mirror of
https://git.datalinker.icu/kijai/ComfyUI-Hunyuan3DWrapper.git
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126 lines
3.8 KiB
Python
126 lines
3.8 KiB
Python
# -*- coding: utf-8 -*-
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import torch.nn as nn
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from typing import Tuple, List, Optional
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# Base class for output of Point to Mesh transformation
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class Point2MeshOutput(object):
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def __init__(self):
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self.mesh_v = None # Vertices of the mesh
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self.mesh_f = None # Faces of the mesh
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self.center = None # Center of the mesh
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self.pc = None # Point cloud data
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# Base class for output of Latent to Mesh transformation
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class Latent2MeshOutput(object):
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def __init__(self):
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self.mesh_v = None # Vertices of the mesh
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self.mesh_f = None # Faces of the mesh
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# Base class for output of Aligned Mesh transformation
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class AlignedMeshOutput(object):
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def __init__(self):
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self.mesh_v = None # Vertices of the mesh
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self.mesh_f = None # Faces of the mesh
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self.surface = None # Surface data
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self.image = None # Aligned image data
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self.text: Optional[str] = None # Aligned text data
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self.shape_text_similarity: Optional[float] = None # Similarity between shape and text
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self.shape_image_similarity: Optional[float] = None # Similarity between shape and image
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# Base class for Shape as Latent with Point to Mesh transformation module
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class ShapeAsLatentPLModule(nn.Module):
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latent_shape: Tuple[int] # Shape of the latent space
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def encode(self, surface, *args, **kwargs):
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raise NotImplementedError
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def decode(self, z_q, *args, **kwargs):
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raise NotImplementedError
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def latent2mesh(self, latents, *args, **kwargs) -> List[Latent2MeshOutput]:
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raise NotImplementedError
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def point2mesh(self, *args, **kwargs) -> List[Point2MeshOutput]:
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raise NotImplementedError
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# Base class for Shape as Latent module
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class ShapeAsLatentModule(nn.Module):
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latent_shape: Tuple[int, int] # Shape of the latent space
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def __init__(self, *args, **kwargs):
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super().__init__()
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def encode(self, *args, **kwargs):
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raise NotImplementedError
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def decode(self, *args, **kwargs):
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raise NotImplementedError
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def query_geometry(self, *args, **kwargs):
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raise NotImplementedError
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# Base class for Aligned Shape as Latent with Point to Mesh transformation module
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class AlignedShapeAsLatentPLModule(nn.Module):
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latent_shape: Tuple[int] # Shape of the latent space
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def set_shape_model_only(self):
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raise NotImplementedError
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def encode(self, surface, *args, **kwargs):
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raise NotImplementedError
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def decode(self, z_q, *args, **kwargs):
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raise NotImplementedError
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def latent2mesh(self, latents, *args, **kwargs) -> List[Latent2MeshOutput]:
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raise NotImplementedError
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def point2mesh(self, *args, **kwargs) -> List[Point2MeshOutput]:
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raise NotImplementedError
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# Base class for Aligned Shape as Latent module
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class AlignedShapeAsLatentModule(nn.Module):
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shape_model: ShapeAsLatentModule # Shape model module
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latent_shape: Tuple[int, int] # Shape of the latent space
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def __init__(self, *args, **kwargs):
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super().__init__()
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def set_shape_model_only(self):
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raise NotImplementedError
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def encode_image_embed(self, *args, **kwargs):
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raise NotImplementedError
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def encode_text_embed(self, *args, **kwargs):
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raise NotImplementedError
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def encode_shape_embed(self, *args, **kwargs):
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raise NotImplementedError
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# Base class for Textured Shape as Latent module
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class TexturedShapeAsLatentModule(nn.Module):
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def __init__(self, *args, **kwargs):
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super().__init__()
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def encode(self, *args, **kwargs):
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raise NotImplementedError
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def decode(self, *args, **kwargs):
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raise NotImplementedError
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def query_geometry(self, *args, **kwargs):
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raise NotImplementedError
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def query_color(self, *args, **kwargs):
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raise NotImplementedError
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