OpenCV/opencv/modules/features2d/test/ocl/test_brute_force_matcher.cpp

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#include "../test_precomp.hpp"
#include "cvconfig.h"
#include "opencv2/ts/ocl_test.hpp"

#ifdef HAVE_OPENCL

namespace opencv_test {
namespace ocl {
PARAM_TEST_CASE(BruteForceMatcher, int, int)
{
    int distType;
    int dim;

    int queryDescCount;
    int countFactor;

    Mat query, train;
    UMat uquery, utrain;

    virtual void SetUp()
    {
        distType = GET_PARAM(0);
        dim = GET_PARAM(1);

        queryDescCount = 300; // must be even number because we split train data in some cases in two
        countFactor = 4; // do not change it

        cv::Mat queryBuf, trainBuf;

        // Generate query descriptors randomly.
        // Descriptor vector elements are integer values.
        queryBuf.create(queryDescCount, dim, CV_32SC1);
        rng.fill(queryBuf, cv::RNG::UNIFORM, cv::Scalar::all(0), cv::Scalar::all(3));
        queryBuf.convertTo(queryBuf, CV_32FC1);

        // Generate train descriptors as follows:
        // copy each query descriptor to train set countFactor times
        // and perturb some one element of the copied descriptors in
        // in ascending order. General boundaries of the perturbation
        // are (0.f, 1.f).
        trainBuf.create(queryDescCount * countFactor, dim, CV_32FC1);
        float step = 1.f / countFactor;
        for (int qIdx = 0; qIdx < queryDescCount; qIdx++)
        {
            cv::Mat queryDescriptor = queryBuf.row(qIdx);
            for (int c = 0; c < countFactor; c++)
            {
                int tIdx = qIdx * countFactor + c;
                cv::Mat trainDescriptor = trainBuf.row(tIdx);
                queryDescriptor.copyTo(trainDescriptor);
                int elem = rng(dim);
                float diff = rng.uniform(step * c, step * (c + 1));
                trainDescriptor.at<float>(0, elem) += diff;
            }
        }

        queryBuf.convertTo(query, CV_32F);
        trainBuf.convertTo(train, CV_32F);
        query.copyTo(uquery);
        train.copyTo(utrain);
    }
};

#ifdef __ANDROID__
OCL_TEST_P(BruteForceMatcher, DISABLED_Match_Single)
#else
OCL_TEST_P(BruteForceMatcher, Match_Single)
#endif
{
    BFMatcher matcher(distType);

    std::vector<cv::DMatch> matches;
    matcher.match(uquery, utrain,  matches);

    ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());

    int badCount = 0;
    for (size_t i = 0; i < matches.size(); i++)
    {
        cv::DMatch match = matches[i];
        if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor) || (match.imgIdx != 0))
            badCount++;
    }

    ASSERT_EQ(0, badCount);
}

#ifdef __ANDROID__
OCL_TEST_P(BruteForceMatcher, DISABLED_KnnMatch_2_Single)
#else
OCL_TEST_P(BruteForceMatcher, KnnMatch_2_Single)
#endif
{
    const int knn = 2;

    BFMatcher matcher(distType);

    std::vector< std::vector<cv::DMatch> > matches;
    matcher.knnMatch(uquery, utrain, matches, knn);

    ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());

    int badCount = 0;
    for (size_t i = 0; i < matches.size(); i++)
    {
        if ((int)matches[i].size() != knn)
            badCount++;
        else
        {
            int localBadCount = 0;
            for (int k = 0; k < knn; k++)
            {
                cv::DMatch match = matches[i][k];
                if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor + k) || (match.imgIdx != 0))
                    localBadCount++;
            }
            badCount += localBadCount > 0 ? 1 : 0;
        }
    }

    ASSERT_EQ(0, badCount);
}

#ifdef __ANDROID__
OCL_TEST_P(BruteForceMatcher, DISABLED_RadiusMatch_Single)
#else
OCL_TEST_P(BruteForceMatcher, RadiusMatch_Single)
#endif
{
    float radius = 1.f / countFactor;

    BFMatcher matcher(distType);

    std::vector< std::vector<cv::DMatch> > matches;
    matcher.radiusMatch(uquery, utrain, matches, radius);

    ASSERT_EQ(static_cast<size_t>(queryDescCount), matches.size());

    int badCount = 0;
    for (size_t i = 0; i < matches.size(); i++)
    {
        if ((int)matches[i].size() != 1)
        {
            badCount++;
        }
        else
        {
            cv::DMatch match = matches[i][0];
            if ((match.queryIdx != (int)i) || (match.trainIdx != (int)i * countFactor) || (match.imgIdx != 0))
                badCount++;
        }
    }

    ASSERT_EQ(0, badCount);
}

OCL_INSTANTIATE_TEST_CASE_P(Matcher, BruteForceMatcher, Combine( Values((int)NORM_L1, (int)NORM_L2),
                                                                Values(57, 64, 83, 128, 179, 256, 304) ) );

}//ocl
}//cvtest

#endif //HAVE_OPENCL