diff --git a/core/dataset.py b/core/dataset.py
index ec8d94d..acac8ba 100644
--- a/core/dataset.py
+++ b/core/dataset.py
@@ -7,7 +7,7 @@ from PytorchBoot.utils.log_util import Log
 import torch
 import os
 import sys
-sys.path.append(r"/media/hofee/data/project/python/nbv_reconstruction/nbv_reconstruction")
+sys.path.append(r"/home/data/hofee/project/nbv_rec/nbv_reconstruction")
 
 from utils.data_load import DataLoadUtil
 from utils.pose import PoseUtil
@@ -17,7 +17,6 @@ from utils.reconstruction import ReconstructionUtil
 
 @stereotype.dataset("nbv_reconstruction_dataset")
 class NBVReconstructionDataset(BaseDataset):
-    DISPLAY_TABLE_POSITION = np.asarray([0,0,0.85])
     def __init__(self, config):
         super(NBVReconstructionDataset, self).__init__(config)
         self.config = config
@@ -206,15 +205,16 @@ if __name__ == "__main__":
     torch.manual_seed(seed)
     np.random.seed(seed)
     config = {
-        "root_dir": "/media/hofee/data/project/python/nbv_reconstruction/sample_for_training/scenes",
-        "split_file": "/media/hofee/data/project/python/nbv_reconstruction/sample_for_training/OmniObject3d_train.txt",
-        "model_dir": "/media/hofee/data/data/scaled_object_meshes",
+        "root_dir": "../data/sample_for_training/scenes",
+        "model_dir": "../data/scaled_object_meshes",
+        "source": "nbv_reconstruction_dataset",
+        "split_file": "../data/sample_for_training/OmniObject3d_train.txt",
         "ratio": 0.5,
         "batch_size": 2,
         "filter_degree": 75,
         "num_workers": 0,
-        "pts_num": 32684,
-        "type": namespace.Mode.TEST,
+        "pts_num": 4096,
+        "type": namespace.Mode.TRAIN,
     }
     ds = NBVReconstructionDataset(config)
     print(len(ds))
diff --git a/utils/data_load.py b/utils/data_load.py
index e9fcc54..afa7b04 100644
--- a/utils/data_load.py
+++ b/utils/data_load.py
@@ -6,7 +6,7 @@ import trimesh
 from utils.pts import PtsUtil
 
 class DataLoadUtil:
-    DISPLAY_TABLE_POSITION = np.asarray([0,0,0.85])
+    DISPLAY_TABLE_POSITION = np.asarray([0,0,0.895])
     @staticmethod
     def get_path(root, scene_name, frame_idx):
         path = os.path.join(root, scene_name, f"{frame_idx}")