void saveToXML() {
xml.clear();
xml.addChild("SKY");
xml.setTo("SKY");
for (auto it = stars.begin(); it != stars.end(); it++) {
ofVec2f p = it->getPosition();
int m = it->getMagnitude();
int id = it->getId();
ofXml star;
star.addChild("STAR");
star.setTo("STAR");
star.addChild("POSITION");
star.setTo("POSITION");
star.addValue("X", p.x);
star.addValue("Y", p.y);
star.setTo("../");
star.addValue("MAGNITUDE", m);
star.addValue("ID", id);
xml.addXml(star);
}
xml.save("mySettings.xml");
}
void KinectV2Classifier::setLearnXml(ofXml &xml)
{
// first save the classifier
if (trained) {
svm.saveModel(ofToDataPath("svmModel.dat"));
}
// event-parameter mappings
xml.addChild("LearnInfo");
xml.setTo("LearnInfo");
// classes
xml.addChild("Classes");
xml.setTo("Classes");
for (int i=0; i<classes.size(); i++) {
ofXml xml_;
xml_.addChild("Class");
xml_.setTo("Class");
xml_.addValue("Name", classes[i]);
xml.addXml(xml_);
}
xml.setToParent();
// ranges
xml.addChild("Ranges");
xml.setTo("Ranges");
for (int i=0; i<min.size(); i++) {
ofXml xml_;
xml_.addChild("Joint");
xml_.setTo("Joint");
xml_.addValue("Min", min[i]);
xml_.addValue("Max", max[i]);
xml.addXml(xml_);
}
xml.setToParent();
vector<vector<float> > & entries = data.getEntries();
if (entries.size() > 0) {
xml.addChild("Training");
xml.setTo("Training");
for (int i = 0; i < entries.size(); i++) {
vector<string> featureStringV;
for (int f=1; f<entries[i].size(); f++) {
featureStringV.push_back(ofToString(entries[i][f]));
}
string featureString = ofJoinString(featureStringV, ",");
double label = entries[i][0];
ofXml xml_;
xml_.addChild("Entry");
xml_.setTo("Entry");
xml_.addValue("Label", label);
xml_.addValue("Features", featureString);
xml.addXml(xml_);
}
xml.setToParent();
}
if (trained) {
xml.addChild("Model");
xml.setTo("Model");
xml.addValue("Path", ofToDataPath("svmModel.dat"));
xml.setToParent();
}
xml.setToParent();
}