Open Source Computer Vision Library https://opencv.org/
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#include "test_precomp.hpp"
#ifdef HAVE_CUDA
namespace opencv_test { namespace {
////////////////////////////////////////////////////////
// Canny
namespace
{
IMPLEMENT_PARAM_CLASS(AppertureSize, int)
IMPLEMENT_PARAM_CLASS(L2gradient, bool)
}
PARAM_TEST_CASE(Canny, cv::cuda::DeviceInfo, AppertureSize, L2gradient, UseRoi)
{
cv::cuda::DeviceInfo devInfo;
int apperture_size;
bool useL2gradient;
bool useRoi;
virtual void SetUp()
{
devInfo = GET_PARAM(0);
apperture_size = GET_PARAM(1);
useL2gradient = GET_PARAM(2);
useRoi = GET_PARAM(3);
cv::cuda::setDevice(devInfo.deviceID());
}
};
CUDA_TEST_P(Canny, Accuracy)
{
cv::Mat img = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
double low_thresh = 50.0;
double high_thresh = 100.0;
cv::Ptr<cv::cuda::CannyEdgeDetector> canny = cv::cuda::createCannyEdgeDetector(low_thresh, high_thresh, apperture_size, useL2gradient);
cv::cuda::GpuMat edges;
canny->detect(loadMat(img, useRoi), edges);
cv::Mat edges_gold;
cv::Canny(img, edges_gold, low_thresh, high_thresh, apperture_size, useL2gradient);
EXPECT_MAT_SIMILAR(edges_gold, edges, 2e-2);
}
class CannyAsyncParallelLoopBody : public cv::ParallelLoopBody
{
public:
CannyAsyncParallelLoopBody(const cv::cuda::GpuMat& d_img_, cv::cuda::GpuMat* edges_, double low_thresh_, double high_thresh_, int apperture_size_, bool useL2gradient_)
: d_img(d_img_), edges(edges_), low_thresh(low_thresh_), high_thresh(high_thresh_), apperture_size(apperture_size_), useL2gradient(useL2gradient_) {}
~CannyAsyncParallelLoopBody() {};
void operator()(const cv::Range& r) const
{
for (int i = r.start; i < r.end; i++) {
cv::cuda::Stream stream;
cv::Ptr<cv::cuda::CannyEdgeDetector> canny = cv::cuda::createCannyEdgeDetector(low_thresh, high_thresh, apperture_size, useL2gradient);
canny->detect(d_img, edges[i], stream);
stream.waitForCompletion();
}
}
protected:
const cv::cuda::GpuMat& d_img;
cv::cuda::GpuMat* edges;
double low_thresh;
double high_thresh;
int apperture_size;
bool useL2gradient;
};
#define NUM_STREAMS 128
CUDA_TEST_P(Canny, Async)
{
if (!supportFeature(devInfo, cv::cuda::FEATURE_SET_COMPUTE_30))
{
throw SkipTestException("CUDA device doesn't support texture objects");
}
else
{
const cv::Mat img = readImage("stereobm/aloe-L.png", cv::IMREAD_GRAYSCALE);
ASSERT_FALSE(img.empty());
const cv::cuda::GpuMat d_img_roi = loadMat(img, useRoi);
double low_thresh = 50.0;
double high_thresh = 100.0;
// Synchronous call
cv::Ptr<cv::cuda::CannyEdgeDetector> canny = cv::cuda::createCannyEdgeDetector(low_thresh, high_thresh, apperture_size, useL2gradient);
cv::cuda::GpuMat edges_gold;
canny->detect(d_img_roi, edges_gold);
// Asynchronous call
cv::cuda::GpuMat edges[NUM_STREAMS];
cv::parallel_for_(cv::Range(0, NUM_STREAMS), CannyAsyncParallelLoopBody(d_img_roi, edges, low_thresh, high_thresh, apperture_size, useL2gradient));
// Compare the results of synchronous call and asynchronous call
for (int i = 0; i < NUM_STREAMS; i++)
EXPECT_MAT_NEAR(edges_gold, edges[i], 0.0);
}
}
INSTANTIATE_TEST_CASE_P(CUDA_ImgProc, Canny, testing::Combine(
ALL_DEVICES,
testing::Values(AppertureSize(3), AppertureSize(5), AppertureSize(7)),
testing::Values(L2gradient(false), L2gradient(true)),
WHOLE_SUBMAT));
}} // namespace
#endif // HAVE_CUDA