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 42663e0a56c1f36f14f057bbf4c7c96316064954..7597a1f2652aeed4fe21b8faacd15e604229b761 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 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 vI1, vI2; + vector 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; +} +