You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
42 lines
1.2 KiB
42 lines
1.2 KiB
from dataclasses import dataclass, field
|
|
from typing import Dict, Optional
|
|
|
|
import torch
|
|
|
|
from .mesh import TriMesh
|
|
|
|
|
|
@dataclass
|
|
class TorchMesh:
|
|
"""
|
|
A 3D triangle mesh with optional data at the vertices and faces.
|
|
"""
|
|
|
|
# [N x 3] array of vertex coordinates.
|
|
verts: torch.Tensor
|
|
|
|
# [M x 3] array of triangles, pointing to indices in verts.
|
|
faces: torch.Tensor
|
|
|
|
# Extra data per vertex and face.
|
|
vertex_channels: Optional[Dict[str, torch.Tensor]] = field(default_factory=dict)
|
|
face_channels: Optional[Dict[str, torch.Tensor]] = field(default_factory=dict)
|
|
|
|
def tri_mesh(self) -> TriMesh:
|
|
"""
|
|
Create a CPU version of the mesh.
|
|
"""
|
|
return TriMesh(
|
|
verts=self.verts.detach().cpu().numpy(),
|
|
faces=self.faces.cpu().numpy(),
|
|
vertex_channels=(
|
|
{k: v.detach().cpu().numpy() for k, v in self.vertex_channels.items()}
|
|
if self.vertex_channels is not None
|
|
else None
|
|
),
|
|
face_channels=(
|
|
{k: v.detach().cpu().numpy() for k, v in self.face_channels.items()}
|
|
if self.face_channels is not None
|
|
else None
|
|
),
|
|
)
|
|
|