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Merge branch 4.x

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This commit is contained in:
Alexander Smorkalov
2025-05-27 16:48:22 +03:00
parent 349b44a485 344f8c6400
commit 350b211b57
167 changed files with 7028 additions and 4687 deletions
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modules/imgproc/src/accum.simd.hpp
+1 -1
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@@ -2825,7 +2825,7 @@ void accW_simd_(const ushort* src, float* dst, const uchar* mask, int len, int c
v_expand(v_src1, v_src10, v_src11);
v_expand(v_src2, v_src20, v_src21);
v_float32 v_dst00, v_dst01, v_dst02, v_dst10, v_dst11, v_dst20, v_dst21;
v_float32 v_dst00, v_dst01, v_dst10, v_dst11, v_dst20, v_dst21;
v_load_deinterleave(dst + x * cn , v_dst00, v_dst10, v_dst20);
v_load_deinterleave(dst + (x + step) * cn, v_dst01, v_dst11, v_dst21);
modules/imgproc/src/bilateral_filter.dispatch.cpp
+27 -14
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@@ -75,10 +75,12 @@ static bool ocl_bilateralFilter_8u(InputArray _src, OutputArray _dst, int d,
if (depth != CV_8U || cn > 4)
return false;
if (sigma_color <= 0)
sigma_color = 1;
if (sigma_space <= 0)
sigma_space = 1;
constexpr double eps = 1e-6;
if( sigma_color <= eps || sigma_space <= eps )
{
_src.copyTo(_dst);
return true;
}
double gauss_color_coeff = -0.5 / (sigma_color * sigma_color);
double gauss_space_coeff = -0.5 / (sigma_space * sigma_space);
@@ -165,10 +167,12 @@ bilateralFilter_8u( const Mat& src, Mat& dst, int d,
CV_Assert( (src.type() == CV_8UC1 || src.type() == CV_8UC3) && src.data != dst.data );
if( sigma_color <= 0 )
sigma_color = 1;
if( sigma_space <= 0 )
sigma_space = 1;
constexpr double eps = 1e-6;
if( sigma_color <= eps || sigma_space <= eps )
{
src.copyTo(dst);
return;
}
double gauss_color_coeff = -0.5/(sigma_color*sigma_color);
double gauss_space_coeff = -0.5/(sigma_space*sigma_space);
@@ -232,10 +236,12 @@ bilateralFilter_32f( const Mat& src, Mat& dst, int d,
CV_Assert( (src.type() == CV_32FC1 || src.type() == CV_32FC3) && src.data != dst.data );
if( sigma_color <= 0 )
sigma_color = 1;
if( sigma_space <= 0 )
sigma_space = 1;
constexpr double eps = 1e-6;
if( sigma_color <= eps || sigma_space <= eps )
{
src.copyTo(dst);
return;
}
double gauss_color_coeff = -0.5/(sigma_color*sigma_color);
double gauss_space_coeff = -0.5/(sigma_space*sigma_space);
@@ -358,9 +364,16 @@ static bool ipp_bilateralFilter(Mat &src, Mat &dst, int d, double sigmaColor, do
#ifdef HAVE_IPP_IW
CV_INSTRUMENT_REGION_IPP();
constexpr double eps = 1e-6;
if( sigmaColor <= eps || sigmaSpace <= eps )
{
src.copyTo(dst);
return true;
}
int radius = IPP_MAX(((d <= 0)?cvRound(sigmaSpace*1.5):d/2), 1);
Ipp32f valSquareSigma = (Ipp32f)((sigmaColor <= 0)?1:sigmaColor*sigmaColor);
Ipp32f posSquareSigma = (Ipp32f)((sigmaSpace <= 0)?1:sigmaSpace*sigmaSpace);
Ipp32f valSquareSigma = (Ipp32f)(sigmaColor*sigmaColor);
Ipp32f posSquareSigma = (Ipp32f)(sigmaSpace*sigmaSpace);
// Acquire data and begin processing
try
modules/imgproc/src/color_hsv.dispatch.cpp
+46 -30
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@@ -257,6 +257,41 @@ bool oclCvtColorBGR2HLS( InputArray _src, OutputArray _dst, int bidx, bool full
return h.run();
}
static UMat init_sdiv_table()
{
cv::Mat sdiv_mat(1, 256, CV_32SC1);
int* sdiv = sdiv_mat.ptr<int>();
const int hsv_shift = 12;
const int v = 255 << hsv_shift;
sdiv[0] = 0;
for(int i = 1; i < 256; i++ )
sdiv[i] = saturate_cast<int>(v/(1.*i));
cv::UMat result;
sdiv_mat.copyTo(result);
return result;
}
static UMat init_hdiv_table(int hrange)
{
cv::Mat hdiv_mat(1, 256, CV_32SC1);
int* hdiv = hdiv_mat.ptr<int>();
const int hsv_shift = 12;
const int v = hrange << hsv_shift;
hdiv[0] = 0;
for (int i = 1; i < 256; i++ )
hdiv[i] = saturate_cast<int>(v/(6.*i));
cv::UMat result;
hdiv_mat.copyTo(result);
return result;
}
bool oclCvtColorBGR2HSV( InputArray _src, OutputArray _dst, int bidx, bool full )
{
OclHelper< Set<3, 4>, Set<3>, Set<CV_8U, CV_32F> > h(_src, _dst, 3);
@@ -274,41 +309,22 @@ bool oclCvtColorBGR2HSV( InputArray _src, OutputArray _dst, int bidx, bool full
if(_src.depth() == CV_8U)
{
static UMat sdiv_data;
static UMat hdiv_data180;
static UMat hdiv_data256;
static int sdiv_table[256];
static int hdiv_table180[256];
static int hdiv_table256[256];
static volatile bool initialized180 = false, initialized256 = false;
volatile bool & initialized = hrange == 180 ? initialized180 : initialized256;
static UMat sdiv_data = init_sdiv_table();
UMat hdiv_data;
if (!initialized)
if (hrange == 180)
{
int * const hdiv_table = hrange == 180 ? hdiv_table180 : hdiv_table256, hsv_shift = 12;
UMat & hdiv_data = hrange == 180 ? hdiv_data180 : hdiv_data256;
sdiv_table[0] = hdiv_table180[0] = hdiv_table256[0] = 0;
int v = 255 << hsv_shift;
if (!initialized180 && !initialized256)
{
for(int i = 1; i < 256; i++ )
sdiv_table[i] = saturate_cast<int>(v/(1.*i));
Mat(1, 256, CV_32SC1, sdiv_table).copyTo(sdiv_data);
}
v = hrange << hsv_shift;
for (int i = 1; i < 256; i++ )
hdiv_table[i] = saturate_cast<int>(v/(6.*i));
Mat(1, 256, CV_32SC1, hdiv_table).copyTo(hdiv_data);
initialized = true;
static UMat hdiv_data180 = init_hdiv_table(180);
hdiv_data = hdiv_data180;
}
else
{
static UMat hdiv_data256 = init_hdiv_table(256);
hdiv_data = hdiv_data256;
}
h.setArg(ocl::KernelArg::PtrReadOnly(sdiv_data));
h.setArg(hrange == 256 ? ocl::KernelArg::PtrReadOnly(hdiv_data256) :
ocl::KernelArg::PtrReadOnly(hdiv_data180));
h.setArg(ocl::KernelArg::PtrReadOnly(hdiv_data));
}
return h.run();
modules/imgproc/src/color_hsv.simd.hpp
+1 -1
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@@ -850,7 +850,7 @@ struct RGB2HLS_b
for ( ; j <= dn*bufChannels - nBlock*bufChannels;
j += nBlock*bufChannels, src += nBlock*4)
{
v_uint8 rgb0, rgb1, rgb2, rgb3, dummy;
v_uint8 rgb0, rgb1, rgb2, dummy;
v_load_deinterleave(src, rgb0, rgb1, rgb2, dummy);
v_uint16 d0,d1,d2,d3,d4,d5;
modules/imgproc/src/hal_replacement.hpp
+20
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@@ -1395,6 +1395,26 @@ inline int hal_ni_polygonMoments(const uchar* src_data, size_t src_size, int src
#define cv_hal_polygonMoments hal_ni_polygonMoments
//! @endcond
/**
@brief Calculates a histogram of a set of arrays
@param src_data Source imgage data
@param src_step Source image step
@param src_type Source image type
@param src_width Source image width
@param src_height Source image height
@param hist_data Histogram data
@param hist_size Histogram size
@param ranges Array of dims arrays of the histogram bin boundaries
@param uniform Flag indicating whether the histogram is uniform or not
@param accumulate Accumulation flag
*/
inline int hal_ni_calcHist(const uchar* src_data, size_t src_step, int src_type, int src_width, int src_height, float* hist_data, int hist_size, const float** ranges, bool uniform, bool accumulate)
{ return CV_HAL_ERROR_NOT_IMPLEMENTED; }
//! @cond IGNORED
#define cv_hal_calcHist hal_ni_calcHist
//! @endcond
//! @}
#if defined(__clang__)
modules/imgproc/src/histogram.cpp
+45
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@@ -910,6 +910,11 @@ void cv::calcHist( const Mat* images, int nimages, const int* channels,
&& _mask.empty() && images[0].dims <= 2 && ranges && ranges[0],
ipp_calchist(images[0], hist, histSize[0], ranges, uniform, accumulate));
if (nimages == 1 && dims == 1 && channels && channels[0] == 0 && _mask.empty() && images[0].dims <= 2 && ranges && ranges[0]) {
CALL_HAL(calcHist, cv_hal_calcHist, images[0].data, images[0].step, images[0].type(), images[0].cols, images[0].rows,
hist.ptr<float>(), histSize[0], ranges, uniform, accumulate);
}
Mat ihist = hist;
ihist.flags = (ihist.flags & ~CV_MAT_TYPE_MASK)|CV_32S;
@@ -1986,6 +1991,46 @@ double cv::compareHist( InputArray _H1, InputArray _H2, int method )
if( (method == cv::HISTCMP_CHISQR) || (method == cv::HISTCMP_CHISQR_ALT))
{
#if CV_SIMD_64F || CV_SIMD_SCALABLE_64F
v_float64 v_eps = vx_setall_f64(DBL_EPSILON);
v_float64 v_one = vx_setall_f64(1.f);
v_float64 v_zero = vx_setzero_f64();
v_float64 v_res = vx_setzero_f64();
for ( ; j <= len - VTraits<v_float32>::vlanes(); j += VTraits<v_float32>::vlanes())
{
v_float32 v_h1 = vx_load(h1 + j), v_h2 = vx_load(h2 + j);
v_float64 v_h1_l = v_cvt_f64(v_h1), v_h1_h = v_cvt_f64_high(v_h1);
v_float64 v_h2_l = v_cvt_f64(v_h2), v_h2_h = v_cvt_f64_high(v_h2);
v_float64 v_a_l, v_a_h;
v_a_l = v_sub(v_h1_l, v_h2_l);
v_a_h = v_sub(v_h1_h, v_h2_h);
v_float64 v_b_l, v_b_h;
if (method == cv::HISTCMP_CHISQR)
{
v_b_l = v_h1_l;
v_b_h = v_h1_h;
}
else
{
v_b_l = v_add(v_h1_l, v_h2_l);
v_b_h = v_add(v_h1_h, v_h2_h);
}
// low part
auto v_res_l = v_mul(v_mul(v_a_l, v_a_l), v_div(v_one, v_b_l));
auto mask = v_gt(v_abs(v_b_l), v_eps);
v_res_l = v_select(mask, v_res_l, v_zero);
v_res = v_add(v_res, v_res_l);
// high part
auto v_res_h = v_mul(v_mul(v_a_h, v_a_h), v_div(v_one, v_b_h));
mask = v_gt(v_abs(v_b_h), v_eps);
v_res_h = v_select(mask, v_res_h, v_zero);
v_res = v_add(v_res, v_res_h);
}
result += v_reduce_sum(v_res);
#endif
for( ; j < len; j++ )
{
double a = h1[j] - h2[j];
modules/imgproc/src/median_blur.simd.hpp
+19 -2
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@@ -13,6 +13,7 @@
// Copyright (C) 2000-2008, 2018, Intel Corporation, all rights reserved.
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
// Copyright (C) 2014-2015, Itseez Inc., all rights reserved.
// Copyright (C) 2025, Advanced Micro Devices, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
@@ -693,8 +694,16 @@ medianBlur_SortNet( const Mat& _src, Mat& _dst, int m )
#else
int nlanes = 1;
#endif
for( ; j <= size.width - nlanes - cn; j += nlanes )
for (; j < size.width - cn; j += nlanes)
{
//handling tail in vectorized path itself
if ( j > size.width - cn - nlanes ) {
if (j == cn || src == dst) {
break;
}
j = size.width - cn - nlanes;
}
VT p0 = vop.load(row0+j-cn), p1 = vop.load(row0+j), p2 = vop.load(row0+j+cn);
VT p3 = vop.load(row1+j-cn), p4 = vop.load(row1+j), p5 = vop.load(row1+j+cn);
VT p6 = vop.load(row2+j-cn), p7 = vop.load(row2+j), p8 = vop.load(row2+j+cn);
@@ -705,6 +714,7 @@ medianBlur_SortNet( const Mat& _src, Mat& _dst, int m )
vop(p3, p6); vop(p1, p4); vop(p2, p5); vop(p4, p7);
vop(p4, p2); vop(p6, p4); vop(p4, p2);
vop.store(dst+j, p4);
}
limit = size.width;
@@ -798,8 +808,14 @@ medianBlur_SortNet( const Mat& _src, Mat& _dst, int m )
#else
int nlanes = 1;
#endif
for( ; j <= size.width - nlanes - cn*2; j += nlanes )
for( ; j < size.width - cn*2; j += nlanes)
{
if ( j > size.width - cn*2 - nlanes ) {
if (j == cn*2 || src == dst) {
break;
}
j = size.width - cn*2 - nlanes;
}
VT p0 = vop.load(row[0]+j-cn*2), p5 = vop.load(row[1]+j-cn*2), p10 = vop.load(row[2]+j-cn*2), p15 = vop.load(row[3]+j-cn*2), p20 = vop.load(row[4]+j-cn*2);
VT p1 = vop.load(row[0]+j-cn*1), p6 = vop.load(row[1]+j-cn*1), p11 = vop.load(row[2]+j-cn*1), p16 = vop.load(row[3]+j-cn*1), p21 = vop.load(row[4]+j-cn*1);
VT p2 = vop.load(row[0]+j-cn*0), p7 = vop.load(row[1]+j-cn*0), p12 = vop.load(row[2]+j-cn*0), p17 = vop.load(row[3]+j-cn*0), p22 = vop.load(row[4]+j-cn*0);
@@ -830,6 +846,7 @@ medianBlur_SortNet( const Mat& _src, Mat& _dst, int m )
vop(p13, p17); vop(p3, p15); vop(p11, p23); vop(p11, p15); vop(p7, p19);
vop(p7, p11); vop(p11, p13); vop(p11, p12);
vop.store(dst+j, p12);
}
limit = size.width;
modules/imgproc/src/pyramids.cpp
-1
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@@ -769,7 +769,6 @@ template <> int PyrUpVecVOneRow<int, uchar>(int** src, uchar* dst, int width)
r20 = *(row2 + x);
int _2r10 = r10 + r10;
int d = r00 + r20 + (_2r10 + _2r10 + _2r10);
int d_shifted = (r10 + r20) << 2;
// Similar to v_rshr_pack_u<6>(d, vx_setzero_s16()).get0()
*(dst + x) = (int)((((unsigned int)d) + ((1 << (6 - 1)))) >> 6);
}