Subversion Repositories seema-scanner

#include "SMReconstructionWorker.h"

#include "AlgorithmGrayCode.h"

#include "AlgorithmPhaseShift.h"

#include <QCoreApplication>

#include <QSettings>

#include <iostream>

#include <opencv2/opencv.hpp>

#include <pcl/filters/statistical_outlier_removal.h>

#include <pcl/io/pcd_io.h>

void SMReconstructionWorker::setup(){

    QSettings settings;

    // Get current calibration

    calibration = settings.value("calibration/parameters").value<SMCalibrationParameters>();

    // Create Algorithm

    dir = (CodingDir)settings.value("pattern/direction", CodingDirHorizontal).toInt();

    if(dir == CodingDirNone)

        std::cerr << "SMCaptureWorker: invalid coding direction " << std::endl;

    int resX = settings.value("projector/resX").toInt();

    int resY = settings.value("projector/resY").toInt();

    QString codec = settings.value("codec", "GrayCode").toString();

    if(codec == "PhaseShift")

        algorithm = new AlgorithmPhaseShift(resX, resY, dir);

    else if(codec == "GrayCode")

        algorithm = new AlgorithmGrayCode(resX, resY, dir);

    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 correspondences

    std::vector<cv::Point2f> q0, q1;

    std::vector<cv::Point3f> color;

    algorithm->getCorrespondences(calibration, frameSequence.frames0, frameSequence.frames0, q0, q1, color);

    // Triangulate

    std::vector<cv::Point3f> Q;

    triangulate(q0, q1, Q);

    // Convert point cloud to PCL format

    pcl::PointCloud<pcl::PointXYZRGB>::Ptr pointCloudPCL(new pcl::PointCloud<pcl::PointXYZRGB>);

    // Interprete as organized point cloud

    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].x; point.g = color[i].y; point.b = color[i].z;

        pointCloudPCL->points[i] = point;

    }

    // Emit result

    emit newPointCloud(pointCloudPCL);

    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::triangulatePoints(P0, P1, q0, q1, Q);

}

//void SMReconstructionWorker::triangulateFromUpVp(cv::Mat &up, cv::Mat &vp, cv::Mat &xyz){

//    std::cerr << "WARNING! NOT FULLY IMPLEMENTED!" << std::endl;

//    int N = up.rows * up.cols;

//    cv::Mat projPointsCam(2, N, CV_32F);

//    uc.reshape(0,1).copyTo(projPointsCam.row(0));

//    vc.reshape(0,1).copyTo(projPointsCam.row(1));

//    cv::Mat projPointsProj(2, N, CV_32F);

//    up.reshape(0,1).copyTo(projPointsProj.row(0));

//    vp.reshape(0,1).copyTo(projPointsProj.row(1));

//    cv::Mat Pc(3,4,CV_32F,cv::Scalar(0.0));

//    cv::Mat(calibration.Kc).copyTo(Pc(cv::Range(0,3), cv::Range(0,3)));

//    cv::Mat Pp(3,4,CV_32F), temp(3,4,CV_32F);

//    cv::Mat(calibration.Rp).copyTo(temp(cv::Range(0,3), cv::Range(0,3)));

//    cv::Mat(calibration.Tp).copyTo(temp(cv::Range(0,3), cv::Range(3,4)));

//    Pp = cv::Mat(calibration.Kp) * temp;

//    cv::Mat xyzw;

//    cv::triangulatePoints(Pc, Pp, projPointsCam, projPointsProj, xyzw);

//    xyz.create(3, N, CV_32F);

//    for(int i=0; i<N; i++){

//        xyz.at<float>(0,i) = xyzw.at<float>(0,i)/xyzw.at<float>(3,i);

//        xyz.at<float>(1,i) = xyzw.at<float>(1,i)/xyzw.at<float>(3,i);

//        xyz.at<float>(2,i) = xyzw.at<float>(2,i)/xyzw.at<float>(3,i);

//    }

//    xyz = xyz.t();

//    xyz = xyz.reshape(3, up.rows);

//}