Changed alpha init spatial lr behavior

scene/gaussian_model.py

@@ -84,7 +84,7 @@ class GaussianModel:
             self.active_sh_degree += 1
 
     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_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()
@@ -98,7 +98,7 @@ class GaussianModel:
         rots = torch.zeros((fused_point_cloud.shape[0], 4), device="cuda")
         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._features_dc = nn.Parameter(features[:,:,0:1].transpose(1, 2).contiguous().requires_grad_(True))
@@ -170,7 +170,7 @@ class GaussianModel:
         PlyData([el]).write(path)
 
     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")
         self._opacity = optimizable_tensors["opacity"]