VectorDouble stddev(VectorDouble v) {
double sum = std::accumulate(v.begin(), v.end(), 0.0);
double mean = sum / v.size();
double sq_sum = std::inner_product(v.begin(), v.end(), v.begin(), 0.0);
double stdev = std::sqrt(sq_sum / v.size() - mean * mean);
return VectorDouble(1, stdev);
}
double SegmentorOTSU::sig_func (VectorDouble k,
kkint32 nbins,
const VectorDouble& P,
kkint32 numClasses
)
{
kkint32 x = 0, y = 0;
// muT = sum((1:nbins).*P);
double muT = 0.0;
for (x = 0, y = 1; x < nbins; ++x, ++y)
muT += y * P[x];
//sigma2T = sum(((1:nbins)-muT).^2.*P);
double sigma2T = 0.0;
for (x = 0, y = 1; x < nbins; ++x, ++y)
sigma2T += (pow ((y - muT), 2.0) * P[x]);
//k = round(k*(nbins-1)+1);
for (x = 0; x < (kkint32)k.size (); ++x)
k[x] = floor (k[x] * (nbins - 1) + 1.0 + 0.5);
//k = sort(k);
sort (k.begin (), k.end ());
//if any(k<1 | k>nbins), y = 1; return, end
if ((k[0] < 1.0) || (k[k.size () - 1] > nbins))
return 1.0;
//k = [0 k nbins]; % Puts '0' at beginning and 'nbins' at the end.
k.insert (k.begin (), 0.0);
k.push_back (nbins);
// sigma2B = 0;
double sigma2B = 0.0;
//for j = 1:numClasses
for (kkint32 j = 0; j < numClasses; ++j)
{
//wj = sum(P(k(j)+1:k(j+1)));
double wj = SumSubSet (P, (kkint32)(k[j] + 1), (kkint32)k[j + 1]);
//if wj==0, y = 1; return, end
if (wj == 0.0)
return 1.0;
//muj = sum((k(j)+1:k(j+1)).*P(k(j)+1:k(j+1)))/wj;
kkint32 idxStart = (kkint32)(k[j] + 1);
kkint32 idxEnd = (kkint32)(k[j + 1]);
double muj = 0.0;
for (kkint32 i = idxStart; i <= idxEnd; ++i)
muj += (i * P[i] / wj);
//sigma2B = sigma2B + wj*(muj-muT)^2;
sigma2B = sigma2B + wj * pow ((muj - muT), 2.0);
}
//y = 1-sigma2B/sigma2T; % within the range [0 1]
return 1.0 - sigma2B / sigma2T;
} /* sig_func */
TrainingSampleCheckerResult checkTrainingSample(const MatrixDouble &in) {
VectorDouble stddev = in.getStdDev();
if (*max_element(stddev.begin(), stddev.end()) < 0.1)
return TrainingSampleCheckerResult(TrainingSampleCheckerResult::WARNING,
"Warning: Gesture contains very little movement.");
return TrainingSampleCheckerResult::SUCCESS;
}
