3D Medical Shapes for Computer Vision” paper, containing 8 different type of structures (classes).

Note

Data objects hold mesh faces instead of edge indices. To convert the mesh to a graph, use the torch_geometric.transforms.FaceToEdge as pre_transform. To convert the mesh to a point cloud, use the torch_geometric.transforms.SamplePoints as transform to sample a fixed number of points on the mesh faces according to their face area.

Parameters:

  • root (str) – Root directory where the dataset should be saved.

  • size (int) – Number of invividual 3D structures to download per type (classes).

  • transform (callable, optional) – A function/transform that takes in an torch_geometric.data.Data object and returns a transformed version. The data object will be transformed before every access. (default: None)

  • pre_transform (callable, optional) – A function/transform that takes in an torch_geometric.data.Data object and returns a transformed version. The data object will be transformed before being saved to disk. (default: None)

  • pre_filter (callable, optional) – A function that takes in an torch_geometric.data.Data object and returns a boolean value, indicating whether the data object should be included in the final dataset. (default: None)

  • force_reload (bool, optional) – Whether to re-process the dataset. (default: False)