402 lines
		
	
	
		
			12 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
			
		
		
	
	
			402 lines
		
	
	
		
			12 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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//  IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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//  By downloading, copying, installing or using the software you agree to this license.
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//  If you do not agree to this license, do not download, install,
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//  copy or use the software.
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//
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//
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//                           License Agreement
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//                For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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//   * Redistribution's of source code must retain the above copyright notice,
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//     this list of conditions and the following disclaimer.
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//
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//   * Redistribution's in binary form must reproduce the above copyright notice,
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//     this list of conditions and the following disclaimer in the documentation
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//     and/or other materials provided with the distribution.
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//
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//   * The name of the copyright holders may not be used to endorse or promote products
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//     derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include "test_precomp.hpp"
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using namespace cv;
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using namespace std;
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class CV_ECC_BaseTest : public cvtest::BaseTest
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{
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public:
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    CV_ECC_BaseTest();
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protected:
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    double computeRMS(const Mat& mat1, const Mat& mat2);
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    bool isMapCorrect(const Mat& mat);
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    double MAX_RMS_ECC;//upper bound for RMS error
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    int ntests;//number of tests per motion type
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    int ECC_iterations;//number of iterations for ECC
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    double ECC_epsilon; //we choose a negative value, so that
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    // ECC_iterations are always executed
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};
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CV_ECC_BaseTest::CV_ECC_BaseTest()
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{
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    MAX_RMS_ECC=0.1;
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    ntests = 3;
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    ECC_iterations = 50;
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    ECC_epsilon = -1; //-> negative value means that ECC_Iterations will be executed
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}
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bool CV_ECC_BaseTest::isMapCorrect(const Mat& map)
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{
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    bool tr = true;
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    float mapVal;
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    for(int i =0; i<map.rows; i++)
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        for(int j=0; j<map.cols; j++){
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            mapVal = map.at<float>(i, j);
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            tr = tr & (!cvIsNaN(mapVal) && (fabs(mapVal) < 1e9));
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        }
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        return tr;
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}
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double CV_ECC_BaseTest::computeRMS(const Mat& mat1, const Mat& mat2){
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    CV_Assert(mat1.rows == mat2.rows);
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    CV_Assert(mat1.cols == mat2.cols);
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    Mat errorMat;
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    subtract(mat1, mat2, errorMat);
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    return sqrt(errorMat.dot(errorMat)/(mat1.rows*mat1.cols));
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}
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class CV_ECC_Test_Translation : public CV_ECC_BaseTest
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{
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public:
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    CV_ECC_Test_Translation();
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protected:
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    void run(int);
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    bool testTranslation(int);
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};
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CV_ECC_Test_Translation::CV_ECC_Test_Translation(){};
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bool CV_ECC_Test_Translation::testTranslation(int from)
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{
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    Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);
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    if (img.empty())
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    {
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        ts->printf( ts->LOG, "test image can not be read");
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        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
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        return false;
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    }
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    Mat testImg;
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    resize(img, testImg, Size(216, 216));
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    cv::RNG rng = ts->get_rng();
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    int progress=0;
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    for (int k=from; k<ntests; k++){
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        ts->update_context( this, k, true );
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        progress = update_progress(progress, k, ntests, 0);
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        Mat translationGround = (Mat_<float>(2,3) << 1, 0, (rng.uniform(10.f, 20.f)),
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            0, 1, (rng.uniform(10.f, 20.f)));
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        Mat warpedImage;
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        warpAffine(testImg, warpedImage, translationGround,
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            Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
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        Mat mapTranslation = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);
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        findTransformECC(warpedImage, testImg, mapTranslation, 0,
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            TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));
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        if (!isMapCorrect(mapTranslation)){
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            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
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            return false;
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        }
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        if (computeRMS(mapTranslation, translationGround)>MAX_RMS_ECC){
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            ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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            ts->printf( ts->LOG, "RMS = %f",
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                computeRMS(mapTranslation, translationGround));
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            return false;
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        }
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    }
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    return true;
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}
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void CV_ECC_Test_Translation::run(int from)
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{
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    if (!testTranslation(from))
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        return;
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    ts->set_failed_test_info(cvtest::TS::OK);
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}
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class CV_ECC_Test_Euclidean : public CV_ECC_BaseTest
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{
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public:
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    CV_ECC_Test_Euclidean();
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protected:
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    void run(int);
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    bool testEuclidean(int);
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};
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CV_ECC_Test_Euclidean::CV_ECC_Test_Euclidean() { }
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bool CV_ECC_Test_Euclidean::testEuclidean(int from)
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{
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    Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);
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    if (img.empty())
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    {
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        ts->printf( ts->LOG, "test image can not be read");
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        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
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        return false;
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    }
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    Mat testImg;
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    resize(img, testImg, Size(216, 216));
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    cv::RNG rng = ts->get_rng();
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    int progress = 0;
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    for (int k=from; k<ntests; k++){
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        ts->update_context( this, k, true );
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        progress = update_progress(progress, k, ntests, 0);
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        double angle = CV_PI/30 + CV_PI*rng.uniform((double)-2.f, (double)2.f)/180;
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        Mat euclideanGround = (Mat_<float>(2,3) << cos(angle), -sin(angle), (rng.uniform(10.f, 20.f)),
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            sin(angle), cos(angle), (rng.uniform(10.f, 20.f)));
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        Mat warpedImage;
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        warpAffine(testImg, warpedImage, euclideanGround,
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            Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
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        Mat mapEuclidean = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);
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        findTransformECC(warpedImage, testImg, mapEuclidean, 1,
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            TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));
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        if (!isMapCorrect(mapEuclidean)){
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            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
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            return false;
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        }
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        if (computeRMS(mapEuclidean, euclideanGround)>MAX_RMS_ECC){
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            ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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            ts->printf( ts->LOG, "RMS = %f",
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                computeRMS(mapEuclidean, euclideanGround));
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            return false;
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        }
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    }
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    return true;
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}
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void CV_ECC_Test_Euclidean::run(int from)
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{
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    if (!testEuclidean(from))
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        return;
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    ts->set_failed_test_info(cvtest::TS::OK);
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}
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class CV_ECC_Test_Affine : public CV_ECC_BaseTest
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{
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public:
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    CV_ECC_Test_Affine();
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protected:
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    void run(int);
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    bool testAffine(int);
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};
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CV_ECC_Test_Affine::CV_ECC_Test_Affine(){};
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bool CV_ECC_Test_Affine::testAffine(int from)
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{
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    Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);
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    if (img.empty())
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    {
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        ts->printf( ts->LOG, "test image can not be read");
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        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
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        return false;
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    }
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    Mat testImg;
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    resize(img, testImg, Size(216, 216));
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    cv::RNG rng = ts->get_rng();
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    int progress = 0;
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    for (int k=from; k<ntests; k++){
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        ts->update_context( this, k, true );
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        progress = update_progress(progress, k, ntests, 0);
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        Mat affineGround = (Mat_<float>(2,3) << (1-rng.uniform(-0.05f, 0.05f)),
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            (rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)),
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            (rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),
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            (rng.uniform(10.f, 20.f)));
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        Mat warpedImage;
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        warpAffine(testImg, warpedImage, affineGround,
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            Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
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        Mat mapAffine = (Mat_<float>(2,3) << 1, 0, 0, 0, 1, 0);
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        findTransformECC(warpedImage, testImg, mapAffine, 2,
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            TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));
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        if (!isMapCorrect(mapAffine)){
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            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
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            return false;
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        }
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        if (computeRMS(mapAffine, affineGround)>MAX_RMS_ECC){
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            ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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            ts->printf( ts->LOG, "RMS = %f",
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                computeRMS(mapAffine, affineGround));
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            return false;
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        }
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    }
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    return true;
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}
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void CV_ECC_Test_Affine::run(int from)
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{
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    if (!testAffine(from))
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        return;
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    ts->set_failed_test_info(cvtest::TS::OK);
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}
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class CV_ECC_Test_Homography : public CV_ECC_BaseTest
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{
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public:
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    CV_ECC_Test_Homography();
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protected:
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    void run(int);
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    bool testHomography(int);
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};
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CV_ECC_Test_Homography::CV_ECC_Test_Homography(){};
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bool CV_ECC_Test_Homography::testHomography(int from)
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{
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    Mat img = imread( string(ts->get_data_path()) + "shared/fruits.png", 0);
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    if (img.empty())
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    {
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        ts->printf( ts->LOG, "test image can not be read");
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        ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_TEST_DATA);
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        return false;
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    }
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    Mat testImg;
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    resize(img, testImg, Size(216, 216));
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    cv::RNG rng = ts->get_rng();
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    int progress = 0;
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    for (int k=from; k<ntests; k++){
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        ts->update_context( this, k, true );
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        progress = update_progress(progress, k, ntests, 0);
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        Mat homoGround = (Mat_<float>(3,3) << (1-rng.uniform(-0.05f, 0.05f)),
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            (rng.uniform(-0.03f, 0.03f)), (rng.uniform(10.f, 20.f)),
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            (rng.uniform(-0.03f, 0.03f)), (1-rng.uniform(-0.05f, 0.05f)),(rng.uniform(10.f, 20.f)),
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            (rng.uniform(0.0001f, 0.0003f)), (rng.uniform(0.0001f, 0.0003f)), 1.f);
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        Mat warpedImage;
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        warpPerspective(testImg, warpedImage, homoGround,
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            Size(200,200), INTER_LINEAR + WARP_INVERSE_MAP);
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        Mat mapHomography = Mat::eye(3, 3, CV_32F);
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        findTransformECC(warpedImage, testImg, mapHomography, 3,
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            TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, ECC_iterations, ECC_epsilon));
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        if (!isMapCorrect(mapHomography)){
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            ts->set_failed_test_info(cvtest::TS::FAIL_INVALID_OUTPUT);
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            return false;
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        }
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        if (computeRMS(mapHomography, homoGround)>MAX_RMS_ECC){
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            ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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            ts->printf( ts->LOG, "RMS = %f",
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                computeRMS(mapHomography, homoGround));
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            return false;
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        }
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    }
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    return true;
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}
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void CV_ECC_Test_Homography::run(int from)
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{
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    if (!testHomography(from))
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        return;
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    ts->set_failed_test_info(cvtest::TS::OK);
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}
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TEST(Video_ECC_Translation, accuracy) { CV_ECC_Test_Translation test; test.safe_run();}
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TEST(Video_ECC_Euclidean, accuracy) { CV_ECC_Test_Euclidean test; test.safe_run(); }
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TEST(Video_ECC_Affine, accuracy) { CV_ECC_Test_Affine test; test.safe_run(); }
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TEST(Video_ECC_Homography, accuracy) { CV_ECC_Test_Homography test; test.safe_run(); }
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