diff --git a/gps_selector.py b/gps_selector.py
index 4feeb55..66d3e5c 100644
--- a/gps_selector.py
+++ b/gps_selector.py
@@ -141,14 +141,15 @@ class GPSSelector:
 
         # 创建输出目录
         os.makedirs(self.output_dir, exist_ok=True)
-        removed_dir = os.path.join(self.output_dir, "removed_images")
-        os.makedirs(removed_dir, exist_ok=True)
 
-        # 移动被删除的图像
-        for img_name in self.selected_points:
+        # 获取所有保留的图片文件名
+        remaining_files = self.gps_points['file'].tolist()
+
+        # 移动保留的图片到输出目录
+        for img_name in remaining_files:
             src = os.path.join(self.image_dir, img_name)
-            dst = os.path.join(removed_dir, img_name)
-            shutil.move(src, dst)
+            dst = os.path.join(self.output_dir, img_name)
+            shutil.copy2(src, dst)  # 使用copy2保留文件的元数据
 
         # 保存剩余点的信息
         self.gps_points.to_csv(
@@ -156,8 +157,8 @@ class GPSSelector:
             index=False
         )
 
-        print(f"已移动 {len(self.selected_points)} 张图片到 {removed_dir}")
-        print(f"保留 {len(self.gps_points)} 个点")
+        print(f"已选择删除 {len(self.selected_points)} 张图片")
+        print(f"已复制 {len(remaining_files)} 张保留的图片到 {self.output_dir}")
 
     def run(self):
         """运行选择器"""
@@ -229,7 +230,7 @@ class GPSSelector:
 if __name__ == "__main__":
     # 使用示例
     selector = GPSSelector(
-        image_dir=r"C:\datasets\134\code\images",
-        output_dir=r"C:\datasets\ODM_output\134"
+        image_dir=r"G:\error_data\20240930091614\project\images",
+        output_dir=r"C:\datasets\ODM_output\error1_L"
     )
     selector.run()
diff --git a/odm_preprocess.py b/odm_preprocess.py
index 2c7b2de..23323b7 100644
--- a/odm_preprocess.py
+++ b/odm_preprocess.py
@@ -286,8 +286,8 @@ class ImagePreprocessor:
 if __name__ == "__main__":
     # 创建配置
     config = PreprocessConfig(
-        image_dir=r"E:\datasets\UAV\1619\project\images",
-        output_dir=r"G:\ODM_output\1619",
+        image_dir=r"G:\test_data\error1_L",
+        output_dir=r"G:\ODM_output\error1_L",
 
         cluster_eps=0.01,
         cluster_min_samples=5,