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) 2020 Intel Corporation
#include "../test_precomp.hpp"
#include <ade/util/iota_range.hpp>
#include <opencv2/gapi/s11n.hpp>
namespace opencv_test
{
TEST(S11N, Pipeline_Crop_Rect)
{
cv::Rect rect_to{ 4,10,37,50 };
cv::Size sz_in = cv::Size(1920, 1080);
cv::Size sz_out = cv::Size(37, 50);
cv::Mat in_mat = cv::Mat::eye(sz_in, CV_8UC1);
cv::Mat out_mat_gapi(sz_out, CV_8UC1);
cv::Mat out_mat_ocv(sz_out, CV_8UC1);
// G-API code //////////////////////////////////////////////////////////////
cv::GMat in;
auto out = cv::gapi::crop(in, rect_to);
auto p = cv::gapi::serialize(cv::GComputation(in, out));
auto c = cv::gapi::deserialize<cv::GComputation>(p);
c.apply(in_mat, out_mat_gapi);
// OpenCV code /////////////////////////////////////////////////////////////
{
out_mat_ocv = in_mat(rect_to);
}
// Comparison //////////////////////////////////////////////////////////////
{
EXPECT_EQ(0, cvtest::norm(out_mat_ocv, out_mat_gapi, NORM_INF));
}
}
TEST(S11N, Pipeline_Canny_Bool)
{
const cv::Size sz_in(1280, 720);
cv::GMat in;
double thrLow = 120.0;
double thrUp = 240.0;
int apSize = 5;
bool l2gr = true;
cv::Mat in_mat = cv::Mat::eye(1280, 720, CV_8UC1);
cv::Mat out_mat_gapi(sz_in, CV_8UC1);
cv::Mat out_mat_ocv(sz_in, CV_8UC1);
// G-API code //////////////////////////////////////////////////////////////
auto out = cv::gapi::Canny(in, thrLow, thrUp, apSize, l2gr);
auto p = cv::gapi::serialize(cv::GComputation(in, out));
auto c = cv::gapi::deserialize<cv::GComputation>(p);
c.apply(in_mat, out_mat_gapi);
// OpenCV code /////////////////////////////////////////////////////////////
{
cv::Canny(in_mat, out_mat_ocv, thrLow, thrUp, apSize, l2gr);
}
// Comparison //////////////////////////////////////////////////////////////
EXPECT_EQ(0, cvtest::norm(out_mat_gapi, out_mat_ocv, NORM_INF));
}
TEST(S11N, Pipeline_Not)
{
cv::GMat in;
auto p = cv::gapi::serialize(cv::GComputation(in, cv::gapi::bitwise_not(in)));
auto c = cv::gapi::deserialize<cv::GComputation>(p);
cv::Mat in_mat = cv::Mat::eye(32, 32, CV_8UC1);
cv::Mat ref_mat = ~in_mat;
cv::Mat out_mat;
c.apply(in_mat, out_mat);
EXPECT_EQ(0, cvtest::norm(out_mat, ref_mat, NORM_INF));
out_mat = cv::Mat();
auto cc = c.compile(cv::descr_of(in_mat));
cc(in_mat, out_mat);
EXPECT_EQ(0, cvtest::norm(out_mat, ref_mat, NORM_INF));
}
TEST(S11N, Pipeline_Sum_Scalar)
{
cv::GMat in;
auto p = cv::gapi::serialize(cv::GComputation(in, cv::gapi::sum(in)));
auto c = cv::gapi::deserialize<cv::GComputation>(p);
cv::Mat in_mat = cv::Mat::eye(32, 32, CV_8UC1);
cv::Scalar ref_scl = cv::sum(in_mat);
cv::Scalar out_scl;
c.apply(in_mat, out_scl);
EXPECT_EQ(out_scl, ref_scl);
out_scl = cv::Scalar();
auto cc = c.compile(cv::descr_of(in_mat));
cc(in_mat, out_scl);
EXPECT_EQ(out_scl, ref_scl);
}
TEST(S11N, Pipeline_BinaryOp)
{
cv::GMat a, b;
auto p = cv::gapi::serialize(cv::GComputation(a, b, cv::gapi::add(a, b)));
auto c = cv::gapi::deserialize<cv::GComputation>(p);
cv::Mat in_mat = cv::Mat::eye(32, 32, CV_8UC1);
cv::Mat ref_mat = (in_mat + in_mat);
cv::Mat out_mat;
c.apply(in_mat, in_mat, out_mat);
EXPECT_EQ(0, cvtest::norm(out_mat, ref_mat, NORM_INF));
out_mat = cv::Mat();
auto cc = c.compile(cv::descr_of(in_mat), cv::descr_of(in_mat));
cc(in_mat, in_mat, out_mat);
EXPECT_EQ(0, cvtest::norm(out_mat, ref_mat, NORM_INF));
}
TEST(S11N, Pipeline_Binary_Sum_Scalar)
{
cv::GMat a, b;
auto p = cv::gapi::serialize(cv::GComputation(a, b, cv::gapi::sum(a + b)));
auto c = cv::gapi::deserialize<cv::GComputation>(p);
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;
c.apply(in_mat, in_mat, out_scl);
EXPECT_EQ(out_scl, ref_scl);
out_scl = cv::Scalar();
auto cc = c.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(S11N, 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);
auto p = cv::gapi::serialize(cv::GComputation(cv::GIn(in), cv::GOut(y_sharp, out)));
auto c = cv::gapi::deserialize<cv::GComputation>(p);
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, cvtest::norm(diffBGR[0], NORM_INF));
EXPECT_EQ(0, cvtest::norm(diffBGR[1], NORM_INF));
EXPECT_EQ(0, cvtest::norm(diffBGR[2], NORM_INF));
}
// 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(S11N, Pipeline_CustomRGB2YUV)
{
const cv::Size sz(1280, 720);
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);
auto p = cv::gapi::serialize(cv::GComputation({r, g, b}, {y, u, v}));
auto c = cv::gapi::deserialize<cv::GComputation>(p);
c.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, cvtest::norm(diff_y, NORM_INF));
EXPECT_EQ(0, cvtest::norm(diff_u, NORM_INF));
EXPECT_EQ(0, cvtest::norm(diff_v, NORM_INF));
}
}
} // namespace opencv_test