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Code Packages Releases Wiki Activity

created wrappers for new NPP functions

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removed void integral(const GpuMat& src, GpuMat& sum, GpuMat& sqsum, Stream& stream) - it fails with NPP_NOT_IMPLEMENTED error
updated docs, accuracy and performance tests
This commit is contained in:
Vladislav Vinogradov
2012-02-22 10:00:53 +00:00
parent e426dfc396
commit 2d30480982
37 changed files with 1984 additions and 566 deletions
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modules/gpu/test/test_arithm.cpp
+175 -10
View File
@@ -69,10 +69,10 @@ PARAM_TEST_CASE(ArithmTestBase, cv::gpu::DeviceInfo, MatType, UseRoi)
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat1 = randomMat(rng, size, type, 1, 16, false);
mat2 = randomMat(rng, size, type, 1, 16, false);
mat1 = randomMat(rng, size, type, 5, 16, false);
mat2 = randomMat(rng, size, type, 5, 16, false);
val = cv::Scalar(rng.uniform(0.1, 3.0), rng.uniform(0.1, 3.0), rng.uniform(0.1, 3.0), rng.uniform(0.1, 3.0));
val = cv::Scalar(rng.uniform(1, 3), rng.uniform(1, 3), rng.uniform(1, 3), rng.uniform(1, 3));
}
};
@@ -115,7 +115,8 @@ TEST_P(Add, Scalar)
INSTANTIATE_TEST_CASE_P(Arithm, Add, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_16UC1, CV_32SC1, CV_32FC1),
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4,
CV_32SC1, CV_32SC2, CV_32SC3, CV_32FC1, CV_32FC2, CV_32FC3, CV_32FC4),
USE_ROI));
////////////////////////////////////////////////////////////////////////////////
@@ -157,7 +158,8 @@ TEST_P(Subtract, Scalar)
INSTANTIATE_TEST_CASE_P(Arithm, Subtract, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_16UC1, CV_32SC1, CV_32FC1),
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_16SC1, CV_16SC2, CV_16SC3, CV_16SC4,
CV_32SC1, CV_32SC2, CV_32SC3, CV_32FC1, CV_32FC2, CV_32FC3, CV_32FC4),
USE_ROI));
////////////////////////////////////////////////////////////////////////////////
@@ -199,7 +201,8 @@ TEST_P(Multiply, Scalar)
INSTANTIATE_TEST_CASE_P(Arithm, Multiply, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_16UC1, CV_32SC1, CV_32FC1),
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_16SC1, CV_16SC3, CV_16SC4,
CV_32SC1, CV_32SC3, CV_32FC1, CV_32FC3, CV_32FC4),
USE_ROI));
////////////////////////////////////////////////////////////////////////////////
@@ -220,7 +223,7 @@ TEST_P(Divide, Array)
gpuRes.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 1.0);
EXPECT_MAT_NEAR(dst_gold, dst, mat1.depth() == CV_32F ? 1e-5 : 1);
}
TEST_P(Divide, Scalar)
@@ -236,12 +239,13 @@ TEST_P(Divide, Scalar)
gpuRes.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 1e-5);
EXPECT_MAT_NEAR(dst_gold, dst, mat1.depth() == CV_32F ? 1e-5 : 1);
}
INSTANTIATE_TEST_CASE_P(Arithm, Divide, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_16UC1, CV_32SC1, CV_32FC1),
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_16SC1, CV_16SC3, CV_16SC4,
CV_32SC1, CV_32SC3, CV_32FC1, CV_32FC3, CV_32FC4),
USE_ROI));
////////////////////////////////////////////////////////////////////////////////
@@ -312,6 +316,83 @@ INSTANTIATE_TEST_CASE_P(Arithm, Absdiff, Combine(
Values(CV_8UC1, CV_16UC1, CV_32SC1, CV_32FC1),
USE_ROI));
////////////////////////////////////////////////////////////////////////////////
// abs
struct Abs : ArithmTestBase {};
TEST_P(Abs, Array)
{
cv::Mat dst_gold = cv::abs(mat1);
cv::Mat dst;
cv::gpu::GpuMat gpuRes;
cv::gpu::abs(loadMat(mat1, useRoi), gpuRes);
gpuRes.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(Arithm, Abs, Combine(
ALL_DEVICES,
Values(CV_16SC1, CV_32FC1),
USE_ROI));
////////////////////////////////////////////////////////////////////////////////
// Sqr
struct Sqr : ArithmTestBase {};
TEST_P(Sqr, Array)
{
cv::Mat dst_gold;
cv::multiply(mat1, mat1, dst_gold);
cv::Mat dst;
cv::gpu::GpuMat gpuRes;
cv::gpu::sqr(loadMat(mat1, useRoi), gpuRes);
gpuRes.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(Arithm, Sqr, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_16UC1, CV_16SC1, CV_32FC1),
USE_ROI));
////////////////////////////////////////////////////////////////////////////////
// Sqrt
struct Sqrt : ArithmTestBase {};
TEST_P(Sqrt, Array)
{
cv::Mat dst_gold;
cv::sqrt(mat1, dst_gold);
cv::Mat dst;
cv::gpu::GpuMat gpuRes;
cv::gpu::sqrt(loadMat(mat1, useRoi), gpuRes);
gpuRes.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(Arithm, Sqrt, Combine(
ALL_DEVICES,
Values(MatType(CV_32FC1)),
USE_ROI));
////////////////////////////////////////////////////////////////////////////////
// compare
@@ -513,7 +594,7 @@ TEST_P(Flip, Accuracy)
INSTANTIATE_TEST_CASE_P(Arithm, Flip, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_8UC4),
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32SC1, CV_32SC3, CV_32SC4, CV_32FC1, CV_32FC3, CV_32FC4),
Values((int)FLIP_BOTH, (int)FLIP_X, (int)FLIP_Y),
USE_ROI));
@@ -1329,6 +1410,90 @@ INSTANTIATE_TEST_CASE_P(Arithm, Bitwise, Combine(
ALL_DEVICES,
ALL_TYPES));
PARAM_TEST_CASE(BitwiseScalar, cv::gpu::DeviceInfo, MatType)
{
cv::gpu::DeviceInfo devInfo;
int type;
cv::Size size;
cv::Mat mat;
cv::Scalar sc;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
type = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::RNG& rng = cvtest::TS::ptr()->get_rng();
size = cv::Size(rng.uniform(100, 200), rng.uniform(100, 200));
mat.create(size, type);
for (int i = 0; i < mat.rows; ++i)
{
cv::Mat row(1, static_cast<int>(mat.cols * mat.elemSize()), CV_8U, (void*)mat.ptr(i));
rng.fill(row, cv::RNG::UNIFORM, cv::Scalar(0), cv::Scalar(255));
}
sc = cv::Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
}
};
TEST_P(BitwiseScalar, Or)
{
cv::Mat dst_gold;
cv::bitwise_or(mat, sc, dst_gold);
cv::Mat dst;
cv::gpu::GpuMat dev_dst;
cv::gpu::bitwise_or(loadMat(mat), sc, dev_dst);
dev_dst.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
TEST_P(BitwiseScalar, And)
{
cv::Mat dst_gold;
cv::bitwise_and(mat, sc, dst_gold);
cv::Mat dst;
cv::gpu::GpuMat dev_dst;
cv::gpu::bitwise_and(loadMat(mat), sc, dev_dst);
dev_dst.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
TEST_P(BitwiseScalar, Xor)
{
cv::Mat dst_gold;
cv::bitwise_xor(mat, sc, dst_gold);
cv::Mat dst;
cv::gpu::GpuMat dev_dst;
cv::gpu::bitwise_xor(loadMat(mat), sc, dev_dst);
dev_dst.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(Arithm, BitwiseScalar, Combine(
ALL_DEVICES,
Values(CV_8UC1, CV_8UC3, CV_8UC4, CV_16UC1, CV_16UC3, CV_16UC4, CV_32SC1, CV_32SC3, CV_32SC4)));
//////////////////////////////////////////////////////////////////////////////
// addWeighted
modules/gpu/test/test_imgproc.cpp
+43
View File
@@ -2377,6 +2377,49 @@ INSTANTIATE_TEST_CASE_P(ImgProc, CvtColor, Combine(
Values(CV_8U, CV_16U, CV_32F),
USE_ROI));
///////////////////////////////////////////////////////////////////////////////////////////////////////
// swapChannels
PARAM_TEST_CASE(SwapChannels, cv::gpu::DeviceInfo, UseRoi)
{
cv::gpu::DeviceInfo devInfo;
bool useRoi;
cv::Mat img;
cv::Mat dst_gold;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
useRoi = GET_PARAM(1);
cv::gpu::setDevice(devInfo.deviceID());
cv::Mat imgBase = readImage("stereobm/aloe-L.png");
ASSERT_FALSE(imgBase.empty());
cv::cvtColor(imgBase, img, cv::COLOR_BGR2BGRA);
cv::cvtColor(img, dst_gold, cv::COLOR_BGRA2RGBA);
}
};
TEST_P(SwapChannels, Accuracy)
{
cv::gpu::GpuMat gpuImage = loadMat(img, useRoi);
const int dstOrder[] = {2, 1, 0, 3};
cv::gpu::swapChannels(gpuImage, dstOrder);
cv::Mat dst;
gpuImage.download(dst);
EXPECT_MAT_NEAR(dst_gold, dst, 0.0);
}
INSTANTIATE_TEST_CASE_P(ImgProc, SwapChannels, Combine(ALL_DEVICES, USE_ROI));
///////////////////////////////////////////////////////////////////////////////////////////////////////
// histograms
modules/gpu/test/test_main.cpp
+1 -1
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@@ -136,7 +136,7 @@ int main(int argc, char** argv)
#else // HAVE_CUDA
int main(int argc, char** argv)
int main()
{
printf("OpenCV was built without CUDA support\n");
return 0;