Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
//
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// Intel License Agreement
// For Open Source Computer Vision Library
//
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#include "test_precomp.hpp"
using namespace cv;
using namespace std;
/*////////////////////// emd_test /////////////////////////*/
class CV_EMDTest : public cvtest::BaseTest
{
public:
CV_EMDTest();
protected:
void run(int);
};
CV_EMDTest::CV_EMDTest()
{
}
void CV_EMDTest::run( int )
{
int code = cvtest::TS::OK;
const double success_error_level = 1e-6;
#define M 10000
double emd0 = 2460./210;
static float cost[] =
{
16, 16, 13, 22, 17,
14, 14, 13, 19, 15,
19, 19, 20, 23, M,
M , 0, M, 0, 0
};
static float w1[] = { 50, 60, 50, 50 },
w2[] = { 30, 20, 70, 30, 60 };
Mat _w1(4, 1, CV_32F, w1);
Mat _w2(5, 1, CV_32F, w2);
Mat _cost(_w1.rows, _w2.rows, CV_32F, cost);
float emd = EMD( _w1, _w2, -1, _cost );
if( fabs( emd - emd0 ) > success_error_level*emd0 )
{
ts->printf( cvtest::TS::LOG,
"The computed distance is %.2f, while it should be %.2f\n", emd, emd0 );
code = cvtest::TS::FAIL_BAD_ACCURACY;
}
if( code < 0 )
ts->set_failed_test_info( code );
}
TEST(Imgproc_EMD, regression) { CV_EMDTest test; test.safe_run(); }
/* End of file. */