void EdgeBoxesImpl::getBoundingBoxes(InputArray edge_map, InputArray orientation_map, std::vector<Rect> &boxes)
{
CV_Assert(edge_map.depth() == CV_32F);
CV_Assert(orientation_map.depth() == CV_32F);
Mat E = edge_map.getMat().t();
Mat O = orientation_map.getMat().t();
h = E.cols;
w = E.rows;
clusterEdges(E, O);
prepDataStructs(E);
Boxes b;
scoreAllBoxes(b);
boxesNms(b, _beta, _eta, _maxBoxes);
// create output boxes
int n = (int) b.size();
boxes.resize(n);
for(int i=0; i < n; i++)
{
boxes[i] = Rect((int)b[i].x + 1, (int)b[i].y + 1, (int)b[i].w, (int)b[i].h);
}
}
void EdgeBoxGenerator::scoreAllBoxes( Boxes &boxes )
{
// get list of all boxes roughly distributed in grid
boxes.resize(0); int arRad, scNum; float minSize=sqrt(_minBoxArea);
arRad = int(log(_maxAspectRatio)/log(_arStep*_arStep));
scNum = int(ceil(log(std::max(w,h)/minSize)/log(_scStep)));
for( int s=0; s<scNum; s++ ) {
int a, r, c, bh, bw, kr, kc, bId=-1; float ar, sc;
for( a=0; a<2*arRad+1; a++ ) {
ar=pow(_arStep,float(a-arRad)); sc=minSize*pow(_scStep,float(s));
bh=int(sc/ar); kr=std::max(2,int(bh*_rcStepRatio));
bw=int(sc*ar); kc=std::max(2,int(bw*_rcStepRatio));
for( c=0; c<w-bw+kc; c+=kc ) for( r=0; r<h-bh+kr; r+=kr ) {
Box b; b.r=r; b.c=c; b.h=bh; b.w=bw; boxes.push_back(b);
}
}
}
// score all boxes, refine top candidates, perform nms
int i, k=0, m = int(boxes.size());
for( i=0; i<m; i++ ) {
scoreBox(boxes[i]);
if( !boxes[i].s ) continue; k++;
refineBox(boxes[i]);
}
sort(boxes.rbegin(),boxes.rend(),boxesCompare);
boxes.resize(k); boxesNms(boxes,_beta,_eta,_maxBoxes);
}
void Problem::make_boxes_mx(Boxes boxes, mxArray *mx) {
for (int i = 0; i < boxes.size(); ++i) {
// Creates a matrix(boxes.size(), 2) and stores the interval inside the box
mxArray *box = mxCreateDoubleMatrix(boxes[i].size(), 2, mxREAL);
make_interval_mx(boxes[i], mxGetPr(box));
mxSetCell(mx, i, mxDuplicateArray(box));
};
}
void EdgeBoxesImpl::boxesNms(Boxes &boxes, float thr, float eta, int maxBoxes)
{
sort(boxes.rbegin(), boxes.rend(), boxesCompare);
if (thr > .99f) return;
const int nBin = 10000;
const float step = 1 / thr;
const float lstep = log(step);
vector<Boxes> kept;
kept.resize(nBin + 1);
int n = (int) boxes.size();
int i = 0;
int j, k, b;
int m = 0;
int d = 1;
while (i < n && m < maxBoxes)
{
b = boxes[i].w * boxes[i].h;
bool keep = 1;
b = clamp((int)(ceil(log(float(b)) / lstep)), d, nBin - d);
for (j = b - d; j <= b + d; j++)
{
for (k = 0; k < (int)kept[j].size(); k++)
{
if (keep)
keep = boxesOverlap(boxes[i], kept[j][k]) <= thr;
}
}
if (keep)
{
kept[b].push_back(boxes[i]);
m++;
}
i++;
if (keep && eta < 1.0f && thr > .5f)
{
thr *= eta;
d = (int)ceil(log(1.0f / thr) / lstep);
}
}
boxes.resize(m);
i = 0;
for (j = 0; j < nBin; j++)
{
for (k = 0; k < (int)kept[j].size(); k++)
{
boxes[i++] = kept[j][k];
}
}
sort(boxes.rbegin(), boxes.rend(), boxesCompare);
}
void get_edge_boxes(Mat &im, vector<vector<float> > &bbs) {
Mat ime, grad_ori, ime_t, grad_ori_t;
// setup and run EdgeBoxGenerator
EdgeBoxGenerator edgeBoxGen; Boxes boxes;
edgeBoxGen._alpha = 0.65;
edgeBoxGen._beta = 0.75;
edgeBoxGen._eta = 1;
edgeBoxGen._minScore = 0.01;
edgeBoxGen._maxBoxes = 10000;
edgeBoxGen._edgeMinMag = 0.1;
edgeBoxGen._edgeMergeThr = 0.5;
edgeBoxGen._clusterMinMag = 0.5;
edgeBoxGen._maxAspectRatio = 3;
edgeBoxGen._minBoxArea = 1000;
edgeBoxGen._gamma = 2;
edgeBoxGen._kappa = 1.5;
double t = (double)getTickCount();
edge_detect(im, ime, grad_ori, string("/home/samarth/Documents/MATLAB/edges/cpp/external/gop_1.3/data/sf.dat"));
//vis_matrix(ime, "E");
transpose(ime, ime_t);
transpose(grad_ori, grad_ori_t);
if(!(ime_t.isContinuous() && grad_ori_t.isContinuous())) {
cout << "Matrices are not continuous, hence the Array struct will not work" << endl;
}
arrayf E; E._x = ime_t.ptr<float>();
arrayf O; O._x = grad_ori_t.ptr<float>();
Size sz = ime.size();
int h = sz.height; O._h=E._h=h;
int w = sz.width; O._w=E._w=w;
arrayf V;
edgeBoxGen.generate( boxes, E, O, V );
t = ((double)getTickCount() - t)/getTickFrequency();
cout << "Generated boxes, t = " << t*1000 << " ms" << endl;
// create output bbs
int n = (int) boxes.size();
//cout << "Found " << n << " boxes" << endl;
bbs.resize(n, vector<float>(5, 0));
for(int i=0; i<n; i++) {
bbs[i][0] = (float) boxes[i].c+1;
bbs[i][1] = (float) boxes[i].r+1;
bbs[i][2] = (float) boxes[i].w;
bbs[i][3] = (float) boxes[i].h;
bbs[i][4] = boxes[i].s;
}
}
void edgeBoxes(float*EE, float* OO, int h, int w, float _alpha, float _beta, float _minScore, float _maxBoxes, float _edgeMinMag, float _edgeMergeThr, float _clusterMinMag,
float _maxAspectRatio, float _minBoxArea, float _gamma, float _kappa, vector<bb>& bbs)
{
arrayf E; E._x = EE;
arrayf O; O._x = OO;
O._h = E._h = h;
O._w = E._w = w;
// optionally create memory for visualization
// setup and run EdgeBoxGenerator
EdgeBoxGenerator edgeBoxGen; Boxes boxes;
edgeBoxGen._alpha = float(_alpha);
edgeBoxGen._beta = float(_beta);
edgeBoxGen._minScore = float(_minScore);
edgeBoxGen._maxBoxes = int(_maxBoxes);
edgeBoxGen._edgeMinMag = float(_edgeMinMag);
edgeBoxGen._edgeMergeThr = float(_edgeMergeThr);
edgeBoxGen._clusterMinMag = float(_clusterMinMag);
edgeBoxGen._maxAspectRatio = float(_maxAspectRatio);
edgeBoxGen._minBoxArea = float(_minBoxArea);
edgeBoxGen._gamma = float(_gamma);
edgeBoxGen._kappa = float(_kappa);
arrayf V;
V._h = h; V._w = w;
edgeBoxGen.generate(boxes, E, O, V);
// create output bbs and output to Matlab
int n = (int)boxes.size();
bb tmp_bb;
for (int i = 0; i < n; i++)
{
//tmp_bb.coord[0] = (float)boxes[i].c + 1;
//tmp_bb.coord[1] = (float)boxes[i].r + 1;
//tmp_bb.coord[2] = (float)boxes[i].w + 1;
//tmp_bb.coord[3] = (float)boxes[i].h + 1;
tmp_bb.coord[0] = (float)boxes[i].c;
tmp_bb.coord[1] = (float)boxes[i].r;
tmp_bb.coord[2] = (float)boxes[i].w;
tmp_bb.coord[3] = (float)boxes[i].h;
tmp_bb.score = boxes[i].s;
bbs.push_back(tmp_bb);
}
}
void EdgeBoxesImpl::scoreAllBoxes(Boxes &boxes)
{
// get list of all boxes roughly distributed in grid
boxes.resize(0);
int ayRad, sxNum;
float minSize = sqrt(_minBoxArea);
ayRad = (int)(log(_maxAspectRatio) / log(_ayStep * _ayStep));
sxNum = (int)(ceil(log(max(w, h) / minSize) / log(_sxStep)));
for (int s = 0; s < sxNum; s++)
{
int a, y, x, bh, bw, ky, kx = -1;
float ay, sx;
for (a = 0; a < 2 * ayRad + 1; a++)
{
ay = pow(_ayStep, float(a - ayRad));
sx = minSize * pow(_sxStep, float(s));
bh = (int)(sx / ay);
ky = max(2, (int)(bh * _xyStepRatio));
bw = (int)(sx * ay);
kx = max(2, (int)(bw * _xyStepRatio));
for (x = 0; x < w - bw + kx; x += kx)
{
for (y = 0; y < h - bh + ky; y += ky)
{
Box b;
b.y = y;
b.x = x;
b.h = bh;
b.w = bw;
boxes.push_back(b);
}
}
}
}
// score all boxes, refine top candidates
int i, k = 0, m = (int)boxes.size();
for (i = 0; i < m; i++)
{
scoreBox(boxes[i]);
if (!boxes[i].score) continue;
k++;
refineBox(boxes[i]);
}
sort(boxes.rbegin(), boxes.rend(), boxesCompare);
boxes.resize(k);
}
// Matlab entry point: bbs = mex( E, O, prm1, prm2, ... )
void mexFunction( int nl, mxArray *pl[], int nr, const mxArray *pr[] )
{
// check and get inputs
if(nr != 13) mexErrMsgTxt("Thirteen inputs required.");
if(nl > 2) mexErrMsgTxt("At most two outputs expected.");
if(mxGetClassID(pr[0])!=mxSINGLE_CLASS) mexErrMsgTxt("E must be a float*");
if(mxGetClassID(pr[1])!=mxSINGLE_CLASS) mexErrMsgTxt("O must be a float*");
arrayf E; E._x = (float*) mxGetData(pr[0]);
arrayf O; O._x = (float*) mxGetData(pr[1]);
int h = (int) mxGetM(pr[0]); O._h=E._h=h;
int w = (int) mxGetN(pr[0]); O._w=E._w=w;
// optionally create memory for visualization
arrayf V; if( nl>1 ) {
const int ds[3] = {h,w,3};
pl[1] = mxCreateNumericArray(3,ds,mxSINGLE_CLASS,mxREAL);
V._x = (float*) mxGetData(pl[1]); V._h=h; V._w=w;
}
// setup and run EdgeBoxGenerator
EdgeBoxGenerator edgeBoxGen; Boxes boxes;
edgeBoxGen._alpha = float(mxGetScalar(pr[2]));
edgeBoxGen._beta = float(mxGetScalar(pr[3]));
edgeBoxGen._minScore = float(mxGetScalar(pr[4]));
edgeBoxGen._maxBoxes = int(mxGetScalar(pr[5]));
edgeBoxGen._edgeMinMag = float(mxGetScalar(pr[6]));
edgeBoxGen._edgeMergeThr = float(mxGetScalar(pr[7]));
edgeBoxGen._clusterMinMag = float(mxGetScalar(pr[8]));
edgeBoxGen._maxAspectRatio = float(mxGetScalar(pr[9]));
edgeBoxGen._minBoxArea = float(mxGetScalar(pr[10]));
edgeBoxGen._gamma = float(mxGetScalar(pr[11]));
edgeBoxGen._kappa = float(mxGetScalar(pr[12]));
edgeBoxGen.generate( boxes, E, O, V );
// create output bbs and output to Matlab
int n = (int) boxes.size();
pl[0] = mxCreateNumericMatrix(n,5,mxSINGLE_CLASS,mxREAL);
float *bbs = (float*) mxGetData(pl[0]);
for(int i=0; i<n; i++) {
bbs[ i + 0*n ] = (float) boxes[i].c+1;
bbs[ i + 1*n ] = (float) boxes[i].r+1;
bbs[ i + 2*n ] = (float) boxes[i].w;
bbs[ i + 3*n ] = (float) boxes[i].h;
bbs[ i + 4*n ] = boxes[i].s;
}
}
void mexFunction(int nlhs, mxArray *out[], int nrhs, const mxArray *input[]) {
float thr=0.5, eta=1;
int maxBoxes=100000;
if(mxGetClassID(input[0])!=mxSINGLE_CLASS) mexErrMsgTxt("first input must be single");
if (nrhs==4) eta = (float) mxGetScalar(input[3]);
if (nrhs>=3) maxBoxes = (int) mxGetScalar(input[2]);
if (nrhs<2) mexErrMsgTxt("Usage: nms_c(boxes, thre, max_nbox=Inf, eta=1)");
thr = (float) mxGetScalar(input[1]);
float* boxes_array = (float*)mxGetPr( input[0] );
int nbox = (int) mxGetM(input[0]); //number of input boxes
//mexPrintf("nbox: %d, thr: %f \n", nbox, thr);
int x2,y2;
Boxes boxes;
boxes.resize(0);
for(int i=0; i<nbox; i++) {
Box b;
b.c = (int)boxes_array[ i + 0*nbox ]-1;
b.r = (int)boxes_array[ i + 1*nbox ]-1;
x2 = (int) boxes_array[ i + 2*nbox ]-1;
y2 = (int) boxes_array[ i + 3*nbox ]-1;
b.w = (int) x2 - b.c + 1;
b.h = (int) y2 - b.r + 1;
b.s = (float) boxes_array[ i + 4*nbox ];
boxes.push_back(b);
}
boxesNms(boxes, thr, maxBoxes, eta);
//output
int n = (int) boxes.size();
out[0] = mxCreateNumericMatrix(n,5,mxSINGLE_CLASS,mxREAL);
float *bbs = (float*) mxGetData(out[0]);
for(int i=0; i<n; i++) {
bbs[ i + 0*n ] = (float) boxes[i].c+1;
bbs[ i + 1*n ] = (float) boxes[i].r+1;
bbs[ i + 2*n ] = (float) (boxes[i].c+boxes[i].w);
bbs[ i + 3*n ] = (float) (boxes[i].r+boxes[i].h);
bbs[ i + 4*n ] = boxes[i].s;
}
}
void boxesNms( Boxes &boxes, float thr, int maxBoxes )
{
sort(boxes.rbegin(),boxes.rend(),boxesCompare);
if( thr>.99 ) return; const int nBin=10000;
const float step=1/thr, lstep=log(step);
vector<Boxes> kept; kept.resize(nBin+1);
int i=0, j, k, n=(int) boxes.size(), m=0, b;
while( i<n && m<maxBoxes ) {
b = boxes[i].w*boxes[i].h; bool keep=1;
b = clamp(int(ceil(log(float(b))/lstep)),1,nBin-1);
for( j=b-1; j<=b+1; j++ )
for( k=0; k<(int)kept[j].size(); k++ ) if( keep )
keep = boxesOverlap( boxes[i], kept[j][k] ) <= thr;
if(keep) { kept[b].push_back(boxes[i]); m++; } i++;
}
boxes.resize(m); i=0;
for( j=0; j<nBin; j++ )
for( k=0; k<(int)kept[j].size(); k++ )
boxes[i++]=kept[j][k];
sort(boxes.rbegin(),boxes.rend(),boxesCompare);
}