更新笛卡尔坐标
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@ -208,7 +208,11 @@ class ImagePreprocessor:
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self.gps_points, grid_size=self.config.grid_size
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)
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grid_points = grid_divider.assign_to_grids(self.gps_points, grids)
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self.logger.info(f"成功划分为 {len(grid_points)} 个网格")
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# 将grid_divider添加到grid_points中
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grid_points['grid_divider'] = grid_divider
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self.logger.info(f"成功划分为 {len(grid_points)-1} 个网格") # -1是因为包含了grid_divider
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# 生成image_groups.txt文件
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try:
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@ -10,50 +10,89 @@ class MergeObj:
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self.output_dir = output_dir
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self.logger = logging.getLogger('UAV_Preprocess.MergeObj')
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def merge_two_objs(self, obj1_path: str, obj2_path: str, output_path: str):
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"""使用Open3D合并两个OBJ文件"""
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try:
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self.logger.info("开始合并OBJ模型")
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self.logger.info(f"输入模型1: {obj1_path}")
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self.logger.info(f"输入模型2: {obj2_path}")
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self.logger.info(f"输出模型: {output_path}")
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def read_obj(self, file_path):
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"""读取.obj文件，返回顶点列表和面列表"""
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vertices = []
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faces = []
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with open(file_path, 'r') as file:
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for line in file:
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parts = line.split()
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if len(parts) == 0:
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continue
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if parts[0] == 'v': # 顶点
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vertices.append([float(parts[1]), float(parts[2]), float(parts[3])])
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elif parts[0] == 'f': # 面
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faces.append([int(parts[1].split('/')[0]), int(parts[2].split('/')[0]), int(parts[3].split('/')[0])])
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return vertices, faces
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def write_obj(self, file_path, vertices, faces):
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"""将修改后的顶点和面列表写入到.obj文件"""
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with open(file_path, 'w') as file:
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for vertex in vertices:
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file.write(f"v {vertex[0]} {vertex[1]} {vertex[2]}\n")
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for face in faces:
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file.write(f"f {face[0]} {face[1]} {face[2]}\n")
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def translate_vertices(self, vertices, translation):
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"""平移顶点"""
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return [[v[0] + translation[0], v[1] + translation[1], v[2] + translation[2]] for v in vertices]
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def merge_two_objs(self, obj1_path: str, obj2_path: str, output_path: str, translation):
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"""合并两个OBJ文件"""
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try:
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self.logger.info(f"开始合并OBJ模型:\n输入1: {obj1_path}\n输入2: {obj2_path}")
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# 检查输入文件是否存在
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if not os.path.exists(obj1_path) or not os.path.exists(obj2_path):
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raise FileNotFoundError("输入模型文件不存在")
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# 读取OBJ文件
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mesh1 = o3d.io.read_triangle_mesh(obj1_path)
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mesh2 = o3d.io.read_triangle_mesh(obj2_path)
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if mesh1.is_empty() or mesh2.is_empty():
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raise ValueError("无法读取OBJ文件或文件为空")
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# # 计算并对齐中心点
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# center1 = mesh1.get_center()
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# center2 = mesh2.get_center()
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# translation_vector = center2 - center1
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# mesh2.translate(translation_vector)
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# 不对齐，直接合并网格
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combined_mesh = mesh1 + mesh2
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# 优化合并后的网格
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combined_mesh.remove_duplicated_vertices()
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combined_mesh.remove_duplicated_triangles()
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combined_mesh.compute_vertex_normals()
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# 保存合并后的模型
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if not o3d.io.write_triangle_mesh(output_path, combined_mesh):
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raise RuntimeError("保存合并后的模型失败")
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# 读取两个obj文件
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vertices1, faces1 = self.read_obj(obj1_path)
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vertices2, faces2 = self.read_obj(obj2_path)
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# 平移第二个模型的顶点
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vertices2_translated = self.translate_vertices(vertices2, translation)
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# 合并顶点和面
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all_vertices = vertices1 + vertices2_translated
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all_faces = faces1 + [[f[0] + len(vertices1), f[1] + len(vertices1), f[2] + len(vertices1)] for f in faces2]
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# 写入合并后的obj文件
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self.write_obj(output_path, all_vertices, all_faces)
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self.logger.info(f"模型合并成功，已保存至: {output_path}")
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except Exception as e:
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self.logger.error(f"合并OBJ模型时发生错误: {str(e)}", exc_info=True)
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raise
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def merge_grid_obj(self, grid_points: Dict[int, pd.DataFrame]):
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def calculate_translation(self, grid_idx: int, grid_points: Dict[int, pd.DataFrame], grid_size: float) -> tuple:
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"""根据网格索引和大小计算平移量"""
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# 从grid_points中获取网格划分器
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grid_divider = grid_points.get('grid_divider', None)
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if grid_divider is None:
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# 如果没有grid_divider，使用默认的计算方式
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row = grid_idx // 2
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col = grid_idx % 2
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else:
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# 使用grid_divider获取正确的网格坐标
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row, col = grid_divider.get_grid_coordinates(grid_idx)
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# 计算平移量，考虑到重叠
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overlap_factor = 0.9 # 重叠因子，与grid_divider中的overlap对应
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x_translation = col * grid_size * overlap_factor
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y_translation = row * grid_size * overlap_factor
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self.logger.info(
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f"网格 {grid_idx} 的位置: 行={row}, 列={col}"
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)
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return (x_translation, y_translation, 0) # z轴不需要平移
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def merge_grid_obj(self, grid_points: Dict[int, pd.DataFrame], grid_size: float = 500):
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"""合并所有网格的OBJ模型"""
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self.logger.info("开始合并所有网格的OBJ模型")
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@ -66,17 +105,19 @@ class MergeObj:
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try:
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for grid_idx, points in grid_points.items():
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if grid_idx == 'grid_divider': # 跳过grid_divider对象
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continue
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grid_obj = os.path.join(
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self.output_dir,
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f"grid_{grid_idx + 1}",
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"project",
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"odm_texturing_25d",
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"odm_texturing",
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"odm_textured_model_geo.obj"
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)
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if not os.path.exists(grid_obj):
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self.logger.warning(
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f"网格 {grid_idx + 1} 的OBJ文件不存在: {grid_obj}")
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self.logger.warning(f"网格 {grid_idx + 1} 的OBJ文件不存在: {grid_obj}")
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continue
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if input_obj1 is None:
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@ -84,25 +125,31 @@ class MergeObj:
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self.logger.info(f"设置第一个输入OBJ: {input_obj1}")
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else:
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input_obj2 = grid_obj
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output_obj = os.path.join(
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self.output_dir, "merged_model.obj")
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output_obj = os.path.join(self.output_dir, f"merged_model_{merge_count}.obj")
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# 计算当前网格的平移量
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translation = self.calculate_translation(grid_idx, grid_points, grid_size)
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self.logger.info(
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f"开始合并第 {merge_count + 1} 次:\n"
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f"输入1: {input_obj1}\n"
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f"输入2: {input_obj2}\n"
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f"平移量: {translation}\n"
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f"输出: {output_obj}"
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)
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self.merge_two_objs(input_obj1, input_obj2, output_obj)
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self.merge_two_objs(input_obj1, input_obj2, output_obj, translation)
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merge_count += 1
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input_obj1 = output_obj
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input_obj2 = None
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# 最后的结果重命名为merged_model.obj
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final_output = os.path.join(self.output_dir, "merged_model.obj")
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if os.path.exists(input_obj1) and input_obj1 != final_output:
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os.rename(input_obj1, final_output)
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self.logger.info(
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f"OBJ模型合并完成，共执行 {merge_count} 次合并，"
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f"最终输出文件: {input_obj1}"
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f"最终输出文件: {final_output}"
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)
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except Exception as e:
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@ -1,34 +0,0 @@
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import open3d as o3d
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import numpy as np
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# 读取 .obj 文件
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def load_obj(file_path):
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mesh = o3d.io.read_triangle_mesh(file_path)
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if not mesh.is_empty():
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return mesh
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else:
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raise ValueError(f"Failed to load {file_path}")
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# 合并两个网格
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def merge_meshes(mesh1, mesh2):
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# 直接合并网格
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combined_mesh = mesh1 + mesh2
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return combined_mesh
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# 保存合并后的网格
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def save_merged_mesh(mesh, output_path):
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o3d.io.write_triangle_mesh(output_path, mesh)
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print(f"Saved merged mesh to {output_path}")
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# 示例用法
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mesh1 = load_obj("model1.obj")
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mesh2 = load_obj("model2.obj")
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# 合并两个网格
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merged_mesh = merge_meshes(mesh1, mesh2)
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# 保存合并后的网格
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save_merged_mesh(merged_mesh, "merged_model.obj")
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# 可视化合并后的网格
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o3d.visualization.draw_geometries([merged_mesh])
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65
tools/merge_two_obj.py
Normal file
65
tools/merge_two_obj.py
Normal file
@ -0,0 +1,65 @@
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def read_obj(file_path):
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"""
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读取.obj文件，返回顶点列表和面列表
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"""
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vertices = []
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faces = []
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with open(file_path, 'r') as file:
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for line in file:
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parts = line.split()
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if len(parts) == 0:
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continue
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if parts[0] == 'v': # 顶点
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vertices.append([float(parts[1]), float(parts[2]), float(parts[3])])
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elif parts[0] == 'f': # 面
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faces.append([int(parts[1].split('/')[0]), int(parts[2].split('/')[0]), int(parts[3].split('/')[0])])
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return vertices, faces
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def write_obj(file_path, vertices, faces):
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"""
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将修改后的顶点和面列表写入到.obj文件
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"""
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with open(file_path, 'w') as file:
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for vertex in vertices:
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file.write(f"v {vertex[0]} {vertex[1]} {vertex[2]}\n")
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for face in faces:
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file.write(f"f {face[0]} {face[1]} {face[2]}\n")
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def translate_vertices(vertices, translation):
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"""
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平移顶点，translation 是一个三维向量，例如 (500, 0, 0) 会沿 X 轴平移 500 米
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"""
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return [[v[0] + translation[0], v[1] + translation[1], v[2] + translation[2]] for v in vertices]
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def merge_objs(obj1_path, obj2_path, output_path, translation=(500, 0, 0)):
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"""
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合并两个.obj文件，并对第二个文件的顶点进行平移
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obj1_path 和 obj2_path 是输入的.obj文件路径
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output_path 是输出的合并后的.obj文件路径
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translation 是平移向量，默认为沿 X 轴平移 500 米
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"""
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# 读取第一个 obj 文件
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vertices1, faces1 = read_obj(obj1_path)
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# 读取第二个 obj 文件
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vertices2, faces2 = read_obj(obj2_path)
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# 平移第二个 obj 文件的顶点
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vertices2_translated = translate_vertices(vertices2, translation)
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# 合并顶点和面
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all_vertices = vertices1 + vertices2_translated
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all_faces = faces1 + [[f[0] + len(vertices1), f[1] + len(vertices1), f[2] + len(vertices1)] for f in faces2]
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# 写入合并后的 obj 文件
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write_obj(output_path, all_vertices, all_faces)
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print(f"合并完成，结果保存在 {output_path}")
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# 示例调用
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obj1_path = 'model1.obj' # 第一个 .obj 文件
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obj2_path = 'model2.obj' # 第二个 .obj 文件
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output_path = 'merged_model.obj' # 输出合并后的 .obj 文件
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merge_objs(obj1_path, obj2_path, output_path, translation=(500, 0, 0))
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@ -12,10 +12,12 @@ class GridDivider:
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self.output_dir = output_dir
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self.logger = logging.getLogger('UAV_Preprocess.GridDivider')
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self.logger.info(f"初始化网格划分器，重叠率: {overlap}")
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self.num_grids_width = 0 # 添加网格数量属性
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self.num_grids_height = 0
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def divide_grids(self, points_df, grid_size=500):
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"""计算边界框并划分九宫格"""
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self.logger.info("开始划分九宫格")
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"""计算边界框并划分网格"""
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self.logger.info("开始划分网格")
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min_lat, max_lat = points_df['lat'].min(), points_df['lat'].max()
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min_lon, max_lon = points_df['lon'].min(), points_df['lon'].max()
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@ -24,45 +26,55 @@ class GridDivider:
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width = geodesic((min_lat, min_lon), (min_lat, max_lon)).meters
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height = geodesic((min_lat, min_lon), (max_lat, min_lon)).meters
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self.logger.info(
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f"区域宽度: {width:.2f}米, 高度: {height:.2f}米"
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)
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self.logger.info(f"区域宽度: {width:.2f}米, 高度: {height:.2f}米")
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# 计算需要划分的网格数量
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num_grids_width = int(
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width / grid_size) if int(width / grid_size) > 0 else 1
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num_grids_height = int(
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height / grid_size) if int(height / grid_size) > 0 else 1
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self.num_grids_width = max(int(width / grid_size), 1)
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self.num_grids_height = max(int(height / grid_size), 1)
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# 计算每个网格对应的经纬度步长
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lat_step = (max_lat - min_lat) / num_grids_height
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lon_step = (max_lon - min_lon) / num_grids_width
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lat_step = (max_lat - min_lat) / self.num_grids_height
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lon_step = (max_lon - min_lon) / self.num_grids_width
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grids = []
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for i in range(num_grids_height):
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for j in range(num_grids_width):
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grid_min_lat = min_lat + i * lat_step - self.overlap * lat_step
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grid_max_lat = min_lat + \
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(i + 1) * lat_step + self.overlap * lat_step
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grid_min_lon = min_lon + j * lon_step - self.overlap * lon_step
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grid_max_lon = min_lon + \
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(j + 1) * lon_step + self.overlap * lon_step
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grids.append((grid_min_lat, grid_max_lat,
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grid_min_lon, grid_max_lon))
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grid_indices = {} # 存储网格的二维索引
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grid_idx = 0
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for i in range(self.num_grids_height):
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for j in range(self.num_grids_width):
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grid_min_lat = min_lat + i * lat_step - self.overlap * lat_step
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grid_max_lat = min_lat + (i + 1) * lat_step + self.overlap * lat_step
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grid_min_lon = min_lon + j * lon_step - self.overlap * lon_step
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grid_max_lon = min_lon + (j + 1) * lon_step + self.overlap * lon_step
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grids.append((grid_min_lat, grid_max_lat, grid_min_lon, grid_max_lon))
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grid_indices[grid_idx] = (i, j) # 存储每个网格的行列索引
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self.logger.debug(
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f"网格[{i},{j}]: 纬度[{grid_min_lat:.6f}, {grid_max_lat:.6f}], "
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f"网格[{i},{j}] (索引{grid_idx}): 纬度[{grid_min_lat:.6f}, {grid_max_lat:.6f}], "
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f"经度[{grid_min_lon:.6f}, {grid_max_lon:.6f}]"
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)
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grid_idx += 1
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self.logger.info(
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f"成功划分为 {len(grids)} 个网格 ({num_grids_width}x{num_grids_height})")
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f"成功划分为 {len(grids)} 个网格 ({self.num_grids_width}x{self.num_grids_height})")
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# 保存网格索引信息
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self.grid_indices = grid_indices
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# 添加可视化调用
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self.visualize_grids(points_df, grids)
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return grids
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def get_grid_coordinates(self, grid_idx):
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"""获取网格的二维坐标"""
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return self.grid_indices.get(grid_idx, (0, 0))
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def get_grid_dimensions(self):
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"""获取网格的维度"""
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return self.num_grids_width, self.num_grids_height
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def assign_to_grids(self, points_df, grids):
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||||
"""将点分配到对应网格"""
|
||||
self.logger.info(f"开始将 {len(points_df)} 个点分配到网格中")
|
||||
|
||||
Loading…
Reference in New Issue
Block a user