Merge pull request #21378 from sturkmen72:fix_legacy_constants

modules/core/perf/perf_reduce.cpp

@@ -23,7 +23,7 @@ PERF_TEST_P(Size_MatType_ROp, reduceR,
     int reduceOp = get<2>(GetParam());
 
     int ddepth = -1;
-    if( CV_MAT_DEPTH(matType) < CV_32S && (reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG) )
+    if( CV_MAT_DEPTH(matType) < CV_32S && (reduceOp == REDUCE_SUM || reduceOp == REDUCE_AVG) )
         ddepth = CV_32S;
 
     Mat src(sz, matType);
@@ -51,7 +51,7 @@ PERF_TEST_P(Size_MatType_ROp, reduceC,
     int reduceOp = get<2>(GetParam());
 
     int ddepth = -1;
-    if( CV_MAT_DEPTH(matType)< CV_32S && (reduceOp == CV_REDUCE_SUM || reduceOp == CV_REDUCE_AVG) )
+    if( CV_MAT_DEPTH(matType)< CV_32S && (reduceOp == REDUCE_SUM || reduceOp == REDUCE_AVG) )
         ddepth = CV_32S;
 
     Mat src(sz, matType);

modules/core/src/matmul.dispatch.cpp

@@ -804,7 +804,7 @@ void calcCovarMatrix( InputArray _src, OutputArray _covar, InputOutputArray _mea
     else
     {
         ctype = std::max(CV_MAT_DEPTH(ctype >= 0 ? ctype : type), CV_32F);
-        reduce( _src, _mean, takeRows ? 0 : 1, CV_REDUCE_AVG, ctype );
+        reduce( _src, _mean, takeRows ? 0 : 1, REDUCE_AVG, ctype );
         mean = _mean.getMat();
     }
 

modules/core/src/matrix_operations.cpp

@@ -616,7 +616,7 @@ static bool ocl_reduce(InputArray _src, OutputArray _dst,
     if (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F))
         return false;
 
-    if (op == CV_REDUCE_AVG)
+    if (op == REDUCE_AVG)
     {
         if (sdepth < CV_32S && ddepth < CV_32S)
             ddepth = CV_32S;
@@ -654,7 +654,7 @@ static bool ocl_reduce(InputArray _src, OutputArray _dst,
         _dst.create(dsize, dtype);
         UMat dst = _dst.getUMat();
 
-        if (op0 == CV_REDUCE_AVG)
+        if (op0 == REDUCE_AVG)
             k.args(ocl::KernelArg::ReadOnly(src),
                       ocl::KernelArg::WriteOnlyNoSize(dst), 1.0f / src.cols);
         else
@@ -690,7 +690,7 @@ static bool ocl_reduce(InputArray _src, OutputArray _dst,
         ocl::KernelArg srcarg = ocl::KernelArg::ReadOnly(src),
                 temparg = ocl::KernelArg::WriteOnlyNoSize(dst);
 
-        if (op0 == CV_REDUCE_AVG)
+        if (op0 == REDUCE_AVG)
             k.args(srcarg, temparg, 1.0f / (dim == 0 ? src.rows : src.cols));
         else
             k.args(srcarg, temparg);
@@ -717,8 +717,8 @@ void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype)
     int ddepth = CV_MAT_DEPTH(dtype);
 
     CV_Assert( cn == CV_MAT_CN(dtype) );
-    CV_Assert( op == CV_REDUCE_SUM || op == CV_REDUCE_MAX ||
-               op == CV_REDUCE_MIN || op == CV_REDUCE_AVG );
+    CV_Assert( op == REDUCE_SUM || op == REDUCE_MAX ||
+               op == REDUCE_MIN || op == REDUCE_AVG );
 
     CV_OCL_RUN(_dst.isUMat(),
                ocl_reduce(_src, _dst, dim, op, op0, stype, dtype))
@@ -732,9 +732,9 @@ void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype)
     _dst.create(dim == 0 ? 1 : src.rows, dim == 0 ? src.cols : 1, dtype);
     Mat dst = _dst.getMat(), temp = dst;
 
-    if( op == CV_REDUCE_AVG )
+    if( op == REDUCE_AVG )
     {
-        op = CV_REDUCE_SUM;
+        op = REDUCE_SUM;
         if( sdepth < CV_32S && ddepth < CV_32S )
         {
             temp.create(dst.rows, dst.cols, CV_32SC(cn));
@@ -745,7 +745,7 @@ void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype)
     ReduceFunc func = 0;
     if( dim == 0 )
     {
-        if( op == CV_REDUCE_SUM )
+        if( op == REDUCE_SUM )
         {
             if(sdepth == CV_8U && ddepth == CV_32S)
                 func = GET_OPTIMIZED(reduceSumR8u32s);
@@ -768,7 +768,7 @@ void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype)
             else if(sdepth == CV_64F && ddepth == CV_64F)
                 func = reduceSumR64f64f;
         }
-        else if(op == CV_REDUCE_MAX)
+        else if(op == REDUCE_MAX)
         {
             if(sdepth == CV_8U && ddepth == CV_8U)
                 func = GET_OPTIMIZED(reduceMaxR8u);
@@ -781,7 +781,7 @@ void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype)
             else if(sdepth == CV_64F && ddepth == CV_64F)
                 func = reduceMaxR64f;
         }
-        else if(op == CV_REDUCE_MIN)
+        else if(op == REDUCE_MIN)
         {
             if(sdepth == CV_8U && ddepth == CV_8U)
                 func = GET_OPTIMIZED(reduceMinR8u);
@@ -797,7 +797,7 @@ void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype)
     }
     else
     {
-        if(op == CV_REDUCE_SUM)
+        if(op == REDUCE_SUM)
         {
             if(sdepth == CV_8U && ddepth == CV_32S)
                 func = GET_OPTIMIZED(reduceSumC8u32s);
@@ -820,7 +820,7 @@ void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype)
             else if(sdepth == CV_64F && ddepth == CV_64F)
                 func = reduceSumC64f64f;
         }
-        else if(op == CV_REDUCE_MAX)
+        else if(op == REDUCE_MAX)
         {
             if(sdepth == CV_8U && ddepth == CV_8U)
                 func = GET_OPTIMIZED(reduceMaxC8u);
@@ -833,7 +833,7 @@ void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype)
             else if(sdepth == CV_64F && ddepth == CV_64F)
                 func = reduceMaxC64f;
         }
-        else if(op == CV_REDUCE_MIN)
+        else if(op == REDUCE_MIN)
         {
             if(sdepth == CV_8U && ddepth == CV_8U)
                 func = GET_OPTIMIZED(reduceMinC8u);
@@ -854,7 +854,7 @@ void cv::reduce(InputArray _src, OutputArray _dst, int dim, int op, int dtype)
 
     func( src, temp );
 
-    if( op0 == CV_REDUCE_AVG )
+    if( op0 == REDUCE_AVG )
         temp.convertTo(dst, dst.type(), 1./(dim == 0 ? src.rows : src.cols));
 }
 
@@ -868,9 +868,9 @@ template<typename T> static void sort_( const Mat& src, Mat& dst, int flags )
 {
     AutoBuffer<T> buf;
     int n, len;
-    bool sortRows = (flags & 1) == CV_SORT_EVERY_ROW;
+    bool sortRows = (flags & 1) == SORT_EVERY_ROW;
     bool inplace = src.data == dst.data;
-    bool sortDescending = (flags & CV_SORT_DESCENDING) != 0;
+    bool sortDescending = (flags & SORT_DESCENDING) != 0;
 
     if( sortRows )
         n = src.rows, len = src.cols;
@@ -940,8 +940,8 @@ static bool ipp_sort(const Mat& src, Mat& dst, int flags)
 {
     CV_INSTRUMENT_REGION_IPP();
 
-    bool        sortRows        = (flags & 1) == CV_SORT_EVERY_ROW;
-    bool        sortDescending  = (flags & CV_SORT_DESCENDING) != 0;
+    bool        sortRows        = (flags & 1) == SORT_EVERY_ROW;
+    bool        sortDescending  = (flags & SORT_DESCENDING) != 0;
     bool        inplace         = (src.data == dst.data);
     int         depth           = src.depth();
     IppDataType type            = ippiGetDataType(depth);
@@ -1013,8 +1013,8 @@ template<typename T> static void sortIdx_( const Mat& src, Mat& dst, int flags )
 {
     AutoBuffer<T> buf;
     AutoBuffer<int> ibuf;
-    bool sortRows = (flags & 1) == CV_SORT_EVERY_ROW;
-    bool sortDescending = (flags & CV_SORT_DESCENDING) != 0;
+    bool sortRows = (flags & 1) == SORT_EVERY_ROW;
+    bool sortDescending = (flags & SORT_DESCENDING) != 0;
 
     CV_Assert( src.data != dst.data );
 

modules/core/test/ocl/test_arithm.cpp

@@ -1819,8 +1819,8 @@ OCL_TEST_P(ReduceSum, Mat)
     {
         generateTestData();
 
-        OCL_OFF(cv::reduce(src_roi, dst_roi, dim, CV_REDUCE_SUM, dtype));
-        OCL_ON(cv::reduce(usrc_roi, udst_roi, dim, CV_REDUCE_SUM, dtype));
+        OCL_OFF(cv::reduce(src_roi, dst_roi, dim, REDUCE_SUM, dtype));
+        OCL_ON(cv::reduce(usrc_roi, udst_roi, dim, REDUCE_SUM, dtype));
 
         double eps = ddepth <= CV_32S ? 1 : 7e-4;
         OCL_EXPECT_MATS_NEAR(dst, eps);
@@ -1835,8 +1835,8 @@ OCL_TEST_P(ReduceMax, Mat)
     {
         generateTestData();
 
-        OCL_OFF(cv::reduce(src_roi, dst_roi, dim, CV_REDUCE_MAX, dtype));
-        OCL_ON(cv::reduce(usrc_roi, udst_roi, dim, CV_REDUCE_MAX, dtype));
+        OCL_OFF(cv::reduce(src_roi, dst_roi, dim, REDUCE_MAX, dtype));
+        OCL_ON(cv::reduce(usrc_roi, udst_roi, dim, REDUCE_MAX, dtype));
 
         OCL_EXPECT_MATS_NEAR(dst, 0);
     }
@@ -1850,8 +1850,8 @@ OCL_TEST_P(ReduceMin, Mat)
     {
         generateTestData();
 
-        OCL_OFF(cv::reduce(src_roi, dst_roi, dim, CV_REDUCE_MIN, dtype));
-        OCL_ON(cv::reduce(usrc_roi, udst_roi, dim, CV_REDUCE_MIN, dtype));
+        OCL_OFF(cv::reduce(src_roi, dst_roi, dim, REDUCE_MIN, dtype));
+        OCL_ON(cv::reduce(usrc_roi, udst_roi, dim, REDUCE_MIN, dtype));
 
         OCL_EXPECT_MATS_NEAR(dst, 0);
     }
@@ -1865,8 +1865,8 @@ OCL_TEST_P(ReduceAvg, Mat)
     {
         generateTestData();
 
-        OCL_OFF(cv::reduce(src_roi, dst_roi, dim, CV_REDUCE_AVG, dtype));
-        OCL_ON(cv::reduce(usrc_roi, udst_roi, dim, CV_REDUCE_AVG, dtype));
+        OCL_OFF(cv::reduce(src_roi, dst_roi, dim, REDUCE_AVG, dtype));
+        OCL_ON(cv::reduce(usrc_roi, udst_roi, dim, REDUCE_AVG, dtype));
 
         double eps = ddepth <= CV_32S ? 1 : 6e-6;
         OCL_EXPECT_MATS_NEAR(dst, eps);

modules/core/test/test_mat.cpp

@@ -93,7 +93,7 @@ int Core_ReduceTest::checkOp( const Mat& src, int dstType, int opType, const Mat
 {
     int srcType = src.type();
     bool support = false;
-    if( opType == CV_REDUCE_SUM || opType == CV_REDUCE_AVG )
+    if( opType == REDUCE_SUM || opType == REDUCE_AVG )
     {
         if( srcType == CV_8U && (dstType == CV_32S || dstType == CV_32F || dstType == CV_64F) )
             support = true;
@@ -106,7 +106,7 @@ int Core_ReduceTest::checkOp( const Mat& src, int dstType, int opType, const Mat
         if( srcType == CV_64F && dstType == CV_64F)
             support = true;
     }
-    else if( opType == CV_REDUCE_MAX )
+    else if( opType == REDUCE_MAX )
     {
         if( srcType == CV_8U && dstType == CV_8U )
             support = true;
@@ -115,7 +115,7 @@ int Core_ReduceTest::checkOp( const Mat& src, int dstType, int opType, const Mat
         if( srcType == CV_64F && dstType == CV_64F )
             support = true;
     }
-    else if( opType == CV_REDUCE_MIN )
+    else if( opType == REDUCE_MIN )
     {
         if( srcType == CV_8U && dstType == CV_8U)
             support = true;
@@ -128,7 +128,7 @@ int Core_ReduceTest::checkOp( const Mat& src, int dstType, int opType, const Mat
         return cvtest::TS::OK;
 
     double eps = 0.0;
-    if ( opType == CV_REDUCE_SUM || opType == CV_REDUCE_AVG )
+    if ( opType == REDUCE_SUM || opType == REDUCE_AVG )
     {
         if ( dstType == CV_32F )
             eps = 1.e-5;
@@ -152,10 +152,10 @@ int Core_ReduceTest::checkOp( const Mat& src, int dstType, int opType, const Mat
     if( check )
     {
         char msg[100];
-        const char* opTypeStr = opType == CV_REDUCE_SUM ? "CV_REDUCE_SUM" :
-        opType == CV_REDUCE_AVG ? "CV_REDUCE_AVG" :
-        opType == CV_REDUCE_MAX ? "CV_REDUCE_MAX" :
-        opType == CV_REDUCE_MIN ? "CV_REDUCE_MIN" : "unknown operation type";
+        const char* opTypeStr = opType == REDUCE_SUM ? "REDUCE_SUM" :
+        opType == REDUCE_AVG ? "REDUCE_AVG" :
+        opType == REDUCE_MAX ? "REDUCE_MAX" :
+        opType == REDUCE_MIN ? "REDUCE_MIN" : "unknown operation type";
         string srcTypeStr, dstTypeStr;
         getMatTypeStr( src.type(), srcTypeStr );
         getMatTypeStr( dstType, dstTypeStr );
@@ -195,19 +195,19 @@ int Core_ReduceTest::checkCase( int srcType, int dstType, int dim, Size sz )
         CV_Assert( 0 );
 
     // 1. sum
-    tempCode = checkOp( src, dstType, CV_REDUCE_SUM, sum, dim );
+    tempCode = checkOp( src, dstType, REDUCE_SUM, sum, dim );
     code = tempCode != cvtest::TS::OK ? tempCode : code;
 
     // 2. avg
-    tempCode = checkOp( src, dstType, CV_REDUCE_AVG, avg, dim );
+    tempCode = checkOp( src, dstType, REDUCE_AVG, avg, dim );
     code = tempCode != cvtest::TS::OK ? tempCode : code;
 
     // 3. max
-    tempCode = checkOp( src, dstType, CV_REDUCE_MAX, max, dim );
+    tempCode = checkOp( src, dstType, REDUCE_MAX, max, dim );
     code = tempCode != cvtest::TS::OK ? tempCode : code;
 
     // 4. min
-    tempCode = checkOp( src, dstType, CV_REDUCE_MIN, min, dim );
+    tempCode = checkOp( src, dstType, REDUCE_MIN, min, dim );
     code = tempCode != cvtest::TS::OK ? tempCode : code;
 
     return code;
@@ -315,7 +315,7 @@ TEST(Core_PCA, accuracy)
     Mat rBackPrjTestPoints = rPCA.backProject( rPrjTestPoints );
 
     Mat avg(1, sz.width, CV_32FC1 );
-    cv::reduce( rPoints, avg, 0, CV_REDUCE_AVG );
+    cv::reduce( rPoints, avg, 0, REDUCE_AVG );
     Mat Q = rPoints - repeat( avg, rPoints.rows, 1 ), Qt = Q.t(), eval, evec;
     Q = Qt * Q;
     Q = Q /(float)rPoints.rows;
@@ -1559,10 +1559,10 @@ TEST(Reduce, regression_should_fail_bug_4594)
     cv::Mat src = cv::Mat::eye(4, 4, CV_8U);
     std::vector<int> dst;
 
-    EXPECT_THROW(cv::reduce(src, dst, 0, CV_REDUCE_MIN, CV_32S), cv::Exception);
-    EXPECT_THROW(cv::reduce(src, dst, 0, CV_REDUCE_MAX, CV_32S), cv::Exception);
-    EXPECT_NO_THROW(cv::reduce(src, dst, 0, CV_REDUCE_SUM, CV_32S));
-    EXPECT_NO_THROW(cv::reduce(src, dst, 0, CV_REDUCE_AVG, CV_32S));
+    EXPECT_THROW(cv::reduce(src, dst, 0, REDUCE_MIN, CV_32S), cv::Exception);
+    EXPECT_THROW(cv::reduce(src, dst, 0, REDUCE_MAX, CV_32S), cv::Exception);
+    EXPECT_NO_THROW(cv::reduce(src, dst, 0, REDUCE_SUM, CV_32S));
+    EXPECT_NO_THROW(cv::reduce(src, dst, 0, REDUCE_AVG, CV_32S));
 }
 
 TEST(Mat, push_back_vector)

modules/core/test/test_math.cpp

@@ -3018,7 +3018,7 @@ TEST(CovariationMatrixVectorOfMatWithMean, accuracy)
     cv::randu(src,cv::Scalar(-128), cv::Scalar(128));
     cv::Mat goldMean;
 
-    cv::reduce(src,goldMean,0 ,CV_REDUCE_AVG, CV_32F);
+    cv::reduce(src,goldMean,0 ,REDUCE_AVG, CV_32F);
 
     cv::calcCovarMatrix(src,gold,goldMean,singleMatFlags,CV_32F);
 

modules/core/test/test_precomp.hpp

@@ -6,9 +6,6 @@
 
 #include "opencv2/ts.hpp"
 #include "opencv2/ts/ocl_test.hpp"
-#include "opencv2/core/core_c.h"
-
-#include "opencv2/core/cvdef.h"
 #include "opencv2/core/private.hpp"
 #include "opencv2/core/hal/hal.hpp"
 

modules/core/test/test_umat.cpp

@@ -1398,8 +1398,8 @@ TEST(UMat, testTempObjects_Mat_issue_8693)
     randu(srcUMat, -1.f, 1.f);
     srcUMat.copyTo(srcMat);
 
-    reduce(srcUMat, srcUMat, 0, CV_REDUCE_SUM);
-    reduce(srcMat, srcMat, 0, CV_REDUCE_SUM);
+    reduce(srcUMat, srcUMat, 0, REDUCE_SUM);
+    reduce(srcMat, srcMat, 0, REDUCE_SUM);
 
     srcUMat.convertTo(srcUMat, CV_64FC1);
     srcMat.convertTo(srcMat, CV_64FC1);

modules/imgcodecs/src/grfmt_exr.cpp

@@ -637,7 +637,7 @@ bool  ExrEncoder::write( const Mat& img, const std::vector<int>& params )
 
     for( size_t i = 0; i < params.size(); i += 2 )
     {
-        if( params[i] == CV_IMWRITE_EXR_TYPE )
+        if( params[i] == IMWRITE_EXR_TYPE )
         {
             switch( params[i+1] )
             {

modules/imgcodecs/src/grfmt_jpeg.cpp

@@ -643,23 +643,23 @@ bool JpegEncoder::write( const Mat& img, const std::vector<int>& params )
 
         for( size_t i = 0; i < params.size(); i += 2 )
         {
-            if( params[i] == CV_IMWRITE_JPEG_QUALITY )
+            if( params[i] == IMWRITE_JPEG_QUALITY )
             {
                 quality = params[i+1];
                 quality = MIN(MAX(quality, 0), 100);
             }
 
-            if( params[i] == CV_IMWRITE_JPEG_PROGRESSIVE )
+            if( params[i] == IMWRITE_JPEG_PROGRESSIVE )
             {
                 progressive = params[i+1];
             }
 
-            if( params[i] == CV_IMWRITE_JPEG_OPTIMIZE )
+            if( params[i] == IMWRITE_JPEG_OPTIMIZE )
             {
                 optimize = params[i+1];
             }
 
-            if( params[i] == CV_IMWRITE_JPEG_LUMA_QUALITY )
+            if( params[i] == IMWRITE_JPEG_LUMA_QUALITY )
             {
                 if (params[i+1] >= 0)
                 {
@@ -674,7 +674,7 @@ bool JpegEncoder::write( const Mat& img, const std::vector<int>& params )
                 }
             }
 
-            if( params[i] == CV_IMWRITE_JPEG_CHROMA_QUALITY )
+            if( params[i] == IMWRITE_JPEG_CHROMA_QUALITY )
             {
                 if (params[i+1] >= 0)
                 {
@@ -682,7 +682,7 @@ bool JpegEncoder::write( const Mat& img, const std::vector<int>& params )
                 }
             }
 
-            if( params[i] == CV_IMWRITE_JPEG_RST_INTERVAL )
+            if( params[i] == IMWRITE_JPEG_RST_INTERVAL )
             {
                 rst_interval = params[i+1];
                 rst_interval = MIN(MAX(rst_interval, 0), 65535L);

modules/imgcodecs/src/grfmt_pam.cpp

@@ -111,12 +111,12 @@ static bool rgb_convert (void *src, void *target, int width, int target_channels
     int target_depth);
 
 const static struct pam_format formats[] = {
-    {CV_IMWRITE_PAM_FORMAT_NULL, "", NULL, {0, 0, 0, 0} },
-    {CV_IMWRITE_PAM_FORMAT_BLACKANDWHITE, "BLACKANDWHITE", NULL, {0, 0, 0, 0} },
-    {CV_IMWRITE_PAM_FORMAT_GRAYSCALE, "GRAYSCALE", NULL, {0, 0, 0, 0} },
-    {CV_IMWRITE_PAM_FORMAT_GRAYSCALE_ALPHA, "GRAYSCALE_ALPHA", NULL, {0, 0, 0, 0} },
-    {CV_IMWRITE_PAM_FORMAT_RGB, "RGB", rgb_convert, {0, 1, 2, 0} },
-    {CV_IMWRITE_PAM_FORMAT_RGB_ALPHA, "RGB_ALPHA", NULL, {0, 1, 2, 0} },
+    {IMWRITE_PAM_FORMAT_NULL, "", NULL, {0, 0, 0, 0} },
+    {IMWRITE_PAM_FORMAT_BLACKANDWHITE, "BLACKANDWHITE", NULL, {0, 0, 0, 0} },
+    {IMWRITE_PAM_FORMAT_GRAYSCALE, "GRAYSCALE", NULL, {0, 0, 0, 0} },
+    {IMWRITE_PAM_FORMAT_GRAYSCALE_ALPHA, "GRAYSCALE_ALPHA", NULL, {0, 0, 0, 0} },
+    {IMWRITE_PAM_FORMAT_RGB, "RGB", rgb_convert, {0, 1, 2, 0} },
+    {IMWRITE_PAM_FORMAT_RGB_ALPHA, "RGB_ALPHA", NULL, {0, 1, 2, 0} },
 };
 #define PAM_FORMATS_NO (sizeof (fields) / sizeof ((fields)[0]))
 
@@ -341,7 +341,7 @@ PAMDecoder::PAMDecoder()
     m_offset = -1;
     m_buf_supported = true;
     bit_mode = false;
-    selected_fmt = CV_IMWRITE_PAM_FORMAT_NULL;
+    selected_fmt = IMWRITE_PAM_FORMAT_NULL;
     m_maxval = 0;
     m_channels = 0;
     m_sampledepth = 0;
@@ -462,14 +462,14 @@ bool PAMDecoder::readHeader()
 
         if (flds_endhdr && flds_height && flds_width && flds_depth && flds_maxval)
         {
-            if (selected_fmt == CV_IMWRITE_PAM_FORMAT_NULL)
+            if (selected_fmt == IMWRITE_PAM_FORMAT_NULL)
             {
                 if (m_channels == 1 && m_maxval == 1)
-                    selected_fmt = CV_IMWRITE_PAM_FORMAT_BLACKANDWHITE;
+                    selected_fmt = IMWRITE_PAM_FORMAT_BLACKANDWHITE;
                 else if (m_channels == 1 && m_maxval < 256)
-                    selected_fmt = CV_IMWRITE_PAM_FORMAT_GRAYSCALE;
+                    selected_fmt = IMWRITE_PAM_FORMAT_GRAYSCALE;
                 else if (m_channels == 3 && m_maxval < 256)
-                    selected_fmt = CV_IMWRITE_PAM_FORMAT_RGB;
+                    selected_fmt = IMWRITE_PAM_FORMAT_RGB;
             }
             m_type = CV_MAKETYPE(m_sampledepth, m_channels);
             m_offset = m_strm.getPos();
@@ -512,7 +512,7 @@ bool PAMDecoder::readData(Mat& img)
     if( m_offset < 0 || !m_strm.isOpened())
         return false;
 
-    if (selected_fmt != CV_IMWRITE_PAM_FORMAT_NULL)
+    if (selected_fmt != IMWRITE_PAM_FORMAT_NULL)
         fmt = &formats[selected_fmt];
     else {
         /* default layout handling */
@@ -662,8 +662,8 @@ bool PAMEncoder::write( const Mat& img, const std::vector<int>& params )
 
     /* parse save file type */
     for( size_t i = 0; i < params.size(); i += 2 )
-        if( params[i] == CV_IMWRITE_PAM_TUPLETYPE ) {
-            if ( params[i+1] > CV_IMWRITE_PAM_FORMAT_NULL &&
+        if( params[i] == IMWRITE_PAM_TUPLETYPE ) {
+            if ( params[i+1] > IMWRITE_PAM_FORMAT_NULL &&
                  params[i+1] < (int) PAM_FORMATS_NO)
                 fmt = &formats[params[i+1]];
         }

modules/imgcodecs/src/grfmt_webp.cpp

@@ -243,7 +243,7 @@ bool WebPEncoder::write(const Mat& img, const std::vector<int>& params)
 
     if (params.size() > 1)
     {
-        if (params[0] == CV_IMWRITE_WEBP_QUALITY)
+        if (params[0] == IMWRITE_WEBP_QUALITY)
         {
             comp_lossless = false;
             quality = static_cast<float>(params[1]);

modules/imgcodecs/src/loadsave.cpp

@@ -562,7 +562,7 @@ imreadmulti_(const String& filename, int flags, std::vector<Mat>& mats, int star
             if ((flags & IMREAD_ANYDEPTH) == 0)
                 type = CV_MAKETYPE(CV_8U, CV_MAT_CN(type));
 
-            if ((flags & CV_LOAD_IMAGE_COLOR) != 0 ||
+            if ((flags & IMREAD_COLOR) != 0 ||
                 ((flags & IMREAD_ANYCOLOR) != 0 && CV_MAT_CN(type) > 1))
                 type = CV_MAKETYPE(CV_MAT_DEPTH(type), 3);
             else

modules/imgcodecs/src/precomp.hpp

@@ -43,11 +43,8 @@
 #define __IMGCODECS_H_
 
 #include "opencv2/imgcodecs.hpp"
-#include "opencv2/imgcodecs/legacy/constants_c.h"
-
 #include "opencv2/core/utility.hpp"
 #include "opencv2/core/private.hpp"
-
 #include "opencv2/imgproc.hpp"
 
 #include <stdlib.h>

modules/ml/src/em.cpp

@@ -656,7 +656,7 @@ public:
 
         // Update weights
         // not normalized first
-        reduce(trainProbs, weights, 0, CV_REDUCE_SUM);
+        reduce(trainProbs, weights, 0, REDUCE_SUM);
 
         // Update means
         means.create(nclusters, dim, CV_64FC1);

modules/ml/test/test_precomp.hpp

@@ -4,7 +4,6 @@
 #include "opencv2/ts.hpp"
 #include <opencv2/ts/cuda_test.hpp> // EXPECT_MAT_NEAR
 #include "opencv2/ml.hpp"
-#include "opencv2/core/core_c.h"
 
 #include <fstream>
 using std::ifstream;

modules/objdetect/src/hog.cpp

@@ -42,7 +42,6 @@
 
 #include "precomp.hpp"
 #include "cascadedetect.hpp"
-#include "opencv2/core/core_c.h"
 #include "opencv2/core/hal/intrin.hpp"
 #include "opencl_kernels_objdetect.hpp"