recent hyperparam.: prune opacity thres, reset opacity, znear

Author: semyeong-yu

scene/cameras.py

@@ -78,7 +78,7 @@ def __init__(self, resolution, colmap_id, R, T, FoVx, FoVy, depth_params, image,
             self.invdepthmap = torch.from_numpy(self.invdepthmap[None]).to(self.data_device)
 
         self.zfar = 100.0
-        self.znear = 0.01
+        self.znear = 0.1 # 6DGS # 3DGS: 0.01
 
         self.trans = trans
         self.scale = scale

scene/gaussian_model.py

@@ -394,7 +394,7 @@ def save_ply(self, path):
         PlyData([el]).write(path)
 
     def reset_opacity(self):
-        opacities_new = self.inverse_opacity_activation(torch.min(self.get_opacity, torch.ones_like(self.get_opacity)*0.01))
+        opacities_new = self.inverse_opacity_activation(torch.min(self.get_opacity, torch.ones_like(self.get_opacity)*0.02)) # 6DGS # 3DGS: 0.01
         optimizable_tensors = self.replace_tensor_to_optimizer(opacities_new, "opacity")
         self._opacity = optimizable_tensors["opacity"]
 

train.py

@@ -175,7 +175,7 @@ def training(dataset, opt, pipe, testing_iterations, saving_iterations, checkpoi
 
                 if iteration > opt.densify_from_iter and iteration % opt.densification_interval == 0:
                     size_threshold = 20 if iteration > opt.opacity_reset_interval else None
-                    gaussians.densify_and_prune(opt.densify_grad_threshold, 0.01, scene.cameras_extent, size_threshold, radii) # min opacity threshold is hard-coded # 0.005
+                    gaussians.densify_and_prune(opt.densify_grad_threshold, 0.01, scene.cameras_extent, size_threshold, radii) # 6DGS # min opacity threshold is hard-coded # 3DGS: 0.005
 
                 if iteration % opt.opacity_reset_interval == 0 or (dataset.white_background and iteration == opt.densify_from_iter):
                 # if dataset.white_background and iteration == opt.densify_from_iter: # 6DGS