learnopencv/FaceDetectionComparison/face_detection_dlib_mmod.cpp

#include <iostream>
#include <string>
#include <vector>
#include <stdlib.h>
#include <opencv2/core.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>

#include <dlib/opencv.h>
#include <dlib/image_processing.h>
#include <dlib/dnn.h>
#include <dlib/data_io.h>

using namespace cv;
using namespace std;
using namespace dlib;

// Network Definition
/////////////////////////////////////////////////////////////////////////////////////////////////////
template <long num_filters, typename SUBNET> using con5d = con<num_filters,5,5,2,2,SUBNET>;
template <long num_filters, typename SUBNET> using con5  = con<num_filters,5,5,1,1,SUBNET>;

template <typename SUBNET> using downsampler  = relu<affine<con5d<32, relu<affine<con5d<32, relu<affine<con5d<16,SUBNET>>>>>>>>>;
template <typename SUBNET> using rcon5  = relu<affine<con5<45,SUBNET>>>;

using net_type = loss_mmod<con<1,9,9,1,1,rcon5<rcon5<rcon5<downsampler<input_rgb_image_pyramid<pyramid_down<6>>>>>>>>;
/////////////////////////////////////////////////////////////////////////////////////////////////////

void detectFaceDlibMMOD(net_type mmodFaceDetector, Mat &frameDlibMmod, int inHeight=300, int inWidth=0)
{

    int frameHeight = frameDlibMmod.rows;
    int frameWidth = frameDlibMmod.cols;
    if (!inWidth)
        inWidth = (int)((frameWidth / (float)frameHeight) * inHeight);

    float scaleHeight = frameHeight / (float)inHeight;
    float scaleWidth = frameWidth / (float)inWidth;

    Mat frameDlibMmodSmall;
    resize(frameDlibMmod, frameDlibMmodSmall, Size(inWidth, inHeight));

    // Convert OpenCV image format to Dlib's image format
    cv_image<bgr_pixel> dlibIm(frameDlibMmodSmall);
    matrix<rgb_pixel> dlibMatrix;
    assign_image(dlibMatrix, dlibIm);

    // Detect faces in the image
    std::vector<dlib::mmod_rect> faceRects = mmodFaceDetector(dlibMatrix);

    for ( size_t i = 0; i < faceRects.size(); i++ )
    {
        int x1 = (int)(faceRects[i].rect.left() * scaleWidth);
        int y1 = (int)(faceRects[i].rect.top() * scaleHeight);
        int x2 = (int)(faceRects[i].rect.right() * scaleWidth);
        int y2 = (int)(faceRects[i].rect.bottom() * scaleHeight);
        cv::rectangle(frameDlibMmod, Point(x1, y1), Point(x2, y2), Scalar(0,255,0), (int)(frameHeight/150.0), 4);
    }
}

int main( int argc, const char** argv )
{
    String mmodModelPath = "models/mmod_human_face_detector.dat";
    net_type mmodFaceDetector;
    deserialize(mmodModelPath) >> mmodFaceDetector;

    VideoCapture source;
    if (argc == 1)
        source.open(0, CAP_V4L);
    else
        source.open(argv[1]);

    Mat frame;

    double tt_dlibMmod = 0;
    double fpsDlibMmod = 0;
    while (true)
    {
        source >> frame;
        if (frame.empty())
            break;

        double t = cv::getTickCount();
        detectFaceDlibMMOD ( mmodFaceDetector, frame );
        tt_dlibMmod = ((double)cv::getTickCount() - t)/cv::getTickFrequency();
        fpsDlibMmod = 1/tt_dlibMmod;

        putText(frame, format("DLIB MMOD; FPS = %.2f",fpsDlibMmod), Point(10, 50), FONT_HERSHEY_SIMPLEX, 1.3, Scalar(0, 0, 255), 4);
        imshow("DLIB - MMOD Face Detection", frame);

        int k = waitKey(5);
        if(k == 27)
        {
            destroyAllWindows();
            break;
        }
    }
}