root/modules/video/test/test_ecc.cpp

DEFINITIONS

1. isMapCorrect
2. computeRMS
3. testTranslation
4. run
5. testEuclidean
6. run
7. testAffine
8. run
9. testHomography
10. run
11. testMask
12. run
13. TEST
14. TEST
15. TEST
16. TEST
17. TEST

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#include "test_precomp.hpp"

using namespace cv;
using namespace std;

class CV_ECC_BaseTest : public cvtest::BaseTest
{
public:
    CV_ECC_BaseTest();

protected:

    double computeRMS(const Mat& mat1, const Mat& mat2);
    bool isMapCorrect(const Mat& mat);


    double MAX_RMS_ECC;//upper bound for RMS error
    int ntests;//number of tests per motion type
    int ECC_iterations;//number of iterations for ECC
    double ECC_epsilon; //we choose a negative value, so that
    // ECC_iterations are always executed
};

CV_ECC_BaseTest::CV_ECC_BaseTest()
{
    MAX_RMS_ECC=0.1;
    ntests = 3;
    ECC_iterations = 50;
    ECC_epsilon = -1; //-> negative value means that ECC_Iterations will be executed
}


bool CV_ECC_BaseTest::isMapCorrect(const Mat& map)
{
    bool tr = true;
    float mapVal;
    for(int i =0; i<map.rows; i++)
        for(int j=0; j<map.cols; j++){
            mapVal = map.at<float>(i, j);
            tr = tr & (!cvIsNaN(mapVal) && (fabs(mapVal) < 1e9));
        }

        return tr;
}

double CV_ECC_BaseTest::computeRMS(const Mat& mat1, const Mat& mat2){

    CV_Assert(mat1.rows == mat2.rows);
    CV_Assert(mat1.cols == mat2.cols);

    Mat errorMat;
    subtract(mat1, mat2, errorMat);

    return sqrt(errorMat.dot(errorMat)/(mat1.rows*mat1.cols));
}


class CV_ECC_Test_Translation : public CV_ECC_BaseTest
{
public:
    CV_ECC_Test_Translation();
protected:
    void run(int);

    bool testTranslation(int);
};

CV_ECC_Test_Translation::CV_ECC_Test_Translation(){}

bool CV_ECC_Test_Translation::testTranslation(int from)
{
    Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);


    if (img.empty())
    {
        ts->printf( ts->LOG, "test image can not be read");
        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
        return false;
    }
    Mat testImg;
    resize(img, testImg, Size(216, 216));

    cv::RNG rng = ts->get_rng();

    int progress=0;

    for (int k=from; k<ntests; k++){

        ts->update_context( this, k, true );
        progress = update_progress(progress, k, ntests, 0);

        Mat translationGround = (Mat_<float>(2,3) << 1, 0, (rng.uniform(10.f, 20.f)),
            0, 1, (rng.uniform(10.f, 20.f)));

        Mat warpedImage;

        warpAffine(testImg, warpedImage, translationGround,
            Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);

        Mat mapTranslation = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);

        findTransformECC(warpedImage, testImg, mapTranslation, 0,
            TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));

        if (!isMapCorrect(mapTranslation)){
            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
            return false;
        }

        if (computeRMS(mapTranslation, translationGround)>MAX_RMS_ECC){
            ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
            ts->printf( ts->LOG, "RMS = %f",
                computeRMS(mapTranslation, translationGround));
            return false;
        }

    }
    return true;
}

void CV_ECC_Test_Translation::run(int from)
{

    if (!testTranslation(from))
        return;

    ts->set_failed_test_info(cvtest::TS::OK);
}



class CV_ECC_Test_Euclidean : public CV_ECC_BaseTest
{
public:
    CV_ECC_Test_Euclidean();
protected:
    void run(int);

    bool testEuclidean(int);
};

CV_ECC_Test_Euclidean::CV_ECC_Test_Euclidean() { }

bool CV_ECC_Test_Euclidean::testEuclidean(int from)
{
    Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);


    if (img.empty())
    {
        ts->printf( ts->LOG, "test image can not be read");
        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
        return false;
    }
    Mat testImg;
    resize(img, testImg, Size(216, 216));

    cv::RNG rng = ts->get_rng();

    int progress = 0;
    for (int k=from; k<ntests; k++){
        ts->update_context( this, k, true );
        progress = update_progress(progress, k, ntests, 0);

        double angle = CV_PI/30 + CV_PI*rng.uniform((double)-2.f, (double)2.f)/180;

        Mat euclideanGround = (Mat_<float>(2,3) << cos(angle), -sin(angle), (rng.uniform(10.f, 20.f)),
            sin(angle), cos(angle), (rng.uniform(10.f, 20.f)));

        Mat warpedImage;

        warpAffine(testImg, warpedImage, euclideanGround,
            Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);

        Mat mapEuclidean = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);

        findTransformECC(warpedImage, testImg, mapEuclidean, 1,
            TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));

        if (!isMapCorrect(mapEuclidean)){
            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
            return false;
        }

        if (computeRMS(mapEuclidean, euclideanGround)>MAX_RMS_ECC){
            ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
            ts->printf( ts->LOG, "RMS = %f",
                computeRMS(mapEuclidean, euclideanGround));
            return false;
        }

    }
    return true;
}


void CV_ECC_Test_Euclidean::run(int from)
{

    if (!testEuclidean(from))
        return;

    ts->set_failed_test_info(cvtest::TS::OK);
}

class CV_ECC_Test_Affine : public CV_ECC_BaseTest
{
public:
    CV_ECC_Test_Affine();
protected:
    void run(int);

    bool testAffine(int);
};

CV_ECC_Test_Affine::CV_ECC_Test_Affine(){}


bool CV_ECC_Test_Affine::testAffine(int from)
{
    Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);

    if (img.empty())
    {
        ts->printf( ts->LOG, "test image can not be read");
        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
        return false;
    }
    Mat testImg;
    resize(img, testImg, Size(216, 216));

    cv::RNG rng = ts->get_rng();

    int progress = 0;
    for (int k=from; k<ntests; k++){
        ts->update_context( this, k, true );
        progress = update_progress(progress, k, ntests, 0);


        Mat affineGround = (Mat_<float>(2,3) << (1-rng.uniform(-0.05f, 0.05f)),
            (rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)),
            (rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),
            (rng.uniform(10.f, 20.f)));

        Mat warpedImage;

        warpAffine(testImg, warpedImage, affineGround,
            Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);

        Mat mapAffine = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);

        findTransformECC(warpedImage, testImg, mapAffine, 2,
            TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));

        if (!isMapCorrect(mapAffine)){
            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
            return false;
        }

        if (computeRMS(mapAffine, affineGround)>MAX_RMS_ECC){
            ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
            ts->printf( ts->LOG, "RMS = %f",
                computeRMS(mapAffine, affineGround));
            return false;
        }

    }

    return true;
}


void CV_ECC_Test_Affine::run(int from)
{

    if (!testAffine(from))
        return;

    ts->set_failed_test_info(cvtest::TS::OK);
}

class CV_ECC_Test_Homography : public CV_ECC_BaseTest
{
public:
    CV_ECC_Test_Homography();
protected:
    void run(int);

    bool testHomography(int);
};

CV_ECC_Test_Homography::CV_ECC_Test_Homography(){}

bool CV_ECC_Test_Homography::testHomography(int from)
{
    Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);


    if (img.empty())
    {
        ts->printf( ts->LOG, "test image can not be read");
        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
        return false;
    }
    Mat testImg;
    resize(img, testImg, Size(216, 216));

    cv::RNG rng = ts->get_rng();

    int progress = 0;
    for (int k=from; k<ntests; k++){
        ts->update_context( this, k, true );
        progress = update_progress(progress, k, ntests, 0);

        Mat homoGround = (Mat_<float>(3,3) << (1-rng.uniform(-0.05f, 0.05f)),
            (rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)),
            (rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),(rng.uniform(10.f, 20.f)),
            (rng.uniform(0.0001f, 0.0003f)), (rng.uniform(0.0001f, 0.0003f)), 1.f);

        Mat warpedImage;

        warpPerspective(testImg, warpedImage, homoGround,
            Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);

        Mat mapHomography = Mat::eye(3, 3, CV_32F);

        findTransformECC(warpedImage, testImg, mapHomography, 3,
            TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));

        if (!isMapCorrect(mapHomography)){
            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
            return false;
        }

        if (computeRMS(mapHomography, homoGround)>MAX_RMS_ECC){
            ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
            ts->printf( ts->LOG, "RMS = %f",
                computeRMS(mapHomography, homoGround));
            return false;
        }

    }
    return true;
}

void CV_ECC_Test_Homography::run(int from)
{
    if (!testHomography(from))
        return;

    ts->set_failed_test_info(cvtest::TS::OK);
}

class CV_ECC_Test_Mask : public CV_ECC_BaseTest
{
public:
    CV_ECC_Test_Mask();
protected:
    void run(int);

    bool testMask(int);
};

CV_ECC_Test_Mask::CV_ECC_Test_Mask(){}

bool CV_ECC_Test_Mask::testMask(int from)
{
    Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);


    if (img.empty())
    {
        ts->printf( ts->LOG, "test image can not be read");
        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
        return false;
    }
    Mat scaledImage;
    resize(img, scaledImage, Size(216, 216));

    Mat_<float> testImg;
    scaledImage.convertTo(testImg, testImg.type());

    cv::RNG rng = ts->get_rng();

    int progress=0;

    for (int k=from; k<ntests; k++){

        ts->update_context( this, k, true );
        progress = update_progress(progress, k, ntests, 0);

        Mat translationGround = (Mat_<float>(2,3) << 1, 0, (rng.uniform(10.f, 20.f)),
            0, 1, (rng.uniform(10.f, 20.f)));

        Mat warpedImage;

        warpAffine(testImg, warpedImage, translationGround,
            Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);

        Mat mapTranslation = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);

        Mat_<unsigned char> mask = Mat_<unsigned char>::ones(testImg.rows, testImg.cols);
        for (int i=testImg.rows*2/3; i<testImg.rows; i++) {
          for (int j=testImg.cols*2/3; j<testImg.cols; j++) {
            testImg(i, j) = 0;
            mask(i, j) = 0;
          }
        }

        findTransformECC(warpedImage, testImg, mapTranslation, 0,
            TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon), mask);

        if (!isMapCorrect(mapTranslation)){
            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
            return false;
        }

        if (computeRMS(mapTranslation, translationGround)>MAX_RMS_ECC){
            ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
            ts->printf( ts->LOG, "RMS = %f",
                computeRMS(mapTranslation, translationGround));
            return false;
        }

    }
    return true;
}

void CV_ECC_Test_Mask::run(int from)
{
    if (!testMask(from))
        return;

    ts->set_failed_test_info(cvtest::TS::OK);
}

TEST(Video_ECC_Translation, accuracy) { CV_ECC_Test_Translation test; test.safe_run();}
TEST(Video_ECC_Euclidean, accuracy) { CV_ECC_Test_Euclidean test; test.safe_run(); }
TEST(Video_ECC_Affine, accuracy) { CV_ECC_Test_Affine test; test.safe_run(); }
TEST(Video_ECC_Homography, accuracy) { CV_ECC_Test_Homography test; test.safe_run(); }
TEST(Video_ECC_Mask, accuracy) { CV_ECC_Test_Mask test; test.safe_run(); }