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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。
<!–more–>
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_image1
cvtColor(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;
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