1. /*-------------全局变量----------------*/
    2. int value;
    3. void callBack(int, void*);
    4. Mat img1, img2;
    5. /*--------------主函数-----------------*/
    6. int main()
    7. {
    8.     system("color F0");
    9.     ReadMat(img1, "D:/OpenCV/watch.jpg");
    10.     value = 100;
    11.     namedWindow("改变亮度");
    12.     createTrackbar("亮度值百分比", "改变亮度", &value, 600, callBack, 0);
    13.     waitKey(0);
    14.     return 0;
    16. }
    20. /*-------------函数实现----------------*/
    21. static void callBack(int, void*)
    22. {
    23.     float a = value / 100.0;
    24.     img2 = img1 * a;
    25.     imshow("改变亮度", img2);
    26. }
    2. #define WINDOW "原图"
    5. /*-------------全局变量----------------*/
    7. Mat g_srcImage, g_dstImage;
    8. Point previousPoint;
    9. bool P = false;
    10. void On_mouse(int event, int x, int y, int flags, void*);
    11. /*--------------主函数-----------------*/
    12. int main()
    13. {
    14.     system("color F0");
    15.     Mat img1,sobel,scharr,canny,laplace;
    16.     ReadMat(g_srcImage, "D:/OpenCV/ycy2.jpg");
    17.     imshow(WINDOW, g_srcImage);
    18.     setMouseCallback(WINDOW, On_mouse, 0);
    19.     waitKey(0);
    20.     return 0;
    22. }
    26. /*-------------函数实现----------------*/
    27. void On_mouse(int event, int x, int y, int flags, void*)
    28. {
    29.     switch (event)
    30.     {
    31.     case EVENT_LBUTTONUP:
    32.     {
    33.         P = false;
    34.     }
    35.     break;
    36.     case EVENT_LBUTTONDOWN:
    37.     {
    39.         previousPoint = Point(x, y);
    41.         P = true;
    42.     }
    43.     break;
    45.     case EVENT_MOUSEMOVE:
    46.     {
    47.         if (P)
    48.         {
    49.             Point pt(x, y);
    50.             line(g_srcImage, previousPoint, pt, Scalar(0, 0, 255), 2, 5, 0);
    51.             previousPoint = pt;
    52.             imshow(WINDOW, g_srcImage);
    53.         }
    54.     }
    55.     break;
    56.     }
    57. }
    1.     vector<Mat> bgr_planes;
    2.     split(src, bgr_planes);
    4.     int histsize = 256;
    5.     float range[] = { 0,256 };
    6.     const float* histRanges = { range };
    7.     Mat b_hist, g_hist, r_hist;    
    8.     calcHist(&bgr_planes[0], 1, 0, Mat(), b_hist, 1, &histsize, &histRanges, true, false);
    9.     calcHist(&bgr_planes[1], 1, 0, Mat(), g_hist, 1, &histsize, &histRanges, true, false);
    10.     calcHist(&bgr_planes[2], 1, 0, Mat(), r_hist, 1, &histsize, &histRanges, true, false);
    11.     int hist_h = 400;//直方图的图像的高
    12.     int hist_w = 512;// 直方图的图像的宽
    13.     int bin_w = hist_w / histsize;//直方图的等级
    14.     Mat histImage(hist_w, hist_h, CV_8UC3, Scalar(0, 0, 0));//绘制直方图显示的图像
    15.     normalize(b_hist, b_hist, 0, hist_h, NORM_MINMAX, -1, Mat());//归一化
    16.     normalize(g_hist, g_hist, 0, hist_h, NORM_MINMAX, -1, Mat());
    17.     normalize(r_hist, r_hist, 0, hist_h, NORM_MINMAX, -1, Mat());
    18.     for (int i = 1; i < histsize; i++)
    19.     {
    20.         //绘制蓝色分量直方图
    21.         line(histImage, Point((i - 1) * bin_w, hist_h - cvRound(b_hist.at<float>(i - 1))),
    22.             Point((i)*bin_w, hist_h - cvRound(b_hist.at<float>(i))), Scalar(255, 0, 0), 2);
    23.         //绘制绿色分量直方图
    24.         line(histImage, Point((i - 1) * bin_w, hist_h - cvRound(g_hist.at<float>(i - 1))),
    25.             Point((i)*bin_w, hist_h - cvRound(g_hist.at<float>(i))), Scalar(0, 255, 0), 2);
    26.         //绘制红色分量直方图
    27.         line(histImage, Point((i - 1) * bin_w, hist_h - cvRound(r_hist.at<float>(i - 1))),
    28.             Point((i)*bin_w, hist_h - cvRound(r_hist.at<float>(i))), Scalar(0, 0, 255), 2);
    29.     }
    1. /*--------------main-----------------*/
    2. int main()
    3. {
    4.     system("color F0");
    5.     Mat src,gray;
    6.     ReadMat(src, "D:/OpenCV/ycy.jpg");
    7.     Mat canny;
    8.     Canny(src, canny, 50, 100);
    9.     GaussianBlur(canny, canny, Size(3, 3), 10, 10);
    10.     Mat struct0 = getStructuringElement(1, Size(3, 3));
    11.     erode(canny, canny, struct0);
    12.     vector<vector<Point>> contours;
    13.     findContours(canny, contours, RETR_CCOMP, CHAIN_APPROX_NONE);
    14.     for (int n = 0; n < contours.size(); n++)
    15.     {
    16.         double area = contourArea(contours[n]);
    17.         if (area >= 1000)
    18.         {
    19.             Rect rect = boundingRect(contours[n]);
    20.             rectangle(src, rect, Scalar(0, 0, 255), 2);
    22.             RotatedRect rrect = minAreaRect(contours[n]);
    23.             Point2f points[4];
    24.             rrect.points(points);
    25.             Point2f cpt = rrect.center;
    26.             for (int i = 0; i < 4; i++)
    27.             {
    28.                 if (i == 3)
    29.                 {
    30.                     line(src, points[i], points[0], Scalar(0, 255, 0), 2);
    31.                     break;
    32.                 }
    33.                 line(src, points[i], points[i + 1], Scalar(0, 255, 0), 2);
    34.             }
    35.         }
    36.         else
    37.         {
    38.             continue;
    39.         }
    40.     }
    41.     resize(src, src, Size(600, 600));
    42.     imshow("1", src);
    43.     waitKey(0);
    44.     return 0;
    46. }
    1. /*--------------main-----------------*/
    2. int main()
    3. {
    4.     system("color F0");
    5.     Mat src,gray;
    6.     ReadMat(src, "D:/OpenCV/ycy2.jpg");
    7.     cvtColor(src, gray, COLOR_BGR2GRAY);
    8.     imshow("0", gray);
    10.     Mat harris;
    11.     int blockSize = 2;
    12.     int apertureSize = 3;
    13.     cornerHarris(gray, harris, blockSize, apertureSize, 0.04);
    15.     Mat harrisn;
    16.     normalize(harris, harrisn, 0, 255, NORM_MINMAX);
    17.     convertScaleAbs(harrisn, harrisn);
    18.     vector<KeyPoint> kpts;
    19.     for (int row = 0; row < harrisn.rows; row++)
    20.     {
    21.         for (int col = 0; col < harrisn.cols; col++)
    22.         {
    23.             int R = harrisn.at<uchar>(row, col);
    24.             if (R > 200)
    25.             {
    26.                 KeyPoint kpt;
    27.                 kpt.pt.x = row;
    28.                 kpt.pt.y = col;
    29.                 kpts.push_back(kpt);
    30.             }
    31.         }
    32.     }
    33.     drawKeypoints(src, kpts, src);
    34.     imshow("1", src);
    35.     waitKey(0);
    36.     return 0;
    38. }
    1. int main()
    2. {
    3.     system("color F0");
    4.     Mat src,gray;
    5.     ReadMat(src, "D:/OpenCV/ycy2.jpg");
    6.     Mat copy;
    7.     ReadMat(copy, "D:/OpenCV/ycy2_in_scene.jpg");
    9.     vector<KeyPoint> Keypoints1, Keypoints2;
    10.     Mat descriptions1, description2;
    12.     orb_features(src, Keypoints1, descriptions1);
    13.     orb_features(copy, Keypoints2, description2);
    15.     vector<DMatch> matches;
    16.     BFMatcher matcher(NORM_HAMMING);
    17.     matcher.match(descriptions1, description2, matches);
    18.     cout << "numbers:" << matches.size() << endl;
    19. //汉明距离筛选
    20.     double min_dist = 10000, max_dist = 0;
    21.     for (int i = 0; i < matches.size(); i++)
    22.     {
    23.         double dist = matches[i].distance;
    24.         if (dist < min_dist) min_dist = dist;
    25.         if (dist > max_dist) max_dist = dist;
    27.     }
    29.     vector<DMatch> goodmatches;
    30.     for (int i = 0; i < matches.size(); i++)
    31.     {
    32.         if (matches[i].distance <= std::max(2*min_dist,20.0))
    33.         {
    34.             goodmatches.push_back(matches[i]);
    35.         }
    36.     }
    38.     Mat outimg, outhamimg;
    39.     drawMatches(src, Keypoints1, copy, Keypoints2, matches, outimg);
    40.     drawMatches(src, Keypoints1, copy, Keypoints2, goodmatches, outhamimg);
    42.     resize(outimg, outimg, Size(), 0.3, 0.3);
    43.     resize(outhamimg, outhamimg, Size(), 0.3, 0.3);
    44.     imshow("1", outimg);
    45.     imshow("2", outhamimg);
    46.     waitKey(0);
    47.     return 0;
    49. }
    1. int main(int argc, char* argv[])
    2. {
    3.     Mat camera;
    4.     CascadeClassifier cascade;
    5.     string faceCascadeName = "D:/OpenCV/opencv/build/etc/haarcascades/haarcascade_frontalface_alt.xml";
    6.     cascade.load(faceCascadeName);
    9.     VideoCapture cap(0);
    11.     if (!cap.isOpened())
    12.     {
    13.         cout << "No video!" << endl;
    14.         return -1;
    15.     }
    17.     while (true)
    18.     {
    19.         cap >> camera;
    20.         FaceDetection(camera, cascade);
    21.         imshow("camera", camera);
    22.         if (waitKey(10) == 27)
    23.         {
    24.             break;
    25.         }
    26.     }
    28.     cap.release();
    29.     destroyAllWindows();
    30.     return 0;
    31. }

    1.mp4 (2.33MB)