Remove culling

utils/app_utils.py

@@ -158,15 +158,13 @@ def export_to_obj(reconstruction, ply_out_path):
         assert v.shape[0] == 1, "Expected batch size to be 0"
         reconstruction[k] = v[0]
 
-    non_transparent_points = torch.where(reconstruction["opacity"] > 0.005)[0]
-
-    xyz = reconstruction["xyz"][non_transparent_points].detach().cpu().numpy()
+    xyz = reconstruction["xyz"].detach().cpu().numpy()
     normals = np.zeros_like(xyz)
-    f_dc = reconstruction["features_dc"][non_transparent_points].detach().transpose(1, 2).flatten(start_dim=1).contiguous().cpu().numpy()
-    f_rest = reconstruction["features_rest"][non_transparent_points].detach().transpose(1, 2).flatten(start_dim=1).contiguous().cpu().numpy()
-    opacities = reconstruction["opacity"][non_transparent_points].detach().cpu().numpy()
-    scale = reconstruction["scaling"][non_transparent_points].detach().cpu().numpy()
-    rotation = reconstruction["rotation"][non_transparent_points].detach().cpu().numpy()
+    f_dc = reconstruction["features_dc"].detach().transpose(1, 2).flatten(start_dim=1).contiguous().cpu().numpy()
+    f_rest = reconstruction["features_rest"].detach().transpose(1, 2).flatten(start_dim=1).contiguous().cpu().numpy()
+    opacities = reconstruction["opacity"].detach().cpu().numpy()
+    scale = reconstruction["scaling"].detach().cpu().numpy()
+    rotation = reconstruction["rotation"].detach().cpu().numpy()
 
     dtype_full = [(attribute, 'f4') for attribute in construct_list_of_attributes()]