2011-02-10 04:55:11 +08:00
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/*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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2017-11-05 21:48:40 +08:00
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namespace opencv_test {
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2011-02-10 04:55:11 +08:00
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static void test_convertHomogeneous( const Mat& _src, Mat& _dst )
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{
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Mat src = _src, dst = _dst;
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int i, count, sdims, ddims;
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int sstep1, sstep2, dstep1, dstep2;
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if( src.depth() != CV_64F )
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_src.convertTo(src, CV_64F);
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2012-10-17 15:12:04 +08:00
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2011-02-10 04:55:11 +08:00
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if( dst.depth() != CV_64F )
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dst.create(dst.size(), CV_MAKETYPE(CV_64F, _dst.channels()));
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if( src.rows > src.cols )
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{
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count = src.rows;
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sdims = src.channels()*src.cols;
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2011-07-19 20:27:07 +08:00
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sstep1 = (int)(src.step/sizeof(double));
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2011-02-10 04:55:11 +08:00
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sstep2 = 1;
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}
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else
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{
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count = src.cols;
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sdims = src.channels()*src.rows;
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if( src.rows == 1 )
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{
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sstep1 = sdims;
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sstep2 = 1;
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}
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else
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{
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sstep1 = 1;
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2011-07-19 20:27:07 +08:00
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sstep2 = (int)(src.step/sizeof(double));
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2011-02-10 04:55:11 +08:00
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}
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}
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if( dst.rows > dst.cols )
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{
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CV_Assert( count == dst.rows );
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ddims = dst.channels()*dst.cols;
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2011-07-19 20:27:07 +08:00
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dstep1 = (int)(dst.step/sizeof(double));
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2011-02-10 04:55:11 +08:00
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dstep2 = 1;
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}
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else
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{
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2021-11-28 02:34:52 +08:00
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CV_Assert( count == dst.cols );
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2011-02-10 04:55:11 +08:00
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ddims = dst.channels()*dst.rows;
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if( dst.rows == 1 )
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{
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dstep1 = ddims;
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dstep2 = 1;
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}
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else
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{
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dstep1 = 1;
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2011-07-19 20:27:07 +08:00
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dstep2 = (int)(dst.step/sizeof(double));
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2011-02-10 04:55:11 +08:00
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}
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}
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double* s = src.ptr<double>();
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double* d = dst.ptr<double>();
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if( sdims <= ddims )
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{
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int wstep = dstep2*(ddims - 1);
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for( i = 0; i < count; i++, s += sstep1, d += dstep1 )
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{
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double x = s[0];
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double y = s[sstep2];
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d[wstep] = 1;
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d[0] = x;
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d[dstep2] = y;
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if( sdims >= 3 )
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{
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d[dstep2*2] = s[sstep2*2];
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if( sdims == 4 )
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d[dstep2*3] = s[sstep2*3];
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}
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}
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}
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else
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{
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int wstep = sstep2*(sdims - 1);
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for( i = 0; i < count; i++, s += sstep1, d += dstep1 )
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{
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double w = s[wstep];
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double x = s[0];
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double y = s[sstep2];
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w = w ? 1./w : 1;
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d[0] = x*w;
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d[dstep2] = y*w;
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if( ddims == 3 )
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d[dstep2*2] = s[sstep2*2]*w;
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}
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}
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if( dst.data != _dst.data )
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dst.convertTo(_dst, _dst.depth());
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}
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2017-11-05 21:48:40 +08:00
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namespace {
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2011-02-10 04:55:11 +08:00
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/********************************** convert homogeneous *********************************/
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class CV_ConvertHomogeneousTest : public cvtest::ArrayTest
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{
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public:
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CV_ConvertHomogeneousTest();
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protected:
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2018-11-02 05:27:06 +08:00
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int read_params( const cv::FileStorage& fs );
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2011-02-10 04:55:11 +08:00
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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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void fill_array( int test_case_idx, int i, int j, Mat& arr );
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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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int dims1, dims2;
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int pt_count;
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};
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CV_ConvertHomogeneousTest::CV_ConvertHomogeneousTest()
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{
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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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element_wise_relative_error = false;
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pt_count = dims1 = dims2 = 0;
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}
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2018-11-02 05:27:06 +08:00
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int CV_ConvertHomogeneousTest::read_params( const cv::FileStorage& fs )
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2011-02-10 04:55:11 +08:00
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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_ConvertHomogeneousTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
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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 pt_depth1 = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
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2018-11-09 21:12:22 +08:00
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int pt_depth2 = pt_depth1;//cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
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2011-02-10 04:55:11 +08:00
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double pt_count_exp = cvtest::randReal(rng)*6 + 1;
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int t;
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pt_count = cvRound(exp(pt_count_exp));
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pt_count = MAX( pt_count, 5 );
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2018-11-09 21:12:22 +08:00
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dims1 = 2 + (cvtest::randInt(rng) % 2);
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dims2 = dims1 + 1;
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2011-02-10 04:55:11 +08:00
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if( cvtest::randInt(rng) % 2 )
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CV_SWAP( dims1, dims2, t );
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types[INPUT][0] = CV_MAKETYPE(pt_depth1, 1);
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2024-10-10 15:20:22 +08:00
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sizes[INPUT][0] = Size(dims1, pt_count);
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2011-02-10 04:55:11 +08:00
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if( cvtest::randInt(rng) % 2 )
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{
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2018-11-09 21:12:22 +08:00
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types[INPUT][0] = CV_MAKETYPE(pt_depth1, dims1);
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2011-02-10 04:55:11 +08:00
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if( cvtest::randInt(rng) % 2 )
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2024-10-10 15:20:22 +08:00
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sizes[INPUT][0] = Size(pt_count, 1);
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2018-11-09 21:12:22 +08:00
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else
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2024-10-10 15:20:22 +08:00
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sizes[INPUT][0] = Size(1, pt_count);
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2011-02-10 04:55:11 +08:00
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}
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2018-11-09 21:12:22 +08:00
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types[OUTPUT][0] = CV_MAKETYPE(pt_depth2, dims2);
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2024-10-10 15:20:22 +08:00
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sizes[OUTPUT][0] = Size(1, pt_count);
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2011-02-10 04:55:11 +08:00
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types[REF_OUTPUT][0] = types[OUTPUT][0];
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sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
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}
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double CV_ConvertHomogeneousTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
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{
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return 1e-5;
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}
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void CV_ConvertHomogeneousTest::fill_array( int /*test_case_idx*/, int /*i*/, int /*j*/, Mat& arr )
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{
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Mat temp( 1, pt_count, CV_MAKETYPE(CV_64FC1,dims1) );
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RNG& rng = ts->get_rng();
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2024-10-10 15:20:22 +08:00
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Scalar low = Scalar::all(0), high = Scalar::all(10);
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2011-02-10 04:55:11 +08:00
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if( dims1 > dims2 )
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low.val[dims1-1] = 1.;
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cvtest::randUni( rng, temp, low, high );
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test_convertHomogeneous( temp, arr );
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}
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void CV_ConvertHomogeneousTest::run_func()
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{
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2018-11-09 21:12:22 +08:00
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cv::Mat _input = test_mat[INPUT][0], &_output = test_mat[OUTPUT][0];
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if( dims1 > dims2 )
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cv::convertPointsFromHomogeneous(_input, _output);
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else
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cv::convertPointsToHomogeneous(_input, _output);
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2011-02-10 04:55:11 +08:00
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}
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void CV_ConvertHomogeneousTest::prepare_to_validation( int /*test_case_idx*/ )
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{
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test_convertHomogeneous( test_mat[INPUT][0], test_mat[REF_OUTPUT][0] );
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}
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/************************** compute corresponding epipolar lines ************************/
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class CV_ComputeEpilinesTest : public cvtest::ArrayTest
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{
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public:
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CV_ComputeEpilinesTest();
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protected:
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2018-11-02 05:27:06 +08:00
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int read_params( const cv::FileStorage& fs );
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2011-02-10 04:55:11 +08:00
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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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void fill_array( int test_case_idx, int i, int j, Mat& arr );
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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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int which_image;
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int dims;
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int pt_count;
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};
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CV_ComputeEpilinesTest::CV_ComputeEpilinesTest()
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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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element_wise_relative_error = false;
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pt_count = dims = which_image = 0;
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}
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2018-11-02 05:27:06 +08:00
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int CV_ComputeEpilinesTest::read_params( const cv::FileStorage& fs )
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2011-02-10 04:55:11 +08:00
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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_ComputeEpilinesTest::get_test_array_types_and_sizes( int /*test_case_idx*/,
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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 fm_depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
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int pt_depth = cvtest::randInt(rng) % 2 == 0 ? CV_32F : CV_64F;
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2018-11-09 21:12:22 +08:00
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int ln_depth = pt_depth;
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2012-03-28 21:37:14 +08:00
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double pt_count_exp = cvtest::randReal(rng)*6;
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2011-02-10 04:55:11 +08:00
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which_image = 1 + (cvtest::randInt(rng) % 2);
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pt_count = cvRound(exp(pt_count_exp));
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2012-03-28 21:37:14 +08:00
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pt_count = MAX( pt_count, 1 );
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bool few_points = pt_count < 5;
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2011-02-10 04:55:11 +08:00
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dims = 2 + (cvtest::randInt(rng) % 2);
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types[INPUT][0] = CV_MAKETYPE(pt_depth, 1);
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2024-10-10 15:20:22 +08:00
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sizes[INPUT][0] = Size(dims, pt_count);
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2018-11-09 21:12:22 +08:00
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if( cvtest::randInt(rng) % 2 || few_points )
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2011-02-10 04:55:11 +08:00
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{
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2018-11-09 21:12:22 +08:00
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types[INPUT][0] = CV_MAKETYPE(pt_depth, dims);
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if( cvtest::randInt(rng) % 2 )
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2024-10-10 15:20:22 +08:00
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sizes[INPUT][0] = Size(pt_count, 1);
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2018-11-09 21:12:22 +08:00
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else
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2024-10-10 15:20:22 +08:00
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sizes[INPUT][0] = Size(1, pt_count);
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2011-02-10 04:55:11 +08:00
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}
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types[INPUT][1] = CV_MAKETYPE(fm_depth, 1);
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2024-10-10 15:20:22 +08:00
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sizes[INPUT][1] = Size(3, 3);
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2011-02-10 04:55:11 +08:00
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2018-11-09 21:12:22 +08:00
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types[OUTPUT][0] = CV_MAKETYPE(ln_depth, 3);
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2024-10-10 15:20:22 +08:00
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sizes[OUTPUT][0] = Size(1, pt_count);
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2011-02-10 04:55:11 +08:00
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types[REF_OUTPUT][0] = types[OUTPUT][0];
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sizes[REF_OUTPUT][0] = sizes[OUTPUT][0];
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}
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double CV_ComputeEpilinesTest::get_success_error_level( int /*test_case_idx*/, int /*i*/, int /*j*/ )
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|
|
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{
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|
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return 1e-5;
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}
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void CV_ComputeEpilinesTest::fill_array( int test_case_idx, int i, int j, Mat& arr )
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|
|
|
{
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RNG& rng = ts->get_rng();
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if( i == INPUT && j == 0 )
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{
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Mat temp( 1, pt_count, CV_MAKETYPE(CV_64FC1,dims) );
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2024-10-10 15:20:22 +08:00
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cvtest::randUni( rng, temp, Scalar(0,0,1), Scalar::all(10) );
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2011-02-10 04:55:11 +08:00
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test_convertHomogeneous( temp, arr );
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}
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else if( i == INPUT && j == 1 )
|
2024-10-10 15:20:22 +08:00
|
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cvtest::randUni( rng, arr, Scalar::all(0), Scalar::all(10) );
|
2011-02-10 04:55:11 +08:00
|
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|
else
|
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cvtest::ArrayTest::fill_array( test_case_idx, i, j, arr );
|
|
|
|
}
|
|
|
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|
void CV_ComputeEpilinesTest::run_func()
|
|
|
|
{
|
2018-11-09 21:12:22 +08:00
|
|
|
cv::Mat _points = test_mat[INPUT][0], _F = test_mat[INPUT][1], &_lines = test_mat[OUTPUT][0];
|
|
|
|
cv::computeCorrespondEpilines( _points, which_image, _F, _lines );
|
2011-02-10 04:55:11 +08:00
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
void CV_ComputeEpilinesTest::prepare_to_validation( int /*test_case_idx*/ )
|
|
|
|
{
|
|
|
|
Mat pt( 1, pt_count, CV_MAKETYPE(CV_64F, 3) );
|
|
|
|
Mat lines( 1, pt_count, CV_MAKETYPE(CV_64F, 3) );
|
|
|
|
double f[9];
|
|
|
|
Mat F( 3, 3, CV_64F, f );
|
|
|
|
|
|
|
|
test_convertHomogeneous( test_mat[INPUT][0], pt );
|
|
|
|
test_mat[INPUT][1].convertTo(F, CV_64F);
|
|
|
|
if( which_image == 2 )
|
|
|
|
cv::transpose( F, F );
|
|
|
|
|
|
|
|
for( int i = 0; i < pt_count; i++ )
|
|
|
|
{
|
|
|
|
double* p = pt.ptr<double>() + i*3;
|
|
|
|
double* l = lines.ptr<double>() + i*3;
|
|
|
|
double t0 = f[0]*p[0] + f[1]*p[1] + f[2]*p[2];
|
|
|
|
double t1 = f[3]*p[0] + f[4]*p[1] + f[5]*p[2];
|
|
|
|
double t2 = f[6]*p[0] + f[7]*p[1] + f[8]*p[2];
|
|
|
|
double d = sqrt(t0*t0 + t1*t1);
|
|
|
|
d = d ? 1./d : 1.;
|
|
|
|
l[0] = t0*d; l[1] = t1*d; l[2] = t2*d;
|
|
|
|
}
|
|
|
|
|
|
|
|
test_convertHomogeneous( lines, test_mat[REF_OUTPUT][0] );
|
|
|
|
}
|
|
|
|
|
|
|
|
TEST(Calib3d_ConvertHomogeneoous, accuracy) { CV_ConvertHomogeneousTest test; test.safe_run(); }
|
|
|
|
TEST(Calib3d_ComputeEpilines, accuracy) { CV_ComputeEpilinesTest test; test.safe_run(); }
|
2012-03-28 21:37:14 +08:00
|
|
|
|
2015-05-26 04:43:39 +08:00
|
|
|
TEST(Calib3d_FindFundamentalMat, correctMatches)
|
|
|
|
{
|
|
|
|
double fdata[] = {0, 0, 0, 0, 0, -1, 0, 1, 0};
|
|
|
|
double p1data[] = {200, 0, 1};
|
|
|
|
double p2data[] = {170, 0, 1};
|
|
|
|
|
|
|
|
Mat F(3, 3, CV_64F, fdata);
|
|
|
|
Mat p1(1, 1, CV_64FC2, p1data);
|
|
|
|
Mat p2(1, 1, CV_64FC2, p2data);
|
|
|
|
Mat np1, np2;
|
|
|
|
|
|
|
|
correctMatches(F, p1, p2, np1, np2);
|
|
|
|
|
|
|
|
cout << np1 << endl;
|
|
|
|
cout << np2 << endl;
|
|
|
|
}
|
|
|
|
|
2017-11-05 21:48:40 +08:00
|
|
|
}} // namespace
|
2011-02-10 04:55:11 +08:00
|
|
|
/* End of file. */
|