| from typing import * |
| import torch |
| from ..voxel import Voxel |
| import cumesh |
| from flex_gemm.ops.grid_sample import grid_sample_3d |
|
|
|
|
| class Mesh: |
| def __init__(self, |
| vertices, |
| faces, |
| vertex_attrs=None |
| ): |
| self.vertices = vertices.float() |
| self.faces = faces.int() |
| self.vertex_attrs = vertex_attrs |
| |
| @property |
| def device(self): |
| return self.vertices.device |
| |
| def to(self, device, non_blocking=False): |
| return Mesh( |
| self.vertices.to(device, non_blocking=non_blocking), |
| self.faces.to(device, non_blocking=non_blocking), |
| self.vertex_attrs.to(device, non_blocking=non_blocking) if self.vertex_attrs is not None else None, |
| ) |
| |
| def cuda(self, non_blocking=False): |
| return self.to('cuda', non_blocking=non_blocking) |
| |
| def cpu(self): |
| return self.to('cpu') |
| |
| def fill_holes(self, max_hole_perimeter=3e-2): |
| vertices = self.vertices.cuda() |
| faces = self.faces.cuda() |
| |
| mesh = cumesh.CuMesh() |
| mesh.init(vertices, faces) |
| mesh.get_edges() |
| mesh.get_boundary_info() |
| if mesh.num_boundaries == 0: |
| return |
| mesh.get_vertex_edge_adjacency() |
| mesh.get_vertex_boundary_adjacency() |
| mesh.get_manifold_boundary_adjacency() |
| mesh.read_manifold_boundary_adjacency() |
| mesh.get_boundary_connected_components() |
| mesh.get_boundary_loops() |
| if mesh.num_boundary_loops == 0: |
| return |
| mesh.fill_holes(max_hole_perimeter=max_hole_perimeter) |
| new_vertices, new_faces = mesh.read() |
| |
| self.vertices = new_vertices.to(self.device) |
| self.faces = new_faces.to(self.device) |
| |
| def remove_faces(self, face_mask: torch.Tensor): |
| vertices = self.vertices.cuda() |
| faces = self.faces.cuda() |
| |
| mesh = cumesh.CuMesh() |
| mesh.init(vertices, faces) |
| mesh.remove_faces(face_mask) |
| new_vertices, new_faces = mesh.read() |
| |
| self.vertices = new_vertices.to(self.device) |
| self.faces = new_faces.to(self.device) |
| |
| def simplify(self, target=1000000, verbose: bool=False, options: dict={}): |
| vertices = self.vertices.cuda() |
| faces = self.faces.cuda() |
| |
| mesh = cumesh.CuMesh() |
| mesh.init(vertices, faces) |
| mesh.simplify(target, verbose=verbose, options=options) |
| new_vertices, new_faces = mesh.read() |
| |
| self.vertices = new_vertices.to(self.device) |
| self.faces = new_faces.to(self.device) |
|
|
|
|
| class TextureFilterMode: |
| CLOSEST = 0 |
| LINEAR = 1 |
|
|
|
|
| class TextureWrapMode: |
| CLAMP_TO_EDGE = 0 |
| REPEAT = 1 |
| MIRRORED_REPEAT = 2 |
|
|
|
|
| class AlphaMode: |
| OPAQUE = 0 |
| MASK = 1 |
| BLEND = 2 |
|
|
|
|
| class Texture: |
| def __init__( |
| self, |
| image: torch.Tensor, |
| filter_mode: TextureFilterMode = TextureFilterMode.LINEAR, |
| wrap_mode: TextureWrapMode = TextureWrapMode.REPEAT |
| ): |
| self.image = image |
| self.filter_mode = filter_mode |
| self.wrap_mode = wrap_mode |
|
|
| def to(self, device, non_blocking=False): |
| return Texture( |
| self.image.to(device, non_blocking=non_blocking), |
| self.filter_mode, |
| self.wrap_mode, |
| ) |
|
|
|
|
| class PbrMaterial: |
| def __init__( |
| self, |
| base_color_texture: Optional[Texture] = None, |
| base_color_factor: Union[torch.Tensor, List[float]] = [1.0, 1.0, 1.0], |
| metallic_texture: Optional[Texture] = None, |
| metallic_factor: float = 1.0, |
| roughness_texture: Optional[Texture] = None, |
| roughness_factor: float = 1.0, |
| alpha_texture: Optional[Texture] = None, |
| alpha_factor: float = 1.0, |
| alpha_mode: AlphaMode = AlphaMode.OPAQUE, |
| alpha_cutoff: float = 0.5, |
| ): |
| self.base_color_texture = base_color_texture |
| self.base_color_factor = torch.tensor(base_color_factor, dtype=torch.float32)[:3] |
| self.metallic_texture = metallic_texture |
| self.metallic_factor = metallic_factor |
| self.roughness_texture = roughness_texture |
| self.roughness_factor = roughness_factor |
| self.alpha_texture = alpha_texture |
| self.alpha_factor = alpha_factor |
| self.alpha_mode = alpha_mode |
| self.alpha_cutoff = alpha_cutoff |
|
|
| def to(self, device, non_blocking=False): |
| return PbrMaterial( |
| base_color_texture=self.base_color_texture.to(device, non_blocking=non_blocking) if self.base_color_texture is not None else None, |
| base_color_factor=self.base_color_factor.to(device, non_blocking=non_blocking), |
| metallic_texture=self.metallic_texture.to(device, non_blocking=non_blocking) if self.metallic_texture is not None else None, |
| metallic_factor=self.metallic_factor, |
| roughness_texture=self.roughness_texture.to(device, non_blocking=non_blocking) if self.roughness_texture is not None else None, |
| roughness_factor=self.roughness_factor, |
| alpha_texture=self.alpha_texture.to(device, non_blocking=non_blocking) if self.alpha_texture is not None else None, |
| alpha_factor=self.alpha_factor, |
| alpha_mode=self.alpha_mode, |
| alpha_cutoff=self.alpha_cutoff, |
| ) |
|
|
|
|
| class MeshWithPbrMaterial(Mesh): |
| def __init__(self, |
| vertices, |
| faces, |
| material_ids, |
| uv_coords, |
| materials: List[PbrMaterial], |
| ): |
| self.vertices = vertices.float() |
| self.faces = faces.int() |
| self.material_ids = material_ids |
| self.uv_coords = uv_coords |
| self.materials = materials |
| self.layout = { |
| 'base_color': slice(0, 3), |
| 'metallic': slice(3, 4), |
| 'roughness': slice(4, 5), |
| 'alpha': slice(5, 6), |
| } |
|
|
| def to(self, device, non_blocking=False): |
| return MeshWithPbrMaterial( |
| self.vertices.to(device, non_blocking=non_blocking), |
| self.faces.to(device, non_blocking=non_blocking), |
| self.material_ids.to(device, non_blocking=non_blocking), |
| self.uv_coords.to(device, non_blocking=non_blocking), |
| [material.to(device, non_blocking=non_blocking) for material in self.materials], |
| ) |
|
|
|
|
| class MeshWithVoxel(Mesh, Voxel): |
| def __init__(self, |
| vertices: torch.Tensor, |
| faces: torch.Tensor, |
| origin: list, |
| voxel_size: float, |
| coords: torch.Tensor, |
| attrs: torch.Tensor, |
| voxel_shape: torch.Size, |
| layout: Dict = {}, |
| ): |
| self.vertices = vertices.float() |
| self.faces = faces.int() |
| self.origin = torch.tensor(origin, dtype=torch.float32, device=self.device) |
| self.voxel_size = voxel_size |
| self.coords = coords |
| self.attrs = attrs |
| self.voxel_shape = voxel_shape |
| self.layout = layout |
|
|
| def to(self, device, non_blocking=False): |
| return MeshWithVoxel( |
| self.vertices.to(device, non_blocking=non_blocking), |
| self.faces.to(device, non_blocking=non_blocking), |
| self.origin.tolist(), |
| self.voxel_size, |
| self.coords.to(device, non_blocking=non_blocking), |
| self.attrs.to(device, non_blocking=non_blocking), |
| self.voxel_shape, |
| self.layout, |
| ) |
| |
| def query_attrs(self, xyz): |
| grid = ((xyz - self.origin) / self.voxel_size).reshape(1, -1, 3) |
| vertex_attrs = grid_sample_3d( |
| self.attrs, |
| torch.cat([torch.zeros_like(self.coords[..., :1]), self.coords], dim=-1), |
| self.voxel_shape, |
| grid, |
| mode='trilinear' |
| )[0] |
| return vertex_attrs |
| |
| def query_vertex_attrs(self): |
| return self.query_attrs(self.vertices) |
|
|