2014-04-28 20:01:42 +08:00
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/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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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) 2008, Willow Garage Inc., all rights reserved.
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//M*/
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/*
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OpenCV wrapper of reference implementation of
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[1] Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces.
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Pablo F. Alcantarilla, J. Nuevo and Adrien Bartoli.
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In British Machine Vision Conference (BMVC), Bristol, UK, September 2013
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http://www.robesafe.com/personal/pablo.alcantarilla/papers/Alcantarilla13bmvc.pdf
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@author Eugene Khvedchenya <ekhvedchenya@gmail.com>
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*/
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2014-04-05 15:25:46 +08:00
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#include "precomp.hpp"
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2014-07-30 22:02:08 +08:00
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#include "kaze/AKAZEFeatures.h"
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#include <iostream>
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using namespace std;
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2014-04-05 15:25:46 +08:00
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namespace cv
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{
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AKAZE::AKAZE()
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: descriptor(DESCRIPTOR_MLDB)
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, descriptor_channels(3)
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, descriptor_size(0)
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2014-07-30 22:02:08 +08:00
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, threshold(0.001f)
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, octaves(4)
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, sublevels(4)
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, diffusivity(DIFF_PM_G2)
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2014-05-09 23:46:00 +08:00
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{
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}
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2014-04-05 15:25:46 +08:00
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2014-07-30 22:02:08 +08:00
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AKAZE::AKAZE(int _descriptor_type, int _descriptor_size, int _descriptor_channels,
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float _threshold, int _octaves, int _sublevels, int _diffusivity)
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: descriptor(_descriptor_type)
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, descriptor_channels(_descriptor_channels)
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, descriptor_size(_descriptor_size)
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, threshold(_threshold)
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, octaves(_octaves)
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, sublevels(_sublevels)
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, diffusivity(_diffusivity)
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2014-04-05 15:25:46 +08:00
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{
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}
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AKAZE::~AKAZE()
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{
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}
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// returns the descriptor size in bytes
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int AKAZE::descriptorSize() const
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{
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switch (descriptor)
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{
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case cv::DESCRIPTOR_KAZE:
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case cv::DESCRIPTOR_KAZE_UPRIGHT:
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return 64;
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case cv::DESCRIPTOR_MLDB:
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case cv::DESCRIPTOR_MLDB_UPRIGHT:
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// We use the full length binary descriptor -> 486 bits
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if (descriptor_size == 0)
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{
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int t = (6 + 36 + 120) * descriptor_channels;
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return (int)ceil(t / 8.);
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}
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else
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{
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// We use the random bit selection length binary descriptor
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return (int)ceil(descriptor_size / 8.);
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}
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default:
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return -1;
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}
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}
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// returns the descriptor type
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int AKAZE::descriptorType() const
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{
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switch (descriptor)
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{
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case cv::DESCRIPTOR_KAZE:
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case cv::DESCRIPTOR_KAZE_UPRIGHT:
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return CV_32F;
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2014-07-30 22:02:08 +08:00
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case cv::DESCRIPTOR_MLDB:
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case cv::DESCRIPTOR_MLDB_UPRIGHT:
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return CV_8U;
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default:
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return -1;
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2014-04-05 15:25:46 +08:00
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}
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}
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// returns the default norm type
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int AKAZE::defaultNorm() const
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{
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switch (descriptor)
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{
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2014-07-30 22:02:08 +08:00
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case cv::DESCRIPTOR_KAZE:
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case cv::DESCRIPTOR_KAZE_UPRIGHT:
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2014-05-09 23:46:00 +08:00
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return cv::NORM_L2;
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2014-07-30 22:02:08 +08:00
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case cv::DESCRIPTOR_MLDB:
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case cv::DESCRIPTOR_MLDB_UPRIGHT:
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2014-05-09 23:46:00 +08:00
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return cv::NORM_HAMMING;
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default:
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return -1;
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2014-04-05 15:25:46 +08:00
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}
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}
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void AKAZE::operator()(InputArray image, InputArray mask,
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std::vector<KeyPoint>& keypoints,
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OutputArray descriptors,
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bool useProvidedKeypoints) const
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{
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cv::Mat img = image.getMat();
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if (img.type() != CV_8UC1)
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cvtColor(image, img, COLOR_BGR2GRAY);
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Mat img1_32;
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img.convertTo(img1_32, CV_32F, 1.0 / 255.0, 0);
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cv::Mat& desc = descriptors.getMatRef();
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AKAZEOptions options;
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options.descriptor = descriptor;
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options.descriptor_channels = descriptor_channels;
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options.descriptor_size = descriptor_size;
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options.img_width = img.cols;
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options.img_height = img.rows;
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options.dthreshold = threshold;
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options.omax = octaves;
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options.nsublevels = sublevels;
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options.diffusivity = diffusivity;
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AKAZEFeatures impl(options);
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impl.Create_Nonlinear_Scale_Space(img1_32);
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if (!useProvidedKeypoints)
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{
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impl.Feature_Detection(keypoints);
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}
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if (!mask.empty())
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{
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cv::KeyPointsFilter::runByPixelsMask(keypoints, mask.getMat());
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}
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impl.Compute_Descriptors(keypoints, desc);
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2014-04-28 15:51:09 +08:00
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2014-04-28 21:23:58 +08:00
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CV_Assert((!desc.rows || desc.cols == descriptorSize()));
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2014-04-29 03:25:27 +08:00
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CV_Assert((!desc.rows || (desc.type() == descriptorType())));
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2014-04-05 15:25:46 +08:00
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}
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void AKAZE::detectImpl(InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask) const
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{
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cv::Mat img = image.getMat();
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if (img.type() != CV_8UC1)
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cvtColor(image, img, COLOR_BGR2GRAY);
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Mat img1_32;
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img.convertTo(img1_32, CV_32F, 1.0 / 255.0, 0);
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AKAZEOptions options;
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options.descriptor = descriptor;
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options.descriptor_channels = descriptor_channels;
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options.descriptor_size = descriptor_size;
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options.img_width = img.cols;
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options.img_height = img.rows;
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AKAZEFeatures impl(options);
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impl.Create_Nonlinear_Scale_Space(img1_32);
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impl.Feature_Detection(keypoints);
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if (!mask.empty())
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{
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cv::KeyPointsFilter::runByPixelsMask(keypoints, mask.getMat());
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}
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}
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void AKAZE::computeImpl(InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors) const
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{
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cv::Mat img = image.getMat();
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if (img.type() != CV_8UC1)
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cvtColor(image, img, COLOR_BGR2GRAY);
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Mat img1_32;
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img.convertTo(img1_32, CV_32F, 1.0 / 255.0, 0);
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cv::Mat& desc = descriptors.getMatRef();
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AKAZEOptions options;
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options.descriptor = descriptor;
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options.descriptor_channels = descriptor_channels;
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options.descriptor_size = descriptor_size;
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options.img_width = img.cols;
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options.img_height = img.rows;
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AKAZEFeatures impl(options);
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impl.Create_Nonlinear_Scale_Space(img1_32);
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impl.Compute_Descriptors(keypoints, desc);
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2014-04-28 21:23:58 +08:00
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CV_Assert((!desc.rows || desc.cols == descriptorSize()));
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2014-04-29 03:25:27 +08:00
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CV_Assert((!desc.rows || (desc.type() == descriptorType())));
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2014-04-05 15:25:46 +08:00
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}
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2014-07-30 22:02:08 +08:00
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}
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