OpenCV(4): Mat对象

注：转载请标明原文出处链接：https://xiongyiming.blog.csdn.net/article/details/106931100

1基础知识

Mat对象 OpenCV2.0之后引进的图像数据结构、自动分配内存、不存在内存泄漏的问题，是面向对象的数据结构。Mat对象分为头部 和 数据两个部分。

IplImage 是从2001年OpenCV发布之后就一直存在，是C语言风格的数据结构，需要开发者自己分配与管理内存，对大的程序使用它容易导致内存泄漏问题。IplImage从本质上讲，它是Mat对象，但它还有其他一些成员变量将矩阵解释为图像。

Mat对象构造函数有：

Mat();
Mat(int rows, int cols, int type);
Mat(Size size, int type)
Mat(int rows, int cols, int type, const Scalar $s);
Mat(int ndims, const int *sizes, int type);
Mat(int ndims, const int *sizes, int type, const Scalar &s);

Mat对象常用的函数有：

void copyTo(Mat mat);
void convertTo(Mat dst, int type);
Mat clone();
int channels();
int depth();
bool empty();
uchar* ptr(i=0);

Mat对象使用的注意事项
(1) 部分复制：一般情况下只会复制Mat对象的头部和指针部分，不会复制数据部分

Mat A= imread(imgFilePath);
Mat B(A)  // 只复制

(2) 完全复制：如果把Mat对象的头部和数据部分一起复制，可以通过如下两个代码

实现
Mat F = A.clone(); 
或 
Mat G; 
A.copyTo(G);

Mat对象使用的四个要点

1. 输出图像的内存是自动分配的；
2. 使用OpenCV的C++接口，不需要考虑内存分配问题；
3. 赋值操作和拷贝构造函数只会复制头部分；
4. 使用clone与copyTo两个函数实现数据完全复制；

2 代码示例

2.1 创建一张空白图像

代码

#include <opencv2/core/core.hpp> 
#include <opencv2/imgcodecs.hpp> 
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>

#include <iostream>
#include <math.h>




using namespace cv;
using namespace std;
int main(int argc, char** args) {
	Mat src = imread("ZXP1.jpg", IMREAD_UNCHANGED);
	if (src.empty()) {
		cout << "could not find the image resource..." << std::endl;
		return -1;
	}
	namedWindow("Original Image", CV_WINDOW_AUTOSIZE);
	imshow("Original Image", src);


	Mat dst; 
	dst = Mat(src.size(), src.type()); //或者用 dst.create(src.size(), src.type());
	dst = Scalar(255, 255, 255);
	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);


	waitKey(0);

	return 0;
}

运行结果

2.2 clone

代码

#include <opencv2/core/core.hpp> 
#include <opencv2/imgcodecs.hpp> 
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>

#include <iostream>
#include <math.h>




using namespace cv;
using namespace std;
int main(int argc, char** args) {
	Mat src = imread("ZXP1.jpg", IMREAD_UNCHANGED);
	if (src.empty()) {
		cout << "could not find the image resource..." << std::endl;
		return -1;
	}
	namedWindow("Original Image", CV_WINDOW_AUTOSIZE);
	imshow("Original Image", src);

	/*
	Mat dst; 
	dst = Mat(src.size(), src.type());
	dst = Scalar(255, 255, 255);
	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);
	*/
	Mat dst = src.clone();
	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);


	waitKey(0);

	return 0;
}

运行结果

2.3 cvtcolor

代码

#include <opencv2/core/core.hpp> 
#include <opencv2/imgcodecs.hpp> 
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>

#include <iostream>
#include <math.h>




using namespace cv;
using namespace std;
int main(int argc, char** args) {
	Mat src = imread("ZXP1.jpg", IMREAD_UNCHANGED);
	if (src.empty()) {
		cout << "could not find the image resource..." << std::endl;
		return -1;
	}
	namedWindow("Original Image", CV_WINDOW_AUTOSIZE);
	imshow("Original Image", src);

	/*
	Mat dst; 
	dst = Mat(src.size(), src.type());
	dst = Scalar(255, 255, 255);
	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);
	*/
	Mat dst; 
	src.copyTo(dst);
	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);


	waitKey(0);

	return 0;
}

运行结果

2.4 channels

代码

#include <opencv2/core/core.hpp> 
#include <opencv2/imgcodecs.hpp> 
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>

#include <iostream>
#include <math.h>




using namespace cv;
using namespace std;
int main(int argc, char** args) {
	Mat src = imread("ZXP1.jpg", IMREAD_UNCHANGED);
	if (src.empty()) {
		cout << "could not find the image resource..." << std::endl;
		return -1;
	}
	namedWindow("Original Image", CV_WINDOW_AUTOSIZE);
	imshow("Original Image", src);

	/*
	Mat dst; 
	dst = Mat(src.size(), src.type());
	dst = Scalar(255, 255, 255);
	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);
	*/
	Mat dst; 

	
	cvtColor(src, dst, CV_BGR2GRAY);
	printf("原始图像的通道数为：%d\n", src.channels());
	printf("输出图像的通道数为：%d\n", dst.channels());

	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);


	waitKey(0);

	return 0;
}

运行结果

2.5 cols、rows 和 uchar* ptr

代码

#include <opencv2/core/core.hpp> 
#include <opencv2/imgcodecs.hpp> 
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>

#include <iostream>
#include <math.h>




using namespace cv;
using namespace std;
int main(int argc, char** args) {
	Mat src = imread("ZXP1.jpg", IMREAD_UNCHANGED);
	if (src.empty()) {
		cout << "could not find the image resource..." << std::endl;
		return -1;
	}
	namedWindow("Original Image", CV_WINDOW_AUTOSIZE);
	imshow("Original Image", src);

	/*
	Mat dst; 
	dst = Mat(src.size(), src.type());
	dst = Scalar(255, 255, 255);
	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);
	*/

	Mat dst; 
	
	cvtColor(src, dst, CV_BGR2GRAY);
	printf("原始图像的通道数为：%d\n", src.channels());
	printf("输出图像的通道数为：%d\n", dst.channels());

	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);

	
	int rows = dst.rows;
	int cols = dst.cols;
	printf("rows = %d , cols = %d\n", rows, cols);

	const uchar* firstRow = dst.ptr<uchar>(0);
	printf("first pixel value = %d\n", *firstRow);

	waitKey(0);

	return 0;
}

运行结果

2.6 构建一个窗口

代码

#include <opencv2/core/core.hpp> 
#include <opencv2/imgcodecs.hpp> 
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>

#include <iostream>
#include <math.h>




using namespace cv;
using namespace std;
int main(int argc, char** args) {
	Mat src = imread("ZXP1.jpg", IMREAD_UNCHANGED);
	if (src.empty()) {
		cout << "could not find the image resource..." << std::endl;
		return -1;
	}
	namedWindow("Original Image", CV_WINDOW_AUTOSIZE);
	imshow("Original Image", src);

	/*
	Mat dst; 
	dst = Mat(src.size(), src.type());
	dst = Scalar(255, 255, 255);
	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);
	*/
	Mat dst; 

	
	cvtColor(src, dst, CV_BGR2GRAY);
	printf("原始图像的通道数为：%d\n", src.channels());
	printf("输出图像的通道数为：%d\n", dst.channels());

	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);

	
	int rows = dst.rows;
	int cols = dst.cols;
	printf("rows = %d , cols = %d\n", rows, cols);

	const uchar* firstRow = dst.ptr<uchar>(0);
	printf("first pixel value = %d\n", *firstRow);

	Mat M1(3, 3, CV_8UC3, Scalar(255, 255, 255));
	cout << "M1=" << endl << M1 << endl;


	waitKey(0);

	return 0;
}

运行结果

注意

1. 对于int类型8位，CvMat矩阵对应的参数类型为 CV_8UC1、CV_8UC2、CV_8UC3 (其中，数字1、2、3表示通道数，比如 RGB 图像有3通道，就用CV_8UC3，灰度图像就用CV_8UC1)
2. 对于float类型32位，对应CvMat数据结构参数为：CV_32FC1、CV_32FC2、CV_32FC3等；
3. 对于double 类型64位，对应CvMat数据结构参数为：CV_64FC1、CV_64FC2、CV_64FC3等。

2.7 zeros

代码

#include <opencv2/core/core.hpp> 
#include <opencv2/imgcodecs.hpp> 
#include <opencv2/opencv.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/highgui/highgui_c.h>

#include <iostream>
#include <math.h>




using namespace cv;
using namespace std;
int main(int argc, char** args) {
	Mat src = imread("ZXP1.jpg", IMREAD_UNCHANGED);
	if (src.empty()) {
		cout << "could not find the image resource..." << std::endl;
		return -1;
	}
	namedWindow("Original Image", CV_WINDOW_AUTOSIZE);
	imshow("Original Image", src);

	/*
	Mat dst; 
	dst = Mat(src.size(), src.type());
	dst = Scalar(255, 255, 255);
	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);
	*/
	Mat dst; 

	
	cvtColor(src, dst, CV_BGR2GRAY);
	printf("原始图像的通道数为：%d\n", src.channels());
	printf("输出图像的通道数为：%d\n", dst.channels());

	namedWindow("Output Image", CV_WINDOW_AUTOSIZE);
	imshow("Output Image", dst);

	

	Mat M2 = Mat::zeros(3, 3, CV_8UC1);
	cout << "M2=" << endl << M2 << endl;


	waitKey(0);

	return 0;
}

运行结果

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参考资料

[1] https://edu.51cto.com/course/7521.html?source=so