fixed Bug #2252

error in the tutorial Similarity check (PNSR and SSIM) on the GPU

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 42663e0..7597a1f 100644 (file)
--- 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;\r
     vector<gpu::GpuMat> vI1, vI2;\r
 \r
-    gpu::GpuMat mu1, mu2; \r
-    gpu::GpuMat mu1_2, mu2_2, mu1_mu2; \r
+    gpu::GpuMat mu1, mu2;\r
+    gpu::GpuMat mu1_2, mu2_2, mu1_mu2;\r
 \r
-    gpu::GpuMat sigma1_2, sigma2_2, sigma12; \r
-    gpu::GpuMat t3; \r
+    gpu::GpuMat sigma1_2, sigma2_2, sigma12;\r
+    gpu::GpuMat t3;\r
 \r
     gpu::GpuMat ssim_map;\r
 \r
@@ -56,7 +56,7 @@ void help()
 \r
 int main(int argc, char *argv[])\r
 {\r
-    help(); \r
+    help();\r
     Mat I1 = imread(argv[1]);           // Read the two images\r
     Mat I2 = imread(argv[2]);\r
 \r
@@ -69,13 +69,13 @@ int main(int argc, char *argv[])
     BufferPSNR bufferPSNR;\r
     BufferMSSIM bufferMSSIM;\r
 \r
-    int TIMES; \r
-    stringstream sstr(argv[3]); \r
+    int TIMES;\r
+    stringstream sstr(argv[3]);\r
     sstr >> TIMES;\r
     double time, result;\r
 \r
     //------------------------------- PSNR CPU ----------------------------------------------------\r
-    time = (double)getTickCount();    \r
+    time = (double)getTickCount();\r
 \r
     for (int i = 0; i < TIMES; ++i)\r
         result = getPSNR(I1,I2);\r
@@ -84,10 +84,10 @@ int main(int argc, char *argv[])
     time /= TIMES;\r
 \r
     cout << "Time of PSNR CPU (averaged for " << TIMES << " runs): " << time << " milliseconds."\r
-        << " With result of: " <<  result << endl; \r
+        << " With result of: " <<  result << endl;\r
 \r
     //------------------------------- PSNR GPU ----------------------------------------------------\r
-    time = (double)getTickCount();    \r
+    time = (double)getTickCount();\r
 \r
     for (int i = 0; i < TIMES; ++i)\r
         result = getPSNR_GPU(I1,I2);\r
@@ -96,7 +96,7 @@ int main(int argc, char *argv[])
     time /= TIMES;\r
 \r
     cout << "Time of PSNR GPU (averaged for " << TIMES << " runs): " << time << " milliseconds."\r
-        << " With result of: " <<  result << endl; \r
+        << " With result of: " <<  result << endl;\r
 \r
     //------------------------------- PSNR GPU Optimized--------------------------------------------\r
     time = (double)getTickCount();                                  // Initial call\r
@@ -105,20 +105,20 @@ int main(int argc, char *argv[])
     cout << "Initial call GPU optimized:              " << time  <<" milliseconds."\r
         << " With result of: " << result << endl;\r
 \r
-    time = (double)getTickCount();    \r
+    time = (double)getTickCount();\r
     for (int i = 0; i < TIMES; ++i)\r
         result = getPSNR_GPU_optimized(I1, I2, bufferPSNR);\r
 \r
     time = 1000*((double)getTickCount() - time)/getTickFrequency();\r
     time /= TIMES;\r
 \r
-    cout << "Time of PSNR GPU OPTIMIZED ( / " << TIMES << " runs): " << time \r
-        << " milliseconds." << " With result of: " <<  result << endl << endl; \r
+    cout << "Time of PSNR GPU OPTIMIZED ( / " << TIMES << " runs): " << time\r
+        << " milliseconds." << " With result of: " <<  result << endl << endl;\r
 \r
 \r
     //------------------------------- SSIM CPU -----------------------------------------------------\r
     Scalar x;\r
-    time = (double)getTickCount();    \r
+    time = (double)getTickCount();\r
 \r
     for (int i = 0; i < TIMES; ++i)\r
         x = getMSSIM(I1,I2);\r
@@ -127,10 +127,10 @@ int main(int argc, char *argv[])
     time /= TIMES;\r
 \r
     cout << "Time of MSSIM CPU (averaged for " << TIMES << " runs): " << time << " milliseconds."\r
-        << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl; \r
+        << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;\r
 \r
     //------------------------------- SSIM GPU -----------------------------------------------------\r
-    time = (double)getTickCount();    \r
+    time = (double)getTickCount();\r
 \r
     for (int i = 0; i < TIMES; ++i)\r
         x = getMSSIM_GPU(I1,I2);\r
@@ -139,16 +139,16 @@ int main(int argc, char *argv[])
     time /= TIMES;\r
 \r
     cout << "Time of MSSIM GPU (averaged for " << TIMES << " runs): " << time << " milliseconds."\r
-        << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl; \r
+        << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;\r
 \r
     //------------------------------- SSIM GPU Optimized--------------------------------------------\r
-    time = (double)getTickCount();    \r
+    time = (double)getTickCount();\r
     x = getMSSIM_GPU_optimized(I1,I2, bufferMSSIM);\r
     time = 1000*((double)getTickCount() - time)/getTickFrequency();\r
     cout << "Time of MSSIM GPU Initial Call            " << time << " milliseconds."\r
-        << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl; \r
+        << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl;\r
 \r
-    time = (double)getTickCount();    \r
+    time = (double)getTickCount();\r
 \r
     for (int i = 0; i < TIMES; ++i)\r
         x = getMSSIM_GPU_optimized(I1,I2, bufferMSSIM);\r
@@ -157,14 +157,14 @@ int main(int argc, char *argv[])
     time /= TIMES;\r
 \r
     cout << "Time of MSSIM GPU OPTIMIZED ( / " << TIMES << " runs): " << time << " milliseconds."\r
-        << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl << endl; \r
+        << " With result of B" << x.val[0] << " G" << x.val[1] << " R" << x.val[2] << endl << endl;\r
     return 0;\r
 }\r
 \r
 \r
 double getPSNR(const Mat& I1, const Mat& I2)\r
 {\r
-    Mat s1; \r
+    Mat s1;\r
     absdiff(I1, I2, s1);       // |I1 - I2|\r
     s1.convertTo(s1, CV_32F);  // cannot make a square on 8 bits\r
     s1 = s1.mul(s1);           // |I1 - I2|^2\r
@@ -186,7 +186,7 @@ double getPSNR(const Mat& I1, const Mat& I2)
 \r
 \r
 double getPSNR_GPU_optimized(const Mat& I1, const Mat& I2, BufferPSNR& b)\r
-{    \r
+{\r
     b.gI1.upload(I1);\r
     b.gI2.upload(I2);\r
 \r
@@ -210,7 +210,7 @@ double getPSNR_GPU_optimized(const Mat& I1, const Mat& I2, BufferPSNR& b)
 \r
 double getPSNR_GPU(const Mat& I1, const Mat& I2)\r
 {\r
-    gpu::GpuMat gI1, gI2, gs, t1,t2; \r
+    gpu::GpuMat gI1, gI2, gs, t1,t2;\r
 \r
     gI1.upload(I1);\r
     gI2.upload(I2);\r
@@ -218,7 +218,7 @@ double getPSNR_GPU(const Mat& I1, const Mat& I2)
     gI1.convertTo(t1, CV_32F);\r
     gI2.convertTo(t2, CV_32F);\r
 \r
-    gpu::absdiff(t1.reshape(1), t2.reshape(1), gs); \r
+    gpu::absdiff(t1.reshape(1), t2.reshape(1), gs);\r
     gpu::multiply(gs, gs, gs);\r
 \r
     Scalar s = gpu::sum(gs);\r
@@ -235,14 +235,14 @@ double getPSNR_GPU(const Mat& I1, const Mat& I2)
 }\r
 \r
 Scalar getMSSIM( const Mat& i1, const Mat& i2)\r
-{ \r
+{\r
     const double C1 = 6.5025, C2 = 58.5225;\r
     /***************************** INITS **********************************/\r
     int d     = CV_32F;\r
 \r
-    Mat I1, I2; \r
+    Mat I1, I2;\r
     i1.convertTo(I1, d);           // cannot calculate on one byte large values\r
-    i2.convertTo(I2, d); \r
+    i2.convertTo(I2, d);\r
 \r
     Mat I2_2   = I2.mul(I2);        // I2^2\r
     Mat I1_2   = I1.mul(I1);        // I1^2\r
@@ -254,11 +254,11 @@ Scalar getMSSIM( const Mat& i1, const Mat& i2)
     GaussianBlur(I1, mu1, Size(11, 11), 1.5);\r
     GaussianBlur(I2, mu2, Size(11, 11), 1.5);\r
 \r
-    Mat mu1_2   =   mu1.mul(mu1);    \r
-    Mat mu2_2   =   mu2.mul(mu2); \r
+    Mat mu1_2   =   mu1.mul(mu1);\r
+    Mat mu2_2   =   mu2.mul(mu2);\r
     Mat mu1_mu2 =   mu1.mul(mu2);\r
 \r
-    Mat sigma1_2, sigma2_2, sigma12; \r
+    Mat sigma1_2, sigma2_2, sigma12;\r
 \r
     GaussianBlur(I1_2, sigma1_2, Size(11, 11), 1.5);\r
     sigma1_2 -= mu1_2;\r
@@ -270,28 +270,28 @@ Scalar getMSSIM( const Mat& i1, const Mat& i2)
     sigma12 -= mu1_mu2;\r
 \r
     ///////////////////////////////// FORMULA ////////////////////////////////\r
-    Mat t1, t2, t3; \r
+    Mat t1, t2, t3;\r
 \r
-    t1 = 2 * mu1_mu2 + C1; \r
-    t2 = 2 * sigma12 + C2; \r
+    t1 = 2 * mu1_mu2 + C1;\r
+    t2 = 2 * sigma12 + C2;\r
     t3 = t1.mul(t2);              // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))\r
 \r
-    t1 = mu1_2 + mu2_2 + C1; \r
-    t2 = sigma1_2 + sigma2_2 + C2;     \r
+    t1 = mu1_2 + mu2_2 + C1;\r
+    t2 = sigma1_2 + sigma2_2 + C2;\r
     t1 = t1.mul(t2);               // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))\r
 \r
     Mat ssim_map;\r
     divide(t3, t1, ssim_map);      // ssim_map =  t3./t1;\r
 \r
     Scalar mssim = mean( ssim_map ); // mssim = average of ssim map\r
-    return mssim; \r
+    return mssim;\r
 }\r
 \r
 Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)\r
-{ \r
+{\r
     const float C1 = 6.5025f, C2 = 58.5225f;\r
     /***************************** INITS **********************************/\r
-    gpu::GpuMat gI1, gI2, gs1, t1,t2; \r
+    gpu::GpuMat gI1, gI2, gs1, t1,t2;\r
 \r
     gI1.upload(i1);\r
     gI2.upload(i2);\r
@@ -299,14 +299,14 @@ Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)
     gI1.convertTo(t1, CV_MAKE_TYPE(CV_32F, gI1.channels()));\r
     gI2.convertTo(t2, CV_MAKE_TYPE(CV_32F, gI2.channels()));\r
 \r
-    vector<gpu::GpuMat> vI1, vI2; \r
+    vector<gpu::GpuMat> vI1, vI2;\r
     gpu::split(t1, vI1);\r
     gpu::split(t2, vI2);\r
     Scalar mssim;\r
 \r
     for( int i = 0; i < gI1.channels(); ++i )\r
     {\r
-        gpu::GpuMat I2_2, I1_2, I1_I2; \r
+        gpu::GpuMat I2_2, I1_2, I1_I2;\r
 \r
         gpu::multiply(vI2[i], vI2[i], I2_2);        // I2^2\r
         gpu::multiply(vI1[i], vI1[i], I1_2);        // I1^2\r
@@ -317,45 +317,45 @@ Scalar getMSSIM_GPU( const Mat& i1, const Mat& i2)
         gpu::GaussianBlur(vI1[i], mu1, Size(11, 11), 1.5);\r
         gpu::GaussianBlur(vI2[i], mu2, Size(11, 11), 1.5);\r
 \r
-        gpu::GpuMat mu1_2, mu2_2, mu1_mu2; \r
-        gpu::multiply(mu1, mu1, mu1_2);   \r
-        gpu::multiply(mu2, mu2, mu2_2);   \r
-        gpu::multiply(mu1, mu2, mu1_mu2);   \r
+        gpu::GpuMat mu1_2, mu2_2, mu1_mu2;\r
+        gpu::multiply(mu1, mu1, mu1_2);\r
+        gpu::multiply(mu2, mu2, mu2_2);\r
+        gpu::multiply(mu1, mu2, mu1_mu2);\r
 \r
-        gpu::GpuMat sigma1_2, sigma2_2, sigma12; \r
+        gpu::GpuMat sigma1_2, sigma2_2, sigma12;\r
 \r
         gpu::GaussianBlur(I1_2, sigma1_2, Size(11, 11), 1.5);\r
-        sigma1_2 -= mu1_2;\r
+        gpu::subtract(sigma1_2, mu1_2, sigma1_2); // sigma1_2 -= mu1_2;\r
 \r
         gpu::GaussianBlur(I2_2, sigma2_2, Size(11, 11), 1.5);\r
-        sigma2_2 -= mu2_2;\r
+        gpu::subtract(sigma2_2, mu2_2, sigma2_2); // sigma2_2 -= mu2_2;\r
 \r
         gpu::GaussianBlur(I1_I2, sigma12, Size(11, 11), 1.5);\r
-        sigma12 -= mu1_mu2;\r
+        gpu::subtract(sigma12, mu1_mu2, sigma12); // sigma12 -= mu1_mu2;\r
 \r
         ///////////////////////////////// FORMULA ////////////////////////////////\r
-        gpu::GpuMat t1, t2, t3; \r
+        gpu::GpuMat t1, t2, t3;\r
 \r
-        t1 = 2 * mu1_mu2 + C1; \r
-        t2 = 2 * sigma12 + C2; \r
-        gpu::multiply(t1, t2, t3);     // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))\r
+        mu1_mu2.convertTo(t1, -1, 2, C1); // t1 = 2 * mu1_mu2 + C1;\r
+        sigma12.convertTo(t2, -1, 2, C2); // t2 = 2 * sigma12 + C2;\r
+        gpu::multiply(t1, t2, t3);        // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))\r
 \r
-        t1 = mu1_2 + mu2_2 + C1; \r
-        t2 = sigma1_2 + sigma2_2 + C2;     \r
-        gpu::multiply(t1, t2, t1);     // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))\r
+        gpu::addWeighted(mu1_2, 1.0, mu2_2, 1.0, C1, t1);       // t1 = mu1_2 + mu2_2 + C1;\r
+        gpu::addWeighted(sigma1_2, 1.0, sigma2_2, 1.0, C2, t2); // t2 = sigma1_2 + sigma2_2 + C2;\r
+        gpu::multiply(t1, t2, t1);                              // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))\r
 \r
         gpu::GpuMat ssim_map;\r
         gpu::divide(t3, t1, ssim_map);      // ssim_map =  t3./t1;\r
 \r
-        Scalar s = gpu::sum(ssim_map);    \r
+        Scalar s = gpu::sum(ssim_map);\r
         mssim.val[i] = s.val[0] / (ssim_map.rows * ssim_map.cols);\r
 \r
     }\r
-    return mssim; \r
+    return mssim;\r
 }\r
 \r
 Scalar getMSSIM_GPU_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b)\r
-{ \r
+{\r
     int cn = i1.channels();\r
 \r
     const float C1 = 6.5025f, C2 = 58.5225f;\r
@@ -367,60 +367,63 @@ Scalar getMSSIM_GPU_optimized( const Mat& i1, const Mat& i2, BufferMSSIM& b)
     gpu::Stream stream;\r
 \r
     stream.enqueueConvert(b.gI1, b.t1, CV_32F);\r
-    stream.enqueueConvert(b.gI2, b.t2, CV_32F);      \r
+    stream.enqueueConvert(b.gI2, b.t2, CV_32F);\r
 \r
     gpu::split(b.t1, b.vI1, stream);\r
     gpu::split(b.t2, b.vI2, stream);\r
     Scalar mssim;\r
 \r
+    gpu::GpuMat buf;\r
+\r
     for( int i = 0; i < b.gI1.channels(); ++i )\r
-    {        \r
+    {\r
         gpu::multiply(b.vI2[i], b.vI2[i], b.I2_2, stream);        // I2^2\r
         gpu::multiply(b.vI1[i], b.vI1[i], b.I1_2, stream);        // I1^2\r
         gpu::multiply(b.vI1[i], b.vI2[i], b.I1_I2, stream);       // I1 * I2\r
 \r
-        gpu::GaussianBlur(b.vI1[i], b.mu1, Size(11, 11), 1.5, 0, BORDER_DEFAULT, -1, stream);\r
-        gpu::GaussianBlur(b.vI2[i], b.mu2, Size(11, 11), 1.5, 0, BORDER_DEFAULT, -1, stream);\r
+        gpu::GaussianBlur(b.vI1[i], b.mu1, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);\r
+        gpu::GaussianBlur(b.vI2[i], b.mu2, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);\r
 \r
-        gpu::multiply(b.mu1, b.mu1, b.mu1_2, stream);   \r
-        gpu::multiply(b.mu2, b.mu2, b.mu2_2, stream);   \r
-        gpu::multiply(b.mu1, b.mu2, b.mu1_mu2, stream);   \r
+        gpu::multiply(b.mu1, b.mu1, b.mu1_2, stream);\r
+        gpu::multiply(b.mu2, b.mu2, b.mu2_2, stream);\r
+        gpu::multiply(b.mu1, b.mu2, b.mu1_mu2, stream);\r
 \r
-        gpu::GaussianBlur(b.I1_2, b.sigma1_2, Size(11, 11), 1.5, 0, BORDER_DEFAULT, -1, stream);\r
-        gpu::subtract(b.sigma1_2, b.mu1_2, b.sigma1_2, stream);\r
+        gpu::GaussianBlur(b.I1_2, b.sigma1_2, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);\r
+        gpu::subtract(b.sigma1_2, b.mu1_2, b.sigma1_2, gpu::GpuMat(), -1, stream);\r
         //b.sigma1_2 -= b.mu1_2;  - This would result in an extra data transfer operation\r
 \r
-        gpu::GaussianBlur(b.I2_2, b.sigma2_2, Size(11, 11), 1.5, 0, BORDER_DEFAULT, -1, stream);\r
-        gpu::subtract(b.sigma2_2, b.mu2_2, b.sigma2_2, stream);\r
+        gpu::GaussianBlur(b.I2_2, b.sigma2_2, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);\r
+        gpu::subtract(b.sigma2_2, b.mu2_2, b.sigma2_2, gpu::GpuMat(), -1, stream);\r
         //b.sigma2_2 -= b.mu2_2;\r
 \r
-        gpu::GaussianBlur(b.I1_I2, b.sigma12, Size(11, 11), 1.5, 0, BORDER_DEFAULT, -1, stream);\r
-        gpu::subtract(b.sigma12, b.mu1_mu2, b.sigma12, stream);\r
+        gpu::GaussianBlur(b.I1_I2, b.sigma12, Size(11, 11), buf, 1.5, 0, BORDER_DEFAULT, -1, stream);\r
+        gpu::subtract(b.sigma12, b.mu1_mu2, b.sigma12, gpu::GpuMat(), -1, stream);\r
         //b.sigma12 -= b.mu1_mu2;\r
 \r
         //here too it would be an extra data transfer due to call of operator*(Scalar, Mat)\r
-        gpu::multiply(b.mu1_mu2, 2, b.t1, stream); //b.t1 = 2 * b.mu1_mu2 + C1; \r
-        gpu::add(b.t1, C1, b.t1, stream);\r
-        gpu::multiply(b.sigma12, 2, b.t2, stream); //b.t2 = 2 * b.sigma12 + C2; \r
-        gpu::add(b.t2, C2, b.t2, stream);     \r
+        gpu::multiply(b.mu1_mu2, 2, b.t1, 1, -1, stream); //b.t1 = 2 * b.mu1_mu2 + C1;\r
+        gpu::add(b.t1, C1, b.t1, gpu::GpuMat(), -1, stream);\r
+        gpu::multiply(b.sigma12, 2, b.t2, 1, -1, stream); //b.t2 = 2 * b.sigma12 + C2;\r
+        gpu::add(b.t2, C2, b.t2, gpu::GpuMat(), -12, stream);\r
 \r
-        gpu::multiply(b.t1, b.t2, b.t3, stream);     // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))\r
+        gpu::multiply(b.t1, b.t2, b.t3, 1, -1, stream);     // t3 = ((2*mu1_mu2 + C1).*(2*sigma12 + C2))\r
 \r
-        gpu::add(b.mu1_2, b.mu2_2, b.t1, stream);\r
-        gpu::add(b.t1, C1, b.t1, stream);\r
+        gpu::add(b.mu1_2, b.mu2_2, b.t1, gpu::GpuMat(), -1, stream);\r
+        gpu::add(b.t1, C1, b.t1, gpu::GpuMat(), -1, stream);\r
 \r
-        gpu::add(b.sigma1_2, b.sigma2_2, b.t2, stream);\r
-        gpu::add(b.t2, C2, b.t2, stream);\r
+        gpu::add(b.sigma1_2, b.sigma2_2, b.t2, gpu::GpuMat(), -1, stream);\r
+        gpu::add(b.t2, C2, b.t2, gpu::GpuMat(), -1, stream);\r
 \r
 \r
-        gpu::multiply(b.t1, b.t2, b.t1, stream);     // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))        \r
-        gpu::divide(b.t3, b.t1, b.ssim_map, stream);      // ssim_map =  t3./t1;\r
+        gpu::multiply(b.t1, b.t2, b.t1, 1, -1, stream);     // t1 =((mu1_2 + mu2_2 + C1).*(sigma1_2 + sigma2_2 + C2))\r
+        gpu::divide(b.t3, b.t1, b.ssim_map, 1, -1, stream);      // ssim_map =  t3./t1;\r
 \r
         stream.waitForCompletion();\r
 \r
-        Scalar s = gpu::sum(b.ssim_map, b.buf);    \r
+        Scalar s = gpu::sum(b.ssim_map, b.buf);\r
         mssim.val[i] = s.val[0] / (b.ssim_map.rows * b.ssim_map.cols);\r
 \r
     }\r
-    return mssim; \r
-}
\ No newline at end of file
+    return mssim;\r
+}\r
+\r