wehub-resource-sync
39 lines
1.3 KiB
C++
39 lines
1.3 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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// KNN brute-force findNearest: dominated by the per-sample L2 distance reduction.
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typedef TestBaseWithParam< tuple<int, int, int> > KNNFindNearest; // (train samples, dims, K)
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PERF_TEST_P(KNNFindNearest, brute_force, testing::Values(
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make_tuple(5000, 128, 5),
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make_tuple(10000, 64, 10)))
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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 K = get<2>(GetParam());
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const int nquery = 2000;
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Mat train(nsamples, dims, CV_32F), responses(nsamples, 1, CV_32F), query(nquery, dims, CV_32F);
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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<float>(i) = (float)(i & 1);
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Ptr<KNearest> knn = KNearest::create();
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knn->setAlgorithmType(KNearest::BRUTE_FORCE);
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knn->setDefaultK(K);
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knn->train(train, ROW_SAMPLE, responses);
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Mat results, neighbors, dists;
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TEST_CYCLE() knn->findNearest(query, K, results, neighbors, dists);
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SANITY_CHECK_NOTHING();
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}
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}} // namespace
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