[53eab2]: src / hugin_cpfind / cpfind / PanoDetector.cpp Maximize Restore History

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PanoDetector.cpp    995 lines (917 with data), 32.3 kB

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// -*- c-basic-offset: 4 ; tab-width: 4 -*-
/*
* Copyright (C) 2007-2008 Anael Orlinski
*
* This file is part of Panomatic.
*
* Panomatic is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* Panomatic is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with Panomatic; if not, write to the Free Software
* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
*/
#include "PanoDetector.h"
#include <iostream>
#include <fstream>
#include <sstream>
#include <boost/foreach.hpp>
#include <time.h>
#include "zthread/Runnable.h"
#include "zthread/PoolExecutor.h"
#include "Utils.h"
#include "Tracer.h"
#include <algorithms/nona/ComputeImageROI.h>
#include <nona/RemappedPanoImage.h>
#include <nona/ImageRemapper.h>
//for multi row strategy
#include <panodata/StandardImageVariableGroups.h>
#include <PT/Panorama.h>
#include <PT/ImageGraph.h>
#include <algorithms/optimizer/PTOptimizer.h>
#include <algorithms/basic/CalculateOverlap.h>
#include "ImageImport.h"
#ifdef _WINDOWS
#include <windows.h>
#include <direct.h>
#else
#include <unistd.h>
#endif
#ifdef __APPLE__
#include <hugin_config.h>
#include <mach-o/dyld.h> /* _NSGetExecutablePath */
#include <limits.h> /* PATH_MAX */
#include <libgen.h> /* dirname */
#endif
#ifndef srandom
#define srandom srand
#endif
using namespace std;
using namespace ZThread;
using namespace HuginBase;
using namespace AppBase;
using namespace HuginBase::Nona;
using namespace hugin_utils;
#define TRACE_IMG(X) {if (_panoDetector.getVerbose() == 1) {TRACE_INFO("i" << _imgData._number << " : " << X << endl);}}
#define TRACE_PAIR(X) {if (_panoDetector.getVerbose() == 1){ TRACE_INFO("i" << _matchData._i1->_number << " <> " \
"i" << _matchData._i2->_number << " : " << X << endl);}}
std::string includeTrailingPathSep(std::string path)
{
std::string pathWithSep(path);
#ifdef _WINDOWS
if(pathWithSep[pathWithSep.length()-1]!='\\' || pathWithSep[pathWithSep.length()-1]!='/')
pathWithSep.append("\\");
#else
if(pathWithSep[pathWithSep.length()-1]!='/')
pathWithSep.append("/");
#endif
return pathWithSep;
};
std::string getKeyfilenameFor(std::string keyfilesPath, std::string filename)
{
std::string newfilename;
if(keyfilesPath.empty())
{
//if no path for keyfiles is given we are saving into the same directory as image file
newfilename=stripExtension(filename);
}
else
{
newfilename=includeTrailingPathSep(keyfilesPath);
newfilename.append(stripPath(stripExtension(filename)));
};
newfilename.append(".key");
return newfilename;
};
PanoDetector::PanoDetector() :
_writeAllKeyPoints(false), _verbose(1),
_sieve1Width(10), _sieve1Height(10), _sieve1Size(100),
_kdTreeSearchSteps(200), _kdTreeSecondDistance(0.25), _ransacIters(1000), _ransacDistanceThres(50),
_sieve2Width(5), _sieve2Height(5),_sieve2Size(1), _test(false), _cores(utils::getCPUCount()),
_minimumMatches(6), _linearMatch(false), _linearMatchLen(1), _downscale(true), _cache(false), _cleanup(false),
_keypath(""), _outputFile("default.pto"), _celeste(false), _celesteThreshold(0.5), _celesteRadius(20), _multirow(false)
{
_panoramaInfo = new Panorama();
}
bool PanoDetector::checkData()
{
// test linear match data
if (_linearMatchLen < 1)
{
std::cout << "Linear match length must be at least 1." << std::endl;
return false;
}
if(_linearMatch && _multirow)
{
std::cout << "Linear match and multi row matching strategy does not work together." << std::endl;
return false;
};
// check the test mode
if (_test)
{
if (_filesData.size() != 2)
{
std::cout << "In test mode you must provide exactly 2 images." << std::endl;
return false;
}
}
return true;
}
void PanoDetector::printDetails()
{
cout << "Input file : " << _inputFile << endl;
if (_keyPointsIdx.size() != 0)
{
cout << "Output file(s) : keyfile(s) for images";
for (unsigned int i = 0; i < _keyPointsIdx.size(); ++i)
cout << " " << _keyPointsIdx[i] << endl;
}
else
{
cout << "Output file : " << _outputFile << endl;
}
cout << "Number of CPU : " << _cores << endl << endl;
cout << "Input image options" << endl;
cout << " Downscale to half-size : " << (_downscale?"yes":"no") << endl;
if (_gradDescriptor) {
cout << "Gradient based description" << endl;
}
if(_celeste)
{
cout << "Celeste options" << endl;
cout << " Threshold : " << _celesteThreshold << endl;
cout << " Radius : " << _celesteRadius << endl;
}
cout << "Sieve 1 Options" << endl;
cout << " Width : " << _sieve1Width << endl;
cout << " Height : " << _sieve1Height << endl;
cout << " Size : " << _sieve1Size << endl;
cout << " ==> Maximum keypoints per image : " << _sieve1Size * _sieve1Height * _sieve1Width << endl;
cout << "KDTree Options" << endl;
cout << " Search steps : " << _kdTreeSearchSteps << endl;
cout << " Second match distance : " << _kdTreeSecondDistance << endl;
cout << "Matching Options" << endl;
if(_linearMatch)
{
cout << " Mode : Linear match with length of " << _linearMatch << " image" << endl;
}
else
{
if(_multirow)
{
cout << " Mode : Multi row" << endl;
}
else
{
cout << " Mode : All pairs" << endl;
};
};
cout << " Distance threshold : " << _ransacDistanceThres << endl;
cout << "RANSAC Options" << endl;
cout << " Mode : ";
switch (_ransacMode) {
case RANSACOptimizer::AUTO:
cout << "auto" << endl;
break;
case RANSACOptimizer::HOMOGRAPHY:
cout << "homography" << endl;
break;
case RANSACOptimizer::RPY:
cout << "roll, pitch, yaw" << endl;
break;
case RANSACOptimizer::RPYV:
cout << "roll, pitch, yaw, fov" << endl;
break;
case RANSACOptimizer::RPYVB:
cout << "roll, pitch, yaw, fov, distortion" << endl;
break;
}
cout << " Iterations : " << _ransacIters << endl;
cout << " Distance threshold : " << _ransacDistanceThres << endl;
cout << "Sieve 2 Options" << endl;
cout << " Width : " << _sieve2Width << endl;
cout << " Height : " << _sieve2Height << endl;
cout << " Size : " << _sieve2Size << endl;
cout << " ==> Maximum matches per image pair : " << _sieve2Size * _sieve2Height * _sieve2Width << endl;
}
void PanoDetector::printFilenames()
{
cout << endl << "Project contains the following images:" << endl;
for(unsigned int i=0;i<_panoramaInfo->getNrOfImages();i++)
{
std::string name(_panoramaInfo->getImage(i).getFilename());
if(name.compare(0,_prefix.length(),_prefix)==0)
name=name.substr(_prefix.length(),name.length()-_prefix.length());
cout << "Image " << i << endl << " Imagefile: " << name << endl;
bool writeKeyfileForImage=false;
if(_keyPointsIdx.size()>0)
{
for(unsigned j=0;j<_keyPointsIdx.size() && !writeKeyfileForImage;j++)
{
writeKeyfileForImage=_keyPointsIdx[j]==i;
};
};
if(_cache || _filesData[i]._hasakeyfile || writeKeyfileForImage)
{
name=_filesData[i]._keyfilename;
if(name.compare(0,_prefix.length(),_prefix)==0)
name=name.substr(_prefix.length(),name.length()-_prefix.length());
cout << " Keyfile : " << name << (_filesData[i]._hasakeyfile?" (will be used)":"") << endl;
};
cout << " Remapped : " << (_filesData[i]._needsremap?"yes":"no") << endl;
};
};
// definition of a runnable class for image data
class ImgDataRunnable : public Runnable
{
public:
ImgDataRunnable(PanoDetector::ImgData& iImageData, const PanoDetector& iPanoDetector) :
_imgData(iImageData), _panoDetector(iPanoDetector) {};
void run()
{
TRACE_IMG("Analyzing image...");
if (!PanoDetector::AnalyzeImage(_imgData, _panoDetector)) return;
PanoDetector::FindKeyPointsInImage(_imgData, _panoDetector);
PanoDetector::FilterKeyPointsInImage(_imgData, _panoDetector);
PanoDetector::MakeKeyPointDescriptorsInImage(_imgData, _panoDetector);
PanoDetector::RemapBackKeypoints(_imgData, _panoDetector);
PanoDetector::BuildKDTreesInImage(_imgData, _panoDetector);
PanoDetector::FreeMemoryInImage(_imgData, _panoDetector);
}
private:
const PanoDetector& _panoDetector;
PanoDetector::ImgData& _imgData;
};
// definition of a runnable class for writeKeyPoints
class WriteKeyPointsRunnable : public Runnable
{
public:
WriteKeyPointsRunnable(PanoDetector::ImgData& iImageData, const PanoDetector& iPanoDetector) :
_imgData(iImageData), _panoDetector(iPanoDetector) {};
void run()
{
TRACE_IMG("Analyzing image...");
if (!PanoDetector::AnalyzeImage(_imgData, _panoDetector)) return;
PanoDetector::FindKeyPointsInImage(_imgData, _panoDetector);
PanoDetector::FilterKeyPointsInImage(_imgData, _panoDetector);
PanoDetector::MakeKeyPointDescriptorsInImage(_imgData, _panoDetector);
PanoDetector::RemapBackKeypoints(_imgData, _panoDetector);
PanoDetector::FreeMemoryInImage(_imgData, _panoDetector);
}
private:
const PanoDetector& _panoDetector;
PanoDetector::ImgData& _imgData;
};
// definition of a runnable class for keypoints data
class LoadKeypointsDataRunnable : public Runnable
{
public:
LoadKeypointsDataRunnable(PanoDetector::ImgData& iImageData, const PanoDetector& iPanoDetector) :
_imgData(iImageData), _panoDetector(iPanoDetector) {};
void run()
{
TRACE_IMG("Loading keypoints...");
PanoDetector::LoadKeypoints(_imgData, _panoDetector);
PanoDetector::BuildKDTreesInImage(_imgData, _panoDetector);
}
private:
const PanoDetector& _panoDetector;
PanoDetector::ImgData& _imgData;
};
// definition of a runnable class for MatchData
class MatchDataRunnable : public Runnable
{
public:
MatchDataRunnable(PanoDetector::MatchData& iMatchData, const PanoDetector& iPanoDetector) :
_matchData(iMatchData), _panoDetector(iPanoDetector) {};
void run()
{
//TRACE_PAIR("Matching...");
PanoDetector::FindMatchesInPair(_matchData, _panoDetector);
PanoDetector::RansacMatchesInPair(_matchData, _panoDetector);
PanoDetector::FilterMatchesInPair(_matchData, _panoDetector);
TRACE_PAIR("Found " << _matchData._matches.size() << " matches");
}
private:
const PanoDetector& _panoDetector;
PanoDetector::MatchData& _matchData;
};
bool PanoDetector::LoadSVMModel()
{
string model_file = ("celeste.model");
ifstream test(model_file.c_str());
if (!test.good())
{
#if _WINDOWS
char buffer[MAX_PATH];//always use MAX_PATH for filepaths
GetModuleFileNameA(NULL,buffer,sizeof(buffer));
string working_path=(buffer);
string install_path_model="";
//remove filename
std::string::size_type pos=working_path.rfind("\\");
if(pos!=std::string::npos)
{
working_path.erase(pos);
//remove last dir: should be bin
pos=working_path.rfind("\\");
if(pos!=std::string::npos)
{
working_path.erase(pos);
//append path delimiter and path
working_path.append("\\share\\hugin\\data\\");
install_path_model=working_path;
}
}
#elif defined MAC_SELF_CONTAINED_BUNDLE
//string install_path_model = ("./xrc/");
char path[PATH_MAX + 1];
uint32_t size = sizeof(path);
string install_path_model("");
if (_NSGetExecutablePath(path, &size) == 0)
{
//install_path_model=path;
install_path_model=dirname(path);
install_path_model.append("/xrc/");
cout << "Detected path " << install_path_model << endl << endl;
}
#else
string install_path_model = (INSTALL_DATA_DIR);
#endif
install_path_model.append(model_file);
ifstream test2(install_path_model.c_str());
if (!test2.good())
{
cout << endl << "Couldn't open SVM model file " << model_file << endl;
cout << "Also tried " << install_path_model << endl << endl;
return false;
};
model_file = install_path_model;
}
if(!celeste::loadSVMmodel(svmModel,model_file))
{
svmModel=NULL;
return false;
};
return true;
};
void PanoDetector::run()
{
// init the random time generator
srandom((unsigned int)time(NULL));
PoolExecutor aExecutor(_cores);
// Load the input project file
if(!loadProject())
{
return;
};
if(_writeAllKeyPoints)
{
for(unsigned int i=0;i<_panoramaInfo->getNrOfImages();i++)
{
_keyPointsIdx.push_back(i);
};
};
if(_cleanup)
{
CleanupKeyfiles();
return;
};
svmModel=NULL;
if(_celeste)
{
TRACE_INFO("\nLoading Celeste model file...\n");
if(!LoadSVMModel())
{
setCeleste(false);
};
};
//print some more information about the images
if (_verbose > 0) {
printFilenames();
}
// 2. run analysis of images or keypoints
try
{
if (_keyPointsIdx.size() != 0)
{
if (_verbose > 0)
TRACE_INFO(endl<< "--- Analyze Images ---" << endl);
for (unsigned int i = 0; i < _keyPointsIdx.size(); ++i)
{
aExecutor.execute(new WriteKeyPointsRunnable(_filesData[_keyPointsIdx[i]], *this));
};
}
else
{
TRACE_INFO(endl<< "--- Analyze Images ---" << endl);
for (ImgDataIt_t aB = _filesData.begin(); aB != _filesData.end(); ++aB)
{
if (aB->second._hasakeyfile)
{
aExecutor.execute(new LoadKeypointsDataRunnable(aB->second, *this));
}
else
{
aExecutor.execute(new ImgDataRunnable(aB->second, *this));
}
}
}
aExecutor.wait();
}
catch(Synchronization_Exception& e)
{
TRACE_ERROR(e.what() << endl);
if(svmModel!=NULL)
{
celeste::destroySVMmodel(svmModel);
};
return;
}
if(svmModel!=NULL)
{
celeste::destroySVMmodel(svmModel);
};
// check if the load of images succeed.
if (!checkLoadSuccess())
{
TRACE_INFO("One or more images failed to load. Exiting.");
return;
}
if(_cache)
{
TRACE_INFO(endl << "--- Cache keyfiles to disc ---" << endl);
for (ImgDataIt_t aB = _filesData.begin(); aB != _filesData.end(); ++aB)
{
if (!aB->second._hasakeyfile)
{
TRACE_INFO("i" << aB->second._number << " : Caching keypoints..." << endl);
writeKeyfile(aB->second);
};
};
};
// Detect matches if writeKeyPoints wasn't set
if(_keyPointsIdx.size() == 0)
{
if(_multirow)
{
if(!matchMultiRow(aExecutor))
{
return;
};
}
else
{
if(!match(aExecutor))
{
return;
};
};
}
// 5. write output
if (_keyPointsIdx.size() != 0)
{
//Write all keyfiles
TRACE_INFO(endl<< "--- Write Keyfiles output ---" << endl << endl);
for (unsigned int i = 0; i < _keyPointsIdx.size(); ++i)
{
writeKeyfile(_filesData[_keyPointsIdx[i]]);
};
}
else
{
/// Write output project
TRACE_INFO(endl<< "--- Write Project output ---" << endl);
writeOutput();
TRACE_INFO("Written output to " << _outputFile << endl << endl);
};
}
bool PanoDetector::match(PoolExecutor& aExecutor)
{
// 3. prepare matches
prepareMatches();
// 4. find matches
TRACE_INFO(endl<< "--- Find matches ---" << endl);
try
{
BOOST_FOREACH(MatchData& aMD, _matchesData)
aExecutor.execute(new MatchDataRunnable(aMD, *this));
aExecutor.wait();
}
catch(Synchronization_Exception& e)
{
TRACE_ERROR(e.what() << endl);
return false;
}
// Add detected matches to _panoramaInfo
BOOST_FOREACH(MatchData& aM, _matchesData)
BOOST_FOREACH(lfeat::PointMatchPtr& aPM, aM._matches)
_panoramaInfo->addCtrlPoint(ControlPoint(aM._i1->_number, aPM->_img1_x, aPM->_img1_y,
aM._i2->_number, aPM->_img2_x, aPM->_img2_y));
return true;
};
bool PanoDetector::loadProject()
{
ifstream ptoFile(_inputFile.c_str());
if (ptoFile.bad()) {
cerr << "ERROR: could not open file: '" << _inputFile << "'!" << endl;
return false;
}
_prefix=hugin_utils::getPathPrefix(_inputFile);
if(_prefix.empty())
{
// Get the current working directory:
char* buffer;
#ifdef _WINDOWS
#define getcwd _getcwd
#endif
if((buffer=getcwd(NULL,0))!=NULL)
{
_prefix.append(buffer);
free(buffer);
_prefix=includeTrailingPathSep(_prefix);
}
};
_panoramaInfo->setFilePrefix(_prefix);
AppBase::DocumentData::ReadWriteError err = _panoramaInfo->readData(ptoFile);
if (err != AppBase::DocumentData::SUCCESSFUL) {
cerr << "ERROR: couldn't parse panos tool script: '" << _inputFile << "'!" << endl;
return false;
}
// Create a copy of panoramaInfo that will be used to define
// image options
_panoramaInfoCopy=_panoramaInfo->duplicate();
// Add images found in the project file to _filesData
unsigned int nImg = _panoramaInfo->getNrOfImages();
unsigned int imgWithKeyfile=0;
for (unsigned int imgNr = 0; imgNr < nImg; ++imgNr)
{
// insert the image in the map
_filesData.insert(make_pair(imgNr, ImgData()));
// get the data
ImgData& aImgData = _filesData[imgNr];
// get a copy of image info
SrcPanoImage img = _panoramaInfoCopy.getSrcImage(imgNr);
// set the name
aImgData._name = img.getFilename();
// modify image position in the copy
img.setYaw(0);
img.setRoll(0);
img.setPitch(0);
img.setX(0);
img.setY(0);
img.setZ(0);
img.setActive(true);
img.setResponseType(SrcPanoImage::RESPONSE_LINEAR);
img.setExposureValue(0);
_panoramaInfoCopy.setImage(imgNr,img);
// Number pointing to image info in _panoramaInfo
aImgData._number = imgNr;
aImgData._needsremap=(img.getHFOV()>=65 && img.getProjection() != SrcPanoImage::FISHEYE_STEREOGRAPHIC);
// set image detection size
if(aImgData._needsremap)
{
_filesData[imgNr]._detectWidth = max(img.getSize().width(),img.getSize().height());
_filesData[imgNr]._detectHeight = max(img.getSize().width(),img.getSize().height());
}
else
{
_filesData[imgNr]._detectWidth = img.getSize().width();
_filesData[imgNr]._detectHeight = img.getSize().height();
};
if (_downscale)
{
_filesData[imgNr]._detectWidth >>= 1;
_filesData[imgNr]._detectHeight >>= 1;
}
// set image remapping options
if(aImgData._needsremap)
{
aImgData._projOpts.setProjection(PanoramaOptions::STEREOGRAPHIC);
aImgData._projOpts.setHFOV(250);
aImgData._projOpts.setVFOV(250);
aImgData._projOpts.setWidth(250);
aImgData._projOpts.setHeight(250);
// determine size of output image.
// The old code did not work with images with images with a FOV
// approaching 180 degrees
vigra::Rect2D roi=estimateOutputROI(_panoramaInfoCopy,aImgData._projOpts,imgNr);
double scalefactor = max((double)_filesData[imgNr]._detectWidth / roi.width(),
(double)_filesData[imgNr]._detectHeight / roi.height() );
// resize output canvas
vigra::Size2D canvasSize((int)aImgData._projOpts.getWidth() * scalefactor,
(int)aImgData._projOpts.getHeight() * scalefactor);
aImgData._projOpts.setWidth(canvasSize.width(), false);
aImgData._projOpts.setHeight(canvasSize.height());
// set roi to cover the remapped input image
roi = roi * scalefactor;
_filesData[imgNr]._detectWidth = roi.width();
_filesData[imgNr]._detectHeight = roi.height();
aImgData._projOpts.setROI(roi);
}
// Specify if the image has an associated keypoint file
aImgData._keyfilename = getKeyfilenameFor(_keypath,aImgData._name);
ifstream keyfile(aImgData._keyfilename.c_str());
aImgData._hasakeyfile = keyfile.good();
if(aImgData._hasakeyfile)
{
imgWithKeyfile++;
};
}
//update masks, convert positive masks into negative masks
//because positive masks works only if the images are on the final positions
_panoramaInfoCopy.updateMasks(true);
//if all images has keyfile, we don't need to load celeste model file
if(nImg==imgWithKeyfile)
{
_celeste=false;
};
return true;
}
bool PanoDetector::checkLoadSuccess()
{
if(_keyPointsIdx.size()!=0)
{
for (unsigned int i = 0; i < _keyPointsIdx.size(); ++i)
{
if(_filesData[_keyPointsIdx[i]]._loadFail)
{
return false;
};
};
}
else
{
for (unsigned int aFileN = 0; aFileN < _filesData.size(); ++aFileN)
{
if(_filesData[aFileN]._loadFail)
{
return false;
};
};
};
return true;
}
void PanoDetector::CleanupKeyfiles()
{
for (ImgDataIt_t aB = _filesData.begin(); aB != _filesData.end(); ++aB)
{
if (aB->second._hasakeyfile)
{
remove(aB->second._keyfilename.c_str());
};
};
};
void PanoDetector::prepareMatches()
{
int aLen = _filesData.size();
if (_linearMatch)
aLen = _linearMatchLen;
if (aLen >= _filesData.size())
aLen = _filesData.size() - 1;
for (unsigned int i1 = 0; i1 < _filesData.size(); ++i1)
{
int aEnd = i1 + 1 + aLen;
if (_filesData.size() < aEnd)
aEnd = _filesData.size();
for (unsigned int i2 = (i1+1); i2 < aEnd; ++i2)
{
// create a new entry in the matches map
_matchesData.push_back(MatchData());
MatchData& aM = _matchesData.back();
aM._i1 = &(_filesData[i1]);
aM._i2 = &(_filesData[i2]);
}
}
}
struct img_ev
{
unsigned int img_nr;
double ev;
};
struct stack_img
{
unsigned int layer_nr;
std::vector<img_ev> images;
};
bool sort_img_ev (img_ev i1, img_ev i2) { return (i1.ev<i2.ev); };
bool PanoDetector::matchMultiRow(PoolExecutor& aExecutor)
{
//step 1
std::vector<stack_img> stack_images;
HuginBase::StandardImageVariableGroups* variable_groups = new HuginBase::StandardImageVariableGroups(*_panoramaInfo);
for(unsigned int i=0; i<_panoramaInfo->getNrOfImages(); i++)
{
unsigned int stack_nr=variable_groups->getStacks().getPartNumber(i);
//check, if this stack is already in list
bool found=false;
unsigned int index=0;
for(index=0;index<stack_images.size();index++)
{
found=(stack_images[index].layer_nr==stack_nr);
if(found)
{
break;
};
};
if(!found)
{
//new stack
stack_images.resize(stack_images.size()+1);
index=stack_images.size()-1;
//add new stack
stack_images[index].layer_nr=stack_nr;
};
//add new image
unsigned int new_image_index=stack_images[index].images.size();
stack_images[index].images.resize(new_image_index+1);
stack_images[index].images[new_image_index].img_nr=i;
stack_images[index].images[new_image_index].ev=_panoramaInfo->getImage(i).getExposure();
};
delete variable_groups;
//get image with median exposure for search with cp generator
vector<unsigned int> images_layer;
UIntSet images_layer_set;
for(unsigned int i=0;i<stack_images.size();i++)
{
std::sort(stack_images[i].images.begin(),stack_images[i].images.end(),sort_img_ev);
unsigned int index=0;
if(stack_images[i].images[0].ev!=stack_images[i].images[stack_images[i].images.size()-1].ev)
{
index=stack_images[i].images.size() / 2;
};
images_layer.push_back(stack_images[i].images[index].img_nr);
images_layer_set.insert(stack_images[i].images[index].img_nr);
if(stack_images[i].images.size()>1)
{
//build match list for stacks
for(unsigned int j=0;j<stack_images[i].images.size()-1;j++)
{
_matchesData.push_back(MatchData());
MatchData& aM=_matchesData.back();
aM._i1=&(_filesData[stack_images[i].images[j].img_nr]);
aM._i2=&(_filesData[stack_images[i].images[j+1].img_nr]);
};
};
};
//build match data list for image pairs
if(images_layer.size()>1)
{
for(unsigned int i=0;i<images_layer.size()-1;i++)
{
_matchesData.push_back(MatchData());
MatchData& aM = _matchesData.back();
aM._i1 = &(_filesData[images_layer[i]]);
aM._i2 = &(_filesData[images_layer[i+1]]);
};
};
TRACE_INFO(endl<< "--- Find matches ---" << endl);
try
{
BOOST_FOREACH(MatchData& aMD, _matchesData)
aExecutor.execute(new MatchDataRunnable(aMD, *this));
aExecutor.wait();
}
catch(Synchronization_Exception& e)
{
TRACE_ERROR(e.what() << endl);
return false;
}
// Add detected matches to _panoramaInfo
BOOST_FOREACH(MatchData& aM, _matchesData)
BOOST_FOREACH(lfeat::PointMatchPtr& aPM, aM._matches)
_panoramaInfo->addCtrlPoint(ControlPoint(aM._i1->_number, aPM->_img1_x, aPM->_img1_y,
aM._i2->_number, aPM->_img2_x, aPM->_img2_y));
// step 2: connect all image groups
_matchesData.clear();
CPGraph graph;
createCPGraph(*_panoramaInfo, graph);
CPComponents comps;
int n = findCPComponents(graph, comps);
if(n>1)
{
vector<unsigned int> ImagesGroups;
for(unsigned int i=0;i<n;i++)
{
ImagesGroups.push_back(*(comps[i].begin()));
if(comps[i].size()>1)
ImagesGroups.push_back(*(comps[i].rbegin()));
};
for(unsigned int i=0;i<ImagesGroups.size()-1;i++)
{
for(unsigned int j=i+1;j<ImagesGroups.size();j++)
{
_matchesData.push_back(MatchData());
MatchData& aM = _matchesData.back();
aM._i1 = &(_filesData[ImagesGroups[i]]);
aM._i2 = &(_filesData[ImagesGroups[j]]);
};
};
TRACE_INFO(endl<< "--- Find matches in images groups ---" << endl);
try
{
BOOST_FOREACH(MatchData& aMD, _matchesData)
aExecutor.execute(new MatchDataRunnable(aMD, *this));
aExecutor.wait();
}
catch(Synchronization_Exception& e)
{
TRACE_ERROR(e.what() << endl);
return false;
}
BOOST_FOREACH(MatchData& aM, _matchesData)
BOOST_FOREACH(lfeat::PointMatchPtr& aPM, aM._matches)
_panoramaInfo->addCtrlPoint(ControlPoint(aM._i1->_number, aPM->_img1_x, aPM->_img1_y,
aM._i2->_number, aPM->_img2_x, aPM->_img2_y));
};
// step 3: now connect all overlapping images
_matchesData.clear();
createCPGraph(*_panoramaInfo,graph);
if(findCPComponents(graph, comps)==1 && images_layer.size()>2)
{
PT::Panorama optPano=_panoramaInfo->getSubset(images_layer_set);
//next steps happens only when all images are connected;
//now optimize panorama
PanoramaOptions opts = _panoramaInfo->getOptions();
opts.setProjection(PanoramaOptions::EQUIRECTANGULAR);
opts.optimizeReferenceImage=0;
// calculate proper scaling, 1:1 resolution.
// Otherwise optimizer distances are meaningless.
opts.setWidth(30000, false);
opts.setHeight(15000);
optPano.setOptions(opts);
int w = optPano.calcOptimalWidth();
opts.setWidth(w);
opts.setHeight(w/2);
optPano.setOptions(opts);
//generate optimize vector, optimize only yaw and pitch
OptimizeVector optvars;
const SrcPanoImage & anchorImage = optPano.getImage(opts.optimizeReferenceImage);
for (unsigned i=0; i < optPano.getNrOfImages(); i++)
{
std::set<std::string> imgopt;
if(i==opts.optimizeReferenceImage)
{
//optimize only anchors pitch, not yaw
imgopt.insert("p");
}
else
{
imgopt.insert("p");
imgopt.insert("y");
};
optvars.push_back(imgopt);
}
optPano.setOptimizeVector(optvars);
if (getVerbose() < 2)
{
PT_setProgressFcn(ptProgress);
PT_setInfoDlgFcn(ptinfoDlg);
};
HuginBase::PTools::optimize(optPano);
if (getVerbose() < 2)
{
PT_setProgressFcn(NULL);
PT_setInfoDlgFcn(NULL);
};
HuginBase::CalculateImageOverlap overlap(&optPano);
overlap.calculate(10);
for(unsigned int i=0;i<images_layer.size()-2;i++)
{
for(unsigned int j=i+2;j<images_layer.size();j++)
{
if(overlap.getOverlap(i,j)>0)
{
_matchesData.push_back(MatchData());
MatchData& aM = _matchesData.back();
aM._i1 = &(_filesData[images_layer[i]]);
aM._i2 = &(_filesData[images_layer[j]]);
};
};
};
TRACE_INFO(endl<< "--- Find matches for overlapping images ---" << endl);
try
{
BOOST_FOREACH(MatchData& aMD, _matchesData)
aExecutor.execute(new MatchDataRunnable(aMD, *this));
aExecutor.wait();
}
catch(Synchronization_Exception& e)
{
TRACE_ERROR(e.what() << endl);
return false;
}
// Add detected matches to _panoramaInfo
BOOST_FOREACH(MatchData& aM, _matchesData)
BOOST_FOREACH(lfeat::PointMatchPtr& aPM, aM._matches)
_panoramaInfo->addCtrlPoint(ControlPoint(aM._i1->_number, aPM->_img1_x, aPM->_img1_y,
aM._i2->_number, aPM->_img2_x, aPM->_img2_y));
};
return true;
};