修改瓦片的偏移

odm_preprocess.py

@@ -298,8 +298,8 @@ class ImagePreprocessor:
             self.cluster()
             self.filter_isolated_points()
             self.filter_time_group_overlap()
-            center_lat, center_lon = self.calculate_center_coordinates()
             # self.filter_alternate_images()
+            center_lat, center_lon = self.calculate_center_coordinates()
             grid_points, translations = self.divide_grids()
             self.copy_images(grid_points)
             self.logger.info("预处理任务完成")

odm_preprocess_fast.py

@@ -4,10 +4,7 @@ from datetime import timedelta
 from dataclasses import dataclass
 from typing import Dict, Tuple
 import psutil
-
-import matplotlib.pyplot as plt
 import pandas as pd
-from tqdm import tqdm
 
 from filter.cluster_filter import GPSCluster
 from filter.time_group_overlap_filter import TimeGroupOverlapFilter
@@ -20,6 +17,7 @@ from utils.visualizer import FilterVisualizer
 from post_pro.merge_tif import MergeTif
 from post_pro.merge_obj import MergeObj
 from post_pro.merge_laz import MergePly
+from post_pro.conv_obj import ConvertOBJ
 
 
 @dataclass
@@ -187,6 +185,28 @@ class ImagePreprocessor:
         self.visualizer.visualize_filter_step(
             self.gps_points, previous_points, "3-Time Group Overlap")
 
+    def calculate_center_coordinates(self):
+        """计算剩余点的中心经纬度坐标"""
+        mean_lat = self.gps_points['lat'].mean()
+        mean_lon = self.gps_points['lon'].mean()
+        self.logger.info(f"区域中心坐标：纬度 {mean_lat:.6f}, 经度 {mean_lon:.6f}")
+        return mean_lat, mean_lon
+
+    def filter_alternate_images(self):
+        """按时间顺序隔一个删一个图像来降低密度"""
+        previous_points = self.gps_points.copy()
+
+        # 按时间戳排序
+        self.gps_points = self.gps_points.sort_values('date')
+
+        # 保留索引为偶数的行（即隔一个保留一个）
+        self.gps_points = self.gps_points.iloc[::2].reset_index(drop=True)
+
+        self.visualizer.visualize_filter_step(
+            self.gps_points, previous_points, "4-Alternate Images")
+
+        self.logger.info(f"交替过滤后剩余 {len(self.gps_points)} 个点")
+
     def divide_grids(self) -> Tuple[Dict[tuple, pd.DataFrame], Dict[tuple, tuple]]:
         """划分网格
         Returns:
@@ -220,7 +240,7 @@ class ImagePreprocessor:
 
             os.makedirs(output_dir, exist_ok=True)
 
-            for point in tqdm(points, desc=f"复制网格 ({grid_id[0]},{grid_id[1]}) 的图像"):
+            for point in points:
                 src = os.path.join(self.config.image_dir, point["file"])
                 dst = os.path.join(output_dir, point["file"])
                 shutil.copy(src, dst)
@@ -245,7 +265,13 @@ class ImagePreprocessor:
         merger = MergeObj(self.config.output_dir)
         merger.merge_grid_obj(grid_points, translations)
 
-    def post_process(self, successful_grid_points: Dict[tuple, pd.DataFrame], grid_points: Dict[tuple, pd.DataFrame], translations: Dict[tuple, tuple]):
+    def convert_obj(self, grid_points: Dict[tuple, pd.DataFrame], center_lat: float, center_lon: float):
+        """转换OBJ模型"""
+        self.logger.info("开始转换OBJ模型")
+        converter = ConvertOBJ(self.config.output_dir, center_lat, center_lon)
+        converter.convert_grid_obj(grid_points)
+
+    def post_process(self, successful_grid_points: Dict[tuple, pd.DataFrame], grid_points: Dict[tuple, pd.DataFrame], translations: Dict[tuple, tuple], center_lat: float, center_lon: float):
         """后处理：合并或复制处理结果"""
         if len(successful_grid_points) < len(grid_points):
             self.logger.warning(
@@ -256,12 +282,14 @@ class ImagePreprocessor:
         if self.config.mode == "快拼模式":
             self.merge_tif(successful_grid_points, self.config.produce_dem)
         elif self.config.mode == "三维模式":
-            self.merge_ply(successful_grid_points)
+            # self.merge_ply(successful_grid_points)
-            self.merge_obj(successful_grid_points, translations)
+            # self.merge_obj(successful_grid_points, translations)
+            self.convert_obj(successful_grid_points, center_lat, center_lon)
         else:
             self.merge_tif(successful_grid_points, self.config.produce_dem)
-            self.merge_ply(successful_grid_points)
+            # self.merge_ply(successful_grid_points)
-            self.merge_obj(successful_grid_points, translations)
+            # self.merge_obj(successful_grid_points, translations)
+            self.convert_obj(successful_grid_points, center_lat, center_lon)
 
     def process(self):
         """执行完整的预处理流程"""
@@ -270,15 +298,17 @@ class ImagePreprocessor:
             self.cluster()
             self.filter_isolated_points()
             self.filter_time_group_overlap()
+            center_lat, center_lon = self.calculate_center_coordinates()
+            # self.filter_alternate_images()
             grid_points, translations = self.divide_grids()
             # self.copy_images(grid_points)
-            self.logger.info("预处理任务完成")
+            # 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)
             successful_grid_points = grid_points
             self.post_process(successful_grid_points,
-                              grid_points, translations)
+                              grid_points, translations, center_lat, center_lon)
 
         except Exception as e:
             self.logger.error(f"处理过程中发生错误: {str(e)}", exc_info=True)

post_pro/conv_obj.py

@@ -13,17 +13,19 @@ class ConvertOBJ:
         
     def convert_grid_obj(self, grid_points):
         """转换每个网格的OBJ文件为OSGB格式"""
-        os.makedirs(os.path.join(self.output_dir, "osgb"), exist_ok=True)
+        os.makedirs(os.path.join(self.output_dir, "osgb", "Data"), exist_ok=True)
+        tile_infos = []
+        
         for grid_id in grid_points.keys():
             try:
-                self._convert_single_grid(grid_id)
+                tile_info = self._convert_single_grid(grid_id, grid_points)
+                tile_infos.append(tile_info)
             except Exception as e:
                 self.logger.error(f"网格 {grid_id} 转换失败: {str(e)}")
         
-        # 在所有网格处理完成后创建总的metadata.xml
+        self._create_merged_metadata(tile_infos)
-        self._create_merged_metadata()
         
-    def _convert_single_grid(self, grid_id):
+    def _convert_single_grid(self, grid_id, grid_points):
         """转换单个网格的OBJ文件"""
         # 1. 构建相关路径
         grid_name = f"grid_{grid_id[0]}_{grid_id[1]}"
@@ -40,9 +42,24 @@ class ConvertOBJ:
         self.logger.info(f"开始转换网格 {grid_id} 的OBJ文件")
         output_osgb = os.path.join(texturing_dir, "Tile.osgb")
         
+        # 计算当前网格相对于中心点的偏移
+        grid_data = grid_points[grid_id]
+        lats = [point['lat'] for point in grid_data]
+        lons = [point['lon'] for point in grid_data]
+        
+        min_lat = min(lats)
+        min_lon = min(lons)
+        
+        # 计算偏移量（米）
+        offset_x = self._calculate_distance(self.center_lat, self.center_lon, self.center_lat, min_lon)
+        offset_y = self._calculate_distance(self.center_lat, self.center_lon, min_lat, self.center_lon)
+        
+        # 修改转换命令，使用正确的参数格式
         cmd = (
-            f"osgconv --compressed --smooth --fix-transparency -o 0,1,0-0,0,-1 "
+            f"osgconv {obj_file} {output_osgb} "
-            f"{obj_file} {output_osgb}"
+            f"--compressed --smooth --fix-transparency "
+            f"-t {offset_x},{offset_y},0 "  # 使用 -t 参数进行平移
+            f"-o 0,1,0-0,0,-1"
         )
         
         try:
@@ -65,20 +82,82 @@ class ConvertOBJ:
         target_osgb = os.path.join(tile_dir, f"Tile_{grid_id[0]}_{grid_id[1]}.osgb")
         shutil.copy2(output_osgb, target_osgb)
         
-        self.logger.info(f"网格 {grid_id} 转换完成")
+        # 计算当前网格的边界框
+        grid_data = grid_points[grid_id]
+        # 假设grid_data是一个列表，每个元素都是包含lat和lon的字典
+        lats = [point['lat'] for point in grid_data]
+        lons = [point['lon'] for point in grid_data]
         
-    def _create_merged_metadata(self):
+        min_lat = min(lats)
+        max_lat = max(lats)
+        min_lon = min(lons)
+        max_lon = max(lons)
+        
+        # 计算相对于中心点的偏移
+        offset_x = self._calculate_distance(self.center_lat, self.center_lon, self.center_lat, min_lon)
+        offset_y = self._calculate_distance(self.center_lat, self.center_lon, min_lat, self.center_lon)
+        
+        tile_info = {
+            'id': f"{grid_id[0]}_{grid_id[1]}",
+            'bounds': {
+                'min_lat': min_lat,
+                'max_lat': max_lat,
+                'min_lon': min_lon,
+                'max_lon': max_lon
+            },
+            'offset': (offset_x, offset_y)
+        }
+        return tile_info
+
+    def _calculate_distance(self, lat1, lon1, lat2, lon2):
+        """计算两点间的距离（米）"""
+        from math import sin, cos, sqrt, atan2, radians
+        R = 6371000  # 地球半径（米）
+        
+        lat1, lon1, lat2, lon2 = map(radians, [lat1, lon1, lat2, lon2])
+        dlat = lat2 - lat1
+        dlon = lon2 - lon1
+        
+        a = sin(dlat/2)**2 + cos(lat1) * cos(lat2) * sin(dlon/2)**2
+        c = 2 * atan2(sqrt(a), sqrt(1-a))
+        return R * c
+
+    def _create_merged_metadata(self, tile_infos):
         """创建合并后的metadata.xml文件"""
         metadata_content = f"""<?xml version="1.0" encoding="utf-8"?>
 <ModelMetadata version="1">
-    <!--Spatial Reference System-->
     <SRS>EPSG:4326</SRS>
-    <!--Origin in Spatial Reference System-->
     <SRSOrigin>{self.center_lon},{self.center_lat},0.000000</SRSOrigin>
+    <TileStructure>
+        <RootNode>
+            <BoundingBox>
+                <MinLat>{min([t['bounds']['min_lat'] for t in tile_infos])}</MinLat>
+                <MaxLat>{max([t['bounds']['max_lat'] for t in tile_infos])}</MaxLat>
+                <MinLon>{min([t['bounds']['min_lon'] for t in tile_infos])}</MinLon>
+                <MaxLon>{max([t['bounds']['max_lon'] for t in tile_infos])}</MaxLon>
+            </BoundingBox>
+            <Tiles>"""
+        
+        for tile in tile_infos:
+            metadata_content += f"""
+                    <Tile id="{tile['id']}">
+                        <Offset>{tile['offset'][0]},{tile['offset'][1]},0</Offset>
+                        <BoundingBox>
+                            <MinLat>{tile['bounds']['min_lat']}</MinLat>
+                            <MaxLat>{tile['bounds']['max_lat']}</MaxLat>
+                            <MinLon>{tile['bounds']['min_lon']}</MinLon>
+                            <MaxLon>{tile['bounds']['max_lon']}</MaxLon>
+                        </BoundingBox>
+                    </Tile>"""
+        
+        metadata_content += """
+                </Tiles>
+            </RootNode>
+        </TileStructure>
         <Texture>
             <ColorSource>Visible</ColorSource>
         </Texture>
-</ModelMetadata>"""
+    </ModelMetadata>"""
         
         metadata_file = os.path.join(self.output_dir, "osgb", "metadata.xml")
         with open(metadata_file, 'w', encoding='utf-8') as f: