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b964943517
Add a new function that approximates the polygon bounding a convex hull with a certain number of sides #25607 merge PR with <https://github.com/opencv/opencv_extra/pull/1179> This PR is based on the paper [View Frustum Optimization To Maximize Object’s Image Area](https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=1fbd43f3827fffeb76641a9c5ab5b625eb5a75ba). # Problem I needed to reduce the number of vertices of the convex hull so that the additional area was minimal, andall vertices of the original contour enter the new contour. ![image](https://github.com/Fest1veNapkin/opencv/assets/98156294/efac35f6-b8f0-46ec-91e4-60800432620c) ![image](https://github.com/Fest1veNapkin/opencv/assets/98156294/2292d9d7-1c10-49c9-8489-23221b4b28f7) # Description Initially in the contour of n vertices, at each stage we consider the intersection points of the lines formed by each adjacent edges. Each of these intersection points will form a triangle with vertices through which lines pass. Let's choose a triangle with the minimum area and merge the two vertices at the intersection point. We continue until there are more vertices than the specified number of sides of the approximated polygon. ![image](https://github.com/Fest1veNapkin/opencv/assets/98156294/b87b21c4-112e-450d-a776-2a120048ca30) # Complexity: Using a std::priority_queue or std::set time complexity is **(O(n\*ln(n))**, memory **O(n)**, n - number of vertices in convex hull. count of sides - the number of points by which we must reduce. ![image](https://github.com/Fest1veNapkin/opencv/assets/98156294/31ad5562-a67d-4e3c-bdc2-29f8b52caf88) ## Comment If epsilon_percentage more 0, algorithm can return more values than _side_. Algorithm returns OutputArray. If OutputArray.type() equals 0, algorithm returns values with InputArray.type(). New test uses image which are not in opencv_extra, needs to be added. ### Pull Request Readiness Checklist See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request - [ ] I agree to contribute to the project under Apache 2 License. - [ ] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV - [ ] The PR is proposed to the proper branch - [ ] There is a reference to the original bug report and related work - [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable Patch to opencv_extra has the same branch name. - [ ] The feature is well documented and sample code can be built with the project CMake
456 lines
14 KiB
C++
456 lines
14 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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namespace opencv_test { namespace {
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//
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// TODO!!!:
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// check_slice (and/or check) seem(s) to be broken, or this is a bug in function
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// (or its inability to handle possible self-intersections in the generated contours).
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//
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// At least, if // return TotalErrors;
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// is uncommented in check_slice, the test fails easily.
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// So, now (and it looks like since 0.9.6)
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// we only check that the set of vertices of the approximated polygon is
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// a subset of vertices of the original contour.
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//
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class CV_ApproxPolyTest : public cvtest::BaseTest
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{
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public:
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CV_ApproxPolyTest();
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~CV_ApproxPolyTest();
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void clear();
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//int write_default_params(CvFileStorage* fs);
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protected:
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//int read_params( const cv::FileStorage& fs );
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int check_slice( CvPoint StartPt, CvPoint EndPt,
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CvSeqReader* SrcReader, float Eps,
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int* j, int Count );
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int check( CvSeq* SrcSeq, CvSeq* DstSeq, float Eps );
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bool get_contour( int /*type*/, CvSeq** Seq, int* d,
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CvMemStorage* storage );
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void run(int);
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};
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CV_ApproxPolyTest::CV_ApproxPolyTest()
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{
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}
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CV_ApproxPolyTest::~CV_ApproxPolyTest()
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{
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clear();
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}
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void CV_ApproxPolyTest::clear()
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{
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cvtest::BaseTest::clear();
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}
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/*int CV_ApproxPolyTest::write_default_params( CvFileStorage* fs )
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{
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cvtest::BaseTest::write_default_params( fs );
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if( ts->get_testing_mode() != cvtest::TS::TIMING_MODE )
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{
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write_param( fs, "test_case_count", test_case_count );
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}
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return 0;
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}
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int CV_ApproxPolyTest::read_params( const cv::FileStorage& fs )
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{
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int code = cvtest::BaseTest::read_params( fs );
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if( code < 0 )
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return code;
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test_case_count = cvReadInt( find_param( fs, "test_case_count" ), test_case_count );
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min_log_size = cvtest::clipInt( min_log_size, 1, 10 );
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return 0;
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}*/
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bool CV_ApproxPolyTest::get_contour( int /*type*/, CvSeq** Seq, int* d,
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CvMemStorage* storage )
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{
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RNG& rng = ts->get_rng();
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int max_x = INT_MIN, max_y = INT_MIN, min_x = INT_MAX, min_y = INT_MAX;
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int i;
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CvSeq* seq;
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int total = cvtest::randInt(rng) % 1000 + 1;
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Point center;
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int radius, angle;
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double deg_to_rad = CV_PI/180.;
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Point pt;
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center.x = cvtest::randInt( rng ) % 1000;
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center.y = cvtest::randInt( rng ) % 1000;
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radius = cvtest::randInt( rng ) % 1000;
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angle = cvtest::randInt( rng ) % 360;
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seq = cvCreateSeq( CV_SEQ_POLYGON, sizeof(CvContour), sizeof(CvPoint), storage );
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for( i = 0; i < total; i++ )
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{
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int d_radius = cvtest::randInt( rng ) % 10 - 5;
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int d_angle = 360/total;//cvtest::randInt( rng ) % 10 - 5;
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pt.x = cvRound( center.x + radius*cos(angle*deg_to_rad));
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pt.y = cvRound( center.x - radius*sin(angle*deg_to_rad));
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radius += d_radius;
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angle += d_angle;
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cvSeqPush( seq, &pt );
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max_x = MAX( max_x, pt.x );
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max_y = MAX( max_y, pt.y );
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min_x = MIN( min_x, pt.x );
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min_y = MIN( min_y, pt.y );
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}
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*d = (max_x - min_x)*(max_x - min_x) + (max_y - min_y)*(max_y - min_y);
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*Seq = seq;
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return true;
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}
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int CV_ApproxPolyTest::check_slice( CvPoint StartPt, CvPoint EndPt,
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CvSeqReader* SrcReader, float Eps,
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int* _j, int Count )
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{
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///////////
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Point Pt;
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///////////
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bool flag;
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double dy,dx;
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double A,B,C;
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double Sq;
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double sin_a = 0;
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double cos_a = 0;
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double d = 0;
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double dist;
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///////////
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int j, TotalErrors = 0;
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////////////////////////////////
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if( SrcReader == NULL )
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{
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CV_Assert( false );
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return 0;
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}
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///////// init line ////////////
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flag = true;
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dx = (double)StartPt.x - (double)EndPt.x;
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dy = (double)StartPt.y - (double)EndPt.y;
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if( ( dx == 0 ) && ( dy == 0 ) ) flag = false;
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else
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{
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A = -dy;
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B = dx;
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C = dy * (double)StartPt.x - dx * (double)StartPt.y;
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Sq = sqrt( A*A + B*B );
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sin_a = B/Sq;
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cos_a = A/Sq;
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d = C/Sq;
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}
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/////// find start point and check distance ////////
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for( j = *_j; j < Count; j++ )
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{
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{ CvPoint pt_ = CV_STRUCT_INITIALIZER; CV_READ_SEQ_ELEM(pt_, *SrcReader); Pt = pt_; }
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if( StartPt.x == Pt.x && StartPt.y == Pt.y ) break;
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else
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{
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if( flag ) dist = sin_a * Pt.y + cos_a * Pt.x - d;
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else dist = sqrt( (double)(EndPt.y - Pt.y)*(EndPt.y - Pt.y) + (EndPt.x - Pt.x)*(EndPt.x - Pt.x) );
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if( dist > Eps ) TotalErrors++;
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}
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}
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*_j = j;
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(void) TotalErrors; // To avoid -Wunused-but-set-variable warning
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//return TotalErrors;
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return 0;
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}
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int CV_ApproxPolyTest::check( CvSeq* SrcSeq, CvSeq* DstSeq, float Eps )
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{
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//////////
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CvSeqReader DstReader;
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CvSeqReader SrcReader;
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CvPoint StartPt = {0, 0}, EndPt = {0, 0};
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///////////
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int TotalErrors = 0;
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///////////
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int Count;
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int i,j;
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CV_Assert( SrcSeq && DstSeq );
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////////// init ////////////////////
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Count = SrcSeq->total;
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cvStartReadSeq( DstSeq, &DstReader, 0 );
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cvStartReadSeq( SrcSeq, &SrcReader, 0 );
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CV_READ_SEQ_ELEM( StartPt, DstReader );
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for( i = 0 ; i < Count ; )
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{
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CV_READ_SEQ_ELEM( EndPt, SrcReader );
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i++;
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if( StartPt.x == EndPt.x && StartPt.y == EndPt.y ) break;
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}
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///////// start ////////////////
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for( i = 1, j = 0 ; i <= DstSeq->total ; )
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{
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///////// read slice ////////////
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EndPt.x = StartPt.x;
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EndPt.y = StartPt.y;
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CV_READ_SEQ_ELEM( StartPt, DstReader );
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i++;
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TotalErrors += check_slice( StartPt, EndPt, &SrcReader, Eps, &j, Count );
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if( j > Count )
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{
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TotalErrors++;
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return TotalErrors;
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} //if( !flag )
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} // for( int i = 0 ; i < DstSeq->total ; i++ )
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return TotalErrors;
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}
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//extern CvTestContourGenerator cvTsTestContours[];
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void CV_ApproxPolyTest::run( int /*start_from*/ )
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{
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int code = cvtest::TS::OK;
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CvMemStorage* storage = 0;
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////////////// Variables ////////////////
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int IntervalsCount = 10;
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///////////
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//CvTestContourGenerator Cont;
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CvSeq* SrcSeq = NULL;
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CvSeq* DstSeq;
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int iDiam;
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float dDiam, Eps, EpsStep;
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for( int i = 0; i < 30; i++ )
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{
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CvMemStoragePos pos;
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ts->update_context( this, i, false );
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///////////////////// init contour /////////
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dDiam = 0;
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while( sqrt(dDiam) / IntervalsCount == 0 )
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{
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if( storage != 0 )
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cvReleaseMemStorage(&storage);
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storage = cvCreateMemStorage( 0 );
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if( get_contour( 0, &SrcSeq, &iDiam, storage ) )
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dDiam = (float)iDiam;
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}
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dDiam = (float)sqrt( dDiam );
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storage = SrcSeq->storage;
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////////////////// test /////////////
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EpsStep = dDiam / IntervalsCount ;
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for( Eps = EpsStep ; Eps < dDiam ; Eps += EpsStep )
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{
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cvSaveMemStoragePos( storage, &pos );
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////////// call function ////////////
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DstSeq = cvApproxPoly( SrcSeq, SrcSeq->header_size, storage,
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CV_POLY_APPROX_DP, Eps );
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if( DstSeq == NULL )
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{
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ts->printf( cvtest::TS::LOG,
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"cvApproxPoly returned NULL for contour #%d, epsilon = %g\n", i, Eps );
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code = cvtest::TS::FAIL_INVALID_OUTPUT;
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goto _exit_;
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} // if( DstSeq == NULL )
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code = check( SrcSeq, DstSeq, Eps );
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if( code != 0 )
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{
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ts->printf( cvtest::TS::LOG,
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"Incorrect result for the contour #%d approximated with epsilon=%g\n", i, Eps );
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code = cvtest::TS::FAIL_BAD_ACCURACY;
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goto _exit_;
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}
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cvRestoreMemStoragePos( storage, &pos );
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} // for( Eps = EpsStep ; Eps <= Diam ; Eps += EpsStep )
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///////////// free memory ///////////////////
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cvReleaseMemStorage(&storage);
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} // for( int i = 0; NULL != ( Cont = Contours[i] ) ; i++ )
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_exit_:
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cvReleaseMemStorage(&storage);
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if( code < 0 )
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ts->set_failed_test_info( code );
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}
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TEST(Imgproc_ApproxPoly, accuracy) { CV_ApproxPolyTest test; test.safe_run(); }
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//Tests to make sure that unreasonable epsilon (error)
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//values never get passed to the Douglas-Peucker algorithm.
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TEST(Imgproc_ApproxPoly, bad_epsilon)
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{
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std::vector<Point2f> inputPoints;
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inputPoints.push_back(Point2f(0.0f, 0.0f));
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std::vector<Point2f> outputPoints;
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double eps = std::numeric_limits<double>::infinity();
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ASSERT_ANY_THROW(approxPolyDP(inputPoints, outputPoints, eps, false));
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eps = 9e99;
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ASSERT_ANY_THROW(approxPolyDP(inputPoints, outputPoints, eps, false));
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eps = -1e-6;
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ASSERT_ANY_THROW(approxPolyDP(inputPoints, outputPoints, eps, false));
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eps = NAN;
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ASSERT_ANY_THROW(approxPolyDP(inputPoints, outputPoints, eps, false));
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}
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struct ApproxPolyN: public testing::Test
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{
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void SetUp()
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{
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vector<vector<Point>> inputPoints = {
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{ {87, 103}, {100, 112}, {96, 138}, {80, 169}, {60, 183}, {38, 176}, {41, 145}, {56, 118}, {76, 104} },
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{ {196, 102}, {205, 118}, {174, 196}, {152, 207}, {102, 194}, {100, 175}, {131, 109} },
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{ {372, 101}, {377, 119}, {337, 238}, {324, 248}, {240, 229}, {199, 214}, {232, 123}, {245, 103} },
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{ {463, 86}, {563, 112}, {574, 135}, {596, 221}, {518, 298}, {412, 266}, {385, 164}, {462, 86} }
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};
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Mat image(600, 600, CV_8UC1, Scalar(0));
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for (vector<Point>& polygon : inputPoints) {
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polylines(image, { polygon }, true, Scalar(255), 1);
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}
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findContours(image, contours, RETR_LIST, CHAIN_APPROX_NONE);
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}
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vector<vector<Point>> contours;
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};
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TEST_F(ApproxPolyN, accuracyInt)
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{
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vector<vector<Point>> rightCorners = {
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{ {72, 187}, {37, 176}, {42, 127}, {133, 64} },
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{ {168, 212}, {92, 192}, {131, 109}, {213, 100} },
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{ {72, 187}, {37, 176}, {42, 127}, {133, 64} },
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{ {384, 100}, {333, 251}, {197, 220}, {239, 103} },
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{ {168, 212}, {92, 192}, {131, 109}, {213, 100} },
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{ {333, 251}, {197, 220}, {239, 103}, {384, 100} },
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{ {542, 6}, {596, 221}, {518, 299}, {312, 236} },
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{ {596, 221}, {518, 299}, {312, 236}, {542, 6} }
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};
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EXPECT_EQ(rightCorners.size(), contours.size());
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for (size_t i = 0; i < contours.size(); ++i) {
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std::vector<Point> corners;
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approxPolyN(contours[i], corners, 4, -1, true);
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ASSERT_EQ(rightCorners[i], corners );
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}
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}
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TEST_F(ApproxPolyN, accuracyFloat)
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{
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vector<vector<Point2f>> rightCorners = {
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{ {72.f, 187.f}, {37.f, 176.f}, {42.f, 127.f}, {133.f, 64.f} },
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{ {168.f, 212.f}, {92.f, 192.f}, {131.f, 109.f}, {213.f, 100.f} },
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{ {72.f, 187.f}, {37.f, 176.f}, {42.f, 127.f}, {133.f, 64.f} },
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{ {384.f, 100.f}, {333.f, 251.f}, {197.f, 220.f}, {239.f, 103.f} },
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{ {168.f, 212.f}, {92.f, 192.f}, {131.f, 109.f}, {213.f, 100.f} },
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{ {333.f, 251.f}, {197.f, 220.f}, {239.f, 103.f}, {384.f, 100.f} },
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{ {542.f, 6.f}, {596.f, 221.f}, {518.f, 299.f}, {312.f, 236.f} },
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{ {596.f, 221.f}, {518.f, 299.f}, {312.f, 236.f}, {542.f, 6.f} }
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};
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EXPECT_EQ(rightCorners.size(), contours.size());
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for (size_t i = 0; i < contours.size(); ++i) {
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std::vector<Point2f> corners;
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approxPolyN(contours[i], corners, 4, -1, true);
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EXPECT_LT(cvtest::norm(rightCorners[i], corners, NORM_INF), .5f);
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}
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}
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TEST_F(ApproxPolyN, bad_args)
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{
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Mat contour(10, 1, CV_32FC2);
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vector<vector<Point>> bad_contours;
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vector<Point> corners;
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ASSERT_ANY_THROW(approxPolyN(contour, corners, 0));
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ASSERT_ANY_THROW(approxPolyN(contour, corners, 3, 0));
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ASSERT_ANY_THROW(approxPolyN(bad_contours, corners, 4));
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}
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}} // namespace
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