C++ opencv 学习

文章目录

1、创建窗口
2、读取图片
3、视频采集
4、Mat的使用
5、异或操作
6、通道分离，通道合并
7、色彩空间转换
8、最大值、最小值
9、绘制图像
10、多边形绘制
11、随机数
12、鼠标实时绘制矩形
13、归一化
14、resize操作
15、旋转翻转
16、视频操作
17、模糊操作
18、高斯模糊操作

1、创建窗口

c++写法：

void test2()
{
    Mat img = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    cout<<img.depth()<<" "<<img.channels()<<endl;
    namedWindow("new",cv::WINDOW_AUTOSIZE);
    imshow("new",img);
    waitKey(0);
    destroyAllWindows();
}

python写法：

def test():
    cv2.namedWindow('new', cv2.WINDOW_NORMAL)
    cv2.imshow('new', 0)
    key = cv2.waitKey(0)
    if key & 0xFF  == ord('q'):
        cv2.destroyAllWindows()

2、读取图片

c++写法，操作图像，将图像转换为hsv然后调整亮度值，转换会BGR格式显示

void test2()
{
    Mat img = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    cout<<img.depth()<<" "<<img.channels()<<endl;
    namedWindow("new",cv::WINDOW_AUTOSIZE);
    imshow("new",img);
    waitKey(0);

    Mat gray,hsv;
    cvtColor(img,gray,cv::COLOR_BGR2GRAY);
    imshow("new",gray);
    waitKey(0);

    cvtColor(img,hsv,cv::COLOR_BGR2HSV);
    imshow("new",hsv);
    waitKey(0);

    Mat channels[3];
    // 将HSV图像分离为三个单独的通道,这将把HSV图像的三个通道分别存储在channels数组的不同元素中
    split(hsv,channels);
    int bright = 50;
    channels[2] += bright;
    // 将亮度通道的像素值限制在0到255之间,大于255截断为255
    threshold(channels[2],channels[2],255,255,cv::THRESH_TRUNC);
    // 将修改后的通道合并为单个图像
    cv::merge(channels, 3, hsv);
    Mat outputImage;
    cv::cvtColor(hsv, outputImage, cv::COLOR_HSV2BGR);

    imshow("new",outputImage);
    waitKey(0);
    destroyAllWindows();
}

@param filename Name of file to be loaded.
@param flags Flag that can take values of cv::ImreadModes

CV_EXPORTS_W Mat imread( const String& filename, int flags = IMREAD_COLOR );

flags标识符介绍：
IMREAD_GRAYSCALE = 0, 灰度图
IMREAD_COLOR = 1，原本是什么颜色就显示什么颜色

def test2():
    cv2.namedWindow('new', cv2.WINDOW_AUTOSIZE)
    img = cv2.imread(img_name, 1)
    cv2.imshow('new', img)
    cv2.waitKey(0)
    cv2.destroyAllWindows()
	cv2.imwrite('1.png',img)

3、视频采集

def test3():
    # cv2.namedWindow('new', cv2.WINDOW_AUTOSIZE)
    # 获取视频设置 
    cap = cv2.VideoCapture(0)
    while True:
        ret, frame = cap.read()
        cv2.imshow('video', frame)
        key = cv2.waitKey(10)
        if (key & 0xFF) == ord('q'):
            break
    cap.release()
    cv2.destroyAllWindows()

录制视频

def test4():
    fourcc = cv2.VideoWriter_fourcc(*'MJPG')
    vw = cv2.VideoWriter('./out.mp4', fourcc, 25, (1920, 1080))
    cap = cv2.VideoCapture(0)

    # 判断摄像头是否打开状态
    while cap.isOpened():
        ret, frame = cap.read()
        if ret == True:
            cv2.imshow('video', frame)

            # 写数据到多媒体文件
            vw.write(frame)

            key = cv2.waitKey(10)
            if (key & 0xFF) == ord('q'):
                break
        else:
            break
    cap.release()
    cv2.release()
    cv2.destroyAllWindows()

在这里插入图片描述

import cv2


# 色彩空间
# hsv：色相、饱和度、明亮度
# yuv：4:2:0 4:2:2 4:4:4

def callback():
    pass

def test7():
    cv2.namedWindow('color',cv2.WINDOW_NORMAL)
    img = cv2.imread('./1.png')
    colorspaces = [cv2.COLOR_BGR2RGBA,cv2.COLOR_BGR2BRGA,
                   cv2.COLOR_BGR2GRAY,cv2.COLOR_BGR2HSV_FULLL,
                   cv2.COLOR_BGR2YUV]
    cv2.createTrackbar('curcolor','color',0,len(colorspaces),callback)
    while True:
        index = cv2.getTrackbarPos('curcolor','color')
        cvt_img = cv2.cvtColor(img,colorspaces[index])
        cv2.imshow('color',img)
        key = cv2.waitKey(10)
        if key & 0xFF == ord('q'):
            break
    cv2.destroyAllWindows()

if __name__ == '__main__':
    test7()

4、Mat的使用

深拷贝和浅拷贝

void test3()
{
    Mat img,m1,m2;
    img = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    // 克隆，深拷贝
    m1 = img.clone();
    img.copyTo(m2);

    // 创建空白图像
    Mat m3 = Mat::zeros(Size(8,8),CV_8UC1);
    // 创建全部为1的通道，如果创建的是3通道，则只有每个元素的第一个通道为1
    Mat m4 = Mat::ones(Size(8,8),CV_8UC3);
    cout<<m3.cols<<m3.rows<<m3.channels()<<endl;

    // 3通道时候：每个元素的第一个通道为1
    m4 = 127;
    // 给3个通道都复值
    m4 = Scalar(127,127,127);
}

像素值操作：
1、根据下标操作
2、根据指针操作

void test4()
{
    // 像素遍历操作
    namedWindow("new",WINDOW_NORMAL);
    Mat img,gray;
    img = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    for(int i=0;i<img.rows;i++){
        for(int j=0;j<img.cols;j++){
            Vec3b bgr = img.at<Vec3b>(i,j);
            img.at<Vec3b>(i,j)[0] = 255 - bgr[0];
            img.at<Vec3b>(i,j)[1] = 255 - bgr[1];
            img.at<Vec3b>(i,j)[2] = 255 - bgr[2];
        }
    }
    imshow("new",img);
    waitKey(0);

    cvtColor(img,gray,cv::COLOR_BGR2GRAY);
    for(int i=0;i<gray.rows;i++){
        for(int j=0;j<gray.cols;j++){
            int pt = img.at<uchar>(i,j);
            img.at<uchar>(i,j) = 255 - pt;
        }
    }
    imshow("new",gray);
    waitKey(0);

    // 基于指针访问 速度更快
    for(int i=0;i<img.rows;i++){
        uchar *current_row = img.ptr<uchar>(i);
        for(int j=0;j<img.cols;j++){
            if(img.channels() == 1){
                int pt = *current_row;
                *current_row++ = 255 - pt;
            }else if(img.channels() == 3){
                *current_row++ = 255 - *current_row;
                *current_row++ = 255 - *current_row;
                *current_row++ = 255 - *current_row;
            }
        }
    }
    destroyAllWindows();
}

像素值的加减乘除

void test5()
{
    // 像素操作
    namedWindow("new",WINDOW_NORMAL);
    Mat img,gray;
    img = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");

    Mat m = Mat::zeros(img.size(),img.type());
    m = Scalar(2,2,2);
    Mat dst;

    // 乘法运算，超过255的时候会截断
    multiply(img,m,dst);

    // 加法操作
    add(img,m,dst);

    // 减法
    subtract(img,m,dst);

    // 除法
    divide(img,m,dst);

    // saturate_cast会做一个范围判定，是否在uchar范围内
    // saturate_cast<uchar>(p1,p2);
    imshow("new",dst);
    waitKey(0);
    destroyAllWindows();
}

GUI操作

void on_trac(int val,void *userdata)
{
    Mat *data = (Mat*)userdata;
    Mat m = Mat::zeros(data->size(),data->type());
    m = Scalar(val,val,val);

    Mat dst;
    add(*data,m,dst);
    imshow("new",dst);
}

void test6()
{
    namedWindow("new",WINDOW_AUTOSIZE);
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    int maxValue = 100;
    int light = 50;
    cout<<src.type()<<endl;
    createTrackbar("Value Bar","new",&light,maxValue,on_trac,(void *)(&src));
    on_trac(50,&src);
}

addWeighted函数解释

dst = src1 * alpha + src2 * beta + gamma

5、异或操作

// 异或操作
void test7()
{
    Mat m1 = Mat::zeros(Size(255,255), CV_8UC3);
    Mat m2 = Mat::zeros(Size(255,255), CV_8UC3);
    rectangle(m1,Rect(100,100,80,80),Scalar(255,255,0),-1,LINE_8,0);
    rectangle(m2,Rect(130,130,80,80),Scalar(255,0,255),-1,LINE_8,0);
    imshow("new",m1);
    waitKey(0);
    imshow("new",m2);
    waitKey(0);

    Mat dst;
    // 按位与（都为真就为真）
    bitwise_and(m1,m2,dst);
    imshow("new",dst);
    waitKey(0);

    // 按位或（一个为真就为真）
    bitwise_or(m1,m2,dst);
    imshow("new",dst);
    waitKey(0);

    // 按位取反
    bitwise_not(m1,dst);
    imshow("new",dst);
    waitKey(0);

    // 异或（不同为真，相同为假）
    bitwise_xor(m1,m2,dst);
    imshow("new",dst);
    waitKey(0);
    destroyAllWindows();
}

6、通道分离，通道合并

// 通道分离，通道合并
void test8()
{
    namedWindow("new",WINDOW_AUTOSIZE);
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    imshow("new",src);
    waitKey(0);
    vector<Mat> mv;
    split(src,mv);
    imshow("new",mv[0]);
    waitKey(0);
    imshow("new",mv[1]);
    waitKey(0);
    imshow("new",mv[2]);
    waitKey(0);

    // 将蓝色和绿色通道全部置0，只保留红色通道，然后合并
    mv[0] = 0;
    mv[1] = 0;
    Mat dst;
    merge(mv,dst);
    imshow("new",dst);
    waitKey(0);

    // 通道融合
    // 第三个参数，0通道到2通道，1通道到1通道，2通道到0通道
    int from_to[] = {0,2,1,1,2,0};
    mixChannels(&src,1,&dst,1,from_to,3);
    imshow("new",dst);
    waitKey(0);
}

7、色彩空间转换

// 色彩空间转换
void test9()
{
    namedWindow("new",WINDOW_AUTOSIZE);
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/green.jpg");
    Mat dst,mask;
    cvtColor(src,dst,COLOR_BGR2HSV);

    // 出来一张2值化的图像，绿色背景是白色，人物是黑色
    inRange(dst,Scalar(35,43,46),Scalar(77,255,255),mask);

    Mat redback = Mat::zeros(src.size(),src.type());
    redback = Scalar(40,40,200);

    // 取放之后人物酒变成白色了,背景是黑色的
    bitwise_not(mask,mask);

    // 只拷贝不为0的区域，为0的区域不拷贝
    src.copyTo(redback,mask);
    imshow("new",redback);
    waitKey(0);
}

8、最大值、最小值

// 最大值、最小值
// 均值，方差
// 方差衡量数据集中值的离散程度，数据集中差异较小时，标准方差较小，差异较大时，方差较大(携带有效信息就越多)
// 1、计算出均值
// 2、计算每个元素与平均值的差的平方
// 3、计算平方差的平均值，得到的平方差相加，然后除以数据点的总数
// 4、取平方根：将平均平方差的值进行平方根运算，得到标准方差。

void test10()
{
    namedWindow("new",WINDOW_AUTOSIZE);
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/green.jpg",cv::IMREAD_GRAYSCALE);
    double minv,maxv;
    Point minLoc,maxLoc;
    minMaxLoc(src,&minv,&maxv,&minLoc,&maxLoc,Mat());
    cout<<"minv:"<<minv<<" maxv:"<<maxv<<" minLoc:"<<minLoc<<" maxLoc:"<<maxLoc<<endl;
    Mat mean,stddev;
    meanStdDev(src,mean,stddev);
    cout<<mean<<" "<<stddev<<endl;
}

9、绘制图像

void test11()
{
    namedWindow("new",WINDOW_AUTOSIZE);
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/green.jpg",cv::IMREAD_COLOR);
    // 绘制矩形
    Mat bg = Mat::zeros(src.size(),src.type());
    Mat dst;
    Rect rect(100,100,200,200);
    rectangle(bg,rect,Scalar(20,20,255),2,LINE_8,0);

    // 绘制圆，圆心坐标Point，15是半径
    circle(src,Point(350,400),150,Scalar(255,0,0),2,LINE_8,0);
    // 图像融合
    addWeighted(src,0.7,bg,0.3,0,dst);

    // 绘制线 两个点的位置
    line(bg,Point(100,100),Point(350,400),Scalar(0,255,0),2,LINE_8,0);

    // 绘制椭圆
    RotatedRect rrt;
    rrt.center = Point(200,200);
    rrt.size = Size(100,200);
    rrt.angle = 0;
    ellipse(src,rrt,Scalar(0,255,255),2,8);
    imshow("new",dst);
    waitKey(0);
}

10、多边形绘制

// 多边形绘制
void test13()
{
    Mat bg = Mat::zeros(Size(512,512),CV_8UC3);
    Point p1(100,200);
    Point p2(350,100);
    Point p3(450,280);
    Point p4(320,450);
    Point p5(80,400);
    vector<Point> pts;
    pts.push_back(p1);
    pts.push_back(p2);
    pts.push_back(p3);
    pts.push_back(p4);
    pts.push_back(p5);
    polylines(bg,pts, true,Scalar(0,0,255),2,LINE_8,0);
    // 填充多边形
//    fillPoly()
    imshow("new",bg);
    waitKey(0);
}

11、随机数

void test12()
{
    Mat bg = Mat::zeros(Size(512,512),CV_8UC3);
    int w = bg.cols;
    int h = bg.rows;
    // 随机数
    RNG rng(12345);
    while (true){
        int c = waitKey(10);
        if(c == 27) break;
        int x1 = rng.uniform(0,w);
        int y1 = rng.uniform(0,h);
        int x2 = rng.uniform(0,w);
        int y2 = rng.uniform(0,h);
        // 每次画之前清理一下
        bg = Scalar(0,0,0);
        line(bg,Point(x1,y1),Point(x2,y2),
             Scalar(rng.uniform(0,255)
             ,rng.uniform(0,255),rng.uniform(0,255)),1,LINE_AA,0);
        imshow("new",bg);
    }
}

12、鼠标实时绘制矩形

Point sp(-1, -1);
Point ed(-1, -1);
Mat temp;

static void on_draw(int event, int x, int y, int flags, void* userdata)
{
    Mat img = *((Mat*)userdata);
    if (event == EVENT_LBUTTONDOWN) {
        sp.x = x;
        sp.y = y;
        cout << "sp.x:" << sp.x << " sp.y:" << sp.y << endl;
    }
    else if (event == EVENT_LBUTTONUP) {
        ed.x = x;
        ed.y = y;
        cout << "ed.x:" << ed.x << " ed.y:" << ed.y << endl;
        int x1 = x - sp.x;
        int y1 = y - sp.y;
        if (x1 > 0 && y1 > 0) {
            Rect rect(sp.x, sp.y, x1, y1);
            temp.copyTo(img);
            imshow("ROI区域", img(rect));
            rectangle(img,rect,Scalar(0,0,255),2,8,0);
            imshow("new", img);
            sp.x = -1;
            sp.y = -1;
        }
    }
    else if (event == EVENT_MOUSEMOVE) {
        if (sp.x > 0 && sp.y > 0) {
            ed.x = x;
            ed.y = y;
            int dx = ed.x - sp.x;
            int dy = ed.y - sp.y;
            if (dx > 0 && dy > 0) {
                Rect box(sp.x, sp.y, dx, dy);
                temp.copyTo(img);
                rectangle(img, box, Scalar(0, 0, 255), 2, 8, 0);
                imshow("new", img);
            }
        }
    }
}

void test14()
{
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    namedWindow("new", WINDOW_AUTOSIZE);
    setMouseCallback("new", on_draw, (void*)&src);
    src.copyTo(temp);
    imshow("new", src);
    waitKey(0);
    destroyAllWindows();
}

13、归一化

// 1、MINMAX
void test15()
{
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    namedWindow("new", WINDOW_AUTOSIZE);

    Mat img,img2;
    cout<<src.type()<<endl;
    src.convertTo(src,CV_32FC3);
    cout<<src.type()<<endl;

    normalize(src,img,1.0,0,NORM_MINMAX);
    // imshow想显示浮点数据，必须归一化0-1之间
    imshow("new",img);
    normalize(img,img2,255.0,0,NORM_MINMAX);
    img2.convertTo(img2,CV_8UC3);
    imshow("new1",img2);
    waitKey(0);
}

14、resize操作

// resize
void test16()
{
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    namedWindow("new", WINDOW_AUTOSIZE);

    Mat zoomin,zoomout;
    int w = src.cols;
    int h = src.rows;
    resize(src,zoomin,Size(w/2,h/2),0,0,INTER_LINEAR);
    resize(src,zoomout,Size(w*1.5,h*1.5),0,0,INTER_LINEAR);
    imshow("1",src);
    imshow("2",zoomin);
    imshow("3",zoomout);
    waitKey(0);
}

15、旋转翻转

void test17()
{
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
//    namedWindow("new", WINDOW_AUTOSIZE);
    Mat dst,left,m1,m3;
    flip(src,dst,0);
    flip(src,left,1);
    flip(src,m1,-1);
    imshow("上下翻转",dst);
    imshow("左右翻转",left);
    imshow("180度旋转",m1);
    waitKey(0);

    // 图像旋转
    Mat d,M;
    int w = src.cols;
    int h = src.rows;
    M = getRotationMatrix2D(Point2f(w/2,h/2),45,1.0);
    double cos = abs(M.at<double>(0,0));
    double sin = abs(M.at<double>(0,1));

    int nw = cos * w + sin * h;
    int nh = sin * w + cos * h;
    M.at<double>(0,2) += (nw/2-w/2);
    M.at<double>(1,2) += (nh/2-h/2);
    warpAffine(src,d,M,Size(nw,nh),INTER_LINEAR,0,Scalar(0,0,255));
    imshow("new",d);
    waitKey(0);
}

16、视频操作


void test18()
{
    VideoCapture cap(0);
    Mat fram;
    while(true){
        cap.read(fram);
        if(fram.empty()){
            break;
        }
        flip(fram,fram,1);
        imshow("new",fram);
        int n = waitKey(10);
        if(n == 27){
            break;
        }
    }
    cap.release();
}

17、模糊操作

// 图像卷积模糊操作
void test19()
{
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    namedWindow("new", WINDOW_AUTOSIZE);
    Mat dst;
    blur(src,dst,Size(3,3),Point(-1,-1));
    imshow("new",dst);
    waitKey(0);
}

18、高斯模糊操作

// 高斯双边模糊
void test21()
{
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    namedWindow("new", WINDOW_AUTOSIZE);
    Mat dst;
    bilateralFilter(src,dst,0,100,10);
    imshow("new",dst);
    waitKey(0);
}

// 高斯模糊
void test20()
{
    Mat src = imread("/Users/zhulei/CLionProjects/opencv_test/1.jpg");
    namedWindow("new", WINDOW_AUTOSIZE);
    Rect rect(100,100,500,500);
    Mat roi = src(rect);
    GaussianBlur(roi,roi,Size(0,0),15);
    roi.copyTo(src(rect));
    imshow("new",src);
    waitKey(0);
}