opencv

演示

• 输入说明 原图在顶层后然后再去按键，不然会失效（未知原因）
  1.roberts 边缘检测
  2.sobel算子
  3.Canny算子
  4.Laplace算子
  5.Canny算子，轮廓显示
  空格 人脸检测
• 准备一张图片
• 效果 默认显示原图和灰阶图
  

1. roberts 边缘检测

//roberts 边缘检测
Mat roberts(Mat srcImage)
{
    Mat dstImage = srcImage.clone();
    int nRows = dstImage.rows;
    int nCols = dstImage.cols;
    for (int i = 0; i < nRows - 1; i++) {
        for (int j = 0; j < nCols - 1; j++) {
            //根据公式计算
            int t1 = (srcImage.at<uchar>(i, j) -
                srcImage.at<uchar>(i + 1, j + 1)) *
                (srcImage.at<uchar>(i, j) -
                    srcImage.at<uchar>(i + 1, j + 1));
            int t2 = (srcImage.at<uchar>(i + 1, j) -
                srcImage.at<uchar>(i, j + 1)) *
                (srcImage.at<uchar>(i + 1, j) -
                    srcImage.at<uchar>(i, j + 1));
            //计算g（x,y）
            dstImage.at<uchar>(i, j) = (uchar)sqrt(t1 + t2);
        }
    }
    return dstImage;
}

2. sobel算子

 Sobel(src_gray, grad_x, CV_16S, 1, 0, 3, 1, 1, BORDER_DEFAULT);//求x方向梯度
            convertScaleAbs(grad_x, abs_grad_x);//转换格式 8u
            Sobel(src_gray, grad_y, CV_16S, 0, 1, 3, 1, 1, BORDER_DEFAULT);//求y方向梯度  
            convertScaleAbs(grad_y, abs_grad_y);
            //合并梯度
            addWeighted(abs_grad_x, 0.5, abs_grad_y, 0.5, 0, dst);
            cv::imshow("solbel算子", dst);

3. Canny算子

  //3.Canny算子
            Mat canny_output;
            vector<vector<Point> > contours;

            vector<Vec4i> hierarchy;
            Canny(src_gray, canny_output, 100, 300);
            cv::imshow("Canny算子", canny_output);

4. Laplace算子

       Laplacian(src_gray, dst, -1, 3);
       cv::imshow("Laplace算子", dst);

5. Canny算子，轮廓显示

 Mat canny_output;
            vector<vector<Point> > contours;
            vector<Vec4i> hierarchy;
            Canny(src_gray, canny_output, 100, 300);
            // 寻找轮廓
            findContours(canny_output, contours, hierarchy, RETR_EXTERNAL, CHAIN_APPROX_TC89_KCOS);
            /// 绘出轮廓
            Mat drawing = Mat::zeros(canny_output.size(), CV_8UC3);
            for (int i = 0; i < contours.size(); i++)
            {
                Scalar color = Scalar(rng.uniform(0, 255), rng.uniform(0, 255), rng.uniform(0, 255));
                drawContours(drawing, contours, i, color, 2, 8, hierarchy, 0, Point());
            }
            //在窗体中显示结果
            namedWindow("Contours", WINDOW_AUTOSIZE);
            cv::imshow("Contours", drawing);

空格 人脸检测 官方的模型，不太精确

//人脸检测的
            CascadeClassifier faceCascade;
            int ret = faceCascade.load("data/haarcascades/haarcascade_frontalface_alt.xml");   //加载分类器，注意文件路径
            //int ret = faceCascade.load("cascade.xml");   //加载分类器，注意文件路径
            if (!ret)//从指定的文件目录中加载级联分类器
            {
                cerr << "ERROR:Could not load classifier cascade" << endl;
                continue;
            }
            Mat imgGray;
            vector<Rect> faces;

            if (src.channels() == 3)
            {
                cvtColor(src, imgGray, COLOR_RGB2GRAY);
            }
            else
            {
                imgGray = src;
            }
            equalizeHist(imgGray, imgGray);

            faceCascade.detectMultiScale(imgGray, faces, 1.1, 4, 0, Size(65, 65));   //检测人脸

            if (faces.size() > 0)
            {
                for (int i = 0; i < faces.size(); i++)
                {
                    //rectangle(src, Point(faces[i].x, faces[i].y), Point(faces[i].x + faces[i].width, faces[i].y + faces[i].height),
                    //    Scalar(0, 255, 0), 1, 8);    //框出人脸位置
                    rectangle(src, faces[i], Scalar(0, 0, 255), 2, 8, 0);
                }
            }
            else {
                cerr << "ERROR:Could not detect face" << endl;
                continue;
            }
            // namedWindow("FacesOfPrettyGirl", WINDOW_NORMAL);
            cv::imshow("FacesDetect", src);