void auxCreateYmatrix(vector<MatType> &ymatrix,DynVars const &dynVars,Parameters const ðer,int site)
{
int i,j;
ymatrix[28]=MatType(0.34,0);
ymatrix[35]=MatType(0.34,0);
for (i=0;i<6;i++) {
for (j=i+1;j<6;j++) {
ymatrix[i+j*6]=conj(ymatrix[j+i*6]);
}
}
// for (i=0;i<36;i++) {
// ymatrix[i] *= ether.J[0];
//cerr<<"i "<<jmatrix[i]<<endl;
// }
}
AssertionResult assertMatNear(const char* expr1, const char* expr2, const char* eps_expr, InputArray m1_, InputArray m2_, double eps)
{
Mat m1 = getMat(m1_);
Mat m2 = getMat(m2_);
if (m1.size() != m2.size())
{
return AssertionFailure() << "Matrices \"" << expr1 << "\" and \"" << expr2 << "\" have different sizes : \""
<< expr1 << "\" [" << PrintToString(m1.size()) << "] vs \""
<< expr2 << "\" [" << PrintToString(m2.size()) << "]";
}
if (m1.type() != m2.type())
{
return AssertionFailure() << "Matrices \"" << expr1 << "\" and \"" << expr2 << "\" have different types : \""
<< expr1 << "\" [" << PrintToString(MatType(m1.type())) << "] vs \""
<< expr2 << "\" [" << PrintToString(MatType(m2.type())) << "]";
}
Mat diff;
absdiff(m1.reshape(1), m2.reshape(1), diff);
double maxVal = 0.0;
Point maxLoc;
minMaxLocGold(diff, 0, &maxVal, 0, &maxLoc);
if (maxVal > eps)
{
return AssertionFailure() << "The max difference between matrices \"" << expr1 << "\" and \"" << expr2
<< "\" is " << maxVal << " at (" << maxLoc.y << ", " << maxLoc.x / m1.channels() << ")"
<< ", which exceeds \"" << eps_expr << "\", where \""
<< expr1 << "\" at (" << maxLoc.y << ", " << maxLoc.x / m1.channels() << ") evaluates to " << printMatVal(m1, maxLoc) << ", \""
<< expr2 << "\" at (" << maxLoc.y << ", " << maxLoc.x / m1.channels() << ") evaluates to " << printMatVal(m2, maxLoc) << ", \""
<< eps_expr << "\" evaluates to " << eps;
}
return AssertionSuccess();
}
vector<MatType> types(int depth_start, int depth_end, int cn_start, int cn_end)
{
vector<MatType> v;
v.reserve((depth_end - depth_start + 1) * (cn_end - cn_start + 1));
for (int depth = depth_start; depth <= depth_end; ++depth)
{
for (int cn = cn_start; cn <= cn_end; ++cn)
{
v.push_back(MatType(CV_MAKE_TYPE(depth, cn)));
}
}
return v;
}
void auxCreateJmatrix(vector<MatType> &jmatrix, DynVars const &dynVars,Parameters const ðer,int site)
{
int i,j;
jmatrix[0]=0.5*cos(dynVars.theta[site]);
jmatrix[1]=MatType(0.5*sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(3.0),
-0.5*sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(3.0));
jmatrix[2]=0.0;
jmatrix[3]=0.0;
jmatrix[4]=MatType(0.5*sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(3.0),
0.5*sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(3.0));
jmatrix[5]=cos(dynVars.theta[site])/6.0;
jmatrix[6]=MatType(sin(dynVars.theta[site])*cos(dynVars.phi[site])/3.0,
-sin(dynVars.theta[site])*sin(dynVars.phi[site])/3.0);
jmatrix[7]=0.0;
jmatrix[8]=0.0;
jmatrix[9]=MatType(sin(dynVars.theta[site])*cos(dynVars.phi[site])/3.0,
sin(dynVars.theta[site])*sin(dynVars.phi[site])/3.0);
jmatrix[10]= -jmatrix[5];
jmatrix[11]= MatType(0.5*sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(3.0),
-0.5*sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(3.0));
jmatrix[12]=0.0;
jmatrix[13]=0.0;
jmatrix[14]=MatType(0.5*sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(3.0),
0.5*sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(3.0));
jmatrix[15]= -jmatrix[0];
for (i=0;i<4;i++) {
for (j=i+1;j<4;j++) {
jmatrix[i+j*4]=conj(jmatrix[j+i*4]);
}
}
for (i=0;i<16;i++) {
jmatrix[i] *= ether.J[0];
//cerr<<"i "<<jmatrix[i]<<endl;
}
}
static MatType ones(const Sparsity& sp) { return MatType(sp, 1, false);}
static MatType zeros(const Sparsity& sp) { return MatType(sp, 0, false);}
cv::gpu::GpuMat dst;
cv::gpu::resize(src, dst, cv::Size(), f, f, interpolation);
declare.time(1.0);
TEST_CYCLE()
{
cv::gpu::resize(src, dst, cv::Size(), f, f, interpolation);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, Resize, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR),
Interpolation(cv::INTER_CUBIC), Interpolation(cv::INTER_AREA)),
testing::Values(Scale(0.5), Scale(0.3), Scale(2.0))));
GPU_PERF_TEST(ResizeArea, cv::gpu::DeviceInfo, cv::Size, MatType, Scale)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int interpolation = cv::INTER_AREA;
double f = GET_PARAM(3);
EXPECT_MAT_SIMILAR(cpu_desc, gpu_desc, 1e-1);
}
OCL_TEST_P(HOG, Detect)
{
HOGDescriptor hog;
hog.winSize = winSize;
hog.gammaCorrection = true;
if (winSize.width == 48 && winSize.height == 96)
hog.setSVMDetector(hog.getDaimlerPeopleDetector());
else
hog.setSVMDetector(hog.getDefaultPeopleDetector());
std::vector<Rect> cpu_found;
std::vector<Rect> gpu_found;
OCL_OFF(hog.detectMultiScale(img, cpu_found, 0, Size(8, 8), Size(0, 0), 1.05, 6));
OCL_ON(hog.detectMultiScale(uimg, gpu_found, 0, Size(8, 8), Size(0, 0), 1.05, 6));
EXPECT_LT(checkRectSimilarity(img.size(), cpu_found, gpu_found), 0.05);
}
INSTANTIATE_TEST_CASE_P(OCL_ObjDetect, HOG, testing::Combine(
testing::Values(Size(64, 128), Size(48, 96)),
testing::Values( MatType(CV_8UC1) ) ) );
}} // namespace
#endif
void auxCreateJmatrix(vector<MatType> &jmatrix,DynVars const &dynVars,Parameters const ðer,int site)
{
int i,j;
jmatrix[0]=0.5*cos(dynVars.theta[site]);
jmatrix[1]=0.0;
jmatrix[2]=MatType(0.5*sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(3.0),
-0.5*sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(3.0));
jmatrix[3]=0.0;
jmatrix[4]=MatType(sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(6.0),
-sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(6.0));
jmatrix[5]=0.0;
jmatrix[6]=0.0;
jmatrix[7]=-cos(dynVars.theta[site])/6.0;
jmatrix[8]=MatType(sin(dynVars.theta[site])*cos(dynVars.phi[site])/3.0,
sin(dynVars.theta[site])*sin(dynVars.phi[site])/3.0);
jmatrix[9]=MatType(0.5*sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(3.0),
-0.5*sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(3.0));
jmatrix[10]=MatType(-sin(dynVars.theta[site])*cos(dynVars.phi[site])/(3.0*sqrt(2.0)),
-sin(dynVars.theta[site])*sin(dynVars.phi[site])/(3.0*sqrt(2.0)));
jmatrix[11]=-sqrt(2.0)*cos(dynVars.theta[site])/3.0;
//jmatrix[11]=-2.0*cos(dynVars.theta[site])/sqrt(3.0);
// jmatrix[11]=0;
jmatrix[12]= MatType(0.5*sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(3.0),
0.5*sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(3.0));
jmatrix[13]=MatType(sin(dynVars.theta[site])*cos(dynVars.phi[site])/3.0,
-sin(dynVars.theta[site])*sin(dynVars.phi[site])/3.0);
jmatrix[14]= -jmatrix[7];
jmatrix[15]=0.0;
jmatrix[16]= jmatrix[11];
jmatrix[17]=MatType(sin(dynVars.theta[site])*cos(dynVars.phi[site])/(3.0*sqrt(2.0)),
-sin(dynVars.theta[site])*sin(dynVars.phi[site])/(3.0*sqrt(2.0)));
jmatrix[18]=0.0;
jmatrix[19]=MatType(0.5*sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(3.0),
0.5*sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(3.0));
jmatrix[20]= 0.0;
jmatrix[21]= -jmatrix[0];
jmatrix[22]= 0.0;
jmatrix[23]=MatType(-sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(6.0),
-sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(6.0));
jmatrix[24]= MatType(sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(6.0),
sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(6.0));
jmatrix[25]=MatType(-sin(dynVars.theta[site])*cos(dynVars.phi[site])/(3.0*sqrt(2.0)),
sin(dynVars.theta[site])*sin(dynVars.phi[site])/(3.0*sqrt(2.0)));
jmatrix[26]=jmatrix[11];
jmatrix[27]= 0.0;
jmatrix[28]= jmatrix[7];
jmatrix[29]= MatType(-sin(dynVars.theta[site])*cos(dynVars.phi[site])/6.0,
sin(dynVars.theta[site])*sin(dynVars.phi[site])/6.0);
jmatrix[30]= 0.0;
jmatrix[31]= jmatrix[11];
jmatrix[32]=MatType(sin(dynVars.theta[site])*cos(dynVars.phi[site])/(3.0*sqrt(2.0)),
sin(dynVars.theta[site])*sin(dynVars.phi[site])/(3.0*sqrt(2.0)));
jmatrix[33]=MatType(-sin(dynVars.theta[site])*cos(dynVars.phi[site])/sqrt(6.0),
sin(dynVars.theta[site])*sin(dynVars.phi[site])/sqrt(6.0));
jmatrix[34]= MatType(-sin(dynVars.theta[site])*cos(dynVars.phi[site])/6.0,
-sin(dynVars.theta[site])*sin(dynVars.phi[site])/6.0);
jmatrix[35]= jmatrix[14];
for (i=0;i<6;i++) {
for (j=i+1;j<6;j++) {
jmatrix[i+j*6]=conj(jmatrix[j+i*6]);
}
}
for (i=0;i<36;i++) {
jmatrix[i] *= ether.J[0];
//cerr<<"i "<<jmatrix[i]<<endl;
}
}
void Unpooling(const MatType& input, const double value, MatType& output)
{
output = MatType(input.n_rows, input.n_cols);
output.fill(value / input.n_elem);
}
/** \brief create a sparse matrix with all zeros */
static MatType sparse(int nrow=1, int ncol=1) { return MatType(Sparsity::sparse(nrow, ncol));}
