OpenCV中的 HOGDescriptor 类

其定义在  object.hpp中找到的：

struct CV_EXPORTS_W HOGDescriptor
{
public:
    enum { L2Hys=0 };
    enum { DEFAULT_NLEVELS=64 };

CV_WRAP HOGDescriptor() : winSize(64,128), blockSize(16,16), blockStride(8,8),
        cellSize(8,8), nbins(9), derivAperture(1), winSigma(-1),
        histogramNormType(HOGDescriptor::L2Hys), L2HysThreshold(0.2), gammaCorrection(true),
        nlevels(HOGDescriptor::DEFAULT_NLEVELS)
    {}

CV_WRAP HOGDescriptor(Size _winSize, Size _blockSize, Size _blockStride,
                  Size _cellSize, int _nbins, int _derivAperture=1, double _winSigma=-1,
                  int _histogramNormType=HOGDescriptor::L2Hys,
                  double _L2HysThreshold=0.2, bool _gammaCorrection=false,
                  int _nlevels=HOGDescriptor::DEFAULT_NLEVELS)
    : winSize(_winSize), blockSize(_blockSize), blockStride(_blockStride), cellSize(_cellSize),
    nbins(_nbins), derivAperture(_derivAperture), winSigma(_winSigma),
    histogramNormType(_histogramNormType), L2HysThreshold(_L2HysThreshold),
    gammaCorrection(_gammaCorrection), nlevels(_nlevels)
    {}

CV_WRAP HOGDescriptor(const String& filename)
    {
        load(filename);
    }

HOGDescriptor(const HOGDescriptor& d)
    {
        d.copyTo(*this);
    }

virtual ~HOGDescriptor() {}

CV_WRAP size_t getDescriptorSize() const;
    CV_WRAP bool checkDetectorSize() const;
    CV_WRAP double getWinSigma() const;

CV_WRAP virtual void setSVMDetector(InputArray _svmdetector);

virtual bool read(FileNode& fn);
    virtual void write(FileStorage& fs, const String& objname) const;

CV_WRAP virtual bool load(const String& filename, const String& objname=String());
    CV_WRAP virtual void save(const String& filename, const String& objname=String()) const;
    virtual void copyTo(HOGDescriptor& c) const;

CV_WRAP virtual void compute(const Mat& img,
                        CV_OUT vector<float>& descriptors,
                        Size winStride=Size(), Size padding=Size(),
                        const vector<Point>& locations=vector<Point>()) const;
    //with found weights output
    CV_WRAP virtual void detect(const Mat& img, CV_OUT vector<Point>& foundLocations,
                        CV_OUT vector<double>& weights,
                        double hitThreshold=0, Size winStride=Size(),
                        Size padding=Size(),
                        const vector<Point>& searchLocations=vector<Point>()) const;
    //without found weights output
    virtual void detect(const Mat& img, CV_OUT vector<Point>& foundLocations,
                        double hitThreshold=0, Size winStride=Size(),
                        Size padding=Size(),
                        const vector<Point>& searchLocations=vector<Point>()) const;
    //with result weights output
    CV_WRAP virtual void detectMultiScale(const Mat& img, CV_OUT vector<Rect>& foundLocations,
                                  CV_OUT vector<double>& foundWeights, double hitThreshold=0,
                                  Size winStride=Size(), Size padding=Size(), double scale=1.05,
                                  double finalThreshold=2.0,bool useMeanshiftGrouping = false) const;
    //without found weights output
    virtual void detectMultiScale(const Mat& img, CV_OUT vector<Rect>& foundLocations,
                                  double hitThreshold=0, Size winStride=Size(),
                                  Size padding=Size(), double scale=1.05,
                                  double finalThreshold=2.0, bool useMeanshiftGrouping = false) const;