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148 lines
5.6 KiB
148 lines
5.6 KiB
/*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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