Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
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// Intel License Agreement
// For Open Source Computer Vision Library
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#include "test_precomp.hpp"
using namespace cv;
using namespace std;
using namespace gpu;
class CV_GpuMatOpSetToTest : public cvtest::BaseTest
{
public:
CV_GpuMatOpSetToTest();
~CV_GpuMatOpSetToTest() {}
protected:
void run(int);
bool testSetTo(cv::Mat& cpumat, gpu::GpuMat& gpumat, const cv::Mat& cpumask = cv::Mat(), const cv::gpu::GpuMat& gpumask = cv::gpu::GpuMat());
private:
int rows;
int cols;
Scalar s;
};
CV_GpuMatOpSetToTest::CV_GpuMatOpSetToTest()
{
rows = 35;
cols = 67;
s.val[0] = 127.0;
s.val[1] = 127.0;
s.val[2] = 127.0;
s.val[3] = 127.0;
}
bool CV_GpuMatOpSetToTest::testSetTo(cv::Mat& cpumat, gpu::GpuMat& gpumat, const cv::Mat& cpumask, const cv::gpu::GpuMat& gpumask)
{
cpumat.setTo(s, cpumask);
gpumat.setTo(s, gpumask);
double ret = norm(cpumat, gpumat, NORM_INF);
if (ret < std::numeric_limits<double>::epsilon())
return true;
else
{
ts->printf(cvtest::TS::LOG, "\nNorm: %f\n", ret);
return false;
}
}
void CV_GpuMatOpSetToTest::run( int /* start_from */)
{
bool is_test_good = true;
cv::Mat cpumask(rows, cols, CV_8UC1);
cv::RNG& rng = ts->get_rng();
rng.fill(cpumask, RNG::UNIFORM, cv::Scalar::all(0.0), cv::Scalar(1.5));
cv::gpu::GpuMat gpumask(cpumask);
int lastType = CV_32F;
if (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE))
lastType = CV_64F;
for (int i = 0; i <= lastType; i++)
{
for (int cn = 1; cn <= 4; ++cn)
{
int mat_type = CV_MAKETYPE(i, cn);
Mat cpumat(rows, cols, mat_type, Scalar::all(0));
GpuMat gpumat(cpumat);
is_test_good &= testSetTo(cpumat, gpumat, cpumask, gpumask);
}
}
if (is_test_good == true)
ts->set_failed_test_info(cvtest::TS::OK);
else
ts->set_failed_test_info(cvtest::TS::FAIL_GENERIC);
}
TEST(GpuMat_setTo, accuracy) { CV_GpuMatOpSetToTest test; test.safe_run(); }