diff --git a/cad.py b/cad.py
index 641bad9..d47a963 100644
--- a/cad.py
+++ b/cad.py
@@ -3,7 +3,6 @@ import os
 import subprocess
 
 
-
 def convert_dxf_to_dwg(dxf_files: List[str]):
     cad_file_path = r"D:/Program Files/Cad2022/AutoCAD 2022/accoreconsole.exe"
     first_dwg_file = dxf_files[0]
@@ -15,9 +14,16 @@ def convert_dxf_to_dwg(dxf_files: List[str]):
             new_dwg_name = f"{file_name_path}.dwg"
             if os.path.exists(new_dwg_name):
                 os.remove(new_dwg_name)
+            new_dwg_name = new_dwg_name.replace("//", "/")
             f.write(f'saveas 2004 "{new_dwg_name}"\n')
             cmd = rf'"{cad_file_path}" /s "{script_path}" /i "{dxf}" /iso'
-        subprocess.call(cmd,stderr=subprocess.DEVNULL,stdin=subprocess.DEVNULL,stdout=subprocess.DEVNULL)
+        cmd = cmd.replace("//", "/")
+        subprocess.call(
+            cmd,
+            stderr=subprocess.DEVNULL,
+            stdin=subprocess.DEVNULL,
+            stdout=subprocess.DEVNULL,
+        )
 
 
 def convert_dxf_to_dwg1(dxf_files: List[str]):
diff --git a/dem.py b/dem.py
index 5922644..2ca8bc8 100644
--- a/dem.py
+++ b/dem.py
@@ -378,7 +378,8 @@ class Dem:
         path_length = (
             (point_x_s - point_x_e) ** 2 + (point_y_s - point_y_e) ** 2
         ) ** 0.5
-        dem_resolution = self._dem_resolution  # dem的精度
+        # dem_resolution = self._dem_resolution  # dem的精度
+        dem_resolution = 5
         # TODO:设定为5m 1个点。
         n = round(path_length / dem_resolution)
         # n = round(path_length / 5)
@@ -397,7 +398,9 @@ class Dem:
         left_offset_y = side_width * math.sin(line_angel + math.pi / 2)
         left_offset_point_x = center_point_x + left_offset_x
         left_offset_point_y = center_point_y + left_offset_y
-        right_offset_point_x = center_point_x - left_offset_x  # 向左偏移和向右偏移正好是相反的
+        right_offset_point_x = (
+            center_point_x - left_offset_x
+        )  # 向左偏移和向右偏移正好是相反的
         right_offset_point_y = center_point_y - left_offset_y
         r = np.array(
             [