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Commit 73c152ab authored by Andrey Kamaev's avatar Andrey Kamaev
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Merged the trunk r8575:8583 (INTER_AREA interpolation for GPU resize)

parent ab20da0f
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modules/gpu/perf/perf_imgproc.cpp
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......@@ -5,27 +5,32 @@
//////////////////////////////////////////////////////////////////////
// Remap
GPU_PERF_TEST(Remap, cv::gpu::DeviceInfo, cv::Size, perf::MatType, Interpolation, BorderMode)
GPU_PERF_TEST(Remap, cv::gpu::DeviceInfo, cv::Size, MatType, Interpolation, BorderMode)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int interpolation = GET_PARAM(3);
int borderMode = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
fill(src_host, 0, 255);
cv::Mat xmap_host(size, CV_32FC1);
cv::Mat ymap_host(size, CV_32FC1);
fill(xmap_host, 0, size.width);
declare.in(src_host, xmap_host, ymap_host, WARMUP_RNG);
cv::Mat ymap_host(size, CV_32FC1);
fill(ymap_host, 0, size.height);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat xmap(xmap_host);
cv::gpu::GpuMat ymap(ymap_host);
cv::gpu::GpuMat dst;
cv::gpu::remap(src, dst, xmap, ymap, interpolation, borderMode);
declare.time(3.0);
TEST_CYCLE()
......@@ -35,578 +40,815 @@ GPU_PERF_TEST(Remap, cv::gpu::DeviceInfo, cv::Size, perf::MatType, Interpolation
}
INSTANTIATE_TEST_CASE_P(ImgProc, Remap, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_8UC4, CV_16UC1, CV_32FC1),
testing::Values((int) cv::INTER_NEAREST, (int) cv::INTER_LINEAR, (int) cv::INTER_CUBIC),
testing::Values((int) cv::BORDER_REFLECT101, (int) cv::BORDER_REPLICATE, (int) cv::BORDER_CONSTANT)));
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
testing::Values(BorderMode(cv::BORDER_REFLECT101), BorderMode(cv::BORDER_REPLICATE), BorderMode(cv::BORDER_CONSTANT), BorderMode(cv::BORDER_REFLECT), BorderMode(cv::BORDER_WRAP))));
//////////////////////////////////////////////////////////////////////
// MeanShiftFiltering
// Resize
GPU_PERF_TEST_1(MeanShiftFiltering, cv::gpu::DeviceInfo)
{
cv::gpu::DeviceInfo devInfo = GetParam();
IMPLEMENT_PARAM_CLASS(Scale, double)
GPU_PERF_TEST(Resize, cv::gpu::DeviceInfo, cv::Size, MatType, Interpolation, Scale)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat img = readImage("gpu/meanshift/cones.png");
ASSERT_FALSE(img.empty());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int interpolation = GET_PARAM(3);
double f = GET_PARAM(4);
cv::Mat rgba;
cv::cvtColor(img, rgba, cv::COLOR_BGR2BGRA);
cv::Mat src_host(size, type);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(rgba);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
declare.time(5.0);
cv::gpu::resize(src, dst, cv::Size(), f, f, interpolation);
declare.time(1.0);
TEST_CYCLE()
{
cv::gpu::meanShiftFiltering(src, dst, 50, 50);
cv::gpu::resize(src, dst, cv::Size(), f, f, interpolation);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, MeanShiftFiltering, ALL_DEVICES);
INSTANTIATE_TEST_CASE_P(ImgProc, Resize, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR),
Interpolation(cv::INTER_CUBIC), Interpolation(cv::INTER_AREA)),
testing::Values(Scale(0.5), Scale(0.3), Scale(2.0))));
//////////////////////////////////////////////////////////////////////
// MeanShiftProc
// WarpAffine
GPU_PERF_TEST_1(MeanShiftProc, cv::gpu::DeviceInfo)
GPU_PERF_TEST(WarpAffine, cv::gpu::DeviceInfo, cv::Size, MatType, Interpolation, BorderMode)
{
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat img = readImage("gpu/meanshift/cones.png");
ASSERT_FALSE(img.empty());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int interpolation = GET_PARAM(3);
int borderMode = GET_PARAM(4);
cv::Mat rgba;
cv::cvtColor(img, rgba, cv::COLOR_BGR2BGRA);
cv::Mat src_host(size, type);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(rgba);
cv::gpu::GpuMat dstr;
cv::gpu::GpuMat dstsp;
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
declare.time(5.0);
const double aplha = CV_PI / 4;
double mat[2][3] = { {std::cos(aplha), -std::sin(aplha), src.cols / 2},
{std::sin(aplha), std::cos(aplha), 0}};
cv::Mat M(2, 3, CV_64F, (void*) mat);
cv::gpu::warpAffine(src, dst, M, size, interpolation, borderMode);
TEST_CYCLE()
{
cv::gpu::meanShiftProc(src, dstr, dstsp, 50, 50);
cv::gpu::warpAffine(src, dst, M, size, interpolation, borderMode);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, MeanShiftProc, ALL_DEVICES);
INSTANTIATE_TEST_CASE_P(ImgProc, WarpAffine, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
testing::Values(BorderMode(cv::BORDER_REFLECT101), BorderMode(cv::BORDER_REPLICATE), BorderMode(cv::BORDER_CONSTANT), BorderMode(cv::BORDER_REFLECT), BorderMode(cv::BORDER_WRAP))));
//////////////////////////////////////////////////////////////////////
// MeanShiftSegmentation
// WarpPerspective
GPU_PERF_TEST_1(MeanShiftSegmentation, cv::gpu::DeviceInfo)
GPU_PERF_TEST(WarpPerspective, cv::gpu::DeviceInfo, cv::Size, MatType, Interpolation, BorderMode)
{
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat img = readImage("gpu/meanshift/cones.png");
ASSERT_FALSE(img.empty());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int interpolation = GET_PARAM(3);
int borderMode = GET_PARAM(4);
cv::Mat rgba;
cv::cvtColor(img, rgba, cv::COLOR_BGR2BGRA);
cv::Mat src_host(size, type);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(rgba);
cv::Mat dst;
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
declare.time(5.0);
const double aplha = CV_PI / 4;
double mat[3][3] = { {std::cos(aplha), -std::sin(aplha), src.cols / 2},
{std::sin(aplha), std::cos(aplha), 0},
{0.0, 0.0, 1.0}};
cv::Mat M(3, 3, CV_64F, (void*) mat);
cv::gpu::warpPerspective(src, dst, M, size, interpolation, borderMode);
TEST_CYCLE()
{
meanShiftSegmentation(src, dst, 10, 10, 20);
cv::gpu::warpPerspective(src, dst, M, size, interpolation, borderMode);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, MeanShiftSegmentation, ALL_DEVICES);
INSTANTIATE_TEST_CASE_P(ImgProc, WarpPerspective, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
testing::Values(BorderMode(cv::BORDER_REFLECT101), BorderMode(cv::BORDER_REPLICATE), BorderMode(cv::BORDER_CONSTANT), BorderMode(cv::BORDER_REFLECT), BorderMode(cv::BORDER_WRAP))));
//////////////////////////////////////////////////////////////////////
// DrawColorDisp
// CopyMakeBorder
GPU_PERF_TEST(DrawColorDisp, cv::gpu::DeviceInfo, cv::Size, perf::MatType)
GPU_PERF_TEST(CopyMakeBorder, cv::gpu::DeviceInfo, cv::Size, MatType, BorderMode)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
int borderType = GET_PARAM(3);
cv::Mat src_host(size, type);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::copyMakeBorder(src, dst, 5, 5, 5, 5, borderType);
TEST_CYCLE()
{
cv::gpu::drawColorDisp(src, dst, 255);
cv::gpu::copyMakeBorder(src, dst, 5, 5, 5, 5, borderType);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, DrawColorDisp, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_16SC1)));
INSTANTIATE_TEST_CASE_P(ImgProc, CopyMakeBorder, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(BorderMode(cv::BORDER_REFLECT101), BorderMode(cv::BORDER_REPLICATE), BorderMode(cv::BORDER_CONSTANT), BorderMode(cv::BORDER_REFLECT), BorderMode(cv::BORDER_WRAP))));
//////////////////////////////////////////////////////////////////////
// ReprojectImageTo3D
// Threshold
CV_ENUM(ThreshOp, cv::THRESH_BINARY, cv::THRESH_BINARY_INV, cv::THRESH_TRUNC, cv::THRESH_TOZERO, cv::THRESH_TOZERO_INV)
#define ALL_THRESH_OPS testing::Values(ThreshOp(cv::THRESH_BINARY), ThreshOp(cv::THRESH_BINARY_INV), ThreshOp(cv::THRESH_TRUNC), ThreshOp(cv::THRESH_TOZERO), ThreshOp(cv::THRESH_TOZERO_INV))
GPU_PERF_TEST(ReprojectImageTo3D, cv::gpu::DeviceInfo, cv::Size, perf::MatType)
GPU_PERF_TEST(Threshold, cv::gpu::DeviceInfo, cv::Size, MatDepth, ThreshOp)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
cv::Size size = GET_PARAM(1);
int depth = GET_PARAM(2);
int threshOp = GET_PARAM(3);
declare.in(src_host, WARMUP_RNG);
cv::Mat src_host(size, depth);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::threshold(src, dst, 100.0, 255.0, threshOp);
TEST_CYCLE()
{
cv::gpu::reprojectImageTo3D(src, dst, cv::Mat::ones(4, 4, CV_32FC1));
cv::gpu::threshold(src, dst, 100.0, 255.0, threshOp);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, ReprojectImageTo3D, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_16SC1)));
INSTANTIATE_TEST_CASE_P(ImgProc, Threshold, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_32F), MatDepth(CV_64F)),
ALL_THRESH_OPS));
//////////////////////////////////////////////////////////////////////
// CvtColor
// Integral
GPU_PERF_TEST(CvtColor, cv::gpu::DeviceInfo, cv::Size, perf::MatType, CvtColorInfo)
GPU_PERF_TEST(Integral, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
CvtColorInfo info = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, CV_MAKETYPE(type, info.scn));
cv::Size size = GET_PARAM(1);
declare.in(src_host, WARMUP_RNG);
cv::Mat src_host(size, CV_8UC1);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::GpuMat buf;
cv::gpu::integralBuffered(src, dst, buf);
TEST_CYCLE()
{
cv::gpu::cvtColor(src, dst, info.code, info.dcn);
cv::gpu::integralBuffered(src, dst, buf);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, CvtColor, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_16UC1, CV_32FC1),
testing::Values(
CvtColorInfo(4, 4, cv::COLOR_RGBA2BGRA), CvtColorInfo(4, 1, cv::COLOR_BGRA2GRAY), CvtColorInfo(1, 4, cv::COLOR_GRAY2BGRA),
CvtColorInfo(4, 4, cv::COLOR_BGR2XYZ), CvtColorInfo(4, 4, cv::COLOR_BGR2YCrCb), CvtColorInfo(4, 4, cv::COLOR_YCrCb2BGR),
CvtColorInfo(4, 4, cv::COLOR_BGR2HSV), CvtColorInfo(4, 4, cv::COLOR_HSV2BGR))));
INSTANTIATE_TEST_CASE_P(ImgProc, Integral, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
//////////////////////////////////////////////////////////////////////
// SwapChannels
// Integral_Sqr
GPU_PERF_TEST(SwapChannels, cv::gpu::DeviceInfo, cv::Size)
GPU_PERF_TEST(Integral_Sqr, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, CV_8UC4);
cv::Size size = GET_PARAM(1);
declare.in(src_host, WARMUP_RNG);
cv::Mat src_host(size, CV_8UC1);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
const int dstOrder[] = {2, 1, 0, 3};
cv::gpu::sqrIntegral(src, dst);
TEST_CYCLE()
{
cv::gpu::swapChannels(src, dstOrder);
cv::gpu::sqrIntegral(src, dst);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, SwapChannels, testing::Combine(ALL_DEVICES, GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, Integral_Sqr, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
//////////////////////////////////////////////////////////////////////
// Threshold
// HistEven_OneChannel
GPU_PERF_TEST(Threshold, cv::gpu::DeviceInfo, cv::Size, perf::MatType)
GPU_PERF_TEST(HistEven_OneChannel, cv::gpu::DeviceInfo, cv::Size, MatDepth)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
cv::Size size = GET_PARAM(1);
int depth = GET_PARAM(2);
declare.in(src_host, WARMUP_RNG);
cv::Mat src_host(size, depth);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst(size, type);
cv::gpu::GpuMat hist;
cv::gpu::GpuMat buf;
cv::gpu::histEven(src, hist, buf, 30, 0, 180);
TEST_CYCLE()
{
cv::gpu::threshold(src, dst, 100.0, 255.0, cv::THRESH_BINARY);
cv::gpu::histEven(src, hist, buf, 30, 0, 180);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, Threshold, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_16UC1, CV_32FC1)));
INSTANTIATE_TEST_CASE_P(ImgProc, HistEven_OneChannel, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_16S))));
//////////////////////////////////////////////////////////////////////
// Resize
// HistEven_FourChannel
GPU_PERF_TEST(Resize, cv::gpu::DeviceInfo, cv::Size, perf::MatType, Interpolation, double)
GPU_PERF_TEST(HistEven_FourChannel, cv::gpu::DeviceInfo, cv::Size, MatDepth)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int interpolation = GET_PARAM(3);
double f = GET_PARAM(4);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
cv::Size size = GET_PARAM(1);
int depth = GET_PARAM(2);
declare.in(src_host, WARMUP_RNG);
cv::Mat src_host(size, CV_MAKE_TYPE(depth, 4));
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::GpuMat hist[4];
cv::gpu::GpuMat buf;
int histSize[] = {30, 30, 30, 30};
int lowerLevel[] = {0, 0, 0, 0};
int upperLevel[] = {180, 180, 180, 180};
declare.time(1.0);
cv::gpu::histEven(src, hist, buf, histSize, lowerLevel, upperLevel);
TEST_CYCLE()
{
cv::gpu::resize(src, dst, cv::Size(), f, f, interpolation);
cv::gpu::histEven(src, hist, buf, histSize, lowerLevel, upperLevel);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, Resize, testing::Combine(
ALL_DEVICES,
testing::Values(perf::szSXGA, perf::sz1080p),
testing::Values(CV_8UC1, CV_8UC4, CV_16UC1, CV_32FC1),
testing::Values((int) cv::INTER_NEAREST, (int) cv::INTER_LINEAR, (int) cv::INTER_CUBIC),
testing::Values(0.5, 2.0)));
INSTANTIATE_TEST_CASE_P(ImgProc, HistEven_FourChannel, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_16S))));
//////////////////////////////////////////////////////////////////////
// WarpAffine
// CalcHist
GPU_PERF_TEST(WarpAffine, cv::gpu::DeviceInfo, cv::Size, perf::MatType, Interpolation)
GPU_PERF_TEST(CalcHist, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int interpolation = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
cv::Size size = GET_PARAM(1);
declare.in(src_host, WARMUP_RNG);
cv::Mat src_host(size, CV_8UC1);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::GpuMat hist;
cv::gpu::GpuMat buf;
const double aplha = CV_PI / 4;
double mat[2][3] = { {std::cos(aplha), -std::sin(aplha), src.cols / 2},
{std::sin(aplha), std::cos(aplha), 0}};
cv::Mat M(2, 3, CV_64F, (void*) mat);
cv::gpu::calcHist(src, hist, buf);
TEST_CYCLE()
{
cv::gpu::warpAffine(src, dst, M, size, interpolation, cv::BORDER_CONSTANT, cv::Scalar());
cv::gpu::calcHist(src, hist, buf);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, WarpAffine, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32FC1, CV_32FC3, CV_32FC4),
testing::Values((int) cv::INTER_NEAREST, (int) cv::INTER_LINEAR, (int) cv::INTER_CUBIC)));
INSTANTIATE_TEST_CASE_P(ImgProc, CalcHist, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
//////////////////////////////////////////////////////////////////////
// WarpPerspective
// EqualizeHist
GPU_PERF_TEST(WarpPerspective, cv::gpu::DeviceInfo, cv::Size, perf::MatType, Interpolation)
GPU_PERF_TEST(EqualizeHist, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int interpolation = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
cv::Size size = GET_PARAM(1);
declare.in(src_host, WARMUP_RNG);
cv::Mat src_host(size, CV_8UC1);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::GpuMat hist;
cv::gpu::GpuMat buf;
const double aplha = CV_PI / 4;
double mat[3][3] = { {std::cos(aplha), -std::sin(aplha), src.cols / 2},
{std::sin(aplha), std::cos(aplha), 0},
{0.0, 0.0, 1.0}};
cv::Mat M(3, 3, CV_64F, (void*) mat);
cv::gpu::equalizeHist(src, dst, hist, buf);
TEST_CYCLE()
{
cv::gpu::warpPerspective(src, dst, M, size, interpolation, cv::BORDER_CONSTANT, cv::Scalar());
cv::gpu::equalizeHist(src, dst, hist, buf);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, WarpPerspective, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32FC1, CV_32FC3, CV_32FC4),
testing::Values((int) cv::INTER_NEAREST, (int) cv::INTER_LINEAR, (int) cv::INTER_CUBIC)));
INSTANTIATE_TEST_CASE_P(ImgProc, EqualizeHist, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
//////////////////////////////////////////////////////////////////////
// BuildWarpPlaneMaps
// ColumnSum
GPU_PERF_TEST(BuildWarpPlaneMaps, cv::gpu::DeviceInfo, cv::Size)
GPU_PERF_TEST(ColumnSum, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, CV_32FC1);
fill(src_host, 0, 255);
cv::gpu::GpuMat map_x;
cv::gpu::GpuMat map_y;
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::columnSum(src, dst);
TEST_CYCLE()
{
cv::gpu::buildWarpPlaneMaps(size, cv::Rect(0, 0, size.width, size.height), cv::Mat::eye(3, 3, CV_32FC1),
cv::Mat::ones(3, 3, CV_32FC1), cv::Mat::zeros(1, 3, CV_32F), 1.0, map_x, map_y);
cv::gpu::columnSum(src, dst);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, BuildWarpPlaneMaps, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, ColumnSum, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
//////////////////////////////////////////////////////////////////////
// BuildWarpCylindricalMaps
// Canny
GPU_PERF_TEST(BuildWarpCylindricalMaps, cv::gpu::DeviceInfo, cv::Size)
IMPLEMENT_PARAM_CLASS(AppertureSize, int)
IMPLEMENT_PARAM_CLASS(L2gradient, bool)
GPU_PERF_TEST(Canny, cv::gpu::DeviceInfo, AppertureSize, L2gradient)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
int apperture_size = GET_PARAM(1);
bool useL2gradient = GET_PARAM(2);
cv::Mat image_host = readImage("perf/1280x1024.jpg", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(image_host.empty());
cv::gpu::GpuMat image(image_host);
cv::gpu::GpuMat dst;
cv::gpu::CannyBuf buf;
cv::gpu::Canny(image, buf, dst, 50.0, 100.0, apperture_size, useL2gradient);
TEST_CYCLE()
{
cv::gpu::Canny(image, buf, dst, 50.0, 100.0, apperture_size, useL2gradient);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, Canny, testing::Combine(
ALL_DEVICES,
testing::Values(AppertureSize(3), AppertureSize(5)),
testing::Values(L2gradient(false), L2gradient(true))));
//////////////////////////////////////////////////////////////////////
// MeanShiftFiltering
GPU_PERF_TEST_1(MeanShiftFiltering, cv::gpu::DeviceInfo)
{
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
cv::gpu::GpuMat map_x;
cv::gpu::GpuMat map_y;
cv::Mat img = readImage("gpu/meanshift/cones.png");
ASSERT_FALSE(img.empty());
cv::Mat rgba;
cv::cvtColor(img, rgba, cv::COLOR_BGR2BGRA);
cv::gpu::GpuMat src(rgba);
cv::gpu::GpuMat dst;
cv::gpu::meanShiftFiltering(src, dst, 50, 50);
declare.time(5.0);
TEST_CYCLE()
{
cv::gpu::buildWarpCylindricalMaps(size, cv::Rect(0, 0, size.width, size.height), cv::Mat::eye(3, 3, CV_32FC1),
cv::Mat::ones(3, 3, CV_32FC1), 1.0, map_x, map_y);
cv::gpu::meanShiftFiltering(src, dst, 50, 50);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, BuildWarpCylindricalMaps, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, MeanShiftFiltering, ALL_DEVICES);
//////////////////////////////////////////////////////////////////////
// BuildWarpSphericalMaps
// MeanShiftProc
GPU_PERF_TEST(BuildWarpSphericalMaps, cv::gpu::DeviceInfo, cv::Size)
GPU_PERF_TEST_1(MeanShiftProc, cv::gpu::DeviceInfo)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat img = readImage("gpu/meanshift/cones.png");
ASSERT_FALSE(img.empty());
cv::Mat rgba;
cv::cvtColor(img, rgba, cv::COLOR_BGR2BGRA);
cv::gpu::GpuMat src(rgba);
cv::gpu::GpuMat dstr;
cv::gpu::GpuMat dstsp;
cv::gpu::meanShiftProc(src, dstr, dstsp, 50, 50);
declare.time(5.0);
TEST_CYCLE()
{
cv::gpu::meanShiftProc(src, dstr, dstsp, 50, 50);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, MeanShiftProc, ALL_DEVICES);
//////////////////////////////////////////////////////////////////////
// MeanShiftSegmentation
GPU_PERF_TEST_1(MeanShiftSegmentation, cv::gpu::DeviceInfo)
{
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
cv::gpu::GpuMat map_x;
cv::gpu::GpuMat map_y;
cv::Mat img = readImage("gpu/meanshift/cones.png");
ASSERT_FALSE(img.empty());
cv::Mat rgba;
cv::cvtColor(img, rgba, cv::COLOR_BGR2BGRA);
cv::gpu::GpuMat src(rgba);
cv::Mat dst;
meanShiftSegmentation(src, dst, 10, 10, 20);
declare.time(5.0);
TEST_CYCLE()
{
cv::gpu::buildWarpSphericalMaps(size, cv::Rect(0, 0, size.width, size.height), cv::Mat::eye(3, 3, CV_32FC1),
cv::Mat::ones(3, 3, CV_32FC1), 1.0, map_x, map_y);
meanShiftSegmentation(src, dst, 10, 10, 20);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, BuildWarpSphericalMaps, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, MeanShiftSegmentation, ALL_DEVICES);
//////////////////////////////////////////////////////////////////////
// Rotate
// BlendLinear
GPU_PERF_TEST(Rotate, cv::gpu::DeviceInfo, cv::Size, perf::MatType, Interpolation)
GPU_PERF_TEST(BlendLinear, cv::gpu::DeviceInfo, cv::Size, MatType)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int interpolation = GET_PARAM(3);
cv::Mat img1_host(size, type);
fill(img1_host, 0, 255);
cv::Mat img2_host(size, type);
fill(img2_host, 0, 255);
cv::gpu::GpuMat img1(img1_host);
cv::gpu::GpuMat img2(img2_host);
cv::gpu::GpuMat weights1(size, CV_32FC1, cv::Scalar::all(0.5));
cv::gpu::GpuMat weights2(size, CV_32FC1, cv::Scalar::all(0.5));
cv::gpu::GpuMat dst;
cv::gpu::blendLinear(img1, img2, weights1, weights2, dst);
TEST_CYCLE()
{
cv::gpu::blendLinear(img1, img2, weights1, weights2, dst);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, BlendLinear, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4))));
//////////////////////////////////////////////////////////////////////
// Convolve
IMPLEMENT_PARAM_CLASS(KSize, int)
IMPLEMENT_PARAM_CLASS(Ccorr, bool)
GPU_PERF_TEST(Convolve, cv::gpu::DeviceInfo, cv::Size, KSize, Ccorr)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
cv::Size size = GET_PARAM(1);
int templ_size = GET_PARAM(2);
bool ccorr = GET_PARAM(3);
declare.in(src_host, WARMUP_RNG);
cv::gpu::GpuMat image = cv::gpu::createContinuous(size, CV_32FC1);
image.setTo(cv::Scalar(1.0));
cv::gpu::GpuMat templ = cv::gpu::createContinuous(templ_size, templ_size, CV_32FC1);
templ.setTo(cv::Scalar(1.0));
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::ConvolveBuf buf;
cv::gpu::convolve(image, templ, dst, ccorr, buf);
declare.time(2.0);
TEST_CYCLE()
{
cv::gpu::rotate(src, dst, size, 30.0, 0, 0, interpolation);
cv::gpu::convolve(image, templ, dst, ccorr, buf);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, Rotate, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32FC1, CV_32FC3, CV_32FC4),
testing::Values((int) cv::INTER_NEAREST, (int) cv::INTER_LINEAR, (int) cv::INTER_CUBIC)));
INSTANTIATE_TEST_CASE_P(ImgProc, Convolve, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(KSize(3), KSize(9), KSize(17), KSize(27), KSize(32), KSize(64)),
testing::Values(Ccorr(false), Ccorr(true))));
//////////////////////////////////////////////////////////////////////
// CopyMakeBorder
////////////////////////////////////////////////////////////////////////////////
// MatchTemplate_8U
GPU_PERF_TEST(CopyMakeBorder, cv::gpu::DeviceInfo, cv::Size, perf::MatType, BorderMode)
CV_ENUM(TemplateMethod, cv::TM_SQDIFF, cv::TM_SQDIFF_NORMED, cv::TM_CCORR, cv::TM_CCORR_NORMED, cv::TM_CCOEFF, cv::TM_CCOEFF_NORMED)
#define ALL_TEMPLATE_METHODS testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_SQDIFF_NORMED), TemplateMethod(cv::TM_CCORR), TemplateMethod(cv::TM_CCORR_NORMED), TemplateMethod(cv::TM_CCOEFF), TemplateMethod(cv::TM_CCOEFF_NORMED))
IMPLEMENT_PARAM_CLASS(TemplateSize, cv::Size)
GPU_PERF_TEST(MatchTemplate_8U, cv::gpu::DeviceInfo, cv::Size, TemplateSize, Channels, TemplateMethod)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int borderType = GET_PARAM(3);
cv::Size templ_size = GET_PARAM(2);
int cn = GET_PARAM(3);
int method = GET_PARAM(4);
cv::Mat image_host(size, CV_MAKE_TYPE(CV_8U, cn));
fill(image_host, 0, 255);
cv::Mat templ_host(templ_size, CV_MAKE_TYPE(CV_8U, cn));
fill(templ_host, 0, 255);
cv::gpu::GpuMat image(image_host);
cv::gpu::GpuMat templ(templ_host);
cv::gpu::GpuMat dst;
cv::gpu::matchTemplate(image, templ, dst, method);
TEST_CYCLE()
{
cv::gpu::matchTemplate(image, templ, dst, method);
}
};
INSTANTIATE_TEST_CASE_P(ImgProc, MatchTemplate_8U, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16)), TemplateSize(cv::Size(30, 30))),
testing::Values(Channels(1), Channels(3), Channels(4)),
ALL_TEMPLATE_METHODS));
////////////////////////////////////////////////////////////////////////////////
// MatchTemplate_32F
GPU_PERF_TEST(MatchTemplate_32F, cv::gpu::DeviceInfo, cv::Size, TemplateSize, Channels, TemplateMethod)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
cv::Size size = GET_PARAM(1);
cv::Size templ_size = GET_PARAM(2);
int cn = GET_PARAM(3);
int method = GET_PARAM(4);
declare.in(src_host, WARMUP_RNG);
cv::Mat image_host(size, CV_MAKE_TYPE(CV_32F, cn));
fill(image_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::Mat templ_host(templ_size, CV_MAKE_TYPE(CV_32F, cn));
fill(templ_host, 0, 255);
cv::gpu::GpuMat image(image_host);
cv::gpu::GpuMat templ(templ_host);
cv::gpu::GpuMat dst;
cv::gpu::matchTemplate(image, templ, dst, method);
TEST_CYCLE()
{
cv::gpu::copyMakeBorder(src, dst, 5, 5, 5, 5, borderType);
cv::gpu::matchTemplate(image, templ, dst, method);
}
}
};
INSTANTIATE_TEST_CASE_P(ImgProc, CopyMakeBorder, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_8UC4, CV_32FC1),
testing::Values((int) cv::BORDER_REPLICATE, (int) cv::BORDER_REFLECT, (int) cv::BORDER_WRAP, (int) cv::BORDER_CONSTANT)));
INSTANTIATE_TEST_CASE_P(ImgProc, MatchTemplate_32F, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(TemplateSize(cv::Size(5, 5)), TemplateSize(cv::Size(16, 16)), TemplateSize(cv::Size(30, 30))),
testing::Values(Channels(1), Channels(3), Channels(4)),
testing::Values(TemplateMethod(cv::TM_SQDIFF), TemplateMethod(cv::TM_CCORR))));
//////////////////////////////////////////////////////////////////////
// Integral
// MulSpectrums
GPU_PERF_TEST(Integral, cv::gpu::DeviceInfo, cv::Size)
CV_FLAGS(DftFlags, 0, cv::DFT_INVERSE, cv::DFT_SCALE, cv::DFT_ROWS, cv::DFT_COMPLEX_OUTPUT, cv::DFT_REAL_OUTPUT)
GPU_PERF_TEST(MulSpectrums, cv::gpu::DeviceInfo, cv::Size, DftFlags)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, CV_8UC1);
cv::Size size = GET_PARAM(1);
int flag = GET_PARAM(2);
cv::Mat a_host(size, CV_32FC2);
fill(a_host, 0, 100);
declare.in(src_host, WARMUP_RNG);
cv::Mat b_host(size, CV_32FC2);
fill(b_host, 0, 100);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat a(a_host);
cv::gpu::GpuMat b(b_host);
cv::gpu::GpuMat dst;
cv::gpu::GpuMat buf;
cv::gpu::mulSpectrums(a, b, dst, flag);
TEST_CYCLE()
{
cv::gpu::integralBuffered(src, dst, buf);
cv::gpu::mulSpectrums(a, b, dst, flag);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, Integral, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, MulSpectrums, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(DftFlags(0), DftFlags(cv::DFT_ROWS))));
//////////////////////////////////////////////////////////////////////
// IntegralSqr
// MulAndScaleSpectrums
GPU_PERF_TEST(IntegralSqr, cv::gpu::DeviceInfo, cv::Size)
GPU_PERF_TEST(MulAndScaleSpectrums, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
float scale = 1.f / size.area();
cv::Mat src_host(size, CV_8UC1);
cv::Mat src1_host(size, CV_32FC2);
fill(src1_host, 0, 100);
declare.in(src_host, WARMUP_RNG);
cv::Mat src2_host(size, CV_32FC2);
fill(src2_host, 0, 100);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat src1(src1_host);
cv::gpu::GpuMat src2(src2_host);
cv::gpu::GpuMat dst;
cv::gpu::mulAndScaleSpectrums(src1, src2, dst, cv::DFT_ROWS, scale, false);
TEST_CYCLE()
{
cv::gpu::sqrIntegral(src, dst);
cv::gpu::mulAndScaleSpectrums(src1, src2, dst, cv::DFT_ROWS, scale, false);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, IntegralSqr, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, MulAndScaleSpectrums, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
//////////////////////////////////////////////////////////////////////
// ColumnSum
// Dft
GPU_PERF_TEST(ColumnSum, cv::gpu::DeviceInfo, cv::Size)
GPU_PERF_TEST(Dft, cv::gpu::DeviceInfo, cv::Size, DftFlags)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, CV_32FC1);
cv::Size size = GET_PARAM(1);
int flag = GET_PARAM(2);
declare.in(src_host, WARMUP_RNG);
cv::Mat src_host(size, CV_32FC2);
fill(src_host, 0, 100);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::dft(src, dst, size, flag);
declare.time(2.0);
TEST_CYCLE()
{
cv::gpu::columnSum(src, dst);
cv::gpu::dft(src, dst, size, flag);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, ColumnSum, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, Dft, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(DftFlags(0), DftFlags(cv::DFT_ROWS), DftFlags(cv::DFT_INVERSE))));
//////////////////////////////////////////////////////////////////////
// CornerHarris
GPU_PERF_TEST(CornerHarris, cv::gpu::DeviceInfo, perf::MatType)
IMPLEMENT_PARAM_CLASS(BlockSize, int)
IMPLEMENT_PARAM_CLASS(ApertureSize, int)
GPU_PERF_TEST(CornerHarris, cv::gpu::DeviceInfo, MatType, BorderMode, BlockSize, ApertureSize)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
int type = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
int type = GET_PARAM(1);
int borderType = GET_PARAM(2);
int blockSize = GET_PARAM(3);
int apertureSize = GET_PARAM(4);
cv::Mat img = readImage("gpu/stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
......@@ -616,31 +858,38 @@ GPU_PERF_TEST(CornerHarris, cv::gpu::DeviceInfo, perf::MatType)
cv::gpu::GpuMat dst;
cv::gpu::GpuMat Dx;
cv::gpu::GpuMat Dy;
cv::gpu::GpuMat buf;
int blockSize = 3;
int ksize = 7;
double k = 0.5;
cv::gpu::cornerHarris(src, dst, Dx, Dy, buf, blockSize, apertureSize, k, borderType);
TEST_CYCLE()
{
cv::gpu::cornerHarris(src, dst, Dx, Dy, blockSize, ksize, k);
cv::gpu::cornerHarris(src, dst, Dx, Dy, buf, blockSize, apertureSize, k, borderType);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, CornerHarris, testing::Combine(
ALL_DEVICES,
testing::Values(CV_8UC1, CV_32FC1)));
ALL_DEVICES,
testing::Values(MatType(CV_8UC1), MatType(CV_32FC1)),
testing::Values(BorderMode(cv::BORDER_REFLECT101), BorderMode(cv::BORDER_REPLICATE), BorderMode(cv::BORDER_REFLECT)),
testing::Values(BlockSize(3), BlockSize(5), BlockSize(7)),
testing::Values(ApertureSize(0), ApertureSize(3), ApertureSize(5), ApertureSize(7))));
//////////////////////////////////////////////////////////////////////
// CornerMinEigenVal
GPU_PERF_TEST(CornerMinEigenVal, cv::gpu::DeviceInfo, perf::MatType)
GPU_PERF_TEST(CornerMinEigenVal, cv::gpu::DeviceInfo, MatType, BorderMode, BlockSize, ApertureSize)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
int type = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
int type = GET_PARAM(1);
int borderType = GET_PARAM(2);
int blockSize = GET_PARAM(3);
int apertureSize = GET_PARAM(4);
cv::Mat img = readImage("gpu/stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
......@@ -650,337 +899,344 @@ GPU_PERF_TEST(CornerMinEigenVal, cv::gpu::DeviceInfo, perf::MatType)
cv::gpu::GpuMat dst;
cv::gpu::GpuMat Dx;
cv::gpu::GpuMat Dy;
cv::gpu::GpuMat buf;
int blockSize = 3;
int ksize = 7;
cv::gpu::cornerMinEigenVal(src, dst, Dx, Dy, buf, blockSize, apertureSize, borderType);
TEST_CYCLE()
{
cv::gpu::cornerMinEigenVal(src, dst, Dx, Dy, blockSize, ksize);
cv::gpu::cornerMinEigenVal(src, dst, Dx, Dy, buf, blockSize, apertureSize, borderType);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, CornerMinEigenVal, testing::Combine(
ALL_DEVICES,
testing::Values(CV_8UC1, CV_32FC1)));
ALL_DEVICES,
testing::Values(MatType(CV_8UC1), MatType(CV_32FC1)),
testing::Values(BorderMode(cv::BORDER_REFLECT101), BorderMode(cv::BORDER_REPLICATE), BorderMode(cv::BORDER_REFLECT)),
testing::Values(BlockSize(3), BlockSize(5), BlockSize(7)),
testing::Values(ApertureSize(0), ApertureSize(3), ApertureSize(5), ApertureSize(7))));
//////////////////////////////////////////////////////////////////////
// MulSpectrums
// BuildWarpPlaneMaps
GPU_PERF_TEST(MulSpectrums, cv::gpu::DeviceInfo, cv::Size)
GPU_PERF_TEST(BuildWarpPlaneMaps, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat a_host(size, CV_32FC2);
cv::Mat b_host(size, CV_32FC2);
cv::Size size = GET_PARAM(1);
declare.in(a_host, b_host, WARMUP_RNG);
cv::Mat K = cv::Mat::eye(3, 3, CV_32FC1);
cv::Mat R = cv::Mat::ones(3, 3, CV_32FC1);
cv::Mat T = cv::Mat::zeros(1, 3, CV_32F);
cv::gpu::GpuMat map_x;
cv::gpu::GpuMat map_y;
cv::gpu::GpuMat a(a_host);
cv::gpu::GpuMat b(b_host);
cv::gpu::GpuMat dst;
cv::gpu::buildWarpPlaneMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, T, 1.0, map_x, map_y);
TEST_CYCLE()
{
cv::gpu::mulSpectrums(a, b, dst, 0);
cv::gpu::buildWarpPlaneMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, T, 1.0, map_x, map_y);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, MulSpectrums, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, BuildWarpPlaneMaps, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
//////////////////////////////////////////////////////////////////////
// Dft
// BuildWarpCylindricalMaps
GPU_PERF_TEST(Dft, cv::gpu::DeviceInfo, cv::Size)
GPU_PERF_TEST(BuildWarpCylindricalMaps, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, CV_32FC2);
declare.in(src_host, WARMUP_RNG);
cv::Size size = GET_PARAM(1);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::Mat K = cv::Mat::eye(3, 3, CV_32FC1);
cv::Mat R = cv::Mat::ones(3, 3, CV_32FC1);
cv::gpu::GpuMat map_x;
cv::gpu::GpuMat map_y;
declare.time(2.0);
cv::gpu::buildWarpCylindricalMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, 1.0, map_x, map_y);
TEST_CYCLE()
{
cv::gpu::dft(src, dst, size);
cv::gpu::buildWarpCylindricalMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, 1.0, map_x, map_y);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, Dft, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, BuildWarpCylindricalMaps, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
//////////////////////////////////////////////////////////////////////
// Convolve
// BuildWarpSphericalMaps
GPU_PERF_TEST(Convolve, cv::gpu::DeviceInfo, cv::Size, int, bool)
GPU_PERF_TEST(BuildWarpSphericalMaps, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
int templ_size = GET_PARAM(2);
bool ccorr = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
cv::gpu::GpuMat image = cv::gpu::createContinuous(size, CV_32FC1);
cv::gpu::GpuMat templ = cv::gpu::createContinuous(templ_size, templ_size, CV_32FC1);
image.setTo(cv::Scalar(1.0));
templ.setTo(cv::Scalar(1.0));
cv::Size size = GET_PARAM(1);
cv::gpu::GpuMat dst;
cv::gpu::ConvolveBuf buf;
cv::Mat K = cv::Mat::eye(3, 3, CV_32FC1);
cv::Mat R = cv::Mat::ones(3, 3, CV_32FC1);
cv::gpu::GpuMat map_x;
cv::gpu::GpuMat map_y;
declare.time(2.0);
cv::gpu::buildWarpSphericalMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, 1.0, map_x, map_y);
TEST_CYCLE()
{
cv::gpu::convolve(image, templ, dst, ccorr, buf);
cv::gpu::buildWarpSphericalMaps(size, cv::Rect(0, 0, size.width, size.height), K, R, 1.0, map_x, map_y);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, Convolve, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(3, 9, 27, 32, 64),
testing::Bool()));
INSTANTIATE_TEST_CASE_P(ImgProc, BuildWarpSphericalMaps, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
//////////////////////////////////////////////////////////////////////
// PyrDown
// Rotate
GPU_PERF_TEST(PyrDown, cv::gpu::DeviceInfo, cv::Size, perf::MatType)
GPU_PERF_TEST(Rotate, cv::gpu::DeviceInfo, cv::Size, MatType, Interpolation)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
int interpolation = GET_PARAM(3);
cv::Mat src_host(size, type);
declare.in(src_host, WARMUP_RNG);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::rotate(src, dst, size, 30.0, 0, 0, interpolation);
TEST_CYCLE()
{
cv::gpu::pyrDown(src, dst);
cv::gpu::rotate(src, dst, size, 30.0, 0, 0, interpolation);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, PyrDown, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_8UC4, CV_16SC3, CV_32FC1)));
INSTANTIATE_TEST_CASE_P(ImgProc, Rotate, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC))));
//////////////////////////////////////////////////////////////////////
// PyrUp
// PyrDown
GPU_PERF_TEST(PyrUp, cv::gpu::DeviceInfo, cv::Size, perf::MatType)
GPU_PERF_TEST(PyrDown, cv::gpu::DeviceInfo, cv::Size, MatType)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
declare.in(src_host, WARMUP_RNG);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::pyrDown(src, dst);
TEST_CYCLE()
{
cv::gpu::pyrUp(src, dst);
cv::gpu::pyrDown(src, dst);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, PyrUp, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_8UC4, CV_16SC3, CV_32FC1)));
INSTANTIATE_TEST_CASE_P(ImgProc, PyrDown, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4))));
//////////////////////////////////////////////////////////////////////
// BlendLinear
// PyrUp
GPU_PERF_TEST(BlendLinear, cv::gpu::DeviceInfo, cv::Size, perf::MatType)
GPU_PERF_TEST(PyrUp, cv::gpu::DeviceInfo, cv::Size, MatType)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat img1_host(size, type);
cv::Mat img2_host(size, type);
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
declare.in(img1_host, img2_host, WARMUP_RNG);
cv::Mat src_host(size, type);
fill(src_host, 0, 255);
cv::gpu::GpuMat img1(img1_host);
cv::gpu::GpuMat img2(img2_host);
cv::gpu::GpuMat weights1(size, CV_32FC1, cv::Scalar::all(0.5));
cv::gpu::GpuMat weights2(size, CV_32FC1, cv::Scalar::all(0.5));
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::pyrUp(src, dst);
TEST_CYCLE()
{
cv::gpu::blendLinear(img1, img2, weights1, weights2, dst);
cv::gpu::pyrUp(src, dst);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, BlendLinear, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_32FC1)));
INSTANTIATE_TEST_CASE_P(ImgProc, PyrUp, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4))));
//////////////////////////////////////////////////////////////////////
// AlphaComp
// CvtColor
GPU_PERF_TEST(AlphaComp, cv::gpu::DeviceInfo, cv::Size, perf::MatType, AlphaOp)
GPU_PERF_TEST(CvtColor, cv::gpu::DeviceInfo, cv::Size, MatDepth, CvtColorInfo)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int alpha_op = GET_PARAM(3);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat img1_host(size, type);
cv::Mat img2_host(size, type);
cv::Size size = GET_PARAM(1);
int depth = GET_PARAM(2);
CvtColorInfo info = GET_PARAM(3);
declare.in(img1_host, img2_host, WARMUP_RNG);
cv::Mat src_host(size, CV_MAKETYPE(depth, info.scn));
fill(src_host, 0, 255);
cv::gpu::GpuMat img1(img1_host);
cv::gpu::GpuMat img2(img2_host);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
TEST_CYCLE()
{
cv::gpu::alphaComp(img1, img2, dst, alpha_op);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, AlphaComp, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC4, CV_16UC4, CV_32SC4, CV_32FC4),
testing::Values((int)cv::gpu::ALPHA_OVER, (int)cv::gpu::ALPHA_IN, (int)cv::gpu::ALPHA_OUT, (int)cv::gpu::ALPHA_ATOP, (int)cv::gpu::ALPHA_XOR, (int)cv::gpu::ALPHA_PLUS, (int)cv::gpu::ALPHA_OVER_PREMUL, (int)cv::gpu::ALPHA_IN_PREMUL, (int)cv::gpu::ALPHA_OUT_PREMUL, (int)cv::gpu::ALPHA_ATOP_PREMUL, (int)cv::gpu::ALPHA_XOR_PREMUL, (int)cv::gpu::ALPHA_PLUS_PREMUL, (int)cv::gpu::ALPHA_PREMUL)));
//////////////////////////////////////////////////////////////////////
// Canny
GPU_PERF_TEST_1(Canny, cv::gpu::DeviceInfo)
{
cv::gpu::DeviceInfo devInfo = GetParam();
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat image_host = readImage("perf/1280x1024.jpg", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(image_host.empty());
cv::gpu::GpuMat image(image_host);
cv::gpu::GpuMat dst;
cv::gpu::CannyBuf buf;
cv::gpu::cvtColor(src, dst, info.code, info.dcn);
TEST_CYCLE()
{
cv::gpu::Canny(image, buf, dst, 50.0, 100.0);
cv::gpu::cvtColor(src, dst, info.code, info.dcn);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, Canny, ALL_DEVICES);
INSTANTIATE_TEST_CASE_P(ImgProc, CvtColor, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatDepth(CV_8U), MatDepth(CV_16U), MatDepth(CV_32F)),
testing::Values(CvtColorInfo(4, 4, cv::COLOR_RGBA2BGRA),
CvtColorInfo(4, 1, cv::COLOR_BGRA2GRAY),
CvtColorInfo(1, 4, cv::COLOR_GRAY2BGRA),
CvtColorInfo(3, 3, cv::COLOR_BGR2XYZ),
CvtColorInfo(3, 3, cv::COLOR_XYZ2BGR),
CvtColorInfo(3, 3, cv::COLOR_BGR2YCrCb),
CvtColorInfo(3, 3, cv::COLOR_YCrCb2BGR),
CvtColorInfo(3, 3, cv::COLOR_BGR2YUV),
CvtColorInfo(3, 3, cv::COLOR_YUV2BGR),
CvtColorInfo(3, 3, cv::COLOR_BGR2HSV),
CvtColorInfo(3, 3, cv::COLOR_HSV2BGR),
CvtColorInfo(3, 3, cv::COLOR_BGR2HLS),
CvtColorInfo(3, 3, cv::COLOR_HLS2BGR))));
//////////////////////////////////////////////////////////////////////
// CalcHist
// SwapChannels
GPU_PERF_TEST(CalcHist, cv::gpu::DeviceInfo, cv::Size)
GPU_PERF_TEST(SwapChannels, cv::gpu::DeviceInfo, cv::Size)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, CV_8UC1);
cv::Size size = GET_PARAM(1);
declare.in(src_host, WARMUP_RNG);
cv::Mat src_host(size, CV_8UC4);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat hist;
cv::gpu::GpuMat buf;
const int dstOrder[] = {2, 1, 0, 3};
cv::gpu::swapChannels(src, dstOrder);
TEST_CYCLE()
{
cv::gpu::calcHist(src, hist, buf);
cv::gpu::swapChannels(src, dstOrder);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, CalcHist, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, SwapChannels, testing::Combine(ALL_DEVICES, GPU_TYPICAL_MAT_SIZES));
//////////////////////////////////////////////////////////////////////
// EqualizeHist
// AlphaComp
GPU_PERF_TEST(EqualizeHist, cv::gpu::DeviceInfo, cv::Size)
CV_ENUM(AlphaOp, cv::gpu::ALPHA_OVER, cv::gpu::ALPHA_IN, cv::gpu::ALPHA_OUT, cv::gpu::ALPHA_ATOP, cv::gpu::ALPHA_XOR, cv::gpu::ALPHA_PLUS, cv::gpu::ALPHA_OVER_PREMUL, cv::gpu::ALPHA_IN_PREMUL, cv::gpu::ALPHA_OUT_PREMUL, cv::gpu::ALPHA_ATOP_PREMUL, cv::gpu::ALPHA_XOR_PREMUL, cv::gpu::ALPHA_PLUS_PREMUL, cv::gpu::ALPHA_PREMUL)
GPU_PERF_TEST(AlphaComp, cv::gpu::DeviceInfo, cv::Size, MatType, AlphaOp)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::Size size = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, CV_8UC1);
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
int alpha_op = GET_PARAM(3);
declare.in(src_host, WARMUP_RNG);
cv::Mat img1_host(size, type);
fill(img1_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::Mat img2_host(size, type);
fill(img2_host, 0, 255);
cv::gpu::GpuMat img1(img1_host);
cv::gpu::GpuMat img2(img2_host);
cv::gpu::GpuMat dst;
cv::gpu::GpuMat hist;
cv::gpu::GpuMat buf;
cv::gpu::alphaComp(img1, img2, dst, alpha_op);
TEST_CYCLE()
{
cv::gpu::equalizeHist(src, dst, hist, buf);
cv::gpu::alphaComp(img1, img2, dst, alpha_op);
}
}
INSTANTIATE_TEST_CASE_P(ImgProc, EqualizeHist, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES));
INSTANTIATE_TEST_CASE_P(ImgProc, AlphaComp, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC4), MatType(CV_16UC4), MatType(CV_32SC4), MatType(CV_32FC4)),
testing::Values(AlphaOp(cv::gpu::ALPHA_OVER),
AlphaOp(cv::gpu::ALPHA_IN),
AlphaOp(cv::gpu::ALPHA_OUT),
AlphaOp(cv::gpu::ALPHA_ATOP),
AlphaOp(cv::gpu::ALPHA_XOR),
AlphaOp(cv::gpu::ALPHA_PLUS),
AlphaOp(cv::gpu::ALPHA_OVER_PREMUL),
AlphaOp(cv::gpu::ALPHA_IN_PREMUL),
AlphaOp(cv::gpu::ALPHA_OUT_PREMUL),
AlphaOp(cv::gpu::ALPHA_ATOP_PREMUL),
AlphaOp(cv::gpu::ALPHA_XOR_PREMUL),
AlphaOp(cv::gpu::ALPHA_PLUS_PREMUL),
AlphaOp(cv::gpu::ALPHA_PREMUL))));
//////////////////////////////////////////////////////////////////////
// ImagePyramid
GPU_PERF_TEST(ImagePyramid_build, cv::gpu::DeviceInfo, cv::Size, perf::MatType)
GPU_PERF_TEST(ImagePyramid_build, cv::gpu::DeviceInfo, cv::Size, MatType)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
declare.in(src_host, WARMUP_RNG);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::ImagePyramid pyr;
pyr.build(src, 5);
TEST_CYCLE()
{
pyr.build(src, 5);
......@@ -988,27 +1244,30 @@ GPU_PERF_TEST(ImagePyramid_build, cv::gpu::DeviceInfo, cv::Size, perf::MatType)
}
INSTANTIATE_TEST_CASE_P(ImgProc, ImagePyramid_build, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32FC1, CV_32FC3, CV_32FC4)));
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4))));
GPU_PERF_TEST(ImagePyramid_getLayer, cv::gpu::DeviceInfo, cv::Size, perf::MatType)
GPU_PERF_TEST(ImagePyramid_getLayer, cv::gpu::DeviceInfo, cv::Size, MatType)
{
cv::gpu::DeviceInfo devInfo = GET_PARAM(0);
cv::gpu::setDevice(devInfo.deviceID());
cv::Size size = GET_PARAM(1);
int type = GET_PARAM(2);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat src_host(size, type);
declare.in(src_host, WARMUP_RNG);
fill(src_host, 0, 255);
cv::gpu::GpuMat src(src_host);
cv::gpu::GpuMat dst;
cv::gpu::ImagePyramid pyr(src, 3);
pyr.getLayer(dst, cv::Size(size.width / 2 + 10, size.height / 2 + 10));
TEST_CYCLE()
{
pyr.getLayer(dst, cv::Size(size.width / 2 + 10, size.height / 2 + 10));
......@@ -1016,8 +1275,10 @@ GPU_PERF_TEST(ImagePyramid_getLayer, cv::gpu::DeviceInfo, cv::Size, perf::MatTyp
}
INSTANTIATE_TEST_CASE_P(ImgProc, ImagePyramid_getLayer, testing::Combine(
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32FC1, CV_32FC3, CV_32FC4)));
ALL_DEVICES,
GPU_TYPICAL_MAT_SIZES,
testing::Values(MatType(CV_8UC1), MatType(CV_8UC3), MatType(CV_8UC4),
MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4),
MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4))));
#endif
modules/gpu/perf/perf_utility.hpp
View file @ 73c152ab
......@@ -3,15 +3,16 @@
void fill(cv::Mat& m, double a, double b);
using perf::MatType;
using perf::MatDepth;
enum {HORIZONTAL_AXIS = 0, VERTICAL_AXIS = 1, BOTH_AXIS = -1};
CV_ENUM(MorphOp, cv::MORPH_ERODE, cv::MORPH_DILATE)
CV_ENUM(BorderMode, cv::BORDER_REFLECT101, cv::BORDER_REPLICATE, cv::BORDER_CONSTANT, cv::BORDER_REFLECT, cv::BORDER_WRAP)
CV_ENUM(FlipCode, HORIZONTAL_AXIS, VERTICAL_AXIS, BOTH_AXIS)
CV_ENUM(Interpolation, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC)
CV_ENUM(MatchMethod, cv::TM_SQDIFF, cv::TM_SQDIFF_NORMED, cv::TM_CCORR, cv::TM_CCORR_NORMED, cv::TM_CCOEFF, cv::TM_CCOEFF_NORMED)
CV_ENUM(NormType, cv::NORM_INF, cv::NORM_L1, cv::NORM_L2)
CV_ENUM(AlphaOp, cv::gpu::ALPHA_OVER, cv::gpu::ALPHA_IN, cv::gpu::ALPHA_OUT, cv::gpu::ALPHA_ATOP, cv::gpu::ALPHA_XOR, cv::gpu::ALPHA_PLUS, cv::gpu::ALPHA_OVER_PREMUL, cv::gpu::ALPHA_IN_PREMUL, cv::gpu::ALPHA_OUT_PREMUL, cv::gpu::ALPHA_ATOP_PREMUL, cv::gpu::ALPHA_XOR_PREMUL, cv::gpu::ALPHA_PLUS_PREMUL, cv::gpu::ALPHA_PREMUL)
CV_ENUM(Interpolation, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC, cv::INTER_AREA)
CV_ENUM(NormType, cv::NORM_INF, cv::NORM_L1, cv::NORM_L2, cv::NORM_HAMMING)
struct CvtColorInfo
{
......@@ -24,6 +25,22 @@ struct CvtColorInfo
void PrintTo(const CvtColorInfo& info, std::ostream* os);
#define IMPLEMENT_PARAM_CLASS(name, type) \
class name \
{ \
public: \
name ( type arg = type ()) : val_(arg) {} \
operator type () const {return val_;} \
private: \
type val_; \
}; \
inline void PrintTo( name param, std::ostream* os) \
{ \
*os << #name << " = " << testing::PrintToString(static_cast< type >(param)); \
}
IMPLEMENT_PARAM_CLASS(Channels, int)
namespace cv { namespace gpu
{
void PrintTo(const cv::gpu::DeviceInfo& info, std::ostream* os);
......@@ -55,8 +72,6 @@ namespace cv { namespace gpu
cv::Mat readImage(const std::string& fileName, int flags = cv::IMREAD_COLOR);
bool supportFeature(const cv::gpu::DeviceInfo& info, cv::gpu::FeatureSet feature);
const std::vector<cv::gpu::DeviceInfo>& devices();
std::vector<cv::gpu::DeviceInfo> devices(cv::gpu::FeatureSet feature);
......
modules/gpu/src/cuda/resize.cu
View file @ 73c152ab
......@@ -46,6 +46,7 @@
#include "opencv2/gpu/device/vec_math.hpp"
#include "opencv2/gpu/device/saturate_cast.hpp"
#include "opencv2/gpu/device/filters.hpp"
# include <cfloat>
namespace cv { namespace gpu { namespace device
{
......@@ -65,6 +66,17 @@ namespace cv { namespace gpu { namespace device
}
}
template <typename Ptr2D, typename T> __global__ void resize_area(const Ptr2D src, float fx, float fy, DevMem2D_<T> dst)
{
const int x = blockDim.x * blockIdx.x + threadIdx.x;
const int y = blockDim.y * blockIdx.y + threadIdx.y;
if (x < dst.cols && y < dst.rows)
{
dst(y, x) = saturate_cast<T>(src(y, x));
}
}
template <template <typename> class Filter, typename T> struct ResizeDispatcherStream
{
static void call(DevMem2D_<T> src, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream)
......@@ -74,13 +86,47 @@ namespace cv { namespace gpu { namespace device
BrdReplicate<T> brd(src.rows, src.cols);
BorderReader< PtrStep<T>, BrdReplicate<T> > brdSrc(src, brd);
Filter< BorderReader< PtrStep<T>, BrdReplicate<T> > > filteredSrc(brdSrc);
Filter< BorderReader< PtrStep<T>, BrdReplicate<T> > > filteredSrc(brdSrc, fx, fy);
resize<<<grid, block, 0, stream>>>(filteredSrc, fx, fy, dst);
cudaSafeCall( cudaGetLastError() );
}
};
template <typename T> struct ResizeDispatcherStream<AreaFilter, T>
{
static void call(DevMem2D_<T> src, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream)
{
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
BrdConstant<T> brd(src.rows, src.cols);
BorderReader< PtrStep<T>, BrdConstant<T> > brdSrc(src, brd);
AreaFilter< BorderReader< PtrStep<T>, BrdConstant<T> > > filteredSrc(brdSrc, fx, fy);
resize_area<<<grid, block, 0, stream>>>(filteredSrc, fx, fy, dst);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <typename T> struct ResizeDispatcherStream<IntegerAreaFilter, T>
{
static void call(DevMem2D_<T> src, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream)
{
dim3 block(32, 8);
dim3 grid(divUp(dst.cols, block.x), divUp(dst.rows, block.y));
BrdConstant<T> brd(src.rows, src.cols);
BorderReader< PtrStep<T>, BrdConstant<T> > brdSrc(src, brd);
IntegerAreaFilter< BorderReader< PtrStep<T>, BrdConstant<T> > > filteredSrc(brdSrc, fx, fy);
resize_area<<<grid, block, 0, stream>>>(filteredSrc, fx, fy, dst);
cudaSafeCall( cudaGetLastError() );
if (stream == 0)
cudaSafeCall( cudaDeviceSynchronize() );
}
};
template <template <typename> class Filter, typename T> struct ResizeDispatcherNonStream
{
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, float fx, float fy, DevMem2D_<T> dst)
......@@ -169,15 +215,35 @@ namespace cv { namespace gpu { namespace device
}
};
template <typename T> struct ResizeDispatcher<AreaFilter, T>
{
static void call(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream)
{
int iscale_x = round(fx);
int iscale_y = round(fy);
if( std::abs(fx - iscale_x) < FLT_MIN && std::abs(fy - iscale_y) < FLT_MIN)
ResizeDispatcherStream<IntegerAreaFilter, T>::call(src, fx, fy, dst, stream);
else
ResizeDispatcherStream<AreaFilter, T>::call(src, fx, fy, dst, stream);
}
};
template <typename T> void resize_gpu(DevMem2Db src, DevMem2Db srcWhole, int xoff, int yoff, float fx, float fy,
DevMem2Db dst, int interpolation, cudaStream_t stream)
{
typedef void (*caller_t)(DevMem2D_<T> src, DevMem2D_<T> srcWhole, int xoff, int yoff, float fx, float fy, DevMem2D_<T> dst, cudaStream_t stream);
static const caller_t callers[3] =
static const caller_t callers[4] =
{
ResizeDispatcher<PointFilter, T>::call, ResizeDispatcher<LinearFilter, T>::call, ResizeDispatcher<CubicFilter, T>::call
ResizeDispatcher<PointFilter, T>::call,
ResizeDispatcher<LinearFilter, T>::call,
ResizeDispatcher<CubicFilter, T>::call,
ResizeDispatcher<AreaFilter, T>::call
};
// chenge to linear if area interpolation upscaling
if (interpolation == 3 && (fx <= 1.f || fy <= 1.f))
interpolation = 1;
callers[interpolation](static_cast< DevMem2D_<T> >(src), static_cast< DevMem2D_<T> >(srcWhole), xoff, yoff, fx, fy,
static_cast< DevMem2D_<T> >(dst), stream);
......
modules/gpu/src/opencv2/gpu/device/filters.hpp
View file @ 73c152ab
......@@ -55,7 +55,7 @@ namespace cv { namespace gpu { namespace device
typedef typename Ptr2D::elem_type elem_type;
typedef float index_type;
explicit __host__ __device__ __forceinline__ PointFilter(const Ptr2D& src_) : src(src_) {}
explicit __host__ __device__ __forceinline__ PointFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f) : src(src_) {}
__device__ __forceinline__ elem_type operator ()(float y, float x) const
{
......@@ -70,7 +70,7 @@ namespace cv { namespace gpu { namespace device
typedef typename Ptr2D::elem_type elem_type;
typedef float index_type;
explicit __host__ __device__ __forceinline__ LinearFilter(const Ptr2D& src_) : src(src_) {}
explicit __host__ __device__ __forceinline__ LinearFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f) : src(src_) {}
__device__ __forceinline__ elem_type operator ()(float y, float x) const
{
......@@ -107,7 +107,7 @@ namespace cv { namespace gpu { namespace device
typedef float index_type;
typedef typename TypeVec<float, VecTraits<elem_type>::cn>::vec_type work_type;
explicit __host__ __device__ __forceinline__ CubicFilter(const Ptr2D& src_) : src(src_) {}
explicit __host__ __device__ __forceinline__ CubicFilter(const Ptr2D& src_, float fx = 0.f, float fy = 0.f) : src(src_) {}
static __device__ __forceinline__ float bicubicCoeff(float x_)
{
......@@ -154,6 +154,111 @@ namespace cv { namespace gpu { namespace device
const Ptr2D src;
};
// for integer scaling
template <typename Ptr2D> struct IntegerAreaFilter
{
typedef typename Ptr2D::elem_type elem_type;
typedef float index_type;
explicit __host__ __device__ __forceinline__ IntegerAreaFilter(const Ptr2D& src_, float scale_x_, float scale_y_)
: src(src_), scale_x(scale_x_), scale_y(scale_y_), scale(1.f / (scale_x * scale_y)) {}
__device__ __forceinline__ elem_type operator ()(float y, float x) const
{
float fsx1 = x * scale_x;
float fsx2 = fsx1 + scale_x;
int sx1 = __float2int_ru(fsx1);
int sx2 = __float2int_rd(fsx2);
float fsy1 = y * scale_y;
float fsy2 = fsy1 + scale_y;
int sy1 = __float2int_ru(fsy1);
int sy2 = __float2int_rd(fsy2);
typedef typename TypeVec<float, VecTraits<elem_type>::cn>::vec_type work_type;
work_type out = VecTraits<work_type>::all(0.f);
for(int dy = sy1; dy < sy2; ++dy)
for(int dx = sx1; dx < sx2; ++dx)
{
out = out + src(dy, dx) * scale;
}
return saturate_cast<elem_type>(out);
}
const Ptr2D src;
float scale_x, scale_y ,scale;
};
template <typename Ptr2D> struct AreaFilter
{
typedef typename Ptr2D::elem_type elem_type;
typedef float index_type;
explicit __host__ __device__ __forceinline__ AreaFilter(const Ptr2D& src_, float scale_x_, float scale_y_)
: src(src_), scale_x(scale_x_), scale_y(scale_y_){}
__device__ __forceinline__ elem_type operator ()(float y, float x) const
{
float fsx1 = x * scale_x;
float fsx2 = fsx1 + scale_x;
int sx1 = __float2int_ru(fsx1);
int sx2 = __float2int_rd(fsx2);
float fsy1 = y * scale_y;
float fsy2 = fsy1 + scale_y;
int sy1 = __float2int_ru(fsy1);
int sy2 = __float2int_rd(fsy2);
float scale = 1.f / (fminf(scale_x, src.width - fsx1) * fminf(scale_y, src.height - fsy1));
typedef typename TypeVec<float, VecTraits<elem_type>::cn>::vec_type work_type;
work_type out = VecTraits<work_type>::all(0.f);
for (int dy = sy1; dy < sy2; ++dy)
{
for (int dx = sx1; dx < sx2; ++dx)
out = out + src(dy, dx) * scale;
if (sx1 > fsx1)
out = out + src(dy, (sx1 -1) ) * ((sx1 - fsx1) * scale);
if (sx2 < fsx2)
out = out + src(dy, sx2) * ((fsx2 -sx2) * scale);
}
if (sy1 > fsy1)
for (int dx = sx1; dx < sx2; ++dx)
out = out + src( (sy1 - 1) , dx) * ((sy1 -fsy1) * scale);
if (sy2 < fsy2)
for (int dx = sx1; dx < sx2; ++dx)
out = out + src(sy2, dx) * ((fsy2 -sy2) * scale);
if ((sy1 > fsy1) && (sx1 > fsx1))
out = out + src( (sy1 - 1) , (sx1 - 1)) * ((sy1 -fsy1) * (sx1 -fsx1) * scale);
if ((sy1 > fsy1) && (sx2 < fsx2))
out = out + src( (sy1 - 1) , sx2) * ((sy1 -fsy1) * (fsx2 -sx2) * scale);
if ((sy2 < fsy2) && (sx2 < fsx2))
out = out + src(sy2, sx2) * ((fsy2 -sy2) * (fsx2 -sx2) * scale);
if ((sy2 < fsy2) && (sx1 > fsx1))
out = out + src(sy2, (sx1 - 1)) * ((fsy2 -sy2) * (sx1 -fsx1) * scale);
return saturate_cast<elem_type>(out);
}
const Ptr2D src;
float scale_x, scale_y;
int width, haight;
};
}}} // namespace cv { namespace gpu { namespace device
#endif // __OPENCV_GPU_FILTERS_HPP__
modules/gpu/src/opencv2/gpu/device/vec_traits.hpp
View file @ 73c152ab
......@@ -221,7 +221,7 @@ namespace cv { namespace gpu { namespace device
template<> struct VecTraits<char>
{
typedef char elem_type;
typedef char elem_type;
enum {cn=1};
static __device__ __host__ __forceinline__ char all(char v) {return v;}
static __device__ __host__ __forceinline__ char make(char x) {return x;}
......@@ -229,7 +229,7 @@ namespace cv { namespace gpu { namespace device
};
template<> struct VecTraits<schar>
{
typedef schar elem_type;
typedef schar elem_type;
enum {cn=1};
static __device__ __host__ __forceinline__ schar all(schar v) {return v;}
static __device__ __host__ __forceinline__ schar make(schar x) {return x;}
......
modules/gpu/src/resize.cpp
View file @ 73c152ab
......@@ -61,7 +61,8 @@ namespace cv { namespace gpu { namespace device
void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, double fy, int interpolation, Stream& s)
{
CV_Assert(src.depth() <= CV_32F && src.channels() <= 4);
CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || interpolation == INTER_CUBIC);
CV_Assert(interpolation == INTER_NEAREST || interpolation == INTER_LINEAR
|| interpolation == INTER_CUBIC || interpolation == INTER_AREA);
CV_Assert(!(dsize == Size()) || (fx > 0 && fy > 0));
if (dsize == Size())
......@@ -90,7 +91,7 @@ void cv::gpu::resize(const GpuMat& src, GpuMat& dst, Size dsize, double fx, doub
src.locateROI(wholeSize, ofs);
bool useNpp = (src.type() == CV_8UC1 || src.type() == CV_8UC4);
useNpp = useNpp && (interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || src.type() == CV_8UC4);
useNpp = useNpp && (interpolation == INTER_NEAREST || interpolation == INTER_LINEAR || (src.type() == CV_8UC4 && interpolation != INTER_AREA));
if (useNpp)
{
......
modules/gpu/test/test_resize.cpp
View file @ 73c152ab
......@@ -48,7 +48,8 @@
namespace
{
template <typename T, template <typename> class Interpolator> void resizeImpl(const cv::Mat& src, cv::Mat& dst, double fx, double fy)
template <typename T, template <typename> class Interpolator>
void resizeImpl(const cv::Mat& src, cv::Mat& dst, double fx, double fy)
{
const int cn = src.channels();
......@@ -156,6 +157,51 @@ INSTANTIATE_TEST_CASE_P(GPU_ImgProc, Resize, testing::Combine(
testing::Values(Interpolation(cv::INTER_NEAREST), Interpolation(cv::INTER_LINEAR), Interpolation(cv::INTER_CUBIC)),
WHOLE_SUBMAT));
/////////////////
PARAM_TEST_CASE(ResizeArea, cv::gpu::DeviceInfo, cv::Size, MatType, double, Interpolation, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
cv::Size size;
double coeff;
int interpolation;
int type;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
size = GET_PARAM(1);
type = GET_PARAM(2);
coeff = GET_PARAM(3);
interpolation = GET_PARAM(4);
useRoi = GET_PARAM(5);
cv::gpu::setDevice(devInfo.deviceID());
}
};
TEST_P(ResizeArea, Accuracy)
{
cv::Mat src = randomMat(size, type);
cv::gpu::GpuMat dst = createMat(cv::Size(cv::saturate_cast<int>(src.cols * coeff), cv::saturate_cast<int>(src.rows * coeff)), type, useRoi);
cv::gpu::resize(loadMat(src, useRoi), dst, cv::Size(), coeff, coeff, interpolation);
cv::Mat dst_cpu;
cv::resize(src, dst_cpu, cv::Size(), coeff, coeff, interpolation);
EXPECT_MAT_NEAR(dst_cpu, dst, src.depth() == CV_32F ? 1e-2 : 1.0);
}
INSTANTIATE_TEST_CASE_P(GPU_ImgProc, ResizeArea, testing::Combine(
ALL_DEVICES,
DIFFERENT_SIZES,
testing::Values(MatType(CV_8UC3), MatType(CV_16UC1), MatType(CV_16UC3), MatType(CV_16UC4), MatType(CV_32FC1), MatType(CV_32FC3), MatType(CV_32FC4)),
testing::Values(0.3, 0.5),
testing::Values(Interpolation(cv::INTER_AREA)),
WHOLE_SUBMAT));
///////////////////////////////////////////////////////////////////
// Test NPP
......
modules/gpu/test/utility.hpp
View file @ 73c152ab
......@@ -277,7 +277,7 @@ IMPLEMENT_PARAM_CLASS(Channels, int)
CV_ENUM(NormCode, cv::NORM_INF, cv::NORM_L1, cv::NORM_L2, cv::NORM_TYPE_MASK, cv::NORM_RELATIVE, cv::NORM_MINMAX)
CV_ENUM(Interpolation, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC)
CV_ENUM(Interpolation, cv::INTER_NEAREST, cv::INTER_LINEAR, cv::INTER_CUBIC, cv::INTER_AREA)
CV_ENUM(BorderType, cv::BORDER_REFLECT101, cv::BORDER_REPLICATE, cv::BORDER_CONSTANT, cv::BORDER_REFLECT, cv::BORDER_WRAP)
#define ALL_BORDER_TYPES testing::Values(BorderType(cv::BORDER_REFLECT101), BorderType(cv::BORDER_REPLICATE), BorderType(cv::BORDER_CONSTANT), BorderType(cv::BORDER_REFLECT), BorderType(cv::BORDER_WRAP))
......
modules/imgproc/src/imgwarp.cpp
View file @ 73c152ab
......@@ -878,8 +878,8 @@ struct VResizeLinear
VecOp vecOp;
int x = vecOp((const uchar**)src, (uchar*)dst, (const uchar*)beta, width);
#if CV_ENABLE_UNROLLED
for( ; x <= width - 4; x += 4 )
#if CV_ENABLE_UNROLLED
for( ; x <= width - 4; x += 4 )
{
WT t0, t1;
t0 = S0[x]*b0 + S1[x]*b1;
......@@ -1035,7 +1035,7 @@ struct VResizeLanczos4
CastOp castOp;
VecOp vecOp;
int k, x = vecOp((const uchar**)src, (uchar*)dst, (const uchar*)beta, width);
#if CV_ENABLE_UNROLLED
#if CV_ENABLE_UNROLLED
for( ; x <= width - 4; x += 4 )
{
WT b = beta[0];
......@@ -1130,7 +1130,7 @@ static void resizeGeneric_( const Mat& src, Mat& dst,
if( k0 < ksize )
hresize( srows + k0, rows + k0, ksize - k0, xofs, alpha,
ssize.width, dsize.width, cn, xmin, xmax );
vresize( (const WT**)rows, (T*)(dst.data + dst.step*dy), beta, dsize.width );
vresize( (const WT**)rows, (T*)(dst.data + dst.step*dy), beta, dsize.width );
}
}
......@@ -1163,8 +1163,8 @@ static void resizeAreaFast_( const Mat& src, Mat& dst, const int* ofs, const int
{
const T* S = (const T*)(src.data + src.step*sy0) + xofs[dx];
WT sum = 0;
k=0;
#if CV_ENABLE_UNROLLED
k=0;
#if CV_ENABLE_UNROLLED
for( ; k <= area - 4; k += 4 )
sum += S[ofs[k]] + S[ofs[k+1]] + S[ofs[k+2]] + S[ofs[k+3]];
#endif
......@@ -1272,15 +1272,18 @@ static void resizeArea_( const Mat& src, Mat& dst, const DecimateAlpha* xofs, in
WT beta1 = 1 - beta;
T* D = (T*)(dst.data + dst.step*cur_dy);
if( fabs(beta) < 1e-3 )
{
if(cur_dy >= dsize.height) return;
for( dx = 0; dx < dsize.width; dx++ )
{
D[dx] = saturate_cast<T>(sum[dx] + buf[dx]);
D[dx] = saturate_cast<T>((sum[dx] + buf[dx]) / min(scale_y, src.rows - cur_dy * scale_y));
sum[dx] = buf[dx] = 0;
}
}
else
for( dx = 0; dx < dsize.width; dx++ )
{
D[dx] = saturate_cast<T>(sum[dx] + buf[dx]*beta1);
D[dx] = saturate_cast<T>((sum[dx] + buf[dx]* beta1)/ min(scale_y, src.rows - cur_dy*scale_y));
sum[dx] = buf[dx]*beta;
buf[dx] = 0;
}
......@@ -1329,11 +1332,11 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
resizeGeneric_<
HResizeLinear<uchar, int, short,
INTER_RESIZE_COEF_SCALE,
HResizeLinearVec_8u32s>,
HResizeLinearVec_8u32s>,
VResizeLinear<uchar, int, short,
FixedPtCast<int, uchar, INTER_RESIZE_COEF_BITS*2>,
VResizeLinearVec_32s8u> >,
0,
VResizeLinearVec_32s8u> >,
0,
resizeGeneric_<
HResizeLinear<ushort, float, float, 1,
HResizeLinearVec_16u32f>,
......@@ -1344,7 +1347,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
HResizeLinearVec_16s32f>,
VResizeLinear<short, float, float, Cast<float, short>,
VResizeLinearVec_32f16s> >,
0,
0,
resizeGeneric_<
HResizeLinear<float, float, float, 1,
HResizeLinearVec_32f>,
......@@ -1374,7 +1377,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
HResizeCubic<short, float, float>,
VResizeCubic<short, float, float, Cast<float, short>,
VResizeCubicVec_32f16s> >,
0,
0,
resizeGeneric_<
HResizeCubic<float, float, float>,
VResizeCubic<float, float, float, Cast<float, float>,
......@@ -1396,10 +1399,10 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
resizeGeneric_<HResizeLanczos4<ushort, float, float>,
VResizeLanczos4<ushort, float, float, Cast<float, ushort>,
VResizeNoVec> >,
resizeGeneric_<HResizeLanczos4<short, float, float>,
resizeGeneric_<HResizeLanczos4<short, float, float>,
VResizeLanczos4<short, float, float, Cast<float, short>,
VResizeNoVec> >,
0,
0,
resizeGeneric_<HResizeLanczos4<float, float, float>,
VResizeLanczos4<float, float, float, Cast<float, float>,
VResizeNoVec> >,
......@@ -1412,8 +1415,8 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
static ResizeAreaFastFunc areafast_tab[] =
{
resizeAreaFast_<uchar, int>, 0,
resizeAreaFast_<ushort, float>,
resizeAreaFast_<short, float>,
resizeAreaFast_<ushort, float>,
resizeAreaFast_<short, float>,
0,
resizeAreaFast_<float, float>,
resizeAreaFast_<double, double>,
......@@ -1498,7 +1501,6 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
AutoBuffer<DecimateAlpha> _xofs(ssize.width*2);
DecimateAlpha* xofs = _xofs;
double scale = 1.f/(scale_x*scale_y);
for( dx = 0, k = 0; dx < dsize.width; dx++ )
{
......@@ -1512,7 +1514,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
assert( k < ssize.width*2 );
xofs[k].di = dx*cn;
xofs[k].si = (sx1-1)*cn;
xofs[k++].alpha = (float)((sx1 - fsx1)*scale);
xofs[k++].alpha = (float)((sx1 - fsx1) / min(scale_x, src.cols - fsx1));
}
for( sx = sx1; sx < sx2; sx++ )
......@@ -1520,7 +1522,7 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
assert( k < ssize.width*2 );
xofs[k].di = dx*cn;
xofs[k].si = sx*cn;
xofs[k++].alpha = (float)scale;
xofs[k++].alpha = 1.f / min(scale_x, src.cols - fsx1);
}
if( fsx2 - sx2 > 1e-3 )
......@@ -1528,10 +1530,9 @@ void cv::resize( InputArray _src, OutputArray _dst, Size dsize,
assert( k < ssize.width*2 );
xofs[k].di = dx*cn;
xofs[k].si = sx2*cn;
xofs[k++].alpha = (float)((fsx2 - sx2)*scale);
xofs[k++].alpha = (float)(min(fsx2 - sx2, 1.) / min(scale_x, src.cols - fsx1));
}
}
func( src, dst, xofs, k ,scale_y);
return;
}
......@@ -3480,7 +3481,7 @@ void cvLinearPolar( const CvArr* srcarr, CvArr* dstarr,
if( !CV_ARE_TYPES_EQ( src, dst ))
CV_Error( CV_StsUnmatchedFormats, "" );
ssize.width = src->cols;
ssize.width = src->cols;
ssize.height = src->rows;
dsize.width = dst->cols;
dsize.height = dst->rows;
......
modules/imgproc/test/test_imgwarp.cpp
View file @ 73c152ab
......@@ -1462,6 +1462,49 @@ TEST(Imgproc_fitLine_Mat_3dC1, regression)
ASSERT_EQ(line2.size(), (size_t)6);
}
TEST(Imgproc_resize_area, regression)
{
static ushort input_data[16 * 16] = {
90, 94, 80, 3, 231, 2, 186, 245, 188, 165, 10, 19, 201, 169, 8, 228,
86, 5, 203, 120, 136, 185, 24, 94, 81, 150, 163, 137, 88, 105, 132, 132,
236, 48, 250, 218, 19, 52, 54, 221, 159, 112, 45, 11, 152, 153, 112, 134,
78, 133, 136, 83, 65, 76, 82, 250, 9, 235, 148, 26, 236, 179, 200, 50,
99, 51, 103, 142, 201, 65, 176, 33, 49, 226, 177, 109, 46, 21, 67, 130,
54, 125, 107, 154, 145, 51, 199, 189, 161, 142, 231, 240, 139, 162, 240, 22,
231, 86, 79, 106, 92, 47, 146, 156, 36, 207, 71, 33, 2, 244, 221, 71,
44, 127, 71, 177, 75, 126, 68, 119, 200, 129, 191, 251, 6, 236, 247, 6,
133, 175, 56, 239, 147, 221, 243, 154, 242, 82, 106, 99, 77, 158, 60, 229,
2, 42, 24, 174, 27, 198, 14, 204, 246, 251, 141, 31, 114, 163, 29, 147,
121, 53, 74, 31, 147, 189, 42, 98, 202, 17, 228, 123, 209, 40, 77, 49,
112, 203, 30, 12, 205, 25, 19, 106, 145, 185, 163, 201, 237, 223, 247, 38,
33, 105, 243, 117, 92, 179, 204, 248, 160, 90, 73, 126, 2, 41, 213, 204,
6, 124, 195, 201, 230, 187, 210, 167, 48, 79, 123, 159, 145, 218, 105, 209,
240, 152, 136, 235, 235, 164, 157, 9, 152, 38, 27, 209, 120, 77, 238, 196,
240, 233, 10, 241, 90, 67, 12, 79, 0, 43, 58, 27, 83, 199, 190, 182};
static ushort expected_data[5 * 5] = {
120, 100, 151, 101, 130,
106, 115, 141, 130, 127,
91, 136, 170, 114, 140,
104, 122, 131, 147, 133,
161, 163, 70, 107, 182
};
cv::Mat src(16, 16, CV_16UC1, input_data);
cv::Mat actual;
cv::Mat expected(5,5,CV_16UC1, expected_data);
cv::resize(src, actual, cv::Size(), 0.3, 0.3, INTER_AREA);
ASSERT_EQ(actual.type(), expected.type());
ASSERT_EQ(actual.size(), expected.size());
Mat diff;
absdiff(actual, expected, diff);
Mat one_channel_diff = diff.reshape(1);
ASSERT_EQ(norm(one_channel_diff, cv::NORM_INF),0);
}
//////////////////////////////////////////////////////////////////////////
TEST(Imgproc_Resize, accuracy) { CV_ResizeTest test; test.safe_run(); }
......
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