int main(int argc, char *argv[]){
LARGE_INTEGER frequency;
LARGE_INTEGER t1, t2;
double elapsedTime;
int ret = 0;
QueryPerformanceFrequency(&frequency);
QueryPerformanceCounter(&t1);
if(argc != 2){
printhelp();
return EXIT_FAILURE;
}
startLogger("log.txt");
readSettingsFromConfigFile(argv[1]);
setUpSpectrum();
logIt(DEBUG, "pathToSlice=%s", cfg.pathToSlice);
logIt(DEBUG, "pathToOutputReconstruction=%s", cfg.pathToOutputReconstruction);
setUpAttenuation();
logIt(INFO, "Everything set up successfully. Starting simulation...");
ret = simulation(cfg.pathToSlice, cfg.pathToOutputSinogram);
reconstruction(cfg.pathToOutputSinogram, cfg.pathToOutputReconstruction);
QueryPerformanceCounter(&t2);
elapsedTime = (double)(t2.QuadPart - t1.QuadPart) / frequency.QuadPart;
logIt(INFO, "Total computation time: %f seconds.", elapsedTime);
logIt(INFO, "Reconstructed image saved as %s. Exiting...", cfg.pathToOutputReconstruction);
logIt(DEBUG, "main(int argc, char *argv[]) finished.");
stopLogger();
return ret;
}
void main_constz() {
string gen_name, det_name, root_name;
string gen_prefix = "events_z";
string det_prefix = "measures_z";
string root_prefix = "reconstruction_z";
string str_buff;
string str_dat = ".dat";
string str_root = ".root";
stringstream ss;
double z_val;
for (int i = 0; i <= 30; i++) {
z_val = double(i);
cout << "Starting analysis with z = " << z_val << "..." << endl;
ss << z_val;
ss >> str_buff;
gen_name = gen_prefix + str_buff;
det_name = det_prefix + str_buff;
root_name = root_prefix + str_buff;
ss.clear();
cout << '\t' << "Generation..." << '\n' << endl;
generation(gen_name.c_str(), "CONST Z");
cout << '\t' << "Detector response..." << '\n' << endl;
detector(gen_name.c_str(), det_name.c_str());
cout << '\t' << "Reconstruction..." << '\n' << endl;
reconstruction(gen_name.c_str(), det_name.c_str(), root_name.c_str());
cout << '\n' << "-------------------------" << '\n' << endl;
}
}
int main(int argc, char* argv[])
{
std::ifstream in((argc>1)?argv[1]:"data/half.xyz");
std::istream_iterator<Point_3> begin(in);
std::istream_iterator<Point_3> end;
Perimeter perimeter(0.5);
Triangulation_3 dt(begin, end);
Reconstruction reconstruction(dt, perimeter);
reconstruction.run();
std::cout << reconstruction.number_of_outliers() << " outliers:\n" << std::endl;
BOOST_FOREACH(const Point_3& p, reconstruction.outliers()){
std::cout << p << std::endl;
}
std::cout << "Boundaries:" << std::endl ;
BOOST_FOREACH(const Vertex_on_boundary_range & vobr, reconstruction.boundaries()){
std::cout << "boundary\n";
// As we use BOOST_FOREACH we do not use the type Boundary_range
BOOST_FOREACH(Vertex_handle v, vobr){
std::cout << v->point() << std::endl;
}
}
int main(int argc, char* argv[])
{
std::ifstream in((argc>1)?argv[1]:"data/half.xyz");
std::istream_iterator<Point_3> begin(in);
std::istream_iterator<Point_3> end;
Triangulation_3 dt(begin,end);
Reconstruction reconstruction(dt);
reconstruction.run();
const TDS_2& tds = reconstruction.triangulation_data_structure_2();
std::cout << "solid produced with CGAL::Advancing_front_surface_reconstruction\n";
for(TDS_2::Face_iterator fit = tds.faces_begin();
fit != tds.faces_end();
++fit){
if(reconstruction.has_on_surface(fit)){
Triangulation_3::Facet f = fit->facet();
Triangulation_3::Cell_handle ch = f.first;
int ci = f.second;
Point_3 points[3];
for(int i = 0, j = 0; i < 4; i++){
if(ci != i){
points[j] = ch->vertex(i)->point();
j++;
}
}
std::cout << " facet normal "
<< CGAL::unit_normal(points[0],points[1], points[2]) << "\n"
<< " outer loop\n"
<< " vertex " << points[0] << "\n"
<< " vertex " << points[1] << "\n"
<< " vertex " << points[2] << "\n"
<< " endloop\n"
<< " endfacet\n";
}
}
std::cout << "endsolid" << std::endl;
return 0;
}
int draw_reconstruction_bitmap(PSIRT *psirt) {
int i=0,j=0;
double* pixel_intensity = reconstruction(psirt);
// DESENHAR
bmpfile_t *bmp = bmp_create(RES_X, RES_Y, 24);
for (i = 0; i < RES_X; i++) {
for (j = 0; j < RES_Y; j++) {
double pixel = pixel_intensity[i + (j * RES_X)];
// Alternativa 1: função linear simples
int paint_of_choice = (pixel * 255);
// Alternativa 2: função polinomial
#ifdef REC_PAINT_POLY
paint_of_choice = pow(pixel, 2) * 255;
#endif
// Alternativa 3: função exponencial
#ifdef REC_PAINT_EXP
paint_of_choice = pow(pixel, pixel) * 255;
#endif
// Alternativa 3: função customizada
#ifdef REC_PAINT_CUSTOM
paint_of_choice = 255;
if (pixel < .2)
paint_of_choice = 0;
else if (pixel < .4)
paint_of_choice = 255 / 4;
#endif
rgb_pixel_t pix = { paint_of_choice, paint_of_choice, paint_of_choice, 0 };
bmp_set_pixel(bmp, i, j, pix);
}
}
bmp_save(bmp, "psirt_output.bmp");
bmp_destroy(bmp);
free(pixel_intensity);
return i;
}
/**
perform reconstruction
*/
int rec(void)
{
std::string file_name = po.get("source");
std::cout << "loading source..." <<std::endl;
std::auto_ptr<ImageModel> handle(new ImageModel);
if (!handle->load_from_file(file_name.c_str()))
{
std::cout << "Load src file failed:" << handle->error_msg << std::endl;
return 1;
}
std::cout << "src loaded" <<std::endl;
if (po.has("flip"))
{
std::string flip_seq = po.get("flip");
for(unsigned int index = 0;index < flip_seq.length();++index)
if(flip_seq[index] >= '0' && flip_seq[index] <= '5')
{
handle->flip(flip_seq[index]-'0');
std::cout << "Flip image volume:" << (int)flip_seq[index]-'0' << std::endl;
}
}
// apply affine transformation
if (po.has("affine"))
{
std::cout << "reading transformation matrix" <<std::endl;
std::ifstream in(po.get("affine").c_str());
std::vector<double> T((std::istream_iterator<float>(in)),
(std::istream_iterator<float>()));
if(T.size() != 12)
{
std::cout << "Invalid transfformation matrix." <<std::endl;
return 1;
}
image::transformation_matrix<double> affine;
affine.load_from_transform(T.begin());
std::cout << "rotating images" << std::endl;
handle->rotate(handle->voxel.dim,affine);
}
float param[4] = {0,0,0,0};
int method_index = 0;
method_index = po.get("method",int(0));
std::cout << "method=" << method_index << std::endl;
if(method_index == 0) // DSI
param[0] = 17.0;
if(method_index == 2)
{
param[0] = 5;
param[1] = 15;
}
if(method_index == 3) // QBI-SH
{
param[0] = 0.006;
param[1] = 8;
}
if(method_index == 4)
param[0] = 1.2;
if(method_index == 6) // Convert to HARDI
{
param[0] = 1.25;
param[1] = 3000;
param[2] = 0.05;
}
if(method_index == 7)
{
if (po.has("template"))
{
std::cout << "loading external template:" << po.get("template") << std::endl;
fa_template_imp.template_file_name = po.get("template");
}
if(!fa_template_imp.load_from_file())
{
std::cout << "failed to locate template for QSDR reconstruction" << std::endl;
return -1;
}
param[0] = 1.2;
param[1] = 2.0;
std::fill(handle->mask.begin(),handle->mask.end(),1.0);
}
param[3] = 0.0002;
if(po.get("deconvolution",int(0)))
{
param[2] = 7;
}
if(po.get("decomposition",int(0)))
{
param[3] = 0.05;
param[4] = 10;
}
if (po.has("param0"))
{
param[0] = po.get("param0",float(0));
std::cout << "param0=" << param[0] << std::endl;
}
if (po.has("param1"))
{
param[1] = po.get("param1",float(0));
std::cout << "param1=" << param[1] << std::endl;
}
if (po.has("param2"))
{
param[2] = po.get("param2",float(0));
std::cout << "param2=" << param[2] << std::endl;
}
if (po.has("param3"))
{
param[3] = po.get("param3",float(0));
std::cout << "param3=" << param[3] << std::endl;
}
if (po.has("param4"))
{
param[4] = po.get("param4",float(0));
std::cout << "param4=" << param[4] << std::endl;
}
handle->voxel.ti.init(po.get("odf_order",int(8)));
handle->voxel.need_odf = po.get("record_odf",int(0));
handle->voxel.output_jacobian = po.get("output_jac",int(0));
handle->voxel.output_mapping = po.get("output_map",int(0));
handle->voxel.output_diffusivity = po.get("output_dif",int(1));
handle->voxel.output_tensor = po.get("output_tensor",int(0));
handle->voxel.output_rdi = po.get("output_rdi",int(1));
handle->voxel.odf_deconvolusion = po.get("deconvolution",int(0));
handle->voxel.odf_decomposition = po.get("decomposition",int(0));
handle->voxel.max_fiber_number = po.get("num_fiber",int(5));
handle->voxel.r2_weighted = po.get("r2_weighted",int(0));
handle->voxel.reg_method = po.get("reg_method",int(0));
handle->voxel.interpo_method = po.get("interpo_method",int(2));
handle->voxel.csf_calibration = po.get("csf_calibration",int(0)) && method_index == 4;
std::vector<unsigned int> shell;
calculate_shell(handle->voxel.bvalues,shell);
handle->voxel.half_sphere = po.get("half_sphere",
int(((shell.size() > 5) && (shell[1] - shell[0] <= 3)) ? 1:0));
handle->voxel.scheme_balance = po.get("scheme_balance",
int((shell.size() <= 5) && !shell.empty() && handle->voxel.bvalues.size()-shell.back() < 100 ? 1:0));
{
if(handle->voxel.need_odf)
std::cout << "record ODF in the fib file" << std::endl;
if(handle->voxel.odf_deconvolusion)
std::cout << "apply deconvolution" << std::endl;
if(handle->voxel.odf_decomposition)
std::cout << "apply decomposition" << std::endl;
if(handle->voxel.r2_weighted && method_index == 4)
std::cout << "r2 weighted is used for GQI" << std::endl;
}
if(po.has("other_image"))
{
QStringList file_list = QString(po.get("other_image").c_str()).split(";");
for(unsigned int i = 0;i < file_list.size();++i)
{
QStringList name_value = file_list[i].split(",");
if(name_value.size() != 2)
{
std::cout << "Invalid command: " << file_list[i].toStdString() << std::endl;
return 0;
}
if(!add_other_image(handle.get(),name_value[0],name_value[1],true))
return 0;
}
}
if(po.has("mask"))
{
std::string mask_file = po.get("mask");
std::cout << "reading mask..." << mask_file << std::endl;
gz_nifti header;
if(header.load_from_file(mask_file.c_str()))
{
image::basic_image<unsigned char,3> external_mask;
header.toLPS(external_mask);
if(external_mask.geometry() != handle->voxel.dim)
std::cout << "In consistent the mask dimension...using default mask" << std::endl;
else
handle->mask = external_mask;
}
else
std::cout << "fail reading the mask...using default mask" << std::endl;
}
if(po.get("motion_correction",int(0)))
{
std::vector<image::affine_transform<double> > arg;
unsigned int progress = 0;
bool terminated = false;
std::cout << "correct for motion and eddy current..." << std::endl;
rec_motion_correction(handle.get(),po.get("thread_count",int(std::thread::hardware_concurrency())),
arg,progress,terminated);
std::cout << "Done." <<std::endl;
}
std::cout << "start reconstruction..." <<std::endl;
const char* msg = reconstruction(handle.get(),method_index,
param,po.get("check_btable",int(1)),
po.get("thread_count",int(std::thread::hardware_concurrency())));
if (!msg)
std::cout << "Reconstruction finished:" << msg << std::endl;
return 0;
}
int main(int, char**)
{
cv::VideoCapture cap(1); // open the default camera
if(!cap.isOpened()){ // check if we succeeded
std::cout << "Cannot open the camera ! " << std::endl;
return -1;
}
cv::Mat frame; // Matrice dans laquelle on va récupérer l'image
while(true)
{
cap >> frame;
segmentation(frame);
cv::namedWindow("images",CV_WINDOW_AUTOSIZE);
cv::imshow("images", frame);
//cv::imwrite("/usr/users/promo2016/pierrard_reg/TL/test.png", frame);
std::vector<std::vector<cv::Point>> contours; // variable dans laquelle on récupèrera la liste des contours
cv::Mat frame_conv; // variable qui va contenir l'image en nuances de gris
cv::cvtColor(frame, frame_conv, CV_RGB2GRAY); // conversion de l'image courante en couleur en niveaux de gris
cv::findContours(frame_conv, contours, CV_RETR_EXTERNAL, CV_CHAIN_APPROX_NONE);
cv::Scalar color( rand()&255, rand()&255, rand()&255 ); // définition d'une couleur tirée aléatoirement
cv::Mat dst = cv::Mat::zeros(frame.rows, frame.cols, CV_8UC3); // Matrice qui va afficher le contour le plus long
if (contours.size() != 0) {
contours = find_longest_contour(contours);
cv::drawContours(dst, contours, -1, color);
std::vector<std::complex<double>> coeff = descripteur_fourier_normal(contours, 10);
double scale = 0.25 * std::min(frame.cols, frame.rows); // coefficient multiplicateur permettant d'obtenir des valeurs plus espacées des coordonnées des points
std::vector<std::vector<cv::Point>> contfil = reconstruction(coeff, 200, 10, z_moyen(contours), scale); // on récupère les points du contour reconstruit
cv::Mat dst2 = cv::Mat::zeros(frame.rows, frame.cols, CV_8UC3); // Matrice dans laquelle on affichera le contour reconstruit
cv::drawContours(dst2, contfil, -1, color);
cv::namedWindow("contours",CV_WINDOW_AUTOSIZE);
cv::imshow("contours", dst);
cv::namedWindow("reconstruction",CV_WINDOW_AUTOSIZE);
cv::imshow("reconstruction", dst2);
}
if(cv::waitKey(30) >= 0) break;
}
/* int c_max = 10;
std::map< std::string, std::vector< std::vector< std::complex<double> > > > database = fourier_descriptor_extraction(c_max);
for (auto& it : database) {
std::cout << it.first << " : " << std::endl;;
for (auto& it2 : it.second[0]) {
std::cout << it2 << ", ";
}
std::cout << std::endl;
}*/
return 0;
}
bool CalculationThread::singleStep(int x, int y) {
if(!seedmap) init();
Patch* block = 0;
if(x==-1)
block = seedmap->matchNext();
else {
int xlocal = ((float)x/400.0) * (seedmap->sourceImage_.size().width / blockSize_);
int ylocal = ((float)y/400.0) * (seedmap->sourceImage_.size().height / blockSize_);
block = seedmap->getPatch(xlocal,ylocal);
seedmap->match(block);
}
if (!block) return false;
if (!block->matches_) return true;
cv::Mat tmpImage = base_.clone();
float colorScale = 255.0 / seedmap->crit_.maxError_;
if(!block->finalMatch_) {
for(uint i=0; i<block->matches_->size(); i++) {
Match* match = block->matches_->at(i);
Polygon hull = match->hull_;
// highlight match
for(int j=0; j<4; j++)
cv::line(tmpImage, hull.verts[j], hull.verts[(j+1) % 4], cv::Scalar(0,255-match->error_*colorScale,match->error_*colorScale,100));
foreach(cv::Point2f p, block->pointsSrc_)
cv::line(tmpImage, p+cv::Point2f(block->x_,block->y_), p+cv::Point2f(block->x_,block->y_), cv::Scalar(0,155,00,100));
}
}
if(block->finalMatch_) {
// highlight match
cv::Mat selection(block->finalMatch_->t_.transformMat_, cv::Rect(0,0,3,2));
cv::Mat inverted;
invertAffineTransform(selection, inverted);
for (int i=0; i<2; i++)
for(int j=0; j<3; j++)
std::cout << inverted.at<float>(i,j) << " ";
for(int j=0; j<4; j++)
std::cout << block->finalMatch_->hull_.verts[j].m_v[0] << " " << block->finalMatch_->hull_.verts[j].m_v[1] << std::endl;
for(int j=0; j<4; j++)
cv::line(tmpImage, block->finalMatch_->hull_.verts[j], block->finalMatch_->hull_.verts[(j+1) % 4], cv::Scalar(100,255,0,100));
}
debugWidgetR->fromIpl( tmpImage, "preview" );
debugWidgetR->updateGL();
cv::Mat reconstruction(seedmap->debugReconstruction());
debugWidgetL->fromIpl( reconstruction, "reconstruction" );
debugWidgetL->updateGL();
return true;
}
