OpenCV - GrabCut与自定义前景/背景模型

问题描述

我想使用在OpenCV上实现的GrabCut算法。

I want to use the GrabCut algorithm implemented on OpenCV.

如这是函数签名：

 c $ c = mode = GC_EVAL  ？运行方法，如果需要，我需要如何对模型进行编码？ / p> 
 

Is it possible to populate those models whith existing data and run the method with mode=GC_EVAL?, if so, how do I need to encode the models?
推荐答案
在opencv / sources / modules / imgproc / src / grabcut.cpp中，你可以看看模型编码：
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 );
}
所以你需要为每个模型cv :: Mat 1 x 65双（componentsCount等于5）。每个组件有3个手段，因为它在RGB颜色空间中进行计算。使用GC_EVAL确实会使模型完好无损，但我从未尝试过使用预先计算的模型。 
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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