//============================================================================== //============================================================================== //============================================================================== //============================================================================== //============================================================================== //============================================================================== void patch_models:: train(ft_data &data, const vector<Point2f> &ref, const Size psize, const Size ssize, const bool mirror, const float var, const float lambda, const float mu_init, const int nsamples, const bool visi) { //set reference shape int n = ref.size(); reference = Mat(ref).reshape(1,2*n); Size wsize = psize + ssize; //train each patch model in turn patches.resize(n); for(int i = 0; i < n; i++){ if(visi)cout << "training patch " << i << "..." << endl; vector<Mat> images(0); for(int j = 0; j < data.n_images(); j++){ Mat im = data.get_image(j,0); // imshow("im",im); vector<Point2f> p = data.get_points(j,false); Mat pt = Mat(p).reshape(1,2*n); Mat S = this->calc_simil(pt),A(2,3,CV_32F); A.fl(0,0) = S.fl(0,0); A.fl(0,1) = S.fl(0,1); A.fl(1,0) = S.fl(1,0); A.fl(1,1) = S.fl(1,1); A.fl(0,2) = pt.fl(2*i ) - (A.fl(0,0) * (wsize.width-1)/2 + A.fl(0,1)*(wsize.height-1)/2); A.fl(1,2) = pt.fl(2*i+1) - (A.fl(1,0) * (wsize.width-1)/2 + A.fl(1,1)*(wsize.height-1)/2); Mat I; warpAffine(im,I,A,wsize,INTER_LINEAR+WARP_INVERSE_MAP); images.push_back(I); if(mirror){ im = data.get_image(j,1); p = data.get_points(j,true); pt = Mat(p).reshape(1,2*n); S = this->calc_simil(pt); A.fl(0,0) = S.fl(0,0); A.fl(0,1) = S.fl(0,1); A.fl(1,0) = S.fl(1,0); A.fl(1,1) = S.fl(1,1); A.fl(0,2) = pt.fl(2*i ) - (A.fl(0,0) * (wsize.width-1)/2 + A.fl(0,1)*(wsize.height-1)/2); A.fl(1,2) = pt.fl(2*i+1) - (A.fl(1,0) * (wsize.width-1)/2 + A.fl(1,1)*(wsize.height-1)/2); warpAffine(im,I,A,wsize,INTER_LINEAR+WARP_INVERSE_MAP); images.push_back(I); } } patches[i].train(images,psize,var,lambda,mu_init,nsamples,visi); } }
int set_current_image(const int idx = 0){ if((idx < 0) || (idx > int(data.imnames.size())))return 0; image = data.get_image(idx,2); return 1; }
//============================================================================== void face_detector:: train(ft_data &data, const string fname, const Mat &ref, const bool mirror, const bool visi, const float frac, const float scaleFactor, const int minNeighbours, const Size minSize) { detector.load(fname.c_str()); detector_fname = fname; reference = ref.clone(); vector<float> xoffset(0),yoffset(0),zoffset(0); for(int i = 0; i < data.n_images(); i++){ Mat im = data.get_image(i,0); if(im.empty())continue; vector<Point2f> p = data.get_points(i,false); int n = p.size(); Mat pt = Mat(p).reshape(1,2*n); vector<Rect> faces; Mat eqIm; equalizeHist(im,eqIm); detector.detectMultiScale(eqIm,faces,scaleFactor,minNeighbours,0 |CV_HAAR_FIND_BIGGEST_OBJECT |CV_HAAR_SCALE_IMAGE,minSize); if(faces.size() >= 1){ if(visi){ Mat I; cvtColor(im,I,CV_GRAY2RGB); for(int i = 0; i < n; i++)circle(I,p[i],1,CV_RGB(0,255,0),2,CV_AA); rectangle(I,faces[0].tl(),faces[0].br(),CV_RGB(255,0,0),3); imshow("face detector training",I); waitKey(10); } //check if enough points are in detected rectangle if(this->enough_bounded_points(pt,faces[0],frac)){ Point2f center = this->center_of_mass(pt); float w = faces[0].width; xoffset.push_back((center.x - (faces[0].x+0.5*faces[0].width ))/w); yoffset.push_back((center.y - (faces[0].y+0.5*faces[0].height))/w); zoffset.push_back(this->calc_scale(pt)/w); } } if(mirror){ im = data.get_image(i,1); if(im.empty())continue; p = data.get_points(i,true); pt = Mat(p).reshape(1,2*n); equalizeHist(im,eqIm); detector.detectMultiScale(eqIm,faces,scaleFactor,minNeighbours,0 |CV_HAAR_FIND_BIGGEST_OBJECT |CV_HAAR_SCALE_IMAGE,minSize); if(faces.size() >= 1){ if(visi){ Mat I; cvtColor(im,I,CV_GRAY2RGB); for(int i = 0; i < n; i++)circle(I,p[i],1,CV_RGB(0,255,0),2,CV_AA); rectangle(I,faces[0].tl(),faces[0].br(),CV_RGB(255,0,0),3); imshow("face detector training",I); waitKey(10); } //check if enough points are in detected rectangle if(this->enough_bounded_points(pt,faces[0],frac)){ Point2f center = this->center_of_mass(pt); float w = faces[0].width; xoffset.push_back((center.x - (faces[0].x+0.5*faces[0].width ))/w); yoffset.push_back((center.y - (faces[0].y+0.5*faces[0].height))/w); zoffset.push_back(this->calc_scale(pt)/w); } } } } //choose median value Mat X = Mat(xoffset),Xsort,Y = Mat(yoffset),Ysort,Z = Mat(zoffset),Zsort; cv::sort(X,Xsort,CV_SORT_EVERY_COLUMN|CV_SORT_ASCENDING); int nx = Xsort.rows; cv::sort(Y,Ysort,CV_SORT_EVERY_COLUMN|CV_SORT_ASCENDING); int ny = Ysort.rows; cv::sort(Z,Zsort,CV_SORT_EVERY_COLUMN|CV_SORT_ASCENDING); int nz = Zsort.rows; detector_offset = Vec3f(Xsort.fl(nx/2),Ysort.fl(ny/2),Zsort.fl(nz/2)); return; }