小修bug

odm_preprocess.py

@@ -46,6 +46,7 @@ class PreprocessConfig:
     grid_size: float = 500
     # 几个pipline过程是否开启
     mode: str = "快拼模式"
+    produce_dem: bool = False
 
 
 class ImagePreprocessor:
@@ -237,11 +238,11 @@ class ImagePreprocessor:
                 shutil.copy(src, dst)
             self.logger.info(f"网格 ({grid_id[0]},{grid_id[1]}) 包含 {len(points)} 张图像")
 
-    def merge_tif(self, grid_points: Dict[tuple, pd.DataFrame]):
+    def merge_tif(self, grid_points: Dict[tuple, pd.DataFrame], produce_dem: bool):
         """合并所有网格的影像产品"""
         self.logger.info("开始合并所有影像产品")
         merger = MergeTif(self.config.output_dir)
-        merger.merge_all_tifs(grid_points)
+        merger.merge_all_tifs(grid_points, produce_dem)
 
     def merge_ply(self, grid_points: Dict[tuple, pd.DataFrame]):
         """合并所有网格的PLY点云"""
@@ -266,8 +267,8 @@ class ImagePreprocessor:
             self.copy_images(grid_points)
             self.logger.info("预处理任务完成")
 
-            self.odm_monitor.process_all_grids(grid_points)
+            self.odm_monitor.process_all_grids(grid_points, self.config.produce_dem)
-            self.merge_tif(grid_points)
+            self.merge_tif(grid_points, self.config.produce_dem)
             self.merge_ply(grid_points)
             self.merge_obj(grid_points, translations)
         except Exception as e:
@@ -278,8 +279,8 @@ class ImagePreprocessor:
 if __name__ == "__main__":
     # 创建配置
     config = PreprocessConfig(
-        image_dir=r"E:\datasets\UAV\1815\project\images",
+        image_dir=r"E:\datasets\UAV\283\project\images",
-        output_dir=r"G:\ODM_output\1815",
+        output_dir=r"G:\ODM_output\283",
 
         cluster_eps=0.01,
         cluster_min_samples=5,
@@ -295,11 +296,12 @@ if __name__ == "__main__":
         filter_dense_distance_threshold=10,
         filter_time_threshold=timedelta(minutes=5),
 
-        grid_size=500,
+        grid_size=400,
         grid_overlap=0.1,
 
 
         mode="重建模式",
+        produce_dem=False,
     )
 
     # 创建处理器并执行

post_pro/merge_obj.py

@@ -4,6 +4,7 @@ import numpy as np
 from typing import Dict
 import pandas as pd
 import shutil
+import time
 
 
 class MergeObj:
@@ -124,8 +125,23 @@ class MergeObj:
             materials2 = self.read_mtl(mtl2_path)
             
             # 创建材质名称映射（使用与MTL文件相同的命名格式）
-            material_map1 = {old_name: f"material_{grid_id1[0]}_{grid_id1[1]}_{old_name}" for old_name in materials1.keys()}
+            material_map1 = {}
-            material_map2 = {old_name: f"material_{grid_id2[0]}_{grid_id2[1]}_{old_name}" for old_name in materials2.keys()}
+            material_map2 = {}
+            
+            # 处理第一个模型的材质映射
+            for old_name in materials1.keys():
+                # 如果材质名称已经包含了网格ID前缀，就不再添加
+                if old_name.startswith(f"material_{grid_id1[0]}_{grid_id1[1]}_"):
+                    material_map1[old_name] = old_name
+                else:
+                    material_map1[old_name] = f"material_{grid_id1[0]}_{grid_id1[1]}_{old_name}"
+
+            # 处理第二个模型的材质映射
+            for old_name in materials2.keys():
+                if old_name.startswith(f"material_{grid_id2[0]}_{grid_id2[1]}_"):
+                    material_map2[old_name] = old_name
+                else:
+                    material_map2[old_name] = f"material_{grid_id2[0]}_{grid_id2[1]}_{old_name}"
 
             # 平移第二个模型的顶点
             vertices2_translated = self.translate_vertices(vertices2, translation)
@@ -315,24 +331,51 @@ class MergeObj:
             # 合并OBJ文件
             reference_id = list(grid_files.keys())[0]
             merged_obj = grid_files[reference_id]['obj']
+            temp_files = []  # 记录所有中间文件
 
             for grid_id, files in list(grid_files.items())[1:]:
                 translation = translations[grid_id]
                 translation = (translation[0], translation[1], 0)
 
-                output_obj = os.path.join(
+                # 生成临时输出文件名
+                temp_output = os.path.join(
                     output_model_dir,
-                    f"merged_model_{reference_id[0]}_{reference_id[1]}_{grid_id[0]}_{grid_id[1]}.obj"
+                    f"temp_merged_{int(time.time())}.obj"
                 )
+                temp_files.append(temp_output)  # 添加到临时文件列表
 
-                self.merge_two_objs(merged_obj, files['obj'], output_obj, translation, reference_id, grid_id)
+                self.merge_two_objs(merged_obj, files['obj'], temp_output, translation, reference_id, grid_id)
-                merged_obj = output_obj
+                
+                # 如果上一个merged_obj是临时文件，则删除它
+                if merged_obj != grid_files[reference_id]['obj'] and os.path.exists(merged_obj):
+                    try:
+                        os.remove(merged_obj)
+                    except Exception as e:
+                        self.logger.warning(f"删除临时文件失败: {merged_obj}, 错误: {str(e)}")
+                
+                merged_obj = temp_output
 
             # 最终结果
             final_obj = os.path.join(output_model_dir, "merged_model.obj")
-            if os.path.exists(merged_obj) and merged_obj != final_obj:
+            try:
+                if os.path.exists(final_obj):
+                    os.remove(final_obj)
+                os.rename(merged_obj, final_obj)
+            except Exception as e:
+                self.logger.warning(f"重命名最终文件失败: {str(e)}")
                 shutil.copy2(merged_obj, final_obj)
+                try:
                     os.remove(merged_obj)
+                except:
+                    pass
+
+            # 清理所有临时文件
+            for temp_file in temp_files:
+                if os.path.exists(temp_file):
+                    try:
+                        os.remove(temp_file)
+                    except Exception as e:
+                        self.logger.warning(f"删除临时文件失败: {temp_file}, 错误: {str(e)}")
 
             self.logger.info(
                 f"模型合并完成，输出目录: {output_model_dir}\n"

post_pro/merge_tif.py

@@ -3,6 +3,8 @@ import logging
 import os
 from typing import Dict
 import pandas as pd
+import time
+import shutil
 
 
 class MergeTif:
@@ -25,13 +27,17 @@ class MergeTif:
                 raise FileNotFoundError(error_msg)
 
             # 打开影像，检查投影是否一致
-            datasets = [gdal.Open(tif) for tif in [input_tif1, input_tif2]]
+            datasets = []
-            if None in datasets:
+            try:
-                error_msg = "无法打开输入影像文件"
+                for tif in [input_tif1, input_tif2]:
+                    ds = gdal.Open(tif)
+                    if ds is None:
+                        error_msg = f"无法打开影像文件: {tif}"
                         self.logger.error(error_msg)
                         raise ValueError(error_msg)
+                    datasets.append(ds)
 
-            projections = [dataset.GetProjection() for dataset in datasets]
+                projections = [ds.GetProjection() for ds in datasets]
                 self.logger.debug(f"影像1投影: {projections[0]}")
                 self.logger.debug(f"影像2投影: {projections[1]}")
 
@@ -41,6 +47,17 @@ class MergeTif:
                     self.logger.error(error_msg)
                     raise ValueError(error_msg)
 
+                # 如果输出文件已存在，先删除
+                if os.path.exists(output_tif):
+                    try:
+                        os.remove(output_tif)
+                    except Exception as e:
+                        self.logger.warning(f"删除已存在的输出文件失败: {str(e)}")
+                        # 生成一个新的输出文件名
+                        base, ext = os.path.splitext(output_tif)
+                        output_tif = f"{base}_{int(time.time())}{ext}"
+                        self.logger.info(f"使用新的输出文件名: {output_tif}")
+
                 # 创建 GDAL Warp 选项
                 warp_options = gdal.WarpOptions(
                     format="GTiff",
@@ -51,8 +68,7 @@ class MergeTif:
                 )
 
                 self.logger.info("开始执行影像拼接...")
-            result = gdal.Warp(
+                result = gdal.Warp(output_tif, datasets, options=warp_options)
-                output_tif, [input_tif1, input_tif2], options=warp_options)
 
                 if result is None:
                     error_msg = "影像拼接失败"
@@ -65,10 +81,19 @@ class MergeTif:
                     width = output_dataset.RasterXSize
                     height = output_dataset.RasterYSize
                     bands = output_dataset.RasterCount
-                self.logger.info(f"拼接完成，输出影像大小: {width}x{height}，波段数: {bands}")
+                    self.logger.info(
+                        f"拼接完成，输出影像大小: {width}x{height}，波段数: {bands}")
+                    output_dataset = None  # 显式关闭数据集
 
                 self.logger.info(f"影像拼接成功，输出文件保存至: {output_tif}")
 
+            finally:
+                # 确保所有数据集都被正确关闭
+                for ds in datasets:
+                    if ds:
+                        ds = None
+                result = None
+
         except Exception as e:
             self.logger.error(f"影像拼接过程中发生错误: {str(e)}", exc_info=True)
             raise
@@ -108,25 +133,58 @@ class MergeTif:
                     self.logger.info(f"设置第一个输入{product_name}: {input_tif1}")
                 else:
                     input_tif2 = grid_tif
-                    output_tif = os.path.join(
+                    # 生成带时间戳的临时输出文件名
-                        self.output_dir, f"merged_{product_info['output']}")
+                    temp_output = os.path.join(
+                        self.output_dir,
+                        f"temp_merged_{int(time.time())}_{product_info['output']}"
+                    )
 
                     self.logger.info(
                         f"开始合并{product_name}第 {merge_count + 1} 次:\n"
                         f"输入1: {input_tif1}\n"
                         f"输入2: {input_tif2}\n"
-                        f"输出: {output_tif}"
+                        f"输出: {temp_output}"
                     )
 
-                    self.merge_two_tifs(input_tif1, input_tif2, output_tif)
+                    self.merge_two_tifs(input_tif1, input_tif2, temp_output)
                     merge_count += 1
 
-                    input_tif1 = output_tif
+                    # 如果之前的输入文件是临时文件，则删除它
+                    if 'temp_merged_' in input_tif1:
+                        try:
+                            os.remove(input_tif1)
+                        except Exception as e:
+                            self.logger.warning(f"删除临时文件失败: {str(e)}")
+
+                    input_tif1 = temp_output
                     input_tif2 = None
 
+            # 重命名最终的临时文件为目标文件名
+            final_output = os.path.join(
+                self.output_dir, product_info['output'])
+            if os.path.exists(final_output):
+                try:
+                    os.remove(final_output)
+                except Exception as e:
+                    self.logger.warning(f"删除已存在的最终输出文件失败: {str(e)}")
+                    final_output = os.path.join(
+                        self.output_dir,
+                        f"merged_{int(time.time())}_{product_info['output']}"
+                    )
+
+            try:
+                os.rename(input_tif1, final_output)
+            except Exception as e:
+                self.logger.warning(f"重命名最终文件失败: {str(e)}")
+                shutil.copy2(input_tif1, final_output)
+                try:
+                    os.remove(input_tif1)
+                except:
+                    pass
+
             self.logger.info(
                 f"{product_name}合并完成，共执行 {merge_count} 次合并，"
-                f"最终输出文件: {input_tif1}"
+                f"最终输出文件: {final_output}"
             )
 
         except Exception as e:
@@ -134,7 +192,7 @@ class MergeTif:
                 f"{product_name}合并过程中发生错误: {str(e)}", exc_info=True)
             raise
 
-    def merge_all_tifs(self, grid_points: Dict[tuple, pd.DataFrame]):
+    def merge_all_tifs(self, grid_points: Dict[tuple, pd.DataFrame], produce_dem: bool):
         """合并所有产品（正射影像、DSM和DTM）"""
         try:
             products = [
@@ -144,6 +202,10 @@ class MergeTif:
                     'filename': 'odm_orthophoto.original.tif',
                     'output': 'orthophoto.tif'
                 },
+
+            ]
+            if produce_dem:
+                products.append(
                     {
                         'name': 'DSM',
                         'path': 'odm_dem',
@@ -156,7 +218,7 @@ class MergeTif:
                         'filename': 'dtm.original.tif',
                         'output': 'dtm.tif'
                     }
-            ]
+                )
 
             for product in products:
                 self.merge_grid_tif(grid_points, product)

utils/grid_divider.py

@@ -149,9 +149,9 @@ class GridDivider:
                 plt.text(center_lon, center_lat, f"({i},{j})",  # 显示(i,j)
                          horizontalalignment='center', verticalalignment='center')
 
-        plt.title('网格划分与GPS点分布图')
+        plt.title('Grid Division and GPS Point Distribution')
-        plt.xlabel('经度')
+        plt.xlabel('Longitude')
-        plt.ylabel('纬度')
+        plt.ylabel('Latitude')
         plt.legend()
         plt.grid(True)
 

utils/odm_monitor.py

@@ -20,8 +20,12 @@ class ODMProcessMonitor:
             success_markers.append('odm_texturing')
         return all(os.path.exists(os.path.join(grid_dir, 'project', marker)) for marker in success_markers)
 
-    def run_odm_with_monitor(self, grid_dir: str, grid_id: tuple, fast_mode: bool = True) -> Tuple[bool, str]:
+    def run_odm_with_monitor(self, grid_dir: str, grid_id: tuple, fast_mode: bool = True, produce_dem: bool = False) -> Tuple[bool, str]:
         """运行ODM命令"""
+        if produce_dem and fast_mode:
+            self.logger.error("快拼模式下无法生成DEM，请调整生产参数")
+            return False, "快拼模式下无法生成DEM，请调整生产参数"
+
         self.logger.info(f"开始处理网格 ({grid_id[0]},{grid_id[1]})")
 
         # 构建Docker命令
@@ -37,6 +41,12 @@ class ODMProcessMonitor:
             f"--orthophoto-resolution 10 "
         )
 
+        if produce_dem:
+            docker_command += (
+                f"--dsm "
+                f"--dtm "
+            )
+
         if fast_mode:
             docker_command += (
                 f"--fast-orthophoto "
@@ -60,7 +70,7 @@ class ODMProcessMonitor:
             self.logger.error(f"网格 ({grid_id[0]},{grid_id[1]}) 处理失败")
             return False, f"网格 ({grid_id[0]},{grid_id[1]}) 处理失败"
 
-    def process_all_grids(self, grid_points: Dict[tuple, pd.DataFrame]):
+    def process_all_grids(self, grid_points: Dict[tuple, pd.DataFrame], produce_dem: bool):
         """处理所有网格"""
         self.logger.info("开始执行网格处理")
         for grid_id in grid_points.keys():
@@ -71,7 +81,8 @@ class ODMProcessMonitor:
             success, error_msg = self.run_odm_with_monitor(
                 grid_dir=grid_dir,
                 grid_id=grid_id,
-                fast_mode=(self.mode == "快拼模式")
+                fast_mode=(self.mode == "快拼模式"),
+                produce_dem=produce_dem
             )
 
             if not success: