/*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) 2009-2010, 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*/ #include "precomp.hpp" #include <algorithm> #include <vector> #include <iostream> #include <iomanip> namespace cv { namespace xfeatures2d { /* * BRIEF Descriptor */ class BriefDescriptorExtractorImpl : public BriefDescriptorExtractor { public: enum { PATCH_SIZE = 48, KERNEL_SIZE = 9 }; // bytes is a length of descriptor in bytes. It can be equal 16, 32 or 64 bytes. BriefDescriptorExtractorImpl( int bytes = 32, bool use_orientation = false ); virtual void read( const FileNode& ) CV_OVERRIDE; virtual void write( FileStorage& ) const CV_OVERRIDE; virtual int descriptorSize() const CV_OVERRIDE; virtual int descriptorType() const CV_OVERRIDE; virtual int defaultNorm() const CV_OVERRIDE; virtual void compute(InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors) CV_OVERRIDE; protected: typedef void(*PixelTestFn)(InputArray, const std::vector<KeyPoint>&, OutputArray, bool use_orientation ); int bytes_; bool use_orientation_; PixelTestFn test_fn_; }; Ptr<BriefDescriptorExtractor> BriefDescriptorExtractor::create( int bytes, bool use_orientation ) { return makePtr<BriefDescriptorExtractorImpl>(bytes, use_orientation ); } inline int smoothedSum(const Mat& sum, const KeyPoint& pt, int y, int x, bool use_orientation, Matx21f R) { static const int HALF_KERNEL = BriefDescriptorExtractorImpl::KERNEL_SIZE / 2; if ( use_orientation ) { int rx = (int)(((float)x)*R(1,0) - ((float)y)*R(0,0)); int ry = (int)(((float)x)*R(0,0) + ((float)y)*R(1,0)); if (rx > 24) rx = 24; if (rx < -24) rx = -24; if (ry > 24) ry = 24; if (ry < -24) ry = -24; x = rx; y = ry; } const int img_y = (int)(pt.pt.y + 0.5) + y; const int img_x = (int)(pt.pt.x + 0.5) + x; return sum.at<int>(img_y + HALF_KERNEL + 1, img_x + HALF_KERNEL + 1) - sum.at<int>(img_y + HALF_KERNEL + 1, img_x - HALF_KERNEL) - sum.at<int>(img_y - HALF_KERNEL, img_x + HALF_KERNEL + 1) + sum.at<int>(img_y - HALF_KERNEL, img_x - HALF_KERNEL); } static void pixelTests16(InputArray _sum, const std::vector<KeyPoint>& keypoints, OutputArray _descriptors, bool use_orientation ) { Matx21f R; Mat sum = _sum.getMat(), descriptors = _descriptors.getMat(); for (size_t i = 0; i < keypoints.size(); ++i) { uchar* desc = descriptors.ptr(static_cast<int>(i)); const KeyPoint& pt = keypoints[i]; if ( use_orientation ) { float angle = pt.angle; angle *= (float)(CV_PI/180.f); R(0,0) = sin(angle); R(1,0) = cos(angle); } #include "generated_16.i" } } static void pixelTests32(InputArray _sum, const std::vector<KeyPoint>& keypoints, OutputArray _descriptors, bool use_orientation) { Matx21f R; Mat sum = _sum.getMat(), descriptors = _descriptors.getMat(); for (size_t i = 0; i < keypoints.size(); ++i) { uchar* desc = descriptors.ptr(static_cast<int>(i)); const KeyPoint& pt = keypoints[i]; if ( use_orientation ) { float angle = pt.angle; angle *= (float)(CV_PI / 180.f); R(0,0) = sin(angle); R(1,0) = cos(angle); } #include "generated_32.i" } } static void pixelTests64(InputArray _sum, const std::vector<KeyPoint>& keypoints, OutputArray _descriptors, bool use_orientation) { Matx21f R; Mat sum = _sum.getMat(), descriptors = _descriptors.getMat(); for (size_t i = 0; i < keypoints.size(); ++i) { uchar* desc = descriptors.ptr(static_cast<int>(i)); const KeyPoint& pt = keypoints[i]; if ( use_orientation ) { float angle = pt.angle; angle *= (float)(CV_PI/180.f); R(0,0) = sin(angle); R(1,0) = cos(angle); } #include "generated_64.i" } } BriefDescriptorExtractorImpl::BriefDescriptorExtractorImpl(int bytes, bool use_orientation) : bytes_(bytes), test_fn_(NULL) { use_orientation_ = use_orientation; switch (bytes) { case 16: test_fn_ = pixelTests16; break; case 32: test_fn_ = pixelTests32; break; case 64: test_fn_ = pixelTests64; break; default: CV_Error(Error::StsBadArg, "bytes must be 16, 32, or 64"); } } int BriefDescriptorExtractorImpl::descriptorSize() const { return bytes_; } int BriefDescriptorExtractorImpl::descriptorType() const { return CV_8UC1; } int BriefDescriptorExtractorImpl::defaultNorm() const { return NORM_HAMMING; } void BriefDescriptorExtractorImpl::read( const FileNode& fn) { int dSize = fn["descriptorSize"]; switch (dSize) { case 16: test_fn_ = pixelTests16; break; case 32: test_fn_ = pixelTests32; break; case 64: test_fn_ = pixelTests64; break; default: CV_Error(Error::StsBadArg, "descriptorSize must be 16, 32, or 64"); } bytes_ = dSize; } void BriefDescriptorExtractorImpl::write( FileStorage& fs) const { fs << "descriptorSize" << bytes_; } void BriefDescriptorExtractorImpl::compute(InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors) { // Construct integral image for fast smoothing (box filter) Mat sum; Mat grayImage = image.getMat(); if( image.type() != CV_8U ) cvtColor( image, grayImage, COLOR_BGR2GRAY ); ///TODO allow the user to pass in a precomputed integral image //if(image.type() == CV_32S) // sum = image; //else integral( grayImage, sum, CV_32S); //Remove keypoints very close to the border KeyPointsFilter::runByImageBorder(keypoints, image.size(), PATCH_SIZE/2 + KERNEL_SIZE/2); descriptors.create((int)keypoints.size(), bytes_, CV_8U); descriptors.setTo(Scalar::all(0)); test_fn_(sum, keypoints, descriptors, use_orientation_); } } } // namespace cv