a part of PR #11364 (extended findNonZero & PSNR) (#11837)

* a part of https://github.com/opencv/opencv/pull/11364 by Tetragramm. Rewritten and extended findNonZero & PSNR to support more types, not just 8u.

* fixed compile & doxygen warnings

* fixed small bug in findNonZero test

modules/core/include/opencv2/core.hpp

@@ -599,7 +599,7 @@ or
     // access pixel coordinates
     Point pnt = locations[i];
 @endcode
-@param src single-channel array (type CV_8UC1)
+@param src single-channel array
 @param idx the output array, type of cv::Mat or std::vector<Point>, corresponding to non-zero indices in the input
 */
 CV_EXPORTS_W void findNonZero( InputArray src, OutputArray idx );
@@ -699,7 +699,8 @@ CV_EXPORTS double norm( const SparseMat& src, int normType );
 
 /** @brief Computes the Peak Signal-to-Noise Ratio (PSNR) image quality metric.
 
-This function calculates the Peak Signal-to-Noise Ratio (PSNR) image quality metric in decibels (dB), between two input arrays src1 and src2. Arrays must have depth CV_8U.
+This function calculates the Peak Signal-to-Noise Ratio (PSNR) image quality metric in decibels (dB),
+between two input arrays src1 and src2. The arrays must have the same type.
 
 The PSNR is calculated as follows:
 
@@ -707,13 +708,15 @@ The PSNR is calculated as follows:
 \texttt{PSNR} = 10 \cdot \log_{10}{\left( \frac{R^2}{MSE} \right) }
 \f]
 
-where R is the maximum integer value of depth CV_8U (255) and MSE is the mean squared error between the two arrays.
+where R is the maximum integer value of depth (e.g. 255 in the case of CV_8U data)
+and MSE is the mean squared error between the two arrays.
 
 @param src1 first input array.
 @param src2 second input array of the same size as src1.
+@param R the maximum pixel value (255 by default)
 
   */
-CV_EXPORTS_W double PSNR(InputArray src1, InputArray src2);
+CV_EXPORTS_W double PSNR(InputArray src1, InputArray src2, double R=255.);
 
 /** @brief naive nearest neighbor finder
 

modules/core/src/count_non_zero.cpp

@@ -393,25 +393,60 @@ void cv::findNonZero( InputArray _src, OutputArray _idx )
     CV_INSTRUMENT_REGION()
 
     Mat src = _src.getMat();
-    CV_Assert( src.type() == CV_8UC1 );
-    int n = countNonZero(src);
-    if( n == 0 )
+    CV_Assert( src.channels() == 1 && src.dims == 2 );
+
+    int depth = src.depth();
+    std::vector<Point> idxvec;
+    int rows = src.rows, cols = src.cols;
+    AutoBuffer<int> buf_(cols + 1);
+    int* buf = buf_;
+
+    for( int i = 0; i < rows; i++ )
     {
-        _idx.release();
-        return;
+        int j, k = 0;
+        const uchar* ptr8 = src.ptr(i);
+        if( depth == CV_8U || depth == CV_8S )
+        {
+            for( j = 0; j < cols; j++ )
+                if( ptr8[j] != 0 ) buf[k++] = j;
+        }
+        else if( depth == CV_16U || depth == CV_16S )
+        {
+            const ushort* ptr16 = (const ushort*)ptr8;
+            for( j = 0; j < cols; j++ )
+                if( ptr16[j] != 0 ) buf[k++] = j;
+        }
+        else if( depth == CV_32S )
+        {
+            const int* ptr32s = (const int*)ptr8;
+            for( j = 0; j < cols; j++ )
+                if( ptr32s[j] != 0 ) buf[k++] = j;
+        }
+        else if( depth == CV_32F )
+        {
+            const float* ptr32f = (const float*)ptr8;
+            for( j = 0; j < cols; j++ )
+                if( ptr32f[j] != 0 ) buf[k++] = j;
+        }
+        else
+        {
+            const double* ptr64f = (const double*)ptr8;
+            for( j = 0; j < cols; j++ )
+                if( ptr64f[j] != 0 ) buf[k++] = j;
+        }
+
+        if( k > 0 )
+        {
+            size_t sz = idxvec.size();
+            idxvec.resize(sz + k);
+            for( j = 0; j < k; j++ )
+                idxvec[sz + j] = Point(buf[j], i);
+        }
     }
-    if( _idx.kind() == _InputArray::MAT && !_idx.getMatRef().isContinuous() )
+
+    if( idxvec.empty() || (_idx.kind() == _InputArray::MAT && !_idx.getMatRef().isContinuous()) )
         _idx.release();
-    _idx.create(n, 1, CV_32SC2);
-    Mat idx = _idx.getMat();
-    CV_Assert(idx.isContinuous());
-    Point* idx_ptr = idx.ptr<Point>();
 
-    for( int i = 0; i < src.rows; i++ )
-    {
-        const uchar* bin_ptr = src.ptr(i);
-        for( int j = 0; j < src.cols; j++ )
-            if( bin_ptr[j] )
-                *idx_ptr++ = Point(j, i);
-    }
+    if( !idxvec.empty() )
+        Mat(idxvec).copyTo(_idx);
 }

modules/core/src/norm.cpp

@@ -1251,13 +1251,13 @@ cv::Hamming::ResultType cv::Hamming::operator()( const unsigned char* a, const u
     return cv::hal::normHamming(a, b, size);
 }
 
-double cv::PSNR(InputArray _src1, InputArray _src2)
+double cv::PSNR(InputArray _src1, InputArray _src2, double R)
 {
     CV_INSTRUMENT_REGION()
 
     //Input arrays must have depth CV_8U
-    CV_Assert( _src1.depth() == CV_8U && _src2.depth() == CV_8U );
+    CV_Assert( _src1.type() == _src2.type() );
 
     double diff = std::sqrt(norm(_src1, _src2, NORM_L2SQR)/(_src1.total()*_src1.channels()));
-    return 20*log10(255./(diff+DBL_EPSILON));
+    return 20*log10(R/(diff+DBL_EPSILON));
 }

modules/core/test/test_arithm.cpp

@@ -1847,13 +1847,54 @@ INSTANTIATE_TEST_CASE_P(Arithm, SubtractOutputMatNotEmpty, testing::Combine(
     testing::Values(-1, CV_16S, CV_32S, CV_32F),
     testing::Bool()));
 
-TEST(Core_FindNonZero, singular)
+TEST(Core_FindNonZero, regression)
 {
     Mat img(10, 10, CV_8U, Scalar::all(0));
-    vector<Point> pts, pts2(10);
+    vector<Point> pts, pts2(5);
     findNonZero(img, pts);
     findNonZero(img, pts2);
     ASSERT_TRUE(pts.empty() && pts2.empty());
+
+    RNG rng((uint64)-1);
+    size_t nz = 0;
+    for( int i = 0; i < 10; i++ )
+    {
+        int idx = rng.uniform(0, img.rows*img.cols);
+        if( !img.data[idx] ) nz++;
+        img.data[idx] = (uchar)rng.uniform(1, 256);
+    }
+    findNonZero(img, pts);
+    ASSERT_TRUE(pts.size() == nz);
+
+    img.convertTo( img, CV_8S );
+    pts.clear();
+    findNonZero(img, pts);
+    ASSERT_TRUE(pts.size() == nz);
+
+    img.convertTo( img, CV_16U );
+    pts.resize(pts.size()*2);
+    findNonZero(img, pts);
+    ASSERT_TRUE(pts.size() == nz);
+
+    img.convertTo( img, CV_16S );
+    pts.resize(pts.size()*3);
+    findNonZero(img, pts);
+    ASSERT_TRUE(pts.size() == nz);
+
+    img.convertTo( img, CV_32S );
+    pts.resize(pts.size()*4);
+    findNonZero(img, pts);
+    ASSERT_TRUE(pts.size() == nz);
+
+    img.convertTo( img, CV_32F );
+    pts.resize(pts.size()*5);
+    findNonZero(img, pts);
+    ASSERT_TRUE(pts.size() == nz);
+
+    img.convertTo( img, CV_64F );
+    pts.clear();
+    findNonZero(img, pts);
+    ASSERT_TRUE(pts.size() == nz);
 }
 
 TEST(Core_BoolVector, support)