class CV_EXPORTS Mat
{
public:
    Mat();
    Mat(int rows, int cols, int type);
    Mat(Size size, int type);
    Mat(int rows, int cols, int type, const Scalar& s);
    Mat(Size size, int type, const Scalar& s);
    Mat(int ndims, const int* sizes, int type);
    Mat(const std::vector<int>& sizes, int type);
    Mat(int ndims, const int* sizes, int type, const Scalar& s);
    Mat(const std::vector<int>& sizes, int type, const Scalar& s);
    Mat(const Mat& m);
    Mat(int rows, int cols, int type, void* data, size_t step=AUTO_STEP);
    Mat(Size size, int type, void* data, size_t step=AUTO_STEP);
    .......
    .........................
    ................................
          /*! includes several bit-fields:
         - the magic signature
         - continuity flag
         - depth
         - number of channels
     */
    int flags;
    //! the matrix dimensionality, >= 2
    int dims;
    //! the number of rows and columns or (-1, -1) when the matrix has more than 2 dimensions
    int rows, cols;
    //! pointer to the data
    uchar* data;

    //! helper fields used in locateROI and adjustROI
    const uchar* datastart;
    const uchar* dataend;
    const uchar* datalimit;

    //! custom allocator
    MatAllocator* allocator;
    //! and the standard allocator
    static MatAllocator* getStdAllocator();
    static MatAllocator* getDefaultAllocator();
    static void setDefaultAllocator(MatAllocator* allocator);

    //! internal use method: updates the continuity flag
    void updateContinuityFlag();

    //! interaction with UMat
    UMatData* u;

    MatSize size;
    MatStep step;

protected:
    template<typename _Tp, typename Functor> void forEach_impl(const Functor& operation);
};

//創(chuàng)建行數(shù)為 rows，列數(shù)為 col，類(lèi)型為 type 的圖像;
Mat::Mat(int rows, int cols, int type);
//創(chuàng)建大小為 size，類(lèi)型為 type 的圖像;
Mat::Mat(Size size, int type)
//創(chuàng)建行數(shù)為 rows，列數(shù)為 col，類(lèi)型為 type 的圖像，并將所有元素初始 化為值 s;
Mat::Mat(int rows, int cols, int type, const Scalar& s);
//創(chuàng)建大小為 size，類(lèi)型為 type 的圖像，并將所有元素初始化為值 s;
Mat::Mat(Size size, int type, const Scalar& s);

Mat mat; 
mat.create(2, 2, CV_8UC3);

Point point;
point.x=2;
point.y=5;
或
Point point=Point(2,5);

 Scalar scalar=Scalar(0,2,255);

//Vec 是Matx的一個(gè)派生類(lèi)，一個(gè)一維的Matx,和vector很類(lèi)似。Matx是個(gè)輕量級(jí)的Mat,必須在使用前規(guī)定好大小。
template<typename _Tp> class Scalar_ : public Vec<_Tp, 4>
{
public:
    //! default constructor
    Scalar_();
    Scalar_(_Tp v0, _Tp v1, _Tp v2=0, _Tp v3=0);
    Scalar_(_Tp v0);

    Scalar_(const Scalar_& s);
    Scalar_(Scalar_&& s) CV_NOEXCEPT;

    Scalar_& operator=(const Scalar_& s);
    Scalar_& operator=(Scalar_&& s) CV_NOEXCEPT;

    template<typename _Tp2, int cn>
    Scalar_(const Vec<_Tp2, cn>& v);

    //! returns a scalar with all elements set to v0
    static Scalar_<_Tp> all(_Tp v0);

    //! conversion to another data type
    template<typename T2> operator Scalar_<T2>() const;

    //! per-element product
    Scalar_<_Tp> mul(const Scalar_<_Tp>& a, double scale=1 ) const;

    //! returns (v0, -v1, -v2, -v3)
    Scalar_<_Tp> conj() const;

    //! returns true iff v1 == v2 == v3 == 0
    bool isReal() const;
};

typedef Scalar_<double> Scalar;

typedef Size_<int> Size2i;
typedef Size_<int64> Size2l;
typedef Size_<float> Size2f;
typedef Size_<double> Size2d;
typedef Size2i Size;

template<typename _Tp> class Size_
{
public:
    typedef _Tp value_type;

    //! default constructor
  //構(gòu)造函數(shù)
    Size_();
    Size_(_Tp _width, _Tp _height);
    Size_(const Size_& sz);
    Size_(Size_&& sz) CV_NOEXCEPT;
    Size_(const Point_<_Tp>& pt);

    Size_& operator = (const Size_& sz);
    Size_& operator = (Size_&& sz) CV_NOEXCEPT;
    //! the area (width*height)
  //區(qū)域(width*height)
    _Tp area() const;
    //! aspect ratio (width/height)
    double aspectRatio() const;
    //! true if empty
    bool empty() const;

    //! conversion of another data type.
  //轉(zhuǎn)化為另一種數(shù)據(jù)類(lèi)型
    template<typename _Tp2> operator Size_<_Tp2>() const;
     //常用屬性，模版類(lèi)型的寬度和高度
    _Tp width; //!< the width 寬度
    _Tp height; //!< the height高度
};

 Size size=Size(2,3);
 size.width;
 size.height;

  Rect rect1=Rect(0,0,100,120);
  Rect rect2=Rect(10,10,100,120);
  Rect rect=rect1|rect2;
  Rect rect3=rect1&rect2;

  Rect rect=Rect(10,10,100,120);
  Rect rect1=rect+point;
  Rect rect2=rect+size;

CV_EXPORTS_W void cvtColor( InputArray src, OutputArray dst, int code, int dstCn = 0 );

 cvtColor(matInput, grayMat,COLOR_BGR2GRAY);

/** the color conversion codes
@see @ref imgproc_color_conversions
@ingroup imgproc_color_conversions
 */
enum ColorConversionCodes {
    COLOR_BGR2BGRA     = 0, //!< add alpha channel to RGB or BGR image
    COLOR_RGB2RGBA     = COLOR_BGR2BGRA,

    COLOR_BGRA2BGR     = 1, //!< remove alpha channel from RGB or BGR image
    COLOR_RGBA2RGB     = COLOR_BGRA2BGR,

    COLOR_BGR2RGBA     = 2, //!< convert between RGB and BGR color spaces (with or without alpha channel)
    COLOR_RGB2BGRA     = COLOR_BGR2RGBA,

    COLOR_RGBA2BGR     = 3,
    COLOR_BGRA2RGB     = COLOR_RGBA2BGR,
    ...........
    ...................
    ..............................
        //! Demosaicing with alpha channel
    COLOR_BayerBG2BGRA = 139,
    COLOR_BayerGB2BGRA = 140,
    COLOR_BayerRG2BGRA = 141,
    COLOR_BayerGR2BGRA = 142,

    COLOR_BayerBG2RGBA = COLOR_BayerRG2BGRA,
    COLOR_BayerGB2RGBA = COLOR_BayerGR2BGRA,
    COLOR_BayerRG2RGBA = COLOR_BayerBG2BGRA,
    COLOR_BayerGR2RGBA = COLOR_BayerGB2BGRA,

    COLOR_COLORCVT_MAX  = 143
};

//顏色空間縮減
void colorReduce(Mat& matInput,Mat& matoutput,int div){
    //復(fù)制輸入圖像
    matoutput=matInput.clone();
    int rows=matoutput.rows;//行數(shù)，高度
    int cols=matoutput.cols*matoutput.channels();//列數(shù)*通道數(shù)=每一行元素的個(gè)數(shù)
    //遍歷圖像矩陣//寬度
    for (int i=0; i<rows; i++) {//行循環(huán)
        uchar *data=matoutput.ptr<uchar>(i);//取出第i行首地址
        for (int j=0; j<cols; j++) {//列循環(huán)
            data[j]=data[j]/div*div+div/2;//開(kāi)始處理每一個(gè)像素
        }
    }
}

//顏色空間縮減
void colorReduceIterator(Mat& matInput,Mat& matoutput,int div){
    //復(fù)制輸入圖像
    matoutput=matInput.clone();
    //初始位置迭代器
    Mat_<Vec3b>::iterator it=matoutput.begin<Vec3b>();
    //終止位置的迭代器
    Mat_<Vec3b>::iterator itend =matoutput.end<Vec3b>();
    //遍歷圖像矩陣
    for (;it!=itend;++it) {
        //處理每一個(gè)像素
        (*it)[0]=(*it)[0]/div*div+div/2;
        (*it)[1]=(*it)[1]/div*div+div/2;
        (*it)[2]=(*it)[2]/div*div+div/2;
    }
}

//顏色空間縮減
void colorReduceVec(Mat& matInput,Mat& matoutput,int div){
    //參數(shù)準(zhǔn)備
    matoutput=matInput.clone();
    int rows=matoutput.rows;//行數(shù)
    int cols=matoutput.cols;//列數(shù)
    for (int i=0; i<rows; i++) {
        for (int j=0; j<cols; j++) {//處理每一個(gè)像素
            //藍(lán)色通道
            matoutput.at<Vec3b>(i,j)[0]=matoutput.at<Vec3b>(i,j)[0]/div*div+div/2;
             //綠色通道
            matoutput.at<Vec3b>(i,j)[1]=matoutput.at<Vec3b>(i,j)[1]/div*div+div/2;
            //紅色通道
            matoutput.at<Vec3b>(i,j)[2]=matoutput.at<Vec3b>(i,j)[2]/div*div+div/2;
        }
    }
}

//置灰
-(UIImage *)grayInPutImage:(UIImage *)inputImage{
    cv::Mat matInput=[[CVUtil sharedInstance]cvMatFromUIImage:inputImage];
    cv:: Mat grayMat;
    cv::cvtColor(matInput, grayMat,cv::COLOR_BGR2GRAY);
    UIImage *imag=[[CVUtil sharedInstance]UIImageFromCVMat:grayMat];
    return imag;
}

//方框?yàn)V波操作
-(UIImage *)boxFilterInPutImage:(UIImage *)inputImage value:(int)value{
    Mat matInput=[[CVUtil sharedInstance]cvMatFromUIImage:inputImage];
    Mat boxFilterMat;
    boxFilter(matInput, boxFilterMat, -1,cv::Size(value+1,value+1));
    UIImage *imag=[[CVUtil sharedInstance]UIImageFromCVMat:boxFilterMat];
    return imag;
}

//均值濾波操作
-(UIImage *)blurInPutImage:(UIImage *)inputImage value:(int)value{
    Mat matInput=[[CVUtil sharedInstance]cvMatFromUIImage:inputImage];
    Mat blurMat;
    blur(matInput, blurMat, cv::Size(value+1,value+1),cv::Point(-1,-1));
    UIImage *imag=[[CVUtil sharedInstance]UIImageFromCVMat:blurMat];
    return imag;
}

//高斯濾波操作
-(UIImage *)gaussianBlurInPutImage:(UIImage *)inputImage value:(int)value{
    Mat matInput=[[CVUtil sharedInstance]cvMatFromUIImage:inputImage];
    Mat gaussianBlurMat;
    GaussianBlur(matInput, gaussianBlurMat, cv::Size(value*2+1,value*2+1), 0,0);
    UIImage *imag=[[CVUtil sharedInstance]UIImageFromCVMat:gaussianBlurMat];
    return imag;
}

//中值濾波操作
-(UIImage *)medianBlurInPutImage:(UIImage *)inputImage value:(int)value{
    Mat matInput=[[CVUtil sharedInstance]cvMatFromUIImage:inputImage];
    Mat medianBlurMat;
    medianBlur(matInput, medianBlurMat,value*2+1);
    UIImage *imag=[[CVUtil sharedInstance]UIImageFromCVMat:medianBlurMat];
    return imag;
}

//雙邊濾波操作
-(UIImage *)bilateralFilterInPutImage:(UIImage *)inputImage value:(int)value{
    Mat matInput=[[CVUtil sharedInstance]cvMatFromUIImage:inputImage];
    Mat bilateralFilterMat;
    Mat grayMat;
    cvtColor(matInput, grayMat,cv::COLOR_BGR2GRAY);
    bilateralFilter(grayMat, bilateralFilterMat, value, (double)value*2, (double)value/2);
    UIImage *imag=[[CVUtil sharedInstance]UIImageFromCVMat:bilateralFilterMat];
    return imag;
}

//腐蝕操作
- (UIImage *)erodeInPutImage:(UIImage *)inputImage value:(int)value{
    Mat matInput=[[CVUtil sharedInstance]cvMatFromUIImage:inputImage];
    Mat element;
    element=cv::getStructuringElement(MORPH_RECT, cv::Size(2*value+1,2*value+1),cv::Point(value,value));
    Mat desimg;
    erode(matInput,desimg,element);
    UIImage *imag=[[CVUtil sharedInstance]UIImageFromCVMat:desimg];
    return imag;
}

//膨脹操作
- (UIImage *)dilateInPutImage:(UIImage *)inputImage value:(int)value{
    Mat matInput=[[CVUtil sharedInstance]cvMatFromUIImage:inputImage];
    Mat element;
    element=cv::getStructuringElement(MORPH_RECT, cv::Size(2*value+1,2*value+1),cv::Point(value,value));
    Mat desimg;
    dilate(matInput,desimg,element);
    UIImage *imag=[[CVUtil sharedInstance]UIImageFromCVMat:desimg];
    return imag;
}

//邊緣檢測(cè)
-(UIImage *)cannyInPutImage:(UIImage *)inputImage value:(int)value{
    if (value==0) {
        return inputImage;
    }
    Mat srcImage=[[CVUtil sharedInstance]cvMatFromUIImage:inputImage];
    Mat destImage;
    destImage.create(srcImage.size(), srcImage.type());
    Mat grayImage;
    cvtColor(srcImage, grayImage, COLOR_BGR2GRAY);
    Mat edge;
    blur(grayImage,edge,cv::Size(value,value));
    Canny(edge, edge, 13, 9 ,3);
    destImage=Scalar::all(0);
    srcImage.copyTo(destImage, edge);
    UIImage *imag=[[CVUtil sharedInstance]UIImageFromCVMat:destImage];
    return imag;
}

//調(diào)整對(duì)比度和亮度
-(UIImage *)contrasAndBrightInPutImage:(UIImage *)inputImage alpha:(NSInteger)alpha beta:(NSInteger)beta{
    Mat g_srcImage=[[CVUtil sharedInstance]cvMatFromUIImage:inputImage];
    if(g_srcImage.empty()){
        return nil;
    }
    Mat g_dstImage=Mat::zeros(g_srcImage.size(),g_srcImage.type());
    int height=g_srcImage.rows;
    int width=g_srcImage.cols;
    for (int row=0; row<height; row++) {
        for (int col=0; col<width; col++) {
            for (int c=0; c<4; c++) {//4通道BGRA圖像
                g_dstImage.at<Vec4b>(row,col)[c]=saturate_cast<uchar>((alpha*0.01)*(g_srcImage.at<Vec4b>(row,col)[c])+beta);
            }
        }
    }
    UIImage *imag=[[CVUtil sharedInstance]UIImageFromCVMat:g_dstImage];
    return imag;
}