OPENCV Study Notes (iv)--MAT basic image Container Mat object information header, matrix creation, deep copy, shallow copy detailed

We know that Mat is an image container class, a data structure consisting of two parts: the head of the matrix-the data stored in the space created by class objects instantiated by class mat classes---is the information of this matrix, when we use Mat object to declare class objects, It just creates a mat header and does not create a matrix, that is, we do not have space for the image that will be stored 2--matrix head-contains: the size of the matrix----such as---class mat----data members in this class rows, COLS---You can specify the size of the image 2--storage method------corresponds to---Various mat constructors 3--store address 4--and a----pointer to a matrix that----store all pixel values 2--so when you pass an image and create a copy in a program, The large overhead is caused by the matrix, not the information header. 3--OPENCV is an image processing library that includes a large number of image processing functions, and in order to solve the problem, it is often necessary to use multiple functions in the library, so it is a common thing to pass an image in a function. Also, don't forget that we're talking about a computationally large graph processing algorithm, so unless it's a last resort, We should not copy large images, because this will reduce the speed of the program 4--in order to solve this problem, OPENCV uses the---Reference counting mechanism, the idea is to let each mat object has its own information header, but share a matrix. Implemented by having the matrix pointer point to the same address. The copy constructor is only copied: the 2--matrix pointer without copying the matrix./***************************************************************************** Program function: Mat basic image Container Mat object information header, matrix body creation, deep copy, shallow copy detailed writing environment: opencv2.4.8+vs2010 location Time: Shaanxi Normal University 2016.4.2 5 Author Information: September **********************************************************************************************//****** "Header file. namespace contains section" ***********************************/#include <opencv2/highgui/highgui.hpp> #include <opencv2/core/core.hpp> #include <iostream>using namespace CV; using namespace Std; the size of the memory space occupied by the #define MAT_INFO_HEADER_SIZE "MAT Image Container class header----->" #define WINDOW_SRC_NAME "" Original image "#de Fine Window_dst_name "" Copy constructor Image "" #define WINDOW_ASSIGN_NAME "" Assignment image "" #define Window_roi_name "" ROI Original image partial Data "" # Define Window_range_name "" RANGE Specified image Data section ""/***************************************** "Main () function" ***************** /int Main (int argc,char** argv) {/***** One thing to note here is that the definition of class objects in C + + is significantly different from the definition of objects in Java: * "1" in C + +, When an object of a class is defined, it is assigned the storage space of the class---say, in C + +, when you use a class to define a class object, you actually instantiate the class---, resulting in a class of----concrete instance * "2" and Java,     The definition of the class object and the instantiation of the class to the object are performed separately: * "1" person Lili---Class object definition---opens up a four-byte space----Lili This class object is actually equivalent to an object pointer in C + +, and there is no---concrete instance of the class being generated * "2" Java can only be manually, with the new keyword to instantiate a class of objects, as follows: * lili=new person (); ****///"1" only created the information header part mat src,assign;//"2" We'll test it here, Mat. The size of the memory space occupied by the head cout<<mat_info_header_size<<sizeof (SRC) << "bytes" <<endl;    "3" here, for the matrix to open up memory space---this equivalent to---matrix Src=imread ("D:\\scenery.png", Cv_load_image_color); "4" Display picture imshow (WINDOW_SRC_NAME,SRC);//"5" Use copy constructor, copy only information header of matrix-----Typical Shallow copy Mat DST (SRC); assign=src;//"6" Displays picture Imshow ( WINDOW_DST_NAME,DST); Imshow (window_assign_name,assign);/***** "1" is known through the results of the above code. All the Mat objects end up pointing to a----data matrix that is also unique. Although their * information headers are different, the changes made to the image matrix by any object can affect other objects * "2" in fact, different mat class objects are just different ways of accessing the same data. ****//***** "1" Here is a more powerful feature: You can create information headers that reference only part of the data------image matrix. For example, to create an area of interest (ROI), you only need to create an information header with boundary information * "2" instance as follows: * Mat Dstroi (Src,rect (0,0,100,100)) * Mat dstroi_1 (Range:all () , Range (1,3)) ****///"7" uses a rectangle to define the ROI area Mat Dstroi (Src,rect (0,0,200,200));//"8" Create window + display image Namedwindow (window_roi_name , cv_window_autosize); Imshow (window_roi_name,dstroi);//"9" uses rows rows and columns cols to intercept images of the specified area of the original image//"10" The area of the specified SRC image includes all lines of the image and columns from No. 0 to 199th//"11" Mat Mat::operator (range _rowrange, range _colrange) const----created for a sub-array of SRC objects/ /new information header, below the equivalent of Src.colrange () Mat dstrange=src (Range::all (), Range (0,200)); Namedwindow (Window_range_name,cv_window_autosize); Imshow (window_range_name,dstrange);/*** "1" Now you may ask, if the matrix belongs to more than one Mat object, who is responsible for cleaning when it is not needed? The answer is: the last * object that uses it. Implemented by reference counting mechanism. Whenever someone copies a mat object's header, it increases the number of references to the matrix; Conversely, when a head is released, the count is reduced by one; When the count is zero, the matrix is cleaned up. * "2" in this method we created by way of Mat Src is a static object of the----class, in the process of running the program, such an object * occupies space allocated and the time of release is fixed ***//*** "1" but, at some point, you still want to copy the Matrix itself ( Not just information headers and matrix pointers), you can copy---functions with---deep: * Mat clone () const;* void CopyTo (outputarray m) const;* void CopyTo (Outputarray m, I  Nputarray mask) const; **/mat Dstdeep1=src.clone ();    Mat Dstdeep2;src.copyto (SRC); "12" After deep copy, then, we change again, will not affect the original image//"13" For example, we now set all the elements in the image as white//"14" To access the color image of the pixel for (int i=0;i<dstdeep1.rows;i++) {for (int j=0;j<dstdeep1.cols;j++) {dstdeep1.at<vec3b> (i,j) [0]=255;//blue channel dstdeep1.at<vec3b> (I,J) [1 ]=255;//Red channel dstdeep1.at<vec3b> (I,J) [2]=255;//Green channel}}imshow ("Original image" ", SRC); Imshow (" "Image after deep copy processing" ", DSTDEEP1 ); Waitkey (0);} Now, to summarize, we need to remember that the memory allocation for the output image in the 1--OPENCV function is automatic (if not specifically specified) when 2--uses the OpenCV C + + interface. No need to consider memory release issues 3--copy operator and copy constructor only copy---information header 4--using function clOne () or CopyTo () to copy the matrix of a pair of images 



OPENCV Study Notes (iv)--MAT basic image Container Mat object information header, matrix creation, deep copy, shallow copy detailed