/*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_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 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. */