mirror of
https://github.com/opencv/opencv.git
synced 2024-12-15 01:39:10 +08:00
6350bfbf79
imgproc: C-API cleanup, drawContours refactor #25564 Changes: * moved several macros from types_c.h to cvdef.h (assuming we will continue using them) * removed some cases of C-API usage in _imgproc_ module (`CV_TERMCRIT_*` and `CV_CMP_*`) * refactored `drawContours` to use C++ API instead of calling `cvDrawContours` + test for filled contours with holes (case with non-filled contours is simpler and is covered in some other tests) #### Note: There is one case where old drawContours behavior doesn't match the new one - when `contourIdx == -1` (means "draw all contours") and `maxLevel == 0` (means draw only selected contours, but not what is inside). From the docs: > **contourIdx** Parameter indicating a contour to draw. If it is negative, all the contours are drawn. > **maxLevel** Maximal level for drawn contours. If it is 0, only the specified contour is drawn. If it is 1, the function draws the contour(s) and all the nested contours. If it is 2, the function draws the contours, all the nested contours, all the nested-to-nested contours, and so on. This parameter is only taken into account when there is hierarchy available. Old behavior - only one first contour is drawn:  a New behavior (also expected by the test) - all contours are drawn: 
2489 lines
76 KiB
C++
2489 lines
76 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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/*static int
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cvTsPointConvexPolygon( CvPoint2D32f pt, CvPoint2D32f* v, int n )
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{
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CvPoint2D32f v0 = v[n-1];
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int i, sign = 0;
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for( i = 0; i < n; i++ )
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{
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CvPoint2D32f v1 = v[i];
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float dx = pt.x - v0.x, dy = pt.y - v0.y;
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float dx1 = v1.x - v0.x, dy1 = v1.y - v0.y;
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double t = (double)dx*dy1 - (double)dx1*dy;
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if( fabs(t) > DBL_EPSILON )
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{
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if( t*sign < 0 )
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break;
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if( sign == 0 )
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sign = t < 0 ? -1 : 1;
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}
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else if( fabs(dx) + fabs(dy) < DBL_EPSILON )
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return i+1;
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v0 = v1;
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}
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return i < n ? -1 : 0;
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}*/
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CV_INLINE double
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cvTsDist( CvPoint2D32f a, CvPoint2D32f b )
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{
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double dx = a.x - b.x;
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double dy = a.y - b.y;
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return sqrt(dx*dx + dy*dy);
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}
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CV_INLINE double
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cvTsDist( const Point2f& a, const Point2f& b )
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{
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double dx = a.x - b.x;
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double dy = a.y - b.y;
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return sqrt(dx*dx + dy*dy);
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}
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CV_INLINE double
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cvTsPtLineDist( CvPoint2D32f pt, CvPoint2D32f a, CvPoint2D32f b )
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{
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double d0 = cvTsDist( pt, a ), d1;
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double dd = cvTsDist( a, b );
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if( dd < FLT_EPSILON )
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return d0;
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d1 = cvTsDist( pt, b );
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dd = fabs((double)(pt.x - a.x)*(b.y - a.y) - (double)(pt.y - a.y)*(b.x - a.x))/dd;
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d0 = MIN( d0, d1 );
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return MIN( d0, dd );
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}
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static double
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cvTsPointPolygonTest( CvPoint2D32f pt, const CvPoint2D32f* vv, int n, int* _idx=0, int* _on_edge=0 )
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{
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int i;
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Point2f v = vv[n-1], v0;
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double min_dist_num = FLT_MAX, min_dist_denom = 1;
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int min_dist_idx = -1, min_on_edge = 0;
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int counter = 0;
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double result;
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for( i = 0; i < n; i++ )
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{
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double dx, dy, dx1, dy1, dx2, dy2, dist_num, dist_denom = 1;
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int on_edge = 0, idx = i;
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v0 = v; v = vv[i];
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dx = v.x - v0.x; dy = v.y - v0.y;
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dx1 = pt.x - v0.x; dy1 = pt.y - v0.y;
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dx2 = pt.x - v.x; dy2 = pt.y - v.y;
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if( dx2*dx + dy2*dy >= 0 )
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dist_num = dx2*dx2 + dy2*dy2;
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else if( dx1*dx + dy1*dy <= 0 )
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{
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dist_num = dx1*dx1 + dy1*dy1;
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idx = i - 1;
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if( idx < 0 ) idx = n-1;
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}
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else
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{
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dist_num = (dy1*dx - dx1*dy);
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dist_num *= dist_num;
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dist_denom = dx*dx + dy*dy;
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on_edge = 1;
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}
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if( dist_num*min_dist_denom < min_dist_num*dist_denom )
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{
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min_dist_num = dist_num;
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min_dist_denom = dist_denom;
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min_dist_idx = idx;
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min_on_edge = on_edge;
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if( min_dist_num == 0 )
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break;
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}
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if( (v0.y <= pt.y && v.y <= pt.y) ||
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(v0.y > pt.y && v.y > pt.y) ||
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(v0.x < pt.x && v.x < pt.x) )
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continue;
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dist_num = dy1*dx - dx1*dy;
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if( dy < 0 )
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dist_num = -dist_num;
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counter += dist_num > 0;
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}
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result = sqrt(min_dist_num/min_dist_denom);
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if( counter % 2 == 0 )
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result = -result;
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if( _idx )
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*_idx = min_dist_idx;
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if( _on_edge )
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*_on_edge = min_on_edge;
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return result;
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}
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static cv::Point2f
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cvTsMiddlePoint(const cv::Point2f &a, const cv::Point2f &b)
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{
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return cv::Point2f((a.x + b.x) / 2, (a.y + b.y) / 2);
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}
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static bool
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cvTsIsPointOnLineSegment(const cv::Point2f &x, const cv::Point2f &a, const cv::Point2f &b)
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{
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double d1 = cvTsDist(cvPoint2D32f(x.x, x.y), cvPoint2D32f(a.x, a.y));
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double d2 = cvTsDist(cvPoint2D32f(x.x, x.y), cvPoint2D32f(b.x, b.y));
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double d3 = cvTsDist(cvPoint2D32f(a.x, a.y), cvPoint2D32f(b.x, b.y));
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return (abs(d1 + d2 - d3) <= (1E-4));
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}
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/****************************************************************************************\
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* Base class for shape descriptor tests *
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\****************************************************************************************/
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class CV_BaseShapeDescrTest : public cvtest::BaseTest
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{
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public:
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CV_BaseShapeDescrTest();
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virtual ~CV_BaseShapeDescrTest();
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void clear();
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protected:
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int read_params( const cv::FileStorage& fs );
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void run_func(void);
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int prepare_test_case( int test_case_idx );
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int validate_test_results( int test_case_idx );
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virtual void generate_point_set( void* points );
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virtual void extract_points();
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int min_log_size;
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int max_log_size;
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int dims;
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bool enable_flt_points;
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CvMemStorage* storage;
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CvSeq* points1;
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CvMat* points2;
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void* points;
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void* result;
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double low_high_range;
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Scalar low, high;
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bool test_cpp;
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};
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CV_BaseShapeDescrTest::CV_BaseShapeDescrTest()
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{
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points1 = 0;
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points2 = 0;
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points = 0;
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storage = 0;
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test_case_count = 500;
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min_log_size = 0;
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max_log_size = 10;
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low = high = cvScalarAll(0);
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low_high_range = 50;
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dims = 2;
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enable_flt_points = true;
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test_cpp = false;
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}
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CV_BaseShapeDescrTest::~CV_BaseShapeDescrTest()
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{
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clear();
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}
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void CV_BaseShapeDescrTest::clear()
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{
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cvtest::BaseTest::clear();
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cvReleaseMemStorage( &storage );
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cvReleaseMat( &points2 );
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points1 = 0;
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points = 0;
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}
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int CV_BaseShapeDescrTest::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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read( find_param( fs, "struct_count" ), test_case_count, test_case_count );
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read( find_param( fs, "min_log_size" ), min_log_size, min_log_size );
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read( find_param( fs, "max_log_size" ), max_log_size, max_log_size );
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min_log_size = cvtest::clipInt( min_log_size, 0, 8 );
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max_log_size = cvtest::clipInt( max_log_size, 0, 10 );
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if( min_log_size > max_log_size )
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{
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int t;
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CV_SWAP( min_log_size, max_log_size, t );
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}
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return 0;
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}
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void CV_BaseShapeDescrTest::generate_point_set( void* pointsSet )
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{
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RNG& rng = ts->get_rng();
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int i, k, n, total, point_type;
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CvSeqReader reader;
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uchar* data = 0;
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double a[4], b[4];
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for( k = 0; k < 4; k++ )
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{
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a[k] = high.val[k] - low.val[k];
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b[k] = low.val[k];
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}
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memset( &reader, 0, sizeof(reader) );
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if( CV_IS_SEQ(pointsSet) )
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{
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CvSeq* ptseq = (CvSeq*)pointsSet;
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total = ptseq->total;
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point_type = CV_SEQ_ELTYPE(ptseq);
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cvStartReadSeq( ptseq, &reader );
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}
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else
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{
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CvMat* ptm = (CvMat*)pointsSet;
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CV_Assert( CV_IS_MAT(ptm) && CV_IS_MAT_CONT(ptm->type) );
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total = ptm->rows + ptm->cols - 1;
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point_type = CV_MAT_TYPE(ptm->type);
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data = ptm->data.ptr;
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}
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n = CV_MAT_CN(point_type);
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point_type = CV_MAT_DEPTH(point_type);
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CV_Assert( (point_type == CV_32S || point_type == CV_32F) && n <= 4 );
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for( i = 0; i < total; i++ )
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{
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int* pi;
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float* pf;
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if( reader.ptr )
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{
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pi = (int*)reader.ptr;
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pf = (float*)reader.ptr;
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CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader );
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}
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else
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{
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pi = (int*)data + i*n;
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pf = (float*)data + i*n;
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}
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if( point_type == CV_32S )
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for( k = 0; k < n; k++ )
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pi[k] = cvRound(cvtest::randReal(rng)*a[k] + b[k]);
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else
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for( k = 0; k < n; k++ )
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pf[k] = (float)(cvtest::randReal(rng)*a[k] + b[k]);
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}
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}
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int CV_BaseShapeDescrTest::prepare_test_case( int test_case_idx )
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{
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int size;
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int use_storage = 0;
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int point_type;
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int i;
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RNG& rng = ts->get_rng();
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cvtest::BaseTest::prepare_test_case( test_case_idx );
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clear();
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size = cvRound( exp((cvtest::randReal(rng) * (max_log_size - min_log_size) + min_log_size)*CV_LOG2) );
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use_storage = cvtest::randInt(rng) % 2;
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point_type = CV_MAKETYPE(cvtest::randInt(rng) %
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(enable_flt_points ? 2 : 1) ? CV_32F : CV_32S, dims);
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if( use_storage )
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{
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storage = cvCreateMemStorage( (cvtest::randInt(rng)%10 + 1)*1024 );
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points1 = cvCreateSeq( point_type, sizeof(CvSeq), CV_ELEM_SIZE(point_type), storage );
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cvSeqPushMulti( points1, 0, size );
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points = points1;
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}
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else
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{
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int rows = 1, cols = size;
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if( cvtest::randInt(rng) % 2 )
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rows = size, cols = 1;
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points2 = cvCreateMat( rows, cols, point_type );
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points = points2;
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}
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for( i = 0; i < 4; i++ )
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{
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low.val[i] = (cvtest::randReal(rng)-0.5)*low_high_range*2;
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high.val[i] = (cvtest::randReal(rng)-0.5)*low_high_range*2;
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if( low.val[i] > high.val[i] )
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{
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double t;
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CV_SWAP( low.val[i], high.val[i], t );
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}
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if( high.val[i] < low.val[i] + 1 )
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high.val[i] += 1;
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}
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generate_point_set( points );
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test_cpp = (cvtest::randInt(rng) & 16) == 0;
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return 1;
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}
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void CV_BaseShapeDescrTest::extract_points()
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{
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if( points1 )
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{
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points2 = cvCreateMat( 1, points1->total, CV_SEQ_ELTYPE(points1) );
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cvCvtSeqToArray( points1, points2->data.ptr );
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}
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if( CV_MAT_DEPTH(points2->type) != CV_32F && enable_flt_points )
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{
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CvMat tmp = cvMat( points2->rows, points2->cols,
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(points2->type & ~CV_MAT_DEPTH_MASK) | CV_32F, points2->data.ptr );
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cvConvert( points2, &tmp );
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}
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}
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void CV_BaseShapeDescrTest::run_func(void)
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{
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}
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int CV_BaseShapeDescrTest::validate_test_results( int /*test_case_idx*/ )
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{
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extract_points();
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return 0;
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}
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|
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/****************************************************************************************\
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* Convex Hull Test *
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\****************************************************************************************/
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class CV_ConvHullTest : public CV_BaseShapeDescrTest
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{
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public:
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CV_ConvHullTest();
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virtual ~CV_ConvHullTest();
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void clear();
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protected:
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void run_func(void);
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int prepare_test_case( int test_case_idx );
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int validate_test_results( int test_case_idx );
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CvSeq* hull1;
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CvMat* hull2;
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void* hull_storage;
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int orientation;
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int return_points;
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};
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CV_ConvHullTest::CV_ConvHullTest()
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{
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hull1 = 0;
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hull2 = 0;
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hull_storage = 0;
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orientation = return_points = 0;
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}
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|
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CV_ConvHullTest::~CV_ConvHullTest()
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{
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clear();
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}
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|
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void CV_ConvHullTest::clear()
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{
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CV_BaseShapeDescrTest::clear();
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cvReleaseMat( &hull2 );
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hull1 = 0;
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hull_storage = 0;
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}
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|
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int CV_ConvHullTest::prepare_test_case( int test_case_idx )
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|
{
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int code = CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
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int use_storage_for_hull = 0;
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RNG& rng = ts->get_rng();
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if( code <= 0 )
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return code;
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orientation = cvtest::randInt(rng) % 2 ? CV_CLOCKWISE : CV_COUNTER_CLOCKWISE;
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return_points = cvtest::randInt(rng) % 2;
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use_storage_for_hull = (cvtest::randInt(rng) % 2) && !test_cpp;
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if( use_storage_for_hull )
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{
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if( !storage )
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storage = cvCreateMemStorage( (cvtest::randInt(rng)%10 + 1)*1024 );
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hull_storage = storage;
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}
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else
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{
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int rows, cols;
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int sz = points1 ? points1->total : points2->cols + points2->rows - 1;
|
|
int point_type = points1 ? CV_SEQ_ELTYPE(points1) : CV_MAT_TYPE(points2->type);
|
|
|
|
if( cvtest::randInt(rng) % 2 )
|
|
rows = sz, cols = 1;
|
|
else
|
|
rows = 1, cols = sz;
|
|
|
|
hull2 = cvCreateMat( rows, cols, return_points ? point_type : CV_32SC1 );
|
|
hull_storage = hull2;
|
|
}
|
|
|
|
return code;
|
|
}
|
|
|
|
|
|
void CV_ConvHullTest::run_func()
|
|
{
|
|
if(!test_cpp)
|
|
hull1 = cvConvexHull2( points, hull_storage, orientation, return_points );
|
|
else
|
|
{
|
|
cv::Mat _points = cv::cvarrToMat(points);
|
|
bool clockwise = orientation == CV_CLOCKWISE;
|
|
size_t n = 0;
|
|
if( !return_points )
|
|
{
|
|
std::vector<int> _hull;
|
|
cv::convexHull(_points, _hull, clockwise);
|
|
n = _hull.size();
|
|
memcpy(hull2->data.ptr, &_hull[0], n*sizeof(_hull[0]));
|
|
}
|
|
else if(_points.type() == CV_32SC2)
|
|
{
|
|
std::vector<cv::Point> _hull;
|
|
cv::convexHull(_points, _hull, clockwise);
|
|
n = _hull.size();
|
|
memcpy(hull2->data.ptr, &_hull[0], n*sizeof(_hull[0]));
|
|
}
|
|
else if(_points.type() == CV_32FC2)
|
|
{
|
|
std::vector<cv::Point2f> _hull;
|
|
cv::convexHull(_points, _hull, clockwise);
|
|
n = _hull.size();
|
|
memcpy(hull2->data.ptr, &_hull[0], n*sizeof(_hull[0]));
|
|
}
|
|
if(hull2->rows > hull2->cols)
|
|
hull2->rows = (int)n;
|
|
else
|
|
hull2->cols = (int)n;
|
|
}
|
|
}
|
|
|
|
|
|
int CV_ConvHullTest::validate_test_results( int test_case_idx )
|
|
{
|
|
int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
|
|
CvMat* hull = 0;
|
|
CvMat* mask = 0;
|
|
int i, point_count, hull_count;
|
|
CvPoint2D32f *p, *h;
|
|
CvSeq header, hheader, *ptseq, *hseq;
|
|
CvSeqBlock block, hblock;
|
|
|
|
if( points1 )
|
|
ptseq = points1;
|
|
else
|
|
ptseq = cvMakeSeqHeaderForArray( CV_MAT_TYPE(points2->type),
|
|
sizeof(CvSeq), CV_ELEM_SIZE(points2->type), points2->data.ptr,
|
|
points2->rows + points2->cols - 1, &header, &block );
|
|
point_count = ptseq->total;
|
|
p = (CvPoint2D32f*)(points2->data.ptr);
|
|
|
|
if( hull1 )
|
|
hseq = hull1;
|
|
else
|
|
hseq = cvMakeSeqHeaderForArray( CV_MAT_TYPE(hull2->type),
|
|
sizeof(CvSeq), CV_ELEM_SIZE(hull2->type), hull2->data.ptr,
|
|
hull2->rows + hull2->cols - 1, &hheader, &hblock );
|
|
hull_count = hseq->total;
|
|
hull = cvCreateMat( 1, hull_count, CV_32FC2 );
|
|
mask = cvCreateMat( 1, hull_count, CV_8UC1 );
|
|
cvZero( mask );
|
|
Mat _mask = cvarrToMat(mask);
|
|
|
|
h = (CvPoint2D32f*)(hull->data.ptr);
|
|
|
|
// extract convex hull points
|
|
if( return_points )
|
|
{
|
|
cvCvtSeqToArray( hseq, hull->data.ptr );
|
|
if( CV_SEQ_ELTYPE(hseq) != CV_32FC2 )
|
|
{
|
|
CvMat tmp = cvMat( hull->rows, hull->cols, CV_32SC2, hull->data.ptr );
|
|
cvConvert( &tmp, hull );
|
|
}
|
|
}
|
|
else
|
|
{
|
|
CvSeqReader reader;
|
|
cvStartReadSeq( hseq, &reader );
|
|
|
|
for( i = 0; i < hull_count; i++ )
|
|
{
|
|
schar* ptr = reader.ptr;
|
|
int idx;
|
|
CV_NEXT_SEQ_ELEM( hseq->elem_size, reader );
|
|
|
|
if( hull1 )
|
|
idx = cvSeqElemIdx( ptseq, *(uchar**)ptr );
|
|
else
|
|
idx = *(int*)ptr;
|
|
|
|
if( idx < 0 || idx >= point_count )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "Invalid convex hull point #%d\n", i );
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
goto _exit_;
|
|
}
|
|
h[i] = p[idx];
|
|
}
|
|
}
|
|
|
|
// check that the convex hull is a convex polygon
|
|
if( hull_count >= 3 )
|
|
{
|
|
CvPoint2D32f pt0 = h[hull_count-1];
|
|
for( i = 0; i < hull_count; i++ )
|
|
{
|
|
int j = i+1;
|
|
CvPoint2D32f pt1 = h[i], pt2 = h[j < hull_count ? j : 0];
|
|
float dx0 = pt1.x - pt0.x, dy0 = pt1.y - pt0.y;
|
|
float dx1 = pt2.x - pt1.x, dy1 = pt2.y - pt1.y;
|
|
double t = (double)dx0*dy1 - (double)dx1*dy0;
|
|
if( (t < 0) ^ (orientation != CV_COUNTER_CLOCKWISE) )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The convex hull is not convex or has a wrong orientation (vtx %d)\n", i );
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
goto _exit_;
|
|
}
|
|
pt0 = pt1;
|
|
}
|
|
}
|
|
|
|
// check that all the points are inside the hull or on the hull edge
|
|
// and at least hull_point points are at the hull vertices
|
|
for( i = 0; i < point_count; i++ )
|
|
{
|
|
int idx = 0, on_edge = 0;
|
|
double pptresult = cvTsPointPolygonTest( p[i], h, hull_count, &idx, &on_edge );
|
|
|
|
if( pptresult < 0 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The point #%d is outside of the convex hull\n", i );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
if( pptresult < FLT_EPSILON && !on_edge )
|
|
mask->data.ptr[idx] = (uchar)1;
|
|
}
|
|
|
|
if( cvtest::norm( _mask, Mat::zeros(_mask.dims, _mask.size, _mask.type()), NORM_L1 ) != hull_count )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "Not every convex hull vertex coincides with some input point\n" );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
_exit_:
|
|
|
|
cvReleaseMat( &hull );
|
|
cvReleaseMat( &mask );
|
|
if( code < 0 )
|
|
ts->set_failed_test_info( code );
|
|
return code;
|
|
}
|
|
|
|
|
|
/****************************************************************************************\
|
|
* MinAreaRect Test *
|
|
\****************************************************************************************/
|
|
|
|
class CV_MinAreaRectTest : public CV_BaseShapeDescrTest
|
|
{
|
|
public:
|
|
CV_MinAreaRectTest();
|
|
|
|
protected:
|
|
void run_func(void);
|
|
int validate_test_results( int test_case_idx );
|
|
|
|
CvBox2D box;
|
|
CvPoint2D32f box_pt[4];
|
|
};
|
|
|
|
|
|
CV_MinAreaRectTest::CV_MinAreaRectTest()
|
|
{
|
|
}
|
|
|
|
|
|
void CV_MinAreaRectTest::run_func()
|
|
{
|
|
if(!test_cpp)
|
|
{
|
|
box = cvMinAreaRect2( points, storage );
|
|
cvBoxPoints( box, box_pt );
|
|
}
|
|
else
|
|
{
|
|
cv::RotatedRect r = cv::minAreaRect(cv::cvarrToMat(points));
|
|
box = cvBox2D(r);
|
|
r.points((cv::Point2f*)box_pt);
|
|
}
|
|
}
|
|
|
|
|
|
int CV_MinAreaRectTest::validate_test_results( int test_case_idx )
|
|
{
|
|
double eps = 1e-1;
|
|
int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
|
|
int i, j, point_count = points2->rows + points2->cols - 1;
|
|
CvPoint2D32f *p = (CvPoint2D32f*)(points2->data.ptr);
|
|
int mask[] = {0,0,0,0};
|
|
|
|
// check that the bounding box is a rotated rectangle:
|
|
// 1. diagonals should be equal
|
|
// 2. they must intersect in their middle points
|
|
{
|
|
double d0 = cvTsDist( box_pt[0], box_pt[2] );
|
|
double d1 = cvTsDist( box_pt[1], box_pt[3] );
|
|
|
|
double x0 = (box_pt[0].x + box_pt[2].x)*0.5;
|
|
double y0 = (box_pt[0].y + box_pt[2].y)*0.5;
|
|
double x1 = (box_pt[1].x + box_pt[3].x)*0.5;
|
|
double y1 = (box_pt[1].y + box_pt[3].y)*0.5;
|
|
|
|
if( fabs(d0 - d1) + fabs(x0 - x1) + fabs(y0 - y1) > eps*MAX(d0,d1) )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The bounding box is not a rectangle\n" );
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
goto _exit_;
|
|
}
|
|
}
|
|
|
|
#if 0
|
|
{
|
|
int n = 4;
|
|
double a = 8, c = 8, b = 100, d = 150;
|
|
CvPoint bp[4], *bpp = bp;
|
|
cvNamedWindow( "test", 1 );
|
|
IplImage* img = cvCreateImage( cvSize(500,500), 8, 3 );
|
|
cvZero(img);
|
|
for( i = 0; i < point_count; i++ )
|
|
cvCircle(img,cvPoint(cvRound(p[i].x*a+b),cvRound(p[i].y*c+d)), 3, CV_RGB(0,255,0), -1 );
|
|
for( i = 0; i < n; i++ )
|
|
bp[i] = cvPoint(cvRound(box_pt[i].x*a+b),cvRound(box_pt[i].y*c+d));
|
|
cvPolyLine( img, &bpp, &n, 1, 1, CV_RGB(255,255,0), 1, cv::LINE_AA, 0 );
|
|
cvShowImage( "test", img );
|
|
cvWaitKey();
|
|
cvReleaseImage(&img);
|
|
}
|
|
#endif
|
|
|
|
// check that the box includes all the points
|
|
// and there is at least one point at (or very close to) every box side
|
|
for( i = 0; i < point_count; i++ )
|
|
{
|
|
int idx = 0, on_edge = 0;
|
|
double pptresult = cvTsPointPolygonTest( p[i], box_pt, 4, &idx, &on_edge );
|
|
if( pptresult < -eps )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The point #%d is outside of the box\n", i );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
if( pptresult < eps )
|
|
{
|
|
for( j = 0; j < 4; j++ )
|
|
{
|
|
double d = cvTsPtLineDist( p[i], box_pt[(j-1)&3], box_pt[j] );
|
|
if( d < eps )
|
|
mask[j] = (uchar)1;
|
|
}
|
|
}
|
|
}
|
|
|
|
if( mask[0] + mask[1] + mask[2] + mask[3] != 4 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "Not every box side has a point nearby\n" );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
_exit_:
|
|
|
|
if( code < 0 )
|
|
ts->set_failed_test_info( code );
|
|
return code;
|
|
}
|
|
|
|
|
|
/****************************************************************************************\
|
|
* MinEnclosingTriangle Test *
|
|
\****************************************************************************************/
|
|
|
|
class CV_MinTriangleTest : public CV_BaseShapeDescrTest
|
|
{
|
|
public:
|
|
CV_MinTriangleTest();
|
|
|
|
protected:
|
|
void run_func(void);
|
|
int validate_test_results( int test_case_idx );
|
|
std::vector<cv::Point2f> getTriangleMiddlePoints();
|
|
|
|
std::vector<cv::Point2f> convexPolygon;
|
|
std::vector<cv::Point2f> triangle;
|
|
};
|
|
|
|
|
|
CV_MinTriangleTest::CV_MinTriangleTest()
|
|
{
|
|
}
|
|
|
|
std::vector<cv::Point2f> CV_MinTriangleTest::getTriangleMiddlePoints()
|
|
{
|
|
std::vector<cv::Point2f> triangleMiddlePoints;
|
|
|
|
for (int i = 0; i < 3; i++) {
|
|
triangleMiddlePoints.push_back(cvTsMiddlePoint(triangle[i], triangle[(i + 1) % 3]));
|
|
}
|
|
|
|
return triangleMiddlePoints;
|
|
}
|
|
|
|
|
|
void CV_MinTriangleTest::run_func()
|
|
{
|
|
std::vector<cv::Point2f> pointsAsVector;
|
|
|
|
cv::cvarrToMat(points).convertTo(pointsAsVector, CV_32F);
|
|
|
|
cv::minEnclosingTriangle(pointsAsVector, triangle);
|
|
cv::convexHull(pointsAsVector, convexPolygon, true, true);
|
|
}
|
|
|
|
|
|
int CV_MinTriangleTest::validate_test_results( int test_case_idx )
|
|
{
|
|
bool errorEnclosed = false, errorMiddlePoints = false, errorFlush = true;
|
|
double eps = 1e-4;
|
|
int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
|
|
|
|
#if 0
|
|
{
|
|
int n = 3;
|
|
double a = 8, c = 8, b = 100, d = 150;
|
|
CvPoint bp[4], *bpp = bp;
|
|
cvNamedWindow( "test", 1 );
|
|
IplImage* img = cvCreateImage( cvSize(500,500), 8, 3 );
|
|
cvZero(img);
|
|
for( i = 0; i < point_count; i++ )
|
|
cvCircle(img,cvPoint(cvRound(p[i].x*a+b),cvRound(p[i].y*c+d)), 3, CV_RGB(0,255,0), -1 );
|
|
for( i = 0; i < n; i++ )
|
|
bp[i] = cvPoint(cvRound(triangle[i].x*a+b),cvRound(triangle[i].y*c+d));
|
|
cvPolyLine( img, &bpp, &n, 1, 1, CV_RGB(255,255,0), 1, cv::LINE_AA, 0 );
|
|
cvShowImage( "test", img );
|
|
cvWaitKey();
|
|
cvReleaseImage(&img);
|
|
}
|
|
#endif
|
|
|
|
int polygonVertices = (int) convexPolygon.size();
|
|
|
|
if (polygonVertices > 2) {
|
|
// Check if all points are enclosed by the triangle
|
|
for (int i = 0; (i < polygonVertices) && (!errorEnclosed); i++)
|
|
{
|
|
if (cv::pointPolygonTest(triangle, cv::Point2f(convexPolygon[i].x, convexPolygon[i].y), true) < (-eps))
|
|
errorEnclosed = true;
|
|
}
|
|
|
|
// Check if triangle edges middle points touch the polygon
|
|
std::vector<cv::Point2f> middlePoints = getTriangleMiddlePoints();
|
|
|
|
for (int i = 0; (i < 3) && (!errorMiddlePoints); i++)
|
|
{
|
|
bool isTouching = false;
|
|
|
|
for (int j = 0; (j < polygonVertices) && (!isTouching); j++)
|
|
{
|
|
if (cvTsIsPointOnLineSegment(middlePoints[i], convexPolygon[j],
|
|
convexPolygon[(j + 1) % polygonVertices]))
|
|
isTouching = true;
|
|
}
|
|
|
|
errorMiddlePoints = (isTouching) ? false : true;
|
|
}
|
|
|
|
// Check if at least one of the edges is flush
|
|
for (int i = 0; (i < 3) && (errorFlush); i++)
|
|
{
|
|
for (int j = 0; (j < polygonVertices) && (errorFlush); j++)
|
|
{
|
|
if ((cvTsIsPointOnLineSegment(convexPolygon[j], triangle[i],
|
|
triangle[(i + 1) % 3])) &&
|
|
(cvTsIsPointOnLineSegment(convexPolygon[(j + 1) % polygonVertices], triangle[i],
|
|
triangle[(i + 1) % 3])))
|
|
errorFlush = false;
|
|
}
|
|
}
|
|
|
|
// Report any found errors
|
|
if (errorEnclosed)
|
|
{
|
|
ts->printf( cvtest::TS::LOG,
|
|
"All points should be enclosed by the triangle.\n" );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
}
|
|
else if (errorMiddlePoints)
|
|
{
|
|
ts->printf( cvtest::TS::LOG,
|
|
"All triangle edges middle points should touch the convex hull of the points.\n" );
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
}
|
|
else if (errorFlush)
|
|
{
|
|
ts->printf( cvtest::TS::LOG,
|
|
"At least one edge of the enclosing triangle should be flush with one edge of the polygon.\n" );
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
}
|
|
}
|
|
|
|
if ( code < 0 )
|
|
ts->set_failed_test_info( code );
|
|
|
|
return code;
|
|
}
|
|
|
|
|
|
/****************************************************************************************\
|
|
* MinEnclosingCircle Test *
|
|
\****************************************************************************************/
|
|
|
|
class CV_MinCircleTest : public CV_BaseShapeDescrTest
|
|
{
|
|
public:
|
|
CV_MinCircleTest();
|
|
|
|
protected:
|
|
void run_func(void);
|
|
int validate_test_results( int test_case_idx );
|
|
|
|
Point2f center;
|
|
float radius;
|
|
};
|
|
|
|
|
|
CV_MinCircleTest::CV_MinCircleTest()
|
|
{
|
|
}
|
|
|
|
|
|
void CV_MinCircleTest::run_func()
|
|
{
|
|
if(!test_cpp)
|
|
{
|
|
CvPoint2D32f c_center = cvPoint2D32f(center);
|
|
cvMinEnclosingCircle( points, &c_center, &radius );
|
|
center = c_center;
|
|
}
|
|
else
|
|
{
|
|
cv::Point2f tmpcenter;
|
|
cv::minEnclosingCircle(cv::cvarrToMat(points), tmpcenter, radius);
|
|
center = tmpcenter;
|
|
}
|
|
}
|
|
|
|
|
|
int CV_MinCircleTest::validate_test_results( int test_case_idx )
|
|
{
|
|
double eps = 1.03;
|
|
int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
|
|
int i, j = 0, point_count = points2->rows + points2->cols - 1;
|
|
Point2f *p = (Point2f*)(points2->data.ptr);
|
|
Point2f v[3];
|
|
|
|
#if 0
|
|
{
|
|
double a = 2, b = 200, d = 400;
|
|
cvNamedWindow( "test", 1 );
|
|
IplImage* img = cvCreateImage( cvSize(500,500), 8, 3 );
|
|
cvZero(img);
|
|
for( i = 0; i < point_count; i++ )
|
|
cvCircle(img,cvPoint(cvRound(p[i].x*a+b),cvRound(p[i].y*a+d)), 3, CV_RGB(0,255,0), -1 );
|
|
cvCircle( img, cvPoint(cvRound(center.x*a+b),cvRound(center.y*a+d)),
|
|
cvRound(radius*a), CV_RGB(255,255,0), 1 );
|
|
cvShowImage( "test", img );
|
|
cvWaitKey();
|
|
cvReleaseImage(&img);
|
|
}
|
|
#endif
|
|
|
|
// check that the circle contains all the points inside and
|
|
// remember at most 3 points that are close to the boundary
|
|
for( i = 0; i < point_count; i++ )
|
|
{
|
|
double d = cvTsDist(p[i], center);
|
|
if( d > radius )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The point #%d is outside of the circle\n", i );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
if( radius - d < eps*radius && j < 3 )
|
|
v[j++] = p[i];
|
|
}
|
|
|
|
if( point_count >= 2 && (j < 2 || (j == 2 && cvTsDist(v[0],v[1]) < (radius-1)*2/eps)) )
|
|
{
|
|
ts->printf( cvtest::TS::LOG,
|
|
"There should be at least 3 points near the circle boundary or 2 points on the diameter\n" );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
_exit_:
|
|
|
|
if( code < 0 )
|
|
ts->set_failed_test_info( code );
|
|
return code;
|
|
}
|
|
|
|
/****************************************************************************************\
|
|
* MinEnclosingCircle Test 2 *
|
|
\****************************************************************************************/
|
|
|
|
class CV_MinCircleTest2 : public CV_BaseShapeDescrTest
|
|
{
|
|
public:
|
|
CV_MinCircleTest2();
|
|
protected:
|
|
RNG rng;
|
|
void run_func(void);
|
|
int validate_test_results( int test_case_idx );
|
|
float delta;
|
|
};
|
|
|
|
|
|
CV_MinCircleTest2::CV_MinCircleTest2()
|
|
{
|
|
rng = ts->get_rng();
|
|
}
|
|
|
|
|
|
void CV_MinCircleTest2::run_func()
|
|
{
|
|
Point2f center = Point2f(rng.uniform(0.0f, 1000.0f), rng.uniform(0.0f, 1000.0f));;
|
|
float radius = rng.uniform(0.0f, 500.0f);
|
|
float angle = (float)rng.uniform(0.0f, (float)(CV_2PI));
|
|
vector<Point2f> pts;
|
|
pts.push_back(center + Point2f(radius * cos(angle), radius * sin(angle)));
|
|
angle += (float)CV_PI;
|
|
pts.push_back(center + Point2f(radius * cos(angle), radius * sin(angle)));
|
|
float radius2 = radius * radius;
|
|
float x = rng.uniform(center.x - radius, center.x + radius);
|
|
float deltaX = x - center.x;
|
|
float upperBoundY = sqrt(radius2 - deltaX * deltaX);
|
|
float y = rng.uniform(center.y - upperBoundY, center.y + upperBoundY);
|
|
pts.push_back(Point2f(x, y));
|
|
// Find the minimum area enclosing circle
|
|
Point2f calcCenter;
|
|
float calcRadius;
|
|
minEnclosingCircle(pts, calcCenter, calcRadius);
|
|
delta = (float)cv::norm(calcCenter - center) + abs(calcRadius - radius);
|
|
}
|
|
|
|
int CV_MinCircleTest2::validate_test_results( int test_case_idx )
|
|
{
|
|
float eps = 1.0F;
|
|
int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
|
|
if (delta > eps)
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "Delta center and calcCenter > %f\n", eps );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
ts->set_failed_test_info( code );
|
|
}
|
|
return code;
|
|
}
|
|
|
|
/****************************************************************************************\
|
|
* minEnclosingCircle Test 3 *
|
|
\****************************************************************************************/
|
|
|
|
TEST(Imgproc_minEnclosingCircle, basic_test)
|
|
{
|
|
vector<Point2f> pts;
|
|
pts.push_back(Point2f(0, 0));
|
|
pts.push_back(Point2f(10, 0));
|
|
pts.push_back(Point2f(5, 1));
|
|
const float EPS = 1.0e-3f;
|
|
Point2f center;
|
|
float radius;
|
|
|
|
// pts[2] is within the circle with diameter pts[0] - pts[1].
|
|
// 2
|
|
// 0 1
|
|
// NB: The triangle is obtuse, so the only pts[0] and pts[1] are on the circle.
|
|
minEnclosingCircle(pts, center, radius);
|
|
EXPECT_NEAR(center.x, 5, EPS);
|
|
EXPECT_NEAR(center.y, 0, EPS);
|
|
EXPECT_NEAR(5, radius, EPS);
|
|
|
|
// pts[2] is on the circle with diameter pts[0] - pts[1].
|
|
// 2
|
|
// 0 1
|
|
pts[2] = Point2f(5, 5);
|
|
minEnclosingCircle(pts, center, radius);
|
|
EXPECT_NEAR(center.x, 5, EPS);
|
|
EXPECT_NEAR(center.y, 0, EPS);
|
|
EXPECT_NEAR(5, radius, EPS);
|
|
|
|
// pts[2] is outside the circle with diameter pts[0] - pts[1].
|
|
// 2
|
|
//
|
|
//
|
|
// 0 1
|
|
// NB: The triangle is acute, so all 3 points are on the circle.
|
|
pts[2] = Point2f(5, 10);
|
|
minEnclosingCircle(pts, center, radius);
|
|
EXPECT_NEAR(center.x, 5, EPS);
|
|
EXPECT_NEAR(center.y, 3.75, EPS);
|
|
EXPECT_NEAR(6.25f, radius, EPS);
|
|
|
|
// The 3 points are colinear.
|
|
pts[2] = Point2f(3, 0);
|
|
minEnclosingCircle(pts, center, radius);
|
|
EXPECT_NEAR(center.x, 5, EPS);
|
|
EXPECT_NEAR(center.y, 0, EPS);
|
|
EXPECT_NEAR(5, radius, EPS);
|
|
|
|
// 2 points are the same.
|
|
pts[2] = pts[1];
|
|
minEnclosingCircle(pts, center, radius);
|
|
EXPECT_NEAR(center.x, 5, EPS);
|
|
EXPECT_NEAR(center.y, 0, EPS);
|
|
EXPECT_NEAR(5, radius, EPS);
|
|
|
|
// 3 points are the same.
|
|
pts[0] = pts[1];
|
|
minEnclosingCircle(pts, center, radius);
|
|
EXPECT_NEAR(center.x, 10, EPS);
|
|
EXPECT_NEAR(center.y, 0, EPS);
|
|
EXPECT_NEAR(0, radius, EPS);
|
|
}
|
|
|
|
TEST(Imgproc_minEnclosingCircle, regression_16051) {
|
|
vector<Point2f> pts;
|
|
pts.push_back(Point2f(85, 1415));
|
|
pts.push_back(Point2f(87, 1415));
|
|
pts.push_back(Point2f(89, 1414));
|
|
pts.push_back(Point2f(89, 1414));
|
|
pts.push_back(Point2f(87, 1412));
|
|
Point2f center;
|
|
float radius;
|
|
minEnclosingCircle(pts, center, radius);
|
|
EXPECT_NEAR(center.x, 86.9f, 1e-3);
|
|
EXPECT_NEAR(center.y, 1414.1f, 1e-3);
|
|
EXPECT_NEAR(2.1024551f, radius, 1e-3);
|
|
}
|
|
|
|
/****************************************************************************************\
|
|
* Perimeter Test *
|
|
\****************************************************************************************/
|
|
|
|
class CV_PerimeterTest : public CV_BaseShapeDescrTest
|
|
{
|
|
public:
|
|
CV_PerimeterTest();
|
|
|
|
protected:
|
|
int prepare_test_case( int test_case_idx );
|
|
void run_func(void);
|
|
int validate_test_results( int test_case_idx );
|
|
CvSlice slice;
|
|
int is_closed;
|
|
double result;
|
|
};
|
|
|
|
|
|
CV_PerimeterTest::CV_PerimeterTest()
|
|
{
|
|
}
|
|
|
|
|
|
int CV_PerimeterTest::prepare_test_case( int test_case_idx )
|
|
{
|
|
int code = CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
|
|
RNG& rng = ts->get_rng();
|
|
int total;
|
|
|
|
if( code < 0 )
|
|
return code;
|
|
|
|
is_closed = cvtest::randInt(rng) % 2;
|
|
|
|
if( points1 )
|
|
{
|
|
points1->flags |= CV_SEQ_KIND_CURVE;
|
|
if( is_closed )
|
|
points1->flags |= CV_SEQ_FLAG_CLOSED;
|
|
total = points1->total;
|
|
}
|
|
else
|
|
total = points2->cols + points2->rows - 1;
|
|
|
|
if( (cvtest::randInt(rng) % 3) && !test_cpp )
|
|
{
|
|
slice.start_index = cvtest::randInt(rng) % total;
|
|
slice.end_index = cvtest::randInt(rng) % total;
|
|
}
|
|
else
|
|
slice = CV_WHOLE_SEQ;
|
|
|
|
return 1;
|
|
}
|
|
|
|
|
|
void CV_PerimeterTest::run_func()
|
|
{
|
|
if(!test_cpp)
|
|
result = cvArcLength( points, slice, points1 ? -1 : is_closed );
|
|
else
|
|
result = cv::arcLength(cv::cvarrToMat(points),
|
|
!points1 ? is_closed != 0 : (points1->flags & CV_SEQ_FLAG_CLOSED) != 0);
|
|
}
|
|
|
|
|
|
int CV_PerimeterTest::validate_test_results( int test_case_idx )
|
|
{
|
|
int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
|
|
int i, len = slice.end_index - slice.start_index, total = points2->cols + points2->rows - 1;
|
|
double result0 = 0;
|
|
Point2f prev_pt, pt;
|
|
CvPoint2D32f *ptr;
|
|
|
|
if( len < 0 )
|
|
len += total;
|
|
|
|
len = MIN( len, total );
|
|
//len -= !is_closed && len == total;
|
|
|
|
ptr = (CvPoint2D32f*)points2->data.fl;
|
|
prev_pt = ptr[(is_closed ? slice.start_index+len-1 : slice.start_index) % total];
|
|
|
|
for( i = 0; i < len + (len < total && (!is_closed || len==1)); i++ )
|
|
{
|
|
pt = ptr[(i + slice.start_index) % total];
|
|
double dx = pt.x - prev_pt.x, dy = pt.y - prev_pt.y;
|
|
result0 += sqrt(dx*dx + dy*dy);
|
|
prev_pt = pt;
|
|
}
|
|
|
|
if( cvIsNaN(result) || cvIsInf(result) )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "cvArcLength() returned invalid value (%g)\n", result );
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
}
|
|
else if( fabs(result - result0) > FLT_EPSILON*100*result0 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The function returned %g, while the correct result is %g\n", result, result0 );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
}
|
|
|
|
if( code < 0 )
|
|
ts->set_failed_test_info( code );
|
|
return code;
|
|
}
|
|
|
|
|
|
/****************************************************************************************\
|
|
* FitEllipse Test *
|
|
\****************************************************************************************/
|
|
|
|
class CV_FitEllipseTest : public CV_BaseShapeDescrTest
|
|
{
|
|
public:
|
|
CV_FitEllipseTest();
|
|
|
|
protected:
|
|
int prepare_test_case( int test_case_idx );
|
|
void generate_point_set( void* points );
|
|
void run_func(void);
|
|
int validate_test_results( int test_case_idx );
|
|
RotatedRect box0, box;
|
|
double min_ellipse_size, max_noise;
|
|
};
|
|
|
|
|
|
CV_FitEllipseTest::CV_FitEllipseTest()
|
|
{
|
|
min_log_size = 5; // for robust ellipse fitting a dozen of points is needed at least
|
|
max_log_size = 10;
|
|
min_ellipse_size = 10;
|
|
max_noise = 0.05;
|
|
}
|
|
|
|
|
|
void CV_FitEllipseTest::generate_point_set( void* pointsSet )
|
|
{
|
|
RNG& rng = ts->get_rng();
|
|
int i, total, point_type;
|
|
CvSeqReader reader;
|
|
uchar* data = 0;
|
|
double a, b;
|
|
|
|
box0.center.x = (float)((low.val[0] + high.val[0])*0.5);
|
|
box0.center.y = (float)((low.val[1] + high.val[1])*0.5);
|
|
box0.size.width = (float)(MAX(high.val[0] - low.val[0], min_ellipse_size)*2);
|
|
box0.size.height = (float)(MAX(high.val[1] - low.val[1], min_ellipse_size)*2);
|
|
box0.angle = (float)(cvtest::randReal(rng)*180);
|
|
a = cos(box0.angle*CV_PI/180.);
|
|
b = sin(box0.angle*CV_PI/180.);
|
|
|
|
if( box0.size.width > box0.size.height )
|
|
{
|
|
float t;
|
|
CV_SWAP( box0.size.width, box0.size.height, t );
|
|
}
|
|
memset( &reader, 0, sizeof(reader) );
|
|
|
|
if( CV_IS_SEQ(pointsSet) )
|
|
{
|
|
CvSeq* ptseq = (CvSeq*)pointsSet;
|
|
total = ptseq->total;
|
|
point_type = CV_SEQ_ELTYPE(ptseq);
|
|
cvStartReadSeq( ptseq, &reader );
|
|
}
|
|
else
|
|
{
|
|
CvMat* ptm = (CvMat*)pointsSet;
|
|
CV_Assert( CV_IS_MAT(ptm) && CV_IS_MAT_CONT(ptm->type) );
|
|
total = ptm->rows + ptm->cols - 1;
|
|
point_type = CV_MAT_TYPE(ptm->type);
|
|
data = ptm->data.ptr;
|
|
}
|
|
|
|
CV_Assert(point_type == CV_32SC2 || point_type == CV_32FC2);
|
|
|
|
for( i = 0; i < total; i++ )
|
|
{
|
|
CvPoint* pp;
|
|
CvPoint2D32f p = {0, 0};
|
|
double angle = cvtest::randReal(rng)*CV_PI*2;
|
|
double x = box0.size.height*0.5*(cos(angle) + (cvtest::randReal(rng)-0.5)*2*max_noise);
|
|
double y = box0.size.width*0.5*(sin(angle) + (cvtest::randReal(rng)-0.5)*2*max_noise);
|
|
p.x = (float)(box0.center.x + a*x + b*y);
|
|
p.y = (float)(box0.center.y - b*x + a*y);
|
|
|
|
if( reader.ptr )
|
|
{
|
|
pp = (CvPoint*)reader.ptr;
|
|
CV_NEXT_SEQ_ELEM( sizeof(*pp), reader );
|
|
}
|
|
else
|
|
pp = ((CvPoint*)data) + i;
|
|
if( point_type == CV_32SC2 )
|
|
{
|
|
pp->x = cvRound(p.x);
|
|
pp->y = cvRound(p.y);
|
|
}
|
|
else
|
|
*(CvPoint2D32f*)pp = p;
|
|
}
|
|
}
|
|
|
|
|
|
int CV_FitEllipseTest::prepare_test_case( int test_case_idx )
|
|
{
|
|
min_log_size = MAX(min_log_size,4);
|
|
max_log_size = MAX(min_log_size,max_log_size);
|
|
return CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
|
|
}
|
|
|
|
|
|
void CV_FitEllipseTest::run_func()
|
|
{
|
|
if(!test_cpp)
|
|
box = cvFitEllipse2( points );
|
|
else
|
|
box = cv::fitEllipse(cv::cvarrToMat(points));
|
|
}
|
|
|
|
int CV_FitEllipseTest::validate_test_results( int test_case_idx )
|
|
{
|
|
int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
|
|
double diff_angle;
|
|
|
|
if( cvIsNaN(box.center.x) || cvIsInf(box.center.x) ||
|
|
cvIsNaN(box.center.y) || cvIsInf(box.center.y) ||
|
|
cvIsNaN(box.size.width) || cvIsInf(box.size.width) ||
|
|
cvIsNaN(box.size.height) || cvIsInf(box.size.height) ||
|
|
cvIsNaN(box.angle) || cvIsInf(box.angle) )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "Some of the computed ellipse parameters are invalid (x=%g,y=%g,w=%g,h=%g,angle=%g)\n",
|
|
box.center.x, box.center.y, box.size.width, box.size.height, box.angle );
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
goto _exit_;
|
|
}
|
|
|
|
box.angle = (float)(90-box.angle);
|
|
if( box.angle < 0 )
|
|
box.angle += 360;
|
|
if( box.angle > 360 )
|
|
box.angle -= 360;
|
|
|
|
if( fabs(box.center.x - box0.center.x) > 3 ||
|
|
fabs(box.center.y - box0.center.y) > 3 ||
|
|
fabs(box.size.width - box0.size.width) > 0.1*fabs(box0.size.width) ||
|
|
fabs(box.size.height - box0.size.height) > 0.1*fabs(box0.size.height) )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "The computed ellipse center and/or size are incorrect:\n\t"
|
|
"(x=%.1f,y=%.1f,w=%.1f,h=%.1f), while it should be (x=%.1f,y=%.1f,w=%.1f,h=%.1f)\n",
|
|
box.center.x, box.center.y, box.size.width, box.size.height,
|
|
box0.center.x, box0.center.y, box0.size.width, box0.size.height );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
diff_angle = fabs(box0.angle - box.angle);
|
|
diff_angle = MIN( diff_angle, fabs(diff_angle - 360));
|
|
diff_angle = MIN( diff_angle, fabs(diff_angle - 180));
|
|
|
|
if( box0.size.height >= 1.3*box0.size.width && diff_angle > 30 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "Incorrect ellipse angle (=%1.f, should be %1.f)\n",
|
|
box.angle, box0.angle );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
_exit_:
|
|
|
|
#if 0
|
|
if( code < 0 )
|
|
{
|
|
cvNamedWindow( "test", 0 );
|
|
IplImage* img = cvCreateImage( cvSize(cvRound(low_high_range*4),
|
|
cvRound(low_high_range*4)), 8, 3 );
|
|
cvZero( img );
|
|
|
|
box.center.x += (float)low_high_range*2;
|
|
box.center.y += (float)low_high_range*2;
|
|
cvEllipseBox( img, box, CV_RGB(255,0,0), 3, 8 );
|
|
|
|
for( int i = 0; i < points2->rows + points2->cols - 1; i++ )
|
|
{
|
|
CvPoint pt;
|
|
pt.x = cvRound(points2->data.fl[i*2] + low_high_range*2);
|
|
pt.y = cvRound(points2->data.fl[i*2+1] + low_high_range*2);
|
|
cvCircle( img, pt, 1, CV_RGB(255,255,255), -1, 8 );
|
|
}
|
|
|
|
cvShowImage( "test", img );
|
|
cvReleaseImage( &img );
|
|
cvWaitKey(0);
|
|
}
|
|
#endif
|
|
|
|
if( code < 0 )
|
|
{
|
|
ts->set_failed_test_info( code );
|
|
}
|
|
return code;
|
|
}
|
|
|
|
|
|
class CV_FitEllipseSmallTest : public cvtest::BaseTest
|
|
{
|
|
public:
|
|
CV_FitEllipseSmallTest() {}
|
|
~CV_FitEllipseSmallTest() {}
|
|
protected:
|
|
void run(int)
|
|
{
|
|
Size sz(50, 50);
|
|
vector<vector<Point> > c;
|
|
c.push_back(vector<Point>());
|
|
int scale = 1;
|
|
Point ofs = Point(0,0);//sz.width/2, sz.height/2) - Point(4,4)*scale;
|
|
c[0].push_back(Point(2, 0)*scale+ofs);
|
|
c[0].push_back(Point(0, 2)*scale+ofs);
|
|
c[0].push_back(Point(0, 6)*scale+ofs);
|
|
c[0].push_back(Point(2, 8)*scale+ofs);
|
|
c[0].push_back(Point(6, 8)*scale+ofs);
|
|
c[0].push_back(Point(8, 6)*scale+ofs);
|
|
c[0].push_back(Point(8, 2)*scale+ofs);
|
|
c[0].push_back(Point(6, 0)*scale+ofs);
|
|
|
|
RotatedRect e = fitEllipse(c[0]);
|
|
CV_Assert( fabs(e.center.x - 4) <= 1. &&
|
|
fabs(e.center.y - 4) <= 1. &&
|
|
fabs(e.size.width - 9) <= 1. &&
|
|
fabs(e.size.height - 9) <= 1. );
|
|
}
|
|
};
|
|
|
|
|
|
// Regression test for incorrect fitEllipse result reported in Bug #3989
|
|
// Check edge cases for rotation angles of ellipse ([-180, 90, 0, 90, 180] degrees)
|
|
class CV_FitEllipseParallelTest : public CV_FitEllipseTest
|
|
{
|
|
public:
|
|
CV_FitEllipseParallelTest();
|
|
~CV_FitEllipseParallelTest();
|
|
protected:
|
|
void generate_point_set( void* points );
|
|
void run_func(void);
|
|
Mat pointsMat;
|
|
};
|
|
|
|
CV_FitEllipseParallelTest::CV_FitEllipseParallelTest()
|
|
{
|
|
min_ellipse_size = 5;
|
|
}
|
|
|
|
void CV_FitEllipseParallelTest::generate_point_set( void* )
|
|
{
|
|
RNG& rng = ts->get_rng();
|
|
int height = (int)(MAX(high.val[0] - low.val[0], min_ellipse_size));
|
|
int width = (int)(MAX(high.val[1] - low.val[1], min_ellipse_size));
|
|
const int angle = ( (cvtest::randInt(rng) % 5) - 2 ) * 90;
|
|
const int dim = max(height, width);
|
|
const Point center = Point(dim*2, dim*2);
|
|
|
|
if( width > height )
|
|
{
|
|
int t;
|
|
CV_SWAP( width, height, t );
|
|
}
|
|
|
|
Mat image = Mat::zeros(dim*4, dim*4, CV_8UC1);
|
|
ellipse(image, center, Size(height, width), angle,
|
|
0, 360, Scalar(255, 0, 0), 1, 8);
|
|
|
|
box0.center.x = (float)center.x;
|
|
box0.center.y = (float)center.y;
|
|
box0.size.width = (float)width*2;
|
|
box0.size.height = (float)height*2;
|
|
box0.angle = (float)angle;
|
|
|
|
vector<vector<Point> > contours;
|
|
findContours(image, contours, RETR_EXTERNAL, CHAIN_APPROX_NONE);
|
|
Mat(contours[0]).convertTo(pointsMat, CV_32F);
|
|
}
|
|
|
|
void CV_FitEllipseParallelTest::run_func()
|
|
{
|
|
box = cv::fitEllipse(pointsMat);
|
|
}
|
|
|
|
CV_FitEllipseParallelTest::~CV_FitEllipseParallelTest(){
|
|
pointsMat.release();
|
|
}
|
|
|
|
/****************************************************************************************\
|
|
* FitLine Test *
|
|
\****************************************************************************************/
|
|
|
|
class CV_FitLineTest : public CV_BaseShapeDescrTest
|
|
{
|
|
public:
|
|
CV_FitLineTest();
|
|
|
|
protected:
|
|
int prepare_test_case( int test_case_idx );
|
|
void generate_point_set( void* points );
|
|
void run_func(void);
|
|
int validate_test_results( int test_case_idx );
|
|
double max_noise;
|
|
AutoBuffer<float> line, line0;
|
|
int dist_type;
|
|
double reps, aeps;
|
|
};
|
|
|
|
|
|
CV_FitLineTest::CV_FitLineTest()
|
|
{
|
|
min_log_size = 5; // for robust line fitting a dozen of points is needed at least
|
|
max_log_size = 10;
|
|
max_noise = 0.05;
|
|
}
|
|
|
|
void CV_FitLineTest::generate_point_set( void* pointsSet )
|
|
{
|
|
RNG& rng = ts->get_rng();
|
|
int i, k, n, total, point_type;
|
|
CvSeqReader reader;
|
|
uchar* data = 0;
|
|
double s = 0;
|
|
|
|
n = dims;
|
|
for( k = 0; k < n; k++ )
|
|
{
|
|
line0[k+n] = (float)((low.val[k] + high.val[k])*0.5);
|
|
line0[k] = (float)(high.val[k] - low.val[k]);
|
|
if( cvtest::randInt(rng) % 2 )
|
|
line0[k] = -line0[k];
|
|
s += (double)line0[k]*line0[k];
|
|
}
|
|
|
|
s = 1./sqrt(s);
|
|
for( k = 0; k < n; k++ )
|
|
line0[k] = (float)(line0[k]*s);
|
|
|
|
memset( &reader, 0, sizeof(reader) );
|
|
|
|
if( CV_IS_SEQ(pointsSet) )
|
|
{
|
|
CvSeq* ptseq = (CvSeq*)pointsSet;
|
|
total = ptseq->total;
|
|
point_type = CV_MAT_DEPTH(CV_SEQ_ELTYPE(ptseq));
|
|
cvStartReadSeq( ptseq, &reader );
|
|
}
|
|
else
|
|
{
|
|
CvMat* ptm = (CvMat*)pointsSet;
|
|
CV_Assert( CV_IS_MAT(ptm) && CV_IS_MAT_CONT(ptm->type) );
|
|
total = ptm->rows + ptm->cols - 1;
|
|
point_type = CV_MAT_DEPTH(CV_MAT_TYPE(ptm->type));
|
|
data = ptm->data.ptr;
|
|
}
|
|
|
|
for( i = 0; i < total; i++ )
|
|
{
|
|
int* pi;
|
|
float* pf;
|
|
float p[4], t;
|
|
if( reader.ptr )
|
|
{
|
|
pi = (int*)reader.ptr;
|
|
pf = (float*)reader.ptr;
|
|
CV_NEXT_SEQ_ELEM( reader.seq->elem_size, reader );
|
|
}
|
|
else
|
|
{
|
|
pi = (int*)data + i*n;
|
|
pf = (float*)data + i*n;
|
|
}
|
|
|
|
t = (float)((cvtest::randReal(rng)-0.5)*low_high_range*2);
|
|
|
|
for( k = 0; k < n; k++ )
|
|
{
|
|
p[k] = (float)((cvtest::randReal(rng)-0.5)*max_noise*2 + t*line0[k] + line0[k+n]);
|
|
|
|
if( point_type == CV_32S )
|
|
pi[k] = cvRound(p[k]);
|
|
else
|
|
pf[k] = p[k];
|
|
}
|
|
}
|
|
}
|
|
|
|
int CV_FitLineTest::prepare_test_case( int test_case_idx )
|
|
{
|
|
RNG& rng = ts->get_rng();
|
|
dims = cvtest::randInt(rng) % 2 + 2;
|
|
line.allocate(dims * 2);
|
|
line0.allocate(dims * 2);
|
|
min_log_size = MAX(min_log_size,5);
|
|
max_log_size = MAX(min_log_size,max_log_size);
|
|
int code = CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
|
|
dist_type = cvtest::randInt(rng) % 6 + 1;
|
|
dist_type += dist_type == CV_DIST_C;
|
|
reps = 0.1; aeps = 0.01;
|
|
return code;
|
|
}
|
|
|
|
|
|
void CV_FitLineTest::run_func()
|
|
{
|
|
if(!test_cpp)
|
|
cvFitLine( points, dist_type, 0, reps, aeps, line.data());
|
|
else if(dims == 2)
|
|
cv::fitLine(cv::cvarrToMat(points), (cv::Vec4f&)line[0], dist_type, 0, reps, aeps);
|
|
else
|
|
cv::fitLine(cv::cvarrToMat(points), (cv::Vec6f&)line[0], dist_type, 0, reps, aeps);
|
|
}
|
|
|
|
int CV_FitLineTest::validate_test_results( int test_case_idx )
|
|
{
|
|
int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
|
|
int k, max_k = 0;
|
|
double vec_diff = 0, t;
|
|
|
|
//std::cout << dims << " " << Mat(1, dims*2, CV_32FC1, line.data()) << " " << Mat(1, dims, CV_32FC1, line0.data()) << std::endl;
|
|
|
|
for( k = 0; k < dims*2; k++ )
|
|
{
|
|
if( cvIsNaN(line[k]) || cvIsInf(line[k]) )
|
|
{
|
|
ts->printf( cvtest::TS::LOG, "Some of the computed line parameters are invalid (line[%d]=%g)\n",
|
|
k, line[k] );
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
goto _exit_;
|
|
}
|
|
}
|
|
|
|
if( fabs(line0[1]) > fabs(line0[0]) )
|
|
max_k = 1;
|
|
if( fabs(line0[dims-1]) > fabs(line0[max_k]) )
|
|
max_k = dims-1;
|
|
if( line0[max_k] < 0 )
|
|
for( k = 0; k < dims; k++ )
|
|
line0[k] = -line0[k];
|
|
if( line[max_k] < 0 )
|
|
for( k = 0; k < dims; k++ )
|
|
line[k] = -line[k];
|
|
|
|
for( k = 0; k < dims; k++ )
|
|
{
|
|
double dt = line[k] - line0[k];
|
|
vec_diff += dt*dt;
|
|
}
|
|
|
|
if( sqrt(vec_diff) > 0.05 )
|
|
{
|
|
if( dims == 2 )
|
|
ts->printf( cvtest::TS::LOG,
|
|
"The computed line vector (%.2f,%.2f) is different from the actual (%.2f,%.2f)\n",
|
|
line[0], line[1], line0[0], line0[1] );
|
|
else
|
|
ts->printf( cvtest::TS::LOG,
|
|
"The computed line vector (%.2f,%.2f,%.2f) is different from the actual (%.2f,%.2f,%.2f)\n",
|
|
line[0], line[1], line[2], line0[0], line0[1], line0[2] );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
t = (line[max_k+dims] - line0[max_k+dims])/line0[max_k];
|
|
for( k = 0; k < dims; k++ )
|
|
{
|
|
double p = line0[k+dims] + t*line0[k] - line[k+dims];
|
|
vec_diff += p*p;
|
|
}
|
|
|
|
if( sqrt(vec_diff) > 1*MAX(fabs(t),1) )
|
|
{
|
|
if( dims == 2 )
|
|
ts->printf( cvtest::TS::LOG,
|
|
"The computed line point (%.2f,%.2f) is too far from the actual line\n",
|
|
line[2]+line0[2], line[3]+line0[3] );
|
|
else
|
|
ts->printf( cvtest::TS::LOG,
|
|
"The computed line point (%.2f,%.2f,%.2f) is too far from the actual line\n",
|
|
line[3]+line0[3], line[4]+line0[4], line[5]+line0[5] );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
goto _exit_;
|
|
}
|
|
|
|
_exit_:
|
|
|
|
if( code < 0 )
|
|
{
|
|
ts->set_failed_test_info( code );
|
|
}
|
|
return code;
|
|
}
|
|
|
|
/****************************************************************************************\
|
|
* ContourMoments Test *
|
|
\****************************************************************************************/
|
|
|
|
|
|
static void
|
|
cvTsGenerateTousledBlob( CvPoint2D32f center, CvSize2D32f axes,
|
|
double max_r_scale, double angle, CvArr* points, RNG& rng )
|
|
{
|
|
int i, total, point_type;
|
|
uchar* data = 0;
|
|
CvSeqReader reader;
|
|
memset( &reader, 0, sizeof(reader) );
|
|
|
|
if( CV_IS_SEQ(points) )
|
|
{
|
|
CvSeq* ptseq = (CvSeq*)points;
|
|
total = ptseq->total;
|
|
point_type = CV_SEQ_ELTYPE(ptseq);
|
|
cvStartReadSeq( ptseq, &reader );
|
|
}
|
|
else
|
|
{
|
|
CvMat* ptm = (CvMat*)points;
|
|
CV_Assert( CV_IS_MAT(ptm) && CV_IS_MAT_CONT(ptm->type) );
|
|
total = ptm->rows + ptm->cols - 1;
|
|
point_type = CV_MAT_TYPE(ptm->type);
|
|
data = ptm->data.ptr;
|
|
}
|
|
|
|
CV_Assert( point_type == CV_32SC2 || point_type == CV_32FC2 );
|
|
|
|
for( i = 0; i < total; i++ )
|
|
{
|
|
CvPoint* pp;
|
|
Point2f p;
|
|
|
|
double phi0 = 2*CV_PI*i/total;
|
|
double phi = CV_PI*angle/180.;
|
|
double t = cvtest::randReal(rng)*max_r_scale + (1 - max_r_scale);
|
|
double ta = axes.height*t;
|
|
double tb = axes.width*t;
|
|
double c0 = cos(phi0)*ta, s0 = sin(phi0)*tb;
|
|
double c = cos(phi), s = sin(phi);
|
|
p.x = (float)(c0*c - s0*s + center.x);
|
|
p.y = (float)(c0*s + s0*c + center.y);
|
|
|
|
if( reader.ptr )
|
|
{
|
|
pp = (CvPoint*)reader.ptr;
|
|
CV_NEXT_SEQ_ELEM( sizeof(*pp), reader );
|
|
}
|
|
else
|
|
pp = ((CvPoint*)data) + i;
|
|
|
|
if( point_type == CV_32SC2 )
|
|
{
|
|
pp->x = cvRound(p.x);
|
|
pp->y = cvRound(p.y);
|
|
}
|
|
else
|
|
*(CvPoint2D32f*)pp = cvPoint2D32f(p);
|
|
}
|
|
}
|
|
|
|
|
|
class CV_ContourMomentsTest : public CV_BaseShapeDescrTest
|
|
{
|
|
public:
|
|
CV_ContourMomentsTest();
|
|
|
|
protected:
|
|
int prepare_test_case( int test_case_idx );
|
|
void generate_point_set( void* points );
|
|
void run_func(void);
|
|
int validate_test_results( int test_case_idx );
|
|
CvMoments moments0, moments;
|
|
double area0, area;
|
|
Size2f axes;
|
|
Point2f center;
|
|
int max_max_r_scale;
|
|
double max_r_scale, angle;
|
|
Size img_size;
|
|
};
|
|
|
|
|
|
CV_ContourMomentsTest::CV_ContourMomentsTest()
|
|
{
|
|
min_log_size = 3;
|
|
max_log_size = 8;
|
|
max_max_r_scale = 15;
|
|
low_high_range = 200;
|
|
enable_flt_points = false;
|
|
}
|
|
|
|
|
|
void CV_ContourMomentsTest::generate_point_set( void* pointsSet )
|
|
{
|
|
RNG& rng = ts->get_rng();
|
|
float max_sz;
|
|
|
|
axes.width = (float)((cvtest::randReal(rng)*0.9 + 0.1)*low_high_range);
|
|
axes.height = (float)((cvtest::randReal(rng)*0.9 + 0.1)*low_high_range);
|
|
max_sz = MAX(axes.width, axes.height);
|
|
|
|
img_size.width = img_size.height = cvRound(low_high_range*2.2);
|
|
|
|
center.x = (float)(img_size.width*0.5 + (cvtest::randReal(rng)-0.5)*(img_size.width - max_sz*2)*0.8);
|
|
center.y = (float)(img_size.height*0.5 + (cvtest::randReal(rng)-0.5)*(img_size.height - max_sz*2)*0.8);
|
|
|
|
CV_Assert( 0 < center.x - max_sz && center.x + max_sz < img_size.width &&
|
|
0 < center.y - max_sz && center.y + max_sz < img_size.height );
|
|
|
|
max_r_scale = cvtest::randReal(rng)*max_max_r_scale*0.01;
|
|
angle = cvtest::randReal(rng)*360;
|
|
|
|
cvTsGenerateTousledBlob( cvPoint2D32f(center), cvSize2D32f(axes), max_r_scale, angle, pointsSet, rng );
|
|
|
|
if( points1 )
|
|
points1->flags = CV_SEQ_MAGIC_VAL + CV_SEQ_POLYGON;
|
|
}
|
|
|
|
|
|
int CV_ContourMomentsTest::prepare_test_case( int test_case_idx )
|
|
{
|
|
min_log_size = MAX(min_log_size,3);
|
|
max_log_size = MIN(max_log_size,8);
|
|
max_log_size = MAX(min_log_size,max_log_size);
|
|
int code = CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
|
|
return code;
|
|
}
|
|
|
|
|
|
void CV_ContourMomentsTest::run_func()
|
|
{
|
|
if(!test_cpp)
|
|
{
|
|
cvMoments( points, &moments );
|
|
area = cvContourArea( points );
|
|
}
|
|
else
|
|
{
|
|
moments = cvMoments(cv::moments(cv::cvarrToMat(points)));
|
|
area = cv::contourArea(cv::cvarrToMat(points));
|
|
}
|
|
}
|
|
|
|
|
|
int CV_ContourMomentsTest::validate_test_results( int test_case_idx )
|
|
{
|
|
int code = CV_BaseShapeDescrTest::validate_test_results( test_case_idx );
|
|
int i, n = (int)(sizeof(moments)/sizeof(moments.inv_sqrt_m00));
|
|
CvMat* img = cvCreateMat( img_size.height, img_size.width, CV_8UC1 );
|
|
CvPoint* pt = (CvPoint*)points2->data.i;
|
|
int count = points2->cols + points2->rows - 1;
|
|
double max_v0 = 0;
|
|
|
|
cvZero(img);
|
|
cvFillPoly( img, &pt, &count, 1, cvScalarAll(1));
|
|
cvMoments( img, &moments0 );
|
|
|
|
for( i = 0; i < n; i++ )
|
|
{
|
|
double t = fabs((&moments0.m00)[i]);
|
|
max_v0 = MAX(max_v0, t);
|
|
}
|
|
|
|
for( i = 0; i <= n; i++ )
|
|
{
|
|
double v = i < n ? (&moments.m00)[i] : area;
|
|
double v0 = i < n ? (&moments0.m00)[i] : moments0.m00;
|
|
|
|
if( cvIsNaN(v) || cvIsInf(v) )
|
|
{
|
|
ts->printf( cvtest::TS::LOG,
|
|
"The contour %s is invalid (=%g)\n", i < n ? "moment" : "area", v );
|
|
code = cvtest::TS::FAIL_INVALID_OUTPUT;
|
|
break;
|
|
}
|
|
|
|
if( fabs(v - v0) > 0.1*max_v0 )
|
|
{
|
|
ts->printf( cvtest::TS::LOG,
|
|
"The computed contour %s is %g, while it should be %g\n",
|
|
i < n ? "moment" : "area", v, v0 );
|
|
code = cvtest::TS::FAIL_BAD_ACCURACY;
|
|
break;
|
|
}
|
|
}
|
|
|
|
if( code < 0 )
|
|
{
|
|
ts->set_failed_test_info( code );
|
|
}
|
|
|
|
cvReleaseMat( &img );
|
|
return code;
|
|
}
|
|
|
|
|
|
////////////////////////////////////// Perimeter/Area/Slice test ///////////////////////////////////
|
|
|
|
class CV_PerimeterAreaSliceTest : public cvtest::BaseTest
|
|
{
|
|
public:
|
|
CV_PerimeterAreaSliceTest();
|
|
~CV_PerimeterAreaSliceTest();
|
|
protected:
|
|
void run(int);
|
|
};
|
|
|
|
CV_PerimeterAreaSliceTest::CV_PerimeterAreaSliceTest()
|
|
{
|
|
}
|
|
CV_PerimeterAreaSliceTest::~CV_PerimeterAreaSliceTest() {}
|
|
|
|
void CV_PerimeterAreaSliceTest::run( int )
|
|
{
|
|
Ptr<CvMemStorage> storage(cvCreateMemStorage());
|
|
RNG& rng = theRNG();
|
|
const double min_r = 90, max_r = 120;
|
|
|
|
for( int i = 0; i < 100; i++ )
|
|
{
|
|
ts->update_context( this, i, true );
|
|
int n = rng.uniform(3, 30);
|
|
cvClearMemStorage(storage);
|
|
CvSeq* contour = cvCreateSeq(CV_SEQ_POLYGON, sizeof(CvSeq), sizeof(CvPoint), storage);
|
|
double dphi = CV_PI*2/n;
|
|
Point center;
|
|
center.x = rng.uniform(cvCeil(max_r), cvFloor(640-max_r));
|
|
center.y = rng.uniform(cvCeil(max_r), cvFloor(480-max_r));
|
|
|
|
for( int j = 0; j < n; j++ )
|
|
{
|
|
CvPoint pt = CV_STRUCT_INITIALIZER;
|
|
double r = rng.uniform(min_r, max_r);
|
|
double phi = j*dphi;
|
|
pt.x = cvRound(center.x + r*cos(phi));
|
|
pt.y = cvRound(center.y - r*sin(phi));
|
|
cvSeqPush(contour, &pt);
|
|
}
|
|
|
|
CvSlice slice = {0, 0};
|
|
for(;;)
|
|
{
|
|
slice.start_index = rng.uniform(-n/2, 3*n/2);
|
|
slice.end_index = rng.uniform(-n/2, 3*n/2);
|
|
int len = cvSliceLength(slice, contour);
|
|
if( len > 2 )
|
|
break;
|
|
}
|
|
CvSeq *cslice = cvSeqSlice(contour, slice);
|
|
/*printf( "%d. (%d, %d) of %d, length = %d, length1 = %d\n",
|
|
i, slice.start_index, slice.end_index,
|
|
contour->total, cvSliceLength(slice, contour), cslice->total );
|
|
|
|
double area0 = cvContourArea(cslice);
|
|
double area1 = cvContourArea(contour, slice);
|
|
if( area0 != area1 )
|
|
{
|
|
ts->printf(cvtest::TS::LOG,
|
|
"The contour area slice is computed differently (%g vs %g)\n", area0, area1 );
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
|
return;
|
|
}*/
|
|
|
|
double len0 = cvArcLength(cslice, CV_WHOLE_SEQ, 1);
|
|
double len1 = cvArcLength(contour, slice, 1);
|
|
if( len0 != len1 )
|
|
{
|
|
ts->printf(cvtest::TS::LOG,
|
|
"The contour arc length is computed differently (%g vs %g)\n", len0, len1 );
|
|
ts->set_failed_test_info( cvtest::TS::FAIL_BAD_ACCURACY );
|
|
return;
|
|
}
|
|
}
|
|
ts->set_failed_test_info(cvtest::TS::OK);
|
|
}
|
|
|
|
|
|
TEST(Imgproc_ConvexHull, accuracy) { CV_ConvHullTest test; test.safe_run(); }
|
|
TEST(Imgproc_MinAreaRect, accuracy) { CV_MinAreaRectTest test; test.safe_run(); }
|
|
TEST(Imgproc_MinTriangle, accuracy) { CV_MinTriangleTest test; test.safe_run(); }
|
|
TEST(Imgproc_MinCircle, accuracy) { CV_MinCircleTest test; test.safe_run(); }
|
|
TEST(Imgproc_MinCircle2, accuracy) { CV_MinCircleTest2 test; test.safe_run(); }
|
|
TEST(Imgproc_ContourPerimeter, accuracy) { CV_PerimeterTest test; test.safe_run(); }
|
|
TEST(Imgproc_FitEllipse, accuracy) { CV_FitEllipseTest test; test.safe_run(); }
|
|
TEST(Imgproc_FitEllipse, parallel) { CV_FitEllipseParallelTest test; test.safe_run(); }
|
|
TEST(Imgproc_FitLine, accuracy) { CV_FitLineTest test; test.safe_run(); }
|
|
TEST(Imgproc_ContourMoments, accuracy) { CV_ContourMomentsTest test; test.safe_run(); }
|
|
TEST(Imgproc_ContourPerimeterSlice, accuracy) { CV_PerimeterAreaSliceTest test; test.safe_run(); }
|
|
TEST(Imgproc_FitEllipse, small) { CV_FitEllipseSmallTest test; test.safe_run(); }
|
|
|
|
|
|
|
|
PARAM_TEST_CASE(ConvexityDefects_regression_5908, bool, int)
|
|
{
|
|
public:
|
|
int start_index;
|
|
bool clockwise;
|
|
|
|
Mat contour;
|
|
|
|
virtual void SetUp()
|
|
{
|
|
clockwise = GET_PARAM(0);
|
|
start_index = GET_PARAM(1);
|
|
|
|
const int N = 11;
|
|
const Point2i points[N] = {
|
|
Point2i(154, 408),
|
|
Point2i(45, 223),
|
|
Point2i(115, 275), // inner
|
|
Point2i(104, 166),
|
|
Point2i(154, 256), // inner
|
|
Point2i(169, 144),
|
|
Point2i(185, 256), // inner
|
|
Point2i(235, 170),
|
|
Point2i(240, 320), // inner
|
|
Point2i(330, 287),
|
|
Point2i(224, 390)
|
|
};
|
|
|
|
contour = Mat(N, 1, CV_32SC2);
|
|
for (int i = 0; i < N; i++)
|
|
{
|
|
contour.at<Point2i>(i) = (!clockwise) // image and convexHull coordinate systems are different
|
|
? points[(start_index + i) % N]
|
|
: points[N - 1 - ((start_index + i) % N)];
|
|
}
|
|
}
|
|
};
|
|
|
|
TEST_P(ConvexityDefects_regression_5908, simple)
|
|
{
|
|
std::vector<int> hull;
|
|
cv::convexHull(contour, hull, clockwise, false);
|
|
|
|
std::vector<Vec4i> result;
|
|
cv::convexityDefects(contour, hull, result);
|
|
|
|
EXPECT_EQ(4, (int)result.size());
|
|
}
|
|
|
|
INSTANTIATE_TEST_CASE_P(Imgproc, ConvexityDefects_regression_5908,
|
|
testing::Combine(
|
|
testing::Bool(),
|
|
testing::Values(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
|
|
));
|
|
|
|
TEST(Imgproc_FitLine, regression_15083)
|
|
{
|
|
int points2i_[] = {
|
|
432, 654,
|
|
370, 656,
|
|
390, 656,
|
|
410, 656,
|
|
348, 658
|
|
};
|
|
Mat points(5, 1, CV_32SC2, points2i_);
|
|
|
|
Vec4f lineParam;
|
|
fitLine(points, lineParam, DIST_L1, 0, 0.01, 0.01);
|
|
EXPECT_GE(fabs(lineParam[0]), fabs(lineParam[1]) * 4) << lineParam;
|
|
}
|
|
|
|
TEST(Imgproc_FitLine, regression_4903)
|
|
{
|
|
float points2f_[] = {
|
|
1224.0, 576.0,
|
|
1234.0, 683.0,
|
|
1215.0, 471.0,
|
|
1184.0, 137.0,
|
|
1079.0, 377.0,
|
|
1239.0, 788.0,
|
|
};
|
|
Mat points(6, 1, CV_32FC2, points2f_);
|
|
|
|
Vec4f lineParam;
|
|
fitLine(points, lineParam, DIST_WELSCH, 0, 0.01, 0.01);
|
|
EXPECT_GE(fabs(lineParam[1]), fabs(lineParam[0]) * 4) << lineParam;
|
|
}
|
|
|
|
#if 0
|
|
#define DRAW(x) x
|
|
#else
|
|
#define DRAW(x)
|
|
#endif
|
|
|
|
// the Python test by @hannarud is converted to C++; see the issue #4539
|
|
TEST(Imgproc_ConvexityDefects, ordering_4539)
|
|
{
|
|
int contour[][2] =
|
|
{
|
|
{26, 9}, {25, 10}, {24, 10}, {23, 10}, {22, 10}, {21, 10}, {20, 11}, {19, 11}, {18, 11}, {17, 12},
|
|
{17, 13}, {18, 14}, {18, 15}, {18, 16}, {18, 17}, {19, 18}, {19, 19}, {20, 20}, {21, 21}, {21, 22},
|
|
{22, 23}, {22, 24}, {23, 25}, {23, 26}, {24, 27}, {25, 28}, {26, 29}, {27, 30}, {27, 31}, {28, 32},
|
|
{29, 32}, {30, 33}, {31, 34}, {30, 35}, {29, 35}, {30, 35}, {31, 34}, {32, 34}, {33, 34}, {34, 33},
|
|
{35, 32}, {35, 31}, {35, 30}, {36, 29}, {37, 28}, {37, 27}, {38, 26}, {39, 25}, {40, 24}, {40, 23},
|
|
{41, 22}, {42, 21}, {42, 20}, {42, 19}, {43, 18}, {43, 17}, {44, 16}, {45, 15}, {45, 14}, {46, 13},
|
|
{46, 12}, {45, 11}, {44, 11}, {43, 11}, {42, 10}, {41, 10}, {40, 9}, {39, 9}, {38, 9}, {37, 9},
|
|
{36, 9}, {35, 9}, {34, 9}, {33, 9}, {32, 9}, {31, 9}, {30, 9}, {29, 9}, {28, 9}, {27, 9}
|
|
};
|
|
int npoints = (int)(sizeof(contour)/sizeof(contour[0][0])/2);
|
|
Mat contour_(1, npoints, CV_32SC2, contour);
|
|
vector<Point> hull;
|
|
vector<int> hull_ind;
|
|
vector<Vec4i> defects;
|
|
|
|
// first, check the original contour as-is, without intermediate fillPoly/drawContours.
|
|
convexHull(contour_, hull_ind, false, false);
|
|
EXPECT_THROW( convexityDefects(contour_, hull_ind, defects), cv::Exception );
|
|
|
|
int scale = 20;
|
|
contour_ *= (double)scale;
|
|
|
|
Mat canvas_gray(Size(60*scale, 45*scale), CV_8U, Scalar::all(0));
|
|
const Point* ptptr = contour_.ptr<Point>();
|
|
fillPoly(canvas_gray, &ptptr, &npoints, 1, Scalar(255, 255, 255));
|
|
|
|
vector<vector<Point> > contours;
|
|
findContours(canvas_gray, contours, noArray(), RETR_LIST, CHAIN_APPROX_SIMPLE);
|
|
convexHull(contours[0], hull_ind, false, false);
|
|
|
|
// the original contour contains self-intersections,
|
|
// therefore convexHull does not return a monotonous sequence of points
|
|
// and therefore convexityDefects throws an exception
|
|
EXPECT_THROW( convexityDefects(contours[0], hull_ind, defects), cv::Exception );
|
|
|
|
#if 1
|
|
// one way to eliminate the contour self-intersection in this particular case is to apply dilate(),
|
|
// so that the self-repeating points are not self-repeating anymore
|
|
dilate(canvas_gray, canvas_gray, Mat());
|
|
#else
|
|
// another popular technique to eliminate such thin "hair" is to use morphological "close" operation,
|
|
// which is erode() + dilate()
|
|
erode(canvas_gray, canvas_gray, Mat());
|
|
dilate(canvas_gray, canvas_gray, Mat());
|
|
#endif
|
|
|
|
// after the "fix", the newly retrieved contour should not have self-intersections,
|
|
// and everything should work well
|
|
findContours(canvas_gray, contours, noArray(), RETR_LIST, CHAIN_APPROX_SIMPLE);
|
|
convexHull(contours[0], hull, false, true);
|
|
convexHull(contours[0], hull_ind, false, false);
|
|
|
|
DRAW(Mat canvas(Size(60*scale, 45*scale), CV_8UC3, Scalar::all(0));
|
|
drawContours(canvas, contours, -1, Scalar(255, 255, 255), -1));
|
|
|
|
size_t nhull = hull.size();
|
|
ASSERT_EQ( nhull, hull_ind.size() );
|
|
|
|
if( nhull > 2 )
|
|
{
|
|
bool initial_lt = hull_ind[0] < hull_ind[1];
|
|
for( size_t i = 0; i < nhull; i++ )
|
|
{
|
|
int ind = hull_ind[i];
|
|
Point pt = contours[0][ind];
|
|
|
|
ASSERT_EQ(pt, hull[i]);
|
|
if( i > 0 )
|
|
{
|
|
// check that the convex hull indices are monotone
|
|
if( initial_lt )
|
|
{
|
|
ASSERT_LT(hull_ind[i-1], hull_ind[i]);
|
|
}
|
|
else
|
|
{
|
|
ASSERT_GT(hull_ind[i-1], hull_ind[i]);
|
|
}
|
|
}
|
|
DRAW(circle(canvas, pt, 7, Scalar(180, 0, 180), -1, LINE_AA);
|
|
putText(canvas, format("%d (%d)", (int)i, ind), pt+Point(15, 0), FONT_HERSHEY_SIMPLEX, 0.4, Scalar(200, 0, 200), 1, LINE_AA));
|
|
//printf("%d. ind=%d, pt=(%d, %d)\n", (int)i, ind, pt.x, pt.y);
|
|
}
|
|
}
|
|
|
|
convexityDefects(contours[0], hull_ind, defects);
|
|
|
|
for(size_t i = 0; i < defects.size(); i++ )
|
|
{
|
|
Vec4i d = defects[i];
|
|
//printf("defect %d. start=%d, end=%d, farthest=%d, depth=%d\n", (int)i, d[0], d[1], d[2], d[3]);
|
|
EXPECT_LT(d[0], d[1]);
|
|
EXPECT_LE(d[0], d[2]);
|
|
EXPECT_LE(d[2], d[1]);
|
|
|
|
DRAW(Point start = contours[0][d[0]];
|
|
Point end = contours[0][d[1]];
|
|
Point far = contours[0][d[2]];
|
|
line(canvas, start, end, Scalar(255, 255, 128), 3, LINE_AA);
|
|
line(canvas, start, far, Scalar(255, 150, 255), 3, LINE_AA);
|
|
line(canvas, end, far, Scalar(255, 150, 255), 3, LINE_AA);
|
|
circle(canvas, start, 7, Scalar(0, 0, 255), -1, LINE_AA);
|
|
circle(canvas, end, 7, Scalar(0, 0, 255), -1, LINE_AA);
|
|
circle(canvas, far, 7, Scalar(255, 0, 0), -1, LINE_AA));
|
|
}
|
|
|
|
DRAW(imshow("defects", canvas);
|
|
waitKey());
|
|
}
|
|
|
|
#undef DRAW
|
|
|
|
TEST(Imgproc_ConvexHull, overflow)
|
|
{
|
|
std::vector<Point> points;
|
|
std::vector<Point2f> pointsf;
|
|
|
|
points.push_back(Point(14763, 2890));
|
|
points.push_back(Point(14388, 72088));
|
|
points.push_back(Point(62810, 72274));
|
|
points.push_back(Point(63166, 3945));
|
|
points.push_back(Point(56782, 3945));
|
|
points.push_back(Point(56763, 3077));
|
|
points.push_back(Point(34666, 2965));
|
|
points.push_back(Point(34547, 2953));
|
|
points.push_back(Point(34508, 2866));
|
|
points.push_back(Point(34429, 2965));
|
|
|
|
size_t i, n = points.size();
|
|
for( i = 0; i < n; i++ )
|
|
pointsf.push_back(Point2f(points[i]));
|
|
|
|
std::vector<int> hull;
|
|
std::vector<int> hullf;
|
|
|
|
convexHull(points, hull, false, false);
|
|
convexHull(pointsf, hullf, false, false);
|
|
|
|
ASSERT_EQ(hull, hullf);
|
|
}
|
|
|
|
static
|
|
bool checkMinAreaRect(const RotatedRect& rr, const Mat& c, double eps = 0.5f)
|
|
{
|
|
int N = c.rows;
|
|
|
|
Mat rr_pts;
|
|
boxPoints(rr, rr_pts);
|
|
|
|
double maxError = 0.0;
|
|
int nfailed = 0;
|
|
for (int i = 0; i < N; i++)
|
|
{
|
|
double d = pointPolygonTest(rr_pts, c.at<Point2f>(i), true);
|
|
maxError = std::max(-d, maxError);
|
|
if (d < -eps)
|
|
nfailed++;
|
|
}
|
|
|
|
if (nfailed)
|
|
std::cout << "nfailed=" << nfailed << " (total=" << N << ") maxError=" << maxError << std::endl;
|
|
return nfailed == 0;
|
|
}
|
|
|
|
TEST(Imgproc_minAreaRect, reproducer_18157)
|
|
{
|
|
const int N = 168;
|
|
float pts_[N][2] = {
|
|
{ 1903, 266 }, { 1897, 267 }, { 1893, 268 }, { 1890, 269 },
|
|
{ 1878, 275 }, { 1875, 277 }, { 1872, 279 }, { 1868, 282 },
|
|
{ 1862, 287 }, { 1750, 400 }, { 1748, 402 }, { 1742, 407 },
|
|
{ 1742, 408 }, { 1740, 410 }, { 1738, 412 }, { 1593, 558 },
|
|
{ 1590, 560 }, { 1588, 562 }, { 1586, 564 }, { 1580, 570 },
|
|
{ 1443, 709 }, { 1437, 714 }, { 1435, 716 }, { 1304, 848 },
|
|
{ 1302, 850 }, { 1292, 860 }, { 1175, 979 }, { 1172, 981 },
|
|
{ 1049, 1105 }, { 936, 1220 }, { 933, 1222 }, { 931, 1224 },
|
|
{ 830, 1326 }, { 774, 1383 }, { 769, 1389 }, { 766, 1393 },
|
|
{ 764, 1396 }, { 762, 1399 }, { 760, 1402 }, { 757, 1408 },
|
|
{ 757, 1410 }, { 755, 1413 }, { 754, 1416 }, { 753, 1420 },
|
|
{ 752, 1424 }, { 752, 1442 }, { 753, 1447 }, { 754, 1451 },
|
|
{ 755, 1454 }, { 757, 1457 }, { 757, 1459 }, { 761, 1467 },
|
|
{ 763, 1470 }, { 765, 1473 }, { 767, 1476 }, { 771, 1481 },
|
|
{ 779, 1490 }, { 798, 1510 }, { 843, 1556 }, { 847, 1560 },
|
|
{ 851, 1564 }, { 863, 1575 }, { 907, 1620 }, { 909, 1622 },
|
|
{ 913, 1626 }, { 1154, 1866 }, { 1156, 1868 }, { 1158, 1870 },
|
|
{ 1207, 1918 }, { 1238, 1948 }, { 1252, 1961 }, { 1260, 1968 },
|
|
{ 1264, 1971 }, { 1268, 1974 }, { 1271, 1975 }, { 1273, 1977 },
|
|
{ 1283, 1982 }, { 1286, 1983 }, { 1289, 1984 }, { 1294, 1985 },
|
|
{ 1300, 1986 }, { 1310, 1986 }, { 1316, 1985 }, { 1320, 1984 },
|
|
{ 1323, 1983 }, { 1326, 1982 }, { 1338, 1976 }, { 1341, 1974 },
|
|
{ 1344, 1972 }, { 1349, 1968 }, { 1358, 1960 }, { 1406, 1911 },
|
|
{ 1421, 1897 }, { 1624, 1693 }, { 1788, 1528 }, { 1790, 1526 },
|
|
{ 1792, 1524 }, { 1794, 1522 }, { 1796, 1520 }, { 1798, 1518 },
|
|
{ 1800, 1516 }, { 1919, 1396 }, { 1921, 1394 }, { 2038, 1275 },
|
|
{ 2047, 1267 }, { 2048, 1265 }, { 2145, 1168 }, { 2148, 1165 },
|
|
{ 2260, 1052 }, { 2359, 952 }, { 2434, 876 }, { 2446, 863 },
|
|
{ 2450, 858 }, { 2453, 854 }, { 2455, 851 }, { 2457, 846 },
|
|
{ 2459, 844 }, { 2460, 842 }, { 2460, 840 }, { 2462, 837 },
|
|
{ 2463, 834 }, { 2464, 830 }, { 2465, 825 }, { 2465, 809 },
|
|
{ 2464, 804 }, { 2463, 800 }, { 2462, 797 }, { 2461, 794 },
|
|
{ 2456, 784 }, { 2454, 781 }, { 2452, 778 }, { 2450, 775 },
|
|
{ 2446, 770 }, { 2437, 760 }, { 2412, 734 }, { 2410, 732 },
|
|
{ 2408, 730 }, { 2382, 704 }, { 2380, 702 }, { 2378, 700 },
|
|
{ 2376, 698 }, { 2372, 694 }, { 2370, 692 }, { 2368, 690 },
|
|
{ 2366, 688 }, { 2362, 684 }, { 2360, 682 }, { 2252, 576 },
|
|
{ 2250, 573 }, { 2168, 492 }, { 2166, 490 }, { 2085, 410 },
|
|
{ 2026, 352 }, { 1988, 315 }, { 1968, 296 }, { 1958, 287 },
|
|
{ 1953, 283 }, { 1949, 280 }, { 1946, 278 }, { 1943, 276 },
|
|
{ 1940, 274 }, { 1936, 272 }, { 1934, 272 }, { 1931, 270 },
|
|
{ 1928, 269 }, { 1925, 268 }, { 1921, 267 }, { 1915, 266 }
|
|
};
|
|
|
|
Mat contour(N, 1, CV_32FC2, (void*)pts_);
|
|
|
|
RotatedRect rr = cv::minAreaRect(contour);
|
|
|
|
EXPECT_TRUE(checkMinAreaRect(rr, contour)) << rr.center << " " << rr.size << " " << rr.angle;
|
|
}
|
|
|
|
TEST(Imgproc_minAreaRect, reproducer_19769_lightweight)
|
|
{
|
|
const int N = 23;
|
|
float pts_[N][2] = {
|
|
{1325, 732}, {1248, 808}, {582, 1510}, {586, 1524},
|
|
{595, 1541}, {599, 1547}, {789, 1745}, {829, 1786},
|
|
{997, 1958}, {1116, 2074}, {1207, 2066}, {1216, 2058},
|
|
{1231, 2044}, {1265, 2011}, {2036, 1254}, {2100, 1191},
|
|
{2169, 1123}, {2315, 979}, {2395, 900}, {2438, 787},
|
|
{2434, 782}, {2416, 762}, {2266, 610}
|
|
};
|
|
Mat contour(N, 1, CV_32FC2, (void*)pts_);
|
|
|
|
RotatedRect rr = cv::minAreaRect(contour);
|
|
|
|
EXPECT_TRUE(checkMinAreaRect(rr, contour)) << rr.center << " " << rr.size << " " << rr.angle;
|
|
}
|
|
|
|
TEST(Imgproc_minAreaRect, reproducer_19769)
|
|
{
|
|
const int N = 169;
|
|
float pts_[N][2] = {
|
|
{1854, 227}, {1850, 228}, {1847, 229}, {1835, 235},
|
|
{1832, 237}, {1829, 239}, {1825, 242}, {1818, 248},
|
|
{1807, 258}, {1759, 306}, {1712, 351}, {1708, 356},
|
|
{1658, 404}, {1655, 408}, {1602, 459}, {1599, 463},
|
|
{1542, 518}, {1477, 582}, {1402, 656}, {1325, 732},
|
|
{1248, 808}, {1161, 894}, {1157, 898}, {1155, 900},
|
|
{1068, 986}, {1060, 995}, {1058, 997}, {957, 1097},
|
|
{956, 1097}, {814, 1238}, {810, 1242}, {805, 1248},
|
|
{610, 1442}, {603, 1450}, {599, 1455}, {596, 1459},
|
|
{594, 1462}, {592, 1465}, {590, 1470}, {588, 1472},
|
|
{586, 1476}, {586, 1478}, {584, 1481}, {583, 1485},
|
|
{582, 1490}, {582, 1510}, {583, 1515}, {584, 1518},
|
|
{585, 1521}, {586, 1524}, {593, 1538}, {595, 1541},
|
|
{597, 1544}, {599, 1547}, {603, 1552}, {609, 1559},
|
|
{623, 1574}, {645, 1597}, {677, 1630}, {713, 1667},
|
|
{753, 1707}, {789, 1744}, {789, 1745}, {829, 1786},
|
|
{871, 1828}, {909, 1867}, {909, 1868}, {950, 1910},
|
|
{953, 1912}, {997, 1958}, {1047, 2009}, {1094, 2056},
|
|
{1105, 2066}, {1110, 2070}, {1113, 2072}, {1116, 2074},
|
|
{1119, 2076}, {1122, 2077}, {1124, 2079}, {1130, 2082},
|
|
{1133, 2083}, {1136, 2084}, {1139, 2085}, {1142, 2086},
|
|
{1148, 2087}, {1166, 2087}, {1170, 2086}, {1174, 2085},
|
|
{1177, 2084}, {1180, 2083}, {1188, 2079}, {1190, 2077},
|
|
{1193, 2076}, {1196, 2074}, {1199, 2072}, {1202, 2070},
|
|
{1207, 2066}, {1216, 2058}, {1231, 2044}, {1265, 2011},
|
|
{1314, 1962}, {1360, 1917}, {1361, 1917}, {1408, 1871},
|
|
{1457, 1822}, {1508, 1773}, {1512, 1768}, {1560, 1722},
|
|
{1617, 1665}, {1671, 1613}, {1730, 1554}, {1784, 1502},
|
|
{1786, 1500}, {1787, 1498}, {1846, 1440}, {1850, 1437},
|
|
{1908, 1380}, {1974, 1314}, {2034, 1256}, {2036, 1254},
|
|
{2100, 1191}, {2169, 1123}, {2242, 1051}, {2315, 979},
|
|
{2395, 900}, {2426, 869}, {2435, 859}, {2438, 855},
|
|
{2440, 852}, {2442, 849}, {2443, 846}, {2445, 844},
|
|
{2446, 842}, {2446, 840}, {2448, 837}, {2449, 834},
|
|
{2450, 829}, {2450, 814}, {2449, 809}, {2448, 806},
|
|
{2447, 803}, {2442, 793}, {2440, 790}, {2438, 787},
|
|
{2434, 782}, {2428, 775}, {2416, 762}, {2411, 758},
|
|
{2342, 688}, {2340, 686}, {2338, 684}, {2266, 610},
|
|
{2260, 605}, {2170, 513}, {2075, 417}, {2073, 415},
|
|
{2069, 412}, {1955, 297}, {1955, 296}, {1913, 254},
|
|
{1904, 246}, {1897, 240}, {1894, 238}, {1891, 236},
|
|
{1888, 234}, {1880, 230}, {1877, 229}, {1874, 228},
|
|
{1870, 227}
|
|
};
|
|
Mat contour(N, 1, CV_32FC2, (void*)pts_);
|
|
|
|
RotatedRect rr = cv::minAreaRect(contour);
|
|
|
|
EXPECT_TRUE(checkMinAreaRect(rr, contour)) << rr.center << " " << rr.size << " " << rr.angle;
|
|
}
|
|
|
|
TEST(Imgproc_minEnclosingTriangle, regression_17585)
|
|
{
|
|
const int N = 3;
|
|
float pts_[N][2] = { {0, 0}, {0, 1}, {1, 1} };
|
|
cv::Mat points(N, 2, CV_32FC1, static_cast<void*>(pts_));
|
|
vector<Point2f> triangle;
|
|
|
|
EXPECT_NO_THROW(minEnclosingTriangle(points, triangle));
|
|
}
|
|
|
|
TEST(Imgproc_minEnclosingTriangle, regression_20890)
|
|
{
|
|
vector<Point> points;
|
|
points.push_back(Point(0, 0));
|
|
points.push_back(Point(0, 1));
|
|
points.push_back(Point(1, 1));
|
|
vector<Point2f> triangle;
|
|
|
|
EXPECT_NO_THROW(minEnclosingTriangle(points, triangle));
|
|
}
|
|
|
|
TEST(Imgproc_minEnclosingTriangle, regression_mat_with_diff_channels)
|
|
{
|
|
const int N = 3;
|
|
float pts_[N][2] = { {0, 0}, {0, 1}, {1, 1} };
|
|
cv::Mat points1xN(1, N, CV_32FC2, static_cast<void*>(pts_));
|
|
cv::Mat pointsNx1(N, 1, CV_32FC2, static_cast<void*>(pts_));
|
|
vector<Point2f> triangle;
|
|
|
|
EXPECT_NO_THROW(minEnclosingTriangle(points1xN, triangle));
|
|
EXPECT_NO_THROW(minEnclosingTriangle(pointsNx1, triangle));
|
|
}
|
|
|
|
}} // namespace
|
|
/* End of file. */
|