8000 fix legacy constants by sturkmen72 · Pull Request #21378 · opencv/opencv · GitHub
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fix legacy constants #21378

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Jan 4, 2022
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fix legacy constants #21378

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4 changes: 2 additions & 2 deletions modules/core/perf/perf_reduce.cpp
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Expand Up @@ -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);
Expand Down Expand Up @@ -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);
Expand Down
2 changes: 1 addition & 1 deletion modules/core/src/matmul.dispatch.cpp
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Expand Up @@ -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();
}

Expand Down
40 changes: 20 additions & 20 deletions modules/core/src/matrix_operations.cpp
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Expand Up @@ -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;
Expand Down Expand Up @@ -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
Expand Down Expand Up @@ -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);
Expand All @@ -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))
Expand All @@ -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));
Expand All @@ -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);
Expand All @@ -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);
Expand All @@ -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);
Expand All @@ -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);
Expand All @@ -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);
Expand All @@ -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);
Expand All @@ -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));
}

Expand All @@ -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;
Expand 9E12 Down Expand Up @@ -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);
Expand Down Expand Up @@ -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 );

Expand Down
16 changes: 8 additions & 8 deletions modules/core/test/ocl/test_arithm.cpp
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Expand Up @@ -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);
Expand All @@ -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);
}
Expand All @@ -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);
}
Expand All @@ -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);
Expand Down
34 changes: 17 additions & 17 deletions modules/core/test/test_mat.cpp
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Expand Up @@ -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;
Expand All @@ -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;
Expand All @@ -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;
Expand All @@ -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;
Expand All @@ -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 );
Expand Down Expand Up @@ -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;
Expand Down Expand Up @@ -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;
Expand Down Expand Up @@ -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)
Expand Down
2 changes: 1 addition & 1 deletion modules/core/test/test_math.cpp
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Expand Up @@ -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);

Expand Down
3 changes: 0 additions & 3 deletions modules/core/test/test_precomp.hpp
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Expand Up @@ -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"

Expand Down
4 changes: 2 additions & 2 deletions modules/core/test/test_umat.cpp
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Expand Up @@ -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);< 1241 /span>
srcMat.convertTo(srcMat, CV_64FC1);
Expand Down
2 changes: 1 addition & 1 deletion modules/imgcodecs/src/grfmt_exr.cpp
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Expand Up @@ -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] )
{
Expand Down
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