void detect( InputArray _image, std::vector<KeyPoint>& keypoints, InputArray _mask ) { CV_INSTRUMENT_REGION() std::vector<Point2f> corners; if (_image.isUMat()) { UMat ugrayImage; if( _image.type() != CV_8U ) cvtColor( _image, ugrayImage, COLOR_BGR2GRAY ); else ugrayImage = _image.getUMat(); goodFeaturesToTrack( ugrayImage, corners, nfeatures, qualityLevel, minDistance, _mask, blockSize, useHarrisDetector, k ); } else { Mat image = _image.getMat(), grayImage = image; if( image.type() != CV_8U ) cvtColor( image, grayImage, COLOR_BGR2GRAY ); goodFeaturesToTrack( grayImage, corners, nfeatures, qualityLevel, minDistance, _mask, blockSize, useHarrisDetector, k ); } keypoints.resize(corners.size()); std::vector<Point2f>::const_iterator corner_it = corners.begin(); std::vector<KeyPoint>::iterator keypoint_it = keypoints.begin(); for( ; corner_it != corners.end(); ++corner_it, ++keypoint_it ) *keypoint_it = KeyPoint( *corner_it, (float)blockSize ); }
void cv::superres::arrCopy(InputArray src, OutputArray dst) { if (dst.isUMat() || src.isUMat()) { src.copyTo(dst); return; } typedef void (*func_t)(InputArray src, OutputArray dst); static const func_t funcs[10][10] = { { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }, { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu }, { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu }, { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu }, { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu }, { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu }, { 0, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, mat2mat, arr2buf, 0, mat2gpu }, { 0, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, buf2arr, 0, buf2arr }, { 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 }, { 0, gpu2mat, gpu2mat, gpu2mat, gpu2mat, gpu2mat, gpu2mat, arr2buf, 0 , gpu2gpu }, }; const int src_kind = src.kind() >> _InputArray::KIND_SHIFT; const int dst_kind = dst.kind() >> _InputArray::KIND_SHIFT; CV_Assert( src_kind >= 0 && src_kind < 10 ); CV_Assert( dst_kind >= 0 && dst_kind < 10 ); const func_t func = funcs[src_kind][dst_kind]; CV_Assert( func != 0 ); func(src, dst); }
static std::vector<Mat> extractMatVector(InputArray in) { if (in.isMat() || in.isUMat()) { return std::vector<Mat>(1, in.getMat()); } else if (in.isMatVector()) { return *static_cast<const std::vector<Mat>*>(in.getObj()); } else if (in.isUMatVector()) { std::vector<Mat> vmat; in.getMatVector(vmat); return vmat; } else { CV_Assert(in.isMat() || in.isMatVector() || in.isUMat() || in.isUMatVector()); return std::vector<Mat>(); } }
void cv::fastNlMeansDenoisingColored( InputArray _src, OutputArray _dst, float h, float hForColorComponents, int templateWindowSize, int searchWindowSize) { int type = _src.type(), depth = CV_MAT_DEPTH(type), cn = CV_MAT_CN(type); if (type != CV_8UC3 && type != CV_8UC4) { CV_Error(Error::StsBadArg, "Type of input image should be CV_8UC3!"); return; } CV_OCL_RUN(_src.dims() <= 2 && (_dst.isUMat() || _src.isUMat()), ocl_fastNlMeansDenoisingColored(_src, _dst, h, hForColorComponents, templateWindowSize, searchWindowSize)) Mat src = _src.getMat(); _dst.create(src.size(), type); Mat dst = _dst.getMat(); Mat src_lab; cvtColor(src, src_lab, COLOR_LBGR2Lab); Mat l(src.size(), CV_8U); Mat ab(src.size(), CV_8UC2); Mat l_ab[] = { l, ab }; int from_to[] = { 0,0, 1,1, 2,2 }; mixChannels(&src_lab, 1, l_ab, 2, from_to, 3); fastNlMeansDenoising(l, l, h, templateWindowSize, searchWindowSize); fastNlMeansDenoising(ab, ab, hForColorComponents, templateWindowSize, searchWindowSize); Mat l_ab_denoised[] = { l, ab }; Mat dst_lab(src.size(), CV_MAKE_TYPE(depth, 3)); mixChannels(l_ab_denoised, 2, &dst_lab, 1, from_to, 3); cvtColor(dst_lab, dst, COLOR_Lab2LBGR, cn); }
void cv::fastNlMeansDenoising( InputArray _src, OutputArray _dst, float h, int templateWindowSize, int searchWindowSize) { CV_OCL_RUN(_src.dims() <= 2 && (_src.isUMat() || _dst.isUMat()), ocl_fastNlMeansDenoising(_src, _dst, h, templateWindowSize, searchWindowSize)) Mat src = _src.getMat(); _dst.create(src.size(), src.type()); Mat dst = _dst.getMat(); #ifdef HAVE_TEGRA_OPTIMIZATION if(tegra::fastNlMeansDenoising(src, dst, h, templateWindowSize, searchWindowSize)) return; #endif switch (src.type()) { case CV_8U: parallel_for_(cv::Range(0, src.rows), FastNlMeansDenoisingInvoker<uchar>( src, dst, templateWindowSize, searchWindowSize, h)); break; case CV_8UC2: parallel_for_(cv::Range(0, src.rows), FastNlMeansDenoisingInvoker<cv::Vec2b>( src, dst, templateWindowSize, searchWindowSize, h)); break; case CV_8UC3: parallel_for_(cv::Range(0, src.rows), FastNlMeansDenoisingInvoker<cv::Vec3b>( src, dst, templateWindowSize, searchWindowSize, h)); break; default: CV_Error(Error::StsBadArg, "Unsupported image format! Only CV_8UC1, CV_8UC2 and CV_8UC3 are supported"); } }
int cv::meanShift( InputArray _probImage, Rect& window, TermCriteria criteria ) { CV_INSTRUMENT_REGION() Size size; int cn; Mat mat; UMat umat; bool isUMat = _probImage.isUMat(); if (isUMat) umat = _probImage.getUMat(), cn = umat.channels(), size = umat.size(); else mat = _probImage.getMat(), cn = mat.channels(), size = mat.size(); Rect cur_rect = window; CV_Assert( cn == 1 ); if( window.height <= 0 || window.width <= 0 ) CV_Error( Error::StsBadArg, "Input window has non-positive sizes" ); window = window & Rect(0, 0, size.width, size.height); double eps = (criteria.type & TermCriteria::EPS) ? std::max(criteria.epsilon, 0.) : 1.; eps = cvRound(eps*eps); int i, niters = (criteria.type & TermCriteria::MAX_ITER) ? std::max(criteria.maxCount, 1) : 100; for( i = 0; i < niters; i++ ) { cur_rect = cur_rect & Rect(0, 0, size.width, size.height); if( cur_rect == Rect() ) { cur_rect.x = size.width/2; cur_rect.y = size.height/2; } cur_rect.width = std::max(cur_rect.width, 1); cur_rect.height = std::max(cur_rect.height, 1); Moments m = isUMat ? moments(umat(cur_rect)) : moments(mat(cur_rect)); // Calculating center of mass if( fabs(m.m00) < DBL_EPSILON ) break; int dx = cvRound( m.m10/m.m00 - window.width*0.5 ); int dy = cvRound( m.m01/m.m00 - window.height*0.5 ); int nx = std::min(std::max(cur_rect.x + dx, 0), size.width - cur_rect.width); int ny = std::min(std::max(cur_rect.y + dy, 0), size.height - cur_rect.height); dx = nx - cur_rect.x; dy = ny - cur_rect.y; cur_rect.x = nx; cur_rect.y = ny; // Check for coverage centers mass & window if( dx*dx + dy*dy < eps ) break; } window = cur_rect; return i; }
cv::RotatedRect cv::CamShift( InputArray _probImage, Rect& window, TermCriteria criteria ) { CV_INSTRUMENT_REGION() const int TOLERANCE = 10; Size size; Mat mat; UMat umat; bool isUMat = _probImage.isUMat(); if (isUMat) umat = _probImage.getUMat(), size = umat.size(); else mat = _probImage.getMat(), size = mat.size(); meanShift( _probImage, window, criteria ); window.x -= TOLERANCE; if( window.x < 0 ) window.x = 0; window.y -= TOLERANCE; if( window.y < 0 ) window.y = 0; window.width += 2 * TOLERANCE; if( window.x + window.width > size.width ) window.width = size.width - window.x; window.height += 2 * TOLERANCE; if( window.y + window.height > size.height ) window.height = size.height - window.y; // Calculating moments in new center mass Moments m = isUMat ? moments(umat(window)) : moments(mat(window)); double m00 = m.m00, m10 = m.m10, m01 = m.m01; double mu11 = m.mu11, mu20 = m.mu20, mu02 = m.mu02; if( fabs(m00) < DBL_EPSILON ) return RotatedRect(); double inv_m00 = 1. / m00; int xc = cvRound( m10 * inv_m00 + window.x ); int yc = cvRound( m01 * inv_m00 + window.y ); double a = mu20 * inv_m00, b = mu11 * inv_m00, c = mu02 * inv_m00; // Calculating width & height double square = std::sqrt( 4 * b * b + (a - c) * (a - c) ); // Calculating orientation double theta = atan2( 2 * b, a - c + square ); // Calculating width & length of figure double cs = cos( theta ); double sn = sin( theta ); double rotate_a = cs * cs * mu20 + 2 * cs * sn * mu11 + sn * sn * mu02; double rotate_c = sn * sn * mu20 - 2 * cs * sn * mu11 + cs * cs * mu02; double length = std::sqrt( rotate_a * inv_m00 ) * 4; double width = std::sqrt( rotate_c * inv_m00 ) * 4; // In case, when tetta is 0 or 1.57... the Length & Width may be exchanged if( length < width ) { std::swap( length, width ); std::swap( cs, sn ); theta = CV_PI*0.5 - theta; } // Saving results int _xc = cvRound( xc ); int _yc = cvRound( yc ); int t0 = cvRound( fabs( length * cs )); int t1 = cvRound( fabs( width * sn )); t0 = MAX( t0, t1 ) + 2; window.width = MIN( t0, (size.width - _xc) * 2 ); t0 = cvRound( fabs( length * sn )); t1 = cvRound( fabs( width * cs )); t0 = MAX( t0, t1 ) + 2; window.height = MIN( t0, (size.height - _yc) * 2 ); window.x = MAX( 0, _xc - window.width / 2 ); window.y = MAX( 0, _yc - window.height / 2 ); window.width = MIN( size.width - window.x, window.width ); window.height = MIN( size.height - window.y, window.height ); RotatedRect box; box.size.height = (float)length; box.size.width = (float)width; box.angle = (float)((CV_PI*0.5+theta)*180./CV_PI); while(box.angle < 0) box.angle += 360; while(box.angle >= 360) box.angle -= 360; if(box.angle >= 180) box.angle -= 180; box.center = Point2f( window.x + window.width*0.5f, window.y + window.height*0.5f); return box; }