• PCL交互选择ROI区域

    PCL的配置和如何配准点云可见博主之前的博客

    win10环境下PCL安装和配置回顾（一）_竹叶青lvye的博客-CSDN博客_pcl win10

    win10环境下PCL安装和配置回顾（二）_竹叶青lvye的博客-CSDN博客_win10 安装pcl

    PCL - 3D点云配准(registration)介绍_竹叶青lvye的博客-CSDN博客

    其它的PCL方面常用的一些点云算法，可自己花时间去研读，这边想去简单实现下ROI区域交互式的选择，接下还是延续前面几篇博客所用的PCL的配置。

    一. 生成测试点云

    这边点云选择

    mirrors / pointcloudlibrary / data · GitCode

    里面的learn5.pcd点云

     这里自定义了一个旋转平移矩阵（将点云通过这个变换为另外一个点云），详细见如下代码：

    1. #include   // for pcl::make_shared
    2. #include 
    3. #include 
    4. #include 
    5. #include 
    6.  
    7. #include 
    8. #include 
    9.  
    10. #include 
    11.  
    12. #include 
    13. #include 
    14. #include 
    15.  
    16. #include 
    17.  
    18.  
    19. #include 
    20.  
    21. using pcl::visualization::PointCloudColorHandlerGenericField;
    22. using pcl::visualization::PointCloudColorHandlerCustom;
    23.  
    24. //convenient typedefs
    25. typedef pcl::PointXYZ PointT;
    26. typedef pcl::PointCloud PointCloud;
    27. typedef pcl::PointNormal PointNormalT;
    28. typedef pcl::PointCloud PointCloudWithNormals;
    29.  
    30. int main()
    31. {
    32. 	PointCloud::Ptr cloud_src(new PointCloud);
    33. 	PointCloud::Ptr cloud_tgt(new PointCloud);
    34.  
    35. 	pcl::io::loadPCDFile("D:\\PCL\\data-master\\segmentation\\mOSD\\learn\\learn5.pcd", *cloud_src);
    36.  
    37. 	Eigen::Matrix4f transform_1 = Eigen::Matrix4f::Identity();//定义绕X轴的旋转矩阵，并初始化为单位阵
    38.  
    39. 	float theta = M_PI / 4; // The angle of rotation in radians
    40. 	transform_1(0, 0) = std::cos(theta);
    41. 	transform_1(0, 1) = -sin(theta);
    42. 	transform_1(1, 0) = sin(theta);
    43. 	transform_1(1, 1) = std::cos(theta);
    44.  
    45. 	transform_1(0, 3) = 0.7f;
    46. 	transform_1(1, 3) = 0.6f;
    47. 	transform_1(2, 3) = 1.2f;
    48.  
    49. 	pcl::transformPointCloud(*cloud_src, *cloud_tgt, transform_1);
    50.  
    51. 	std::cout << "cloud_src size: " << cloud_src->size() << std::endl;
    52. 	std::cout << "cloud_target size: " << cloud_tgt->size() << std::endl;
    53.  
    54. 	pcl::visualization::PCLVisualizer* p;
    55. 	int vp_1, vp_2;
    56.  
    57. 	p = new pcl::visualization::PCLVisualizer("view");
    58.  
    59. 	PointCloudColorHandlerCustom src_h(cloud_src, 255, 0, 0);
    60. 	PointCloudColorHandlerCustom tgt_h(cloud_tgt, 0, 255, 0);
    61.  
    62. 	p->addPointCloud(cloud_src, src_h, "vp1_src");
    63. 	p->addPointCloud(cloud_tgt, tgt_h, "vp1_target");
    64.  
    65.  
    66. 	p->spin();
    67.  
    68. 	return (0);
    69. }

     运行结果如下：

    二. 交互点选

    接下来在变换前的点云数据上点选一个ROI区域，代码如下：

    1. #include   // for pcl::make_shared
    2. #include 
    3. #include 
    4. #include 
    5. #include 
    6.  
    7. #include 
    8. #include 
    9.  
    10. #include 
    11.  
    12. #include 
    13. #include 
    14. #include 
    15.  
    16. #include 
    17.  
    18. #include 
    19. #include 
    20. #include 
    21. #include 
    22.  
    23. #include 
    24.  
    25. using pcl::visualization::PointCloudColorHandlerGenericField;
    26. using pcl::visualization::PointCloudColorHandlerCustom;
    27.  
    28. //convenient typedefs
    29. typedef pcl::PointXYZ PointT;
    30. typedef pcl::PointCloud PointCloud;
    31. typedef pcl::PointNormal PointNormalT;
    32. typedef pcl::PointCloud PointCloudWithNormals;
    33.  
    34. //Mutex 
    35. boost::mutex cloud_mutex;
    36.  
    37. struct callback_args
    38. {
    39. 	PointCloud::Ptr clicked_points_3d;
    40. 	pcl::visualization::PCLVisualizer::Ptr viewerPtr;
    41. };
    42.  
    43. //点选函数
    44. void pointPick_callback(const pcl::visualization::PointPickingEvent& event, void* args)
    45. {
    46. 	struct callback_args* data = (struct callback_args*)args;
    47. 	if (event.getPointIndex() == -1)
    48. 	{
    49. 		return;
    50. 	}
    51.  
    52. 	//提取当前点
    53. 	PointT current_point;
    54. 	event.getPoint(current_point.x, current_point.y, current_point.z);
    55. 	data->clicked_points_3d->points.push_back(current_point);
    56.  
    57. 	//显示当前点
    58. 	pcl::visualization::PointCloudColorHandlerCustom red(data->clicked_points_3d, 255, 0, 0);
    59. 	data->viewerPtr->removePointCloud("clicked_points");
    60. 	data->viewerPtr->addPointCloud(data->clicked_points_3d, red, "clicked_points");
    61. 	data->viewerPtr->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 10, "clicked_points");
    62. 	cout << current_point << endl;
    63. }
    64.  
    65.  
    66. int main()
    67. {
    68. 	PointCloud::Ptr cloud_src(new PointCloud);
    69. 	PointCloud::Ptr cloud_tgt(new PointCloud);
    70.  
    71. 	pcl::io::loadPCDFile("D:\\PCL\\data-master\\segmentation\\mOSD\\learn\\learn5.pcd", *cloud_src);
    72.  
    73. 	Eigen::Matrix4f transform_1 = Eigen::Matrix4f::Identity();//定义绕X轴的旋转矩阵，并初始化为单位阵
    74.  
    75. 	float theta = M_PI / 4; // The angle of rotation in radians
    76. 	transform_1(0, 0) = std::cos(theta);
    77. 	transform_1(0, 1) = -sin(theta);
    78. 	transform_1(1, 0) = sin(theta);
    79. 	transform_1(1, 1) = std::cos(theta);
    80.  
    81. 	transform_1(0, 3) = 0.7f;
    82. 	transform_1(1, 3) = 0.6f;
    83. 	transform_1(2, 3) = 1.2f;
    84.  
    85. 	pcl::transformPointCloud(*cloud_src, *cloud_tgt, transform_1);
    86.  
    87. 	std::cout << "cloud_src size: " << cloud_src->size() << std::endl;
    88. 	std::cout << "cloud_target size: " << cloud_tgt->size() << std::endl;
    89.  
    90. 	
    91.  
    92. 	pcl::visualization::PCLVisualizer* p;
    93.  
    94. 	p = new pcl::visualization::PCLVisualizer("view");
    95.  
    96. 	cloud_mutex.lock();    // for not overwriting the point cloud
    97.  
    98. 	PointCloudColorHandlerCustom src_h(cloud_src, 0, 0, 255);
    99. 	PointCloudColorHandlerCustom tgt_h(cloud_tgt, 0, 255, 0);
    100.  
    101. 	p->setBackgroundColor(0.5, 0.5, 0.1, 0); // 设置背景为深灰
    102.  
    103. 	p->addPointCloud(cloud_src, src_h, "vp1_src");
    104. 	p->addPointCloud(cloud_tgt, tgt_h, "vp1_target");
    105.  
    106. 	struct callback_args cb_args;
    107. 	PointCloud::Ptr clicked_points_3d(new PointCloud);
    108.  
    109. 	cb_args.clicked_points_3d = clicked_points_3d;
    110. 	cb_args.viewerPtr = pcl::visualization::PCLVisualizer::Ptr(p);
    111. 	p->registerPointPickingCallback(pointPick_callback, (void*)&cb_args);
    112.  
    113. 	cout << "->Shift + 鼠标左键选点，按 ‘Q’结束选点" << endl;
    114.  
    115. 	p->spin();
    116.  
    117. 	cout << "->选点结束" << endl;
    118.  
    119. 	Eigen::Affine3f affine(transform_1);
    120.  
    121. 	PointT conver_point = pcl::transformPoint(cb_args.clicked_points_3d->points[0], affine);
    122. 	std::cout << "use the affine to covert the point: " << std::endl;
    123. 	std::cout << conver_point << std::endl;
    124.  
    125. 	cloud_mutex.unlock();
    126.  
    127. 	while (!p->wasStopped())
    128. 	{
    129. 		p->spinOnce(100);
    130. 		boost::this_thread::sleep(boost::posix_time::microseconds(100000));
    131. 	}
    132.  
    133. 	return (0);
    134. }

    运行程序，可看到如下先点选了蓝色点云上的一个角点，又鼠标点选了绿色点云上对应位置处的一角点。这个两个点云的点同时也在点云上show出来了。

     按了Q退出点选模式后，程序会将点云的绿色处的点去由变换矩阵变化下，算出来的值，可看到和上面鼠标点选的绿色点云的角点坐标是近似的。

     

    三. 将点云上的ROI区域跟随目标的变换而变化，并在其变换后的点云数据上画出立体框

    代码如下，在第一个点云上可以通过鼠标点选ROI区域，完毕后会在第二个点云上会产生一个ROI区域，可看到是跟随目标变化的。

    1. #include   // for pcl::make_shared
    2. #include 
    3. #include 
    4. #include 
    5. #include 
    6.  
    7. #include 
    8. #include 
    9.  
    10. #include 
    11.  
    12. #include 
    13. #include 
    14. #include 
    15.  
    16. #include 
    17.  
    18. #include 
    19. #include 
    20. #include 
    21. #include 
    22.  
    23. #include 
    24.  
    25. #include 
    26.  
    27. using pcl::visualization::PointCloudColorHandlerGenericField;
    28. using pcl::visualization::PointCloudColorHandlerCustom;
    29.  
    30. //convenient typedefs
    31. typedef pcl::PointXYZ PointT;
    32. typedef pcl::PointCloud PointCloud;
    33. typedef pcl::PointNormal PointNormalT;
    34. typedef pcl::PointCloud PointCloudWithNormals;
    35.  
    36. pcl::PointCloud::Ptr points;
    37.  
    38. //Mutex 
    39. boost::mutex cloud_mutex;
    40. int count = 0;
    41.  
    42.  
    43.  
    44. struct callback_args
    45. {
    46. 	PointCloud::Ptr clicked_points_3d;
    47. 	PointCloud::Ptr clicked_points_3d_convert;
    48. 	pcl::visualization::PCLVisualizer::Ptr viewerPtr;
    49. 	Eigen::Affine3f affine;
    50. };
    51.  
    52. //点选函数
    53. void pointPick_callback(const pcl::visualization::PointPickingEvent& event, void* args)
    54. {
    55. 	count++;
    56.  
    57. 	struct callback_args* data = (struct callback_args*)args;
    58. 	if (event.getPointIndex() == -1)
    59. 	{
    60. 		return;
    61. 	}
    62.  
    63. 	//提取当前点
    64. 	PointT current_point;
    65. 	event.getPoint(current_point.x, current_point.y, current_point.z);
    66. 	data->clicked_points_3d->points.push_back(current_point);
    67.  
    68. 	//显示当前点
    69. 	pcl::visualization::PointCloudColorHandlerCustom red(data->clicked_points_3d, 255, 0, 0);
    70. 	data->viewerPtr->removePointCloud("clicked_points");
    71. 	data->viewerPtr->addPointCloud(data->clicked_points_3d, red, "clicked_points");
    72. 	data->viewerPtr->setPointCloudRenderingProperties(pcl::visualization::PCL_VISUALIZER_POINT_SIZE, 10, "clicked_points");
    73.  
    74. 	//添加点索引号
    75. 	PointT position(current_point.x, current_point.y + 0.01, current_point.z);
    76. 	data->viewerPtr->addText3D(std::to_string(count), position, 0.1, 1,0,0);
    77.  
    78. 	data->viewerPtr->resetCameraViewpoint();
    79.  
    80. 	
    81. 	cout << current_point << endl;
    82. 	PointT convert_point = pcl::transformPoint(current_point, data->affine);
    83. 	data->clicked_points_3d_convert->points.push_back(convert_point);
    84.  
    85. 	if (count == 6)
    86. 	{
    87. 		//方向包围盒OBB
    88. 		pcl::MomentOfInertiaEstimation  feature_extractor;
    89. 		feature_extractor.setInputCloud(data->clicked_points_3d);
    90. 		feature_extractor.compute();
    91.  
    92. 		pcl::PointXYZ min_point_OBB;
    93. 		pcl::PointXYZ max_point_OBB;
    94. 		pcl::PointXYZ position_OBB;
    95. 		Eigen::Matrix3f rotational_matrix_OBB;
    96. 		feature_extractor.getOBB(min_point_OBB, max_point_OBB, position_OBB, rotational_matrix_OBB);
    97.  
    98. 		Eigen::Vector3f position(position_OBB.x, position_OBB.y, position_OBB.z);
    99. 		Eigen::Quaternionf quat(rotational_matrix_OBB);
    100. 		data->viewerPtr->addCube(position, quat, max_point_OBB.x - min_point_OBB.x, max_point_OBB.y - min_point_OBB.y, max_point_OBB.z - min_point_OBB.z, "OBB");
    101. 		data->viewerPtr->setShapeRenderingProperties(pcl::visualization::PCL_VISUALIZER_REPRESENTATION, pcl::visualization::PCL_VISUALIZER_REPRESENTATION_WIREFRAME, "OBB");
    102.  
    103. 		
    104. 		feature_extractor.setInputCloud(data->clicked_points_3d_convert);
    105. 		feature_extractor.compute();
    106.  
    107. 		feature_extractor.getOBB(min_point_OBB, max_point_OBB, position_OBB, rotational_matrix_OBB);
    108.  
    109. 		Eigen::Vector3f positionConvert(position_OBB.x, position_OBB.y, position_OBB.z);
    110. 		Eigen::Quaternionf quatConvert(rotational_matrix_OBB);
    111.  
    112. 		data->viewerPtr->addCube(positionConvert, quatConvert, max_point_OBB.x - min_point_OBB.x, max_point_OBB.y - min_point_OBB.y, max_point_OBB.z - min_point_OBB.z, "OBBConvert");
    113. 		data->viewerPtr->setShapeRenderingProperties(pcl::visualization::PCL_VISUALIZER_REPRESENTATION, pcl::visualization::PCL_VISUALIZER_REPRESENTATION_WIREFRAME, "OBBConvert");
    114. 	}
    115. }
    116.  
    117.  
    118. int main()
    119. {
    120. 	PointCloud::Ptr cloud_src(new PointCloud);
    121. 	PointCloud::Ptr cloud_tgt(new PointCloud);
    122.  
    123. 	pcl::io::loadPCDFile("D:\\PCL\\data-master\\segmentation\\mOSD\\learn\\learn5.pcd", *cloud_src);
    124.  
    125. 	Eigen::Matrix4f transform_1 = Eigen::Matrix4f::Identity();//定义绕X轴的旋转矩阵，并初始化为单位阵
    126.  
    127. 	float theta = M_PI / 4; // The angle of rotation in radians
    128. 	transform_1(0, 0) = std::cos(theta);
    129. 	transform_1(0, 1) = -sin(theta);
    130. 	transform_1(1, 0) = sin(theta);
    131. 	transform_1(1, 1) = std::cos(theta);
    132.  
    133. 	transform_1(0, 3) = 0.7f;
    134. 	transform_1(1, 3) = 0.6f;
    135. 	transform_1(2, 3) = 1.2f;
    136.  
    137. 	pcl::transformPointCloud(*cloud_src, *cloud_tgt, transform_1);
    138.  
    139. 	std::cout << "cloud_src size: " << cloud_src->size() << std::endl;
    140. 	std::cout << "cloud_target size: " << cloud_tgt->size() << std::endl;
    141.  
    142. 	
    143.  
    144. 	pcl::visualization::PCLVisualizer* p;
    145.  
    146. 	p = new pcl::visualization::PCLVisualizer("view");
    147.  
    148. 	cloud_mutex.lock();    // for not overwriting the point cloud
    149.  
    150. 	PointCloudColorHandlerCustom src_h(cloud_src, 0, 0, 255);
    151. 	PointCloudColorHandlerCustom tgt_h(cloud_tgt, 0, 255, 0);
    152.  
    153. 	p->setBackgroundColor(0.5, 0.5, 0.1, 0); // 设置背景为深灰
    154.  
    155. 	p->addPointCloud(cloud_src, src_h, "vp1_src");
    156. 	p->addPointCloud(cloud_tgt, tgt_h, "vp1_target");
    157.  
    158. 	struct callback_args cb_args;
    159. 	PointCloud::Ptr clicked_points_3d(new PointCloud);
    160. 	PointCloud::Ptr clicked_points_3d_convert(new PointCloud);
    161.  
    162. 	cb_args.clicked_points_3d = clicked_points_3d;
    163. 	cb_args.clicked_points_3d_convert = clicked_points_3d_convert;
    164.  
    165. 	cb_args.viewerPtr = pcl::visualization::PCLVisualizer::Ptr(p);
    166. 	//cb_args.viewerPtr->addCoordinateSystem(0.5);
    167. 	PointT position(0, 0, 0);
    168. 	PointT positionx(1, 0, 0);
    169. 	PointT positiony(0, 1, 0);
    170. 	PointT positionz(0, 0, 1);
    171. 	cb_args.viewerPtr->addArrow(positionx, position,0,0,1,false, "x");
    172. 	cb_args.viewerPtr->addArrow(positiony, position, 0,1, 0,false, "y");
    173. 	cb_args.viewerPtr->addArrow(positionz, position, 1, 0, 0,false, "z");
    174.  
    175. 	cb_args.viewerPtr->addText3D("x", positionx, 0.2, 0, 0, 1,"x1");
    176. 	cb_args.viewerPtr->addText3D("y", positiony, 0.2, 0, 1, 0,"y1");
    177. 	
    178.  
    179. 	Eigen::Affine3f affine(transform_1);
    180. 	cb_args.affine = affine;
    181.  
    182. 	p->registerPointPickingCallback(pointPick_callback, (void*)&cb_args);
    183.  
    184. 	cout << "->Shift + 鼠标左键选点，按 ‘Q’结束选点" << endl;
    185.  
    186. 	p->spin();
    187.  
    188. 	cout << "->选点结束" << endl;
    189.  
    190. 	
    191.  
    192. 	PointT conver_point = pcl::transformPoint(cb_args.clicked_points_3d->points[0], affine);
    193. 	std::cout << "use the affine to covert the point: " << std::endl;
    194. 	std::cout << conver_point << std::endl;
    195.  
    196. 	cloud_mutex.unlock();
    197.  
    198. 	while (!p->wasStopped())
    199. 	{
    200. 		p->spinOnce(100);
    201. 		boost::this_thread::sleep(boost::posix_time::microseconds(100000));
    202. 	}
    203.  
    204. 	return (0);
    205. }

    执行效果如下：

     可看到，此段代码实现了ROI区域跟随点云变化的功能。

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  • 原文地址：https://blog.csdn.net/jiugeshao/article/details/127835172