SampleMarkerlessCreator.cpp

This is an example that demonstrates the use of FernImageDetector to train a Fern classifier.

using namespace std;
using namespace alvar;
int main(int argc, char *argv[])
{
try {
// Output usage message
std::string filename(argv[0]);
filename = filename.substr(filename.find_last_of('\\') + 1);
std::cout << "SampleMarkerlessCreator" << std::endl;
std::cout << "=======================" << std::endl;
std::cout << std::endl;
std::cout << "Description:" << std::endl;
std::cout << " This is an example of how to use the 'FernImageDetector' class" << std::endl;
std::cout << " to train a Fern classifier for markerless image-based tracking." << std::endl;
std::cout << " The image should contain many unique features and be in the range" << std::endl;
std::cout << " of 200x200 to 500x500 pixels. A '.dat' file will be saved in the" << std::endl;
std::cout << " same directory as the image and can be used with the" << std::endl;
std::cout << " SampleMarkerlessDetector sample." << std::endl;
std::cout << std::endl;
std::cout << "Usage:" << std::endl;
std::cout << " " << filename << " filename" << std::endl;
std::cout << std::endl;
std::cout << " filename filename of image to train" << std::endl;
std::cout << std::endl;
if (argc < 2) {
std::cout << "Filename not specified." << std::endl;
return 0;
}
std::cout << "Training classifier." << std::endl;
std::string imageFilename(argv[1]);
fernDetector.train(imageFilename);
std::cout << "Writing classifier." << std::endl;
std::string classifierFilename = imageFilename + ".dat";
if (!fernDetector.write(classifierFilename)) {
std::cout << "Writing classifier failed." << std::endl;
return 1;
}
return 0;
}
catch (const std::exception &e) {
std::cout << "Exception: " << e.what() << endl;
}
catch (...) {
std::cout << "Exception: unknown" << std::endl;
}
}


ar_track_alvar
Author(s): Scott Niekum
autogenerated on Thu Jun 6 2019 19:27:23