int main(int argc, char **argv){
std::string filename("");
unsigned int scale = 5, dmst = 2, window = 3, detectorType = 0, descriptorType = 0, distanceType = 2, strategy = 0;
double baseSigma = 0.2, sigmaStep = 1.4, minPeak = 0.34, minPeakDistance = 0.001, acceptanceSigma = 0.1, success = 0.95, inlier = 0.4, matchingThreshold = 0.4;
bool useMaxRange = false;
int i = 1;
while(i < argc){
if(strncmp("-filename", argv[i], sizeof("-filename")) == 0 ){
filename = argv[++i];
i++;
} else if(strncmp("-detector", argv[i], sizeof("-detector")) == 0 ){
detectorType = atoi(argv[++i]);
i++;
} else if(strncmp("-descriptor", argv[i], sizeof("-descriptor")) == 0 ){
descriptorType = atoi(argv[++i]);
i++;
} else if(strncmp("-distance", argv[i], sizeof("-distance")) == 0 ){
distanceType = atoi(argv[++i]);
i++;
} else if(strncmp("-strategy", argv[i], sizeof("-strategy")) == 0 ){
strategy = atoi(argv[++i]);
i++;
} else if(strncmp("-baseSigma", argv[i], sizeof("-baseSigma")) == 0 ){
baseSigma = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-sigmaStep", argv[i], sizeof("-sigmaStep")) == 0 ){
sigmaStep = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-minPeak", argv[i], sizeof("-minPeak")) == 0 ){
minPeak = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-minPeakDistance", argv[i], sizeof("-minPeakDistance")) == 0 ){
minPeakDistance = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-scale", argv[i], sizeof("-scale")) == 0 ){
scale = atoi(argv[++i]);
i++;
} else if(strncmp("-dmst", argv[i], sizeof("-dmst")) == 0 ){
dmst = atoi(argv[++i]);
i++;
} else if(strncmp("-window", argv[i], sizeof("-window")) == 0 ){
window = atoi(argv[++i]);
i++;
} else if(strncmp("-acceptanceSigma", argv[i], sizeof("-acceptanceSigma")) == 0 ){
acceptanceSigma = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-success", argv[i], sizeof("-success")) == 0 ){
success = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-inlier", argv[i], sizeof("-inlier")) == 0 ){
inlier = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-matchingThreshold", argv[i], sizeof("-matchingThreshold")) == 0 ){
matchingThreshold = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-localSkip", argv[i], sizeof("-localSkip")) == 0 ){
m_localSkip = atoi(argv[++i]);
i++;
} else if(strncmp("-help", argv[i], sizeof("-localSkip")) == 0 ){
help();
exit(0);
} else {
i++;
}
}
if(!filename.size()){
help();
exit(-1);
}
CarmenLogWriter writer;
CarmenLogReader reader;
m_sensorReference = LogSensorStream(&reader, &writer);
m_sensorReference.load(filename);
SimpleMinMaxPeakFinder *m_peakMinMax = new SimpleMinMaxPeakFinder(minPeak, minPeakDistance);
std::string detector("");
switch(detectorType){
case 0:
m_detectorCurvature = new CurvatureDetector(m_peakMinMax, scale, baseSigma, sigmaStep, dmst);
m_detectorCurvature->setUseMaxRange(useMaxRange);
m_detector = m_detectorCurvature;
detector = "curvature";
break;
case 1:
m_detectorNormalEdge = new NormalEdgeDetector(m_peakMinMax, scale, baseSigma, sigmaStep, window);
m_detectorNormalEdge->setUseMaxRange(useMaxRange);
m_detector = m_detectorNormalEdge;
detector = "edge";
break;
case 2:
m_detectorNormalBlob = new NormalBlobDetector(m_peakMinMax, scale, baseSigma, sigmaStep, window);
m_detectorNormalBlob->setUseMaxRange(useMaxRange);
m_detector = m_detectorNormalBlob;
detector = "blob";
break;
case 3:
m_detectorRange = new RangeDetector(m_peakMinMax, scale, baseSigma, sigmaStep);
m_detectorRange->setUseMaxRange(useMaxRange);
m_detector = m_detectorRange;
detector = "range";
break;
default:
std::cerr << "Wrong detector type" << std::endl;
exit(-1);
}
HistogramDistance<double> *dist = NULL;
std::string distance("");
switch(distanceType){
case 0:
dist = new EuclideanDistance<double>();
distance = "euclid";
break;
case 1:
dist = new Chi2Distance<double>();
distance = "chi2";
break;
case 2:
dist = new SymmetricChi2Distance<double>();
distance = "symchi2";
break;
case 3:
dist = new BatthacharyyaDistance<double>();
distance = "batt";
break;
case 4:
dist = new KullbackLeiblerDistance<double>();
distance = "kld";
break;
case 5:
dist = new JensenShannonDistance<double>();
distance = "jsd";
break;
default:
std::cerr << "Wrong distance type" << std::endl;
exit(-1);
}
std::string descriptor("");
switch(descriptorType){
case 0:
m_betaGenerator = new BetaGridGenerator(0.02, 0.5, 4, 12);
m_betaGenerator->setDistanceFunction(dist);
m_descriptor = m_betaGenerator;
descriptor = "beta";
break;
case 1:
m_shapeGenerator = new ShapeContextGenerator(0.02, 0.5, 4, 12);
m_shapeGenerator->setDistanceFunction(dist);
m_descriptor = m_shapeGenerator;
descriptor = "shape";
break;
default:
std::cerr << "Wrong descriptor type" << std::endl;
exit(-1);
}
switch(strategy){
case 0:
m_ransac = new RansacFeatureSetMatcher(acceptanceSigma * acceptanceSigma * 5.99, success, inlier, matchingThreshold, acceptanceSigma * acceptanceSigma * 3.84, false);
break;
case 1:
m_ransac = new RansacMultiFeatureSetMatcher(acceptanceSigma * acceptanceSigma * 5.99, success, inlier, matchingThreshold, acceptanceSigma * acceptanceSigma * 3.84, false);
break;
default:
std::cerr << "Wrong strategy type" << std::endl;
exit(-1);
}
std::cerr << "Processing file:\t" << filename << "\nDetector:\t\t" << detector << "\nDescriptor:\t\t" << descriptor << "\nDistance:\t\t" << distance << std::endl;
m_sensorReference.seek(0,END);
unsigned int end = m_sensorReference.tell();
m_sensorReference.seek(0,BEGIN);
m_pointsReference.resize(end + 1);
m_posesReference.resize(end + 1);
detectLog();
countLog();
describeLog();
std::string outfile = filename;
timerclear(&ransacTime);
std::string bar(50,' ');
bar[0] = '#';
unsigned int progress = 0;
for(unsigned int i =0; i < m_pointsReference.size(); i++){
unsigned int currentProgress = (i*100)/(m_pointsReference.size() - 1);
if (progress < currentProgress){
progress = currentProgress;
bar[progress/2] = '#';
std::cout << "\rMatching [" << bar << "] " << progress << "%" << std::flush;
}
match(i);
}
std::cout << " done." << std::endl;
std::stringstream matchFile;
std::stringstream errorFile;
std::stringstream timeFile;
matchFile << outfile << "_" << detector << "_" << descriptor << "_" << distance << "_match.dat";
errorFile << outfile << "_" << detector << "_" << descriptor << "_" << distance << "_error.dat";
timeFile << outfile << "_" << detector << "_" << descriptor << "_" << distance << "_time.dat";
std::ofstream matchOut(matchFile.str().c_str());
std::ofstream errorOut(errorFile.str().c_str());
std::ofstream timeOut(timeFile.str().c_str());
matchOut << "# Number of matches according to various strategies" << std::endl;
matchOut << "# The valid matches are the one with at least n correspondences in the inlier set " << std::endl;
matchOut << "# where n = {0, 3, 5, 7, 9, 11, 13, 15}, one for each line " << std::endl;
matchOut << "# optimal \t correspondence \t residual \v valid" << std::endl;
errorOut << "# Mean error according to various strategies" << std::endl;
errorOut << "# The valid matches are the one with at least n correspondences in the inlier set " << std::endl;
errorOut << "# where n = {0, 3, 5, 7, 9, 11, 13, 15}, one for each line " << std::endl;
errorOut << "# optimal \t correspondence \t residual \v valid" << std::endl;
timeOut << "# Total time spent for the various steps" << std::endl;
timeOut << "# detection \t description \t RANSAC" << std::endl;
for(unsigned int c = 0; c < 8; c++){
matchOut << m_match[c] << "\t" << m_matchC[c] << "\t" << m_matchR[c] << "\t" << m_valid[c] << std::endl;
errorOut << m_error[c]/m_valid[c] << "\t" << m_errorC[c]/m_valid[c] << "\t" << m_errorR[c]/m_valid[c] << "\t" << m_valid[c] << std::endl;
}
timeOut << double(detectTime.tv_sec) + 1e-06 * double(detectTime.tv_usec) << "\t"
<< double(describeTime.tv_sec) + 1e-06 * double(describeTime.tv_usec) << "\t"
<< double(ransacTime.tv_sec) + 1e-06 * double(ransacTime.tv_usec) << std::endl;
}
int main(int argc, char **argv){
std::string filename(""), vocabulary("Vocabulary.voc");
unsigned int scale = 5, dmst = 2, window = 3, detectorType = 0, descriptorType = 0, distanceType = 2;
double baseSigma = 0.2, sigmaStep = 1.4, minPeak = 0.34, minPeakDistance = 0.001;
bool useMaxRange = false;
int i = 1;
while(i < argc){
if(strncmp("-filename", argv[i], sizeof("-filename")) == 0 ){
filename = argv[++i];
i++;
} else if(strncmp("-vocabulary", argv[i], sizeof("-vocabulary")) == 0 ){
vocabulary = argv[++i];
i++;
} else if(strncmp("-detector", argv[i], sizeof("-detector")) == 0 ){
detectorType = atoi(argv[++i]);
i++;
} else if(strncmp("-descriptor", argv[i], sizeof("-descriptor")) == 0 ){
descriptorType = atoi(argv[++i]);
i++;
} else if(strncmp("-distance", argv[i], sizeof("-distance")) == 0 ){
distanceType = atoi(argv[++i]);
i++;
} else if(strncmp("-baseSigma", argv[i], sizeof("-baseSigma")) == 0 ){
baseSigma = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-sigmaStep", argv[i], sizeof("-sigmaStep")) == 0 ){
sigmaStep = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-minPeak", argv[i], sizeof("-minPeak")) == 0 ){
minPeak = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-minPeakDistance", argv[i], sizeof("-minPeakDistance")) == 0 ){
minPeakDistance = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-scale", argv[i], sizeof("-scale")) == 0 ){
scale = atoi(argv[++i]);
i++;
} else if(strncmp("-dmst", argv[i], sizeof("-dmst")) == 0 ){
dmst = atoi(argv[++i]);
i++;
} else if(strncmp("-window", argv[i], sizeof("-window")) == 0 ){
window = atoi(argv[++i]);
i++;
} else if(strncmp("-help", argv[i], sizeof("-localSkip")) == 0 ){
help();
exit(0);
} else {
i++;
}
}
if(!filename.size()){
help();
exit(-1);
}
CarmenLogWriter writer;
CarmenLogReader reader;
m_sensorReference = LogSensorStream(&reader, &writer);
m_sensorReference.load(filename);
SimpleMinMaxPeakFinder *m_peakMinMax = new SimpleMinMaxPeakFinder(minPeak, minPeakDistance);
std::string detector("");
switch(detectorType){
case 0:
m_detectorCurvature = new CurvatureDetector(m_peakMinMax, scale, baseSigma, sigmaStep, dmst);
m_detectorCurvature->setUseMaxRange(useMaxRange);
m_detector = m_detectorCurvature;
detector = "curvature";
break;
case 1:
m_detectorNormalEdge = new NormalEdgeDetector(m_peakMinMax, scale, baseSigma, sigmaStep, window);
m_detectorNormalEdge->setUseMaxRange(useMaxRange);
m_detector = m_detectorNormalEdge;
detector = "edge";
break;
case 2:
m_detectorNormalBlob = new NormalBlobDetector(m_peakMinMax, scale, baseSigma, sigmaStep, window);
m_detectorNormalBlob->setUseMaxRange(useMaxRange);
m_detector = m_detectorNormalBlob;
detector = "blob";
break;
case 3:
m_detectorRange = new RangeDetector(m_peakMinMax, scale, baseSigma, sigmaStep);
m_detectorRange->setUseMaxRange(useMaxRange);
m_detector = m_detectorRange;
detector = "range";
break;
default:
std::cerr << "Wrong detector type" << std::endl;
exit(-1);
}
HistogramDistance<double> *dist = NULL;
std::string distance("");
switch(distanceType){
case 0:
dist = new EuclideanDistance<double>();
distance = "euclid";
break;
case 1:
dist = new Chi2Distance<double>();
distance = "chi2";
break;
case 2:
dist = new SymmetricChi2Distance<double>();
distance = "symchi2";
break;
case 3:
dist = new BatthacharyyaDistance<double>();
distance = "batt";
break;
case 4:
dist = new KullbackLeiblerDistance<double>();
distance = "kld";
break;
case 5:
dist = new JensenShannonDistance<double>();
distance = "jsd";
break;
default:
std::cerr << "Wrong distance type" << std::endl;
exit(-1);
}
std::string descriptor("");
switch(descriptorType){
case 0:
m_betaGenerator = new BetaGridGenerator(0.02, 0.5, 4, 12);
m_betaGenerator->setDistanceFunction(dist);
m_descriptor = m_betaGenerator;
descriptor = "beta";
break;
case 1:
m_shapeGenerator = new ShapeContextGenerator(0.02, 0.5, 4, 12);
m_shapeGenerator->setDistanceFunction(dist);
m_descriptor = m_shapeGenerator;
descriptor = "shape";
break;
default:
std::cerr << "Wrong descriptor type" << std::endl;
exit(-1);
}
std::cerr << "Processing file:\t" << filename << "\nDetector:\t\t" << detector << "\nDescriptor:\t\t" << descriptor << "\nDistance:\t\t" << distance << "\nVocabulary:\t\t" << vocabulary << std::endl;
std::ifstream vocabularyStream(vocabulary.c_str());
boost::archive::binary_iarchive vocabularyArchive(vocabularyStream);
vocabularyArchive >> histogramVocabulary;
m_sensorReference.seek(0,END);
unsigned int end = m_sensorReference.tell();
m_sensorReference.seek(0,BEGIN);
m_pointsReference.resize(end + 1);
m_posesReference.resize(end + 1);
writePoses();
try {
std::string featureFile = filename.substr(0,filename.find_last_of('.')) + ".flt";
std::ifstream featureStream(featureFile.c_str());
boost::archive::binary_iarchive featureArchive(featureStream);
std::cout << "Loading feature file " << featureFile << " ...";
featureArchive >> m_pointsReference;
std::cout << " done." << std::endl;
} catch(boost::archive::archive_exception& exc) {
detectLog();
countLog();
describeLog();
}
std::string bowFile = filename.substr(0,filename.find_last_of('.')) + ".bow";
std::ofstream bowStream(bowFile.c_str());
writeBoW(bowStream);
}
int main(int argc, char **argv){
std::string filename("");
unsigned int scale = 5, dmst = 2, window = 3, detectorType = 0, descriptorType = 0, distanceType = 2, strategy = 0;
double baseSigma = 0.2, sigmaStep = 1.4, minPeak = 0.34, minPeakDistance = 0.001, success = 0.95, inlier = 0.4, matchingThreshold = 0.4;
bool useMaxRange = false;
int i = 1;
while(i < argc){
if(strncmp("-filename", argv[i], sizeof("-filename")) == 0 ){
filename = argv[++i];
i++;
} else if(strncmp("-detector", argv[i], sizeof("-detector")) == 0 ){
detectorType = atoi(argv[++i]);
i++;
} else if(strncmp("-descriptor", argv[i], sizeof("-descriptor")) == 0 ){
descriptorType = atoi(argv[++i]);
i++;
} else if(strncmp("-corresp", argv[i], sizeof("-corresp")) == 0 ){
corresp = atoi(argv[++i]);
i++;
} else if(strncmp("-distance", argv[i], sizeof("-distance")) == 0 ){
distanceType = atoi(argv[++i]);
i++;
} else if(strncmp("-baseSigma", argv[i], sizeof("-baseSigma")) == 0 ){
baseSigma = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-sigmaStep", argv[i], sizeof("-sigmaStep")) == 0 ){
sigmaStep = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-minPeak", argv[i], sizeof("-minPeak")) == 0 ){
minPeak = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-minPeakDistance", argv[i], sizeof("-minPeakDistance")) == 0 ){
minPeakDistance = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-scale", argv[i], sizeof("-scale")) == 0 ){
scale = atoi(argv[++i]);
i++;
} else if(strncmp("-dmst", argv[i], sizeof("-dmst")) == 0 ){
dmst = atoi(argv[++i]);
i++;
} else if(strncmp("-window", argv[i], sizeof("-window")) == 0 ){
scale = atoi(argv[++i]);
i++;
} else if(strncmp("-acceptanceSigma", argv[i], sizeof("-acceptanceSigma")) == 0 ){
acceptanceSigma = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-success", argv[i], sizeof("-success")) == 0 ){
success = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-inlier", argv[i], sizeof("-inlier")) == 0 ){
inlier = strtod(argv[++i], NULL);
i++;
} else if(strncmp("-matchingThreshold", argv[i], sizeof("-matchingThreshold")) == 0 ){
matchingThreshold = strtod(argv[++i], NULL);
i++;
} else {
i++;
}
}
if(!filename.size()){
help();
exit(-1);
}
CarmenLogWriter writer;
CarmenLogReader reader;
m_sensorReference = LogSensorStream(&reader, &writer);
m_sensorReference.load(filename);
SimpleMinMaxPeakFinder *m_peakMinMax = new SimpleMinMaxPeakFinder(minPeak, minPeakDistance);
std::string detector("");
switch(detectorType){
case 0:
m_detectorCurvature = new CurvatureDetector(m_peakMinMax, scale, baseSigma, sigmaStep, dmst);
m_detectorCurvature->setUseMaxRange(useMaxRange);
m_detector = m_detectorCurvature;
detector = "curvature";
break;
case 1:
m_detectorNormalEdge = new NormalEdgeDetector(m_peakMinMax, scale, baseSigma, sigmaStep, window);
m_detectorNormalEdge->setUseMaxRange(useMaxRange);
m_detector = m_detectorNormalEdge;
detector = "edge";
break;
case 2:
m_detectorNormalBlob = new NormalBlobDetector(m_peakMinMax, scale, baseSigma, sigmaStep, window);
m_detectorNormalBlob->setUseMaxRange(useMaxRange);
m_detector = m_detectorNormalBlob;
detector = "blob";
break;
case 3:
m_detectorRange = new RangeDetector(m_peakMinMax, scale, baseSigma, sigmaStep);
m_detectorRange->setUseMaxRange(useMaxRange);
m_detector = m_detectorRange;
detector = "range";
break;
default:
std::cerr << "Wrong detector type" << std::endl;
exit(-1);
}
HistogramDistance<double> *dist = NULL;
std::string distance("");
switch(distanceType){
case 0:
dist = new EuclideanDistance<double>();
distance = "euclid";
break;
case 1:
dist = new Chi2Distance<double>();
distance = "chi2";
break;
case 2:
dist = new SymmetricChi2Distance<double>();
distance = "symchi2";
break;
case 3:
dist = new BatthacharyyaDistance<double>();
distance = "batt";
break;
case 4:
dist = new KullbackLeiblerDistance<double>();
distance = "kld";
break;
case 5:
dist = new JensenShannonDistance<double>();
distance = "jsd";
break;
default:
std::cerr << "Wrong distance type" << std::endl;
exit(-1);
}
std::string descriptor("");
switch(descriptorType){
case 0:
m_betaGenerator = new BetaGridGenerator(0.02, 0.5, 4, 12);
m_betaGenerator->setDistanceFunction(dist);
m_descriptor = m_betaGenerator;
descriptor = "beta";
break;
case 1:
m_shapeGenerator = new ShapeContextGenerator(0.02, 0.5, 4, 12);
m_shapeGenerator->setDistanceFunction(dist);
m_descriptor = m_shapeGenerator;
descriptor = "shape";
break;
default:
std::cerr << "Wrong descriptor type" << std::endl;
exit(-1);
}
std::cerr << "Processing file:\t" << filename << "\nDetector:\t\t" << detector << "\nDescriptor:\t\t" << descriptor << "\nDistance:\t\t" << distance << std::endl;
switch(strategy){
case 0:
m_ransac = new RansacFeatureSetMatcher(acceptanceSigma * acceptanceSigma * 5.99, success, inlier, matchingThreshold, acceptanceSigma * acceptanceSigma * 3.84, false);
break;
case 1:
m_ransac = new RansacMultiFeatureSetMatcher(acceptanceSigma * acceptanceSigma * 5.99, success, inlier, matchingThreshold, acceptanceSigma * acceptanceSigma * 3.84, false);
break;
default:
std::cerr << "Wrong strategy type" << std::endl;
exit(-1);
}
m_sensorReference.seek(0,END);
unsigned int end = m_sensorReference.tell();
m_sensorReference.seek(0,BEGIN);
m_pointsReference.resize(end + 1);
m_posesReference.resize(end + 1);
computeBoundingBox();
detectLog();
describeLog();
std::stringstream mapFile;
mapFile << filename << "_map.png";
/* cairo_surface_t * cairoMapSurface = cairo_pdf_surface_create(mapFile.str().c_str(), sizeX, sizeY);
cairo_surface_t * cairoOutSurface = cairo_pdf_surface_create(outFile.str().c_str(), sizeX, sizeY);*/
cairo_surface_t * cairoMapSurface = cairo_image_surface_create(CAIRO_FORMAT_ARGB32, sizeX, sizeY);
// cairo_surface_t * cairoMapSurface = cairo_svg_surface_create(mapFile.str().c_str(), sizeX, sizeY);
cairoMap = cairo_create(cairoMapSurface);
std::stringstream outDir;
outDir << filename << "_" << detector << "_" << descriptor << "_" << distance << "/";
mkdir(outDir.str().c_str(), S_IRWXU | S_IRWXG | S_IROTH | S_IXOTH);
computeMap();
std::string bar(50,' ');
bar[0] = '#';
unsigned int progress = 0;
for(unsigned int i =0; i < m_pointsReference.size(); i++){
unsigned int currentProgress = (i*100)/(m_pointsReference.size() - 1);
if (progress < currentProgress){
progress = currentProgress;
bar[progress/2] = '#';
std::cout << "\rMatching [" << bar << "] " << progress << "%" << std::flush;
}
std::stringstream outFile;
outFile << outDir.str() << "frame_";
outFile.width(4);
outFile.fill('0');
outFile << std::right << i << ".png";
cairo_surface_t * cairoOutSurface = cairo_image_surface_create(CAIRO_FORMAT_ARGB32, sizeX, sizeY);
// cairo_surface_t * cairoOutSurface = cairo_svg_surface_create(outFile.str().c_str(), sizeX, sizeY);
cairoOut = cairo_create(cairoOutSurface);
cairo_translate(cairoOut, -offsetX, -offsetY);
cairo_scale(cairoOut, scaleFactor, scaleFactor);
cairo_set_line_width(cairoOut, 1./scaleFactor);
match(i);
cairo_surface_write_to_png(cairoOutSurface, outFile.str().c_str());
cairo_surface_destroy(cairoOutSurface);
cairo_destroy(cairoOut);
}
std::cout << " done." << std::endl;
cairo_surface_write_to_png(cairoMapSurface, mapFile.str().c_str());
cairo_surface_destroy(cairoMapSurface);
cairo_destroy(cairoMap);
// cairo_show_page(cairoOut);
}