diff --git a/configs/server/server_train_config.yaml b/configs/server/server_train_config.yaml
index db56e2a..a55b0b2 100644
--- a/configs/server/server_train_config.yaml
+++ b/configs/server/server_train_config.yaml
@@ -7,7 +7,7 @@ runner:
     parallel: False
     
   experiment:
-    name: overfit_ab_global_and_partial_global
+    name: train_ab_global_and_partial_global
     root_dir: "experiments"
     use_checkpoint: False
     epoch: -1 # -1 stands for last epoch
@@ -32,10 +32,10 @@ runner:
   
 dataset:
   OmniObject3d_train:
-    root_dir: "/data/hofee/nbv_rec_part2_preprocessed"
+    root_dir: "/data/hofee/data/new_full_data"
     model_dir: "../data/scaled_object_meshes"
     source: nbv_reconstruction_dataset
-    split_file: "/data/hofee/data/sample.txt"
+    split_file: "/data/hofee/data/new_full_data_list/OmniObject3d_train.txt"
     type: train
     cache: True
     ratio: 1
@@ -45,32 +45,32 @@ dataset:
     load_from_preprocess: True
 
   OmniObject3d_test:
-    root_dir: "/data/hofee/nbv_rec_part2_preprocessed"
+    root_dir: "/data/hofee/data/new_full_data"
     model_dir: "../data/scaled_object_meshes"
     source: nbv_reconstruction_dataset
-    split_file: "/data/hofee/data/sample.txt"
+    split_file: "/data/hofee/data/new_full_data_list/OmniObject3d_test.txt"
     type: test
     cache: True
     filter_degree: 75
     eval_list:
       - pose_diff
-    ratio: 0.05
+    ratio: 1
     batch_size: 80
     num_workers: 12
     pts_num: 8192
     load_from_preprocess: True
 
   OmniObject3d_val:
-    root_dir: "/data/hofee/nbv_rec_part2_preprocessed"
+    root_dir: "/data/hofee/data/new_full_data"
     model_dir: "../data/scaled_object_meshes"
     source: nbv_reconstruction_dataset
-    split_file: "/data/hofee/data/sample.txt"
+    split_file: "/data/hofee/data/new_full_data_list/OmniObject3d_train.txt"
     type: test
     cache: True
     filter_degree: 75
     eval_list:
       - pose_diff
-    ratio: 0.005
+    ratio: 0.1
     batch_size: 80
     num_workers: 12
     pts_num: 8192
diff --git a/core/nbv_dataset.py b/core/nbv_dataset.py
index 01442a7..6583e5b 100644
--- a/core/nbv_dataset.py
+++ b/core/nbv_dataset.py
@@ -35,7 +35,7 @@ class NBVReconstructionDataset(BaseDataset):
             #self.model_dir = config["model_dir"]
             self.filter_degree = config["filter_degree"]
         if self.type == namespace.Mode.TRAIN:
-            scale_ratio = 50
+            scale_ratio = 1
             self.datalist = self.datalist*scale_ratio
         if self.cache:
             expr_root = ConfigManager.get("runner", "experiment", "root_dir")
@@ -149,7 +149,7 @@ class NBVReconstructionDataset(BaseDataset):
                 DataLoadUtil.load_from_preprocessed_pts(view_path)
             )
             downsampled_target_point_cloud = PtsUtil.random_downsample_point_cloud(
-                target_point_cloud, self.pts_num, replace=False
+                target_point_cloud, self.pts_num
             )
             scanned_views_pts.append(downsampled_target_point_cloud)
             scanned_coverages_rate.append(coverage_rate)
@@ -177,11 +177,8 @@ class NBVReconstructionDataset(BaseDataset):
         best_to_world_9d = np.concatenate(
             [best_to_world_6d, best_to_world_trans], axis=0
         )
-
-        start_time = time.time()
         
         combined_scanned_views_pts = np.concatenate(scanned_views_pts, axis=0)
-        #Log.info(f"combined_scanned_views_pts shape: {combined_scanned_views_pts.shape}")
         voxel_downsampled_combined_scanned_pts_np, inverse = self.voxel_downsample_with_mapping(combined_scanned_views_pts, 0.003)
         random_downsampled_combined_scanned_pts_np, random_downsample_idx = PtsUtil.random_downsample_point_cloud(voxel_downsampled_combined_scanned_pts_np, self.pts_num, require_idx=True)
 
@@ -197,10 +194,6 @@ class NBVReconstructionDataset(BaseDataset):
             view_unique_downsampled_idx_set = set(view_unique_downsampled_idx)
             mask = np.array([idx in view_unique_downsampled_idx_set for idx in all_random_downsample_idx])
             scanned_pts_mask.append(mask)
-        #Log.info(f"random_downsampled_combined_scanned_pts_np shape: {random_downsampled_combined_scanned_pts_np.shape}")
-        end_time = time.time()
-        #Log.info(f"downsample time: {end_time - start_time}")
-        
         data_item = {
             "scanned_pts": np.asarray(scanned_views_pts, dtype=np.float32), # Ndarray(S x Nv x 3)
             "combined_scanned_pts": np.asarray(random_downsampled_combined_scanned_pts_np, dtype=np.float32), # Ndarray(N x 3)