找不到Feature2D::detectAndCompute的具体实现

问题遇到的现象和发生背景

在学习ORB特征点时，想搞清楚detect和compute两个函数的实现。翻ORB的源代码，发现class CV_EXPORTS_W ORB : public Feature2D，在Feature2D中定义了detect和compute两个函数，找到feature.cpp，找到detect和compute两个函数的实现；这两个函数都是内部调用Feature2D::detectAndCompute函数，但是转到detectAndCompute函数后却没有发现其具体代码实现，只有两行代码CV_INSTRUMENT_REGION();CV_Error(Error::StsNotImplemented, ""); 相关代码如下所示：

问题相关代码，请勿粘贴截图

//Feature2D的类定义：（在feature.hpp文件中
class CV_EXPORTS_W Feature2D : public virtual Algorithm
{
public:
    virtual ~Feature2D();

    /** @brief Detects keypoints in an image (first variant) or image set (second variant).

    @param image Image.
    @param keypoints The detected keypoints. In the second variant of the method keypoints[i] is a set
    of keypoints detected in images[i] .
    @param mask Mask specifying where to look for keypoints (optional). It must be a 8-bit integer
    matrix with non-zero values in the region of interest.
     */
    CV_WRAP virtual void detect( InputArray image,
                                 CV_OUT std::vector& keypoints,
                                 InputArray mask=noArray() );

    /** @overload
    @param images Image set.
    @param keypoints The detected keypoints. In the second variant of the method keypoints[i] is a set
    of keypoints detected in images[i] .
    @param masks Masks for each input image specifying where to look for keypoints (optional).
    masks[i] is a mask for images[i].
    */
    CV_WRAP virtual void detect( InputArrayOfArrays images,
                         CV_OUT std::vector >& keypoints,
                         InputArrayOfArrays masks=noArray() );

    /** @brief Computes the descriptors for a set of keypoints detected in an image (first variant) or image set
    (second variant).

    @param image Image.
    @param keypoints Input collection of keypoints. Keypoints for which a descriptor cannot be
    computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint
    with several dominant orientations (for each orientation).
    @param descriptors Computed descriptors. In the second variant of the method descriptors[i] are
    descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the
    descriptor for keypoint j-th keypoint.
     */
    CV_WRAP virtual void compute( InputArray image,
                                  CV_OUT CV_IN_OUT std::vector& keypoints,
                                  OutputArray descriptors );

    /** @overload

    @param images Image set.
    @param keypoints Input collection of keypoints. Keypoints for which a descriptor cannot be
    computed are removed. Sometimes new keypoints can be added, for example: SIFT duplicates keypoint
    with several dominant orientations (for each orientation).
    @param descriptors Computed descriptors. In the second variant of the method descriptors[i] are
    descriptors computed for a keypoints[i]. Row j is the keypoints (or keypoints[i]) is the
    descriptor for keypoint j-th keypoint.
    */
    CV_WRAP virtual void compute( InputArrayOfArrays images,
                          CV_OUT CV_IN_OUT std::vector >& keypoints,
                          OutputArrayOfArrays descriptors );

    /** Detects keypoints and computes the descriptors */
    CV_WRAP virtual void detectAndCompute( InputArray image, InputArray mask,
                                           CV_OUT std::vector& keypoints,
                                           OutputArray descriptors,
                                           bool useProvidedKeypoints=false );

    CV_WRAP virtual int descriptorSize() const;
    CV_WRAP virtual int descriptorType() const;
    CV_WRAP virtual int defaultNorm() const;

    CV_WRAP void write( const String& fileName ) const;

    CV_WRAP void read( const String& fileName );

    virtual void write( FileStorage&) const;

    virtual void read( const FileNode&);

    //! Return true if detector object is empty
    CV_WRAP virtual bool empty() const;
};

//Feature2D的类实现：（在feature.cpp文件中
void Feature2D::detect( InputArray image,
                        std::vector& keypoints,
                        InputArray mask )
{
    CV_INSTRUMENT_REGION();

    if( image.empty() )
    {
        keypoints.clear();
        return;
    }
    detectAndCompute(image, mask, keypoints, noArray(), false);
}

void Feature2D::compute( InputArray image,
                         std::vector& keypoints,
                         OutputArray descriptors )
{
    CV_INSTRUMENT_REGION();

    if( image.empty() )
    {
        descriptors.release();
        return;
    }
    detectAndCompute(image, noArray(), keypoints, descriptors, true);
}
//下面这个函数就是我想问的，没有发现具体实现。
void Feature2D::detectAndCompute( InputArray, InputArray,
                                  std::vector&,
                                  OutputArray,
                                  bool )
{
    CV_INSTRUMENT_REGION();

    CV_Error(Error::StsNotImplemented, "");
}

我想要达到的结果

希望有知道的指导一下

能够打断点不，可以根据断点+步进查看下具体实现？