149 lines
5.6 KiB
C++
149 lines
5.6 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009-2011, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_STRUCTURED_EDGE_DETECTION_HPP__
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#define __OPENCV_STRUCTURED_EDGE_DETECTION_HPP__
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#ifdef __cplusplus
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/** @file
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@date Jun 17, 2014
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@author Yury Gitman
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*/
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#include <opencv2/core.hpp>
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namespace cv
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{
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namespace ximgproc
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{
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//! @addtogroup ximgproc_edge
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//! @{
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/*!
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Helper class for training part of [P. Dollar and C. L. Zitnick. Structured Forests for Fast Edge Detection, 2013].
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*/
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class CV_EXPORTS_W RFFeatureGetter : public Algorithm
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{
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public:
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/*!
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* This functions extracts feature channels from src.
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* Than StructureEdgeDetection uses this feature space
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* to detect edges.
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*
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* \param src : source image to extract features
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* \param features : output n-channel floating point feature matrix.
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*
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* \param gnrmRad : __rf.options.gradientNormalizationRadius
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* \param gsmthRad : __rf.options.gradientSmoothingRadius
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* \param shrink : __rf.options.shrinkNumber
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* \param outNum : __rf.options.numberOfOutputChannels
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* \param gradNum : __rf.options.numberOfGradientOrientations
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*/
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CV_WRAP virtual void getFeatures(const Mat &src, Mat &features,
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const int gnrmRad,
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const int gsmthRad,
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const int shrink,
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const int outNum,
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const int gradNum) const = 0;
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};
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CV_EXPORTS_W Ptr<RFFeatureGetter> createRFFeatureGetter();
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/** @brief Class implementing edge detection algorithm from @cite Dollar2013 :
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*/
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class CV_EXPORTS_W StructuredEdgeDetection : public Algorithm
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{
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public:
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/** @brief The function detects edges in src and draw them to dst.
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The algorithm underlies this function is much more robust to texture presence, than common
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approaches, e.g. Sobel
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@param _src source image (RGB, float, in [0;1]) to detect edges
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@param _dst destination image (grayscale, float, in [0;1]) where edges are drawn
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@sa Sobel, Canny
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*/
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CV_WRAP virtual void detectEdges(cv::InputArray _src, cv::OutputArray _dst) const = 0;
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/** @brief The function computes orientation from edge image.
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@param _src edge image.
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@param _dst orientation image.
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*/
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CV_WRAP virtual void computeOrientation(cv::InputArray _src, cv::OutputArray _dst) const = 0;
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/** @brief The function edgenms in edge image and suppress edges where edge is stronger in orthogonal direction.
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@param edge_image edge image from detectEdges function.
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@param orientation_image orientation image from computeOrientation function.
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@param _dst suppressed image (grayscale, float, in [0;1])
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@param r radius for NMS suppression.
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@param s radius for boundary suppression.
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@param m multiplier for conservative suppression.
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@param isParallel enables/disables parallel computing.
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*/
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CV_WRAP virtual void edgesNms(cv::InputArray edge_image, cv::InputArray orientation_image, cv::OutputArray _dst, int r = 2, int s = 0, float m = 1, bool isParallel = true) const = 0;
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};
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/*!
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* The only constructor
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*
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* \param model : name of the file where the model is stored
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* \param howToGetFeatures : optional object inheriting from RFFeatureGetter.
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* You need it only if you would like to train your
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* own forest, pass NULL otherwise
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*/
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CV_EXPORTS_W Ptr<StructuredEdgeDetection> createStructuredEdgeDetection(const String &model,
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Ptr<const RFFeatureGetter> howToGetFeatures = Ptr<RFFeatureGetter>());
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//! @}
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}
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}
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#endif
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#endif /* __OPENCV_STRUCTURED_EDGE_DETECTION_HPP__ */
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