使用dlib自带的面向梯度直方图（HOG)和线性分类器方法来检测人脸

之前使用opencv里面CascadeClassifier（级联分类器)来识别人脸，

下面使用dlib库来实现人脸识别。

dlib是一个开源的库，它包含了很多内容有机器学习，图像处理，数值算法等等。

#include <dlib/image_processing/frontal_face_detector.h>
#include <dlib/gui_widgets.h>
#include <dlib/image_io.h>
#include <iostream>

using namespace dlib;
using namespace std;

// ----------------------------------------------------------------------------------------

int main(int argc, char** argv)
{
    try
    {
        if (argc == 1)
        {
            cout << "Give some image files as arguments to this program." << endl;
            return 0;
        }

        frontal_face_detector detector = get_frontal_face_detector();
        image_window win;

        // Loop over all the images provided on the command line.
        for (int i = 1; i < argc; ++i)
        {
            cout << "processing image " << argv[i] << endl;
            array2d<unsigned char> img;
            load_image(img, argv[i]);
            // Make the image bigger by a factor of two.  This is useful since
            // the face detector looks for faces that are about 80 by 80 pixels
            // or larger.  Therefore, if you want to find faces that are smaller
            // than that then you need to upsample the image as we do here by
            // calling pyramid_up().  So this will allow it to detect faces that
            // are at least 40 by 40 pixels in size.  We could call pyramid_up()
            // again to find even smaller faces, but note that every time we
            // upsample the image we make the detector run slower since it must
            // process a larger image.
            pyramid_up(img);

            // Now tell the face detector to give us a list of bounding boxes
            // around all the faces it can find in the image.
            std::vector<rectangle> dets = detector(img);

            cout << "Number of faces detected: " << dets.size() << endl;
            // Now we show the image on the screen and the face detections as
            // red overlay boxes.
            win.clear_overlay();
            win.set_image(img);
            win.add_overlay(dets, rgb_pixel(255, 0, 0));

            cout << "Hit enter to process the next image..." << endl;
            cin.get();
        }
    }
    catch (exception& e)
    {
        cout << "\nexception thrown!" << endl;
        cout << e.what() << endl;
    }
}