25 lines
1.4 KiB
Python
25 lines
1.4 KiB
Python
import torch
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@torch.no_grad()
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def get_state_at_time(pc,viewpoint_camera):
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means3D = pc.get_xyz
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time = torch.tensor(viewpoint_camera.time).to(means3D.device).repeat(means3D.shape[0],1)
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opacity = pc._opacity
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shs = pc.get_features
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# If precomputed 3d covariance is provided, use it. If not, then it will be computed from
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# scaling / rotation by the rasterizer.
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scales = pc._scaling
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rotations = pc._rotation
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cov3D_precomp = None
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# time0 = get_time()
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# means3D_deform, scales_deform, rotations_deform, opacity_deform = pc._deformation(means3D[deformation_point], scales[deformation_point],
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# rotations[deformation_point], opacity[deformation_point],
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# time[deformation_point])
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means3D_final, scales_final, rotations_final, opacity_final, shs_final = pc._deformation(means3D, scales,
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rotations, opacity, shs,
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time)
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scales_final = pc.scaling_activation(scales_final)
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rotations_final = pc.rotation_activation(rotations_final)
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opacity = pc.opacity_activation(opacity_final)
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return means3D_final, scales_final, rotations_final, opacity, shs |