diff --git a/configs/local/view_generate_config.yaml b/configs/local/view_generate_config.yaml
index e2f8779..b58d672 100644
--- a/configs/local/view_generate_config.yaml
+++ b/configs/local/view_generate_config.yaml
@@ -7,12 +7,12 @@ runner:
     name: debug
     root_dir: experiments
   generate:
-    port: 5004
-    from: 0
-    to: 1 # -1 means all
-    object_dir: H:\\AI\\Datasets\\scaled_object_box_meshes
-    table_model_path: "H:\\AI\\Datasets\\table.obj"
-    output_dir: C:\\Document\\Local Project\\nbv_rec\\nbv_reconstruction\\temp
+    port: 5002
+    from: 600
+    to: -1 # -1 means all
+    object_dir: /media/hofee/data/data/object_meshes_part1
+    table_model_path: "/media/hofee/data/data/others/table.obj"
+    output_dir: /media/hofee/repository/data_part_1
     binocular_vision: true
     plane_size: 10
     max_views: 512
diff --git a/preprocess/preprocessor.py b/preprocess/preprocessor.py
index ad8b166..26175b8 100644
--- a/preprocess/preprocessor.py
+++ b/preprocess/preprocessor.py
@@ -87,8 +87,8 @@ def get_scan_points_indices(scan_points, mask, display_table_mask_label, cam_int
 def save_scene_data(root, scene, scene_idx=0, scene_total=1,file_type="txt"):
     
     ''' configuration '''
-    target_mask_label = (0, 255, 0, 255)
-    display_table_mask_label=(0, 0, 255, 255)
+    target_mask_label = (0, 255, 0)
+    display_table_mask_label=(0, 0, 255)
     random_downsample_N = 32768
     voxel_size=0.003
     filter_degree = 75
@@ -158,7 +158,7 @@ def save_scene_data(root, scene, scene_idx=0, scene_total=1,file_type="txt"):
 
 if __name__ == "__main__":
     #root = "/media/hofee/repository/new_data_with_normal"
-    root = r"C:\\Document\\Local Project\\nbv_rec\\nbv_reconstruction\\temp"
+    root = r"/media/hofee/repository/data_part_1"
     # list_path = r"/media/hofee/repository/full_list.txt"
     # scene_list = []
     
@@ -167,8 +167,7 @@ if __name__ == "__main__":
     #         scene_list.append(line.strip())
     scene_list = os.listdir(root)
     from_idx = 0 # 1000
-    to_idx = 1 # 1500
-    print(scene_list)
+    to_idx = 600 # 1500
 
 
     cnt = 0
@@ -176,6 +175,10 @@ if __name__ == "__main__":
     total = to_idx - from_idx
     for scene in scene_list[from_idx:to_idx]:
         start = time.time()
+        if os.path.exists(os.path.join(root, scene, "scan_points.txt")):
+            print(f"Scene {scene} has been processed")
+            cnt+=1
+            continue
         save_scene_data(root, scene, cnt, total, file_type="npy")
         cnt+=1
         end = time.time()
diff --git a/runners/view_generator.py b/runners/view_generator.py
index 2e28c44..634ccbf 100644
--- a/runners/view_generator.py
+++ b/runners/view_generator.py
@@ -9,7 +9,7 @@ class ViewGenerator(Runner):
         self.config_path = config_path
         
     def run(self):
-        result = subprocess.run(['blender', '-b', '-P', '../blender/run_blender.py', '--', self.config_path])
+        result = subprocess.run(['/home/hofee/blender-4.0.2-linux-x64/blender', '-b', '-P', '../blender/run_blender.py', '--', self.config_path])
         print()
 
     def create_experiment(self, backup_name=None):
diff --git a/utils/data_load.py b/utils/data_load.py
index c98347e..83204c4 100644
--- a/utils/data_load.py
+++ b/utils/data_load.py
@@ -29,8 +29,8 @@ class DataLoadUtil:
         # 读取 EXR 文件中的每个通道并转化为浮点数数组
         img_data = []
         for channel in float_channels:
-            channel_data = exr_file.channel(channel, Imath.PixelType(Imath.PixelType.FLOAT))
-            img_data.append(np.frombuffer(channel_data, dtype=np.float32).reshape((height, width)))
+            channel_data = exr_file.channel(channel)
+            img_data.append(np.frombuffer(channel_data, dtype=np.float16).reshape((height, width)))
 
         # 将各通道组合成一个 (height, width, 3) 的 RGB 图像
         img = np.stack(img_data, axis=-1)
@@ -141,8 +141,8 @@ class DataLoadUtil:
         if binocular and not left_only:
 
             def clean_mask(mask_image):
-                green = [0, 255, 0, 255]
-                red = [255, 0, 0, 255]
+                green = [0, 255, 0]
+                red = [255, 0, 0]
                 threshold = 2
                 mask_image = np.where(
                     np.abs(mask_image - green) <= threshold, green, mask_image