#include "ExpressionClassifier.h" using namespace cv; /* sigma describes the classification sharpness. A larger sigma means the boundary between different expressions is more blurry. It won't change the classification, but will give you probabilities that are smoother. */ ExpressionClassifier::ExpressionClassifier() :sigma(10.0) { } void ExpressionClassifier::save(string directory) const { ofDirectory dir(directory); dir.create(true); for(int i = 0; i < size(); i++) { string filename = dir.path() + "/" + expressions[i].getDescription() + ".yml"; cout << "saving to " << filename << endl; expressions[i].save(filename); } } void ExpressionClassifier::load(string directory) { ofDirectory dir(directory); dir.listDir(); int n = dir.size(); expressions.resize(n); for(int i = 0; i < n; i++) { expressions[i].load(dir.getPath(i)); } } unsigned int ExpressionClassifier::classify(const ofxFaceTracker& tracker) { Mat cur; tracker.getObjectPointsMat().copyTo(cur); norm(cur); int n = size(); probability.resize(n); if(n == 0) { return 0; } vector > val(n); double sum = 0; for(int i = 0; i < n; i++){ int m = expressions[i].size(); for(int j = 0; j < m; j++){ double v = norm(cur, expressions[i].getExample(j)); double p = exp(-v * v / sigma); val[i].push_back(p); sum += p; } } for(int i = 0; i < n; i++){ probability[i] = 0; int m = expressions[i].size(); for(int j = 0; j < m; j++) { probability[i] += val[i][j]; } probability[i] /= sum; } return getPrimaryExpression(); } unsigned int ExpressionClassifier::getPrimaryExpression() const { int maxExpression = 0; double maxProbability = 0; for(int i = 0; i < probability.size(); i++) { double cur = getProbability(i); if(cur > maxProbability) { maxExpression = i; maxProbability = cur; } } return maxExpression; } double ExpressionClassifier::getProbability(unsigned int i) const { if(i < probability.size()) { return probability[i]; } else { return 0; } } string ExpressionClassifier::getDescription(unsigned int i) const { return expressions[i].getDescription(); } Expression& ExpressionClassifier::getExpression(unsigned int i) { return expressions[i]; } void ExpressionClassifier::setSigma(double sigma) { this->sigma = sigma; } double ExpressionClassifier::getSigma() const { return sigma; } unsigned int ExpressionClassifier::size() const { return expressions.size(); } void ExpressionClassifier::addExpression(string description) { if(description == "") { description = ofToString(expressions.size()); } expressions.push_back(Expression(description)); } void ExpressionClassifier::addExpression(Expression& expression) { expressions.push_back(expression); } void ExpressionClassifier::addSample(const ofxFaceTracker& tracker) { if(size() == 0) { addExpression(); } expressions.back().addSample(tracker.getObjectPointsMat()); } void ExpressionClassifier::reset() { expressions.clear(); }