Update mesh_utils.py

Simple fix. 

If image calibration is performed through COLMAP undistortion, the image size of the dataset may be different, so it cannot be created as a nested tensor with 'torch.stack'. 
Even with the List of tensors, there are no errors in the subsequent algorithms.

utils/mesh_utils.py

@@ -116,8 +116,8 @@ def reconstruction(self, viewpoint_stack):
             # self.normals.append(normal.cpu())
             # self.depth_normals.append(depth_normal.cpu())
 
-        self.rgbmaps = torch.stack(self.rgbmaps, dim=0)
-        self.depthmaps = torch.stack(self.depthmaps, dim=0)
+        # self.rgbmaps = torch.stack(self.rgbmaps, dim=0)
+        # self.depthmaps = torch.stack(self.depthmaps, dim=0)
         # self.alphamaps = torch.stack(self.alphamaps, dim=0)
         # self.depth_normals = torch.stack(self.depth_normals, dim=0)
         self.estimate_bounding_sphere()
@@ -292,4 +292,4 @@ def export_image(self, path):
             save_img_u8(self.rgbmaps[idx].permute(1,2,0).cpu().numpy(), os.path.join(render_path, '{0:05d}'.format(idx) + ".png"))
             save_img_f32(self.depthmaps[idx][0].cpu().numpy(), os.path.join(vis_path, 'depth_{0:05d}'.format(idx) + ".tiff"))
             # save_img_u8(self.normals[idx].permute(1,2,0).cpu().numpy() * 0.5 + 0.5, os.path.join(vis_path, 'normal_{0:05d}'.format(idx) + ".png"))
-            # save_img_u8(self.depth_normals[idx].permute(1,2,0).cpu().numpy() * 0.5 + 0.5, os.path.join(vis_path, 'depth_normal_{0:05d}'.format(idx) + ".png"))
+            # save_img_u8(self.depth_normals[idx].permute(1,2,0).cpu().numpy() * 0.5 + 0.5, os.path.join(vis_path, 'depth_normal_{0:05d}'.format(idx) + ".png"))