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Diffstat (limited to 'thirdparty1/linux/include/opencv2/ximgproc/structured_edge_detection.hpp')
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diff --git a/thirdparty1/linux/include/opencv2/ximgproc/structured_edge_detection.hpp b/thirdparty1/linux/include/opencv2/ximgproc/structured_edge_detection.hpp new file mode 100644 index 0000000..db6e906 --- /dev/null +++ b/thirdparty1/linux/include/opencv2/ximgproc/structured_edge_detection.hpp @@ -0,0 +1,128 @@ +/*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. +// +// +// License Agreement +// For Open Source Computer Vision Library +// +// Copyright (C) 2000-2008, Intel Corporation, all rights reserved. +// Copyright (C) 2009-2011, Willow Garage Inc., 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 the copyright holders 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*/ + +#ifndef __OPENCV_STRUCTURED_EDGE_DETECTION_HPP__ +#define __OPENCV_STRUCTURED_EDGE_DETECTION_HPP__ +#ifdef __cplusplus + +/** @file +@date Jun 17, 2014 +@author Yury Gitman + */ + +#include <opencv2/core.hpp> + +namespace cv +{ +namespace ximgproc +{ + +//! @addtogroup ximgproc_edge +//! @{ + +/*! + Helper class for training part of [P. Dollar and C. L. Zitnick. Structured Forests for Fast Edge Detection, 2013]. + */ +class CV_EXPORTS_W RFFeatureGetter : public Algorithm +{ +public: + + /*! + * This functions extracts feature channels from src. + * Than StructureEdgeDetection uses this feature space + * to detect edges. + * + * \param src : source image to extract features + * \param features : output n-channel floating point feature matrix. + * + * \param gnrmRad : __rf.options.gradientNormalizationRadius + * \param gsmthRad : __rf.options.gradientSmoothingRadius + * \param shrink : __rf.options.shrinkNumber + * \param outNum : __rf.options.numberOfOutputChannels + * \param gradNum : __rf.options.numberOfGradientOrientations + */ + CV_WRAP virtual void getFeatures(const Mat &src, Mat &features, + const int gnrmRad, + const int gsmthRad, + const int shrink, + const int outNum, + const int gradNum) const = 0; +}; + +CV_EXPORTS_W Ptr<RFFeatureGetter> createRFFeatureGetter(); + + + +/** @brief Class implementing edge detection algorithm from @cite Dollar2013 : + */ +class CV_EXPORTS_W StructuredEdgeDetection : public Algorithm +{ +public: + + /** @brief The function detects edges in src and draw them to dst. + + The algorithm underlies this function is much more robust to texture presence, than common + approaches, e.g. Sobel + @param src source image (RGB, float, in [0;1]) to detect edges + @param dst destination image (grayscale, float, in [0;1]) where edges are drawn + @sa Sobel, Canny + */ + CV_WRAP virtual void detectEdges(const Mat &src, CV_OUT Mat &dst) const = 0; +}; + +/*! +* The only constructor +* +* \param model : name of the file where the model is stored +* \param howToGetFeatures : optional object inheriting from RFFeatureGetter. +* You need it only if you would like to train your +* own forest, pass NULL otherwise +*/ +CV_EXPORTS_W Ptr<StructuredEdgeDetection> createStructuredEdgeDetection(const String &model, + Ptr<const RFFeatureGetter> howToGetFeatures = Ptr<RFFeatureGetter>()); + +//! @} + +} +} +#endif +#endif /* __OPENCV_STRUCTURED_EDGE_DETECTION_HPP__ */ |