obj到osgb的坐标系变换

main.py

@@ -1,6 +1,6 @@
 import argparse
 from datetime import timedelta
-from odm_preprocess import PreprocessConfig, ImagePreprocessor
+from odm_preprocess_fast import PreprocessConfig, ImagePreprocessor
 
 def parse_args():
     parser = argparse.ArgumentParser(description='ODM预处理工具')

odm_preprocess.py

@@ -265,13 +265,13 @@ class ImagePreprocessor:
         merger = MergeObj(self.config.output_dir)
         merger.merge_grid_obj(grid_points, translations)
 
-    def convert_obj(self, grid_points: Dict[tuple, pd.DataFrame], center_lat: float, center_lon: float):
+    def convert_obj(self, grid_points: Dict[tuple, pd.DataFrame]):
         """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 = ConvertOBJ(self.config.output_dir)
         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):
+    def post_process(self, successful_grid_points: Dict[tuple, pd.DataFrame], grid_points: Dict[tuple, pd.DataFrame], translations: Dict[tuple, tuple]):
         """后处理：合并或复制处理结果"""
         if len(successful_grid_points) < len(grid_points):
             self.logger.warning(
@@ -284,12 +284,12 @@ class ImagePreprocessor:
         elif self.config.mode == "三维模式":
             # self.merge_ply(successful_grid_points)
             # self.merge_obj(successful_grid_points, translations)
-            self.convert_obj(successful_grid_points, center_lat, center_lon)
+            self.convert_obj(successful_grid_points)
         else:
             self.merge_tif(successful_grid_points, self.config.produce_dem)
             # self.merge_ply(successful_grid_points)
             # self.merge_obj(successful_grid_points, translations)
-            self.convert_obj(successful_grid_points, center_lat, center_lon)
+            self.convert_obj(successful_grid_points)
 
     def process(self):
         """执行完整的预处理流程"""
@@ -297,9 +297,6 @@ class ImagePreprocessor:
             self.extract_gps()
             self.cluster()
             self.filter_isolated_points()
-            self.filter_time_group_overlap()
-            # 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")
@@ -308,7 +305,7 @@ class ImagePreprocessor:
                 grid_points, self.config.produce_dem)
 
             self.post_process(successful_grid_points,
-                              grid_points, translations, center_lat, center_lon)
+                              grid_points, translations)
 
         except Exception as e:
             self.logger.error(f"处理过程中发生错误: {str(e)}", exc_info=True)

odm_preprocess_fast.py

@@ -265,13 +265,13 @@ class ImagePreprocessor:
         merger = MergeObj(self.config.output_dir)
         merger.merge_grid_obj(grid_points, translations)
 
-    def convert_obj(self, grid_points: Dict[tuple, pd.DataFrame], center_lat: float, center_lon: float):
+    def convert_obj(self, grid_points: Dict[tuple, pd.DataFrame]):
         """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 = ConvertOBJ(self.config.output_dir)
         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):
+    def post_process(self, successful_grid_points: Dict[tuple, pd.DataFrame], grid_points: Dict[tuple, pd.DataFrame], translations: Dict[tuple, tuple]):
         """后处理：合并或复制处理结果"""
         if len(successful_grid_points) < len(grid_points):
             self.logger.warning(
@@ -284,12 +284,12 @@ class ImagePreprocessor:
         elif self.config.mode == "三维模式":
             # self.merge_ply(successful_grid_points)
             # self.merge_obj(successful_grid_points, translations)
-            self.convert_obj(successful_grid_points, center_lat, center_lon)
+            self.convert_obj(successful_grid_points)
         else:
             self.merge_tif(successful_grid_points, self.config.produce_dem)
             # self.merge_ply(successful_grid_points)
             # self.merge_obj(successful_grid_points, translations)
-            self.convert_obj(successful_grid_points, center_lat, center_lon)
+            self.convert_obj(successful_grid_points)
 
     def process(self):
         """执行完整的预处理流程"""
@@ -297,9 +297,6 @@ class ImagePreprocessor:
             self.extract_gps()
             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")
@@ -308,7 +305,7 @@ class ImagePreprocessor:
             #     grid_points, self.config.produce_dem)
             successful_grid_points = grid_points
             self.post_process(successful_grid_points,
-                              grid_points, translations, center_lat, center_lon)
+                              grid_points, translations)
 
         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

@@ -4,13 +4,12 @@ import json
 import shutil
 import logging
 from pyproj import Transformer
+import cv2
 
 
 class ConvertOBJ:
-    def __init__(self, output_dir: str, center_lat: float, center_lon: float):
+    def __init__(self, output_dir: str):
         self.output_dir = output_dir
-        self.center_lat = center_lat
-        self.center_lon = center_lon
         # 用于存储所有grid的UTM范围
         self.min_east = float('inf')
         self.min_north = float('inf')
@@ -59,25 +58,24 @@ class ConvertOBJ:
         grid_name = f"grid_{grid_id[0]}_{grid_id[1]}"
         project_dir = os.path.join(self.output_dir, grid_name, "project")
         texturing_dir = os.path.join(project_dir, "odm_texturing")
+        texturing_dst_dir = os.path.join(project_dir, "odm_texturing_dst")
         opensfm_dir = os.path.join(project_dir, "opensfm")
-        obj_file = os.path.join(texturing_dir, "odm_textured_model_geo.obj")
         log_file = os.path.join(
             project_dir, "odm_orthophoto", "odm_orthophoto_log.txt")
-        if not os.path.exists(obj_file):
+        os.makedirs(texturing_dst_dir, exist_ok=True)
-            raise FileNotFoundError(f"找不到OBJ文件: {obj_file}")
 
-        # 2. 读取UTM偏移量，修改obj文件顶点坐标
+        # 2. 在新文件夹下，利用UTM偏移量，修改obj文件顶点坐标，纹理文件下采样
         utm_offset = self.read_utm_offset(log_file)
         modified_obj = self.modify_obj_coordinates(
-            obj_file, utm_offset)
+            texturing_dir, texturing_dst_dir, utm_offset)
+        self.downsample_texture(texturing_dir, texturing_dst_dir)
 
         # 3. 执行格式转换
         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")
+        output_osgb = os.path.join(texturing_dst_dir, "Tile.osgb")
         cmd = (
             f"osgconv {modified_obj} {output_osgb} "
             f"--compressed --smooth --fix-transparency "
-            # f"-o -90-1,0,0"
         )
         self.logger.info(f"执行osgconv命令：{cmd}")
 
@@ -86,63 +84,33 @@ class ConvertOBJ:
         except subprocess.CalledProcessError as e:
             raise RuntimeError(f"OSGB转换失败: {str(e)}")
 
-        # 4. 读取地理信息
+        # 4. 读取地理信息，计算中心点坐标
         ref_lla_file = os.path.join(opensfm_dir, "reference_lla.json")
         with open(ref_lla_file, 'r') as f:
             ref_lla = json.load(f)
 
-        # 5. 创建OSGB目录结构
+        # 5. 创建OSGB目录结构，复制文件
         osgb_base_dir = os.path.join(self.output_dir, "osgb")
         data_dir = os.path.join(osgb_base_dir, "Data")
         tile_dir = os.path.join(data_dir, f"Tile_{grid_id[0]}_{grid_id[1]}")
         os.makedirs(tile_dir, exist_ok=True)
-
-        # 5. 复制OSGB文件
         target_osgb = os.path.join(
             tile_dir, f"Tile_{grid_id[0]}_{grid_id[1]}.osgb")
         shutil.copy2(output_osgb, target_osgb)
 
-        # 计算当前网格的边界框
+        return ref_lla
-        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]
-
-        min_lat = min(lats)
-        max_lat = max(lats)
-        min_lon = min(lons)
-        max_lon = max(lons)
-
-        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
-            },
-        }
-        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"""
+        center_lon = sum(ref_lla['longitude']
+                         for ref_lla in tile_infos) / len(tile_infos)
+        center_lat = sum(ref_lla['latitude']
+                         for ref_lla in tile_infos) / len(tile_infos)
+
         metadata_content = f"""<?xml version="1.0" encoding="utf-8"?>
 <ModelMetadata version="1">
     <SRS>EPSG:4326</SRS>
-    <SRSOrigin>{self.center_lon},{self.center_lat},0.000000</SRSOrigin>
+    <SRSOrigin>{center_lon},{center_lat},0.000000</SRSOrigin>
         <Texture>
             <ColorSource>Visible</ColorSource>
         </Texture>
@@ -174,13 +142,19 @@ class ConvertOBJ:
             self.logger.error(f"读取UTM偏移量时发生错误: {str(e)}")
             raise
 
-    def modify_obj_coordinates(self, obj_file: str, utm_offset: tuple) -> str:
+    def modify_obj_coordinates(self, texturing_dir: str, texturing_dst_dir: str, utm_offset: tuple) -> str:
         """修改obj文件中的顶点坐标，使用相对坐标系"""
+        obj_file = os.path.join(texturing_dir, "odm_textured_model_geo.obj")
+        obj_dst_file = os.path.join(
+            texturing_dst_dir, "odm_textured_model_geo_utm.obj")
+        if not os.path.exists(obj_file):
+            raise FileNotFoundError(f"找不到OBJ文件: {obj_file}")
+        shutil.copy2(os.path.join(texturing_dir, "odm_textured_model_geo.mtl"),
+                     os.path.join(texturing_dst_dir, "odm_textured_model_geo.mtl"))
         east_offset, north_offset = utm_offset
-        output_obj = obj_file.replace('.obj', '_utm.obj')
 
         try:
-            with open(obj_file, 'r') as f_in, open(output_obj, 'w') as f_out:
+            with open(obj_file, 'r') as f_in, open(obj_dst_file, 'w') as f_out:
                 for line in f_in:
                     if line.startswith('v '):
                         # 处理顶点坐标行
@@ -189,12 +163,60 @@ class ConvertOBJ:
                         x = float(parts[1]) + (east_offset - self.min_east)
                         y = float(parts[2]) + (north_offset - self.min_north)
                         z = float(parts[3])
-                        f_out.write(f'v {x:.6f} {z:.6f} {y:.6f}\n')
+                        f_out.write(f'v {x:.6f} {z:.6f} {-y:.6f}\n')
                     else:
                         # 其他行直接写入
                         f_out.write(line)
 
-            return output_obj
+            return obj_dst_file
         except Exception as e:
             self.logger.error(f"修改obj坐标时发生错误: {str(e)}")
             raise
+
+    def downsample_texture(self, src_dir: str, dst_dir: str):
+        """复制并重命名纹理文件，对大于100MB的文件进行多次下采样，直到文件小于100MB
+        Args:
+            src_dir: 源纹理目录
+            dst_dir: 目标纹理目录
+        """
+        for file in os.listdir(src_dir):
+            if file.lower().endswith(('.png')):
+                src_path = os.path.join(src_dir, file)
+                dst_path = os.path.join(dst_dir, file)
+
+                # 检查文件大小（以字节为单位）
+                file_size = os.path.getsize(src_path)
+                if file_size <= 100 * 1024 * 1024:  # 如果文件小于等于100MB，直接复制
+                    shutil.copy2(src_path, dst_path)
+                else:
+                    # 文件大于100MB，进行下采样
+                    img = cv2.imread(src_path, cv2.IMREAD_UNCHANGED)
+                    if_first_ds = True
+                    while file_size > 100 * 1024 * 1024:  # 大于100MB
+                        self.logger.info(f"纹理文件 {file} 大于100MB，进行下采样")
+
+                        if if_first_ds:
+                            # 计算新的尺寸（长宽各变为1/4）
+                            new_size = (img.shape[1] // 4,
+                                        img.shape[0] // 4)  # 逐步减小尺寸
+                            # 使用双三次插值进行下采样
+                            resized_img = cv2.resize(
+                                img, new_size, interpolation=cv2.INTER_CUBIC)
+                            if_first_ds = False
+                        else:
+                            # 计算新的尺寸（长宽各变为1/2）
+                            new_size = (img.shape[1] // 2,
+                                        img.shape[0] // 2)  # 逐步减小尺寸
+                            # 使用双三次插值进行下采样
+                            resized_img = cv2.resize(
+                                img, new_size, interpolation=cv2.INTER_CUBIC)
+
+                        # 更新文件路径为下采样后的路径
+                        cv2.imwrite(dst_path, resized_img, [
+                                    cv2.IMWRITE_PNG_COMPRESSION, 9])
+
+                        # 更新文件大小和图像
+                        file_size = os.path.getsize(dst_path)
+                        img = cv2.imread(dst_path, cv2.IMREAD_UNCHANGED)
+                        self.logger.info(
+                            f"下采样后文件大小: {file_size / (1024 * 1024):.2f} MB")