/** This function contains the actions performed for each image*/
void processImage(MSAC &msac, int numVps, cv::Mat &imgGRAY, cv::Mat &outputImg)
{
cv::Mat imgCanny;
// Canny
cv::Canny(imgGRAY, imgCanny, 180, 120, 3);
// Hough
vector<vector<cv::Point> > lineSegments;
vector<cv::Point> aux;
#ifndef USE_PPHT
vector<Vec2f> lines;
cv::HoughLines( imgCanny, lines, 1, CV_PI/180, 200);
for(size_t i=0; i< lines.size(); i++)
{
float rho = lines[i][0];
float theta = lines[i][1];
double a = cos(theta), b = sin(theta);
double x0 = a*rho, y0 = b*rho;
Point pt1, pt2;
pt1.x = cvRound(x0 + 1000*(-b));
pt1.y = cvRound(y0 + 1000*(a));
pt2.x = cvRound(x0 - 1000*(-b));
pt2.y = cvRound(y0 - 1000*(a));
aux.clear();
aux.push_back(pt1);
aux.push_back(pt2);
lineSegments.push_back(aux);
line(outputImg, pt1, pt2, CV_RGB(0, 0, 0), 1, 8);
}
#else
vector<Vec4i> lines;
int houghThreshold = 70;
if(imgGRAY.cols*imgGRAY.rows < 400*400)
houghThreshold = 100;
cv::HoughLinesP(imgCanny, lines, 1, CV_PI/180, houghThreshold, 10,10);
while(lines.size() > MAX_NUM_LINES)
{
lines.clear();
houghThreshold += 10;
cv::HoughLinesP(imgCanny, lines, 1, CV_PI/180, houghThreshold, 10, 10);
}
for(size_t i=0; i<lines.size(); i++)
{
Point pt1, pt2;
pt1.x = lines[i][0];
pt1.y = lines[i][1];
pt2.x = lines[i][2];
pt2.y = lines[i][3];
line(outputImg, pt1, pt2, CV_RGB(0,0,0), 2);
/*circle(outputImg, pt1, 2, CV_RGB(255,255,255), CV_FILLED);
circle(outputImg, pt1, 3, CV_RGB(0,0,0),1);
circle(outputImg, pt2, 2, CV_RGB(255,255,255), CV_FILLED);
circle(outputImg, pt2, 3, CV_RGB(0,0,0),1);*/
// Store into vector of pairs of Points for msac
aux.clear();
aux.push_back(pt1);
aux.push_back(pt2);
lineSegments.push_back(aux);
}
#endif
// Multiple vanishing points
std::vector<cv::Mat> vps; // vector of vps: vps[vpNum], with vpNum=0...numDetectedVps
std::vector<std::vector<int> > CS; // index of Consensus Set for all vps: CS[vpNum] is a vector containing indexes of lineSegments belonging to Consensus Set of vp numVp
std::vector<int> numInliers;
std::vector<std::vector<std::vector<cv::Point> > > lineSegmentsClusters;
// Call msac function for multiple vanishing point estimation
msac.multipleVPEstimation(lineSegments, lineSegmentsClusters, numInliers, vps, numVps);
for(int v=0; v<vps.size(); v++)
{
printf("VP %d (%.3f, %.3f, %.3f)", v, vps[v].at<float>(0,0), vps[v].at<float>(1,0), vps[v].at<float>(2,0));
fflush(stdout);
double vpNorm = cv::norm(vps[v]);
if(fabs(vpNorm - 1) < 0.001)
{
printf("(INFINITE)");
fflush(stdout);
}
printf("\n");
}
// Draw line segments according to their cluster
msac.drawCS(outputImg, lineSegmentsClusters, vps);
}
vector<vector<vector<Point> > > Nieto::vp(const Mat1b &inBinaryFrameFiltrado, Mat3b &inVanishingPointImage, const Rect &roi, const int maxNumLines, int houghThresholdInicial, int houghStep, double houghMinLineLength, double houghMaxLineGap) {
double tempoInicio = static_cast<double>(getTickCount());
// pega somente a regi�o de interesse
Mat1b mascaraRoi = Mat1b(inBinaryFrameFiltrado.size(), uchar(0));
mascaraRoi(Rect(roi.x, roi.y, roi.width, roi.height)).setTo(255);
Mat1b binaryFrameFiltradoMasked;
cv::bitwise_and(inBinaryFrameFiltrado, mascaraRoi, binaryFrameFiltradoMasked);
if (display) cvtColor(inBinaryFrameFiltrado, inVanishingPointImage, CV_GRAY2BGR);
// Hough
vector<vector<Point> > lineSegments;
vector<Point> aux;
vector<Vec4i> lines;
int houghThreshold = houghThresholdInicial;
cv::HoughLinesP(binaryFrameFiltradoMasked, lines, 1, CV_PI / 180, houghThreshold, houghMinLineLength, houghMaxLineGap);
while (lines.size() > maxNumLines) {
lines.clear();
houghThreshold += houghStep;
cv::HoughLinesP(binaryFrameFiltradoMasked, lines, 1, CV_PI / 180, houghThreshold, houghMinLineLength, houghMaxLineGap);
}
for (size_t i = 0; i<lines.size(); i++) {
Point pt1, pt2;
pt1.x = lines[i][0];
pt1.y = lines[i][1];
pt2.x = lines[i][2];
pt2.y = lines[i][3];
// modificado
int dx = abs(pt2.x - pt1.x);
int dy = abs(pt2.y - pt1.y);
if (1.0*dx / 3.0 > dy) {
if (display) line(inVanishingPointImage, pt1, pt2, CV_RGB(0, 0, 255), 1);
// continue;
} else{
if (display) line(inVanishingPointImage, pt1, pt2, CV_RGB(0, 255, 0), 1);
}
// Store into vector of pairs of Points for msac
aux.clear();
aux.push_back(pt1);
aux.push_back(pt2);
lineSegments.push_back(aux);
}
// Multiple vanishing points
vector<Mat> vps; // vector of vps: vps[vpNum], with vpNum=0...numDetectedVps
vector<vector<int> > CS; // index of Consensus Set for all vps: CS[vpNum] is a vector containing indexes of lineSegments belonging to Consensus Set of vp numVp
vector<int> numInliers;
vector<vector<vector<Point> > > lineSegmentsClusters;
MSAC msac;
bool msac_verbose = false;
int numVps = 1;
msac.init(MODE_NIETO, inBinaryFrameFiltrado.size(), msac_verbose);
msac.multipleVPEstimation(lineSegments, lineSegmentsClusters, numInliers, vps, numVps); // Call msac function for multiple vanishing point estimation
msac.drawCS(inVanishingPointImage, lineSegmentsClusters, vps); // Draw line segments according to their cluster
// sa�das
this->houghLines = lineSegmentsClusters;
this->vanishingPoint = vps;
// calcula o tempo de execu��o
double tempoFim = static_cast<double>(getTickCount());
double tempoExecutando = ((tempoFim - tempoInicio) / getTickFrequency()) * 1000;
// exibe as sa�das definidas (texto e/ou imagem)
if (verbose) cout << "- nieto.vp: " << tempoExecutando << " ms" << endl;
if (display) imshow("Vanishing Point", inVanishingPointImage);
return { lineSegments };
}
