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Commit 5a01227a authored by Alexander Alekhin's avatar Alexander Alekhin
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imgproc: dispatch box_filter

parent ce3c92eb
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Showing with 77 additions and 1777 deletions
modules/imgproc/CMakeLists.txt
View file @ 5a01227a
set(the_description "Image Processing")
ocv_add_dispatched_file(accum SSE4_1 AVX AVX2)
ocv_add_dispatched_file(bilateral_filter SSE2 AVX2)
ocv_add_dispatched_file(box_filter SSE2 SSE4_1 AVX2)
ocv_add_dispatched_file(filter SSE2 SSE4_1 AVX2)
ocv_add_dispatched_file(color_hsv SSE2 SSE4_1 AVX2)
ocv_add_dispatched_file(color_rgb SSE2 SSE4_1 AVX2)
......
modules/imgproc/src/box_filter.dispatch.cpp
View file @ 5a01227a
......@@ -50,1119 +50,11 @@
#include "opencv2/core/openvx/ovx_defs.hpp"
namespace cv
{
/****************************************************************************************\
Box Filter
\****************************************************************************************/
template<typename T, typename ST>
struct RowSum :
public BaseRowFilter
{
RowSum( int _ksize, int _anchor ) :
BaseRowFilter()
{
ksize = _ksize;
anchor = _anchor;
}
virtual void operator()(const uchar* src, uchar* dst, int width, int cn) CV_OVERRIDE
{
const T* S = (const T*)src;
ST* D = (ST*)dst;
int i = 0, k, ksz_cn = ksize*cn;
width = (width - 1)*cn;
if( ksize == 3 )
{
for( i = 0; i < width + cn; i++ )
{
D[i] = (ST)S[i] + (ST)S[i+cn] + (ST)S[i+cn*2];
}
}
else if( ksize == 5 )
{
for( i = 0; i < width + cn; i++ )
{
D[i] = (ST)S[i] + (ST)S[i+cn] + (ST)S[i+cn*2] + (ST)S[i + cn*3] + (ST)S[i + cn*4];
}
}
else if( cn == 1 )
{
ST s = 0;
for( i = 0; i < ksz_cn; i++ )
s += (ST)S[i];
D[0] = s;
for( i = 0; i < width; i++ )
{
s += (ST)S[i + ksz_cn] - (ST)S[i];
D[i+1] = s;
}
}
else if( cn == 3 )
{
ST s0 = 0, s1 = 0, s2 = 0;
for( i = 0; i < ksz_cn; i += 3 )
{
s0 += (ST)S[i];
s1 += (ST)S[i+1];
s2 += (ST)S[i+2];
}
D[0] = s0;
D[1] = s1;
D[2] = s2;
for( i = 0; i < width; i += 3 )
{
s0 += (ST)S[i + ksz_cn] - (ST)S[i];
s1 += (ST)S[i + ksz_cn + 1] - (ST)S[i + 1];
s2 += (ST)S[i + ksz_cn + 2] - (ST)S[i + 2];
D[i+3] = s0;
D[i+4] = s1;
D[i+5] = s2;
}
}
else if( cn == 4 )
{
ST s0 = 0, s1 = 0, s2 = 0, s3 = 0;
for( i = 0; i < ksz_cn; i += 4 )
{
s0 += (ST)S[i];
s1 += (ST)S[i+1];
s2 += (ST)S[i+2];
s3 += (ST)S[i+3];
}
D[0] = s0;
D[1] = s1;
D[2] = s2;
D[3] = s3;
for( i = 0; i < width; i += 4 )
{
s0 += (ST)S[i + ksz_cn] - (ST)S[i];
s1 += (ST)S[i + ksz_cn + 1] - (ST)S[i + 1];
s2 += (ST)S[i + ksz_cn + 2] - (ST)S[i + 2];
s3 += (ST)S[i + ksz_cn + 3] - (ST)S[i + 3];
D[i+4] = s0;
D[i+5] = s1;
D[i+6] = s2;
D[i+7] = s3;
}
}
else
for( k = 0; k < cn; k++, S++, D++ )
{
ST s = 0;
for( i = 0; i < ksz_cn; i += cn )
s += (ST)S[i];
D[0] = s;
for( i = 0; i < width; i += cn )
{
s += (ST)S[i + ksz_cn] - (ST)S[i];
D[i+cn] = s;
}
}
}
};
template<typename ST, typename T>
struct ColumnSum :
public BaseColumnFilter
{
ColumnSum( int _ksize, int _anchor, double _scale ) :
BaseColumnFilter()
{
ksize = _ksize;
anchor = _anchor;
scale = _scale;
sumCount = 0;
}
virtual void reset() CV_OVERRIDE { sumCount = 0; }
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
int i;
ST* SUM;
bool haveScale = scale != 1;
double _scale = scale;
if( width != (int)sum.size() )
{
sum.resize(width);
sumCount = 0;
}
SUM = &sum[0];
if( sumCount == 0 )
{
memset((void*)SUM, 0, width*sizeof(ST));
for( ; sumCount < ksize - 1; sumCount++, src++ )
{
const ST* Sp = (const ST*)src[0];
for( i = 0; i < width; i++ )
SUM[i] += Sp[i];
}
}
else
{
CV_Assert( sumCount == ksize-1 );
src += ksize-1;
}
for( ; count--; src++ )
{
const ST* Sp = (const ST*)src[0];
const ST* Sm = (const ST*)src[1-ksize];
T* D = (T*)dst;
if( haveScale )
{
for( i = 0; i <= width - 2; i += 2 )
{
ST s0 = SUM[i] + Sp[i], s1 = SUM[i+1] + Sp[i+1];
D[i] = saturate_cast<T>(s0*_scale);
D[i+1] = saturate_cast<T>(s1*_scale);
s0 -= Sm[i]; s1 -= Sm[i+1];
SUM[i] = s0; SUM[i+1] = s1;
}
for( ; i < width; i++ )
{
ST s0 = SUM[i] + Sp[i];
D[i] = saturate_cast<T>(s0*_scale);
SUM[i] = s0 - Sm[i];
}
}
else
{
for( i = 0; i <= width - 2; i += 2 )
{
ST s0 = SUM[i] + Sp[i], s1 = SUM[i+1] + Sp[i+1];
D[i] = saturate_cast<T>(s0);
D[i+1] = saturate_cast<T>(s1);
s0 -= Sm[i]; s1 -= Sm[i+1];
SUM[i] = s0; SUM[i+1] = s1;
}
for( ; i < width; i++ )
{
ST s0 = SUM[i] + Sp[i];
D[i] = saturate_cast<T>(s0);
SUM[i] = s0 - Sm[i];
}
}
dst += dststep;
}
}
double scale;
int sumCount;
std::vector<ST> sum;
};
template<>
struct ColumnSum<int, uchar> :
public BaseColumnFilter
{
ColumnSum( int _ksize, int _anchor, double _scale ) :
BaseColumnFilter()
{
ksize = _ksize;
anchor = _anchor;
scale = _scale;
sumCount = 0;
}
virtual void reset() CV_OVERRIDE { sumCount = 0; }
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
if( width != (int)sum.size() )
{
sum.resize(width);
sumCount = 0;
}
SUM = &sum[0];
if( sumCount == 0 )
{
memset((void*)SUM, 0, width*sizeof(int));
for( ; sumCount < ksize - 1; sumCount++, src++ )
{
const int* Sp = (const int*)src[0];
int i = 0;
#if CV_SIMD
for (; i <= width - v_int32::nlanes; i += v_int32::nlanes)
{
v_store(SUM + i, vx_load(SUM + i) + vx_load(Sp + i));
}
#if CV_SIMD_WIDTH > 16
for (; i <= width - v_int32x4::nlanes; i += v_int32x4::nlanes)
{
v_store(SUM + i, v_load(SUM + i) + v_load(Sp + i));
}
#endif
#endif
for( ; i < width; i++ )
SUM[i] += Sp[i];
}
}
else
{
CV_Assert( sumCount == ksize-1 );
src += ksize-1;
}
for( ; count--; src++ )
{
const int* Sp = (const int*)src[0];
const int* Sm = (const int*)src[1-ksize];
uchar* D = (uchar*)dst;
if( haveScale )
{
int i = 0;
#if CV_SIMD
v_float32 _v_scale = vx_setall_f32((float)_scale);
for( ; i <= width - v_uint16::nlanes; i += v_uint16::nlanes )
{
v_int32 v_s0 = vx_load(SUM + i) + vx_load(Sp + i);
v_int32 v_s01 = vx_load(SUM + i + v_int32::nlanes) + vx_load(Sp + i + v_int32::nlanes);
v_uint32 v_s0d = v_reinterpret_as_u32(v_round(v_cvt_f32(v_s0) * _v_scale));
v_uint32 v_s01d = v_reinterpret_as_u32(v_round(v_cvt_f32(v_s01) * _v_scale));
v_uint16 v_dst = v_pack(v_s0d, v_s01d);
v_pack_store(D + i, v_dst);
v_store(SUM + i, v_s0 - vx_load(Sm + i));
v_store(SUM + i + v_int32::nlanes, v_s01 - vx_load(Sm + i + v_int32::nlanes));
}
#if CV_SIMD_WIDTH > 16
v_float32x4 v_scale = v_setall_f32((float)_scale);
for( ; i <= width-v_uint16x8::nlanes; i+=v_uint16x8::nlanes )
{
v_int32x4 v_s0 = v_load(SUM + i) + v_load(Sp + i);
v_int32x4 v_s01 = v_load(SUM + i + v_int32x4::nlanes) + v_load(Sp + i + v_int32x4::nlanes);
v_uint32x4 v_s0d = v_reinterpret_as_u32(v_round(v_cvt_f32(v_s0) * v_scale));
v_uint32x4 v_s01d = v_reinterpret_as_u32(v_round(v_cvt_f32(v_s01) * v_scale));
v_uint16x8 v_dst = v_pack(v_s0d, v_s01d);
v_pack_store(D + i, v_dst);
v_store(SUM + i, v_s0 - v_load(Sm + i));
v_store(SUM + i + v_int32x4::nlanes, v_s01 - v_load(Sm + i + v_int32x4::nlanes));
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = saturate_cast<uchar>(s0*_scale);
SUM[i] = s0 - Sm[i];
}
}
else
{
int i = 0;
#if CV_SIMD
for( ; i <= width-v_uint16::nlanes; i+=v_uint16::nlanes )
{
v_int32 v_s0 = vx_load(SUM + i) + vx_load(Sp + i);
v_int32 v_s01 = vx_load(SUM + i + v_int32::nlanes) + vx_load(Sp + i + v_int32::nlanes);
v_uint16 v_dst = v_pack(v_reinterpret_as_u32(v_s0), v_reinterpret_as_u32(v_s01));
v_pack_store(D + i, v_dst);
v_store(SUM + i, v_s0 - vx_load(Sm + i));
v_store(SUM + i + v_int32::nlanes, v_s01 - vx_load(Sm + i + v_int32::nlanes));
}
#if CV_SIMD_WIDTH > 16
for( ; i <= width-v_uint16x8::nlanes; i+=v_uint16x8::nlanes )
{
v_int32x4 v_s0 = v_load(SUM + i) + v_load(Sp + i);
v_int32x4 v_s01 = v_load(SUM + i + v_int32x4::nlanes) + v_load(Sp + i + v_int32x4::nlanes);
v_uint16x8 v_dst = v_pack(v_reinterpret_as_u32(v_s0), v_reinterpret_as_u32(v_s01));
v_pack_store(D + i, v_dst);
v_store(SUM + i, v_s0 - v_load(Sm + i));
v_store(SUM + i + v_int32x4::nlanes, v_s01 - v_load(Sm + i + v_int32x4::nlanes));
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = saturate_cast<uchar>(s0);
SUM[i] = s0 - Sm[i];
}
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
int sumCount;
std::vector<int> sum;
};
template<>
struct ColumnSum<ushort, uchar> :
public BaseColumnFilter
{
enum { SHIFT = 23 };
ColumnSum( int _ksize, int _anchor, double _scale ) :
BaseColumnFilter()
{
ksize = _ksize;
anchor = _anchor;
scale = _scale;
sumCount = 0;
divDelta = 0;
divScale = 1;
if( scale != 1 )
{
int d = cvRound(1./scale);
double scalef = ((double)(1 << SHIFT))/d;
divScale = cvFloor(scalef);
scalef -= divScale;
divDelta = d/2;
if( scalef < 0.5 )
divDelta++;
else
divScale++;
}
}
virtual void reset() CV_OVERRIDE { sumCount = 0; }
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
const int ds = divScale;
const int dd = divDelta;
ushort* SUM;
const bool haveScale = scale != 1;
if( width != (int)sum.size() )
{
sum.resize(width);
sumCount = 0;
}
SUM = &sum[0];
if( sumCount == 0 )
{
memset((void*)SUM, 0, width*sizeof(SUM[0]));
for( ; sumCount < ksize - 1; sumCount++, src++ )
{
const ushort* Sp = (const ushort*)src[0];
int i = 0;
#if CV_SIMD
for( ; i <= width - v_uint16::nlanes; i += v_uint16::nlanes )
{
v_store(SUM + i, vx_load(SUM + i) + vx_load(Sp + i));
}
#if CV_SIMD_WIDTH > 16
for( ; i <= width - v_uint16x8::nlanes; i += v_uint16x8::nlanes )
{
v_store(SUM + i, v_load(SUM + i) + v_load(Sp + i));
}
#endif
#endif
for( ; i < width; i++ )
SUM[i] += Sp[i];
}
}
else
{
CV_Assert( sumCount == ksize-1 );
src += ksize-1;
}
for( ; count--; src++ )
{
const ushort* Sp = (const ushort*)src[0];
const ushort* Sm = (const ushort*)src[1-ksize];
uchar* D = (uchar*)dst;
if( haveScale )
{
int i = 0;
#if CV_SIMD
v_uint32 _ds4 = vx_setall_u32((unsigned)ds);
v_uint16 _dd8 = vx_setall_u16((ushort)dd);
for( ; i <= width-v_uint8::nlanes; i+=v_uint8::nlanes )
{
v_uint16 _sm0 = vx_load(Sm + i);
v_uint16 _sm1 = vx_load(Sm + i + v_uint16::nlanes);
v_uint16 _s0 = v_add_wrap(vx_load(SUM + i), vx_load(Sp + i));
v_uint16 _s1 = v_add_wrap(vx_load(SUM + i + v_uint16::nlanes), vx_load(Sp + i + v_uint16::nlanes));
v_uint32 _s00, _s01, _s10, _s11;
v_expand(_s0 + _dd8, _s00, _s01);
v_expand(_s1 + _dd8, _s10, _s11);
_s00 = v_shr<SHIFT>(_s00*_ds4);
_s01 = v_shr<SHIFT>(_s01*_ds4);
_s10 = v_shr<SHIFT>(_s10*_ds4);
_s11 = v_shr<SHIFT>(_s11*_ds4);
v_int16 r0 = v_pack(v_reinterpret_as_s32(_s00), v_reinterpret_as_s32(_s01));
v_int16 r1 = v_pack(v_reinterpret_as_s32(_s10), v_reinterpret_as_s32(_s11));
_s0 = v_sub_wrap(_s0, _sm0);
_s1 = v_sub_wrap(_s1, _sm1);
v_store(D + i, v_pack_u(r0, r1));
v_store(SUM + i, _s0);
v_store(SUM + i + v_uint16::nlanes, _s1);
}
#if CV_SIMD_WIDTH > 16
v_uint32x4 ds4 = v_setall_u32((unsigned)ds);
v_uint16x8 dd8 = v_setall_u16((ushort)dd);
for( ; i <= width-v_uint8x16::nlanes; i+=v_uint8x16::nlanes )
{
v_uint16x8 _sm0 = v_load(Sm + i);
v_uint16x8 _sm1 = v_load(Sm + i + v_uint16x8::nlanes);
v_uint16x8 _s0 = v_add_wrap(v_load(SUM + i), v_load(Sp + i));
v_uint16x8 _s1 = v_add_wrap(v_load(SUM + i + v_uint16x8::nlanes), v_load(Sp + i + v_uint16x8::nlanes));
v_uint32x4 _s00, _s01, _s10, _s11;
v_expand(_s0 + dd8, _s00, _s01);
v_expand(_s1 + dd8, _s10, _s11);
_s00 = v_shr<SHIFT>(_s00*ds4);
_s01 = v_shr<SHIFT>(_s01*ds4);
_s10 = v_shr<SHIFT>(_s10*ds4);
_s11 = v_shr<SHIFT>(_s11*ds4);
v_int16x8 r0 = v_pack(v_reinterpret_as_s32(_s00), v_reinterpret_as_s32(_s01));
v_int16x8 r1 = v_pack(v_reinterpret_as_s32(_s10), v_reinterpret_as_s32(_s11));
_s0 = v_sub_wrap(_s0, _sm0);
_s1 = v_sub_wrap(_s1, _sm1);
v_store(D + i, v_pack_u(r0, r1));
v_store(SUM + i, _s0);
v_store(SUM + i + v_uint16x8::nlanes, _s1);
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = (uchar)((s0 + dd)*ds >> SHIFT);
SUM[i] = (ushort)(s0 - Sm[i]);
}
}
else
{
int i = 0;
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = saturate_cast<uchar>(s0);
SUM[i] = (ushort)(s0 - Sm[i]);
}
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
int sumCount;
int divDelta;
int divScale;
std::vector<ushort> sum;
};
template<>
struct ColumnSum<int, short> :
public BaseColumnFilter
{
ColumnSum( int _ksize, int _anchor, double _scale ) :
BaseColumnFilter()
{
ksize = _ksize;
anchor = _anchor;
scale = _scale;
sumCount = 0;
}
virtual void reset() CV_OVERRIDE { sumCount = 0; }
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
int i;
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
if( width != (int)sum.size() )
{
sum.resize(width);
sumCount = 0;
}
SUM = &sum[0];
if( sumCount == 0 )
{
memset((void*)SUM, 0, width*sizeof(int));
for( ; sumCount < ksize - 1; sumCount++, src++ )
{
const int* Sp = (const int*)src[0];
i = 0;
#if CV_SIMD
for( ; i <= width - v_int32::nlanes; i+=v_int32::nlanes )
{
v_store(SUM + i, vx_load(SUM + i) + vx_load(Sp + i));
}
#if CV_SIMD_WIDTH > 16
for( ; i <= width - v_int32x4::nlanes; i+=v_int32x4::nlanes )
{
v_store(SUM + i, v_load(SUM + i) + v_load(Sp + i));
}
#endif
#endif
for( ; i < width; i++ )
SUM[i] += Sp[i];
}
}
else
{
CV_Assert( sumCount == ksize-1 );
src += ksize-1;
}
#include "box_filter.simd.hpp"
#include "box_filter.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
for( ; count--; src++ )
{
const int* Sp = (const int*)src[0];
const int* Sm = (const int*)src[1-ksize];
short* D = (short*)dst;
if( haveScale )
{
i = 0;
#if CV_SIMD
v_float32 _v_scale = vx_setall_f32((float)_scale);
for( ; i <= width-v_int16::nlanes; i+=v_int16::nlanes )
{
v_int32 v_s0 = vx_load(SUM + i) + vx_load(Sp + i);
v_int32 v_s01 = vx_load(SUM + i + v_int32::nlanes) + vx_load(Sp + i + v_int32::nlanes);
v_int32 v_s0d = v_round(v_cvt_f32(v_s0) * _v_scale);
v_int32 v_s01d = v_round(v_cvt_f32(v_s01) * _v_scale);
v_store(D + i, v_pack(v_s0d, v_s01d));
v_store(SUM + i, v_s0 - vx_load(Sm + i));
v_store(SUM + i + v_int32::nlanes, v_s01 - vx_load(Sm + i + v_int32::nlanes));
}
#if CV_SIMD_WIDTH > 16
v_float32x4 v_scale = v_setall_f32((float)_scale);
for( ; i <= width-v_int16x8::nlanes; i+=v_int16x8::nlanes )
{
v_int32x4 v_s0 = v_load(SUM + i) + v_load(Sp + i);
v_int32x4 v_s01 = v_load(SUM + i + v_int32x4::nlanes) + v_load(Sp + i + v_int32x4::nlanes);
v_int32x4 v_s0d = v_round(v_cvt_f32(v_s0) * v_scale);
v_int32x4 v_s01d = v_round(v_cvt_f32(v_s01) * v_scale);
v_store(D + i, v_pack(v_s0d, v_s01d));
v_store(SUM + i, v_s0 - v_load(Sm + i));
v_store(SUM + i + v_int32x4::nlanes, v_s01 - v_load(Sm + i + v_int32x4::nlanes));
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = saturate_cast<short>(s0*_scale);
SUM[i] = s0 - Sm[i];
}
}
else
{
i = 0;
#if CV_SIMD
for( ; i <= width-v_int16::nlanes; i+=v_int16::nlanes )
{
v_int32 v_s0 = vx_load(SUM + i) + vx_load(Sp + i);
v_int32 v_s01 = vx_load(SUM + i + v_int32::nlanes) + vx_load(Sp + i + v_int32::nlanes);
v_store(D + i, v_pack(v_s0, v_s01));
v_store(SUM + i, v_s0 - vx_load(Sm + i));
v_store(SUM + i + v_int32::nlanes, v_s01 - vx_load(Sm + i + v_int32::nlanes));
}
#if CV_SIMD_WIDTH > 16
for( ; i <= width-v_int16x8::nlanes; i+=v_int16x8::nlanes )
{
v_int32x4 v_s0 = v_load(SUM + i) + v_load(Sp + i);
v_int32x4 v_s01 = v_load(SUM + i + v_int32x4::nlanes) + v_load(Sp + i + v_int32x4::nlanes);
v_store(D + i, v_pack(v_s0, v_s01));
v_store(SUM + i, v_s0 - v_load(Sm + i));
v_store(SUM + i + v_int32x4::nlanes, v_s01 - v_load(Sm + i + v_int32x4::nlanes));
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = saturate_cast<short>(s0);
SUM[i] = s0 - Sm[i];
}
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
int sumCount;
std::vector<int> sum;
};
template<>
struct ColumnSum<int, ushort> :
public BaseColumnFilter
{
ColumnSum( int _ksize, int _anchor, double _scale ) :
BaseColumnFilter()
{
ksize = _ksize;
anchor = _anchor;
scale = _scale;
sumCount = 0;
}
virtual void reset() CV_OVERRIDE { sumCount = 0; }
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
if( width != (int)sum.size() )
{
sum.resize(width);
sumCount = 0;
}
SUM = &sum[0];
if( sumCount == 0 )
{
memset((void*)SUM, 0, width*sizeof(int));
for( ; sumCount < ksize - 1; sumCount++, src++ )
{
const int* Sp = (const int*)src[0];
int i = 0;
#if CV_SIMD
for (; i <= width - v_int32::nlanes; i += v_int32::nlanes)
{
v_store(SUM + i, vx_load(SUM + i) + vx_load(Sp + i));
}
#if CV_SIMD_WIDTH > 16
for (; i <= width - v_int32x4::nlanes; i += v_int32x4::nlanes)
{
v_store(SUM + i, v_load(SUM + i) + v_load(Sp + i));
}
#endif
#endif
for( ; i < width; i++ )
SUM[i] += Sp[i];
}
}
else
{
CV_Assert( sumCount == ksize-1 );
src += ksize-1;
}
for( ; count--; src++ )
{
const int* Sp = (const int*)src[0];
const int* Sm = (const int*)src[1-ksize];
ushort* D = (ushort*)dst;
if( haveScale )
{
int i = 0;
#if CV_SIMD
v_float32 _v_scale = vx_setall_f32((float)_scale);
for( ; i <= width-v_uint16::nlanes; i+=v_uint16::nlanes )
{
v_int32 v_s0 = vx_load(SUM + i) + vx_load(Sp + i);
v_int32 v_s01 = vx_load(SUM + i + v_int32::nlanes) + vx_load(Sp + i + v_int32::nlanes);
v_uint32 v_s0d = v_reinterpret_as_u32(v_round(v_cvt_f32(v_s0) * _v_scale));
v_uint32 v_s01d = v_reinterpret_as_u32(v_round(v_cvt_f32(v_s01) * _v_scale));
v_store(D + i, v_pack(v_s0d, v_s01d));
v_store(SUM + i, v_s0 - vx_load(Sm + i));
v_store(SUM + i + v_int32::nlanes, v_s01 - vx_load(Sm + i + v_int32::nlanes));
}
#if CV_SIMD_WIDTH > 16
v_float32x4 v_scale = v_setall_f32((float)_scale);
for( ; i <= width-v_uint16x8::nlanes; i+=v_uint16x8::nlanes )
{
v_int32x4 v_s0 = v_load(SUM + i) + v_load(Sp + i);
v_int32x4 v_s01 = v_load(SUM + i + v_int32x4::nlanes) + v_load(Sp + i + v_int32x4::nlanes);
v_uint32x4 v_s0d = v_reinterpret_as_u32(v_round(v_cvt_f32(v_s0) * v_scale));
v_uint32x4 v_s01d = v_reinterpret_as_u32(v_round(v_cvt_f32(v_s01) * v_scale));
v_store(D + i, v_pack(v_s0d, v_s01d));
v_store(SUM + i, v_s0 - v_load(Sm + i));
v_store(SUM + i + v_int32x4::nlanes, v_s01 - v_load(Sm + i + v_int32x4::nlanes));
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = saturate_cast<ushort>(s0*_scale);
SUM[i] = s0 - Sm[i];
}
}
else
{
int i = 0;
#if CV_SIMD
for( ; i <= width-v_uint16::nlanes; i+=v_uint16::nlanes )
{
v_int32 v_s0 = vx_load(SUM + i) + vx_load(Sp + i);
v_int32 v_s01 = vx_load(SUM + i + v_int32::nlanes) + vx_load(Sp + i + v_int32::nlanes);
v_store(D + i, v_pack(v_reinterpret_as_u32(v_s0), v_reinterpret_as_u32(v_s01)));
v_store(SUM + i, v_s0 - vx_load(Sm + i));
v_store(SUM + i + v_int32::nlanes, v_s01 - vx_load(Sm + i + v_int32::nlanes));
}
#if CV_SIMD_WIDTH > 16
for( ; i <= width-v_uint16x8::nlanes; i+=v_uint16x8::nlanes )
{
v_int32x4 v_s0 = v_load(SUM + i) + v_load(Sp + i);
v_int32x4 v_s01 = v_load(SUM + i + v_int32x4::nlanes) + v_load(Sp + i + v_int32x4::nlanes);
v_store(D + i, v_pack(v_reinterpret_as_u32(v_s0), v_reinterpret_as_u32(v_s01)));
v_store(SUM + i, v_s0 - v_load(Sm + i));
v_store(SUM + i + v_int32x4::nlanes, v_s01 - v_load(Sm + i + v_int32x4::nlanes));
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = saturate_cast<ushort>(s0);
SUM[i] = s0 - Sm[i];
}
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
int sumCount;
std::vector<int> sum;
};
template<>
struct ColumnSum<int, int> :
public BaseColumnFilter
{
ColumnSum( int _ksize, int _anchor, double _scale ) :
BaseColumnFilter()
{
ksize = _ksize;
anchor = _anchor;
scale = _scale;
sumCount = 0;
}
virtual void reset() CV_OVERRIDE { sumCount = 0; }
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
if( width != (int)sum.size() )
{
sum.resize(width);
sumCount = 0;
}
SUM = &sum[0];
if( sumCount == 0 )
{
memset((void*)SUM, 0, width*sizeof(int));
for( ; sumCount < ksize - 1; sumCount++, src++ )
{
const int* Sp = (const int*)src[0];
int i = 0;
#if CV_SIMD
for( ; i <= width - v_int32::nlanes; i+=v_int32::nlanes )
{
v_store(SUM + i, vx_load(SUM + i) + vx_load(Sp + i));
}
#if CV_SIMD_WIDTH > 16
for( ; i <= width - v_int32x4::nlanes; i+=v_int32x4::nlanes )
{
v_store(SUM + i, v_load(SUM + i) + v_load(Sp + i));
}
#endif
#endif
for( ; i < width; i++ )
SUM[i] += Sp[i];
}
}
else
{
CV_Assert( sumCount == ksize-1 );
src += ksize-1;
}
for( ; count--; src++ )
{
const int* Sp = (const int*)src[0];
const int* Sm = (const int*)src[1-ksize];
int* D = (int*)dst;
if( haveScale )
{
int i = 0;
#if CV_SIMD
v_float32 _v_scale = vx_setall_f32((float)_scale);
for( ; i <= width-v_int32::nlanes; i+=v_int32::nlanes )
{
v_int32 v_s0 = vx_load(SUM + i) + vx_load(Sp + i);
v_int32 v_s0d = v_round(v_cvt_f32(v_s0) * _v_scale);
v_store(D + i, v_s0d);
v_store(SUM + i, v_s0 - vx_load(Sm + i));
}
#if CV_SIMD_WIDTH > 16
v_float32x4 v_scale = v_setall_f32((float)_scale);
for( ; i <= width-v_int32x4::nlanes; i+=v_int32x4::nlanes )
{
v_int32x4 v_s0 = v_load(SUM + i) + v_load(Sp + i);
v_int32x4 v_s0d = v_round(v_cvt_f32(v_s0) * v_scale);
v_store(D + i, v_s0d);
v_store(SUM + i, v_s0 - v_load(Sm + i));
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = saturate_cast<int>(s0*_scale);
SUM[i] = s0 - Sm[i];
}
}
else
{
int i = 0;
#if CV_SIMD
for( ; i <= width-v_int32::nlanes; i+=v_int32::nlanes )
{
v_int32 v_s0 = vx_load(SUM + i) + vx_load(Sp + i);
v_store(D + i, v_s0);
v_store(SUM + i, v_s0 - vx_load(Sm + i));
}
#if CV_SIMD_WIDTH > 16
for( ; i <= width-v_int32x4::nlanes; i+=v_int32x4::nlanes )
{
v_int32x4 v_s0 = v_load(SUM + i) + v_load(Sp + i);
v_store(D + i, v_s0);
v_store(SUM + i, v_s0 - v_load(Sm + i));
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = s0;
SUM[i] = s0 - Sm[i];
}
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
int sumCount;
std::vector<int> sum;
};
template<>
struct ColumnSum<int, float> :
public BaseColumnFilter
{
ColumnSum( int _ksize, int _anchor, double _scale ) :
BaseColumnFilter()
{
ksize = _ksize;
anchor = _anchor;
scale = _scale;
sumCount = 0;
}
virtual void reset() CV_OVERRIDE { sumCount = 0; }
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
if( width != (int)sum.size() )
{
sum.resize(width);
sumCount = 0;
}
SUM = &sum[0];
if( sumCount == 0 )
{
memset((void*)SUM, 0, width*sizeof(int));
for( ; sumCount < ksize - 1; sumCount++, src++ )
{
const int* Sp = (const int*)src[0];
int i = 0;
#if CV_SIMD
for( ; i <= width - v_int32::nlanes; i+=v_int32::nlanes )
{
v_store(SUM + i, vx_load(SUM + i) + vx_load(Sp + i));
}
#if CV_SIMD_WIDTH > 16
for( ; i <= width - v_int32x4::nlanes; i+=v_int32x4::nlanes )
{
v_store(SUM + i, v_load(SUM + i) + v_load(Sp + i));
}
#endif
#endif
for( ; i < width; i++ )
SUM[i] += Sp[i];
}
}
else
{
CV_Assert( sumCount == ksize-1 );
src += ksize-1;
}
for( ; count--; src++ )
{
const int * Sp = (const int*)src[0];
const int * Sm = (const int*)src[1-ksize];
float* D = (float*)dst;
if( haveScale )
{
int i = 0;
#if CV_SIMD
v_float32 _v_scale = vx_setall_f32((float)_scale);
for (; i <= width - v_int32::nlanes; i += v_int32::nlanes)
{
v_int32 v_s0 = vx_load(SUM + i) + vx_load(Sp + i);
v_store(D + i, v_cvt_f32(v_s0) * _v_scale);
v_store(SUM + i, v_s0 - vx_load(Sm + i));
}
#if CV_SIMD_WIDTH > 16
v_float32x4 v_scale = v_setall_f32((float)_scale);
for (; i <= width - v_int32x4::nlanes; i += v_int32x4::nlanes)
{
v_int32x4 v_s0 = v_load(SUM + i) + v_load(Sp + i);
v_store(D + i, v_cvt_f32(v_s0) * v_scale);
v_store(SUM + i, v_s0 - v_load(Sm + i));
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = (float)(s0*_scale);
SUM[i] = s0 - Sm[i];
}
}
else
{
int i = 0;
#if CV_SIMD
for( ; i <= width-v_int32::nlanes; i+=v_int32::nlanes )
{
v_int32 v_s0 = vx_load(SUM + i) + vx_load(Sp + i);
v_store(D + i, v_cvt_f32(v_s0));
v_store(SUM + i, v_s0 - vx_load(Sm + i));
}
#if CV_SIMD_WIDTH > 16
for( ; i <= width-v_int32x4::nlanes; i+=v_int32x4::nlanes )
{
v_int32x4 v_s0 = v_load(SUM + i) + v_load(Sp + i);
v_store(D + i, v_cvt_f32(v_s0));
v_store(SUM + i, v_s0 - v_load(Sm + i));
}
#endif
#endif
for( ; i < width; i++ )
{
int s0 = SUM[i] + Sp[i];
D[i] = (float)(s0);
SUM[i] = s0 - Sm[i];
}
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
int sumCount;
std::vector<int> sum;
};
namespace cv {
#ifdef HAVE_OPENCL
......@@ -1396,109 +288,34 @@ static bool ocl_boxFilter( InputArray _src, OutputArray _dst, int ddepth,
#endif
}
cv::Ptr<cv::BaseRowFilter> cv::getRowSumFilter(int srcType, int sumType, int ksize, int anchor)
Ptr<BaseRowFilter> getRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{
int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(sumType);
CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(srcType) );
if( anchor < 0 )
anchor = ksize/2;
if( sdepth == CV_8U && ddepth == CV_32S )
return makePtr<RowSum<uchar, int> >(ksize, anchor);
if( sdepth == CV_8U && ddepth == CV_16U )
return makePtr<RowSum<uchar, ushort> >(ksize, anchor);
if( sdepth == CV_8U && ddepth == CV_64F )
return makePtr<RowSum<uchar, double> >(ksize, anchor);
if( sdepth == CV_16U && ddepth == CV_32S )
return makePtr<RowSum<ushort, int> >(ksize, anchor);
if( sdepth == CV_16U && ddepth == CV_64F )
return makePtr<RowSum<ushort, double> >(ksize, anchor);
if( sdepth == CV_16S && ddepth == CV_32S )
return makePtr<RowSum<short, int> >(ksize, anchor);
if( sdepth == CV_32S && ddepth == CV_32S )
return makePtr<RowSum<int, int> >(ksize, anchor);
if( sdepth == CV_16S && ddepth == CV_64F )
return makePtr<RowSum<short, double> >(ksize, anchor);
if( sdepth == CV_32F && ddepth == CV_64F )
return makePtr<RowSum<float, double> >(ksize, anchor);
if( sdepth == CV_64F && ddepth == CV_64F )
return makePtr<RowSum<double, double> >(ksize, anchor);
CV_Error_( CV_StsNotImplemented,
("Unsupported combination of source format (=%d), and buffer format (=%d)",
srcType, sumType));
CV_INSTRUMENT_REGION();
CV_CPU_DISPATCH(getRowSumFilter, (srcType, sumType, ksize, anchor),
CV_CPU_DISPATCH_MODES_ALL);
}
cv::Ptr<cv::BaseColumnFilter> cv::getColumnSumFilter(int sumType, int dstType, int ksize,
int anchor, double scale)
Ptr<BaseColumnFilter> getColumnSumFilter(int sumType, int dstType, int ksize, int anchor, double scale)
{
int sdepth = CV_MAT_DEPTH(sumType), ddepth = CV_MAT_DEPTH(dstType);
CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(dstType) );
if( anchor < 0 )
anchor = ksize/2;
if( ddepth == CV_8U && sdepth == CV_32S )
return makePtr<ColumnSum<int, uchar> >(ksize, anchor, scale);
if( ddepth == CV_8U && sdepth == CV_16U )
return makePtr<ColumnSum<ushort, uchar> >(ksize, anchor, scale);
if( ddepth == CV_8U && sdepth == CV_64F )
return makePtr<ColumnSum<double, uchar> >(ksize, anchor, scale);
if( ddepth == CV_16U && sdepth == CV_32S )
return makePtr<ColumnSum<int, ushort> >(ksize, anchor, scale);
if( ddepth == CV_16U && sdepth == CV_64F )
return makePtr<ColumnSum<double, ushort> >(ksize, anchor, scale);
if( ddepth == CV_16S && sdepth == CV_32S )
return makePtr<ColumnSum<int, short> >(ksize, anchor, scale);
if( ddepth == CV_16S && sdepth == CV_64F )
return makePtr<ColumnSum<double, short> >(ksize, anchor, scale);
if( ddepth == CV_32S && sdepth == CV_32S )
return makePtr<ColumnSum<int, int> >(ksize, anchor, scale);
if( ddepth == CV_32F && sdepth == CV_32S )
return makePtr<ColumnSum<int, float> >(ksize, anchor, scale);
if( ddepth == CV_32F && sdepth == CV_64F )
return makePtr<ColumnSum<double, float> >(ksize, anchor, scale);
if( ddepth == CV_64F && sdepth == CV_32S )
return makePtr<ColumnSum<int, double> >(ksize, anchor, scale);
if( ddepth == CV_64F && sdepth == CV_64F )
return makePtr<ColumnSum<double, double> >(ksize, anchor, scale);
CV_Error_( CV_StsNotImplemented,
("Unsupported combination of sum format (=%d), and destination format (=%d)",
sumType, dstType));
CV_INSTRUMENT_REGION();
CV_CPU_DISPATCH(getColumnSumFilter, (sumType, dstType, ksize, anchor, scale),
CV_CPU_DISPATCH_MODES_ALL);
}
cv::Ptr<cv::FilterEngine> cv::createBoxFilter( int srcType, int dstType, Size ksize,
Point anchor, bool normalize, int borderType )
Ptr<FilterEngine> createBoxFilter(int srcType, int dstType, Size ksize,
Point anchor, bool normalize, int borderType)
{
int sdepth = CV_MAT_DEPTH(srcType);
int cn = CV_MAT_CN(srcType), sumType = CV_64F;
if( sdepth == CV_8U && CV_MAT_DEPTH(dstType) == CV_8U &&
ksize.width*ksize.height <= 256 )
sumType = CV_16U;
else if( sdepth <= CV_32S && (!normalize ||
ksize.width*ksize.height <= (sdepth == CV_8U ? (1<<23) :
sdepth == CV_16U ? (1 << 15) : (1 << 16))) )
sumType = CV_32S;
sumType = CV_MAKETYPE( sumType, cn );
Ptr<BaseRowFilter> rowFilter = getRowSumFilter(srcType, sumType, ksize.width, anchor.x );
Ptr<BaseColumnFilter> columnFilter = getColumnSumFilter(sumType,
dstType, ksize.height, anchor.y, normalize ? 1./(ksize.width*ksize.height) : 1);
CV_INSTRUMENT_REGION();
return makePtr<FilterEngine>(Ptr<BaseFilter>(), rowFilter, columnFilter,
srcType, dstType, sumType, borderType );
CV_CPU_DISPATCH(createBoxFilter, (srcType, dstType, ksize, anchor, normalize, borderType),
CV_CPU_DISPATCH_MODES_ALL);
}
#ifdef HAVE_OPENVX
namespace cv
{
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_BOX_3x3>(int w, int h) { return w*h < 640 * 480; }
}
......@@ -1570,12 +387,9 @@ namespace cv
return true;
}
}
#endif
#if defined(HAVE_IPP)
namespace cv
{
static bool ipp_boxfilter(Mat &src, Mat &dst, Size ksize, Point anchor, bool normalize, int borderType)
{
#ifdef HAVE_IPP_IW
......@@ -1620,13 +434,12 @@ static bool ipp_boxfilter(Mat &src, Mat &dst, Size ksize, Point anchor, bool nor
return false;
#endif
}
}
#endif
void cv::boxFilter( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType )
void boxFilter(InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType)
{
CV_INSTRUMENT_REGION();
......@@ -1674,8 +487,8 @@ void cv::boxFilter( InputArray _src, OutputArray _dst, int ddepth,
}
void cv::blur( InputArray src, OutputArray dst,
Size ksize, Point anchor, int borderType )
void blur(InputArray src, OutputArray dst,
Size ksize, Point anchor, int borderType)
{
CV_INSTRUMENT_REGION();
......@@ -1687,77 +500,17 @@ void cv::blur( InputArray src, OutputArray dst,
Squared Box Filter
\****************************************************************************************/
namespace cv
{
template<typename T, typename ST>
struct SqrRowSum :
public BaseRowFilter
{
SqrRowSum( int _ksize, int _anchor ) :
BaseRowFilter()
{
ksize = _ksize;
anchor = _anchor;
}
virtual void operator()(const uchar* src, uchar* dst, int width, int cn) CV_OVERRIDE
{
const T* S = (const T*)src;
ST* D = (ST*)dst;
int i = 0, k, ksz_cn = ksize*cn;
width = (width - 1)*cn;
for( k = 0; k < cn; k++, S++, D++ )
{
ST s = 0;
for( i = 0; i < ksz_cn; i += cn )
{
ST val = (ST)S[i];
s += val*val;
}
D[0] = s;
for( i = 0; i < width; i += cn )
{
ST val0 = (ST)S[i], val1 = (ST)S[i + ksz_cn];
s += val1*val1 - val0*val0;
D[i+cn] = s;
}
}
}
};
static Ptr<BaseRowFilter> getSqrRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{
int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(sumType);
CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(srcType) );
if( anchor < 0 )
anchor = ksize/2;
if( sdepth == CV_8U && ddepth == CV_32S )
return makePtr<SqrRowSum<uchar, int> >(ksize, anchor);
if( sdepth == CV_8U && ddepth == CV_64F )
return makePtr<SqrRowSum<uchar, double> >(ksize, anchor);
if( sdepth == CV_16U && ddepth == CV_64F )
return makePtr<SqrRowSum<ushort, double> >(ksize, anchor);
if( sdepth == CV_16S && ddepth == CV_64F )
return makePtr<SqrRowSum<short, double> >(ksize, anchor);
if( sdepth == CV_32F && ddepth == CV_64F )
return makePtr<SqrRowSum<float, double> >(ksize, anchor);
if( sdepth == CV_64F && ddepth == CV_64F )
return makePtr<SqrRowSum<double, double> >(ksize, anchor);
CV_Error_( CV_StsNotImplemented,
("Unsupported combination of source format (=%d), and buffer format (=%d)",
srcType, sumType));
}
CV_INSTRUMENT_REGION();
CV_CPU_DISPATCH(getSqrRowSumFilter, (srcType, sumType, ksize, anchor),
CV_CPU_DISPATCH_MODES_ALL);
}
void cv::sqrBoxFilter( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType )
void sqrBoxFilter(InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType)
{
CV_INSTRUMENT_REGION();
......@@ -1801,4 +554,4 @@ void cv::sqrBoxFilter( InputArray _src, OutputArray _dst, int ddepth,
f->apply( src, dst, wsz, ofs );
}
/* End of file. */
} // namespace
modules/imgproc/src/box_filter.simd.hpp
View file @ 5a01227a
......@@ -42,21 +42,25 @@
//M*/
#include "precomp.hpp"
#include <vector>
#include "opencv2/core/hal/intrin.hpp"
#include "opencl_kernels_imgproc.hpp"
#include "opencv2/core/openvx/ovx_defs.hpp"
namespace cv {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
Ptr<BaseRowFilter> getRowSumFilter(int srcType, int sumType, int ksize, int anchor);
Ptr<BaseColumnFilter> getColumnSumFilter(int sumType, int dstType, int ksize, int anchor, double scale);
Ptr<FilterEngine> createBoxFilter(int srcType, int dstType, Size ksize,
Point anchor, bool normalize, int borderType);
namespace cv
{
Ptr<BaseRowFilter> getSqrRowSumFilter(int srcType, int sumType, int ksize, int anchor);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
/****************************************************************************************\
Box Filter
\****************************************************************************************/
namespace {
template<typename T, typename ST>
struct RowSum :
public BaseRowFilter
......@@ -70,6 +74,8 @@ struct RowSum :
virtual void operator()(const uchar* src, uchar* dst, int width, int cn) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
const T* S = (const T*)src;
ST* D = (ST*)dst;
int i = 0, k, ksz_cn = ksize*cn;
......@@ -183,6 +189,8 @@ struct ColumnSum :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int i;
ST* SUM;
bool haveScale = scale != 1;
......@@ -281,6 +289,8 @@ struct ColumnSum<int, uchar> :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
......@@ -408,9 +418,6 @@ struct ColumnSum<int, uchar> :
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
......@@ -452,6 +459,8 @@ public BaseColumnFilter
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
const int ds = divScale;
const int dd = divDelta;
ushort* SUM;
......@@ -586,9 +595,6 @@ public BaseColumnFilter
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
......@@ -616,6 +622,8 @@ struct ColumnSum<int, short> :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int i;
int* SUM;
bool haveScale = scale != 1;
......@@ -739,9 +747,6 @@ struct ColumnSum<int, short> :
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
......@@ -767,6 +772,8 @@ struct ColumnSum<int, ushort> :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
......@@ -888,9 +895,6 @@ struct ColumnSum<int, ushort> :
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
......@@ -915,6 +919,8 @@ struct ColumnSum<int, int> :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
......@@ -1022,9 +1028,6 @@ struct ColumnSum<int, int> :
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
......@@ -1050,6 +1053,8 @@ struct ColumnSum<int, float> :
virtual void operator()(const uchar** src, uchar* dst, int dststep, int count, int width) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
int* SUM;
bool haveScale = scale != 1;
double _scale = scale;
......@@ -1154,9 +1159,6 @@ struct ColumnSum<int, float> :
}
dst += dststep;
}
#if CV_SIMD
vx_cleanup();
#endif
}
double scale;
......@@ -1164,243 +1166,13 @@ struct ColumnSum<int, float> :
std::vector<int> sum;
};
#ifdef HAVE_OPENCL
} // namespace anon
static bool ocl_boxFilter3x3_8UC1( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor, int borderType, bool normalize )
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
if (ddepth < 0)
ddepth = sdepth;
if (anchor.x < 0)
anchor.x = ksize.width / 2;
if (anchor.y < 0)
anchor.y = ksize.height / 2;
if ( !(dev.isIntel() && (type == CV_8UC1) &&
(_src.offset() == 0) && (_src.step() % 4 == 0) &&
(_src.cols() % 16 == 0) && (_src.rows() % 2 == 0) &&
(anchor.x == 1) && (anchor.y == 1) &&
(ksize.width == 3) && (ksize.height == 3)) )
return false;
float alpha = 1.0f / (ksize.height * ksize.width);
Size size = _src.size();
size_t globalsize[2] = { 0, 0 };
size_t localsize[2] = { 0, 0 };
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
globalsize[0] = size.width / 16;
globalsize[1] = size.height / 2;
char build_opts[1024];
sprintf(build_opts, "-D %s %s", borderMap[borderType], normalize ? "-D NORMALIZE" : "");
ocl::Kernel kernel("boxFilter3x3_8UC1_cols16_rows2", cv::ocl::imgproc::boxFilter3x3_oclsrc, build_opts);
if (kernel.empty())
return false;
UMat src = _src.getUMat();
_dst.create(size, CV_MAKETYPE(ddepth, cn));
if (!(_dst.offset() == 0 && _dst.step() % 4 == 0))
return false;
UMat dst = _dst.getUMat();
int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = kernel.set(idxArg, (int)src.step);
idxArg = kernel.set(idxArg, ocl::KernelArg::PtrWriteOnly(dst));
idxArg = kernel.set(idxArg, (int)dst.step);
idxArg = kernel.set(idxArg, (int)dst.rows);
idxArg = kernel.set(idxArg, (int)dst.cols);
if (normalize)
idxArg = kernel.set(idxArg, (float)alpha);
return kernel.run(2, globalsize, (localsize[0] == 0) ? NULL : localsize, false);
}
static bool ocl_boxFilter( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor, int borderType, bool normalize, bool sqr = false )
Ptr<BaseRowFilter> getRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{
const ocl::Device & dev = ocl::Device::getDefault();
int type = _src.type(), sdepth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type), esz = CV_ELEM_SIZE(type);
bool doubleSupport = dev.doubleFPConfig() > 0;
if (ddepth < 0)
ddepth = sdepth;
if (cn > 4 || (!doubleSupport && (sdepth == CV_64F || ddepth == CV_64F)) ||
_src.offset() % esz != 0 || _src.step() % esz != 0)
return false;
if (anchor.x < 0)
anchor.x = ksize.width / 2;
if (anchor.y < 0)
anchor.y = ksize.height / 2;
int computeUnits = ocl::Device::getDefault().maxComputeUnits();
float alpha = 1.0f / (ksize.height * ksize.width);
Size size = _src.size(), wholeSize;
bool isolated = (borderType & BORDER_ISOLATED) != 0;
borderType &= ~BORDER_ISOLATED;
int wdepth = std::max(CV_32F, std::max(ddepth, sdepth)),
wtype = CV_MAKE_TYPE(wdepth, cn), dtype = CV_MAKE_TYPE(ddepth, cn);
const char * const borderMap[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT", 0, "BORDER_REFLECT_101" };
size_t globalsize[2] = { (size_t)size.width, (size_t)size.height };
size_t localsize_general[2] = { 0, 1 }, * localsize = NULL;
UMat src = _src.getUMat();
if (!isolated)
{
Point ofs;
src.locateROI(wholeSize, ofs);
}
int h = isolated ? size.height : wholeSize.height;
int w = isolated ? size.width : wholeSize.width;
size_t maxWorkItemSizes[32];
ocl::Device::getDefault().maxWorkItemSizes(maxWorkItemSizes);
int tryWorkItems = (int)maxWorkItemSizes[0];
ocl::Kernel kernel;
if (dev.isIntel() && !(dev.type() & ocl::Device::TYPE_CPU) &&
((ksize.width < 5 && ksize.height < 5 && esz <= 4) ||
(ksize.width == 5 && ksize.height == 5 && cn == 1)))
{
if (w < ksize.width || h < ksize.height)
return false;
// Figure out what vector size to use for loading the pixels.
int pxLoadNumPixels = cn != 1 || size.width % 4 ? 1 : 4;
int pxLoadVecSize = cn * pxLoadNumPixels;
// Figure out how many pixels per work item to compute in X and Y
// directions. Too many and we run out of registers.
int pxPerWorkItemX = 1, pxPerWorkItemY = 1;
if (cn <= 2 && ksize.width <= 4 && ksize.height <= 4)
{
pxPerWorkItemX = size.width % 8 ? size.width % 4 ? size.width % 2 ? 1 : 2 : 4 : 8;
pxPerWorkItemY = size.height % 2 ? 1 : 2;
}
else if (cn < 4 || (ksize.width <= 4 && ksize.height <= 4))
{
pxPerWorkItemX = size.width % 2 ? 1 : 2;
pxPerWorkItemY = size.height % 2 ? 1 : 2;
}
globalsize[0] = size.width / pxPerWorkItemX;
globalsize[1] = size.height / pxPerWorkItemY;
// Need some padding in the private array for pixels
int privDataWidth = roundUp(pxPerWorkItemX + ksize.width - 1, pxLoadNumPixels);
// Make the global size a nice round number so the runtime can pick
// from reasonable choices for the workgroup size
const int wgRound = 256;
globalsize[0] = roundUp(globalsize[0], wgRound);
char build_options[1024], cvt[2][40];
sprintf(build_options, "-D cn=%d "
"-D ANCHOR_X=%d -D ANCHOR_Y=%d -D KERNEL_SIZE_X=%d -D KERNEL_SIZE_Y=%d "
"-D PX_LOAD_VEC_SIZE=%d -D PX_LOAD_NUM_PX=%d "
"-D PX_PER_WI_X=%d -D PX_PER_WI_Y=%d -D PRIV_DATA_WIDTH=%d -D %s -D %s "
"-D PX_LOAD_X_ITERATIONS=%d -D PX_LOAD_Y_ITERATIONS=%d "
"-D srcT=%s -D srcT1=%s -D dstT=%s -D dstT1=%s -D WT=%s -D WT1=%s "
"-D convertToWT=%s -D convertToDstT=%s%s%s -D PX_LOAD_FLOAT_VEC_CONV=convert_%s -D OP_BOX_FILTER",
cn, anchor.x, anchor.y, ksize.width, ksize.height,
pxLoadVecSize, pxLoadNumPixels,
pxPerWorkItemX, pxPerWorkItemY, privDataWidth, borderMap[borderType],
isolated ? "BORDER_ISOLATED" : "NO_BORDER_ISOLATED",
privDataWidth / pxLoadNumPixels, pxPerWorkItemY + ksize.height - 1,
ocl::typeToStr(type), ocl::typeToStr(sdepth), ocl::typeToStr(dtype),
ocl::typeToStr(ddepth), ocl::typeToStr(wtype), ocl::typeToStr(wdepth),
ocl::convertTypeStr(sdepth, wdepth, cn, cvt[0]),
ocl::convertTypeStr(wdepth, ddepth, cn, cvt[1]),
normalize ? " -D NORMALIZE" : "", sqr ? " -D SQR" : "",
ocl::typeToStr(CV_MAKE_TYPE(wdepth, pxLoadVecSize)) //PX_LOAD_FLOAT_VEC_CONV
);
if (!kernel.create("filterSmall", cv::ocl::imgproc::filterSmall_oclsrc, build_options))
return false;
}
else
{
localsize = localsize_general;
for ( ; ; )
{
int BLOCK_SIZE_X = tryWorkItems, BLOCK_SIZE_Y = std::min(ksize.height * 10, size.height);
while (BLOCK_SIZE_X > 32 && BLOCK_SIZE_X >= ksize.width * 2 && BLOCK_SIZE_X > size.width * 2)
BLOCK_SIZE_X /= 2;
while (BLOCK_SIZE_Y < BLOCK_SIZE_X / 8 && BLOCK_SIZE_Y * computeUnits * 32 < size.height)
BLOCK_SIZE_Y *= 2;
if (ksize.width > BLOCK_SIZE_X || w < ksize.width || h < ksize.height)
return false;
char cvt[2][50];
String opts = format("-D LOCAL_SIZE_X=%d -D BLOCK_SIZE_Y=%d -D ST=%s -D DT=%s -D WT=%s -D convertToDT=%s -D convertToWT=%s"
" -D ANCHOR_X=%d -D ANCHOR_Y=%d -D KERNEL_SIZE_X=%d -D KERNEL_SIZE_Y=%d -D %s%s%s%s%s"
" -D ST1=%s -D DT1=%s -D cn=%d",
BLOCK_SIZE_X, BLOCK_SIZE_Y, ocl::typeToStr(type), ocl::typeToStr(CV_MAKE_TYPE(ddepth, cn)),
ocl::typeToStr(CV_MAKE_TYPE(wdepth, cn)),
ocl::convertTypeStr(wdepth, ddepth, cn, cvt[0]),
ocl::convertTypeStr(sdepth, wdepth, cn, cvt[1]),
anchor.x, anchor.y, ksize.width, ksize.height, borderMap[borderType],
isolated ? " -D BORDER_ISOLATED" : "", doubleSupport ? " -D DOUBLE_SUPPORT" : "",
normalize ? " -D NORMALIZE" : "", sqr ? " -D SQR" : "",
ocl::typeToStr(sdepth), ocl::typeToStr(ddepth), cn);
localsize[0] = BLOCK_SIZE_X;
globalsize[0] = divUp(size.width, BLOCK_SIZE_X - (ksize.width - 1)) * BLOCK_SIZE_X;
globalsize[1] = divUp(size.height, BLOCK_SIZE_Y);
kernel.create("boxFilter", cv::ocl::imgproc::boxFilter_oclsrc, opts);
if (kernel.empty())
return false;
size_t kernelWorkGroupSize = kernel.workGroupSize();
if (localsize[0] <= kernelWorkGroupSize)
break;
if (BLOCK_SIZE_X < (int)kernelWorkGroupSize)
return false;
tryWorkItems = (int)kernelWorkGroupSize;
}
}
_dst.create(size, CV_MAKETYPE(ddepth, cn));
UMat dst = _dst.getUMat();
int idxArg = kernel.set(0, ocl::KernelArg::PtrReadOnly(src));
idxArg = kernel.set(idxArg, (int)src.step);
int srcOffsetX = (int)((src.offset % src.step) / src.elemSize());
int srcOffsetY = (int)(src.offset / src.step);
int srcEndX = isolated ? srcOffsetX + size.width : wholeSize.width;
int srcEndY = isolated ? srcOffsetY + size.height : wholeSize.height;
idxArg = kernel.set(idxArg, srcOffsetX);
idxArg = kernel.set(idxArg, srcOffsetY);
idxArg = kernel.set(idxArg, srcEndX);
idxArg = kernel.set(idxArg, srcEndY);
idxArg = kernel.set(idxArg, ocl::KernelArg::WriteOnly(dst));
if (normalize)
idxArg = kernel.set(idxArg, (float)alpha);
return kernel.run(2, globalsize, localsize, false);
}
#endif
}
CV_INSTRUMENT_REGION();
cv::Ptr<cv::BaseRowFilter> cv::getRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{
int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(sumType);
CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(srcType) );
......@@ -1434,9 +1206,10 @@ cv::Ptr<cv::BaseRowFilter> cv::getRowSumFilter(int srcType, int sumType, int ksi
}
cv::Ptr<cv::BaseColumnFilter> cv::getColumnSumFilter(int sumType, int dstType, int ksize,
int anchor, double scale)
Ptr<BaseColumnFilter> getColumnSumFilter(int sumType, int dstType, int ksize, int anchor, double scale)
{
CV_INSTRUMENT_REGION();
int sdepth = CV_MAT_DEPTH(sumType), ddepth = CV_MAT_DEPTH(dstType);
CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(dstType) );
......@@ -1474,9 +1247,11 @@ cv::Ptr<cv::BaseColumnFilter> cv::getColumnSumFilter(int sumType, int dstType, i
}
cv::Ptr<cv::FilterEngine> cv::createBoxFilter( int srcType, int dstType, Size ksize,
Point anchor, bool normalize, int borderType )
Ptr<FilterEngine> createBoxFilter(int srcType, int dstType, Size ksize,
Point anchor, bool normalize, int borderType)
{
CV_INSTRUMENT_REGION();
int sdepth = CV_MAT_DEPTH(srcType);
int cn = CV_MAT_CN(srcType), sumType = CV_64F;
if( sdepth == CV_8U && CV_MAT_DEPTH(dstType) == CV_8U &&
......@@ -1496,199 +1271,12 @@ cv::Ptr<cv::FilterEngine> cv::createBoxFilter( int srcType, int dstType, Size ks
srcType, dstType, sumType, borderType );
}
#ifdef HAVE_OPENVX
namespace cv
{
namespace ovx {
template <> inline bool skipSmallImages<VX_KERNEL_BOX_3x3>(int w, int h) { return w*h < 640 * 480; }
}
static bool openvx_boxfilter(InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType)
{
if (ddepth < 0)
ddepth = CV_8UC1;
if (_src.type() != CV_8UC1 || ddepth != CV_8U || !normalize ||
_src.cols() < 3 || _src.rows() < 3 ||
ksize.width != 3 || ksize.height != 3 ||
(anchor.x >= 0 && anchor.x != 1) ||
(anchor.y >= 0 && anchor.y != 1) ||
ovx::skipSmallImages<VX_KERNEL_BOX_3x3>(_src.cols(), _src.rows()))
return false;
Mat src = _src.getMat();
if ((borderType & BORDER_ISOLATED) == 0 && src.isSubmatrix())
return false; //Process isolated borders only
vx_enum border;
switch (borderType & ~BORDER_ISOLATED)
{
case BORDER_CONSTANT:
border = VX_BORDER_CONSTANT;
break;
case BORDER_REPLICATE:
border = VX_BORDER_REPLICATE;
break;
default:
return false;
}
_dst.create(src.size(), CV_8UC1);
Mat dst = _dst.getMat();
try
{
ivx::Context ctx = ovx::getOpenVXContext();
Mat a;
if (dst.data != src.data)
a = src;
else
src.copyTo(a);
ivx::Image
ia = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(a.cols, a.rows, 1, (vx_int32)(a.step)), a.data),
ib = ivx::Image::createFromHandle(ctx, VX_DF_IMAGE_U8,
ivx::Image::createAddressing(dst.cols, dst.rows, 1, (vx_int32)(dst.step)), dst.data);
//ATTENTION: VX_CONTEXT_IMMEDIATE_BORDER attribute change could lead to strange issues in multi-threaded environments
//since OpenVX standard says nothing about thread-safety for now
ivx::border_t prevBorder = ctx.immediateBorder();
ctx.setImmediateBorder(border, (vx_uint8)(0));
ivx::IVX_CHECK_STATUS(vxuBox3x3(ctx, ia, ib));
ctx.setImmediateBorder(prevBorder);
}
catch (const ivx::RuntimeError & e)
{
VX_DbgThrow(e.what());
}
catch (const ivx::WrapperError & e)
{
VX_DbgThrow(e.what());
}
return true;
}
}
#endif
#if defined(HAVE_IPP)
namespace cv
{
static bool ipp_boxfilter(Mat &src, Mat &dst, Size ksize, Point anchor, bool normalize, int borderType)
{
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP();
#if IPP_VERSION_X100 < 201801
// Problem with SSE42 optimization for 16s and some 8u modes
if(ipp::getIppTopFeatures() == ippCPUID_SSE42 && (((src.depth() == CV_16S || src.depth() == CV_16U) && (src.channels() == 3 || src.channels() == 4)) || (src.depth() == CV_8U && src.channels() == 3 && (ksize.width > 5 || ksize.height > 5))))
return false;
// Other optimizations has some degradations too
if((((src.depth() == CV_16S || src.depth() == CV_16U) && (src.channels() == 4)) || (src.depth() == CV_8U && src.channels() == 1 && (ksize.width > 5 || ksize.height > 5))))
return false;
#endif
if(!normalize)
return false;
if(!ippiCheckAnchor(anchor, ksize))
return false;
try
{
::ipp::IwiImage iwSrc = ippiGetImage(src);
::ipp::IwiImage iwDst = ippiGetImage(dst);
::ipp::IwiSize iwKSize = ippiGetSize(ksize);
::ipp::IwiBorderSize borderSize(iwKSize);
::ipp::IwiBorderType ippBorder(ippiGetBorder(iwSrc, borderType, borderSize));
if(!ippBorder)
return false;
CV_INSTRUMENT_FUN_IPP(::ipp::iwiFilterBox, iwSrc, iwDst, iwKSize, ::ipp::IwDefault(), ippBorder);
}
catch (const ::ipp::IwException &)
{
return false;
}
return true;
#else
CV_UNUSED(src); CV_UNUSED(dst); CV_UNUSED(ksize); CV_UNUSED(anchor); CV_UNUSED(normalize); CV_UNUSED(borderType);
return false;
#endif
}
}
#endif
void cv::boxFilter( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType )
{
CV_INSTRUMENT_REGION();
CV_OCL_RUN(_dst.isUMat() &&
(borderType == BORDER_REPLICATE || borderType == BORDER_CONSTANT ||
borderType == BORDER_REFLECT || borderType == BORDER_REFLECT_101),
ocl_boxFilter3x3_8UC1(_src, _dst, ddepth, ksize, anchor, borderType, normalize))
CV_OCL_RUN(_dst.isUMat(), ocl_boxFilter(_src, _dst, ddepth, ksize, anchor, borderType, normalize))
Mat src = _src.getMat();
int stype = src.type(), sdepth = CV_MAT_DEPTH(stype), cn = CV_MAT_CN(stype);
if( ddepth < 0 )
ddepth = sdepth;
_dst.create( src.size(), CV_MAKETYPE(ddepth, cn) );
Mat dst = _dst.getMat();
if( borderType != BORDER_CONSTANT && normalize && (borderType & BORDER_ISOLATED) != 0 )
{
if( src.rows == 1 )
ksize.height = 1;
if( src.cols == 1 )
ksize.width = 1;
}
Point ofs;
Size wsz(src.cols, src.rows);
if(!(borderType&BORDER_ISOLATED))
src.locateROI( wsz, ofs );
CALL_HAL(boxFilter, cv_hal_boxFilter, src.ptr(), src.step, dst.ptr(), dst.step, src.cols, src.rows, sdepth, ddepth, cn,
ofs.x, ofs.y, wsz.width - src.cols - ofs.x, wsz.height - src.rows - ofs.y, ksize.width, ksize.height,
anchor.x, anchor.y, normalize, borderType&~BORDER_ISOLATED);
CV_OVX_RUN(true,
openvx_boxfilter(src, dst, ddepth, ksize, anchor, normalize, borderType))
CV_IPP_RUN_FAST(ipp_boxfilter(src, dst, ksize, anchor, normalize, borderType));
borderType = (borderType&~BORDER_ISOLATED);
Ptr<FilterEngine> f = createBoxFilter( src.type(), dst.type(),
ksize, anchor, normalize, borderType );
f->apply( src, dst, wsz, ofs );
}
void cv::blur( InputArray src, OutputArray dst,
Size ksize, Point anchor, int borderType )
{
CV_INSTRUMENT_REGION();
boxFilter( src, dst, -1, ksize, anchor, true, borderType );
}
/****************************************************************************************\
Squared Box Filter
\****************************************************************************************/
namespace cv
{
namespace {
template<typename T, typename ST>
struct SqrRowSum :
......@@ -1703,6 +1291,8 @@ struct SqrRowSum :
virtual void operator()(const uchar* src, uchar* dst, int width, int cn) CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
const T* S = (const T*)src;
ST* D = (ST*)dst;
int i = 0, k, ksz_cn = ksize*cn;
......@@ -1727,7 +1317,9 @@ struct SqrRowSum :
}
};
static Ptr<BaseRowFilter> getSqrRowSumFilter(int srcType, int sumType, int ksize, int anchor)
} // namespace anon
Ptr<BaseRowFilter> getSqrRowSumFilter(int srcType, int sumType, int ksize, int anchor)
{
int sdepth = CV_MAT_DEPTH(srcType), ddepth = CV_MAT_DEPTH(sumType);
CV_Assert( CV_MAT_CN(sumType) == CV_MAT_CN(srcType) );
......@@ -1753,52 +1345,6 @@ static Ptr<BaseRowFilter> getSqrRowSumFilter(int srcType, int sumType, int ksize
srcType, sumType));
}
}
void cv::sqrBoxFilter( InputArray _src, OutputArray _dst, int ddepth,
Size ksize, Point anchor,
bool normalize, int borderType )
{
CV_INSTRUMENT_REGION();
int srcType = _src.type(), sdepth = CV_MAT_DEPTH(srcType), cn = CV_MAT_CN(srcType);
Size size = _src.size();
if( ddepth < 0 )
ddepth = sdepth < CV_32F ? CV_32F : CV_64F;
if( borderType != BORDER_CONSTANT && normalize )
{
if( size.height == 1 )
ksize.height = 1;
if( size.width == 1 )
ksize.width = 1;
}
CV_OCL_RUN(_dst.isUMat() && _src.dims() <= 2,
ocl_boxFilter(_src, _dst, ddepth, ksize, anchor, borderType, normalize, true))
int sumDepth = CV_64F;
if( sdepth == CV_8U )
sumDepth = CV_32S;
int sumType = CV_MAKETYPE( sumDepth, cn ), dstType = CV_MAKETYPE(ddepth, cn);
Mat src = _src.getMat();
_dst.create( size, dstType );
Mat dst = _dst.getMat();
Ptr<BaseRowFilter> rowFilter = getSqrRowSumFilter(srcType, sumType, ksize.width, anchor.x );
Ptr<BaseColumnFilter> columnFilter = getColumnSumFilter(sumType,
dstType, ksize.height, anchor.y,
normalize ? 1./(ksize.width*ksize.height) : 1);
Ptr<FilterEngine> f = makePtr<FilterEngine>(Ptr<BaseFilter>(), rowFilter, columnFilter,
srcType, dstType, sumType, borderType );
Point ofs;
Size wsz(src.cols, src.rows);
src.locateROI( wsz, ofs );
f->apply( src, dst, wsz, ofs );
}
/* End of file. */
#endif
CV_CPU_OPTIMIZATION_NAMESPACE_END
} // namespace
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