opencv/modules/3d/test/test_fundam.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
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// this list of conditions and the following disclaimer.
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#include "test_precomp.hpp"
namespace opencv_test {
static void test_convertHomogeneous( const Mat& _src, Mat& _dst )
{
Mat src = _src, dst = _dst;
int i, count, sdims, ddims;
int sstep1, sstep2, dstep1, dstep2;
if( src.depth() != CV_64F )
_src.convertTo(src, CV_64F);
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if( dst.depth() != CV_64F )
dst.create(dst.size(), CV_MAKETYPE(CV_64F, _dst.channels()));
if( src.rows > src.cols )
{
count = src.rows;
sdims = src.channels()*src.cols;
sstep1 = (int)(src.step/sizeof(double));
sstep2 = 1;
}
else
{
count = src.cols;
sdims = src.channels()*src.rows;
if( src.rows == 1 )
{
sstep1 = sdims;
sstep2 = 1;
}
else
{
sstep1 = 1;
sstep2 = (int)(src.step/sizeof(double));
}
}
if( dst.rows > dst.cols )
{
CV_Assert( count == dst.rows );
ddims = dst.channels()*dst.cols;
dstep1 = (int)(dst.step/sizeof(double));
dstep2 = 1;
}
else
{
CV_Assert( count == dst.cols );
ddims = dst.channels()*dst.rows;
if( dst.rows == 1 )
{
dstep1 = ddims;
dstep2 = 1;
}
else
{
dstep1 = 1;
dstep2 = (int)(dst.step/sizeof(double));
}
}
double* s = src.ptr<double>();
double* d = dst.ptr<double>();
if( sdims <= ddims )
{
int wstep = dstep2*(ddims - 1);
for( i = 0; i < count; i++, s += sstep1, d += dstep1 )
{
double x = s[0];
double y = s[sstep2];
d[wstep] = 1;
d[0] = x;
d[dstep2] = y;
if( sdims >= 3 )
{
d[dstep2*2] = s[sstep2*2];
if( sdims == 4 )
d[dstep2*3] = s[sstep2*3];
}
}
}
else
{
int wstep = sstep2*(sdims - 1);
for( i = 0; i < count; i++, s += sstep1, d += dstep1 )
{
double w = s[wstep];
double x = s[0];
double y = s[sstep2];
w = w ? 1./w : 1;
d[0] = x*w;
d[dstep2] = y*w;
if( ddims == 3 )
d[dstep2*2] = s[sstep2*2]*w;
}
}
if( dst.data != _dst.data )
dst.convertTo(_dst, _dst.depth());
}
namespace {
/********************************** convert homogeneous *********************************/
class CV_ConvertHomogeneousTest : public cvtest::ArrayTest
{
public:
CV_ConvertHomogeneousTest();
protected:
int read_params( const cv::FileStorage& fs );
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
void fill_array( int test_case_idx, int i, int j, Mat& arr );
double get_success_error_level( int test_case_idx, int i, int j );
void run_func();
void prepare_to_validation( int );
int dims1, dims2;
int pt_count;
};
CV_ConvertHomogeneousTest::CV_ConvertHomogeneousTest()
{
test_array[INPUT].push_back(NULL);
test_array[OUTPUT].push_back(NULL);
test_array[REF_OUTPUT].push_back(NULL);
element_wise_relative_error = false;
pt_count = dims1 = dims2 = 0;
}
int CV_ConvertHomogeneousTest::read_params( const cv::FileStorage& fs )
{
int code = cvtest::ArrayTest::read_params( fs );
return code;
}
void CV_ConvertHomogeneousTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
vector<vector<Size> >& sizes, vector<vector<int> >& types )
{
RNG& rng = ts->get_rng();
int pt_depth1 = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
int pt_depth2 = pt_depth1;//cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
double pt_count_exp = cvtest::randReal(rng)*6 + 1;
int t;
pt_count = cvRound(exp(pt_count_exp));
pt_count = MAX( pt_count, 5 );
dims1 = 2 + (cvtest::randInt(rng) % 2);
dims2 = dims1 + 1;
if( cvtest::randInt(rng) % 2 )
CV_SWAP( dims1, dims2, t );
types[INPUT][0] = CV_MAKETYPE(pt_depth1, 1);
sizes[INPUT][0] = Size(dims1, pt_count);
if( cvtest::randInt(rng) % 2 )
{
types[INPUT][0] = CV_MAKETYPE(pt_depth1, dims1);
if( cvtest::randInt(rng) % 2 )
sizes[INPUT][0] = Size(pt_count, 1);
else
sizes[INPUT][0] = Size(1, pt_count);
}
types[OUTPUT][0] = CV_MAKETYPE(pt_depth2, dims2);
sizes[OUTPUT][0] = Size(1, pt_count);
types[REF_OUTPUT][0] = types[OUTPUT][0];
sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
}
double CV_ConvertHomogeneousTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
return 1e-5;
}
void CV_ConvertHomogeneousTest::fill_array( int /*test_case_idx*/, int /*i*/, int /*j*/, Mat& arr )
{
Mat temp( 1, pt_count, CV_MAKETYPE(CV_64FC1,dims1) );
RNG& rng = ts->get_rng();
Scalar low = Scalar::all(0), high = Scalar::all(10);
if( dims1 > dims2 )
low.val[dims1-1] = 1.;
cvtest::randUni( rng, temp, low, high );
test_convertHomogeneous( temp, arr );
}
void CV_ConvertHomogeneousTest::run_func()
{
cv::Mat _input = test_mat[INPUT][0], &_output = test_mat[OUTPUT][0];
if( dims1 > dims2 )
cv::convertPointsFromHomogeneous(_input, _output);
else
cv::convertPointsToHomogeneous(_input, _output);
}
void CV_ConvertHomogeneousTest::prepare_to_validation( int /*test_case_idx*/ )
{
test_convertHomogeneous( test_mat[INPUT][0], test_mat[REF_OUTPUT][0] );
}
/************************** compute corresponding epipolar lines ************************/
class CV_ComputeEpilinesTest : public cvtest::ArrayTest
{
public:
CV_ComputeEpilinesTest();
protected:
int read_params( const cv::FileStorage& fs );
void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
void fill_array( int test_case_idx, int i, int j, Mat& arr );
double get_success_error_level( int test_case_idx, int i, int j );
void run_func();
void prepare_to_validation( int );
int which_image;
int dims;
int pt_count;
};
CV_ComputeEpilinesTest::CV_ComputeEpilinesTest()
{
test_array[INPUT].push_back(NULL);
test_array[INPUT].push_back(NULL);
test_array[OUTPUT].push_back(NULL);
test_array[REF_OUTPUT].push_back(NULL);
element_wise_relative_error = false;
pt_count = dims = which_image = 0;
}
int CV_ComputeEpilinesTest::read_params( const cv::FileStorage& fs )
{
int code = cvtest::ArrayTest::read_params( fs );
return code;
}
void CV_ComputeEpilinesTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
vector<vector<Size> >& sizes, vector<vector<int> >& types )
{
RNG& rng = ts->get_rng();
int fm_depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
int pt_depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
int ln_depth = pt_depth;
double pt_count_exp = cvtest::randReal(rng)*6;
which_image = 1 + (cvtest::randInt(rng) % 2);
pt_count = cvRound(exp(pt_count_exp));
pt_count = MAX( pt_count, 1 );
bool few_points = pt_count < 5;
dims = 2 + (cvtest::randInt(rng) % 2);
types[INPUT][0] = CV_MAKETYPE(pt_depth, 1);
sizes[INPUT][0] = Size(dims, pt_count);
if( cvtest::randInt(rng) % 2 || few_points )
{
types[INPUT][0] = CV_MAKETYPE(pt_depth, dims);
if( cvtest::randInt(rng) % 2 )
sizes[INPUT][0] = Size(pt_count, 1);
else
sizes[INPUT][0] = Size(1, pt_count);
}
types[INPUT][1] = CV_MAKETYPE(fm_depth, 1);
sizes[INPUT][1] = Size(3, 3);
types[OUTPUT][0] = CV_MAKETYPE(ln_depth, 3);
sizes[OUTPUT][0] = Size(1, pt_count);
types[REF_OUTPUT][0] = types[OUTPUT][0];
sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
}
double CV_ComputeEpilinesTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
{
return 1e-5;
}
void CV_ComputeEpilinesTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
{
RNG& rng = ts->get_rng();
if( i == INPUT && j == 0 )
{
Mat temp( 1, pt_count, CV_MAKETYPE(CV_64FC1,dims) );
cvtest::randUni( rng, temp, Scalar(0,0,1), Scalar::all(10) );
test_convertHomogeneous( temp, arr );
}
else if( i == INPUT && j == 1 )
cvtest::randUni( rng, arr, Scalar::all(0), Scalar::all(10) );
else
cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
}
void CV_ComputeEpilinesTest::run_func()
{
cv::Mat _points = test_mat[INPUT][0], _F = test_mat[INPUT][1], &_lines = test_mat[OUTPUT][0];
cv::computeCorrespondEpilines( _points, which_image, _F, _lines );
}
void CV_ComputeEpilinesTest::prepare_to_validation( int /*test_case_idx*/ )
{
Mat pt( 1, pt_count, CV_MAKETYPE(CV_64F, 3) );
Mat lines( 1, pt_count, CV_MAKETYPE(CV_64F, 3) );
double f[9];
Mat F( 3, 3, CV_64F, f );
test_convertHomogeneous( test_mat[INPUT][0], pt );
test_mat[INPUT][1].convertTo(F, CV_64F);
if( which_image == 2 )
cv::transpose( F, F );
for( int i = 0; i < pt_count; i++ )
{
double* p = pt.ptr<double>() + i*3;
double* l = lines.ptr<double>() + i*3;
double t0 = f[0]*p[0] + f[1]*p[1] + f[2]*p[2];
double t1 = f[3]*p[0] + f[4]*p[1] + f[5]*p[2];
double t2 = f[6]*p[0] + f[7]*p[1] + f[8]*p[2];
double d = sqrt(t0*t0 + t1*t1);
d = d ? 1./d : 1.;
l[0] = t0*d; l[1] = t1*d; l[2] = t2*d;
}
test_convertHomogeneous( lines, test_mat[REF_OUTPUT][0] );
}
TEST(Calib3d_ConvertHomogeneoous, accuracy) { CV_ConvertHomogeneousTest test; test.safe_run(); }
TEST(Calib3d_ComputeEpilines, accuracy) { CV_ComputeEpilinesTest test; test.safe_run(); }
TEST(Calib3d_FindFundamentalMat, correctMatches)
{
double fdata[] = {0, 0, 0, 0, 0, -1, 0, 1, 0};
double p1data[] = {200, 0, 1};
double p2data[] = {170, 0, 1};
Mat F(3, 3, CV_64F, fdata);
Mat p1(1, 1, CV_64FC2, p1data);
Mat p2(1, 1, CV_64FC2, p2data);
Mat np1, np2;
correctMatches(F, p1, p2, np1, np2);
cout << np1 << endl;
cout << np2 << endl;
}
}} // namespace
/* End of file. */