import os import logging import numpy as np from typing import Dict import pandas as pd class MergeObj: def __init__(self, output_dir: str): self.output_dir = output_dir self.logger = logging.getLogger('UAV_Preprocess.MergeObj') def read_obj(self, file_path): """读取.obj文件，返回顶点列表和面列表""" vertices = [] faces = [] with open(file_path, 'r') as file: for line in file: parts = line.split() if len(parts) == 0: continue if parts[0] == 'v': # 顶点 vertices.append([float(parts[1]), float(parts[2]), float(parts[3])]) elif parts[0] == 'f': # 面 faces.append([int(parts[1].split('/')[0]), int(parts[2].split('/')[0]), int(parts[3].split('/')[0])]) return vertices, faces def write_obj(self, file_path, vertices, faces): """将修改后的顶点和面列表写入到.obj文件""" with open(file_path, 'w') as file: for vertex in vertices: file.write(f"v {vertex[0]} {vertex[1]} {vertex[2]}\n") for face in faces: file.write(f"f {face[0]} {face[1]} {face[2]}\n") def translate_vertices(self, vertices, translation): """平移顶点""" return [[v[0] + translation[0], v[1] + translation[1], v[2] + translation[2]] for v in vertices] def merge_two_objs(self, obj1_path: str, obj2_path: str, output_path: str, translation): """合并两个OBJ文件""" try: self.logger.info(f"开始合并OBJ模型:\n输入1: {obj1_path}\n输入2: {obj2_path}") # 检查输入文件是否存在 if not os.path.exists(obj1_path) or not os.path.exists(obj2_path): raise FileNotFoundError("输入模型文件不存在") # 读取两个obj文件 vertices1, faces1 = self.read_obj(obj1_path) vertices2, faces2 = self.read_obj(obj2_path) # 平移第二个模型的顶点 vertices2_translated = self.translate_vertices(vertices2, translation) # 合并顶点和面 all_vertices = vertices1 + vertices2_translated all_faces = faces1 + [[f[0] + len(vertices1), f[1] + len(vertices1), f[2] + len(vertices1)] for f in faces2] # 写入合并后的obj文件 self.write_obj(output_path, all_vertices, all_faces) self.logger.info(f"模型合并成功，已保存至: {output_path}") except Exception as e: self.logger.error(f"合并OBJ模型时发生错误: {str(e)}", exc_info=True) raise def calculate_translation(self, grid_idx: int, grid_points: Dict[int, pd.DataFrame], grid_size: float) -> tuple: """根据网格索引和大小计算平移量""" # 从grid_points中获取网格划分器 grid_divider = grid_points.get('grid_divider', None) if grid_divider is None: # 如果没有grid_divider，使用默认的计算方式 row = grid_idx // 2 col = grid_idx % 2 else: # 使用grid_divider获取正确的网格坐标 row, col = grid_divider.get_grid_coordinates(grid_idx) # 计算平移量，考虑到重叠 overlap_factor = 0.9 # 重叠因子，与grid_divider中的overlap对应 x_translation = col * grid_size * overlap_factor y_translation = row * grid_size * overlap_factor self.logger.info( f"网格 {grid_idx} 的位置: 行={row}, 列={col}" ) return (x_translation, y_translation, 0) # z轴不需要平移 def merge_grid_obj(self, grid_points: Dict[int, pd.DataFrame], grid_size: float = 500): """合并所有网格的OBJ模型""" self.logger.info("开始合并所有网格的OBJ模型") if len(grid_points) < 2: self.logger.info("只有一个网格，无需合并") return input_obj1, input_obj2 = None, None merge_count = 0 try: for grid_idx, points in grid_points.items(): if grid_idx == 'grid_divider': # 跳过grid_divider对象 continue grid_obj = os.path.join( self.output_dir, f"grid_{grid_idx + 1}", "project", "odm_texturing", "odm_textured_model_geo.obj" ) if not os.path.exists(grid_obj): self.logger.warning(f"网格 {grid_idx + 1} 的OBJ文件不存在: {grid_obj}") continue if input_obj1 is None: input_obj1 = grid_obj self.logger.info(f"设置第一个输入OBJ: {input_obj1}") else: input_obj2 = grid_obj output_obj = os.path.join(self.output_dir, f"merged_model_{merge_count}.obj") # 计算当前网格的平移量 translation = self.calculate_translation(grid_idx, grid_points, grid_size) self.logger.info( f"开始合并第 {merge_count + 1} 次:\n" f"平移量: {translation}\n" f"输出: {output_obj}" ) self.merge_two_objs(input_obj1, input_obj2, output_obj, translation) merge_count += 1 input_obj1 = output_obj input_obj2 = None # 最后的结果重命名为merged_model.obj final_output = os.path.join(self.output_dir, "merged_model.obj") if os.path.exists(input_obj1) and input_obj1 != final_output: os.rename(input_obj1, final_output) self.logger.info( f"OBJ模型合并完成，共执行 {merge_count} 次合并，" f"最终输出文件: {final_output}" ) except Exception as e: self.logger.error(f"OBJ模型合并过程中发生错误: {str(e)}", exc_info=True) raise if __name__ == "__main__": import sys sys.path.append(os.path.dirname( os.path.dirname(os.path.abspath(__file__)))) from utils.logger import setup_logger import pandas as pd # 设置输出目录和日志 output_dir = r"G:\ODM_output\1009" setup_logger(output_dir) # 构造测试用的grid_points字典 # 假设我们有两个网格，每个网格包含一些GPS点的DataFrame grid_points = { 0: pd.DataFrame({ 'latitude': [39.9, 39.91], 'longitude': [116.3, 116.31], 'altitude': [100, 101] }), 1: pd.DataFrame({ 'latitude': [39.92, 39.93], 'longitude': [116.32, 116.33], 'altitude': [102, 103] }) } # 创建MergeObj实例并执行合并 merge_obj = MergeObj(output_dir) merge_obj.merge_grid_obj(grid_points)