NICE_SemSeg/semseg/SemanticSegmentation.cpp

/**
* @file SemanticSegmentation.cpp
* @brief abstract interface for semantic segmentation algorithms
* @author Erik Rodner, Alexander Freytag, Sven Sickert
* @date 03/19/2009

*/
#include "SemanticSegmentation.h"

#include "vislearning/baselib/Preprocess.h"
#include "vislearning/baselib/Globals.h"

#include <iostream>

using namespace OBJREC;
using namespace std;
using namespace NICE;

///////////////////// ///////////////////// /////////////////////
//                   CONSTRUCTORS / DESTRUCTORS
///////////////////// ///////////////////// /////////////////////     

SemanticSegmentation::SemanticSegmentation ( )
    : iterationCountSuffix(1)
{
    this->imagetype = IMAGETYPE_RGB;
    this->classNames = new ClassNames();
    this->run3Dseg = false;
    this->coarseMode = false;
}

SemanticSegmentation::SemanticSegmentation ( const Config *conf,
                                             const ClassNames *classNames )
    : iterationCountSuffix(1)
{
    ///////////
    // same code as in empty constructor - duplication can be avoided with C++11 allowing for constructor delegation
    ///////////

    ///////////
    // here comes the new code part different from the empty constructor
    ///////////

    this->classNames = classNames;

    this->initFromConfig( conf );
}

SemanticSegmentation::~SemanticSegmentation()
{
}

void SemanticSegmentation::initFromConfig(const Config* conf, const string& s_confSection)
{
    std::string imagetype_s = conf->gS ( "main", "imagetype", "rgb" );
    coarseMode = conf->gB( "main", "coarse_mode", false );
    run3Dseg = conf->gB( "main", "run_3dseg", false );

    if ( imagetype_s == "rgb" )
        imagetype = IMAGETYPE_RGB;
    else if ( imagetype_s == "gray" )
        imagetype = IMAGETYPE_GRAY;
    else {
        fprintf ( stderr, "SemanticSegmentation:: unknown image type option\n" );
        exit ( -1 );
    }

    // dangerous!!!
    Preprocess::Init ( conf );
}

///////////////////// ///////////////////// /////////////////////
//                      SEGMENTATION STUFF
///////////////////// ///////////////////// /////////////////////

void SemanticSegmentation::semanticseg (
        const std::string & filename,
        NICE::ImageT<int> & segresult,
        NICE::MultiChannelImageT<double> & probabilities )
{
    Globals::setCurrentImgFN ( filename );
    CachedExample *ce;
    if ( imagetype == IMAGETYPE_RGB )
    {
        NICE::ColorImage img = Preprocess::ReadImgAdvRGB ( filename );
        ce = new CachedExample ( img );
    } else {

        NICE::Image img = Preprocess::ReadImgAdv ( filename );
        ce = new CachedExample ( img );
    }

    this->semanticseg ( ce, segresult, probabilities );
    delete ce;
}

void SemanticSegmentation::semanticseg (
        const std::vector<std::string> & filelist,
        NICE::MultiChannelImageT<int> & segresult,
        NICE::MultiChannelImage3DT<double> & probabilities )
{
    //NICE::MultiChannelImage3DT<int> img;
    //make3DImage( filelist, img );
    CachedExample *ce = new CachedExample (filelist);

    this->semanticseg ( ce, segresult, probabilities );
    delete ce;
}

void SemanticSegmentation::classify ( const std::vector<std::string> & filelist,
                                      NICE::MultiChannelImageT<int> & segresult,
                                      NICE::MultiChannelImage3DT<double> & probabilities )
{
    for ( int it = 0; it < ( int ) filelist.size(); it++ )
    {
        NICE::MultiChannelImageT<double> probs;
        NICE::ImageT<int> res ( segresult.width(), segresult.height() );
        this->semanticseg( filelist[it], res, probs );
        probabilities.addChannel( probs );
        segresult.addChannel( res );
    }
}

///////////////////// ///////////////////// /////////////////////
//                      DATA CONVERSION
///////////////////// ///////////////////// ///////////////////// 
void SemanticSegmentation::convertLSetToSparseExamples ( Examples &examples, LabeledSetVector &lvec )
{
#ifdef DEBUG_PRINTS
    cout << "SemSegRegionBased::convertLSetToExamples starts" << endl;
#endif
    for ( map< int, vector<NICE::Vector *> >::iterator iter = lvec.begin(); iter != lvec.end(); ++iter )
    {
        for ( int j = 0; j < ( int ) iter->second.size(); j++ )
        {
            Vector &tmp = * ( iter->second[j] );
            int dim = tmp.size();
            SparseVector *vec = new SparseVector ( dim );
            for ( int j = 0; j < dim; j++ )
            {
                if ( tmp[j] != 0.0 )
                {
                    ( *vec ) [j] = tmp[j];
                }
            }
            Example ex;
            ex.svec = vec;
            examples.push_back ( pair<int, Example> ( iter->first, ex ) );
        }
    }
    lvec.clear();
#ifdef DEBUG_PRINTS
    cout << "SemSegRegionBased::convertLSetToExamples finished" << endl;
#endif
}

void SemanticSegmentation::convertLSetToExamples ( Examples &examples, LabeledSetVector &lvec, const bool & removeOldDataPointer )
{
#ifdef DEBUG_PRINTS
    cout << "SemSegRegionBased::convertLSetToExamples starts" << endl;
#endif
    for ( map< int, vector<NICE::Vector *> >::iterator iter = lvec.begin(); iter != lvec.end(); ++iter )
    {
        for ( int j = 0; j < (int)iter->second.size(); j++ )
        {
            NICE::Vector *vec = new NICE::Vector ( * ( iter->second[j] ) );
            Example ex ( vec );
            examples.push_back ( pair<int, Example> ( iter->first, ex ) );
        }
    }

    if (!removeOldDataPointer)
    {
        //NOTE this is only useful, if our classifier does NOT need the data explicitely
        lvec.clear();
    }
    else
    {
        lvec.removePointersToDataWithoutDeletion();
        //after setting all the pointers to NULL, we can savely clear the LSet without deleting the previously
        //stored features, which might be needed somewhere else, e.g., in the VCNearestNeighbour
        lvec.clear();
    }

#ifdef DEBUG_PRINTS
    cout << "SemSegRegionBased::convertLSetToExamples finished" << endl;
#endif
}

void SemanticSegmentation::convertExamplesToLSet ( Examples &examples, LabeledSetVector &lvec )
{
#ifdef DEBUG_PRINTS
    cout << "SemSegRegionBased::convertExamplesToLSet starts" << endl;
#endif
    lvec.clear();
    for ( int i = 0; i < ( int ) examples.size(); i++ )
    {
        if ( examples[i].second.vec != NULL )
        {
            lvec.add ( examples[i].first, *examples[i].second.vec );
            delete examples[i].second.vec;
            examples[i].second.vec = NULL;
        }
        else
        {
            if ( examples[i].second.svec != NULL )
            {
                NICE::Vector v;
                examples[i].second.svec->convertToVectorT(v);
                lvec.add ( examples[i].first, v );
                delete examples[i].second.svec;
                examples[i].second.svec = NULL;
            }
            else
            {
                throw ( "no features for LabeledSet" );
            }
        }

    }
    examples.clear();
#ifdef DEBUG_PRINTS
    cout << "SemSegRegionBased::convertExamplesToLSet finished" << endl;
#endif
}

void SemanticSegmentation::convertExamplesToVVector ( VVector &feats, Examples &examples, vector<int> &label )
{
#ifdef DEBUG_PRINTS
    cout << "SemSegRegionBased::convertExamplesToVVector starts" << endl;
#endif
    feats.clear();
    label.clear();
    for ( int i = 0; i < ( int ) examples.size(); i++ )
    {
        label.push_back ( examples[i].first );
        feats.push_back ( *examples[i].second.vec );
        delete examples[i].second.vec;
        examples[i].second.vec = NULL;
    }
    examples.clear();
#ifdef DEBUG_PRINTS
    cout << "SemSegRegionBased::convertExamplesToVVector finished" << endl;
#endif
}

void SemanticSegmentation::convertVVectorToExamples ( VVector &feats, Examples &examples, vector<int> &label )
{
#ifdef DEBUG_PRINTS
    cout << "SemSegRegionBased::convertVVectorToExamples starts" << endl;
#endif
    for ( int i = 0; i < ( int ) feats.size(); i++ )
    {
        NICE::Vector *v = new NICE::Vector ( feats[i] );
        Example ex ( v );
        ex.position = 0; //TODO: hier mal was besseres überlegen, damit Klassifikator wieder Bildspezifisch lernt
        examples.push_back ( pair<int, Example> ( label[i], ex ) );
        feats[i].clear();
    }
    feats.clear();
    label.clear();
#ifdef DEBUG_PRINTS
    cout << "SemSegRegionBased::convertVVectorToExamples finished" << endl;
#endif
}

void SemanticSegmentation::setIterationCountSuffix( const int & _iterationCountSuffix)
{
    this->iterationCountSuffix = _iterationCountSuffix;
}

void SemanticSegmentation::setClassNames ( const OBJREC::ClassNames * _classNames )
{
    this->classNames = _classNames;
}

void SemanticSegmentation::saveProbabilityMapAsImage ( const NICE::MultiChannelImage3DT<double> & prob )
{
    std::string s;

    for ( int cl = 0; cl < prob.channels(); cl++ )
        for ( int z = 0; z < prob.depth(); z++ )
        {
            NICE::ColorImage img( prob.width(),prob.height() );
            NICE::ImageT<double> m = prob.getChannelT(z, cl);
            imageToPseudoColor(m, img);

            std::stringstream out;
            out << "probmap_s" << z << "_c" << cl << ".ppm";
            s = out.str();
            img.write( s );

            //showImage(img, "Probability map");
            //getchar();
        }
}

///////////////////// INTERFACE PERSISTENT /////////////////////
// interface specific methods for store and restore
///////////////////// INTERFACE PERSISTENT /////////////////////

void SemanticSegmentation::restore ( std::istream & is, int format )
{
    //delete everything we knew so far...
    this->clear();

    bool b_restoreVerbose ( false );
#ifdef B_RESTOREVERBOSE
    b_restoreVerbose = true;
#endif

    if ( is.good() )
    {
        if ( b_restoreVerbose )
            std::cerr << " restore SemanticSegmentation" << std::endl;

        std::string tmp;
        is >> tmp; //class name

        if ( ! this->isStartTag( tmp, "SemanticSegmentation" ) )
        {
            std::cerr << " WARNING - attempt to restore SemanticSegmentation, but start flag " << tmp << " does not match! Aborting... " << std::endl;
            throw;
        }

        is.precision (numeric_limits<double>::digits10 + 1);

        bool b_endOfBlock ( false ) ;

        while ( !b_endOfBlock )
        {
            is >> tmp; // start of block

            if ( this->isEndTag( tmp, "SemanticSegmentation" ) )
            {
                b_endOfBlock = true;
                continue;
            }

            tmp = this->removeStartTag ( tmp );

            if ( b_restoreVerbose )
                std::cerr << " currently restore section " << tmp << " in SemanticSegmentation" << std::endl;

            if ( tmp.compare("classNames") == 0 )
            {
                //dirty solution to circumvent the const-flag
                const_cast<ClassNames*>(this->classNames)->restore ( is, format );

                is >> tmp; // end of block
                tmp = this->removeEndTag ( tmp );
            }
            else if ( tmp.compare("imagetype") == 0 )
            {
                unsigned int ui_imagetyp;
                is >> ui_imagetyp;
                this->imagetype = static_cast<IMAGETYP> ( ui_imagetyp );

                is >> tmp; // end of block
                tmp = this->removeEndTag ( tmp );
            }
            else if ( tmp.compare("iterationCountSuffix") == 0 )
            {
                is >> this->iterationCountSuffix;

                is >> tmp; // end of block
                tmp = this->removeEndTag ( tmp );
            }
            else
            {
                std::cerr << "WARNING -- unexpected SemanticSegmentation object -- " << tmp << " -- for restoration... aborting" << std::endl;
                throw;
            }
        }
    }
    else
    {
        std::cerr << "SemanticSegmentation::restore -- InStream not initialized - restoring not possible!" << std::endl;
        throw;
    }


    //TODO check whether we also have to do something linke Preprocess::Init ( conf );
}

void SemanticSegmentation::store ( std::ostream & os, int format ) const
{
    if (os.good())
    {
        // show starting point
        os << this->createStartTag( "SemanticSegmentation" ) << std::endl;

        os.precision (numeric_limits<double>::digits10 + 1);

        os << this->createStartTag( "classNames" ) << std::endl;
        this->classNames->store ( os, format );
        os << this->createEndTag( "classNames" ) << std::endl;

        //

        os << this->createStartTag( "imagetype" ) << std::endl;
        os << imagetype << std::endl;
        os << this->createEndTag( "imagetype" ) << std::endl;

        //

        os << this->createStartTag( "iterationCountSuffix" ) << std::endl;
        os << iterationCountSuffix << std::endl;
        os << this->createEndTag( "iterationCountSuffix" ) << std::endl;

        // done
        os << this->createEndTag( "SemanticSegmentation" ) << std::endl;
    }
    else
    {
        std::cerr << "OutStream not initialized - storing not possible!" << std::endl;
    }
}

void SemanticSegmentation::clear ()
{
    //TODO
}