UniqAI/gaussian-splatting
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Changed alpha init spatial lr behavior

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bkerbl 2023-07-13 13:12:45 +02:00
parent 73ad40f414
commit b1a35bc94b
1 changed files with 3 additions and 3 deletions
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6
scene/gaussian_model.py
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@ -84,7 +84,7 @@ class GaussianModel:
self.active_sh_degree += 1 self.active_sh_degree += 1
def create_from_pcd(self, pcd : BasicPointCloud, spatial_lr_scale : float): def create_from_pcd(self, pcd : BasicPointCloud, spatial_lr_scale : float):
self.spatial_lr_scale = 5#spatial_lr_scale self.spatial_lr_scale = 5
fused_point_cloud = torch.tensor(np.asarray(pcd.points)).float().cuda() fused_point_cloud = torch.tensor(np.asarray(pcd.points)).float().cuda()
fused_color = RGB2SH(torch.tensor(np.asarray(pcd.colors)).float().cuda()) fused_color = RGB2SH(torch.tensor(np.asarray(pcd.colors)).float().cuda())
features = torch.zeros((fused_color.shape[0], 3, (self.max_sh_degree + 1) ** 2)).float().cuda() features = torch.zeros((fused_color.shape[0], 3, (self.max_sh_degree + 1) ** 2)).float().cuda()
@ -98,7 +98,7 @@ class GaussianModel:
rots = torch.zeros((fused_point_cloud.shape[0], 4), device="cuda") rots = torch.zeros((fused_point_cloud.shape[0], 4), device="cuda")
rots[:, 0] = 1 rots[:, 0] = 1
opacities = inverse_sigmoid(0.5 * torch.ones((fused_point_cloud.shape[0], 1), dtype=torch.float, device="cuda")) opacities = inverse_sigmoid(0.1 * torch.ones((fused_point_cloud.shape[0], 1), dtype=torch.float, device="cuda"))
self._xyz = nn.Parameter(fused_point_cloud.requires_grad_(True)) self._xyz = nn.Parameter(fused_point_cloud.requires_grad_(True))
self._features_dc = nn.Parameter(features[:,:,0:1].transpose(1, 2).contiguous().requires_grad_(True)) self._features_dc = nn.Parameter(features[:,:,0:1].transpose(1, 2).contiguous().requires_grad_(True))
@ -170,7 +170,7 @@ class GaussianModel:
PlyData([el]).write(path) PlyData([el]).write(path)
def reset_opacity(self): def reset_opacity(self):
opacities_new = inverse_sigmoid(torch.ones_like(self.get_opacity)*0.01) opacities_new = inverse_sigmoid(torch.min(self.get_opacity, torch.ones_like(self.get_opacity)*0.01))
optimizable_tensors = self.replace_tensor_to_optimizer(opacities_new, "opacity") optimizable_tensors = self.replace_tensor_to_optimizer(opacities_new, "opacity")
self._opacity = optimizable_tensors["opacity"] self._opacity = optimizable_tensors["opacity"]