OpenCV的Mat类型以及根本函数应用
Mat和IplImage的区别
Mat和IplImage的次要区别
在OpenCV中IplImage是示意一个图像的构造体，也是从OpenCV1.0到目前最为重要的一个构造；在之前的图像示意用IplImage，而且之前的OpenCV是用C语言编写的，提供的接口也是C语言接口。
Mat是起初OpenCV封装的一个C++类，用来示意一个图像，和IplImage示意基本一致，然而Mat还增加了一些图像函数。
IplImage
IplImage数据结构的定义在opencvbuildincludeopencv2coretypes_c.h文件中。
typedef struct _IplImage{ int nSize; /* sizeof(IplImage) */ int ID; /* version (=0)*/ int nChannels; /* Most of OpenCV functions support 1,2,3 or 4 channels */ int alphaChannel; /* Ignored by OpenCV */ int depth; /* Pixel depth in bits: IPL_DEPTH_8U, IPL_DEPTH_8S, IPL_DEPTH_16S, IPL_DEPTH_32S, IPL_DEPTH_32F and IPL_DEPTH_64F are supported. */ char colorModel[4]; /* Ignored by OpenCV */ char channelSeq[4]; /* ditto */ int dataOrder; /* 0 - interleaved color channels, 1 - separate color channels. cvCreateImage can only create interleaved images */ int origin; /* 0 - top-left origin, 1 - bottom-left origin (Windows bitmaps style). */ int align; /* Alignment of image rows (4 or 8). OpenCV ignores it and uses widthStep instead. */ int width; /* Image width in pixels. */ int height; /* Image height in pixels. */ struct _IplROI *roi; /* Image ROI. If NULL, the whole image is selected. */ struct _IplImage *maskROI; /* Must be NULL. */ void *imageId; /* " " */ struct _IplTileInfo *tileInfo; /* " " */ int imageSize; /* Image data size in bytes (==image->height*image->widthStep in case of interleaved data)*/ char *imageData; /* Pointer to aligned image data. */ int widthStep; /* Size of aligned image row in bytes. */ int BorderMode[4]; /* Ignored by OpenCV. */ int BorderConst[4]; /* Ditto. */ char *imageDataOrigin; /* Pointer to very origin of image data (not necessarily aligned) - needed for correct deallocation */}IplImage;可见，IplImage是一个示意图像的构造体：C语言操作OpenCV的数据结构。位置等同于Mat，能够说是历史版本了。
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Mat
Mat这个数据结构定义在opencvbuildincludeopencv2corecore.hpp这个文件。
class CV_EXPORTS Mat{public: //! default constructor Mat(); //! constructs 2D matrix of the specified size and type // (_type is CV_8UC1, CV_64FC3, CV_32SC(12) etc.) Mat(int rows, int cols, int type); Mat(Size size, int type); //! constucts 2D matrix and fills it with the specified value _s. Mat(int rows, int cols, int type, const Scalar& s); Mat(Size size, int type, const Scalar& s); //! constructs n-dimensional matrix Mat(int ndims, const int* sizes, int type); Mat(int ndims, const int* sizes, int type, const Scalar& s); //! copy constructor Mat(const Mat& m); //! constructor for matrix headers pointing to user-allocated data 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); Mat(int ndims, const int* sizes, int type, void* data, const size_t* steps=0); //! creates a matrix header for a part of the bigger matrix Mat(const Mat& m, const Range& rowRange, const Range& colRange=Range::all()); Mat(const Mat& m, const Rect& roi); Mat(const Mat& m, const Range* ranges); //! converts old-style CvMat to the new matrix; the data is not copied by default Mat(const CvMat* m, bool copyData=false); //! converts old-style CvMatND to the new matrix; the data is not copied by default Mat(const CvMatND* m, bool copyData=false); //! converts old-style IplImage to the new matrix; the data is not copied by default Mat(const IplImage* img, bool copyData=false); //! builds matrix from std::vector with or without copying the data ......protected: void initEmpty();};Mat是OpenCV最根本的数据结构，Mat即矩阵（Matrix）的缩写咱们在读取图片的时候就是将图片定义为Mat类型，其重载的构造函数一大堆。
其中有一个构造函数能够很不便的间接将IplImage转化为Mat
Mat(const IplImage* img, bool copyData=false);根本函数应用
imread
性能：从一个文件中载入图片
定义：
Mat imread( const string& filename, int flags=1 );■第一个参数，const string&类型的filename，这是咱们须要载入的图片路径名。
在Windows操作系统下，OpenCV的imread函数反对罕用的图片类型，比方bmp,jpg,jpeg,png等等。
■第二个参数，int类型的flags，为载入标识，它指定一个加载图像的色彩类型。能够看到它自带缺省值1.所以有时候这个参数在调用时咱们能够疏忽。如果在调用时疏忽这个参数，就示意载入三通道的彩色图像。具体起因看上面的解释。
flags是int型的变量，咱们能够按如下形式取值：
- flags >0返回一个3通道的彩色图像。
- flags =0返回灰度图像。
- flags <0返回蕴含Alpha通道的加载的图像。
须要留神的点：输入的图像默认状况下是不载入Alpha通道进来的。如果咱们须要载入Alpha通道的话呢，这里就须要取负值。
所以默认值flags=1示意载入三通道的彩色图像。
imshow
性能：显示一个图像
定义：
void imshow(const string& winname, InputArray mat); ■ 第一个参数，const string&类型的winname，填须要显示的窗口标识名称。
■ 第二个参数，InputArray 类型的mat，填须要显示的图像。
InputArray 类型是什么类型？
通过转到定义，咱们能够在opencvbuildincludeopencv2highguihighgui.hpp文件中找到imshow的原型：
CV_EXPORTS_W void imshow(const string& winname, InputArray mat);进一步对InputArray转到定义，在opencvbuildincludeopencv2corecore.hpp文件中查到一个typedef申明：
typedef const _InputArray& InputArray; 这其实一个类型申明援用，就是说_InputArray和InputArray是一个意思，而后再次对_InputArray进行转到定义，终于，在opencvbuildincludeopencv2corecore.hpp文件中发现了InputArray的真身：
class CV_EXPORTS _InputArray{public: enum { KIND_SHIFT = 16, FIXED_TYPE = 0x8000 << KIND_SHIFT, FIXED_SIZE = 0x4000 << KIND_SHIFT, KIND_MASK = ~(FIXED_TYPE|FIXED_SIZE) - (1 << KIND_SHIFT) + 1, NONE = 0 << KIND_SHIFT, MAT = 1 << KIND_SHIFT, MATX = 2 << KIND_SHIFT, STD_VECTOR = 3 << KIND_SHIFT, STD_VECTOR_VECTOR = 4 << KIND_SHIFT, STD_VECTOR_MAT = 5 << KIND_SHIFT, EXPR = 6 << KIND_SHIFT, OPENGL_BUFFER = 7 << KIND_SHIFT, OPENGL_TEXTURE = 8 << KIND_SHIFT, GPU_MAT = 9 << KIND_SHIFT, OCL_MAT =10 << KIND_SHIFT }; _InputArray(); _InputArray(const Mat& m); _InputArray(const MatExpr& expr); template<typename _Tp> _InputArray(const _Tp* vec, int n); template<typename _Tp> _InputArray(const vector<_Tp>& vec); template<typename _Tp> _InputArray(const vector<vector<_Tp> >& vec); _InputArray(const vector<Mat>& vec); template<typename _Tp> _InputArray(const vector<Mat_<_Tp> >& vec); template<typename _Tp> _InputArray(const Mat_<_Tp>& m); template<typename _Tp, int m, int n> _InputArray(const Matx<_Tp, m, n>& matx); _InputArray(const Scalar& s); _InputArray(const double& val); // < Deprecated _InputArray(const GlBuffer& buf); _InputArray(const GlTexture& tex); // > _InputArray(const gpu::GpuMat& d_mat); _InputArray(const ogl::Buffer& buf); _InputArray(const ogl::Texture2D& tex); virtual Mat getMat(int i=-1) const; virtual void getMatVector(vector<Mat>& mv) const; // < Deprecated virtual GlBuffer getGlBuffer() const; virtual GlTexture getGlTexture() const; // > virtual gpu::GpuMat getGpuMat() const; /*virtual*/ ogl::Buffer getOGlBuffer() const; /*virtual*/ ogl::Texture2D getOGlTexture2D() const; virtual int kind() const; virtual Size size(int i=-1) const; virtual size_t total(int i=-1) const; virtual int type(int i=-1) const; virtual int depth(int i=-1) const; virtual int channels(int i=-1) const; virtual bool empty() const;#ifdef OPENCV_CAN_BREAK_BINARY_COMPATIBILITY virtual ~_InputArray();#endif int flags; void* obj; Size sz;};能够看到，_InputArray类的外面首先定义了一个枚举，而后定了各个构造函数和虚函数。很多时候，遇到函数原型中的InputArray类型，咱们把它简略地当做Mat类型就行了。
imshow 函数用于在指定的窗口中显示图像。如果窗口是用CV_WINDOW_AUTOSIZE（默认值）标记创立的，那么显示图像原始大小。否则，将图像进行缩放以适宜窗口。而imshow 函数缩放图像，取决于图像的深度：
- 如果载入的图像是8位无符号类型（8-bit unsigned），就显示图像原本的样子。
- 如果图像是16位无符号类型（16-bit unsigned）或32位整型（32-bit integer），便用像素值除以256。也就是说，值的范畴是[0,255 x 256]映射到[0,255]。
- 如果图像是32位浮点型（32-bit floating-point），像素值便要乘以255。也就是说，该值的范畴是[0,1]映射到[0,255]。
imwrite
性能：输入图像到文件
定义：
bool imwrite( const string& filename, InputArray img, const vector<int>& params=vector<int>());■ 第一个参数，const string&类型的filename，填须要写入的文件名就行了，带上后缀，比方，“123.jpg”这样。
■ 第二个参数，InputArray类型的img，个别填一个Mat类型的图像数据就行了。
■ 第三个参数，const vector<int>&类型的params，示意为特定格局保留的参数编码，它有默认值vector<int>()，所以个别状况下不须要填写。
cvtcolor
性能：将一个图像的色彩空间转换到另一种（Converts an image from one color space to another.）
参考：cvtcolor
定义：
void cvtColor( InputArray src, OutputArray dst, int code, int dstCn=0 );■ 第一个参数，InputArray类型的src ,-- Source image
■ 第二个参数，OutputArray类型的dst，Destination image of the same size and depth as src
■ 第三个参数，int类型的code，色彩空间变换代码Color space conversion code。
具体的变换代码参见：opencvbuildincludeopencv2imgproctypes_c.h文件中的第87行，枚举类型。
/* Constants for color conversion */enum{ CV_BGR2BGRA =0, CV_RGB2RGBA =CV_BGR2BGRA, CV_BGRA2BGR =1, CV_RGBA2RGB =CV_BGRA2BGR, CV_BGR2RGBA =2, CV_RGB2BGRA =CV_BGR2RGBA, CV_RGBA2BGR =3, CV_BGRA2RGB =CV_RGBA2BGR, CV_BGR2RGB =4, CV_RGB2BGR =CV_BGR2RGB, CV_BGRA2RGBA =5, CV_RGBA2BGRA =CV_BGRA2RGBA, CV_BGR2GRAY =6, CV_RGB2GRAY =7, CV_GRAY2BGR =8, CV_GRAY2RGB =CV_GRAY2BGR, CV_GRAY2BGRA =9, CV_GRAY2RGBA =CV_GRAY2BGRA, CV_BGRA2GRAY =10, CV_RGBA2GRAY =11, CV_BGR2BGR565 =12, CV_RGB2BGR565 =13, CV_BGR5652BGR =14, CV_BGR5652RGB =15, CV_BGRA2BGR565 =16, CV_RGBA2BGR565 =17, CV_BGR5652BGRA =18, CV_BGR5652RGBA =19, CV_GRAY2BGR565 =20, CV_BGR5652GRAY =21, CV_BGR2BGR555 =22, CV_RGB2BGR555 =23, CV_BGR5552BGR =24, CV_BGR5552RGB =25, CV_BGRA2BGR555 =26, CV_RGBA2BGR555 =27, CV_BGR5552BGRA =28, CV_BGR5552RGBA =29, CV_GRAY2BGR555 =30, CV_BGR5552GRAY =31, CV_BGR2XYZ =32, CV_RGB2XYZ =33, CV_XYZ2BGR =34, CV_XYZ2RGB =35, CV_BGR2YCrCb =36, CV_RGB2YCrCb =37, CV_YCrCb2BGR =38, CV_YCrCb2RGB =39, CV_BGR2HSV =40, CV_RGB2HSV =41, CV_BGR2Lab =44, CV_RGB2Lab =45, CV_BayerBG2BGR =46, CV_BayerGB2BGR =47, CV_BayerRG2BGR =48, CV_BayerGR2BGR =49, CV_BayerBG2RGB =CV_BayerRG2BGR, CV_BayerGB2RGB =CV_BayerGR2BGR, CV_BayerRG2RGB =CV_BayerBG2BGR, CV_BayerGR2RGB =CV_BayerGB2BGR, CV_BGR2Luv =50, CV_RGB2Luv =51, CV_BGR2HLS =52, CV_RGB2HLS =53, CV_HSV2BGR =54, CV_HSV2RGB =55, CV_Lab2BGR =56, CV_Lab2RGB =57, CV_Luv2BGR =58, CV_Luv2RGB =59, CV_HLS2BGR =60, CV_HLS2RGB =61, CV_BayerBG2BGR_VNG =62, CV_BayerGB2BGR_VNG =63, CV_BayerRG2BGR_VNG =64, CV_BayerGR2BGR_VNG =65, CV_BayerBG2RGB_VNG =CV_BayerRG2BGR_VNG, CV_BayerGB2RGB_VNG =CV_BayerGR2BGR_VNG, CV_BayerRG2RGB_VNG =CV_BayerBG2BGR_VNG, CV_BayerGR2RGB_VNG =CV_BayerGB2BGR_VNG, CV_BGR2HSV_FULL = 66, CV_RGB2HSV_FULL = 67, CV_BGR2HLS_FULL = 68, CV_RGB2HLS_FULL = 69, CV_HSV2BGR_FULL = 70, CV_HSV2RGB_FULL = 71, CV_HLS2BGR_FULL = 72, CV_HLS2RGB_FULL = 73, CV_LBGR2Lab = 74, CV_LRGB2Lab = 75, CV_LBGR2Luv = 76, CV_LRGB2Luv = 77, CV_Lab2LBGR = 78, CV_Lab2LRGB = 79, CV_Luv2LBGR = 80, CV_Luv2LRGB = 81, CV_BGR2YUV = 82, CV_RGB2YUV = 83, CV_YUV2BGR = 84, CV_YUV2RGB = 85, CV_BayerBG2GRAY = 86, CV_BayerGB2GRAY = 87, CV_BayerRG2GRAY = 88, CV_BayerGR2GRAY = 89, //YUV 4:2:0 formats family CV_YUV2RGB_NV12 = 90, CV_YUV2BGR_NV12 = 91, CV_YUV2RGB_NV21 = 92, CV_YUV2BGR_NV21 = 93, CV_YUV420sp2RGB = CV_YUV2RGB_NV21, CV_YUV420sp2BGR = CV_YUV2BGR_NV21, CV_YUV2RGBA_NV12 = 94, CV_YUV2BGRA_NV12 = 95, CV_YUV2RGBA_NV21 = 96, CV_YUV2BGRA_NV21 = 97, CV_YUV420sp2RGBA = CV_YUV2RGBA_NV21, CV_YUV420sp2BGRA = CV_YUV2BGRA_NV21, CV_YUV2RGB_YV12 = 98, CV_YUV2BGR_YV12 = 99, CV_YUV2RGB_IYUV = 100, CV_YUV2BGR_IYUV = 101, CV_YUV2RGB_I420 = CV_YUV2RGB_IYUV, CV_YUV2BGR_I420 = CV_YUV2BGR_IYUV, CV_YUV420p2RGB = CV_YUV2RGB_YV12, CV_YUV420p2BGR = CV_YUV2BGR_YV12, CV_YUV2RGBA_YV12 = 102, CV_YUV2BGRA_YV12 = 103, CV_YUV2RGBA_IYUV = 104, CV_YUV2BGRA_IYUV = 105, CV_YUV2RGBA_I420 = CV_YUV2RGBA_IYUV, CV_YUV2BGRA_I420 = CV_YUV2BGRA_IYUV, CV_YUV420p2RGBA = CV_YUV2RGBA_YV12, CV_YUV420p2BGRA = CV_YUV2BGRA_YV12, CV_YUV2GRAY_420 = 106, CV_YUV2GRAY_NV21 = CV_YUV2GRAY_420, CV_YUV2GRAY_NV12 = CV_YUV2GRAY_420, CV_YUV2GRAY_YV12 = CV_YUV2GRAY_420, CV_YUV2GRAY_IYUV = CV_YUV2GRAY_420, CV_YUV2GRAY_I420 = CV_YUV2GRAY_420, CV_YUV420sp2GRAY = CV_YUV2GRAY_420, CV_YUV420p2GRAY = CV_YUV2GRAY_420, //YUV 4:2:2 formats family CV_YUV2RGB_UYVY = 107, CV_YUV2BGR_UYVY = 108, //CV_YUV2RGB_VYUY = 109, //CV_YUV2BGR_VYUY = 110, CV_YUV2RGB_Y422 = CV_YUV2RGB_UYVY, CV_YUV2BGR_Y422 = CV_YUV2BGR_UYVY, CV_YUV2RGB_UYNV = CV_YUV2RGB_UYVY, CV_YUV2BGR_UYNV = CV_YUV2BGR_UYVY, CV_YUV2RGBA_UYVY = 111, CV_YUV2BGRA_UYVY = 112, //CV_YUV2RGBA_VYUY = 113, //CV_YUV2BGRA_VYUY = 114, CV_YUV2RGBA_Y422 = CV_YUV2RGBA_UYVY, CV_YUV2BGRA_Y422 = CV_YUV2BGRA_UYVY, CV_YUV2RGBA_UYNV = CV_YUV2RGBA_UYVY, CV_YUV2BGRA_UYNV = CV_YUV2BGRA_UYVY, CV_YUV2RGB_YUY2 = 115, CV_YUV2BGR_YUY2 = 116, CV_YUV2RGB_YVYU = 117, CV_YUV2BGR_YVYU = 118, CV_YUV2RGB_YUYV = CV_YUV2RGB_YUY2, CV_YUV2BGR_YUYV = CV_YUV2BGR_YUY2, CV_YUV2RGB_YUNV = CV_YUV2RGB_YUY2, CV_YUV2BGR_YUNV = CV_YUV2BGR_YUY2, CV_YUV2RGBA_YUY2 = 119, CV_YUV2BGRA_YUY2 = 120, CV_YUV2RGBA_YVYU = 121, CV_YUV2BGRA_YVYU = 122, CV_YUV2RGBA_YUYV = CV_YUV2RGBA_YUY2, CV_YUV2BGRA_YUYV = CV_YUV2BGRA_YUY2, CV_YUV2RGBA_YUNV = CV_YUV2RGBA_YUY2, CV_YUV2BGRA_YUNV = CV_YUV2BGRA_YUY2, CV_YUV2GRAY_UYVY = 123, CV_YUV2GRAY_YUY2 = 124, //CV_YUV2GRAY_VYUY = CV_YUV2GRAY_UYVY, CV_YUV2GRAY_Y422 = CV_YUV2GRAY_UYVY, CV_YUV2GRAY_UYNV = CV_YUV2GRAY_UYVY, CV_YUV2GRAY_YVYU = CV_YUV2GRAY_YUY2, CV_YUV2GRAY_YUYV = CV_YUV2GRAY_YUY2, CV_YUV2GRAY_YUNV = CV_YUV2GRAY_YUY2, // alpha premultiplication CV_RGBA2mRGBA = 125, CV_mRGBA2RGBA = 126, CV_RGB2YUV_I420 = 127, CV_BGR2YUV_I420 = 128, CV_RGB2YUV_IYUV = CV_RGB2YUV_I420, CV_BGR2YUV_IYUV = CV_BGR2YUV_I420, CV_RGBA2YUV_I420 = 129, CV_BGRA2YUV_I420 = 130, CV_RGBA2YUV_IYUV = CV_RGBA2YUV_I420, CV_BGRA2YUV_IYUV = CV_BGRA2YUV_I420, CV_RGB2YUV_YV12 = 131, CV_BGR2YUV_YV12 = 132, CV_RGBA2YUV_YV12 = 133, CV_BGRA2YUV_YV12 = 134, CV_COLORCVT_MAX = 135};■ 第四个参数，int类型的dstCn，dst中的通道数（channel number ），dstCn默认为0，示意 dst中通道数主动从src和code中获取。
示例：
//将彩色图像image1变换为灰度图像gray_image1cvtColor(image1,gray_image1,CV_RGB2GRAY);综合示例
// VS2010 + OpenCV2.4.9#include<opencv2/core/core.hpp>#include<opencv2/highgui/highgui.hpp>using namespace cv;int main( ){ Mat girl=imread("girl.jpg"); //载入图像到Mat namedWindow("girl.jpg"); imshow("girl.jpg",girl); //载入图片 Mat image= imread("11.jpg",199); //载入后先显示 namedWindow("11.jpg"); imshow("11.jpg",image); //输入一张jpg图片到工程目录下 imwrite("10.jpg",image); waitKey(); return 0;}记得帮我点赞哦！
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