如何使用 C++ 中的 OpenCV 即時檢測人臉?


即時檢測人臉與在靜止圖片中檢測人臉類似。 即時人臉檢測唯一的區別在於,我們必須採用影片流方式執行程式。在此程式中,我們使用了 'VideoCapture()' 函式。此函式從其他攝像頭捕獲影片,並將幀臨時儲存在分配給它的矩陣中。此函式從預設攝像頭捕獲影片,並將幀臨時儲存在 'real_time' 矩陣中。

以下程式對即時人臉進行檢測:

示例

#include<iostream>
#include<opencv2/highgui/highgui.hpp>
#include<opencv2/imgproc/imgproc.hpp>
//This header includes definition of 'rectangle()' function//
#include<opencv2/objdetect/objdetect.hpp>
//This header includes the definition of Cascade Classifier//
#include<string>
using namespace std;
using namespace cv;
int main(int argc, char** argv) {
   Mat video_stream;//Declaring a matrix hold frames from video stream//
   VideoCapture real_time(0);//capturing video from default webcam//
   namedWindow("Face Detection");//Declaring an window to show the result//
   string trained_classifier_location = "C:/opencv/sources/data/haarcascades/haarcascade_frontalface_alt.xml";//Defining the location our XML Trained Classifier in a string//
   CascadeClassifier faceDetector;//Declaring an object named 'face detector' of CascadeClassifier class//
   faceDetector.load(trained_classifier_location);//loading the XML trained classifier in the object//
   vector<Rect>faces;//Declaring a rectangular vector named faces//
   while (true) {
      faceDetector.detectMultiScale(video_stream, faces, 1.1, 4, CASCADE_SCALE_IMAGE, Size(30, 30));//Detecting the faces in 'image_with_humanfaces' matrix//
      real_time.read(video_stream);// reading frames from camera and loading them in 'video_stream' Matrix//
      for (int i = 0; i < faces.size(); i++){ //for locating the face
         Mat faceROI = video_stream(faces[i]);//Storing face in the matrix//
         int x = faces[i].x;//Getting the initial row value of face rectangle's starting point//
         int y = faces[i].y;//Getting the initial column value of face rectangle's starting point//
         int h = y + faces[i].height;//Calculating the height of the rectangle//
         int w = x + faces[i].width;//Calculating the width of the rectangle//
         rectangle(video_stream, Point(x, y), Point(w, h), Scalar(255, 0, 255), 2, 8, 0);//Drawing a rectangle using around the faces//
      }
      imshow("Face Detection", video_stream);
      //Showing the detected face//
      if (waitKey(10) == 27){ //wait time for each frame is 10 milliseconds//
         break;
      }
   }
   return 0;
}

輸出

更新時間: 2021-03-10

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