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import torch.nn as nn |
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from typing import Tuple, List, Optional |
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import pytorch_lightning as pl |
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class Point2MeshOutput(object): |
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def __init__(self): |
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self.mesh_v = None |
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self.mesh_f = None |
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self.center = None |
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self.pc = None |
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class Latent2MeshOutput(object): |
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def __init__(self): |
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self.mesh_v = None |
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self.mesh_f = None |
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class AlignedMeshOutput(object): |
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def __init__(self): |
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self.mesh_v = None |
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self.mesh_f = None |
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self.surface = None |
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self.image = None |
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self.text: Optional[str] = None |
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self.shape_text_similarity: Optional[float] = None |
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self.shape_image_similarity: Optional[float] = None |
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class ShapeAsLatentPLModule(pl.LightningModule): |
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latent_shape: Tuple[int] |
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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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class ShapeAsLatentModule(nn.Module): |
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latent_shape: Tuple[int, int] |
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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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class AlignedShapeAsLatentPLModule(pl.LightningModule): |
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latent_shape: Tuple[int] |
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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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class AlignedShapeAsLatentModule(nn.Module): |
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shape_model: ShapeAsLatentModule |
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latent_shape: Tuple[int, int] |
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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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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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