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Merge remote-tracking branch 'upstream/3.4' into merge-3.4

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Alexander Alekhin 2019-07-18 19:15:14 +00:00
commit 199ddff13b
15 changed files with 437 additions and 394 deletions
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3
modules/calib3d/CMakeLists.txt
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@ -1,4 +1,7 @@
set(the_description "Camera Calibration and 3D Reconstruction")
ocv_add_dispatched_file(undistort SSE2 AVX2)
set(debug_modules "")
if(DEBUG_opencv_calib3d)
list(APPEND debug_modules opencv_highgui)

19
modules/calib3d/perf/perf_undistort.cpp Normal file
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@ -0,0 +1,19 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
#include "perf_precomp.hpp"
namespace opencv_test {
PERF_TEST(Undistort, InitUndistortMap)
{
Size size_w_h(512 + 3, 512);
Mat k(3, 3, CV_32FC1);
Mat d(1, 14, CV_64FC1);
Mat dst(size_w_h, CV_32FC2);
declare.in(k, d, WARMUP_RNG).out(dst);
TEST_CYCLE() initUndistortRectifyMap(k, d, noArray(), k, size_w_h, CV_32FC2, dst, noArray());
SANITY_CHECK_NOTHING();
}
}

194
modules/calib3d/src/undistort.avx2.cpp
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@ -1,194 +0,0 @@
/*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.
// 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 "undistort.hpp"
namespace cv
{
int initUndistortRectifyMapLine_AVX(float* m1f, float* m2f, short* m1, ushort* m2, double* matTilt, const double* ir,
double& _x, double& _y, double& _w, int width, int m1type,
double k1, double k2, double k3, double k4, double k5, double k6,
double p1, double p2, double s1, double s2, double s3, double s4,
double u0, double v0, double fx, double fy)
{
int j = 0;
static const __m256d __one = _mm256_set1_pd(1.0);
static const __m256d __two = _mm256_set1_pd(2.0);
const __m256d __matTilt_00 = _mm256_set1_pd(matTilt[0]);
const __m256d __matTilt_10 = _mm256_set1_pd(matTilt[3]);
const __m256d __matTilt_20 = _mm256_set1_pd(matTilt[6]);
const __m256d __matTilt_01 = _mm256_set1_pd(matTilt[1]);
const __m256d __matTilt_11 = _mm256_set1_pd(matTilt[4]);
const __m256d __matTilt_21 = _mm256_set1_pd(matTilt[7]);
const __m256d __matTilt_02 = _mm256_set1_pd(matTilt[2]);
const __m256d __matTilt_12 = _mm256_set1_pd(matTilt[5]);
const __m256d __matTilt_22 = _mm256_set1_pd(matTilt[8]);
for (; j <= width - 4; j += 4, _x += 4 * ir[0], _y += 4 * ir[3], _w += 4 * ir[6])
{
// Question: Should we load the constants first?
__m256d __w = _mm256_div_pd(__one, _mm256_set_pd(_w + 3 * ir[6], _w + 2 * ir[6], _w + ir[6], _w));
__m256d __x = _mm256_mul_pd(_mm256_set_pd(_x + 3 * ir[0], _x + 2 * ir[0], _x + ir[0], _x), __w);
__m256d __y = _mm256_mul_pd(_mm256_set_pd(_y + 3 * ir[3], _y + 2 * ir[3], _y + ir[3], _y), __w);
__m256d __x2 = _mm256_mul_pd(__x, __x);
__m256d __y2 = _mm256_mul_pd(__y, __y);
__m256d __r2 = _mm256_add_pd(__x2, __y2);
__m256d __2xy = _mm256_mul_pd(__two, _mm256_mul_pd(__x, __y));
__m256d __kr = _mm256_div_pd(
#if CV_FMA3
_mm256_fmadd_pd(_mm256_fmadd_pd(_mm256_fmadd_pd(_mm256_set1_pd(k3), __r2, _mm256_set1_pd(k2)), __r2, _mm256_set1_pd(k1)), __r2, __one),
_mm256_fmadd_pd(_mm256_fmadd_pd(_mm256_fmadd_pd(_mm256_set1_pd(k6), __r2, _mm256_set1_pd(k5)), __r2, _mm256_set1_pd(k4)), __r2, __one)
#else
_mm256_add_pd(__one, _mm256_mul_pd(_mm256_add_pd(_mm256_mul_pd(_mm256_add_pd(_mm256_mul_pd(_mm256_set1_pd(k3), __r2), _mm256_set1_pd(k2)), __r2), _mm256_set1_pd(k1)), __r2)),
_mm256_add_pd(__one, _mm256_mul_pd(_mm256_add_pd(_mm256_mul_pd(_mm256_add_pd(_mm256_mul_pd(_mm256_set1_pd(k6), __r2), _mm256_set1_pd(k5)), __r2), _mm256_set1_pd(k4)), __r2))
#endif
);
__m256d __r22 = _mm256_mul_pd(__r2, __r2);
#if CV_FMA3
__m256d __xd = _mm256_fmadd_pd(__x, __kr,
_mm256_add_pd(
_mm256_fmadd_pd(_mm256_set1_pd(p1), __2xy, _mm256_mul_pd(_mm256_set1_pd(p2), _mm256_fmadd_pd(__two, __x2, __r2))),
_mm256_fmadd_pd(_mm256_set1_pd(s1), __r2, _mm256_mul_pd(_mm256_set1_pd(s2), __r22))));
__m256d __yd = _mm256_fmadd_pd(__y, __kr,
_mm256_add_pd(
_mm256_fmadd_pd(_mm256_set1_pd(p1), _mm256_fmadd_pd(__two, __y2, __r2), _mm256_mul_pd(_mm256_set1_pd(p2), __2xy)),
_mm256_fmadd_pd(_mm256_set1_pd(s3), __r2, _mm256_mul_pd(_mm256_set1_pd(s4), __r22))));
__m256d __vecTilt2 = _mm256_fmadd_pd(__matTilt_20, __xd, _mm256_fmadd_pd(__matTilt_21, __yd, __matTilt_22));
#else
__m256d __xd = _mm256_add_pd(
_mm256_mul_pd(__x, __kr),
_mm256_add_pd(
_mm256_add_pd(
_mm256_mul_pd(_mm256_set1_pd(p1), __2xy),
_mm256_mul_pd(_mm256_set1_pd(p2), _mm256_add_pd(__r2, _mm256_mul_pd(__two, __x2)))),
_mm256_add_pd(
_mm256_mul_pd(_mm256_set1_pd(s1), __r2),
_mm256_mul_pd(_mm256_set1_pd(s2), __r22))));
__m256d __yd = _mm256_add_pd(
_mm256_mul_pd(__y, __kr),
_mm256_add_pd(
_mm256_add_pd(
_mm256_mul_pd(_mm256_set1_pd(p1), _mm256_add_pd(__r2, _mm256_mul_pd(__two, __y2))),
_mm256_mul_pd(_mm256_set1_pd(p2), __2xy)),
_mm256_add_pd(
_mm256_mul_pd(_mm256_set1_pd(s3), __r2),
_mm256_mul_pd(_mm256_set1_pd(s4), __r22))));
__m256d __vecTilt2 = _mm256_add_pd(_mm256_add_pd(
_mm256_mul_pd(__matTilt_20, __xd), _mm256_mul_pd(__matTilt_21, __yd)), __matTilt_22);
#endif
__m256d __invProj = _mm256_blendv_pd(
_mm256_div_pd(__one, __vecTilt2), __one,
_mm256_cmp_pd(__vecTilt2, _mm256_setzero_pd(), _CMP_EQ_OQ));
#if CV_FMA3
__m256d __u = _mm256_fmadd_pd(__matTilt_00, __xd, _mm256_fmadd_pd(__matTilt_01, __yd, __matTilt_02));
__u = _mm256_fmadd_pd(_mm256_mul_pd(_mm256_set1_pd(fx), __invProj), __u, _mm256_set1_pd(u0));
__m256d __v = _mm256_fmadd_pd(__matTilt_10, __xd, _mm256_fmadd_pd(__matTilt_11, __yd, __matTilt_12));
__v = _mm256_fmadd_pd(_mm256_mul_pd(_mm256_set1_pd(fy), __invProj), __v, _mm256_set1_pd(v0));
#else
__m256d __u = _mm256_add_pd(_mm256_add_pd(
_mm256_mul_pd(__matTilt_00, __xd), _mm256_mul_pd(__matTilt_01, __yd)), __matTilt_02);
__u = _mm256_add_pd(_mm256_mul_pd(_mm256_mul_pd(_mm256_set1_pd(fx), __invProj), __u), _mm256_set1_pd(u0));
__m256d __v = _mm256_add_pd(_mm256_add_pd(
_mm256_mul_pd(__matTilt_10, __xd), _mm256_mul_pd(__matTilt_11, __yd)), __matTilt_12);
__v = _mm256_add_pd(_mm256_mul_pd(_mm256_mul_pd(_mm256_set1_pd(fy), __invProj), __v), _mm256_set1_pd(v0));
#endif
if (m1type == CV_32FC1)
{
_mm_storeu_ps(&m1f[j], _mm256_cvtpd_ps(__u));
_mm_storeu_ps(&m2f[j], _mm256_cvtpd_ps(__v));
}
else if (m1type == CV_32FC2)
{
__m128 __u_float = _mm256_cvtpd_ps(__u);
__m128 __v_float = _mm256_cvtpd_ps(__v);
_mm_storeu_ps(&m1f[j * 2], _mm_unpacklo_ps(__u_float, __v_float));
_mm_storeu_ps(&m1f[j * 2 + 4], _mm_unpackhi_ps(__u_float, __v_float));
}
else // m1type == CV_16SC2
{
__u = _mm256_mul_pd(__u, _mm256_set1_pd(INTER_TAB_SIZE));
__v = _mm256_mul_pd(__v, _mm256_set1_pd(INTER_TAB_SIZE));
__m128i __iu = _mm256_cvtpd_epi32(__u);
__m128i __iv = _mm256_cvtpd_epi32(__v);
static const __m128i __INTER_TAB_SIZE_m1 = _mm_set1_epi32(INTER_TAB_SIZE - 1);
__m128i __m2 = _mm_add_epi32(
_mm_mullo_epi32(_mm_and_si128(__iv, __INTER_TAB_SIZE_m1), _mm_set1_epi32(INTER_TAB_SIZE)),
_mm_and_si128(__iu, __INTER_TAB_SIZE_m1));
__m2 = _mm_packus_epi32(__m2, __m2);
_mm_maskstore_epi64((long long int*) &m2[j], _mm_set_epi32(0, 0, 0xFFFFFFFF, 0xFFFFFFFF), __m2);
// gcc4.9 does not support _mm256_set_m128
// __m256i __m1 = _mm256_set_m128i(__iv, __iu);
__m256i __m1 = _mm256_setzero_si256();
__m1 = _mm256_inserti128_si256(__m1, __iu, 0);
__m1 = _mm256_inserti128_si256(__m1, __iv, 1);
__m1 = _mm256_srai_epi32(__m1, INTER_BITS); // v3 v2 v1 v0 u3 u2 u1 u0 (int32_t)
static const __m256i __permute_mask = _mm256_set_epi32(7, 3, 6, 2, 5, 1, 4, 0);
__m1 = _mm256_permutevar8x32_epi32(__m1, __permute_mask); // v3 u3 v2 u2 v1 u1 v0 u0 (int32_t)
__m1 = _mm256_packs_epi32(__m1, __m1); // x x x x v3 u3 v2 u2 x x x x v1 u1 v0 u0 (int16_t)
_mm_storeu_si128((__m128i*) &m1[j * 2], _mm256_extracti128_si256(_mm256_permute4x64_epi64(__m1, (2 << 2) + 0), 0));
}
}
_mm256_zeroupper();
return j;
}
}
/* End of file */

158
modules/calib3d/src/undistort.cpp → modules/calib3d/src/undistort.dispatch.cpp
View File

@ -42,11 +42,16 @@
#include "precomp.hpp"
#include "distortion_model.hpp"
#include "undistort.hpp"
#include "calib3d_c_api.h"
cv::Mat cv::getDefaultNewCameraMatrix( InputArray _cameraMatrix, Size imgsize,
#include "undistort.simd.hpp"
#include "undistort.simd_declarations.hpp" // defines CV_CPU_DISPATCH_MODES_ALL=AVX2,...,BASELINE based on CMakeLists.txt content
namespace cv
{
Mat getDefaultNewCameraMatrix( InputArray _cameraMatrix, Size imgsize,
bool centerPrincipalPoint )
{
Mat cameraMatrix = _cameraMatrix.getMat();
@ -63,134 +68,22 @@ cv::Mat cv::getDefaultNewCameraMatrix( InputArray _cameraMatrix, Size imgsize,
return newCameraMatrix;
}
class initUndistortRectifyMapComputer : public cv::ParallelLoopBody
namespace {
Ptr<ParallelLoopBody> getInitUndistortRectifyMapComputer(Size _size, Mat &_map1, Mat &_map2, int _m1type,
const double* _ir, Matx33d &_matTilt,
double _u0, double _v0, double _fx, double _fy,
double _k1, double _k2, double _p1, double _p2,
double _k3, double _k4, double _k5, double _k6,
double _s1, double _s2, double _s3, double _s4)
{
public:
initUndistortRectifyMapComputer(
cv::Size _size, cv::Mat &_map1, cv::Mat &_map2, int _m1type,
const double* _ir, cv::Matx33d &_matTilt,
double _u0, double _v0, double _fx, double _fy,
double _k1, double _k2, double _p1, double _p2,
double _k3, double _k4, double _k5, double _k6,
double _s1, double _s2, double _s3, double _s4)
: size(_size),
map1(_map1),
map2(_map2),
m1type(_m1type),
ir(_ir),
matTilt(_matTilt),
u0(_u0),
v0(_v0),
fx(_fx),
fy(_fy),
k1(_k1),
k2(_k2),
p1(_p1),
p2(_p2),
k3(_k3),
k4(_k4),
k5(_k5),
k6(_k6),
s1(_s1),
s2(_s2),
s3(_s3),
s4(_s4) {
#if CV_TRY_AVX2
useAVX2 = cv::checkHardwareSupport(CV_CPU_AVX2);
#endif
}
CV_INSTRUMENT_REGION();
void operator()( const cv::Range& range ) const CV_OVERRIDE
{
const int begin = range.start;
const int end = range.end;
CV_CPU_DISPATCH(getInitUndistortRectifyMapComputer, (_size, _map1, _map2, _m1type, _ir, _matTilt, _u0, _v0, _fx, _fy, _k1, _k2, _p1, _p2, _k3, _k4, _k5, _k6, _s1, _s2, _s3, _s4),
CV_CPU_DISPATCH_MODES_ALL);
}
}
for( int i = begin; i < end; i++ )
{
float* m1f = map1.ptr<float>(i);
float* m2f = map2.empty() ? 0 : map2.ptr<float>(i);
short* m1 = (short*)m1f;
ushort* m2 = (ushort*)m2f;
double _x = i*ir[1] + ir[2], _y = i*ir[4] + ir[5], _w = i*ir[7] + ir[8];
int j = 0;
if (m1type == CV_16SC2)
CV_Assert(m1 != NULL && m2 != NULL);
else if (m1type == CV_32FC1)
CV_Assert(m1f != NULL && m2f != NULL);
else
CV_Assert(m1 != NULL);
#if CV_TRY_AVX2
if( useAVX2 )
j = cv::initUndistortRectifyMapLine_AVX(m1f, m2f, m1, m2,
matTilt.val, ir, _x, _y, _w, size.width, m1type,
k1, k2, k3, k4, k5, k6, p1, p2, s1, s2, s3, s4, u0, v0, fx, fy);
#endif
for( ; j < size.width; j++, _x += ir[0], _y += ir[3], _w += ir[6] )
{
double w = 1./_w, x = _x*w, y = _y*w;
double x2 = x*x, y2 = y*y;
double r2 = x2 + y2, _2xy = 2*x*y;
double kr = (1 + ((k3*r2 + k2)*r2 + k1)*r2)/(1 + ((k6*r2 + k5)*r2 + k4)*r2);
double xd = (x*kr + p1*_2xy + p2*(r2 + 2*x2) + s1*r2+s2*r2*r2);
double yd = (y*kr + p1*(r2 + 2*y2) + p2*_2xy + s3*r2+s4*r2*r2);
cv::Vec3d vecTilt = matTilt*cv::Vec3d(xd, yd, 1);
double invProj = vecTilt(2) ? 1./vecTilt(2) : 1;
double u = fx*invProj*vecTilt(0) + u0;
double v = fy*invProj*vecTilt(1) + v0;
if( m1type == CV_16SC2 )
{
int iu = cv::saturate_cast<int>(u*cv::INTER_TAB_SIZE);
int iv = cv::saturate_cast<int>(v*cv::INTER_TAB_SIZE);
m1[j*2] = (short)(iu >> cv::INTER_BITS);
m1[j*2+1] = (short)(iv >> cv::INTER_BITS);
m2[j] = (ushort)((iv & (cv::INTER_TAB_SIZE-1))*cv::INTER_TAB_SIZE + (iu & (cv::INTER_TAB_SIZE-1)));
}
else if( m1type == CV_32FC1 )
{
m1f[j] = (float)u;
m2f[j] = (float)v;
}
else
{
m1f[j*2] = (float)u;
m1f[j*2+1] = (float)v;
}
}
}
}
private:
cv::Size size;
cv::Mat &map1;
cv::Mat &map2;
int m1type;
const double* ir;
cv::Matx33d &matTilt;
double u0;
double v0;
double fx;
double fy;
double k1;
double k2;
double p1;
double p2;
double k3;
double k4;
double k5;
double k6;
double s1;
double s2;
double s3;
double s4;
#if CV_TRY_AVX2
bool useAVX2;
#endif
};
void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoeffs,
void initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoeffs,
InputArray _matR, InputArray _newCameraMatrix,
Size size, int m1type, OutputArray _map1, OutputArray _map2 )
{
@ -263,17 +156,17 @@ void cv::initUndistortRectifyMap( InputArray _cameraMatrix, InputArray _distCoef
double tauY = distCoeffs.cols + distCoeffs.rows - 1 >= 14 ? distPtr[13] : 0.;
// Matrix for trapezoidal distortion of tilted image sensor
cv::Matx33d matTilt = cv::Matx33d::eye();
cv::detail::computeTiltProjectionMatrix(tauX, tauY, &matTilt);
Matx33d matTilt = Matx33d::eye();
detail::computeTiltProjectionMatrix(tauX, tauY, &matTilt);
parallel_for_(Range(0, size.height), initUndistortRectifyMapComputer(
parallel_for_(Range(0, size.height), *getInitUndistortRectifyMapComputer(
size, map1, map2, m1type, ir, matTilt, u0, v0,
fx, fy, k1, k2, p1, p2, k3, k4, k5, k6, s1, s2, s3, s4));
}
void cv::undistort( InputArray _src, OutputArray _dst, InputArray _cameraMatrix,
InputArray _distCoeffs, InputArray _newCameraMatrix )
void undistort( InputArray _src, OutputArray _dst, InputArray _cameraMatrix,
InputArray _distCoeffs, InputArray _newCameraMatrix )
{
CV_INSTRUMENT_REGION();
@ -319,6 +212,7 @@ void cv::undistort( InputArray _src, OutputArray _dst, InputArray _cameraMatrix,
}
}
}
CV_IMPL void
cvUndistort2( const CvArr* srcarr, CvArr* dstarr, const CvMat* Aarr, const CvMat* dist_coeffs, const CvMat* newAarr )

59
modules/calib3d/src/undistort.hpp
View File

@ -1,59 +0,0 @@
/*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.
// 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*/
#ifndef OPENCV_CALIB3D_UNDISTORT_HPP
#define OPENCV_CALIB3D_UNDISTORT_HPP
namespace cv
{
#if CV_TRY_AVX2
int initUndistortRectifyMapLine_AVX(float* m1f, float* m2f, short* m1, ushort* m2, double* matTilt, const double* ir,
double& _x, double& _y, double& _w, int width, int m1type,
double k1, double k2, double k3, double k4, double k5, double k6,
double p1, double p2, double s1, double s2, double s3, double s4,
double u0, double v0, double fx, double fy);
#endif
}
#endif // OPENCV_CALIB3D_UNDISTORT_HPP
/* End of file */

324
modules/calib3d/src/undistort.simd.hpp Normal file
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@ -0,0 +1,324 @@
/*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.
// 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 "opencv2/core/hal/intrin.hpp"
namespace cv {
CV_CPU_OPTIMIZATION_NAMESPACE_BEGIN
// forward declarations
Ptr<ParallelLoopBody> getInitUndistortRectifyMapComputer(Size _size, Mat &_map1, Mat &_map2, int _m1type,
const double* _ir, Matx33d &_matTilt,
double _u0, double _v0, double _fx, double _fy,
double _k1, double _k2, double _p1, double _p2,
double _k3, double _k4, double _k5, double _k6,
double _s1, double _s2, double _s3, double _s4);
#ifndef CV_CPU_OPTIMIZATION_DECLARATIONS_ONLY
namespace
{
class initUndistortRectifyMapComputer : public ParallelLoopBody
{
public:
initUndistortRectifyMapComputer(
Size _size, Mat &_map1, Mat &_map2, int _m1type,
const double* _ir, Matx33d &_matTilt,
double _u0, double _v0, double _fx, double _fy,
double _k1, double _k2, double _p1, double _p2,
double _k3, double _k4, double _k5, double _k6,
double _s1, double _s2, double _s3, double _s4)
: size(_size),
map1(_map1),
map2(_map2),
m1type(_m1type),
ir(_ir),
matTilt(_matTilt),
u0(_u0),
v0(_v0),
fx(_fx),
fy(_fy),
k1(_k1),
k2(_k2),
p1(_p1),
p2(_p2),
k3(_k3),
k4(_k4),
k5(_k5),
k6(_k6),
s1(_s1),
s2(_s2),
s3(_s3),
s4(_s4) {
#if CV_SIMD_64F
for (int i = 0; i < 2 * v_float64::nlanes; ++i)
{
s_x[i] = ir[0] * i;
s_y[i] = ir[3] * i;
s_w[i] = ir[6] * i;
}
#endif
}
void operator()( const cv::Range& range ) const CV_OVERRIDE
{
CV_INSTRUMENT_REGION();
const int begin = range.start;
const int end = range.end;
for( int i = begin; i < end; i++ )
{
float* m1f = map1.ptr<float>(i);
float* m2f = map2.empty() ? 0 : map2.ptr<float>(i);
short* m1 = (short*)m1f;
ushort* m2 = (ushort*)m2f;
double _x = i*ir[1] + ir[2], _y = i*ir[4] + ir[5], _w = i*ir[7] + ir[8];
int j = 0;
if (m1type == CV_16SC2)
CV_Assert(m1 != NULL && m2 != NULL);
else if (m1type == CV_32FC1)
CV_Assert(m1f != NULL && m2f != NULL);
else
CV_Assert(m1 != NULL);
#if CV_SIMD_64F
const v_float64 v_one = vx_setall_f64(1.0);
for (; j <= size.width - 2*v_float64::nlanes; j += 2*v_float64::nlanes, _x += 2*v_float64::nlanes * ir[0], _y += 2*v_float64::nlanes * ir[3], _w += 2*v_float64::nlanes * ir[6])
{
v_float64 m_0, m_1, m_2, m_3;
m_2 = v_one / (vx_setall_f64(_w) + vx_load(s_w));
m_3 = v_one / (vx_setall_f64(_w) + vx_load(s_w + v_float64::nlanes));
m_0 = vx_setall_f64(_x); m_1 = vx_setall_f64(_y);
v_float64 x_0 = (m_0 + vx_load(s_x)) * m_2;
v_float64 x_1 = (m_0 + vx_load(s_x + v_float64::nlanes)) * m_3;
v_float64 y_0 = (m_1 + vx_load(s_y)) * m_2;
v_float64 y_1 = (m_1 + vx_load(s_y + v_float64::nlanes)) * m_3;
v_float64 xd_0 = x_0 * x_0;
v_float64 yd_0 = y_0 * y_0;
v_float64 xd_1 = x_1 * x_1;
v_float64 yd_1 = y_1 * y_1;
v_float64 r2_0 = xd_0 + yd_0;
v_float64 r2_1 = xd_1 + yd_1;
m_1 = vx_setall_f64(k3);
m_2 = vx_setall_f64(k2);
m_3 = vx_setall_f64(k1);
m_0 = v_muladd(v_muladd(v_muladd(m_1, r2_0, m_2), r2_0, m_3), r2_0, v_one);
m_1 = v_muladd(v_muladd(v_muladd(m_1, r2_1, m_2), r2_1, m_3), r2_1, v_one);
m_3 = vx_setall_f64(k6);
m_2 = vx_setall_f64(k5);
m_0 /= v_muladd(v_muladd(v_muladd(m_3, r2_0, m_2), r2_0, vx_setall_f64(k4)), r2_0, v_one);
m_1 /= v_muladd(v_muladd(v_muladd(m_3, r2_1, m_2), r2_1, vx_setall_f64(k4)), r2_1, v_one);
x_0 *= m_0; y_0 *= m_0; x_1 *= m_1; y_1 *= m_1;
m_0 = vx_setall_f64(p1);
m_1 = vx_setall_f64(p2);
m_2 = vx_setall_f64(2.0);
xd_0 = v_muladd(v_muladd(m_2, xd_0, r2_0), m_1, x_0);
yd_0 = v_muladd(v_muladd(m_2, yd_0, r2_0), m_0, y_0);
xd_1 = v_muladd(v_muladd(m_2, xd_1, r2_1), m_1, x_1);
yd_1 = v_muladd(v_muladd(m_2, yd_1, r2_1), m_0, y_1);
m_0 *= m_2; m_1 *= m_2;
m_2 = x_0 * y_0;
m_3 = x_1 * y_1;
xd_0 = v_muladd(m_0, m_2, xd_0);
yd_0 = v_muladd(m_1, m_2, yd_0);
xd_1 = v_muladd(m_0, m_3, xd_1);
yd_1 = v_muladd(m_1, m_3, yd_1);
m_0 = r2_0 * r2_0;
m_1 = r2_1 * r2_1;
m_2 = vx_setall_f64(s2);
m_3 = vx_setall_f64(s1);
xd_0 = v_muladd(m_3, r2_0, v_muladd(m_2, m_0, xd_0));
xd_1 = v_muladd(m_3, r2_1, v_muladd(m_2, m_1, xd_1));
m_2 = vx_setall_f64(s4);
m_3 = vx_setall_f64(s3);
yd_0 = v_muladd(m_3, r2_0, v_muladd(m_2, m_0, yd_0));
yd_1 = v_muladd(m_3, r2_1, v_muladd(m_2, m_1, yd_1));
m_0 = vx_setall_f64(matTilt.val[0]);
m_1 = vx_setall_f64(matTilt.val[1]);
m_2 = vx_setall_f64(matTilt.val[2]);
x_0 = v_muladd(m_0, xd_0, v_muladd(m_1, yd_0, m_2));
x_1 = v_muladd(m_0, xd_1, v_muladd(m_1, yd_1, m_2));
m_0 = vx_setall_f64(matTilt.val[3]);
m_1 = vx_setall_f64(matTilt.val[4]);
m_2 = vx_setall_f64(matTilt.val[5]);
y_0 = v_muladd(m_0, xd_0, v_muladd(m_1, yd_0, m_2));
y_1 = v_muladd(m_0, xd_1, v_muladd(m_1, yd_1, m_2));
m_0 = vx_setall_f64(matTilt.val[6]);
m_1 = vx_setall_f64(matTilt.val[7]);
m_2 = vx_setall_f64(matTilt.val[8]);
r2_0 = v_muladd(m_0, xd_0, v_muladd(m_1, yd_0, m_2));
r2_1 = v_muladd(m_0, xd_1, v_muladd(m_1, yd_1, m_2));
m_0 = vx_setzero_f64();
r2_0 = v_select(r2_0 == m_0, v_one, v_one / r2_0);
r2_1 = v_select(r2_1 == m_0, v_one, v_one / r2_1);
m_0 = vx_setall_f64(fx);
m_1 = vx_setall_f64(u0);
m_2 = vx_setall_f64(fy);
m_3 = vx_setall_f64(v0);
x_0 = v_muladd(m_0 * r2_0, x_0, m_1);
y_0 = v_muladd(m_2 * r2_0, y_0, m_3);
x_1 = v_muladd(m_0 * r2_1, x_1, m_1);
y_1 = v_muladd(m_2 * r2_1, y_1, m_3);
if (m1type == CV_32FC1)
{
v_store(&m1f[j], v_cvt_f32(x_0, x_1));
v_store(&m2f[j], v_cvt_f32(y_0, y_1));
}
else if (m1type == CV_32FC2)
{
v_float32 mf0, mf1;
v_zip(v_cvt_f32(x_0, x_1), v_cvt_f32(y_0, y_1), mf0, mf1);
v_store(&m1f[j * 2], mf0);
v_store(&m1f[j * 2 + v_float32::nlanes], mf1);
}
else // m1type == CV_16SC2
{
m_0 = vx_setall_f64(INTER_TAB_SIZE);
x_0 *= m_0; x_1 *= m_0; y_0 *= m_0; y_1 *= m_0;
v_int32 mask = vx_setall_s32(INTER_TAB_SIZE - 1);
v_int32 iu = v_round(x_0, x_1);
v_int32 iv = v_round(y_0, y_1);
v_pack_u_store(&m2[j], (iu & mask) + (iv & mask) * vx_setall_s32(INTER_TAB_SIZE));
v_int32 out0, out1;
v_zip(iu >> INTER_BITS, iv >> INTER_BITS, out0, out1);
v_store(&m1[j * 2], v_pack(out0, out1));
}
}
vx_cleanup();
#endif
for( ; j < size.width; j++, _x += ir[0], _y += ir[3], _w += ir[6] )
{
double w = 1./_w, x = _x*w, y = _y*w;
double x2 = x*x, y2 = y*y;
double r2 = x2 + y2, _2xy = 2*x*y;
double kr = (1 + ((k3*r2 + k2)*r2 + k1)*r2)/(1 + ((k6*r2 + k5)*r2 + k4)*r2);
double xd = (x*kr + p1*_2xy + p2*(r2 + 2*x2) + s1*r2+s2*r2*r2);
double yd = (y*kr + p1*(r2 + 2*y2) + p2*_2xy + s3*r2+s4*r2*r2);
Vec3d vecTilt = matTilt*cv::Vec3d(xd, yd, 1);
double invProj = vecTilt(2) ? 1./vecTilt(2) : 1;
double u = fx*invProj*vecTilt(0) + u0;
double v = fy*invProj*vecTilt(1) + v0;
if( m1type == CV_16SC2 )
{
int iu = saturate_cast<int>(u*INTER_TAB_SIZE);
int iv = saturate_cast<int>(v*INTER_TAB_SIZE);
m1[j*2] = (short)(iu >> INTER_BITS);
m1[j*2+1] = (short)(iv >> INTER_BITS);
m2[j] = (ushort)((iv & (INTER_TAB_SIZE-1))*INTER_TAB_SIZE + (iu & (INTER_TAB_SIZE-1)));
}
else if( m1type == CV_32FC1 )
{
m1f[j] = (float)u;
m2f[j] = (float)v;
}
else
{
m1f[j*2] = (float)u;
m1f[j*2+1] = (float)v;
}
}
}
}
private:
Size size;
Mat &map1;
Mat &map2;
int m1type;
const double* ir;
Matx33d &matTilt;
double u0;
double v0;
double fx;
double fy;
double k1;
double k2;
double p1;
double p2;
double k3;
double k4;
double k5;
double k6;
double s1;
double s2;
double s3;
double s4;
#if CV_SIMD_64F
double s_x[2*v_float64::nlanes];
double s_y[2*v_float64::nlanes];
double s_w[2*v_float64::nlanes];
#endif
};
}
Ptr<ParallelLoopBody> getInitUndistortRectifyMapComputer(Size _size, Mat &_map1, Mat &_map2, int _m1type,
const double* _ir, Matx33d &_matTilt,
double _u0, double _v0, double _fx, double _fy,
double _k1, double _k2, double _p1, double _p2,
double _k3, double _k4, double _k5, double _k6,
double _s1, double _s2, double _s3, double _s4)
{
CV_INSTRUMENT_REGION();
return Ptr<initUndistortRectifyMapComputer>(new initUndistortRectifyMapComputer(_size, _map1, _map2, _m1type, _ir, _matTilt, _u0, _v0, _fx, _fy,
_k1, _k2, _p1, _p2, _k3, _k4, _k5, _k6, _s1, _s2, _s3, _s4));
}
#endif
CV_CPU_OPTIMIZATION_NAMESPACE_END
}
/* End of file */

1
modules/dnn/include/opencv2/dnn/all_layers.hpp
View File

@ -366,6 +366,7 @@ CV__DNN_INLINE_NS_BEGIN
*/
std::vector<std::vector<Range> > sliceRanges;
int axis;
int num_split;
static Ptr<SliceLayer> create(const LayerParams &params);
};

2
modules/dnn/include/opencv2/dnn/dnn.hpp
View File

@ -383,7 +383,7 @@ CV__DNN_INLINE_NS_BEGIN
/** @brief Dump net to String
* @returns String with structure, hyperparameters, backend, target and fusion
* To see correct backend, target and fusion run after forward().
* Call method after setInput(). To see correct backend, target and fusion run after forward().
*/
CV_WRAP String dump();
/** @brief Dump net structure, hyperparameters, backend, target and fusion to dot file

7
modules/dnn/src/dnn.cpp
View File

@ -2979,6 +2979,13 @@ String parseLayerParams(const String& name, const LayerParams& lp) {
String Net::dump()
{
CV_Assert(!empty());
if (impl->netInputLayer->inputsData.empty())
CV_Error(Error::StsError, "Requested set input");
if (!impl->netWasAllocated)
impl->setUpNet();
std::ostringstream out;
std::map<int, LayerData>& map = impl->layers;
int prefBackend = impl->preferableBackend;

8
modules/dnn/src/layers/slice_layer.cpp
View File

@ -61,6 +61,7 @@ public:
{
setParamsFrom(params);
axis = params.get<int>("axis", 1);
num_split = params.get<int>("num_split", 0);
if (params.has("slice_point"))
{
CV_Assert(!params.has("begin") && !params.has("size") && !params.has("end"));
@ -141,9 +142,10 @@ public:
else // Divide input blob on equal parts by axis.
{
CV_Assert(0 <= axis && axis < inpShape.size());
CV_Assert(requiredOutputs > 0 && inpShape[axis] % requiredOutputs == 0);
inpShape[axis] /= requiredOutputs;
outputs.resize(requiredOutputs, inpShape);
int splits = num_split ? num_split : requiredOutputs;
CV_Assert(splits > 0 && inpShape[axis] % splits == 0);
inpShape[axis] /= splits;
outputs.resize(splits, inpShape);
}
return false;
}

3
modules/dnn/src/tensorflow/tf_importer.cpp
View File

@ -1410,6 +1410,9 @@ void TFImporter::populateNet(Net dstNet)
axis = toNCHW(axis);
layerParams.set("axis", axis);
if (hasLayerAttr(layer, "num_split"))
layerParams.set("num_split", getLayerAttr(layer, "num_split").i());
int id = dstNet.addLayer(name, "Slice", layerParams);
layer_id[name] = id;

20
modules/dnn/test/test_misc.cpp
View File

@ -78,6 +78,26 @@ TEST(readNet, Regression)
EXPECT_FALSE(net.empty());
}
typedef testing::TestWithParam<tuple<Backend, Target> > dump;
TEST_P(dump, Regression)
{
const int backend = get<0>(GetParam());
const int target = get<1>(GetParam());
Net net = readNet(findDataFile("dnn/squeezenet_v1.1.prototxt"),
findDataFile("dnn/squeezenet_v1.1.caffemodel", false));
int size[] = {1, 3, 227, 227};
Mat input = cv::Mat::ones(4, size, CV_32F);
net.setInput(input);
net.setPreferableBackend(backend);
net.setPreferableTarget(target);
EXPECT_FALSE(net.dump().empty());
net.forward();
EXPECT_FALSE(net.dump().empty());
}
INSTANTIATE_TEST_CASE_P(/**/, dump, dnnBackendsAndTargets());
class FirstCustomLayer CV_FINAL : public Layer
{
public:

2
modules/dnn/test/test_onnx_importer.cpp
View File

@ -605,7 +605,7 @@ TEST_P(Test_ONNX_nets, Resnet34_kinetics)
if (target != DNN_TARGET_CPU)
throw SkipTestException("Only CPU is supported");
String onnxmodel = findDataFile("dnn/resnet-34_kinetics.onnx");
String onnxmodel = findDataFile("dnn/resnet-34_kinetics.onnx", false);
Mat image0 = imread(findDataFile("dnn/dog416.png"));
Mat image1 = imread(findDataFile("dnn/street.png"));

5
modules/dnn/test/test_tf_importer.cpp
View File

@ -350,6 +350,11 @@ TEST_P(Test_TensorFlow_layers, l2_normalize_3d)
runTensorFlowNet("l2_normalize_3d");
}
TEST_P(Test_TensorFlow_layers, Split)
{
runTensorFlowNet("split");
}
class Test_TensorFlow_nets : public DNNTestLayer {};
TEST_P(Test_TensorFlow_nets, MobileNet_SSD)

26
modules/imgproc/src/thresh.cpp
View File

@ -1142,6 +1142,9 @@ getThreshVal_Otsu_8u( const Mat& _src )
const int N = 256;
int i, j, h[N] = {0};
#if CV_ENABLE_UNROLLED
int h_unrolled[3][N] = {};
#endif
for( i = 0; i < size.height; i++ )
{
const uchar* src = _src.ptr() + step*i;
@ -1150,9 +1153,9 @@ getThreshVal_Otsu_8u( const Mat& _src )
for( ; j <= size.width - 4; j += 4 )
{
int v0 = src[j], v1 = src[j+1];
h[v0]++; h[v1]++;
h[v0]++; h_unrolled[0][v1]++;
v0 = src[j+2]; v1 = src[j+3];
h[v0]++; h[v1]++;
h_unrolled[1][v0]++; h_unrolled[2][v1]++;
}
#endif
for( ; j < size.width; j++ )
@ -1161,7 +1164,12 @@ getThreshVal_Otsu_8u( const Mat& _src )
double mu = 0, scale = 1./(size.width*size.height);
for( i = 0; i < N; i++ )
{
#if CV_ENABLE_UNROLLED
h[i] += h_unrolled[0][i] + h_unrolled[1][i] + h_unrolled[2][i];
#endif
mu += i*(double)h[i];
}
mu *= scale;
double mu1 = 0, q1 = 0;
@ -1206,6 +1214,9 @@ getThreshVal_Triangle_8u( const Mat& _src )
const int N = 256;
int i, j, h[N] = {0};
#if CV_ENABLE_UNROLLED
int h_unrolled[3][N] = {};
#endif
for( i = 0; i < size.height; i++ )
{
const uchar* src = _src.ptr() + step*i;
@ -1214,9 +1225,9 @@ getThreshVal_Triangle_8u( const Mat& _src )
for( ; j <= size.width - 4; j += 4 )
{
int v0 = src[j], v1 = src[j+1];
h[v0]++; h[v1]++;
h[v0]++; h_unrolled[0][v1]++;
v0 = src[j+2]; v1 = src[j+3];
h[v0]++; h[v1]++;
h_unrolled[1][v0]++; h_unrolled[2][v1]++;
}
#endif
for( ; j < size.width; j++ )
@ -1227,6 +1238,13 @@ getThreshVal_Triangle_8u( const Mat& _src )
int temp;
bool isflipped = false;
#if CV_ENABLE_UNROLLED
for( i = 0; i < N; i++ )
{
h[i] += h_unrolled[0][i] + h_unrolled[1][i] + h_unrolled[2][i];
}
#endif
for( i = 0; i < N; i++ )
{
if( h[i] > 0 )