diff --git a/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp b/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp
index 42663e0a56..7597a1f265 100644
--- a/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp
+++ b/samples/cpp/tutorial_code/gpu/gpu-basics-similarity/gpu-basics-similarity.cpp
@@ -30,11 +30,11 @@ struct BufferMSSIM // Optimized GPU versions
gpu::GpuMat I1_2, I2_2, I1_I2;
vector<gpu::GpuMat> vI1, vI2;
- gpu::GpuMat mu1, mu2;
- gpu::GpuMat mu1_2, mu2_2, mu1_mu2;
+ gpu::GpuMat mu1, mu2;
+ gpu::GpuMat mu1_2, mu2_2, mu1_mu2;
- gpu::GpuMat sigma1_2, sigma2_2, sigma12;
- gpu::GpuMat t3;
+ gpu::GpuMat sigma1_2, sigma2_2, sigma12;
+ gpu::GpuMat t3;
gpu::GpuMat ssim_map;
@@ -56,7 +56,7 @@ void help()
int main(int argc, char *argv[])
{
- help();
+ help();
Mat I1 = imread(argv[1]); // Read the two images
Mat I2 = imread(argv[2]);
@@ -69,13 +69,13 @@ int main(int argc, char *argv[])
BufferPSNR bufferPSNR;
BufferMSSIM bufferMSSIM;
- int TIMES;
- stringstream sstr(argv[3]);
+ int TIMES;
+ stringstream sstr(argv[3]);
sstr >> TIMES;
double time, result;
//------------------------------- PSNR CPU ----------------------------------------------------
- time = (double)getTickCount();
+ time = (double)getTickCount();
for (int i = 0; i < TIMES; ++i)
result = getPSNR(I1,I2);
@@ -84,10 +84,10 @@ int main(int argc, char *argv[])
time /= TIMES;
cout << "Time of PSNR CPU (averaged for " << TIMES << " runs): " << time << " milliseconds."
- << " With result of: " << result << endl;
+ << " With result of: " << result << endl;
//------------------------------- PSNR GPU ----------------------------------------------------
- time = (double)getTickCount();
+ time = (double)getTickCount();
for (int i = 0; i < TIMES; ++i)
result = getPSNR_GPU(I1,I2);
@@ -96,7 +96,7 @@ int main(int argc, char *argv[])
time /= TIMES;
cout << "Time of PSNR GPU (averaged for " << TIMES << " runs): " << time << " milliseconds."
- << " With result of: " << result << endl;
+ << " With result of: " << result << endl;
//------------------------------- PSNR GPU Optimized--------------------------------------------
time = (double)getTickCount(); // Initial call
@@ -105,20 +105,20 @@ int main(int argc, char *argv[])
cout << "Initial call GPU optimized: " << time <<" milliseconds."
<< " With result of: " << result << endl;
- time = (double)getTickCount();
+ time = (double)getTickCount();
for (int i = 0; i < TIMES; ++i)
result = getPSNR_GPU_optimized(I1, I2, bufferPSNR);
time = 1000*((double)getTickCount() - time)/getTickFrequency();
time /= TIMES;
- cout << "Time of PSNR GPU OPTIMIZED ( / " << TIMES << " runs): " << time
- << " milliseconds." << " With result of: " << result << endl << endl;
+ cout << "Time of PSNR GPU OPTIMIZED ( / " << TIMES << " runs): " << time
+ << " milliseconds." << " With result of: " << result << endl << endl;
//------------------------------- SSIM CPU -----------------------------------------------------
Scalar x;
- time = (double)getTickCount();
+ time = (double)getTickCount();
for (int i = 0; i < TIMES; ++i)
x = getMSSIM(I1,I2);
@@ -127,10 +127,10 @@ int main(int argc, char *argv[])
time /= TIMES;
cout << "Time of MSSIM CPU (averaged for " << TIMES << " runs): " << time << " milliseconds."
- << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;
+ << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;
//------------------------------- SSIM GPU -----------------------------------------------------
- time = (double)getTickCount();
+ time = (double)getTickCount();
for (int i = 0; i < TIMES; ++i)
x = getMSSIM_GPU(I1,I2);
@@ -139,16 +139,16 @@ int main(int argc, char *argv[])
time /= TIMES;
cout << "Time of MSSIM GPU (averaged for " << TIMES << " runs): " << time << " milliseconds."
- << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;
+ << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;
//------------------------------- SSIM GPU Optimized--------------------------------------------
- time = (double)getTickCount();
+ time = (double)getTickCount();
x = getMSSIM_GPU_optimized(I1,I2, bufferMSSIM);
time = 1000*((double)getTickCount() - time)/getTickFrequency();
cout << "Time of MSSIM GPU Initial Call " << time << " milliseconds."
- << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;
+ << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;
- time = (double)getTickCount();
+ time = (double)getTickCount();
for (int i = 0; i < TIMES; ++i)
x = getMSSIM_GPU_optimized(I1,I2, bufferMSSIM);
@@ -157,14 +157,14 @@ int main(int argc, char *argv[])
time /= TIMES;
cout << "Time of MSSIM GPU OPTIMIZED ( / " << TIMES << " runs): " << time << " milliseconds."
- << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl << endl;
+ << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl << endl;
return 0;
}
double getPSNR(const Mat& I1, const Mat& I2)
{
- Mat s1;
+ Mat s1;
absdiff(I1, I2, s1); // |I1 - I2|
s1.convertTo(s1, CV_32F); // cannot make a square on 8 bits
s1 = s1.mul(s1); // |I1 - I2|^2
@@ -186,7 +186,7 @@ double getPSNR(const Mat& I1, const Mat& I2)
double getPSNR_GPU_optimized(const Mat& I1, const Mat& I2, BufferPSNR& b)
-{
+{
b.gI1.upload(I1);
b.gI2.upload(I2);
@@ -210,7 +210,7 @@ double getPSNR_GPU_optimized(const Mat& I1, const Mat& I2, BufferPSNR& b)
double getPSNR_GPU(const Mat& I1, const Mat& I2)
{
- gpu::GpuMat gI1, gI2, gs, t1,t2;
+ gpu::GpuMat gI1, gI2, gs, t1,t2;
gI1.upload(I1);
gI2.upload(I2);
@@ -218,7 +218,7 @@ double getPSNR_GPU(const Mat& I1, const Mat& I2)
gI1.convertTo(t1, CV_32F);
gI2.convertTo(t2, CV_32F);
- gpu::absdiff(t1.reshape(1), t2.reshape(1), gs);
+ gpu::absdiff(t1.reshape(1), t2.reshape(1), gs);
gpu::multiply(gs, gs, gs);
Scalar s = gpu::sum(gs);
@@ -235,14 +235,14 @@ double getPSNR_GPU(const Mat& I1, const Mat& I2)
}
Scalar getMSSIM( const Mat& i1, const Mat& i2)
-{
+{
const double C1 = 6.5025, C2 = 58.5225;
/***************************** INITS **********************************/
int d = CV_32F;
- Mat I1, I2;
+ Mat I1, I2;
i1.convertTo(I1, d); // cannot calculate on one byte large values
- i2.convertTo(I2, d);
+ i2.convertTo(I2, d);
Mat I2_2 = I2.mul(I2); // I2^2
Mat I1_2 = I1.mul(I1); // I1^2
@@ -254,11 +254,11 @@ Scalar getMSSIM( const Mat& i1, const Mat& i2)
GaussianBlur(I1, mu1, Size(11, 11), 1.5);
GaussianBlur(I2, mu2, Size(11, 11), 1.5);
- Mat mu1_2 = mu1.mul(mu1);
- Mat mu2_2 = mu2.mul(mu2);
+ Mat mu1_2 = mu1.mul(mu1);
+ Mat mu2_2 = mu2.mul(mu2);
Mat mu1_mu2 = mu1.mul(mu2);
- Mat sigma1_2, sigma2_2, sigma12;
+ Mat sigma1_2, sigma2_2, sigma12;
GaussianBlur(I1_2, sigma1_2, Size(11, 11), 1.5);
sigma1_2 -= mu1_2;
@@ -270,28 +270,28 @@ Scalar getMSSIM( const Mat& i1, const Mat& i2)
sigma12 -= mu1_mu2;
///////////////////////////////// FORMULA ////////////////////////////////
- Mat t1, t2, t3;
+ Mat t1, t2, t3;
- t1 = 2 * mu1_mu2 + C1;
- t2 = 2 * sigma12 + C2;
+ t1 = 2 * mu1_mu2 + C1;
+ t2 = 2 * sigma12 + C2;
t3 = t1.mul(t2); // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
- t1 = mu1_2 + mu2_2 + C1;
- t2 = sigma1_2 + sigma2_2 + C2;
+ t1 = mu1_2 + mu2_2 + C1;
+ t2 = sigma1_2 + sigma2_2 + C2;
t1 = t1.mul(t2); // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
Mat ssim_map;
divide(t3, t1, ssim_map); // ssim_map = t3./t1;
Scalar mssim = mean( ssim_map ); // mssim = average of ssim map
- return mssim;
+ return mssim;
}
Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)
-{
+{
const float C1 = 6.5025f, C2 = 58.5225f;
/***************************** INITS **********************************/
- gpu::GpuMat gI1, gI2, gs1, t1,t2;
+ gpu::GpuMat gI1, gI2, gs1, t1,t2;
gI1.upload(i1);
gI2.upload(i2);
@@ -299,14 +299,14 @@ Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)
gI1.convertTo(t1, CV_MAKE_TYPE(CV_32F, gI1.channels()));
gI2.convertTo(t2, CV_MAKE_TYPE(CV_32F, gI2.channels()));
- vector<gpu::GpuMat> vI1, vI2;
+ vector<gpu::GpuMat> vI1, vI2;
gpu::split(t1, vI1);
gpu::split(t2, vI2);
Scalar mssim;
for( int i = 0; i < gI1.channels(); ++i )
{
- gpu::GpuMat I2_2, I1_2, I1_I2;
+ gpu::GpuMat I2_2, I1_2, I1_I2;
gpu::multiply(vI2[i], vI2[i], I2_2); // I2^2
gpu::multiply(vI1[i], vI1[i], I1_2); // I1^2
@@ -317,45 +317,45 @@ Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)
gpu::GaussianBlur(vI1[i], mu1, Size(11, 11), 1.5);
gpu::GaussianBlur(vI2[i], mu2, Size(11, 11), 1.5);
- gpu::GpuMat mu1_2, mu2_2, mu1_mu2;
- gpu::multiply(mu1, mu1, mu1_2);
- gpu::multiply(mu2, mu2, mu2_2);
- gpu::multiply(mu1, mu2, mu1_mu2);
+ gpu::GpuMat mu1_2, mu2_2, mu1_mu2;
+ gpu::multiply(mu1, mu1, mu1_2);
+ gpu::multiply(mu2, mu2, mu2_2);
+ gpu::multiply(mu1, mu2, mu1_mu2);
- gpu::GpuMat sigma1_2, sigma2_2, sigma12;
+ gpu::GpuMat sigma1_2, sigma2_2, sigma12;
gpu::GaussianBlur(I1_2, sigma1_2, Size(11, 11), 1.5);
- sigma1_2 -= mu1_2;
+ gpu::subtract(sigma1_2, mu1_2, sigma1_2); // sigma1_2 -= mu1_2;
gpu::GaussianBlur(I2_2, sigma2_2, Size(11, 11), 1.5);
- sigma2_2 -= mu2_2;
+ gpu::subtract(sigma2_2, mu2_2, sigma2_2); // sigma2_2 -= mu2_2;
gpu::GaussianBlur(I1_I2, sigma12, Size(11, 11), 1.5);
- sigma12 -= mu1_mu2;
+ gpu::subtract(sigma12, mu1_mu2, sigma12); // sigma12 -= mu1_mu2;
///////////////////////////////// FORMULA ////////////////////////////////
- gpu::GpuMat t1, t2, t3;
+ gpu::GpuMat t1, t2, t3;
- t1 = 2 * mu1_mu2 + C1;
- t2 = 2 * sigma12 + C2;
- gpu::multiply(t1, t2, t3); // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
+ mu1_mu2.convertTo(t1, -1, 2, C1); // t1 = 2 * mu1_mu2 + C1;
+ sigma12.convertTo(t2, -1, 2, C2); // t2 = 2 * sigma12 + C2;
+ gpu::multiply(t1, t2, t3); // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
- t1 = mu1_2 + mu2_2 + C1;
- t2 = sigma1_2 + sigma2_2 + C2;
- gpu::multiply(t1, t2, t1); // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
+ gpu::addWeighted(mu1_2, 1.0, mu2_2, 1.0, C1, t1); // t1 = mu1_2 + mu2_2 + C1;
+ gpu::addWeighted(sigma1_2, 1.0, sigma2_2, 1.0, C2, t2); // t2 = sigma1_2 + sigma2_2 + C2;
+ gpu::multiply(t1, t2, t1); // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
gpu::GpuMat ssim_map;
gpu::divide(t3, t1, ssim_map); // ssim_map = t3./t1;
- Scalar s = gpu::sum(ssim_map);
+ Scalar s = gpu::sum(ssim_map);
mssim.val[i] = s.val[0] / (ssim_map.rows * ssim_map.cols);
}
- return mssim;
+ return mssim;
}
Scalar getMSSIM_GPU_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b)
-{
+{
int cn = i1.channels();
const float C1 = 6.5025f, C2 = 58.5225f;
@@ -367,60 +367,63 @@ Scalar getMSSIM_GPU_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b)
gpu::Stream stream;
stream.enqueueConvert(b.gI1, b.t1, CV_32F);
- stream.enqueueConvert(b.gI2, b.t2, CV_32F);
+ stream.enqueueConvert(b.gI2, b.t2, CV_32F);
gpu::split(b.t1, b.vI1, stream);
gpu::split(b.t2, b.vI2, stream);
Scalar mssim;
+ gpu::GpuMat buf;
+
for( int i = 0; i < b.gI1.channels(); ++i )
- {
+ {
gpu::multiply(b.vI2[i], b.vI2[i], b.I2_2, stream); // I2^2
gpu::multiply(b.vI1[i], b.vI1[i], b.I1_2, stream); // I1^2
gpu::multiply(b.vI1[i], b.vI2[i], b.I1_I2, stream); // I1 * I2
- gpu::GaussianBlur(b.vI1[i], b.mu1, Size(11, 11), 1.5, 0, BORDER_DEFAULT, -1, stream);
- gpu::GaussianBlur(b.vI2[i], b.mu2, Size(11, 11), 1.5, 0, BORDER_DEFAULT, -1, stream);
+ gpu::GaussianBlur(b.vI1[i], b.mu1, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);
+ gpu::GaussianBlur(b.vI2[i], b.mu2, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);
- gpu::multiply(b.mu1, b.mu1, b.mu1_2, stream);
- gpu::multiply(b.mu2, b.mu2, b.mu2_2, stream);
- gpu::multiply(b.mu1, b.mu2, b.mu1_mu2, stream);
+ gpu::multiply(b.mu1, b.mu1, b.mu1_2, stream);
+ gpu::multiply(b.mu2, b.mu2, b.mu2_2, stream);
+ gpu::multiply(b.mu1, b.mu2, b.mu1_mu2, stream);
- gpu::GaussianBlur(b.I1_2, b.sigma1_2, Size(11, 11), 1.5, 0, BORDER_DEFAULT, -1, stream);
- gpu::subtract(b.sigma1_2, b.mu1_2, b.sigma1_2, stream);
+ gpu::GaussianBlur(b.I1_2, b.sigma1_2, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);
+ gpu::subtract(b.sigma1_2, b.mu1_2, b.sigma1_2, gpu::GpuMat(), -1, stream);
//b.sigma1_2 -= b.mu1_2; - This would result in an extra data transfer operation
- gpu::GaussianBlur(b.I2_2, b.sigma2_2, Size(11, 11), 1.5, 0, BORDER_DEFAULT, -1, stream);
- gpu::subtract(b.sigma2_2, b.mu2_2, b.sigma2_2, stream);
+ gpu::GaussianBlur(b.I2_2, b.sigma2_2, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);
+ gpu::subtract(b.sigma2_2, b.mu2_2, b.sigma2_2, gpu::GpuMat(), -1, stream);
//b.sigma2_2 -= b.mu2_2;
- gpu::GaussianBlur(b.I1_I2, b.sigma12, Size(11, 11), 1.5, 0, BORDER_DEFAULT, -1, stream);
- gpu::subtract(b.sigma12, b.mu1_mu2, b.sigma12, stream);
+ gpu::GaussianBlur(b.I1_I2, b.sigma12, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);
+ gpu::subtract(b.sigma12, b.mu1_mu2, b.sigma12, gpu::GpuMat(), -1, stream);
//b.sigma12 -= b.mu1_mu2;
//here too it would be an extra data transfer due to call of operator*(Scalar, Mat)
- gpu::multiply(b.mu1_mu2, 2, b.t1, stream); //b.t1 = 2 * b.mu1_mu2 + C1;
- gpu::add(b.t1, C1, b.t1, stream);
- gpu::multiply(b.sigma12, 2, b.t2, stream); //b.t2 = 2 * b.sigma12 + C2;
- gpu::add(b.t2, C2, b.t2, stream);
+ gpu::multiply(b.mu1_mu2, 2, b.t1, 1, -1, stream); //b.t1 = 2 * b.mu1_mu2 + C1;
+ gpu::add(b.t1, C1, b.t1, gpu::GpuMat(), -1, stream);
+ gpu::multiply(b.sigma12, 2, b.t2, 1, -1, stream); //b.t2 = 2 * b.sigma12 + C2;
+ gpu::add(b.t2, C2, b.t2, gpu::GpuMat(), -12, stream);
- gpu::multiply(b.t1, b.t2, b.t3, stream); // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
+ gpu::multiply(b.t1, b.t2, b.t3, 1, -1, stream); // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))
- gpu::add(b.mu1_2, b.mu2_2, b.t1, stream);
- gpu::add(b.t1, C1, b.t1, stream);
+ gpu::add(b.mu1_2, b.mu2_2, b.t1, gpu::GpuMat(), -1, stream);
+ gpu::add(b.t1, C1, b.t1, gpu::GpuMat(), -1, stream);
- gpu::add(b.sigma1_2, b.sigma2_2, b.t2, stream);
- gpu::add(b.t2, C2, b.t2, stream);
+ gpu::add(b.sigma1_2, b.sigma2_2, b.t2, gpu::GpuMat(), -1, stream);
+ gpu::add(b.t2, C2, b.t2, gpu::GpuMat(), -1, stream);
- gpu::multiply(b.t1, b.t2, b.t1, stream); // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
- gpu::divide(b.t3, b.t1, b.ssim_map, stream); // ssim_map = t3./t1;
+ gpu::multiply(b.t1, b.t2, b.t1, 1, -1, stream); // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))
+ gpu::divide(b.t3, b.t1, b.ssim_map, 1, -1, stream); // ssim_map = t3./t1;
stream.waitForCompletion();
- Scalar s = gpu::sum(b.ssim_map, b.buf);
+ Scalar s = gpu::sum(b.ssim_map, b.buf);
mssim.val[i] = s.val[0] / (b.ssim_map.rows * b.ssim_map.cols);
}
- return mssim;
-}
\ No newline at end of file
+ return mssim;
+}
+