opencv/modules/calib3d/test/test_undistort.cpp

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#include "test_precomp.hpp"
#include "opencv2/imgproc/imgproc_c.h"
#include "opencv2/calib3d/calib3d_c.h"
namespace opencv_test { namespace {
class CV_DefaultNewCameraMatrixTest : public cvtest::ArrayTest
{
public:
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CV_DefaultNewCameraMatrixTest();
protected:
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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:
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cv::Size img_size;
cv::Mat camera_mat;
cv::Mat new_camera_mat;
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int matrix_type;
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bool center_principal_point;
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static const int MAX_X = 2048;
static const int MAX_Y = 2048;
//static const int MAX_VAL = 10000;
};
CV_DefaultNewCameraMatrixTest::CV_DefaultNewCameraMatrixTest()
{
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test_array[INPUT].push_back(NULL);
test_array[OUTPUT].push_back(NULL);
test_array[REF_OUTPUT].push_back(NULL);
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matrix_type = 0;
center_principal_point = false;
}
void CV_DefaultNewCameraMatrixTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
{
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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)
{
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int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
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if (code <= 0)
return code;
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RNG& rng = ts->get_rng();
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img_size.width = cvtest::randInt(rng) % MAX_X + 1;
img_size.height = cvtest::randInt(rng) % MAX_Y + 1;
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center_principal_point = ((cvtest::randInt(rng) % 2)!=0);
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// 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;
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return code;
}
void CV_DefaultNewCameraMatrixTest::run_func()
{
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new_camera_mat = cv::getDefaultNewCameraMatrix(camera_mat,img_size,center_principal_point);
}
void CV_DefaultNewCameraMatrixTest::prepare_to_validation( int /*test_case_idx*/ )
{
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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() );
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if (!center_principal_point)
{
cvtest::copy(src, dst);
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}
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() );
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}
}
//---------
class CV_UndistortPointsTest : public cvtest::ArrayTest
{
public:
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CV_UndistortPointsTest();
protected:
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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:
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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()
{
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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);
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useCPlus = useDstMat = false;
zero_new_cam = zero_distortion = zero_R = false;
}
void CV_UndistortPointsTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
{
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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)
{
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RNG& rng = ts->get_rng();
int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
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if (code <= 0)
return code;
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useDstMat = (cvtest::randInt(rng) % 2) == 0;
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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);
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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);
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//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);
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//copying data
//src_points = &_points;
_points.convertTo(test_mat[INPUT][0], test_mat[INPUT][0].type());
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_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());
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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;
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if (useCPlus)
{
_points.convertTo(src_points, CV_32F);
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camera_mat = test_mat[INPUT][1];
distortion_coeffs = test_mat[INPUT][2];
R = test_mat[INPUT][3];
P = test_mat[INPUT][4];
}
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return code;
}
void CV_UndistortPointsTest::prepare_to_validation(int /*test_case_idx*/)
{
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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);
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cvtest::convert(test_mat[INPUT][1], __camera, __camera.type());
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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 = cvMat(dst_points_mat);
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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());
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}
CvMat* input2 = zero_distortion ? 0 : &_distort;
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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());
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cvtest::copy(test_mat[INPUT][0], test_mat[OUTPUT][0]);
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delete[] dist;
delete[] proj;
delete[] points;
delete[] r_points;
}
void CV_UndistortPointsTest::run_func()
{
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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 = cvMat(test_mat[INPUT][0]), _input1 = cvMat(test_mat[INPUT][1]), _input2, _input3, _input4;
CvMat _output = cvMat(test_mat[TEMP][0]);
if(!zero_distortion)
_input2 = cvMat(test_mat[INPUT][2]);
if(!zero_R)
_input3 = cvMat(test_mat[INPUT][3]);
if(!zero_new_cam)
_input4 = cvMat(test_mat[INPUT][4]);
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cvUndistortPoints(&_input0, &_output, &_input1,
zero_distortion ? 0 : &_input2,
zero_R ? 0 : &_input3,
zero_new_cam ? 0 : &_input4);
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}
}
void CV_UndistortPointsTest::distortPoints(const CvMat* _src, CvMat* _dst, const CvMat* _cameraMatrix,
const CvMat* _distCoeffs,
const CvMat* matR, const CvMat* matP)
{
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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)
{
cvtest::convert(cvarrToMat(matP), cvarrToMat(__P), -1);
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}
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);
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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);
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__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);
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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*/ )
{
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return 5e-2;
}
//------------------------------------------------------
class CV_InitUndistortRectifyMapTest : public cvtest::ArrayTest
{
public:
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CV_InitUndistortRectifyMapTest();
protected:
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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:
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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()
{
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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);
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useCPlus = false;
zero_distortion = zero_new_cam = zero_R = false;
_mapx = _mapy = NULL;
mat_type = 0;
}
void CV_InitUndistortRectifyMapTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
{
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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)
{
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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);
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new_cam[8] = 1;
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//new_cam[0] = cam[0];
//new_cam[4] = cam[4];
//new_cam[2] = cam[2];
//new_cam[5] = cam[5];
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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%
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//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);
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//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());
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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;
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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];
}
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return code;
}
void CV_InitUndistortRectifyMapTest::prepare_to_validation(int/* test_case_idx*/)
{
#if 0
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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());
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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;
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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];
}
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//---
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);
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//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;
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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 = cvMat(test_mat[INPUT][1]);
CvMat _input2 = cvMat(test_mat[INPUT][2]);
CvMat _input3 = cvMat(test_mat[INPUT][3]);
CvMat _input4 = cvMat(test_mat[INPUT][4]);
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cvtest::convert(cvarrToMat(&_input1), cvarrToMat(&_camera), -1);
cvtest::convert(cvarrToMat(&_input2), cvarrToMat(&_distort), -1);
cvtest::convert(cvarrToMat(&_input3), cvarrToMat(&_rot), -1);
cvtest::convert(cvarrToMat(&_input4), cvarrToMat(&_new_cam), -1);
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//Applying precalculated undistort rectify map
if (!useCPlus)
{
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mapx = cv::cvarrToMat(_mapx);
mapy = cv::cvarrToMat(_mapy);
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}
cv::Mat map1,map2;
cv::convertMaps(mapx,mapy,map1,map2,CV_32FC1);
CvMat _map1 = cvMat(map1);
CvMat _map2 = cvMat(map2);
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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);
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//cvTsDistortPoints(&_points,&ref_points,&_camera,&_distort,&_rot,&_new_cam);
CvMat dst = cvMat(test_mat[REF_OUTPUT][0]);
cvtest::convert(cvarrToMat(&ref_points), cvarrToMat(&dst), -1);
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cvtest::copy(test_mat[INPUT][0],test_mat[OUTPUT][0]);
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delete[] dist;
delete[] new_cam;
delete[] points;
delete[] r_points;
cvReleaseMat(&_mapx);
cvReleaseMat(&_mapy);
#endif
}
void CV_InitUndistortRectifyMapTest::run_func()
{
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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 = cvMat(test_mat[INPUT][1]), input2, input3, input4;
if( !zero_distortion )
input2 = cvMat(test_mat[INPUT][2]);
if( !zero_R )
input3 = cvMat(test_mat[INPUT][3]);
if( !zero_new_cam )
input4 = cvMat(test_mat[INPUT][4]);
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cvInitUndistortRectifyMap(&input1,
zero_distortion ? 0 : &input2,
zero_R ? 0 : &input3,
zero_new_cam ? 0 : &input4,
_mapx,_mapy);
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}
}
double CV_InitUndistortRectifyMapTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
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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(); }
////////////////////////////// undistort /////////////////////////////////
static void test_remap( const Mat& src, Mat& dst, const Mat& mapx, const Mat& mapy,
Mat* mask=0, int interpolation=CV_INTER_LINEAR )
{
int x, y, k;
int drows = dst.rows, dcols = dst.cols;
int srows = src.rows, scols = src.cols;
const uchar* sptr0 = src.ptr();
int depth = src.depth(), cn = src.channels();
int elem_size = (int)src.elemSize();
int step = (int)(src.step / CV_ELEM_SIZE(depth));
int delta;
if( interpolation != CV_INTER_CUBIC )
{
delta = 0;
scols -= 1; srows -= 1;
}
else
{
delta = 1;
scols = MAX(scols - 3, 0);
srows = MAX(srows - 3, 0);
}
int scols1 = MAX(scols - 2, 0);
int srows1 = MAX(srows - 2, 0);
if( mask )
*mask = Scalar::all(0);
for( y = 0; y < drows; y++ )
{
uchar* dptr = dst.ptr(y);
const float* mx = mapx.ptr<float>(y);
const float* my = mapy.ptr<float>(y);
uchar* m = mask ? mask->ptr(y) : 0;
for( x = 0; x < dcols; x++, dptr += elem_size )
{
float xs = mx[x];
float ys = my[x];
int ixs = cvFloor(xs);
int iys = cvFloor(ys);
if( (unsigned)(ixs - delta - 1) >= (unsigned)scols1 ||
(unsigned)(iys - delta - 1) >= (unsigned)srows1 )
{
if( m )
m[x] = 1;
if( (unsigned)(ixs - delta) >= (unsigned)scols ||
(unsigned)(iys - delta) >= (unsigned)srows )
continue;
}
xs -= ixs;
ys -= iys;
switch( depth )
{
case CV_8U:
{
const uchar* sptr = sptr0 + iys*step + ixs*cn;
for( k = 0; k < cn; k++ )
{
float v00 = sptr[k];
float v01 = sptr[cn + k];
float v10 = sptr[step + k];
float v11 = sptr[step + cn + k];
v00 = v00 + xs*(v01 - v00);
v10 = v10 + xs*(v11 - v10);
v00 = v00 + ys*(v10 - v00);
dptr[k] = (uchar)cvRound(v00);
}
}
break;
case CV_16U:
{
const ushort* sptr = (const ushort*)sptr0 + iys*step + ixs*cn;
for( k = 0; k < cn; k++ )
{
float v00 = sptr[k];
float v01 = sptr[cn + k];
float v10 = sptr[step + k];
float v11 = sptr[step + cn + k];
v00 = v00 + xs*(v01 - v00);
v10 = v10 + xs*(v11 - v10);
v00 = v00 + ys*(v10 - v00);
((ushort*)dptr)[k] = (ushort)cvRound(v00);
}
}
break;
case CV_32F:
{
const float* sptr = (const float*)sptr0 + iys*step + ixs*cn;
for( k = 0; k < cn; k++ )
{
float v00 = sptr[k];
float v01 = sptr[cn + k];
float v10 = sptr[step + k];
float v11 = sptr[step + cn + k];
v00 = v00 + xs*(v01 - v00);
v10 = v10 + xs*(v11 - v10);
v00 = v00 + ys*(v10 - v00);
((float*)dptr)[k] = (float)v00;
}
}
break;
default:
assert(0);
}
}
}
}
class CV_ImgWarpBaseTest : public cvtest::ArrayTest
{
public:
CV_ImgWarpBaseTest( bool warp_matrix );
protected:
int read_params( CvFileStorage* fs );
int prepare_test_case( int test_case_idx );
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
void get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& high );
void fill_array( int test_case_idx, int i, int j, Mat& arr );
int interpolation;
int max_interpolation;
double spatial_scale_zoom, spatial_scale_decimate;
};
CV_ImgWarpBaseTest::CV_ImgWarpBaseTest( bool warp_matrix )
{
test_array[INPUT].push_back(NULL);
if( warp_matrix )
test_array[INPUT].push_back(NULL);
test_array[INPUT_OUTPUT].push_back(NULL);
test_array[REF_INPUT_OUTPUT].push_back(NULL);
max_interpolation = 5;
interpolation = 0;
element_wise_relative_error = false;
spatial_scale_zoom = 0.01;
spatial_scale_decimate = 0.005;
}
int CV_ImgWarpBaseTest::read_params( CvFileStorage* fs )
{
int code = cvtest::ArrayTest::read_params( fs );
return code;
}
void CV_ImgWarpBaseTest::get_minmax_bounds( int i, int j, int type, Scalar& low, Scalar& high )
{
cvtest::ArrayTest::get_minmax_bounds( i, j, type, low, high );
if( CV_MAT_DEPTH(type) == CV_32F )
{
low = Scalar::all(-10.);
high = Scalar::all(10);
}
}
void CV_ImgWarpBaseTest::get_test_array_types_and_sizes( int test_case_idx,
vector<vector<Size> >& sizes, vector<vector<int> >& types )
{
RNG& rng = ts->get_rng();
int depth = cvtest::randInt(rng) % 3;
int cn = cvtest::randInt(rng) % 3 + 1;
cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
depth = depth == 0 ? CV_8U : depth == 1 ? CV_16U : CV_32F;
cn += cn == 2;
types[INPUT][0] = types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = CV_MAKETYPE(depth, cn);
if( test_array[INPUT].size() > 1 )
types[INPUT][1] = cvtest::randInt(rng) & 1 ? CV_32FC1 : CV_64FC1;
interpolation = cvtest::randInt(rng) % max_interpolation;
}
void CV_ImgWarpBaseTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
{
if( i != INPUT || j != 0 )
cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
}
int CV_ImgWarpBaseTest::prepare_test_case( int test_case_idx )
{
int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
Mat& img = test_mat[INPUT][0];
int i, j, cols = img.cols;
int type = img.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type);
double scale = depth == CV_16U ? 1000. : 255.*0.5;
double space_scale = spatial_scale_decimate;
vector<float> buffer(img.cols*cn);
if( code <= 0 )
return code;
if( test_mat[INPUT_OUTPUT][0].cols >= img.cols &&
test_mat[INPUT_OUTPUT][0].rows >= img.rows )
space_scale = spatial_scale_zoom;
for( i = 0; i < img.rows; i++ )
{
uchar* ptr = img.ptr(i);
switch( cn )
{
case 1:
for( j = 0; j < cols; j++ )
buffer[j] = (float)((sin((i+1)*space_scale)*sin((j+1)*space_scale)+1.)*scale);
break;
case 2:
for( j = 0; j < cols; j++ )
{
buffer[j*2] = (float)((sin((i+1)*space_scale)+1.)*scale);
buffer[j*2+1] = (float)((sin((i+j)*space_scale)+1.)*scale);
}
break;
case 3:
for( j = 0; j < cols; j++ )
{
buffer[j*3] = (float)((sin((i+1)*space_scale)+1.)*scale);
buffer[j*3+1] = (float)((sin(j*space_scale)+1.)*scale);
buffer[j*3+2] = (float)((sin((i+j)*space_scale)+1.)*scale);
}
break;
case 4:
for( j = 0; j < cols; j++ )
{
buffer[j*4] = (float)((sin((i+1)*space_scale)+1.)*scale);
buffer[j*4+1] = (float)((sin(j*space_scale)+1.)*scale);
buffer[j*4+2] = (float)((sin((i+j)*space_scale)+1.)*scale);
buffer[j*4+3] = (float)((sin((i-j)*space_scale)+1.)*scale);
}
break;
default:
assert(0);
}
/*switch( depth )
{
case CV_8U:
for( j = 0; j < cols*cn; j++ )
ptr[j] = (uchar)cvRound(buffer[j]);
break;
case CV_16U:
for( j = 0; j < cols*cn; j++ )
((ushort*)ptr)[j] = (ushort)cvRound(buffer[j]);
break;
case CV_32F:
for( j = 0; j < cols*cn; j++ )
((float*)ptr)[j] = (float)buffer[j];
break;
default:
assert(0);
}*/
cv::Mat src(1, cols*cn, CV_32F, &buffer[0]);
cv::Mat dst(1, cols*cn, depth, ptr);
src.convertTo(dst, dst.type());
}
return code;
}
class CV_UndistortTest : public CV_ImgWarpBaseTest
{
public:
CV_UndistortTest();
protected:
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
void run_func();
int prepare_test_case( int test_case_idx );
void prepare_to_validation( int /*test_case_idx*/ );
double get_success_error_level( int test_case_idx, int i, int j );
void fill_array( int test_case_idx, int i, int j, Mat& arr );
private:
bool useCPlus;
cv::Mat input0;
cv::Mat input1;
cv::Mat input2;
cv::Mat input_new_cam;
cv::Mat input_output;
bool zero_new_cam;
bool zero_distortion;
};
CV_UndistortTest::CV_UndistortTest() : CV_ImgWarpBaseTest( false )
{
//spatial_scale_zoom = spatial_scale_decimate;
test_array[INPUT].push_back(NULL);
test_array[INPUT].push_back(NULL);
test_array[INPUT].push_back(NULL);
spatial_scale_decimate = spatial_scale_zoom;
}
void CV_UndistortTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
{
RNG& rng = ts->get_rng();
CV_ImgWarpBaseTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
int type = types[INPUT][0];
type = CV_MAKETYPE( CV_8U, CV_MAT_CN(type) );
types[INPUT][0] = types[INPUT_OUTPUT][0] = types[REF_INPUT_OUTPUT][0] = type;
types[INPUT][1] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
types[INPUT][2] = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
sizes[INPUT][1] = cvSize(3,3);
sizes[INPUT][2] = cvtest::randInt(rng)%2 ? cvSize(4,1) : cvSize(1,4);
types[INPUT][3] = types[INPUT][1];
sizes[INPUT][3] = sizes[INPUT][1];
interpolation = CV_INTER_LINEAR;
}
void CV_UndistortTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
{
if( i != INPUT )
CV_ImgWarpBaseTest::fill_array( test_case_idx, i, j, arr );
}
void CV_UndistortTest::run_func()
{
if (!useCPlus)
{
CvMat a = cvMat(test_mat[INPUT][1]), k = cvMat(test_mat[INPUT][2]);
cvUndistort2( test_array[INPUT][0], test_array[INPUT_OUTPUT][0], &a, &k);
}
else
{
if (zero_distortion)
{
cv::undistort(input0,input_output,input1,cv::Mat());
}
else
{
cv::undistort(input0,input_output,input1,input2);
}
}
}
double CV_UndistortTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
int depth = test_mat[INPUT][0].depth();
return depth == CV_8U ? 16 : depth == CV_16U ? 1024 : 5e-2;
}
int CV_UndistortTest::prepare_test_case( int test_case_idx )
{
RNG& rng = ts->get_rng();
int code = CV_ImgWarpBaseTest::prepare_test_case( test_case_idx );
const Mat& src = test_mat[INPUT][0];
double k[4], a[9] = {0,0,0,0,0,0,0,0,1};
double new_cam[9] = {0,0,0,0,0,0,0,0,1};
double sz = MAX(src.rows, src.cols);
Mat& _new_cam0 = test_mat[INPUT][3];
Mat _new_cam(test_mat[INPUT][3].rows,test_mat[INPUT][3].cols,CV_64F,new_cam);
Mat& _a0 = test_mat[INPUT][1];
Mat _a(3,3,CV_64F,a);
Mat& _k0 = test_mat[INPUT][2];
Mat _k(_k0.rows,_k0.cols, CV_MAKETYPE(CV_64F,_k0.channels()),k);
if( code <= 0 )
return code;
double aspect_ratio = cvtest::randReal(rng)*0.6 + 0.7;
a[2] = (src.cols - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
a[5] = (src.rows - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
a[0] = sz/(0.9 - cvtest::randReal(rng)*0.6);
a[4] = aspect_ratio*a[0];
k[0] = cvtest::randReal(rng)*0.06 - 0.03;
k[1] = cvtest::randReal(rng)*0.06 - 0.03;
if( k[0]*k[1] > 0 )
k[1] = -k[1];
if( cvtest::randInt(rng)%4 != 0 )
{
k[2] = cvtest::randReal(rng)*0.004 - 0.002;
k[3] = cvtest::randReal(rng)*0.004 - 0.002;
}
else
k[2] = k[3] = 0;
new_cam[0] = a[0] + (cvtest::randReal(rng) - (double)0.5)*0.2*a[0]; //10%
new_cam[4] = a[4] + (cvtest::randReal(rng) - (double)0.5)*0.2*a[4]; //10%
new_cam[2] = a[2] + (cvtest::randReal(rng) - (double)0.5)*0.3*test_mat[INPUT][0].rows; //15%
new_cam[5] = a[5] + (cvtest::randReal(rng) - (double)0.5)*0.3*test_mat[INPUT][0].cols; //15%
_a.convertTo(_a0, _a0.depth());
zero_distortion = (cvtest::randInt(rng)%2) == 0 ? false : true;
_k.convertTo(_k0, _k0.depth());
zero_new_cam = (cvtest::randInt(rng)%2) == 0 ? false : true;
_new_cam.convertTo(_new_cam0, _new_cam0.depth());
//Testing C++ code
useCPlus = ((cvtest::randInt(rng) % 2)!=0);
if (useCPlus)
{
input0 = test_mat[INPUT][0];
input1 = test_mat[INPUT][1];
input2 = test_mat[INPUT][2];
input_new_cam = test_mat[INPUT][3];
}
return code;
}
void CV_UndistortTest::prepare_to_validation( int /*test_case_idx*/ )
{
if (useCPlus)
{
Mat& output = test_mat[INPUT_OUTPUT][0];
input_output.convertTo(output, output.type());
}
Mat& src = test_mat[INPUT][0];
Mat& dst = test_mat[REF_INPUT_OUTPUT][0];
Mat& dst0 = test_mat[INPUT_OUTPUT][0];
Mat mapx, mapy;
cvtest::initUndistortMap( test_mat[INPUT][1], test_mat[INPUT][2], dst.size(), mapx, mapy );
Mat mask( dst.size(), CV_8U );
test_remap( src, dst, mapx, mapy, &mask, interpolation );
dst.setTo(Scalar::all(0), mask);
dst0.setTo(Scalar::all(0), mask);
}
class CV_UndistortMapTest : public cvtest::ArrayTest
{
public:
CV_UndistortMapTest();
protected:
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
void run_func();
int prepare_test_case( int test_case_idx );
void prepare_to_validation( int /*test_case_idx*/ );
double get_success_error_level( int test_case_idx, int i, int j );
void fill_array( int test_case_idx, int i, int j, Mat& arr );
private:
bool dualChannel;
};
CV_UndistortMapTest::CV_UndistortMapTest()
{
test_array[INPUT].push_back(NULL);
test_array[INPUT].push_back(NULL);
test_array[OUTPUT].push_back(NULL);
test_array[OUTPUT].push_back(NULL);
test_array[REF_OUTPUT].push_back(NULL);
test_array[REF_OUTPUT].push_back(NULL);
element_wise_relative_error = false;
}
void CV_UndistortMapTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
{
RNG& rng = ts->get_rng();
cvtest::ArrayTest::get_test_array_types_and_sizes( test_case_idx, sizes, types );
int depth = cvtest::randInt(rng)%2 ? CV_64F : CV_32F;
Size sz = sizes[OUTPUT][0];
types[INPUT][0] = types[INPUT][1] = depth;
dualChannel = cvtest::randInt(rng)%2 == 0;
types[OUTPUT][0] = types[OUTPUT][1] =
types[REF_OUTPUT][0] = types[REF_OUTPUT][1] = dualChannel ? CV_32FC2 : CV_32F;
sizes[INPUT][0] = cvSize(3,3);
sizes[INPUT][1] = cvtest::randInt(rng)%2 ? cvSize(4,1) : cvSize(1,4);
sz.width = MAX(sz.width,16);
sz.height = MAX(sz.height,16);
sizes[OUTPUT][0] = sizes[OUTPUT][1] =
sizes[REF_OUTPUT][0] = sizes[REF_OUTPUT][1] = sz;
}
void CV_UndistortMapTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
{
if( i != INPUT )
cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
}
void CV_UndistortMapTest::run_func()
{
CvMat a = cvMat(test_mat[INPUT][0]), k = cvMat(test_mat[INPUT][1]);
if (!dualChannel )
cvInitUndistortMap( &a, &k, test_array[OUTPUT][0], test_array[OUTPUT][1] );
else
cvInitUndistortMap( &a, &k, test_array[OUTPUT][0], 0 );
}
double CV_UndistortMapTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
return 1e-3;
}
int CV_UndistortMapTest::prepare_test_case( int test_case_idx )
{
RNG& rng = ts->get_rng();
int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
const Mat& mapx = test_mat[OUTPUT][0];
double k[4], a[9] = {0,0,0,0,0,0,0,0,1};
double sz = MAX(mapx.rows, mapx.cols);
Mat& _a0 = test_mat[INPUT][0], &_k0 = test_mat[INPUT][1];
Mat _a(3,3,CV_64F,a);
Mat _k(_k0.rows,_k0.cols, CV_MAKETYPE(CV_64F,_k0.channels()),k);
if( code <= 0 )
return code;
double aspect_ratio = cvtest::randReal(rng)*0.6 + 0.7;
a[2] = (mapx.cols - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
a[5] = (mapx.rows - 1)*0.5 + cvtest::randReal(rng)*10 - 5;
a[0] = sz/(0.9 - cvtest::randReal(rng)*0.6);
a[4] = aspect_ratio*a[0];
k[0] = cvtest::randReal(rng)*0.06 - 0.03;
k[1] = cvtest::randReal(rng)*0.06 - 0.03;
if( k[0]*k[1] > 0 )
k[1] = -k[1];
k[2] = cvtest::randReal(rng)*0.004 - 0.002;
k[3] = cvtest::randReal(rng)*0.004 - 0.002;
_a.convertTo(_a0, _a0.depth());
_k.convertTo(_k0, _k0.depth());
if (dualChannel)
{
test_mat[REF_OUTPUT][1] = Scalar::all(0);
test_mat[OUTPUT][1] = Scalar::all(0);
}
return code;
}
void CV_UndistortMapTest::prepare_to_validation( int )
{
Mat mapx, mapy;
cvtest::initUndistortMap( test_mat[INPUT][0], test_mat[INPUT][1], test_mat[REF_OUTPUT][0].size(), mapx, mapy );
if( !dualChannel )
{
mapx.copyTo(test_mat[REF_OUTPUT][0]);
mapy.copyTo(test_mat[REF_OUTPUT][1]);
}
else
{
Mat p[2] = {mapx, mapy};
cv::merge(p, 2, test_mat[REF_OUTPUT][0]);
}
}
TEST(Calib3d_Undistort, accuracy) { CV_UndistortTest test; test.safe_run(); }
TEST(Calib3d_InitUndistortMap, accuracy) { CV_UndistortMapTest test; test.safe_run(); }
}} // namespace