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/*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] Fast Explicit Diffusion for Accelerated Features in Nonlinear Scale Spaces.
Pablo F. Alcantarilla, J. Nuevo and Adrien Bartoli.
In British Machine Vision Conference (BMVC), Bristol, UK, September 2013
http://www.robesafe.com/personal/pablo.alcantarilla/papers/Alcantarilla13bmvc.pdf
@author Eugene Khvedchenya <ekhvedchenya@gmail.com>
*/
#include "precomp.hpp"
#include "akaze/AKAZEFeatures.h"
namespace cv
{
AKAZE::AKAZE()
: descriptor(DESCRIPTOR_MLDB)
, descriptor_channels(3)
, descriptor_size(0)
{
}
AKAZE::AKAZE(DESCRIPTOR_TYPE _descriptor_type, int _descriptor_size, int _descriptor_channels)
: descriptor(_descriptor_type)
, descriptor_channels(_descriptor_channels)
, descriptor_size(_descriptor_size)
{
}
AKAZE::~AKAZE()
{
}
// returns the descriptor size in bytes
int AKAZE::descriptorSize() const
{
switch (descriptor)
{
case cv::AKAZE::DESCRIPTOR_KAZE:
case cv::AKAZE::DESCRIPTOR_KAZE_UPRIGHT:
return 64;
case cv::AKAZE::DESCRIPTOR_MLDB:
case cv::AKAZE::DESCRIPTOR_MLDB_UPRIGHT:
// We use the full length binary descriptor -> 486 bits
if (descriptor_size == 0)
{
int t = (6 + 36 + 120) * descriptor_channels;
return (int)ceil(t / 8.);
}
else
{
// We use the random bit selection length binary descriptor
return (int)ceil(descriptor_size / 8.);
}
default:
return -1;
}
}
// returns the descriptor type
int AKAZE::descriptorType() const
{
switch (descriptor)
{
case cv::AKAZE::DESCRIPTOR_KAZE:
case cv::AKAZE::DESCRIPTOR_KAZE_UPRIGHT:
return CV_32F;
case cv::AKAZE::DESCRIPTOR_MLDB:
case cv::AKAZE::DESCRIPTOR_MLDB_UPRIGHT:
return CV_8U;
default:
return -1;
}
}
// returns the default norm type
int AKAZE::defaultNorm() const
{
switch (descriptor)
{
case cv::AKAZE::DESCRIPTOR_KAZE:
case cv::AKAZE::DESCRIPTOR_KAZE_UPRIGHT:
return cv::NORM_L2;
case cv::AKAZE::DESCRIPTOR_MLDB:
case cv::AKAZE::DESCRIPTOR_MLDB_UPRIGHT:
return cv::NORM_HAMMING;
default:
return -1;
}
}
void AKAZE::operator()(InputArray image, InputArray mask,
std::vector<KeyPoint>& keypoints,
OutputArray descriptors,
bool useProvidedKeypoints) const
{
cv::Mat img = image.getMat();
if (img.type() != CV_8UC1)
cvtColor(image, img, COLOR_BGR2GRAY);
Mat img1_32;
img.convertTo(img1_32, CV_32F, 1.0 / 255.0, 0);
cv::Mat& desc = descriptors.getMatRef();
AKAZEOptions options;
options.descriptor = static_cast<DESCRIPTOR_TYPE>(descriptor);
options.descriptor_channels = descriptor_channels;
options.descriptor_size = descriptor_size;
options.img_width = img.cols;
options.img_height = img.rows;
AKAZEFeatures impl(options);
impl.Create_Nonlinear_Scale_Space(img1_32);
if (!useProvidedKeypoints)
{
impl.Feature_Detection(keypoints);
}
if (!mask.empty())
{
cv::KeyPointsFilter::runByPixelsMask(keypoints, mask.getMat());
}
impl.Compute_Descriptors(keypoints, desc);
CV_Assert((!desc.rows || desc.cols == descriptorSize()));
CV_Assert((!desc.rows || (desc.type() == descriptorType())));
}
void AKAZE::detectImpl(InputArray image, std::vector<KeyPoint>& keypoints, InputArray mask) const
{
cv::Mat img = image.getMat();
if (img.type() != CV_8UC1)
cvtColor(image, img, COLOR_BGR2GRAY);
Mat img1_32;
img.convertTo(img1_32, CV_32F, 1.0 / 255.0, 0);
AKAZEOptions options;
options.descriptor = static_cast<DESCRIPTOR_TYPE>(descriptor);
options.descriptor_channels = descriptor_channels;
options.descriptor_size = descriptor_size;
options.img_width = img.cols;
options.img_height = img.rows;
AKAZEFeatures impl(options);
impl.Create_Nonlinear_Scale_Space(img1_32);
impl.Feature_Detection(keypoints);
if (!mask.empty())
{
cv::KeyPointsFilter::runByPixelsMask(keypoints, mask.getMat());
}
}
void AKAZE::computeImpl(InputArray image, std::vector<KeyPoint>& keypoints, OutputArray descriptors) const
{
cv::Mat img = image.getMat();
if (img.type() != CV_8UC1)
cvtColor(image, img, COLOR_BGR2GRAY);
Mat img1_32;
img.convertTo(img1_32, CV_32F, 1.0 / 255.0, 0);
cv::Mat& desc = descriptors.getMatRef();
AKAZEOptions options;
options.descriptor = static_cast<DESCRIPTOR_TYPE>(descriptor);
options.descriptor_channels = descriptor_channels;
options.descriptor_size = descriptor_size;
options.img_width = img.cols;
options.img_height = img.rows;
AKAZEFeatures impl(options);
impl.Create_Nonlinear_Scale_Space(img1_32);
impl.Compute_Descriptors(keypoints, desc);
CV_Assert((!desc.rows || desc.cols == descriptorSize()));
CV_Assert((!desc.rows || (desc.type() == descriptorType())));
}
}