规范代码格式

odm_preprocess.py

@@ -64,8 +64,8 @@ class ImagePreprocessor:
         self.logger.info("开始过滤GPS点")
         filter = GPSFilter(self.config.output_dir)
 
-        self.logger.info(f"开始过滤孤立点 (距离阈值: {self.config.filter_distance_threshold}, 最小邻居数: {
-                         self.config.filter_min_neighbors})")
+        self.logger.info(
+            f"开始过滤孤立点(距离阈值: {self.config.filter_distance_threshold}, 最小邻居数: {self.config.filter_min_neighbors})")
         self.gps_points = filter.filter_isolated_points(
             self.gps_points,
             self.config.filter_distance_threshold,
@@ -73,8 +73,8 @@ class ImagePreprocessor:
         )
         self.logger.info(f"孤立点过滤后剩余 {len(self.gps_points)} 个GPS点")
 
-        self.logger.info(f"开始过滤密集点 (网格大小: {self.config.filter_grid_size}, 距离阈值: {
-                         self.config.filter_dense_distance_threshold})")
+        self.logger.info(
+            f"开始过滤密集点(网格大小: {self.config.filter_grid_size}, 距离阈值: {self.config.filter_dense_distance_threshold})")
         self.gps_points = filter.filter_dense_points(
             self.gps_points,
             grid_size=self.config.filter_grid_size,
@@ -90,7 +90,8 @@ class ImagePreprocessor:
 
         self.logger.info(f"开始划分网格 (重叠率: {self.config.grid_overlap})")
         grid_divider = GridDivider(overlap=self.config.grid_overlap)
-        grids = grid_divider.divide_grids(self.gps_points, grid_size=self.config.grid_size)
+        grids = grid_divider.divide_grids(
+            self.gps_points, grid_size=self.config.grid_size)
         grid_points = grid_divider.assign_to_grids(self.gps_points, grids)
         self.logger.info(f"成功划分为 {len(grid_points)} 个网格")
         return grid_points
@@ -104,9 +105,11 @@ class ImagePreprocessor:
 
         for grid_idx, points in grid_points.items():
             if self.config.enable_grid_division:
-                output_dir = os.path.join(self.config.output_dir, f'grid_{grid_idx + 1}', 'project', 'images')
+                output_dir = os.path.join(
+                    self.config.output_dir, f'grid_{grid_idx + 1}', 'project', 'images')
             else:
-                output_dir = os.path.join(self.config.output_dir, 'project', 'images')
+                output_dir = os.path.join(
+                    self.config.output_dir, 'project', 'images')
 
             os.makedirs(output_dir, exist_ok=True)
 
@@ -134,18 +137,19 @@ class ImagePreprocessor:
 
         # 绘制所有原始点
         plt.scatter(original_points_df['lon'],
-                   original_points_df['lat'],
-                   color='blue', 
-                   label="Original Points", 
-                   alpha=0.6)
+                    original_points_df['lat'],
+                    color='blue',
+                    label="Original Points",
+                    alpha=0.6)
 
         # 绘制被过滤的点
-        filtered_points_df = original_points_df[original_points_df['file'].isin(filtered_files)]
+        filtered_points_df = original_points_df[original_points_df['file'].isin(
+            filtered_files)]
         plt.scatter(filtered_points_df['lon'],
-                   filtered_points_df['lat'],
-                   color="red", 
-                   label="Filtered Points", 
-                   alpha=0.6)
+                    filtered_points_df['lat'],
+                    color="red",
+                    label="Filtered Points",
+                    alpha=0.6)
 
         # 设置图形属性
         plt.title("GPS Coordinates of Images", fontsize=14)
@@ -181,8 +185,8 @@ class ImagePreprocessor:
 if __name__ == '__main__':
     # 创建配置
     config = PreprocessConfig(
-        image_dir=r'C:\datasets\1815\images',
-        output_dir=r'C:\datasets\1815\output',
+        image_dir=r'E:\datasets\UAV\1815',
+        output_dir=r'E:\datasets\UAV\1815\output',
         filter_grid_size=0.001,
         filter_dense_distance_threshold=10,
         filter_distance_threshold=0.001,

preprocess/command_runner.py

@@ -4,6 +4,7 @@ import subprocess
 from typing import Dict
 import pandas as pd
 
+
 class CommandRunner:
     """执行网格处理命令的类"""