torch_geometric.datasets.ModelNet

class ModelNet(root: str, name: str = '10', train: bool = True, transform: Optional[Callable] = None, pre_transform: Optional[Callable] = None, pre_filter: Optional[Callable] = None)[source]

Bases: InMemoryDataset

The ModelNet10/40 datasets from the “3D ShapeNets: A Deep Representation for Volumetric Shapes” paper, containing CAD models of 10 and 40 categories, respectively.

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.

  • name (str, optional) – The name of the dataset ("10" for ModelNet10, "40" for ModelNet40). (default: "10")

  • train (bool, optional) – If True, loads the training dataset, otherwise the test dataset. (default: True)

  • 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)

STATS:

Name

#graphs

#nodes

#edges

#features

#classes

ModelNet10

4,899

~9,508.2

~37,450.5

3

10

ModelNet40

12,311

~17,744.4

~66,060.9

3

40