//--------------------------------------------------------------
void ArmCalibration::setup()
{
ofSetWindowTitle("arm calibration");
LoadFeatures();
gKinect = new ofxKinect();
if (IsFeatureKinectActive())
{
MAX_Z = 4.0f;
double fx_d, fy_d, fx_rgb, fy_rgb;
float cx_d, cy_d, cx_rgb, cy_rgb;
ofVec3f T_rgb;
ofMatrix4x4 R_rgb;
getKinectCalibData("data/calib/kinect-calib-27May.yml",
fx_d, fy_d, cx_d, cy_d,
fx_rgb, fy_rgb, cx_rgb, cy_rgb,
T_rgb, R_rgb);
gKinect->getCalibration().setCalibValues(
fx_d, fy_d, cx_d, cy_d,
fx_rgb, fy_rgb, cx_rgb, cy_rgb,
T_rgb, R_rgb);
gKinect->init();
gKinect->setVerbose(true);
gKinect->open();
}
arduino.setup();
}
void
MayaPlugin::Load(MObject& pluginObject)
{
char finalVersionStr[256];
#ifdef WIN32
sprintf_s(finalVersionStr, sizeof(finalVersionStr), "%s, %s @ %s", m_versionString.asChar(), __DATE__, __TIME__);
#else
sprintf(finalVersionStr, "%s, | %s @ %s", m_versionString.asChar(), __DATE__, __TIME__);
#endif
MFnPlugin plugin(pluginObject, m_authorString.asChar(), finalVersionStr, "Any");
LoadFeatures(plugin);
}
/** Constructor
*/
CSeqFeature::CSeqFeature()
:seqfeature_verbosity(0),
maxDuration(0),
minDuration(0),
numOfSeq(0),
numOfAllSeq(0),
featureDimension(0),
featureFile(""),
nnz(0),
density(0)
{
CTimer loadfeaturetime;
// decide the format string to use
if(sizeof(Scalar) == sizeof(double))
{
svec_feature_index_and_value_format = "%d:%lf";
scalar_value_format = "%lf";
}
else
{
svec_feature_index_and_value_format = "%d:%f";
scalar_value_format = "%f";
}
// get configurations
Configuration &config = Configuration::GetInstance();
featureFile = config.GetString("Data.featureFile");
if(config.IsSet("Data.verbosity"))
seqfeature_verbosity = config.GetInt("Data.verbosity");
// read dataset into memory
if(seqfeature_verbosity >= 1)
std::cout << "Loading feature file... "<< std::endl;
loadfeaturetime.Start();
LoadFeatures();
loadfeaturetime.Stop();
// in centralized dataset, serial computation mode
numOfAllSeq = numOfSeq;
if(seqfeature_verbosity >= 2)
{
std::cout << "loadfeaturetime : " << loadfeaturetime.CPUTotal() << std::endl;
}
}
int main(int argc, char** argv)
{
std::string p_feature_img = "";
std::string p_density = "";
std::string p_fn_points = "";
std::string p_out = "";
unsigned p_num = 250;
bool p_verbose = false;
unsigned p_repetitions = 1;
bool p_error = false;
bool p_save_density = true;
// parameters
asp::Parameters params = asp::parameters_default();
namespace po = boost::program_options;
po::options_description desc;
desc.add_options()
("help", "produce help message")
("features", po::value(&p_feature_img), "feature image (leave empty for uniform image)")
("density", po::value(&p_density), "density function image (leave empty for test function)")
("points", po::value(&p_fn_points), "file with points to use as seeds (for DDS)")
("out", po::value(&p_out), "filename of result file with samples points")
("num", po::value(&p_num), "number of points to sample")
("p_num_iterations", po::value(¶ms.num_iterations), "number of DALIC iterations")
("p_pds_mode", po::value(¶ms.pds_mode), "Poisson Disk Sampling method")
("p_seed_mean_radius_factor", po::value(¶ms.seed_mean_radius_factor), "size factor for initial cluster mean feature")
("p_coverage", po::value(¶ms.coverage), "DALIC cluster search factor")
("p_weight_compact", po::value(¶ms.weight_compact), "weight for compactness term")
("verbose", po::value(&p_verbose), "verbose")
("repetitions", po::value(&p_repetitions), "repetitions")
("error", po::value(&p_error), "error")
("save_density", po::value(&p_save_density), "save_density")
;
po::variables_map vm;
po::store(po::parse_command_line(argc, argv, desc), vm);
po::notify(vm);
if(vm.count("help")) {
std::cerr << desc << std::endl;
return 1;
}
// load
bool is_features_null = p_feature_img.empty();
bool is_density_null = p_density.empty();
Eigen::MatrixXf rho;
std::vector<Eigen::Vector3f> features;
int width = -1, height = -1;
if(is_density_null && is_features_null) {
std::cerr << "ERROR feature or density must not be both empty!" << std::endl;
return 1;
}
if(!is_features_null) {
features = LoadFeatures(p_feature_img, width, height);
if(p_verbose) std::cout << "Loaded features dim=" << width << "x" << height << "." << std::endl;
}
if(!is_density_null) {
rho = density::LoadDensity(p_density);
if(p_verbose) std::cout << "Loaded density dim=" << rho.rows() << "x" << rho.cols() << ", sum=" << rho.sum() << "." << std::endl;
}
if(is_features_null) {
width = rho.rows();
height = rho.cols();
features.resize(width*height, Eigen::Vector3f{1,1,1});
if(p_verbose) std::cout << "Created uniform features dim=" << rho.rows() << "x" << rho.cols() << "." << std::endl;
}
if(is_density_null) {
//rho = CreateDensity(p_size, p_size, [](float x, float y) { return TestDensityFunction(x,y); } );
rho = CreateDensity(width, height, [](float x, float y) { return 1.0f; } );
if(p_verbose) std::cout << "Created density dim=" << rho.rows() << "x" << rho.cols() << ", sum=" << rho.sum() << "." << std::endl;
}
assert(width == rho.rows());
assert(height == rho.cols());
std::vector<Eigen::Vector2f> seed_points;
if(!p_fn_points.empty()) {
std::ifstream ifs(p_fn_points);
if(!ifs.is_open()) {
std::cerr << "Error opening file '" << p_fn_points << "'" << std::endl;
}
std::string line;
while(getline(ifs, line)) {
std::istringstream ss(line);
std::vector<float> q;
while(!ss.eof()) {
float v;
ss >> v;
q.push_back(v);
}
seed_points.push_back({q[0], q[1]});
}
}