|
|
|
/*M///////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
//
|
|
|
|
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
|
|
|
|
//
|
|
|
|
// By downloading, copying, installing or using the software you agree to this license.
|
|
|
|
// If you do not agree to this license, do not download, install,
|
|
|
|
// copy or use the software.
|
|
|
|
//
|
|
|
|
//
|
|
|
|
// License Agreement
|
|
|
|
// For Open Source Computer Vision Library
|
|
|
|
//
|
|
|
|
// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
|
|
|
|
// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
|
|
|
|
// Copyright (C) 2014-2015, Itseez Inc., all rights reserved.
|
|
|
|
// Third party copyrights are property of their respective owners.
|
|
|
|
//
|
|
|
|
// Redistribution and use in source and binary forms, with or without modification,
|
|
|
|
// are permitted provided that the following conditions are met:
|
|
|
|
//
|
|
|
|
// * Redistribution's of source code must retain the above copyright notice,
|
|
|
|
// this list of conditions and the following disclaimer.
|
|
|
|
//
|
|
|
|
// * Redistribution's in binary form must reproduce the above copyright notice,
|
|
|
|
// this list of conditions and the following disclaimer in the documentation
|
|
|
|
// and/or other materials provided with the distribution.
|
|
|
|
//
|
|
|
|
// * The name of the copyright holders may not be used to endorse or promote products
|
|
|
|
// derived from this software without specific prior written permission.
|
|
|
|
//
|
|
|
|
// This software is provided by the copyright holders and contributors "as is" and
|
|
|
|
// any express or implied warranties, including, but not limited to, the implied
|
|
|
|
// warranties of merchantability and fitness for a particular purpose are disclaimed.
|
|
|
|
// In no event shall the Intel Corporation or contributors be liable for any direct,
|
|
|
|
// indirect, incidental, special, exemplary, or consequential damages
|
|
|
|
// (including, but not limited to, procurement of substitute goods or services;
|
|
|
|
// loss of use, data, or profits; or business interruption) however caused
|
|
|
|
// and on any theory of liability, whether in contract, strict liability,
|
|
|
|
// or tort (including negligence or otherwise) arising in any way out of
|
|
|
|
// the use of this software, even if advised of the possibility of such damage.
|
|
|
|
//
|
|
|
|
//M*/
|
|
|
|
|
|
|
|
#include "precomp.hpp"
|
|
|
|
#include "opencl_kernels_imgproc.hpp"
|
|
|
|
|
|
|
|
namespace cv
|
|
|
|
{
|
|
|
|
|
|
|
|
static void calcMinEigenVal( const Mat& _cov, Mat& _dst )
|
|
|
|
{
|
|
|
|
int i, j;
|
|
|
|
Size size = _cov.size();
|
|
|
|
#if CV_SSE
|
|
|
|
volatile bool simd = checkHardwareSupport(CV_CPU_SSE);
|
|
|
|
#endif
|
|
|
|
|
|
|
|
if( _cov.isContinuous() && _dst.isContinuous() )
|
|
|
|
{
|
|
|
|
size.width *= size.height;
|
|
|
|
size.height = 1;
|
|
|
|
}
|
|
|
|
|
|
|
|
for( i = 0; i < size.height; i++ )
|
|
|
|
{
|
|
|
|
const float* cov = _cov.ptr<float>(i);
|
|
|
|
float* dst = _dst.ptr<float>(i);
|
|
|
|
j = 0;
|
|
|
|
#if CV_SSE
|
|
|
|
if( simd )
|
|
|
|
{
|
|
|
|
__m128 half = _mm_set1_ps(0.5f);
|
|
|
|
for( ; j <= size.width - 4; j += 4 )
|
|
|
|
{
|
|
|
|
__m128 t0 = _mm_loadu_ps(cov + j*3); // a0 b0 c0 x
|
|
|
|
__m128 t1 = _mm_loadu_ps(cov + j*3 + 3); // a1 b1 c1 x
|
|
|
|
__m128 t2 = _mm_loadu_ps(cov + j*3 + 6); // a2 b2 c2 x
|
|
|
|
__m128 t3 = _mm_loadu_ps(cov + j*3 + 9); // a3 b3 c3 x
|
|
|
|
__m128 a, b, c, t;
|
|
|
|
t = _mm_unpacklo_ps(t0, t1); // a0 a1 b0 b1
|
|
|
|
c = _mm_unpackhi_ps(t0, t1); // c0 c1 x x
|
|
|
|
b = _mm_unpacklo_ps(t2, t3); // a2 a3 b2 b3
|
|
|
|
c = _mm_movelh_ps(c, _mm_unpackhi_ps(t2, t3)); // c0 c1 c2 c3
|
|
|
|
a = _mm_movelh_ps(t, b);
|
|
|
|
b = _mm_movehl_ps(b, t);
|
|
|
|
a = _mm_mul_ps(a, half);
|
|
|
|
c = _mm_mul_ps(c, half);
|
|
|
|
t = _mm_sub_ps(a, c);
|
|
|
|
t = _mm_add_ps(_mm_mul_ps(t, t), _mm_mul_ps(b,b));
|
|
|
|
a = _mm_sub_ps(_mm_add_ps(a, c), _mm_sqrt_ps(t));
|
|
|
|
_mm_storeu_ps(dst + j, a);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
#elif CV_NEON
|
|
|
|
float32x4_t v_half = vdupq_n_f32(0.5f);
|
|
|
|
for( ; j <= size.width - 4; j += 4 )
|
|
|
|
{
|
|
|
|
float32x4x3_t v_src = vld3q_f32(cov + j * 3);
|
|
|
|
float32x4_t v_a = vmulq_f32(v_src.val[0], v_half);
|
|
|
|
float32x4_t v_b = v_src.val[1];
|
|
|
|
float32x4_t v_c = vmulq_f32(v_src.val[2], v_half);
|
|
|
|
|
|
|
|
float32x4_t v_t = vsubq_f32(v_a, v_c);
|
|
|
|
v_t = vmlaq_f32(vmulq_f32(v_t, v_t), v_b, v_b);
|
|
|
|
vst1q_f32(dst + j, vsubq_f32(vaddq_f32(v_a, v_c), cv_vsqrtq_f32(v_t)));
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
for( ; j < size.width; j++ )
|
|
|
|
{
|
|
|
|
float a = cov[j*3]*0.5f;
|
|
|
|
float b = cov[j*3+1];
|
|
|
|
float c = cov[j*3+2]*0.5f;
|
|
|
|
dst[j] = (float)((a + c) - std::sqrt((a - c)*(a - c) + b*b));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
static void calcHarris( const Mat& _cov, Mat& _dst, double k )
|
|
|
|
{
|
|
|
|
int i, j;
|
|
|
|
Size size = _cov.size();
|
|
|
|
#if CV_SSE
|
|
|
|
volatile bool simd = checkHardwareSupport(CV_CPU_SSE);
|
|
|
|
#endif
|
|
|
|
|
|
|
|
if( _cov.isContinuous() && _dst.isContinuous() )
|
|
|
|
{
|
|
|
|
size.width *= size.height;
|
|
|
|
size.height = 1;
|
|
|
|
}
|
|
|
|
|
|
|
|
for( i = 0; i < size.height; i++ )
|
|
|
|
{
|
|
|
|
const float* cov = _cov.ptr<float>(i);
|
|
|
|
float* dst = _dst.ptr<float>(i);
|
|
|
|
j = 0;
|
|
|
|
|
|
|
|
#if CV_SSE
|
|
|
|
if( simd )
|
|
|
|
{
|
|
|
|
__m128 k4 = _mm_set1_ps((float)k);
|
|
|
|
for( ; j <= size.width - 4; j += 4 )
|
|
|
|
{
|
|
|
|
__m128 t0 = _mm_loadu_ps(cov + j*3); // a0 b0 c0 x
|
|
|
|
__m128 t1 = _mm_loadu_ps(cov + j*3 + 3); // a1 b1 c1 x
|
|
|
|
__m128 t2 = _mm_loadu_ps(cov + j*3 + 6); // a2 b2 c2 x
|
|
|
|
__m128 t3 = _mm_loadu_ps(cov + j*3 + 9); // a3 b3 c3 x
|
|
|
|
__m128 a, b, c, t;
|
|
|
|
t = _mm_unpacklo_ps(t0, t1); // a0 a1 b0 b1
|
|
|
|
c = _mm_unpackhi_ps(t0, t1); // c0 c1 x x
|
|
|
|
b = _mm_unpacklo_ps(t2, t3); // a2 a3 b2 b3
|
|
|
|
c = _mm_movelh_ps(c, _mm_unpackhi_ps(t2, t3)); // c0 c1 c2 c3
|
|
|
|
a = _mm_movelh_ps(t, b);
|
|
|
|
b = _mm_movehl_ps(b, t);
|
|
|
|
t = _mm_add_ps(a, c);
|
|
|
|
a = _mm_sub_ps(_mm_mul_ps(a, c), _mm_mul_ps(b, b));
|
|
|
|
t = _mm_mul_ps(_mm_mul_ps(k4, t), t);
|
|
|
|
a = _mm_sub_ps(a, t);
|
|
|
|
_mm_storeu_ps(dst + j, a);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
#elif CV_NEON
|
|
|
|
float32x4_t v_k = vdupq_n_f32((float)k);
|
|
|
|
|
|
|
|
for( ; j <= size.width - 4; j += 4 )
|
|
|
|
{
|
|
|
|
float32x4x3_t v_src = vld3q_f32(cov + j * 3);
|
|
|
|
float32x4_t v_a = v_src.val[0], v_b = v_src.val[1], v_c = v_src.val[2];
|
|
|
|
float32x4_t v_ac_bb = vmlsq_f32(vmulq_f32(v_a, v_c), v_b, v_b);
|
|
|
|
float32x4_t v_ac = vaddq_f32(v_a, v_c);
|
|
|
|
vst1q_f32(dst + j, vmlsq_f32(v_ac_bb, v_k, vmulq_f32(v_ac, v_ac)));
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
|
|
|
|
for( ; j < size.width; j++ )
|
|
|
|
{
|
|
|
|
float a = cov[j*3];
|
|
|
|
float b = cov[j*3+1];
|
|
|
|
float c = cov[j*3+2];
|
|
|
|
dst[j] = (float)(a*c - b*b - k*(a + c)*(a + c));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
static void eigen2x2( const float* cov, float* dst, int n )
|
|
|
|
{
|
|
|
|
for( int j = 0; j < n; j++ )
|
|
|
|
{
|
|
|
|
double a = cov[j*3];
|
|
|
|
double b = cov[j*3+1];
|
|
|
|
double c = cov[j*3+2];
|
|
|
|
|
|
|
|
double u = (a + c)*0.5;
|
|
|
|
double v = std::sqrt((a - c)*(a - c)*0.25 + b*b);
|
|
|
|
double l1 = u + v;
|
|
|
|
double l2 = u - v;
|
|
|
|
|
|
|
|
double x = b;
|
|
|
|
double y = l1 - a;
|
|
|
|
double e = fabs(x);
|
|
|
|
|
|
|
|
if( e + fabs(y) < 1e-4 )
|
|
|
|
{
|
|
|
|
y = b;
|
|
|
|
x = l1 - c;
|
|
|
|
e = fabs(x);
|
|
|
|
if( e + fabs(y) < 1e-4 )
|
|
|
|
{
|
|
|
|
e = 1./(e + fabs(y) + FLT_EPSILON);
|
|
|
|
x *= e, y *= e;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
double d = 1./std::sqrt(x*x + y*y + DBL_EPSILON);
|
|
|
|
dst[6*j] = (float)l1;
|
|
|
|
dst[6*j + 2] = (float)(x*d);
|
|
|
|
dst[6*j + 3] = (float)(y*d);
|
|
|
|
|
|
|
|
x = b;
|
|
|
|
y = l2 - a;
|
|
|
|
e = fabs(x);
|
|
|
|
|
|
|
|
if( e + fabs(y) < 1e-4 )
|
|
|
|
{
|
|
|
|
y = b;
|
|
|
|
x = l2 - c;
|
|
|
|
e = fabs(x);
|
|
|
|
if( e + fabs(y) < 1e-4 )
|
|
|
|
{
|
|
|
|
e = 1./(e + fabs(y) + FLT_EPSILON);
|
|
|
|
x *= e, y *= e;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
d = 1./std::sqrt(x*x + y*y + DBL_EPSILON);
|
|
|
|
dst[6*j + 1] = (float)l2;
|
|
|
|
dst[6*j + 4] = (float)(x*d);
|
|
|
|
dst[6*j + 5] = (float)(y*d);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
static void calcEigenValsVecs( const Mat& _cov, Mat& _dst )
|
|
|
|
{
|
|
|
|
Size size = _cov.size();
|
|
|
|
if( _cov.isContinuous() && _dst.isContinuous() )
|
|
|
|
{
|
|
|
|
size.width *= size.height;
|
|
|
|
size.height = 1;
|
|
|
|
}
|
|
|
|
|
|
|
|
for( int i = 0; i < size.height; i++ )
|
|
|
|
{
|
|
|
|
const float* cov = _cov.ptr<float>(i);
|
|
|
|
float* dst = _dst.ptr<float>(i);
|
|
|
|
|
|
|
|
eigen2x2(cov, dst, size.width);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
enum { MINEIGENVAL=0, HARRIS=1, EIGENVALSVECS=2 };
|
|
|
|
|
|
|
|
|
|
|
|
static void
|
|
|
|
cornerEigenValsVecs( const Mat& src, Mat& eigenv, int block_size,
|
|
|
|
int aperture_size, int op_type, double k=0.,
|
|
|
|
int borderType=BORDER_DEFAULT )
|
|
|
|
{
|
|
|
|
#ifdef HAVE_TEGRA_OPTIMIZATION
|
|
|
|
if (tegra::useTegra() && tegra::cornerEigenValsVecs(src, eigenv, block_size, aperture_size, op_type, k, borderType))
|
|
|
|
return;
|
|
|
|
#endif
|
|
|
|
#if CV_SSE2
|
|
|
|
bool haveSSE2 = checkHardwareSupport(CV_CPU_SSE2);
|
|
|
|
#endif
|
|
|
|
|
|
|
|
int depth = src.depth();
|
|
|
|
double scale = (double)(1 << ((aperture_size > 0 ? aperture_size : 3) - 1)) * block_size;
|
|
|
|
if( aperture_size < 0 )
|
|
|
|
scale *= 2.0;
|
|
|
|
if( depth == CV_8U )
|
|
|
|
scale *= 255.0;
|
|
|
|
scale = 1.0/scale;
|
|
|
|
|
|
|
|
CV_Assert( src.type() == CV_8UC1 || src.type() == CV_32FC1 );
|
|
|
|
|
|
|
|
Mat Dx, Dy;
|
|
|
|
if( aperture_size > 0 )
|
|
|
|
{
|
|
|
|
Sobel( src, Dx, CV_32F, 1, 0, aperture_size, scale, 0, borderType );
|
|
|
|
Sobel( src, Dy, CV_32F, 0, 1, aperture_size, scale, 0, borderType );
|
|
|
|
}
|
|
|
|
else
|
|
|
|
{
|
|
|
|
Scharr( src, Dx, CV_32F, 1, 0, scale, 0, borderType );
|
|
|
|
Scharr( src, Dy, CV_32F, 0, 1, scale, 0, borderType );
|
|
|
|
}
|
|
|
|
|
|
|
|
Size size = src.size();
|
|
|
|
Mat cov( size, CV_32FC3 );
|
|
|
|
int i, j;
|
|
|
|
|
|
|
|
for( i = 0; i < size.height; i++ )
|
|
|
|
{
|
|
|
|
float* cov_data = cov.ptr<float>(i);
|
|
|
|
const float* dxdata = Dx.ptr<float>(i);
|
|
|
|
const float* dydata = Dy.ptr<float>(i);
|
|
|
|
j = 0;
|
|
|
|
|
|
|
|
#if CV_NEON
|
|
|
|
for( ; j <= size.width - 4; j += 4 )
|
|
|
|
{
|
|
|
|
float32x4_t v_dx = vld1q_f32(dxdata + j);
|
|
|
|
float32x4_t v_dy = vld1q_f32(dydata + j);
|
|
|
|
|
|
|
|
float32x4x3_t v_dst;
|
|
|
|
v_dst.val[0] = vmulq_f32(v_dx, v_dx);
|
|
|
|
v_dst.val[1] = vmulq_f32(v_dx, v_dy);
|
|
|
|
v_dst.val[2] = vmulq_f32(v_dy, v_dy);
|
|
|
|
|
|
|
|
vst3q_f32(cov_data + j * 3, v_dst);
|
|
|
|
}
|
|
|
|
#elif CV_SSE2
|
|
|
|
if (haveSSE2)
|
|
|
|
{
|
|
|
|
for( ; j <= size.width - 8; j += 8 )
|
|
|
|
{
|
|
|
|
__m128 v_dx_0 = _mm_loadu_ps(dxdata + j);
|
|
|
|
__m128 v_dx_1 = _mm_loadu_ps(dxdata + j + 4);
|
|
|
|
__m128 v_dy_0 = _mm_loadu_ps(dydata + j);
|
|
|
|
__m128 v_dy_1 = _mm_loadu_ps(dydata + j + 4);
|
|
|
|
|
|
|
|
__m128 v_dx2_0 = _mm_mul_ps(v_dx_0, v_dx_0);
|
|
|
|
__m128 v_dxy_0 = _mm_mul_ps(v_dx_0, v_dy_0);
|
|
|
|
__m128 v_dy2_0 = _mm_mul_ps(v_dy_0, v_dy_0);
|
|
|
|
__m128 v_dx2_1 = _mm_mul_ps(v_dx_1, v_dx_1);
|
|
|
|
__m128 v_dxy_1 = _mm_mul_ps(v_dx_1, v_dy_1);
|
|
|
|
__m128 v_dy2_1 = _mm_mul_ps(v_dy_1, v_dy_1);
|
|
|
|
|
|
|
|
_mm_interleave_ps(v_dx2_0, v_dx2_1, v_dxy_0, v_dxy_1, v_dy2_0, v_dy2_1);
|
|
|
|
|
|
|
|
_mm_storeu_ps(cov_data + j * 3, v_dx2_0);
|
|
|
|
_mm_storeu_ps(cov_data + j * 3 + 4, v_dx2_1);
|
|
|
|
_mm_storeu_ps(cov_data + j * 3 + 8, v_dxy_0);
|
|
|
|
_mm_storeu_ps(cov_data + j * 3 + 12, v_dxy_1);
|
|
|
|
_mm_storeu_ps(cov_data + j * 3 + 16, v_dy2_0);
|
|
|
|
_mm_storeu_ps(cov_data + j * 3 + 20, v_dy2_1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
|
|
|
|
for( ; j < size.width; j++ )
|
|
|
|
{
|
|
|
|
float dx = dxdata[j];
|
|
|
|
float dy = dydata[j];
|
|
|
|
|
|
|
|
cov_data[j*3] = dx*dx;
|
|
|
|
cov_data[j*3+1] = dx*dy;
|
|
|
|
cov_data[j*3+2] = dy*dy;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
boxFilter(cov, cov, cov.depth(), Size(block_size, block_size),
|
|
|
|
Point(-1,-1), false, borderType );
|
|
|
|
|
|
|
|
if( op_type == MINEIGENVAL )
|
|
|
|
calcMinEigenVal( cov, eigenv );
|
|
|
|
else if( op_type == HARRIS )
|
|
|
|
calcHarris( cov, eigenv, k );
|
|
|
|
else if( op_type == EIGENVALSVECS )
|
|
|
|
calcEigenValsVecs( cov, eigenv );
|
|
|
|
}
|
|
|
|
|
|
|
|
#ifdef HAVE_OPENCL
|
|
|
|
|
|
|
|
static bool extractCovData(InputArray _src, UMat & Dx, UMat & Dy, int depth,
|
|
|
|
float scale, int aperture_size, int borderType)
|
|
|
|
{
|
|
|
|
UMat src = _src.getUMat();
|
|
|
|
|
|
|
|
Size wholeSize;
|
|
|
|
Point ofs;
|
|
|
|
src.locateROI(wholeSize, ofs);
|
|
|
|
|
|
|
|
const int sobel_lsz = 16;
|
|
|
|
if ((aperture_size == 3 || aperture_size == 5 || aperture_size == 7 || aperture_size == -1) &&
|
|
|
|
wholeSize.height > sobel_lsz + (aperture_size >> 1) &&
|
|
|
|
wholeSize.width > sobel_lsz + (aperture_size >> 1))
|
|
|
|
{
|
|
|
|
CV_Assert(depth == CV_8U || depth == CV_32F);
|
|
|
|
|
|
|
|
Dx.create(src.size(), CV_32FC1);
|
|
|
|
Dy.create(src.size(), CV_32FC1);
|
|
|
|
|
|
|
|
size_t localsize[2] = { sobel_lsz, sobel_lsz };
|
|
|
|
size_t globalsize[2] = { localsize[0] * (1 + (src.cols - 1) / localsize[0]),
|
|
|
|
localsize[1] * (1 + (src.rows - 1) / localsize[1]) };
|
|
|
|
|
|
|
|
int src_offset_x = (int)((src.offset % src.step) / src.elemSize());
|
|
|
|
int src_offset_y = (int)(src.offset / src.step);
|
|
|
|
|
|
|
|
const char * const borderTypes[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT",
|
|
|
|
"BORDER_WRAP", "BORDER_REFLECT101" };
|
|
|
|
|
|
|
|
ocl::Kernel k(format("sobel%d", aperture_size).c_str(), ocl::imgproc::covardata_oclsrc,
|
|
|
|
cv::format("-D BLK_X=%d -D BLK_Y=%d -D %s -D SRCTYPE=%s%s",
|
|
|
|
(int)localsize[0], (int)localsize[1], borderTypes[borderType], ocl::typeToStr(depth),
|
|
|
|
aperture_size < 0 ? " -D SCHARR" : ""));
|
|
|
|
if (k.empty())
|
|
|
|
return false;
|
|
|
|
|
|
|
|
k.args(ocl::KernelArg::PtrReadOnly(src), (int)src.step, src_offset_x, src_offset_y,
|
|
|
|
ocl::KernelArg::WriteOnlyNoSize(Dx), ocl::KernelArg::WriteOnly(Dy),
|
|
|
|
wholeSize.height, wholeSize.width, scale);
|
|
|
|
|
|
|
|
return k.run(2, globalsize, localsize, false);
|
|
|
|
}
|
|
|
|
else
|
|
|
|
{
|
|
|
|
if (aperture_size > 0)
|
|
|
|
{
|
|
|
|
Sobel(_src, Dx, CV_32F, 1, 0, aperture_size, scale, 0, borderType);
|
|
|
|
Sobel(_src, Dy, CV_32F, 0, 1, aperture_size, scale, 0, borderType);
|
|
|
|
}
|
|
|
|
else
|
|
|
|
{
|
|
|
|
Scharr(_src, Dx, CV_32F, 1, 0, scale, 0, borderType);
|
|
|
|
Scharr(_src, Dy, CV_32F, 0, 1, scale, 0, borderType);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
|
|
|
|
static bool ocl_cornerMinEigenValVecs(InputArray _src, OutputArray _dst, int block_size,
|
|
|
|
int aperture_size, double k, int borderType, int op_type)
|
|
|
|
{
|
|
|
|
CV_Assert(op_type == HARRIS || op_type == MINEIGENVAL);
|
|
|
|
|
|
|
|
if ( !(borderType == BORDER_CONSTANT || borderType == BORDER_REPLICATE ||
|
|
|
|
borderType == BORDER_REFLECT || borderType == BORDER_REFLECT_101) )
|
|
|
|
return false;
|
|
|
|
|
|
|
|
int type = _src.type(), depth = CV_MAT_DEPTH(type);
|
|
|
|
if ( !(type == CV_8UC1 || type == CV_32FC1) )
|
|
|
|
return false;
|
|
|
|
|
|
|
|
const char * const borderTypes[] = { "BORDER_CONSTANT", "BORDER_REPLICATE", "BORDER_REFLECT",
|
|
|
|
"BORDER_WRAP", "BORDER_REFLECT101" };
|
|
|
|
const char * const cornerType[] = { "CORNER_MINEIGENVAL", "CORNER_HARRIS", 0 };
|
|
|
|
|
|
|
|
|
|
|
|
double scale = (double)(1 << ((aperture_size > 0 ? aperture_size : 3) - 1)) * block_size;
|
|
|
|
if (aperture_size < 0)
|
|
|
|
scale *= 2.0;
|
|
|
|
if (depth == CV_8U)
|
|
|
|
scale *= 255.0;
|
|
|
|
scale = 1.0 / scale;
|
|
|
|
|
|
|
|
UMat Dx, Dy;
|
|
|
|
if (!extractCovData(_src, Dx, Dy, depth, (float)scale, aperture_size, borderType))
|
|
|
|
return false;
|
|
|
|
|
|
|
|
ocl::Kernel cornelKernel("corner", ocl::imgproc::corner_oclsrc,
|
|
|
|
format("-D anX=%d -D anY=%d -D ksX=%d -D ksY=%d -D %s -D %s",
|
|
|
|
block_size / 2, block_size / 2, block_size, block_size,
|
|
|
|
borderTypes[borderType], cornerType[op_type]));
|
|
|
|
if (cornelKernel.empty())
|
|
|
|
return false;
|
|
|
|
|
|
|
|
_dst.createSameSize(_src, CV_32FC1);
|
|
|
|
UMat dst = _dst.getUMat();
|
|
|
|
|
|
|
|
cornelKernel.args(ocl::KernelArg::ReadOnly(Dx), ocl::KernelArg::ReadOnly(Dy),
|
|
|
|
ocl::KernelArg::WriteOnly(dst), (float)k);
|
|
|
|
|
|
|
|
size_t blockSizeX = 256, blockSizeY = 1;
|
|
|
|
size_t gSize = blockSizeX - block_size / 2 * 2;
|
|
|
|
size_t globalSizeX = (Dx.cols) % gSize == 0 ? Dx.cols / gSize * blockSizeX : (Dx.cols / gSize + 1) * blockSizeX;
|
|
|
|
size_t rows_per_thread = 2;
|
|
|
|
size_t globalSizeY = ((Dx.rows + rows_per_thread - 1) / rows_per_thread) % blockSizeY == 0 ?
|
|
|
|
((Dx.rows + rows_per_thread - 1) / rows_per_thread) :
|
|
|
|
(((Dx.rows + rows_per_thread - 1) / rows_per_thread) / blockSizeY + 1) * blockSizeY;
|
|
|
|
|
|
|
|
size_t globalsize[2] = { globalSizeX, globalSizeY }, localsize[2] = { blockSizeX, blockSizeY };
|
|
|
|
return cornelKernel.run(2, globalsize, localsize, false);
|
|
|
|
}
|
|
|
|
|
|
|
|
static bool ocl_preCornerDetect( InputArray _src, OutputArray _dst, int ksize, int borderType, int depth )
|
|
|
|
{
|
|
|
|
UMat Dx, Dy, D2x, D2y, Dxy;
|
|
|
|
|
|
|
|
if (!extractCovData(_src, Dx, Dy, depth, 1, ksize, borderType))
|
|
|
|
return false;
|
|
|
|
|
|
|
|
Sobel( _src, D2x, CV_32F, 2, 0, ksize, 1, 0, borderType );
|
|
|
|
Sobel( _src, D2y, CV_32F, 0, 2, ksize, 1, 0, borderType );
|
|
|
|
Sobel( _src, Dxy, CV_32F, 1, 1, ksize, 1, 0, borderType );
|
|
|
|
|
|
|
|
_dst.create( _src.size(), CV_32FC1 );
|
|
|
|
UMat dst = _dst.getUMat();
|
|
|
|
|
|
|
|
double factor = 1 << (ksize - 1);
|
|
|
|
if( depth == CV_8U )
|
|
|
|
factor *= 255;
|
|
|
|
factor = 1./(factor * factor * factor);
|
|
|
|
|
|
|
|
ocl::Kernel k("preCornerDetect", ocl::imgproc::precornerdetect_oclsrc);
|
|
|
|
if (k.empty())
|
|
|
|
return false;
|
|
|
|
|
|
|
|
k.args(ocl::KernelArg::ReadOnlyNoSize(Dx), ocl::KernelArg::ReadOnlyNoSize(Dy),
|
|
|
|
ocl::KernelArg::ReadOnlyNoSize(D2x), ocl::KernelArg::ReadOnlyNoSize(D2y),
|
|
|
|
ocl::KernelArg::ReadOnlyNoSize(Dxy), ocl::KernelArg::WriteOnly(dst), (float)factor);
|
|
|
|
|
|
|
|
size_t globalsize[2] = { dst.cols, dst.rows };
|
|
|
|
return k.run(2, globalsize, NULL, false);
|
|
|
|
}
|
|
|
|
|
|
|
|
#endif
|
|
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
#if defined(HAVE_IPP)
|
|
|
|
namespace cv
|
|
|
|
{
|
|
|
|
static bool ipp_cornerMinEigenVal( InputArray _src, OutputArray _dst, int blockSize, int ksize, int borderType )
|
|
|
|
{
|
|
|
|
#if IPP_VERSION_X100 >= 800
|
|
|
|
Mat src = _src.getMat();
|
|
|
|
_dst.create( src.size(), CV_32FC1 );
|
|
|
|
Mat dst = _dst.getMat();
|
|
|
|
|
|
|
|
{
|
|
|
|
typedef IppStatus (CV_STDCALL * ippiMinEigenValGetBufferSize)(IppiSize, int, int, int*);
|
|
|
|
typedef IppStatus (CV_STDCALL * ippiMinEigenVal)(const void*, int, Ipp32f*, int, IppiSize, IppiKernelType, int, int, Ipp8u*);
|
|
|
|
IppiKernelType kerType;
|
|
|
|
int kerSize = ksize;
|
|
|
|
if (ksize < 0)
|
|
|
|
{
|
|
|
|
kerType = ippKernelScharr;
|
|
|
|
kerSize = 3;
|
|
|
|
} else
|
|
|
|
{
|
|
|
|
kerType = ippKernelSobel;
|
|
|
|
}
|
|
|
|
bool isolated = (borderType & BORDER_ISOLATED) != 0;
|
|
|
|
int borderTypeNI = borderType & ~BORDER_ISOLATED;
|
|
|
|
if ((borderTypeNI == BORDER_REPLICATE && (!src.isSubmatrix() || isolated)) &&
|
|
|
|
(kerSize == 3 || kerSize == 5) && (blockSize == 3 || blockSize == 5))
|
|
|
|
{
|
|
|
|
ippiMinEigenValGetBufferSize getBufferSizeFunc = 0;
|
|
|
|
ippiMinEigenVal minEigenValFunc = 0;
|
|
|
|
float norm_coef = 0.f;
|
|
|
|
|
|
|
|
if (src.type() == CV_8UC1)
|
|
|
|
{
|
|
|
|
getBufferSizeFunc = (ippiMinEigenValGetBufferSize) ippiMinEigenValGetBufferSize_8u32f_C1R;
|
|
|
|
minEigenValFunc = (ippiMinEigenVal) ippiMinEigenVal_8u32f_C1R;
|
|
|
|
norm_coef = 1.f / 255.f;
|
|
|
|
} else if (src.type() == CV_32FC1)
|
|
|
|
{
|
|
|
|
getBufferSizeFunc = (ippiMinEigenValGetBufferSize) ippiMinEigenValGetBufferSize_32f_C1R;
|
|
|
|
minEigenValFunc = (ippiMinEigenVal) ippiMinEigenVal_32f_C1R;
|
|
|
|
norm_coef = 255.f;
|
|
|
|
}
|
|
|
|
norm_coef = kerType == ippKernelSobel ? norm_coef : norm_coef / 2.45f;
|
|
|
|
|
|
|
|
if (getBufferSizeFunc && minEigenValFunc)
|
|
|
|
{
|
|
|
|
int bufferSize;
|
|
|
|
IppiSize srcRoi = { src.cols, src.rows };
|
|
|
|
IppStatus ok = getBufferSizeFunc(srcRoi, kerSize, blockSize, &bufferSize);
|
|
|
|
if (ok >= 0)
|
|
|
|
{
|
|
|
|
AutoBuffer<uchar> buffer(bufferSize);
|
|
|
|
ok = minEigenValFunc(src.ptr(), (int) src.step, dst.ptr<Ipp32f>(), (int) dst.step, srcRoi, kerType, kerSize, blockSize, buffer);
|
|
|
|
CV_SUPPRESS_DEPRECATED_START
|
|
|
|
if (ok >= 0) ok = ippiMulC_32f_C1IR(norm_coef, dst.ptr<Ipp32f>(), (int) dst.step, srcRoi);
|
|
|
|
CV_SUPPRESS_DEPRECATED_END
|
|
|
|
if (ok >= 0)
|
|
|
|
{
|
|
|
|
CV_IMPL_ADD(CV_IMPL_IPP);
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
#else
|
|
|
|
CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(blockSize); CV_UNUSED(borderType);
|
|
|
|
#endif
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
|
|
|
|
void cv::cornerMinEigenVal( InputArray _src, OutputArray _dst, int blockSize, int ksize, int borderType )
|
|
|
|
{
|
|
|
|
CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
|
|
|
|
ocl_cornerMinEigenValVecs(_src, _dst, blockSize, ksize, 0.0, borderType, MINEIGENVAL))
|
|
|
|
|
|
|
|
#ifdef HAVE_IPP
|
|
|
|
int kerSize = (ksize < 0)?3:ksize;
|
|
|
|
bool isolated = (borderType & BORDER_ISOLATED) != 0;
|
|
|
|
int borderTypeNI = borderType & ~BORDER_ISOLATED;
|
|
|
|
#endif
|
|
|
|
CV_IPP_RUN(((borderTypeNI == BORDER_REPLICATE && (!_src.isSubmatrix() || isolated)) &&
|
|
|
|
(kerSize == 3 || kerSize == 5) && (blockSize == 3 || blockSize == 5)) && IPP_VERSION_X100 >= 800,
|
|
|
|
ipp_cornerMinEigenVal( _src, _dst, blockSize, ksize, borderType ));
|
|
|
|
|
|
|
|
|
|
|
|
Mat src = _src.getMat();
|
|
|
|
_dst.create( src.size(), CV_32FC1 );
|
|
|
|
Mat dst = _dst.getMat();
|
|
|
|
|
|
|
|
cornerEigenValsVecs( src, dst, blockSize, ksize, MINEIGENVAL, 0, borderType );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
#if defined(HAVE_IPP)
|
|
|
|
namespace cv
|
|
|
|
{
|
|
|
|
static bool ipp_cornerHarris( InputArray _src, OutputArray _dst, int blockSize, int ksize, double k, int borderType )
|
|
|
|
{
|
|
|
|
#if IPP_VERSION_X100 >= 810 && IPP_DISABLE_BLOCK
|
|
|
|
Mat src = _src.getMat();
|
|
|
|
_dst.create( src.size(), CV_32FC1 );
|
|
|
|
Mat dst = _dst.getMat();
|
|
|
|
|
|
|
|
{
|
|
|
|
int type = src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
|
|
|
|
int borderTypeNI = borderType & ~BORDER_ISOLATED;
|
|
|
|
bool isolated = (borderType & BORDER_ISOLATED) != 0;
|
|
|
|
|
|
|
|
if ( (ksize == 3 || ksize == 5) && (type == CV_8UC1 || type == CV_32FC1) &&
|
|
|
|
(borderTypeNI == BORDER_CONSTANT || borderTypeNI == BORDER_REPLICATE) && cn == 1 && (!src.isSubmatrix() || isolated) )
|
|
|
|
{
|
|
|
|
IppiSize roisize = { src.cols, src.rows };
|
|
|
|
IppiMaskSize masksize = ksize == 5 ? ippMskSize5x5 : ippMskSize3x3;
|
|
|
|
IppDataType datatype = type == CV_8UC1 ? ipp8u : ipp32f;
|
|
|
|
Ipp32s bufsize = 0;
|
|
|
|
|
|
|
|
double scale = (double)(1 << ((ksize > 0 ? ksize : 3) - 1)) * blockSize;
|
|
|
|
if (ksize < 0)
|
|
|
|
scale *= 2.0;
|
|
|
|
if (depth == CV_8U)
|
|
|
|
scale *= 255.0;
|
|
|
|
scale = std::pow(scale, -4.0);
|
|
|
|
|
|
|
|
if (ippiHarrisCornerGetBufferSize(roisize, masksize, blockSize, datatype, cn, &bufsize) >= 0)
|
|
|
|
{
|
|
|
|
Ipp8u * buffer = ippsMalloc_8u(bufsize);
|
|
|
|
IppiDifferentialKernel filterType = ksize > 0 ? ippFilterSobel : ippFilterScharr;
|
|
|
|
IppiBorderType borderTypeIpp = borderTypeNI == BORDER_CONSTANT ? ippBorderConst : ippBorderRepl;
|
|
|
|
IppStatus status = (IppStatus)-1;
|
|
|
|
|
|
|
|
if (depth == CV_8U)
|
|
|
|
status = ippiHarrisCorner_8u32f_C1R((const Ipp8u *)src.data, (int)src.step, (Ipp32f *)dst.data, (int)dst.step, roisize,
|
|
|
|
filterType, masksize, blockSize, (Ipp32f)k, (Ipp32f)scale, borderTypeIpp, 0, buffer);
|
|
|
|
else if (depth == CV_32F)
|
|
|
|
status = ippiHarrisCorner_32f_C1R((const Ipp32f *)src.data, (int)src.step, (Ipp32f *)dst.data, (int)dst.step, roisize,
|
|
|
|
filterType, masksize, blockSize, (Ipp32f)k, (Ipp32f)scale, borderTypeIpp, 0, buffer);
|
|
|
|
ippsFree(buffer);
|
|
|
|
|
|
|
|
if (status >= 0)
|
|
|
|
{
|
|
|
|
CV_IMPL_ADD(CV_IMPL_IPP);
|
|
|
|
return true;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
#else
|
|
|
|
CV_UNUSED(_src); CV_UNUSED(_dst); CV_UNUSED(blockSize); CV_UNUSED(ksize); CV_UNUSED(k); CV_UNUSED(borderType);
|
|
|
|
#endif
|
|
|
|
return false;
|
|
|
|
}
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
|
|
|
|
void cv::cornerHarris( InputArray _src, OutputArray _dst, int blockSize, int ksize, double k, int borderType )
|
|
|
|
{
|
|
|
|
CV_OCL_RUN(_src.dims() <= 2 && _dst.isUMat(),
|
|
|
|
ocl_cornerMinEigenValVecs(_src, _dst, blockSize, ksize, k, borderType, HARRIS))
|
|
|
|
|
|
|
|
#ifdef HAVE_IPP
|
|
|
|
int borderTypeNI = borderType & ~BORDER_ISOLATED;
|
|
|
|
bool isolated = (borderType & BORDER_ISOLATED) != 0;
|
|
|
|
#endif
|
|
|
|
CV_IPP_RUN(((ksize == 3 || ksize == 5) && (_src.type() == CV_8UC1 || _src.type() == CV_32FC1) &&
|
|
|
|
(borderTypeNI == BORDER_CONSTANT || borderTypeNI == BORDER_REPLICATE) && CV_MAT_CN(_src.type()) == 1 &&
|
|
|
|
(!_src.isSubmatrix() || isolated)) && IPP_VERSION_X100 >= 810 && IPP_DISABLE_BLOCK, ipp_cornerHarris( _src, _dst, blockSize, ksize, k, borderType ));
|
|
|
|
|
|
|
|
|
|
|
|
Mat src = _src.getMat();
|
|
|
|
_dst.create( src.size(), CV_32FC1 );
|
|
|
|
Mat dst = _dst.getMat();
|
|
|
|
|
|
|
|
|
|
|
|
cornerEigenValsVecs( src, dst, blockSize, ksize, HARRIS, k, borderType );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void cv::cornerEigenValsAndVecs( InputArray _src, OutputArray _dst, int blockSize, int ksize, int borderType )
|
|
|
|
{
|
|
|
|
Mat src = _src.getMat();
|
|
|
|
Size dsz = _dst.size();
|
|
|
|
int dtype = _dst.type();
|
|
|
|
|
|
|
|
if( dsz.height != src.rows || dsz.width*CV_MAT_CN(dtype) != src.cols*6 || CV_MAT_DEPTH(dtype) != CV_32F )
|
|
|
|
_dst.create( src.size(), CV_32FC(6) );
|
|
|
|
Mat dst = _dst.getMat();
|
|
|
|
cornerEigenValsVecs( src, dst, blockSize, ksize, EIGENVALSVECS, 0, borderType );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void cv::preCornerDetect( InputArray _src, OutputArray _dst, int ksize, int borderType )
|
|
|
|
{
|
|
|
|
int type = _src.type();
|
|
|
|
CV_Assert( type == CV_8UC1 || type == CV_32FC1 );
|
|
|
|
|
|
|
|
CV_OCL_RUN( _src.dims() <= 2 && _dst.isUMat(),
|
|
|
|
ocl_preCornerDetect(_src, _dst, ksize, borderType, CV_MAT_DEPTH(type)))
|
|
|
|
|
|
|
|
Mat Dx, Dy, D2x, D2y, Dxy, src = _src.getMat();
|
|
|
|
_dst.create( src.size(), CV_32FC1 );
|
|
|
|
Mat dst = _dst.getMat();
|
|
|
|
|
|
|
|
Sobel( src, Dx, CV_32F, 1, 0, ksize, 1, 0, borderType );
|
|
|
|
Sobel( src, Dy, CV_32F, 0, 1, ksize, 1, 0, borderType );
|
|
|
|
Sobel( src, D2x, CV_32F, 2, 0, ksize, 1, 0, borderType );
|
|
|
|
Sobel( src, D2y, CV_32F, 0, 2, ksize, 1, 0, borderType );
|
|
|
|
Sobel( src, Dxy, CV_32F, 1, 1, ksize, 1, 0, borderType );
|
|
|
|
|
|
|
|
double factor = 1 << (ksize - 1);
|
|
|
|
if( src.depth() == CV_8U )
|
|
|
|
factor *= 255;
|
|
|
|
factor = 1./(factor * factor * factor);
|
|
|
|
#if CV_NEON || CV_SSE2
|
|
|
|
float factor_f = (float)factor;
|
|
|
|
#endif
|
|
|
|
|
|
|
|
#if CV_SSE2
|
|
|
|
volatile bool haveSSE2 = cv::checkHardwareSupport(CV_CPU_SSE2);
|
|
|
|
__m128 v_factor = _mm_set1_ps(factor_f), v_m2 = _mm_set1_ps(-2.0f);
|
|
|
|
#endif
|
|
|
|
|
|
|
|
Size size = src.size();
|
|
|
|
int i, j;
|
|
|
|
for( i = 0; i < size.height; i++ )
|
|
|
|
{
|
|
|
|
float* dstdata = dst.ptr<float>(i);
|
|
|
|
const float* dxdata = Dx.ptr<float>(i);
|
|
|
|
const float* dydata = Dy.ptr<float>(i);
|
|
|
|
const float* d2xdata = D2x.ptr<float>(i);
|
|
|
|
const float* d2ydata = D2y.ptr<float>(i);
|
|
|
|
const float* dxydata = Dxy.ptr<float>(i);
|
|
|
|
|
|
|
|
j = 0;
|
|
|
|
|
|
|
|
#if CV_SSE2
|
|
|
|
if (haveSSE2)
|
|
|
|
{
|
|
|
|
for( ; j <= size.width - 4; j += 4 )
|
|
|
|
{
|
|
|
|
__m128 v_dx = _mm_loadu_ps((const float *)(dxdata + j));
|
|
|
|
__m128 v_dy = _mm_loadu_ps((const float *)(dydata + j));
|
|
|
|
|
|
|
|
__m128 v_s1 = _mm_mul_ps(_mm_mul_ps(v_dx, v_dx), _mm_loadu_ps((const float *)(d2ydata + j)));
|
|
|
|
__m128 v_s2 = _mm_mul_ps(_mm_mul_ps(v_dy, v_dy), _mm_loadu_ps((const float *)(d2xdata + j)));
|
|
|
|
__m128 v_s3 = _mm_mul_ps(_mm_mul_ps(v_dx, v_dy), _mm_loadu_ps((const float *)(dxydata + j)));
|
|
|
|
v_s1 = _mm_mul_ps(v_factor, _mm_add_ps(v_s1, _mm_add_ps(v_s2, _mm_mul_ps(v_s3, v_m2))));
|
|
|
|
_mm_storeu_ps(dstdata + j, v_s1);
|
|
|
|
}
|
|
|
|
}
|
|
|
|
#elif CV_NEON
|
|
|
|
for( ; j <= size.width - 4; j += 4 )
|
|
|
|
{
|
|
|
|
float32x4_t v_dx = vld1q_f32(dxdata + j), v_dy = vld1q_f32(dydata + j);
|
|
|
|
float32x4_t v_s = vmulq_f32(v_dx, vmulq_f32(v_dx, vld1q_f32(d2ydata + j)));
|
|
|
|
v_s = vmlaq_f32(v_s, vld1q_f32(d2xdata + j), vmulq_f32(v_dy, v_dy));
|
|
|
|
v_s = vmlaq_f32(v_s, vld1q_f32(dxydata + j), vmulq_n_f32(vmulq_f32(v_dy, v_dx), -2));
|
|
|
|
vst1q_f32(dstdata + j, vmulq_n_f32(v_s, factor_f));
|
|
|
|
}
|
|
|
|
#endif
|
|
|
|
|
|
|
|
for( ; j < size.width; j++ )
|
|
|
|
{
|
|
|
|
float dx = dxdata[j];
|
|
|
|
float dy = dydata[j];
|
|
|
|
dstdata[j] = (float)(factor*(dx*dx*d2ydata[j] + dy*dy*d2xdata[j] - 2*dx*dy*dxydata[j]));
|
|
|
|
}
|
|
|
|
}
|
|
|
|
}
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvCornerMinEigenVal( const CvArr* srcarr, CvArr* dstarr,
|
|
|
|
int block_size, int aperture_size )
|
|
|
|
{
|
|
|
|
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
|
|
|
|
|
|
|
|
CV_Assert( src.size() == dst.size() && dst.type() == CV_32FC1 );
|
|
|
|
cv::cornerMinEigenVal( src, dst, block_size, aperture_size, cv::BORDER_REPLICATE );
|
|
|
|
}
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvCornerHarris( const CvArr* srcarr, CvArr* dstarr,
|
|
|
|
int block_size, int aperture_size, double k )
|
|
|
|
{
|
|
|
|
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
|
|
|
|
|
|
|
|
CV_Assert( src.size() == dst.size() && dst.type() == CV_32FC1 );
|
|
|
|
cv::cornerHarris( src, dst, block_size, aperture_size, k, cv::BORDER_REPLICATE );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvCornerEigenValsAndVecs( const void* srcarr, void* dstarr,
|
|
|
|
int block_size, int aperture_size )
|
|
|
|
{
|
|
|
|
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
|
|
|
|
|
|
|
|
CV_Assert( src.rows == dst.rows && src.cols*6 == dst.cols*dst.channels() && dst.depth() == CV_32F );
|
|
|
|
cv::cornerEigenValsAndVecs( src, dst, block_size, aperture_size, cv::BORDER_REPLICATE );
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
CV_IMPL void
|
|
|
|
cvPreCornerDetect( const void* srcarr, void* dstarr, int aperture_size )
|
|
|
|
{
|
|
|
|
cv::Mat src = cv::cvarrToMat(srcarr), dst = cv::cvarrToMat(dstarr);
|
|
|
|
|
|
|
|
CV_Assert( src.size() == dst.size() && dst.type() == CV_32FC1 );
|
|
|
|
cv::preCornerDetect( src, dst, aperture_size, cv::BORDER_REPLICATE );
|
|
|
|
}
|
|
|
|
|
|
|
|
/* End of file */
|