OpenCV1

/*!* \file Capture.cpp
*
* \author ranjiewen
* \date 十一月 2016
*
*  http://www.cnblogs.com/tanfy/p/5552270.html

解析opencv自帶人臉識別源碼（……/opencv-3.1.0/samples/cpp/facedetect.cpp）
*/
#include "opencv2/objdetect.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include <iostream>

using namespace std;
using namespace cv;

static void help()
{
    cout << "\nThis program demonstrates the cascade recognizer. Now you can use Haar or LBP features.\n"
        "This classifier can recognize many kinds of rigid objects, once the appropriate classifier is trained.\n"
        "It's most known use is for faces.\n"
        "Usage:\n"
        "./facedetect [--cascade=<cascade_path> this is the primary trained classifier such as frontal face]\n"
        "   [--nested-cascade[=nested_cascade_path this an optional secondary classifier such as eyes]]\n"
        "   [--scale=<image scale greater or equal to 1, try 1.3 for example>]\n"
        "   [--try-flip]\n"
        "   [filename|camera_index]\n\n"
        "see facedetect.cmd for one call:\n"
        "./facedetect --cascade=\"../../data/haarcascades/haarcascade_frontalface_alt.xml\" --nested-cascade=\"../../data/haarcascades/haarcascade_eye_tree_eyeglasses.xml\" --scale=1.3\n\n"
        "During execution:\n\tHit any key to quit.\n"
        "\tUsing OpenCV version " << CV_VERSION << "\n" << endl;
}

void detectAndDraw(Mat& img, CascadeClassifier& cascade,
    CascadeClassifier& nestedCascade,
    double scale, bool tryflip);

string cascadeName;
string nestedCascadeName;



int main(int argc, const char** argv)
{
    VideoCapture capture;
    Mat frame, image;
    string inputName;
    bool tryflip;

    // CascadeClassifier是Opencv中作人臉檢測的時候的一個級聯分類器，如今有兩種選擇：一是使用老版本的CvHaarClassifierCascade函數，一是使用新版本的CascadeClassifier類。老版本的分類器只支持類Haar特徵，而新版本的分類器既能夠使用Haar，也能夠使用LBP特徵。
    CascadeClassifier cascade, nestedCascade;
    double scale;

    cv::CommandLineParser parser(argc, argv,
        "{help h||}"
        "{cascade|D:/opencv/sources/data/haarcascades/haarcascade_frontalface_alt.xml|}"   //默認路徑實在安裝路徑下sample，修改了路徑，以便加載load成功
        "{nested-cascade|D:/opencv/sources/data/haarcascades/haarcascade_eye_tree_eyeglasses.xml|}"  //修改路徑
        "{scale|1|}{try-flip||}{@filename||}" //文件爲空時，設置攝像頭，實時檢測人臉
        );
    if (parser.has("help"))
    {
        help();
        return 0;
    }

    cascadeName = parser.get<string>("cascade");
    nestedCascadeName = parser.get<string>("nested-cascade");
    scale = parser.get<double>("scale");
    if (scale < 1)
        scale = 1;
    tryflip = parser.has("try-flip");
    inputName = parser.get<string>("@filename");
    std::cout << inputName << std::endl;  // test
    if (!parser.check())
    {
        parser.printErrors();
        return 0;
    }

    // 加載模型
    if (!nestedCascade.load(nestedCascadeName))
        cerr << "WARNING: Could not load classifier cascade for nested objects" << endl;
    if (!cascade.load(cascadeName))
    {
        cerr << "ERROR: Could not load classifier cascade" << endl;
        help();
        return -1;
    }
    // 讀取攝像頭
    // isdigit檢測字符是否爲阿拉伯數字 
    if (inputName.empty() || (isdigit(inputName[0]) && inputName.size() == 1))
    {
        int c = inputName.empty() ? 0 : inputName[0] - '0';
        // 此處若系統在虛擬機上，需在虛擬機中設置接管攝像頭：虛擬機(M)-> 可移動設備 -> 攝像頭名稱 -> 鏈接(斷開與主機鏈接)
        if (!capture.open(c))
            cout << "Capture from camera #" << c << " didn't work" << endl;
        else {
            capture.set(CV_CAP_PROP_FRAME_WIDTH, 640);
            capture.set(CV_CAP_PROP_FRAME_HEIGHT, 480);
        }
    }
    else if (inputName.size())
    {
        image = imread(inputName, 1);
        if (image.empty())
        {
            if (!capture.open(inputName))
                cout << "Could not read " << inputName << endl;
        }
    }
    else
    {
        image = imread("../data/lena.jpg", 1);
        if (image.empty()) cout << "Couldn't read ../data/lena.jpg" << endl;
    }

    if (capture.isOpened())
    {
        cout << "Video capturing has been started ..." << endl;


        for (;;)
        {
            std::cout << "capturing..." << std::endl;  // test
            capture >> frame;
            if (frame.empty())
                break;

            Mat frame1 = frame.clone();
            std::cout << "Start to detect..." << std::endl;  // test
            detectAndDraw(frame1, cascade, nestedCascade, scale, tryflip);

            int c = waitKey(10);
            if (c == 27 || c == 'q' || c == 'Q')
                break;
        }
    }
    else
    {
        cout << "Detecting face(s) in " << inputName << endl;
        if (!image.empty())
        {
            detectAndDraw(image, cascade, nestedCascade, scale, tryflip);
            waitKey(0);
        }
        else if (!inputName.empty())
        {
            /* assume it is a text file containing the
            list of the image filenames to be processed - one per line */
            FILE* f = fopen(inputName.c_str(), "rt");
            if (f)
            {
                char buf[1000 + 1];
                while (fgets(buf, 1000, f))
                {
                    int len = (int)strlen(buf), c;
                    while (len > 0 && isspace(buf[len - 1]))
                        len--;
                    buf[len] = '\0';
                    cout << "file " << buf << endl;
                    image = imread(buf, 1);
                    if (!image.empty())
                    {
                        detectAndDraw(image, cascade, nestedCascade, scale, tryflip);
                        c = waitKey(0);
                        if (c == 27 || c == 'q' || c == 'Q')
                            break;
                    }
                    else
                    {
                        cerr << "Aw snap, couldn't read image " << buf << endl;
                    }
                }
                fclose(f);
            }
        }
    }

    return 0;
}

void detectAndDraw(Mat& img, CascadeClassifier& cascade,
    CascadeClassifier& nestedCascade,
    double scale, bool tryflip)
{
    double t = 0;
    vector<Rect> faces, faces2;
    const static Scalar colors[] =
    {
        Scalar(255, 0, 0),
        Scalar(255, 128, 0),
        Scalar(255, 255, 0),
        Scalar(0, 255, 0),
        Scalar(0, 128, 255),
        Scalar(0, 255, 255),
        Scalar(0, 0, 255),
        Scalar(255, 0, 255)
    };
    Mat gray, smallImg;

    cvtColor(img, gray, COLOR_BGR2GRAY);
    double fx = 1 / scale;
    resize(gray, smallImg, Size(), fx, fx, INTER_LINEAR);
    equalizeHist(smallImg, smallImg);

    t = (double)cvGetTickCount();
    cascade.detectMultiScale(smallImg, faces,
        1.1, 2, 0
        //|CASCADE_FIND_BIGGEST_OBJECT
        //|CASCADE_DO_ROUGH_SEARCH
        | CASCADE_SCALE_IMAGE,
        Size(30, 30));
    if (tryflip)
    {
        flip(smallImg, smallImg, 1);
        cascade.detectMultiScale(smallImg, faces2,
            1.1, 2, 0
            //|CASCADE_FIND_BIGGEST_OBJECT
            //|CASCADE_DO_ROUGH_SEARCH
            | CASCADE_SCALE_IMAGE,
            Size(30, 30));
        for (vector<Rect>::const_iterator r = faces2.begin(); r != faces2.end(); r++)
        {
            faces.push_back(Rect(smallImg.cols - r->x - r->width, r->y, r->width, r->height));
        }
    }
    t = (double)cvGetTickCount() - t;
    printf("detection time = %g ms\n", t / ((double)cvGetTickFrequency()*1000.));
    for (size_t i = 0; i < faces.size(); i++)
    {
        Rect r = faces[i];
        Mat smallImgROI;
        vector<Rect> nestedObjects;
        Point center;
        Scalar color = colors[i % 8];
        int radius;

        double aspect_ratio = (double)r.width / r.height;
        if (0.75 < aspect_ratio && aspect_ratio < 1.3)
        {
            center.x = cvRound((r.x + r.width*0.5)*scale);
            center.y = cvRound((r.y + r.height*0.5)*scale);
            radius = cvRound((r.width + r.height)*0.25*scale);
            circle(img, center, radius, color, 3, 8, 0);
        }
        else
            rectangle(img, cvPoint(cvRound(r.x*scale), cvRound(r.y*scale)),
                cvPoint(cvRound((r.x + r.width - 1)*scale), cvRound((r.y + r.height - 1)*scale)),
                color, 3, 8, 0);
        if (nestedCascade.empty())
            continue;
        smallImgROI = smallImg(r);
        nestedCascade.detectMultiScale(smallImgROI, nestedObjects,
            1.1, 2, 0
            //|CASCADE_FIND_BIGGEST_OBJECT
            //|CASCADE_DO_ROUGH_SEARCH
            //|CASCADE_DO_CANNY_PRUNING
            | CASCADE_SCALE_IMAGE,
            Size(30, 30));
        for (size_t j = 0; j < nestedObjects.size(); j++)
        {
            Rect nr = nestedObjects[j];
            center.x = cvRound((r.x + nr.x + nr.width*0.5)*scale);
            center.y = cvRound((r.y + nr.y + nr.height*0.5)*scale);
            radius = cvRound((nr.width + nr.height)*0.25*scale);
            circle(img, center, radius, color, 3, 8, 0);
        }
    }
    imshow("result", img);
}




/*****************************************************
* \file Capture.cpp
* \date 2016/11/10 0:22
* \author ranjiewen
* \contact: ranjiewen@outlook.com
* \問題描述：
http://www.cnblogs.com/lingshaohu/archive/2011/12/16/2290017.html

* \問題分析：
能夠存avi,可是不能打開，待改善
*****************************************************/

//#include <iostream>
//#include <opencv2/opencv.hpp>
//using namespace cv;;
//using namespace std;
//int main()
//{
//    CvCapture* capture = cvCaptureFromCAM(-1);
//    CvVideoWriter* video = NULL;
//    IplImage* frame = NULL;
//    int n;
//    if (!capture) //若是不能打開攝像頭給出警告
//    {
//        cout << "Can not open the camera." << endl;
//        return -1;
//    }
//    else
//    {
//        frame = cvQueryFrame(capture); //首先取得攝像頭中的一幀
//        video = cvCreateVideoWriter("camera.avi", CV_FOURCC('X', 'V', 'I', 'D'), 25,
//            cvSize(frame->width, frame->height)); //建立CvVideoWriter對象並分配空間
//        //保存的文件名爲camera.avi，編碼要在運行程序時選擇，大小就是攝像頭視頻的大小，幀頻率是32
//        if (video) //若是能建立CvVideoWriter對象則代表成功
//        {
//            cout << "VideoWriter has created." << endl;
//        }
//
//        cvNamedWindow("Camera Video", 1); //新建一個窗口
//        int i = 0;
//        while (i <= 300) // 讓它循環200次自動中止錄取
//        {
//            frame = cvQueryFrame(capture); //從CvCapture中得到一幀
//            if (!frame)
//            {
//                cout << "Can not get frame from the capture." << endl;
//                break;
//            }
//            n = cvWriteFrame(video, frame); //判斷是否寫入成功，若是返回的是1，表示寫入成功
//            cout << n << endl;
//            cvShowImage("Camera Video", frame); //顯示視頻內容的圖片
//            i++;
//            if (cvWaitKey(2) > 0)
//                break; //有其餘鍵盤響應，則退出
//        }
//
//        cvReleaseVideoWriter(&video);
//        cvReleaseCapture(&capture);
//        cvDestroyWindow("Camera Video");
//    }
//    return 0;
//}