// 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 #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 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 TestParams: public TestFunctional, public TestWithParam{}; template class TestPerfParams: public TestFunctional, public perf::TestBaseWithParam{}; using compare_f = std::function; using compare_scalar_f = std::function; template struct Wrappable { compare_f to_compare_f() { T t = *static_cast(this); return [t](const cv::Mat &a, const cv::Mat &b) { return t(a, b); }; } }; template struct WrappableScalar { compare_scalar_f to_compare_f() { T t = *static_cast(this); return [t](const cv::Scalar &a, const cv::Scalar &b) { return t(a, b); }; } }; class AbsExact : public Wrappable { 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 { 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 { 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 { 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 { 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 { 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 { 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"; } }