Subversion Repositories seema-scanner

#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);


}