wehub-resource-sync
49 lines
1.7 KiB
C++
49 lines
1.7 KiB
C++
// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#include "perf_precomp.hpp"
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namespace opencv_test { namespace {
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// SVM::predict is dominated by the per-feature kernel reduction over the support
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// vectors: calc_non_rbf_base (LINEAR/POLY/SIGMOID dot product), calc_rbf
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// (squared distance), calc_intersec (min-sum) and calc_chi2. Train data is kept
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// non-negative so the INTER and CHI2 kernels stay in their valid domain.
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typedef TestBaseWithParam< tuple<int, int, int> > SVMPredict; // (samples, dims, kernelType)
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PERF_TEST_P(SVMPredict, kernels, testing::Combine(
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testing::Values(1500),
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testing::Values(512),
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testing::Values((int)SVM::RBF, (int)SVM::POLY, (int)SVM::INTER, (int)SVM::CHI2)))
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{
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const int nsamples = get<0>(GetParam());
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const int dims = get<1>(GetParam());
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const int kernel = get<2>(GetParam());
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const int nquery = 1000;
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Mat train(nsamples, dims, CV_32F), query(nquery, dims, CV_32F);
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Mat responses(nsamples, 1, CV_32S);
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RNG& rng = theRNG();
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rng.fill(train, RNG::UNIFORM, 0.f, 1.f);
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rng.fill(query, RNG::UNIFORM, 0.f, 1.f);
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for (int i = 0; i < nsamples; i++)
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responses.at<int>(i) = i & 1;
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Ptr<SVM> svm = SVM::create();
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svm->setType(SVM::C_SVC);
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svm->setKernel(kernel);
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svm->setC(1);
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svm->setGamma(0.1);
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svm->setDegree(3); // POLY
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svm->setCoef0(1); // POLY
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svm->setTermCriteria(TermCriteria(TermCriteria::MAX_ITER, 1000, 1e-3));
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svm->train(train, ROW_SAMPLE, responses);
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Mat results;
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TEST_CYCLE() svm->predict(query, results);
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SANITY_CHECK_NOTHING();
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}
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}} // namespace
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