opencv/modules/nonfree/test/test_surf.ocl.cpp

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//    Peng Xiao, pengxiao@multicorewareinc.com
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#include "test_precomp.hpp"

#ifdef HAVE_OPENCV_OCL

using namespace std;
using std::tr1::get;

static bool keyPointsEquals(const cv::KeyPoint& p1, const cv::KeyPoint& p2)
{
    const double maxPtDif = 0.1;
    const double maxSizeDif = 0.1;
    const double maxAngleDif = 0.1;
    const double maxResponseDif = 0.01;

    double dist = cv::norm(p1.pt - p2.pt);

    if (dist < maxPtDif &&
        fabs(p1.size - p2.size) < maxSizeDif &&
        abs(p1.angle - p2.angle) < maxAngleDif &&
        abs(p1.response - p2.response) < maxResponseDif &&
        p1.octave == p2.octave &&
        p1.class_id == p2.class_id)
    {
        return true;
    }

    return false;
}

static int getMatchedPointsCount(std::vector<cv::KeyPoint>& gold, std::vector<cv::KeyPoint>& actual)
{
    std::sort(actual.begin(), actual.end(), perf::comparators::KeypointGreater());
    std::sort(gold.begin(), gold.end(), perf::comparators::KeypointGreater());

    int validCount = 0;

    for (size_t i = 0; i < gold.size(); ++i)
    {
        const cv::KeyPoint& p1 = gold[i];
        const cv::KeyPoint& p2 = actual[i];

        if (keyPointsEquals(p1, p2))
            ++validCount;
    }

    return validCount;
}

static int getMatchedPointsCount(const std::vector<cv::KeyPoint>& keypoints1, const std::vector<cv::KeyPoint>& keypoints2, const std::vector<cv::DMatch>& matches)
{
    int validCount = 0;

    for (size_t i = 0; i < matches.size(); ++i)
    {
        const cv::DMatch& m = matches[i];

        const cv::KeyPoint& p1 = keypoints1[m.queryIdx];
        const cv::KeyPoint& p2 = keypoints2[m.trainIdx];

        if (keyPointsEquals(p1, p2))
            ++validCount;
    }

    return validCount;
}

#define PARAM_TEST_CASE(name, ...) struct name : testing::TestWithParam< std::tr1::tuple< __VA_ARGS__ > >
#define IMPLEMENT_PARAM_CLASS(name, type) \
    namespace { class name { \
    public: \
        name ( type arg = type ()) : val_(arg) {} \
        operator type () const {return val_;} \
    private: \
        type val_; \
    }; \
    inline void PrintTo( name param, std::ostream* os) {*os << #name <<  "=" << testing::PrintToString(static_cast< type >(param));}}

IMPLEMENT_PARAM_CLASS(HessianThreshold, double)
IMPLEMENT_PARAM_CLASS(Octaves, int)
IMPLEMENT_PARAM_CLASS(OctaveLayers, int)
IMPLEMENT_PARAM_CLASS(Extended, bool)
IMPLEMENT_PARAM_CLASS(Upright, bool)

PARAM_TEST_CASE(SURF, HessianThreshold, Octaves, OctaveLayers, Extended, Upright)
{
    double hessianThreshold;
    int nOctaves;
    int nOctaveLayers;
    bool extended;
    bool upright;

    virtual void SetUp()
    {
        hessianThreshold = get<0>(GetParam());
        nOctaves = get<1>(GetParam());
        nOctaveLayers = get<2>(GetParam());
        extended = get<3>(GetParam());
        upright = get<4>(GetParam());
    }
};

TEST_P(SURF, DISABLED_Detector)
{
    cv::Mat image  = cv::imread(string(cvtest::TS::ptr()->get_data_path()) + "shared/fruits.png", cv::IMREAD_GRAYSCALE);
    ASSERT_FALSE(image.empty());

    cv::ocl::SURF_OCL surf;
    surf.hessianThreshold = static_cast<float>(hessianThreshold);
    surf.nOctaves = nOctaves;
    surf.nOctaveLayers = nOctaveLayers;
    surf.extended = extended;
    surf.upright = upright;
    surf.keypointsRatio = 0.05f;

    std::vector<cv::KeyPoint> keypoints;
    surf(cv::ocl::oclMat(image), cv::ocl::oclMat(), keypoints);

    cv::SURF surf_gold;
    surf_gold.hessianThreshold = hessianThreshold;
    surf_gold.nOctaves = nOctaves;
    surf_gold.nOctaveLayers = nOctaveLayers;
    surf_gold.extended = extended;
    surf_gold.upright = upright;

    std::vector<cv::KeyPoint> keypoints_gold;
    surf_gold(image, cv::noArray(), keypoints_gold);

    ASSERT_EQ(keypoints_gold.size(), keypoints.size());
    int matchedCount = getMatchedPointsCount(keypoints_gold, keypoints);
    double matchedRatio = static_cast<double>(matchedCount) / keypoints_gold.size();

    EXPECT_GT(matchedRatio, 0.99);
}

TEST_P(SURF, DISABLED_Descriptor)
{
    cv::Mat image  = cv::imread(string(cvtest::TS::ptr()->get_data_path()) + "shared/fruits.png", cv::IMREAD_GRAYSCALE);
    ASSERT_FALSE(image.empty());

    cv::ocl::SURF_OCL surf;
    surf.hessianThreshold = static_cast<float>(hessianThreshold);
    surf.nOctaves = nOctaves;
    surf.nOctaveLayers = nOctaveLayers;
    surf.extended = extended;
    surf.upright = upright;
    surf.keypointsRatio = 0.05f;

    cv::SURF surf_gold;
    surf_gold.hessianThreshold = hessianThreshold;
    surf_gold.nOctaves = nOctaves;
    surf_gold.nOctaveLayers = nOctaveLayers;
    surf_gold.extended = extended;
    surf_gold.upright = upright;

    std::vector<cv::KeyPoint> keypoints;
    surf_gold(image, cv::noArray(), keypoints);

    cv::ocl::oclMat descriptors;
    surf(cv::ocl::oclMat(image), cv::ocl::oclMat(), keypoints, descriptors, true);

    cv::Mat descriptors_gold;
    surf_gold(image, cv::noArray(), keypoints, descriptors_gold, true);

    cv::BFMatcher matcher(cv::NORM_L2);
    std::vector<cv::DMatch> matches;
    matcher.match(descriptors_gold, cv::Mat(descriptors), matches);

    int matchedCount = getMatchedPointsCount(keypoints, keypoints, matches);
    double matchedRatio = static_cast<double>(matchedCount) / keypoints.size();

    EXPECT_GT(matchedRatio, 0.35);
}

INSTANTIATE_TEST_CASE_P(OCL_Features2D, SURF, testing::Combine(
    testing::Values(HessianThreshold(500.0), HessianThreshold(1000.0)),
    testing::Values(Octaves(3), Octaves(4)),
    testing::Values(OctaveLayers(2), OctaveLayers(3)),
    testing::Values(Extended(false), Extended(true)),
    testing::Values(Upright(false), Upright(true))));

#endif // HAVE_OPENCV_OCL