本文整理汇总了C++中pointcloud::Ptr::swap方法的典型用法代码示例。如果您正苦于以下问题：C++ Ptr::swap方法的具体用法？C++ Ptr::swap怎么用？C++ Ptr::swap使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pointcloud::Ptr的用法示例。
在下文中一共展示了Ptr::swap方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C++代码示例。
示例1: viewer
void Mapper::viewer()
{
pcl::visualization::CloudViewer viewer("viewer");
PointCloud::Ptr globalMap (new PointCloud);
pcl::VoxelGrid<PointT> voxel;
voxel.setLeafSize( resolution, resolution, resolution );
while (shutdownFlag == false)
{
static int cntGlobalUpdate = 0;
if ( poseGraph.keyframes.size() <= this->keyframe_size )
{
usleep(1000);
continue;
}
// keyframe is updated
PointCloud::Ptr tmp(new PointCloud());
if (cntGlobalUpdate % 15 == 0)
{
// update all frames
cout<<"redrawing frames"<<endl;
globalMap->clear();
for ( int i=0; i<poseGraph.keyframes.size(); i+=2 )
{
PointCloud::Ptr cloud = this->generatePointCloud(poseGraph.keyframes[i]);
*globalMap += *cloud;
}
}
else
{
for ( int i=poseGraph.keyframes.size()-1; i>=0 && i>poseGraph.keyframes.size()-6; i-- )
{
PointCloud::Ptr cloud = this->generatePointCloud(poseGraph.keyframes[i]);
*globalMap += *cloud;
}
}
cntGlobalUpdate ++ ;
//voxel
voxel.setInputCloud( globalMap );
voxel.filter( *tmp );
keyframe_size = poseGraph.keyframes.size();
globalMap->swap( *tmp );
viewer.showCloud( globalMap );
cout<<"points in global map: "<<globalMap->points.size()<<endl;
}
}示例2: main
int main( int argc, char** argv )
{
vector<cv::Mat> colorImgs, depthImgs; // 彩色图和深度图
vector<Eigen::Isometry3d> poses; // 相机位姿
ifstream fin("./data/pose.txt");
if (!fin)
{
cerr<<"cannot find pose file"<<endl;
return 1;
}
for ( int i=0; i<5; i++ )
{
boost::format fmt( "./data/%s/%d.%s" ); //图像文件格式
colorImgs.push_back( cv::imread( (fmt%"color"%(i+1)%"png").str() ));
depthImgs.push_back( cv::imread( (fmt%"depth"%(i+1)%"pgm").str(), -1 )); // 使用-1读取原始图像
double data[7] = {0};
for ( int i=0; i<7; i++ )
{
fin>>data[i];
}
Eigen::Quaterniond q( data[6], data[3], data[4], data[5] );
Eigen::Isometry3d T(q);
T.pretranslate( Eigen::Vector3d( data[0], data[1], data[2] ));
poses.push_back( T );
}
// 计算点云并拼接
// 相机内参
double cx = 325.5;
double cy = 253.5;
double fx = 518.0;
double fy = 519.0;
double depthScale = 1000.0;
cout<<"正在将图像转换为点云..."<<endl;
// 定义点云使用的格式：这里用的是XYZRGB
typedef pcl::PointXYZRGB PointT;
typedef pcl::PointCloud<PointT> PointCloud;
// 新建一个点云
PointCloud::Ptr pointCloud( new PointCloud );
for ( int i=0; i<5; i++ )
{
PointCloud::Ptr current( new PointCloud );
cout<<"转换图像中: "<<i+1<<endl;
cv::Mat color = colorImgs[i];
cv::Mat depth = depthImgs[i];
Eigen::Isometry3d T = poses[i];
for ( int v=0; v<color.rows; v++ )
for ( int u=0; u<color.cols; u++ )
{
unsigned int d = depth.ptr<unsigned short> ( v )[u]; // 深度值
if ( d==0 ) continue; // 为0表示没有测量到
if ( d >= 7000 ) continue; // 深度太大时不稳定，去掉
Eigen::Vector3d point;
point[2] = double(d)/depthScale;
point[0] = (u-cx)*point[2]/fx;
point[1] = (v-cy)*point[2]/fy;
Eigen::Vector3d pointWorld = T*point;
PointT p ;
p.x = pointWorld[0];
p.y = pointWorld[1];
p.z = pointWorld[2];
p.b = color.data[ v*color.step+u*color.channels() ];
p.g = color.data[ v*color.step+u*color.channels()+1 ];
p.r = color.data[ v*color.step+u*color.channels()+2 ];
current->points.push_back( p );
}
// depth filter and statistical removal
PointCloud::Ptr tmp ( new PointCloud );
pcl::StatisticalOutlierRemoval<PointT> statistical_filter;
statistical_filter.setMeanK(50);
statistical_filter.setStddevMulThresh(1.0);
statistical_filter.setInputCloud(current);
statistical_filter.filter( *tmp );
(*pointCloud) += *tmp;
}
pointCloud->is_dense = false;
cout<<"点云共有"<<pointCloud->size()<<"个点."<<endl;
// voxel filter
pcl::VoxelGrid<PointT> voxel_filter;
voxel_filter.setLeafSize( 0.01, 0.01, 0.01 ); // resolution
PointCloud::Ptr tmp ( new PointCloud );
voxel_filter.setInputCloud( pointCloud );
voxel_filter.filter( *tmp );
tmp->swap( *pointCloud );
cout<<"滤波之后，点云共有"<<pointCloud->size()<<"个点."<<endl;
pcl::io::savePCDFileBinary("map.pcd", *pointCloud );
return 0;
}