/*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) 2008, 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 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*/ /* OpenCV wrapper of reference implementation of [1] KAZE Features. Pablo F. Alcantarilla, Adrien Bartoli and Andrew J. Davison. In European Conference on Computer Vision (ECCV), Fiorenze, Italy, October 2012 http://www.robesafe.com/personal/pablo.alcantarilla/papers/Alcantarilla12eccv.pdf @author Eugene Khvedchenya */ #include "precomp.hpp" #include "kaze/KAZEFeatures.h" namespace cv { class KAZE_Impl : public KAZE { public: KAZE_Impl(bool _extended, bool _upright, float _threshold, int _octaves, int _sublevels, int _diffusivity) : extended(_extended) , upright(_upright) , threshold(_threshold) , octaves(_octaves) , sublevels(_sublevels) , diffusivity(_diffusivity) { } virtual ~KAZE_Impl() {} void setExtended(bool extended_) { extended = extended_; } bool getExtended() const { return extended; } void setUpright(bool upright_) { upright = upright_; } bool getUpright() const { return upright; } void setThreshold(double threshold_) { threshold = (float)threshold_; } double getThreshold() const { return threshold; } void setNOctaves(int octaves_) { octaves = octaves_; } int getNOctaves() const { return octaves; } void setNOctaveLayers(int octaveLayers_) { sublevels = octaveLayers_; } int getNOctaveLayers() const { return sublevels; } void setDiffusivity(int diff_) { diffusivity = diff_; } int getDiffusivity() const { return diffusivity; } // returns the descriptor size in bytes int descriptorSize() const { return extended ? 128 : 64; } // returns the descriptor type int descriptorType() const { return CV_32F; } // returns the default norm type int defaultNorm() const { return NORM_L2; } void detectAndCompute(InputArray image, InputArray mask, std::vector& keypoints, OutputArray descriptors, bool useProvidedKeypoints) { cv::Mat img = image.getMat(); if (img.channels() > 1) cvtColor(image, img, COLOR_BGR2GRAY); Mat img1_32; if ( img.depth() == CV_32F ) img1_32 = img; else if ( img.depth() == CV_8U ) img.convertTo(img1_32, CV_32F, 1.0 / 255.0, 0); else if ( img.depth() == CV_16U ) img.convertTo(img1_32, CV_32F, 1.0 / 65535.0, 0); CV_Assert( ! img1_32.empty() ); KAZEOptions options; options.img_width = img.cols; options.img_height = img.rows; options.extended = extended; options.upright = upright; options.dthreshold = threshold; options.omax = octaves; options.nsublevels = sublevels; options.diffusivity = diffusivity; KAZEFeatures impl(options); impl.Create_Nonlinear_Scale_Space(img1_32); if (!useProvidedKeypoints) { impl.Feature_Detection(keypoints); } if (!mask.empty()) { cv::KeyPointsFilter::runByPixelsMask(keypoints, mask.getMat()); } if( descriptors.needed() ) { Mat& desc = descriptors.getMatRef(); impl.Feature_Description(keypoints, desc); CV_Assert((!desc.rows || desc.cols == descriptorSize())); CV_Assert((!desc.rows || (desc.type() == descriptorType()))); } } void write(FileStorage& fs) const { fs << "extended" << (int)extended; fs << "upright" << (int)upright; fs << "threshold" << threshold; fs << "octaves" << octaves; fs << "sublevels" << sublevels; fs << "diffusivity" << diffusivity; } void read(const FileNode& fn) { extended = (int)fn["extended"] != 0; upright = (int)fn["upright"] != 0; threshold = (float)fn["threshold"]; octaves = (int)fn["octaves"]; sublevels = (int)fn["sublevels"]; diffusivity = (int)fn["diffusivity"]; } bool extended; bool upright; float threshold; int octaves; int sublevels; int diffusivity; }; Ptr KAZE::create(bool extended, bool upright, float threshold, int octaves, int sublevels, int diffusivity) { return makePtr(extended, upright, threshold, octaves, sublevels, diffusivity); } }