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, force_reload: bool = False)[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
aspre_transform
. To convert the mesh to a point cloud, use thetorch_geometric.transforms.SamplePoints
astransform
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
)force_reload (bool, optional) – Whether to re-process the dataset. (default:
False
)
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