视觉SLAM14讲使用第八章深度图片进行点云图绘制
第八章中有9章深度图,能否进行点云图的绘制呢,像第五章一样,我进行了尝试,明天会下载整个数据集更新的。
目前只用九组深度图片。
cmakelist:
cmake_minimum_required( VERSION 2.8 )
project( test_read )
set( CMAKE_BUILD_TYPE Release )
set( CMAKE_CXX_FLAGS "-std=c++14 -O3" )
# opencv
find_package( OpenCV REQUIRED )
include_directories( ${OpenCV_INCLUDE_DIRS} )
# eigen
include_directories( "/usr/include/eigen3/" )
# pcl
find_package( PCL 1.9 REQUIRED COMPONENT common io )
list (REMOVE_ITEM PCL_LIBRARIES "vtkproj4")
add_executable( test_read main.cpp )
target_link_libraries( test_read ${OpenCV_LIBS} ${PCL_LIBRARIES} )
cpp:
#include <iostream>
#include <fstream>
#include <string>
#include <list>
#include <vector>
#include <chrono>
#include <sstream>
using namespace std;
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/features2d/features2d.hpp>
#include <opencv2/video/tracking.hpp>
#include <iostream>
#include <fstream>
#include <opencv2/core/core.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <Eigen/Geometry>
#include <boost/format.hpp> // for formating strings
#include <pcl/point_types.h>
#include <pcl/io/pcd_io.h>
double string_to_double(string data_string)
{
stringstream ss;
double data_double;
ss<<data_string;
ss>>data_double;
return(data_double);
}
int main( int argc, char** argv )
{
if ( argc != 2 )
{
cout<<"usage: useLK path_to_dataset"<<endl;
return 1;
}
string path_to_dataset = argv[1];
string associate_file1 = path_to_dataset + "/associate.txt";
string associate_file2 = path_to_dataset + "/groundtruth.txt";
ifstream fin1( associate_file1 );
if ( !fin1 )
{
cerr<<"I cann't find associate.txt!"<<endl;
return 1;
}
ifstream fin2( associate_file2 );
if ( !fin2 )
{
cerr<<"I cann't find groundtruth.txt!"<<endl;
return 1;
}
string rgb_file, depth_file, time_rgb, time_depth;
cv::Mat color, depth, last_color;
vector<cv::Mat> colorImgs, depthImgs; // 彩色图和深度图
vector<Eigen::Isometry3d, Eigen::aligned_allocator<Eigen::Isometry3d>> poses; // 相机位姿
double time_error;int flag=0;
for ( int index=0; index<9; index++ )
{
flag=0;
fin1>>time_rgb>>rgb_file>>time_depth>>depth_file;
color = cv::imread( path_to_dataset+"/"+rgb_file );
colorImgs.push_back( color );
depth = cv::imread( path_to_dataset+"/"+depth_file, -1 );
depthImgs.push_back( depth ); // 使用-1读取原始图像
for(;flag==0;)
{
double data[8] = {0};
for ( auto& d:data )
fin2>>d;
if(abs(2*data[0]-string_to_double(time_rgb)-string_to_double(time_depth))<0.01)
{
cout<<data[0]<<endl;
Eigen::Quaterniond q( data[7], data[4], data[5], data[6] );
Eigen::Isometry3d T(q);
T.pretranslate( Eigen::Vector3d( data[1], data[2], data[3] ));
poses.push_back( T );
flag=1;
}
}
}
// 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<9; i++ )
{
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
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 ];
pointCloud->points.push_back( p );
}
}
pointCloud->is_dense = false;
cout<<"点云共有"<<pointCloud->size()<<"个点."<<endl;
pcl::io::savePCDFileBinary("map.pcd", *pointCloud );
return 0;
}
效果: