void MFEval(const MultiSample& s, std::vector<Eigen::VectorXd>& featVecs)
{
// default implementation
featVecs.resize(s.GetRects().size());
for (int i = 0; i < (int)featVecs.size(); ++i)
{
featVecs[i] = MFEval(s.GetSample(i));
}
}
void LaRank::Eval(const MultiSample& sample, std::vector<double>& results)
{
const FloatRect& centre(sample.GetRects()[0]);
vector<VectorXd> fvs;
const_cast<Features&>(m_features).Eval(sample, fvs);
results.resize(fvs.size());
for (int i = 0; i < (int)fvs.size(); ++i)
{
// express y in coord frame of centre sample
FloatRect y(sample.GetRects()[i]);
y.Translate(-centre.XMin(), -centre.YMin());
results[i] = Evaluate(fvs[i], y);
}
}
void LaRank::Update(const MultiSample& sample, int y)
{
// add new support pattern
SupportPattern* sp = new SupportPattern;
const vector<FloatRect>& rects = sample.GetRects();
FloatRect centre = rects[y];
for (int i = 0; i < (int)rects.size(); ++i)
{
// express r in coord frame of centre sample
FloatRect r = rects[i];
r.Translate(-centre.XMin(), -centre.YMin());
sp->yv.push_back(r);
if (!m_config.quietMode && m_config.debugMode)
{
// store a thumbnail for each sample
Mat im(kTileSize, kTileSize, CV_8UC1);
IntRect rect = rects[i];
cv::Rect roi(rect.XMin(), rect.YMin(), rect.Width(), rect.Height());
cv::resize(sample.GetImage().GetImage(0)(roi), im, im.size());
sp->images.push_back(im);
}
}
// evaluate features for each sample
sp->x.resize(rects.size());
const_cast<Features&>(m_features).Eval(sample, sp->x);
sp->y = y;
sp->refCount = 0;
m_sps.push_back(sp);
ProcessNew((int)m_sps.size()-1);
BudgetMaintenance();
for (int i = 0; i < 10; ++i)
{
Reprocess();
BudgetMaintenance();
}
}
