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2145 lines
82 KiB
C++
2145 lines
82 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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// Intel License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000, Intel Corporation, 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 Intel Corporation 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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#include "opencv2/calib3d/calib3d_c.h"
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#include <limits>
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using namespace std;
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using namespace cv;
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#if 0
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class CV_ProjectPointsTest : public cvtest::ArrayTest
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{
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public:
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CV_ProjectPointsTest();
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protected:
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int read_params( CvFileStorage* fs );
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void fill_array( int test_case_idx, int i, int j, Mat& arr );
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int prepare_test_case( int test_case_idx );
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void get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types );
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double get_success_error_level( int test_case_idx, int i, int j );
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void run_func();
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void prepare_to_validation( int );
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bool calc_jacobians;
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};
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CV_ProjectPointsTest::CV_ProjectPointsTest()
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: cvtest::ArrayTest( "3d-ProjectPoints", "cvProjectPoints2", "" )
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{
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test_array[INPUT].push_back(NULL); // rotation vector
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test_array[OUTPUT].push_back(NULL); // rotation matrix
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test_array[OUTPUT].push_back(NULL); // jacobian (J)
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test_array[OUTPUT].push_back(NULL); // rotation vector (backward transform result)
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test_array[OUTPUT].push_back(NULL); // inverse transform jacobian (J1)
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test_array[OUTPUT].push_back(NULL); // J*J1 (or J1*J) == I(3x3)
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test_array[REF_OUTPUT].push_back(NULL);
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test_array[REF_OUTPUT].push_back(NULL);
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test_array[REF_OUTPUT].push_back(NULL);
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test_array[REF_OUTPUT].push_back(NULL);
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test_array[REF_OUTPUT].push_back(NULL);
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element_wise_relative_error = false;
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calc_jacobians = false;
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}
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int CV_ProjectPointsTest::read_params( CvFileStorage* fs )
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{
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int code = cvtest::ArrayTest::read_params( fs );
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return code;
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}
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void CV_ProjectPointsTest::get_test_array_types_and_sizes(
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int /*test_case_idx*/, vector<vector<Size> >& sizes, vector<vector<int> >& types )
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{
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RNG& rng = ts->get_rng();
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int depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
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int i, code;
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code = cvtest::randInt(rng) % 3;
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types[INPUT][0] = CV_MAKETYPE(depth, 1);
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if( code == 0 )
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{
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sizes[INPUT][0] = cvSize(1,1);
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types[INPUT][0] = CV_MAKETYPE(depth, 3);
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}
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else if( code == 1 )
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sizes[INPUT][0] = cvSize(3,1);
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else
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sizes[INPUT][0] = cvSize(1,3);
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sizes[OUTPUT][0] = cvSize(3, 3);
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types[OUTPUT][0] = CV_MAKETYPE(depth, 1);
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types[OUTPUT][1] = CV_MAKETYPE(depth, 1);
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if( cvtest::randInt(rng) % 2 )
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sizes[OUTPUT][1] = cvSize(3,9);
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else
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sizes[OUTPUT][1] = cvSize(9,3);
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types[OUTPUT][2] = types[INPUT][0];
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sizes[OUTPUT][2] = sizes[INPUT][0];
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types[OUTPUT][3] = types[OUTPUT][1];
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sizes[OUTPUT][3] = cvSize(sizes[OUTPUT][1].height, sizes[OUTPUT][1].width);
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types[OUTPUT][4] = types[OUTPUT][1];
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sizes[OUTPUT][4] = cvSize(3,3);
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calc_jacobians = 1;//cvtest::randInt(rng) % 3 != 0;
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if( !calc_jacobians )
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sizes[OUTPUT][1] = sizes[OUTPUT][3] = sizes[OUTPUT][4] = cvSize(0,0);
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for( i = 0; i < 5; i++ )
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{
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types[REF_OUTPUT][i] = types[OUTPUT][i];
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sizes[REF_OUTPUT][i] = sizes[OUTPUT][i];
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}
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}
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double CV_ProjectPointsTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int j )
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{
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return j == 4 ? 1e-2 : 1e-2;
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}
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void CV_ProjectPointsTest::fill_array( int /*test_case_idx*/, int /*i*/, int /*j*/, CvMat* arr )
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{
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double r[3], theta0, theta1, f;
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CvMat _r = cvMat( arr->rows, arr->cols, CV_MAKETYPE(CV_64F,CV_MAT_CN(arr->type)), r );
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RNG& rng = ts->get_rng();
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r[0] = cvtest::randReal(rng)*CV_PI*2;
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r[1] = cvtest::randReal(rng)*CV_PI*2;
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r[2] = cvtest::randReal(rng)*CV_PI*2;
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theta0 = sqrt(r[0]*r[0] + r[1]*r[1] + r[2]*r[2]);
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theta1 = fmod(theta0, CV_PI*2);
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if( theta1 > CV_PI )
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theta1 = -(CV_PI*2 - theta1);
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f = theta1/(theta0 ? theta0 : 1);
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r[0] *= f;
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r[1] *= f;
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r[2] *= f;
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cvTsConvert( &_r, arr );
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}
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int CV_ProjectPointsTest::prepare_test_case( int test_case_idx )
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{
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int code = cvtest::ArrayTest::prepare_test_case( test_case_idx );
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return code;
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}
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void CV_ProjectPointsTest::run_func()
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{
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CvMat *v2m_jac = 0, *m2v_jac = 0;
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if( calc_jacobians )
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{
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v2m_jac = &test_mat[OUTPUT][1];
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m2v_jac = &test_mat[OUTPUT][3];
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}
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cvProjectPoints2( &test_mat[INPUT][0], &test_mat[OUTPUT][0], v2m_jac );
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cvProjectPoints2( &test_mat[OUTPUT][0], &test_mat[OUTPUT][2], m2v_jac );
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}
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void CV_ProjectPointsTest::prepare_to_validation( int /*test_case_idx*/ )
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{
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const CvMat* vec = &test_mat[INPUT][0];
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CvMat* m = &test_mat[REF_OUTPUT][0];
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CvMat* vec2 = &test_mat[REF_OUTPUT][2];
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CvMat* v2m_jac = 0, *m2v_jac = 0;
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double theta0, theta1;
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if( calc_jacobians )
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{
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v2m_jac = &test_mat[REF_OUTPUT][1];
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m2v_jac = &test_mat[REF_OUTPUT][3];
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}
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cvTsProjectPoints( vec, m, v2m_jac );
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cvTsProjectPoints( m, vec2, m2v_jac );
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cvTsCopy( vec, vec2 );
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theta0 = cvtest::norm( cvarrtomat(vec2), 0, CV_L2 );
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theta1 = fmod( theta0, CV_PI*2 );
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if( theta1 > CV_PI )
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theta1 = -(CV_PI*2 - theta1);
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cvScale( vec2, vec2, theta1/(theta0 ? theta0 : 1) );
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if( calc_jacobians )
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{
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//cvInvert( v2m_jac, m2v_jac, CV_SVD );
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if( cvtest::norm(cvarrtomat(&test_mat[OUTPUT][3]), 0, CV_C) < 1000 )
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{
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cvTsGEMM( &test_mat[OUTPUT][1], &test_mat[OUTPUT][3],
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1, 0, 0, &test_mat[OUTPUT][4],
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v2m_jac->rows == 3 ? 0 : CV_GEMM_A_T + CV_GEMM_B_T );
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}
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else
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{
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cvTsSetIdentity( &test_mat[OUTPUT][4], cvScalarAll(1.) );
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cvTsCopy( &test_mat[REF_OUTPUT][2], &test_mat[OUTPUT][2] );
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}
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cvTsSetIdentity( &test_mat[REF_OUTPUT][4], cvScalarAll(1.) );
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}
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}
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CV_ProjectPointsTest ProjectPoints_test;
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#endif
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// --------------------------------- CV_CameraCalibrationTest --------------------------------------------
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class CV_CameraCalibrationTest : public cvtest::BaseTest
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{
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public:
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CV_CameraCalibrationTest();
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~CV_CameraCalibrationTest();
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void clear();
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protected:
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int compare(double* val, double* refVal, int len,
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double eps, const char* paramName);
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virtual void calibrate( int imageCount, int* pointCounts,
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CvSize imageSize, CvPoint2D64f* imagePoints, CvPoint3D64f* objectPoints,
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double* distortionCoeffs, double* cameraMatrix, double* translationVectors,
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double* rotationMatrices, double *stdDevs, double* perViewErrors, int flags ) = 0;
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virtual void project( int pointCount, CvPoint3D64f* objectPoints,
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double* rotationMatrix, double* translationVector,
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double* cameraMatrix, double* distortion, CvPoint2D64f* imagePoints ) = 0;
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void run(int);
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};
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CV_CameraCalibrationTest::CV_CameraCalibrationTest()
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{
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}
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CV_CameraCalibrationTest::~CV_CameraCalibrationTest()
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{
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clear();
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}
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void CV_CameraCalibrationTest::clear()
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{
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cvtest::BaseTest::clear();
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}
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int CV_CameraCalibrationTest::compare(double* val, double* ref_val, int len,
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double eps, const char* param_name )
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{
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return cvtest::cmpEps2_64f( ts, val, ref_val, len, eps, param_name );
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}
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void CV_CameraCalibrationTest::run( int start_from )
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{
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int code = cvtest::TS::OK;
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cv::String filepath;
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cv::String filename;
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CvSize imageSize;
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CvSize etalonSize;
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int numImages;
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CvPoint2D64f* imagePoints;
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CvPoint3D64f* objectPoints;
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CvPoint2D64f* reprojectPoints;
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double* transVects;
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double* rotMatrs;
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double* stdDevs;
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double* perViewErrors;
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double* goodTransVects;
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double* goodRotMatrs;
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double* goodPerViewErrors;
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double* goodStdDevs;
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double cameraMatrix[3*3];
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double distortion[5]={0,0,0,0,0};
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double goodDistortion[4];
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int* numbers;
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FILE* file = 0;
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FILE* datafile = 0;
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int i,j;
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int currImage;
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int currPoint;
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int calibFlags;
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char i_dat_file[100];
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int numPoints;
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int numTests;
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int currTest;
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imagePoints = 0;
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objectPoints = 0;
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reprojectPoints = 0;
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numbers = 0;
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transVects = 0;
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rotMatrs = 0;
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goodTransVects = 0;
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goodRotMatrs = 0;
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int progress = 0;
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int values_read = -1;
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filepath = cv::format("%scv/cameracalibration/", ts->get_data_path().c_str() );
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filename = cv::format("%sdatafiles.txt", filepath.c_str() );
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datafile = fopen( filename.c_str(), "r" );
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if( datafile == 0 )
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{
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ts->printf( cvtest::TS::LOG, "Could not open file with list of test files: %s\n", filename.c_str() );
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code = cvtest::TS::FAIL_MISSING_TEST_DATA;
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goto _exit_;
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}
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values_read = fscanf(datafile,"%d",&numTests);
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CV_Assert(values_read == 1);
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for( currTest = start_from; currTest < numTests; currTest++ )
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{
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values_read = fscanf(datafile,"%s",i_dat_file);
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CV_Assert(values_read == 1);
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filename = cv::format("%s%s", filepath.c_str(), i_dat_file);
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file = fopen(filename.c_str(),"r");
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ts->update_context( this, currTest, true );
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if( file == 0 )
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{
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ts->printf( cvtest::TS::LOG,
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"Can't open current test file: %s\n",filename.c_str());
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if( numTests == 1 )
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{
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code = cvtest::TS::FAIL_MISSING_TEST_DATA;
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goto _exit_;
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}
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continue; // if there is more than one test, just skip the test
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}
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values_read = fscanf(file,"%d %d\n",&(imageSize.width),&(imageSize.height));
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CV_Assert(values_read == 2);
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if( imageSize.width <= 0 || imageSize.height <= 0 )
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{
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ts->printf( cvtest::TS::LOG, "Image size in test file is incorrect\n" );
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code = cvtest::TS::FAIL_INVALID_TEST_DATA;
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goto _exit_;
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}
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/* Read etalon size */
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values_read = fscanf(file,"%d %d\n",&(etalonSize.width),&(etalonSize.height));
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CV_Assert(values_read == 2);
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if( etalonSize.width <= 0 || etalonSize.height <= 0 )
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{
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ts->printf( cvtest::TS::LOG, "Pattern size in test file is incorrect\n" );
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code = cvtest::TS::FAIL_INVALID_TEST_DATA;
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goto _exit_;
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}
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numPoints = etalonSize.width * etalonSize.height;
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/* Read number of images */
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values_read = fscanf(file,"%d\n",&numImages);
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CV_Assert(values_read == 1);
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if( numImages <=0 )
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{
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ts->printf( cvtest::TS::LOG, "Number of images in test file is incorrect\n");
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code = cvtest::TS::FAIL_INVALID_TEST_DATA;
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goto _exit_;
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}
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/* Need to allocate memory */
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imagePoints = (CvPoint2D64f*)cvAlloc( numPoints *
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numImages * sizeof(CvPoint2D64f));
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objectPoints = (CvPoint3D64f*)cvAlloc( numPoints *
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numImages * sizeof(CvPoint3D64f));
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reprojectPoints = (CvPoint2D64f*)cvAlloc( numPoints *
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numImages * sizeof(CvPoint2D64f));
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/* Alloc memory for numbers */
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numbers = (int*)cvAlloc( numImages * sizeof(int));
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/* Fill it by numbers of points of each image*/
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for( currImage = 0; currImage < numImages; currImage++ )
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{
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numbers[currImage] = etalonSize.width * etalonSize.height;
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}
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/* Allocate memory for translate vectors and rotmatrixs*/
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transVects = (double*)cvAlloc(3 * 1 * numImages * sizeof(double));
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rotMatrs = (double*)cvAlloc(3 * 3 * numImages * sizeof(double));
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stdDevs = (double*)cvAlloc((CV_CALIB_NINTRINSIC + 6*numImages) * sizeof(double));
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perViewErrors = (double*)cvAlloc(numImages * sizeof(double));
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goodTransVects = (double*)cvAlloc(3 * 1 * numImages * sizeof(double));
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goodRotMatrs = (double*)cvAlloc(3 * 3 * numImages * sizeof(double));
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goodPerViewErrors = (double*)cvAlloc(numImages * sizeof(double));
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goodStdDevs = (double*)cvAlloc((CV_CALIB_NINTRINSIC + 6*numImages) * sizeof(double));
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/* Read object points */
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i = 0;/* shift for current point */
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for( currImage = 0; currImage < numImages; currImage++ )
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{
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for( currPoint = 0; currPoint < numPoints; currPoint++ )
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{
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double x,y,z;
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values_read = fscanf(file,"%lf %lf %lf\n",&x,&y,&z);
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CV_Assert(values_read == 3);
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(objectPoints+i)->x = x;
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(objectPoints+i)->y = y;
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(objectPoints+i)->z = z;
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i++;
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}
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}
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/* Read image points */
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i = 0;/* shift for current point */
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for( currImage = 0; currImage < numImages; currImage++ )
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{
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for( currPoint = 0; currPoint < numPoints; currPoint++ )
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{
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double x,y;
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values_read = fscanf(file,"%lf %lf\n",&x,&y);
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CV_Assert(values_read == 2);
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(imagePoints+i)->x = x;
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(imagePoints+i)->y = y;
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i++;
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}
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}
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/* Read good data computed before */
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/* Focal lengths */
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double goodFcx,goodFcy;
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values_read = fscanf(file,"%lf %lf",&goodFcx,&goodFcy);
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CV_Assert(values_read == 2);
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/* Principal points */
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double goodCx,goodCy;
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values_read = fscanf(file,"%lf %lf",&goodCx,&goodCy);
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CV_Assert(values_read == 2);
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/* Read distortion */
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|
|
values_read = fscanf(file,"%lf",goodDistortion+0); CV_Assert(values_read == 1);
|
|
values_read = fscanf(file,"%lf",goodDistortion+1); CV_Assert(values_read == 1);
|
|
values_read = fscanf(file,"%lf",goodDistortion+2); CV_Assert(values_read == 1);
|
|
values_read = fscanf(file,"%lf",goodDistortion+3); CV_Assert(values_read == 1);
|
|
|
|
/* Read good Rot matrices */
|
|
for( currImage = 0; currImage < numImages; currImage++ )
|
|
{
|
|
for( i = 0; i < 3; i++ )
|
|
for( j = 0; j < 3; j++ )
|
|
{
|
|
values_read = fscanf(file, "%lf", goodRotMatrs + currImage * 9 + j * 3 + i);
|
|
CV_Assert(values_read == 1);
|
|
}
|
|
}
|
|
|
|
/* Read good Trans vectors */
|
|
for( currImage = 0; currImage < numImages; currImage++ )
|
|
{
|
|
for( i = 0; i < 3; i++ )
|
|
{
|
|
values_read = fscanf(file, "%lf", goodTransVects + currImage * 3 + i);
|
|
CV_Assert(values_read == 1);
|
|
}
|
|
}
|
|
|
|
/* Read good stdDeviations */
|
|
for (i = 0; i < CV_CALIB_NINTRINSIC + numImages*6; i++)
|
|
{
|
|
values_read = fscanf(file, "%lf", goodStdDevs + i);
|
|
CV_Assert(values_read == 1);
|
|
}
|
|
|
|
calibFlags = 0
|
|
// + CV_CALIB_FIX_PRINCIPAL_POINT
|
|
// + CV_CALIB_ZERO_TANGENT_DIST
|
|
// + CV_CALIB_FIX_ASPECT_RATIO
|
|
// + CV_CALIB_USE_INTRINSIC_GUESS
|
|
+ CV_CALIB_FIX_K3
|
|
+ CV_CALIB_FIX_K4+CV_CALIB_FIX_K5
|
|
+ CV_CALIB_FIX_K6
|
|
;
|
|
memset( cameraMatrix, 0, 9*sizeof(cameraMatrix[0]) );
|
|
cameraMatrix[0] = cameraMatrix[4] = 807.;
|
|
cameraMatrix[2] = (imageSize.width - 1)*0.5;
|
|
cameraMatrix[5] = (imageSize.height - 1)*0.5;
|
|
cameraMatrix[8] = 1.;
|
|
|
|
/* Now we can calibrate camera */
|
|
calibrate( numImages,
|
|
numbers,
|
|
imageSize,
|
|
imagePoints,
|
|
objectPoints,
|
|
distortion,
|
|
cameraMatrix,
|
|
transVects,
|
|
rotMatrs,
|
|
stdDevs,
|
|
perViewErrors,
|
|
calibFlags );
|
|
|
|
/* ---- Reproject points to the image ---- */
|
|
for( currImage = 0; currImage < numImages; currImage++ )
|
|
{
|
|
int nPoints = etalonSize.width * etalonSize.height;
|
|
project( nPoints,
|
|
objectPoints + currImage * nPoints,
|
|
rotMatrs + currImage * 9,
|
|
transVects + currImage * 3,
|
|
cameraMatrix,
|
|
distortion,
|
|
reprojectPoints + currImage * nPoints);
|
|
}
|
|
|
|
/* ----- Compute reprojection error ----- */
|
|
i = 0;
|
|
double dx,dy;
|
|
double rx,ry;
|
|
double meanDx,meanDy;
|
|
double maxDx = 0.0;
|
|
double maxDy = 0.0;
|
|
|
|
meanDx = 0;
|
|
meanDy = 0;
|
|
for( currImage = 0; currImage < numImages; currImage++ )
|
|
{
|
|
double imageMeanDx = 0;
|
|
double imageMeanDy = 0;
|
|
for( currPoint = 0; currPoint < etalonSize.width * etalonSize.height; currPoint++ )
|
|
{
|
|
rx = reprojectPoints[i].x;
|
|
ry = reprojectPoints[i].y;
|
|
dx = rx - imagePoints[i].x;
|
|
dy = ry - imagePoints[i].y;
|
|
|
|
meanDx += dx;
|
|
meanDy += dy;
|
|
|
|
imageMeanDx += dx*dx;
|
|
imageMeanDy += dy*dy;
|
|
|
|
dx = fabs(dx);
|
|
dy = fabs(dy);
|
|
|
|
if( dx > maxDx )
|
|
maxDx = dx;
|
|
|
|
if( dy > maxDy )
|
|
maxDy = dy;
|
|
i++;
|
|
}
|
|
goodPerViewErrors[currImage] = sqrt( (imageMeanDx + imageMeanDy) /
|
|
(etalonSize.width * etalonSize.height));
|
|
|
|
//only for c-version of test (it does not provides evaluation of perViewErrors
|
|
//and returns zeros)
|
|
if(perViewErrors[currImage] == 0.0)
|
|
perViewErrors[currImage] = goodPerViewErrors[currImage];
|
|
}
|
|
|
|
meanDx /= numImages * etalonSize.width * etalonSize.height;
|
|
meanDy /= numImages * etalonSize.width * etalonSize.height;
|
|
|
|
/* ========= Compare parameters ========= */
|
|
|
|
/* ----- Compare focal lengths ----- */
|
|
code = compare(cameraMatrix+0,&goodFcx,1,0.1,"fx");
|
|
if( code < 0 )
|
|
goto _exit_;
|
|
|
|
code = compare(cameraMatrix+4,&goodFcy,1,0.1,"fy");
|
|
if( code < 0 )
|
|
goto _exit_;
|
|
|
|
/* ----- Compare principal points ----- */
|
|
code = compare(cameraMatrix+2,&goodCx,1,0.1,"cx");
|
|
if( code < 0 )
|
|
goto _exit_;
|
|
|
|
code = compare(cameraMatrix+5,&goodCy,1,0.1,"cy");
|
|
if( code < 0 )
|
|
goto _exit_;
|
|
|
|
/* ----- Compare distortion ----- */
|
|
code = compare(distortion,goodDistortion,4,0.1,"[k1,k2,p1,p2]");
|
|
if( code < 0 )
|
|
goto _exit_;
|
|
|
|
/* ----- Compare rot matrixs ----- */
|
|
code = compare(rotMatrs,goodRotMatrs, 9*numImages,0.05,"rotation matrices");
|
|
if( code < 0 )
|
|
goto _exit_;
|
|
|
|
/* ----- Compare rot matrixs ----- */
|
|
code = compare(transVects,goodTransVects, 3*numImages,0.1,"translation vectors");
|
|
if( code < 0 )
|
|
goto _exit_;
|
|
|
|
/* ----- Compare per view re-projection errors ----- */
|
|
code = compare(perViewErrors,goodPerViewErrors, numImages,0.1,"per view errors vector");
|
|
if( code < 0 )
|
|
goto _exit_;
|
|
|
|
/* ----- Compare standard deviations of parameters ----- */
|
|
//only for c-version of test (it does not provides evaluation of stdDevs
|
|
//and returns zeros)
|
|
for ( i = 0; i < CV_CALIB_NINTRINSIC + 6*numImages; i++)
|
|
{
|
|
if(stdDevs[i] == 0.0)
|
|
stdDevs[i] = goodStdDevs[i];
|
|
}
|
|
code = compare(stdDevs,goodStdDevs, CV_CALIB_NINTRINSIC + 6*numImages,.5,"stdDevs vector");
|
|
if( code < 0 )
|
|
goto _exit_;
|
|
|
|
if( maxDx > 1.0 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG,
|
|
"Error in reprojection maxDx=%f > 1.0\n",maxDx);
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY; goto _exit_;
|
|
}
|
|
|
|
if( maxDy > 1.0 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG,
|
|
"Error in reprojection maxDy=%f > 1.0\n",maxDy);
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY; goto _exit_;
|
|
}
|
|
|
|
progress = update_progress( progress, currTest, numTests, 0 );
|
|
|
|
cvFree(&imagePoints);
|
|
cvFree(&objectPoints);
|
|
cvFree(&reprojectPoints);
|
|
cvFree(&numbers);
|
|
|
|
cvFree(&transVects);
|
|
cvFree(&rotMatrs);
|
|
cvFree(&stdDevs);
|
|
cvFree(&perViewErrors);
|
|
cvFree(&goodTransVects);
|
|
cvFree(&goodRotMatrs);
|
|
cvFree(&goodPerViewErrors);
|
|
cvFree(&goodStdDevs);
|
|
|
|
fclose(file);
|
|
file = 0;
|
|
}
|
|
|
|
_exit_:
|
|
|
|
if( file )
|
|
fclose(file);
|
|
|
|
if( datafile )
|
|
fclose(datafile);
|
|
|
|
/* Free all allocated memory */
|
|
cvFree(&imagePoints);
|
|
cvFree(&objectPoints);
|
|
cvFree(&reprojectPoints);
|
|
cvFree(&numbers);
|
|
|
|
cvFree(&transVects);
|
|
cvFree(&rotMatrs);
|
|
cvFree(&goodTransVects);
|
|
cvFree(&goodRotMatrs);
|
|
|
|
if( code < 0 )
|
|
ts->set_failed_test_info( code );
|
|
}
|
|
|
|
// --------------------------------- CV_CameraCalibrationTest_C --------------------------------------------
|
|
|
|
class CV_CameraCalibrationTest_C : public CV_CameraCalibrationTest
|
|
{
|
|
public:
|
|
CV_CameraCalibrationTest_C(){}
|
|
protected:
|
|
virtual void calibrate( int imageCount, int* pointCounts,
|
|
CvSize imageSize, CvPoint2D64f* imagePoints, CvPoint3D64f* objectPoints,
|
|
double* distortionCoeffs, double* cameraMatrix, double* translationVectors,
|
|
double* rotationMatrices, double *stdDevs, double* perViewErrors, int flags );
|
|
virtual void project( int pointCount, CvPoint3D64f* objectPoints,
|
|
double* rotationMatrix, double* translationVector,
|
|
double* cameraMatrix, double* distortion, CvPoint2D64f* imagePoints );
|
|
};
|
|
|
|
void CV_CameraCalibrationTest_C::calibrate(int imageCount, int* pointCounts,
|
|
CvSize imageSize, CvPoint2D64f* imagePoints, CvPoint3D64f* objectPoints,
|
|
double* distortionCoeffs, double* cameraMatrix, double* translationVectors,
|
|
double* rotationMatrices, double *stdDevs, double *perViewErrors, int flags )
|
|
{
|
|
int i, total = 0;
|
|
for( i = 0; i < imageCount; i++ )
|
|
{
|
|
perViewErrors[i] = 0.0;
|
|
total += pointCounts[i];
|
|
}
|
|
|
|
for( i = 0; i < CV_CALIB_NINTRINSIC + imageCount*6; i++)
|
|
{
|
|
stdDevs[i] = 0.0;
|
|
}
|
|
|
|
CvMat _objectPoints = cvMat(1, total, CV_64FC3, objectPoints);
|
|
CvMat _imagePoints = cvMat(1, total, CV_64FC2, imagePoints);
|
|
CvMat _pointCounts = cvMat(1, imageCount, CV_32S, pointCounts);
|
|
CvMat _cameraMatrix = cvMat(3, 3, CV_64F, cameraMatrix);
|
|
CvMat _distCoeffs = cvMat(4, 1, CV_64F, distortionCoeffs);
|
|
CvMat _rotationMatrices = cvMat(imageCount, 9, CV_64F, rotationMatrices);
|
|
CvMat _translationVectors = cvMat(imageCount, 3, CV_64F, translationVectors);
|
|
|
|
cvCalibrateCamera2(&_objectPoints, &_imagePoints, &_pointCounts, imageSize,
|
|
&_cameraMatrix, &_distCoeffs, &_rotationMatrices, &_translationVectors, flags);
|
|
}
|
|
|
|
void CV_CameraCalibrationTest_C::project( int pointCount, CvPoint3D64f* objectPoints,
|
|
double* rotationMatrix, double* translationVector,
|
|
double* cameraMatrix, double* distortion, CvPoint2D64f* imagePoints )
|
|
{
|
|
CvMat _objectPoints = cvMat(1, pointCount, CV_64FC3, objectPoints);
|
|
CvMat _imagePoints = cvMat(1, pointCount, CV_64FC2, imagePoints);
|
|
CvMat _cameraMatrix = cvMat(3, 3, CV_64F, cameraMatrix);
|
|
CvMat _distCoeffs = cvMat(4, 1, CV_64F, distortion);
|
|
CvMat _rotationMatrix = cvMat(3, 3, CV_64F, rotationMatrix);
|
|
CvMat _translationVector = cvMat(1, 3, CV_64F, translationVector);
|
|
|
|
cvProjectPoints2(&_objectPoints, &_rotationMatrix, &_translationVector, &_cameraMatrix, &_distCoeffs, &_imagePoints);
|
|
}
|
|
|
|
// --------------------------------- CV_CameraCalibrationTest_CPP --------------------------------------------
|
|
|
|
class CV_CameraCalibrationTest_CPP : public CV_CameraCalibrationTest
|
|
{
|
|
public:
|
|
CV_CameraCalibrationTest_CPP(){}
|
|
protected:
|
|
virtual void calibrate( int imageCount, int* pointCounts,
|
|
CvSize imageSize, CvPoint2D64f* imagePoints, CvPoint3D64f* objectPoints,
|
|
double* distortionCoeffs, double* cameraMatrix, double* translationVectors,
|
|
double* rotationMatrices, double *stdDevs, double* perViewErrors, int flags );
|
|
virtual void project( int pointCount, CvPoint3D64f* objectPoints,
|
|
double* rotationMatrix, double* translationVector,
|
|
double* cameraMatrix, double* distortion, CvPoint2D64f* imagePoints );
|
|
};
|
|
|
|
void CV_CameraCalibrationTest_CPP::calibrate(int imageCount, int* pointCounts,
|
|
CvSize _imageSize, CvPoint2D64f* _imagePoints, CvPoint3D64f* _objectPoints,
|
|
double* _distortionCoeffs, double* _cameraMatrix, double* translationVectors,
|
|
double* rotationMatrices, double *stdDevs, double *perViewErrors, int flags )
|
|
{
|
|
vector<vector<Point3f> > objectPoints( imageCount );
|
|
vector<vector<Point2f> > imagePoints( imageCount );
|
|
Size imageSize = _imageSize;
|
|
Mat cameraMatrix, distCoeffs(1,4,CV_64F,Scalar::all(0));
|
|
vector<Mat> rvecs, tvecs;
|
|
Mat stdDevsMatInt, stdDevsMatExt;
|
|
Mat perViewErrorsMat;
|
|
|
|
CvPoint3D64f* op = _objectPoints;
|
|
CvPoint2D64f* ip = _imagePoints;
|
|
vector<vector<Point3f> >::iterator objectPointsIt = objectPoints.begin();
|
|
vector<vector<Point2f> >::iterator imagePointsIt = imagePoints.begin();
|
|
for( int i = 0; i < imageCount; ++objectPointsIt, ++imagePointsIt, i++ )
|
|
{
|
|
int num = pointCounts[i];
|
|
objectPointsIt->resize( num );
|
|
imagePointsIt->resize( num );
|
|
vector<Point3f>::iterator oIt = objectPointsIt->begin();
|
|
vector<Point2f>::iterator iIt = imagePointsIt->begin();
|
|
for( int j = 0; j < num; ++oIt, ++iIt, j++, op++, ip++)
|
|
{
|
|
oIt->x = (float)op->x, oIt->y = (float)op->y, oIt->z = (float)op->z;
|
|
iIt->x = (float)ip->x, iIt->y = (float)ip->y;
|
|
}
|
|
}
|
|
|
|
calibrateCamera( objectPoints,
|
|
imagePoints,
|
|
imageSize,
|
|
cameraMatrix,
|
|
distCoeffs,
|
|
rvecs,
|
|
tvecs,
|
|
stdDevsMatInt,
|
|
stdDevsMatExt,
|
|
perViewErrorsMat,
|
|
flags );
|
|
|
|
assert( stdDevsMatInt.type() == CV_64F );
|
|
assert( stdDevsMatInt.total() == static_cast<size_t>(CV_CALIB_NINTRINSIC) );
|
|
memcpy( stdDevs, stdDevsMatInt.ptr(), CV_CALIB_NINTRINSIC*sizeof(double) );
|
|
|
|
assert( stdDevsMatExt.type() == CV_64F );
|
|
assert( stdDevsMatExt.total() == static_cast<size_t>(6*imageCount) );
|
|
memcpy( stdDevs + CV_CALIB_NINTRINSIC, stdDevsMatExt.ptr(), 6*imageCount*sizeof(double) );
|
|
|
|
assert( perViewErrorsMat.type() == CV_64F);
|
|
assert( perViewErrorsMat.total() == static_cast<size_t>(imageCount) );
|
|
memcpy( perViewErrors, perViewErrorsMat.ptr(), imageCount*sizeof(double) );
|
|
|
|
assert( cameraMatrix.type() == CV_64FC1 );
|
|
memcpy( _cameraMatrix, cameraMatrix.ptr(), 9*sizeof(double) );
|
|
|
|
assert( cameraMatrix.type() == CV_64FC1 );
|
|
memcpy( _distortionCoeffs, distCoeffs.ptr(), 4*sizeof(double) );
|
|
|
|
vector<Mat>::iterator rvecsIt = rvecs.begin();
|
|
vector<Mat>::iterator tvecsIt = tvecs.begin();
|
|
double *rm = rotationMatrices,
|
|
*tm = translationVectors;
|
|
assert( rvecsIt->type() == CV_64FC1 );
|
|
assert( tvecsIt->type() == CV_64FC1 );
|
|
for( int i = 0; i < imageCount; ++rvecsIt, ++tvecsIt, i++, rm+=9, tm+=3 )
|
|
{
|
|
Mat r9( 3, 3, CV_64FC1 );
|
|
Rodrigues( *rvecsIt, r9 );
|
|
memcpy( rm, r9.ptr(), 9*sizeof(double) );
|
|
memcpy( tm, tvecsIt->ptr(), 3*sizeof(double) );
|
|
}
|
|
}
|
|
|
|
void CV_CameraCalibrationTest_CPP::project( int pointCount, CvPoint3D64f* _objectPoints,
|
|
double* rotationMatrix, double* translationVector,
|
|
double* _cameraMatrix, double* distortion, CvPoint2D64f* _imagePoints )
|
|
{
|
|
Mat objectPoints( pointCount, 3, CV_64FC1, _objectPoints );
|
|
Mat rmat( 3, 3, CV_64FC1, rotationMatrix ),
|
|
rvec( 1, 3, CV_64FC1 ),
|
|
tvec( 1, 3, CV_64FC1, translationVector );
|
|
Mat cameraMatrix( 3, 3, CV_64FC1, _cameraMatrix );
|
|
Mat distCoeffs( 1, 4, CV_64FC1, distortion );
|
|
vector<Point2f> imagePoints;
|
|
Rodrigues( rmat, rvec );
|
|
|
|
objectPoints.convertTo( objectPoints, CV_32FC1 );
|
|
projectPoints( objectPoints, rvec, tvec,
|
|
cameraMatrix, distCoeffs, imagePoints );
|
|
vector<Point2f>::const_iterator it = imagePoints.begin();
|
|
for( int i = 0; it != imagePoints.end(); ++it, i++ )
|
|
{
|
|
_imagePoints[i] = cvPoint2D64f( it->x, it->y );
|
|
}
|
|
}
|
|
|
|
|
|
//----------------------------------------- CV_CalibrationMatrixValuesTest --------------------------------
|
|
|
|
class CV_CalibrationMatrixValuesTest : public cvtest::BaseTest
|
|
{
|
|
public:
|
|
CV_CalibrationMatrixValuesTest() {}
|
|
protected:
|
|
void run(int);
|
|
virtual void calibMatrixValues( const Mat& cameraMatrix, Size imageSize,
|
|
double apertureWidth, double apertureHeight, double& fovx, double& fovy, double& focalLength,
|
|
Point2d& principalPoint, double& aspectRatio ) = 0;
|
|
};
|
|
|
|
void CV_CalibrationMatrixValuesTest::run(int)
|
|
{
|
|
int code = cvtest::TS::OK;
|
|
const double fcMinVal = 1e-5;
|
|
const double fcMaxVal = 1000;
|
|
const double apertureMaxVal = 0.01;
|
|
|
|
RNG rng = ts->get_rng();
|
|
|
|
double fx, fy, cx, cy, nx, ny;
|
|
Mat cameraMatrix( 3, 3, CV_64FC1 );
|
|
cameraMatrix.setTo( Scalar(0) );
|
|
fx = cameraMatrix.at<double>(0,0) = rng.uniform( fcMinVal, fcMaxVal );
|
|
fy = cameraMatrix.at<double>(1,1) = rng.uniform( fcMinVal, fcMaxVal );
|
|
cx = cameraMatrix.at<double>(0,2) = rng.uniform( fcMinVal, fcMaxVal );
|
|
cy = cameraMatrix.at<double>(1,2) = rng.uniform( fcMinVal, fcMaxVal );
|
|
cameraMatrix.at<double>(2,2) = 1;
|
|
|
|
Size imageSize( 600, 400 );
|
|
|
|
double apertureWidth = (double)rng * apertureMaxVal,
|
|
apertureHeight = (double)rng * apertureMaxVal;
|
|
|
|
double fovx, fovy, focalLength, aspectRatio,
|
|
goodFovx, goodFovy, goodFocalLength, goodAspectRatio;
|
|
Point2d principalPoint, goodPrincipalPoint;
|
|
|
|
|
|
calibMatrixValues( cameraMatrix, imageSize, apertureWidth, apertureHeight,
|
|
fovx, fovy, focalLength, principalPoint, aspectRatio );
|
|
|
|
// calculate calibration matrix values
|
|
goodAspectRatio = fy / fx;
|
|
|
|
if( apertureWidth != 0.0 && apertureHeight != 0.0 )
|
|
{
|
|
nx = imageSize.width / apertureWidth;
|
|
ny = imageSize.height / apertureHeight;
|
|
}
|
|
else
|
|
{
|
|
nx = 1.0;
|
|
ny = goodAspectRatio;
|
|
}
|
|
|
|
goodFovx = (atan2(cx, fx) + atan2(imageSize.width - cx, fx)) * 180.0 / CV_PI;
|
|
goodFovy = (atan2(cy, fy) + atan2(imageSize.height - cy, fy)) * 180.0 / CV_PI;
|
|
|
|
goodFocalLength = fx / nx;
|
|
|
|
goodPrincipalPoint.x = cx / nx;
|
|
goodPrincipalPoint.y = cy / ny;
|
|
|
|
// check results
|
|
if( fabs(fovx - goodFovx) > FLT_EPSILON )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad fovx (real=%f, good = %f\n", fovx, goodFovx );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
if( fabs(fovy - goodFovy) > FLT_EPSILON )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad fovy (real=%f, good = %f\n", fovy, goodFovy );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
if( fabs(focalLength - goodFocalLength) > FLT_EPSILON )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad focalLength (real=%f, good = %f\n", focalLength, goodFocalLength );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
if( fabs(aspectRatio - goodAspectRatio) > FLT_EPSILON )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad aspectRatio (real=%f, good = %f\n", aspectRatio, goodAspectRatio );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
if( norm( principalPoint - goodPrincipalPoint ) > FLT_EPSILON )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad principalPoint\n" );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
_exit_:
|
|
RNG& _rng = ts->get_rng();
|
|
_rng = rng;
|
|
ts->set_failed_test_info( code );
|
|
}
|
|
|
|
//----------------------------------------- CV_CalibrationMatrixValuesTest_C --------------------------------
|
|
|
|
class CV_CalibrationMatrixValuesTest_C : public CV_CalibrationMatrixValuesTest
|
|
{
|
|
public:
|
|
CV_CalibrationMatrixValuesTest_C(){}
|
|
protected:
|
|
virtual void calibMatrixValues( const Mat& cameraMatrix, Size imageSize,
|
|
double apertureWidth, double apertureHeight, double& fovx, double& fovy, double& focalLength,
|
|
Point2d& principalPoint, double& aspectRatio );
|
|
};
|
|
|
|
void CV_CalibrationMatrixValuesTest_C::calibMatrixValues( const Mat& _cameraMatrix, Size imageSize,
|
|
double apertureWidth, double apertureHeight,
|
|
double& fovx, double& fovy, double& focalLength,
|
|
Point2d& principalPoint, double& aspectRatio )
|
|
{
|
|
CvMat cameraMatrix = _cameraMatrix;
|
|
CvPoint2D64f pp;
|
|
cvCalibrationMatrixValues( &cameraMatrix, imageSize, apertureWidth, apertureHeight,
|
|
&fovx, &fovy, &focalLength, &pp, &aspectRatio );
|
|
principalPoint.x = pp.x;
|
|
principalPoint.y = pp.y;
|
|
}
|
|
|
|
|
|
//----------------------------------------- CV_CalibrationMatrixValuesTest_CPP --------------------------------
|
|
|
|
class CV_CalibrationMatrixValuesTest_CPP : public CV_CalibrationMatrixValuesTest
|
|
{
|
|
public:
|
|
CV_CalibrationMatrixValuesTest_CPP() {}
|
|
protected:
|
|
virtual void calibMatrixValues( const Mat& cameraMatrix, Size imageSize,
|
|
double apertureWidth, double apertureHeight, double& fovx, double& fovy, double& focalLength,
|
|
Point2d& principalPoint, double& aspectRatio );
|
|
};
|
|
|
|
void CV_CalibrationMatrixValuesTest_CPP::calibMatrixValues( const Mat& cameraMatrix, Size imageSize,
|
|
double apertureWidth, double apertureHeight,
|
|
double& fovx, double& fovy, double& focalLength,
|
|
Point2d& principalPoint, double& aspectRatio )
|
|
{
|
|
calibrationMatrixValues( cameraMatrix, imageSize, apertureWidth, apertureHeight,
|
|
fovx, fovy, focalLength, principalPoint, aspectRatio );
|
|
}
|
|
|
|
|
|
//----------------------------------------- CV_ProjectPointsTest --------------------------------
|
|
void calcdfdx( const vector<vector<Point2f> >& leftF, const vector<vector<Point2f> >& rightF, double eps, Mat& dfdx )
|
|
{
|
|
const int fdim = 2;
|
|
CV_Assert( !leftF.empty() && !rightF.empty() && !leftF[0].empty() && !rightF[0].empty() );
|
|
CV_Assert( leftF[0].size() == rightF[0].size() );
|
|
CV_Assert( fabs(eps) > std::numeric_limits<double>::epsilon() );
|
|
int fcount = (int)leftF[0].size(), xdim = (int)leftF.size();
|
|
|
|
dfdx.create( fcount*fdim, xdim, CV_64FC1 );
|
|
|
|
vector<vector<Point2f> >::const_iterator arrLeftIt = leftF.begin();
|
|
vector<vector<Point2f> >::const_iterator arrRightIt = rightF.begin();
|
|
for( int xi = 0; xi < xdim; xi++, ++arrLeftIt, ++arrRightIt )
|
|
{
|
|
CV_Assert( (int)arrLeftIt->size() == fcount );
|
|
CV_Assert( (int)arrRightIt->size() == fcount );
|
|
vector<Point2f>::const_iterator lIt = arrLeftIt->begin();
|
|
vector<Point2f>::const_iterator rIt = arrRightIt->begin();
|
|
for( int fi = 0; fi < dfdx.rows; fi+=fdim, ++lIt, ++rIt )
|
|
{
|
|
dfdx.at<double>(fi, xi ) = 0.5 * ((double)(rIt->x - lIt->x)) / eps;
|
|
dfdx.at<double>(fi+1, xi ) = 0.5 * ((double)(rIt->y - lIt->y)) / eps;
|
|
}
|
|
}
|
|
}
|
|
|
|
class CV_ProjectPointsTest : public cvtest::BaseTest
|
|
{
|
|
public:
|
|
CV_ProjectPointsTest() {}
|
|
protected:
|
|
void run(int);
|
|
virtual void project( const Mat& objectPoints,
|
|
const Mat& rvec, const Mat& tvec,
|
|
const Mat& cameraMatrix,
|
|
const Mat& distCoeffs,
|
|
vector<Point2f>& imagePoints,
|
|
Mat& dpdrot, Mat& dpdt, Mat& dpdf,
|
|
Mat& dpdc, Mat& dpddist,
|
|
double aspectRatio=0 ) = 0;
|
|
};
|
|
|
|
void CV_ProjectPointsTest::run(int)
|
|
{
|
|
//typedef float matType;
|
|
|
|
int code = cvtest::TS::OK;
|
|
const int pointCount = 100;
|
|
|
|
const float zMinVal = 10.0f, zMaxVal = 100.0f,
|
|
rMinVal = -0.3f, rMaxVal = 0.3f,
|
|
tMinVal = -2.0f, tMaxVal = 2.0f;
|
|
|
|
const float imgPointErr = 1e-3f,
|
|
dEps = 1e-3f;
|
|
|
|
double err;
|
|
|
|
Size imgSize( 600, 800 );
|
|
Mat_<float> objPoints( pointCount, 3), rvec( 1, 3), rmat, tvec( 1, 3 ), cameraMatrix( 3, 3 ), distCoeffs( 1, 4 ),
|
|
leftRvec, rightRvec, leftTvec, rightTvec, leftCameraMatrix, rightCameraMatrix, leftDistCoeffs, rightDistCoeffs;
|
|
|
|
RNG rng = ts->get_rng();
|
|
|
|
// generate data
|
|
cameraMatrix << 300.f, 0.f, imgSize.width/2.f,
|
|
0.f, 300.f, imgSize.height/2.f,
|
|
0.f, 0.f, 1.f;
|
|
distCoeffs << 0.1, 0.01, 0.001, 0.001;
|
|
|
|
rvec(0,0) = rng.uniform( rMinVal, rMaxVal );
|
|
rvec(0,1) = rng.uniform( rMinVal, rMaxVal );
|
|
rvec(0,2) = rng.uniform( rMinVal, rMaxVal );
|
|
Rodrigues( rvec, rmat );
|
|
|
|
tvec(0,0) = rng.uniform( tMinVal, tMaxVal );
|
|
tvec(0,1) = rng.uniform( tMinVal, tMaxVal );
|
|
tvec(0,2) = rng.uniform( tMinVal, tMaxVal );
|
|
|
|
for( int y = 0; y < objPoints.rows; y++ )
|
|
{
|
|
Mat point(1, 3, CV_32FC1, objPoints.ptr(y) );
|
|
float z = rng.uniform( zMinVal, zMaxVal );
|
|
point.at<float>(0,2) = z;
|
|
point.at<float>(0,0) = (rng.uniform(2.f,(float)(imgSize.width-2)) - cameraMatrix(0,2)) / cameraMatrix(0,0) * z;
|
|
point.at<float>(0,1) = (rng.uniform(2.f,(float)(imgSize.height-2)) - cameraMatrix(1,2)) / cameraMatrix(1,1) * z;
|
|
point = (point - tvec) * rmat;
|
|
}
|
|
|
|
vector<Point2f> imgPoints;
|
|
vector<vector<Point2f> > leftImgPoints;
|
|
vector<vector<Point2f> > rightImgPoints;
|
|
Mat dpdrot, dpdt, dpdf, dpdc, dpddist,
|
|
valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist;
|
|
|
|
project( objPoints, rvec, tvec, cameraMatrix, distCoeffs,
|
|
imgPoints, dpdrot, dpdt, dpdf, dpdc, dpddist, 0 );
|
|
|
|
// calculate and check image points
|
|
assert( (int)imgPoints.size() == pointCount );
|
|
vector<Point2f>::const_iterator it = imgPoints.begin();
|
|
for( int i = 0; i < pointCount; i++, ++it )
|
|
{
|
|
Point3d p( objPoints(i,0), objPoints(i,1), objPoints(i,2) );
|
|
double z = p.x*rmat(2,0) + p.y*rmat(2,1) + p.z*rmat(2,2) + tvec(0,2),
|
|
x = (p.x*rmat(0,0) + p.y*rmat(0,1) + p.z*rmat(0,2) + tvec(0,0)) / z,
|
|
y = (p.x*rmat(1,0) + p.y*rmat(1,1) + p.z*rmat(1,2) + tvec(0,1)) / z,
|
|
r2 = x*x + y*y,
|
|
r4 = r2*r2;
|
|
Point2f validImgPoint;
|
|
double a1 = 2*x*y,
|
|
a2 = r2 + 2*x*x,
|
|
a3 = r2 + 2*y*y,
|
|
cdist = 1+distCoeffs(0,0)*r2+distCoeffs(0,1)*r4;
|
|
validImgPoint.x = static_cast<float>((double)cameraMatrix(0,0)*(x*cdist + (double)distCoeffs(0,2)*a1 + (double)distCoeffs(0,3)*a2)
|
|
+ (double)cameraMatrix(0,2));
|
|
validImgPoint.y = static_cast<float>((double)cameraMatrix(1,1)*(y*cdist + (double)distCoeffs(0,2)*a3 + distCoeffs(0,3)*a1)
|
|
+ (double)cameraMatrix(1,2));
|
|
|
|
if( fabs(it->x - validImgPoint.x) > imgPointErr ||
|
|
fabs(it->y - validImgPoint.y) > imgPointErr )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad image point\n" );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
}
|
|
|
|
// check derivatives
|
|
// 1. rotation
|
|
leftImgPoints.resize(3);
|
|
rightImgPoints.resize(3);
|
|
for( int i = 0; i < 3; i++ )
|
|
{
|
|
rvec.copyTo( leftRvec ); leftRvec(0,i) -= dEps;
|
|
project( objPoints, leftRvec, tvec, cameraMatrix, distCoeffs,
|
|
leftImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
rvec.copyTo( rightRvec ); rightRvec(0,i) += dEps;
|
|
project( objPoints, rightRvec, tvec, cameraMatrix, distCoeffs,
|
|
rightImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
}
|
|
calcdfdx( leftImgPoints, rightImgPoints, dEps, valDpdrot );
|
|
err = cvtest::norm( dpdrot, valDpdrot, NORM_INF );
|
|
if( err > 3 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad dpdrot: too big difference = %g\n", err );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
}
|
|
|
|
// 2. translation
|
|
for( int i = 0; i < 3; i++ )
|
|
{
|
|
tvec.copyTo( leftTvec ); leftTvec(0,i) -= dEps;
|
|
project( objPoints, rvec, leftTvec, cameraMatrix, distCoeffs,
|
|
leftImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
tvec.copyTo( rightTvec ); rightTvec(0,i) += dEps;
|
|
project( objPoints, rvec, rightTvec, cameraMatrix, distCoeffs,
|
|
rightImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
}
|
|
calcdfdx( leftImgPoints, rightImgPoints, dEps, valDpdt );
|
|
if( cvtest::norm( dpdt, valDpdt, NORM_INF ) > 0.2 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad dpdtvec\n" );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
}
|
|
|
|
// 3. camera matrix
|
|
// 3.1. focus
|
|
leftImgPoints.resize(2);
|
|
rightImgPoints.resize(2);
|
|
cameraMatrix.copyTo( leftCameraMatrix ); leftCameraMatrix(0,0) -= dEps;
|
|
project( objPoints, rvec, tvec, leftCameraMatrix, distCoeffs,
|
|
leftImgPoints[0], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
cameraMatrix.copyTo( leftCameraMatrix ); leftCameraMatrix(1,1) -= dEps;
|
|
project( objPoints, rvec, tvec, leftCameraMatrix, distCoeffs,
|
|
leftImgPoints[1], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
cameraMatrix.copyTo( rightCameraMatrix ); rightCameraMatrix(0,0) += dEps;
|
|
project( objPoints, rvec, tvec, rightCameraMatrix, distCoeffs,
|
|
rightImgPoints[0], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
cameraMatrix.copyTo( rightCameraMatrix ); rightCameraMatrix(1,1) += dEps;
|
|
project( objPoints, rvec, tvec, rightCameraMatrix, distCoeffs,
|
|
rightImgPoints[1], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
calcdfdx( leftImgPoints, rightImgPoints, dEps, valDpdf );
|
|
if ( cvtest::norm( dpdf, valDpdf, NORM_L2 ) > 0.2 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad dpdf\n" );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
}
|
|
// 3.2. principal point
|
|
leftImgPoints.resize(2);
|
|
rightImgPoints.resize(2);
|
|
cameraMatrix.copyTo( leftCameraMatrix ); leftCameraMatrix(0,2) -= dEps;
|
|
project( objPoints, rvec, tvec, leftCameraMatrix, distCoeffs,
|
|
leftImgPoints[0], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
cameraMatrix.copyTo( leftCameraMatrix ); leftCameraMatrix(1,2) -= dEps;
|
|
project( objPoints, rvec, tvec, leftCameraMatrix, distCoeffs,
|
|
leftImgPoints[1], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
cameraMatrix.copyTo( rightCameraMatrix ); rightCameraMatrix(0,2) += dEps;
|
|
project( objPoints, rvec, tvec, rightCameraMatrix, distCoeffs,
|
|
rightImgPoints[0], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
cameraMatrix.copyTo( rightCameraMatrix ); rightCameraMatrix(1,2) += dEps;
|
|
project( objPoints, rvec, tvec, rightCameraMatrix, distCoeffs,
|
|
rightImgPoints[1], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
calcdfdx( leftImgPoints, rightImgPoints, dEps, valDpdc );
|
|
if ( cvtest::norm( dpdc, valDpdc, NORM_L2 ) > 0.2 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad dpdc\n" );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
}
|
|
|
|
// 4. distortion
|
|
leftImgPoints.resize(distCoeffs.cols);
|
|
rightImgPoints.resize(distCoeffs.cols);
|
|
for( int i = 0; i < distCoeffs.cols; i++ )
|
|
{
|
|
distCoeffs.copyTo( leftDistCoeffs ); leftDistCoeffs(0,i) -= dEps;
|
|
project( objPoints, rvec, tvec, cameraMatrix, leftDistCoeffs,
|
|
leftImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
distCoeffs.copyTo( rightDistCoeffs ); rightDistCoeffs(0,i) += dEps;
|
|
project( objPoints, rvec, tvec, cameraMatrix, rightDistCoeffs,
|
|
rightImgPoints[i], valDpdrot, valDpdt, valDpdf, valDpdc, valDpddist, 0 );
|
|
}
|
|
calcdfdx( leftImgPoints, rightImgPoints, dEps, valDpddist );
|
|
if( cvtest::norm( dpddist, valDpddist, NORM_L2 ) > 0.3 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "bad dpddist\n" );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
}
|
|
|
|
_exit_:
|
|
RNG& _rng = ts->get_rng();
|
|
_rng = rng;
|
|
ts->set_failed_test_info( code );
|
|
}
|
|
|
|
//----------------------------------------- CV_ProjectPointsTest_C --------------------------------
|
|
class CV_ProjectPointsTest_C : public CV_ProjectPointsTest
|
|
{
|
|
public:
|
|
CV_ProjectPointsTest_C() {}
|
|
protected:
|
|
virtual void project( const Mat& objectPoints,
|
|
const Mat& rvec, const Mat& tvec,
|
|
const Mat& cameraMatrix,
|
|
const Mat& distCoeffs,
|
|
vector<Point2f>& imagePoints,
|
|
Mat& dpdrot, Mat& dpdt, Mat& dpdf,
|
|
Mat& dpdc, Mat& dpddist,
|
|
double aspectRatio=0 );
|
|
};
|
|
|
|
void CV_ProjectPointsTest_C::project( const Mat& opoints, const Mat& rvec, const Mat& tvec,
|
|
const Mat& cameraMatrix, const Mat& distCoeffs, vector<Point2f>& ipoints,
|
|
Mat& dpdrot, Mat& dpdt, Mat& dpdf, Mat& dpdc, Mat& dpddist, double aspectRatio)
|
|
{
|
|
int npoints = opoints.cols*opoints.rows*opoints.channels()/3;
|
|
ipoints.resize(npoints);
|
|
dpdrot.create(npoints*2, 3, CV_64F);
|
|
dpdt.create(npoints*2, 3, CV_64F);
|
|
dpdf.create(npoints*2, 2, CV_64F);
|
|
dpdc.create(npoints*2, 2, CV_64F);
|
|
dpddist.create(npoints*2, distCoeffs.rows + distCoeffs.cols - 1, CV_64F);
|
|
CvMat _objectPoints = opoints, _imagePoints = Mat(ipoints);
|
|
CvMat _rvec = rvec, _tvec = tvec, _cameraMatrix = cameraMatrix, _distCoeffs = distCoeffs;
|
|
CvMat _dpdrot = dpdrot, _dpdt = dpdt, _dpdf = dpdf, _dpdc = dpdc, _dpddist = dpddist;
|
|
|
|
cvProjectPoints2( &_objectPoints, &_rvec, &_tvec, &_cameraMatrix, &_distCoeffs,
|
|
&_imagePoints, &_dpdrot, &_dpdt, &_dpdf, &_dpdc, &_dpddist, aspectRatio );
|
|
}
|
|
|
|
|
|
//----------------------------------------- CV_ProjectPointsTest_CPP --------------------------------
|
|
class CV_ProjectPointsTest_CPP : public CV_ProjectPointsTest
|
|
{
|
|
public:
|
|
CV_ProjectPointsTest_CPP() {}
|
|
protected:
|
|
virtual void project( const Mat& objectPoints,
|
|
const Mat& rvec, const Mat& tvec,
|
|
const Mat& cameraMatrix,
|
|
const Mat& distCoeffs,
|
|
vector<Point2f>& imagePoints,
|
|
Mat& dpdrot, Mat& dpdt, Mat& dpdf,
|
|
Mat& dpdc, Mat& dpddist,
|
|
double aspectRatio=0 );
|
|
};
|
|
|
|
void CV_ProjectPointsTest_CPP::project( const Mat& objectPoints, const Mat& rvec, const Mat& tvec,
|
|
const Mat& cameraMatrix, const Mat& distCoeffs, vector<Point2f>& imagePoints,
|
|
Mat& dpdrot, Mat& dpdt, Mat& dpdf, Mat& dpdc, Mat& dpddist, double aspectRatio)
|
|
{
|
|
Mat J;
|
|
projectPoints( objectPoints, rvec, tvec, cameraMatrix, distCoeffs, imagePoints, J, aspectRatio);
|
|
J.colRange(0, 3).copyTo(dpdrot);
|
|
J.colRange(3, 6).copyTo(dpdt);
|
|
J.colRange(6, 8).copyTo(dpdf);
|
|
J.colRange(8, 10).copyTo(dpdc);
|
|
J.colRange(10, J.cols).copyTo(dpddist);
|
|
}
|
|
|
|
///////////////////////////////// Stereo Calibration /////////////////////////////////////
|
|
|
|
class CV_StereoCalibrationCornerTest : public cvtest::BaseTest
|
|
{
|
|
public:
|
|
CV_StereoCalibrationCornerTest();
|
|
~CV_StereoCalibrationCornerTest();
|
|
void clear();
|
|
protected:
|
|
void run(int);
|
|
};
|
|
|
|
CV_StereoCalibrationCornerTest::CV_StereoCalibrationCornerTest()
|
|
{
|
|
}
|
|
|
|
|
|
CV_StereoCalibrationCornerTest::~CV_StereoCalibrationCornerTest()
|
|
{
|
|
clear();
|
|
}
|
|
|
|
void CV_StereoCalibrationCornerTest::clear()
|
|
{
|
|
cvtest::BaseTest::clear();
|
|
}
|
|
|
|
static bool resizeCameraMatrix(const Mat &in_cm, Mat &dst_cm, double scale)
|
|
{
|
|
if (in_cm.empty() || in_cm.cols != 3 || in_cm.rows != 3 || in_cm.type() != CV_64FC1)
|
|
return false;
|
|
dst_cm = in_cm * scale;
|
|
dst_cm.at<double>(2, 2) = 1.0;
|
|
return true;
|
|
}
|
|
|
|
// see https://github.com/opencv/opencv/pull/6836 for details
|
|
void CV_StereoCalibrationCornerTest::run(int)
|
|
{
|
|
const Matx33d M1(906.7857732303256, 0.0, 1026.456125870669,
|
|
0.0, 906.7857732303256, 540.0531577669913,
|
|
0.0, 0.0, 1.0);
|
|
const Matx33d M2(906.782205162265, 0.0, 1014.619997352785,
|
|
0.0, 906.782205162265, 561.9990018887295,
|
|
0.0, 0.0, 1.0);
|
|
const Matx<double, 5, 1> D1(0.0064836857220181504, 0.033880363848984636, 0.0, 0.0, -0.042996356352306114);
|
|
const Matx<double, 5, 1> D2(0.023754068600491646, -0.02364619610835259, 0.0, 0.0, 0.0015014971456262652);
|
|
|
|
const Size imageSize(2048, 1088);
|
|
const double scale = 0.25;
|
|
|
|
const Matx33d Rot(0.999788461750194, -0.015696495349844446, -0.013291041528534329,
|
|
0.015233019205877604, 0.999296086451901, -0.034282455101525826,
|
|
0.01381980018141639, 0.03407274036010432, 0.9993238021218641);
|
|
const Matx31d T(-1.552005597952028, 0.0019508251875105093, -0.023335501616116062);
|
|
|
|
// generate camera matrices for resized image rectification.
|
|
Mat srcM1(M1), srcM2(M2);
|
|
Mat rszM1, rszM2;
|
|
resizeCameraMatrix(srcM1, rszM1, scale);
|
|
resizeCameraMatrix(srcM2, rszM2, scale);
|
|
Size rszImageSize(cvRound(scale * imageSize.width), cvRound(scale * imageSize.height));
|
|
Size srcImageSize = imageSize;
|
|
// apply stereoRectify
|
|
Mat srcR[2], srcP[2], srcQ;
|
|
Mat rszR[2], rszP[2], rszQ;
|
|
stereoRectify(srcM1, D1, srcM2, D2, srcImageSize, Rot, T,
|
|
srcR[0], srcR[1], srcP[0], srcP[1], srcQ,
|
|
CALIB_ZERO_DISPARITY, 0);
|
|
stereoRectify(rszM1, D1, rszM2, D2, rszImageSize, Rot, T,
|
|
rszR[0], rszR[1], rszP[0], rszP[1], rszQ,
|
|
CALIB_ZERO_DISPARITY, 0);
|
|
// generate remap maps
|
|
Mat srcRmap[2], rszRmap[2];
|
|
initUndistortRectifyMap(srcM1, D1, srcR[0], srcP[0], srcImageSize, CV_32FC2, srcRmap[0], srcRmap[1]);
|
|
initUndistortRectifyMap(rszM1, D1, rszR[0], rszP[0], rszImageSize, CV_32FC2, rszRmap[0], rszRmap[1]);
|
|
|
|
// generate source image
|
|
// it's an artificial pattern with white rect in the center
|
|
Mat image(imageSize, CV_8UC3);
|
|
image.setTo(0);
|
|
image(cv::Rect(imageSize.width / 3, imageSize.height / 3, imageSize.width / 3, imageSize.height / 3)).setTo(255);
|
|
|
|
// perform remap-resize
|
|
Mat src_result;
|
|
remap(image, src_result, srcRmap[0], srcRmap[1], INTER_LINEAR);
|
|
resize(src_result, src_result, Size(), scale, scale, INTER_LINEAR);
|
|
// perform resize-remap
|
|
Mat rsz_result;
|
|
resize(image, rsz_result, Size(), scale, scale, INTER_LINEAR);
|
|
remap(rsz_result, rsz_result, rszRmap[0], rszRmap[1], INTER_LINEAR);
|
|
|
|
// modifying the camera matrix with resizeCameraMatrix must yield the same
|
|
// result as calibrating the downscaled images
|
|
int cnz = countNonZero((cv::Mat(src_result - rsz_result) != 0)(
|
|
cv::Rect(src_result.cols / 3, src_result.rows / 3,
|
|
(int)(src_result.cols / 3.1), int(src_result.rows / 3.1))));
|
|
if (cnz)
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The camera matrix is wrong for downscaled image\n");
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
|
}
|
|
}
|
|
|
|
class CV_StereoCalibrationTest : public cvtest::BaseTest
|
|
{
|
|
public:
|
|
CV_StereoCalibrationTest();
|
|
~CV_StereoCalibrationTest();
|
|
void clear();
|
|
protected:
|
|
bool checkPandROI( int test_case_idx,
|
|
const Mat& M, const Mat& D, const Mat& R,
|
|
const Mat& P, Size imgsize, Rect roi );
|
|
|
|
// covers of tested functions
|
|
virtual double calibrateStereoCamera( const vector<vector<Point3f> >& objectPoints,
|
|
const vector<vector<Point2f> >& imagePoints1,
|
|
const vector<vector<Point2f> >& imagePoints2,
|
|
Mat& cameraMatrix1, Mat& distCoeffs1,
|
|
Mat& cameraMatrix2, Mat& distCoeffs2,
|
|
Size imageSize, Mat& R, Mat& T,
|
|
Mat& E, Mat& F, TermCriteria criteria, int flags ) = 0;
|
|
virtual void rectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,
|
|
const Mat& cameraMatrix2, const Mat& distCoeffs2,
|
|
Size imageSize, const Mat& R, const Mat& T,
|
|
Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,
|
|
double alpha, Size newImageSize,
|
|
Rect* validPixROI1, Rect* validPixROI2, int flags ) = 0;
|
|
virtual bool rectifyUncalibrated( const Mat& points1,
|
|
const Mat& points2, const Mat& F, Size imgSize,
|
|
Mat& H1, Mat& H2, double threshold=5 ) = 0;
|
|
virtual void triangulate( const Mat& P1, const Mat& P2,
|
|
const Mat &points1, const Mat &points2,
|
|
Mat &points4D ) = 0;
|
|
virtual void correct( const Mat& F,
|
|
const Mat &points1, const Mat &points2,
|
|
Mat &newPoints1, Mat &newPoints2 ) = 0;
|
|
|
|
void run(int);
|
|
};
|
|
|
|
|
|
CV_StereoCalibrationTest::CV_StereoCalibrationTest()
|
|
{
|
|
}
|
|
|
|
|
|
CV_StereoCalibrationTest::~CV_StereoCalibrationTest()
|
|
{
|
|
clear();
|
|
}
|
|
|
|
void CV_StereoCalibrationTest::clear()
|
|
{
|
|
cvtest::BaseTest::clear();
|
|
}
|
|
|
|
bool CV_StereoCalibrationTest::checkPandROI( int test_case_idx, const Mat& M, const Mat& D, const Mat& R,
|
|
const Mat& P, Size imgsize, Rect roi )
|
|
{
|
|
const double eps = 0.05;
|
|
const int N = 21;
|
|
int x, y, k;
|
|
vector<Point2f> pts, upts;
|
|
|
|
// step 1. check that all the original points belong to the destination image
|
|
for( y = 0; y < N; y++ )
|
|
for( x = 0; x < N; x++ )
|
|
pts.push_back(Point2f((float)x*imgsize.width/(N-1), (float)y*imgsize.height/(N-1)));
|
|
|
|
undistortPoints(Mat(pts), upts, M, D, R, P );
|
|
for( k = 0; k < N*N; k++ )
|
|
if( upts[k].x < -imgsize.width*eps || upts[k].x > imgsize.width*(1+eps) ||
|
|
upts[k].y < -imgsize.height*eps || upts[k].y > imgsize.height*(1+eps) )
|
|
{
|
|
ts->printf(cvtest::TS::LOG, "Test #%d. The point (%g, %g) was mapped to (%g, %g) which is out of image\n",
|
|
test_case_idx, pts[k].x, pts[k].y, upts[k].x, upts[k].y);
|
|
return false;
|
|
}
|
|
|
|
// step 2. check that all the points inside ROI belong to the original source image
|
|
Mat temp(imgsize, CV_8U), utemp, map1, map2;
|
|
temp = Scalar::all(1);
|
|
initUndistortRectifyMap(M, D, R, P, imgsize, CV_16SC2, map1, map2);
|
|
remap(temp, utemp, map1, map2, INTER_LINEAR);
|
|
|
|
if(roi.x < 0 || roi.y < 0 || roi.x + roi.width > imgsize.width || roi.y + roi.height > imgsize.height)
|
|
{
|
|
ts->printf(cvtest::TS::LOG, "Test #%d. The ROI=(%d, %d, %d, %d) is outside of the imge rectangle\n",
|
|
test_case_idx, roi.x, roi.y, roi.width, roi.height);
|
|
return false;
|
|
}
|
|
double s = sum(utemp(roi))[0];
|
|
if( s > roi.area() || roi.area() - s > roi.area()*(1-eps) )
|
|
{
|
|
ts->printf(cvtest::TS::LOG, "Test #%d. The ratio of black pixels inside the valid ROI (~%g%%) is too large\n",
|
|
test_case_idx, s*100./roi.area());
|
|
return false;
|
|
}
|
|
|
|
return true;
|
|
}
|
|
|
|
void CV_StereoCalibrationTest::run( int )
|
|
{
|
|
const int ntests = 1;
|
|
const double maxReprojErr = 2;
|
|
const double maxScanlineDistErr_c = 3;
|
|
const double maxScanlineDistErr_uc = 4;
|
|
FILE* f = 0;
|
|
|
|
for(int testcase = 1; testcase <= ntests; testcase++)
|
|
{
|
|
cv::String filepath;
|
|
char buf[1000];
|
|
filepath = cv::format("%scv/stereo/case%d/stereo_calib.txt", ts->get_data_path().c_str(), testcase );
|
|
f = fopen(filepath.c_str(), "rt");
|
|
Size patternSize;
|
|
vector<string> imglist;
|
|
|
|
if( !f || !fgets(buf, sizeof(buf)-3, f) || sscanf(buf, "%d%d", &patternSize.width, &patternSize.height) != 2 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The file %s can not be opened or has invalid content\n", filepath.c_str() );
|
|
ts->set_failed_test_info( f ? cvtest::TS::FAIL_INVALID_TEST_DATA : cvtest::TS::FAIL_MISSING_TEST_DATA );
|
|
fclose(f);
|
|
return;
|
|
}
|
|
|
|
for(;;)
|
|
{
|
|
if( !fgets( buf, sizeof(buf)-3, f ))
|
|
break;
|
|
size_t len = strlen(buf);
|
|
while( len > 0 && isspace(buf[len-1]))
|
|
buf[--len] = '\0';
|
|
if( buf[0] == '#')
|
|
continue;
|
|
filepath = cv::format("%scv/stereo/case%d/%s", ts->get_data_path().c_str(), testcase, buf );
|
|
imglist.push_back(string(filepath));
|
|
}
|
|
fclose(f);
|
|
|
|
if( imglist.size() == 0 || imglist.size() % 2 != 0 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The number of images is 0 or an odd number in the case #%d\n", testcase );
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_TEST_DATA );
|
|
return;
|
|
}
|
|
|
|
int nframes = (int)(imglist.size()/2);
|
|
int npoints = patternSize.width*patternSize.height;
|
|
vector<vector<Point3f> > objpt(nframes);
|
|
vector<vector<Point2f> > imgpt1(nframes);
|
|
vector<vector<Point2f> > imgpt2(nframes);
|
|
Size imgsize;
|
|
int total = 0;
|
|
|
|
for( int i = 0; i < nframes; i++ )
|
|
{
|
|
Mat left = imread(imglist[i*2]);
|
|
Mat right = imread(imglist[i*2+1]);
|
|
if(left.empty() || right.empty())
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "Can not load images %s and %s, testcase %d\n",
|
|
imglist[i*2].c_str(), imglist[i*2+1].c_str(), testcase );
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_MISSING_TEST_DATA );
|
|
return;
|
|
}
|
|
imgsize = left.size();
|
|
bool found1 = findChessboardCorners(left, patternSize, imgpt1[i]);
|
|
bool found2 = findChessboardCorners(right, patternSize, imgpt2[i]);
|
|
if(!found1 || !found2)
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The function could not detect boards on the images %s and %s, testcase %d\n",
|
|
imglist[i*2].c_str(), imglist[i*2+1].c_str(), testcase );
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
|
return;
|
|
}
|
|
total += (int)imgpt1[i].size();
|
|
for( int j = 0; j < npoints; j++ )
|
|
objpt[i].push_back(Point3f((float)(j%patternSize.width), (float)(j/patternSize.width), 0.f));
|
|
}
|
|
|
|
// rectify (calibrated)
|
|
Mat M1 = Mat::eye(3,3,CV_64F), M2 = Mat::eye(3,3,CV_64F), D1(5,1,CV_64F), D2(5,1,CV_64F), R, T, E, F;
|
|
M1.at<double>(0,2) = M2.at<double>(0,2)=(imgsize.width-1)*0.5;
|
|
M1.at<double>(1,2) = M2.at<double>(1,2)=(imgsize.height-1)*0.5;
|
|
D1 = Scalar::all(0);
|
|
D2 = Scalar::all(0);
|
|
double err = calibrateStereoCamera(objpt, imgpt1, imgpt2, M1, D1, M2, D2, imgsize, R, T, E, F,
|
|
TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS, 30, 1e-6),
|
|
CV_CALIB_SAME_FOCAL_LENGTH
|
|
//+ CV_CALIB_FIX_ASPECT_RATIO
|
|
+ CV_CALIB_FIX_PRINCIPAL_POINT
|
|
+ CV_CALIB_ZERO_TANGENT_DIST
|
|
+ CV_CALIB_FIX_K3
|
|
+ CV_CALIB_FIX_K4 + CV_CALIB_FIX_K5 //+ CV_CALIB_FIX_K6
|
|
);
|
|
err /= nframes*npoints;
|
|
if( err > maxReprojErr )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The average reprojection error is too big (=%g), testcase %d\n", err, testcase);
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
|
return;
|
|
}
|
|
|
|
Mat R1, R2, P1, P2, Q;
|
|
Rect roi1, roi2;
|
|
rectify(M1, D1, M2, D2, imgsize, R, T, R1, R2, P1, P2, Q, 1, imgsize, &roi1, &roi2, 0);
|
|
Mat eye33 = Mat::eye(3,3,CV_64F);
|
|
Mat R1t = R1.t(), R2t = R2.t();
|
|
|
|
if( cvtest::norm(R1t*R1 - eye33, NORM_L2) > 0.01 ||
|
|
cvtest::norm(R2t*R2 - eye33, NORM_L2) > 0.01 ||
|
|
abs(determinant(F)) > 0.01)
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The computed (by rectify) R1 and R2 are not orthogonal,"
|
|
"or the computed (by calibrate) F is not singular, testcase %d\n", testcase);
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
|
return;
|
|
}
|
|
|
|
if(!checkPandROI(testcase, M1, D1, R1, P1, imgsize, roi1))
|
|
{
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
|
return;
|
|
}
|
|
|
|
if(!checkPandROI(testcase, M2, D2, R2, P2, imgsize, roi2))
|
|
{
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
|
return;
|
|
}
|
|
|
|
//check that Tx after rectification is equal to distance between cameras
|
|
double tx = fabs(P2.at<double>(0, 3) / P2.at<double>(0, 0));
|
|
if (fabs(tx - cvtest::norm(T, NORM_L2)) > 1e-5)
|
|
{
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
|
return;
|
|
}
|
|
|
|
//check that Q reprojects points before the camera
|
|
double testPoint[4] = {0.0, 0.0, 100.0, 1.0};
|
|
Mat reprojectedTestPoint = Q * Mat_<double>(4, 1, testPoint);
|
|
CV_Assert(reprojectedTestPoint.type() == CV_64FC1);
|
|
if( reprojectedTestPoint.at<double>(2) / reprojectedTestPoint.at<double>(3) < 0 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "A point after rectification is reprojected behind the camera, testcase %d\n", testcase);
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
|
}
|
|
|
|
//check that Q reprojects the same points as reconstructed by triangulation
|
|
const float minCoord = -300.0f;
|
|
const float maxCoord = 300.0f;
|
|
const float minDisparity = 0.1f;
|
|
const float maxDisparity = 60.0f;
|
|
const int pointsCount = 500;
|
|
const float requiredAccuracy = 1e-3f;
|
|
const float allowToFail = 0.2f; // 20%
|
|
RNG& rng = ts->get_rng();
|
|
|
|
Mat projectedPoints_1(2, pointsCount, CV_32FC1);
|
|
Mat projectedPoints_2(2, pointsCount, CV_32FC1);
|
|
Mat disparities(1, pointsCount, CV_32FC1);
|
|
|
|
rng.fill(projectedPoints_1, RNG::UNIFORM, minCoord, maxCoord);
|
|
rng.fill(disparities, RNG::UNIFORM, minDisparity, maxDisparity);
|
|
projectedPoints_2.row(0) = projectedPoints_1.row(0) - disparities;
|
|
Mat ys_2 = projectedPoints_2.row(1);
|
|
projectedPoints_1.row(1).copyTo(ys_2);
|
|
|
|
Mat points4d;
|
|
triangulate(P1, P2, projectedPoints_1, projectedPoints_2, points4d);
|
|
Mat homogeneousPoints4d = points4d.t();
|
|
const int dimension = 4;
|
|
homogeneousPoints4d = homogeneousPoints4d.reshape(dimension);
|
|
Mat triangulatedPoints;
|
|
convertPointsFromHomogeneous(homogeneousPoints4d, triangulatedPoints);
|
|
|
|
Mat sparsePoints;
|
|
sparsePoints.push_back(projectedPoints_1);
|
|
sparsePoints.push_back(disparities);
|
|
sparsePoints = sparsePoints.t();
|
|
sparsePoints = sparsePoints.reshape(3);
|
|
Mat reprojectedPoints;
|
|
perspectiveTransform(sparsePoints, reprojectedPoints, Q);
|
|
|
|
Mat diff;
|
|
absdiff(triangulatedPoints, reprojectedPoints, diff);
|
|
Mat mask = diff > requiredAccuracy;
|
|
mask = mask.reshape(1);
|
|
mask = mask.col(0) | mask.col(1) | mask.col(2);
|
|
int numFailed = countNonZero(mask);
|
|
#if 0
|
|
std::cout << "numFailed=" << numFailed << std::endl;
|
|
for (int i = 0; i < triangulatedPoints.rows; i++)
|
|
{
|
|
if (mask.at<uchar>(i))
|
|
{
|
|
// failed points usually have 'w'~0 (points4d[3])
|
|
std::cout << "i=" << i << " triangulatePoints=" << triangulatedPoints.row(i) << " reprojectedPoints=" << reprojectedPoints.row(i) << std::endl <<
|
|
" points4d=" << points4d.col(i).t() << " projectedPoints_1=" << projectedPoints_1.col(i).t() << " disparities=" << disparities.col(i).t() << std::endl;
|
|
}
|
|
}
|
|
#endif
|
|
|
|
if (numFailed >= allowToFail * pointsCount)
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "Points reprojected with a matrix Q and points reconstructed by triangulation are different (tolerance=%g, failed=%d), testcase %d\n",
|
|
requiredAccuracy, numFailed, testcase);
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
|
}
|
|
|
|
//check correctMatches
|
|
const float constraintAccuracy = 1e-5f;
|
|
Mat newPoints1, newPoints2;
|
|
Mat points1 = projectedPoints_1.t();
|
|
points1 = points1.reshape(2, 1);
|
|
Mat points2 = projectedPoints_2.t();
|
|
points2 = points2.reshape(2, 1);
|
|
correctMatches(F, points1, points2, newPoints1, newPoints2);
|
|
Mat newHomogeneousPoints1, newHomogeneousPoints2;
|
|
convertPointsToHomogeneous(newPoints1, newHomogeneousPoints1);
|
|
convertPointsToHomogeneous(newPoints2, newHomogeneousPoints2);
|
|
newHomogeneousPoints1 = newHomogeneousPoints1.reshape(1);
|
|
newHomogeneousPoints2 = newHomogeneousPoints2.reshape(1);
|
|
Mat typedF;
|
|
F.convertTo(typedF, newHomogeneousPoints1.type());
|
|
for (int i = 0; i < newHomogeneousPoints1.rows; ++i)
|
|
{
|
|
Mat error = newHomogeneousPoints2.row(i) * typedF * newHomogeneousPoints1.row(i).t();
|
|
CV_Assert(error.rows == 1 && error.cols == 1);
|
|
if (cvtest::norm(error, NORM_L2) > constraintAccuracy)
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "Epipolar constraint is violated after correctMatches, testcase %d\n", testcase);
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_INVALID_OUTPUT );
|
|
}
|
|
}
|
|
|
|
// rectifyUncalibrated
|
|
CV_Assert( imgpt1.size() == imgpt2.size() );
|
|
Mat _imgpt1( total, 1, CV_32FC2 ), _imgpt2( total, 1, CV_32FC2 );
|
|
vector<vector<Point2f> >::const_iterator iit1 = imgpt1.begin();
|
|
vector<vector<Point2f> >::const_iterator iit2 = imgpt2.begin();
|
|
for( int pi = 0; iit1 != imgpt1.end(); ++iit1, ++iit2 )
|
|
{
|
|
vector<Point2f>::const_iterator pit1 = iit1->begin();
|
|
vector<Point2f>::const_iterator pit2 = iit2->begin();
|
|
CV_Assert( iit1->size() == iit2->size() );
|
|
for( ; pit1 != iit1->end(); ++pit1, ++pit2, pi++ )
|
|
{
|
|
_imgpt1.at<Point2f>(pi,0) = Point2f( pit1->x, pit1->y );
|
|
_imgpt2.at<Point2f>(pi,0) = Point2f( pit2->x, pit2->y );
|
|
}
|
|
}
|
|
|
|
Mat _M1, _M2, _D1, _D2;
|
|
vector<Mat> _R1, _R2, _T1, _T2;
|
|
calibrateCamera( objpt, imgpt1, imgsize, _M1, _D1, _R1, _T1, 0 );
|
|
calibrateCamera( objpt, imgpt2, imgsize, _M2, _D2, _R2, _T2, 0 );
|
|
undistortPoints( _imgpt1, _imgpt1, _M1, _D1, Mat(), _M1 );
|
|
undistortPoints( _imgpt2, _imgpt2, _M2, _D2, Mat(), _M2 );
|
|
|
|
Mat matF, _H1, _H2;
|
|
matF = findFundamentalMat( _imgpt1, _imgpt2 );
|
|
rectifyUncalibrated( _imgpt1, _imgpt2, matF, imgsize, _H1, _H2 );
|
|
|
|
Mat rectifPoints1, rectifPoints2;
|
|
perspectiveTransform( _imgpt1, rectifPoints1, _H1 );
|
|
perspectiveTransform( _imgpt2, rectifPoints2, _H2 );
|
|
|
|
bool verticalStereo = abs(P2.at<double>(0,3)) < abs(P2.at<double>(1,3));
|
|
double maxDiff_c = 0, maxDiff_uc = 0;
|
|
for( int i = 0, k = 0; i < nframes; i++ )
|
|
{
|
|
vector<Point2f> temp[2];
|
|
undistortPoints(Mat(imgpt1[i]), temp[0], M1, D1, R1, P1);
|
|
undistortPoints(Mat(imgpt2[i]), temp[1], M2, D2, R2, P2);
|
|
|
|
for( int j = 0; j < npoints; j++, k++ )
|
|
{
|
|
double diff_c = verticalStereo ? abs(temp[0][j].x - temp[1][j].x) : abs(temp[0][j].y - temp[1][j].y);
|
|
Point2f d = rectifPoints1.at<Point2f>(k,0) - rectifPoints2.at<Point2f>(k,0);
|
|
double diff_uc = verticalStereo ? abs(d.x) : abs(d.y);
|
|
maxDiff_c = max(maxDiff_c, diff_c);
|
|
maxDiff_uc = max(maxDiff_uc, diff_uc);
|
|
if( maxDiff_c > maxScanlineDistErr_c )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The distance between %s coordinates is too big(=%g) (used calibrated stereo), testcase %d\n",
|
|
verticalStereo ? "x" : "y", diff_c, testcase);
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
|
return;
|
|
}
|
|
if( maxDiff_uc > maxScanlineDistErr_uc )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The distance between %s coordinates is too big(=%g) (used uncalibrated stereo), testcase %d\n",
|
|
verticalStereo ? "x" : "y", diff_uc, testcase);
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
|
return;
|
|
}
|
|
}
|
|
}
|
|
|
|
ts->printf( cvtest::TS::LOG, "Testcase %d. Max distance (calibrated) =%g\n"
|
|
"Max distance (uncalibrated) =%g\n", testcase, maxDiff_c, maxDiff_uc );
|
|
}
|
|
}
|
|
|
|
//-------------------------------- CV_StereoCalibrationTest_C ------------------------------
|
|
|
|
class CV_StereoCalibrationTest_C : public CV_StereoCalibrationTest
|
|
{
|
|
public:
|
|
CV_StereoCalibrationTest_C() {}
|
|
protected:
|
|
virtual double calibrateStereoCamera( const vector<vector<Point3f> >& objectPoints,
|
|
const vector<vector<Point2f> >& imagePoints1,
|
|
const vector<vector<Point2f> >& imagePoints2,
|
|
Mat& cameraMatrix1, Mat& distCoeffs1,
|
|
Mat& cameraMatrix2, Mat& distCoeffs2,
|
|
Size imageSize, Mat& R, Mat& T,
|
|
Mat& E, Mat& F, TermCriteria criteria, int flags );
|
|
virtual void rectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,
|
|
const Mat& cameraMatrix2, const Mat& distCoeffs2,
|
|
Size imageSize, const Mat& R, const Mat& T,
|
|
Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,
|
|
double alpha, Size newImageSize,
|
|
Rect* validPixROI1, Rect* validPixROI2, int flags );
|
|
virtual bool rectifyUncalibrated( const Mat& points1,
|
|
const Mat& points2, const Mat& F, Size imgSize,
|
|
Mat& H1, Mat& H2, double threshold=5 );
|
|
virtual void triangulate( const Mat& P1, const Mat& P2,
|
|
const Mat &points1, const Mat &points2,
|
|
Mat &points4D );
|
|
virtual void correct( const Mat& F,
|
|
const Mat &points1, const Mat &points2,
|
|
Mat &newPoints1, Mat &newPoints2 );
|
|
};
|
|
|
|
double CV_StereoCalibrationTest_C::calibrateStereoCamera( const vector<vector<Point3f> >& objectPoints,
|
|
const vector<vector<Point2f> >& imagePoints1,
|
|
const vector<vector<Point2f> >& imagePoints2,
|
|
Mat& cameraMatrix1, Mat& distCoeffs1,
|
|
Mat& cameraMatrix2, Mat& distCoeffs2,
|
|
Size imageSize, Mat& R, Mat& T,
|
|
Mat& E, Mat& F, TermCriteria criteria, int flags )
|
|
{
|
|
cameraMatrix1.create( 3, 3, CV_64F );
|
|
cameraMatrix2.create( 3, 3, CV_64F);
|
|
distCoeffs1.create( 1, 5, CV_64F);
|
|
distCoeffs2.create( 1, 5, CV_64F);
|
|
R.create(3, 3, CV_64F);
|
|
T.create(3, 1, CV_64F);
|
|
E.create(3, 3, CV_64F);
|
|
F.create(3, 3, CV_64F);
|
|
|
|
int nimages = (int)objectPoints.size(), total = 0;
|
|
for( int i = 0; i < nimages; i++ )
|
|
{
|
|
total += (int)objectPoints[i].size();
|
|
}
|
|
|
|
Mat npoints( 1, nimages, CV_32S ),
|
|
objPt( 1, total, DataType<Point3f>::type ),
|
|
imgPt( 1, total, DataType<Point2f>::type ),
|
|
imgPt2( 1, total, DataType<Point2f>::type );
|
|
|
|
Point2f* imgPtData2 = imgPt2.ptr<Point2f>();
|
|
Point3f* objPtData = objPt.ptr<Point3f>();
|
|
Point2f* imgPtData = imgPt.ptr<Point2f>();
|
|
for( int i = 0, ni = 0, j = 0; i < nimages; i++, j += ni )
|
|
{
|
|
ni = (int)objectPoints[i].size();
|
|
npoints.ptr<int>()[i] = ni;
|
|
std::copy(objectPoints[i].begin(), objectPoints[i].end(), objPtData + j);
|
|
std::copy(imagePoints1[i].begin(), imagePoints1[i].end(), imgPtData + j);
|
|
std::copy(imagePoints2[i].begin(), imagePoints2[i].end(), imgPtData2 + j);
|
|
}
|
|
CvMat _objPt = objPt, _imgPt = imgPt, _imgPt2 = imgPt2, _npoints = npoints;
|
|
CvMat _cameraMatrix1 = cameraMatrix1, _distCoeffs1 = distCoeffs1;
|
|
CvMat _cameraMatrix2 = cameraMatrix2, _distCoeffs2 = distCoeffs2;
|
|
CvMat matR = R, matT = T, matE = E, matF = F;
|
|
|
|
return cvStereoCalibrate(&_objPt, &_imgPt, &_imgPt2, &_npoints, &_cameraMatrix1,
|
|
&_distCoeffs1, &_cameraMatrix2, &_distCoeffs2, imageSize,
|
|
&matR, &matT, &matE, &matF, flags, criteria );
|
|
}
|
|
|
|
void CV_StereoCalibrationTest_C::rectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,
|
|
const Mat& cameraMatrix2, const Mat& distCoeffs2,
|
|
Size imageSize, const Mat& R, const Mat& T,
|
|
Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,
|
|
double alpha, Size newImageSize,
|
|
Rect* validPixROI1, Rect* validPixROI2, int flags )
|
|
{
|
|
int rtype = CV_64F;
|
|
R1.create(3, 3, rtype);
|
|
R2.create(3, 3, rtype);
|
|
P1.create(3, 4, rtype);
|
|
P2.create(3, 4, rtype);
|
|
Q.create(4, 4, rtype);
|
|
CvMat _cameraMatrix1 = cameraMatrix1, _distCoeffs1 = distCoeffs1;
|
|
CvMat _cameraMatrix2 = cameraMatrix2, _distCoeffs2 = distCoeffs2;
|
|
CvMat matR = R, matT = T, _R1 = R1, _R2 = R2, _P1 = P1, _P2 = P2, matQ = Q;
|
|
cvStereoRectify( &_cameraMatrix1, &_cameraMatrix2, &_distCoeffs1, &_distCoeffs2,
|
|
imageSize, &matR, &matT, &_R1, &_R2, &_P1, &_P2, &matQ, flags,
|
|
alpha, newImageSize, (CvRect*)validPixROI1, (CvRect*)validPixROI2);
|
|
}
|
|
|
|
bool CV_StereoCalibrationTest_C::rectifyUncalibrated( const Mat& points1,
|
|
const Mat& points2, const Mat& F, Size imgSize, Mat& H1, Mat& H2, double threshold )
|
|
{
|
|
H1.create(3, 3, CV_64F);
|
|
H2.create(3, 3, CV_64F);
|
|
CvMat _pt1 = points1, _pt2 = points2, matF, *pF=0, _H1 = H1, _H2 = H2;
|
|
if( F.size() == Size(3, 3) )
|
|
pF = &(matF = F);
|
|
return cvStereoRectifyUncalibrated(&_pt1, &_pt2, pF, imgSize, &_H1, &_H2, threshold) > 0;
|
|
}
|
|
|
|
void CV_StereoCalibrationTest_C::triangulate( const Mat& P1, const Mat& P2,
|
|
const Mat &points1, const Mat &points2,
|
|
Mat &points4D )
|
|
{
|
|
CvMat _P1 = P1, _P2 = P2, _points1 = points1, _points2 = points2;
|
|
points4D.create(4, points1.cols, points1.type());
|
|
CvMat _points4D = points4D;
|
|
cvTriangulatePoints(&_P1, &_P2, &_points1, &_points2, &_points4D);
|
|
}
|
|
|
|
void CV_StereoCalibrationTest_C::correct( const Mat& F,
|
|
const Mat &points1, const Mat &points2,
|
|
Mat &newPoints1, Mat &newPoints2 )
|
|
{
|
|
CvMat _F = F, _points1 = points1, _points2 = points2;
|
|
newPoints1.create(1, points1.cols, points1.type());
|
|
newPoints2.create(1, points2.cols, points2.type());
|
|
CvMat _newPoints1 = newPoints1, _newPoints2 = newPoints2;
|
|
cvCorrectMatches(&_F, &_points1, &_points2, &_newPoints1, &_newPoints2);
|
|
}
|
|
|
|
//-------------------------------- CV_StereoCalibrationTest_CPP ------------------------------
|
|
|
|
class CV_StereoCalibrationTest_CPP : public CV_StereoCalibrationTest
|
|
{
|
|
public:
|
|
CV_StereoCalibrationTest_CPP() {}
|
|
protected:
|
|
virtual double calibrateStereoCamera( const vector<vector<Point3f> >& objectPoints,
|
|
const vector<vector<Point2f> >& imagePoints1,
|
|
const vector<vector<Point2f> >& imagePoints2,
|
|
Mat& cameraMatrix1, Mat& distCoeffs1,
|
|
Mat& cameraMatrix2, Mat& distCoeffs2,
|
|
Size imageSize, Mat& R, Mat& T,
|
|
Mat& E, Mat& F, TermCriteria criteria, int flags );
|
|
virtual void rectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,
|
|
const Mat& cameraMatrix2, const Mat& distCoeffs2,
|
|
Size imageSize, const Mat& R, const Mat& T,
|
|
Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,
|
|
double alpha, Size newImageSize,
|
|
Rect* validPixROI1, Rect* validPixROI2, int flags );
|
|
virtual bool rectifyUncalibrated( const Mat& points1,
|
|
const Mat& points2, const Mat& F, Size imgSize,
|
|
Mat& H1, Mat& H2, double threshold=5 );
|
|
virtual void triangulate( const Mat& P1, const Mat& P2,
|
|
const Mat &points1, const Mat &points2,
|
|
Mat &points4D );
|
|
virtual void correct( const Mat& F,
|
|
const Mat &points1, const Mat &points2,
|
|
Mat &newPoints1, Mat &newPoints2 );
|
|
};
|
|
|
|
double CV_StereoCalibrationTest_CPP::calibrateStereoCamera( const vector<vector<Point3f> >& objectPoints,
|
|
const vector<vector<Point2f> >& imagePoints1,
|
|
const vector<vector<Point2f> >& imagePoints2,
|
|
Mat& cameraMatrix1, Mat& distCoeffs1,
|
|
Mat& cameraMatrix2, Mat& distCoeffs2,
|
|
Size imageSize, Mat& R, Mat& T,
|
|
Mat& E, Mat& F, TermCriteria criteria, int flags )
|
|
{
|
|
return stereoCalibrate( objectPoints, imagePoints1, imagePoints2,
|
|
cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2,
|
|
imageSize, R, T, E, F, flags, criteria );
|
|
}
|
|
|
|
void CV_StereoCalibrationTest_CPP::rectify( const Mat& cameraMatrix1, const Mat& distCoeffs1,
|
|
const Mat& cameraMatrix2, const Mat& distCoeffs2,
|
|
Size imageSize, const Mat& R, const Mat& T,
|
|
Mat& R1, Mat& R2, Mat& P1, Mat& P2, Mat& Q,
|
|
double alpha, Size newImageSize,
|
|
Rect* validPixROI1, Rect* validPixROI2, int flags )
|
|
{
|
|
stereoRectify( cameraMatrix1, distCoeffs1, cameraMatrix2, distCoeffs2,
|
|
imageSize, R, T, R1, R2, P1, P2, Q, flags, alpha, newImageSize,validPixROI1, validPixROI2 );
|
|
}
|
|
|
|
bool CV_StereoCalibrationTest_CPP::rectifyUncalibrated( const Mat& points1,
|
|
const Mat& points2, const Mat& F, Size imgSize, Mat& H1, Mat& H2, double threshold )
|
|
{
|
|
return stereoRectifyUncalibrated( points1, points2, F, imgSize, H1, H2, threshold );
|
|
}
|
|
|
|
void CV_StereoCalibrationTest_CPP::triangulate( const Mat& P1, const Mat& P2,
|
|
const Mat &points1, const Mat &points2,
|
|
Mat &points4D )
|
|
{
|
|
triangulatePoints(P1, P2, points1, points2, points4D);
|
|
}
|
|
|
|
void CV_StereoCalibrationTest_CPP::correct( const Mat& F,
|
|
const Mat &points1, const Mat &points2,
|
|
Mat &newPoints1, Mat &newPoints2 )
|
|
{
|
|
correctMatches(F, points1, points2, newPoints1, newPoints2);
|
|
}
|
|
|
|
///////////////////////////////////////////////////////////////////////////////////////////////////
|
|
|
|
TEST(Calib3d_CalibrateCamera_C, regression) { CV_CameraCalibrationTest_C test; test.safe_run(); }
|
|
TEST(Calib3d_CalibrateCamera_CPP, regression) { CV_CameraCalibrationTest_CPP test; test.safe_run(); }
|
|
TEST(Calib3d_CalibrationMatrixValues_C, accuracy) { CV_CalibrationMatrixValuesTest_C test; test.safe_run(); }
|
|
TEST(Calib3d_CalibrationMatrixValues_CPP, accuracy) { CV_CalibrationMatrixValuesTest_CPP test; test.safe_run(); }
|
|
TEST(Calib3d_ProjectPoints_C, accuracy) { CV_ProjectPointsTest_C test; test.safe_run(); }
|
|
TEST(Calib3d_ProjectPoints_CPP, regression) { CV_ProjectPointsTest_CPP test; test.safe_run(); }
|
|
TEST(Calib3d_StereoCalibrate_C, regression) { CV_StereoCalibrationTest_C test; test.safe_run(); }
|
|
TEST(Calib3d_StereoCalibrate_CPP, regression) { CV_StereoCalibrationTest_CPP test; test.safe_run(); }
|
|
TEST(Calib3d_StereoCalibrateCorner, regression) { CV_StereoCalibrationCornerTest test; test.safe_run(); }
|
|
|
|
TEST(Calib3d_Triangulate, accuracy)
|
|
{
|
|
// the testcase from http://code.opencv.org/issues/4334
|
|
{
|
|
double P1data[] = { 250, 0, 200, 0, 0, 250, 150, 0, 0, 0, 1, 0 };
|
|
double P2data[] = { 250, 0, 200, -250, 0, 250, 150, 0, 0, 0, 1, 0 };
|
|
Mat P1(3, 4, CV_64F, P1data), P2(3, 4, CV_64F, P2data);
|
|
|
|
float x1data[] = { 200.f, 0.f };
|
|
float x2data[] = { 170.f, 1.f };
|
|
float Xdata[] = { 0.f, -5.f, 25/3.f };
|
|
Mat x1(2, 1, CV_32F, x1data);
|
|
Mat x2(2, 1, CV_32F, x2data);
|
|
Mat res0(1, 3, CV_32F, Xdata);
|
|
Mat res_, res;
|
|
|
|
triangulatePoints(P1, P2, x1, x2, res_);
|
|
transpose(res_, res_);
|
|
convertPointsFromHomogeneous(res_, res);
|
|
res = res.reshape(1, 1);
|
|
|
|
cout << "[1]:" << endl;
|
|
cout << "\tres0: " << res0 << endl;
|
|
cout << "\tres: " << res << endl;
|
|
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ASSERT_LE(norm(res, res0, NORM_INF), 1e-1);
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}
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// another testcase http://code.opencv.org/issues/3461
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{
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Matx33d K1(6137.147949, 0.000000, 644.974609,
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0.000000, 6137.147949, 573.442749,
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0.000000, 0.000000, 1.000000);
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Matx33d K2(6137.147949, 0.000000, 644.674438,
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0.000000, 6137.147949, 573.079834,
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0.000000, 0.000000, 1.000000);
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|
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Matx34d RT1(1, 0, 0, 0,
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0, 1, 0, 0,
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0, 0, 1, 0);
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Matx34d RT2(0.998297, 0.0064108, -0.0579766, 143.614334,
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-0.0065818, 0.999975, -0.00275888, -5.160085,
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0.0579574, 0.00313577, 0.998314, 96.066109);
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Matx34d P1 = K1*RT1;
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Matx34d P2 = K2*RT2;
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|
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float x1data[] = { 438.f, 19.f };
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float x2data[] = { 452.363600f, 16.452225f };
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float Xdata[] = { -81.049530f, -215.702804f, 2401.645449f };
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Mat x1(2, 1, CV_32F, x1data);
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Mat x2(2, 1, CV_32F, x2data);
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Mat res0(1, 3, CV_32F, Xdata);
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Mat res_, res;
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|
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triangulatePoints(P1, P2, x1, x2, res_);
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transpose(res_, res_);
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convertPointsFromHomogeneous(res_, res);
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res = res.reshape(1, 1);
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|
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cout << "[2]:" << endl;
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cout << "\tres0: " << res0 << endl;
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cout << "\tres: " << res << endl;
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|
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ASSERT_LE(norm(res, res0, NORM_INF), 2);
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|
}
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|
}
|