Merge pull request #12825 from alalek:issue_8413_3.4

pull/12843/head
Alexander Alekhin 6 years ago
commit 72eccb7694
  1. 26
      modules/core/src/arithm.cpp
  2. 4
      modules/core/src/convert_scale.cpp
  3. 25
      modules/core/src/mathfuncs.cpp
  4. 4
      modules/core/src/matmul.cpp
  5. 29
      modules/core/src/opencl/arithm.cl
  6. 97
      modules/core/test/test_arithm.cpp

@ -105,14 +105,18 @@ static bool ocl_binary_op(InputArray _src1, InputArray _src2, OutputArray _dst,
int scalarcn = kercn == 3 ? 4 : kercn;
int rowsPerWI = d.isIntel() ? 4 : 1;
sprintf(opts, "-D %s%s -D %s -D dstT=%s%s -D dstT_C1=%s -D workST=%s -D cn=%d -D rowsPerWI=%d",
const int dstDepth = srcdepth;
const int dstType = CV_MAKETYPE(dstDepth, kercn);
const int dstType1 = CV_MAKETYPE(dstDepth, 1);
const int scalarType = CV_MAKETYPE(srcdepth, scalarcn);
sprintf(opts, "-D %s%s -D %s%s -D dstT=%s -D DEPTH_dst=%d -D dstT_C1=%s -D workST=%s -D cn=%d -D rowsPerWI=%d",
haveMask ? "MASK_" : "", haveScalar ? "UNARY_OP" : "BINARY_OP", oclop2str[oclop],
bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, kercn)) :
ocl::typeToStr(CV_MAKETYPE(srcdepth, kercn)), doubleSupport ? " -D DOUBLE_SUPPORT" : "",
bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, 1)) :
ocl::typeToStr(CV_MAKETYPE(srcdepth, 1)),
bitwise ? ocl::memopTypeToStr(CV_MAKETYPE(srcdepth, scalarcn)) :
ocl::typeToStr(CV_MAKETYPE(srcdepth, scalarcn)),
doubleSupport ? " -D DOUBLE_SUPPORT" : "",
bitwise ? ocl::memopTypeToStr(dstType) : ocl::typeToStr(dstType),
dstDepth,
bitwise ? ocl::memopTypeToStr(dstType1) : ocl::typeToStr(dstType1),
bitwise ? ocl::memopTypeToStr(scalarType) : ocl::typeToStr(scalarType),
kercn, rowsPerWI);
ocl::Kernel k("KF", ocl::core::arithm_oclsrc, opts);
@ -501,12 +505,12 @@ static bool ocl_arithm_op(InputArray _src1, InputArray _src2, OutputArray _dst,
char cvtstr[4][32], opts[1024];
sprintf(opts, "-D %s%s -D %s -D srcT1=%s -D srcT1_C1=%s -D srcT2=%s -D srcT2_C1=%s "
"-D dstT=%s -D dstT_C1=%s -D workT=%s -D workST=%s -D scaleT=%s -D wdepth=%d -D convertToWT1=%s "
"-D dstT=%s -D DEPTH_dst=%d -D dstT_C1=%s -D workT=%s -D workST=%s -D scaleT=%s -D wdepth=%d -D convertToWT1=%s "
"-D convertToWT2=%s -D convertToDT=%s%s -D cn=%d -D rowsPerWI=%d -D convertFromU=%s",
(haveMask ? "MASK_" : ""), (haveScalar ? "UNARY_OP" : "BINARY_OP"),
oclop2str[oclop], ocl::typeToStr(CV_MAKETYPE(depth1, kercn)),
ocl::typeToStr(depth1), ocl::typeToStr(CV_MAKETYPE(depth2, kercn)),
ocl::typeToStr(depth2), ocl::typeToStr(CV_MAKETYPE(ddepth, kercn)),
ocl::typeToStr(depth2), ocl::typeToStr(CV_MAKETYPE(ddepth, kercn)), ddepth,
ocl::typeToStr(ddepth), ocl::typeToStr(CV_MAKETYPE(wdepth, kercn)),
ocl::typeToStr(CV_MAKETYPE(wdepth, scalarcn)),
ocl::typeToStr(wdepth), wdepth,
@ -1152,12 +1156,12 @@ static bool ocl_compare(InputArray _src1, InputArray _src2, OutputArray _dst, in
const char * const operationMap[] = { "==", ">", ">=", "<", "<=", "!=" };
char cvt[40];
String opts = format("-D %s -D srcT1=%s -D dstT=%s -D workT=srcT1 -D cn=%d"
String opts = format("-D %s -D srcT1=%s -D dstT=%s -D DEPTH_dst=%d -D workT=srcT1 -D cn=%d"
" -D convertToDT=%s -D OP_CMP -D CMP_OPERATOR=%s -D srcT1_C1=%s"
" -D srcT2_C1=%s -D dstT_C1=%s -D workST=%s -D rowsPerWI=%d%s",
haveScalar ? "UNARY_OP" : "BINARY_OP",
ocl::typeToStr(CV_MAKE_TYPE(depth1, kercn)),
ocl::typeToStr(CV_8UC(kercn)), kercn,
ocl::typeToStr(CV_8UC(kercn)), CV_8U, kercn,
ocl::convertTypeStr(depth1, CV_8U, kercn, cvt),
operationMap[op], ocl::typeToStr(depth1),
ocl::typeToStr(depth1), ocl::typeToStr(CV_8U),

@ -376,10 +376,10 @@ static bool ocl_convertScaleAbs( InputArray _src, OutputArray _dst, double alpha
int rowsPerWI = d.isIntel() ? 4 : 1;
char cvt[2][50];
int wdepth = std::max(depth, CV_32F);
String build_opt = format("-D OP_CONVERT_SCALE_ABS -D UNARY_OP -D dstT=%s -D srcT1=%s"
String build_opt = format("-D OP_CONVERT_SCALE_ABS -D UNARY_OP -D dstT=%s -D DEPTH_dst=%d -D srcT1=%s"
" -D workT=%s -D wdepth=%d -D convertToWT1=%s -D convertToDT=%s"
" -D workT1=%s -D rowsPerWI=%d%s",
ocl::typeToStr(CV_8UC(kercn)),
ocl::typeToStr(CV_8UC(kercn)), CV_8U,
ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)),
ocl::typeToStr(CV_MAKE_TYPE(wdepth, kercn)), wdepth,
ocl::convertTypeStr(depth, wdepth, kercn, cvt[0]),

@ -71,8 +71,8 @@ static bool ocl_math_op(InputArray _src1, InputArray _src2, OutputArray _dst, in
int rowsPerWI = d.isIntel() ? 4 : 1;
ocl::Kernel k("KF", ocl::core::arithm_oclsrc,
format("-D %s -D %s -D dstT=%s -D rowsPerWI=%d%s", _src2.empty() ? "UNARY_OP" : "BINARY_OP",
oclop2str[oclop], ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)), rowsPerWI,
format("-D %s -D %s -D dstT=%s -D DEPTH_dst=%d -D rowsPerWI=%d%s", _src2.empty() ? "UNARY_OP" : "BINARY_OP",
oclop2str[oclop], ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)), depth, rowsPerWI,
double_support ? " -D DOUBLE_SUPPORT" : ""));
if (k.empty())
return false;
@ -238,9 +238,9 @@ static bool ocl_cartToPolar( InputArray _src1, InputArray _src2,
return false;
ocl::Kernel k("KF", ocl::core::arithm_oclsrc,
format("-D BINARY_OP -D dstT=%s -D depth=%d -D rowsPerWI=%d -D OP_CTP_%s%s",
ocl::typeToStr(CV_MAKE_TYPE(depth, 1)),
depth, rowsPerWI, angleInDegrees ? "AD" : "AR",
format("-D BINARY_OP -D dstT=%s -D DEPTH_dst=%d -D rowsPerWI=%d -D OP_CTP_%s%s",
ocl::typeToStr(CV_MAKE_TYPE(depth, 1)), depth,
rowsPerWI, angleInDegrees ? "AD" : "AR",
doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
if (k.empty())
return false;
@ -474,9 +474,10 @@ static bool ocl_polarToCart( InputArray _mag, InputArray _angle,
return false;
ocl::Kernel k("KF", ocl::core::arithm_oclsrc,
format("-D dstT=%s -D rowsPerWI=%d -D depth=%d -D BINARY_OP -D OP_PTC_%s%s",
ocl::typeToStr(CV_MAKE_TYPE(depth, 1)), rowsPerWI,
depth, angleInDegrees ? "AD" : "AR",
format("-D dstT=%s -D DEPTH_dst=%d -D rowsPerWI=%d -D BINARY_OP -D OP_PTC_%s%s",
ocl::typeToStr(CV_MAKE_TYPE(depth, 1)), depth,
rowsPerWI,
angleInDegrees ? "AD" : "AR",
doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
if (k.empty())
return false;
@ -1174,8 +1175,8 @@ static bool ocl_pow(InputArray _src, double power, OutputArray _dst,
const char * const op = issqrt ? "OP_SQRT" : is_ipower ? "OP_POWN" : "OP_POW";
ocl::Kernel k("KF", ocl::core::arithm_oclsrc,
format("-D dstT=%s -D depth=%d -D rowsPerWI=%d -D %s -D UNARY_OP%s",
ocl::typeToStr(depth), depth, rowsPerWI, op,
format("-D dstT=%s -D DEPTH_dst=%d -D rowsPerWI=%d -D %s -D UNARY_OP%s",
ocl::typeToStr(depth), depth, rowsPerWI, op,
doubleSupport ? " -D DOUBLE_SUPPORT" : ""));
if (k.empty())
return false;
@ -1565,8 +1566,8 @@ static bool ocl_patchNaNs( InputOutputArray _a, float value )
{
int rowsPerWI = ocl::Device::getDefault().isIntel() ? 4 : 1;
ocl::Kernel k("KF", ocl::core::arithm_oclsrc,
format("-D UNARY_OP -D OP_PATCH_NANS -D dstT=float -D rowsPerWI=%d",
rowsPerWI));
format("-D UNARY_OP -D OP_PATCH_NANS -D dstT=float -D DEPTH_dst=%d -D rowsPerWI=%d",
CV_32F, rowsPerWI));
if (k.empty())
return false;

@ -2359,10 +2359,10 @@ static bool ocl_scaleAdd( InputArray _src1, double alpha, InputArray _src2, Outp
char cvt[2][50];
ocl::Kernel k("KF", ocl::core::arithm_oclsrc,
format("-D OP_SCALE_ADD -D BINARY_OP -D dstT=%s -D workT=%s -D convertToWT1=%s"
format("-D OP_SCALE_ADD -D BINARY_OP -D dstT=%s -D DEPTH_dst=%d -D workT=%s -D convertToWT1=%s"
" -D srcT1=dstT -D srcT2=dstT -D convertToDT=%s -D workT1=%s"
" -D wdepth=%d%s -D rowsPerWI=%d",
ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)),
ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)), depth,
ocl::typeToStr(CV_MAKE_TYPE(wdepth, kercn)),
ocl::convertTypeStr(depth, wdepth, kercn, cvt[0]),
ocl::convertTypeStr(wdepth, depth, kercn, cvt[1]),

@ -71,7 +71,30 @@
#pragma OPENCL FP_FAST_FMA ON
#endif
#if depth <= 5
#if !defined(DEPTH_dst)
#error "Kernel configuration error: DEPTH_dst value is required"
#elif !(DEPTH_dst >= 0 && DEPTH_dst <= 7)
#error "Kernel configuration error: invalid DEPTH_dst value"
#endif
#if defined(depth)
#error "Kernel configuration error: ambiguous 'depth' value is defined, use 'DEPTH_dst' instead"
#endif
#if DEPTH_dst < 5 /* CV_32F */
#define CV_DST_TYPE_IS_INTEGER
#else
#define CV_DST_TYPE_IS_FP
#endif
#if DEPTH_dst != 6 /* CV_64F */
#define CV_DST_TYPE_FIT_32F 1
#else
#define CV_DST_TYPE_FIT_32F 0
#endif
#if CV_DST_TYPE_FIT_32F
#define CV_PI M_PI_F
#else
#define CV_PI M_PI
@ -283,7 +306,7 @@
#define PROCESS_ELEM storedst(pown(srcelem1, srcelem2))
#elif defined OP_SQRT
#if depth <= 5
#if CV_DST_TYPE_FIT_32F
#define PROCESS_ELEM storedst(native_sqrt(srcelem1))
#else
#define PROCESS_ELEM storedst(sqrt(srcelem1))
@ -324,7 +347,7 @@
#endif
#elif defined OP_CTP_AD || defined OP_CTP_AR
#if depth <= 5
#if CV_DST_TYPE_FIT_32F
#define CV_EPSILON FLT_EPSILON
#else
#define CV_EPSILON DBL_EPSILON

@ -2201,4 +2201,101 @@ TEST(Core_MeanStdDev, regression_multichannel)
}
}
template <typename T> static inline
void testDivideInitData(Mat& src1, Mat& src2)
{
CV_StaticAssert(std::numeric_limits<T>::is_integer, "");
const static T src1_[] = {
0, 0, 0, 0,
8, 8, 8, 8,
-8, -8, -8, -8
};
Mat(3, 4, traits::Type<T>::value, (void*)src1_).copyTo(src1);
const static T src2_[] = {
1, 2, 0, std::numeric_limits<T>::max(),
1, 2, 0, std::numeric_limits<T>::max(),
1, 2, 0, std::numeric_limits<T>::max(),
};
Mat(3, 4, traits::Type<T>::value, (void*)src2_).copyTo(src2);
}
template <typename T> static inline
void testDivideInitDataFloat(Mat& src1, Mat& src2)
{
CV_StaticAssert(!std::numeric_limits<T>::is_integer, "");
const static T src1_[] = {
0, 0, 0, 0,
8, 8, 8, 8,
-8, -8, -8, -8
};
Mat(3, 4, traits::Type<T>::value, (void*)src1_).copyTo(src1);
const static T src2_[] = {
1, 2, 0, std::numeric_limits<T>::infinity(),
1, 2, 0, std::numeric_limits<T>::infinity(),
1, 2, 0, std::numeric_limits<T>::infinity(),
};
Mat(3, 4, traits::Type<T>::value, (void*)src2_).copyTo(src2);
}
template <> inline void testDivideInitData<float>(Mat& src1, Mat& src2) { testDivideInitDataFloat<float>(src1, src2); }
template <> inline void testDivideInitData<double>(Mat& src1, Mat& src2) { testDivideInitDataFloat<double>(src1, src2); }
template <typename T> static inline
void testDivideChecks(const Mat& dst)
{
ASSERT_FALSE(dst.empty());
for (int y = 0; y < dst.rows; y++)
{
for (int x = 0; x < dst.cols; x++)
{
if (x == 2)
{
EXPECT_EQ(0, dst.at<T>(y, x)) << "dst(" << y << ", " << x << ") = " << dst.at<T>(y, x);
}
}
}
}
template <typename T, bool isUMat> static inline
void testDivide()
{
Mat src1, src2;
testDivideInitData<T>(src1, src2);
ASSERT_FALSE(src1.empty()); ASSERT_FALSE(src2.empty());
Mat dst;
if (!isUMat)
{
cv::divide(src1, src2, dst);
}
else
{
UMat usrc1, usrc2, udst;
src1.copyTo(usrc1);
src2.copyTo(usrc2);
cv::divide(usrc1, usrc2, udst);
udst.copyTo(dst);
}
testDivideChecks<T>(dst);
if (::testing::Test::HasFailure())
{
std::cout << "src1 = " << std::endl << src1 << std::endl;
std::cout << "src2 = " << std::endl << src2 << std::endl;
std::cout << "dst = " << std::endl << dst << std::endl;
}
}
TEST(Core_DivideRules, type_32s) { testDivide<int, false>(); }
TEST(UMat_Core_DivideRules, type_32s) { testDivide<int, true>(); }
TEST(Core_DivideRules, type_16s) { testDivide<short, false>(); }
TEST(UMat_Core_DivideRules, type_16s) { testDivide<short, true>(); }
TEST(Core_DivideRules, type_32f) { testDivide<float, false>(); }
TEST(UMat_Core_DivideRules, type_32f) { testDivide<float, true>(); }
TEST(Core_DivideRules, type_64f) { testDivide<double, false>(); }
TEST(UMat_Core_DivideRules, type_64f) { testDivide<double, true>(); }
}} // namespace

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