添加高精度模式

main.py

@@ -13,6 +13,8 @@ def parse_args():
     # 可选参数
     parser.add_argument('--mode', default='三维模式',
                         choices=['快拼模式', '三维模式', '重建模式'], help='处理模式')
+    parser.add_argument('--accuracy', default='medium',
+                        choices=['high', 'medium', 'low'], help='精度')
     parser.add_argument('--grid_size', type=float, default=800, help='网格大小(米)')
     parser.add_argument('--grid_overlap', type=float,
                         default=0.05, help='网格重叠率')
@@ -30,6 +32,7 @@ def main():
         image_dir=args.image_dir,
         output_dir=args.output_dir,
         mode=args.mode,
+        accuracy=args.accuracy,
         grid_size=args.grid_size,
         grid_overlap=args.grid_overlap,
         produce_dem=True,

odm_preprocess.py

@@ -44,6 +44,7 @@ class PreprocessConfig:
     grid_size: float = 500
     # 几个pipline过程是否开启
     mode: str = "快拼模式"
+    accuracy: str = "medium"
     produce_dem: bool = False
 
 
@@ -305,7 +306,7 @@ class ImagePreprocessor:
             self.logger.info("预处理任务完成")
 
             successful_grid_points = self.odm_monitor.process_all_grids(
-                grid_points, self.config.produce_dem)
+                grid_points, self.config.produce_dem, self.config.accuracy)
 
             self.post_process(successful_grid_points,
                               grid_points, translations)

utils/odm_monitor.py

@@ -128,7 +128,7 @@ class ODMProcessMonitor:
             self.logger.error(f"检查正射影像时发生错误: {str(e)}")
             return False
 
-    def run_odm_with_monitor(self, grid_dir: str, grid_id: tuple, produce_dem: bool = False) -> Tuple[bool, str]:
+    def run_odm_with_monitor(self, grid_dir: str, grid_id: tuple, produce_dem: bool = False, accuracy = 'medium') -> Tuple[bool, str]:
         """运行ODM命令"""
         self.logger.info(f"开始处理网格 ({grid_id[0]},{grid_id[1]})")
         success = False
@@ -158,8 +158,15 @@ class ODMProcessMonitor:
                     f"--use-hybrid-bundle-adjustment "
                     f"--optimize-disk-space "
                     # f"--feature-type sift "
-                    # f"--feature-quality ultra "
                 )
+                if accuracy == "high":
+                    docker_command += (
+                        f"--feature-quality ultra "
+                        f"--pc-quality ultra "
+                        f"--mesh-size 3000000 "
+                        f"--mesh-octree-depth 12 "
+                        f"--orthophoto-resolution 2 "
+                    )
 
                 # 根据是否使用lowest quality添加参数
                 if use_lowest_quality:
@@ -254,7 +261,7 @@ class ODMProcessMonitor:
 
         return success, error_msg
 
-    def process_all_grids(self, grid_points: Dict[tuple, pd.DataFrame], produce_dem: bool) -> Dict[tuple, pd.DataFrame]:
+    def process_all_grids(self, grid_points: Dict[tuple, pd.DataFrame], produce_dem: bool, accuracy: str) -> Dict[tuple, pd.DataFrame]:
         """处理所有网格
 
         Returns:
@@ -273,7 +280,8 @@ class ODMProcessMonitor:
                 success, error_msg = self.run_odm_with_monitor(
                     grid_dir=grid_dir,
                     grid_id=grid_id,
-                    produce_dem=produce_dem
+                    produce_dem=produce_dem,
+                    accuracy=accuracy
                 )
 
                 if success: