正文之前

虽然三天后就是毕业答辩的日子了。但是我仍然在这个时候保持着优秀的作死精神！！居然今天花了起码三个小时看OpenCV。。。。。而且居然还看出了不少东西。。下面放放我今天学的东西

正文

//##########################打开摄像头##########################
#include <iostream>
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;

int main() {
    VideoCapture cap(0);
    if(!cap.isOpened()){
        return -1;
    }
    Mat frame;
    Mat edges;
    bool stoped = false;
    while (!stoped){
        cap>>frame;
        cvtColor(frame, edges, CV_BGR2GRAY);
//        GaussianBlur(edges, edges, Size(7,7), 1.5, 1.5);
//        Canny(edges, edges, 0, 30 ,0);
        imshow("The Video Now!", frame);
        if(waitKey(10) >=0 ){
            stoped = true;
        }
    }
    return 0;
}

//##########################打开摄像头##########################

这个是打开摄像头的~ ，效果如图

人脸识别这个有点问题。。而且还要两个很长的辅助文件。。大家伙自己去玩吧。。。我就不奉陪了。。

//##########################人脸识别##########################
//#include "opencv2/objdetect.hpp"
//#include "opencv2/highgui.hpp"
//#include "opencv2/imgproc.hpp"
//
//#include <stdio.h>
//
//using namespace std;
//using namespace cv;
//
///** Function Headers */
//void detectAndDisplay( Mat frame );
//
///** Global variables */
//String face_cascade_name, eyes_cascade_name;
//CascadeClassifier face_cascade;
//CascadeClassifier eyes_cascade;
//String window_name = "Capture - Face detection";
//
///** @function main */
//int main( int argc, const char** argv )
//{
//    CommandLineParser parser(argc, argv,
//                             "{help h||}"
//                                     "{face_cascade|haarcascade_frontalface_alt.xml|}"
//                                     "{eyes_cascade|haarcascade_eye_tree_eyeglasses.xml|}");
//
//    parser.about( "\nThis program demonstrates using the cv::CascadeClassifier class to detect objects (Face + eyes) in a video stream.\n"
//                          "You can use Haar or LBP features.\n\n" );
//    parser.printMessage();
//
//    face_cascade_name = parser.get<String>("face_cascade");
//    eyes_cascade_name = parser.get<String>("eyes_cascade");
//    VideoCapture capture;
//    Mat frame;
//
//    //-- 1. Load the cascades
//    if( !face_cascade.load( face_cascade_name ) ){ printf("--(!)Error loading face cascade\n"); return -1; };
//    if( !eyes_cascade.load( eyes_cascade_name ) ){ printf("--(!)Error loading eyes cascade\n"); return -1; };
//
//    //-- 2. Read the video stream
//    capture.open( 0 );
//    if ( ! capture.isOpened() ) { printf("--(!)Error opening video capture\n"); return -1; }
//
//    while ( capture.read(frame) )
//    {
//        if( frame.empty() )
//        {
//            printf(" --(!) No captured frame -- Break!");
//            break;
//        }
//
//        //-- 3. Apply the classifier to the frame
//        detectAndDisplay( frame );
//
//        if( waitKey(10) == 27 ) { break; } // escape
//    }
//    return 0;
//}
//
///** @function detectAndDisplay */
//void detectAndDisplay( Mat frame )
//{
//    std::vector<Rect> faces;
//    Mat frame_gray;
//
//    cvtColor( frame, frame_gray, COLOR_BGR2GRAY );
//    equalizeHist( frame_gray, frame_gray );
//
//    //-- Detect faces
//    face_cascade.detectMultiScale( frame_gray, faces, 1.1, 2, 0|CASCADE_SCALE_IMAGE, Size(60, 60) );
//
//    for ( size_t i = 0; i < faces.size(); i++ )
//    {
//        Point center( faces[i].x + faces[i].width/2, faces[i].y + faces[i].height/2 );
//        ellipse( frame, center, Size( faces[i].width/2, faces[i].height/2 ), 0, 0, 360, Scalar( 255, 0, 255 ), 4, 8, 0 );
//
//        Mat faceROI = frame_gray( faces[i] );
//        std::vector<Rect> eyes;
//
//        //-- In each face, detect eyes
//        eyes_cascade.detectMultiScale( faceROI, eyes, 1.1, 2, 0 |CASCADE_SCALE_IMAGE, Size(30, 30) );
//
//        for ( size_t j = 0; j < eyes.size(); j++ )
//        {
//            Point eye_center( faces[i].x + eyes[j].x + eyes[j].width/2, faces[i].y + eyes[j].y + eyes[j].height/2 );
//            int radius = cvRound( (eyes[j].width + eyes[j].height)*0.25 );
//            circle( frame, eye_center, radius, Scalar( 255, 0, 0 ), 4, 8, 0 );
//        }
//    }
//    //-- Show what you got
//    imshow( window_name, frame );
//}

//##########################打开摄像头##########################

//##########################追踪点##########################

#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"

#include <iostream>
#include <ctype.h>

using namespace cv;
using namespace std;

static void help()
{
    // print a welcome message, and the OpenCV version
    cout << "\nThis is a demo of Lukas-Kanade optical flow lkdemo(),\n"
            "Using OpenCV version " << CV_VERSION << endl;
    cout << "\nIt uses camera by default, but you can provide a path to video as an argument.\n";
    cout << "\nHot keys: \n"
            "\tESC - quit the program\n"
            "\tr - auto-initialize tracking\n"
            "\tc - delete all the points\n"
            "\tn - switch the \"night\" mode on/off\n"
            "To add/remove a feature point click it\n" << endl;
}

Point2f point;
bool addRemovePt = false;

static void onMouse( int event, int x, int y, int /*flags*/, void* /*param*/ )
{
    if( event == EVENT_LBUTTONDOWN )
    {
        point = Point2f((float)x, (float)y);
        addRemovePt = true;
    }
}

int main( int argc, char** argv )
{
    VideoCapture cap;
    TermCriteria termcrit(TermCriteria::COUNT|TermCriteria::EPS,20,0.03);
    Size subPixWinSize(10,10), winSize(31,31);

    const int MAX_COUNT = 500;
    bool needToInit = false;
    bool nightMode = false;

    help();
    cv::CommandLineParser parser(argc, argv, "{@input|0|}");
    string input = parser.get<string>("@input");

    if( input.size() == 1 && isdigit(input[0]) )
        cap.open(input[0] - '0');
    else
        cap.open(input);

    if( !cap.isOpened() )
    {
        cout << "Could not initialize capturing...\n";
        return 0;
    }

    namedWindow( "LK Demo", 1 );
    setMouseCallback( "LK Demo", onMouse, 0 );

    Mat gray, prevGray, image, frame;
    vector<Point2f> points[2];

    for(;;)
    {
        cap >> frame;
        if( frame.empty() )
            break;

        frame.copyTo(image);
        cvtColor(image, gray, COLOR_BGR2GRAY);

        if( nightMode )
            image = Scalar::all(0);

        if( needToInit )
        {
            // automatic initialization
            goodFeaturesToTrack(gray, points[1], MAX_COUNT, 0.01, 10, Mat(), 3, 3, 0, 0.04);
            cornerSubPix(gray, points[1], subPixWinSize, Size(-1,-1), termcrit);
            addRemovePt = false;
        }
        else if( !points[0].empty() )
        {
            vector<uchar> status;
            vector<float> err;
            if(prevGray.empty())
                gray.copyTo(prevGray);
            calcOpticalFlowPyrLK(prevGray, gray, points[0], points[1], status, err, winSize,
                                 3, termcrit, 0, 0.001);
            size_t i, k;
            for( i = k = 0; i < points[1].size(); i++ )
            {
                if( addRemovePt )
                {
                    if( norm(point - points[1][i]) <= 5 )
                    {
                        addRemovePt = false;
                        continue;
                    }
                }

                if( !status[i] )
                    continue;

                points[1][k++] = points[1][i];
                circle( image, points[1][i], 3, Scalar(0,255,0), -1, 8);
            }
            points[1].resize(k);
        }

        if( addRemovePt && points[1].size() < (size_t)MAX_COUNT )
        {
            vector<Point2f> tmp;
            tmp.push_back(point);
            cornerSubPix( gray, tmp, winSize, Size(-1,-1), termcrit);
            points[1].push_back(tmp[0]);
            addRemovePt = false;
        }

        needToInit = false;
        imshow("LK Demo", image);

        char c = (char)waitKey(10);
        if( c == 27 )
            break;
        switch( c )
        {
            case 'r':
                needToInit = true;
                break;
            case 'c':
                points[0].clear();
                points[1].clear();
                break;
            case 'n':
                nightMode = !nightMode;
                break;
        }

        std::swap(points[1], points[0]);
        cv::swap(prevGray, gray);
    }

    return 0;
}

//##########################追踪点##########################

算了。怕卵子哦。。男生没什么好扭扭捏捏的。。。我就长这样。。。

#include <opencv2/core/utility.hpp>
#include "opencv2/video/tracking.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"

#include <iostream>
#include <ctype.h>

using namespace cv;
using namespace std;

Mat image;

bool backprojMode = false;
bool selectObject = false;
int trackObject = 0;
bool showHist = true;
Point origin;
Rect selection;
int vmin = 10, vmax = 256, smin = 30;

// User draws box around object to track. This triggers CAMShift to start tracking
static void onMouse( int event, int x, int y, int, void* )
{
    if( selectObject )
    {
        selection.x = MIN(x, origin.x);
        selection.y = MIN(y, origin.y);
        selection.width = std::abs(x - origin.x);
        selection.height = std::abs(y - origin.y);

        selection &= Rect(0, 0, image.cols, image.rows);
    }

    switch( event )
    {
        case EVENT_LBUTTONDOWN:
            origin = Point(x,y);
            selection = Rect(x,y,0,0);
            selectObject = true;
            break;
        case EVENT_LBUTTONUP:
            selectObject = false;
            if( selection.width > 0 && selection.height > 0 )
                trackObject = -1;   // Set up CAMShift properties in main() loop
            break;
    }
}

string hot_keys =
        "\n\nHot keys: \n"
                "\tESC - quit the program\n"
                "\tc - stop the tracking\n"
                "\tb - switch to/from backprojection view\n"
                "\th - show/hide object histogram\n"
                "\tp - pause video\n"
                "To initialize tracking, select the object with mouse\n";

static void help()
{
    cout << "\nThis is a demo that shows mean-shift based tracking\n"
            "You select a color objects such as your face and it tracks it.\n"
            "This reads from video camera (0 by default, or the camera number the user enters\n"
            "Usage: \n"
            "   ./camshiftdemo [camera number]\n";
    cout << hot_keys;
}

const char* keys =
        {
                "{help h | | show help message}{@camera_number| 0 | camera number}"
        };

int main( int argc, const char** argv )
{
    VideoCapture cap;
    Rect trackWindow;
    int hsize = 16;
    float hranges[] = {0,180};
    const float* phranges = hranges;
    CommandLineParser parser(argc, argv, keys);
    if (parser.has("help"))
    {
        help();
        return 0;
    }
    int camNum = parser.get<int>(0);
    cap.open(camNum);

    if( !cap.isOpened() )
    {
        help();
        cout << "***Could not initialize capturing...***\n";
        cout << "Current parameter's value: \n";
        parser.printMessage();
        return -1;
    }
    cout << hot_keys;
    namedWindow( "Histogram", 0 );
    namedWindow( "CamShift Demo", 0 );
    setMouseCallback( "CamShift Demo", onMouse, 0 );
    createTrackbar( "Vmin", "CamShift Demo", &vmin, 256, 0 );
    createTrackbar( "Vmax", "CamShift Demo", &vmax, 256, 0 );
    createTrackbar( "Smin", "CamShift Demo", &smin, 256, 0 );

    Mat frame, hsv, hue, mask, hist, histimg = Mat::zeros(200, 320, CV_8UC3), backproj;
    bool paused = false;

    for(;;)
    {
        if( !paused )
        {
            cap >> frame;
            if( frame.empty() )
                break;
        }

        frame.copyTo(image);

        if( !paused )
        {
            cvtColor(image, hsv, COLOR_BGR2HSV);

            if( trackObject )
            {
                int _vmin = vmin, _vmax = vmax;

                inRange(hsv, Scalar(0, smin, MIN(_vmin,_vmax)),
                        Scalar(180, 256, MAX(_vmin, _vmax)), mask);
                int ch[] = {0, 0};
                hue.create(hsv.size(), hsv.depth());
                mixChannels(&hsv, 1, &hue, 1, ch, 1);

                if( trackObject < 0 )
                {
                    // Object has been selected by user, set up CAMShift search properties once
                    Mat roi(hue, selection), maskroi(mask, selection);
                    calcHist(&roi, 1, 0, maskroi, hist, 1, &hsize, &phranges);
                    normalize(hist, hist, 0, 255, NORM_MINMAX);

                    trackWindow = selection;
                    trackObject = 1; // Don't set up again, unless user selects new ROI

                    histimg = Scalar::all(0);
                    int binW = histimg.cols / hsize;
                    Mat buf(1, hsize, CV_8UC3);
                    for( int i = 0; i < hsize; i++ )
                        buf.at<Vec3b>(i) = Vec3b(saturate_cast<uchar>(i*180./hsize), 255, 255);
                    cvtColor(buf, buf, COLOR_HSV2BGR);

                    for( int i = 0; i < hsize; i++ )
                    {
                        int val = saturate_cast<int>(hist.at<float>(i)*histimg.rows/255);
                        rectangle( histimg, Point(i*binW,histimg.rows),
                                   Point((i+1)*binW,histimg.rows - val),
                                   Scalar(buf.at<Vec3b>(i)), -1, 8 );
                    }
                }

                // Perform CAMShift
                calcBackProject(&hue, 1, 0, hist, backproj, &phranges);
                backproj &= mask;
                RotatedRect trackBox = CamShift(backproj, trackWindow,
                                                TermCriteria( TermCriteria::EPS | TermCriteria::COUNT, 10, 1 ));
                if( trackWindow.area() <= 1 )
                {
                    int cols = backproj.cols, rows = backproj.rows, r = (MIN(cols, rows) + 5)/6;
                    trackWindow = Rect(trackWindow.x - r, trackWindow.y - r,
                                       trackWindow.x + r, trackWindow.y + r) &
                                  Rect(0, 0, cols, rows);
                }

                if( backprojMode )
                    cvtColor( backproj, image, COLOR_GRAY2BGR );
                ellipse( image, trackBox, Scalar(0,0,255), 3, LINE_AA );
            }
        }
        else if( trackObject < 0 )
            paused = false;

        if( selectObject && selection.width > 0 && selection.height > 0 )
        {
            Mat roi(image, selection);
            bitwise_not(roi, roi);
        }

        imshow( "CamShift Demo", image );
        imshow( "Histogram", histimg );

        char c = (char)waitKey(10);
        if( c == 27 )
            break;
        switch(c)
        {
            case 'b':
                backprojMode = !backprojMode;
                break;
            case 'c':
                trackObject = 0;
                histimg = Scalar::all(0);
                break;
            case 'h':
                showHist = !showHist;
                if( !showHist )
                    destroyWindow( "Histogram" );
                else
                    namedWindow( "Histogram", 1 );
                break;
            case 'p':
                paused = !paused;
                break;
            default:
                ;
        }
    }

    return 0;
}

物体追踪。。这个比较蠢。。

//##########################图片混合##########################
#include <iostream>
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;

int main() {
    Mat image = imread("/Users/zhangzhaobo/CLionProjects/CDB/kate.jpg");
    Mat logo = imread("/Users/zhangzhaobo/CLionProjects/CDB/miaomiao.jpg");

    Mat imageROI;
    imageROI = image(Range(350,350+logo.rows), Range(600,600+logo.cols));
    addWeighted(imageROI, 0.3, logo, 1, 0, imageROI);

    namedWindow("[3] Mix");
    imshow("[3] Mix", image);

    Vec3f intensity=image.at<Vec3f>(100,20);
    cout<<intensity[0]<<"->"<<intensity[1]<<"->"<<intensity[2]<<endl;
    imwrite("/Users/zhangzhaobo/CLionProjects/CDB/Mix.jpg", image);
    waitKey();
    return 0;
}

//##########################图片混合##########################

下面是图片混合。。。还蛮好用的。。

//##########################反色处理##########################

#include <iostream>
#include <opencv2/opencv.hpp>

using namespace cv;
using namespace std;
int main(int argc, char** args)
{
    Mat image = imread("/Users/zhangzhaobo/CLionProjects/CDB/miaomiao.jpg");
    if (image.empty())
    {
        cout << "不能加载图像..." << std::endl;
        return -1;
    }

    Mat dst;
    cvtColor(image, dst, CV_BGR2GRAY);

    int height = image.rows;
    int width = image.cols;
    int channels = image.channels();
    printf("height=%d,width=%d channels=%d",height,width,channels);


    for (int row = 0; row < height;row++)
    {
        for (int col = 0; col < width;col++)
        {
            if (channels==3)
            {
//                image.at<Vec3b>(row, col)[0] = 0;//blue 通道
//                image.at<Vec3b>(row, col)[1] = 0;//green 通道
//                image.at<Vec3b>(row, col)[2] = 255 - image.at<Vec3b>(row, col)[2];// red 通道

//                image.at<Vec3b>(row, col)[0] = 255 - image.at<Vec3b>(row, col)[0];//blue 通道
//                image.at<Vec3b>(row, col)[1] = 255 - image.at<Vec3b>(row, col)[1];//green 通道
//                image.at<Vec3b>(row, col)[2] = 255 - image.at<Vec3b>(row, col)[2];// red 通道

//                image.at<Vec3b>(row, col)[0] = 0;//blue 通道
//                image.at<Vec3b>(row, col)[1] = 255 - image.at<Vec3b>(row, col)[1];//green 通道
//                image.at<Vec3b>(row, col)[2] = 0;// red 通道


                image.at<Vec3b>(row, col)[0] = 255 - image.at<Vec3b>(row, col)[0];//blue 通道
                image.at<Vec3b>(row, col)[1] = 0;//green 通道
                image.at<Vec3b>(row, col)[2] = 0;// red 通道

            }
            //else if (channels==1)
            //{
            //  dst.at<uchar>(row, col) = 255 - dst.at<uchar>(row, col);
            //}
        }
    }
    namedWindow("输出图像-2", CV_WINDOW_AUTOSIZE);
    imshow("输出图像-2", image);
    waitKey(0);
    return 0;
}

//##########################反色处理##########################

这个是通道。也可以用来反相。随便你设置吧。

#include <iostream>
#include <opencv2/opencv.hpp>

#define WINDOW_NAME "【程序窗口】"
using namespace cv;
using namespace std;


void on_MouseHandle(int event, int x, int y, int flags, void * param);
void DrawRectangle(Mat & img, Rect box);
void ShowHelpText();

Rect g_rectangle;
bool g_bDrawingBox = false;
RNG g_rng(12345);

int main(int argc, char ** argv)
{
    Rect g_rectangle = Rect(-1,-1,0,0);
    Mat srcImage(600,800,CV_8UC3),tempIamge;
    srcImage.copyTo(tempIamge);
    g_rectangle = Rect(-1,-1,0,0);
    srcImage = Scalar::all(0);

    namedWindow(WINDOW_NAME);
    setMouseCallback(WINDOW_NAME,on_MouseHandle,(void *) &srcImage);

    while(true)
    {
        srcImage.copyTo(tempIamge);
        if (g_bDrawingBox)
        {
            DrawRectangle(tempIamge,g_rectangle);
        }
        imshow(WINDOW_NAME, tempIamge);
        if (waitKey(10)==27) break;
    }
    return 0;
}


void on_MouseHandle(int event, int x, int y, int flags, void * param)
{
    Mat & image = *(Mat *)param;
    switch(event)
    {
        case EVENT_MOUSEMOVE:
        {
            if (g_bDrawingBox)
            {
                g_rectangle.width = x - g_rectangle.x;
                g_rectangle.height = y - g_rectangle.y;
            }
            break;
        }
        case EVENT_LBUTTONDOWN:
        {
            g_bDrawingBox =true;
            g_rectangle = Rect(x,y,0,0);
            break;
        }
        case EVENT_LBUTTONUP:
        {
            g_bDrawingBox = false;
            if (g_rectangle.width < 0)
            {
                g_rectangle.x += g_rectangle.width;
                g_rectangle.width *= -1;
            }
            if (g_rectangle.height < 0)
            {
                g_rectangle.y += g_rectangle.height;
                g_rectangle.height *= -1;
            }
            DrawRectangle(image, g_rectangle);
            break;
        }
    }
}

void DrawRectangle(Mat & img, Rect box)
{
    rectangle(img, box.tl(), box.br(),Scalar(g_rng.uniform(0,255),g_rng.uniform(0,255),g_rng.uniform(0,255)));
}

最后是鼠标追踪。。。这个很好玩。。基本可实现画矩形的需求。。。当然，后续可以开发一个画图软件。。。不过。。。算了。不干了。。重复性工作。。

正文之后

OK！写完跑步去咯~ 对了今天还做了一个python的画图的动画。。给你看看~

曲线拟合动画