// OpenCV_Exam08_Mat.cpp : Defines the entry point for the console application.

//

#include "stdafx.h"

#include <opencv.hpp>

#ifdef _DEBUG

#pragma comment (lib, "opencv_world300d.lib")

#else

#pragma comment (lib, "opencv_world300.lib")

#endif

#include <iostream>

#include <string>

#include "opencv2/core/core.hpp"

#include "opencv2/core/ocl.hpp"

#include "opencv2/highgui/highgui.hpp"

using namespace std;

using namespace cv;

using namespace cv::ocl;

#define M_MOG  1

#define M_MOG2 2

int main(int argc, const char** argv)

{

        /*cv::CommandLineParser cmd(argc, argv,

                "{ c | camera | false       | use camera }"

                "{ f | file   | 768x576.avi | input video file }"

                "{ m | method | mog         | method (mog, mog2) }"

                "{ h | help   | false       | print help message }");

        if (cmd.get<bool>("help"))

        {

                cout << "Usage : bgfg_segm [options]" << endl;

                cout << "Available options:" << endl;

                cmd.printParams();

                return EXIT_SUCCESS;

        }*/

        bool useCamera = false;//cmd.get<bool>("camera");

        string file = "..\\768x576.avi";//cmd.get<string>("file");

        string method = "mog2";//cmd.get<string>("method");

        if (method != "knn" && method != "mog2")

        {

                cerr << "Incorrect method" << endl;

                return EXIT_FAILURE;

        }

        VideoCapture cap;

        if (useCamera)

                cap.open(0);

        else

                cap.open(file);

        if (!cap.isOpened())

        {

                cout << "can not open camera or video file" << endl;

                return EXIT_FAILURE;

        }

        /*Ptr<BackgroundSubtractor> bg_model = method == "knn" ?

                createBackgroundSubtractorKNN().dynamicCast<BackgroundSubtractor>() :

                createBackgroundSubtractorMOG2().dynamicCast<BackgroundSubtractor>();*/

        Ptr<BackgroundSubtractorMOG2> bg_model = createBackgroundSubtractorMOG2(100, 16, false);

        //Ptr<BackgroundSubtractorKNN> bg_model = createBackgroundSubtractorKNN();

        Mat img0, img, fgmask, fgimg;

        bool update_bg_model = true;

        bool smoothMask = false;

        int64 start = cv::getTickCount();

        for(;;)

        {

                cap >> img0;

                if( img0.empty() )

                        break;

                img = img0;//

                //resize(img0, img, Size(640, 640*img0.rows/img0.cols), INTER_LINEAR);

                if( fgimg.empty() )

                        fgimg.create(img.size(), img.type());

                //update the model

                bg_model->apply(img, fgmask);

                if (smoothMask)

                {

                        GaussianBlur(fgmask, fgmask, Size(11, 11), 3.5, 3.5);

                        threshold(fgmask, fgmask, 10, 255, THRESH_BINARY);

                }

                fgimg = Scalar::all(0);

                img.copyTo(fgimg, fgmask);

                Mat bgimg;

                bg_model->getBackgroundImage(bgimg);

                imshow("image", img);

                imshow("foreground mask", fgmask);

                imshow("foreground image", fgimg);

                if (!bgimg.empty())

                        imshow("mean background image", bgimg);

                char k = (char)waitKey(30);

                if (k == 27) break;

                if (k == ' ')

                {

                        update_bg_model = !update_bg_model;

                        if (update_bg_model)

                                printf("Background update is on\n");

                        else

                                printf("Background update is off\n");

                }

        }

        double t = (cv::getTickCount() - start) / cv::getTickFrequency();

        std::cout << "t : " << t << std::endl;

        getchar();

        return EXIT_SUCCESS;

}