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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 "gapi_fluid_test_kernels.hpp"
namespace opencv_test
{
using namespace cv::gapi_test_kernels;
G_TYPED_KERNEL(TCopy, <GMat(GMat)>, "test.fluid.copy")
{
static GMatDesc outMeta(const cv::GMatDesc &in) {
return in;
}
};
GAPI_FLUID_KERNEL(FCopy, TCopy, false)
{
static const int Window = 1;
static void run(const cv::gapi::fluid::View &in,
cv::gapi::fluid::Buffer &out)
{
const uint8_t* in_row = in .InLine <uint8_t>(0);
uint8_t* out_row = out.OutLine<uint8_t>();
for (int i = 0, w = in.length(); i < w; i++)
{
//std::cout << std::setw(4) << int(in_row[i]);
out_row[i] = in_row[i];
}
//std::cout << std::endl;
}
};
GAPI_FLUID_KERNEL(FResizeNN1Lpi, cv::gapi::core::GResize, false)
{
static const int Window = 1;
static const auto Kind = GFluidKernel::Kind::Resize;
static void run(const cv::gapi::fluid::View& in, cv::Size /*sz*/, double /*fx*/, double /*fy*/, int /*interp*/,
cv::gapi::fluid::Buffer& out)
{
auto length = out.length();
double vRatio = (double)in.meta().size.height / out.meta().size.height;
double hRatio = (double)in.length() / length;
auto y = out.y();
auto inY = in.y();
for (int l = 0; l < out.lpi(); l++)
{
auto sy = static_cast<int>((y+l) * vRatio);
int idx = sy - inY;
const auto src = in.InLine <unsigned char>(idx);
auto dst = out.OutLine<unsigned char>(l);
for (int x = 0; x < length; x++)
{
auto inX = static_cast<int>(x * hRatio);
dst[x] = src[inX];
}
}
}
};
namespace
{
namespace func
{
template <class Mapper>
void initScratch(const cv::GMatDesc& in, cv::Size outSz, cv::gapi::fluid::Buffer &scratch)
{
CV_Assert(in.depth == CV_8U && in.chan == 1);
cv::Size scratch_size{static_cast<int>(outSz.width * sizeof(typename Mapper::Unit)), 1};
cv::GMatDesc desc;
desc.chan = 1;
desc.depth = CV_8UC1;
desc.size = scratch_size;
cv::gapi::fluid::Buffer buffer(desc);
scratch = std::move(buffer);
auto mapX = scratch.OutLine<typename Mapper::Unit>();
double hRatio = (double)in.size.width / outSz.width;
for (int x = 0, w = outSz.width; x < w; x++)
{
mapX[x] = Mapper::map(hRatio, 0, in.size.width, x);
}
}
template <class Mapper>
inline void calcRow(const cv::gapi::fluid::View& in, cv::gapi::fluid::Buffer& out, cv::gapi::fluid::Buffer &scratch)
{
double vRatio = (double)in.meta().size.height / out.meta().size.height;
auto mapX = scratch.OutLine<typename Mapper::Unit>();
auto inY = in.y();
auto inH = in.meta().size.height;
auto outY = out.y();
auto length = out.length();
for (int l = 0; l < out.lpi(); l++)
{
auto mapY = Mapper::map(vRatio, inY, inH, outY + l);
const auto src0 = in.InLine <unsigned char>(mapY.s0);
const auto src1 = in.InLine <unsigned char>(mapY.s1);
auto dst = out.OutLine<unsigned char>(l);
for (int x = 0; x < length; x++)
{
auto alpha0 = mapX[x].alpha0;
auto alpha1 = mapX[x].alpha1;
auto sx0 = mapX[x].s0;
auto sx1 = mapX[x].s1;
int res0 = src0[sx0]*alpha0 + src0[sx1]*alpha1;
int res1 = src1[sx0]*alpha0 + src1[sx1]*alpha1;
dst[x] = uchar(( ((mapY.alpha0 * (res0 >> 4)) >> 16) + ((mapY.alpha1 * (res1 >> 4)) >> 16) + 2)>>2);
}
}
}
} // namespace func
constexpr static const int INTER_RESIZE_COEF_BITS = 11;
constexpr static const int INTER_RESIZE_COEF_SCALE = 1 << INTER_RESIZE_COEF_BITS;
namespace linear
{
struct Mapper
{
struct Unit
{
short alpha0;
short alpha1;
int s0;
int s1;
};
static inline Unit map(double ratio, int start, int max, int outCoord)
{
auto f = static_cast<float>((outCoord + 0.5f) * ratio - 0.5f);
int s = cvFloor(f);
f -= s;
Unit u;
u.s0 = std::max(s - start, 0);
u.s1 = ((f == 0.0) || s + 1 >= max) ? s - start : s - start + 1;
u.alpha0 = saturate_cast<short>((1.0f - f) * INTER_RESIZE_COEF_SCALE);
u.alpha1 = saturate_cast<short>((f) * INTER_RESIZE_COEF_SCALE);
return u;
}
};
} // namespace linear
namespace areaUpscale
{
struct Mapper
{
struct Unit
{
short alpha0;
short alpha1;
int s0;
int s1;
};
static inline Unit map(double ratio, int start, int max, int outCoord)
{
int s = cvFloor(outCoord*ratio);
float f = (float)((outCoord+1) - (s+1)/ratio);
f = f <= 0 ? 0.f : f - cvFloor(f);
Unit u;
u.s0 = std::max(s - start, 0);
u.s1 = ((f == 0.0) || s + 1 >= max) ? s - start : s - start + 1;
u.alpha0 = saturate_cast<short>((1.0f - f) * INTER_RESIZE_COEF_SCALE);
u.alpha1 = saturate_cast<short>((f) * INTER_RESIZE_COEF_SCALE);
return u;
}
};
} // namespace areaUpscale
} // anonymous namespace
GAPI_FLUID_KERNEL(FResizeLinear1Lpi, cv::gapi::core::GResize, true)
{
static const int Window = 1;
static const auto Kind = GFluidKernel::Kind::Resize;
static void initScratch(const cv::GMatDesc& in,
cv::Size outSz, double /*fx*/, double /*fy*/, int /*interp*/,
cv::gapi::fluid::Buffer &scratch)
{
func::initScratch<linear::Mapper>(in, outSz, scratch);
}
static void resetScratch(cv::gapi::fluid::Buffer& /*scratch*/)
{}
static void run(const cv::gapi::fluid::View& in, cv::Size /*sz*/, double /*fx*/, double /*fy*/, int /*interp*/,
cv::gapi::fluid::Buffer& out, cv::gapi::fluid::Buffer &scratch)
{
func::calcRow<linear::Mapper>(in, out, scratch);
}
};
namespace
{
// FIXME
// Move to some common place (to reuse/align with ResizeAgent)
auto startInCoord = [](int outCoord, double ratio) {
return static_cast<int>(outCoord * ratio + 1e-3);
};
auto endInCoord = [](int outCoord, double ratio) {
return static_cast<int>(std::ceil((outCoord + 1) * ratio - 1e-3));
};
} // namespace
GAPI_FLUID_KERNEL(FResizeArea1Lpi, cv::gapi::core::GResize, false)
{
static const int Window = 1;
static const auto Kind = GFluidKernel::Kind::Resize;
static void run(const cv::gapi::fluid::View& in, cv::Size /*sz*/, double /*fx*/, double /*fy*/, int /*interp*/,
cv::gapi::fluid::Buffer& out)
{
auto firstOutLineIdx = out.y();
auto firstViewLineIdx = in.y();
auto length = out.length();
double vRatio = (double)in.meta().size.height / out.meta().size.height;
double hRatio = (double)in.length() / length;
for (int l = 0; l < out.lpi(); l++)
{
int outY = firstOutLineIdx + l;
int startY = startInCoord(outY, vRatio);
int endY = endInCoord (outY, vRatio);
auto dst = out.OutLine<unsigned char>(l);
for (int x = 0; x < length; x++)
{
float res = 0.0;
int startX = startInCoord(x, hRatio);
int endX = endInCoord (x, hRatio);
for (int inY = startY; inY < endY; inY++)
{
double startCoordY = inY / vRatio;
double endCoordY = startCoordY + 1/vRatio;
if (startCoordY < outY) startCoordY = outY;
if (endCoordY > outY + 1) endCoordY = outY + 1;
float fracY = static_cast<float>((inY == startY || inY == endY - 1) ? endCoordY - startCoordY : 1/vRatio);
const auto src = in.InLine <unsigned char>(inY - firstViewLineIdx);
float rowSum = 0.0f;
for (int inX = startX; inX < endX; inX++)
{
double startCoordX = inX / hRatio;
double endCoordX = startCoordX + 1/hRatio;
if (startCoordX < x) startCoordX = x;
if (endCoordX > x + 1) endCoordX = x + 1;
float fracX = static_cast<float>((inX == startX || inX == endX - 1) ? endCoordX - startCoordX : 1/hRatio);
rowSum += src[inX] * fracX;
}
res += rowSum * fracY;
}
dst[x] = static_cast<unsigned char>(std::rint(res));
}
}
}
};
GAPI_FLUID_KERNEL(FResizeAreaUpscale1Lpi, cv::gapi::core::GResize, true)
{
static const int Window = 1;
static const auto Kind = GFluidKernel::Kind::Resize;
static void initScratch(const cv::GMatDesc& in,
cv::Size outSz, double /*fx*/, double /*fy*/, int /*interp*/,
cv::gapi::fluid::Buffer &scratch)
{
func::initScratch<areaUpscale::Mapper>(in, outSz, scratch);
}
static void resetScratch(cv::gapi::fluid::Buffer& /*scratch*/)
{}
static void run(const cv::gapi::fluid::View& in, cv::Size /*sz*/, double /*fx*/, double /*fy*/, int /*interp*/,
cv::gapi::fluid::Buffer& out, cv::gapi::fluid::Buffer &scratch)
{
func::calcRow<areaUpscale::Mapper>(in, out, scratch);
}
};
#define ADD_RESIZE_KERNEL_WITH_LPI(interp, lpi, scratch) \
struct Resize##interp##lpi##LpiHelper : public FResize##interp##1Lpi { static const int LPI = lpi; }; \
struct FResize##interp##lpi##Lpi : public cv::GFluidKernelImpl<Resize##interp##lpi##LpiHelper, cv::gapi::core::GResize, scratch>{};
ADD_RESIZE_KERNEL_WITH_LPI(NN, 2, false)
ADD_RESIZE_KERNEL_WITH_LPI(NN, 3, false)
ADD_RESIZE_KERNEL_WITH_LPI(NN, 4, false)
ADD_RESIZE_KERNEL_WITH_LPI(Linear, 2, true)
ADD_RESIZE_KERNEL_WITH_LPI(Linear, 3, true)
ADD_RESIZE_KERNEL_WITH_LPI(Linear, 4, true)
ADD_RESIZE_KERNEL_WITH_LPI(Area, 2, false)
ADD_RESIZE_KERNEL_WITH_LPI(Area, 3, false)
ADD_RESIZE_KERNEL_WITH_LPI(Area, 4, false)
ADD_RESIZE_KERNEL_WITH_LPI(AreaUpscale, 2, true)
ADD_RESIZE_KERNEL_WITH_LPI(AreaUpscale, 3, true)
ADD_RESIZE_KERNEL_WITH_LPI(AreaUpscale, 4, true)
#undef ADD_RESIZE_KERNEL_WITH_LPI
static auto fluidResizeTestPackage = [](int interpolation, cv::Size szIn, cv::Size szOut, int lpi = 1)
{
using namespace cv;
using namespace cv::gapi;
bool upscale = szIn.width < szOut.width || szIn.height < szOut.height;
#define RESIZE_CASE(interp, lpi) \
case lpi: pkg = kernels<FCopy, FResize##interp##lpi##Lpi>(); break;
#define RESIZE_SWITCH(interp) \
switch(lpi) \
{ \
RESIZE_CASE(interp, 1) \
RESIZE_CASE(interp, 2) \
RESIZE_CASE(interp, 3) \
RESIZE_CASE(interp, 4) \
default: CV_Assert(false); \
}
GKernelPackage pkg;
switch (interpolation)
{
case INTER_NEAREST: RESIZE_SWITCH(NN); break;
case INTER_LINEAR: RESIZE_SWITCH(Linear); break;
case INTER_AREA:
{
if (upscale)
{
RESIZE_SWITCH(AreaUpscale)
}
else
{
RESIZE_SWITCH(Area);
}
}break;
default: CV_Assert(false);
}
return combine(pkg, fluidTestPackage, unite_policy::KEEP);
#undef RESIZE_SWITCH
#undef RESIZE_CASE
};
struct ResizeTestFluid : public TestWithParam<std::tuple<int, int, cv::Size, std::tuple<cv::Size, cv::Rect>, int, double>> {};
TEST_P(ResizeTestFluid, SanityTest)
{
int type = 0, interp = 0;
cv::Size sz_in, sz_out;
int lpi = 0;
double tolerance = 0.0;
cv::Rect outRoi;
std::tuple<cv::Size, cv::Rect> outSizeAndRoi;
std::tie(type, interp, sz_in, outSizeAndRoi, lpi, tolerance) = GetParam();
std::tie(sz_out, outRoi) = outSizeAndRoi;
if (outRoi == cv::Rect{}) outRoi = {0,0,sz_out.width,sz_out.height};
if (outRoi.width == 0) outRoi.width = sz_out.width;
double fx = 0, fy = 0;
cv::Mat in_mat1 (sz_in, type );
cv::Scalar mean = cv::Scalar(127);
cv::Scalar stddev = cv::Scalar(40.f);
cv::randn(in_mat1, mean, stddev);
cv::Mat out_mat = cv::Mat::zeros(sz_out, type);
cv::Mat out_mat_ocv = cv::Mat::zeros(sz_out, type);
cv::GMat in;
auto mid = TBlur3x3::on(in, cv::BORDER_REPLICATE, {});
auto out = cv::gapi::resize(mid, sz_out, fx, fy, interp);
cv::GComputation c(in, out);
c.apply(in_mat1, out_mat, cv::compile_args(GFluidOutputRois{{outRoi}}, fluidResizeTestPackage(interp, sz_in, sz_out, lpi)));
cv::Mat mid_mat;
cv::blur(in_mat1, mid_mat, {3,3}, {-1,-1}, cv::BORDER_REPLICATE);
cv::resize(mid_mat, out_mat_ocv, sz_out, fx, fy, interp);
cv::Mat absDiff;
cv::absdiff(out_mat(outRoi), out_mat_ocv(outRoi), absDiff);
EXPECT_EQ(0, cv::countNonZero(absDiff > tolerance));
}
INSTANTIATE_TEST_CASE_P(ResizeTestCPU, ResizeTestFluid,
Combine(Values(CV_8UC1),
Values(cv::INTER_NEAREST, cv::INTER_LINEAR),
Values(cv::Size(8, 7),
cv::Size(8, 8),
cv::Size(8, 64),
cv::Size(8, 25),
cv::Size(16, 8),
cv::Size(16, 7)),
Values(std::make_tuple(cv::Size(5, 4), cv::Rect{}),
std::make_tuple(cv::Size(5, 4), cv::Rect{0, 0, 0, 2}),
std::make_tuple(cv::Size(5, 4), cv::Rect{0, 1, 0, 2}),
std::make_tuple(cv::Size(5, 4), cv::Rect{0, 2, 0, 2}),
std::make_tuple(cv::Size(7, 7), cv::Rect{}),
std::make_tuple(cv::Size(7, 7), cv::Rect{0, 0, 0, 3}),
std::make_tuple(cv::Size(7, 7), cv::Rect{0, 2, 0, 2}),
std::make_tuple(cv::Size(7, 7), cv::Rect{0, 4, 0, 3}),
std::make_tuple(cv::Size(8, 4), cv::Rect{}),
std::make_tuple(cv::Size(8, 4), cv::Rect{0, 0, 0, 3}),
std::make_tuple(cv::Size(8, 4), cv::Rect{0, 1, 0, 2}),
std::make_tuple(cv::Size(8, 4), cv::Rect{0, 3, 0, 1})),
Values(1, 2, 3, 4), // lpi
Values(0.0)));
INSTANTIATE_TEST_CASE_P(ResizeAreaTestCPU, ResizeTestFluid,
Combine(Values(CV_8UC1),
Values(cv::INTER_AREA),
Values(cv::Size(8, 7),
cv::Size(8, 8),
cv::Size(8, 64),
cv::Size(8, 25),
cv::Size(16, 8),
cv::Size(16, 7)),
Values(std::make_tuple(cv::Size(5, 4), cv::Rect{}),
std::make_tuple(cv::Size(5, 4), cv::Rect{0, 0, 0, 2}),
std::make_tuple(cv::Size(5, 4), cv::Rect{0, 1, 0, 2}),
std::make_tuple(cv::Size(5, 4), cv::Rect{0, 2, 0, 2}),
std::make_tuple(cv::Size(7, 7), cv::Rect{}),
std::make_tuple(cv::Size(7, 7), cv::Rect{0, 0, 0, 3}),
std::make_tuple(cv::Size(7, 7), cv::Rect{0, 2, 0, 2}),
std::make_tuple(cv::Size(7, 7), cv::Rect{0, 4, 0, 3}),
std::make_tuple(cv::Size(8, 4), cv::Rect{}),
std::make_tuple(cv::Size(8, 4), cv::Rect{0, 0, 0, 3}),
std::make_tuple(cv::Size(8, 4), cv::Rect{0, 1, 0, 2}),
std::make_tuple(cv::Size(8, 4), cv::Rect{0, 3, 0, 1})),
Values(1, 2, 3, 4), // lpi
// Actually this tolerance only for cases where OpenCV
// uses ResizeAreaFast
Values(1.0)));
INSTANTIATE_TEST_CASE_P(ResizeUpscaleTestCPU, ResizeTestFluid,
Combine(Values(CV_8UC1),
Values(cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_AREA),
Values(cv::Size(1, 5),
cv::Size(3, 5),
cv::Size(7, 5),
cv::Size(1, 7),
cv::Size(3, 7),
cv::Size(7, 7)),
Values(std::make_tuple(cv::Size(8, 8), cv::Rect{0,0,8,2}),
std::make_tuple(cv::Size(8, 8), cv::Rect{0,2,8,2}),
std::make_tuple(cv::Size(8, 8), cv::Rect{0,4,8,2}),
std::make_tuple(cv::Size(8, 8), cv::Rect{0,6,8,2}),
std::make_tuple(cv::Size(8, 8), cv::Rect{0,0,8,8}),
std::make_tuple(cv::Size(16, 8), cv::Rect{}),
std::make_tuple(cv::Size(16, 64), cv::Rect{0, 0,16,16}),
std::make_tuple(cv::Size(16, 64), cv::Rect{0,16,16,16}),
std::make_tuple(cv::Size(16, 64), cv::Rect{0,32,16,16}),
std::make_tuple(cv::Size(16, 64), cv::Rect{0,48,16,16}),
std::make_tuple(cv::Size(16, 64), cv::Rect{0, 0,16,64}),
std::make_tuple(cv::Size(16, 25), cv::Rect{0, 0,16, 7}),
std::make_tuple(cv::Size(16, 25), cv::Rect{0, 7,16, 6}),
std::make_tuple(cv::Size(16, 25), cv::Rect{0,13,16, 6}),
std::make_tuple(cv::Size(16, 25), cv::Rect{0,19,16, 6}),
std::make_tuple(cv::Size(16, 25), cv::Rect{0, 0,16, 7}),
std::make_tuple(cv::Size(16, 25), cv::Rect{0, 7,16, 7}),
std::make_tuple(cv::Size(16, 25), cv::Rect{0,14,16, 7}),
std::make_tuple(cv::Size(16, 25), cv::Rect{0,21,16, 4}),
std::make_tuple(cv::Size(16, 25), cv::Rect{0, 0,16,25}),
std::make_tuple(cv::Size(16, 7), cv::Rect{}),
std::make_tuple(cv::Size(16, 8), cv::Rect{})),
Values(1, 2, 3, 4), // lpi
Values(0.0)));
INSTANTIATE_TEST_CASE_P(ResizeUpscaleOneDimDownscaleAnother, ResizeTestFluid,
Combine(Values(CV_8UC1),
Values(cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_AREA),
Values(cv::Size(6, 6),
cv::Size(8, 7),
cv::Size(8, 8),
cv::Size(8, 10),
cv::Size(10, 8),
cv::Size(10, 7)),
Values(std::make_tuple(cv::Size(11, 5), cv::Rect{}),
std::make_tuple(cv::Size(11, 5), cv::Rect{0, 0, 0, 2}),
std::make_tuple(cv::Size(11, 5), cv::Rect{0, 2, 0, 2}),
std::make_tuple(cv::Size(11, 5), cv::Rect{0, 4, 0, 1}),
std::make_tuple(cv::Size(12, 2), cv::Rect{}),
std::make_tuple(cv::Size(12, 2), cv::Rect{0, 0, 0, 1}),
std::make_tuple(cv::Size(12, 2), cv::Rect{0, 1, 0, 1}),
std::make_tuple(cv::Size(23, 3), cv::Rect{}),
std::make_tuple(cv::Size(23, 3), cv::Rect{0, 0, 0, 1}),
std::make_tuple(cv::Size(23, 3), cv::Rect{0, 1, 0, 1}),
std::make_tuple(cv::Size(23, 3), cv::Rect{0, 2, 0, 1}),
std::make_tuple(cv::Size(3, 24), cv::Rect{}),
std::make_tuple(cv::Size(3, 24), cv::Rect{0, 0, 0, 6}),
std::make_tuple(cv::Size(3, 24), cv::Rect{0, 6, 0, 6}),
std::make_tuple(cv::Size(3, 24), cv::Rect{0, 12, 0, 6}),
std::make_tuple(cv::Size(3, 24), cv::Rect{0, 18, 0, 6}),
std::make_tuple(cv::Size(5, 11), cv::Rect{}),
std::make_tuple(cv::Size(5, 11), cv::Rect{0, 0, 0, 3}),
std::make_tuple(cv::Size(5, 11), cv::Rect{0, 3, 0, 3}),
std::make_tuple(cv::Size(5, 11), cv::Rect{0, 6, 0, 3}),
std::make_tuple(cv::Size(5, 11), cv::Rect{0, 9, 0, 2})),
Values(1, 2, 3, 4), // lpi
Values(0.0)));
INSTANTIATE_TEST_CASE_P(Resize400_384TestCPU, ResizeTestFluid,
Combine(Values(CV_8UC1),
Values(cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_AREA),
Values(cv::Size(128, 400)),
Values(std::make_tuple(cv::Size(128, 384), cv::Rect{})),
Values(1, 2, 3, 4), // lpi
Values(0.0)));
INSTANTIATE_TEST_CASE_P(Resize220_400TestCPU, ResizeTestFluid,
Combine(Values(CV_8UC1),
Values(cv::INTER_LINEAR),
Values(cv::Size(220, 220)),
Values(std::make_tuple(cv::Size(400, 400), cv::Rect{})),
Values(1, 2, 3, 4), // lpi
Values(0.0)));
static auto cvBlur = [](const cv::Mat& in, cv::Mat& out, int kernelSize)
{
if (kernelSize == 1)
{
out = in;
}
else
{
cv::blur(in, out, {kernelSize, kernelSize});
}
};
using SizesWithRois = std::tuple<cv::Size, cv::Rect, cv::Size, cv::Rect>;
struct ResizeAndAnotherReaderTest : public TestWithParam<std::tuple<int, int, bool, SizesWithRois>>{};
TEST_P(ResizeAndAnotherReaderTest, SanityTest)
{
bool readFromInput = false;
int interp = -1, kernelSize = -1;
SizesWithRois sizesWithRois;
std::tie(interp, kernelSize, readFromInput, sizesWithRois) = GetParam();
cv::Size sz, resizedSz;
cv::Rect roi, resizedRoi;
std::tie(sz, roi, resizedSz, resizedRoi) = sizesWithRois;
cv::Mat in_mat(sz, CV_8UC1);
cv::Scalar mean = cv::Scalar(127);
cv::Scalar stddev = cv::Scalar(40.f);
cv::randn(in_mat, mean, stddev);
cv::Mat gapi_resize_out = cv::Mat::zeros(resizedSz, CV_8UC1);
cv::Mat gapi_blur_out = cv::Mat::zeros(sz, CV_8UC1);
auto blur = kernelSize == 1 ? &TBlur1x1::on : kernelSize == 3 ? &TBlur3x3::on : &TBlur5x5::on;
cv::GMat in, resize_out, blur_out;
if (readFromInput)
{
resize_out = gapi::resize(in, resizedSz, 0, 0, interp);
blur_out = blur(in, cv::BORDER_DEFAULT, {});
}
else
{
auto mid = TCopy::on(in);
resize_out = gapi::resize(mid, resizedSz, 0, 0, interp);
blur_out = blur(mid, cv::BORDER_DEFAULT, {});
}
cv::GComputation c(GIn(in), GOut(resize_out, blur_out));
c.apply(gin(in_mat), gout(gapi_resize_out, gapi_blur_out), cv::compile_args(GFluidOutputRois{{resizedRoi, roi}},
fluidResizeTestPackage(interp, sz, resizedSz)));
cv::Mat ocv_resize_out = cv::Mat::zeros(resizedSz, CV_8UC1);
cv::resize(in_mat, ocv_resize_out, resizedSz, 0, 0, interp);
cv::Mat ocv_blur_out = cv::Mat::zeros(sz, CV_8UC1);
cvBlur(in_mat, ocv_blur_out, kernelSize);
EXPECT_EQ(0, cv::countNonZero(gapi_resize_out(resizedRoi) != ocv_resize_out(resizedRoi)));
EXPECT_EQ(0, cv::countNonZero(gapi_blur_out(roi) != ocv_blur_out(roi)));
}
INSTANTIATE_TEST_CASE_P(ResizeTestCPU, ResizeAndAnotherReaderTest,
Combine(Values(cv::INTER_NEAREST, cv::INTER_LINEAR),
Values(1, 3, 5),
testing::Bool(), // Read from input directly or place a copy node at start
Values(std::make_tuple(cv::Size{8,8}, cv::Rect{0,0,8,8},
cv::Size{4,4}, cv::Rect{0,0,4,4}),
std::make_tuple(cv::Size{8,8}, cv::Rect{0,0,8,2},
cv::Size{4,4}, cv::Rect{0,0,4,1}),
std::make_tuple(cv::Size{8,8}, cv::Rect{0,2,8,4},
cv::Size{4,4}, cv::Rect{0,1,4,2}),
std::make_tuple(cv::Size{8,8}, cv::Rect{0,4,8,4},
cv::Size{4,4}, cv::Rect{0,2,4,2}),
std::make_tuple(cv::Size{64,64}, cv::Rect{0, 0,64,64},
cv::Size{49,49}, cv::Rect{0, 0,49,49}),
std::make_tuple(cv::Size{64,64}, cv::Rect{0, 0,64,15},
cv::Size{49,49}, cv::Rect{0, 0,49,11}),
std::make_tuple(cv::Size{64,64}, cv::Rect{0,11,64,23},
cv::Size{49,49}, cv::Rect{0, 9,49,17}),
std::make_tuple(cv::Size{64,64}, cv::Rect{0,50,64,14},
cv::Size{49,49}, cv::Rect{0,39,49,10}))));
struct BlursAfterResizeTest : public TestWithParam<std::tuple<int, int, int, bool, std::tuple<cv::Size, cv::Size, cv::Rect>>>{};
TEST_P(BlursAfterResizeTest, SanityTest)
{
bool readFromInput = false;
int interp = -1, kernelSize1 = -1, kernelSize2 = -1;
std::tuple<cv::Size, cv::Size, cv::Rect> sizesWithRoi;
std::tie(interp, kernelSize1, kernelSize2, readFromInput, sizesWithRoi) = GetParam();
cv::Size inSz, outSz;
cv::Rect outRoi;
std::tie(inSz, outSz, outRoi) = sizesWithRoi;
cv::Mat in_mat(inSz, CV_8UC1);
cv::Scalar mean = cv::Scalar(127);
cv::Scalar stddev = cv::Scalar(40.f);
cv::randn(in_mat, mean, stddev);
cv::Mat gapi_out1 = cv::Mat::zeros(outSz, CV_8UC1);
cv::Mat gapi_out2 = cv::Mat::zeros(outSz, CV_8UC1);
auto blur1 = kernelSize1 == 1 ? &TBlur1x1::on : kernelSize1 == 3 ? &TBlur3x3::on : &TBlur5x5::on;
auto blur2 = kernelSize2 == 1 ? &TBlur1x1::on : kernelSize2 == 3 ? &TBlur3x3::on : &TBlur5x5::on;
cv::GMat in, out1, out2;
if (readFromInput)
{
auto resized = gapi::resize(in, outSz, 0, 0, interp);
out1 = blur1(resized, cv::BORDER_DEFAULT, {});
out2 = blur2(resized, cv::BORDER_DEFAULT, {});
}
else
{
auto mid = TCopy::on(in);
auto resized = gapi::resize(mid, outSz, 0, 0, interp);
out1 = blur1(resized, cv::BORDER_DEFAULT, {});
out2 = blur2(resized, cv::BORDER_DEFAULT, {});
}
cv::GComputation c(GIn(in), GOut(out1, out2));
c.apply(gin(in_mat), gout(gapi_out1, gapi_out2), cv::compile_args(GFluidOutputRois{{outRoi, outRoi}},
fluidResizeTestPackage(interp, inSz, outSz)));
cv::Mat ocv_out1 = cv::Mat::zeros(outSz, CV_8UC1);
cv::Mat ocv_out2 = cv::Mat::zeros(outSz, CV_8UC1);
cv::Mat resized = cv::Mat::zeros(outSz, CV_8UC1);
cv::resize(in_mat, resized, outSz, 0, 0, interp);
cvBlur(resized, ocv_out1, kernelSize1);
cvBlur(resized, ocv_out2, kernelSize2);
EXPECT_EQ(0, cv::countNonZero(gapi_out1(outRoi) != ocv_out1(outRoi)));
EXPECT_EQ(0, cv::countNonZero(gapi_out2(outRoi) != ocv_out2(outRoi)));
}
INSTANTIATE_TEST_CASE_P(ResizeTestCPU, BlursAfterResizeTest,
Combine(Values(cv::INTER_NEAREST, cv::INTER_LINEAR),
Values(1, 3, 5),
Values(1, 3, 5),
testing::Bool(), // Read from input directly or place a copy node at start
Values(std::make_tuple(cv::Size{8,8},
cv::Size{4,4}, cv::Rect{0,0,4,4}),
std::make_tuple(cv::Size{8,8},
cv::Size{4,4}, cv::Rect{0,0,4,1}),
std::make_tuple(cv::Size{8,8},
cv::Size{4,4}, cv::Rect{0,1,4,2}),
std::make_tuple(cv::Size{8,8},
cv::Size{4,4}, cv::Rect{0,2,4,2}),
std::make_tuple(cv::Size{64,64},
cv::Size{49,49}, cv::Rect{0, 0,49,49}),
std::make_tuple(cv::Size{64,64},
cv::Size{49,49}, cv::Rect{0, 0,49,11}),
std::make_tuple(cv::Size{64,64},
cv::Size{49,49}, cv::Rect{0, 9,49,17}),
std::make_tuple(cv::Size{64,64},
cv::Size{49,49}, cv::Rect{0,39,49,10}))));
} // namespace opencv_test