void fitLines(const cv::Mat &edges, LFLineFitter &lineFitter)
{
Ptr<Image<uchar> > fdcmEdges;
cv2fdcm(edges, fdcmEdges);
lineFitter.Init();
lineFitter.FitLine(fdcmEdges);
}
void EIEdgeImage::Read(LFLineFitter &lf)
{
SafeRelease();
width_ = lf.rWidth();
height_ = lf.rHeight();
nLines_ = lf.rNLineSegments();
LFLineSegment* lineSegmentMap = lf.rOutputEdgeMap();
lines_ = new LFLineSegment[nLines_];
for (int i=0 ; i<nLines_ ; i++)
lines_[i] = lineSegmentMap[i];
SetLines2Grid();
SetDirections();
}
void main(int argc, char *argv[])
{
//IplImage *inputImage=NULL;
Image<uchar> *inputImage=NULL;
LFLineFitter lf;
if(argc != 4)
{
std::cerr<<"[Syntax] fitline input_edgeMap.pgm output_line.txt output_edgeMap.pgm"<<std::endl;
exit(0);
}
string imageName(argv[1]);
string outFilename(argv[2]);
string outputImageName(argv[3]);
//string imageName("data/hat_edges.pgm");
//string outFilename("data/hat_edges.txt");
//string outputImageName("data/hat_edges_display.pgm");
//inputImage = cvLoadImage(imageName.c_str(),0);
inputImage = ImageIO::LoadPGM(imageName.c_str());
if(inputImage==NULL)
{
std::cerr<<"[ERROR] Fail in reading image "<<imageName<<std::endl;
exit(0);
}
lf.Init();
lf.Configure("para_template_line_fitter.txt");
lf.FitLine(inputImage);
lf.DisplayEdgeMap(inputImage,outputImageName.c_str());
lf.SaveEdgeMap(outFilename.c_str());
//cvReleaseImage(&inputImage);
delete inputImage;
};
void computeNormals(const cv::Mat &edges, cv::Mat &normals, cv::Mat &orientationIndices)
{
//TODO: move up
const int directionsCount = 60;
LFLineFitter lineFitter;
fitLines(edges, lineFitter);
Mat linearMap(edges.size(), CV_8UC1, Scalar(0));
Mat linearMapNormals(edges.size(), CV_32FC2, Scalar::all(std::numeric_limits<float>::quiet_NaN()));
Mat linearMapOrientationIndices(edges.size(), CV_32SC1, Scalar(-1));
for (int i = 0; i < lineFitter.rNLineSegments(); ++i)
{
cv::Point start(lineFitter.outEdgeMap_[i].sx_, lineFitter.outEdgeMap_[i].sy_);
cv::Point end(lineFitter.outEdgeMap_[i].ex_, lineFitter.outEdgeMap_[i].ey_);
LineIterator edgelsIterator(linearMap, start, end);
for(int j = 0; j < edgelsIterator.count; ++j, ++edgelsIterator)
{
**edgelsIterator = 255;
Vec2f normal(lineFitter.outEdgeMap_[i].normal_.x, lineFitter.outEdgeMap_[i].normal_.y);
linearMapNormals.at<Vec2f>(edgelsIterator.pos()) = normal;
linearMapOrientationIndices.at<int>(edgelsIterator.pos()) = theta2Index(lineFitter.outEdgeMap_[i].Theta(), directionsCount);
}
}
// imshow("edges", edges);
// imshow("linearMap", linearMap);
// waitKey();
Mat dt, labels;
distanceTransform(~linearMap, dt, labels, CV_DIST_L2, CV_DIST_MASK_PRECISE, DIST_LABEL_PIXEL);
CV_Assert(linearMap.type() == CV_8UC1);
CV_Assert(labels.type() == CV_32SC1);
std::map<int, cv::Point> label2position;
for (int i = 0; i < linearMap.rows; ++i)
{
for (int j = 0; j < linearMap.cols; ++j)
{
if (linearMap.at<uchar>(i, j) != 0)
{
//TODO: singal error if the label already exists
label2position[labels.at<int>(i, j)] = cv::Point(j, i);
}
}
}
orientationIndices.create(edges.size(), CV_32SC1);
orientationIndices = -1;
normals.create(edges.size(), CV_32FC2);
normals = Scalar::all(std::numeric_limits<float>::quiet_NaN());
for (int i = 0; i < edges.rows; ++i)
{
for (int j = 0; j < edges.cols; ++j)
{
// if (edges.at<uchar>(i, j) != 0)
cv::Point nearestEdgelPosition = label2position[labels.at<int>(i, j)];
normals.at<Vec2f>(i, j) = linearMapNormals.at<Vec2f>(nearestEdgelPosition);
orientationIndices.at<int>(i, j) = linearMapOrientationIndices.at<int>(nearestEdgelPosition);
CV_Assert(orientationIndices.at<int>(i, j) >= 0 && orientationIndices.at<int>(i, j) < directionsCount);
}
}
/*
Mat vis(orientations.size(), CV_8UC1, Scalar(0));
for (int i = 0; i < orientations.rows; ++i)
{
for (int j = 0; j < orientations.cols; ++j)
{
Vec2f elem = orientations.at<Vec2f>(i, j);
vis.at<uchar>(i, j) = (cvIsNaN(elem[0]) || cvIsNaN(elem[1])) ? 0 : 255;
}
}
imshow("final or", vis);
waitKey();
*/
}