【PCL】SolidWorks 三维建模 STL, OBJ 采样生成 PCD 点云数据（附源码） |
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【PCL】SolidWorks 三维建模 STL, OBJ 采样生成 PCD 点云数据（附源码）
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目录&索引
1 前言2 准备工作（相关软件及库）3 实现步骤3.1 三维建模保存 stl 网格文件3.2 stl网格文件转 obj 网格文件a) 在工具里勾选 SW 插件 ScanTo3D，后续格式保存要用b) 以 ScanTo3D 网格文件打开保存的 stlc) 另存为 ScanTo3D(*.obj) 文件
3.3 利用 PCL 采样可执行程序，实现 obj 网格文件转 pcd 点云a) 接下来就是最重要的两步了，在安装 PCL 的路径下 bin 文件夹打开，找到 pcl_mesh_sampling_debug.exe 或 pcl_mesh_sampling_release.exeb) cmd 运行可执行采样文件（obj 文件相同目录）
4 结果5 mesh_sampling 源码（应读者需求，已更新）
这阵子做线结构光视觉检测（钢轨磨耗检测）项目的过程中，发现之前的许多知识点在逐渐遗忘，常言好记性不如烂笔头，故决定把项目中所用到的，把笔者认为有价值且对博友能够产生帮助的内容，记录分享于此。能力有限，如有纰漏，希望博友留下意见与建议。 1 前言磨耗检测项目中，配准阶段将结构光采集的数据集映射到标准廓形的数据集上，以识别其特征，进而计算分析。 其中，建立标准轨头廓形数据模型有两种方法，a）分段函数描述；b）三维模型转 PCD（所选方案）； 选定方案之后，查阅三维模型提取点云数据的相关资料时，发现在 SolidWorks 三维模型中提取生成点云数据的资料较少，且需要下载相关软件或配置需求过高。于是在笔者仔细查阅相关资料后，总结了一种较为方便且利于没有这方面基础的小白阅读完成。 2 准备工作（相关软件及库） SolidWorks 等三维建模软件PCL 点云库 3 实现步骤 3.1 三维建模保存 stl 网格文件
3.2 stl网格文件转 obj 网格文件
a) 在工具里勾选 SW 插件 ScanTo3D，后续格式保存要用
b) 以 ScanTo3D 网格文件打开保存的 stl
c) 另存为 ScanTo3D(*.obj) 文件
3.3 利用 PCL 采样可执行程序，实现 obj 网格文件转 pcd 点云
a) 接下来就是最重要的两步了，在安装 PCL 的路径下 bin 文件夹打开，找到 pcl_mesh_sampling_debug.exe 或 pcl_mesh_sampling_release.exe
b) cmd 运行可执行采样文件（obj 文件相同目录）
4 结果
结果显示，点云文件获取完毕 
当前目录下生成 60kg╱m 钢轨-05.pcd 的文件。下采样控制体素点距或投影模型等相关后续必要操作，标准点云模型满足需求。 如有不明白的地方，欢迎交流。 5 mesh_sampling 源码（应读者需求，已更新） /* * Software License Agreement (BSD License) * * Point Cloud Library (PCL) - www.pointclouds.org * Copyright (c) 2010-2011, Willow Garage, Inc. * * All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * * Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * * Redistributions in binary form must reproduce the above * copyright notice, this list of conditions and the following * disclaimer in the documentation and/or other materials provided * with the distribution. * * Neither the name of the copyright holder(s) nor the names of its * contributors may be used to endorse or promote products derived * from this software without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE * POSSIBILITY OF SUCH DAMAGE. * */ #include #include #include #include #include #include #include #include #include #include #include inline double uniform_deviate (int seed) { double ran = seed * (1.0 / (RAND_MAX + 1.0)); return ran; } inline void randomPointTriangle (float a1, float a2, float a3, float b1, float b2, float b3, float c1, float c2, float c3, Eigen::Vector4f& p) { float r1 = static_cast (uniform_deviate (rand ())); float r2 = static_cast (uniform_deviate (rand ())); float r1sqr = sqrtf (r1); float OneMinR1Sqr = (1 - r1sqr); float OneMinR2 = (1 - r2); a1 *= OneMinR1Sqr; a2 *= OneMinR1Sqr; a3 *= OneMinR1Sqr; b1 *= OneMinR2; b2 *= OneMinR2; b3 *= OneMinR2; c1 = r1sqr * (r2 * c1 + b1) + a1; c2 = r1sqr * (r2 * c2 + b2) + a2; c3 = r1sqr * (r2 * c3 + b3) + a3; p[0] = c1; p[1] = c2; p[2] = c3; p[3] = 0; } inline void randPSurface (vtkPolyData * polydata, std::vector * cumulativeAreas, double totalArea, Eigen::Vector4f& p) { float r = static_cast (uniform_deviate (rand ()) * totalArea); std::vector::iterator low = std::lower_bound (cumulativeAreas->begin (), cumulativeAreas->end (), r); vtkIdType el = vtkIdType (low - cumulativeAreas->begin ()); double A[3], B[3], C[3]; vtkIdType npts = 0; vtkIdType *ptIds = NULL; polydata->GetCellPoints (el, npts, ptIds); polydata->GetPoint (ptIds[0], A); polydata->GetPoint (ptIds[1], B); polydata->GetPoint (ptIds[2], C); randomPointTriangle (float (A[0]), float (A[1]), float (A[2]), float (B[0]), float (B[1]), float (B[2]), float (C[0]), float (C[1]), float (C[2]), p); } void uniform_sampling (vtkSmartPointer polydata, size_t n_samples, pcl::PointCloud & cloud_out) { polydata->BuildCells (); vtkSmartPointer cells = polydata->GetPolys (); double p1[3], p2[3], p3[3], totalArea = 0; std::vector cumulativeAreas (cells->GetNumberOfCells (), 0); size_t i = 0; vtkIdType npts = 0, *ptIds = NULL; for (cells->InitTraversal (); cells->GetNextCell (npts, ptIds); i++) { polydata->GetPoint (ptIds[0], p1); polydata->GetPoint (ptIds[1], p2); polydata->GetPoint (ptIds[2], p3); totalArea += vtkTriangle::TriangleArea (p1, p2, p3); cumulativeAreas[i] = totalArea; } cloud_out.points.resize (n_samples); cloud_out.width = static_cast (n_samples); cloud_out.height = 1; for (i = 0; i print_error ("Syntax is: %s input.{ply,obj} output.pcd \n", argv[0]); print_info (" where options are:\n"); print_info (" -n_samples X = number of samples (default: "); print_value ("%d", default_number_samples); print_info (")\n"); print_info ( " -leaf_size X = the XYZ leaf size for the VoxelGrid -- for data reduction (default: "); print_value ("%f", default_leaf_size); print_info (" m)\n"); } /* ---[ */ int main (int argc, char **argv) { print_info ("Convert a CAD model to a point cloud using uniform sampling. For more information, use: %s -h\n", argv[0]); if (argc print_error ("Need a single output PCD file to continue.\n"); return (-1); } std::vector ply_file_indices = parse_file_extension_argument (argc, argv, ".ply"); std::vector obj_file_indices = parse_file_extension_argument (argc, argv, ".obj"); if (ply_file_indices.size () != 1 && obj_file_indices.size () != 1) { print_error ("Need a single input PLY/OBJ file to continue.\n"); return (-1); } vtkSmartPointer polydata1; if (ply_file_indices.size () == 1) { vtkSmartPointer readerQuery = vtkSmartPointer::New (); readerQuery->SetFileName (argv[ply_file_indices[0]]); } else if (obj_file_indices.size () == 1) { vtkSmartPointer readerQuery = vtkSmartPointer::New (); readerQuery->SetFileName (argv[obj_file_indices[0]]); polydata1 = readerQuery->GetOutput (); polydata1->Update (); } //make sure that the polygons are triangles! vtkSmartPointer triangleFilter = vtkSmartPointer::New (); triangleFilter->SetInput (polydata1); triangleFilter->Update (); vtkSmartPointer triangleMapper = vtkSmartPointer::New (); triangleMapper->SetInputConnection (triangleFilter->GetOutputPort ()); triangleMapper->Update(); polydata1 = triangleMapper->GetInput(); polydata1->Update (); bool INTER_VIS = false; bool VIS = true; if (INTER_VIS) { visualization::PCLVisualizer vis; vis.addModelFromPolyData (polydata1, "mesh1", 0); vis.setRepresentationToSurfaceForAllActors (); vis.spin(); } pcl::PointCloud::Ptr cloud_1 (new pcl::PointCloud); uniform_sampling (polydata1, SAMPLE_POINTS_, *cloud_1); if (INTER_VIS) { visualization::PCLVisualizer vis_sampled; vis_sampled.addPointCloud (cloud_1); vis_sampled.spin (); } // Voxelgrid VoxelGrid grid_; grid_.setInputCloud (cloud_1); grid_.setLeafSize (leaf_size, leaf_size, leaf_size); grid_.filter (*cloud_1); if (VIS) { visualization::PCLVisualizer vis3 ("VOXELIZED SAMPLES CLOUD"); vis3.addPointCloud (cloud_1); vis3.spin (); } savePCDFileASCII (argv[pcd_file_indices[0]], *cloud_1); } |
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