WebSVN – seema-scanner – Diff – /src/SMReconstructionWorker.cpp


#include "SMReconstructionWorker.h"
 
#include "AlgorithmGrayCode.h"
#include "AlgorithmGrayCodeHorzVert.h"
#include "AlgorithmPhaseShift.h"
#include "AlgorithmLineShift.h"
 
#include <QCoreApplication>
#include <QSettings>
 
#include <iostream>
#include <opencv2/opencv.hpp>
 
#include "cvtools.h"
 
#include <pcl/filters/statistical_outlier_removal.h>
#include <pcl/io/pcd_io.h>
#include <pcl/features/normal_3d.h>
 
 
void SMReconstructionWorker::setup(){
 
    QSettings settings;
 
    // Get current calibration
    calibration = settings.value("calibration/parameters").value<SMCalibrationParameters>();
 
    // Create Algorithm
    int resX = settings.value("projector/resX").toInt();
    int resY = settings.value("projector/resY").toInt();
    QString codec = settings.value("algorithm", "GrayCode").toString();
    if(codec == "GrayCode")
        algorithm = new AlgorithmGrayCode(resX, resY);
    else if(codec == "GrayCodeHorzVert")
        algorithm = new AlgorithmGrayCodeHorzVert(resX, resY);
    else if(codec == "PhaseShift")
        algorithm = new AlgorithmPhaseShift(resX, resY);
    else if(codec == "LineShift")
        algorithm = new AlgorithmLineShift(resX, resY);
    else
        std::cerr << "SLScanWorker: invalid codec " << codec.toStdString() << std::endl;
 
 
//    // Precompute lens correction maps
//    cv::Mat eye = cv::Mat::eye(3, 3, CV_32F);
//    cv::initUndistortRectifyMap(calibration.K0, calibration.k0, eye, calibration.K0, cv::Size(calibration.frameWidth, calibration.frameHeight), CV_32FC1, lensMap0Horz, lensMap0Vert);
//    cv::initUndistortRectifyMap(calibration.K0, calibration.k0, eye, calibration.K0, cv::Size(calibration.frameWidth, calibration.frameHeight), CV_32FC1, lensMap1Horz, lensMap1Vert);
 
    //cv::Mat mapHorz, mapVert;
    //cv::normalize(lensMap0Horz, mapHorz, 0, 255, cv::NORM_MINMAX, CV_8U);
    //cv::normalize(lensMap0Vert, mapVert, 0, 255, cv::NORM_MINMAX, CV_8U);
    //cv::imwrite("mapHorz.png", mapHorz);
    //cv::imwrite("mapVert.png", mapVert);
}
 
void SMReconstructionWorker::reconstructPointCloud(SMFrameSequence frameSequence){
 
    time.start();
 
    // Get 3D Points
    std::vector<cv::Point3f> Q;
    std::vector<cv::Vec3b> color;
    algorithm->get3DPoints(calibration, frameSequence.frames0, frameSequence.frames1, Q, color);
 
    // Convert point cloud to PCL format
    pcl::PointCloud<pcl::PointXYZRGB>::Ptr pointCloudPCL(new pcl::PointCloud<pcl::PointXYZRGB>);
 
    pointCloudPCL->width = Q.size();
    pointCloudPCL->height = 1;
    pointCloudPCL->is_dense = false;
 
    pointCloudPCL->points.resize(Q.size());
 
    for(unsigned int i=0; i<Q.size(); i++){
        pcl::PointXYZRGB point;
        point.x = Q[i].x; point.y = Q[i].y; point.z = Q[i].z;
        point.r = color[i][0]; point.g = color[i][1]; point.b = color[i][2];
        pointCloudPCL->points[i] = point;
    }
 
//    // Estimate surface normals
//    pcl::NormalEstimation<pcl::PointXYZRGB, pcl::PointXYZRGBNormal> ne;
//    pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree(new pcl::search::KdTree<pcl::PointXYZRGB>());
//    ne.setSearchMethod(tree);
//    ne.setRadiusSearch(3);
//    ne.setViewPoint(0.0, 0.0, 0.0);
//    ne.setInputCloud(pointCloudPCL);
//    ne.compute(*pointCloudPCL);
 
    // Assemble SMPointCloud data structure
    SMPointCloud smPointCloud;
    smPointCloud.id = frameSequence.id;
    smPointCloud.pointCloud = pointCloudPCL;
    smPointCloud.rotationAngle = frameSequence.rotationAngle;
 
    // Determine transform in world (camera0) coordinate system
    float angleRadians = frameSequence.rotationAngle/180.0*M_PI;
    cv::Vec3f rot_rvec(0.0, -angleRadians, 0.0);
    cv::Mat R;
    cv::Rodrigues(rot_rvec, R);
    smPointCloud.R = calibration.Rr.t()*cv::Matx33f(R)*calibration.Rr;
    smPointCloud.T = calibration.Rr.t()*cv::Matx33f(R)*calibration.Tr - calibration.Rr.t()*calibration.Tr;
 
    // Emit result
    emit newPointCloud(smPointCloud);
 
    std::cout << "SMReconstructionWorker: " << time.elapsed() << "ms" << std::endl;
 
}
 
void SMReconstructionWorker::reconstructPointClouds(std::vector<SMFrameSequence> frameSequences){
 
    // Process sequentially
    for(int i=0; i<frameSequences.size(); i++){
        reconstructPointCloud(frameSequences[i]);
    }
 
}
 
void SMReconstructionWorker::triangulate(std::vector<cv::Point2f>& q0, std::vector<cv::Point2f>& q1, std::vector<cv::Point3f> &Q){
 
    cv::Mat P0(3,4,CV_32F,cv::Scalar(0.0));
    cv::Mat(calibration.K0).copyTo(P0(cv::Range(0,3), cv::Range(0,3)));
 
    cv::Mat temp(3,4,CV_32F);
    cv::Mat(calibration.R1).copyTo(temp(cv::Range(0,3), cv::Range(0,3)));
    cv::Mat(calibration.T1).copyTo(temp(cv::Range(0,3), cv::Range(3,4)));
    cv::Mat P1 = cv::Mat(calibration.K1) * temp;
 
    cv::Mat QMatHomogenous, QMat;
    cv::triangulatePoints(P0, P1, q0, q1, QMatHomogenous);
    cvtools::convertMatFromHomogeneous(QMatHomogenous, QMat);
    cvtools::matToPoints3f(QMat, Q);
 
 
}
 

Subversion Repositories seema-scanner

(root)/src/SMReconstructionWorker.cpp – Rev 107 → 123

Rev 107		Rev 123
1	`#include "SMReconstructionWorker.h"`	1	`#include "SMReconstructionWorker.h"`
2		2
3	`#include "AlgorithmGrayCode.h"`	3	`#include "AlgorithmGrayCode.h"`
4	`#include "AlgorithmGrayCodeHorzVert.h"`	4	`#include "AlgorithmGrayCodeHorzVert.h"`
5	`#include "AlgorithmPhaseShift.h"`	5	`#include "AlgorithmPhaseShift.h"`
-		6	`#include "AlgorithmLineShift.h"`
6		7
7	`#include <QCoreApplication>`	8	`#include <QCoreApplication>`
8	`#include <QSettings>`	9	`#include <QSettings>`
9		10
10	`#include <iostream>`	11	`#include <iostream>`
11	`#include <opencv2/opencv.hpp>`	12	`#include <opencv2/opencv.hpp>`
12		13
13	`#include "cvtools.h"`	14	`#include "cvtools.h"`
14		15
15	`#include <pcl/filters/statistical_outlier_removal.h>`	16	`#include <pcl/filters/statistical_outlier_removal.h>`
16	`#include <pcl/io/pcd_io.h>`	17	`#include <pcl/io/pcd_io.h>`
17	`#include <pcl/features/normal_3d.h>`	18	`#include <pcl/features/normal_3d.h>`
18		19
19		20
20	`void SMReconstructionWorker::setup(){`	21	`void SMReconstructionWorker::setup(){`
21		22
22	`QSettings settings;`	23	`QSettings settings;`
23		24
24	`// Get current calibration`	25	`// Get current calibration`
25	`calibration = settings.value("calibration/parameters").value<SMCalibrationParameters>();`	26	`calibration = settings.value("calibration/parameters").value<SMCalibrationParameters>();`
26		27
27	`// Create Algorithm`	28	`// Create Algorithm`
28	`int resX = settings.value("projector/resX").toInt();`	29	`int resX = settings.value("projector/resX").toInt();`
29	`int resY = settings.value("projector/resY").toInt();`	30	`int resY = settings.value("projector/resY").toInt();`
30	`QString codec = settings.value("algorithm", "GrayCode").toString();`	31	`QString codec = settings.value("algorithm", "GrayCode").toString();`
31	`if(codec == "GrayCode")`	32	`if(codec == "GrayCode")`
32	`algorithm = new AlgorithmGrayCode(resX, resY);`	33	`algorithm = new AlgorithmGrayCode(resX, resY);`
33	`else if(codec == "GrayCodeHorzVert")`	34	`else if(codec == "GrayCodeHorzVert")`
34	`algorithm = new AlgorithmGrayCodeHorzVert(resX, resY);`	35	`algorithm = new AlgorithmGrayCodeHorzVert(resX, resY);`
35	`else if(codec == "PhaseShift")`	36	`else if(codec == "PhaseShift")`
36	`algorithm = new AlgorithmPhaseShift(resX, resY);`	37	`algorithm = new AlgorithmPhaseShift(resX, resY);`
-		38	`else if(codec == "LineShift")`
-		39	`algorithm = new AlgorithmLineShift(resX, resY);`
37	`else`	40	`else`
38	`std::cerr << "SLScanWorker: invalid codec " << codec.toStdString() << std::endl;`	41	`std::cerr << "SLScanWorker: invalid codec " << codec.toStdString() << std::endl;`
39		42
40		43
41	`// // Precompute lens correction maps`	44	`// // Precompute lens correction maps`
42	`// cv::Mat eye = cv::Mat::eye(3, 3, CV_32F);`	45	`// cv::Mat eye = cv::Mat::eye(3, 3, CV_32F);`
43	`// cv::initUndistortRectifyMap(calibration.K0, calibration.k0, eye, calibration.K0, cv::Size(calibration.frameWidth, calibration.frameHeight), CV_32FC1, lensMap0Horz, lensMap0Vert);`	46	`// cv::initUndistortRectifyMap(calibration.K0, calibration.k0, eye, calibration.K0, cv::Size(calibration.frameWidth, calibration.frameHeight), CV_32FC1, lensMap0Horz, lensMap0Vert);`
44	`// cv::initUndistortRectifyMap(calibration.K0, calibration.k0, eye, calibration.K0, cv::Size(calibration.frameWidth, calibration.frameHeight), CV_32FC1, lensMap1Horz, lensMap1Vert);`	47	`// cv::initUndistortRectifyMap(calibration.K0, calibration.k0, eye, calibration.K0, cv::Size(calibration.frameWidth, calibration.frameHeight), CV_32FC1, lensMap1Horz, lensMap1Vert);`
45		48
46	`//cv::Mat mapHorz, mapVert;`	49	`//cv::Mat mapHorz, mapVert;`
47	`//cv::normalize(lensMap0Horz, mapHorz, 0, 255, cv::NORM_MINMAX, CV_8U);`	50	`//cv::normalize(lensMap0Horz, mapHorz, 0, 255, cv::NORM_MINMAX, CV_8U);`
48	`//cv::normalize(lensMap0Vert, mapVert, 0, 255, cv::NORM_MINMAX, CV_8U);`	51	`//cv::normalize(lensMap0Vert, mapVert, 0, 255, cv::NORM_MINMAX, CV_8U);`
49	`//cv::imwrite("mapHorz.png", mapHorz);`	52	`//cv::imwrite("mapHorz.png", mapHorz);`
50	`//cv::imwrite("mapVert.png", mapVert);`	53	`//cv::imwrite("mapVert.png", mapVert);`
51	`}`	54	`}`
52		55
53	`void SMReconstructionWorker::reconstructPointCloud(SMFrameSequence frameSequence){`	56	`void SMReconstructionWorker::reconstructPointCloud(SMFrameSequence frameSequence){`
54		57
55	`time.start();`	58	`time.start();`
56		59
57	`// Get 3D Points`	60	`// Get 3D Points`
58	`std::vector<cv::Point3f> Q;`	61	`std::vector<cv::Point3f> Q;`
59	`std::vector<cv::Vec3b> color;`	62	`std::vector<cv::Vec3b> color;`
60	`algorithm->get3DPoints(calibration, frameSequence.frames0, frameSequence.frames1, Q, color);`	63	`algorithm->get3DPoints(calibration, frameSequence.frames0, frameSequence.frames1, Q, color);`
61		64
62	`// Convert point cloud to PCL format`	65	`// Convert point cloud to PCL format`
63	`pcl::PointCloud<pcl::PointXYZRGB>::Ptr pointCloudPCL(new pcl::PointCloud<pcl::PointXYZRGB>);`	66	`pcl::PointCloud<pcl::PointXYZRGB>::Ptr pointCloudPCL(new pcl::PointCloud<pcl::PointXYZRGB>);`
64		67
65	`pointCloudPCL->width = Q.size();`	68	`pointCloudPCL->width = Q.size();`
66	`pointCloudPCL->height = 1;`	69	`pointCloudPCL->height = 1;`
67	`pointCloudPCL->is_dense = false;`	70	`pointCloudPCL->is_dense = false;`
68		71
69	`pointCloudPCL->points.resize(Q.size());`	72	`pointCloudPCL->points.resize(Q.size());`
70		73
71	`for(unsigned int i=0; i<Q.size(); i++){`	74	`for(unsigned int i=0; i<Q.size(); i++){`
72	`pcl::PointXYZRGB point;`	75	`pcl::PointXYZRGB point;`
73	`point.x = Q[i].x; point.y = Q[i].y; point.z = Q[i].z;`	76	`point.x = Q[i].x; point.y = Q[i].y; point.z = Q[i].z;`
74	`point.r = color[i][0]; point.g = color[i][1]; point.b = color[i][2];`	77	`point.r = color[i][0]; point.g = color[i][1]; point.b = color[i][2];`
75	`pointCloudPCL->points[i] = point;`	78	`pointCloudPCL->points[i] = point;`
76	`}`	79	`}`
77		80
78	`// // Estimate surface normals`	81	`// // Estimate surface normals`
79	`// pcl::NormalEstimation<pcl::PointXYZRGB, pcl::PointXYZRGBNormal> ne;`	82	`// pcl::NormalEstimation<pcl::PointXYZRGB, pcl::PointXYZRGBNormal> ne;`
80	`// pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree(new pcl::search::KdTree<pcl::PointXYZRGB>());`	83	`// pcl::search::KdTree<pcl::PointXYZRGB>::Ptr tree(new pcl::search::KdTree<pcl::PointXYZRGB>());`
81	`// ne.setSearchMethod(tree);`	84	`// ne.setSearchMethod(tree);`
82	`// ne.setRadiusSearch(3);`	85	`// ne.setRadiusSearch(3);`
83	`// ne.setViewPoint(0.0, 0.0, 0.0);`	86	`// ne.setViewPoint(0.0, 0.0, 0.0);`
84	`// ne.setInputCloud(pointCloudPCL);`	87	`// ne.setInputCloud(pointCloudPCL);`
85	`// ne.compute(*pointCloudPCL);`	88	`// ne.compute(*pointCloudPCL);`
86		89
87	`// Assemble SMPointCloud data structure`	90	`// Assemble SMPointCloud data structure`
88	`SMPointCloud smPointCloud;`	91	`SMPointCloud smPointCloud;`
89	`smPointCloud.id = frameSequence.id;`	92	`smPointCloud.id = frameSequence.id;`
90	`smPointCloud.pointCloud = pointCloudPCL;`	93	`smPointCloud.pointCloud = pointCloudPCL;`
91	`smPointCloud.rotationAngle = frameSequence.rotationAngle;`	94	`smPointCloud.rotationAngle = frameSequence.rotationAngle;`
92		95
93	`// Determine transform in world (camera0) coordinate system`	96	`// Determine transform in world (camera0) coordinate system`
94	`float angleRadians = frameSequence.rotationAngle/180.0*M_PI;`	97	`float angleRadians = frameSequence.rotationAngle/180.0*M_PI;`
95	`cv::Vec3f rot_rvec(0.0, -angleRadians, 0.0);`	98	`cv::Vec3f rot_rvec(0.0, -angleRadians, 0.0);`
96	`cv::Mat R;`	99	`cv::Mat R;`
97	`cv::Rodrigues(rot_rvec, R);`	100	`cv::Rodrigues(rot_rvec, R);`
98	`smPointCloud.R = calibration.Rr.t()cv::Matx33f(R)calibration.Rr;`	101	`smPointCloud.R = calibration.Rr.t()cv::Matx33f(R)calibration.Rr;`
99	`smPointCloud.T = calibration.Rr.t()cv::Matx33f(R)calibration.Tr - calibration.Rr.t()*calibration.Tr;`	102	`smPointCloud.T = calibration.Rr.t()cv::Matx33f(R)calibration.Tr - calibration.Rr.t()*calibration.Tr;`
100		103
101	`// Emit result`	104	`// Emit result`
102	`emit newPointCloud(smPointCloud);`	105	`emit newPointCloud(smPointCloud);`
103		106
104	`std::cout << "SMReconstructionWorker: " << time.elapsed() << "ms" << std::endl;`	107	`std::cout << "SMReconstructionWorker: " << time.elapsed() << "ms" << std::endl;`
105		108
106	`}`	109	`}`
107		110
108	`void SMReconstructionWorker::reconstructPointClouds(std::vector<SMFrameSequence> frameSequences){`	111	`void SMReconstructionWorker::reconstructPointClouds(std::vector<SMFrameSequence> frameSequences){`
109		112
110	`// Process sequentially`	113	`// Process sequentially`
111	`for(int i=0; i<frameSequences.size(); i++){`	114	`for(int i=0; i<frameSequences.size(); i++){`
112	`reconstructPointCloud(frameSequences[i]);`	115	`reconstructPointCloud(frameSequences[i]);`
113	`}`	116	`}`
114		117
115	`}`	118	`}`
116		119
117	`void SMReconstructionWorker::triangulate(std::vector<cv::Point2f>& q0, std::vector<cv::Point2f>& q1, std::vector<cv::Point3f> &Q){`	120	`void SMReconstructionWorker::triangulate(std::vector<cv::Point2f>& q0, std::vector<cv::Point2f>& q1, std::vector<cv::Point3f> &Q){`
118		121
119	`cv::Mat P0(3,4,CV_32F,cv::Scalar(0.0));`	122	`cv::Mat P0(3,4,CV_32F,cv::Scalar(0.0));`
120	`cv::Mat(calibration.K0).copyTo(P0(cv::Range(0,3), cv::Range(0,3)));`	123	`cv::Mat(calibration.K0).copyTo(P0(cv::Range(0,3), cv::Range(0,3)));`
121		124
122	`cv::Mat temp(3,4,CV_32F);`	125	`cv::Mat temp(3,4,CV_32F);`
123	`cv::Mat(calibration.R1).copyTo(temp(cv::Range(0,3), cv::Range(0,3)));`	126	`cv::Mat(calibration.R1).copyTo(temp(cv::Range(0,3), cv::Range(0,3)));`
124	`cv::Mat(calibration.T1).copyTo(temp(cv::Range(0,3), cv::Range(3,4)));`	127	`cv::Mat(calibration.T1).copyTo(temp(cv::Range(0,3), cv::Range(3,4)));`
125	`cv::Mat P1 = cv::Mat(calibration.K1) * temp;`	128	`cv::Mat P1 = cv::Mat(calibration.K1) * temp;`
126		129
127	`cv::Mat QMatHomogenous, QMat;`	130	`cv::Mat QMatHomogenous, QMat;`
128	`cv::triangulatePoints(P0, P1, q0, q1, QMatHomogenous);`	131	`cv::triangulatePoints(P0, P1, q0, q1, QMatHomogenous);`
129	`cvtools::convertMatFromHomogeneous(QMatHomogenous, QMat);`	132	`cvtools::convertMatFromHomogeneous(QMatHomogenous, QMat);`
130	`cvtools::matToPoints3f(QMat, Q);`	133	`cvtools::matToPoints3f(QMat, Q);`
131		134
132		135
133	`}`	136	`}`
134		137