mirror of https://github.com/opencv/opencv.git
Open Source Computer Vision Library
https://opencv.org/
You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
549 lines
15 KiB
549 lines
15 KiB
/*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. |
|
// |
|
// |
|
// Intel License Agreement |
|
// For Open Source Computer Vision Library |
|
// |
|
// Copyright (C) 2000, Intel Corporation, 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*/ |
|
|
|
#include "precomp.hpp" |
|
|
|
namespace cv |
|
{ |
|
|
|
/*! */ |
|
class NormHistogramCostExtractorImpl CV_FINAL : public NormHistogramCostExtractor |
|
{ |
|
public: |
|
/* Constructors */ |
|
NormHistogramCostExtractorImpl(int _flag, int _nDummies, float _defaultCost) |
|
{ |
|
flag=_flag; |
|
nDummies=_nDummies; |
|
defaultCost=_defaultCost; |
|
name_ = "HistogramCostExtractor.NOR"; |
|
} |
|
|
|
/* Destructor */ |
|
~NormHistogramCostExtractorImpl() CV_OVERRIDE |
|
{ |
|
} |
|
|
|
//! the main operator |
|
virtual void buildCostMatrix(InputArray descriptors1, InputArray descriptors2, OutputArray costMatrix) CV_OVERRIDE; |
|
|
|
//! Setters/Getters |
|
void setNDummies(int _nDummies) CV_OVERRIDE |
|
{ |
|
nDummies=_nDummies; |
|
} |
|
|
|
int getNDummies() const CV_OVERRIDE |
|
{ |
|
return nDummies; |
|
} |
|
|
|
void setDefaultCost(float _defaultCost) CV_OVERRIDE |
|
{ |
|
defaultCost=_defaultCost; |
|
} |
|
|
|
float getDefaultCost() const CV_OVERRIDE |
|
{ |
|
return defaultCost; |
|
} |
|
|
|
virtual void setNormFlag(int _flag) CV_OVERRIDE |
|
{ |
|
flag=_flag; |
|
} |
|
|
|
virtual int getNormFlag() const CV_OVERRIDE |
|
{ |
|
return flag; |
|
} |
|
|
|
//! write/read |
|
virtual void write(FileStorage& fs) const CV_OVERRIDE |
|
{ |
|
writeFormat(fs); |
|
fs << "name" << name_ |
|
<< "flag" << flag |
|
<< "dummies" << nDummies |
|
<< "default" << defaultCost; |
|
} |
|
|
|
virtual void read(const FileNode& fn) CV_OVERRIDE |
|
{ |
|
CV_Assert( (String)fn["name"] == name_ ); |
|
flag = (int)fn["flag"]; |
|
nDummies = (int)fn["dummies"]; |
|
defaultCost = (float)fn["default"]; |
|
} |
|
|
|
private: |
|
int flag; |
|
int nDummies; |
|
float defaultCost; |
|
|
|
protected: |
|
String name_; |
|
}; |
|
|
|
void NormHistogramCostExtractorImpl::buildCostMatrix(InputArray _descriptors1, InputArray _descriptors2, OutputArray _costMatrix) |
|
{ |
|
CV_INSTRUMENT_REGION(); |
|
|
|
// size of the costMatrix with dummies // |
|
Mat descriptors1=_descriptors1.getMat(); |
|
Mat descriptors2=_descriptors2.getMat(); |
|
int costrows = std::max(descriptors1.rows, descriptors2.rows)+nDummies; |
|
_costMatrix.create(costrows, costrows, CV_32F); |
|
Mat costMatrix=_costMatrix.getMat(); |
|
|
|
|
|
// Obtain copies of the descriptors // |
|
cv::Mat scd1 = descriptors1.clone(); |
|
cv::Mat scd2 = descriptors2.clone(); |
|
|
|
// row normalization // |
|
for(int i=0; i<scd1.rows; i++) |
|
{ |
|
scd1.row(i)/=(sum(scd1.row(i))[0]+FLT_EPSILON); |
|
} |
|
for(int i=0; i<scd2.rows; i++) |
|
{ |
|
scd2.row(i)/=(sum(scd2.row(i))[0]+FLT_EPSILON); |
|
} |
|
|
|
// Compute the Cost Matrix // |
|
for(int i=0; i<costrows; i++) |
|
{ |
|
for(int j=0; j<costrows; j++) |
|
{ |
|
if (i<scd1.rows && j<scd2.rows) |
|
{ |
|
Mat columnDiff = scd1.row(i)-scd2.row(j); |
|
costMatrix.at<float>(i,j)=(float)norm(columnDiff, flag); |
|
} |
|
else |
|
{ |
|
costMatrix.at<float>(i,j)=defaultCost; |
|
} |
|
} |
|
} |
|
} |
|
|
|
Ptr <HistogramCostExtractor> createNormHistogramCostExtractor(int flag, int nDummies, float defaultCost) |
|
{ |
|
return Ptr <HistogramCostExtractor>( new NormHistogramCostExtractorImpl(flag, nDummies, defaultCost) ); |
|
} |
|
|
|
/*! */ |
|
class EMDHistogramCostExtractorImpl CV_FINAL : public EMDHistogramCostExtractor |
|
{ |
|
public: |
|
/* Constructors */ |
|
EMDHistogramCostExtractorImpl(int _flag, int _nDummies, float _defaultCost) |
|
{ |
|
flag=_flag; |
|
nDummies=_nDummies; |
|
defaultCost=_defaultCost; |
|
name_ = "HistogramCostExtractor.EMD"; |
|
} |
|
|
|
/* Destructor */ |
|
~EMDHistogramCostExtractorImpl() CV_OVERRIDE |
|
{ |
|
} |
|
|
|
//! the main operator |
|
virtual void buildCostMatrix(InputArray descriptors1, InputArray descriptors2, OutputArray costMatrix) CV_OVERRIDE; |
|
|
|
//! Setters/Getters |
|
void setNDummies(int _nDummies) CV_OVERRIDE |
|
{ |
|
nDummies=_nDummies; |
|
} |
|
|
|
int getNDummies() const CV_OVERRIDE |
|
{ |
|
return nDummies; |
|
} |
|
|
|
void setDefaultCost(float _defaultCost) CV_OVERRIDE |
|
{ |
|
defaultCost=_defaultCost; |
|
} |
|
|
|
float getDefaultCost() const CV_OVERRIDE |
|
{ |
|
return defaultCost; |
|
} |
|
|
|
virtual void setNormFlag(int _flag) CV_OVERRIDE |
|
{ |
|
flag=_flag; |
|
} |
|
|
|
virtual int getNormFlag() const CV_OVERRIDE |
|
{ |
|
return flag; |
|
} |
|
|
|
//! write/read |
|
virtual void write(FileStorage& fs) const CV_OVERRIDE |
|
{ |
|
writeFormat(fs); |
|
fs << "name" << name_ |
|
<< "flag" << flag |
|
<< "dummies" << nDummies |
|
<< "default" << defaultCost; |
|
} |
|
|
|
virtual void read(const FileNode& fn) CV_OVERRIDE |
|
{ |
|
CV_Assert( (String)fn["name"] == name_ ); |
|
flag = (int)fn["flag"]; |
|
nDummies = (int)fn["dummies"]; |
|
defaultCost = (float)fn["default"]; |
|
} |
|
|
|
private: |
|
int flag; |
|
int nDummies; |
|
float defaultCost; |
|
|
|
protected: |
|
String name_; |
|
}; |
|
|
|
void EMDHistogramCostExtractorImpl::buildCostMatrix(InputArray _descriptors1, InputArray _descriptors2, OutputArray _costMatrix) |
|
{ |
|
CV_INSTRUMENT_REGION(); |
|
|
|
// size of the costMatrix with dummies // |
|
Mat descriptors1=_descriptors1.getMat(); |
|
Mat descriptors2=_descriptors2.getMat(); |
|
int costrows = std::max(descriptors1.rows, descriptors2.rows)+nDummies; |
|
_costMatrix.create(costrows, costrows, CV_32F); |
|
Mat costMatrix=_costMatrix.getMat(); |
|
|
|
// Obtain copies of the descriptors // |
|
cv::Mat scd1=descriptors1.clone(); |
|
cv::Mat scd2=descriptors2.clone(); |
|
|
|
// row normalization // |
|
for(int i=0; i<scd1.rows; i++) |
|
{ |
|
cv::Mat row = scd1.row(i); |
|
scd1.row(i)/=(sum(row)[0]+FLT_EPSILON); |
|
} |
|
for(int i=0; i<scd2.rows; i++) |
|
{ |
|
cv::Mat row = scd2.row(i); |
|
scd2.row(i)/=(sum(row)[0]+FLT_EPSILON); |
|
} |
|
|
|
// Compute the Cost Matrix // |
|
for(int i=0; i<costrows; i++) |
|
{ |
|
for(int j=0; j<costrows; j++) |
|
{ |
|
if (i<scd1.rows && j<scd2.rows) |
|
{ |
|
cv::Mat sig1(scd1.cols,2,CV_32F), sig2(scd2.cols,2,CV_32F); |
|
sig1.col(0)=scd1.row(i).t(); |
|
sig2.col(0)=scd2.row(j).t(); |
|
for (int k=0; k<sig1.rows; k++) |
|
{ |
|
sig1.at<float>(k,1)=float(k); |
|
} |
|
for (int k=0; k<sig2.rows; k++) |
|
{ |
|
sig2.at<float>(k,1)=float(k); |
|
} |
|
|
|
costMatrix.at<float>(i,j) = cv::EMD(sig1, sig2, flag); |
|
} |
|
else |
|
{ |
|
costMatrix.at<float>(i,j) = defaultCost; |
|
} |
|
} |
|
} |
|
} |
|
|
|
Ptr <HistogramCostExtractor> createEMDHistogramCostExtractor(int flag, int nDummies, float defaultCost) |
|
{ |
|
return Ptr <HistogramCostExtractor>( new EMDHistogramCostExtractorImpl(flag, nDummies, defaultCost) ); |
|
} |
|
|
|
/*! */ |
|
class ChiHistogramCostExtractorImpl CV_FINAL : public ChiHistogramCostExtractor |
|
{ |
|
public: |
|
/* Constructors */ |
|
ChiHistogramCostExtractorImpl(int _nDummies, float _defaultCost) |
|
{ |
|
name_ = "HistogramCostExtractor.CHI"; |
|
nDummies=_nDummies; |
|
defaultCost=_defaultCost; |
|
} |
|
|
|
/* Destructor */ |
|
~ChiHistogramCostExtractorImpl() CV_OVERRIDE |
|
{ |
|
} |
|
|
|
//! the main operator |
|
virtual void buildCostMatrix(InputArray descriptors1, InputArray descriptors2, OutputArray costMatrix) CV_OVERRIDE; |
|
|
|
//! setters / getters |
|
void setNDummies(int _nDummies) CV_OVERRIDE |
|
{ |
|
nDummies=_nDummies; |
|
} |
|
|
|
int getNDummies() const CV_OVERRIDE |
|
{ |
|
return nDummies; |
|
} |
|
|
|
void setDefaultCost(float _defaultCost) CV_OVERRIDE |
|
{ |
|
defaultCost=_defaultCost; |
|
} |
|
|
|
float getDefaultCost() const CV_OVERRIDE |
|
{ |
|
return defaultCost; |
|
} |
|
|
|
//! write/read |
|
virtual void write(FileStorage& fs) const CV_OVERRIDE |
|
{ |
|
writeFormat(fs); |
|
fs << "name" << name_ |
|
<< "dummies" << nDummies |
|
<< "default" << defaultCost; |
|
} |
|
|
|
virtual void read(const FileNode& fn) CV_OVERRIDE |
|
{ |
|
CV_Assert( (String)fn["name"] == name_ ); |
|
nDummies = (int)fn["dummies"]; |
|
defaultCost = (float)fn["default"]; |
|
} |
|
|
|
protected: |
|
String name_; |
|
int nDummies; |
|
float defaultCost; |
|
}; |
|
|
|
void ChiHistogramCostExtractorImpl::buildCostMatrix(InputArray _descriptors1, InputArray _descriptors2, OutputArray _costMatrix) |
|
{ |
|
CV_INSTRUMENT_REGION(); |
|
|
|
// size of the costMatrix with dummies // |
|
Mat descriptors1=_descriptors1.getMat(); |
|
Mat descriptors2=_descriptors2.getMat(); |
|
int costrows = std::max(descriptors1.rows, descriptors2.rows)+nDummies; |
|
_costMatrix.create(costrows, costrows, CV_32FC1); |
|
Mat costMatrix=_costMatrix.getMat(); |
|
|
|
// Obtain copies of the descriptors // |
|
cv::Mat scd1=descriptors1.clone(); |
|
cv::Mat scd2=descriptors2.clone(); |
|
|
|
// row normalization // |
|
for(int i=0; i<scd1.rows; i++) |
|
{ |
|
cv::Mat row = scd1.row(i); |
|
scd1.row(i)/=(sum(row)[0]+FLT_EPSILON); |
|
} |
|
for(int i=0; i<scd2.rows; i++) |
|
{ |
|
cv::Mat row = scd2.row(i); |
|
scd2.row(i)/=(sum(row)[0]+FLT_EPSILON); |
|
} |
|
|
|
// Compute the Cost Matrix // |
|
for(int i=0; i<costrows; i++) |
|
{ |
|
for(int j=0; j<costrows; j++) |
|
{ |
|
if (i<scd1.rows && j<scd2.rows) |
|
{ |
|
float csum = 0; |
|
for(int k=0; k<scd2.cols; k++) |
|
{ |
|
float resta=scd1.at<float>(i,k)-scd2.at<float>(j,k); |
|
float suma=scd1.at<float>(i,k)+scd2.at<float>(j,k); |
|
csum += resta*resta/(FLT_EPSILON+suma); |
|
} |
|
costMatrix.at<float>(i,j)=csum/2; |
|
} |
|
else |
|
{ |
|
costMatrix.at<float>(i,j)=defaultCost; |
|
} |
|
} |
|
} |
|
} |
|
|
|
Ptr <HistogramCostExtractor> createChiHistogramCostExtractor(int nDummies, float defaultCost) |
|
{ |
|
return Ptr <HistogramCostExtractor>( new ChiHistogramCostExtractorImpl(nDummies, defaultCost) ); |
|
} |
|
|
|
/*! */ |
|
class EMDL1HistogramCostExtractorImpl CV_FINAL : public EMDL1HistogramCostExtractor |
|
{ |
|
public: |
|
/* Constructors */ |
|
EMDL1HistogramCostExtractorImpl(int _nDummies, float _defaultCost) |
|
{ |
|
name_ = "HistogramCostExtractor.CHI"; |
|
nDummies=_nDummies; |
|
defaultCost=_defaultCost; |
|
} |
|
|
|
/* Destructor */ |
|
~EMDL1HistogramCostExtractorImpl() CV_OVERRIDE |
|
{ |
|
} |
|
|
|
//! the main operator |
|
virtual void buildCostMatrix(InputArray descriptors1, InputArray descriptors2, OutputArray costMatrix) CV_OVERRIDE; |
|
|
|
//! setters / getters |
|
void setNDummies(int _nDummies) CV_OVERRIDE |
|
{ |
|
nDummies=_nDummies; |
|
} |
|
|
|
int getNDummies() const CV_OVERRIDE |
|
{ |
|
return nDummies; |
|
} |
|
|
|
void setDefaultCost(float _defaultCost) CV_OVERRIDE |
|
{ |
|
defaultCost=_defaultCost; |
|
} |
|
|
|
float getDefaultCost() const CV_OVERRIDE |
|
{ |
|
return defaultCost; |
|
} |
|
|
|
//! write/read |
|
virtual void write(FileStorage& fs) const CV_OVERRIDE |
|
{ |
|
writeFormat(fs); |
|
fs << "name" << name_ |
|
<< "dummies" << nDummies |
|
<< "default" << defaultCost; |
|
} |
|
|
|
virtual void read(const FileNode& fn) CV_OVERRIDE |
|
{ |
|
CV_Assert( (String)fn["name"] == name_ ); |
|
nDummies = (int)fn["dummies"]; |
|
defaultCost = (float)fn["default"]; |
|
} |
|
|
|
protected: |
|
String name_; |
|
int nDummies; |
|
float defaultCost; |
|
}; |
|
|
|
void EMDL1HistogramCostExtractorImpl::buildCostMatrix(InputArray _descriptors1, InputArray _descriptors2, OutputArray _costMatrix) |
|
{ |
|
CV_INSTRUMENT_REGION(); |
|
|
|
// size of the costMatrix with dummies // |
|
Mat descriptors1=_descriptors1.getMat(); |
|
Mat descriptors2=_descriptors2.getMat(); |
|
int costrows = std::max(descriptors1.rows, descriptors2.rows)+nDummies; |
|
_costMatrix.create(costrows, costrows, CV_32F); |
|
Mat costMatrix=_costMatrix.getMat(); |
|
|
|
// Obtain copies of the descriptors // |
|
cv::Mat scd1=descriptors1.clone(); |
|
cv::Mat scd2=descriptors2.clone(); |
|
|
|
// row normalization // |
|
for(int i=0; i<scd1.rows; i++) |
|
{ |
|
cv::Mat row = scd1.row(i); |
|
scd1.row(i)/=(sum(row)[0]+FLT_EPSILON); |
|
} |
|
for(int i=0; i<scd2.rows; i++) |
|
{ |
|
cv::Mat row = scd2.row(i); |
|
scd2.row(i)/=(sum(row)[0]+FLT_EPSILON); |
|
} |
|
|
|
// Compute the Cost Matrix // |
|
for(int i=0; i<costrows; i++) |
|
{ |
|
for(int j=0; j<costrows; j++) |
|
{ |
|
if (i<scd1.rows && j<scd2.rows) |
|
{ |
|
cv::Mat sig1(scd1.cols,1,CV_32F), sig2(scd2.cols,1,CV_32F); |
|
sig1.col(0)=scd1.row(i).t(); |
|
sig2.col(0)=scd2.row(j).t(); |
|
costMatrix.at<float>(i,j) = cv::EMDL1(sig1, sig2); |
|
} |
|
else |
|
{ |
|
costMatrix.at<float>(i,j) = defaultCost; |
|
} |
|
} |
|
} |
|
} |
|
|
|
Ptr <HistogramCostExtractor> createEMDL1HistogramCostExtractor(int nDummies, float defaultCost) |
|
{ |
|
return Ptr <HistogramCostExtractor>( new EMDL1HistogramCostExtractorImpl(nDummies, defaultCost) ); |
|
} |
|
|
|
} // cv
|
|
|