Clarification

full_eval.py

@@ -12,7 +12,7 @@
 import os
 from argparse import ArgumentParser
 
-mipnerf360_outdoor_scenes = ["bicycle", "flowers", "garden", "stump", "treehill"]
+mipnerf360_outdoor_scenes = ["flowers", "garden", "stump", "treehill"]
 mipnerf360_indoor_scenes = ["room", "counter", "kitchen", "bonsai"]
 tanks_and_temples_scenes = ["truck", "train"]
 deep_blending_scenes = ["drjohnson", "playroom"]
@@ -37,7 +37,7 @@ if not args.skip_training or not args.skip_rendering:
     args = parser.parse_args()
 
 if not args.skip_training:
-    common_args = " --quiet --eval --test_iterations -1"
+    common_args = "  --eval --save_iterations -1"
     for scene in mipnerf360_outdoor_scenes:
         source = args.mipnerf360 + "/" + scene
         os.system("python train.py -s " + source + " -i images_4 -m " + args.output_path + "/" + scene + common_args)

scene/gaussian_model.py

@@ -84,7 +84,9 @@ class GaussianModel:
             self.active_sh_degree += 1
 
     def create_from_pcd(self, pcd : BasicPointCloud, spatial_lr_scale : float):
+        spatial_lr_scale = 5
         self.spatial_lr_scale = spatial_lr_scale
+        #print(spatial_lr_scale)
         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()