Mat CmSaliencyRC::GetBorderReg(CMat &idx1i, int regNum, double ratio, double thr)
{
// Variance of x and y
vecD vX(regNum), vY(regNum);
int w = idx1i.cols, h = idx1i.rows;{
vecD mX(regNum), mY(regNum), n(regNum); // Mean value of x and y, pixel number of region
for (int y = 0; y < idx1i.rows; y++){
const int *idx = idx1i.ptr<int>(y);
for (int x = 0; x < idx1i.cols; x++, idx++)
mX[*idx] += x, mY[*idx] += y, n[*idx]++;
}
for (int i = 0; i < regNum; i++)
mX[i] /= n[i], mY[i] /= n[i];
for (int y = 0; y < idx1i.rows; y++){
const int *idx = idx1i.ptr<int>(y);
for (int x = 0; x < idx1i.cols; x++, idx++)
vX[*idx] += abs(x - mX[*idx]), vY[*idx] += abs(y - mY[*idx]);
}
for (int i = 0; i < regNum; i++)
vX[i] = vX[i]/n[i] + EPS, vY[i] = vY[i]/n[i] + EPS;
}
// Number of border pixels in x and y border region
vecI xbNum(regNum), ybNum(regNum);
int wGap = cvRound(w * ratio), hGap = cvRound(h * ratio);
vector<Point> bPnts; {
ForPoints2(pnt, 0, 0, w, hGap) // Top region
ybNum[idx1i.at<int>(pnt)]++, bPnts.push_back(pnt);
ForPoints2(pnt, 0, h - hGap, w, h) // Bottom region
ybNum[idx1i.at<int>(pnt)]++, bPnts.push_back(pnt);
ForPoints2(pnt, 0, 0, wGap, h) // Left region
xbNum[idx1i.at<int>(pnt)]++, bPnts.push_back(pnt);
ForPoints2(pnt, w - wGap, 0, w, h)
xbNum[idx1i.at<int>(pnt)]++, bPnts.push_back(pnt);
}
Mat bReg1u(idx1i.size(), CV_8U);{ // likelihood map of border region
double xR = 1.0/(4*hGap), yR = 1.0/(4*wGap);
vector<byte> regL(regNum); // likelihood of each region belongs to border background
for (int i = 0; i < regNum; i++) {
double lk = xbNum[i] * xR / vY[i] + ybNum[i] * yR / vX[i];
regL[i] = lk/thr > 1 ? 255 : 0; //saturate_cast<byte>(255 * lk / thr);
}
for (int r = 0; r < h; r++) {
const int *idx = idx1i.ptr<int>(r);
byte* maskData = bReg1u.ptr<byte>(r);
for (int c = 0; c < w; c++, idx++)
maskData[c] = regL[*idx];
}
}
for (size_t i = 0; i < bPnts.size(); i++)
bReg1u.at<byte>(bPnts[i]) = 255;
return bReg1u;
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
// arguments
const_marray mX(prhs[0]);
const_marray mY(prhs[1]);
const_marray mLam(prhs[2]);
const_marray mAug(prhs[3]);
const_marray mT0(prhs[4]);
const_marray mSkip(prhs[5]);
marray mW = duplicate(prhs[6]);
marray mW0 = duplicate(prhs[7]);
// take inputs
cmat_t X = view2d<double>(mX);
cvec_t Y = view_as_col<double>(mY);
double lambda = mLam.get_scalar();
double aug = mAug.get_scalar();
double t0 = mT0.get_scalar();
index_t skip = (index_t)mSkip.get_scalar();
const index_t d = mX.nrows();
// main
if (aug == 0)
{
vec_t w(mW.ptr_real(), d, 1);
SGD_QN trainer(w, lambda, skip, t0);
run_sgdx(trainer, X, Y, 1);
}
else
{
vec_t w(mW.ptr_real(), d, 1);
double& w0 = *(mW0.ptr_real());
SGD_QN_A trainer(w, w0, lambda, aug, skip, t0);
run_sgdx(trainer, X, Y, 1);
}
// return
plhs[0] = mW;
plhs[1] = mW0;
}
void Dataset::plotData(TLogLevel level)
{
// For logging purpose
FILE_LOG(level) << "Initial points:" ;
for(size_t i = 0; i < mY.size(); i++)
{
FILE_LOG(level) << "X:" << mX[i]
<< "|Y:" << mY(i);
}
const double yPoint = getValueAtMinimum();
const vectord xPoint = getPointAtMinimum();
FILE_LOG(level) << "Best point so far:" ;
FILE_LOG(level) << "X:" << xPoint
<< "|Y:" << yPoint;
} // plotData
