format files to ANSI C style with coolformat

change the download channels to oclchannles()
fix bugs of arithm functions
perf fix of bilateral
bug fix of split test case
add build_warps functions

modules/ocl/include/opencv2/ocl/matrix_operations.hpp

@@ -55,22 +55,22 @@ namespace cv
         //////////////////////////////// oclMat ////////////////////////////////
         ////////////////////////////////////////////////////////////////////////
 
-        inline oclMat::oclMat() : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0), download_channels(0) {}
+        inline oclMat::oclMat() : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0) {}
 
-        inline oclMat::oclMat(int _rows, int _cols, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0), download_channels(0)
+        inline oclMat::oclMat(int _rows, int _cols, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0)
         {
             if( _rows > 0 && _cols > 0 )
                 create( _rows, _cols, _type );
         }
 
-        inline oclMat::oclMat(Size _size, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0), download_channels(0)
+        inline oclMat::oclMat(Size _size, int _type) : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0)
         {
             if( _size.height > 0 && _size.width > 0 )
                 create( _size.height, _size.width, _type );
         }
 
         inline oclMat::oclMat(int _rows, int _cols, int _type, const Scalar &_s)
-            : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0), download_channels(0)
+            : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0)
         {
             if(_rows > 0 && _cols > 0)
             {
@@ -80,7 +80,7 @@ namespace cv
         }
 
         inline oclMat::oclMat(Size _size, int _type, const Scalar &_s)
-            : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0), download_channels(0)
+            : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0)
         {
             if( _size.height > 0 && _size.width > 0 )
             {
@@ -91,7 +91,7 @@ namespace cv
 
         inline oclMat::oclMat(const oclMat &m)
             : flags(m.flags), rows(m.rows), cols(m.cols), step(m.step), data(m.data),
-			refcount(m.refcount), datastart(m.datastart), dataend(m.dataend), clCxt(m.clCxt), offset(m.offset), wholerows(m.wholerows), wholecols(m.wholecols), download_channels(m.download_channels)
+              refcount(m.refcount), datastart(m.datastart), dataend(m.dataend), clCxt(m.clCxt), offset(m.offset), wholerows(m.wholerows), wholecols(m.wholecols)
         {
             if( refcount )
                 CV_XADD(refcount, 1);
@@ -99,9 +99,9 @@ namespace cv
 
         inline oclMat::oclMat(int _rows, int _cols, int _type, void *_data, size_t _step)
             : flags(0), rows(0), cols(0), step(0), data(0), refcount(0),
-              datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0), download_channels(0)
+              datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0)
         {
-			cv::Mat m(_rows,_cols,_type,_data,_step);
+            cv::Mat m(_rows, _cols, _type, _data, _step);
             upload(m);
             //size_t minstep = cols * elemSize();
             //if( step == Mat::AUTO_STEP )
@@ -121,9 +121,9 @@ namespace cv
         inline oclMat::oclMat(Size _size, int _type, void *_data, size_t _step)
             : flags(0), rows(0), cols(0),
               step(0), data(0), refcount(0),
-              datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0), download_channels(0)
+              datastart(0), dataend(0), offset(0), wholerows(0), wholecols(0)
         {
-			cv::Mat m(_size,_type,_data,_step);
+            cv::Mat m(_size, _type, _data, _step);
             upload(m);
             //size_t minstep = cols * elemSize();
             //if( step == Mat::AUTO_STEP )
@@ -152,7 +152,6 @@ namespace cv
             wholerows = m.wholerows;
             wholecols = m.wholecols;
             offset = m.offset;
-			download_channels = m.download_channels;
             if( rowRange == Range::all() )
                 rows = m.rows;
             else
@@ -184,7 +183,7 @@ namespace cv
         inline oclMat::oclMat(const oclMat &m, const Rect &roi)
             : flags(m.flags), rows(roi.height), cols(roi.width),
               step(m.step), data(m.data), refcount(m.refcount),
-			  datastart(m.datastart), dataend(m.dataend), clCxt(m.clCxt), offset(m.offset), wholerows(m.wholerows), wholecols(m.wholecols), download_channels(m.download_channels)
+              datastart(m.datastart), dataend(m.dataend), clCxt(m.clCxt), offset(m.offset), wholerows(m.wholerows), wholecols(m.wholecols)
         {
             flags &= roi.width < m.cols ? ~Mat::CONTINUOUS_FLAG : -1;
             offset += roi.y * step + roi.x * elemSize();
@@ -197,7 +196,7 @@ namespace cv
         }
 
         inline oclMat::oclMat(const Mat &m)
-            : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) , offset(0), wholerows(0), wholecols(0), download_channels(0)
+            : flags(0), rows(0), cols(0), step(0), data(0), refcount(0), datastart(0), dataend(0) , offset(0), wholerows(0), wholecols(0)
         {
             //clCxt = Context::getContext();
             upload(m);
@@ -227,7 +226,6 @@ namespace cv
                 wholerows = m.wholerows;
                 wholecols = m.wholecols;
                 refcount = m.refcount;
-				download_channels = m.download_channels;
             }
             return *this;
         }
@@ -330,7 +328,6 @@ namespace cv
             std::swap( clCxt,  b.clCxt );
             std::swap( wholerows, b.wholerows );
             std::swap( wholecols, b.wholecols );
-			std::swap( download_channels, b.download_channels);
         }
 
         inline void oclMat::locateROI( Size &wholeSize, Point &ofs ) const
@@ -366,7 +363,7 @@ namespace cv
             offset += (row1 - ofs.y) * step + (col1 - ofs.x) * esz;
             rows = row2 - row1;
             cols = col2 - col1;
-            if( esz *cols == step || rows == 1 )
+            if( esz * cols == step || rows == 1 )
                 flags |= Mat::CONTINUOUS_FLAG;
             else
                 flags &= ~Mat::CONTINUOUS_FLAG;
@@ -388,7 +385,7 @@ namespace cv
         }
         inline size_t oclMat::elemSize() const
         {
-            return CV_ELEM_SIZE(flags);
+            return CV_ELEM_SIZE((CV_MAKE_TYPE(type(), oclchannels())));
         }
         inline size_t oclMat::elemSize1() const
         {
@@ -398,6 +395,10 @@ namespace cv
         {
             return CV_MAT_TYPE(flags);
         }
+        inline int oclMat::ocltype() const
+        {
+            return CV_MAKE_TYPE(depth(), oclchannels());
+        }
         inline int oclMat::depth() const
         {
             return CV_MAT_DEPTH(flags);
@@ -406,6 +407,10 @@ namespace cv
         {
             return CV_MAT_CN(flags);
         }
+        inline int oclMat::oclchannels() const
+        {
+            return (CV_MAT_CN(flags)) == 3 ? 4 : (CV_MAT_CN(flags));
+        }
         inline size_t oclMat::step1() const
         {
             return step / elemSize1();
@@ -424,28 +429,28 @@ namespace cv
         inline uchar *oclMat::ptr(int y)
         {
             CV_DbgAssert( (unsigned)y < (unsigned)rows );
-			CV_Error(CV_GpuNotSupported,"This function hasn't been supported yet.\n");
+            CV_Error(CV_GpuNotSupported, "This function hasn't been supported yet.\n");
             return data + step * y;
         }
 
         inline const uchar *oclMat::ptr(int y) const
         {
             CV_DbgAssert( (unsigned)y < (unsigned)rows );
-			CV_Error(CV_GpuNotSupported,"This function hasn't been supported yet.\n");
+            CV_Error(CV_GpuNotSupported, "This function hasn't been supported yet.\n");
             return data + step * y;
         }
 
         template<typename _Tp> inline _Tp *oclMat::ptr(int y)
         {
             CV_DbgAssert( (unsigned)y < (unsigned)rows );
-			CV_Error(CV_GpuNotSupported,"This function hasn't been supported yet.\n");
+            CV_Error(CV_GpuNotSupported, "This function hasn't been supported yet.\n");
             return (_Tp *)(data + step * y);
         }
 
         template<typename _Tp> inline const _Tp *oclMat::ptr(int y) const
         {
             CV_DbgAssert( (unsigned)y < (unsigned)rows );
-			CV_Error(CV_GpuNotSupported,"This function hasn't been supported yet.\n");
+            CV_Error(CV_GpuNotSupported, "This function hasn't been supported yet.\n");
             return (const _Tp *)(data + step * y);
         }
 
@@ -461,7 +466,7 @@ namespace cv
             a.swap(b);
         }
 
-		inline void ensureSizeIsEnough(int rows, int cols, int type, oclMat& m)
+        inline void ensureSizeIsEnough(int rows, int cols, int type, oclMat &m)
         {
             if (m.type() == type && m.rows >= rows && m.cols >= cols)
                 m = m(Rect(0, 0, cols, rows));
@@ -469,10 +474,12 @@ namespace cv
                 m.create(rows, cols, type);
         }
 
-		inline void ensureSizeIsEnough(Size size, int type, oclMat& m)
+        inline void ensureSizeIsEnough(Size size, int type, oclMat &m)
         {
             ensureSizeIsEnough(size.height, size.width, type, m);
         }
+
+
     } /* end of namespace ocl */
 
 } /* end of namespace cv */

modules/ocl/perf/interpolation.hpp

@@ -42,7 +42,7 @@
 #ifndef __OPENCV_TEST_INTERPOLATION_HPP__
 #define __OPENCV_TEST_INTERPOLATION_HPP__
 
-template <typename T> T readVal(const cv::Mat& src, int y, int x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
+template <typename T> T readVal(const cv::Mat &src, int y, int x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
 {
     if (border_type == cv::BORDER_CONSTANT)
         return (y >= 0 && y < src.rows && x >= 0 && x < src.cols) ? src.at<T>(y, x * src.channels() + c) : cv::saturate_cast<T>(borderVal.val[c]);
@@ -52,7 +52,7 @@ template <typename T> T readVal(const cv::Mat& src, int y, int x, int c, int bor
 
 template <typename T> struct NearestInterpolator
 {
-    static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
+    static T getValue(const cv::Mat &src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
     {
         return readVal<T>(src, cvFloor(y), cvFloor(x), c, border_type, borderVal);
     }
@@ -60,7 +60,7 @@ template <typename T> struct NearestInterpolator
 
 template <typename T> struct LinearInterpolator
 {
-    static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
+    static T getValue(const cv::Mat &src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
     {
         x -= 0.5f;
         y -= 0.5f;
@@ -85,7 +85,7 @@ template <typename T> struct CubicInterpolator
 {
     static float getValue(float p[4], float x)
     {
-        return p[1] + 0.5 * x * (p[2] - p[0] + x*(2.0*p[0] - 5.0*p[1] + 4.0*p[2] - p[3] + x*(3.0*(p[1] - p[2]) + p[3] - p[0])));
+        return p[1] + 0.5 * x * (p[2] - p[0] + x * (2.0 * p[0] - 5.0 * p[1] + 4.0 * p[2] - p[3] + x * (3.0 * (p[1] - p[2]) + p[3] - p[0])));
     }
 
     static float getValue(float p[4][4], float x, float y)
@@ -100,7 +100,7 @@ template <typename T> struct CubicInterpolator
         return getValue(arr, y);
     }
 
-    static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
+    static T getValue(const cv::Mat &src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
     {
         int ix = cvRound(x);
         int iy = cvRound(y);

modules/ocl/perf/main.cpp

@@ -74,7 +74,7 @@ void print_info()
 
 }
 
-int main(int argc, char** argv)
+int main(int argc, char **argv)
 {
     std::vector<cv::ocl::Info> oclinfo;
     TS::ptr()->init("ocl");
@@ -82,7 +82,7 @@ int main(int argc, char** argv)
 
     print_info();
     int devnums = getDevice(oclinfo);
-	if(devnums<1)
+    if(devnums < 1)
     {
         std::cout << "no device found\n";
         return -1;

modules/ocl/perf/perf_canny.cpp

@@ -101,7 +101,7 @@ PARAM_TEST_CASE(Canny1, AppertureSize, L2gradient)
 
 TEST_P(Canny1, Performance)
 {
-	cv::Mat img = readImage(FILTER_IMAGE,cv::IMREAD_GRAYSCALE);
+    cv::Mat img = readImage(FILTER_IMAGE, cv::IMREAD_GRAYSCALE);
     ASSERT_FALSE(img.empty());
 
     double low_thresh = 100.0;
@@ -110,19 +110,19 @@ TEST_P(Canny1, Performance)
     cv::Mat edges_gold;
     cv::ocl::oclMat edges;
 
-    double totalgputick=0;
-	double totalgputick_kernel=0;
+    double totalgputick = 0;
+    double totalgputick_kernel = 0;
 
-	double t1=0;
-	double t2=0;
-	for(int j = 0; j < LOOP_TIMES+1; j ++)
+    double t1 = 0;
+    double t2 = 0;
+    for(int j = 0; j < LOOP_TIMES + 1; j ++)
     {
 
         t1 = (double)cvGetTickCount();//gpu start1
 
         cv::ocl::oclMat ocl_img = cv::ocl::oclMat(img);//upload
 
-		t2=(double)cvGetTickCount();//kernel
+        t2 = (double)cvGetTickCount(); //kernel
         cv::ocl::Canny(ocl_img, edges, low_thresh, high_thresh, apperture_size, useL2gradient);
         t2 = (double)cvGetTickCount() - t2;//kernel
 
@@ -134,14 +134,14 @@ TEST_P(Canny1, Performance)
         if(j == 0)
             continue;
 
-		totalgputick=t1+totalgputick;
+        totalgputick = t1 + totalgputick;
 
-		totalgputick_kernel=t2+totalgputick_kernel;	
+        totalgputick_kernel = t2 + totalgputick_kernel;
 
     }
 
-	cout << "average gpu runtime is  " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
-	cout << "average gpu runtime without data transfer is  " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
+    cout << "average gpu runtime is  " << totalgputick / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
+    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
 
 
 }

modules/ocl/perf/perf_columnsum.cpp

@@ -75,24 +75,24 @@ PARAM_TEST_CASE(ColumnSum)
 
 TEST_F(ColumnSum, Performance)
 {
-	cv::Size size(MWIDTH,MHEIGHT);
+    cv::Size size(MWIDTH, MHEIGHT);
     cv::Mat src = randomMat(size, CV_32FC1);
     cv::ocl::oclMat d_dst;
 
-	double totalgputick=0;
-	double totalgputick_kernel=0;
-	double t1=0;
-	double t2=0;
+    double totalgputick = 0;
+    double totalgputick_kernel = 0;
+    double t1 = 0;
+    double t2 = 0;
 
-	for(int j = 0; j < LOOP_TIMES+1; j ++)
+    for(int j = 0; j < LOOP_TIMES + 1; j ++)
     {
 
         t1 = (double)cvGetTickCount();//gpu start1
 
         cv::ocl::oclMat d_src(src);
 
-		t2=(double)cvGetTickCount();//kernel
-		cv::ocl::columnSum(d_src,d_dst);
+        t2 = (double)cvGetTickCount(); //kernel
+        cv::ocl::columnSum(d_src, d_dst);
         t2 = (double)cvGetTickCount() - t2;//kernel
 
         cv::Mat cpu_dst;
@@ -103,13 +103,13 @@ TEST_F(ColumnSum, Performance)
         if(j == 0)
             continue;
 
-		totalgputick=t1+totalgputick;
-		totalgputick_kernel=t2+totalgputick_kernel;	
+        totalgputick = t1 + totalgputick;
+        totalgputick_kernel = t2 + totalgputick_kernel;
 
     }
 
-	cout << "average gpu runtime is  " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
-	cout << "average gpu runtime without data transfer is  " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
+    cout << "average gpu runtime is  " << totalgputick / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
+    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
 
 
 

modules/ocl/perf/perf_fft.cpp

@@ -69,19 +69,19 @@ TEST_P(Dft, C2C)
 
     cv::ocl::oclMat d_b;
 
-	double totalgputick=0;
-	double totalgputick_kernel=0;
-	double t1=0;
-	double t2=0;
+    double totalgputick = 0;
+    double totalgputick_kernel = 0;
+    double t1 = 0;
+    double t2 = 0;
 
-	for(int j = 0; j < LOOP_TIMES+1; j ++)
+    for(int j = 0; j < LOOP_TIMES + 1; j ++)
     {
 
         t1 = (double)cvGetTickCount();//gpu start1
 
-		cv::ocl::oclMat ga=cv::ocl::oclMat(a);//upload
+        cv::ocl::oclMat ga = cv::ocl::oclMat(a); //upload
 
-		t2=(double)cvGetTickCount();//kernel
+        t2 = (double)cvGetTickCount(); //kernel
         cv::ocl::dft(ga, d_b, a.size(), flags);
         t2 = (double)cvGetTickCount() - t2;//kernel
 
@@ -93,13 +93,13 @@ TEST_P(Dft, C2C)
         if(j == 0)
             continue;
 
-		totalgputick=t1+totalgputick;	
-		totalgputick_kernel=t2+totalgputick_kernel;	
+        totalgputick = t1 + totalgputick;
+        totalgputick_kernel = t2 + totalgputick_kernel;
 
     }
 
-	cout << "average gpu runtime is  " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
-	cout << "average gpu runtime without data transfer is  " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
+    cout << "average gpu runtime is  " << totalgputick / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
+    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
 }
 
 

modules/ocl/perf/perf_gemm.cpp

@@ -71,12 +71,12 @@ TEST_P(Gemm, Performance)
     cv::Mat c = randomMat(mat_size, type, 0.0, 10.0);
     cv::ocl::oclMat ocl_dst;
 
-	double totalgputick=0;
-	double totalgputick_kernel=0;
-	double t1=0;
-	double t2=0;
+    double totalgputick = 0;
+    double totalgputick_kernel = 0;
+    double t1 = 0;
+    double t2 = 0;
 
-	for(int j = 0; j < LOOP_TIMES+1; j ++)
+    for(int j = 0; j < LOOP_TIMES + 1; j ++)
     {
 
         t1 = (double)cvGetTickCount();//gpu start1
@@ -85,8 +85,8 @@ TEST_P(Gemm, Performance)
         cv::ocl::oclMat gb = cv::ocl::oclMat(b);//upload
         cv::ocl::oclMat gc = cv::ocl::oclMat(c);//upload
 
-		t2=(double)cvGetTickCount();//kernel
-		cv::ocl::gemm(ga, gb, 1.0,gc, 1.0, ocl_dst, flags);
+        t2 = (double)cvGetTickCount(); //kernel
+        cv::ocl::gemm(ga, gb, 1.0, gc, 1.0, ocl_dst, flags);
         t2 = (double)cvGetTickCount() - t2;//kernel
 
         cv::Mat cpu_dst;
@@ -97,12 +97,12 @@ TEST_P(Gemm, Performance)
         if(j == 0)
             continue;
 
-		totalgputick=t1+totalgputick;	
-		totalgputick_kernel=t2+totalgputick_kernel;	
+        totalgputick = t1 + totalgputick;
+        totalgputick_kernel = t2 + totalgputick_kernel;
 
     }
-	cout << "average gpu runtime is  " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
-    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
+    cout << "average gpu runtime is  " << totalgputick / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
+    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
 }
 
 

modules/ocl/perf/perf_haar.cpp

@@ -53,7 +53,13 @@ using namespace testing;
 using namespace std;
 using namespace cv;
 
-struct getRect { Rect operator ()(const CvAvgComp& e) const { return e.rect; } };
+struct getRect
+{
+    Rect operator ()(const CvAvgComp &e) const
+    {
+        return e.rect;
+    }
+};
 
 PARAM_TEST_CASE(HaarTestBase, int, int)
 {
@@ -68,8 +74,8 @@ PARAM_TEST_CASE(HaarTestBase, int, int)
     virtual void SetUp()
     {
         scale = 1.0;
-		index=0;
-		string cascadeName="../../../data/haarcascades/haarcascade_frontalface_alt.xml";
+        index = 0;
+        string cascadeName = "../../../data/haarcascades/haarcascade_frontalface_alt.xml";
 
         if( (!cascade.load( cascadeName )) || (!cpucascade.load(cascadeName)))
         {
@@ -98,7 +104,7 @@ TEST_F(Haar, FaceDetect)
 
     if(img.empty())
     {
-		std::cout << "Couldn't read test" << index <<".jpg" << std::endl;
+        std::cout << "Couldn't read test" << index << ".jpg" << std::endl;
         return ;
     }
 
@@ -106,45 +112,46 @@ TEST_F(Haar, FaceDetect)
     double t = 0;
     vector<Rect> faces, oclfaces;
 
-	const static Scalar colors[] =  { CV_RGB(0,0,255),
-		CV_RGB(0,128,255),
-		CV_RGB(0,255,255),
-		CV_RGB(0,255,0),
-		CV_RGB(255,128,0),
-		CV_RGB(255,255,0),
-		CV_RGB(255,0,0),
-		CV_RGB(255,0,255)} ;
-
-	Mat gray, smallImg(cvRound (img.rows/scale), cvRound(img.cols/scale), CV_8UC1 );
+    const static Scalar colors[] =  { CV_RGB(0, 0, 255),
+                                      CV_RGB(0, 128, 255),
+                                      CV_RGB(0, 255, 255),
+                                      CV_RGB(0, 255, 0),
+                                      CV_RGB(255, 128, 0),
+                                      CV_RGB(255, 255, 0),
+                                      CV_RGB(255, 0, 0),
+                                      CV_RGB(255, 0, 255)
+                                    } ;
+
+    Mat gray, smallImg(cvRound (img.rows / scale), cvRound(img.cols / scale), CV_8UC1 );
     MemStorage storage(cvCreateMemStorage(0));
     cvtColor( img, gray, CV_BGR2GRAY );
     resize( gray, smallImg, smallImg.size(), 0, 0, INTER_LINEAR );
     equalizeHist( smallImg, smallImg );
 
     t = (double)cvGetTickCount();
-	for(int k= 0; k<LOOP_TIMES; k++)
+    for(int k = 0; k < LOOP_TIMES; k++)
     {
         cpucascade.detectMultiScale( smallImg, faces,  1.1,
                                      3, 0
-			|CV_HAAR_SCALE_IMAGE
-			, Size(30,30), Size(0, 0) );
+                                     | CV_HAAR_SCALE_IMAGE
+                                     , Size(30, 30), Size(0, 0) );
     }
     t = (double)cvGetTickCount() - t ;
-	printf( "cpudetection time = %g ms\n", t/(LOOP_TIMES*(double)cvGetTickFrequency()*1000.) );
+    printf( "cpudetection time = %g ms\n", t / (LOOP_TIMES * (double)cvGetTickFrequency() * 1000.) );
 
     cv::ocl::oclMat image;
-	CvSeq* _objects;
+    CvSeq *_objects;
     t = (double)cvGetTickCount();
-	for(int k= 0; k<LOOP_TIMES; k++)
+    for(int k = 0; k < LOOP_TIMES; k++)
     {
         image.upload(smallImg);
         _objects = cascade.oclHaarDetectObjects( image, storage, 1.1,
                    3, 0
-			|CV_HAAR_SCALE_IMAGE
-			, Size(30,30), Size(0, 0) );
+                   | CV_HAAR_SCALE_IMAGE
+                   , Size(30, 30), Size(0, 0) );
     }
     t = (double)cvGetTickCount() - t ;
-	printf( "ocldetection time = %g ms\n", t/(LOOP_TIMES*(double)cvGetTickFrequency()*1000.) );
+    printf( "ocldetection time = %g ms\n", t / (LOOP_TIMES * (double)cvGetTickFrequency() * 1000.) );
     vector<CvAvgComp> vecAvgComp;
     Seq<CvAvgComp>(_objects).copyTo(vecAvgComp);
     oclfaces.resize(vecAvgComp.size());

modules/ocl/perf/perf_hog.cpp

@@ -100,7 +100,7 @@ PARAM_TEST_CASE(HOG, WinSizw48, bool)
 
 TEST_P(HOG, Performance)
 {
-    cv::Mat img = readImage(FILTER_IMAGE,cv::IMREAD_GRAYSCALE);
+    cv::Mat img = readImage(FILTER_IMAGE, cv::IMREAD_GRAYSCALE);
     ASSERT_FALSE(img.empty());
 
     // define HOG related arguments
@@ -110,7 +110,7 @@ TEST_P(HOG, Performance)
     float hit_threshold = 1.4;
     bool hit_threshold_auto = true;
 
-    int win_width = is48? 48 : 64;
+    int win_width = is48 ? 48 : 64;
     int win_stride_width = 8;
     int win_stride_height = 8;
 
@@ -125,18 +125,18 @@ TEST_P(HOG, Performance)
 
     gpu_hog.setSVMDetector(detector);
 
-    double totalgputick=0;
-    double totalgputick_kernel=0;
+    double totalgputick = 0;
+    double totalgputick_kernel = 0;
 
-    double t1=0;
-    double t2=0;
-    for(int j = 0; j < LOOP_TIMES+1; j ++)
+    double t1 = 0;
+    double t2 = 0;
+    for(int j = 0; j < LOOP_TIMES + 1; j ++)
     {
         t1 = (double)cvGetTickCount();//gpu start1
 
         ocl::oclMat d_src(img);//upload
 
-        t2=(double)cvGetTickCount();//kernel
+        t2 = (double)cvGetTickCount(); //kernel
 
         vector<Rect> found;
         gpu_hog.detectMultiScale(d_src, found, hit_threshold, win_stride,
@@ -151,14 +151,14 @@ TEST_P(HOG, Performance)
         if(j == 0)
             continue;
 
-        totalgputick=t1+totalgputick;
+        totalgputick = t1 + totalgputick;
 
-        totalgputick_kernel=t2+totalgputick_kernel;	
+        totalgputick_kernel = t2 + totalgputick_kernel;
 
     }
 
-    cout << "average gpu runtime is  " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
-    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
+    cout << "average gpu runtime is  " << totalgputick / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
+    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
 }
 
 

modules/ocl/perf/perf_match_template.cpp

@@ -87,7 +87,7 @@ IMPLEMENT_PARAM_CLASS(Channels, int)
 
 IMPLEMENT_PARAM_CLASS(TemplateSize, cv::Size);
 
-const char* TEMPLATE_METHOD_NAMES[6] = {"TM_SQDIFF", "TM_SQDIFF_NORMED", "TM_CCORR", "TM_CCORR_NORMED", "TM_CCOEFF", "TM_CCOEFF_NORMED"};
+const char *TEMPLATE_METHOD_NAMES[6] = {"TM_SQDIFF", "TM_SQDIFF_NORMED", "TM_CCORR", "TM_CCORR_NORMED", "TM_CCOEFF", "TM_CCOEFF_NORMED"};
 
 PARAM_TEST_CASE(MatchTemplate, cv::Size, TemplateSize, Channels, TemplateMethod)
 {
@@ -112,8 +112,8 @@ struct MatchTemplate8U : MatchTemplate {};
 TEST_P(MatchTemplate8U, Performance)
 {
     std::cout << "Method: " << TEMPLATE_METHOD_NAMES[method] << std::endl;
-	std::cout << "Image Size: (" << size.width << ", " << size.height << ")"<< std::endl;
-	std::cout << "Template Size: (" << templ_size.width << ", " << templ_size.height << ")"<< std::endl;
+    std::cout << "Image Size: (" << size.width << ", " << size.height << ")" << std::endl;
+    std::cout << "Template Size: (" << templ_size.width << ", " << templ_size.height << ")" << std::endl;
     std::cout << "Channels: " << cn << std::endl;
 
     cv::Mat image = randomMat(size, CV_MAKETYPE(CV_8U, cn));
@@ -125,12 +125,12 @@ TEST_P(MatchTemplate8U, Performance)
 
 
 
-	double totalgputick=0;
-	double totalgputick_kernel=0;
+    double totalgputick = 0;
+    double totalgputick_kernel = 0;
 
-	double t1=0;
-	double t2=0;
-	for(int j = 0; j < LOOP_TIMES+1; j ++)
+    double t1 = 0;
+    double t2 = 0;
+    for(int j = 0; j < LOOP_TIMES + 1; j ++)
     {
 
         t1 = (double)cvGetTickCount();//gpu start1
@@ -138,7 +138,7 @@ TEST_P(MatchTemplate8U, Performance)
         cv::ocl::oclMat ocl_image = cv::ocl::oclMat(image);//upload
         cv::ocl::oclMat ocl_templ = cv::ocl::oclMat(templ);//upload
 
-		t2=(double)cvGetTickCount();//kernel
+        t2 = (double)cvGetTickCount(); //kernel
         cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);
         t2 = (double)cvGetTickCount() - t2;//kernel
 
@@ -150,13 +150,13 @@ TEST_P(MatchTemplate8U, Performance)
         if(j == 0)
             continue;
 
-		totalgputick=t1+totalgputick;	
-		totalgputick_kernel=t2+totalgputick_kernel;	
+        totalgputick = t1 + totalgputick;
+        totalgputick_kernel = t2 + totalgputick_kernel;
 
     }
 
-	cout << "average gpu runtime is  " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
-	cout << "average gpu runtime without data transfer is  " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
+    cout << "average gpu runtime is  " << totalgputick / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
+    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
 
 
 }
@@ -166,8 +166,8 @@ struct MatchTemplate32F : MatchTemplate {};
 TEST_P(MatchTemplate32F, Performance)
 {
     std::cout << "Method: " << TEMPLATE_METHOD_NAMES[method] << std::endl;
-	std::cout << "Image Size: (" << size.width << ", " << size.height << ")"<< std::endl;
-	std::cout << "Template Size: (" << templ_size.width << ", " << templ_size.height << ")"<< std::endl;
+    std::cout << "Image Size: (" << size.width << ", " << size.height << ")" << std::endl;
+    std::cout << "Template Size: (" << templ_size.width << ", " << templ_size.height << ")" << std::endl;
     std::cout << "Channels: " << cn << std::endl;
     cv::Mat image = randomMat(size, CV_MAKETYPE(CV_32F, cn));
     cv::Mat templ = randomMat(templ_size, CV_MAKETYPE(CV_32F, cn));
@@ -178,11 +178,11 @@ TEST_P(MatchTemplate32F, Performance)
 
 
 
-	double totalgputick=0;
-	double totalgputick_kernel=0;
+    double totalgputick = 0;
+    double totalgputick_kernel = 0;
 
-	double t1=0;
-	double t2=0;
+    double t1 = 0;
+    double t2 = 0;
     for(int j = 0; j < LOOP_TIMES; j ++)
     {
 
@@ -191,7 +191,7 @@ TEST_P(MatchTemplate32F, Performance)
         cv::ocl::oclMat ocl_image = cv::ocl::oclMat(image);//upload
         cv::ocl::oclMat ocl_templ = cv::ocl::oclMat(templ);//upload
 
-		t2=(double)cvGetTickCount();//kernel
+        t2 = (double)cvGetTickCount(); //kernel
         cv::ocl::matchTemplate(ocl_image, ocl_templ, dst, method);
         t2 = (double)cvGetTickCount() - t2;//kernel
 
@@ -200,14 +200,14 @@ TEST_P(MatchTemplate32F, Performance)
 
         t1 = (double)cvGetTickCount() - t1;//gpu end1
 
-		totalgputick=t1+totalgputick;
+        totalgputick = t1 + totalgputick;
 
-		totalgputick_kernel=t2+totalgputick_kernel;	
+        totalgputick_kernel = t2 + totalgputick_kernel;
 
     }
 
-   cout << "average gpu runtime is  " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
-   cout << "average gpu runtime without data transfer is  " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
+    cout << "average gpu runtime is  " << totalgputick / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
+    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
 
 
 
@@ -216,15 +216,15 @@ TEST_P(MatchTemplate32F, Performance)
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate8U,
                         testing::Combine(
-    testing::Values(cv::Size(1280, 1024), cv::Size(MWIDTH, MHEIGHT),cv::Size(1800, 1500)),
+                            testing::Values(cv::Size(1280, 1024), cv::Size(MWIDTH, MHEIGHT), cv::Size(1800, 1500)),
                             testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/),
                             testing::Values(Channels(1), Channels(4)/*, Channels(3)*/),
                             ALL_TEMPLATE_METHODS
                         )
-);
+                       );
 
 INSTANTIATE_TEST_CASE_P(GPU_ImgProc, MatchTemplate32F, testing::Combine(
-    testing::Values(cv::Size(1280, 1024), cv::Size(MWIDTH, MHEIGHT),cv::Size(1800, 1500)),
+                            testing::Values(cv::Size(1280, 1024), cv::Size(MWIDTH, MHEIGHT), cv::Size(1800, 1500)),
                             testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16))/*, TemplateSize(cv::Size(30, 30))*/),
                             testing::Values(Channels(1), Channels(4) /*, Channels(3)*/),
                             testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR))));

modules/ocl/perf/perf_surf.cpp

@@ -58,25 +58,25 @@ using namespace std;
 
 TEST(SURF, Performance)
 {
-    cv::Mat img = readImage(FILTER_IMAGE,cv::IMREAD_GRAYSCALE);
+    cv::Mat img = readImage(FILTER_IMAGE, cv::IMREAD_GRAYSCALE);
     ASSERT_FALSE(img.empty());
 
     ocl::SURF_OCL d_surf;
     ocl::oclMat d_keypoints;
     ocl::oclMat d_descriptors;
 
-    double totalgputick=0;
-    double totalgputick_kernel=0;
+    double totalgputick = 0;
+    double totalgputick_kernel = 0;
 
-    double t1=0;
-    double t2=0;
-    for(int j = 0; j < LOOP_TIMES+1; j ++)
+    double t1 = 0;
+    double t2 = 0;
+    for(int j = 0; j < LOOP_TIMES + 1; j ++)
     {
         t1 = (double)cvGetTickCount();//gpu start1
 
         ocl::oclMat d_src(img);//upload
 
-        t2=(double)cvGetTickCount();//kernel
+        t2 = (double)cvGetTickCount(); //kernel
         d_surf(d_src, ocl::oclMat(), d_keypoints, d_descriptors);
         t2 = (double)cvGetTickCount() - t2;//kernel
 
@@ -89,14 +89,14 @@ TEST(SURF, Performance)
         if(j == 0)
             continue;
 
-        totalgputick=t1+totalgputick;
+        totalgputick = t1 + totalgputick;
 
-        totalgputick_kernel=t2+totalgputick_kernel;	
+        totalgputick_kernel = t2 + totalgputick_kernel;
 
     }
 
-    cout << "average gpu runtime is  " << totalgputick/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
-    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel/((double)cvGetTickFrequency()* LOOP_TIMES *1000.) << "ms" << endl;
+    cout << "average gpu runtime is  " << totalgputick / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
+    cout << "average gpu runtime without data transfer is  " << totalgputick_kernel / ((double)cvGetTickFrequency()* LOOP_TIMES * 1000.) << "ms" << endl;
 
 
 }

modules/ocl/perf/precomp.cpp

@@ -42,4 +42,3 @@
 #include "precomp.hpp"
 
 
-	
\ No newline at end of file

modules/ocl/perf/utility.cpp

@@ -75,13 +75,13 @@ using namespace cvtest;
 
 int randomInt(int minVal, int maxVal)
 {
-    RNG& rng = TS::ptr()->get_rng();
+    RNG &rng = TS::ptr()->get_rng();
     return rng.uniform(minVal, maxVal);
 }
 
 double randomDouble(double minVal, double maxVal)
 {
-    RNG& rng = TS::ptr()->get_rng();
+    RNG &rng = TS::ptr()->get_rng();
     return rng.uniform(minVal, maxVal);
 }
 
@@ -207,19 +207,19 @@ vector<MatType> types(int depth_start, int depth_end, int cn_start, int cn_end)
     return v;
 }
 
-const vector<MatType>& all_types()
+const vector<MatType> &all_types()
 {
     static vector<MatType> v = types(CV_8U, CV_64F, 1, 4);
 
     return v;
 }
 
-Mat readImage(const string& fileName, int flags)
+Mat readImage(const string &fileName, int flags)
 {
     return imread(string(cvtest::TS::ptr()->get_data_path()) + fileName, flags);
 }
 
-Mat readImageType(const string& fname, int type)
+Mat readImageType(const string &fname, int type)
 {
     Mat src = readImage(fname, CV_MAT_CN(type) == 1 ? IMREAD_GRAYSCALE : IMREAD_COLOR);
     if (CV_MAT_CN(type) == 4)
@@ -232,17 +232,17 @@ Mat readImageType(const string& fname, int type)
     return src;
 }
 
-double checkNorm(const Mat& m)
+double checkNorm(const Mat &m)
 {
     return norm(m, NORM_INF);
 }
 
-double checkNorm(const Mat& m1, const Mat& m2)
+double checkNorm(const Mat &m1, const Mat &m2)
 {
     return norm(m1, m2, NORM_INF);
 }
 
-double checkSimilarity(const Mat& m1, const Mat& m2)
+double checkSimilarity(const Mat &m1, const Mat &m2)
 {
     Mat diff;
     matchTemplate(m1, m2, diff, CV_TM_CCORR_NORMED);
@@ -256,7 +256,7 @@ void cv::ocl::PrintTo(const DeviceInfo& info, ostream* os)
 }
 */
 
-void PrintTo(const Inverse& inverse, std::ostream* os)
+void PrintTo(const Inverse &inverse, std::ostream *os)
 {
     if (inverse)
         (*os) << "inverse";

modules/ocl/perf/utility.hpp

@@ -56,7 +56,7 @@ int randomInt(int minVal, int maxVal);
 double randomDouble(double minVal, double maxVal);
 
 //std::string generateVarList(int first,...);
-std::string generateVarList(int& p1,int& p2);
+std::string generateVarList(int &p1, int &p2);
 cv::Size randomSize(int minVal, int maxVal);
 cv::Scalar randomScalar(double minVal, double maxVal);
 cv::Mat randomMat(cv::Size size, int type, double minVal = 0.0, double maxVal = 255.0);
@@ -72,12 +72,12 @@ void showDiff(cv::InputArray gold, cv::InputArray actual, double eps);
 //std::vector<cv::ocl::DeviceInfo> devices(cv::gpu::FeatureSet feature);
 
 //! read image from testdata folder.
-cv::Mat readImage(const std::string& fileName, int flags = cv::IMREAD_COLOR);
-cv::Mat readImageType(const std::string& fname, int type);
+cv::Mat readImage(const std::string &fileName, int flags = cv::IMREAD_COLOR);
+cv::Mat readImageType(const std::string &fname, int type);
 
-double checkNorm(const cv::Mat& m);
-double checkNorm(const cv::Mat& m1, const cv::Mat& m2);
-double checkSimilarity(const cv::Mat& m1, const cv::Mat& m2);
+double checkNorm(const cv::Mat &m);
+double checkNorm(const cv::Mat &m1, const cv::Mat &m2);
+double checkSimilarity(const cv::Mat &m1, const cv::Mat &m2);
 
 #define EXPECT_MAT_NORM(mat, eps) \
 { \
@@ -120,31 +120,34 @@ using perf::MatType;
 std::vector<MatType> types(int depth_start, int depth_end, int cn_start, int cn_end);
 
 //! return vector with all types (depth: CV_8U-CV_64F, channels: 1-4).
-const std::vector<MatType>& all_types();
+const std::vector<MatType> &all_types();
 
 class Inverse
 {
-    public:
+public:
     inline Inverse(bool val = false) : val_(val) {}
 
-        inline operator bool() const { return val_; }
+    inline operator bool() const
+    {
+        return val_;
+    }
 
-    private:
+private:
     bool val_;
 };
 
-void PrintTo(const Inverse& useRoi, std::ostream* os);
+void PrintTo(const Inverse &useRoi, std::ostream *os);
 
 CV_ENUM(CmpCode, cv::CMP_EQ, cv::CMP_GT, cv::CMP_GE, cv::CMP_LT, cv::CMP_LE, cv::CMP_NE)
 
 CV_ENUM(NormCode, cv::NORM_INF, cv::NORM_L1, cv::NORM_L2, cv::NORM_TYPE_MASK, cv::NORM_RELATIVE, cv::NORM_MINMAX)
 
-    enum {FLIP_BOTH = 0, FLIP_X = 1, FLIP_Y = -1};
+enum {FLIP_BOTH = 0, FLIP_X = 1, FLIP_Y = -1};
 CV_ENUM(FlipCode, FLIP_BOTH, FLIP_X, FLIP_Y)
 
 CV_ENUM(ReduceOp, CV_REDUCE_SUM, CV_REDUCE_AVG, CV_REDUCE_MAX, CV_REDUCE_MIN)
 
-    CV_FLAGS(GemmFlags, cv::GEMM_1_T, cv::GEMM_2_T, cv::GEMM_3_T);
+CV_FLAGS(GemmFlags, cv::GEMM_1_T, cv::GEMM_2_T, cv::GEMM_3_T);
 
 CV_ENUM(MorphOp, cv::MORPH_OPEN, cv::MORPH_CLOSE, cv::MORPH_GRADIENT, cv::MORPH_TOPHAT, cv::MORPH_BLACKHAT)
 

modules/ocl/src/blend.cpp

@@ -51,8 +51,11 @@ using namespace cv::ocl;
 using namespace std;
 
 #if !defined (HAVE_OPENCL)
-void cv::ocl::blendLinear(const oclMat& img1, const oclMat& img2, const oclMat& weights1, const oclMat& weights2,
-                            oclMat& result){throw_nogpu();}
+void cv::ocl::blendLinear(const oclMat &img1, const oclMat &img2, const oclMat &weights1, const oclMat &weights2,
+                          oclMat &result)
+{
+    throw_nogpu();
+}
 #else
 namespace cv
 {
@@ -63,12 +66,12 @@ namespace cv
     }
 }
 
-void cv::ocl::blendLinear(const oclMat& img1, const oclMat& img2, const oclMat& weights1, const oclMat& weights2,
-                            oclMat& result)
+void cv::ocl::blendLinear(const oclMat &img1, const oclMat &img2, const oclMat &weights1, const oclMat &weights2,
+                          oclMat &result)
 {
     cv::ocl::Context *ctx = img1.clCxt;
     assert(ctx == img2.clCxt && ctx == weights1.clCxt && ctx == weights2.clCxt);
-	int channels = img1.channels();
+    int channels = img1.oclchannels();
     int depth = img1.depth();
     int rows = img1.rows;
     int cols = img1.cols;
@@ -79,7 +82,7 @@ void cv::ocl::blendLinear(const oclMat& img1, const oclMat& img2, const oclMat&
 
     vector< pair<size_t, const void *> > args;
 
-	if(globalSize[0]!=0)
+    if(globalSize[0] != 0)
     {
         args.push_back( make_pair( sizeof(cl_mem), (void *)&result.data ));
         args.push_back( make_pair( sizeof(cl_mem), (void *)&img1.data ));

modules/ocl/src/color.cpp

@@ -81,9 +81,9 @@ namespace
     void RGB2Gray_caller(const oclMat &src, oclMat &dst, int bidx)
     {
         vector<pair<size_t , const void *> > args;
-        int channels = src.channels();
+        int channels = src.oclchannels();
         char build_options[50];
-        //printf("depth:%d,channels:%d,bidx:%d\n",src.depth(),src.channels(),bidx);
+        //printf("depth:%d,channels:%d,bidx:%d\n",src.depth(),src.oclchannels(),bidx);
         sprintf(build_options, "-D DEPTH_%d", src.depth());
         args.push_back( make_pair( sizeof(cl_int) , (void *)&src.cols));
         args.push_back( make_pair( sizeof(cl_int) , (void *)&src.rows));
@@ -99,7 +99,7 @@ namespace
     void cvtColor_caller(const oclMat &src, oclMat &dst, int code, int dcn)
     {
         Size sz = src.size();
-        int scn = src.channels(), depth = src.depth(), bidx;
+        int scn = src.oclchannels(), depth = src.depth(), bidx;
 
         CV_Assert(depth == CV_8U || depth == CV_16U);
 

modules/ocl/src/columnsum.cpp

@@ -53,7 +53,10 @@ using namespace std;
 
 #if !defined(HAVE_OPENCL)
 
-void cv::ocl::columnSum(const oclMat& src,oclMat& dst){ throw_nogpu(); }
+void cv::ocl::columnSum(const oclMat &src, oclMat &dst)
+{
+    throw_nogpu();
+}
 
 #else /*!HAVE_OPENCL */
 
@@ -61,11 +64,11 @@ namespace cv
 {
     namespace ocl
     {
-		extern const char* imgproc_columnsum;
+        extern const char *imgproc_columnsum;
     }
 }
 
-void cv::ocl::columnSum(const oclMat& src,oclMat& dst)
+void cv::ocl::columnSum(const oclMat &src, oclMat &dst)
 {
     CV_Assert(src.type() == CV_32FC1);
 

modules/ocl/src/gemm.cpp

@@ -51,14 +51,17 @@
 #include "clAmdBlas.h"
 
 #if !defined (HAVE_OPENCL)
-void cv::ocl::dft(const oclMat& src, oclMat& dst, int flags) { throw_nogpu(); }
+void cv::ocl::dft(const oclMat &src, oclMat &dst, int flags)
+{
+    throw_nogpu();
+}
 #else
 
 using namespace cv;
 
-	void cv::ocl::gemm(const oclMat& src1, const oclMat& src2, double alpha,
-		const oclMat& src3, double beta, oclMat& dst, int flags)
-	{
+void cv::ocl::gemm(const oclMat &src1, const oclMat &src2, double alpha,
+                   const oclMat &src3, double beta, oclMat &dst, int flags)
+{
     CV_Assert(src1.cols == src2.rows &&
               (src3.empty() || src1.rows == src3.rows && src2.cols == src3.cols));
     CV_Assert(!(cv::GEMM_3_T & flags)); // cv::GEMM_3_T is not supported
@@ -73,8 +76,8 @@ using namespace cv;
     }
     openCLSafeCall( clAmdBlasSetup() );
 
-		const clAmdBlasTranspose transA = (cv::GEMM_1_T & flags)?clAmdBlasTrans:clAmdBlasNoTrans;
-		const clAmdBlasTranspose transB = (cv::GEMM_2_T & flags)?clAmdBlasTrans:clAmdBlasNoTrans;
+    const clAmdBlasTranspose transA = (cv::GEMM_1_T & flags) ? clAmdBlasTrans : clAmdBlasNoTrans;
+    const clAmdBlasTranspose transB = (cv::GEMM_2_T & flags) ? clAmdBlasTrans : clAmdBlasNoTrans;
     const clAmdBlasOrder     order  = clAmdBlasRowMajor;
 
     const int M = src1.rows;
@@ -156,6 +159,6 @@ using namespace cv;
     break;
     }
     clAmdBlasTeardown();
-	}
+}
 #endif
 #endif

modules/ocl/test/utility.cpp

@@ -207,7 +207,7 @@ vector<MatType> types(int depth_start, int depth_end, int cn_start, int cn_end)
     return v;
 }
 
-const vector<MatType>& all_types()
+const vector<MatType> &all_types()
 {
     static vector<MatType> v = types(CV_8U, CV_64F, 1, 4);