void prod_impl(const viennacl::toeplitz_matrix<SCALARTYPE, ALIGNMENT> & mat,
const viennacl::vector_base<SCALARTYPE> & vec,
viennacl::vector_base<SCALARTYPE> & result)
{
assert(mat.size1() == result.size());
assert(mat.size2() == vec.size());
viennacl::vector<SCALARTYPE> tmp(vec.size() * 4); tmp.clear();
viennacl::vector<SCALARTYPE> tmp2(vec.size() * 4);
viennacl::vector<SCALARTYPE> tep(mat.elements().size() * 2);
viennacl::linalg::real_to_complex(mat.elements(), tep, mat.elements().size());
viennacl::copy(vec.begin(), vec.end(), tmp.begin());
viennacl::linalg::real_to_complex(tmp, tmp2, vec.size() * 2);
viennacl::linalg::convolve(tep, tmp2, tmp);
viennacl::linalg::complex_to_real(tmp, tmp2, vec.size() * 2);
viennacl::copy(tmp2.begin(), tmp2.begin() + static_cast<vcl_ptrdiff_t>(vec.size()), result.begin());
}
cv::Mat SIFT::Less( Mat src,float num )
{
CvSize size=src.size();
Mat tep(size.height,size.width,CV_32F);
for(int i=0;i<size.height;i++)
{
for(int j=0;j<size.width;j++)
{
if(src.at<float>(i,j)<=num)
{
tep.at<float>(i,j)=1;
}
else
{
tep.at<float>(i,j)=0;
}
}
}
return tep;
}
void prod_impl(const viennacl::toeplitz_matrix<SCALARTYPE, ALIGNMENT> & mat,
const viennacl::vector<SCALARTYPE, VECTOR_ALIGNMENT> & vec,
viennacl::vector<SCALARTYPE, VECTOR_ALIGNMENT> & result)
{
assert(mat.size1() == result.size());
assert(mat.size2() == vec.size());
viennacl::vector<SCALARTYPE, VECTOR_ALIGNMENT> tmp(vec.size() * 4);
tmp.clear();
viennacl::vector<SCALARTYPE, VECTOR_ALIGNMENT> tmp2(vec.size() * 4);
viennacl::vector<SCALARTYPE, VECTOR_ALIGNMENT> tep(mat.elements().size() * 2);
viennacl::detail::fft::real_to_complex(mat.elements(), tep, mat.elements().size());
copy(vec, tmp);
viennacl::detail::fft::real_to_complex(tmp, tmp2, vec.size() * 2);
viennacl::linalg::convolve(tep, tmp2, tmp);
viennacl::detail::fft::complex_to_real(tmp, tmp2, vec.size() * 2);
copy(tmp2.begin(), tmp2.begin() + vec.size(), result.begin());
}
cv::Mat SIFT::sp_normalize_sift_arr( Mat sift_arr,float threshold )
{
Mat siftlen=sp_normalize_sift_len(sift_arr);
Mat normalize_ind1=compare(siftlen,threshold);
Mat normalize_ind2=change(normalize_ind1);
Mat sift_arr_hcontrast=search(sift_arr,normalize_ind1);
sift_arr_hcontrast=sift_arr_hcontrast/repmat(search(siftlen,normalize_ind1),1,sift_arr.cols);//此处应为点除
Mat sift_arr_lcontrast=search(sift_arr,normalize_ind2);
sift_arr_lcontrast=sift_arr_lcontrast/threshold;
sift_arr_hcontrast= suppresss(sift_arr_hcontrast,0.2);
sift_arr_lcontrast= suppresss(sift_arr_lcontrast,0.2);
Mat tep(sift_arr_hcontrast.rows,1,CV_32F);
sqrt(sum_row(square(sift_arr_hcontrast)),tep);
sift_arr_hcontrast = sift_arr_hcontrast /repmat(tep, 1,sift_arr.cols);
assign(sift_arr,normalize_ind1,sift_arr_hcontrast);
assign(sift_arr,normalize_ind2,sift_arr_lcontrast);
return sift_arr;
}
cv::Mat SIFT::sp_find_sift_grid( Mat I,Mat gridX,Mat gridY,int patchSize, float sigma_edge )
{
int num_angles=8;
float num_bins=4;
int num_samples=num_bins*num_bins;
int alpha = 9;
//此处需要判断总共传入多少个变量，如果变量数小于5，就把sigma_edge设置为1
float angle_step=2*pi/num_angles;
//初始化angles 为一个一维矩阵从0到2*pi；间隔为angle_step
Mat angles=create(0,2*pi,angle_step);
angles=deleteO(angles); //删除最后一个元素
CvSize size=I.size();
//int hgt=size.height;
//int wid=size.width;
int num_patches=gridX.total();//计算gridX总共有多少个元素
Mat sift_arr=Mat::zeros(num_patches,num_samples*num_angles,CV_32F);
//计算滤波算子
int f_wid = 4 * ceil(sigma_edge) + 1;
Mat G=gaussian(f_wid,sigma_edge);
Mat GX=gradientX(G);
Mat GY=gradientY(G);
GX=GX*2/totalSumO(GX);
GY=GY*2/totalSumO(GY);
Mat I_X(I.rows,I.cols,CV_32F);
I_X=filter2(GX,I); //因为I，图片读入不同，所以I_X不同，与I有关的均布相同，但是，都正确
Mat I_Y(I.rows,I.cols,CV_32F);
I_Y=filter2(GY,I);
Mat T(I_X.rows,I_X.cols,CV_32F);
add(I_X.mul(I_X),I_Y.mul(I_Y),T);
Mat I_mag(I_X.rows,I_X.cols,CV_32F);
sqrt(T,I_mag);
Mat I_theta=matan2(I_Y,I_X);
Mat interval=create(2/num_bins,2,2/num_bins);
interval-=(1/num_bins+1);
Mat sample_x=meshgrid_X(interval,interval);
Mat sample_y=meshgrid_Y(interval,interval);
sample_x=reshapeX(sample_x);//变为一个1维矩阵
sample_y=reshapeX(sample_y);
Mat I_orientation[8] = {Mat::zeros(size,CV_32F)};
for(int i=0;i<8;i++)
{
I_orientation[i] = Mat::zeros(size,CV_32F);
}
float *pt=angles.ptr<float>(0);
for(int a=0;a<num_angles;a++)
{
Mat tep1=mcos(I_theta-pt[a]);//cos
//cout<<tep1.at<float>(0,1)<<endl;
Mat tep(tep1.rows,tep1.cols,CV_32F);
pow(tep1,alpha,tep);
tep=compareB(tep,0);
I_orientation[a]=tep.mul(I_mag);
}
for(int i=0;i<num_patches;i++)
{
double r=patchSize/2;
float l=(float)(i/gridX.rows);
float m=i%gridX.rows;
float cx=gridX.at<float>(m,l)+r-0.5;
float cy=gridY.at<float>(m,l)+r-0.5;
Mat sample_x_t=Add(sample_x*r,cx);
Mat sample_y_t=Add(sample_y*r,cy);
float *pt1=sample_y_t.ptr<float>(0);
float sample_res=pt1[1]-pt1[0];
// int c=(int)i/gridX.rows;
// float *ptc1=gridX.ptr<float>(c);
// int x_lo=ptc1[i%gridX.rows];
int x_lo = gridX.at<float>(i % gridX.rows, i / gridX.rows);
int x_hi=patchSize+x_lo-1;
/* float *ptc2=gridY.ptr<float>(c);*/
int y_lo=gridY.at<float>(i % gridY.rows, i / gridY.rows);
int y_hi=y_lo+patchSize-1;
Mat A=create(x_lo,x_hi,1);
Mat B=create(y_lo,y_hi,1);
Mat sample_px=meshgrid_X(A,B);
Mat sample_py=meshgrid_Y(A,B);
int num_pix = sample_px.total();//计算sample_px元素总数
sample_px=reshapeY(sample_px);
sample_py=reshapeY(sample_py);
Mat dist_px=abs(repmat(sample_px,1,num_samples)-repmat(sample_x_t,num_pix,1));
Mat dist_py=abs(repmat(sample_py,1,num_samples)-repmat(sample_y_t,num_pix,1));
Mat weights_x=dist_px/sample_res;
Mat weights_x_l=Less(weights_x,1);
weights_x=(1-weights_x).mul(weights_x_l);
Mat weights_y=dist_py/sample_res;
Mat weights_y_l=Less(weights_y,1);
weights_y=(1-weights_y).mul(weights_y_l);
Mat weights=weights_x.mul(weights_y);
Mat curr_sift=Mat::zeros(num_angles,num_samples,CV_32F);
for(int a=0;a<num_angles;a++)
{
//Mat I=getNum(I_orientation[a],y_lo,y_hi,x_lo,x_hi);
Mat I = I_orientation[a](Range(y_lo, y_hi), Range(x_lo, x_hi));
Mat tep=reshapeY(I);
// Fill tep with zeros to fit size of weight
if (tep.cols < weights.cols)
{
for (int i = tep.rows; i < weights.rows; i++)
tep.push_back(0.0f);
}
tep=repmat(tep,1,num_samples);
Mat t=tep.mul(weights);
Mat ta=sum_every_col(t);
float *p=ta.ptr<float>(0);
for(int i=0;i<curr_sift.cols;i++)
{
curr_sift.at<float>(a,i)=p[i];
}
}
Mat tp=reshapeX(curr_sift);
float *p=tp.ptr<float>(0);
for(int j=0;j<sift_arr.cols;j++)
{
sift_arr.at<float>(i,j)=p[j];
}
}
return sift_arr;
}
TauContribution<EvalT, Traits>::
TauContribution(Teuchos::ParameterList& p) :
tauFactor(p.get<std::string>("Tau Contribution Name"),
p.get<Teuchos::RCP<PHX::DataLayout> >("QP Scalar Data Layout"))
{
Teuchos::ParameterList* elmd_list =
p.get<Teuchos::ParameterList*>("Parameter List");
Teuchos::RCP<PHX::DataLayout> vector_dl =
p.get< Teuchos::RCP<PHX::DataLayout> >("QP Vector Data Layout");
std::vector<PHX::DataLayout::size_type> dims;
vector_dl->dimensions(dims);
numQPs = dims[1];
numDims = dims[2];
Teuchos::RCP<ParamLib> paramLib =
p.get< Teuchos::RCP<ParamLib> >("Parameter Library", Teuchos::null);
std::string type = elmd_list->get("Tau Contribution Type", "Constant");
if (type == "Constant") {
is_constant = true;
constant_value = elmd_list->get("Value", 0.0);
// Add Trapped Solvent as a Sacado-ized parameter
new Sacado::ParameterRegistration<EvalT, SPL_Traits>(
"Tau Contribution", this, paramLib);
}
else if (type == "Truncated KL Expansion") {
is_constant = false;
PHX::MDField<MeshScalarT,Cell,QuadPoint,Dim>
fx(p.get<std::string>("QP Coordinate Vector Name"), vector_dl);
coordVec = fx;
this->addDependentField(coordVec);
exp_rf_kl =
Teuchos::rcp(new Stokhos::KL::ExponentialRandomField<MeshScalarT>(*elmd_list));
int num_KL = exp_rf_kl->stochasticDimension();
// Add KL random variables as Sacado-ized parameters
rv.resize(num_KL);
for (int i=0; i<num_KL; i++) {
std::string ss = Albany::strint("Trapped Solvent KL Random Variable",i);
new Sacado::ParameterRegistration<EvalT, SPL_Traits>(ss, this, paramLib);
rv[i] = elmd_list->get(ss, 0.0);
}
}
else {
TEUCHOS_TEST_FOR_EXCEPTION(true, Teuchos::Exceptions::InvalidParameter,
"Invalid Trapped Solvent type " << type);
}
if ( p.isType<std::string>("QP Variable Name") ) {
Teuchos::RCP<PHX::DataLayout> scalar_dl =
p.get< Teuchos::RCP<PHX::DataLayout> >("QP Scalar Data Layout");
PHX::MDField<ScalarT,Cell,QuadPoint>
tp(p.get<std::string>("QP Variable Name"), scalar_dl);
Clattice = tp;
this->addDependentField(Clattice);
VmPartial = elmd_list->get("Partial Molar Volume Value", 0.0);
new Sacado::ParameterRegistration<EvalT, SPL_Traits>(
"Partial Molar Volume Value", this, paramLib);
}
else {
VmPartial = 2.0e-6;
}
if ( p.isType<std::string>("Diffusion Coefficient Name") ) {
Teuchos::RCP<PHX::DataLayout> scalar_dl =
p.get< Teuchos::RCP<PHX::DataLayout> >("QP Scalar Data Layout");
PHX::MDField<ScalarT,Cell,QuadPoint>
ap(p.get<std::string>("Diffusion Coefficient Name"), scalar_dl);
DL = ap;
this->addDependentField(DL);
}
/*
if ( p.isType<std::string>("Ideal Gas Constant Name") ) {
Teuchos::RCP<PHX::DataLayout> scalar_dl =
p.get< Teuchos::RCP<PHX::DataLayout> >("QP Scalar Data Layout");
PHX::MDField<ScalarT,Cell,QuadPoint>
idg(p.get<std::string>("Ideal Gas Constant Name"), scalar_dl);
Rideal = idg;
this->addDependentField(Rideal);
}
*/
if ( p.isType<std::string>("Temperature Name") ) {
Teuchos::RCP<PHX::DataLayout> scalar_dl =
p.get< Teuchos::RCP<PHX::DataLayout> >("QP Scalar Data Layout");
PHX::MDField<ScalarT,Cell,QuadPoint>
tep(p.get<std::string>("Temperature Name"), scalar_dl);
temperature = tep;
Rideal = p.get<RealType>("Ideal Gas Constant", 8.3144621);
this->addDependentField(temperature);
}
this->addEvaluatedField(tauFactor);
this->setName("Tau Contribution"+PHX::TypeString<EvalT>::value);
}
