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