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feat: 切换后端至PaddleOCR-NCNN，切换工程为CMake

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1.项目后端整体迁移至PaddleOCR-NCNN算法，已通过基本的兼容性测试
2.工程改为使用CMake组织，后续为了更好地兼容第三方库，不再提供QMake工程
3.重整权利声明文件，重整代码工程，确保最小化侵权风险

Log: 切换后端至PaddleOCR-NCNN，切换工程为CMake
Change-Id: I4d5d2c5d37505a4a24b389b1a4c5d12f17bfa38c
This commit is contained in:
wangzhengyang
2022-05-10 09:54:44 +08:00
parent ecdd171c6f
commit 718c41634f
10018 changed files with 3593797 additions and 186748 deletions
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77
3rdparty/opencv-4.5.4/modules/calib3d/perf/opencl/perf_stereobm.cpp vendored Normal file
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/*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) 2010-2012, Multicoreware, Inc., all rights reserved.
// Copyright (C) 2010-2012, Advanced Micro Devices, 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 "../perf_precomp.hpp"
#include "opencv2/ts/ocl_perf.hpp"
#ifdef HAVE_OPENCL
namespace opencv_test {
namespace ocl {
typedef tuple<int, int> StereoBMFixture_t;
typedef TestBaseWithParam<StereoBMFixture_t> StereoBMFixture;
OCL_PERF_TEST_P(StereoBMFixture, StereoBM, ::testing::Combine(OCL_PERF_ENUM(32, 64, 128), OCL_PERF_ENUM(11,21) ) )
{
const int n_disp = get<0>(GetParam()), winSize = get<1>(GetParam());
UMat left, right, disp;
imread(getDataPath("gpu/stereobm/aloe-L.png"), IMREAD_GRAYSCALE).copyTo(left);
imread(getDataPath("gpu/stereobm/aloe-R.png"), IMREAD_GRAYSCALE).copyTo(right);
ASSERT_FALSE(left.empty());
ASSERT_FALSE(right.empty());
declare.in(left, right);
Ptr<StereoBM> bm = StereoBM::create( n_disp, winSize );
bm->setPreFilterType(bm->PREFILTER_XSOBEL);
bm->setTextureThreshold(0);
OCL_TEST_CYCLE() bm->compute(left, right, disp);
SANITY_CHECK(disp, 1e-3, ERROR_RELATIVE);
}
}//ocl
}//cvtest
#endif

165
3rdparty/opencv-4.5.4/modules/calib3d/perf/perf_affine2d.cpp vendored Normal file
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// 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
// (3-clause BSD License)
//
// Copyright (C) 2015-2016, OpenCV Foundation, 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:
//
// * Redistributions of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistributions 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.
//
// * Neither the names of the copyright holders nor the names of the contributors
// may 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 copyright holders 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 "perf_precomp.hpp"
#include <algorithm>
#include <functional>
namespace opencv_test
{
using namespace perf;
CV_ENUM(Method, RANSAC, LMEDS)
typedef tuple<int, double, Method, size_t> AffineParams;
typedef TestBaseWithParam<AffineParams> EstimateAffine;
#define ESTIMATE_PARAMS Combine(Values(100000, 5000, 100), Values(0.99, 0.95, 0.9), Method::all(), Values(10, 0))
static float rngIn(float from, float to) { return from + (to-from) * (float)theRNG(); }
static Mat rngPartialAffMat() {
double theta = rngIn(0, (float)CV_PI*2.f);
double scale = rngIn(0, 3);
double tx = rngIn(-2, 2);
double ty = rngIn(-2, 2);
double aff[2*3] = { std::cos(theta) * scale, -std::sin(theta) * scale, tx,
std::sin(theta) * scale, std::cos(theta) * scale, ty };
return Mat(2, 3, CV_64F, aff).clone();
}
PERF_TEST_P( EstimateAffine, EstimateAffine2D, ESTIMATE_PARAMS )
{
AffineParams params = GetParam();
const int n = get<0>(params);
const double confidence = get<1>(params);
const int method = get<2>(params);
const size_t refining = get<3>(params);
Mat aff(2, 3, CV_64F);
cv::randu(aff, -2., 2.);
// LMEDS can't handle more than 50% outliers (by design)
int m;
if (method == LMEDS)
m = 3*n/5;
else
m = 2*n/5;
const float shift_outl = 15.f;
const float noise_level = 20.f;
Mat fpts(1, n, CV_32FC2);
Mat tpts(1, n, CV_32FC2);
randu(fpts, 0., 100.);
transform(fpts, tpts, aff);
/* adding noise to some points */
Mat outliers = tpts.colRange(m, n);
outliers.reshape(1) += shift_outl;
Mat noise (outliers.size(), outliers.type());
randu(noise, 0., noise_level);
outliers += noise;
Mat aff_est;
vector<uchar> inliers (n);
warmup(inliers, WARMUP_WRITE);
warmup(fpts, WARMUP_READ);
warmup(tpts, WARMUP_READ);
TEST_CYCLE()
{
aff_est = estimateAffine2D(fpts, tpts, inliers, method, 3, 2000, confidence, refining);
}
// we already have accuracy tests
SANITY_CHECK_NOTHING();
}
PERF_TEST_P( EstimateAffine, EstimateAffinePartial2D, ESTIMATE_PARAMS )
{
AffineParams params = GetParam();
const int n = get<0>(params);
const double confidence = get<1>(params);
const int method = get<2>(params);
const size_t refining = get<3>(params);
Mat aff = rngPartialAffMat();
int m;
// LMEDS can't handle more than 50% outliers (by design)
if (method == LMEDS)
m = 3*n/5;
else
m = 2*n/5;
const float shift_outl = 15.f; const float noise_level = 20.f;
Mat fpts(1, n, CV_32FC2);
Mat tpts(1, n, CV_32FC2);
randu(fpts, 0., 100.);
transform(fpts, tpts, aff);
/* adding noise*/
Mat outliers = tpts.colRange(m, n);
outliers.reshape(1) += shift_outl;
Mat noise (outliers.size(), outliers.type());
randu(noise, 0., noise_level);
outliers += noise;
Mat aff_est;
vector<uchar> inliers (n);
warmup(inliers, WARMUP_WRITE);
warmup(fpts, WARMUP_READ);
warmup(tpts, WARMUP_READ);
TEST_CYCLE()
{
aff_est = estimateAffinePartial2D(fpts, tpts, inliers, method, 3, 2000, confidence, refining);
}
// we already have accuracy tests
SANITY_CHECK_NOTHING();
}
} // namespace opencv_test

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3rdparty/opencv-4.5.4/modules/calib3d/perf/perf_cicrlesGrid.cpp vendored Normal file
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#include "perf_precomp.hpp"
namespace opencv_test
{
using namespace perf;
typedef tuple<std::string, cv::Size> String_Size_t;
typedef perf::TestBaseWithParam<String_Size_t> String_Size;
PERF_TEST_P(String_Size, asymm_circles_grid, testing::Values(
String_Size_t("cv/cameracalibration/asymmetric_circles/acircles1.png", Size(7,13)),
String_Size_t("cv/cameracalibration/asymmetric_circles/acircles2.png", Size(7,13)),
String_Size_t("cv/cameracalibration/asymmetric_circles/acircles3.png", Size(7,13)),
String_Size_t("cv/cameracalibration/asymmetric_circles/acircles4.png", Size(5,5)),
String_Size_t("cv/cameracalibration/asymmetric_circles/acircles5.png", Size(5,5)),
String_Size_t("cv/cameracalibration/asymmetric_circles/acircles6.png", Size(5,5)),
String_Size_t("cv/cameracalibration/asymmetric_circles/acircles7.png", Size(3,9)),
String_Size_t("cv/cameracalibration/asymmetric_circles/acircles8.png", Size(3,9)),
String_Size_t("cv/cameracalibration/asymmetric_circles/acircles9.png", Size(3,9))
)
)
{
string filename = getDataPath(get<0>(GetParam()));
Size gridSize = get<1>(GetParam());
Mat frame = imread(filename);
if (frame.empty())
FAIL() << "Unable to load source image " << filename;
vector<Point2f> ptvec;
ptvec.resize(gridSize.area());
cvtColor(frame, frame, COLOR_BGR2GRAY);
declare.in(frame).out(ptvec);
TEST_CYCLE() ASSERT_TRUE(findCirclesGrid(frame, gridSize, ptvec, CALIB_CB_CLUSTERING | CALIB_CB_ASYMMETRIC_GRID));
SANITY_CHECK(ptvec, 2);
}
} // namespace

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#include "perf_precomp.hpp"
#if defined(HAVE_HPX)
#include <hpx/hpx_main.hpp>
#endif
CV_PERF_TEST_MAIN(calib3d)

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3rdparty/opencv-4.5.4/modules/calib3d/perf/perf_pnp.cpp vendored Normal file
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#include "perf_precomp.hpp"
namespace opencv_test
{
using namespace perf;
CV_ENUM(pnpAlgo, SOLVEPNP_ITERATIVE, SOLVEPNP_EPNP, SOLVEPNP_P3P, SOLVEPNP_DLS, SOLVEPNP_UPNP)
typedef tuple<int, pnpAlgo> PointsNum_Algo_t;
typedef perf::TestBaseWithParam<PointsNum_Algo_t> PointsNum_Algo;
typedef perf::TestBaseWithParam<int> PointsNum;
PERF_TEST_P(PointsNum_Algo, solvePnP,
testing::Combine( //When non planar, DLT needs at least 6 points for SOLVEPNP_ITERATIVE flag
testing::Values(6, 3*9, 7*13), //TODO: find why results on 4 points are too unstable
testing::Values((int)SOLVEPNP_ITERATIVE, (int)SOLVEPNP_EPNP, (int)SOLVEPNP_UPNP, (int)SOLVEPNP_DLS)
)
)
{
int pointsNum = get<0>(GetParam());
pnpAlgo algo = get<1>(GetParam());
vector<Point2f> points2d(pointsNum);
vector<Point3f> points3d(pointsNum);
Mat rvec = Mat::zeros(3, 1, CV_32FC1);
Mat tvec = Mat::zeros(3, 1, CV_32FC1);
Mat distortion = Mat::zeros(5, 1, CV_32FC1);
Mat intrinsics = Mat::eye(3, 3, CV_32FC1);
intrinsics.at<float> (0, 0) = 400.0;
intrinsics.at<float> (1, 1) = 400.0;
intrinsics.at<float> (0, 2) = 640 / 2;
intrinsics.at<float> (1, 2) = 480 / 2;
warmup(points3d, WARMUP_RNG);
warmup(rvec, WARMUP_RNG);
warmup(tvec, WARMUP_RNG);
projectPoints(points3d, rvec, tvec, intrinsics, distortion, points2d);
//add noise
Mat noise(1, (int)points2d.size(), CV_32FC2);
randu(noise, 0, 0.01);
cv::add(points2d, noise, points2d);
declare.in(points3d, points2d);
declare.time(100);
TEST_CYCLE_N(1000)
{
cv::solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, algo);
}
SANITY_CHECK(rvec, 1e-4);
SANITY_CHECK(tvec, 1e-4);
}
PERF_TEST_P(PointsNum_Algo, solvePnPSmallPoints,
testing::Combine(
testing::Values(5),
testing::Values((int)SOLVEPNP_P3P, (int)SOLVEPNP_EPNP, (int)SOLVEPNP_DLS, (int)SOLVEPNP_UPNP)
)
)
{
int pointsNum = get<0>(GetParam());
pnpAlgo algo = get<1>(GetParam());
if( algo == SOLVEPNP_P3P )
pointsNum = 4;
vector<Point2f> points2d(pointsNum);
vector<Point3f> points3d(pointsNum);
Mat rvec = Mat::zeros(3, 1, CV_32FC1);
Mat tvec = Mat::zeros(3, 1, CV_32FC1);
Mat distortion = Mat::zeros(5, 1, CV_32FC1);
Mat intrinsics = Mat::eye(3, 3, CV_32FC1);
intrinsics.at<float> (0, 0) = 400.0f;
intrinsics.at<float> (1, 1) = 400.0f;
intrinsics.at<float> (0, 2) = 640 / 2;
intrinsics.at<float> (1, 2) = 480 / 2;
warmup(points3d, WARMUP_RNG);
warmup(rvec, WARMUP_RNG);
warmup(tvec, WARMUP_RNG);
// normalize Rodrigues vector
Mat rvec_tmp = Mat::eye(3, 3, CV_32F);
cv::Rodrigues(rvec, rvec_tmp);
cv::Rodrigues(rvec_tmp, rvec);
cv::projectPoints(points3d, rvec, tvec, intrinsics, distortion, points2d);
//add noise
Mat noise(1, (int)points2d.size(), CV_32FC2);
randu(noise, -0.001, 0.001);
cv::add(points2d, noise, points2d);
declare.in(points3d, points2d);
declare.time(100);
TEST_CYCLE_N(1000)
{
cv::solvePnP(points3d, points2d, intrinsics, distortion, rvec, tvec, false, algo);
}
SANITY_CHECK(rvec, 1e-1);
SANITY_CHECK(tvec, 1e-2);
}
PERF_TEST_P(PointsNum, DISABLED_SolvePnPRansac, testing::Values(5, 3*9, 7*13))
{
int count = GetParam();
Mat object(1, count, CV_32FC3);
randu(object, -100, 100);
Mat camera_mat(3, 3, CV_32FC1);
randu(camera_mat, 0.5, 1);
camera_mat.at<float>(0, 1) = 0.f;
camera_mat.at<float>(1, 0) = 0.f;
camera_mat.at<float>(2, 0) = 0.f;
camera_mat.at<float>(2, 1) = 0.f;
Mat dist_coef(1, 8, CV_32F, cv::Scalar::all(0));
vector<cv::Point2f> image_vec;
Mat rvec_gold(1, 3, CV_32FC1);
randu(rvec_gold, 0, 1);
Mat tvec_gold(1, 3, CV_32FC1);
randu(tvec_gold, 0, 1);
projectPoints(object, rvec_gold, tvec_gold, camera_mat, dist_coef, image_vec);
Mat image(1, count, CV_32FC2, &image_vec[0]);
Mat rvec;
Mat tvec;
TEST_CYCLE()
{
cv::solvePnPRansac(object, image, camera_mat, dist_coef, rvec, tvec);
}
SANITY_CHECK(rvec, 1e-6);
SANITY_CHECK(tvec, 1e-6);
}
} // namespace

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3rdparty/opencv-4.5.4/modules/calib3d/perf/perf_precomp.hpp vendored Normal file
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// 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
#ifndef __OPENCV_PERF_PRECOMP_HPP__
#define __OPENCV_PERF_PRECOMP_HPP__
#include "opencv2/ts.hpp"
#include "opencv2/calib3d.hpp"
#endif

182
3rdparty/opencv-4.5.4/modules/calib3d/perf/perf_stereosgbm.cpp vendored Normal file
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/*
* 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
* (3 - clause BSD License)
*
* Redistribution and use in source and binary forms, with or without modification,
* are permitted provided that the following conditions are met :
*
* * Redistributions of source code must retain the above copyright notice,
* this list of conditions and the following disclaimer.
*
* * Redistributions 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.
*
* * Neither the names of the copyright holders nor the names of the contributors
* may 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 copyright holders 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.
*/
#include "perf_precomp.hpp"
namespace opencv_test
{
using namespace perf;
using namespace testing;
static void MakeArtificialExample(Mat& dst_left_view, Mat& dst_view);
CV_ENUM(SGBMModes, StereoSGBM::MODE_SGBM, StereoSGBM::MODE_SGBM_3WAY, StereoSGBM::MODE_HH4);
typedef tuple<Size, int, SGBMModes> SGBMParams;
typedef TestBaseWithParam<SGBMParams> TestStereoCorrespSGBM;
#ifndef _DEBUG
PERF_TEST_P( TestStereoCorrespSGBM, SGBM, Combine(Values(Size(1280,720),Size(640,480)), Values(256,128), SGBMModes::all()) )
#else
PERF_TEST_P( TestStereoCorrespSGBM, DISABLED_TooLongInDebug_SGBM, Combine(Values(Size(1280,720),Size(640,480)), Values(256,128), SGBMModes::all()) )
#endif
{
SGBMParams params = GetParam();
Size sz = get<0>(params);
int num_disparities = get<1>(params);
int mode = get<2>(params);
Mat src_left(sz, CV_8UC3);
Mat src_right(sz, CV_8UC3);
Mat dst(sz, CV_16S);
MakeArtificialExample(src_left,src_right);
int wsize = 3;
int P1 = 8*src_left.channels()*wsize*wsize;
TEST_CYCLE()
{
Ptr<StereoSGBM> sgbm = StereoSGBM::create(0,num_disparities,wsize,P1,4*P1,1,63,25,0,0,mode);
sgbm->compute(src_left,src_right,dst);
}
SANITY_CHECK(dst, .01, ERROR_RELATIVE);
}
typedef tuple<Size, int> BMParams;
typedef TestBaseWithParam<BMParams> TestStereoCorrespBM;
PERF_TEST_P(TestStereoCorrespBM, BM, Combine(Values(Size(1280, 720), Size(640, 480)), Values(256, 128)))
{
BMParams params = GetParam();
Size sz = get<0>(params);
int num_disparities = get<1>(params);
Mat src_left(sz, CV_8UC1);
Mat src_right(sz, CV_8UC1);
Mat dst(sz, CV_16S);
MakeArtificialExample(src_left, src_right);
int wsize = 21;
TEST_CYCLE()
{
Ptr<StereoBM> bm = StereoBM::create(num_disparities, wsize);
bm->compute(src_left, src_right, dst);
}
SANITY_CHECK(dst, .01, ERROR_RELATIVE);
}
void MakeArtificialExample(Mat& dst_left_view, Mat& dst_right_view)
{
RNG rng(0);
int w = dst_left_view.cols;
int h = dst_left_view.rows;
//params:
unsigned char bg_level = (unsigned char)rng.uniform(0.0,255.0);
unsigned char fg_level = (unsigned char)rng.uniform(0.0,255.0);
int rect_width = (int)rng.uniform(w/16,w/2);
int rect_height = (int)rng.uniform(h/16,h/2);
int rect_disparity = (int)(0.15*w);
double sigma = 3.0;
int rect_x_offset = (w-rect_width) /2;
int rect_y_offset = (h-rect_height)/2;
if(dst_left_view.channels()==3)
{
dst_left_view = Scalar(Vec3b(bg_level,bg_level,bg_level));
dst_right_view = Scalar(Vec3b(bg_level,bg_level,bg_level));
}
else
{
dst_left_view = Scalar(bg_level);
dst_right_view = Scalar(bg_level);
}
Mat dst_left_view_rect = Mat(dst_left_view, Rect(rect_x_offset,rect_y_offset,rect_width,rect_height));
if(dst_left_view.channels()==3)
dst_left_view_rect = Scalar(Vec3b(fg_level,fg_level,fg_level));
else
dst_left_view_rect = Scalar(fg_level);
rect_x_offset-=rect_disparity;
Mat dst_right_view_rect = Mat(dst_right_view, Rect(rect_x_offset,rect_y_offset,rect_width,rect_height));
if(dst_right_view.channels()==3)
dst_right_view_rect = Scalar(Vec3b(fg_level,fg_level,fg_level));
else
dst_right_view_rect = Scalar(fg_level);
//add some gaussian noise:
unsigned char *l, *r;
for(int i=0;i<h;i++)
{
l = dst_left_view.ptr(i);
r = dst_right_view.ptr(i);
if(dst_left_view.channels()==3)
{
for(int j=0;j<w;j++)
{
l[0] = saturate_cast<unsigned char>(l[0] + rng.gaussian(sigma));
l[1] = saturate_cast<unsigned char>(l[1] + rng.gaussian(sigma));
l[2] = saturate_cast<unsigned char>(l[2] + rng.gaussian(sigma));
l+=3;
r[0] = saturate_cast<unsigned char>(r[0] + rng.gaussian(sigma));
r[1] = saturate_cast<unsigned char>(r[1] + rng.gaussian(sigma));
r[2] = saturate_cast<unsigned char>(r[2] + rng.gaussian(sigma));
r+=3;
}
}
else
{
for(int j=0;j<w;j++)
{
l[0] = saturate_cast<unsigned char>(l[0] + rng.gaussian(sigma));
l++;
r[0] = saturate_cast<unsigned char>(r[0] + rng.gaussian(sigma));
r++;
}
}
}
}
}

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// 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();
}
PERF_TEST(Undistort, DISABLED_InitInverseRectificationMap)
{
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() initInverseRectificationMap(k, d, noArray(), k, size_w_h, CV_32FC2, dst, noArray());
SANITY_CHECK_NOTHING();
}
} // namespace