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


#include "SMReconstructionWorker.h"
 
#include "AlgorithmGrayCode.h"
#include "AlgorithmPhaseShift.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 == "PhaseShift")
        algorithm = new AlgorithmPhaseShift(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(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 70 → 71

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