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https://github.com/graphdeco-inria/gaussian-splatting
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fixed learning rate for spatial
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@ -84,7 +84,7 @@ class GaussianModel:
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self.active_sh_degree += 1
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self.active_sh_degree += 1
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def create_from_pcd(self, pcd : BasicPointCloud, spatial_lr_scale : float):
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def create_from_pcd(self, pcd : BasicPointCloud, spatial_lr_scale : float):
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self.spatial_lr_scale = spatial_lr_scale
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self.spatial_lr_scale = 5#spatial_lr_scale
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fused_point_cloud = torch.tensor(np.asarray(pcd.points)).float().cuda()
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fused_point_cloud = torch.tensor(np.asarray(pcd.points)).float().cuda()
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fused_color = RGB2SH(torch.tensor(np.asarray(pcd.colors)).float().cuda())
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fused_color = RGB2SH(torch.tensor(np.asarray(pcd.colors)).float().cuda())
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features = torch.zeros((fused_color.shape[0], 3, (self.max_sh_degree + 1) ** 2)).float().cuda()
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features = torch.zeros((fused_color.shape[0], 3, (self.max_sh_degree + 1) ** 2)).float().cuda()
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