/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's in binary form must reproduce the above copyright notice, // this list of conditions and the following disclaimer in the documentation // and/or other materials provided with the distribution. // // * The name of the copyright holders may not be used to endorse or promote products // derived from this software without specific prior written permission. // // This software is provided by the copyright holders and contributors "as is" and // any express or implied warranties, including, but not limited to, the implied // warranties of merchantability and fitness for a particular purpose are disclaimed. // In no event shall the Intel Corporation or contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict liability, // or tort (including negligence or otherwise) arising in any way out of // the use of this software, even if advised of the possibility of such damage. // //M*/ #include "test_precomp.hpp" namespace opencv_test { namespace { /// phase correlation class CV_PhaseCorrelatorTest : public cvtest::ArrayTest { public: CV_PhaseCorrelatorTest(); protected: void run( int ); }; CV_PhaseCorrelatorTest::CV_PhaseCorrelatorTest() {} void CV_PhaseCorrelatorTest::run( int ) { ts->set_failed_test_info(cvtest::TS::OK); Mat r1 = Mat::ones(Size(129, 128), CV_64F); Mat r2 = Mat::ones(Size(129, 128), CV_64F); double expectedShiftX = -10.0; double expectedShiftY = -20.0; // draw 10x10 rectangles @ (100, 100) and (90, 80) should see ~(-10, -20) shift here... cv::rectangle(r1, Point(100, 100), Point(110, 110), Scalar(0, 0, 0), cv::FILLED); cv::rectangle(r2, Point(90, 80), Point(100, 90), Scalar(0, 0, 0), cv::FILLED); Mat hann; createHanningWindow(hann, r1.size(), CV_64F); Point2d phaseShift = phaseCorrelate(r1, r2, hann); // test accuracy should be less than 1 pixel... if(std::abs(expectedShiftX - phaseShift.x) >= 1 || std::abs(expectedShiftY - phaseShift.y) >= 1) { ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY ); } } TEST(Imgproc_PhaseCorrelatorTest, accuracy) { CV_PhaseCorrelatorTest test; test.safe_run(); } TEST(Imgproc_PhaseCorrelatorTest, accuracy_real_img) { Mat img = imread(cvtest::TS::ptr()->get_data_path() + "shared/airplane.png", IMREAD_GRAYSCALE); img.convertTo(img, CV_64FC1); const int xLen = 129; const int yLen = 129; const int xShift = 40; const int yShift = 14; Mat roi1 = img(Rect(xShift, yShift, xLen, yLen)); Mat roi2 = img(Rect(0, 0, xLen, yLen)); Mat hann; createHanningWindow(hann, roi1.size(), CV_64F); Point2d phaseShift = phaseCorrelate(roi1, roi2, hann); ASSERT_NEAR(phaseShift.x, (double)xShift, 1.); ASSERT_NEAR(phaseShift.y, (double)yShift, 1.); } TEST(Imgproc_PhaseCorrelatorTest, accuracy_1d_odd_fft) { Mat r1 = Mat::ones(Size(129, 1), CV_64F)*255; // 129 will be completed to 135 before FFT Mat r2 = Mat::ones(Size(129, 1), CV_64F)*255; const int xShift = 10; for(int i = 6; i < 20; i++) { r1.at(i) = 1; r2.at(i + xShift) = 1; } Point2d phaseShift = phaseCorrelate(r1, r2); ASSERT_NEAR(phaseShift.x, (double)xShift, 1.); } ////////////////////// DivSpectrums //////////////////////// class CV_DivSpectrumsTest : public cvtest::ArrayTest { public: CV_DivSpectrumsTest(); protected: void run_func(); void get_test_array_types_and_sizes( int, vector >& sizes, vector >& types ); void prepare_to_validation( int test_case_idx ); int flags; }; CV_DivSpectrumsTest::CV_DivSpectrumsTest() : flags(0) { // Allocate test matrices. test_array[INPUT].push_back(NULL); // first input DFT as a CCS-packed array or complex matrix. test_array[INPUT].push_back(NULL); // second input DFT as a CCS-packed array or complex matrix. test_array[OUTPUT].push_back(NULL); // output DFT as a complex matrix. test_array[REF_OUTPUT].push_back(NULL); // reference output DFT as a complex matrix. test_array[TEMP].push_back(NULL); // first input DFT converted to a complex matrix. test_array[TEMP].push_back(NULL); // second input DFT converted to a complex matrix. test_array[TEMP].push_back(NULL); // output DFT as a CCV-packed array. } void CV_DivSpectrumsTest::get_test_array_types_and_sizes( int test_case_idx, vector >& sizes, vector >& types ) { cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx, sizes, types); RNG& rng = ts->get_rng(); // Get the flag of the input. const int rand_int_flags = cvtest::randInt(rng); flags = rand_int_flags & (CV_DXT_MUL_CONJ | CV_DXT_ROWS); // Get input type. const int rand_int_type = cvtest::randInt(rng); int type; if (rand_int_type % 4) { type = CV_32FC1; } else if (rand_int_type % 4 == 1) { type = CV_32FC2; } else if (rand_int_type % 4 == 2) { type = CV_64FC1; } else { type = CV_64FC2; } for( size_t i = 0; i < types.size(); i++ ) { for( size_t j = 0; j < types[i].size(); j++ ) { types[i][j] = type; } } // Inputs are CCS-packed arrays. Prepare outputs and temporary inputs as complex matrices. if( type == CV_32FC1 || type == CV_64FC1 ) { types[OUTPUT][0] += 8; types[REF_OUTPUT][0] += 8; types[TEMP][0] += 8; types[TEMP][1] += 8; } } /// Helper function to convert a ccs array of depth_t into a complex matrix. template static void convert_from_ccs_helper( const Mat& src0, const Mat& src1, Mat& dst ) { const int cn = src0.channels(); int srcstep = cn; int dststep = 1; if( !dst.isContinuous() ) dststep = (int)(dst.step/dst.elemSize()); if( !src0.isContinuous() ) srcstep = (int)(src0.step/src0.elemSize1()); Complex *dst_data = dst.ptr >(); const depth_t* src0_data = src0.ptr(); const depth_t* src1_data = src1.ptr(); dst_data->re = src0_data[0]; dst_data->im = 0; const int n = dst.cols + dst.rows - 1; const int n2 = (n+1) >> 1; if( (n & 1) == 0 ) { dst_data[n2*dststep].re = src0_data[(cn == 1 ? n-1 : n2)*srcstep]; dst_data[n2*dststep].im = 0; } int delta0 = srcstep; int delta1 = delta0 + (cn == 1 ? srcstep : 1); if( cn == 1 ) srcstep *= 2; for( int i = 1; i < n2; i++, delta0 += srcstep, delta1 += srcstep ) { depth_t t0 = src0_data[delta0]; depth_t t1 = src0_data[delta1]; dst_data[i*dststep].re = t0; dst_data[i*dststep].im = t1; t0 = src1_data[delta0]; t1 = -src1_data[delta1]; dst_data[(n-i)*dststep].re = t0; dst_data[(n-i)*dststep].im = t1; } } /// Helper function to convert a ccs array into a complex matrix. static void convert_from_ccs( const Mat& src0, const Mat& src1, Mat& dst, const int flags ) { if( dst.rows > 1 && (dst.cols > 1 || (flags & DFT_ROWS)) ) { const int count = dst.rows; const int len = dst.cols; const bool is2d = (flags & DFT_ROWS) == 0; for( int i = 0; i < count; i++ ) { const int j = !is2d || i == 0 ? i : count - i; const Mat& src0row = src0.row(i); const Mat& src1row = src1.row(j); Mat dstrow = dst.row(i); convert_from_ccs( src0row, src1row, dstrow, 0 ); } if( is2d ) { const Mat& src0row = src0.col(0); Mat dstrow = dst.col(0); convert_from_ccs( src0row, src0row, dstrow, 0 ); if( (len & 1) == 0 ) { const Mat& src0row_even = src0.col(src0.cols - 1); Mat dstrow_even = dst.col(len/2); convert_from_ccs( src0row_even, src0row_even, dstrow_even, 0 ); } } } else { if( dst.depth() == CV_32F ) { convert_from_ccs_helper( src0, src1, dst ); } else { convert_from_ccs_helper( src0, src1, dst ); } } } /// Helper function to compute complex number (nu_re + nu_im * i) / (de_re + de_im * i). static std::pair divide_complex_numbers( const double nu_re, const double nu_im, const double de_re, const double de_im, const bool conj_de ) { if ( conj_de ) { return divide_complex_numbers( nu_re, nu_im, de_re, -de_im, false /* conj_de */ ); } const double result_de = de_re * de_re + de_im * de_im + DBL_EPSILON; const double result_re = nu_re * de_re + nu_im * de_im; const double result_im = nu_re * (-de_im) + nu_im * de_re; return std::pair(result_re / result_de, result_im / result_de); }; /// Helper function to divide a DFT in src1 by a DFT in src2 with depths depth_t. The DFTs are /// complex matrices. template static void div_complex_helper( const Mat& src1, const Mat& src2, Mat& dst, int flags ) { CV_Assert( src1.size == src2.size && src1.type() == src2.type() ); dst.create( src1.rows, src1.cols, src1.type() ); const int cn = src1.channels(); int cols = src1.cols * cn; for( int i = 0; i < dst.rows; i++ ) { const depth_t *src1_data = src1.ptr(i); const depth_t *src2_data = src2.ptr(i); depth_t *dst_data = dst.ptr(i); for( int j = 0; j < cols; j += 2 ) { std::pair result = divide_complex_numbers( src1_data[j], src1_data[j + 1], src2_data[j], src2_data[j + 1], (flags & CV_DXT_MUL_CONJ) != 0 ); dst_data[j] = (depth_t)result.first; dst_data[j + 1] = (depth_t)result.second; } } } /// Helper function to divide a DFT in src1 by a DFT in src2. The DFTs are complex matrices. static void div_complex( const Mat& src1, const Mat& src2, Mat& dst, const int flags ) { const int type = src1.type(); CV_Assert( type == CV_32FC2 || type == CV_64FC2 ); if ( src1.depth() == CV_32F ) { return div_complex_helper( src1, src2, dst, flags ); } else { return div_complex_helper( src1, src2, dst, flags ); } } void CV_DivSpectrumsTest::prepare_to_validation( int /* test_case_idx */ ) { Mat &src1 = test_mat[INPUT][0]; Mat &src2 = test_mat[INPUT][1]; Mat &ref_dst = test_mat[REF_OUTPUT][0]; const int cn = src1.channels(); // Inputs are CCS-packed arrays. Convert them to complex matrices and get the expected output // as a complex matrix. if( cn == 1 ) { Mat &converted_src1 = test_mat[TEMP][0]; Mat &converted_src2 = test_mat[TEMP][1]; convert_from_ccs( src1, src1, converted_src1, flags ); convert_from_ccs( src2, src2, converted_src2, flags ); div_complex( converted_src1, converted_src2, ref_dst, flags ); } // Inputs are complex matrices. Get the expected output as a complex matrix. else { div_complex( src1, src2, ref_dst, flags ); } } void CV_DivSpectrumsTest::run_func() { const Mat &src1 = test_mat[INPUT][0]; const Mat &src2 = test_mat[INPUT][1]; const int cn = src1.channels(); // Inputs are CCS-packed arrays. Get the output as a CCS-packed array and convert it to a // complex matrix. if ( cn == 1 ) { Mat &dst = test_mat[TEMP][2]; cv::divSpectrums( src1, src2, dst, flags, (flags & CV_DXT_MUL_CONJ) != 0 ); Mat &converted_dst = test_mat[OUTPUT][0]; convert_from_ccs( dst, dst, converted_dst, flags ); } // Inputs are complex matrices. Get the output as a complex matrix. else { Mat &dst = test_mat[OUTPUT][0]; cv::divSpectrums( src1, src2, dst, flags, (flags & CV_DXT_MUL_CONJ) != 0 ); } } TEST(Imgproc_DivSpectrums, accuracy) { CV_DivSpectrumsTest test; test.safe_run(); } }} // namespace