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affine with 1+, lint
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@@ -257,7 +257,7 @@ class SplatfactoModel(Model):
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torch.nn.Linear(32, 32),
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torch.nn.ReLU(),
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torch.nn.Linear(32, 6),
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torch.nn.Sigmoid()
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torch.nn.Sigmoid(),
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)
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@property
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@@ -639,7 +639,7 @@ class SplatfactoModel(Model):
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Mapping of different parameter groups
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"""
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gps = self.get_gaussian_param_groups()
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gps['appearance_embed'] = list(self.appearance_nn.parameters())+list(self.image_embeds.parameters())
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gps["appearance_embed"] = list(self.appearance_nn.parameters()) + list(self.image_embeds.parameters())
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return gps
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def _get_downscale_factor(self):
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@@ -807,10 +807,10 @@ class SplatfactoModel(Model):
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return_alpha=True,
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) # type: ignore
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alpha = alpha[..., None]
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if camera.metadata is not None and 'cam_idx' in camera.metadata:
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if camera.metadata is not None and "cam_idx" in camera.metadata:
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cam_id = camera.metadata["cam_idx"]
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affine_shift = self.appearance_nn(self.image_embeds(torch.tensor(cam_id,device=self.device)))
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rgb = rgb*affine_shift[:3] + affine_shift[3:]
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affine_shift = self.appearance_nn(self.image_embeds(torch.tensor(cam_id, device=self.device)))
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rgb = rgb * (1 + affine_shift[:3]) + affine_shift[3:]
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rgb = torch.clamp(rgb, max=1.0) # type: ignore
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depth_im = None
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if self.config.output_depth_during_training or not self.training:
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