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 "test_precomp.hpp"
#include <stdexcept>
#include <ade/util/iota_range.hpp>
#include "logger.hpp"
namespace opencv_test
{
namespace
{
G_TYPED_KERNEL(GInvalidResize, <GMat(GMat,Size,double,double,int)>, "org.opencv.test.invalid_resize")
{
static GMatDesc outMeta(GMatDesc in, Size, double, double, int) { return in; }
};
GAPI_OCV_KERNEL(GOCVInvalidResize, GInvalidResize)
{
static void run(const cv::Mat& in, cv::Size sz, double fx, double fy, int interp, cv::Mat &out)
{
cv::resize(in, out, sz, fx, fy, interp);
}
};
G_TYPED_KERNEL(GReallocatingCopy, <GMat(GMat)>, "org.opencv.test.reallocating_copy")
{
static GMatDesc outMeta(GMatDesc in) { return in; }
};
GAPI_OCV_KERNEL(GOCVReallocatingCopy, GReallocatingCopy)
{
static void run(const cv::Mat& in, cv::Mat &out)
{
out = in.clone();
}
};
// These definitons test the correct macro work if the kernel has multiple output values
G_TYPED_KERNEL(GRetGArrayTupleOfGMat2Kernel, <GArray<std::tuple<GMat, GMat>>(GMat, Scalar)>, "org.opencv.test.retarrayoftupleofgmat2kernel") {};
G_TYPED_KERNEL(GRetGArraTupleyOfGMat3Kernel, <GArray<std::tuple<GMat, GMat, GMat>>(GMat)>, "org.opencv.test.retarrayoftupleofgmat3kernel") {};
G_TYPED_KERNEL(GRetGArraTupleyOfGMat4Kernel, <GArray<std::tuple<GMat, GMat, GMat, GMat>>(GMat)>, "org.opencv.test.retarrayoftupleofgmat4kernel") {};
G_TYPED_KERNEL(GRetGArraTupleyOfGMat5Kernel, <GArray<std::tuple<GMat, GMat, GMat, GMat, GMat>>(GMat)>, "org.opencv.test.retarrayoftupleofgmat5kernel") {};
G_TYPED_KERNEL(GRetGArraTupleyOfGMat6Kernel, <GArray<std::tuple<GMat, GMat, GMat, GMat, GMat, GMat>>(GMat)>, "org.opencv.test.retarrayoftupleofgmat6kernel") {};
G_TYPED_KERNEL(GRetGArraTupleyOfGMat7Kernel, <GArray<std::tuple<GMat, GMat, GMat, GMat, GMat, GMat, GMat>>(GMat)>, "org.opencv.test.retarrayoftupleofgmat7kernel") {};
G_TYPED_KERNEL(GRetGArraTupleyOfGMat8Kernel, <GArray<std::tuple<GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat>>(GMat)>, "org.opencv.test.retarrayoftupleofgmat8kernel") {};
G_TYPED_KERNEL(GRetGArraTupleyOfGMat9Kernel, <GArray<std::tuple<GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat>>(GMat)>, "org.opencv.test.retarrayoftupleofgmat9kernel") {};
G_TYPED_KERNEL(GRetGArraTupleyOfGMat10Kernel, <GArray<std::tuple<GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat>>(GMat)>, "org.opencv.test.retarrayoftupleofgmat10kernel") {};
G_TYPED_KERNEL_M(GRetGMat2Kernel, <std::tuple<GMat, GMat>(GMat, GMat, GMat)>, "org.opencv.test.retgmat2kernel") {};
G_TYPED_KERNEL_M(GRetGMat3Kernel, <std::tuple<GMat, GMat, GMat>(GMat, GScalar)>, "org.opencv.test.retgmat3kernel") {};
G_TYPED_KERNEL_M(GRetGMat4Kernel, <std::tuple<GMat, GMat, GMat, GMat>(GMat, GArray<int>, GScalar)>, "org.opencv.test.retgmat4kernel") {};
G_TYPED_KERNEL_M(GRetGMat5Kernel, <std::tuple<GMat, GMat, GMat, GMat, GMat>(GMat)>, "org.opencv.test.retgmat5kernel") {};
G_TYPED_KERNEL_M(GRetGMat6Kernel, <std::tuple<GMat, GMat, GMat, GMat, GMat, GMat>(GMat)>, "org.opencv.test.retgmat6kernel") {};
G_TYPED_KERNEL_M(GRetGMat7Kernel, <std::tuple<GMat, GMat, GMat, GMat, GMat, GMat, GMat>(GMat)>, "org.opencv.test.retgmat7kernel") {};
G_TYPED_KERNEL_M(GRetGMat8Kernel, <std::tuple<GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat>(GMat)>, "org.opencv.test.retgmat8kernel") {};
G_TYPED_KERNEL_M(GRetGMat9Kernel, <std::tuple<GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat>(GMat)>, "org.opencv.test.retgmat9kernel") {};
G_TYPED_KERNEL_M(GRetGMat10Kernel, <std::tuple<GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat, GMat>(GMat)>, "org.opencv.test.retgmat10kernel") {};
}
TEST(GAPI_Pipeline, OverloadUnary_MatMat)
{
cv::GMat in;
cv::GComputation comp(in, cv::gapi::bitwise_not(in));
cv::Mat in_mat = cv::Mat::eye(32, 32, CV_8UC1);
cv::Mat ref_mat = ~in_mat;
cv::Mat out_mat;
comp.apply(in_mat, out_mat);
EXPECT_EQ(0, cv::countNonZero(out_mat != ref_mat));
out_mat = cv::Mat();
auto cc = comp.compile(cv::descr_of(in_mat));
cc(in_mat, out_mat);
EXPECT_EQ(0, cv::countNonZero(out_mat != ref_mat));
}
TEST(GAPI_Pipeline, OverloadUnary_MatScalar)
{
cv::GMat in;
cv::GComputation comp(in, cv::gapi::sum(in));
cv::Mat in_mat = cv::Mat::eye(32, 32, CV_8UC1);
cv::Scalar ref_scl = cv::sum(in_mat);
cv::Scalar out_scl;
comp.apply(in_mat, out_scl);
EXPECT_EQ(out_scl, ref_scl);
out_scl = cv::Scalar();
auto cc = comp.compile(cv::descr_of(in_mat));
cc(in_mat, out_scl);
EXPECT_EQ(out_scl, ref_scl);
}
TEST(GAPI_Pipeline, OverloadBinary_Mat)
{
cv::GMat a, b;
cv::GComputation comp(a, b, cv::gapi::add(a, b));
cv::Mat in_mat = cv::Mat::eye(32, 32, CV_8UC1);
cv::Mat ref_mat = (in_mat+in_mat);
cv::Mat out_mat;
comp.apply(in_mat, in_mat, out_mat);
EXPECT_EQ(0, cv::countNonZero(out_mat != ref_mat));
out_mat = cv::Mat();
auto cc = comp.compile(cv::descr_of(in_mat), cv::descr_of(in_mat));
cc(in_mat, in_mat, out_mat);
EXPECT_EQ(0, cv::countNonZero(out_mat != ref_mat));
}
TEST(GAPI_Pipeline, OverloadBinary_Scalar)
{
cv::GMat a, b;
cv::GComputation comp(a, b, cv::gapi::sum(a + b));
cv::Mat in_mat = cv::Mat::eye(32, 32, CV_8UC1);
cv::Scalar ref_scl = cv::sum(in_mat+in_mat);
cv::Scalar out_scl;
comp.apply(in_mat, in_mat, out_scl);
EXPECT_EQ(out_scl, ref_scl);
out_scl = cv::Scalar();
auto cc = comp.compile(cv::descr_of(in_mat), cv::descr_of(in_mat));
cc(in_mat, in_mat, out_scl);
EXPECT_EQ(out_scl, ref_scl);
}
TEST(GAPI_Pipeline, Sharpen)
{
const cv::Size sz_in (1280, 720);
const cv::Size sz_out( 640, 480);
cv::Mat in_mat (sz_in, CV_8UC3);
in_mat = cv::Scalar(128, 33, 53);
cv::Mat out_mat(sz_out, CV_8UC3);
cv::Mat out_mat_y;
cv::Mat out_mat_ocv(sz_out, CV_8UC3);
float sharpen_coeffs[] = {
0.0f, -1.f, 0.0f,
-1.0f, 5.f, -1.0f,
0.0f, -1.f, 0.0f
};
cv::Mat sharpen_kernel(3, 3, CV_32F, sharpen_coeffs);
// G-API code //////////////////////////////////////////////////////////////
cv::GMat in;
auto vga = cv::gapi::resize(in, sz_out);
auto yuv = cv::gapi::RGB2YUV(vga);
auto yuv_p = cv::gapi::split3(yuv);
auto y_sharp = cv::gapi::filter2D(std::get<0>(yuv_p), -1, sharpen_kernel);
auto yuv_new = cv::gapi::merge3(y_sharp, std::get<1>(yuv_p), std::get<2>(yuv_p));
auto out = cv::gapi::YUV2RGB(yuv_new);
cv::GComputation c(cv::GIn(in), cv::GOut(y_sharp, out));
c.apply(cv::gin(in_mat), cv::gout(out_mat_y, out_mat));
// OpenCV code /////////////////////////////////////////////////////////////
{
cv::Mat smaller;
cv::resize(in_mat, smaller, sz_out);
cv::Mat yuv_mat;
cv::cvtColor(smaller, yuv_mat, cv::COLOR_RGB2YUV);
std::vector<cv::Mat> yuv_planar(3);
cv::split(yuv_mat, yuv_planar);
cv::filter2D(yuv_planar[0], yuv_planar[0], -1, sharpen_kernel);
cv::merge(yuv_planar, yuv_mat);
cv::cvtColor(yuv_mat, out_mat_ocv, cv::COLOR_YUV2RGB);
}
// Comparison //////////////////////////////////////////////////////////////
{
cv::Mat diff = out_mat_ocv != out_mat;
std::vector<cv::Mat> diffBGR(3);
cv::split(diff, diffBGR);
EXPECT_EQ(0, cv::countNonZero(diffBGR[0]));
EXPECT_EQ(0, cv::countNonZero(diffBGR[1]));
EXPECT_EQ(0, cv::countNonZero(diffBGR[2]));
}
// Metadata check /////////////////////////////////////////////////////////
{
auto cc = c.compile(cv::descr_of(in_mat));
auto metas = cc.outMetas();
ASSERT_EQ(2u, metas.size());
auto out_y_meta = cv::util::get<cv::GMatDesc>(metas[0]);
auto out_meta = cv::util::get<cv::GMatDesc>(metas[1]);
// Y-output
EXPECT_EQ(CV_8U, out_y_meta.depth);
EXPECT_EQ(1, out_y_meta.chan);
EXPECT_EQ(640, out_y_meta.size.width);
EXPECT_EQ(480, out_y_meta.size.height);
// Final output
EXPECT_EQ(CV_8U, out_meta.depth);
EXPECT_EQ(3, out_meta.chan);
EXPECT_EQ(640, out_meta.size.width);
EXPECT_EQ(480, out_meta.size.height);
}
}
TEST(GAPI_Pipeline, CustomRGB2YUV)
{
const cv::Size sz(1280, 720);
// BEWARE:
//
// std::vector<cv::Mat> out_mats_cv(3, cv::Mat(sz, CV_8U))
//
// creates a vector of 3 elements pointing to the same Mat!
// FIXME: Make a G-API check for that
const int INS = 3;
std::vector<cv::Mat> in_mats(INS);
for (auto i : ade::util::iota(INS))
{
in_mats[i].create(sz, CV_8U);
cv::randu(in_mats[i], cv::Scalar::all(0), cv::Scalar::all(255));
}
const int OUTS = 3;
std::vector<cv::Mat> out_mats_cv(OUTS);
std::vector<cv::Mat> out_mats_gapi(OUTS);
for (auto i : ade::util::iota(OUTS))
{
out_mats_cv [i].create(sz, CV_8U);
out_mats_gapi[i].create(sz, CV_8U);
}
// G-API code //////////////////////////////////////////////////////////////
{
cv::GMat r, g, b;
cv::GMat y = 0.299f*r + 0.587f*g + 0.114f*b;
cv::GMat u = 0.492f*(b - y);
cv::GMat v = 0.877f*(r - y);
cv::GComputation customCvt({r, g, b}, {y, u, v});
customCvt.apply(in_mats, out_mats_gapi);
}
// OpenCV code /////////////////////////////////////////////////////////////
{
cv::Mat r = in_mats[0], g = in_mats[1], b = in_mats[2];
cv::Mat y = 0.299f*r + 0.587f*g + 0.114f*b;
cv::Mat u = 0.492f*(b - y);
cv::Mat v = 0.877f*(r - y);
out_mats_cv[0] = y;
out_mats_cv[1] = u;
out_mats_cv[2] = v;
}
// Comparison //////////////////////////////////////////////////////////////
{
const auto diff = [](cv::Mat m1, cv::Mat m2, int t) {
return cv::abs(m1-m2) > t;
};
// FIXME: Not bit-accurate even now!
cv::Mat
diff_y = diff(out_mats_cv[0], out_mats_gapi[0], 2),
diff_u = diff(out_mats_cv[1], out_mats_gapi[1], 2),
diff_v = diff(out_mats_cv[2], out_mats_gapi[2], 2);
EXPECT_EQ(0, cv::countNonZero(diff_y));
EXPECT_EQ(0, cv::countNonZero(diff_u));
EXPECT_EQ(0, cv::countNonZero(diff_v));
}
}
TEST(GAPI_Pipeline, PipelineWithInvalidKernel)
{
cv::GMat in, out;
cv::Mat in_mat(500, 500, CV_8UC1), out_mat;
out = GInvalidResize::on(in, cv::Size(300, 300), 0.0, 0.0, cv::INTER_LINEAR);
const auto pkg = cv::gapi::kernels<GOCVInvalidResize>();
cv::GComputation comp(cv::GIn(in), cv::GOut(out));
EXPECT_THROW(comp.apply(in_mat, out_mat, cv::compile_args(pkg)), std::logic_error);
}
TEST(GAPI_Pipeline, InvalidOutputComputation)
{
cv::GMat in1, out1, out2, out3;
std::tie(out1, out2, out2) = cv::gapi::split3(in1);
cv::GComputation c({in1}, {out1, out2, out3});
cv::Mat in_mat;
cv::Mat out_mat1, out_mat2, out_mat3, out_mat4;
std::vector<cv::Mat> u_outs = {out_mat1, out_mat2, out_mat3, out_mat4};
std::vector<cv::Mat> u_ins = {in_mat};
EXPECT_THROW(c.apply(u_ins, u_outs), std::logic_error);
}
TEST(GAPI_Pipeline, PipelineAllocatingKernel)
{
cv::GMat in, out;
cv::Mat in_mat(500, 500, CV_8UC1), out_mat;
out = GReallocatingCopy::on(in);
const auto pkg = cv::gapi::kernels<GOCVReallocatingCopy>();
cv::GComputation comp(cv::GIn(in), cv::GOut(out));
EXPECT_THROW(comp.apply(in_mat, out_mat, cv::compile_args(pkg)), std::logic_error);
}
TEST(GAPI_Pipeline, CanUseOwnMatAsOutput)
{
cv::GMat in;
cv::GComputation comp(in, cv::gapi::bitwise_not(in));
cv::Mat in_mat(3, 3, CV_8UC1);
cv::Mat out_mat(3, 3, CV_8UC1);
cv::gapi::own::Mat in_own_mat(in_mat.rows, in_mat.cols, CV_8UC1, in_mat.data);
cv::gapi::own::Mat out_own_mat(out_mat.rows, out_mat.cols, CV_8UC1, out_mat.data);
// FIXME add overload for apply(cv::gapi::own::Mat in, cv::gapi::own::Mat& out)
EXPECT_NO_THROW(comp.apply({in_own_mat}, {out_own_mat}));
}
} // namespace opencv_test