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opencv/modules/core/src/minmax.cpp

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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "precomp.hpp"
#include "opencl_kernels_core.hpp"
#include "opencv2/core/openvx/ovx_defs.hpp"
#include "stat.hpp"
#include "opencv2/core/detail/dispatch_helper.impl.hpp"
#include <algorithm>
#undef HAVE_IPP
#undef CV_IPP_RUN_FAST
#define CV_IPP_RUN_FAST(f, ...)
#undef CV_IPP_RUN
#define CV_IPP_RUN(c, f, ...)
#define IPP_DISABLE_MINMAXIDX_MANY_ROWS 1 // see Core_MinMaxIdx.rows_overflow test
/****************************************************************************************\
* minMaxLoc *
\****************************************************************************************/
namespace cv
{
template<typename T, typename WT> static void
minMaxIdx_( const T* src, const uchar* mask, WT* _minVal, WT* _maxVal,
size_t* _minIdx, size_t* _maxIdx, int len, size_t startIdx )
{
WT minVal = *_minVal, maxVal = *_maxVal;
size_t minIdx = *_minIdx, maxIdx = *_maxIdx;
if( !mask )
{
for( int i = 0; i < len; i++ )
{
T val = src[i];
if( val < minVal )
{
minVal = val;
minIdx = startIdx + i;
}
if( val > maxVal )
{
maxVal = val;
maxIdx = startIdx + i;
}
}
}
else
{
for( int i = 0; i < len; i++ )
{
T val = src[i];
if( mask[i] && val < minVal )
{
minVal = val;
minIdx = startIdx + i;
}
if( mask[i] && val > maxVal )
{
maxVal = val;
maxIdx = startIdx + i;
}
}
}
*_minIdx = minIdx;
*_maxIdx = maxIdx;
*_minVal = minVal;
*_maxVal = maxVal;
}
#if CV_SIMD128
template<typename T, typename WT> CV_ALWAYS_INLINE void
minMaxIdx_init( const T* src, const uchar* mask, WT* minval, WT* maxval,
size_t* minidx, size_t* maxidx, WT &minVal, WT &maxVal,
size_t &minIdx, size_t &maxIdx, const WT minInit, const WT maxInit,
const int nlanes, int len, size_t startidx, int &j, int &len0 )
{
len0 = len & -nlanes;
j = 0;
minVal = *minval, maxVal = *maxval;
minIdx = *minidx, maxIdx = *maxidx;
// To handle start values out of range
if ( minVal < minInit || maxVal < minInit || minVal > maxInit || maxVal > maxInit )
{
uchar done = 0x00;
for ( ; (j < len) && (done != 0x03); j++ )
{
if ( !mask || mask[j] ) {
T val = src[j];
if ( val < minVal )
{
minVal = val;
minIdx = startidx + j;
done |= 0x01;
}
if ( val > maxVal )
{
maxVal = val;
maxIdx = startidx + j;
done |= 0x02;
}
}
}
len0 = j + ((len - j) & -nlanes);
}
}
#if CV_SIMD128_64F
CV_ALWAYS_INLINE double v_reduce_min(const v_float64x2& a)
{
double CV_DECL_ALIGNED(32) idx[2];
v_store_aligned(idx, a);
return std::min(idx[0], idx[1]);
}
CV_ALWAYS_INLINE double v_reduce_max(const v_float64x2& a)
{
double CV_DECL_ALIGNED(32) idx[2];
v_store_aligned(idx, a);
return std::max(idx[0], idx[1]);
}
CV_ALWAYS_INLINE uint64_t v_reduce_min(const v_uint64x2& a)
{
uint64_t CV_DECL_ALIGNED(32) idx[2];
v_store_aligned(idx, a);
return std::min(idx[0], idx[1]);
}
CV_ALWAYS_INLINE v_uint64x2 v_select(const v_uint64x2& mask, const v_uint64x2& a, const v_uint64x2& b)
{
return b ^ ((a ^ b) & mask);
}
#endif
#define MINMAXIDX_REDUCE(suffix, suffix2, maxLimit, IR) \
template<typename T, typename VT, typename IT> CV_ALWAYS_INLINE void \
minMaxIdx_reduce_##suffix( VT &valMin, VT &valMax, IT &idxMin, IT &idxMax, IT &none, \
T &minVal, T &maxVal, size_t &minIdx, size_t &maxIdx, \
size_t delta ) \
{ \
if ( v_check_any(idxMin != none) ) \
{ \
minVal = v_reduce_min(valMin); \
minIdx = (size_t)v_reduce_min(v_select(v_reinterpret_as_##suffix2(v_setall_##suffix((IR)minVal) == valMin), \
idxMin, v_setall_##suffix2(maxLimit))) + delta; \
} \
if ( v_check_any(idxMax != none) ) \
{ \
maxVal = v_reduce_max(valMax); \
maxIdx = (size_t)v_reduce_min(v_select(v_reinterpret_as_##suffix2(v_setall_##suffix((IR)maxVal) == valMax), \
idxMax, v_setall_##suffix2(maxLimit))) + delta; \
} \
}
MINMAXIDX_REDUCE(u8, u8, UCHAR_MAX, uchar)
MINMAXIDX_REDUCE(s8, u8, UCHAR_MAX, uchar)
MINMAXIDX_REDUCE(u16, u16, USHRT_MAX, ushort)
MINMAXIDX_REDUCE(s16, u16, USHRT_MAX, ushort)
MINMAXIDX_REDUCE(s32, u32, UINT_MAX, uint)
MINMAXIDX_REDUCE(f32, u32, (1 << 23) - 1, float)
#if CV_SIMD128_64F
MINMAXIDX_REDUCE(f64, u64, UINT_MAX, double)
#endif
template<typename T, typename WT> CV_ALWAYS_INLINE void
minMaxIdx_finish( const T* src, const uchar* mask, WT* minval, WT* maxval,
size_t* minidx, size_t* maxidx, WT minVal, WT maxVal,
size_t minIdx, size_t maxIdx, int len, size_t startidx,
int j )
{
for ( ; j < len ; j++ )
{
if ( !mask || mask[j] )
{
T val = src[j];
if ( val < minVal )
{
minVal = val;
minIdx = startidx + j;
}
if ( val > maxVal )
{
maxVal = val;
maxIdx = startidx + j;
}
}
}
*minidx = minIdx;
*maxidx = maxIdx;
*minval = minVal;
*maxval = maxVal;
}
#endif
static void minMaxIdx_8u(const uchar* src, const uchar* mask, int* minval, int* maxval,
size_t* minidx, size_t* maxidx, int len, size_t startidx )
{
#if CV_SIMD128
if ( len >= v_uint8x16::nlanes )
{
int j, len0;
int minVal, maxVal;
size_t minIdx, maxIdx;
minMaxIdx_init( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal, minIdx, maxIdx,
(int)0, (int)UCHAR_MAX, v_uint8x16::nlanes, len, startidx, j, len0 );
if ( j <= len0 - v_uint8x16::nlanes )
{
v_uint8x16 inc = v_setall_u8(v_uint8x16::nlanes);
v_uint8x16 none = v_reinterpret_as_u8(v_setall_s8(-1));
v_uint8x16 idxStart(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15);
do
{
v_uint8x16 valMin = v_setall_u8((uchar)minVal), valMax = v_setall_u8((uchar)maxVal);
v_uint8x16 idx = idxStart, idxMin = none, idxMax = none;
int k = j;
size_t delta = startidx + j;
if ( !mask )
{
for( ; k < std::min(len0, j + 15 * v_uint8x16::nlanes); k += v_uint8x16::nlanes )
{
v_uint8x16 data = v_load(src + k);
v_uint8x16 cmpMin = (data < valMin);
v_uint8x16 cmpMax = (data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
}
}
else
{
for( ; k < std::min(len0, j + 15 * v_uint8x16::nlanes); k += v_uint8x16::nlanes )
{
v_uint8x16 data = v_load(src + k);
v_uint8x16 maskVal = v_load(mask + k) != v_setzero_u8();
v_uint8x16 cmpMin = (data < valMin) & maskVal;
v_uint8x16 cmpMax = (data > valMax) & maskVal;
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(cmpMin, data, valMin);
valMax = v_select(cmpMax, data, valMax);
idx += inc;
}
}
j = k;
minMaxIdx_reduce_u8( valMin, valMax, idxMin, idxMax, none, minVal, maxVal,
minIdx, maxIdx, delta );
}
while ( j < len0 );
}
minMaxIdx_finish( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal,
minIdx, maxIdx, len, startidx, j );
}
else
{
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx);
}
#else
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx);
#endif
}
static void minMaxIdx_8s(const schar* src, const uchar* mask, int* minval, int* maxval,
size_t* minidx, size_t* maxidx, int len, size_t startidx )
{
#if CV_SIMD128
if ( len >= v_int8x16::nlanes )
{
int j, len0;
int minVal, maxVal;
size_t minIdx, maxIdx;
minMaxIdx_init( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal, minIdx, maxIdx,
(int)SCHAR_MIN, (int)SCHAR_MAX, v_int8x16::nlanes, len, startidx, j, len0 );
if ( j <= len0 - v_int8x16::nlanes )
{
v_uint8x16 inc = v_setall_u8(v_int8x16::nlanes);
v_uint8x16 none = v_reinterpret_as_u8(v_setall_s8(-1));
v_uint8x16 idxStart(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15);
do
{
v_int8x16 valMin = v_setall_s8((schar)minVal), valMax = v_setall_s8((schar)maxVal);
v_uint8x16 idx = idxStart, idxMin = none, idxMax = none;
int k = j;
size_t delta = startidx + j;
if ( !mask )
{
for( ; k < std::min(len0, j + 15 * v_int8x16::nlanes); k += v_int8x16::nlanes )
{
v_int8x16 data = v_load(src + k);
v_uint8x16 cmpMin = v_reinterpret_as_u8(data < valMin);
v_uint8x16 cmpMax = v_reinterpret_as_u8(data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
}
}
else
{
for( ; k < std::min(len0, j + 15 * v_int8x16::nlanes); k += v_int8x16::nlanes )
{
v_int8x16 data = v_load(src + k);
v_uint8x16 maskVal = v_load(mask + k) != v_setzero_u8();
v_uint8x16 cmpMin = v_reinterpret_as_u8(data < valMin) & maskVal;
v_uint8x16 cmpMax = v_reinterpret_as_u8(data > valMax) & maskVal;
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(v_reinterpret_as_s8(cmpMin), data, valMin);
valMax = v_select(v_reinterpret_as_s8(cmpMax), data, valMax);
idx += inc;
}
}
j = k;
minMaxIdx_reduce_s8( valMin, valMax, idxMin, idxMax, none, minVal, maxVal,
minIdx, maxIdx, delta );
}
while ( j < len0 );
}
minMaxIdx_finish( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal,
minIdx, maxIdx, len, startidx, j );
}
else
{
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx);
}
#else
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx );
#endif
}
static void minMaxIdx_16u(const ushort* src, const uchar* mask, int* minval, int* maxval,
size_t* minidx, size_t* maxidx, int len, size_t startidx )
{
#if CV_SIMD128
if ( len >= v_uint16x8::nlanes )
{
int j, len0;
int minVal, maxVal;
size_t minIdx, maxIdx;
minMaxIdx_init( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal, minIdx, maxIdx,
(int)0, (int)USHRT_MAX, v_uint16x8::nlanes, len, startidx, j, len0 );
if ( j <= len0 - v_uint16x8::nlanes )
{
v_uint16x8 inc = v_setall_u16(v_uint16x8::nlanes);
v_uint16x8 none = v_reinterpret_as_u16(v_setall_s16(-1));
v_uint16x8 idxStart(0, 1, 2, 3, 4, 5, 6, 7);
do
{
v_uint16x8 valMin = v_setall_u16((ushort)minVal), valMax = v_setall_u16((ushort)maxVal);
v_uint16x8 idx = idxStart, idxMin = none, idxMax = none;
int k = j;
size_t delta = startidx + j;
if ( !mask )
{
for( ; k < std::min(len0, j + 8191 * v_uint16x8::nlanes); k += v_uint16x8::nlanes )
{
v_uint16x8 data = v_load(src + k);
v_uint16x8 cmpMin = (data < valMin);
v_uint16x8 cmpMax = (data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
}
}
else
{
for( ; k < std::min(len0, j + 8191 * v_uint16x8::nlanes); k += v_uint16x8::nlanes )
{
v_uint16x8 data = v_load(src + k);
v_uint16x8 maskVal = v_load_expand(mask + k) != v_setzero_u16();
v_uint16x8 cmpMin = (data < valMin) & maskVal;
v_uint16x8 cmpMax = (data > valMax) & maskVal;
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(cmpMin, data, valMin);
valMax = v_select(cmpMax, data, valMax);
idx += inc;
}
}
j = k;
minMaxIdx_reduce_u16( valMin, valMax, idxMin, idxMax, none, minVal, maxVal,
minIdx, maxIdx, delta );
}
while ( j < len0 );
}
minMaxIdx_finish( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal,
minIdx, maxIdx, len, startidx, j );
}
else
{
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx);
}
#else
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx );
#endif
}
static void minMaxIdx_16s(const short* src, const uchar* mask, int* minval, int* maxval,
size_t* minidx, size_t* maxidx, int len, size_t startidx )
{
#if CV_SIMD128
if ( len >= v_int16x8::nlanes )
{
int j, len0;
int minVal, maxVal;
size_t minIdx, maxIdx;
minMaxIdx_init( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal, minIdx, maxIdx,
(int)SHRT_MIN, (int)SHRT_MAX, v_int16x8::nlanes, len, startidx, j, len0 );
if ( j <= len0 - v_int16x8::nlanes )
{
v_uint16x8 inc = v_setall_u16(v_int16x8::nlanes);
v_uint16x8 none = v_reinterpret_as_u16(v_setall_s16(-1));
v_uint16x8 idxStart(0, 1, 2, 3, 4, 5, 6, 7);
do
{
v_int16x8 valMin = v_setall_s16((short)minVal), valMax = v_setall_s16((short)maxVal);
v_uint16x8 idx = idxStart, idxMin = none, idxMax = none;
int k = j;
size_t delta = startidx + j;
if ( !mask )
{
for( ; k < std::min(len0, j + 8191 * v_int16x8::nlanes); k += v_int16x8::nlanes )
{
v_int16x8 data = v_load(src + k);
v_uint16x8 cmpMin = v_reinterpret_as_u16(data < valMin);
v_uint16x8 cmpMax = v_reinterpret_as_u16(data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
}
}
else
{
for( ; k < std::min(len0, j + 8191 * v_int16x8::nlanes); k += v_int16x8::nlanes )
{
v_int16x8 data = v_load(src + k);
v_uint16x8 maskVal = v_load_expand(mask + k) != v_setzero_u16();
v_uint16x8 cmpMin = v_reinterpret_as_u16(data < valMin) & maskVal;
v_uint16x8 cmpMax = v_reinterpret_as_u16(data > valMax) & maskVal;
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(v_reinterpret_as_s16(cmpMin), data, valMin);
valMax = v_select(v_reinterpret_as_s16(cmpMax), data, valMax);
idx += inc;
}
}
j = k;
minMaxIdx_reduce_s16( valMin, valMax, idxMin, idxMax, none, minVal, maxVal,
minIdx, maxIdx, delta );
}
while ( j < len0 );
}
minMaxIdx_finish( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal,
minIdx, maxIdx, len, startidx, j );
}
else
{
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx);
}
#else
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx );
#endif
}
static void minMaxIdx_32s(const int* src, const uchar* mask, int* minval, int* maxval,
size_t* minidx, size_t* maxidx, int len, size_t startidx )
{
#if CV_SIMD128
if ( len >= 2 * v_int32x4::nlanes )
{
int j = 0, len0 = len & -(2 * v_int32x4::nlanes);
int minVal = *minval, maxVal = *maxval;
size_t minIdx = *minidx, maxIdx = *maxidx;
{
v_uint32x4 inc = v_setall_u32(v_int32x4::nlanes);
v_uint32x4 none = v_reinterpret_as_u32(v_setall_s32(-1));
v_uint32x4 idxStart(0, 1, 2, 3);
do
{
v_int32x4 valMin = v_setall_s32(minVal), valMax = v_setall_s32(maxVal);
v_uint32x4 idx = idxStart, idxMin = none, idxMax = none;
int k = j;
size_t delta = startidx + j;
if ( !mask )
{
for( ; k < std::min(len0, j + 32766 * 2 * v_int32x4::nlanes); k += 2 * v_int32x4::nlanes )
{
v_int32x4 data = v_load(src + k);
v_uint32x4 cmpMin = v_reinterpret_as_u32(data < valMin);
v_uint32x4 cmpMax = v_reinterpret_as_u32(data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
data = v_load(src + k + v_int32x4::nlanes);
cmpMin = v_reinterpret_as_u32(data < valMin);
cmpMax = v_reinterpret_as_u32(data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
}
}
else
{
for( ; k < std::min(len0, j + 32766 * 2 * v_int32x4::nlanes); k += 2 * v_int32x4::nlanes )
{
v_int32x4 data = v_load(src + k);
v_uint16x8 maskVal = v_load_expand(mask + k) != v_setzero_u16();
v_int32x4 maskVal1, maskVal2;
v_expand(v_reinterpret_as_s16(maskVal), maskVal1, maskVal2);
v_uint32x4 cmpMin = v_reinterpret_as_u32((data < valMin) & maskVal1);
v_uint32x4 cmpMax = v_reinterpret_as_u32((data > valMax) & maskVal1);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(v_reinterpret_as_s32(cmpMin), data, valMin);
valMax = v_select(v_reinterpret_as_s32(cmpMax), data, valMax);
idx += inc;
data = v_load(src + k + v_int32x4::nlanes);
cmpMin = v_reinterpret_as_u32((data < valMin) & maskVal2);
cmpMax = v_reinterpret_as_u32((data > valMax) & maskVal2);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(v_reinterpret_as_s32(cmpMin), data, valMin);
valMax = v_select(v_reinterpret_as_s32(cmpMax), data, valMax);
idx += inc;
}
}
j = k;
minMaxIdx_reduce_s32( valMin, valMax, idxMin, idxMax, none, minVal, maxVal,
minIdx, maxIdx, delta );
}
while ( j < len0 );
}
minMaxIdx_finish( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal,
minIdx, maxIdx, len, startidx, j );
}
else
{
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx);
}
#else
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx );
#endif
}
static void minMaxIdx_32f(const float* src, const uchar* mask, float* minval, float* maxval,
size_t* minidx, size_t* maxidx, int len, size_t startidx )
{
#if CV_SIMD128
if ( len >= 2 * v_float32x4::nlanes )
{
int j, len0;
float minVal, maxVal;
size_t minIdx, maxIdx;
minMaxIdx_init( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal, minIdx, maxIdx,
FLT_MIN, FLT_MAX, 2 * v_float32x4::nlanes, len, startidx, j, len0 );
if ( j <= len0 - 2 * v_float32x4::nlanes )
{
v_uint32x4 inc = v_setall_u32(v_float32x4::nlanes);
v_uint32x4 none = v_reinterpret_as_u32(v_setall_s32(-1));
v_uint32x4 idxStart(0, 1, 2, 3);
do
{
v_float32x4 valMin = v_setall_f32(minVal), valMax = v_setall_f32(maxVal);
v_uint32x4 idx = idxStart, idxMin = none, idxMax = none;
int k = j;
size_t delta = startidx + j;
if ( !mask )
{
for( ; k < std::min(len0, j + 32766 * 2 * v_float32x4::nlanes); k += 2 * v_float32x4::nlanes )
{
v_float32x4 data = v_load(src + k);
v_uint32x4 cmpMin = v_reinterpret_as_u32(data < valMin);
v_uint32x4 cmpMax = v_reinterpret_as_u32(data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
data = v_load(src + k + v_float32x4::nlanes);
cmpMin = v_reinterpret_as_u32(data < valMin);
cmpMax = v_reinterpret_as_u32(data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
}
}
else
{
for( ; k < std::min(len0, j + 32766 * 2 * v_float32x4::nlanes); k += 2 * v_float32x4::nlanes )
{
v_float32x4 data = v_load(src + k);
v_uint16x8 maskVal = v_load_expand(mask + k) != v_setzero_u16();
v_int32x4 maskVal1, maskVal2;
v_expand(v_reinterpret_as_s16(maskVal), maskVal1, maskVal2);
v_uint32x4 cmpMin = v_reinterpret_as_u32(v_reinterpret_as_s32(data < valMin) & maskVal1);
v_uint32x4 cmpMax = v_reinterpret_as_u32(v_reinterpret_as_s32(data > valMax) & maskVal1);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(v_reinterpret_as_f32(cmpMin), data, valMin);
valMax = v_select(v_reinterpret_as_f32(cmpMax), data, valMax);
idx += inc;
data = v_load(src + k + v_float32x4::nlanes);
cmpMin = v_reinterpret_as_u32(v_reinterpret_as_s32(data < valMin) & maskVal2);
cmpMax = v_reinterpret_as_u32(v_reinterpret_as_s32(data > valMax) & maskVal2);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(v_reinterpret_as_f32(cmpMin), data, valMin);
valMax = v_select(v_reinterpret_as_f32(cmpMax), data, valMax);
idx += inc;
}
}
j = k;
minMaxIdx_reduce_f32( valMin, valMax, idxMin, idxMax, none, minVal, maxVal,
minIdx, maxIdx, delta );
}
while ( j < len0 );
}
minMaxIdx_finish( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal,
minIdx, maxIdx, len, startidx, j );
}
else
{
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx);
}
#else
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx );
#endif
}
static void minMaxIdx_64f(const double* src, const uchar* mask, double* minval, double* maxval,
size_t* minidx, size_t* maxidx, int len, size_t startidx )
{
#if CV_SIMD128_64F
if ( len >= 4 * v_float64x2::nlanes )
{
int j, len0;
double minVal, maxVal;
size_t minIdx, maxIdx;
minMaxIdx_init( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal, minIdx, maxIdx,
DBL_MIN, DBL_MAX, 4 * v_float64x2::nlanes, len, startidx, j, len0 );
if ( j <= len0 - 4 * v_float64x2::nlanes )
{
v_uint64x2 inc = v_setall_u64(v_float64x2::nlanes);
v_uint64x2 none = v_reinterpret_as_u64(v_setall_s64(-1));
v_uint64x2 idxStart(0, 1);
do
{
v_float64x2 valMin = v_setall_f64(minVal), valMax = v_setall_f64(maxVal);
v_uint64x2 idx = idxStart, idxMin = none, idxMax = none;
int k = j;
size_t delta = startidx + j;
if ( !mask )
{
for( ; k < std::min(len0, j + 32764 * 4 * v_float64x2::nlanes); k += 4 * v_float64x2::nlanes )
{
v_float64x2 data = v_load(src + k);
v_uint64x2 cmpMin = v_reinterpret_as_u64(data < valMin);
v_uint64x2 cmpMax = v_reinterpret_as_u64(data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
data = v_load(src + k + v_float64x2::nlanes);
cmpMin = v_reinterpret_as_u64(data < valMin);
cmpMax = v_reinterpret_as_u64(data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
data = v_load(src + k + 2 * v_float64x2::nlanes);
cmpMin = v_reinterpret_as_u64(data < valMin);
cmpMax = v_reinterpret_as_u64(data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
data = v_load(src + k + 3 * v_float64x2::nlanes);
cmpMin = v_reinterpret_as_u64(data < valMin);
cmpMax = v_reinterpret_as_u64(data > valMax);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_min(data, valMin);
valMax = v_max(data, valMax);
idx += inc;
}
}
else
{
for( ; k < std::min(len0, j + 32764 * 4 * v_float64x2::nlanes); k += 4 * v_float64x2::nlanes )
{
v_float64x2 data = v_load(src + k);
v_uint16x8 maskVal = v_load_expand(mask + k) != v_setzero_u16();
v_int32x4 maskVal1, maskVal2;
v_expand(v_reinterpret_as_s16(maskVal), maskVal1, maskVal2);
v_int64x2 maskVal3, maskVal4;
v_expand(maskVal1, maskVal3, maskVal4);
v_uint64x2 cmpMin = v_reinterpret_as_u64(v_reinterpret_as_s64(data < valMin) & maskVal3);
v_uint64x2 cmpMax = v_reinterpret_as_u64(v_reinterpret_as_s64(data > valMax) & maskVal3);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(v_reinterpret_as_f64(cmpMin), data, valMin);
valMax = v_select(v_reinterpret_as_f64(cmpMax), data, valMax);
idx += inc;
data = v_load(src + k + v_float64x2::nlanes);
cmpMin = v_reinterpret_as_u64(v_reinterpret_as_s64(data < valMin) & maskVal4);
cmpMax = v_reinterpret_as_u64(v_reinterpret_as_s64(data > valMax) & maskVal4);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(v_reinterpret_as_f64(cmpMin), data, valMin);
valMax = v_select(v_reinterpret_as_f64(cmpMax), data, valMax);
idx += inc;
data = v_load(src + k + 2 * v_float64x2::nlanes);
v_expand(maskVal2, maskVal3, maskVal4);
cmpMin = v_reinterpret_as_u64(v_reinterpret_as_s64(data < valMin) & maskVal3);
cmpMax = v_reinterpret_as_u64(v_reinterpret_as_s64(data > valMax) & maskVal3);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(v_reinterpret_as_f64(cmpMin), data, valMin);
valMax = v_select(v_reinterpret_as_f64(cmpMax), data, valMax);
idx += inc;
data = v_load(src + k + 3 * v_float64x2::nlanes);
cmpMin = v_reinterpret_as_u64(v_reinterpret_as_s64(data < valMin) & maskVal4);
cmpMax = v_reinterpret_as_u64(v_reinterpret_as_s64(data > valMax) & maskVal4);
idxMin = v_select(cmpMin, idx, idxMin);
idxMax = v_select(cmpMax, idx, idxMax);
valMin = v_select(v_reinterpret_as_f64(cmpMin), data, valMin);
valMax = v_select(v_reinterpret_as_f64(cmpMax), data, valMax);
idx += inc;
}
}
j = k;
minMaxIdx_reduce_f64( valMin, valMax, idxMin, idxMax, none, minVal, maxVal,
minIdx, maxIdx, delta );
}
while ( j < len0 );
}
minMaxIdx_finish( src, mask, minval, maxval, minidx, maxidx, minVal, maxVal,
minIdx, maxIdx, len, startidx, j );
}
else
{
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx);
}
#else
minMaxIdx_(src, mask, minval, maxval, minidx, maxidx, len, startidx );
#endif
}
typedef void (*MinMaxIdxFunc)(const uchar*, const uchar*, int*, int*, size_t*, size_t*, int, size_t);
static MinMaxIdxFunc getMinmaxTab(int depth)
{
static MinMaxIdxFunc minmaxTab[] =
{
(MinMaxIdxFunc)GET_OPTIMIZED(minMaxIdx_8u), (MinMaxIdxFunc)GET_OPTIMIZED(minMaxIdx_8s),
(MinMaxIdxFunc)GET_OPTIMIZED(minMaxIdx_16u), (MinMaxIdxFunc)GET_OPTIMIZED(minMaxIdx_16s),
(MinMaxIdxFunc)GET_OPTIMIZED(minMaxIdx_32s),
(MinMaxIdxFunc)GET_OPTIMIZED(minMaxIdx_32f), (MinMaxIdxFunc)GET_OPTIMIZED(minMaxIdx_64f),
0
};
return minmaxTab[depth];
}
static void ofs2idx(const Mat& a, size_t ofs, int* idx)
{
int i, d = a.dims;
if( ofs > 0 )
{
ofs--;
for( i = d-1; i >= 0; i-- )
{
int sz = a.size[i];
idx[i] = (int)(ofs % sz);
ofs /= sz;
}
}
else
{
for( i = d-1; i >= 0; i-- )
idx[i] = -1;
}
}
#ifdef HAVE_OPENCL
#define MINMAX_STRUCT_ALIGNMENT 8 // sizeof double
template <typename T>
void getMinMaxRes(const Mat & db, double * minVal, double * maxVal,
int* minLoc, int* maxLoc,
int groupnum, int cols, double * maxVal2)
{
uint index_max = std::numeric_limits<uint>::max();
T minval = std::numeric_limits<T>::max();
T maxval = std::numeric_limits<T>::min() > 0 ? -std::numeric_limits<T>::max() : std::numeric_limits<T>::min(), maxval2 = maxval;
uint minloc = index_max, maxloc = index_max;
size_t index = 0;
const T * minptr = NULL, * maxptr = NULL, * maxptr2 = NULL;
const uint * minlocptr = NULL, * maxlocptr = NULL;
if (minVal || minLoc)
{
minptr = db.ptr<T>();
index += sizeof(T) * groupnum;
index = alignSize(index, MINMAX_STRUCT_ALIGNMENT);
}
if (maxVal || maxLoc)
{
maxptr = (const T *)(db.ptr() + index);
index += sizeof(T) * groupnum;
index = alignSize(index, MINMAX_STRUCT_ALIGNMENT);
}
if (minLoc)
{
minlocptr = (const uint *)(db.ptr() + index);
index += sizeof(uint) * groupnum;
index = alignSize(index, MINMAX_STRUCT_ALIGNMENT);
}
if (maxLoc)
{
maxlocptr = (const uint *)(db.ptr() + index);
index += sizeof(uint) * groupnum;
index = alignSize(index, MINMAX_STRUCT_ALIGNMENT);
}
if (maxVal2)
maxptr2 = (const T *)(db.ptr() + index);
for (int i = 0; i < groupnum; i++)
{
if (minptr && minptr[i] <= minval)
{
if (minptr[i] == minval)
{
if (minlocptr)
minloc = std::min(minlocptr[i], minloc);
}
else
{
if (minlocptr)
minloc = minlocptr[i];
minval = minptr[i];
}
}
if (maxptr && maxptr[i] >= maxval)
{
if (maxptr[i] == maxval)
{
if (maxlocptr)
maxloc = std::min(maxlocptr[i], maxloc);
}
else
{
if (maxlocptr)
maxloc = maxlocptr[i];
maxval = maxptr[i];
}
}
if (maxptr2 && maxptr2[i] > maxval2)
maxval2 = maxptr2[i];
}
bool zero_mask = (minLoc && minloc == index_max) ||
(maxLoc && maxloc == index_max);
if (minVal)
*minVal = zero_mask ? 0 : (double)minval;
if (maxVal)
*maxVal = zero_mask ? 0 : (double)maxval;
if (maxVal2)
*maxVal2 = zero_mask ? 0 : (double)maxval2;
if (minLoc)
{
minLoc[0] = zero_mask ? -1 : minloc / cols;
minLoc[1] = zero_mask ? -1 : minloc % cols;
}
if (maxLoc)
{
maxLoc[0] = zero_mask ? -1 : maxloc / cols;
maxLoc[1] = zero_mask ? -1 : maxloc % cols;
}
}
typedef void (*getMinMaxResFunc)(const Mat & db, double * minVal, double * maxVal,
int * minLoc, int *maxLoc, int gropunum, int cols, double * maxVal2);
bool ocl_minMaxIdx( InputArray _src, double* minVal, double* maxVal, int* minLoc, int* maxLoc, InputArray _mask,
int ddepth, bool absValues, InputArray _src2, double * maxVal2)
{
const ocl::Device & dev = ocl::Device::getDefault();
#ifdef __ANDROID__
if (dev.isNVidia())
return false;
#endif
if (dev.deviceVersionMajor() == 1 && dev.deviceVersionMinor() < 2)
{
// 'static' storage class specifier used by "minmaxloc" is available from OpenCL 1.2+ only
return false;
}
bool doubleSupport = dev.doubleFPConfig() > 0, haveMask = !_mask.empty(),
haveSrc2 = _src2.kind() != _InputArray::NONE;
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type),
kercn = haveMask ? cn : std::min(4, ocl::predictOptimalVectorWidth(_src, _src2));
if (depth >= CV_16F)
return false;
// disabled following modes since it occasionally fails on AMD devices (e.g. A10-6800K, sep. 2014)
if ((haveMask || type == CV_32FC1) && dev.isAMD())
return false;
CV_Assert( (cn == 1 && (!haveMask || _mask.type() == CV_8U)) ||
(cn >= 1 && !minLoc && !maxLoc) );
if (ddepth < 0)
ddepth = depth;
CV_Assert(!haveSrc2 || _src2.type() == type);
if (depth == CV_32S)
return false;
if ((depth == CV_64F || ddepth == CV_64F) && !doubleSupport)
return false;
int groupnum = dev.maxComputeUnits();
size_t wgs = dev.maxWorkGroupSize();
int wgs2_aligned = 1;
while (wgs2_aligned < (int)wgs)
wgs2_aligned <<= 1;
wgs2_aligned >>= 1;
bool needMinVal = minVal || minLoc, needMinLoc = minLoc != NULL,
needMaxVal = maxVal || maxLoc, needMaxLoc = maxLoc != NULL;
// in case of mask we must know whether mask is filled with zeros or not
// so let's calculate min or max location, if it's undefined, so mask is zeros
if (!(needMaxLoc || needMinLoc) && haveMask)
{
if (needMinVal)
needMinLoc = true;
else
needMaxLoc = true;
}
char cvt[2][50];
String opts = format("-D DEPTH_%d -D srcT1=%s%s -D WGS=%d -D srcT=%s"
" -D WGS2_ALIGNED=%d%s%s%s -D kercn=%d%s%s%s%s"
" -D dstT1=%s -D dstT=%s -D convertToDT=%s%s%s%s%s -D wdepth=%d -D convertFromU=%s"
" -D MINMAX_STRUCT_ALIGNMENT=%d",
depth, ocl::typeToStr(depth), haveMask ? " -D HAVE_MASK" : "", (int)wgs,
ocl::typeToStr(CV_MAKE_TYPE(depth, kercn)), wgs2_aligned,
doubleSupport ? " -D DOUBLE_SUPPORT" : "",
_src.isContinuous() ? " -D HAVE_SRC_CONT" : "",
_mask.isContinuous() ? " -D HAVE_MASK_CONT" : "", kercn,
needMinVal ? " -D NEED_MINVAL" : "", needMaxVal ? " -D NEED_MAXVAL" : "",
needMinLoc ? " -D NEED_MINLOC" : "", needMaxLoc ? " -D NEED_MAXLOC" : "",
ocl::typeToStr(ddepth), ocl::typeToStr(CV_MAKE_TYPE(ddepth, kercn)),
ocl::convertTypeStr(depth, ddepth, kercn, cvt[0], sizeof(cvt[0])),
absValues ? " -D OP_ABS" : "",
haveSrc2 ? " -D HAVE_SRC2" : "", maxVal2 ? " -D OP_CALC2" : "",
haveSrc2 && _src2.isContinuous() ? " -D HAVE_SRC2_CONT" : "", ddepth,
depth <= CV_32S && ddepth == CV_32S ? ocl::convertTypeStr(CV_8U, ddepth, kercn, cvt[1], sizeof(cvt[1])) : "noconvert",
MINMAX_STRUCT_ALIGNMENT);
ocl::Kernel k("minmaxloc", ocl::core::minmaxloc_oclsrc, opts);
if (k.empty())
return false;
int esz = CV_ELEM_SIZE(ddepth), esz32s = CV_ELEM_SIZE1(CV_32S),
dbsize = groupnum * ((needMinVal ? esz : 0) + (needMaxVal ? esz : 0) +
(needMinLoc ? esz32s : 0) + (needMaxLoc ? esz32s : 0) +
(maxVal2 ? esz : 0))
+ 5 * MINMAX_STRUCT_ALIGNMENT;
UMat src = _src.getUMat(), src2 = _src2.getUMat(), db(1, dbsize, CV_8UC1), mask = _mask.getUMat();
if (cn > 1 && !haveMask)
{
src = src.reshape(1);
src2 = src2.reshape(1);
}
if (haveSrc2)
{
if (!haveMask)
k.args(ocl::KernelArg::ReadOnlyNoSize(src), src.cols, (int)src.total(),
groupnum, ocl::KernelArg::PtrWriteOnly(db), ocl::KernelArg::ReadOnlyNoSize(src2));
else
k.args(ocl::KernelArg::ReadOnlyNoSize(src), src.cols, (int)src.total(),
groupnum, ocl::KernelArg::PtrWriteOnly(db), ocl::KernelArg::ReadOnlyNoSize(mask),
ocl::KernelArg::ReadOnlyNoSize(src2));
}
else
{
if (!haveMask)
k.args(ocl::KernelArg::ReadOnlyNoSize(src), src.cols, (int)src.total(),
groupnum, ocl::KernelArg::PtrWriteOnly(db));
else
k.args(ocl::KernelArg::ReadOnlyNoSize(src), src.cols, (int)src.total(),
groupnum, ocl::KernelArg::PtrWriteOnly(db), ocl::KernelArg::ReadOnlyNoSize(mask));
}
size_t globalsize = groupnum * wgs;
if (!k.run(1, &globalsize, &wgs, true))
return false;
static const getMinMaxResFunc functab[7] =
{
getMinMaxRes<uchar>,
getMinMaxRes<char>,
getMinMaxRes<ushort>,
getMinMaxRes<short>,
getMinMaxRes<int>,
getMinMaxRes<float>,
getMinMaxRes<double>
};
CV_Assert(ddepth <= CV_64F);
getMinMaxResFunc func = functab[ddepth];
int locTemp[2];
func(db.getMat(ACCESS_READ), minVal, maxVal,
needMinLoc ? minLoc ? minLoc : locTemp : minLoc,
needMaxLoc ? maxLoc ? maxLoc : locTemp : maxLoc,
groupnum, src.cols, maxVal2);
return true;
}
#endif
#ifdef HAVE_OPENVX
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_MINMAXLOC>(int w, int h) { return w*h < 3840 * 2160; }
}
static bool openvx_minMaxIdx(Mat &src, double* minVal, double* maxVal, int* minIdx, int* maxIdx, Mat &mask)
{
int stype = src.type();
size_t total_size = src.total();
int rows = src.size[0], cols = rows ? (int)(total_size / rows) : 0;
if ((stype != CV_8UC1 && stype != CV_16SC1) || !mask.empty() ||
(src.dims != 2 && !(src.isContinuous() && cols > 0 && (size_t)rows*cols == total_size))
)
return false;
try
{
ivx::Context ctx = ovx::getOpenVXContext();
ivx::Image
ia = ivx::Image::createFromHandle(ctx, stype == CV_8UC1 ? VX_DF_IMAGE_U8 : VX_DF_IMAGE_S16,
ivx::Image::createAddressing(cols, rows, stype == CV_8UC1 ? 1 : 2, (vx_int32)(src.step[0])), src.ptr());
ivx::Scalar vxMinVal = ivx::Scalar::create(ctx, stype == CV_8UC1 ? VX_TYPE_UINT8 : VX_TYPE_INT16, 0);
ivx::Scalar vxMaxVal = ivx::Scalar::create(ctx, stype == CV_8UC1 ? VX_TYPE_UINT8 : VX_TYPE_INT16, 0);
ivx::Array vxMinInd, vxMaxInd;
ivx::Scalar vxMinCount, vxMaxCount;
if (minIdx)
{
vxMinInd = ivx::Array::create(ctx, VX_TYPE_COORDINATES2D, 1);
vxMinCount = ivx::Scalar::create(ctx, VX_TYPE_UINT32, 0);
}
if (maxIdx)
{
vxMaxInd = ivx::Array::create(ctx, VX_TYPE_COORDINATES2D, 1);
vxMaxCount = ivx::Scalar::create(ctx, VX_TYPE_UINT32, 0);
}
ivx::IVX_CHECK_STATUS(vxuMinMaxLoc(ctx, ia, vxMinVal, vxMaxVal, vxMinInd, vxMaxInd, vxMinCount, vxMaxCount));
if (minVal)
{
*minVal = stype == CV_8UC1 ? vxMinVal.getValue<vx_uint8>() : vxMinVal.getValue<vx_int16>();
}
if (maxVal)
{
*maxVal = stype == CV_8UC1 ? vxMaxVal.getValue<vx_uint8>() : vxMaxVal.getValue<vx_int16>();
}
if (minIdx)
{
if(vxMinCount.getValue<vx_uint32>()<1) throw ivx::RuntimeError(VX_ERROR_INVALID_VALUE, std::string(__func__) + "(): minimum value location not found");
vx_coordinates2d_t loc;
vxMinInd.copyRangeTo(0, 1, &loc);
size_t minidx = loc.y * cols + loc.x + 1;
ofs2idx(src, minidx, minIdx);
}
if (maxIdx)
{
if (vxMaxCount.getValue<vx_uint32>()<1) throw ivx::RuntimeError(VX_ERROR_INVALID_VALUE, std::string(__func__) + "(): maximum value location not found");
vx_coordinates2d_t loc;
vxMaxInd.copyRangeTo(0, 1, &loc);
size_t maxidx = loc.y * cols + loc.x + 1;
ofs2idx(src, maxidx, maxIdx);
}
}
catch (const ivx::RuntimeError & e)
{
VX_DbgThrow(e.what());
}
catch (const ivx::WrapperError & e)
{
VX_DbgThrow(e.what());
}
return true;
}
#endif
#ifdef HAVE_IPP
static IppStatus ipp_minMaxIndex_wrap(const void* pSrc, int srcStep, IppiSize size, IppDataType dataType,
float* pMinVal, float* pMaxVal, IppiPoint* pMinIndex, IppiPoint* pMaxIndex, const Ipp8u*, int)
{
switch(dataType)
{
case ipp8u: return CV_INSTRUMENT_FUN_IPP(ippiMinMaxIndx_8u_C1R, (const Ipp8u*)pSrc, srcStep, size, pMinVal, pMaxVal, pMinIndex, pMaxIndex);
case ipp16u: return CV_INSTRUMENT_FUN_IPP(ippiMinMaxIndx_16u_C1R, (const Ipp16u*)pSrc, srcStep, size, pMinVal, pMaxVal, pMinIndex, pMaxIndex);
case ipp32f: return CV_INSTRUMENT_FUN_IPP(ippiMinMaxIndx_32f_C1R, (const Ipp32f*)pSrc, srcStep, size, pMinVal, pMaxVal, pMinIndex, pMaxIndex);
default: return ippStsDataTypeErr;
}
}
static IppStatus ipp_minMaxIndexMask_wrap(const void* pSrc, int srcStep, IppiSize size, IppDataType dataType,
float* pMinVal, float* pMaxVal, IppiPoint* pMinIndex, IppiPoint* pMaxIndex, const Ipp8u* pMask, int maskStep)
{
switch(dataType)
{
case ipp8u: return CV_INSTRUMENT_FUN_IPP(ippiMinMaxIndx_8u_C1MR, (const Ipp8u*)pSrc, srcStep, pMask, maskStep, size, pMinVal, pMaxVal, pMinIndex, pMaxIndex);
case ipp16u: return CV_INSTRUMENT_FUN_IPP(ippiMinMaxIndx_16u_C1MR, (const Ipp16u*)pSrc, srcStep, pMask, maskStep, size, pMinVal, pMaxVal, pMinIndex, pMaxIndex);
case ipp32f: return CV_INSTRUMENT_FUN_IPP(ippiMinMaxIndx_32f_C1MR, (const Ipp32f*)pSrc, srcStep, pMask, maskStep, size, pMinVal, pMaxVal, pMinIndex, pMaxIndex);
default: return ippStsDataTypeErr;
}
}
static IppStatus ipp_minMax_wrap(const void* pSrc, int srcStep, IppiSize size, IppDataType dataType,
float* pMinVal, float* pMaxVal, IppiPoint*, IppiPoint*, const Ipp8u*, int)
{
IppStatus status;
switch(dataType)
{
#if IPP_VERSION_X100 > 201701 // wrong min values
case ipp8u:
{
Ipp8u val[2];
status = CV_INSTRUMENT_FUN_IPP(ippiMinMax_8u_C1R, (const Ipp8u*)pSrc, srcStep, size, &val[0], &val[1]);
*pMinVal = val[0];
*pMaxVal = val[1];
return status;
}
#endif
case ipp16u:
{
Ipp16u val[2];
status = CV_INSTRUMENT_FUN_IPP(ippiMinMax_16u_C1R, (const Ipp16u*)pSrc, srcStep, size, &val[0], &val[1]);
*pMinVal = val[0];
*pMaxVal = val[1];
return status;
}
case ipp16s:
{
Ipp16s val[2];
status = CV_INSTRUMENT_FUN_IPP(ippiMinMax_16s_C1R, (const Ipp16s*)pSrc, srcStep, size, &val[0], &val[1]);
*pMinVal = val[0];
*pMaxVal = val[1];
return status;
}
case ipp32f: return CV_INSTRUMENT_FUN_IPP(ippiMinMax_32f_C1R, (const Ipp32f*)pSrc, srcStep, size, pMinVal, pMaxVal);
default: return ipp_minMaxIndex_wrap(pSrc, srcStep, size, dataType, pMinVal, pMaxVal, NULL, NULL, NULL, 0);
}
}
static IppStatus ipp_minIdx_wrap(const void* pSrc, int srcStep, IppiSize size, IppDataType dataType,
float* pMinVal, float*, IppiPoint* pMinIndex, IppiPoint*, const Ipp8u*, int)
{
IppStatus status;
switch(dataType)
{
case ipp8u:
{
Ipp8u val;
status = CV_INSTRUMENT_FUN_IPP(ippiMinIndx_8u_C1R, (const Ipp8u*)pSrc, srcStep, size, &val, &pMinIndex->x, &pMinIndex->y);
*pMinVal = val;
return status;
}
case ipp16u:
{
Ipp16u val;
status = CV_INSTRUMENT_FUN_IPP(ippiMinIndx_16u_C1R, (const Ipp16u*)pSrc, srcStep, size, &val, &pMinIndex->x, &pMinIndex->y);
*pMinVal = val;
return status;
}
case ipp16s:
{
Ipp16s val;
status = CV_INSTRUMENT_FUN_IPP(ippiMinIndx_16s_C1R, (const Ipp16s*)pSrc, srcStep, size, &val, &pMinIndex->x, &pMinIndex->y);
*pMinVal = val;
return status;
}
case ipp32f: return CV_INSTRUMENT_FUN_IPP(ippiMinIndx_32f_C1R, (const Ipp32f*)pSrc, srcStep, size, pMinVal, &pMinIndex->x, &pMinIndex->y);
default: return ipp_minMaxIndex_wrap(pSrc, srcStep, size, dataType, pMinVal, NULL, pMinIndex, NULL, NULL, 0);
}
}
static IppStatus ipp_maxIdx_wrap(const void* pSrc, int srcStep, IppiSize size, IppDataType dataType,
float*, float* pMaxVal, IppiPoint*, IppiPoint* pMaxIndex, const Ipp8u*, int)
{
IppStatus status;
switch(dataType)
{
case ipp8u:
{
Ipp8u val;
status = CV_INSTRUMENT_FUN_IPP(ippiMaxIndx_8u_C1R, (const Ipp8u*)pSrc, srcStep, size, &val, &pMaxIndex->x, &pMaxIndex->y);
*pMaxVal = val;
return status;
}
case ipp16u:
{
Ipp16u val;
status = CV_INSTRUMENT_FUN_IPP(ippiMaxIndx_16u_C1R, (const Ipp16u*)pSrc, srcStep, size, &val, &pMaxIndex->x, &pMaxIndex->y);
*pMaxVal = val;
return status;
}
case ipp16s:
{
Ipp16s val;
status = CV_INSTRUMENT_FUN_IPP(ippiMaxIndx_16s_C1R, (const Ipp16s*)pSrc, srcStep, size, &val, &pMaxIndex->x, &pMaxIndex->y);
*pMaxVal = val;
return status;
}
case ipp32f: return CV_INSTRUMENT_FUN_IPP(ippiMaxIndx_32f_C1R, (const Ipp32f*)pSrc, srcStep, size, pMaxVal, &pMaxIndex->x, &pMaxIndex->y);
default: return ipp_minMaxIndex_wrap(pSrc, srcStep, size, dataType, NULL, pMaxVal, NULL, pMaxIndex, NULL, 0);
}
}
typedef IppStatus (*IppMinMaxSelector)(const void* pSrc, int srcStep, IppiSize size, IppDataType dataType,
float* pMinVal, float* pMaxVal, IppiPoint* pMinIndex, IppiPoint* pMaxIndex, const Ipp8u* pMask, int maskStep);
static bool ipp_minMaxIdx(Mat &src, double* _minVal, double* _maxVal, int* _minIdx, int* _maxIdx, Mat &mask)
{
#if IPP_VERSION_X100 >= 700
CV_INSTRUMENT_REGION_IPP();
#if IPP_VERSION_X100 < 201800
// cv::minMaxIdx problem with NaN input
// Disable 32F processing only
if(src.depth() == CV_32F && cv::ipp::getIppTopFeatures() == ippCPUID_SSE42)
return false;
#endif
#if IPP_VERSION_X100 < 201801
// cv::minMaxIdx problem with index positions on AVX
if(!mask.empty() && _maxIdx && cv::ipp::getIppTopFeatures() != ippCPUID_SSE42)
return false;
#endif
IppStatus status;
IppDataType dataType = ippiGetDataType(src.depth());
float minVal = 0;
float maxVal = 0;
IppiPoint minIdx = {-1, -1};
IppiPoint maxIdx = {-1, -1};
float *pMinVal = (_minVal || _minIdx)?&minVal:NULL;
float *pMaxVal = (_maxVal || _maxIdx)?&maxVal:NULL;
IppiPoint *pMinIdx = (_minIdx)?&minIdx:NULL;
IppiPoint *pMaxIdx = (_maxIdx)?&maxIdx:NULL;
IppMinMaxSelector ippMinMaxFun = ipp_minMaxIndexMask_wrap;
if(mask.empty())
{
if(_maxVal && _maxIdx && !_minVal && !_minIdx)
ippMinMaxFun = ipp_maxIdx_wrap;
else if(!_maxVal && !_maxIdx && _minVal && _minIdx)
ippMinMaxFun = ipp_minIdx_wrap;
else if(_maxVal && !_maxIdx && _minVal && !_minIdx)
ippMinMaxFun = ipp_minMax_wrap;
else if(!_maxVal && !_maxIdx && !_minVal && !_minIdx)
return false;
else
ippMinMaxFun = ipp_minMaxIndex_wrap;
}
if(src.dims <= 2)
{
IppiSize size = ippiSize(src.size());
#if defined(_WIN32) && !defined(_WIN64) && IPP_VERSION_X100 == 201900 && IPP_DISABLE_MINMAXIDX_MANY_ROWS
if (size.height > 65536)
return false; // test: Core_MinMaxIdx.rows_overflow
#endif
size.width *= src.channels();
status = ippMinMaxFun(src.ptr(), (int)src.step, size, dataType, pMinVal, pMaxVal, pMinIdx, pMaxIdx, (Ipp8u*)mask.ptr(), (int)mask.step);
if(status < 0)
return false;
if(_minVal)
*_minVal = minVal;
if(_maxVal)
*_maxVal = maxVal;
if(_minIdx)
{
#if IPP_VERSION_X100 < 201801
// Should be just ippStsNoOperation check, but there is a bug in the function so we need additional checks
if(status == ippStsNoOperation && !mask.empty() && !pMinIdx->x && !pMinIdx->y)
#else
if(status == ippStsNoOperation)
#endif
{
_minIdx[0] = -1;
_minIdx[1] = -1;
}
else
{
_minIdx[0] = minIdx.y;
_minIdx[1] = minIdx.x;
}
}
if(_maxIdx)
{
#if IPP_VERSION_X100 < 201801
// Should be just ippStsNoOperation check, but there is a bug in the function so we need additional checks
if(status == ippStsNoOperation && !mask.empty() && !pMaxIdx->x && !pMaxIdx->y)
#else
if(status == ippStsNoOperation)
#endif
{
_maxIdx[0] = -1;
_maxIdx[1] = -1;
}
else
{
_maxIdx[0] = maxIdx.y;
_maxIdx[1] = maxIdx.x;
}
}
}
else
{
const Mat *arrays[] = {&src, mask.empty()?NULL:&mask, NULL};
uchar *ptrs[3] = {NULL};
NAryMatIterator it(arrays, ptrs);
IppiSize size = ippiSize(it.size*src.channels(), 1);
int srcStep = (int)(size.width*src.elemSize1());
int maskStep = size.width;
size_t idxPos = 1;
size_t minIdxAll = 0;
size_t maxIdxAll = 0;
float minValAll = IPP_MAXABS_32F;
float maxValAll = -IPP_MAXABS_32F;
for(size_t i = 0; i < it.nplanes; i++, ++it, idxPos += size.width)
{
status = ippMinMaxFun(ptrs[0], srcStep, size, dataType, pMinVal, pMaxVal, pMinIdx, pMaxIdx, ptrs[1], maskStep);
if(status < 0)
return false;
#if IPP_VERSION_X100 > 201701
// Zero-mask check, function should return ippStsNoOperation warning
if(status == ippStsNoOperation)
continue;
#else
// Crude zero-mask check, waiting for fix in IPP function
if(ptrs[1])
{
Mat localMask(Size(size.width, 1), CV_8U, ptrs[1], maskStep);
if(!cv::countNonZero(localMask))
continue;
}
#endif
if(_minVal && minVal < minValAll)
{
minValAll = minVal;
minIdxAll = idxPos+minIdx.x;
}
if(_maxVal && maxVal > maxValAll)
{
maxValAll = maxVal;
maxIdxAll = idxPos+maxIdx.x;
}
}
if(!src.empty() && mask.empty())
{
if(minIdxAll == 0)
minIdxAll = 1;
if(maxValAll == 0)
maxValAll = 1;
}
if(_minVal)
*_minVal = minValAll;
if(_maxVal)
*_maxVal = maxValAll;
if(_minIdx)
ofs2idx(src, minIdxAll, _minIdx);
if(_maxIdx)
ofs2idx(src, maxIdxAll, _maxIdx);
}
return true;
#else
CV_UNUSED(src); CV_UNUSED(minVal); CV_UNUSED(maxVal); CV_UNUSED(minIdx); CV_UNUSED(maxIdx); CV_UNUSED(mask);
return false;
#endif
}
#endif
}
void cv::minMaxIdx(InputArray _src, double* minVal,
double* maxVal, int* minIdx, int* maxIdx,
InputArray _mask)
{
CV_INSTRUMENT_REGION();
int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
CV_Assert( (cn == 1 && (_mask.empty() || _mask.type() == CV_8U)) ||
(cn > 1 && _mask.empty() && !minIdx && !maxIdx) );
CV_OCL_RUN(OCL_PERFORMANCE_CHECK(_src.isUMat()) && _src.dims() <= 2 && (_mask.empty() || _src.size() == _mask.size()),
ocl_minMaxIdx(_src, minVal, maxVal, minIdx, maxIdx, _mask))
Mat src = _src.getMat(), mask = _mask.getMat();
if (src.dims <= 2)
CALL_HAL(minMaxIdx, cv_hal_minMaxIdx, src.data, src.step, src.cols, src.rows, src.depth(), minVal, maxVal,
minIdx, maxIdx, mask.data);
CV_OVX_RUN(!ovx::skipSmallImages<VX_KERNEL_MINMAXLOC>(src.cols, src.rows),
openvx_minMaxIdx(src, minVal, maxVal, minIdx, maxIdx, mask))
CV_IPP_RUN_FAST(ipp_minMaxIdx(src, minVal, maxVal, minIdx, maxIdx, mask))
MinMaxIdxFunc func = getMinmaxTab(depth);
CV_Assert( func != 0 );
const Mat* arrays[] = {&src, &mask, 0};
uchar* ptrs[2] = {};
NAryMatIterator it(arrays, ptrs);
size_t minidx = 0, maxidx = 0;
int iminval = INT_MAX, imaxval = INT_MIN;
float fminval = std::numeric_limits<float>::infinity(), fmaxval = -fminval;
double dminval = std::numeric_limits<double>::infinity(), dmaxval = -dminval;
size_t startidx = 1;
int *minval = &iminval, *maxval = &imaxval;
int planeSize = (int)it.size*cn;
if( depth == CV_32F )
minval = (int*)&fminval, maxval = (int*)&fmaxval;
else if( depth == CV_64F )
minval = (int*)&dminval, maxval = (int*)&dmaxval;
for( size_t i = 0; i < it.nplanes; i++, ++it, startidx += planeSize )
func( ptrs[0], ptrs[1], minval, maxval, &minidx, &maxidx, planeSize, startidx );
if (!src.empty() && mask.empty())
{
if( minidx == 0 )
minidx = 1;
if( maxidx == 0 )
maxidx = 1;
}
if( minidx == 0 )
dminval = dmaxval = 0;
else if( depth == CV_32F )
dminval = fminval, dmaxval = fmaxval;
else if( depth <= CV_32S )
dminval = iminval, dmaxval = imaxval;
if( minVal )
*minVal = dminval;
if( maxVal )
*maxVal = dmaxval;
if( minIdx )
ofs2idx(src, minidx, minIdx);
if( maxIdx )
ofs2idx(src, maxidx, maxIdx);
}
void cv::minMaxLoc( InputArray _img, double* minVal, double* maxVal,
Point* minLoc, Point* maxLoc, InputArray mask )
{
CV_INSTRUMENT_REGION();
int dims = _img.dims();
CV_CheckLE(dims, 2, "");
minMaxIdx(_img, minVal, maxVal, (int*)minLoc, (int*)maxLoc, mask);
if( minLoc )
{
if (dims == 2)
std::swap(minLoc->x, minLoc->y);
else
minLoc->y = 0;
}
if( maxLoc )
{
if (dims == 2)
std::swap(maxLoc->x, maxLoc->y);
else
maxLoc->y = 0;
}
}
enum class ReduceMode
{
FIRST_MIN = 0, //!< get index of first min occurrence
LAST_MIN = 1, //!< get index of last min occurrence
FIRST_MAX = 2, //!< get index of first max occurrence
LAST_MAX = 3, //!< get index of last max occurrence
};
template <typename T>
struct reduceMinMaxImpl
{
void operator()(const cv::Mat& src, cv::Mat& dst, ReduceMode mode, const int axis) const
{
switch(mode)
{
case ReduceMode::FIRST_MIN:
reduceMinMaxApply<std::less>(src, dst, axis);
break;
case ReduceMode::LAST_MIN:
reduceMinMaxApply<std::less_equal>(src, dst, axis);
break;
case ReduceMode::FIRST_MAX:
reduceMinMaxApply<std::greater>(src, dst, axis);
break;
case ReduceMode::LAST_MAX:
reduceMinMaxApply<std::greater_equal>(src, dst, axis);
break;
}
}
template <template<class> class Cmp>
static void reduceMinMaxApply(const cv::Mat& src, cv::Mat& dst, const int axis)
{
Cmp<T> cmp;
const auto *src_ptr = src.ptr<T>();
auto *dst_ptr = dst.ptr<int32_t>();
const size_t outer_size = src.total(0, axis);
const auto mid_size = static_cast<size_t>(src.size[axis]);
const size_t outer_step = src.total(axis);
const size_t dst_step = dst.total(axis);
const size_t mid_step = src.total(axis + 1);
for (size_t outer = 0; outer < outer_size; ++outer)
{
const size_t outer_offset = outer * outer_step;
const size_t dst_offset = outer * dst_step;
for (size_t mid = 0; mid != mid_size; ++mid)
{
const size_t src_offset = outer_offset + mid * mid_step;
for (size_t inner = 0; inner < mid_step; inner++)
{
int32_t& index = dst_ptr[dst_offset + inner];
const size_t prev = outer_offset + index * mid_step + inner;
const size_t curr = src_offset + inner;
if (cmp(src_ptr[curr], src_ptr[prev]))
{
index = static_cast<int32_t>(mid);
}
}
}
}
}
};
static void reduceMinMax(cv::InputArray src, cv::OutputArray dst, ReduceMode mode, int axis)
{
CV_INSTRUMENT_REGION();
cv::Mat srcMat = src.getMat();
axis = (axis + srcMat.dims) % srcMat.dims;
CV_Assert(srcMat.channels() == 1 && axis >= 0 && axis < srcMat.dims);
std::vector<int> sizes(srcMat.dims);
std::copy(srcMat.size.p, srcMat.size.p + srcMat.dims, sizes.begin());
sizes[axis] = 1;
dst.create(srcMat.dims, sizes.data(), CV_32SC1); // indices
cv::Mat dstMat = dst.getMat();
dstMat.setTo(cv::Scalar::all(0));
if (!srcMat.isContinuous())
{
srcMat = srcMat.clone();
}
bool needs_copy = !dstMat.isContinuous();
if (needs_copy)
{
dstMat = dstMat.clone();
}
cv::detail::depthDispatch<reduceMinMaxImpl>(srcMat.depth(), srcMat, dstMat, mode, axis);
if (needs_copy)
{
dstMat.copyTo(dst);
}
}
void cv::reduceArgMin(InputArray src, OutputArray dst, int axis, bool lastIndex)
{
reduceMinMax(src, dst, lastIndex ? ReduceMode::LAST_MIN : ReduceMode::FIRST_MIN, axis);
}
void cv::reduceArgMax(InputArray src, OutputArray dst, int axis, bool lastIndex)
{
reduceMinMax(src, dst, lastIndex ? ReduceMode::LAST_MAX : ReduceMode::FIRST_MAX, axis);
}