OpenCV 中的 Mat 类 (c++)

Question

根据opencv文档Mat类被描述为：Mat基本上是一个具有两个数据部分的类：矩阵头（包含诸如矩阵大小、用于存储的方法、存储矩阵的地址等信息） on) 指向包含像素值的矩阵的指针

有人可以帮助理解该标头是什么以及该类是如何声明的吗？

Answer 1

根据OpenCV 2.4.xxx：

Mat基本上是a class with two data parts：（the matrix header包含诸如矩阵大小、用于存储的方法、存储矩阵的地址等信息）和a pointer to the matrix containing the pixel values（根据选择的存储方法采用任何维度）。然而matrix header size is constant，矩阵本身的大小可能因图像而异，并且通常要大几个数量级。

一个简单的公式：a Mat object= the matrix header+ the matrix data pointer。

好吧，什么是矩阵数据指针？它是uchar* data，指向矩阵数据。

然后所有其他人都在cv::Mat打电话matrix header。

两部分的优点是什么？我们可以对矩阵进行浅复制，并使用引用计数器进行内存管理。至于引用计数器（计数），它是编程中的一个重要主题。来自维基参考计数器（计数）：In computer science, reference counting is a technique of storing the number of references, pointers, or handles to a resource such as an object, block of memory, disk space or other resource.

您可能对参考计数器中有两个重要功能cv::Mat感兴趣：

void cv::Mat::addref() 和 void cv::Mat::release()

/** @brief Increments the reference counter.
The method increments the reference counter associated with the matrix data. If the matrix header
points to an external data set (see Mat::Mat ), the reference counter is NULL, and the method has no
effect in this case. Normally, to avoid memory leaks, the method should not be called explicitly. It
is called implicitly by the matrix assignment operator. The reference counter increment is an atomic
operation on the platforms that support it. Thus, it is safe to operate on the same matrices
asynchronously in different threads.
 */
void addref();

/** @brief Decrements the reference counter and deallocates the matrix if needed.
The method decrements the reference counter associated with the matrix data. When the reference
counter reaches 0, the matrix data is deallocated and the data and the reference counter pointers
are set to NULL's. If the matrix header points to an external data set (see Mat::Mat ), the
reference counter is NULL, and the method has no effect in this case.
This method can be called manually to force the matrix data deallocation. But since this method is
automatically called in the destructor, or by any other method that changes the data pointer, it is
usually not needed. The reference counter decrement and check for 0 is an atomic operation on the
platforms that support it. Thus, it is safe to operate on the same matrices asynchronously in
different threads.
 */
void release();

当然，也许你只需要注意：

cv::Mat a = cv::Mat::zeros(2,2,CV_8UC1);
cv::Mat b,c;

b = a;       // shallow copy, share the same matrix data by the data pointer
a.copyTo(c); // deep copy, allocate matrix data memory, and assign the new pointer 

演示：

#include <opencv2/opencv.hpp>
using namespace std;
using namespace cv;

int main(){
    cv::Mat a = cv::Mat::zeros(2,2,CV_8UC1);
    cv::Mat b,c;

    b = a;       // shallow copy, share the same matrix data pointer
    a.copyTo(c); // deep copy, allocate matrix data memory, and assign the new pointer

    std::cout << "----- a -----\n" << a << "\n----- b -----\n" << b << "\n----- c -----\n" << c << std::endl;


    std::cout << "\nModify a, b, c:\n";
    a.at<unsigned char>(0,0) = 1; // a, b share the same matrix data
    b.at<unsigned char>(1,0) = 2;
    c.at<unsigned char>(1,1) = 3; // c has independent matrix data

    std::cout << "----- a -----\n" << a << "\n----- b -----\n" << b << "\n----- c -----\n" << c << std::endl;


    return 0;

}

结果：

----- a -----
[  0,   0;
   0,   0]
----- b -----
[  0,   0;
   0,   0]
----- c -----
[  0,   0;
   0,   0]

Modify a, b, c:
----- a -----
[  1,   0;
   2,   0]
----- b -----
[  1,   0;
   2,   0]
----- c -----
[  0,   0;
   0,   3]