Open Source Computer Vision Library https://opencv.org/
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/*M///////////////////////////////////////////////////////////////////////////////////////
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#include "test_precomp.hpp"
#include <fstream>
#include <iterator>
#include <numeric>
using namespace cv;
using namespace std;
using namespace gpu;
class CV_GpuMatOpConvertToTest : public cvtest::BaseTest
{
public:
CV_GpuMatOpConvertToTest() {}
~CV_GpuMatOpConvertToTest() {}
protected:
void run(int);
};
void CV_GpuMatOpConvertToTest::run(int /* start_from */)
{
const Size img_size(67, 35);
const char* types_str[] = {"CV_8U", "CV_8S", "CV_16U", "CV_16S", "CV_32S", "CV_32F", "CV_64F"};
bool passed = true;
int lastType = CV_32F;
if (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE))
lastType = CV_64F;
for (int i = 0; i <= lastType && passed; ++i)
{
for (int j = 0; j <= lastType && passed; ++j)
{
for (int c = 1; c < 5 && passed; ++c)
{
const int src_type = CV_MAKETYPE(i, c);
const int dst_type = j;
cv::RNG& rng = ts->get_rng();
Mat cpumatsrc(img_size, src_type);
rng.fill(cpumatsrc, RNG::UNIFORM, Scalar::all(0), Scalar::all(300));
GpuMat gpumatsrc(cpumatsrc);
Mat cpumatdst;
GpuMat gpumatdst;
cpumatsrc.convertTo(cpumatdst, dst_type, 0.5, 3.0);
gpumatsrc.convertTo(gpumatdst, dst_type, 0.5, 3.0);
double r = norm(cpumatdst, gpumatdst, NORM_INF);
if (r > 1)
{
ts->printf(cvtest::TS::LOG,
"\nFAILED: SRC_TYPE=%sC%d DST_TYPE=%s NORM = %f\n",
types_str[i], c, types_str[j], r);
passed = false;
}
}
}
}
ts->set_failed_test_info(passed ? cvtest::TS::OK : cvtest::TS::FAIL_GENERIC);
}
TEST(GpuMat_convertTo, accuracy) { CV_GpuMatOpConvertToTest test; test.safe_run(); }