BackgroundSubtractorKNN_.cpp

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#include "mexopencv.hpp"
#include "opencv2/video.hpp"
using namespace std;
using namespace cv;

// Persistent objects
namespace {
int last_id = 0;
map<int,Ptr<BackgroundSubtractorKNN> > obj_;
}

void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[])
{
    // Check the number of arguments
    nargchk(nrhs>=2 && nlhs<=1);

    // Argument vector
    vector<MxArray> rhs(prhs, prhs+nrhs);
    int id = rhs[0].toInt();
    string method(rhs[1].toString());

    // constructor call
    if (method == "new") {
        nargchk(nrhs>=2 && (nrhs%2)==0 && nlhs<=1);
        int history = 500;
        double dist2Threshold = 400.0;
        bool detectShadows = true;
        for (int i=2; i<nrhs; i+=2) {
            string key(rhs[i].toString());
            if (key == "History")
                history = rhs[i+1].toInt();
            else if (key == "Dist2Threshold")
                dist2Threshold = rhs[i+1].toDouble();
            else if (key == "DetectShadows")
                detectShadows = rhs[i+1].toBool();
            else
                mexErrMsgIdAndTxt("mexopencv:error",
                    "Unrecognized option %s", key.c_str());
        }
        obj_[++last_id] = createBackgroundSubtractorKNN(
            history, dist2Threshold, detectShadows);
        plhs[0] = MxArray(last_id);
        mexLock();
        return;
    }

    // Big operation switch
    Ptr<BackgroundSubtractorKNN> obj = obj_[id];
    if (obj.empty())
        mexErrMsgIdAndTxt("mexopencv:error", "Object not found id=%d", id);
    if (method == "delete") {
        nargchk(nrhs==2 && nlhs==0);
        obj_.erase(id);
        mexUnlock();
    }
    else if (method == "clear") {
        nargchk(nrhs==2 && nlhs==0);
        obj->clear();
    }
    else if (method == "save") {
        nargchk(nrhs==3 && nlhs==0);
        obj->save(rhs[2].toString());
    }
    else if (method == "load") {
        nargchk(nrhs>=3 && (nrhs%2)==1 && nlhs==0);
        string objname;
        bool loadFromString = false;
        for (int i=3; i<nrhs; i+=2) {
            string key(rhs[i].toString());
            if (key == "ObjName")
                objname = rhs[i+1].toString();
            else if (key == "FromString")
                loadFromString = rhs[i+1].toBool();
            else
                mexErrMsgIdAndTxt("mexopencv:error",
                    "Unrecognized option %s", key.c_str());
        }
        /*
        obj_[id] = (loadFromString ?
            Algorithm::loadFromString<BackgroundSubtractorKNN>(rhs[2].toString(), objname) :
            Algorithm::load<BackgroundSubtractorKNN>(rhs[2].toString(), objname));
        */
        // HACK: workaround for missing BackgroundSubtractorKNN::create()
        FileStorage fs(rhs[2].toString(), FileStorage::READ +
            (loadFromString ? FileStorage::MEMORY : 0));
        if (!fs.isOpened())
            mexErrMsgIdAndTxt("mexopencv:error", "Failed to open file");
        FileNode fn(objname.empty() ? fs.getFirstTopLevelNode() : fs[objname]);
        if (fn.empty())
            mexErrMsgIdAndTxt("mexopencv:error", "Failed to get node");
        obj->read(fn);
        //*/
    }
    else if (method == "empty") {
        nargchk(nrhs==2 && nlhs<=1);
        plhs[0] = MxArray(obj->empty());
    }
    else if (method == "getDefaultName") {
        nargchk(nrhs==2 && nlhs<=1);
        plhs[0] = MxArray(obj->getDefaultName());
    }
    else if (method == "apply") {
        nargchk(nrhs>=3 && (nrhs%2)==1 && nlhs<=1);
        double learningRate = -1;
        for (int i=3; i<nrhs; i+=2) {
            string key(rhs[i].toString());
            if (key == "LearningRate")
                learningRate = rhs[i+1].toDouble();
            else
                mexErrMsgIdAndTxt("mexopencv:error",
                    "Unrecognized option %s", key.c_str());
        }
        Mat image(rhs[2].toMat(CV_8U)), fgmask;
        obj->apply(image, fgmask, learningRate);
        plhs[0] = MxArray(fgmask);
    }
    else if (method == "getBackgroundImage") {
        nargchk(nrhs==2 && nlhs<=1);
        Mat backgroundImage;
        obj->getBackgroundImage(backgroundImage);
        plhs[0] = MxArray(backgroundImage);
    }
    else if (method == "get") {
        nargchk(nrhs==3 && nlhs<=1);
        string prop(rhs[2].toString());
        if (prop == "History")
            plhs[0] = MxArray(obj->getHistory());
        else if (prop == "NSamples")
            plhs[0] = MxArray(obj->getNSamples());
        else if (prop == "kNNSamples")
            plhs[0] = MxArray(obj->getkNNSamples());
        else if (prop == "Dist2Threshold")
            plhs[0] = MxArray(obj->getDist2Threshold());
        else if (prop == "DetectShadows")
            plhs[0] = MxArray(obj->getDetectShadows());
        else if (prop == "ShadowValue")
            plhs[0] = MxArray(obj->getShadowValue());
        else if (prop == "ShadowThreshold")
            plhs[0] = MxArray(obj->getShadowThreshold());
        else
            mexErrMsgIdAndTxt("mexopencv:error",
                "Unrecognized property %s", prop.c_str());
    }
    else if (method == "set") {
        nargchk(nrhs==4 && nlhs==0);
        string prop(rhs[2].toString());
        if (prop == "History")
            obj->setHistory(rhs[3].toInt());
        else if (prop == "NSamples")
            obj->setNSamples(rhs[3].toInt());
        else if (prop == "kNNSamples")
            obj->setkNNSamples(rhs[3].toInt());
        else if (prop == "Dist2Threshold")
            obj->setDist2Threshold(rhs[3].toDouble());
        else if (prop == "DetectShadows")
            obj->setDetectShadows(rhs[3].toBool());
        else if (prop == "ShadowValue")
            obj->setShadowValue(rhs[3].toInt());
        else if (prop == "ShadowThreshold")
            obj->setShadowThreshold(rhs[3].toDouble());
        else
            mexErrMsgIdAndTxt("mexopencv:error",
                "Unrecognized property %s", prop.c_str());
    }
    else
        mexErrMsgIdAndTxt("mexopencv:error",
            "Unrecognized operation %s", method.c_str());
}