OpenCV - GrabCut with custom foreground/background models

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深忆病人
深忆病人 2021-01-03 04:21

I want to use the GrabCut algorithm implemented on OpenCV.

As shown in the documentation this is the function signature:

void grabCut(
    InputArra         


        
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  • 2021-01-03 04:44

    In opencv/sources/modules/imgproc/src/grabcut.cpp you can have a look how the models (GMMs) are encoded:

    GMM::GMM( Mat& _model )
    {
        const int modelSize = 3/*mean*/ + 9/*covariance*/ + 1/*component weight*/;
        if( _model.empty() )
        {
            _model.create( 1, modelSize*componentsCount, CV_64FC1 );
            _model.setTo(Scalar(0));
        }
        else if( (_model.type() != CV_64FC1) || (_model.rows != 1) || (_model.cols != modelSize*componentsCount) )
            CV_Error( CV_StsBadArg, "_model must have CV_64FC1 type, rows == 1 and cols == 13*componentsCount" );
    
        model = _model;
    
        coefs = model.ptr<double>(0);
        mean = coefs + componentsCount;
        cov = mean + 3*componentsCount;
    
        for( int ci = 0; ci < componentsCount; ci++ )
            if( coefs[ci] > 0 )
                 calcInverseCovAndDeterm( ci );
    }
    

    So you need for every model a cv::Mat of 1 x 65 doubles (componentsCount equals 5). There are 3 means per component because its computing in RGB colorspace. Using GC_EVAL would indeed leave the models intact but I never tried it with pre-computed models.

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  • 2021-01-03 04:54

    Even I had a similar problem. This is how I solved it. I edited the GC_EVAL condition in the grabcut source code to this -

    if( mode == GC_EVAL )
       { checkMask( img, mask );
        for( int i = 0; i < iterCount; i++ )
    {
        GCGraph<double> graph;
        assignGMMsComponents( img, mask, bgdGMM, fgdGMM, compIdxs );
    
        constructGCGraph(img, mask, bgdGMM, fgdGMM, lambda, leftW, upleftW, upW, uprightW, graph );
        estimateSegmentation( graph, mask );
        return;    
    }
    }
    

    Notice that the function learnGMMs is not called here. This is done because the Foreground and Background GMMs are precomputed.

    You can save models in a .xml file using the following code snippet.

     FileStorage fs("mymodels.xml", FileStorage::WRITE);
            fs << "BgdModel" << bgdModel;
            fs << "FgdModel" << fgdModel;
    fs.release();
    

    You can retrieve the models using the following code.

    FileStorage fs1("mymodels.xml", FileStorage::READ);
    
            fs1["BgdModel"] >> bgdModel1;
    
            fs1["FgdModel"] >> fgdModel1;
    

    This worked for me.

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