【走进OpenCV】学习Opencv不得不掌握的操作

#include<opencv2\opencv.hpp>   
#include<opencv2\highgui\highgui.hpp>
using namespace std;
using namespace cv;
int main(int argc, char** argv)
{
       //这些方式都是自己拥有独立的内存空间
    Mat img1(2, 2, CV_8UC3, Scalar(0, 0, 255));
    cout << img1 << endl;
    int sz[3] = { 2,2,2 };
    Mat img2(3, sz, CV_8UC1, Scalar(0, 0, 0));
    //cout << img2 << endl;
    Mat img5;
    img5.create(4, 4, CV_8UC3);
    cout << img5 << endl;
    Mat img6 = Mat::zeros(4, 4, CV_8UC3);
    cout << img6 << endl;
    Mat img7 = img6.clone();
    cout << img7 << endl;
    Mat img8;
    img6.copyTo(img8);
    cout << img8 << endl;
    //下面都是浅拷贝，指针指向同一个实例
    Mat img9 = img8;
    Mat img10(img8);
    waitKey(0);
    return 0;
}

#include<opencv2\opencv.hpp>   
#include<opencv2\highgui\highgui.hpp>
using namespace std;
using namespace cv;
int main(int argc, char** argv)
{
    Mat image = imread("lol1.jpg", CV_LOAD_IMAGE_GRAYSCALE); //注意了，必须是载入灰度图
    if (image.empty())
    {
        cout << "read image failure" << endl;
        return -1;
    }
    // 全局二值化
    int th = 100;
    Mat global;
    threshold(image, global, th, 255, CV_THRESH_BINARY_INV);
    // 局部二值化
    int blockSize = 25;
    int constValue = 10;
    Mat local;
    adaptiveThreshold(image, local, 255, CV_ADAPTIVE_THRESH_MEAN_C, CV_THRESH_BINARY_INV, blockSize, constValue);
    imshow("全局二值化", global);
    imshow("局部二值化", local);
    waitKey(0);
    return 0;
}

#include <iostream>
#include <opencv2\opencv.hpp>
using namespace cv;
using namespace std;
int main()
{
    Mat SrcPic = imread("lena.jpg");
    imshow("Src Pic", SrcPic);
    Mat element = getStructuringElement(MORPH_RECT, Size(15, 15)); //getStructuringElement函数返回的是指定形状和尺寸的结构元素
    Mat DstPic;
    erode(SrcPic, DstPic, element); //腐蚀操作
    imshow("腐蚀效果图", DstPic);
    waitKey();
    return 0;
}

#include <iostream>
#include <opencv2\opencv.hpp>
using namespace cv;
using namespace std;
int main()
{
    Mat SrcPic = imread("lena.jpg");
    imshow("Src Pic", SrcPic);
    Mat DstPic;
    blur(SrcPic, DstPic, Size(7, 7));
    imshow("均值模糊效果图", DstPic);
    waitKey();
    return 0;
}

#include <iostream>
#include <opencv2\opencv.hpp>
using namespace cv;
using namespace std;
int main()
{
    Mat SrcPic = imread("lena.jpg");
    imshow("Src Pic", SrcPic);
    Mat DstPic, edge, grayImage;
    //创建与src同类型和同大小的矩阵
    DstPic.create(SrcPic.size(), SrcPic.type());
    //将原始图转化为灰度图
    cvtColor(SrcPic, grayImage, COLOR_BGR2GRAY);
    //先使用3*3内核来降噪
    blur(grayImage, edge, Size(3, 3));
    //运行canny算子
    Canny(edge, edge, 3, 9, 3);
    imshow("边缘提取效果", edge);
    waitKey();
    return 0;
}

#include<opencv2\opencv.hpp>   
#include<opencv2\highgui\highgui.hpp>
using namespace std;
using namespace cv;
int main()
{
    Mat img = imread("lol1.jpg");
    Mat dstImg;
    cvtColor(img, dstImg,COLOR_BGR2GRAY);//从宏名字就可以知道，是彩色图转换到灰度图
    imshow("灰度图", dstImg);
    waitKey(0);
}

#include<opencv2\opencv.hpp>   
#include<opencv2\highgui\highgui.hpp>
using namespace std;
using namespace cv;
//访问每个像素,我喜欢使用指针的方式
int main()
{
    Mat img = imread("lol1.jpg");
    for (int i = 0; i < img.rows; i++)
    {
        uchar* data = img.ptr<uchar>(i);  //获取第i行地址
        for (int j = 0; j < img.cols; j++)
        {
             printf("%d\n",data[j]);
        }
    }
    waitKey(0);
}

#include<opencv2\opencv.hpp>   
#include<opencv2\highgui\highgui.hpp>
using namespace std;
using namespace cv;
//直方图均衡化
int main()
{
    Mat img = imread("lol3.jpg");
    imshow("原始图", img);
    Mat dst;
    cvtColor(img, img, CV_RGB2GRAY);
    imshow("灰度图", img);
    equalizeHist(img, dst);
    imshow("直方图均衡化", dst);
    waitKey(0);
}

#include<opencv2\opencv.hpp>   
#include<opencv2\highgui\highgui.hpp>

using namespace std;
using namespace cv;

//常见数据结构使用方法总结
int main()
{
    //Mat的用法
    Mat m1(2, 2, CV_8UC3, Scalar(0, 0, 255)); //其中的宏的解释：CV_[位数][带符号与否][类型前缀]C[通道数]
    cout << m1 << endl;

    //或者,利用IplImage指针来初始化,将IplImage*转化为Mat
    IplImage* image = cvLoadImage("lena.jpg");
    Mat mat = cvarrToMat(image);

    //Mat转IplImage:
    IplImage img = IplImage(mat);

    //或者
    Mat m2;
    m2.create(4, 5, CV_8UC(2));


    //点的表示:Point
    Point p;
    p.x = 1; //x坐标
    p.y = 1; //y坐标

    //或者
    Point p2(1, 1);

    //颜色的表示：Scalar(b,g,r);注意不是rgb，注意对应关系
    Scalar(1, 1, 1);

    //尺寸的表示:Size
    Size(5, 5);// 宽度和高度都是5

    //矩形的表示：Rect，成员变量有x,y,width,height
    Rect r1(0, 0, 100, 60);
    Rect r2(10, 10, 100, 60);
    Rect r3 = r1 | r2; //两个矩形求交集
    Rect r4 = r1 & r2; //两个矩形求并集

    waitKey(0);

}