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opencv/modules/imgproc/test/test_convhull.cpp

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/*M///////////////////////////////////////////////////////////////////////////////////////
//
// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
//
// By downloading, copying, installing or using the software you agree to this license.
// If you do not agree to this license, do not download, install,
// copy or use the software.
//
//
// Intel License Agreement
// For Open Source Computer Vision Library
//
// Copyright (C) 2000, Intel Corporation, all rights reserved.
// Third party copyrights are property of their respective owners.
//
// Redistribution and use in source and binary forms, with or without modification,
// are permitted provided that the following conditions are met:
//
// * Redistribution's of source code must retain the above copyright notice,
// this list of conditions and the following disclaimer.
//
// * Redistribution's in binary form must reproduce the above copyright notice,
// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
//
// * The name of Intel Corporation may not be used to endorse or promote products
// derived from this software without specific prior written permission.
//
// This software is provided by the copyright holders and contributors "as is" and
// any express or implied warranties, including, but not limited to, the implied
// warranties of merchantability and fitness for a particular purpose are disclaimed.
// In no event shall the Intel Corporation or contributors be liable for any direct,
// indirect, incidental, special, exemplary, or consequential damages
// (including, but not limited to, procurement of substitute goods or services;
// loss of use, data, or profits; or business interruption) however caused
// and on any theory of liability, whether in contract, strict liability,
// or tort (including negligence or otherwise) arising in any way out of
// the use of this software, even if advised of the possibility of such damage.
//
//M*/
#include "test_precomp.hpp"
namespace opencv_test { namespace {
/*static int
cvTsPointConvexPolygon( CvPoint2D32f pt, CvPoint2D32f* v, int n )
{
CvPoint2D32f v0 = v[n-1];
int i, sign = 0;
for( i = 0; i < n; i++ )
{
CvPoint2D32f v1 = v[i];
float dx = pt.x - v0.x, dy = pt.y - v0.y;
float dx1 = v1.x - v0.x, dy1 = v1.y - v0.y;
double t = (double)dx*dy1 - (double)dx1*dy;
if( fabs(t) > DBL_EPSILON )
{
if( t*sign < 0 )
break;
if( sign == 0 )
sign = t < 0 ? -1 : 1;
}
else if( fabs(dx) + fabs(dy) < DBL_EPSILON )
return i+1;
v0 = v1;
}
return i < n ? -1 : 0;
}*/
CV_INLINE double
cvTsDist( CvPoint2D32f a, CvPoint2D32f b )
{
double dx = a.x - b.x;
double dy = a.y - b.y;
return sqrt(dx*dx + dy*dy);
}
CV_INLINE double
cvTsDist( const Point2f& a, const Point2f& b )
{
double dx = a.x - b.x;
double dy = a.y - b.y;
return sqrt(dx*dx + dy*dy);
}
CV_INLINE double
cvTsPtLineDist( CvPoint2D32f pt, CvPoint2D32f a, CvPoint2D32f b )
{
double d0 = cvTsDist( pt, a ), d1;
double dd = cvTsDist( a, b );
if( dd < FLT_EPSILON )
return d0;
d1 = cvTsDist( pt, b );
dd = fabs((double)(pt.x - a.x)*(b.y - a.y) - (double)(pt.y - a.y)*(b.x - a.x))/dd;
d0 = MIN( d0, d1 );
return MIN( d0, dd );
}
static double
cvTsPointPolygonTest( CvPoint2D32f pt, const CvPoint2D32f* vv, int n, int* _idx=0, int* _on_edge=0 )
{
int i;
Point2f v = vv[n-1], v0;
double min_dist_num = FLT_MAX, min_dist_denom = 1;
int min_dist_idx = -1, min_on_edge = 0;
int counter = 0;
double result;
for( i = 0; i < n; i++ )
{
double dx, dy, dx1, dy1, dx2, dy2, dist_num, dist_denom = 1;
int on_edge = 0, idx = i;
v0 = v; v = vv[i];
dx = v.x - v0.x; dy = v.y - v0.y;
dx1 = pt.x - v0.x; dy1 = pt.y - v0.y;
dx2 = pt.x - v.x; dy2 = pt.y - v.y;
if( dx2*dx + dy2*dy >= 0 )
dist_num = dx2*dx2 + dy2*dy2;
else if( dx1*dx + dy1*dy <= 0 )
{
dist_num = dx1*dx1 + dy1*dy1;
idx = i - 1;
if( idx < 0 ) idx = n-1;
}
else
{
dist_num = (dy1*dx - dx1*dy);
dist_num *= dist_num;
dist_denom = dx*dx + dy*dy;
on_edge = 1;
}
if( dist_num*min_dist_denom < min_dist_num*dist_denom )
{
min_dist_num = dist_num;
min_dist_denom = dist_denom;
min_dist_idx = idx;
min_on_edge = on_edge;
if( min_dist_num == 0 )
break;
}
if( (v0.y <= pt.y && v.y <= pt.y) ||
(v0.y > pt.y && v.y > pt.y) ||
(v0.x < pt.x && v.x < pt.x) )
continue;
dist_num = dy1*dx - dx1*dy;
if( dy < 0 )
dist_num = -dist_num;
counter += dist_num > 0;
}
result = sqrt(min_dist_num/min_dist_denom);
if( counter % 2 == 0 )
result = -result;
if( _idx )
*_idx = min_dist_idx;
if( _on_edge )
*_on_edge = min_on_edge;
return result;
}
static cv::Point2f
cvTsMiddlePoint(const cv::Point2f &a, const cv::Point2f &b)
{
return cv::Point2f((a.x + b.x) / 2, (a.y + b.y) / 2);
}
static bool
cvTsIsPointOnLineSegment(const cv::Point2f &x, const cv::Point2f &a, const cv::Point2f &b)
{
double d1 = cvTsDist(cvPoint2D32f(x.x, x.y), cvPoint2D32f(a.x, a.y));
double d2 = cvTsDist(cvPoint2D32f(x.x, x.y), cvPoint2D32f(b.x, b.y));
double d3 = cvTsDist(cvPoint2D32f(a.x, a.y), cvPoint2D32f(b.x, b.y));
return (abs(d1 + d2 - d3) <= (1E-4));
}
/****************************************************************************************\
* Base class for shape descriptor tests *
\****************************************************************************************/
class CV_BaseShapeDescrTest : public cvtest::BaseTest
{
public:
CV_BaseShapeDescrTest();
virtual ~CV_BaseShapeDescrTest();
void clear();
protected:
int read_params( const cv::FileStorage& fs );
void run_func(void);
int prepare_test_case( int test_case_idx );
int validate_test_results( int test_case_idx );
virtual void generate_point_set( void* points );
virtual void extract_points();
int min_log_size;
int max_log_size;
int dims;
bool enable_flt_points;
CvMemStorage* storage;
CvSeq* points1;
CvMat* points2;
void* points;
void* result;
double low_high_range;
Scalar low, high;
bool test_cpp;
};
CV_BaseShapeDescrTest::CV_BaseShapeDescrTest()
{
points1 = 0;
points2 = 0;
points = 0;
storage = 0;
test_case_count = 500;
min_log_size = 0;
max_log_size = 10;
low = high = cvScalarAll(0);
low_high_range = 50;
dims = 2;
enable_flt_points = true;
test_cpp = false;
}
CV_BaseShapeDescrTest::~CV_BaseShapeDescrTest()
{
clear();
}
void CV_BaseShapeDescrTest::clear()
{
cvtest::BaseTest::clear();
cvReleaseMemStorage( &storage );
cvReleaseMat( &points2 );
points1 = 0;
points = 0;
}
int CV_BaseShapeDescrTest::read_params( const cv::FileStorage& fs )
{
int code = cvtest::BaseTest::read_params( fs );
if( code < 0 )
return code;
read( find_param( fs, "struct_count" ), test_case_count, test_case_count );
read( find_param( fs, "min_log_size" ), min_log_size, min_log_size );
read( find_param( fs, "max_log_size" ), max_log_size, max_log_size );
min_log_size = cvtest::clipInt( min_log_size, 0, 8 );
max_log_size = cvtest::clipInt( max_log_size, 0, 10 );
if( min_log_size > max_log_size )
{
int t;
CV_SWAP( min_log_size, max_log_size, t );
}
return 0;
}
void CV_BaseShapeDescrTest::generate_point_set( void* pointsSet )
{
RNG& rng = ts->get_rng();
int i, k, n, total, point_type;
CvSeqReader reader;
uchar* data = 0;
double a[4], b[4];
for( k = 0; k < 4; k++ )
{
a[k] = high.val[k] - low.val[k];
b[k] = low.val[k];
}
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;
}
n = CV_MAT_CN(point_type);
point_type = CV_MAT_DEPTH(point_type);
CV_Assert( (point_type == CV_32S || point_type == CV_32F) && n <= 4 );
for( i = 0; i < total; i++ )
{
int* pi;
float* pf;
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;
}
if( point_type == CV_32S )
for( k = 0; k < n; k++ )
pi[k] = cvRound(cvtest::randReal(rng)*a[k] + b[k]);
else
for( k = 0; k < n; k++ )
pf[k] = (float)(cvtest::randReal(rng)*a[k] + b[k]);
}
}
int CV_BaseShapeDescrTest::prepare_test_case( int test_case_idx )
{
int size;
int use_storage = 0;
int point_type;
int i;
RNG& rng = ts->get_rng();
cvtest::BaseTest::prepare_test_case( test_case_idx );
clear();
size = cvRound( exp((cvtest::randReal(rng) * (max_log_size - min_log_size) + min_log_size)*CV_LOG2) );
use_storage = cvtest::randInt(rng) % 2;
point_type = CV_MAKETYPE(cvtest::randInt(rng) %
(enable_flt_points ? 2 : 1) ? CV_32F : CV_32S, dims);
if( use_storage )
{
storage = cvCreateMemStorage( (cvtest::randInt(rng)%10 + 1)*1024 );
points1 = cvCreateSeq( point_type, sizeof(CvSeq), CV_ELEM_SIZE(point_type), storage );
cvSeqPushMulti( points1, 0, size );
points = points1;
}
else
{
int rows = 1, cols = size;
if( cvtest::randInt(rng) % 2 )
rows = size, cols = 1;
points2 = cvCreateMat( rows, cols, point_type );
points = points2;
}
for( i = 0; i < 4; i++ )
{
low.val[i] = (cvtest::randReal(rng)-0.5)*low_high_range*2;
high.val[i] = (cvtest::randReal(rng)-0.5)*low_high_range*2;
if( low.val[i] > high.val[i] )
{
double t;
CV_SWAP( low.val[i], high.val[i], t );
}
if( high.val[i] < low.val[i] + 1 )
high.val[i] += 1;
}
generate_point_set( points );
test_cpp = (cvtest::randInt(rng) & 16) == 0;
return 1;
}
void CV_BaseShapeDescrTest::extract_points()
{
if( points1 )
{
points2 = cvCreateMat( 1, points1->total, CV_SEQ_ELTYPE(points1) );
cvCvtSeqToArray( points1, points2->data.ptr );
}
if( CV_MAT_DEPTH(points2->type) != CV_32F && enable_flt_points )
{
CvMat tmp = cvMat( points2->rows, points2->cols,
(points2->type & ~CV_MAT_DEPTH_MASK) | CV_32F, points2->data.ptr );
cvConvert( points2, &tmp );
}
}
void CV_BaseShapeDescrTest::run_func(void)
{
}
int CV_BaseShapeDescrTest::validate_test_results( int /*test_case_idx*/ )
{
extract_points();
return 0;
}
/****************************************************************************************\
* Convex Hull Test *
\****************************************************************************************/
class CV_ConvHullTest : public CV_BaseShapeDescrTest
{
public:
CV_ConvHullTest();
virtual ~CV_ConvHullTest();
void clear();
protected:
void run_func(void);
int prepare_test_case( int test_case_idx );
int validate_test_results( int test_case_idx );
CvSeq* hull1;
CvMat* hull2;
void* hull_storage;
int orientation;
int return_points;
};
CV_ConvHullTest::CV_ConvHullTest()
{
hull1 = 0;
hull2 = 0;
hull_storage = 0;
orientation = return_points = 0;
}
CV_ConvHullTest::~CV_ConvHullTest()
{
clear();
}
void CV_ConvHullTest::clear()
{
CV_BaseShapeDescrTest::clear();
cvReleaseMat( &hull2 );
hull1 = 0;
hull_storage = 0;
}
int CV_ConvHullTest::prepare_test_case( int test_case_idx )
{
int code = CV_BaseShapeDescrTest::prepare_test_case( test_case_idx );
int use_storage_for_hull = 0;
RNG& rng = ts->get_rng();
if( code <= 0 )
return code;
orientation = cvtest::randInt(rng) % 2 ? CV_CLOCKWISE : CV_COUNTER_CLOCKWISE;
return_points = cvtest::randInt(rng) % 2;
use_storage_for_hull = (cvtest::randInt(rng) % 2) && !test_cpp;
if( use_storage_for_hull )
{
if( !storage )
storage = cvCreateMemStorage( (cvtest::randInt(rng)%10 + 1)*1024 );
hull_storage = storage;
}
else
{
int rows, cols;
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 )
{
#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);
}
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. */