CODEWITHSUNDEEP
c++copencv
mohammad
mohammad

Reputation: 39

how can i detect webcam and compare the local file to match face OpenCV

The highlighted code demonstrate openCV framework is loaded in my C code and it render Police watching. Which is just to demonstrate it works very smooth and very clean code to write.

Target: My webCAM is connected in to the USB port. I would like to capture the live webcam image and match from a local file (/tmp/myface.png), if live webcam match with local file myface.png, it will show the text "Police watching"

How can i now, capture my webCAM on this following code? 2) When the webCAM is captured, how can i load the file and find if it match, on match it shows that text only.

#include <opencv2/objdetect/objdetect.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
#include <fstream>
#include <iostream>
#include <stdio.h>
using namespace std;
using namespace cv;


#include "opencv/cv.h"
void detectAndDisplay(Mat frame);

//*************


 // Set Region of Interest
    cv::Rect roi_b;
    cv::Rect roi_c;

    size_t ic = 0; // ic is index of current element
    int ac = 0; // ac is area of current element

    size_t ib = 0; // ib is index of biggest element
    int ab = 0; // ab is area of biggest element
    stringstream ssfn;

//*************
 CascadeClassifier face_cascade;
string window_name = "Capture - Face detection";
int filenumber; // Number of file to be saved
string filename;
Mat frameread = imread("test.jpg");


int main(int argc, const char *argv[]){
     if (argc != 4) {
        cout << "usage: " << argv[0] << " </path/to/haar_cascade> </path/to/csv.ext> </path/to/device id>" << endl;
        cout << "\t </path/to/haar_cascade> -- Path to the Haar Cascade for face detection." << endl;
        cout << "\t </path/to/csv.ext> -- Path to the CSV file with the face database." << endl;
        cout << "\t <device id> -- The webcam device id to grab frames from." << endl;
      //  exit(1);
    }
    CascadeClassifier face_cascade;
    CascadeClassifier face_cascade1;
    String fn="C:\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt2.xml";
    String fn1="C:\\opencv\\sources\\data\\haarcascades\\haarcascade_eye.xml";

    face_cascade.load(fn);
    face_cascade1.load(fn1);

    VideoCapture input(0);
    if(!input.isOpened()){return -1;}

    namedWindow("Mezo",1);
    Mat f2;
    Mat frame;
            std::vector<Rect> faces,faces1;

            CvCapture* capture1;
            IplImage* f1;
            Mat crop;
            cv::Rect r;
    //  detectAndDisplay(frameread);
    while(1)
    {
        ic=0;
        ib=0;
        ab=0;
        ac=0;
        input >> frame;
        waitKey(10);
        //cvtColor(frame, frame, CV_BGR2GRAY);
        //cv::equalizeHist(frame,frame);
        face_cascade.detectMultiScale(frame, faces, 1.1, 10, CV_HAAR_SCALE_IMAGE | CV_HAAR_DO_CANNY_PRUNING, cvSize(0,0), cvSize(300,300));
        for(int i=0; i < faces.size();i++)
        {
            Point pt1(faces[i].x+faces[i].width, faces[i].y+faces[i].height);
            Point pt2(faces[i].x,faces[i].y);
            Mat faceROI = frame(faces[i]);
            face_cascade1.detectMultiScale(faceROI, faces1, 1.1, 2, 0 | CV_HAAR_SCALE_IMAGE, Size(30,30));
            for(size_t j=0; j< faces1.size(); j++)
            {
                Point center(faces[i].x+faces1[j].x+faces1[j].width*0.5, faces[i].y+faces1[j].y+faces1[j].height*0.5);
                int radius = cvRound((faces1[j].width+faces1[j].height)*0.25);
                circle(frame, center, radius, Scalar(255,0,0), 2, 8, 0);
            }
            rectangle(frame, pt1, pt2, cvScalar(0,255,0), 2, 8, 0);


        }
        imshow("Result", frame);
        waitKey(3);
        char c = waitKey(3);
        if(c == 27)
            break;
    }
    return 0;
}

Upvotes: 1

Views: 832

Answers (1)

Y.AL
Y.AL

Reputation: 1793

What you are asking about is probably the Face recognition. You should be more clear in your question.

Opencv has a class for doing recognition perfectly, not as you think to do.

Many approaches are available for this technology, Opencv has three algorithms. As well you need to prepare your database of images (labelled faces)

All this steps are described in opencv docs with some examples : http://docs.opencv.org/modules/contrib/doc/facerec/facerec_tutorial.html Just you need to read and apply.

Here you can also find a good tutorial for beginners.

Upvotes: 2

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