929 lines
29 KiB
C++
929 lines
29 KiB
C++
/*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 "test_precomp.hpp"
|
|
|
|
using namespace cv;
|
|
using namespace std;
|
|
|
|
class CV_DefaultNewCameraMatrixTest : public cvtest::ArrayTest
|
|
{
|
|
public:
|
|
CV_DefaultNewCameraMatrixTest();
|
|
protected:
|
|
int prepare_test_case (int test_case_idx);
|
|
void prepare_to_validation( int test_case_idx );
|
|
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
|
|
void run_func();
|
|
|
|
private:
|
|
cv::Size img_size;
|
|
cv::Mat camera_mat;
|
|
cv::Mat new_camera_mat;
|
|
|
|
int matrix_type;
|
|
|
|
bool center_principal_point;
|
|
|
|
static const int MAX_X = 2048;
|
|
static const int MAX_Y = 2048;
|
|
static const int MAX_VAL = 10000;
|
|
};
|
|
|
|
CV_DefaultNewCameraMatrixTest::CV_DefaultNewCameraMatrixTest()
|
|
{
|
|
test_array[INPUT].push_back(NULL);
|
|
test_array[OUTPUT].push_back(NULL);
|
|
test_array[REF_OUTPUT].push_back(NULL);
|
|
}
|
|
|
|
void CV_DefaultNewCameraMatrixTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
|
|
{
|
|
cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx,sizes,types);
|
|
RNG& rng = ts->get_rng();
|
|
matrix_type = types[INPUT][0] = types[OUTPUT][0]= types[REF_OUTPUT][0] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
|
|
sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(3,3);
|
|
}
|
|
|
|
int CV_DefaultNewCameraMatrixTest::prepare_test_case(int test_case_idx)
|
|
{
|
|
int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
|
|
|
|
if (code <= 0)
|
|
return code;
|
|
|
|
RNG& rng = ts->get_rng();
|
|
|
|
img_size.width = cvtest::randInt(rng) % MAX_X + 1;
|
|
img_size.height = cvtest::randInt(rng) % MAX_Y + 1;
|
|
|
|
center_principal_point = ((cvtest::randInt(rng) % 2)!=0);
|
|
|
|
// Generating camera_mat matrix
|
|
double sz = MAX(img_size.width, img_size.height);
|
|
double aspect_ratio = cvtest::randReal(rng)*0.6 + 0.7;
|
|
double a[9] = {0,0,0,0,0,0,0,0,1};
|
|
Mat _a(3,3,CV_64F,a);
|
|
a[2] = (img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
|
|
a[5] = (img_size.height - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
|
|
a[0] = sz/(0.9 - cvtest::randReal(rng)*0.6);
|
|
a[4] = aspect_ratio*a[0];
|
|
|
|
Mat& _a0 = test_mat[INPUT][0];
|
|
cvtest::convert(_a, _a0, _a0.type());
|
|
camera_mat = _a0;
|
|
|
|
return code;
|
|
|
|
}
|
|
|
|
void CV_DefaultNewCameraMatrixTest::run_func()
|
|
{
|
|
new_camera_mat = cv::getDefaultNewCameraMatrix(camera_mat,img_size,center_principal_point);
|
|
}
|
|
|
|
void CV_DefaultNewCameraMatrixTest::prepare_to_validation( int /*test_case_idx*/ )
|
|
{
|
|
const Mat& src = test_mat[INPUT][0];
|
|
Mat& dst = test_mat[REF_OUTPUT][0];
|
|
Mat& test_output = test_mat[OUTPUT][0];
|
|
Mat& output = new_camera_mat;
|
|
cvtest::convert( output, test_output, test_output.type() );
|
|
if (!center_principal_point)
|
|
{
|
|
cvtest::copy(src, dst);
|
|
}
|
|
else
|
|
{
|
|
double a[9] = {0,0,0,0,0,0,0,0,1};
|
|
Mat _a(3,3,CV_64F,a);
|
|
if (matrix_type == CV_64F)
|
|
{
|
|
a[0] = src.at<double>(0,0);
|
|
a[4] = src.at<double>(1,1);
|
|
}
|
|
else
|
|
{
|
|
a[0] = src.at<float>(0,0);
|
|
a[4] = src.at<float>(1,1);
|
|
}
|
|
a[2] = (img_size.width - 1)*0.5;
|
|
a[5] = (img_size.height - 1)*0.5;
|
|
cvtest::convert( _a, dst, dst.type() );
|
|
}
|
|
}
|
|
|
|
//---------
|
|
|
|
class CV_UndistortPointsTest : public cvtest::ArrayTest
|
|
{
|
|
public:
|
|
CV_UndistortPointsTest();
|
|
protected:
|
|
int prepare_test_case (int test_case_idx);
|
|
void prepare_to_validation( int test_case_idx );
|
|
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
|
|
double get_success_error_level( int test_case_idx, int i, int j );
|
|
void run_func();
|
|
void distortPoints(const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatrix,
|
|
const CvMat* _distCoeffs, const CvMat* matR, const CvMat* matP);
|
|
|
|
private:
|
|
bool useCPlus;
|
|
bool useDstMat;
|
|
static const int N_POINTS = 10;
|
|
static const int MAX_X = 2048;
|
|
static const int MAX_Y = 2048;
|
|
|
|
bool zero_new_cam;
|
|
bool zero_distortion;
|
|
bool zero_R;
|
|
|
|
cv::Size img_size;
|
|
cv::Mat dst_points_mat;
|
|
|
|
cv::Mat camera_mat;
|
|
cv::Mat R;
|
|
cv::Mat P;
|
|
cv::Mat distortion_coeffs;
|
|
cv::Mat src_points;
|
|
std::vector<cv::Point2f> dst_points;
|
|
};
|
|
|
|
CV_UndistortPointsTest::CV_UndistortPointsTest()
|
|
{
|
|
test_array[INPUT].push_back(NULL); // points matrix
|
|
test_array[INPUT].push_back(NULL); // camera matrix
|
|
test_array[INPUT].push_back(NULL); // distortion coeffs
|
|
test_array[INPUT].push_back(NULL); // R matrix
|
|
test_array[INPUT].push_back(NULL); // P matrix
|
|
test_array[OUTPUT].push_back(NULL); // distorted dst points
|
|
test_array[TEMP].push_back(NULL); // dst points
|
|
test_array[REF_OUTPUT].push_back(NULL);
|
|
}
|
|
|
|
void CV_UndistortPointsTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
|
|
{
|
|
cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx,sizes,types);
|
|
RNG& rng = ts->get_rng();
|
|
useCPlus = ((cvtest::randInt(rng) % 2)!=0);
|
|
//useCPlus = 0;
|
|
if (useCPlus)
|
|
{
|
|
types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0]= CV_32FC2;
|
|
}
|
|
else
|
|
{
|
|
types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = types[TEMP][0]= cvtest::randInt(rng)%2 ? CV_64FC2 : CV_32FC2;
|
|
}
|
|
types[INPUT][1] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
|
|
types[INPUT][2] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
|
|
types[INPUT][3] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
|
|
types[INPUT][4] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
|
|
|
|
sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = sizes[TEMP][0]= cvtest::randInt(rng)%2 ? cvSize(1,N_POINTS) : cvSize(N_POINTS,1);
|
|
sizes[INPUT][1] = sizes[INPUT][3] = cvSize(3,3);
|
|
sizes[INPUT][4] = cvtest::randInt(rng)%2 ? cvSize(3,3) : cvSize(4,3);
|
|
|
|
if (cvtest::randInt(rng)%2)
|
|
{
|
|
if (cvtest::randInt(rng)%2)
|
|
{
|
|
sizes[INPUT][2] = cvSize(1,4);
|
|
}
|
|
else
|
|
{
|
|
sizes[INPUT][2] = cvSize(1,5);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
if (cvtest::randInt(rng)%2)
|
|
{
|
|
sizes[INPUT][2] = cvSize(4,1);
|
|
}
|
|
else
|
|
{
|
|
sizes[INPUT][2] = cvSize(5,1);
|
|
}
|
|
}
|
|
}
|
|
|
|
int CV_UndistortPointsTest::prepare_test_case(int test_case_idx)
|
|
{
|
|
RNG& rng = ts->get_rng();
|
|
int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
|
|
|
|
if (code <= 0)
|
|
return code;
|
|
|
|
useDstMat = (cvtest::randInt(rng) % 2) == 0;
|
|
|
|
img_size.width = cvtest::randInt(rng) % MAX_X + 1;
|
|
img_size.height = cvtest::randInt(rng) % MAX_Y + 1;
|
|
int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows;
|
|
double cam[9] = {0,0,0,0,0,0,0,0,1};
|
|
vector<double> dist(dist_size);
|
|
vector<double> proj(test_mat[INPUT][4].cols * test_mat[INPUT][4].rows);
|
|
vector<Point2d> points(N_POINTS);
|
|
|
|
Mat _camera(3,3,CV_64F,cam);
|
|
Mat _distort(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,&dist[0]);
|
|
Mat _proj(test_mat[INPUT][4].size(), CV_64F, &proj[0]);
|
|
Mat _points(test_mat[INPUT][0].size(), CV_64FC2, &points[0]);
|
|
|
|
_proj = Scalar::all(0);
|
|
|
|
//Generating points
|
|
for( int i = 0; i < N_POINTS; i++ )
|
|
{
|
|
points[i].x = cvtest::randReal(rng)*img_size.width;
|
|
points[i].y = cvtest::randReal(rng)*img_size.height;
|
|
}
|
|
|
|
//Generating camera matrix
|
|
double sz = MAX(img_size.width,img_size.height);
|
|
double aspect_ratio = cvtest::randReal(rng)*0.6 + 0.7;
|
|
cam[2] = (img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
|
|
cam[5] = (img_size.height - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
|
|
cam[0] = sz/(0.9 - cvtest::randReal(rng)*0.6);
|
|
cam[4] = aspect_ratio*cam[0];
|
|
|
|
//Generating distortion coeffs
|
|
dist[0] = cvtest::randReal(rng)*0.06 - 0.03;
|
|
dist[1] = cvtest::randReal(rng)*0.06 - 0.03;
|
|
if( dist[0]*dist[1] > 0 )
|
|
dist[1] = -dist[1];
|
|
if( cvtest::randInt(rng)%4 != 0 )
|
|
{
|
|
dist[2] = cvtest::randReal(rng)*0.004 - 0.002;
|
|
dist[3] = cvtest::randReal(rng)*0.004 - 0.002;
|
|
if (dist_size > 4)
|
|
dist[4] = cvtest::randReal(rng)*0.004 - 0.002;
|
|
}
|
|
else
|
|
{
|
|
dist[2] = dist[3] = 0;
|
|
if (dist_size > 4)
|
|
dist[4] = 0;
|
|
}
|
|
|
|
//Generating P matrix (projection)
|
|
if( test_mat[INPUT][4].cols != 4 )
|
|
{
|
|
proj[8] = 1;
|
|
if (cvtest::randInt(rng)%2 == 0) // use identity new camera matrix
|
|
{
|
|
proj[0] = 1;
|
|
proj[4] = 1;
|
|
}
|
|
else
|
|
{
|
|
proj[0] = cam[0] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[0]; //10%
|
|
proj[4] = cam[4] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[4]; //10%
|
|
proj[2] = cam[2] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.width; //15%
|
|
proj[5] = cam[5] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.height; //15%
|
|
}
|
|
}
|
|
else
|
|
{
|
|
proj[10] = 1;
|
|
proj[0] = cam[0] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[0]; //10%
|
|
proj[5] = cam[4] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[4]; //10%
|
|
proj[2] = cam[2] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.width; //15%
|
|
proj[6] = cam[5] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.height; //15%
|
|
|
|
proj[3] = (img_size.height + img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
|
|
proj[7] = (img_size.height + img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
|
|
proj[11] = (img_size.height + img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
|
|
}
|
|
|
|
//Generating R matrix
|
|
Mat _rot(3,3,CV_64F);
|
|
Mat rotation(1,3,CV_64F);
|
|
rotation.at<double>(0) = CV_PI*(cvtest::randReal(rng) - (double)0.5); // phi
|
|
rotation.at<double>(1) = CV_PI*(cvtest::randReal(rng) - (double)0.5); // ksi
|
|
rotation.at<double>(2) = CV_PI*(cvtest::randReal(rng) - (double)0.5); //khi
|
|
cvtest::Rodrigues(rotation, _rot);
|
|
|
|
//copying data
|
|
//src_points = &_points;
|
|
_points.convertTo(test_mat[INPUT][0], test_mat[INPUT][0].type());
|
|
_camera.convertTo(test_mat[INPUT][1], test_mat[INPUT][1].type());
|
|
_distort.convertTo(test_mat[INPUT][2], test_mat[INPUT][2].type());
|
|
_rot.convertTo(test_mat[INPUT][3], test_mat[INPUT][3].type());
|
|
_proj.convertTo(test_mat[INPUT][4], test_mat[INPUT][4].type());
|
|
|
|
zero_distortion = (cvtest::randInt(rng)%2) == 0 ? false : true;
|
|
zero_new_cam = (cvtest::randInt(rng)%2) == 0 ? false : true;
|
|
zero_R = (cvtest::randInt(rng)%2) == 0 ? false : true;
|
|
|
|
if (useCPlus)
|
|
{
|
|
_points.convertTo(src_points, CV_32F);
|
|
|
|
camera_mat = test_mat[INPUT][1];
|
|
distortion_coeffs = test_mat[INPUT][2];
|
|
R = test_mat[INPUT][3];
|
|
P = test_mat[INPUT][4];
|
|
}
|
|
|
|
return code;
|
|
}
|
|
|
|
void CV_UndistortPointsTest::prepare_to_validation(int /*test_case_idx*/)
|
|
{
|
|
int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows;
|
|
double cam[9] = {0,0,0,0,0,0,0,0,1};
|
|
double rot[9] = {1,0,0,0,1,0,0,0,1};
|
|
|
|
double* dist = new double[dist_size ];
|
|
double* proj = new double[test_mat[INPUT][4].cols * test_mat[INPUT][4].rows];
|
|
double* points = new double[N_POINTS*2];
|
|
double* r_points = new double[N_POINTS*2];
|
|
//Run reference calculations
|
|
CvMat ref_points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,r_points);
|
|
CvMat _camera = cvMat(3,3,CV_64F,cam);
|
|
CvMat _rot = cvMat(3,3,CV_64F,rot);
|
|
CvMat _distort = cvMat(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,dist);
|
|
CvMat _proj = cvMat(test_mat[INPUT][4].rows,test_mat[INPUT][4].cols,CV_64F,proj);
|
|
CvMat _points= cvMat(test_mat[TEMP][0].rows,test_mat[TEMP][0].cols,CV_64FC2,points);
|
|
|
|
Mat __camera = cvarrToMat(&_camera);
|
|
Mat __distort = cvarrToMat(&_distort);
|
|
Mat __rot = cvarrToMat(&_rot);
|
|
Mat __proj = cvarrToMat(&_proj);
|
|
Mat __points = cvarrToMat(&_points);
|
|
Mat _ref_points = cvarrToMat(&ref_points);
|
|
|
|
cvtest::convert(test_mat[INPUT][1], __camera, __camera.type());
|
|
cvtest::convert(test_mat[INPUT][2], __distort, __distort.type());
|
|
cvtest::convert(test_mat[INPUT][3], __rot, __rot.type());
|
|
cvtest::convert(test_mat[INPUT][4], __proj, __proj.type());
|
|
|
|
if (useCPlus)
|
|
{
|
|
if (useDstMat)
|
|
{
|
|
CvMat temp = dst_points_mat;
|
|
for (int i=0;i<N_POINTS*2;i++)
|
|
{
|
|
points[i] = temp.data.fl[i];
|
|
}
|
|
}
|
|
else
|
|
{
|
|
for (int i=0;i<N_POINTS;i++)
|
|
{
|
|
points[2*i] = dst_points[i].x;
|
|
points[2*i+1] = dst_points[i].y;
|
|
}
|
|
}
|
|
}
|
|
else
|
|
{
|
|
cvtest::convert(test_mat[TEMP][0],__points, __points.type());
|
|
}
|
|
|
|
CvMat* input2 = zero_distortion ? 0 : &_distort;
|
|
CvMat* input3 = zero_R ? 0 : &_rot;
|
|
CvMat* input4 = zero_new_cam ? 0 : &_proj;
|
|
distortPoints(&_points,&ref_points,&_camera,input2,input3,input4);
|
|
|
|
Mat& dst = test_mat[REF_OUTPUT][0];
|
|
cvtest::convert(_ref_points, dst, dst.type());
|
|
|
|
cvtest::copy(test_mat[INPUT][0], test_mat[OUTPUT][0]);
|
|
|
|
delete[] dist;
|
|
delete[] proj;
|
|
delete[] points;
|
|
delete[] r_points;
|
|
}
|
|
|
|
void CV_UndistortPointsTest::run_func()
|
|
{
|
|
|
|
if (useCPlus)
|
|
{
|
|
cv::Mat input2,input3,input4;
|
|
input2 = zero_distortion ? cv::Mat() : cv::Mat(test_mat[INPUT][2]);
|
|
input3 = zero_R ? cv::Mat() : cv::Mat(test_mat[INPUT][3]);
|
|
input4 = zero_new_cam ? cv::Mat() : cv::Mat(test_mat[INPUT][4]);
|
|
|
|
if (useDstMat)
|
|
{
|
|
//cv::undistortPoints(src_points,dst_points_mat,camera_mat,distortion_coeffs,R,P);
|
|
cv::undistortPoints(src_points,dst_points_mat,camera_mat,input2,input3,input4);
|
|
}
|
|
else
|
|
{
|
|
//cv::undistortPoints(src_points,dst_points,camera_mat,distortion_coeffs,R,P);
|
|
cv::undistortPoints(src_points,dst_points,camera_mat,input2,input3,input4);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
CvMat _input0 = test_mat[INPUT][0], _input1 = test_mat[INPUT][1], _input2, _input3, _input4;
|
|
CvMat _output = test_mat[TEMP][0];
|
|
if(!zero_distortion)
|
|
_input2 = test_mat[INPUT][2];
|
|
if(!zero_R)
|
|
_input3 = test_mat[INPUT][3];
|
|
if(!zero_new_cam)
|
|
_input4 = test_mat[INPUT][4];
|
|
cvUndistortPoints(&_input0, &_output, &_input1,
|
|
zero_distortion ? 0 : &_input2,
|
|
zero_R ? 0 : &_input3,
|
|
zero_new_cam ? 0 : &_input4);
|
|
}
|
|
}
|
|
|
|
void CV_UndistortPointsTest::distortPoints(const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatrix,
|
|
const CvMat* _distCoeffs,
|
|
const CvMat* matR, const CvMat* matP)
|
|
{
|
|
double a[9];
|
|
|
|
CvMat* __P;
|
|
if ((!matP)||(matP->cols == 3))
|
|
__P = cvCreateMat(3,3,CV_64F);
|
|
else
|
|
__P = cvCreateMat(3,4,CV_64F);
|
|
if (matP)
|
|
{
|
|
cvTsConvert(matP,__P);
|
|
}
|
|
else
|
|
{
|
|
cvZero(__P);
|
|
__P->data.db[0] = 1;
|
|
__P->data.db[4] = 1;
|
|
__P->data.db[8] = 1;
|
|
}
|
|
CvMat* __R = cvCreateMat(3,3,CV_64F);;
|
|
if (matR)
|
|
{
|
|
cvCopy(matR,__R);
|
|
}
|
|
else
|
|
{
|
|
cvZero(__R);
|
|
__R->data.db[0] = 1;
|
|
__R->data.db[4] = 1;
|
|
__R->data.db[8] = 1;
|
|
}
|
|
for (int i=0;i<N_POINTS;i++)
|
|
{
|
|
int movement = __P->cols > 3 ? 1 : 0;
|
|
double x = (_src->data.db[2*i]-__P->data.db[2])/__P->data.db[0];
|
|
double y = (_src->data.db[2*i+1]-__P->data.db[5+movement])/__P->data.db[4+movement];
|
|
CvMat inverse = cvMat(3,3,CV_64F,a);
|
|
cvInvert(__R,&inverse);
|
|
double w1 = x*inverse.data.db[6]+y*inverse.data.db[7]+inverse.data.db[8];
|
|
double _x = (x*inverse.data.db[0]+y*inverse.data.db[1]+inverse.data.db[2])/w1;
|
|
double _y = (x*inverse.data.db[3]+y*inverse.data.db[4]+inverse.data.db[5])/w1;
|
|
|
|
//Distortions
|
|
|
|
double __x = _x;
|
|
double __y = _y;
|
|
if (_distCoeffs)
|
|
{
|
|
double r2 = _x*_x+_y*_y;
|
|
|
|
__x = _x*(1+_distCoeffs->data.db[0]*r2+_distCoeffs->data.db[1]*r2*r2)+
|
|
2*_distCoeffs->data.db[2]*_x*_y+_distCoeffs->data.db[3]*(r2+2*_x*_x);
|
|
__y = _y*(1+_distCoeffs->data.db[0]*r2+_distCoeffs->data.db[1]*r2*r2)+
|
|
2*_distCoeffs->data.db[3]*_x*_y+_distCoeffs->data.db[2]*(r2+2*_y*_y);
|
|
if ((_distCoeffs->cols > 4) || (_distCoeffs->rows > 4))
|
|
{
|
|
__x+=_x*_distCoeffs->data.db[4]*r2*r2*r2;
|
|
__y+=_y*_distCoeffs->data.db[4]*r2*r2*r2;
|
|
}
|
|
}
|
|
|
|
|
|
_dst->data.db[2*i] = __x*_cameraMatrix->data.db[0]+_cameraMatrix->data.db[2];
|
|
_dst->data.db[2*i+1] = __y*_cameraMatrix->data.db[4]+_cameraMatrix->data.db[5];
|
|
|
|
}
|
|
|
|
cvReleaseMat(&__R);
|
|
cvReleaseMat(&__P);
|
|
|
|
}
|
|
|
|
|
|
double CV_UndistortPointsTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
|
|
{
|
|
return 5e-2;
|
|
}
|
|
|
|
//------------------------------------------------------
|
|
|
|
class CV_InitUndistortRectifyMapTest : public cvtest::ArrayTest
|
|
{
|
|
public:
|
|
CV_InitUndistortRectifyMapTest();
|
|
protected:
|
|
int prepare_test_case (int test_case_idx);
|
|
void prepare_to_validation( int test_case_idx );
|
|
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
|
|
double get_success_error_level( int test_case_idx, int i, int j );
|
|
void run_func();
|
|
|
|
private:
|
|
bool useCPlus;
|
|
static const int N_POINTS = 100;
|
|
static const int MAX_X = 2048;
|
|
static const int MAX_Y = 2048;
|
|
bool zero_new_cam;
|
|
bool zero_distortion;
|
|
bool zero_R;
|
|
|
|
|
|
cv::Size img_size;
|
|
|
|
cv::Mat camera_mat;
|
|
cv::Mat R;
|
|
cv::Mat new_camera_mat;
|
|
cv::Mat distortion_coeffs;
|
|
cv::Mat mapx;
|
|
cv::Mat mapy;
|
|
CvMat* _mapx;
|
|
CvMat* _mapy;
|
|
int mat_type;
|
|
};
|
|
|
|
CV_InitUndistortRectifyMapTest::CV_InitUndistortRectifyMapTest()
|
|
{
|
|
test_array[INPUT].push_back(NULL); // test points matrix
|
|
test_array[INPUT].push_back(NULL); // camera matrix
|
|
test_array[INPUT].push_back(NULL); // distortion coeffs
|
|
test_array[INPUT].push_back(NULL); // R matrix
|
|
test_array[INPUT].push_back(NULL); // new camera matrix
|
|
test_array[OUTPUT].push_back(NULL); // distorted dst points
|
|
test_array[REF_OUTPUT].push_back(NULL);
|
|
}
|
|
|
|
void CV_InitUndistortRectifyMapTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
|
|
{
|
|
cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx,sizes,types);
|
|
RNG& rng = ts->get_rng();
|
|
useCPlus = ((cvtest::randInt(rng) % 2)!=0);
|
|
//useCPlus = 0;
|
|
types[INPUT][0] = types[OUTPUT][0] = types[REF_OUTPUT][0] = CV_64FC2;
|
|
|
|
types[INPUT][1] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
|
|
types[INPUT][2] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
|
|
types[INPUT][3] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
|
|
types[INPUT][4] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
|
|
|
|
sizes[INPUT][0] = sizes[OUTPUT][0] = sizes[REF_OUTPUT][0] = cvSize(N_POINTS,1);
|
|
sizes[INPUT][1] = sizes[INPUT][3] = cvSize(3,3);
|
|
sizes[INPUT][4] = cvSize(3,3);
|
|
|
|
if (cvtest::randInt(rng)%2)
|
|
{
|
|
if (cvtest::randInt(rng)%2)
|
|
{
|
|
sizes[INPUT][2] = cvSize(1,4);
|
|
}
|
|
else
|
|
{
|
|
sizes[INPUT][2] = cvSize(1,5);
|
|
}
|
|
}
|
|
else
|
|
{
|
|
if (cvtest::randInt(rng)%2)
|
|
{
|
|
sizes[INPUT][2] = cvSize(4,1);
|
|
}
|
|
else
|
|
{
|
|
sizes[INPUT][2] = cvSize(5,1);
|
|
}
|
|
}
|
|
}
|
|
|
|
|
|
int CV_InitUndistortRectifyMapTest::prepare_test_case(int test_case_idx)
|
|
{
|
|
RNG& rng = ts->get_rng();
|
|
int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
|
|
|
|
if (code <= 0)
|
|
return code;
|
|
|
|
img_size.width = cvtest::randInt(rng) % MAX_X + 1;
|
|
img_size.height = cvtest::randInt(rng) % MAX_Y + 1;
|
|
|
|
if (useCPlus)
|
|
{
|
|
mat_type = (cvtest::randInt(rng) % 2) == 0 ? CV_32FC1 : CV_16SC2;
|
|
if ((cvtest::randInt(rng) % 4) == 0)
|
|
mat_type = -1;
|
|
if ((cvtest::randInt(rng) % 4) == 0)
|
|
mat_type = CV_32FC2;
|
|
_mapx = 0;
|
|
_mapy = 0;
|
|
}
|
|
else
|
|
{
|
|
int typex = (cvtest::randInt(rng) % 2) == 0 ? CV_32FC1 : CV_16SC2;
|
|
//typex = CV_32FC1; ///!!!!!!!!!!!!!!!!
|
|
int typey = (typex == CV_32FC1) ? CV_32FC1 : CV_16UC1;
|
|
|
|
_mapx = cvCreateMat(img_size.height,img_size.width,typex);
|
|
_mapy = cvCreateMat(img_size.height,img_size.width,typey);
|
|
|
|
|
|
}
|
|
|
|
int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows;
|
|
double cam[9] = {0,0,0,0,0,0,0,0,1};
|
|
vector<double> dist(dist_size);
|
|
vector<double> new_cam(test_mat[INPUT][4].cols * test_mat[INPUT][4].rows);
|
|
vector<Point2d> points(N_POINTS);
|
|
|
|
Mat _camera(3,3,CV_64F,cam);
|
|
Mat _distort(test_mat[INPUT][2].size(),CV_64F,&dist[0]);
|
|
Mat _new_cam(test_mat[INPUT][4].size(),CV_64F,&new_cam[0]);
|
|
Mat _points(test_mat[INPUT][0].size(),CV_64FC2, &points[0]);
|
|
|
|
//Generating points
|
|
for (int i=0;i<N_POINTS;i++)
|
|
{
|
|
points[i].x = cvtest::randReal(rng)*img_size.width;
|
|
points[i].y = cvtest::randReal(rng)*img_size.height;
|
|
}
|
|
|
|
//Generating camera matrix
|
|
double sz = MAX(img_size.width,img_size.height);
|
|
double aspect_ratio = cvtest::randReal(rng)*0.6 + 0.7;
|
|
cam[2] = (img_size.width - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
|
|
cam[5] = (img_size.height - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
|
|
cam[0] = sz/(0.9 - cvtest::randReal(rng)*0.6);
|
|
cam[4] = aspect_ratio*cam[0];
|
|
|
|
//Generating distortion coeffs
|
|
dist[0] = cvtest::randReal(rng)*0.06 - 0.03;
|
|
dist[1] = cvtest::randReal(rng)*0.06 - 0.03;
|
|
if( dist[0]*dist[1] > 0 )
|
|
dist[1] = -dist[1];
|
|
if( cvtest::randInt(rng)%4 != 0 )
|
|
{
|
|
dist[2] = cvtest::randReal(rng)*0.004 - 0.002;
|
|
dist[3] = cvtest::randReal(rng)*0.004 - 0.002;
|
|
if (dist_size > 4)
|
|
dist[4] = cvtest::randReal(rng)*0.004 - 0.002;
|
|
}
|
|
else
|
|
{
|
|
dist[2] = dist[3] = 0;
|
|
if (dist_size > 4)
|
|
dist[4] = 0;
|
|
}
|
|
|
|
//Generating new camera matrix
|
|
_new_cam = Scalar::all(0);
|
|
new_cam[8] = 1;
|
|
|
|
//new_cam[0] = cam[0];
|
|
//new_cam[4] = cam[4];
|
|
//new_cam[2] = cam[2];
|
|
//new_cam[5] = cam[5];
|
|
|
|
new_cam[0] = cam[0] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[0]; //10%
|
|
new_cam[4] = cam[4] + (cvtest::randReal(rng) - (double)0.5)*0.2*cam[4]; //10%
|
|
new_cam[2] = cam[2] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.width; //15%
|
|
new_cam[5] = cam[5] + (cvtest::randReal(rng) - (double)0.5)*0.3*img_size.height; //15%
|
|
|
|
|
|
//Generating R matrix
|
|
Mat _rot(3,3,CV_64F);
|
|
Mat rotation(1,3,CV_64F);
|
|
rotation.at<double>(0) = CV_PI/8*(cvtest::randReal(rng) - (double)0.5); // phi
|
|
rotation.at<double>(1) = CV_PI/8*(cvtest::randReal(rng) - (double)0.5); // ksi
|
|
rotation.at<double>(2) = CV_PI/3*(cvtest::randReal(rng) - (double)0.5); //khi
|
|
cvtest::Rodrigues(rotation, _rot);
|
|
|
|
//cvSetIdentity(_rot);
|
|
//copying data
|
|
cvtest::convert( _points, test_mat[INPUT][0], test_mat[INPUT][0].type());
|
|
cvtest::convert( _camera, test_mat[INPUT][1], test_mat[INPUT][1].type());
|
|
cvtest::convert( _distort, test_mat[INPUT][2], test_mat[INPUT][2].type());
|
|
cvtest::convert( _rot, test_mat[INPUT][3], test_mat[INPUT][3].type());
|
|
cvtest::convert( _new_cam, test_mat[INPUT][4], test_mat[INPUT][4].type());
|
|
|
|
zero_distortion = (cvtest::randInt(rng)%2) == 0 ? false : true;
|
|
zero_new_cam = (cvtest::randInt(rng)%2) == 0 ? false : true;
|
|
zero_R = (cvtest::randInt(rng)%2) == 0 ? false : true;
|
|
|
|
if (useCPlus)
|
|
{
|
|
camera_mat = test_mat[INPUT][1];
|
|
distortion_coeffs = test_mat[INPUT][2];
|
|
R = test_mat[INPUT][3];
|
|
new_camera_mat = test_mat[INPUT][4];
|
|
}
|
|
|
|
return code;
|
|
}
|
|
|
|
void CV_InitUndistortRectifyMapTest::prepare_to_validation(int/* test_case_idx*/)
|
|
{
|
|
#if 0
|
|
int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows;
|
|
double cam[9] = {0,0,0,0,0,0,0,0,1};
|
|
double rot[9] = {1,0,0,0,1,0,0,0,1};
|
|
vector<double> dist(dist_size);
|
|
vector<double> new_cam(test_mat[INPUT][4].cols * test_mat[INPUT][4].rows);
|
|
vector<Point2d> points(N_POINTS);
|
|
vector<Point2d> r_points(N_POINTS);
|
|
//Run reference calculations
|
|
Mat ref_points(test_mat[INPUT][0].size(),CV_64FC2,&r_points[0]);
|
|
Mat _camera(3,3,CV_64F,cam);
|
|
Mat _rot(3,3,CV_64F,rot);
|
|
Mat _distort(test_mat[INPUT][2].size(),CV_64F,&dist[0]);
|
|
Mat _new_cam(test_mat[INPUT][4].size(),CV_64F,&new_cam[0]);
|
|
Mat _points(test_mat[INPUT][0].size(),CV_64FC2,&points[0]);
|
|
|
|
cvtest::convert(test_mat[INPUT][1],_camera,_camera.type());
|
|
cvtest::convert(test_mat[INPUT][2],_distort,_distort.type());
|
|
cvtest::convert(test_mat[INPUT][3],_rot,_rot.type());
|
|
cvtest::convert(test_mat[INPUT][4],_new_cam,_new_cam.type());
|
|
|
|
//Applying precalculated undistort rectify map
|
|
if (!useCPlus)
|
|
{
|
|
mapx = cv::Mat(_mapx);
|
|
mapy = cv::Mat(_mapy);
|
|
}
|
|
cv::Mat map1,map2;
|
|
cv::convertMaps(mapx,mapy,map1,map2,CV_32FC1);
|
|
CvMat _map1 = map1;
|
|
CvMat _map2 = map2;
|
|
const Point2d* sptr = (const Point2d*)test_mat[INPUT][0].data;
|
|
for( int i = 0;i < N_POINTS; i++ )
|
|
{
|
|
int u = saturate_cast<int>(sptr[i].x);
|
|
int v = saturate_cast<int>(sptr[i].y);
|
|
points[i].x = _map1.data.fl[v*_map1.cols + u];
|
|
points[i].y = _map2.data.fl[v*_map2.cols + u];
|
|
}
|
|
|
|
//---
|
|
|
|
cv::undistortPoints(_points, ref_points, _camera,
|
|
zero_distortion ? Mat() : _distort,
|
|
zero_R ? Mat::eye(3,3,CV_64F) : _rot,
|
|
zero_new_cam ? _camera : _new_cam);
|
|
//cvTsDistortPoints(&_points,&ref_points,&_camera,&_distort,&_rot,&_new_cam);
|
|
cvtest::convert(ref_points, test_mat[REF_OUTPUT][0], test_mat[REF_OUTPUT][0].type());
|
|
cvtest::copy(test_mat[INPUT][0],test_mat[OUTPUT][0]);
|
|
|
|
cvReleaseMat(&_mapx);
|
|
cvReleaseMat(&_mapy);
|
|
#else
|
|
int dist_size = test_mat[INPUT][2].cols > test_mat[INPUT][2].rows ? test_mat[INPUT][2].cols : test_mat[INPUT][2].rows;
|
|
double cam[9] = {0,0,0,0,0,0,0,0,1};
|
|
double rot[9] = {1,0,0,0,1,0,0,0,1};
|
|
double* dist = new double[dist_size ];
|
|
double* new_cam = new double[test_mat[INPUT][4].cols * test_mat[INPUT][4].rows];
|
|
double* points = new double[N_POINTS*2];
|
|
double* r_points = new double[N_POINTS*2];
|
|
//Run reference calculations
|
|
CvMat ref_points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,r_points);
|
|
CvMat _camera = cvMat(3,3,CV_64F,cam);
|
|
CvMat _rot = cvMat(3,3,CV_64F,rot);
|
|
CvMat _distort = cvMat(test_mat[INPUT][2].rows,test_mat[INPUT][2].cols,CV_64F,dist);
|
|
CvMat _new_cam = cvMat(test_mat[INPUT][4].rows,test_mat[INPUT][4].cols,CV_64F,new_cam);
|
|
CvMat _points= cvMat(test_mat[INPUT][0].rows,test_mat[INPUT][0].cols,CV_64FC2,points);
|
|
|
|
CvMat _input1 = test_mat[INPUT][1];
|
|
CvMat _input2 = test_mat[INPUT][2];
|
|
CvMat _input3 = test_mat[INPUT][3];
|
|
CvMat _input4 = test_mat[INPUT][4];
|
|
|
|
cvTsConvert(&_input1,&_camera);
|
|
cvTsConvert(&_input2,&_distort);
|
|
cvTsConvert(&_input3,&_rot);
|
|
cvTsConvert(&_input4,&_new_cam);
|
|
|
|
//Applying precalculated undistort rectify map
|
|
if (!useCPlus)
|
|
{
|
|
mapx = cv::Mat(_mapx);
|
|
mapy = cv::Mat(_mapy);
|
|
}
|
|
cv::Mat map1,map2;
|
|
cv::convertMaps(mapx,mapy,map1,map2,CV_32FC1);
|
|
CvMat _map1 = map1;
|
|
CvMat _map2 = map2;
|
|
for (int i=0;i<N_POINTS;i++)
|
|
{
|
|
double u = test_mat[INPUT][0].ptr<double>()[2*i];
|
|
double v = test_mat[INPUT][0].ptr<double>()[2*i+1];
|
|
_points.data.db[2*i] = (double)_map1.data.fl[(int)v*_map1.cols+(int)u];
|
|
_points.data.db[2*i+1] = (double)_map2.data.fl[(int)v*_map2.cols+(int)u];
|
|
}
|
|
|
|
//---
|
|
|
|
cvUndistortPoints(&_points,&ref_points,&_camera,
|
|
zero_distortion ? 0 : &_distort, zero_R ? 0 : &_rot, zero_new_cam ? &_camera : &_new_cam);
|
|
//cvTsDistortPoints(&_points,&ref_points,&_camera,&_distort,&_rot,&_new_cam);
|
|
CvMat dst = test_mat[REF_OUTPUT][0];
|
|
cvTsConvert(&ref_points,&dst);
|
|
|
|
cvtest::copy(test_mat[INPUT][0],test_mat[OUTPUT][0]);
|
|
|
|
delete[] dist;
|
|
delete[] new_cam;
|
|
delete[] points;
|
|
delete[] r_points;
|
|
cvReleaseMat(&_mapx);
|
|
cvReleaseMat(&_mapy);
|
|
#endif
|
|
}
|
|
|
|
void CV_InitUndistortRectifyMapTest::run_func()
|
|
{
|
|
if (useCPlus)
|
|
{
|
|
cv::Mat input2,input3,input4;
|
|
input2 = zero_distortion ? cv::Mat() : test_mat[INPUT][2];
|
|
input3 = zero_R ? cv::Mat() : test_mat[INPUT][3];
|
|
input4 = zero_new_cam ? cv::Mat() : test_mat[INPUT][4];
|
|
cv::initUndistortRectifyMap(camera_mat,input2,input3,input4,img_size,mat_type,mapx,mapy);
|
|
}
|
|
else
|
|
{
|
|
CvMat input1 = test_mat[INPUT][1], input2, input3, input4;
|
|
if( !zero_distortion )
|
|
input2 = test_mat[INPUT][2];
|
|
if( !zero_R )
|
|
input3 = test_mat[INPUT][3];
|
|
if( !zero_new_cam )
|
|
input4 = test_mat[INPUT][4];
|
|
cvInitUndistortRectifyMap(&input1,
|
|
zero_distortion ? 0 : &input2,
|
|
zero_R ? 0 : &input3,
|
|
zero_new_cam ? 0 : &input4,
|
|
_mapx,_mapy);
|
|
}
|
|
}
|
|
|
|
double CV_InitUndistortRectifyMapTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
|
|
{
|
|
return 8;
|
|
}
|
|
|
|
//////////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(Calib3d_DefaultNewCameraMatrix, accuracy) { CV_DefaultNewCameraMatrixTest test; test.safe_run(); }
|
|
TEST(Calib3d_UndistortPoints, accuracy) { CV_UndistortPointsTest test; test.safe_run(); }
|
|
TEST(Calib3d_InitUndistortRectifyMap, accuracy) { CV_InitUndistortRectifyMapTest test; test.safe_run(); }
|