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| # -*- coding: utf-8 -*- | |
| import torch.nn as nn | |
| from typing import Tuple, List, Optional | |
| # Base class for output of Point to Mesh transformation | |
| class Point2MeshOutput(object): | |
| def __init__(self): | |
| self.mesh_v = None # Vertices of the mesh | |
| self.mesh_f = None # Faces of the mesh | |
| self.center = None # Center of the mesh | |
| self.pc = None # Point cloud data | |
| # Base class for output of Latent to Mesh transformation | |
| class Latent2MeshOutput(object): | |
| def __init__(self): | |
| self.mesh_v = None # Vertices of the mesh | |
| self.mesh_f = None # Faces of the mesh | |
| # Base class for output of Aligned Mesh transformation | |
| class AlignedMeshOutput(object): | |
| def __init__(self): | |
| self.mesh_v = None # Vertices of the mesh | |
| self.mesh_f = None # Faces of the mesh | |
| self.surface = None # Surface data | |
| self.image = None # Aligned image data | |
| self.text: Optional[str] = None # Aligned text data | |
| self.shape_text_similarity: Optional[float] = None # Similarity between shape and text | |
| self.shape_image_similarity: Optional[float] = None # Similarity between shape and image | |
| # Base class for Shape as Latent with Point to Mesh transformation module | |
| class ShapeAsLatentPLModule(nn.Module): | |
| latent_shape: Tuple[int] # Shape of the latent space | |
| def encode(self, surface, *args, **kwargs): | |
| raise NotImplementedError | |
| def decode(self, z_q, *args, **kwargs): | |
| raise NotImplementedError | |
| def latent2mesh(self, latents, *args, **kwargs) -> List[Latent2MeshOutput]: | |
| raise NotImplementedError | |
| def point2mesh(self, *args, **kwargs) -> List[Point2MeshOutput]: | |
| raise NotImplementedError | |
| # Base class for Shape as Latent module | |
| class ShapeAsLatentModule(nn.Module): | |
| latent_shape: Tuple[int, int] # Shape of the latent space | |
| def __init__(self, *args, **kwargs): | |
| super().__init__() | |
| def encode(self, *args, **kwargs): | |
| raise NotImplementedError | |
| def decode(self, *args, **kwargs): | |
| raise NotImplementedError | |
| def query_geometry(self, *args, **kwargs): | |
| raise NotImplementedError | |
| # Base class for Aligned Shape as Latent with Point to Mesh transformation module | |
| class AlignedShapeAsLatentPLModule(nn.Module): | |
| latent_shape: Tuple[int] # Shape of the latent space | |
| def set_shape_model_only(self): | |
| raise NotImplementedError | |
| def encode(self, surface, *args, **kwargs): | |
| raise NotImplementedError | |
| def decode(self, z_q, *args, **kwargs): | |
| raise NotImplementedError | |
| def latent2mesh(self, latents, *args, **kwargs) -> List[Latent2MeshOutput]: | |
| raise NotImplementedError | |
| def point2mesh(self, *args, **kwargs) -> List[Point2MeshOutput]: | |
| raise NotImplementedError | |
| # Base class for Aligned Shape as Latent module | |
| class AlignedShapeAsLatentModule(nn.Module): | |
| shape_model: ShapeAsLatentModule # Shape model module | |
| latent_shape: Tuple[int, int] # Shape of the latent space | |
| def __init__(self, *args, **kwargs): | |
| super().__init__() | |
| def set_shape_model_only(self): | |
| raise NotImplementedError | |
| def encode_image_embed(self, *args, **kwargs): | |
| raise NotImplementedError | |
| def encode_text_embed(self, *args, **kwargs): | |
| raise NotImplementedError | |
| def encode_shape_embed(self, *args, **kwargs): | |
| raise NotImplementedError | |
| # Base class for Textured Shape as Latent module | |
| class TexturedShapeAsLatentModule(nn.Module): | |
| def __init__(self, *args, **kwargs): | |
| super().__init__() | |
| def encode(self, *args, **kwargs): | |
| raise NotImplementedError | |
| def decode(self, *args, **kwargs): | |
| raise NotImplementedError | |
| def query_geometry(self, *args, **kwargs): | |
| raise NotImplementedError | |
| def query_color(self, *args, **kwargs): | |
| raise NotImplementedError | |