修复merge_tif bug，TODO: 加入conv_obj2代码（切分obj）

odm_preprocess.py

@@ -250,11 +250,11 @@ class ImagePreprocessor:
             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], produce_dem: bool):
+    def merge_tif(self, grid_points: Dict[tuple, pd.DataFrame], mode: str, 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, produce_dem)
+        merger.merge_all_tifs(grid_points, mode)
 
     def merge_ply(self, grid_points: Dict[tuple, pd.DataFrame]):
         """合并所有网格的PLY点云"""
@@ -282,18 +282,19 @@ class ImagePreprocessor:
                 f"将只合并成功处理的 {len(successful_grid_points)} 个网格"
             )
 
-        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_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)
-        else:
-            self.merge_tif(successful_grid_points, self.config.produce_dem)
+        # if self.config.mode == "快拼模式":
+        self.merge_tif(successful_grid_points, self.config.mode,
+                       self.config.produce_dem)
+        if self.config.mode == "三维模式":
+            # 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)
+        # 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)
 
     def process(self):
         """执行完整的预处理流程"""

odm_preprocess_fast.py

@@ -17,7 +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
+from post_pro.conv_obj2 import ConvertOBJ
 
 
 @dataclass
@@ -44,6 +44,7 @@ class PreprocessConfig:
     grid_size: float = 500
     # 几个pipline过程是否开启
     mode: str = "快拼模式"
+    accuracy: str = "medium"
     produce_dem: bool = False
 
 
@@ -223,6 +224,8 @@ class ImagePreprocessor:
             self.gps_points
         )
         grid_divider.visualize_grids(self.gps_points, grids)
+        if len(grids) >= 20:
+            self.logger.warning("网格数量已超过20, 需要人工调整分区")
 
         return grid_points, translations
 
@@ -302,6 +305,9 @@ class ImagePreprocessor:
             # self.copy_images(grid_points)
             # 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, self.config.accuracy)
+
             # successful_grid_points = self.odm_monitor.process_all_grids(
             #     grid_points, self.config.produce_dem)
             successful_grid_points = grid_points

post_pro/conv_obj2.py

@@ -0,0 +1,262 @@
+import os
+import subprocess
+import json
+import shutil
+import logging
+from pyproj import Transformer
+import cv2
+
+
+class ConvertOBJ:
+    def __init__(self, output_dir: str):
+        self.output_dir = output_dir
+        # 用于存储所有grid的UTM范围
+        self.ref_east = float('inf')
+        self.ref_north = float('inf')
+        # 初始化UTM到WGS84的转换器
+        self.transformer = Transformer.from_crs(
+            "EPSG:32649", "EPSG:4326", always_xy=True)
+        self.logger = logging.getLogger('UAV_Preprocess.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", "Data"), exist_ok=True)
+
+        # 以第一个grid的UTM坐标作为参照系
+        first_grid_id = list(grid_points.keys())[0]
+        first_grid_dir = os.path.join(
+            self.output_dir,
+            f"grid_{first_grid_id[0]}_{first_grid_id[1]}",
+            "project"
+        )
+        log_file = os.path.join(
+            first_grid_dir, "odm_orthophoto", "odm_orthophoto_log.txt")
+        self.ref_east, self.ref_north = self.read_utm_offset(log_file)
+
+        for grid_id in grid_points.keys():
+            try:
+                self._convert_single_grid(grid_id, grid_points)
+            except Exception as e:
+                self.logger.error(f"网格 {grid_id} 转换失败: {str(e)}")
+
+        self._create_merged_metadata()
+
+    def _convert_single_grid(self, grid_id, grid_points):
+        """转换单个网格的OBJ文件"""
+        # 构建相关路径
+        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")
+        split_obj_dir = os.path.join(texturing_dst_dir, "split_obj")
+        opensfm_dir = os.path.join(project_dir, "opensfm")
+        log_file = os.path.join(
+            project_dir, "odm_orthophoto", "odm_orthophoto_log.txt")
+        os.makedirs(texturing_dst_dir, exist_ok=True)
+
+        # 修改obj文件z坐标的值
+        min_25d_z = self.get_min_z_from_obj(os.path.join(
+            project_dir, 'odm_texturing_25d', 'odm_textured_model_geo.obj'))
+        self.modify_z_in_obj(texturing_dir, min_25d_z)
+
+        # 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(
+            texturing_dir, texturing_dst_dir, utm_offset)
+        self.downsample_texture(texturing_dir, texturing_dst_dir)
+
+        # 将obj文件进行切片
+        self.logger.info(f"开始切片网格 {grid_id} 的OBJ文件")
+        os.makedirs(split_obj_dir)
+        cmd = (
+            f"D:\software\Obj2Tiles\Obj2Tiles.exe --stage Splitting --lods 1 --divisions 3 "
+            f"{modified_obj} {split_obj_dir}"
+        )
+        subprocess.run(cmd, check=True)
+
+        # 执行格式转换，Linux下osgconv有问题，记得注释掉
+        self.logger.info(f"开始转换网格 {grid_id} 的OBJ文件")
+        # 先获取split_obj_dir下的所有obj文件
+        obj_lod_dir = os.path.join(split_obj_dir, "LOD-0")
+        obj_files = [f for f in os.listdir(
+            obj_lod_dir) if f.endswith('.obj')]
+        for obj_file in obj_files:
+            obj_path = os.path.join(obj_lod_dir, obj_file)
+            osgb_file = os.path.splitext(obj_file)[0] + '.osgb'
+            osgb_path = os.path.join(split_obj_dir, osgb_file)
+            # 执行 osgconv 命令
+            subprocess.run(['osgconv', obj_path, osgb_path], check=True)
+
+        # 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")
+        for obj_file in obj_files:
+            obj_file_name = os.path.splitext(obj_file)[0]
+            tile_dirs = os.path.join(data_dir, f"{obj_file_name}")
+            os.makedirs(tile_dirs, exist_ok=True)
+            shutil.copy2(os.path.join(split_obj_dir, obj_file_name+".osgb"), tile_dirs)
+
+    def _create_merged_metadata(self):
+        """创建合并后的metadata.xml文件"""
+        # 转换为WGS84经纬度
+        center_lon, center_lat = self.transformer.transform(
+            self.ref_east, self.ref_north)
+        metadata_content = f"""<?xml version="1.0" encoding="utf-8"?>
+<ModelMetadata version="1">
+    <SRS>EPSG:4326</SRS>
+    <SRSOrigin>{center_lon},{center_lat},0</SRSOrigin>
+        <Texture>
+            <ColorSource>Visible</ColorSource>
+        </Texture>
+    </ModelMetadata>"""
+
+        metadata_file = os.path.join(self.output_dir, "osgb", "metadata.xml")
+        with open(metadata_file, 'w', encoding='utf-8') as f:
+            f.write(metadata_content)
+
+    def read_utm_offset(self, log_file: str) -> tuple:
+        """读取UTM偏移量"""
+        try:
+            east_offset = None
+            north_offset = None
+
+            with open(log_file, 'r') as f:
+                lines = f.readlines()
+                for i, line in enumerate(lines):
+                    if 'utm_north_offset' in line and i + 1 < len(lines):
+                        north_offset = float(lines[i + 1].strip())
+                    elif 'utm_east_offset' in line and i + 1 < len(lines):
+                        east_offset = float(lines[i + 1].strip())
+
+            if east_offset is None or north_offset is None:
+                raise ValueError("未找到UTM偏移量")
+
+            return east_offset, north_offset
+        except Exception as e:
+            self.logger.error(f"读取UTM偏移量时发生错误: {str(e)}")
+            raise
+
+    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_modified.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
+        self.logger.info(
+            f"UTM坐标偏移：{east_offset - self.ref_east}, {north_offset - self.ref_north}")
+
+        try:
+            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
+                        parts = line.strip().split()
+                        # 使用相对于整体最小UTM坐标的偏移
+                        x = float(parts[1]) + (east_offset - self.ref_east)
+                        y = float(parts[2]) + (north_offset - self.ref_north)
+                        z = float(parts[3])
+                        f_out.write(f'v {x:.6f} {z:.6f} {-y:.6f}\n')
+                    elif line.startswith('vn '):  # 处理法线向量
+                        parts = line.split()
+                        nx = float(parts[1])
+                        ny = float(parts[2])
+                        nz = float(parts[3])
+                        # 同步反转法线的 Y 轴
+                        new_line = f"vn {nx} {nz} {-ny}\n"
+                        f_out.write(new_line)
+                    else:
+                        # 其他行直接写入
+                        f_out.write(line)
+
+            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")
+
+    def get_min_z_from_obj(self, file_path):
+        min_z = float('inf')  # 初始值设为无穷大
+        with open(file_path, 'r') as obj_file:
+            for line in obj_file:
+                # 检查每一行是否是顶点定义（以 'v ' 开头）
+                if line.startswith('v '):
+                    # 获取顶点坐标
+                    parts = line.split()
+                    # 将z值转换为浮动数字
+                    z = float(parts[3])
+                    # 更新最小z值
+                    if z < min_z:
+                        min_z = z
+        return min_z
+
+    def modify_z_in_obj(self, texturing_dir, min_25d_z):
+        obj_file = os.path.join(texturing_dir, 'odm_textured_model_geo.obj')
+        output_file = os.path.join(
+            texturing_dir, 'odm_textured_model_modified.obj')
+        with open(obj_file, 'r') as f_in, open(output_file, 'w') as f_out:
+            for line in f_in:
+                if line.startswith('v '):  # 顶点坐标行
+                    parts = line.strip().split()
+                    x = float(parts[1])
+                    y = float(parts[2])
+                    z = float(parts[3])
+
+                    if z < min_25d_z:
+                        z = min_25d_z
+
+                    f_out.write(f"v {x} {y} {z}\n")
+                else:
+                    f_out.write(line)

post_pro/merge_tif.py

@@ -192,7 +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], produce_dem: bool):
+    def merge_all_tifs(self, grid_points: Dict[tuple, pd.DataFrame], mode: str):
         """合并所有产品（正射影像、DSM和DTM）"""
         try:
             products = [
@@ -204,7 +204,7 @@ class MergeTif:
                 },
 
             ]
-            if produce_dem:
+            if mode == '三维模式':
                 products.append(
                     {
                         'name': 'DSM',

utils/odm_monitor.py

@@ -182,7 +182,7 @@ class ODMProcessMonitor:
 
                 if self.mode == "快拼模式":
                     docker_command += (
-                        # f"--fast-orthophoto "
+                        f"--fast-orthophoto "
                         f"--skip-3dmodel "
                     )
                 # elif self.mode == "三维模式":