Why is haar cascade very slow opencv c++

I am using haar cascading to detect frontal faces. I have below code:

int main()
{
    Mat image;

    cv::VideoCapture cap;
    cap.open(1); 

    int frame_idx = 0;
    time_t fpsStartTime, fpsEndTime;
    time(&fpsStartTime);
    for (;;)
    {
        frame_idx = frame_idx + 1;
        cap.read(image);

        CascadeClassifier face_cascade;
        face_cascade.load("<PATH");
        std::vector<Rect> faces;
        face_cascade.detectMultiScale(image, faces, 1.1, 2, 0 | cv::CASCADE_SCALE_IMAGE, Size(30, 30));

        // Draw circles on the detected faces
        for (int i = 0; i < faces.size(); i++)
        {
            Point center(faces[i].x + faces[i].width*0.5, faces[i].y + faces[i].height*0.5);

            ellipse(image, center, Size(faces[i].width*0.5, faces[i].height*0.5), 0, 0, 360, Scalar(255, 0, 255), 4, 8, 0);
        }

        cv::imshow("Detected Face", image);
        char k = cv::waitKey(1);
        if (k == 27)
            break;

        time(&fpsEndTime);
        double seconds = difftime(fpsEndTime, fpsStartTime);
        double fps = frame_idx / seconds;
        std::string fps_txt = "FPS: " + std::to_string(fps);  // fps_str.str();
        cout << "FPS :  " << fps_txt << endl;

    }
    return 0;
}

This code is working fine but giving very low FPS. FPS is ~1fps which is very slow. I am running this on Windows 10 laptop with intel i5 CPU. I believe this should not be this much slow.

In debug mode, it gives ~1fps but in release mode it is 4-5fps which again is very slow. I have run some openvino demo's like pedestrian detection which uses 2 openvino model on same hardware and it gives ~17-20fps which is very good.

I am using USB 3.0 logitech brio 4k camera so this cannot be a reason of low fps. My question is why haar cascading is performing very slow. Is there anyway we can enhance its speed and make it more usable. Please help. Thanks

You should not (re)load the classifier on every frame. It should load once before processing frames.

Move the following statements out of the for loop.

CascadeClassifier face_cascade;
face_cascade.load("<PATH");

See a demo on OpenCV Docs.