potok/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2026-07-29 15:23:05 +04:00
Code Packages Releases Wiki Activity

Merge branch 4.x

Browse Source
This commit is contained in:
Alexander Smorkalov
2023-06-01 09:37:38 +03:00
parent d24ffe9a65 fc5d412ba7
commit 5af40a0269
565 changed files with 84396 additions and 17589 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/features2d/src/affine_feature.cpp
+3 -1
View File
@@ -243,7 +243,7 @@ private:
else
mask0 = mask;
pose = Matx23f(1,0,0,
0,1,0);
0,1,0);
if( phi == 0 )
image.copyTo(rotImage);
@@ -276,6 +276,8 @@ private:
}
if( phi != 0 || tilt != 1 )
warpAffine(mask0, warpedMask, pose, warpedImage.size(), INTER_NEAREST);
else
warpedMask = mask0;
}
modules/features2d/src/sift.dispatch.cpp
+28 -11
View File
@@ -72,6 +72,7 @@
#include "precomp.hpp"
#include <opencv2/core/hal/hal.hpp>
#include <opencv2/core/utils/tls.hpp>
#include <opencv2/core/utils/logger.hpp>
#include "sift.simd.hpp"
#include "sift.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
@@ -88,7 +89,8 @@ class SIFT_Impl : public SIFT
public:
explicit SIFT_Impl( int nfeatures = 0, int nOctaveLayers = 3,
double contrastThreshold = 0.04, double edgeThreshold = 10,
double sigma = 1.6, int descriptorType = CV_32F );
double sigma = 1.6, int descriptorType = CV_32F,
bool enable_precise_upscale = true );
//! returns the descriptor size in floats (128)
int descriptorSize() const CV_OVERRIDE;
@@ -136,24 +138,25 @@ protected:
CV_PROP_RW double edgeThreshold;
CV_PROP_RW double sigma;
CV_PROP_RW int descriptor_type;
CV_PROP_RW bool enable_precise_upscale;
};
Ptr<SIFT> SIFT::create( int _nfeatures, int _nOctaveLayers,
double _contrastThreshold, double _edgeThreshold, double _sigma )
double _contrastThreshold, double _edgeThreshold, double _sigma, bool enable_precise_upscale )
{
CV_TRACE_FUNCTION();
return makePtr<SIFT_Impl>(_nfeatures, _nOctaveLayers, _contrastThreshold, _edgeThreshold, _sigma, CV_32F);
return makePtr<SIFT_Impl>(_nfeatures, _nOctaveLayers, _contrastThreshold, _edgeThreshold, _sigma, CV_32F, enable_precise_upscale);
}
Ptr<SIFT> SIFT::create( int _nfeatures, int _nOctaveLayers,
double _contrastThreshold, double _edgeThreshold, double _sigma, int _descriptorType )
double _contrastThreshold, double _edgeThreshold, double _sigma, int _descriptorType, bool enable_precise_upscale )
{
CV_TRACE_FUNCTION();
// SIFT descriptor supports 32bit floating point and 8bit unsigned int.
CV_Assert(_descriptorType == CV_32F || _descriptorType == CV_8U);
return makePtr<SIFT_Impl>(_nfeatures, _nOctaveLayers, _contrastThreshold, _edgeThreshold, _sigma, _descriptorType);
return makePtr<SIFT_Impl>(_nfeatures, _nOctaveLayers, _contrastThreshold, _edgeThreshold, _sigma, _descriptorType, enable_precise_upscale);
}
String SIFT::getDefaultName() const
@@ -170,7 +173,7 @@ unpackOctave(const KeyPoint& kpt, int& octave, int& layer, float& scale)
scale = octave >= 0 ? 1.f/(1 << octave) : (float)(1 << -octave);
}
static Mat createInitialImage( const Mat& img, bool doubleImageSize, float sigma )
static Mat createInitialImage( const Mat& img, bool doubleImageSize, float sigma, bool enable_precise_upscale )
{
CV_TRACE_FUNCTION();
@@ -188,12 +191,22 @@ static Mat createInitialImage( const Mat& img, bool doubleImageSize, float sigma
if( doubleImageSize )
{
sig_diff = sqrtf( std::max(sigma * sigma - SIFT_INIT_SIGMA * SIFT_INIT_SIGMA * 4, 0.01f) );
Mat dbl;
if (enable_precise_upscale) {
dbl.create(Size(gray_fpt.cols*2, gray_fpt.rows*2), gray_fpt.type());
Mat H = Mat::zeros(2, 3, CV_32F);
H.at<float>(0, 0) = 0.5f;
H.at<float>(1, 1) = 0.5f;
cv::warpAffine(gray_fpt, dbl, H, dbl.size(), INTER_LINEAR | WARP_INVERSE_MAP, BORDER_REFLECT);
} else {
#if DoG_TYPE_SHORT
resize(gray_fpt, dbl, Size(gray_fpt.cols*2, gray_fpt.rows*2), 0, 0, INTER_LINEAR_EXACT);
resize(gray_fpt, dbl, Size(gray_fpt.cols*2, gray_fpt.rows*2), 0, 0, INTER_LINEAR_EXACT);
#else
resize(gray_fpt, dbl, Size(gray_fpt.cols*2, gray_fpt.rows*2), 0, 0, INTER_LINEAR);
resize(gray_fpt, dbl, Size(gray_fpt.cols*2, gray_fpt.rows*2), 0, 0, INTER_LINEAR);
#endif
}
Mat result;
GaussianBlur(dbl, result, Size(), sig_diff, sig_diff);
return result;
@@ -459,10 +472,14 @@ static void calcDescriptors(const std::vector<Mat>& gpyr, const std::vector<KeyP
//////////////////////////////////////////////////////////////////////////////////////////
SIFT_Impl::SIFT_Impl( int _nfeatures, int _nOctaveLayers,
double _contrastThreshold, double _edgeThreshold, double _sigma, int _descriptorType )
double _contrastThreshold, double _edgeThreshold, double _sigma, int _descriptorType, bool _enable_precise_upscale)
: nfeatures(_nfeatures), nOctaveLayers(_nOctaveLayers),
contrastThreshold(_contrastThreshold), edgeThreshold(_edgeThreshold), sigma(_sigma), descriptor_type(_descriptorType)
contrastThreshold(_contrastThreshold), edgeThreshold(_edgeThreshold), sigma(_sigma), descriptor_type(_descriptorType),
enable_precise_upscale(_enable_precise_upscale)
{
if (!enable_precise_upscale) {
CV_LOG_ONCE_INFO(NULL, "precise upscale disabled, this is now deprecated as it was found to induce a location bias");
}
}
int SIFT_Impl::descriptorSize() const
@@ -516,7 +533,7 @@ void SIFT_Impl::detectAndCompute(InputArray _image, InputArray _mask,
actualNOctaves = maxOctave - firstOctave + 1;
}
Mat base = createInitialImage(image, firstOctave < 0, (float)sigma);
Mat base = createInitialImage(image, firstOctave < 0, (float)sigma, enable_precise_upscale);
std::vector<Mat> gpyr;
int nOctaves = actualNOctaves > 0 ? actualNOctaves : cvRound(std::log( (double)std::min( base.cols, base.rows ) ) / std::log(2.) - 2) - firstOctave;
modules/features2d/src/sift.simd.hpp
+12 -11
View File
@@ -1003,7 +1003,6 @@ else // CV_8U
#endif
}
#else
float* dst = dstMat.ptr<float>(row);
float nrm1 = 0;
for( k = 0; k < len; k++ )
{
@@ -1011,20 +1010,22 @@ else // CV_8U
nrm1 += rawDst[k];
}
nrm1 = 1.f/std::max(nrm1, FLT_EPSILON);
if( dstMat.type() == CV_32F )
{
for( k = 0; k < len; k++ )
if( dstMat.type() == CV_32F )
{
dst[k] = std::sqrt(rawDst[k] * nrm1);
float *dst = dstMat.ptr<float>(row);
for( k = 0; k < len; k++ )
{
dst[k] = std::sqrt(rawDst[k] * nrm1);
}
}
}
else // CV_8U
{
for( k = 0; k < len; k++ )
else // CV_8U
{
dst[k] = saturate_cast<uchar>(std::sqrt(rawDst[k] * nrm1)*SIFT_INT_DESCR_FCTR);
uint8_t *dst = dstMat.ptr<uint8_t>(row);
for( k = 0; k < len; k++ )
{
dst[k] = saturate_cast<uchar>(std::sqrt(rawDst[k] * nrm1)*SIFT_INT_DESCR_FCTR);
}
}
}
#endif
}