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|
| | #include "test_precomp.hpp"
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| |
|
| | namespace opencv_test { namespace {
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| |
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| |
|
| | class CV_PhaseCorrelatorTest : public cvtest::ArrayTest
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| | {
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| | public:
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| | CV_PhaseCorrelatorTest();
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| | protected:
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| | void run( int );
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| | };
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| |
|
| | CV_PhaseCorrelatorTest::CV_PhaseCorrelatorTest() {}
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| |
|
| | void CV_PhaseCorrelatorTest::run( int )
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| | {
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| | ts->set_failed_test_info(cvtest::TS::OK);
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| |
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| | Mat r1 = Mat::ones(Size(129, 128), CV_64F);
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| | Mat r2 = Mat::ones(Size(129, 128), CV_64F);
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| |
|
| | double expectedShiftX = -10.0;
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| | double expectedShiftY = -20.0;
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| |
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| |
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| | cv::rectangle(r1, Point(100, 100), Point(110, 110), Scalar(0, 0, 0), cv::FILLED);
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| | cv::rectangle(r2, Point(90, 80), Point(100, 90), Scalar(0, 0, 0), cv::FILLED);
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| |
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| | Mat hann;
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| | createHanningWindow(hann, r1.size(), CV_64F);
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| | Point2d phaseShift = phaseCorrelate(r1, r2, hann);
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| |
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| |
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| | if(std::abs(expectedShiftX - phaseShift.x) >= 1 || std::abs(expectedShiftY - phaseShift.y) >= 1)
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| | {
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| | ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
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| | }
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| | }
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| |
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| | TEST(Imgproc_PhaseCorrelatorTest, accuracy) { CV_PhaseCorrelatorTest test; test.safe_run(); }
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| |
|
| | TEST(Imgproc_PhaseCorrelatorTest, accuracy_real_img)
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| | {
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| | Mat img = imread(cvtest::TS::ptr()->get_data_path() + "shared/airplane.png", IMREAD_GRAYSCALE);
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| | img.convertTo(img, CV_64FC1);
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| |
|
| | const int xLen = 129;
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| | const int yLen = 129;
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| | const int xShift = 40;
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| | const int yShift = 14;
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| |
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| | Mat roi1 = img(Rect(xShift, yShift, xLen, yLen));
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| | Mat roi2 = img(Rect(0, 0, xLen, yLen));
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| |
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| | Mat hann;
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| | createHanningWindow(hann, roi1.size(), CV_64F);
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| | Point2d phaseShift = phaseCorrelate(roi1, roi2, hann);
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| |
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| | ASSERT_NEAR(phaseShift.x, (double)xShift, 1.);
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| | ASSERT_NEAR(phaseShift.y, (double)yShift, 1.);
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| | }
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| |
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| | TEST(Imgproc_PhaseCorrelatorTest, accuracy_1d_odd_fft) {
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| | Mat r1 = Mat::ones(Size(129, 1), CV_64F)*255;
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| | Mat r2 = Mat::ones(Size(129, 1), CV_64F)*255;
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| |
|
| | const int xShift = 10;
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| |
|
| | for(int i = 6; i < 20; i++)
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| | {
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| | r1.at<double>(i) = 1;
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| | r2.at<double>(i + xShift) = 1;
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| | }
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| |
|
| | Point2d phaseShift = phaseCorrelate(r1, r2);
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| |
|
| | ASSERT_NEAR(phaseShift.x, (double)xShift, 1.);
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| | }
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| |
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| |
|
| | class CV_DivSpectrumsTest : public cvtest::ArrayTest
|
| | {
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| | public:
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| | CV_DivSpectrumsTest();
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| | protected:
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| | void run_func();
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| | void get_test_array_types_and_sizes( int, vector<vector<Size> >& sizes, vector<vector<int> >& types );
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| | void prepare_to_validation( int test_case_idx );
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| | int flags;
|
| | };
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| |
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| |
|
| | CV_DivSpectrumsTest::CV_DivSpectrumsTest() : flags(0)
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| | {
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| |
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| | test_array[INPUT].push_back(NULL);
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| | test_array[INPUT].push_back(NULL);
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| | test_array[OUTPUT].push_back(NULL);
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| | test_array[REF_OUTPUT].push_back(NULL);
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| | test_array[TEMP].push_back(NULL);
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| | test_array[TEMP].push_back(NULL);
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| | test_array[TEMP].push_back(NULL);
|
| | }
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| |
|
| | void CV_DivSpectrumsTest::get_test_array_types_and_sizes( int test_case_idx, vector<vector<Size> >& sizes, vector<vector<int> >& types )
|
| | {
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| | cvtest::ArrayTest::get_test_array_types_and_sizes(test_case_idx, sizes, types);
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| | RNG& rng = ts->get_rng();
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| |
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| |
|
| | const int rand_int_flags = cvtest::randInt(rng);
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| | flags = rand_int_flags & (CV_DXT_MUL_CONJ | CV_DXT_ROWS);
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| |
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| |
|
| | const int rand_int_type = cvtest::randInt(rng);
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| | int type;
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| |
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| | if (rand_int_type % 4)
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| | {
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| | type = CV_32FC1;
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| | }
|
| | else if (rand_int_type % 4 == 1)
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| | {
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| | type = CV_32FC2;
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| | }
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| | else if (rand_int_type % 4 == 2)
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| | {
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| | type = CV_64FC1;
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| | }
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| | else
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| | {
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| | type = CV_64FC2;
|
| | }
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| |
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| | for( size_t i = 0; i < types.size(); i++ )
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| | {
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| | for( size_t j = 0; j < types[i].size(); j++ )
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| | {
|
| | types[i][j] = type;
|
| | }
|
| | }
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| |
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| |
|
| | if( type == CV_32FC1 || type == CV_64FC1 )
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| | {
|
| | types[OUTPUT][0] += 8;
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| | types[REF_OUTPUT][0] += 8;
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| | types[TEMP][0] += 8;
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| | types[TEMP][1] += 8;
|
| | }
|
| | }
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| |
|
| |
|
| | template<typename depth_t>
|
| | static void convert_from_ccs_helper( const Mat& src0, const Mat& src1, Mat& dst )
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| | {
|
| | const int cn = src0.channels();
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| | int srcstep = cn;
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| | int dststep = 1;
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| |
|
| | if( !dst.isContinuous() )
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| | dststep = (int)(dst.step/dst.elemSize());
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| |
|
| | if( !src0.isContinuous() )
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| | srcstep = (int)(src0.step/src0.elemSize1());
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| |
|
| | Complex<depth_t> *dst_data = dst.ptr<Complex<depth_t> >();
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| | const depth_t* src0_data = src0.ptr<depth_t>();
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| | const depth_t* src1_data = src1.ptr<depth_t>();
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| | dst_data->re = src0_data[0];
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| | dst_data->im = 0;
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| | const int n = dst.cols + dst.rows - 1;
|
| | const int n2 = (n+1) >> 1;
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| |
|
| | if( (n & 1) == 0 )
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| | {
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| | dst_data[n2*dststep].re = src0_data[(cn == 1 ? n-1 : n2)*srcstep];
|
| | dst_data[n2*dststep].im = 0;
|
| | }
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| |
|
| | int delta0 = srcstep;
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| | int delta1 = delta0 + (cn == 1 ? srcstep : 1);
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| |
|
| | if( cn == 1 )
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| | srcstep *= 2;
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| |
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| | for( int i = 1; i < n2; i++, delta0 += srcstep, delta1 += srcstep )
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| | {
|
| | depth_t t0 = src0_data[delta0];
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| | depth_t t1 = src0_data[delta1];
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| |
|
| | dst_data[i*dststep].re = t0;
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| | dst_data[i*dststep].im = t1;
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| |
|
| | t0 = src1_data[delta0];
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| | t1 = -src1_data[delta1];
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| |
|
| | dst_data[(n-i)*dststep].re = t0;
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| | dst_data[(n-i)*dststep].im = t1;
|
| | }
|
| | }
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| |
|
| |
|
| | 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);
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| | 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 );
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| |
|
| | 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<float>( src0, src1, dst );
|
| | }
|
| | else
|
| | {
|
| | convert_from_ccs_helper<double>( src0, src1, dst );
|
| | }
|
| | }
|
| | }
|
| |
|
| |
|
| | static std::pair<double, double> 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 );
|
| | }
|
| |
|
| | 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<double, double>(result_re / result_de, result_im / result_de);
|
| | }
|
| |
|
| |
|
| |
|
| | template <typename depth_t>
|
| | 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;
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| |
|
| | for( int i = 0; i < dst.rows; i++ )
|
| | {
|
| | const depth_t *src1_data = src1.ptr<depth_t>(i);
|
| | const depth_t *src2_data = src2.ptr<depth_t>(i);
|
| | depth_t *dst_data = dst.ptr<depth_t>(i);
|
| | for( int j = 0; j < cols; j += 2 )
|
| | {
|
| | std::pair<double, double> 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;
|
| | }
|
| | }
|
| | }
|
| |
|
| |
|
| | 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<float>( src1, src2, dst, flags );
|
| | }
|
| | else
|
| | {
|
| | return div_complex_helper<double>( src1, src2, dst, flags );
|
| | }
|
| | }
|
| |
|
| | void CV_DivSpectrumsTest::prepare_to_validation( int )
|
| | {
|
| | 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();
|
| |
|
| |
|
| | 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 );
|
| | }
|
| |
|
| | 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();
|
| |
|
| |
|
| |
|
| | 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 );
|
| | }
|
| |
|
| | 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(); }
|
| |
|
| | }}
|
| |
|