可视化模块修改

utils/directory_manager.py

@@ -15,8 +15,11 @@ class DirectoryManager:
     def clean_output_dir(self):
         """清理输出目录"""
         try:
+            if os.path.exists(self.config.output_dir):
                 shutil.rmtree(self.config.output_dir)
                 print(f"已清理输出目录: {self.config.output_dir}")
+            else:
+                pass
         except Exception as e:
             print(f"清理输出目录时发生错误: {str(e)}")
             raise
@@ -65,7 +68,7 @@ class DirectoryManager:
         free_space = disk_usage.free
 
         # 计算所需空间（输入大小的10倍）
-        required_space = input_size * 10
+        required_space = input_size * 8
 
         if free_space < required_space:
             error_msg = (

utils/logger.py

@@ -2,6 +2,7 @@ import logging
 import os
 from datetime import datetime
 
+
 def setup_logger(output_dir):
     # 创建logs目录
     log_dir = os.path.join(output_dir, 'logs')

utils/odm_monitor.py

@@ -85,21 +85,20 @@ class ODMProcessMonitor:
                 self.logger.error("容器运行失败的详细错误日志：")
                 for line in error_msg:
                     self.logger.error(line)
+                container.remove()
+                time.sleep(5)
             else:
                 # 获取所有日志
                 logs = container.logs().decode("utf-8").splitlines()
-
                 # 输出最后 50 行日志
                 self.logger.info("容器运行完成，以下是最后 50 行日志：")
                 for line in logs[-50:]:
                     self.logger.info(line)
                 success = True
                 error_msg = ""
+                container.remove()
                 break
 
-            # 删除容器
-            container.remove()
-            time.sleep(5)
 
         return success, error_msg
 

utils/visualizer.py

@@ -55,28 +55,31 @@ class FilterVisualizer:
         self.logger.info(f"开始生成{step_name}的可视化结果")
 
         # 找出被过滤掉的点
-        filtered_files = set(previous_points['file']) - set(current_points['file'])
+        filtered_files = set(
-        filtered_points = previous_points[previous_points['file'].isin(filtered_files)]
+            previous_points['file']) - set(current_points['file'])
+        filtered_points = previous_points[previous_points['file'].isin(
+            filtered_files)]
 
         # 转换坐标到UTM
-        current_x, current_y = self._convert_to_utm(current_points['lon'], current_points['lat'])
+        current_x, current_y = self._convert_to_utm(
-        filtered_x, filtered_y = self._convert_to_utm(filtered_points['lon'], filtered_points['lat'])
+            current_points['lon'], current_points['lat'])
+        filtered_x, filtered_y = self._convert_to_utm(
+            filtered_points['lon'], filtered_points['lat'])
 
         # 创建图形
-        plt.rcParams['font.sans-serif']=['SimHei']#黑体
+        plt.rcParams['font.sans-serif'] = ['SimHei']  # 黑体
         plt.rcParams['axes.unicode_minus'] = False
-        plt.figure()
+        plt.figure(figsize=(20, 20))
 
         # 绘制保留的点
         plt.scatter(current_x, current_y,
                     color='blue', label='保留的点',
-                   alpha=0.6, s=50)
+                    alpha=0.6, s=5)
 
         # 绘制被过滤的点
         if not filtered_points.empty:
             plt.scatter(filtered_x, filtered_y,
-                       color='red', marker='x', label='过滤的点',
+                        color='red', marker='x', label='过滤的点')
-                       alpha=0.6, s=100)
 
         # 设置图形属性
         plt.title(f"{step_name}后的GPS点\n"
@@ -85,6 +88,7 @@ class FilterVisualizer:
         plt.xlabel("东向坐标 (米)", fontsize=12)
         plt.ylabel("北向坐标 (米)", fontsize=12)
         plt.grid(True)
+        plt.axis('equal')
 
         # 添加统计信息
         stats_text = (
@@ -104,7 +108,8 @@ class FilterVisualizer:
 
         # 保存图形
         save_name = save_name or step_name.lower().replace(' ', '_')
-        save_path = os.path.join(self.output_dir, 'filter_imgs', f'filter_{save_name}.png')
+        save_path = os.path.join(
+            self.output_dir, 'filter_imgs', f'filter_{save_name}.png')
         plt.savefig(save_path, dpi=300, bbox_inches='tight')
         plt.close()