vectori sampleDisc(const vectorf &weights, const uint num) {
vectori inds(num, 0);
int maxind = (int) weights.size() - 1;
// normalize weights
vectorf nw(weights.size());
nw[0] = weights[0];
for (uint k = 1; k < weights.size(); k++)
nw[k] = nw[k - 1] + weights[k];
// get uniform random numbers
static vectorf r;
r = randfloatvec(num);
//#pragma omp parallel for
for (int k = 0; k < (int) num; k++)
for (uint j = 0; j < weights.size(); j++) {
if (r[k] > nw[j] && inds[k] < maxind)
inds[k]++;
else
break;
}
return inds;
}
void EdgeBoxGenerator::clusterEdges( arrayf &E, arrayf &O, arrayf &V )
{
int c, r, cd, rd, i, j; h=E._h; w=E._w;
// greedily merge connected edge pixels into clusters (create _segIds)
_segIds.init(h,w); _segCnt=1;
for( c=0; c<w; c++ ) for( r=0; r<h; r++ ) {
if( c==0 || r==0 || c==w-1 || r==h-1 || E.val(c,r)<=_edgeMinMag )
_segIds.val(c,r)=-1; else _segIds.val(c,r)=0;
}
for( c=1; c<w-1; c++ ) for( r=1; r<h-1; r++ ) {
if(_segIds.val(c,r)!=0) continue;
float sumv=0; int c0=c, r0=r; vectorf vs; vectori cs, rs;
while( sumv < _edgeMergeThr ) {
_segIds.val(c0,r0)=_segCnt;
float o0 = O.val(c0,r0), o1, v; bool found;
for( cd=-1; cd<=1; cd++ ) for( rd=-1; rd<=1; rd++ ) {
if( _segIds.val(c0+cd,r0+rd)!=0 ) continue; found=false;
for( i=0; i<cs.size(); i++ )
if( cs[i]==c0+cd && rs[i]==r0+rd ) { found=true; break; }
if( found ) continue; o1=O.val(c0+cd,r0+rd);
v=fabs(o1-o0)/PI; if(v>.5) v=1-v;
vs.push_back(v); cs.push_back(c0+cd); rs.push_back(r0+rd);
}
float minv=1000; j=0;
for( i=0; i<vs.size(); i++ ) if( vs[i]<minv ) {
minv=vs[i]; c0=cs[i]; r0=rs[i]; j=i;
}
sumv+=minv; if(minv<1000) vs[j]=1000;
}
_segCnt++;
}
// merge or remove small segments
_segMag.resize(_segCnt,0);
for( c=1; c<w-1; c++ ) for( r=1; r<h-1; r++ )
if( (j=_segIds.val(c,r))>0 ) _segMag[j]+=E.val(c,r);
for( c=1; c<w-1; c++ ) for( r=1; r<h-1; r++ )
if( (j=_segIds.val(c,r))>0 && _segMag[j]<=_clusterMinMag)
_segIds.val(c,r)=0;
i=1; while(i>0) {
i=0; for( c=1; c<w-1; c++ ) for( r=1; r<h-1; r++ ) {
if( _segIds.val(c,r)!=0 ) continue;
float o0=O.val(c,r), o1, v, minv=1000; j=0;
for( cd=-1; cd<=1; cd++ ) for( rd=-1; rd<=1; rd++ ) {
if( _segIds.val(c+cd,r+rd)<=0 ) continue; o1=O.val(c+cd,r+rd);
v=fabs(o1-o0)/PI; if(v>.5) v=1-v;
if( v<minv ) { minv=v; j=_segIds.val(c+cd,r+rd); }
}
_segIds.val(c,r)=j; if(j>0) i++;
}
}
// compactify representation
_segMag.assign(_segCnt,0); vectori map(_segCnt,0); _segCnt=1;
for( c=1; c<w-1; c++ ) for( r=1; r<h-1; r++ )
if( (j=_segIds.val(c,r))>0 ) _segMag[j]+=E.val(c,r);
for( i=0; i<_segMag.size(); i++ ) if( _segMag[i]>0 ) map[i]=_segCnt++;
for( c=1; c<w-1; c++ ) for( r=1; r<h-1; r++ )
if( (j=_segIds.val(c,r))>0 ) _segIds.val(c,r)=map[j];
// compute positional means and recompute _segMag
_segMag.assign(_segCnt,0); vectorf meanX(_segCnt,0), meanY(_segCnt,0);
vectorf meanOx(_segCnt,0), meanOy(_segCnt,0), meanO(_segCnt,0);
for( c=1; c<w-1; c++ ) for( r=1; r<h-1; r++ ) {
j=_segIds.val(c,r); if(j<=0) continue;
float m=E.val(c,r), o=O.val(c,r); _segMag[j]+=m;
meanOx[j]+=m*cos(2*o); meanOy[j]+=m*sin(2*o);
meanX[j]+=m*c; meanY[j]+=m*r;
}
for( i=0; i<_segCnt; i++ ) if( _segMag[i]>0 ) {
float m=_segMag[i]; meanX[i]/=m; meanY[i]/=m;
meanO[i]=atan2(meanOy[i]/m,meanOx[i]/m)/2;
}
// compute segment affinities
_segAff.resize(_segCnt); _segAffIdx.resize(_segCnt);
for(i=0; i<_segCnt; i++) _segAff[i].resize(0);
for(i=0; i<_segCnt; i++) _segAffIdx[i].resize(0);
const int rad = 2;
for( c=rad; c<w-rad; c++ ) for( r=rad; r<h-rad; r++ ) {
int s0=_segIds.val(c,r); if( s0<=0 ) continue;
for( cd=-rad; cd<=rad; cd++ ) for( rd=-rad; rd<=rad; rd++ ) {
int s1=_segIds.val(c+cd,r+rd); if(s1<=s0) continue;
bool found = false; for(i=0;i<_segAffIdx[s0].size();i++)
if(_segAffIdx[s0][i] == s1) { found=true; break; }
if( found ) continue;
float o=atan2(meanY[s0]-meanY[s1],meanX[s0]-meanX[s1])+PI/2;
float a=fabs(cos(meanO[s0]-o)*cos(meanO[s1]-o)); a=pow(a,_gamma);
_segAff[s0].push_back(a); _segAffIdx[s0].push_back(s1);
_segAff[s1].push_back(a); _segAffIdx[s1].push_back(s0);
}
}
// compute _segC and _segR
_segC.resize(_segCnt); _segR.resize(_segCnt);
for( c=1; c<w-1; c++ ) for( r=1; r<h-1; r++ )
if( (j=_segIds.val(c,r))>0 ) { _segC[j]=c; _segR[j]=r; }
// optionally create visualization (assume memory initialized is 3*w*h)
if( V._x ) for( c=0; c<w; c++ ) for( r=0; r<h; r++ ) {
i=_segIds.val(c,r);
V.val(c+w*0,r) = i<=0 ? 1 : ((123*i + 128)%255)/255.0f;
V.val(c+w*1,r) = i<=0 ? 1 : ((7*i + 3)%255)/255.0f;
V.val(c+w*2,r) = i<=0 ? 1 : ((174*i + 80)%255)/255.0f;
}
}
void DynamicProgram<T>::argmin(Parts& parts, const vector2DMat& rootv, const vector2DMat& rooti, const vectorf scales, const vector4DMat& Ix, const vector4DMat& Iy, const vector4DMat& Ik, vectorCandidate& candidates) {
// for each scale, and each component, traverse back down the tree to retrieve the part positions
int nscales = scales.size();
#ifdef _OPENMP
#pragma omp parallel for
#endif
for (int n = 0; n < nscales; ++n) {
T scale = scales[n];
for (int c = 0; c < parts.ncomponents(); ++c) {
// get the scores and indices for this tree of parts
const vector2DMat& Iknc = Ik[n][c];
const vector2DMat& Ixnc = Ix[n][c];
const vector2DMat& Iync = Iy[n][c];
int nparts = parts.nparts(c);
// threshold the root score
Mat over_thresh = rootv[n][c] > thresh_;
Mat rootmix = rooti[n][c];
vectorPoint inds;
find(over_thresh, inds);
for (int i = 0; i < inds.size(); ++i) {
Candidate candidate;
vectori xv(nparts);
vectori yv(nparts);
vectori mv(nparts);
for (int p = 0; p < nparts; ++p) {
ComponentPart part = parts.component(c, p);
// calculate the child's points from the parent's points
int x, y, m;
if (part.isRoot()) {
x = xv[0] = inds[i].x;
y = yv[0] = inds[i].y;
m = mv[0] = rootmix.at<int>(inds[i]);
} else {
int idx = part.parent().self();
x = xv[idx];
y = yv[idx];
m = mv[idx];
xv[p] = Ixnc[p][m].at<int>(y,x);
yv[p] = Iync[p][m].at<int>(y,x);
mv[p] = Iknc[p][m].at<int>(y,x);
}
// calculate the bounding rectangle and add it to the Candidate
Point ptwo = Point(2,2);
Point pone = Point(1,1);
Point xy1 = (Point(xv[p],yv[p])-ptwo)*scale;
Point xy2 = xy1 + Point(part.xsize(m), part.ysize(m))*scale - pone;
if (part.isRoot()) candidate.addPart(Rect(xy1, xy2), rootv[n][c].at<T>(inds[i]));
else candidate.addPart(Rect(xy1, xy2), 0.0);
}
#ifdef _OPENMP
#pragma omp critical(addcandidate)
#endif
{
candidates.push_back(candidate);
}
}
}
}
}
//! set the root score of the detection
void setScore(float confidence) { if (confidence_.size() == 0) confidence_.resize(1); confidence_[0] = confidence; }
//! get the root score of the detection. Using for sorting
float score(void) const { return (confidence_.size() > 0) ? confidence_[0] : -std::numeric_limits<double>::infinity(); }
