opencv/modules/gpu/test/test_softcascade.cpp

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#include <test_precomp.hpp>
#include <time.h>

#ifdef HAVE_CUDA
using cv::gpu::GpuMat;

// show detection results on input image with cv::imshow
#define SHOW_DETECTIONS

#if defined SHOW_DETECTIONS
# define SHOW(res)           \
    cv::imshow(#res, result);\
    cv::waitKey(0);
#else
# define SHOW(res)
#endif

#define GPU_TEST_P(fixture, name, params)                         \
    class fixture##_##name : public fixture {                     \
     public:                                                      \
      fixture##_##name() {}                                       \
     protected:                                                   \
      virtual void body();                                        \
    };                                                            \
    TEST_P(fixture##_##name, name /*none*/){ body();}             \
    INSTANTIATE_TEST_CASE_P(/*none*/, fixture##_##name, params);  \
    void fixture##_##name::body()


typedef std::tr1::tuple<std::string, std::string, int> roi_fixture_t;

struct SoftCascadeTest : public ::testing::TestWithParam<roi_fixture_t>
{
    typedef cv::gpu::SoftCascade::Detection detection_t;
    static cv::Rect getFromTable(int idx)
    {
        static const cv::Rect rois[] =
        {
            cv::Rect( 65,  20,  35, 80),
            cv::Rect( 95,  35,  45, 40),
            cv::Rect( 45,  35,  45, 40),
            cv::Rect( 25,  27,  50, 45),
            cv::Rect(100,  50,  45, 40),

            cv::Rect( 60,  30,  45, 40),
            cv::Rect( 40,  55,  50, 40),
            cv::Rect( 48,  37,  72, 80),
            cv::Rect( 48,  32,  85, 58),
            cv::Rect( 48,   0,  32, 27)
        };

        return rois[idx];
    }

    static std::string itoa(long i)
    {
        static char s[65];
        sprintf(s, "%ld", i);
        return std::string(s);
    }

    static std::string getImageName(int level)
    {
        time_t rawtime;
        struct tm * timeinfo;
        char buffer [80];

        time ( &rawtime );
        timeinfo = localtime ( &rawtime );

        strftime (buffer,80,"%Y-%m-%d--%H-%M-%S",timeinfo);
        return "gpu_rec_level_" + itoa(level)+ "_" + std::string(buffer) + ".png";
    }

    static void print(std::ostream &out, const detection_t& d)
    {
        out << "\x1b[32m[ detection]\x1b[0m ("
            << std::setw(4)  << d.x
            << " "
            << std::setw(4)  << d.y
            << ") ("
            << std::setw(4)  << d.w
            << " "
            << std::setw(4)  << d.h
            << ") "
            << std::setw(12) << d.confidence
            <<  std::endl;
    }

    static void printTotal(std::ostream &out, int detbytes)
    {
        out << "\x1b[32m[          ]\x1b[0m Total detections " << (detbytes / sizeof(detection_t)) << std::endl;
    }

    static void writeResult(const cv::Mat& result, const int level)
    {
        std::string path = cv::tempfile(getImageName(level).c_str());
        cv::imwrite(path, result);
        std::cout << "\x1b[32m" << "[          ]" << std::endl << "[ stored in]"<< "\x1b[0m" << path << std::endl;
    }
};

GPU_TEST_P(SoftCascadeTest, detectInROI,
    testing::Combine(
        testing::Values(std::string("../cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
        testing::Values(std::string("../cv/cascadeandhog/bahnhof/image_00000000_0.png")),
        testing::Range(0, 5)))
{
    cv::Mat coloredCpu = cv::imread(cvtest::TS::ptr()->get_data_path() + GET_PARAM(1));
    ASSERT_FALSE(coloredCpu.empty());

    cv::gpu::SoftCascade cascade;
    ASSERT_TRUE(cascade.load(cvtest::TS::ptr()->get_data_path() + GET_PARAM(0)));

    GpuMat colored(coloredCpu), objectBoxes(1, 16384, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1), trois;
    rois.setTo(0);

    int nroi = GET_PARAM(2);
    cv::Mat result(coloredCpu);
    cv::RNG rng;
    for (int i = 0; i < nroi; ++i)
    {
        cv::Rect r = getFromTable(rng(10));
        GpuMat sub(rois, r);
        sub.setTo(1);
        r.x *= 4; r.y *= 4; r.width *= 4; r.height *= 4;
        cv::rectangle(result, r, cv::Scalar(0, 0, 255, 255), 1);
    }

    cv::gpu::transpose(rois, trois);

    cascade.detectMultiScale(colored, trois, objectBoxes);

    ///
    cv::Mat dt(objectBoxes);
    typedef cv::gpu::SoftCascade::Detection detection_t;

    detection_t* dts = (detection_t*)dt.data;

    printTotal(std::cout, dt.cols);
    for (int i = 0; i  < (int)(dt.cols / sizeof(detection_t)); ++i)
    {
        detection_t d = dts[i];
        print(std::cout, d);
        cv::rectangle(result, cv::Rect(d.x, d.y, d.w, d.h), cv::Scalar(255, 0, 0, 255), 1);
    }

    SHOW(result);
}

GPU_TEST_P(SoftCascadeTest, detectInLevel,
        testing::Combine(
        testing::Values(std::string("../cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml")),
        testing::Values(std::string("../cv/cascadeandhog/bahnhof/image_00000000_0.png")),
        testing::Range(0, 47)
        ))
{
    std::string xml =  cvtest::TS::ptr()->get_data_path() + GET_PARAM(0);
    cv::gpu::SoftCascade cascade;
    ASSERT_TRUE(cascade.load(xml));

    cv::Mat coloredCpu = cv::imread(cvtest::TS::ptr()->get_data_path() + GET_PARAM(1));
    ASSERT_FALSE(coloredCpu.empty());

    typedef cv::gpu::SoftCascade::Detection detection_t;
    GpuMat colored(coloredCpu), objectBoxes(1, 100 * sizeof(detection_t), CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
    rois.setTo(1);

    cv::gpu::GpuMat trois;
    cv::gpu::transpose(rois, trois);

    int level = GET_PARAM(2);
    cascade.detectMultiScale(colored, trois, objectBoxes, 1, level);

    cv::Mat dt(objectBoxes);

    detection_t* dts = (detection_t*)dt.data;
    cv::Mat result(coloredCpu);

    printTotal(std::cout, dt.cols);
    for (int i = 0; i  < (int)(dt.cols / sizeof(detection_t)); ++i)
    {
        detection_t d = dts[i];
        print(std::cout, d);
        cv::rectangle(result, cv::Rect(d.x, d.y, d.w, d.h), cv::Scalar(255, 0, 0, 255), 1);
    }

    writeResult(result, level);
    SHOW(result);
}

TEST(SoftCascadeTest, readCascade)
{
    std::string xml = cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/icf-template.xml";
    cv::gpu::SoftCascade cascade;
    ASSERT_TRUE(cascade.load(xml));
}

TEST(SoftCascadeTest, detect)
{
    std::string xml =  cvtest::TS::ptr()->get_data_path() + "../cv/cascadeandhog/sc_cvpr_2012_to_opencv.xml";
    cv::gpu::SoftCascade cascade;
    ASSERT_TRUE(cascade.load(xml));

    cv::Mat coloredCpu = cv::imread(cvtest::TS::ptr()->get_data_path()
        + "../cv/cascadeandhog/bahnhof/image_00000000_0.png");
    ASSERT_FALSE(coloredCpu.empty());

    GpuMat colored(coloredCpu), objectBoxes(1, 100000, CV_8UC1), rois(cascade.getRoiSize(), CV_8UC1);
    rois.setTo(0);
    GpuMat sub(rois, cv::Rect(rois.cols / 4, rois.rows / 4,rois.cols / 2, rois.rows / 2));
    sub.setTo(cv::Scalar::all(1));

    cv::gpu::GpuMat trois;
    cv::gpu::transpose(rois, trois);

    cascade.detectMultiScale(colored, trois, objectBoxes);

    typedef cv::gpu::SoftCascade::Detection Detection;
    cv::Mat detections(objectBoxes);
    ASSERT_EQ(detections.cols / sizeof(Detection) ,3670U);
}
#endif