mirror of
https://github.com/opencv/opencv.git
synced 2024-12-17 19:08:01 +08:00
8f3867756c
fixed the ordering of contour convex hull points * partially fixed the issue #4539 * fixed warnings and test failures * fixed integer overflow (issue #14521) * added comment to force buildbot to re-run * extended the test for the issue 4539. Check the expected behaviour on the original contour as well * added comment; fixed typo, renamed another variable for a little better clarity * added yet another part to the test for issue #4539, where we run convexHull and convexityDetects on the original contour, without any manipulations. the rest of the test stays the same
2311 lines
68 KiB
C++
2311 lines
68 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-5));
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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( CvFileStorage* 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( CvFileStorage* fs )
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{
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int code = cvtest::BaseTest::read_params( fs );
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if( code < 0 )
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return code;
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test_case_count = cvReadInt( find_param( fs, "struct_count" ), test_case_count );
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min_log_size = cvReadInt( find_param( fs, "min_log_size" ), min_log_size );
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max_log_size = cvReadInt( find_param( fs, "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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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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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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* 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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CV_ConvHullTest::~CV_ConvHullTest()
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{
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clear();
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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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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;
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int point_type = points1 ? CV_SEQ_ELTYPE(points1) : CV_MAT_TYPE(points2->type);
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if( cvtest::randInt(rng) % 2 )
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rows = sz, cols = 1;
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else
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rows = 1, cols = sz;
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hull2 = cvCreateMat( rows, cols, return_points ? point_type : CV_32SC1 );
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hull_storage = hull2;
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}
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return code;
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}
|
|
|
|
|
|
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_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_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 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;
|
|
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;
|
|
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;
|
|
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;
|
|
}
|
|
|
|
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);
|
|
|
|
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 )
|
|
{
|
|
#if 0
|
|
cvCmpS( img, 0, img, CV_CMP_GT );
|
|
cvNamedWindow( "test", 1 );
|
|
cvShowImage( "test", img );
|
|
cvWaitKey();
|
|
#endif
|
|
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);
|
|
}
|
|
|
|
}} // namespace
|
|
/* End of file. */
|