Open Source Computer Vision Library https://opencv.org/
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// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html.
//
// Copyright (C) 2018 Intel Corporation
#include <iostream>
#include "opencv2/ts.hpp"
#include "opencv2/gapi.hpp"
namespace
{
inline std::ostream& operator<<(std::ostream& o, const cv::GCompileArg& arg)
{
return o << (arg.tag.empty() ? "empty" : arg.tag);
}
}
namespace opencv_test
{
class TestFunctional
{
public:
cv::Mat in_mat1;
cv::Mat in_mat2;
cv::Mat out_mat_gapi;
cv::Mat out_mat_ocv;
cv::Scalar sc;
cv::Scalar initScalarRandU(unsigned upper)
{
auto& rng = cv::theRNG();
double s1 = rng(upper);
double s2 = rng(upper);
double s3 = rng(upper);
double s4 = rng(upper);
return cv::Scalar(s1, s2, s3, s4);
}
void initMatsRandU(int type, cv::Size sz_in, int dtype, bool createOutputMatrices = true)
{
in_mat1 = cv::Mat(sz_in, type);
in_mat2 = cv::Mat(sz_in, type);
sc = initScalarRandU(100);
cv::randu(in_mat1, cv::Scalar::all(0), cv::Scalar::all(255));
cv::randu(in_mat2, cv::Scalar::all(0), cv::Scalar::all(255));
if (createOutputMatrices && dtype != -1)
{
out_mat_gapi = cv::Mat (sz_in, dtype);
out_mat_ocv = cv::Mat (sz_in, dtype);
}
}
void initMatrixRandU(int type, cv::Size sz_in, int dtype, bool createOutputMatrices = true)
{
in_mat1 = cv::Mat(sz_in, type);
sc = initScalarRandU(100);
cv::randu(in_mat1, cv::Scalar::all(0), cv::Scalar::all(255));
if (createOutputMatrices && dtype != -1)
{
out_mat_gapi = cv::Mat (sz_in, dtype);
out_mat_ocv = cv::Mat (sz_in, dtype);
}
}
void initMatsRandN(int type, cv::Size sz_in, int dtype, bool createOutputMatrices = true)
{
in_mat1 = cv::Mat(sz_in, type);
cv::randn(in_mat1, cv::Scalar::all(127), cv::Scalar::all(40.f));
if (createOutputMatrices && dtype != -1)
{
out_mat_gapi = cv::Mat(sz_in, dtype);
out_mat_ocv = cv::Mat(sz_in, dtype);
}
}
static cv::Mat nonZeroPixels(const cv::Mat& mat)
{
int channels = mat.channels();
std::vector<cv::Mat> split(channels);
cv::split(mat, split);
cv::Mat result;
for (int c=0; c < channels; c++)
{
if (c == 0)
result = split[c] != 0;
else
result = result | (split[c] != 0);
}
return result;
}
static int countNonZeroPixels(const cv::Mat& mat)
{
return cv::countNonZero( nonZeroPixels(mat) );
}
};
template<class T>
class TestParams: public TestFunctional, public TestWithParam<T>{};
template<class T>
class TestPerfParams: public TestFunctional, public perf::TestBaseWithParam<T>{};
using compare_f = std::function<bool(const cv::Mat &a, const cv::Mat &b)>;
using compare_scalar_f = std::function<bool(const cv::Scalar &a, const cv::Scalar &b)>;
template<typename T>
struct Wrappable
{
compare_f to_compare_f()
{
T t = *static_cast<T*const>(this);
return [t](const cv::Mat &a, const cv::Mat &b)
{
return t(a, b);
};
}
};
template<typename T>
struct WrappableScalar
{
compare_scalar_f to_compare_f()
{
T t = *static_cast<T*const>(this);
return [t](const cv::Scalar &a, const cv::Scalar &b)
{
return t(a, b);
};
}
};
class AbsExact : public Wrappable<AbsExact>
{
public:
AbsExact() {}
bool operator() (const cv::Mat& in1, const cv::Mat& in2) const
{
if (cv::norm(in1, in2, NORM_INF) != 0)
{
std::cout << "AbsExact error: G-API output and reference output matrixes are not bitexact equal." << std::endl;
return false;
}
else
{
return true;
}
}
private:
};
class AbsTolerance : public Wrappable<AbsTolerance>
{
public:
AbsTolerance(double tol) : _tol(tol) {}
bool operator() (const cv::Mat& in1, const cv::Mat& in2) const
{
if (cv::norm(in1, in2, NORM_INF) > _tol)
{
std::cout << "AbsTolerance error: Number of different pixels in " << std::endl;
std::cout << "G-API output and reference output matrixes exceeds " << _tol << " pixels threshold." << std::endl;
return false;
}
else
{
return true;
}
}
private:
double _tol;
};
class Tolerance_FloatRel_IntAbs : public Wrappable<Tolerance_FloatRel_IntAbs>
{
public:
Tolerance_FloatRel_IntAbs(double tol, double tol8u) : _tol(tol), _tol8u(tol8u) {}
bool operator() (const cv::Mat& in1, const cv::Mat& in2) const
{
int depth = CV_MAT_DEPTH(in1.type());
{
double err = depth >= CV_32F ? cv::norm(in1, in2, NORM_L1 | NORM_RELATIVE)
: cv::norm(in1, in2, NORM_INF);
double tolerance = depth >= CV_32F ? _tol : _tol8u;
if (err > tolerance)
{
std::cout << "Tolerance_FloatRel_IntAbs error: err=" << err
<< " tolerance=" << tolerance
<< " depth=" << cv::typeToString(depth) << std::endl;
return false;
}
else
{
return true;
}
}
}
private:
double _tol;
double _tol8u;
};
class AbsSimilarPoints : public Wrappable<AbsSimilarPoints>
{
public:
AbsSimilarPoints(double tol, double percent) : _tol(tol), _percent(percent) {}
bool operator() (const cv::Mat& in1, const cv::Mat& in2) const
{
Mat diff;
cv::absdiff(in1, in2, diff);
Mat err_mask = diff > _tol;
int err_points = cv::countNonZero(err_mask.reshape(1));
double max_err_points = _percent * std::max((size_t)1000, in1.total());
if (err_points > max_err_points)
{
std::cout << "AbsSimilarPoints error: err_points=" << err_points
<< " max_err_points=" << max_err_points << " (total=" << in1.total() << ")"
<< " diff_tolerance=" << _tol << std::endl;
return false;
}
else
{
return true;
}
}
private:
double _tol;
double _percent;
};
class ToleranceFilter : public Wrappable<ToleranceFilter>
{
public:
ToleranceFilter(double tol, double tol8u, double inf_tol = 2.0) : _tol(tol), _tol8u(tol8u), _inf_tol(inf_tol) {}
bool operator() (const cv::Mat& in1, const cv::Mat& in2) const
{
int depth = CV_MAT_DEPTH(in1.type());
{
double err_Inf = cv::norm(in1, in2, NORM_INF);
if (err_Inf > _inf_tol)
{
std::cout << "ToleranceFilter error: err_Inf=" << err_Inf << " tolerance=" << _inf_tol << std::endl;
return false;
}
double err = cv::norm(in1, in2, NORM_L2 | NORM_RELATIVE);
double tolerance = depth >= CV_32F ? _tol : _tol8u;
if (err > tolerance)
{
std::cout << "ToleranceFilter error: err=" << err << " tolerance=" << tolerance
<< " depth=" << cv::depthToString(depth)
<< std::endl;
return false;
}
}
return true;
}
private:
double _tol;
double _tol8u;
double _inf_tol;
};
class ToleranceColor : public Wrappable<ToleranceColor>
{
public:
ToleranceColor(double tol, double inf_tol = 2.0) : _tol(tol), _inf_tol(inf_tol) {}
bool operator() (const cv::Mat& in1, const cv::Mat& in2) const
{
{
double err_Inf = cv::norm(in1, in2, NORM_INF);
if (err_Inf > _inf_tol)
{
std::cout << "ToleranceColor error: err_Inf=" << err_Inf << " tolerance=" << _inf_tol << std::endl;;
return false;
}
double err = cv::norm(in1, in2, NORM_L1 | NORM_RELATIVE);
if (err > _tol)
{
std::cout << "ToleranceColor error: err=" << err << " tolerance=" << _tol << std::endl;;
return false;
}
}
return true;
}
private:
double _tol;
double _inf_tol;
};
class AbsToleranceScalar : public WrappableScalar<AbsToleranceScalar>
{
public:
AbsToleranceScalar(double tol) : _tol(tol) {}
bool operator() (const cv::Scalar& in1, const cv::Scalar& in2) const
{
double abs_err = std::abs(in1[0] - in2[0]) / std::max(1.0, std::abs(in2[0]));
if (abs_err > _tol)
{
std::cout << "AbsToleranceScalar error: abs_err=" << abs_err << " tolerance=" << _tol << " in1[0]" << in1[0] << " in2[0]" << in2[0] << std::endl;;
return false;
}
else
{
return true;
}
}
private:
double _tol;
};
} // namespace opencv_test
namespace
{
inline std::ostream& operator<<(std::ostream& os, const opencv_test::compare_f&)
{
return os << "compare_f";
}
}
namespace
{
inline std::ostream& operator<<(std::ostream& os, const opencv_test::compare_scalar_f&)
{
return os << "compare_scalar_f";
}
}