double calcMeanError(const vector<Mat_<double> >& gt_shapes, \
const vector<Mat_<double> >& current_shapes) {
const Config& c = Config::GetInstance();
const int N = gt_shapes.size();
const int landmark_n = c.landmark_n;
double e = 0.;
Mat_<double> delta_shape;
for (int i = 0; i < N; i++) {
delta_shape = gt_shapes[i] - current_shapes[i];
for (int j = 0; j < landmark_n; j++) {
e += std::sqrt(std::pow(delta_shape(0, 2 * j), 2) + \
std::pow(delta_shape(0, 2 * j + 1), 2));
}
}
e /= landmark_n * N;
e /= c.img_o_size;
return e;
}
double calcMeanError(const vector<Mat_<double> >& gt_shapes,
const vector<Mat_<double> >& current_shapes){
const Config& c = Config::GetInstance();
const int N = gt_shapes.size();
const int landmark_n = c.landmark_n;
double e = 0.;
Mat_<double> delta_shape;
for(int i = 0; i < N; i++){
double left_x, left_y, right_x, right_y;
left_x = left_y = right_x = right_y = 0.;
for(int j = 0; j < c.left_pupils.size(); j++){
left_x += gt_shapes[i](0, 2 * c.left_pupils[j]);
left_y += gt_shapes[i](0, 2 * c.left_pupils[j] + 1);
}
left_x /= c.left_pupils.size();
left_y /= c.left_pupils.size();
for(int j = 0; j < c.right_pupils.size(); j++){
right_x += gt_shapes[i](0, 2 * c.right_pupils[j]);
right_y += gt_shapes[i](0, 2 * c.right_pupils[j] + 1);
}
right_x /= c.right_pupils.size();
right_y /= c.right_pupils.size();
double pupil_dis;
pupil_dis = std::sqrt(
std::pow(left_x - right_x, 2) + std::pow(left_y - right_y, 2));
delta_shape = gt_shapes[i] - current_shapes[i];
double e_ = 0.;
for(int j = 0; j < landmark_n; j++){
e_ += std::sqrt(
std::pow(delta_shape(0, 2 * j), 2)
+ std::pow(delta_shape(0, 2 * j + 1), 2));
}
e += e_ / pupil_dis;
}
e /= landmark_n * N;
return e;
}
