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diff --git a/inference-engine/thirdparty/fluid/modules/gapi/test/common/gapi_core_tests_inl.hpp b/inference-engine/thirdparty/fluid/modules/gapi/test/common/gapi_core_tests_inl.hpp
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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
+
+
+#ifndef OPENCV_GAPI_CORE_TESTS_INL_HPP
+#define OPENCV_GAPI_CORE_TESTS_INL_HPP
+
+#include "opencv2/gapi/core.hpp"
+#include "gapi_core_tests.hpp"
+
+namespace opencv_test
+{
+
+TEST_P(MathOpTest, MatricesAccuracyTest )
+{
+ mathOp opType = ADD;
+ int type = 0, dtype = 0;
+ cv::Size sz;
+ double scale = 1; // mul, div
+ bool testWithScalar = false, initOutMatr = false, doReverseOp = false;
+ cv::GCompileArgs compile_args;
+ std::tie(opType, testWithScalar, type, scale, sz, dtype, initOutMatr, doReverseOp, compile_args) = GetParam();
+ initMatsRandU(type, sz, dtype, initOutMatr);
+
+ // G-API code & corresponding OpenCV code ////////////////////////////////
+ cv::GMat in1, in2, out;
+ if( testWithScalar )
+ {
+ cv::GScalar sc1;
+ switch(opType)
+ {
+ case (ADD):
+ {
+ out = cv::gapi::addC(in1, sc1, dtype);
+ cv::add(in_mat1, sc, out_mat_ocv, cv::noArray(), dtype);
+ break;
+ }
+ case (SUB):
+ {
+ if( doReverseOp )
+ {
+ out = cv::gapi::subRC(sc1, in1, dtype);
+ cv::subtract(sc, in_mat1, out_mat_ocv, cv::noArray(), dtype);
+ }
+ else
+ {
+ out = cv::gapi::subC(in1, sc1, dtype);
+ cv::subtract(in_mat1, sc, out_mat_ocv, cv::noArray(), dtype);
+ }
+ break;
+ }
+ case (DIV):
+ {
+ if( doReverseOp )
+ {
+ in_mat1.setTo(1, in_mat1 == 0); // avoid zeros in divide input data
+ out = cv::gapi::divRC(sc1, in1, scale, dtype);
+ cv::divide(sc, in_mat1, out_mat_ocv, scale, dtype);
+ break;
+ }
+ else
+ {
+ sc += Scalar(1, 1, 1, 1); // avoid zeros in divide input data
+ out = cv::gapi::divC(in1, sc1, scale, dtype);
+ cv::divide(in_mat1, sc, out_mat_ocv, scale, dtype);
+ break;
+ }
+ }
+ case (MUL):
+ {
+ // FIXME: add `scale` parameter to mulC
+ out = cv::gapi::mulC(in1, sc1, /* scale, */ dtype);
+ cv::multiply(in_mat1, sc, out_mat_ocv, 1., dtype);
+ break;
+ }
+ default:
+ {
+ FAIL() << "no such math operation type for scalar and matrix!";
+ }
+ }
+ cv::GComputation c(GIn(in1, sc1), GOut(out));
+ c.apply(gin(in_mat1, sc), gout(out_mat_gapi), std::move(compile_args));
+ }
+ else
+ {
+ switch(opType)
+ {
+ case (ADD):
+ {
+ out = cv::gapi::add(in1, in2, dtype);
+ cv::add(in_mat1, in_mat2, out_mat_ocv, cv::noArray(), dtype);
+ break;
+ }
+ case (SUB):
+ {
+ out = cv::gapi::sub(in1, in2, dtype);
+ cv::subtract(in_mat1, in_mat2, out_mat_ocv, cv::noArray(), dtype);
+ break;
+ }
+ case (DIV):
+ {
+ in_mat2.setTo(1, in_mat2 == 0); // avoid zeros in divide input data
+ out = cv::gapi::div(in1, in2, scale, dtype);
+ cv::divide(in_mat1, in_mat2, out_mat_ocv, scale, dtype);
+ break;
+ }
+ case (MUL):
+ {
+ out = cv::gapi::mul(in1, in2, scale, dtype);
+ cv::multiply(in_mat1, in_mat2, out_mat_ocv, scale, dtype);
+ break;
+ }
+ default:
+ {
+ FAIL() << "no such math operation type for matrix and matrix!";
+ }}
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+ c.apply(gin(in_mat1, in_mat2), gout(out_mat_gapi), std::move(compile_args));
+ }
+
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ // TODO: make threshold vs bit-exact criteria be driven by testing parameter
+ #if 1
+ if (CV_MAT_DEPTH(out_mat_ocv.type()) != CV_32F &&
+ CV_MAT_DEPTH(out_mat_ocv.type()) != CV_64F)
+ {
+ // integral: allow 1% of differences, and no diffs by >1 unit
+ EXPECT_LE(countNonZeroPixels(cv::abs(out_mat_gapi - out_mat_ocv) > 0),
+ 0.01*out_mat_ocv.total());
+ EXPECT_LE(countNonZeroPixels(cv::abs(out_mat_gapi - out_mat_ocv) > 1), 0);
+ }
+ else
+ {
+ // floating-point: expect 6 decimal digits - best we expect of F32
+ EXPECT_EQ(0, cv::countNonZero(cv::abs(out_mat_gapi - out_mat_ocv) >
+ 1e-6*cv::abs(out_mat_ocv)));
+ }
+ #else
+ EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
+ #endif
+ EXPECT_EQ(out_mat_gapi.size(), sz);
+ }
+}
+
+TEST_P(MulDoubleTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ int dtype = std::get<2>(param);
+ cv::Size sz_in = std::get<1>(param);
+ bool initOut = std::get<3>(param);
+
+ auto& rng = cv::theRNG();
+ double d = rng.uniform(0.0, 10.0);
+ auto compile_args = std::get<4>(param);
+ initMatrixRandU(type, sz_in, dtype, initOut);
+
+ // G-API code ////////////////////////////////////////////////////////////
+ cv::GMat in1, out;
+ out = cv::gapi::mulC(in1, d, dtype);
+ cv::GComputation c(in1, out);
+ c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
+
+ // OpenCV code ///////////////////////////////////////////////////////////
+ cv::multiply(in_mat1, d, out_mat_ocv, 1, dtype);
+
+ // Comparison ////////////////////////////////////////////////////////////
+#if 1
+ if (CV_MAT_DEPTH(out_mat_ocv.type()) != CV_32F &&
+ CV_MAT_DEPTH(out_mat_ocv.type()) != CV_64F)
+ {
+ // integral: allow 1% of differences, and no diffs by >1 unit
+ EXPECT_LE(countNonZeroPixels(cv::abs(out_mat_gapi - out_mat_ocv) > 0),
+ 0.01*out_mat_ocv.total());
+ EXPECT_LE(countNonZeroPixels(cv::abs(out_mat_gapi - out_mat_ocv) > 1), 0);
+ }
+ else
+ {
+ // floating-point: expect 6 decimal digits - best we expect of F32
+ EXPECT_EQ(0, cv::countNonZero(cv::abs(out_mat_gapi - out_mat_ocv) >
+ 1e-6*cv::abs(out_mat_ocv)));
+ }
+#else
+ EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
+#endif
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+}
+
+TEST_P(DivTest, DISABLED_DivByZeroTest) // https://github.com/opencv/opencv/pull/12826
+{
+ int type = 0, dtype = 0;
+ cv::Size sz_in;
+ bool initOut = false;
+ cv::GCompileArgs compile_args;
+ std::tie(type, sz_in, dtype, initOut, compile_args) = GetParam();
+
+ initMatrixRandU(type, sz_in, dtype, initOut);
+ in_mat2 = cv::Mat(sz_in, type);
+ in_mat2.setTo(cv::Scalar::all(0));
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2;
+ auto out = cv::gapi::div(in1, in2, 1.0, dtype);
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+ c.apply(gin(in_mat1, in_mat2), gout(out_mat_gapi), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::divide(in_mat1, in_mat2, out_mat_ocv, 1.0, dtype);
+ }
+
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(DivCTest, DISABLED_DivByZeroTest) // https://github.com/opencv/opencv/pull/12826
+{
+ int type = 0, dtype = 0;
+ cv::Size sz_in;
+ bool initOut = false;
+ cv::GCompileArgs compile_args;
+ std::tie(type, sz_in, dtype, initOut, compile_args) = GetParam();
+
+ initMatrixRandU(type, sz_in, dtype, initOut);
+ sc = cv::Scalar::all(0);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1;
+ cv::GScalar sc1;
+ auto out = cv::gapi::divC(in1, sc1, dtype);
+ cv::GComputation c(GIn(in1, sc1), GOut(out));
+
+ c.apply(gin(in_mat1, sc), gout(out_mat_gapi), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::divide(in_mat1, sc, out_mat_ocv, dtype);
+ }
+
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ cv::Mat zeros = cv::Mat::zeros(sz_in, type);
+ EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != zeros));
+ }
+}
+
+TEST_P(MeanTest, AccuracyTest)
+{
+ int type = 0;
+ bool initOut = false;
+ cv::Size sz_in;
+ cv::GCompileArgs compile_args;
+ std::tie(type, sz_in, initOut, compile_args) = GetParam();
+ initMatrixRandU(type, sz_in, initOut);
+ cv::Scalar out_norm;
+ cv::Scalar out_norm_ocv;
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in;
+ auto out = cv::gapi::mean(in);
+
+ cv::GComputation c(cv::GIn(in), cv::GOut(out));
+ c.apply(cv::gin(in_mat1), cv::gout(out_norm), std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ out_norm_ocv = cv::mean(in_mat1);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(out_norm[0], out_norm_ocv[0]);
+ }
+}
+
+TEST_P(MaskTest, AccuracyTest)
+{
+ int type = 0;
+ bool initOut = false;
+ cv::Size sz_in;
+ cv::GCompileArgs compile_args;
+ std::tie(type, sz_in, initOut, compile_args) = GetParam();
+ initMatrixRandU(type, sz_in, type, initOut);
+
+ in_mat2 = cv::Mat(sz_in, CV_8UC1);
+ cv::randu(in_mat2, cv::Scalar::all(0), cv::Scalar::all(255));
+ in_mat2 = in_mat2 > 128;
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in, m;
+ auto out = cv::gapi::mask(in, m);
+
+ cv::GComputation c(cv::GIn(in, m), cv::GOut(out));
+ c.apply(cv::gin(in_mat1, in_mat2), cv::gout(out_mat_gapi), std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ out_mat_ocv = cv::Mat::zeros(in_mat1.size(), in_mat1.type());
+ in_mat1.copyTo(out_mat_ocv, in_mat2);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ }
+}
+
+TEST_P(Polar2CartTest, AccuracyTest)
+{
+ auto param = GetParam();
+ cv::Size sz_in = std::get<0>(param);
+ auto compile_args = std::get<2>(param);
+ initMatsRandU(CV_32FC1, sz_in, CV_32FC1, std::get<1>(param));
+
+ cv::Mat out_mat2;
+ cv::Mat out_mat_ocv2;
+ if(std::get<1>(param) == true)
+ {
+ out_mat2 = cv::Mat(sz_in, CV_32FC1);
+ out_mat_ocv2 = cv::Mat(sz_in, CV_32FC1);
+ }
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2, out1, out2;
+ std::tie(out1, out2) = cv::gapi::polarToCart(in1, in2);
+
+ cv::GComputation c(GIn(in1, in2), GOut(out1, out2));
+ c.apply(gin(in_mat1,in_mat2), gout(out_mat_gapi, out_mat2), std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::polarToCart(in_mat1, in_mat2, out_mat_ocv, out_mat_ocv2);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ // Note that we cannot rely on bit-exact sin/cos functions used for this
+ // transform, so we need a threshold for verifying results vs reference.
+ //
+ // Relative threshold like 1e-6 is very restrictive, nearly best we can
+ // expect of single-precision elementary functions implementation.
+ //
+ // However, good idea is making such threshold configurable: parameter
+ // of this test - which a specific test istantiation could setup.
+ //
+ // Note that test instantiation for the OpenCV back-end could even let
+ // the threshold equal to zero, as CV back-end calls the same kernel.
+ //
+ // TODO: Make threshold a configurable parameter of this test (ADE-221)
+
+ cv::Mat &outx = out_mat_gapi,
+ &outy = out_mat2;
+ cv::Mat &refx = out_mat_ocv,
+ &refy = out_mat_ocv2;
+ cv::Mat difx = cv::abs(refx - outx),
+ dify = cv::abs(refy - outy);
+ cv::Mat absx = cv::abs(refx),
+ absy = cv::abs(refy);
+
+ EXPECT_EQ(0, cv::countNonZero(difx > 1e-6*absx));
+ EXPECT_EQ(0, cv::countNonZero(dify > 1e-6*absy));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(Cart2PolarTest, AccuracyTest)
+{
+ auto param = GetParam();
+ cv::Size sz_in = std::get<0>(param);
+ auto compile_args = std::get<2>(param);
+ initMatsRandU(CV_32FC1, sz_in, CV_32FC1, std::get<1>(param));
+
+ cv::Mat out_mat2(sz_in, CV_32FC1);
+ cv::Mat out_mat_ocv2(sz_in, CV_32FC1);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2, out1, out2;
+ std::tie(out1, out2) = cv::gapi::cartToPolar(in1, in2);
+
+ cv::GComputation c(GIn(in1, in2), GOut(out1, out2));
+ c.apply(gin(in_mat1,in_mat2), gout(out_mat_gapi, out_mat2));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::cartToPolar(in_mat1, in_mat2, out_mat_ocv, out_mat_ocv2);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ // Note that we cannot rely on bit-exact sin/cos functions used for this
+ // transform, so we need a threshold for verifying results vs reference.
+ //
+ // Relative threshold like 1e-6 is very restrictive, nearly best we can
+ // expect of single-precision elementary functions implementation.
+ //
+ // However, good idea is making such threshold configurable: parameter
+ // of this test - which a specific test istantiation could setup.
+ //
+ // Note that test instantiation for the OpenCV back-end could even let
+ // the threshold equal to zero, as CV back-end calls the same kernel.
+ //
+ // TODO: Make threshold a configurable parameter of this test (ADE-221)
+
+ cv::Mat &outm = out_mat_gapi,
+ &outa = out_mat2;
+ cv::Mat &refm = out_mat_ocv,
+ &refa = out_mat_ocv2;
+ cv::Mat difm = cv::abs(refm - outm),
+ difa = cv::abs(refa - outa);
+ cv::Mat absm = cv::abs(refm),
+ absa = cv::abs(refa);
+
+ // FIXME: Angle result looks inaccurate at OpenCV
+ // (expected relative accuracy like 1e-6)
+ EXPECT_EQ(0, cv::countNonZero(difm > 1e-6*absm));
+ EXPECT_EQ(0, cv::countNonZero(difa > 1e-3*absa));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(CmpTest, AccuracyTest)
+{
+ CmpTypes opType = CMP_EQ;
+ int type = 0;
+ cv::Size sz;
+ bool testWithScalar = false, initOutMatr = false;
+ cv::GCompileArgs compile_args;
+ std::tie(opType, testWithScalar, type, sz, initOutMatr, compile_args) = GetParam();
+ initMatsRandU(type, sz, CV_8U, initOutMatr);
+
+ // G-API code & corresponding OpenCV code ////////////////////////////////
+ cv::GMat in1, out;
+ if( testWithScalar )
+ {
+ cv::GScalar in2;
+ switch(opType)
+ {
+ case CMP_EQ: out = cv::gapi::cmpEQ(in1, in2); break;
+ case CMP_GT: out = cv::gapi::cmpGT(in1, in2); break;
+ case CMP_GE: out = cv::gapi::cmpGE(in1, in2); break;
+ case CMP_LT: out = cv::gapi::cmpLT(in1, in2); break;
+ case CMP_LE: out = cv::gapi::cmpLE(in1, in2); break;
+ case CMP_NE: out = cv::gapi::cmpNE(in1, in2); break;
+ default: FAIL() << "no such compare operation type for matrix and scalar!";
+ }
+
+ cv::compare(in_mat1, sc, out_mat_ocv, opType);
+
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+ c.apply(gin(in_mat1, sc), gout(out_mat_gapi), std::move(compile_args));
+ }
+ else
+ {
+ cv::GMat in2;
+ switch(opType)
+ {
+ case CMP_EQ: out = cv::gapi::cmpEQ(in1, in2); break;
+ case CMP_GT: out = cv::gapi::cmpGT(in1, in2); break;
+ case CMP_GE: out = cv::gapi::cmpGE(in1, in2); break;
+ case CMP_LT: out = cv::gapi::cmpLT(in1, in2); break;
+ case CMP_LE: out = cv::gapi::cmpLE(in1, in2); break;
+ case CMP_NE: out = cv::gapi::cmpNE(in1, in2); break;
+ default: FAIL() << "no such compare operation type for two matrices!";
+ }
+
+ cv::compare(in_mat1, in_mat2, out_mat_ocv, opType);
+
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+ c.apply(gin(in_mat1, in_mat2), gout(out_mat_gapi), std::move(compile_args));
+ }
+
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
+ EXPECT_EQ(out_mat_gapi.size(), sz);
+ }
+}
+
+TEST_P(BitwiseTest, AccuracyTest)
+{
+ bitwiseOp opType = AND;
+ int type = 0;
+ cv::Size sz;
+ bool initOutMatr = false;
+ cv::GCompileArgs compile_args;
+ std::tie(opType, type, sz, initOutMatr, compile_args) = GetParam();
+ initMatsRandU(type, sz, type, initOutMatr);
+
+ // G-API code & corresponding OpenCV code ////////////////////////////////
+ cv::GMat in1, in2, out;
+ switch(opType)
+ {
+ case AND:
+ {
+ out = cv::gapi::bitwise_and(in1, in2);
+ cv::bitwise_and(in_mat1, in_mat2, out_mat_ocv);
+ break;
+ }
+ case OR:
+ {
+ out = cv::gapi::bitwise_or(in1, in2);
+ cv::bitwise_or(in_mat1, in_mat2, out_mat_ocv);
+ break;
+ }
+ case XOR:
+ {
+ out = cv::gapi::bitwise_xor(in1, in2);
+ cv::bitwise_xor(in_mat1, in_mat2, out_mat_ocv);
+ break;
+ }
+ default:
+ {
+ FAIL() << "no such bitwise operation type!";
+ }
+ }
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+ c.apply(gin(in_mat1, in_mat2), gout(out_mat_gapi), std::move(compile_args));
+
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(out_mat_gapi.size(), sz);
+ }
+}
+
+TEST_P(NotTest, AccuracyTest)
+{
+ auto param = GetParam();
+ cv::Size sz_in = std::get<1>(param);
+ auto compile_args = std::get<3>(param);
+ initMatrixRandU(std::get<0>(param), sz_in, std::get<0>(param), std::get<2>(param));
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in;
+ auto out = cv::gapi::bitwise_not(in);
+ cv::GComputation c(in, out);
+
+ c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::bitwise_not(in_mat1, out_mat_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(SelectTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ cv::Size sz_in = std::get<1>(param);
+ auto compile_args = std::get<3>(param);
+ initMatsRandU(type, sz_in, type, std::get<2>(param));
+ cv::Mat in_mask(sz_in, CV_8UC1);
+ cv::randu(in_mask, cv::Scalar::all(0), cv::Scalar::all(255));
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2, in3;
+ auto out = cv::gapi::select(in1, in2, in3);
+ cv::GComputation c(GIn(in1, in2, in3), GOut(out));
+
+ c.apply(gin(in_mat1, in_mat2, in_mask), gout(out_mat_gapi), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ in_mat2.copyTo(out_mat_ocv);
+ in_mat1.copyTo(out_mat_ocv, in_mask);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(MinTest, AccuracyTest)
+{
+ auto param = GetParam();
+ cv::Size sz_in = std::get<1>(param);
+ auto compile_args = std::get<3>(param);
+ initMatsRandU(std::get<0>(param), sz_in, std::get<0>(param), std::get<2>(param));
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2;
+ auto out = cv::gapi::min(in1, in2);
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+
+ c.apply(gin(in_mat1, in_mat2), gout(out_mat_gapi), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::min(in_mat1, in_mat2, out_mat_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(MaxTest, AccuracyTest)
+{
+ auto param = GetParam();
+ cv::Size sz_in = std::get<1>(param);
+ auto compile_args = std::get<3>(param);
+ initMatsRandU(std::get<0>(param), sz_in, std::get<0>(param), std::get<2>(param));
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2;
+ auto out = cv::gapi::max(in1, in2);
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+
+ c.apply(gin(in_mat1, in_mat2), gout(out_mat_gapi), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::max(in_mat1, in_mat2, out_mat_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(AbsDiffTest, AccuracyTest)
+{
+ auto param = GetParam();
+ cv::Size sz_in = std::get<1>(param);
+ auto compile_args = std::get<3>(param);
+ initMatsRandU(std::get<0>(param), sz_in, std::get<0>(param), std::get<2>(param));
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2;
+ auto out = cv::gapi::absDiff(in1, in2);
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+
+ c.apply(gin(in_mat1, in_mat2), gout(out_mat_gapi), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::absdiff(in_mat1, in_mat2, out_mat_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(AbsDiffCTest, AccuracyTest)
+{
+ auto param = GetParam();
+ cv::Size sz_in = std::get<1>(param);
+ auto compile_args = std::get<3>(param);
+ initMatsRandU(std::get<0>(param), sz_in, std::get<0>(param), std::get<2>(param));
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1;
+ cv::GScalar sc1;
+ auto out = cv::gapi::absDiffC(in1, sc1);
+ cv::GComputation c(cv::GIn(in1, sc1), cv::GOut(out));
+
+ c.apply(gin(in_mat1, sc), gout(out_mat_gapi), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::absdiff(in_mat1, sc, out_mat_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_gapi != out_mat_ocv));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(SumTest, AccuracyTest)
+{
+ auto param = GetParam();
+ cv::Size sz_in = std::get<1>(param);
+ auto tolerance = std::get<3>(param);
+ auto compile_args = std::get<4>(param);
+ //initMatrixRandU(std::get<0>(param), sz_in, std::get<2>(param));
+ initMatsRandN(std::get<0>(param), sz_in, std::get<2>(param)); //TODO: workaround trying to fix SumTest failures
+
+
+ cv::Scalar out_sum;
+ cv::Scalar out_sum_ocv;
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in;
+ auto out = cv::gapi::sum(in);
+
+ cv::GComputation c(cv::GIn(in), cv::GOut(out));
+ c.apply(cv::gin(in_mat1), cv::gout(out_sum), std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ out_sum_ocv = cv::sum(in_mat1);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_LE(std::abs(out_sum[0] - out_sum_ocv[0]) / std::max(1.0, std::abs(out_sum_ocv[0])), tolerance)
+ << "OCV=" << out_sum_ocv[0] << " GAPI=" << out_sum[0];
+ }
+}
+
+TEST_P(AddWeightedTest, AccuracyTest)
+{
+ int type = 0, dtype = 0;
+ cv::Size sz_in;
+ bool initOut = false;
+ cv::GCompileArgs compile_args;
+ double tolerance = 0.0;
+ std::tie(type, sz_in, dtype, initOut, tolerance, compile_args) = GetParam();
+
+ auto& rng = cv::theRNG();
+ double alpha = rng.uniform(0.0, 1.0);
+ double beta = rng.uniform(0.0, 1.0);
+ double gamma = rng.uniform(0.0, 1.0);
+ initMatsRandU(type, sz_in, dtype, initOut);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2;
+ auto out = cv::gapi::addWeighted(in1, alpha, in2, beta, gamma, dtype);
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+
+ c.apply(gin(in_mat1, in_mat2), gout(out_mat_gapi), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::addWeighted(in_mat1, alpha, in_mat2, beta, gamma, out_mat_ocv, dtype);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ // Note, that we cannot expect bitwise results for add-weighted:
+ //
+ // tmp = src1*alpha + src2*beta + gamma;
+ // dst = saturate<DST>( round(tmp) );
+ //
+ // Because tmp is floating-point, dst depends on compiler optimizations
+ //
+ // However, we must expect good accuracy of tmp, and rounding correctly
+
+ cv::Mat failures;
+
+ if (out_mat_ocv.type() == CV_32FC1)
+ {
+ // result: float - may vary in 7th decimal digit
+ failures = abs(out_mat_gapi - out_mat_ocv) > abs(out_mat_ocv) * 1e-6;
+ }
+ else
+ {
+ // result: integral - rounding may vary if fractional part of tmp
+ // is nearly 0.5
+
+ cv::Mat inexact, incorrect, diff, tmp;
+
+ inexact = out_mat_gapi != out_mat_ocv;
+
+ // even if rounded differently, check if still rounded correctly
+ cv::addWeighted(in_mat1, alpha, in_mat2, beta, gamma, tmp, CV_32F);
+ cv::subtract(out_mat_gapi, tmp, diff, cv::noArray(), CV_32F);
+ incorrect = abs(diff) >= tolerance;// 0.5000005f; // relative to 6 digits
+
+ failures = inexact & incorrect;
+ }
+
+ EXPECT_EQ(0, cv::countNonZero(failures));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(NormTest, AccuracyTest)
+{
+ NormTypes opType = NORM_INF;
+ int type = 0;
+ cv::Size sz;
+ double tolerance = 0.0;
+ cv::GCompileArgs compile_args;
+ std::tie(opType, type, sz, tolerance, compile_args) = GetParam();
+ initMatrixRandU(type, sz, type, false);
+
+ cv::Scalar out_norm;
+ cv::Scalar out_norm_ocv;
+
+ // G-API code & corresponding OpenCV code ////////////////////////////////
+ cv::GMat in1;
+ cv::GScalar out;
+ switch(opType)
+ {
+ case NORM_L1: out = cv::gapi::normL1(in1); break;
+ case NORM_L2: out = cv::gapi::normL2(in1); break;
+ case NORM_INF: out = cv::gapi::normInf(in1); break;
+ default: FAIL() << "no such norm operation type!";
+ }
+ out_norm_ocv = cv::norm(in_mat1, opType);
+ cv::GComputation c(GIn(in1), GOut(out));
+ c.apply(gin(in_mat1), gout(out_norm), std::move(compile_args));
+
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_LE(std::abs(out_norm[0] - out_norm_ocv[0]) / std::max(1.0, std::abs(out_norm_ocv[0])), tolerance)
+ << "OCV=" << out_norm_ocv[0] << " GAPI=" << out_norm[0];
+ }
+}
+
+TEST_P(IntegralTest, AccuracyTest)
+{
+ int type = std::get<0>(GetParam());
+ cv::Size sz_in = std::get<1>(GetParam());
+ auto compile_args = std::get<2>(GetParam());
+
+ int type_out = (type == CV_8U) ? CV_32SC1 : CV_64FC1;
+ cv::Mat in_mat1(sz_in, type);
+
+ cv::randu(in_mat1, cv::Scalar::all(0), cv::Scalar::all(255));
+
+ cv::Size sz_out = cv::Size(sz_in.width + 1, sz_in.height + 1);
+ cv::Mat out_mat1(sz_out, type_out);
+ cv::Mat out_mat_ocv1(sz_out, type_out);
+
+ cv::Mat out_mat2(sz_out, CV_64FC1);
+ cv::Mat out_mat_ocv2(sz_out, CV_64FC1);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, out1, out2;
+ std::tie(out1, out2) = cv::gapi::integral(in1, type_out, CV_64FC1);
+ cv::GComputation c(cv::GIn(in1), cv::GOut(out1, out2));
+
+ c.apply(cv::gin(in_mat1), cv::gout(out_mat1, out_mat2), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::integral(in_mat1, out_mat_ocv1, out_mat_ocv2);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv1 != out_mat1));
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv2 != out_mat2));
+ }
+}
+
+TEST_P(ThresholdTest, AccuracyTestBinary)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ cv::Size sz_in = std::get<1>(param);
+ int tt = std::get<2>(param);
+
+ auto compile_args = std::get<4>(param);
+ cv::Scalar thr = initScalarRandU(50);
+ cv::Scalar maxval = initScalarRandU(50) + cv::Scalar(50, 50, 50, 50);
+ initMatrixRandU(type, sz_in, type, std::get<3>(param));
+ cv::Scalar out_scalar;
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, out;
+ cv::GScalar th1, mv1;
+ out = cv::gapi::threshold(in1, th1, mv1, tt);
+ cv::GComputation c(GIn(in1, th1, mv1), GOut(out));
+
+ c.apply(gin(in_mat1, thr, maxval), gout(out_mat_gapi), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::threshold(in_mat1, out_mat_ocv, thr.val[0], maxval.val[0], tt);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ ASSERT_EQ(out_mat_gapi.size(), sz_in);
+ EXPECT_EQ(0, cv::norm(out_mat_ocv, out_mat_gapi, NORM_L1));
+ }
+}
+
+TEST_P(ThresholdOTTest, AccuracyTestOtsu)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ cv::Size sz_in = std::get<1>(param);
+ int tt = std::get<2>(param);
+
+ auto compile_args = std::get<4>(param);
+ cv::Scalar maxval = initScalarRandU(50) + cv::Scalar(50, 50, 50, 50);
+ initMatrixRandU(type, sz_in, type, std::get<3>(param));
+ cv::Scalar out_gapi_scalar;
+ double ocv_res;
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, out;
+ cv::GScalar mv1, scout;
+ std::tie<cv::GMat, cv::GScalar>(out, scout) = cv::gapi::threshold(in1, mv1, tt);
+ cv::GComputation c(cv::GIn(in1, mv1), cv::GOut(out, scout));
+
+ c.apply(gin(in_mat1, maxval), gout(out_mat_gapi, out_gapi_scalar), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ ocv_res = cv::threshold(in_mat1, out_mat_ocv, maxval.val[0], maxval.val[0], tt);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ EXPECT_EQ(ocv_res, out_gapi_scalar.val[0]);
+ }
+}
+
+TEST_P(InRangeTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ cv::Size sz_in = std::get<1>(param);
+
+ auto compile_args = std::get<3>(param);
+ cv::Scalar thrLow = initScalarRandU(100);
+ cv::Scalar thrUp = initScalarRandU(100) + cv::Scalar(100, 100, 100, 100);
+ initMatrixRandU(type, sz_in, type, std::get<2>(param));
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1;
+ cv::GScalar th1, mv1;
+ auto out = cv::gapi::inRange(in1, th1, mv1);
+ cv::GComputation c(GIn(in1, th1, mv1), GOut(out));
+
+ c.apply(gin(in_mat1, thrLow, thrUp), gout(out_mat_gapi), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::inRange(in_mat1, thrLow, thrUp, out_mat_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(Split3Test, AccuracyTest)
+{
+ cv::Size sz_in = std::get<0>(GetParam());
+ auto compile_args = std::get<1>(GetParam());
+ initMatrixRandU(CV_8UC3, sz_in, CV_8UC1);
+
+ cv::Mat out_mat2 = cv::Mat(sz_in, CV_8UC1);
+ cv::Mat out_mat3 = cv::Mat(sz_in, CV_8UC1);
+ cv::Mat out_mat_ocv2 = cv::Mat(sz_in, CV_8UC1);
+ cv::Mat out_mat_ocv3 = cv::Mat(sz_in, CV_8UC1);
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, out1, out2, out3;
+ std::tie(out1, out2, out3) = cv::gapi::split3(in1);
+ cv::GComputation c(cv::GIn(in1), cv::GOut(out1, out2, out3));
+
+ c.apply(cv::gin(in_mat1), cv::gout(out_mat_gapi, out_mat2, out_mat3), std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ std::vector<cv::Mat> out_mats_ocv = {out_mat_ocv, out_mat_ocv2, out_mat_ocv3};
+ cv::split(in_mat1, out_mats_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv2 != out_mat2));
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv3 != out_mat3));
+ }
+}
+
+TEST_P(Split4Test, AccuracyTest)
+{
+ cv::Size sz_in = std::get<0>(GetParam());
+ auto compile_args = std::get<1>(GetParam());
+ initMatrixRandU(CV_8UC4, sz_in, CV_8UC1);
+ cv::Mat out_mat2 = cv::Mat(sz_in, CV_8UC1);
+ cv::Mat out_mat3 = cv::Mat(sz_in, CV_8UC1);
+ cv::Mat out_mat4 = cv::Mat(sz_in, CV_8UC1);
+ cv::Mat out_mat_ocv2 = cv::Mat(sz_in, CV_8UC1);
+ cv::Mat out_mat_ocv3 = cv::Mat(sz_in, CV_8UC1);
+ cv::Mat out_mat_ocv4 = cv::Mat(sz_in, CV_8UC1);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, out1, out2, out3, out4;
+ std::tie(out1, out2, out3, out4) = cv::gapi::split4(in1);
+ cv::GComputation c(cv::GIn(in1), cv::GOut(out1, out2, out3, out4));
+
+ c.apply(cv::gin(in_mat1), cv::gout(out_mat_gapi, out_mat2, out_mat3, out_mat4), std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ std::vector<cv::Mat> out_mats_ocv = {out_mat_ocv, out_mat_ocv2, out_mat_ocv3, out_mat_ocv4};
+ cv::split(in_mat1, out_mats_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv2 != out_mat2));
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv3 != out_mat3));
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv4 != out_mat4));
+ }
+}
+
+static void ResizeAccuracyTest(compare_f cmpF, int type, int interp, cv::Size sz_in, cv::Size sz_out, double fx, double fy, cv::GCompileArgs&& compile_args)
+{
+ cv::Mat in_mat1 (sz_in, type );
+ cv::Scalar mean = cv::Scalar::all(127);
+ cv::Scalar stddev = cv::Scalar::all(40.f);
+
+ cv::randn(in_mat1, mean, stddev);
+
+ auto out_mat_sz = sz_out.area() == 0 ? cv::Size(saturate_cast<int>(sz_in.width *fx),
+ saturate_cast<int>(sz_in.height*fy))
+ : sz_out;
+ cv::Mat out_mat(out_mat_sz, type);
+ cv::Mat out_mat_ocv(out_mat_sz, type);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in;
+ auto out = cv::gapi::resize(in, sz_out, fx, fy, interp);
+
+ cv::GComputation c(in, out);
+ c.apply(in_mat1, out_mat, std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::resize(in_mat1, out_mat_ocv, sz_out, fx, fy, interp);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_TRUE(cmpF(out_mat, out_mat_ocv));
+ }
+}
+
+TEST_P(ResizeTest, AccuracyTest)
+{
+ compare_f cmpF;
+ int type = 0, interp = 0;
+ cv::Size sz_in, sz_out;
+ cv::GCompileArgs compile_args;
+ std::tie(cmpF, type, interp, sz_in, sz_out, compile_args) = GetParam();
+ ResizeAccuracyTest(cmpF, type, interp, sz_in, sz_out, 0.0, 0.0, std::move(compile_args));
+}
+
+TEST_P(ResizeTestFxFy, AccuracyTest)
+{
+ compare_f cmpF;
+ int type = 0, interp = 0;
+ cv::Size sz_in;
+ double fx = 0.0, fy = 0.0;
+ cv::GCompileArgs compile_args;
+ std::tie(cmpF, type, interp, sz_in, fx, fy, compile_args) = GetParam();
+ ResizeAccuracyTest(cmpF, type, interp, sz_in, cv::Size{0, 0}, fx, fy, std::move(compile_args));
+}
+
+TEST_P(Merge3Test, AccuracyTest)
+{
+ cv::Size sz_in = std::get<0>(GetParam());
+ initMatsRandU(CV_8UC1, sz_in, CV_8UC3);
+ auto compile_args = std::get<1>(GetParam());
+ cv::Mat in_mat3(sz_in, CV_8UC1);
+ cv::Scalar mean = cv::Scalar::all(127);
+ cv::Scalar stddev = cv::Scalar::all(40.f);
+
+ cv::randn(in_mat3, mean, stddev);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2, in3;
+ auto out = cv::gapi::merge3(in1, in2, in3);
+
+ cv::GComputation c(cv::GIn(in1, in2, in3), cv::GOut(out));
+ c.apply(cv::gin(in_mat1, in_mat2, in_mat3), cv::gout(out_mat_gapi), std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ std::vector<cv::Mat> in_mats_ocv = {in_mat1, in_mat2, in_mat3};
+ cv::merge(in_mats_ocv, out_mat_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ }
+}
+
+TEST_P(Merge4Test, AccuracyTest)
+{
+ cv::Size sz_in = std::get<0>(GetParam());
+ initMatsRandU(CV_8UC1, sz_in, CV_8UC4);
+ auto compile_args = std::get<1>(GetParam());
+ cv::Mat in_mat3(sz_in, CV_8UC1);
+ cv::Mat in_mat4(sz_in, CV_8UC1);
+ cv::Scalar mean = cv::Scalar::all(127);
+ cv::Scalar stddev = cv::Scalar::all(40.f);
+
+ cv::randn(in_mat3, mean, stddev);
+ cv::randn(in_mat4, mean, stddev);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2, in3, in4;
+ auto out = cv::gapi::merge4(in1, in2, in3, in4);
+
+ cv::GComputation c(cv::GIn(in1, in2, in3, in4), cv::GOut(out));
+ c.apply(cv::gin(in_mat1, in_mat2, in_mat3, in_mat4), cv::gout(out_mat_gapi), std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ std::vector<cv::Mat> in_mats_ocv = {in_mat1, in_mat2, in_mat3, in_mat4};
+ cv::merge(in_mats_ocv, out_mat_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ }
+}
+
+TEST_P(RemapTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ cv::Size sz_in = std::get<1>(param);
+ auto compile_args = std::get<3>(param);
+ initMatrixRandU(type, sz_in, type, std::get<2>(param));
+ cv::Mat in_map1(sz_in, CV_16SC2);
+ cv::Mat in_map2 = cv::Mat();
+ cv::randu(in_map1, cv::Scalar::all(0), cv::Scalar::all(255));
+ cv::Scalar bv = cv::Scalar();
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1;
+ auto out = cv::gapi::remap(in1, in_map1, in_map2, cv::INTER_NEAREST, cv::BORDER_REPLICATE, bv);
+ cv::GComputation c(in1, out);
+
+ c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::remap(in_mat1, out_mat_ocv, in_map1, in_map2, cv::INTER_NEAREST, cv::BORDER_REPLICATE, bv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(FlipTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ int flipCode = std::get<1>(param);
+ cv::Size sz_in = std::get<2>(param);
+ initMatrixRandU(type, sz_in, type, false);
+ auto compile_args = std::get<4>(GetParam());
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in;
+ auto out = cv::gapi::flip(in, flipCode);
+
+ cv::GComputation c(in, out);
+ c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::flip(in_mat1, out_mat_ocv, flipCode);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(CropTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ cv::Rect rect_to = std::get<1>(param);
+ cv::Size sz_in = std::get<2>(param);
+ auto compile_args = std::get<4>(param);
+
+ initMatrixRandU(type, sz_in, type, false);
+ cv::Size sz_out = cv::Size(rect_to.width, rect_to.height);
+ if( std::get<3>(param) == true )
+ {
+ out_mat_gapi = cv::Mat(sz_out, type);
+ out_mat_ocv = cv::Mat(sz_out, type);
+ }
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in;
+ auto out = cv::gapi::crop(in, rect_to);
+
+ cv::GComputation c(in, out);
+ c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::Mat(in_mat1, rect_to).copyTo(out_mat_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(out_mat_gapi.size(), sz_out);
+ }
+}
+
+TEST_P(ConcatHorTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ cv::Size sz_out = std::get<1>(param);
+ auto compile_args = std::get<2>(param);
+
+ int wpart = sz_out.width / 4;
+ cv::Size sz_in1 = cv::Size(wpart, sz_out.height);
+ cv::Size sz_in2 = cv::Size(sz_out.width - wpart, sz_out.height);
+
+ cv::Mat in_mat1 (sz_in1, type );
+ cv::Mat in_mat2 (sz_in2, type);
+ cv::Scalar mean = cv::Scalar::all(127);
+ cv::Scalar stddev = cv::Scalar::all(40.f);
+
+ cv::randn(in_mat1, mean, stddev);
+ cv::randn(in_mat2, mean, stddev);
+
+ cv::Mat out_mat(sz_out, type);
+ cv::Mat out_mat_ocv(sz_out, type);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2;
+ auto out = cv::gapi::concatHor(in1, in2);
+
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+ c.apply(gin(in_mat1, in_mat2), gout(out_mat), std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::hconcat(in_mat1, in_mat2, out_mat_ocv );
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat));
+ }
+}
+
+TEST_P(ConcatVertTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ cv::Size sz_out = std::get<1>(param);
+ auto compile_args = std::get<2>(param);
+
+ int hpart = sz_out.height * 2/3;
+ cv::Size sz_in1 = cv::Size(sz_out.width, hpart);
+ cv::Size sz_in2 = cv::Size(sz_out.width, sz_out.height - hpart);
+
+ cv::Mat in_mat1 (sz_in1, type);
+ cv::Mat in_mat2 (sz_in2, type);
+ cv::Scalar mean = cv::Scalar::all(127);
+ cv::Scalar stddev = cv::Scalar::all(40.f);
+
+ cv::randn(in_mat1, mean, stddev);
+ cv::randn(in_mat2, mean, stddev);
+
+ cv::Mat out_mat(sz_out, type);
+ cv::Mat out_mat_ocv(sz_out, type);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in1, in2;
+ auto out = cv::gapi::concatVert(in1, in2);
+
+ cv::GComputation c(GIn(in1, in2), GOut(out));
+ c.apply(gin(in_mat1, in_mat2), gout(out_mat), std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::vconcat(in_mat1, in_mat2, out_mat_ocv );
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat));
+ }
+}
+
+TEST_P(ConcatVertVecTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ cv::Size sz_out = std::get<1>(param);
+ auto compile_args = std::get<2>(param);
+
+ int hpart1 = sz_out.height * 2/5;
+ int hpart2 = sz_out.height / 5;
+ cv::Size sz_in1 = cv::Size(sz_out.width, hpart1);
+ cv::Size sz_in2 = cv::Size(sz_out.width, hpart2);
+ cv::Size sz_in3 = cv::Size(sz_out.width, sz_out.height - hpart1 - hpart2);
+
+ cv::Mat in_mat1 (sz_in1, type);
+ cv::Mat in_mat2 (sz_in2, type);
+ cv::Mat in_mat3 (sz_in3, type);
+ cv::Scalar mean = cv::Scalar::all(127);
+ cv::Scalar stddev = cv::Scalar::all(40.f);
+
+ cv::randn(in_mat1, mean, stddev);
+ cv::randn(in_mat2, mean, stddev);
+ cv::randn(in_mat3, mean, stddev);
+
+ cv::Mat out_mat(sz_out, type);
+ cv::Mat out_mat_ocv(sz_out, type);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ std::vector <cv::GMat> mats(3);
+ auto out = cv::gapi::concatVert(mats);
+
+ std::vector <cv::Mat> cvmats = {in_mat1, in_mat2, in_mat3};
+
+ cv::GComputation c({mats[0], mats[1], mats[2]}, {out});
+ c.apply(gin(in_mat1, in_mat2, in_mat3), gout(out_mat), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::vconcat(cvmats, out_mat_ocv );
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat));
+ }
+}
+
+TEST_P(ConcatHorVecTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type = std::get<0>(param);
+ cv::Size sz_out = std::get<1>(param);
+ auto compile_args = std::get<2>(param);
+
+ int wpart1 = sz_out.width / 3;
+ int wpart2 = sz_out.width / 4;
+ cv::Size sz_in1 = cv::Size(wpart1, sz_out.height);
+ cv::Size sz_in2 = cv::Size(wpart2, sz_out.height);
+ cv::Size sz_in3 = cv::Size(sz_out.width - wpart1 - wpart2, sz_out.height);
+
+ cv::Mat in_mat1 (sz_in1, type);
+ cv::Mat in_mat2 (sz_in2, type);
+ cv::Mat in_mat3 (sz_in3, type);
+ cv::Scalar mean = cv::Scalar::all(127);
+ cv::Scalar stddev = cv::Scalar::all(40.f);
+
+ cv::randn(in_mat1, mean, stddev);
+ cv::randn(in_mat2, mean, stddev);
+ cv::randn(in_mat3, mean, stddev);
+
+ cv::Mat out_mat(sz_out, type);
+ cv::Mat out_mat_ocv(sz_out, type);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ std::vector <cv::GMat> mats(3);
+ auto out = cv::gapi::concatHor(mats);
+
+ std::vector <cv::Mat> cvmats = {in_mat1, in_mat2, in_mat3};
+
+ cv::GComputation c({mats[0], mats[1], mats[2]}, {out});
+ c.apply(gin(in_mat1, in_mat2, in_mat3), gout(out_mat), std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::hconcat(cvmats, out_mat_ocv );
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat));
+ }
+}
+
+TEST_P(LUTTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type_mat = std::get<0>(param);
+ int type_lut = std::get<1>(param);
+ int type_out = CV_MAKETYPE(CV_MAT_DEPTH(type_lut), CV_MAT_CN(type_mat));
+ cv::Size sz_in = std::get<2>(param);
+ auto compile_args = std::get<4>(GetParam());
+
+ initMatrixRandU(type_mat, sz_in, type_out);
+ cv::Size sz_lut = cv::Size(1, 256);
+ cv::Mat in_lut(sz_lut, type_lut);
+ cv::randu(in_lut, cv::Scalar::all(0), cv::Scalar::all(255));
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in;
+ auto out = cv::gapi::LUT(in, in_lut);
+
+ cv::GComputation c(in, out);
+ c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ cv::LUT(in_mat1, in_lut, out_mat_ocv);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(ConvertToTest, AccuracyTest)
+{
+ auto param = GetParam();
+ int type_mat = std::get<0>(param);
+ int depth_to = std::get<1>(param);
+ cv::Size sz_in = std::get<2>(param);
+ int type_out = CV_MAKETYPE(depth_to, CV_MAT_CN(type_mat));
+ initMatrixRandU(type_mat, sz_in, type_out);
+ auto compile_args = std::get<3>(GetParam());
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in;
+ auto out = cv::gapi::convertTo(in, depth_to);
+
+ cv::GComputation c(in, out);
+ c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
+ // OpenCV code /////////////////////////////////////////////////////////////
+ {
+ in_mat1.convertTo(out_mat_ocv, depth_to);
+ }
+ // Comparison //////////////////////////////////////////////////////////////
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ EXPECT_EQ(out_mat_gapi.size(), sz_in);
+ }
+}
+
+TEST_P(PhaseTest, AccuracyTest)
+{
+ int img_type = -1;
+ cv::Size img_size;
+ bool angle_in_degrees = false;
+ cv::GCompileArgs compile_args;
+ std::tie(img_type, img_size, angle_in_degrees, compile_args) = GetParam();
+ initMatsRandU(img_type, img_size, img_type);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in_x, in_y;
+ auto out = cv::gapi::phase(in_x, in_y, angle_in_degrees);
+
+ cv::GComputation c(in_x, in_y, out);
+ c.apply(in_mat1, in_mat2, out_mat_gapi, std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ cv::phase(in_mat1, in_mat2, out_mat_ocv, angle_in_degrees);
+
+ // Comparison //////////////////////////////////////////////////////////////
+ // FIXME: use a comparison functor instead (after enabling OpenCL)
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ }
+}
+
+TEST_P(SqrtTest, AccuracyTest)
+{
+ int img_type = -1;
+ cv::Size img_size;
+ cv::GCompileArgs compile_args;
+ std::tie(img_type, img_size, compile_args) = GetParam();
+ initMatrixRandU(img_type, img_size, img_type);
+
+ // G-API code //////////////////////////////////////////////////////////////
+ cv::GMat in;
+ auto out = cv::gapi::sqrt(in);
+
+ cv::GComputation c(in, out);
+ c.apply(in_mat1, out_mat_gapi, std::move(compile_args));
+
+ // OpenCV code /////////////////////////////////////////////////////////////
+ cv::sqrt(in_mat1, out_mat_ocv);
+
+ // Comparison //////////////////////////////////////////////////////////////
+ // FIXME: use a comparison functor instead (after enabling OpenCL)
+ {
+ EXPECT_EQ(0, cv::countNonZero(out_mat_ocv != out_mat_gapi));
+ }
+}
+
+
+} // opencv_test
+
+#endif //OPENCV_GAPI_CORE_TESTS_INL_HPP
generated by cgit v1.2.3 (git 2.25.1) at 2024-06-26 02:34:46 +0000