cv2cvtest part2

modules/highgui/test/test_ffmpeg.cpp

@@ -329,7 +329,7 @@ public:
                 EXPECT_EQ(reference.depth(), actual.depth());
                 EXPECT_EQ(reference.channels(), actual.channels());
 
-                double psnr = PSNR(actual, reference);
+                double psnr = cvtest::PSNR(actual, reference);
                 if (psnr < eps)
                 {
     #define SUM cvtest::TS::SUMMARY

modules/highgui/test/test_video_io.cpp

@@ -198,7 +198,7 @@ void CV_HighGuiTest::ImageTest(const string& dir)
         }
 
         const double thresDbell = 20;
-        double psnr = PSNR(loaded, image);
+        double psnr = cvtest::PSNR(loaded, image);
         if (psnr < thresDbell)
         {
             ts->printf(ts->LOG, "Reading image from file: too big difference (=%g) with fmt=%s\n", psnr, ext.c_str());
@@ -235,7 +235,7 @@ void CV_HighGuiTest::ImageTest(const string& dir)
             continue;
         }
 
-        psnr = PSNR(buf_loaded, image);
+        psnr = cvtest::PSNR(buf_loaded, image);
 
         if (psnr < thresDbell)
         {
@@ -316,7 +316,7 @@ void CV_HighGuiTest::VideoTest(const string& dir, const cvtest::VideoFormat& fmt
         Mat img = frames[i];
         Mat img1 = cv::cvarrToMat(ipl1);
 
-        double psnr = PSNR(img1, img);
+        double psnr = cvtest::PSNR(img1, img);
         if (psnr < thresDbell)
         {
             ts->printf(ts->LOG, "Too low frame %d psnr = %gdb\n", i, psnr);
@@ -371,7 +371,7 @@ void CV_HighGuiTest::SpecificImageTest(const string& dir)
         }
 
         const double thresDbell = 20;
-        double psnr = PSNR(loaded, image);
+        double psnr = cvtest::PSNR(loaded, image);
         if (psnr < thresDbell)
         {
             ts->printf(ts->LOG, "Reading image from file: too big difference (=%g) with fmt=bmp\n", psnr);
@@ -408,7 +408,7 @@ void CV_HighGuiTest::SpecificImageTest(const string& dir)
             continue;
         }
 
-        psnr = PSNR(buf_loaded, image);
+        psnr = cvtest::PSNR(buf_loaded, image);
 
         if (psnr < thresDbell)
         {
@@ -521,7 +521,7 @@ void CV_HighGuiTest::SpecificVideoTest(const string& dir, const cvtest::VideoFor
         Mat img = images[i];
 
         const double thresDbell = 40;
-        double psnr = PSNR(img, frame);
+        double psnr = cvtest::PSNR(img, frame);
 
         if (psnr > thresDbell)
         {

modules/highgui/test/test_video_pos.cpp

@@ -160,7 +160,7 @@ public:
                     return;
                 }
 
-                double err = PSNR(img, img0);
+                double err = cvtest::PSNR(img, img0);
 
                 if( err < 20 )
                 {

modules/legacy/test/test_stereomatching.cpp

@@ -278,7 +278,7 @@ float dispRMS( const Mat& computedDisp, const Mat& groundTruthDisp, const Mat& m
         checkTypeAndSizeOfMask( mask, sz );
         pointsCount = countNonZero(mask);
     }
-    return 1.f/sqrt((float)pointsCount) * (float)norm(computedDisp, groundTruthDisp, NORM_L2, mask);
+    return 1.f/sqrt((float)pointsCount) * (float)cvtest::norm(computedDisp, groundTruthDisp, NORM_L2, mask);
 }
 
 /*

modules/optim/test/test_denoise_tvl1.cpp

@@ -41,7 +41,8 @@
 #include "test_precomp.hpp"
 #include "opencv2/highgui.hpp"
 
-void make_noisy(const cv::Mat& img, cv::Mat& noisy, double sigma, double pepper_salt_ratio,cv::RNG& rng){
+void make_noisy(const cv::Mat& img, cv::Mat& noisy, double sigma, double pepper_salt_ratio,cv::RNG& rng)
+{
     noisy.create(img.size(), img.type());
     cv::Mat noise(img.size(), img.type()), mask(img.size(), CV_8U);
     rng.fill(noise,cv::RNG::NORMAL,128.0,sigma);
@@ -54,34 +55,36 @@ void make_noisy(const cv::Mat& img, cv::Mat& noisy, double sigma, double pepper_
     noise.setTo(128, mask);
     cv::addWeighted(noisy, 1, noise, 1, -128, noisy);
 }
-void make_spotty(cv::Mat& img,cv::RNG& rng, int r=3,int n=1000){
+
-    for(int i=0;i<n;i++){
+void make_spotty(cv::Mat& img,cv::RNG& rng, int r=3,int n=1000)
+{
+    for(int i=0;i<n;i++)
+    {
         int x=rng(img.cols-r),y=rng(img.rows-r);
-        if(rng(2)==0){
+        if(rng(2)==0)
             img(cv::Range(y,y+r),cv::Range(x,x+r))=(uchar)0;
-        }else{
+        else
             img(cv::Range(y,y+r),cv::Range(x,x+r))=(uchar)255;
     }
-    }
 }
 
-bool validate_pixel(const cv::Mat& image,int x,int y,uchar val){
+bool validate_pixel(const cv::Mat& image,int x,int y,uchar val)
+{
     printf("test: image(%d,%d)=%d vs %d - %s\n",x,y,(int)image.at<uchar>(x,y),val,(val==image.at<uchar>(x,y))?"true":"false");
     return (image.at<uchar>(x,y)==val);
 }
 
-TEST(Optim_denoise_tvl1, regression_basic){
+TEST(Optim_denoise_tvl1, regression_basic)
+{
     cv::RNG rng(42);
-    cv::Mat img = cv::imread("lena.jpg", 0), noisy,res;
+    cv::Mat img = cv::imread(cvtest::TS::ptr()->get_data_path() + "shared/lena.png", 0), noisy, res;
-    if(img.rows!=512 || img.cols!=512){
+
-        printf("\tplease, put lena.jpg from samples/c in the current folder\n");
+    ASSERT_FALSE(img.empty()) << "Error: can't open 'lena.png'";
-        printf("\tnow, the test will fail...\n");
-        ASSERT_TRUE(false);
-    }
 
     const int obs_num=5;
-    std::vector<cv::Mat> images(obs_num,cv::Mat());
+    std::vector<cv::Mat> images(obs_num, cv::Mat());
-    for(int i=0;i<(int)images.size();i++){
+    for(int i=0;i<(int)images.size();i++)
+    {
         make_noisy(img,images[i], 20, 0.02,rng);
         //make_spotty(images[i],rng);
     }

modules/photo/test/test_denoising.cpp

@@ -73,7 +73,7 @@ TEST(Photo_DenoisingGrayscale, regression)
 
     DUMP(result, expected_path + ".res.png");
 
-    ASSERT_EQ(0, norm(result != expected));
+    ASSERT_EQ(0, cvtest::norm(result, expected, NORM_L2));
 }
 
 TEST(Photo_DenoisingColored, regression)
@@ -93,7 +93,7 @@ TEST(Photo_DenoisingColored, regression)
 
     DUMP(result, expected_path + ".res.png");
 
-    ASSERT_EQ(0, norm(result != expected));
+    ASSERT_EQ(0, cvtest::norm(result, expected, NORM_L2));
 }
 
 TEST(Photo_DenoisingGrayscaleMulti, regression)
@@ -118,7 +118,7 @@ TEST(Photo_DenoisingGrayscaleMulti, regression)
 
     DUMP(result, expected_path + ".res.png");
 
-    ASSERT_EQ(0, norm(result != expected));
+    ASSERT_EQ(0, cvtest::norm(result, expected, NORM_L2));
 }
 
 TEST(Photo_DenoisingColoredMulti, regression)
@@ -143,7 +143,7 @@ TEST(Photo_DenoisingColoredMulti, regression)
 
     DUMP(result, expected_path + ".res.png");
 
-    ASSERT_EQ(0, norm(result != expected));
+    ASSERT_EQ(0, cvtest::norm(result, expected, NORM_L2));
 }
 
 TEST(Photo_White, issue_2646)

modules/photo/test/test_inpaint.cpp

@@ -91,8 +91,8 @@ void CV_InpaintTest::run( int )
     absdiff( orig, res1, diff1 );
     absdiff( orig, res2, diff2 );
 
-    double n1 = norm(diff1.reshape(1), NORM_INF, inv_mask.reshape(1));
+    double n1 = cvtest::norm(diff1.reshape(1), NORM_INF, inv_mask.reshape(1));
-    double n2 = norm(diff2.reshape(1), NORM_INF, inv_mask.reshape(1));
+    double n2 = cvtest::norm(diff2.reshape(1), NORM_INF, inv_mask.reshape(1));
 
     if (n1 != 0 || n2 != 0)
     {
@@ -103,8 +103,8 @@ void CV_InpaintTest::run( int )
     absdiff( exp1, res1, diff1 );
     absdiff( exp2, res2, diff2 );
 
-    n1 = norm(diff1.reshape(1), NORM_INF, mask.reshape(1));
+    n1 = cvtest::norm(diff1.reshape(1), NORM_INF, mask.reshape(1));
-    n2 = norm(diff2.reshape(1), NORM_INF, mask.reshape(1));
+    n2 = cvtest::norm(diff2.reshape(1), NORM_INF, mask.reshape(1));
 
     const int jpeg_thres = 3;
     if (n1 > jpeg_thres || n2 > jpeg_thres)

modules/stitching/test/test_blenders.cpp

@@ -73,6 +73,6 @@ TEST(MultiBandBlender, CanBlendTwoImages)
     Mat result; result_s.convertTo(result, CV_8U);
 
     Mat expected = imread(string(cvtest::TS::ptr()->get_data_path()) + "stitching/baboon_lena.png");
-    double rmsErr = norm(expected, result, NORM_L2) / sqrt(double(expected.size().area()));
+    double rmsErr = cvtest::norm(expected, result, NORM_L2) / sqrt(double(expected.size().area()));
     ASSERT_LT(rmsErr, 1e-3);
 }

modules/ts/include/opencv2/ts.hpp

@@ -129,6 +129,7 @@ CV_EXPORTS void minMaxLoc(const Mat& src, double* minval, double* maxval,
 CV_EXPORTS double norm(InputArray src, int normType, InputArray mask=noArray());
 CV_EXPORTS double norm(InputArray src1, InputArray src2, int normType, InputArray mask=noArray());
 CV_EXPORTS Scalar mean(const Mat& src, const Mat& mask=Mat());
+CV_EXPORTS double PSNR(InputArray src1, InputArray src2);
 
 CV_EXPORTS bool cmpUlps(const Mat& data, const Mat& refdata, int expMaxDiff, double* realMaxDiff, vector<int>* idx);
 

modules/ts/src/ts_func.cpp

@@ -1399,6 +1399,12 @@ double norm(InputArray _src1, InputArray _src2, int normType, InputArray _mask)
     return isRelative ? result / (cvtest::norm(src2, normType) + DBL_EPSILON) : result;
 }
 
+double PSNR(InputArray _src1, InputArray _src2)
+{
+    CV_Assert( _src1.depth() == CV_8U );
+    double diff = std::sqrt(cvtest::norm(_src1, _src2, NORM_L2SQR)/(_src1.total()*_src1.channels()));
+    return 20*log10(255./(diff+DBL_EPSILON));
+}
 
 template<typename _Tp> static double
 crossCorr_(const _Tp* src1, const _Tp* src2, size_t total)

modules/video/test/test_estimaterigid.cpp

@@ -109,8 +109,8 @@ bool CV_RigidTransform_Test::testNPoints(int from)
 
         Mat aff_est = estimateRigidTransform(fpts, tpts, true);
 
-        double thres = 0.1*norm(aff);
+        double thres = 0.1*cvtest::norm(aff, NORM_L2);
-        double d = norm(aff_est, aff, NORM_L2);
+        double d = cvtest::norm(aff_est, aff, NORM_L2);
         if (d > thres)
         {
             double dB=0, nB=0;
@@ -120,7 +120,7 @@ bool CV_RigidTransform_Test::testNPoints(int from)
                 Mat B = A - repeat(A.row(0), 3, 1), Bt = B.t();
                 B = Bt*B;
                 dB = cv::determinant(B);
-                nB = norm(B);
+                nB = cvtest::norm(B, NORM_L2);
                 if( fabs(dB) < 0.01*nB )
                     continue;
             }
@@ -154,11 +154,11 @@ bool CV_RigidTransform_Test::testImage()
     Mat aff_est = estimateRigidTransform(img, rotated, true);
 
     const double thres = 0.033;
-    if (norm(aff_est, aff, NORM_INF) > thres)
+    if (cvtest::norm(aff_est, aff, NORM_INF) > thres)
     {
         ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
         ts->printf( cvtest::TS::LOG, "Threshold = %f, norm of difference = %f", thres,
-            norm(aff_est, aff, NORM_INF) );
+            cvtest::norm(aff_est, aff, NORM_INF) );
         return false;
     }