Scaling LR fixed

arguments/__init__.py

@@ -76,7 +76,7 @@ class OptimizationParams(ParamGroup):
         self.position_lr_max_steps = 30_000
         self.feature_lr = 0.0025
         self.opacity_lr = 0.05
-        self.scaling_lr = 0.001
+        self.scaling_lr = 0.005
         self.rotation_lr = 0.001
         self.percent_dense = 0.01
         self.lambda_dssim = 0.2

scene/gaussian_model.py

@@ -152,11 +152,11 @@ class GaussianModel:
         self.denom = torch.zeros((self.get_xyz.shape[0], 1), device="cuda")
 
         l = [
-            {'params': [self._xyz], 'lr': training_args.position_lr_init*self.spatial_lr_scale, "name": "xyz"},
+            {'params': [self._xyz], 'lr': training_args.position_lr_init * self.spatial_lr_scale, "name": "xyz"},
             {'params': [self._features_dc], 'lr': training_args.feature_lr, "name": "f_dc"},
             {'params': [self._features_rest], 'lr': training_args.feature_lr / 20.0, "name": "f_rest"},
             {'params': [self._opacity], 'lr': training_args.opacity_lr, "name": "opacity"},
-            {'params': [self._scaling], 'lr': training_args.scaling_lr*self.spatial_lr_scale, "name": "scaling"},
+            {'params': [self._scaling], 'lr': training_args.scaling_lr, "name": "scaling"},
             {'params': [self._rotation], 'lr': training_args.rotation_lr, "name": "rotation"}
         ]
 

train.py

@@ -162,8 +162,8 @@ def training_report(tb_writer, iteration, Ll1, loss, l1_loss, elapsed, testing_i
 
         for config in validation_configs:
             if config['cameras'] and len(config['cameras']) > 0:
-                l1_test = 0
-                psnr_test = 0
+                l1_test = 0.0
+                psnr_test = 0.0
                 for idx, viewpoint in enumerate(config['cameras']):
                     image = torch.clamp(renderFunc(viewpoint, scene.gaussians, *renderArgs)["render"], 0.0, 1.0)
                     gt_image = torch.clamp(viewpoint.original_image.to("cuda"), 0.0, 1.0)
@@ -171,8 +171,8 @@ def training_report(tb_writer, iteration, Ll1, loss, l1_loss, elapsed, testing_i
                         tb_writer.add_images(config['name'] + "_view_{}/render".format(viewpoint.image_name), image[None], global_step=iteration)
                         if iteration == testing_iterations[0]:
                             tb_writer.add_images(config['name'] + "_view_{}/ground_truth".format(viewpoint.image_name), gt_image[None], global_step=iteration)
-                    l1_test += l1_loss(image, gt_image).mean()
-                    psnr_test += psnr(image, gt_image).mean()
+                    l1_test += l1_loss(image, gt_image).mean().double()
+                    psnr_test += psnr(image, gt_image).mean().double()
                 psnr_test /= len(config['cameras'])
                 l1_test /= len(config['cameras'])          
                 print("\n[ITER {}] Evaluating {}: L1 {} PSNR {}".format(iteration, config['name'], l1_test, psnr_test))