ported GPU test to GTest framework
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modules/gpu/test/test_operator_convert_to.cpp
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110
modules/gpu/test/test_operator_convert_to.cpp
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// For Open Source Computer Vision Library
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//M*/
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#include "test_precomp.hpp"
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#include <fstream>
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#include <iterator>
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#include <numeric>
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using namespace cv;
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using namespace std;
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using namespace gpu;
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class CV_GpuMatOpConvertToTest : public cvtest::BaseTest
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{
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public:
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CV_GpuMatOpConvertToTest() {}
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~CV_GpuMatOpConvertToTest() {}
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protected:
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void run(int);
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};
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void CV_GpuMatOpConvertToTest::run(int /* start_from */)
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{
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const Size img_size(67, 35);
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const char* types_str[] = {"CV_8U", "CV_8S", "CV_16U", "CV_16S", "CV_32S", "CV_32F", "CV_64F"};
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bool passed = true;
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int lastType = CV_32F;
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if (TargetArchs::builtWith(NATIVE_DOUBLE) && DeviceInfo().supports(NATIVE_DOUBLE))
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lastType = CV_64F;
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for (int i = 0; i <= lastType && passed; ++i)
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{
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for (int j = 0; j <= lastType && passed; ++j)
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{
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for (int c = 1; c < 5 && passed; ++c)
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{
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const int src_type = CV_MAKETYPE(i, c);
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const int dst_type = j;
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cv::RNG& rng = ts->get_rng();
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Mat cpumatsrc(img_size, src_type);
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rng.fill(cpumatsrc, RNG::UNIFORM, Scalar::all(0), Scalar::all(300));
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GpuMat gpumatsrc(cpumatsrc);
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Mat cpumatdst;
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GpuMat gpumatdst;
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cpumatsrc.convertTo(cpumatdst, dst_type, 0.5, 3.0);
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gpumatsrc.convertTo(gpumatdst, dst_type, 0.5, 3.0);
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double r = norm(cpumatdst, gpumatdst, NORM_INF);
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if (r > 1)
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{
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ts->printf(cvtest::TS::LOG,
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"\nFAILED: SRC_TYPE=%sC%d DST_TYPE=%s NORM = %f\n",
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types_str[i], c, types_str[j], r);
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passed = false;
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}
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}
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}
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}
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ts->set_failed_test_info(passed ? cvtest::TS::OK : cvtest::TS::FAIL_GENERIC);
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}
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TEST(GpuMat_convertTo, accuracy) { CV_GpuMatOpConvertToTest test; test.safe_run(); }
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