Open Source Computer Vision Library https://opencv.org/
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#include "test_precomp.hpp"
using namespace cv;
using namespace std;
#include <string>
#include <iostream>
#include <fstream>
#include <functional>
#include <iterator>
#include <limits>
#include <numeric>
class CV_Affine3D_EstTest : public cvtest::BaseTest
{
public:
CV_Affine3D_EstTest();
~CV_Affine3D_EstTest();
protected:
void run(int);
bool test4Points();
bool testNPoints();
};
CV_Affine3D_EstTest::CV_Affine3D_EstTest()
{
}
CV_Affine3D_EstTest::~CV_Affine3D_EstTest() {}
float rngIn(float from, float to) { return from + (to-from) * (float)theRNG(); }
struct WrapAff
{
const double *F;
WrapAff(const Mat& aff) : F(aff.ptr<double>()) {}
Point3f operator()(const Point3f& p)
{
return Point3d( p.x * F[0] + p.y * F[1] + p.z * F[2] + F[3],
p.x * F[4] + p.y * F[5] + p.z * F[6] + F[7],
p.x * F[8] + p.y * F[9] + p.z * F[10] + F[11] );
}
};
bool CV_Affine3D_EstTest::test4Points()
{
Mat aff(3, 4, CV_64F);
cv::randu(aff, Scalar(1), Scalar(3));
// setting points that are no in the same line
Mat fpts(1, 4, CV_32FC3);
Mat tpts(1, 4, CV_32FC3);
fpts.ptr<Point3f>()[0] = Point3f( rngIn(1,2), rngIn(1,2), rngIn(5, 6) );
fpts.ptr<Point3f>()[1] = Point3f( rngIn(3,4), rngIn(3,4), rngIn(5, 6) );
fpts.ptr<Point3f>()[2] = Point3f( rngIn(1,2), rngIn(3,4), rngIn(5, 6) );
fpts.ptr<Point3f>()[3] = Point3f( rngIn(3,4), rngIn(1,2), rngIn(5, 6) );
transform(fpts.ptr<Point3f>(), fpts.ptr<Point3f>() + 4, tpts.ptr<Point3f>(), WrapAff(aff));
Mat aff_est;
vector<uchar> outliers;
estimateAffine3D(fpts, tpts, aff_est, outliers);
const double thres = 1e-3;
if (norm(aff_est, aff, NORM_INF) > thres)
{
//cout << norm(aff_est, aff, NORM_INF) << endl;
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return false;
}
return true;
}
struct Noise
{
float l;
Noise(float level) : l(level) {}
Point3f operator()(const Point3f& p)
{
RNG& rng = theRNG();
return Point3f( p.x + l * (float)rng, p.y + l * (float)rng, p.z + l * (float)rng);
}
};
bool CV_Affine3D_EstTest::testNPoints()
{
Mat aff(3, 4, CV_64F);
cv::randu(aff, Scalar(-2), Scalar(2));
// setting points that are no in the same line
const int n = 100;
const int m = 3*n/5;
const Point3f shift_outl = Point3f(15, 15, 15);
const float noise_level = 20.f;
Mat fpts(1, n, CV_32FC3);
Mat tpts(1, n, CV_32FC3);
randu(fpts, Scalar::all(0), Scalar::all(100));
transform(fpts.ptr<Point3f>(), fpts.ptr<Point3f>() + n, tpts.ptr<Point3f>(), WrapAff(aff));
/* adding noise*/
transform(tpts.ptr<Point3f>() + m, tpts.ptr<Point3f>() + n, tpts.ptr<Point3f>() + m, bind2nd(plus<Point3f>(), shift_outl));
transform(tpts.ptr<Point3f>() + m, tpts.ptr<Point3f>() + n, tpts.ptr<Point3f>() + m, Noise(noise_level));
Mat aff_est;
vector<uchar> outl;
int res = estimateAffine3D(fpts, tpts, aff_est, outl);
if (!res)
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return false;
}
const double thres = 1e-4;
if (norm(aff_est, aff, NORM_INF) > thres)
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return false;
}
bool outl_good = count(outl.begin(), outl.end(), 1) == m &&
m == accumulate(outl.begin(), outl.begin() + m, 0);
if (!outl_good)
{
ts->set_failed_test_info(cvtest::TS::FAIL_MISMATCH);
return false;
}
return true;
}
void CV_Affine3D_EstTest::run( int /* start_from */)
{
cvtest::DefaultRngAuto dra;
if (!test4Points())
return;
if (!testNPoints())
return;
ts->set_failed_test_info(cvtest::TS::OK);
}
TEST(Calib3d_EstimateAffineTransform, accuracy) { CV_Affine3D_EstTest test; test.safe_run(); }