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/////////////////////////////////////////////////////////////////////////

// Author:      Zhongze Hu

// Subject:     Circulant Structure of Tracking-by-detection with Kernels

// Algorithm:   ECCV12, Jo~ao F. Henriques, Exploiting the Circulant

//			    Structure of Tracking-by-detection with Kernels

// Matlab code: http://home.isr.uc.pt/~henriques/circulant/index.html

// Date:        01/13/2015

/////////////////////////////////////////////////////////////////////////

#include "CSK_Tracker.h"

#include <iostream>

#include <fstream>

using namespace std;

bool tracking_flag = false;

cv::Mat org, dst, img, tmp;

int Wid, Hei, X, Y;

void on_mouse(int event, int x, int y, int flags, void *ustc)//event鼠标事件代号，x,y鼠标坐标，flags拖拽和键盘操作的代号

{

	static cv::Point pre_pt = (-1, -1);//初始坐标

	static cv::Point cur_pt = (-1, -1);//实时坐标

	char temp[16];

	if (!tracking_flag) {

		if (event == CV_EVENT_LBUTTONDOWN)//左键按下，读取初始坐标，并在图像上该点处划圆

		{

			//org.copyTo(img);//将原始图片复制到img中

			org = img.clone();

			sprintf(temp, "(%d,%d)", x, y);

			pre_pt = cv::Point(x, y);

			putText(img, temp, pre_pt, cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0, 255), 1, 8);//在窗口上显示坐标

			circle(img, pre_pt, 2, cv::Scalar(255, 0, 0, 0), CV_FILLED, CV_AA, 0);//划圆

			imshow("img", img);

		}

		else if (event == CV_EVENT_MOUSEMOVE && !(flags & CV_EVENT_FLAG_LBUTTON))//左键没有按下的情况下鼠标移动的处理函数

		{

			img.copyTo(tmp);//将img复制到临时图像tmp上，用于显示实时坐标

			sprintf(temp, "(%d,%d)", x, y);

			cur_pt = cv::Point(x, y);

			putText(tmp, temp, cur_pt, cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0, 255));//只是实时显示鼠标移动的坐标

			imshow("img", tmp);

		}

		else if (event == CV_EVENT_MOUSEMOVE && (flags & CV_EVENT_FLAG_LBUTTON))//左键按下时，鼠标移动，则在图像上划矩形

		{

			img.copyTo(tmp);

			sprintf(temp, "(%d,%d)", x, y);

			cur_pt = cv::Point(x, y);

			putText(tmp, temp, cur_pt, cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0, 255));

			rectangle(tmp, pre_pt, cur_pt, cv::Scalar(0, 255, 0, 0), 1, 8, 0);//在临时图像上实时显示鼠标拖动时形成的矩形

			imshow("img", tmp);

		}

		else if (event == CV_EVENT_LBUTTONUP)//左键松开，将在图像上划矩形

		{

			//org.copyTo(img);

			img.copyTo(tmp);

			sprintf(temp, "(%d,%d)", x, y);

			cur_pt = cv::Point(x, y);

			putText(img, temp, cur_pt, cv::FONT_HERSHEY_SIMPLEX, 0.5, cv::Scalar(0, 0, 0, 255));

			circle(img, pre_pt, 2, cv::Scalar(255, 0, 0, 0), CV_FILLED, CV_AA, 0);

			rectangle(img, pre_pt, cur_pt, cv::Scalar(0, 255, 0, 0), 1, 8, 0);//根据初始点和结束点，将矩形画到img上

			imshow("img", img);

			img.copyTo(tmp);

			//截取矩形包围的图像，并保存到dst中

			int width = abs(pre_pt.x - cur_pt.x);

			int height = abs(pre_pt.y - cur_pt.y);

			if (width == 0 || height == 0)

			{

				printf("width == 0 || height == 0");

				return;

			}

			Wid = width;

			Hei = height;

			X = pre_pt.x + width / 2;

			Y = pre_pt.y + height / 2;

			tracking_flag = true;

			//dst = org(Rect(min(cur_pt.x, pre_pt.x), min(cur_pt.y, pre_pt.y), width, height));

			//namedWindow("dst");

			//imshow("dst", dst);

			//waitKey(0);

		}

	}

}

void main()

{

	TCHAR szName[] = TEXT("Local\\FHY_SYSTEM_0");

	TrackBox BOX;

	hMapFile = CreateFileMapping(

		INVALID_HANDLE_VALUE,    // use paging file

		NULL,                    // default security

		PAGE_READWRITE,          // read/write access

		0,                       // maximum object size (high-order DWORD)

		BUF_SIZE,                // maximum object size (low-order DWORD)

		szName);                 // name of mapping object

	if (hMapFile == NULL)

	{

		/*printf(TEXT("Could not create file mapping object (%d).\n"),

			GetLastError());*/

		return;

	}

	pBuffer = (LPTSTR)MapViewOfFile(hMapFile,   // handle to map object

		FILE_MAP_ALL_ACCESS, // read/write permission

		0,

		0,

		BUF_SIZE);

	if (pBuffer == NULL)

	{

		/*printf(TEXT("Could not map view of file (%d).\n"),

			GetLastError());*/

		CloseHandle(hMapFile);

		return;

	}

	BOX.x = 0;

	BOX.y = 0;

	BOX.flag = tracking_flag;

	CSK_Tracker my_tracker;

	string file_name;

	ifstream infile("input/Dudek/Name.txt");

	//getline(infile,file_name);

	//my_tracker.run_tracker("..\\..\\data\\tiger.avi",Point(16 + 36/2,28 + 36/2),36);

	//my_tracker.run_tracker("..\\..\\data\\boy.avi",Point(374+68/2, 77+68/2),68);

	//my_tracker.run_tracker("..\\..\\CSK\\data\\oldman.avi",Point(186+50/2, 118+50/2),50);

	//VideoCapture capture("input/bike1.avi");

	//Mat frame = imread(file_name);

	////if (!capture.isOpened())

	//if(frame.empty())

	//{

	//	cout << "open video failed!" << endl;

	//	return;

	//}

	//int frame_count = int(capture.get(CV_CAP_PROP_FRAME_COUNT));

	int frame_count = 1490;

	//double rate = capture.get(CV_CAP_PROP_FPS);

	//int width = capture.get(CV_CAP_PROP_FRAME_WIDTH);

	//int height = capture.get(CV_CAP_PROP_FRAME_HEIGHT);

	int width = 320;

	int height = 240;

	cv::Mat frame;

	cv::Mat frame_last;

	cv::Mat alphaf;

	cv::VideoCapture capture(0);

	capture.set(CV_CAP_PROP_FRAME_WIDTH, 1920);

	capture.set(CV_CAP_PROP_FRAME_HEIGHT, 1080);

	while (true)

	{

		if (!tracking_flag)

		{

			capture.read(img);

			cv::namedWindow("img");//定义一个img窗口

			cv::setMouseCallback("img", on_mouse, 0);//调用回调函数

			imshow("img", img);

			memcpy(BOX_DATA, &BOX, sizeof(TrackBox));

			char key = cvWaitKey(10);

			if (key == 'q') break;

		}

		else

		{

			cv::Point pos_first = cv::Point(X, Y);

			int target_sz[2] = { Hei,Wid };

			my_tracker.tracke_one(pos_first,target_sz, capture, tracking_flag);

		}

	}

}

　　

//#ifdef _CSK_TRACKER_H_

//#define  _CSK_TRACKER_H_

#include "opencv2/core/core.hpp"

#include "opencv2/imgproc/imgproc.hpp"

#include "opencv2/highgui/highgui.hpp"

#include <iostream>

#include <fstream>

#include <Windows.h>

#define FRAME_SIZE 1920*1080

#define BUF_SIZE  FRAME_SIZE*60

typedef struct

{

	int x;

	int y;

	/*int zx;

	int zy;*/

	int width;

	int height;

	int flag = 0;

}TrackBox; //目标检测的上下顶点；

typedef struct

{

	int width;

	int height;

	int type;

}imgInfHead;

#define BUF_SIZE FRAME_SIZE*10

#define FRAME_SIZE 1920*1080

extern HANDLE hMapFile;

extern LPCTSTR pBuffer;

#define BOX_DATA      (char*)pBuffer+FRAME_SIZE*0  //

#define SEND_IMG00_HEAD (char*)pBuffer+FRAME_SIZE*1 //图像头信息首地址

#define SEND_IMG00_DATA (char*)pBuffer+FRAME_SIZE*2  //图像数据区首地址

//using namespace cv;

using namespace std;

class CSK_Tracker

{

public:

	CSK_Tracker();

	~CSK_Tracker();

	TrackBox BOX;

	void hann2d(cv::Mat& m);

	cv::Mat dense_guess_kernel(double digma, cv::Mat x, cv::Mat y);

	cv::Mat dense_guess_kernel(double digma, cv::Mat x);

	cv::Mat get_subwindow(cv::Mat im, cv::Point pos, int* sz, cv::Mat cos_window);

	//void run_tracker(string video_name, Point pos, int target_sz);

	//void tracke_one(ifstream &infile, cv::Point pos_first, int frame_count, int* target_sz, cv::VideoCapture capture);

	void tracke_one(cv::Point pos_first, int* target_sz, cv::VideoCapture capture, bool &tracking_flag);

	void tracke_one(ifstream &infile, cv::Point pos_first, int frame_count, int* target_sz, cv::VideoCapture capture);

	cv::Mat conj(cv::Mat a);

	cv::Mat c_div(cv::Mat a, cv::Mat b);//a./b

	cv::Mat c_mul(cv::Mat a, cv::Mat b);//a.*b

	cv::Mat fft2d(cv::Mat src);

	void print_mat(cv::Mat a, string file_name);//打印矩阵，debug用

	void print_img(cv::Mat a, string file_name);//打印图片灰度值

private:

	static const double padding;

	static const double output_sigma_factor;

	static const double sigma;

	static const double lambda;

	static const double interp_factor;

	static const string test_file;

};

//#endif

　　

#include "CSK_Tracker.h"

using namespace std;

const double CSK_Tracker::padding = 1;

const double CSK_Tracker::output_sigma_factor = 1.0/16;

const double CSK_Tracker::sigma = 0.2;

const double CSK_Tracker::lambda = 0.01;

const double CSK_Tracker::interp_factor = 0.075;

const string CSK_Tracker::test_file = "H:\\CV\\CSK\\data\\result_c.txt";

HANDLE hMapFile;

LPCTSTR pBuffer;

CSK_Tracker::CSK_Tracker()

{

}

CSK_Tracker::~CSK_Tracker()

{

}

void CSK_Tracker::hann2d(cv::Mat& m)

{

	cv::Mat a(m.rows,1,CV_32FC1);

	cv::Mat b(m.cols,1,CV_32FC1);

	for (int i = 0; i < m.rows; i++)

	{

		float t = 0.5 * (1 - cos(2*CV_PI*i/(m.rows - 1)));

		a.at<float>(i,0) = t;

	}

	for (int i = 0; i < m.cols; i++)

	{

		float t = 0.5 * (1 - cos(2*CV_PI*i/(m.cols - 1)));

		b.at<float>(i,0) = t;

	}

	m = a * b.t();

}

cv::Mat CSK_Tracker::dense_guess_kernel(double sigma, cv::Mat x, cv::Mat y)

{

	//xf = fft2(x)

	cv::Mat xf = fft2d(x);

	vector<cv::Mat> xf_ri(xf.channels());

	cv::split(xf,xf_ri);

	//xx = x(:)' * x(:);

	double xx = 0;

	cv::Scalar sum_x = cv::sum(x.mul(x));

	for (int i = 0; i < sum_x.cols; i++)

	{

		xx += sum_x[i];

	}

	//yf = fft2(y)

	cv::Mat yf = fft2d(y);

	vector<cv::Mat> yf_ri(yf.channels());

	cv::split(yf,yf_ri);

	//yy = y(:)' * y(:);

	double yy = 0;

	cv::Scalar sum_y = sum(y.mul(y));

	for (int i = 0; i < sum_y.cols; i++)

	{

		yy += sum_y[i];

	}

	//xyf = xf. * conj(yf)

	cv::Mat xyf = c_mul(xf,conj(yf));

	//xy = real(circshift(ifft2(xyf), floor(size(x)/2)));

	idft(xyf,xyf);

	xyf = xyf/(xyf.rows*xyf.cols);

	vector<cv::Mat> xy_ri(xyf.channels());

	cv::split(xyf,xy_ri);

	cv::Mat xy = xy_ri[0];

	int cx = xy.cols/2;

	int cy = xy.rows/2;

	cv::Mat q0(xy, cv::Rect(0, 0, cx, cy));   // Top-Left - Create a ROI per quadrant

	cv::Mat q1(xy, cv::Rect(cx, 0, cx, cy));  // Top-Right

	cv::Mat q2(xy, cv::Rect(0, cy, cx, cy));  // Bottom-Left

	cv::Mat q3(xy, cv::Rect(cx, cy, cx, cy)); // Bottom-Right

	cv::Mat tmp;                           // swap quadrants (Top-Left with Bottom-Right)

	q0.copyTo(tmp);

	q3.copyTo(q0);

	tmp.copyTo(q3);

	q1.copyTo(tmp);                    // swap quadrant (Top-Right with Bottom-Left)

	q2.copyTo(q1);

	tmp.copyTo(q2);

	int numel_x = x.rows*x.cols;

	cv::Mat k;

	exp((-1/pow(sigma,2))*(cv::max)((xx+yy-2*xy)/numel_x,0),k);

	return k;

}

cv::Mat CSK_Tracker::dense_guess_kernel(double sigma, cv::Mat x)

{

	//xf = fft2(x)

	cv::Mat xf = fft2d(x);

	vector<cv::Mat> xf_ri(xf.channels());

	cv::split(xf,xf_ri);

	//xx = x(:)' * x(:);

	double xx = 0;

	cv::Scalar sum_x = sum(x.mul(x));

	for (int i = 0; i < sum_x.cols; i++)

	{

		xx += sum_x[i];

	}

	//yf = xf

	//yy = xx

	cv::Mat yf;

	xf.copyTo(yf);

	double yy = xx;

	vector<cv::Mat> yf_ri(yf.channels());

	cv::split(yf,yf_ri);

	//xyf = xf. * conj(yf)

	cv::Mat xyf = c_mul(xf,conj(yf));

	//xy = real(circshift(ifft2(xyf), floor(size(x)/2)));

	idft(xyf,xyf);

	xyf = xyf/(xyf.rows*xyf.cols);

	vector<cv::Mat> xy_ri(xyf.channels());

	cv::split(xyf,xy_ri);

	cv::Mat xy = xy_ri[0];

	//print_mat(xy,"xyf.txt");

	int cx = xy.cols/2;

	int cy = xy.rows/2;

	cv::Mat q0(xy, cv::Rect(0, 0, cx, cy));   // Top-Left - Create a ROI per quadrant

	cv::Mat q1(xy, cv::Rect(cx, 0, cx, cy));  // Top-Right

	cv::Mat q2(xy, cv::Rect(0, cy, cx, cy));  // Bottom-Left

	cv::Mat q3(xy, cv::Rect(cx, cy, cx, cy)); // Bottom-Right

	cv::Mat tmp;                           // swap quadrants (Top-Left with Bottom-Right)

	q0.copyTo(tmp);

	q3.copyTo(q0);

	tmp.copyTo(q3);

	q1.copyTo(tmp);                    // swap quadrant (Top-Right with Bottom-Left)

	q2.copyTo(q1);

	tmp.copyTo(q2);

	int numel_x = x.rows*x.cols;

	cv::Mat k;

	exp((-1/pow(sigma,2))*(cv::max)((xx+yy-2*xy)/numel_x,0),k);

	return k;

}

cv::Mat CSK_Tracker::get_subwindow(cv::Mat im, cv::Point pos, int* sz, cv::Mat cos_window)

{

	//xs = floor(pos(2)) + (1:sz(2)) - floor(sz(2)/2);

	//ys = floor(pos(1)) + (1:sz(1)) - floor(sz(1)/2);

	vector<int> xs(sz[1]);

	vector<int> ys(sz[0]);

	for (int i = 0; i < sz[1]; i++)

	{

		xs[i] = floor(pos.x) + i - floor(sz[1]/2);

		xs[i] = (cv::max)((cv::min)(xs[i],im.cols - 1),0);

	}

	for (int i = 0; i < sz[0]; i++){

		ys[i] = floor(pos.y) + i - floor(sz[0]/2);

		ys[i] = (cv::max)((cv::min)(ys[i],im.rows - ,0);

	}

	//cout << xs[0]<<" "<< xs[1]<< " "<<xs[2]<<'\n';

	//cout << ys[0]<<" "<< ys[1]<< " "<<ys[2];

    //xs(xs < 1) = 1;

    //ys(ys < 1) = 1;

    //xs(xs > size(im,2)) = size(im,2);

    //ys(ys > size(im,1)) = size(im,1);

	/*for (int i = 0; i < sz[0]; i++)

	{

		xs[i] = max(min(xs[i],im.cols - 1),0);

		ys[i] = max(min(ys[i],im.cols - 1),0);

	}*/

	cv::Mat out(sz[0],sz[1],CV_32FC1);

	for (int i = 0; i < sz[0]; i++)

	{

		for (int j = 0; j < sz[1]; j++)

		{

			out.at<float>(i,j) = float(im.at<uchar>(ys[i],xs[j]))/255 - 0.5;

		}

	}

	//print_mat(out,"out.txt");

	out = cos_window.mul(out);

	//print_mat(out,"out.txt");

	return out;

}

void CSK_Tracker::tracke_one(cv::Point pos_first, int* target_sz, cv::VideoCapture capture, bool &tracking_flag)

{

	//%window size, taking padding into account

	int sz[2] = { floor(target_sz[0] * (1 + padding)),floor(target_sz[1] * (1 + padding)) };

	//%desired output (gaussian shaped), bandwidth proportional to target size

	double output_sigma = sqrt(target_sz[0] * target_sz[1])*output_sigma_factor;

	cv::Mat rs(sz[0], sz[1], CV_32FC1);

	cv::Mat cs(sz[0], sz[1], CV_32FC1);

	for (int i = 0; i < sz[0]; i++)

	{

		for (int j = 0; j < sz[1]; j++)

		{

			rs.at<float>(i, j) = i - sz[0] / 2 + 1;

			cs.at<float>(i, j) = j - sz[1] / 2 + 1;

		}

	}

	//print_mat(rs,"rs.txt");

	//print_mat(cs,"cs.txt");

	cv::Mat y;

	exp((-0.5 / pow(output_sigma, 2))*(rs.mul(rs) + cs.mul(cs)), y);

	//print_mat(y,"y.txt");

	//yf = fft2(y)

	cv::Mat yf;

	//IplImage *y_temp = &IplImage(y);

	yf = fft2d(y);

	vector<cv::Mat> yf_ri(yf.channels());

	cv::split(yf, yf_ri);

	//%store pre-computed cosine window

	cv::Mat cos_window(sz[0], sz[1], CV_32FC1);

	hann2d(cos_window);

	//print_mat(cos_window,"cos_window.txt");

	cv::Mat frame;

	cv::Mat org;

	cv::Mat x;

	cv::Mat k;

	cv::Mat z;

	cv::Mat alphaf;

	cv::Mat new_alphaf;

	cv::Point pos = pos_first;

	//VideoCapture capture(0);

	cv::namedWindow("img");

	string file_name;

	int i = 0;

	while (tracking_flag)

	{

		capture.read(org);

		if (org.empty())

		{

			cout << "fail to open frame" << i << endl;

			break;

		}

		if (org.channels() > 1)

		{

			cvtColor(org, frame, CV_BGR2GRAY);

		}

		//%extract and pre-process subwindow

		/*ofstream F("frame.txt");

		for(int p = 0;p < frame.rows;p ++){

		for(int q = 0;q < frame.cols;q++){

		F << int(frame.at<uchar>(p,q)) << " ";

		}

		F << '\n';

		}*/

		//cout<<frame.rows<<" "<<frame.cols<<endl;

		//imshow("track_frame",frame);

		//cvWaitKey(10);

		//cout<< int(frame.at<float>(239,10)) << int(frame.at<float>(239,20))<< endl;

		//imwrite("frame.jpg",frame);

		//print_img(frame,"frame.txt");

		x = get_subwindow(frame, pos, sz, cos_window);

		//print_mat(x,"x.txt");

		if (i > 0)

		{

			k = dense_guess_kernel(sigma, x, z);

			//print_mat(k,"k.txt");

			//kf = fft2(k)

			//IplImage* k_temp = &IplImage(k);

			cv::Mat kf = fft2d(k);

			vector<cv::Mat> kf_ri(kf.channels());

			cv::split(kf, kf_ri);

			//print_mat(kf_ri[0],"kf.txt");

			//response = real(ifft2(alphaf .* fft2(k)));   %(Eq. 9)

			vector<cv::Mat> response_ri(2);

			cv::Mat response = c_mul(alphaf, kf);

			idft(response, response);

			response = response / (response.rows*response.cols);

			cv::split(response, response_ri);

			//print_mat(response_ri[0],"response.txt");

			//%target location is at the maximum response

			int max_row, max_col;

			double max_response = 0;

			for (int j = 0; j < response_ri[0].rows; j++)

			{

				for (int k = 0; k < response_ri[0].cols; k++)

				{

					if (response_ri[0].at<float>(j, k) > max_response)

					{

						max_response = response_ri[0].at<float>(j, k);

						max_row = j;

						max_col = k;

					}

				}

			}

			pos = pos - cv::Point(floor(sz[1] / 2), floor(sz[0] / 2)) + cv::Point(max_col + 1, max_row + 1);

		}

		x = get_subwindow(frame, pos, sz, cos_window);

		//print_mat(x,"x.txt");

		k = dense_guess_kernel(sigma, x);

		//print_mat(k,"k.txt");

		//new_alphaf = yf ./ (fft2(k) + lambda);   %(Eq. 7)

		//IplImage *k_t = &IplImage(k);

		new_alphaf = c_div(yf, (fft2d(k) + lambda));

		vector<cv::Mat> new_alphaf_ri(2);

		cv::split(new_alphaf, new_alphaf_ri);

		//print_mat(new_alphaf_ri[0],"new_alphaf.txt");

		cv::Mat new_z = x;

		if (i == 0)

		{

			alphaf = new_alphaf;

			z = x;

		}

		else

		{

			alphaf = (1 - interp_factor) * alphaf + interp_factor*new_alphaf;

			z = (1 - interp_factor) * z + interp_factor * new_z;

		}

		i++;

		cv::Mat frame_print;

		org.copyTo(frame_print);

		rectangle(frame_print, cv::Point(pos.x - target_sz[1] / 2, pos.y - target_sz[0] / 2), cv::Point(pos.x + target_sz[1] / 2, pos.y + target_sz[0] / 2), CV_RGB(255, 255, 255), 1);

		circle(frame_print, cv::Point(pos.x, pos.y), 2, cvScalar(255, 0, 0));

		//rectangle(frame_print, cv::Point(frame_print.cols/2 - 30, frame_print.rows/2 - 30), cv::Point(frame_print.cols / 2 + 30, frame_print.rows / 2 + 30), CV_RGB(0, 255, 0), 1);

		circle(frame_print, cv::Point(frame_print.cols/2, frame_print.rows/2), 15, cvScalar(255, 0, 255));

		imshow("img", frame_print);

		BOX.x = pos.x;

		BOX.y = pos.y;

		BOX.width = target_sz[1];

		BOX.height = target_sz[0];

		BOX.flag = tracking_flag;

		memcpy(BOX_DATA, &BOX, sizeof(TrackBox));

		imgInfHead img_inf_head;

		img_inf_head.width = org.cols;

		img_inf_head.height = org.rows;

		img_inf_head.type = org.type();

		int channels = org.channels();

		memcpy(SEND_IMG00_HEAD, &img_inf_head, sizeof(imgInfHead));

		memcpy(SEND_IMG00_DATA, org.data, org.cols*org.rows*channels);

		if (cvWaitKey(10) == 's')

		{

			tracking_flag = false;

		}

	}

	return;

}

void CSK_Tracker::tracke_one(ifstream &infile, cv::Point pos_first, int frame_count, int* target_sz, cv::VideoCapture capture)

{

	//%window size, taking padding into account

	int sz[2] = { floor(target_sz[0] * (1 + padding)),floor(target_sz[1] * (1 + padding)) };

	//%desired output (gaussian shaped), bandwidth proportional to target size

	double output_sigma = sqrt(target_sz[0] * target_sz[1])*output_sigma_factor;

	cv::Mat rs(sz[0], sz[1], CV_32FC1);

	cv::Mat cs(sz[0], sz[1], CV_32FC1);

	for (int i = 0; i < sz[0]; i++)

	{

		for (int j = 0; j < sz[1]; j++)

		{

			rs.at<float>(i, j) = i - sz[0] / 2 + 1;

			cs.at<float>(i, j) = j - sz[1] / 2 + 1;

		}

	}

	//print_mat(rs,"rs.txt");

	//print_mat(cs,"cs.txt");

	cv::Mat y;

	exp((-0.5 / pow(output_sigma, 2))*(rs.mul(rs) + cs.mul(cs)), y);

	//print_mat(y,"y.txt");

	//yf = fft2(y)

	cv::Mat yf;

	//IplImage *y_temp = &IplImage(y);

	yf = fft2d(y);

	vector<cv::Mat> yf_ri(yf.channels());

	cv::split(yf, yf_ri);

	//%store pre-computed cosine window

	cv::Mat cos_window(sz[0], sz[1], CV_32FC1);

	hann2d(cos_window);

	//print_mat(cos_window,"cos_window.txt");

	cv::Mat frame;

	cv::Mat x;

	cv::Mat k;

	cv::Mat z;

	cv::Mat alphaf;

	cv::Mat new_alphaf;

	cv::Point pos = pos_first;

	cv::namedWindow("haha");

	string file_name;

	for (int i = 0; i < frame_count; ++i) {

		double totaltime;

		if (!capture.read(frame))

		{

			cout << "读取视频失败" << endl;

			return;

		}

		/*getline(infile,file_name);

		frame = imread(file_name);*/

		if (frame.empty())

		{

			cout << "fail to open frame" << i << endl;

			break;

		}

		if (frame.channels() > 1)

		{

			cvtColor(frame, frame, CV_BGR2GRAY);

		}

		//%extract and pre-process subwindow

		/*ofstream F("frame.txt");

		for(int p = 0;p < frame.rows;p ++){

		for(int q = 0;q < frame.cols;q++){

		F << int(frame.at<uchar>(p,q)) << " ";

		}

		F << '\n';

		}*/

		//cout<<frame.rows<<" "<<frame.cols<<endl;

		//imshow("track_frame",frame);

		//cvWaitKey(10);

		//cout<< int(frame.at<float>(239,10)) << int(frame.at<float>(239,20))<< endl;

		//imwrite("frame.jpg",frame);

		//print_img(frame,"frame.txt");

		x = get_subwindow(frame, pos, sz, cos_window);

		//print_mat(x,"x.txt");

		if (i > 0)

		{

			k = dense_guess_kernel(sigma, x, z);

			//print_mat(k,"k.txt");

			//kf = fft2(k)

			//IplImage* k_temp = &IplImage(k);

			cv::Mat kf = fft2d(k);

			vector<cv::Mat> kf_ri(kf.channels());

			cv::split(kf, kf_ri);

			//print_mat(kf_ri[0],"kf.txt");

			//response = real(ifft2(alphaf .* fft2(k)));   %(Eq. 9)

			vector<cv::Mat> response_ri(2);

			cv::Mat response = c_mul(alphaf, kf);

			idft(response, response);

			response = response / (response.rows*response.cols);

			cv::split(response, response_ri);

			//print_mat(response_ri[0],"response.txt");

			//%target location is at the maximum response

			int max_row, max_col;

			double max_response = 0;

			for (int j = 0; j < response_ri[0].rows; j++)

			{

				for (int k = 0; k < response_ri[0].cols; k++)

				{

					if (response_ri[0].at<float>(j, k) > max_response)

					{

						max_response = response_ri[0].at<float>(j, k);

						max_row = j;

						max_col = k;

					}

				}

			}

			pos = pos - cv::Point(floor(sz[1] / 2), floor(sz[0] / 2)) + cv::Point(max_col + 1, max_row + 1);

		}

		x = get_subwindow(frame, pos, sz, cos_window);

		//print_mat(x,"x.txt");

		k = dense_guess_kernel(sigma, x);

		//print_mat(k,"k.txt");

		//new_alphaf = yf ./ (fft2(k) + lambda);   %(Eq. 7)

		//IplImage *k_t = &IplImage(k);

		new_alphaf = c_div(yf, (fft2d(k) + lambda));

		vector<cv::Mat> new_alphaf_ri(2);

		cv::split(new_alphaf, new_alphaf_ri);

		//print_mat(new_alphaf_ri[0],"new_alphaf.txt");

		cv::Mat new_z = x;

		if (i == 0)

		{

			alphaf = new_alphaf;

			z = x;

		}

		else

		{

			alphaf = (1 - interp_factor) * alphaf + interp_factor*new_alphaf;

			z = (1 - interp_factor) * z + interp_factor * new_z;

		}

		//draw

		// 		rectangle(frame,Point(pos.x - target_sz/2,pos.y - target_sz/2),Point(pos.x + target_sz/2,pos.y + target_sz/2),CV_RGB(255,255,255),2);

		// 		imshow("haha",frame);

		// 		uchar key;

		// 		key = waitKey(10);

		// 		if (key == 'q')

		// 		{

		// 			break;

		// 		}

		cv::Mat frame_print;

		frame.copyTo(frame_print);

		cv::rectangle(frame_print, cv::Point(pos.x - target_sz[1] / 2, pos.y - target_sz[0] / 2), cv::Point(pos.x + target_sz[1] / 2, pos.y + target_sz[0] / 2), CV_RGB(255, 255, 255), 1);

		cv::circle(frame_print, cv::Point(pos.x, pos.y), 2, cvScalar(255, 0, 0));

		/*totaltime = (double)(finish - start) / CLOCKS_PER_SEC;*/

		//cout << "\n此程序的运行时间为" << totaltime * 1000 << "ms！" << endl;

		imshow("haha", frame_print);

		cvWaitKey(10);

	}

	return;

}

//void CSK_Tracker::run_tracker(string video_name, Point pos, int target_sz)

//{

//

//	VideoCapture capture(video_name);

//	if (!capture.isOpened())

//	{

//		cout << "Fail to open video " << video_name << endl;

//		return;

//	}

//	int frame_count = int(capture.get(CV_CAP_PROP_FRAME_COUNT));

//	double rate = capture.get(CV_CAP_PROP_FPS);

//	int width = capture.get(CV_CAP_PROP_FRAME_WIDTH);

//	int height = capture.get(CV_CAP_PROP_FRAME_HEIGHT);

//

//	//%window size, taking padding into account

//	int sz = floor(target_sz * (1 + padding));

//

//	//%desired output (gaussian shaped), bandwidth proportional to target size

//	double output_sigma = target_sz*output_sigma_factor;

//	Mat rs(sz,sz,CV_32FC1);

//	Mat cs(sz,sz,CV_32FC1);

//	for (int i = 0; i < sz; i++)

//	{

//		for (int j = 0; j < sz; j++)

//		{

//			rs.at<float>(i,j) = i - sz/2 +1;

//			cs.at<float>(i,j) = j - sz/2 +1;

//		}

//	}

//

//	Mat y;

//	exp((-0.5/pow(output_sigma,2))*(rs.mul(rs) + cs.mul(cs)),y);

//

//	//yf = fft2(y)

//	Mat yf;

//	yf = fft2d(y);

//	vector<Mat> yf_ri(yf.channels());

//	cv::split(yf,yf_ri);

//

//

//	//%store pre-computed cosine window

//	Mat cos_window(sz,sz,CV_32FC1);

//	hann2d(cos_window);

//

//	vector<Point> position(frame_count);

//

//	Mat frame;

//	Mat x;

//	Mat k;

//	Mat z;

//	Mat alphaf;

//	Mat new_alphaf;

//

//	namedWindow("haha");

//

//	for (int i = 0; i < frame_count; i++)

//	{

//		if (!capture.read(frame))

//		{

//			cout << "read frame failed!" << endl;

//		}

//		if (frame.channels() > 1)

//		{

//			cvtColor(frame,frame,CV_BGR2GRAY);

//		}

//

//		//%extract and pre-process subwindow

//

//		x = get_subwindow(frame, pos, sz, cos_window);

//

//

//		if (i > 0)

//		{

//			k = dense_guess_kernel(sigma,x,z);

//

//			//kf = fft2(k)

//			Mat kf = fft2d(k);

//			vector<Mat> kf_ri(kf.channels());

//			cv::split(kf,kf_ri);

//

//			//response = real(ifft2(alphaf .* fft2(k)));   %(Eq. 9)

//

//			vector<Mat> response_ri(2);

//			Mat response = c_mul(alphaf,kf);

//			idft(response,response);

//			response = response/(response.rows*response.cols);

//			cv::split(response,response_ri);

//

//			//%target location is at the maximum response

//			int max_row, max_col;

//			double max_response = 0;

//			for (int j = 0; j < response_ri[0].rows; j++)

//			{

//				for (int k = 0; k < response_ri[0].cols; k++)

//				{

//					if (response_ri[0].at<float>(j,k) > max_response)

//					{

//						max_response = response_ri[0].at<float>(j,k);

//						max_row = j;

//						max_col = k;

//					}

//				}

//			}

//			pos = pos - Point(floor(sz/2),floor(sz/2)) + Point(max_col,max_row);

//		}

//

//		x = get_subwindow(frame,pos,sz,cos_window);

//		k = dense_guess_kernel(sigma,x);

//		//new_alphaf = yf ./ (fft2(k) + lambda);   %(Eq. 7)

//		new_alphaf = c_div(yf,(fft2d(k) + lambda));

//		vector<Mat> new_alphaf_ri(2);

//		cv::split(new_alphaf,new_alphaf_ri);

//

//		Mat new_z = x;

//

//		if (i == 0)

//		{

//			alphaf = new_alphaf;

//			z = x;

//		}

//		else

//		{

//			alphaf = (1 - interp_factor) * alphaf +interp_factor*new_alphaf;

//			z = (1 - interp_factor) * z + interp_factor * new_z;

//		}

//

//		position[i] = pos;

//

//		//draw

//		rectangle(frame,Point(pos.x - target_sz/2,pos.y - target_sz/2),Point(pos.x + target_sz/2,pos.y + target_sz/2),CV_RGB(255,255,255),2);

//		imshow("haha",frame);

//		uchar key;

//		key = waitKey(10);

//		if (key == 'q')

//		{

//			break;

//		}

//	}

//}

cv::Mat CSK_Tracker::conj(cv::Mat a)

{

	cv::Mat b;

	a.copyTo(b);

	vector<cv::Mat> b_ri(2);

	cv::split(b,b_ri);

	b_ri[1] = -b_ri[1];

	merge(b_ri,b);

	return b;

}

cv::Mat CSK_Tracker::c_mul(cv::Mat a, cv::Mat b)

{

	if (!(a.channels() == 2 || b.channels() == 2))

	{

		cout << "c_mul error!" << endl;

	}

	vector<cv::Mat> a_ri(2);

	vector<cv::Mat> b_ri(2);

	cv::split(a,a_ri);

	cv::split(b,b_ri);

	vector<cv::Mat> c_ri(2);

	c_ri[0] = a_ri[0].mul(b_ri[0]) - a_ri[1].mul(b_ri[1]);

	c_ri[1] = a_ri[0].mul(b_ri[1]) + a_ri[1].mul(b_ri[0]);

	cv::Mat c;

	merge(c_ri,c);

	return c;

}

cv::Mat CSK_Tracker::c_div(cv::Mat a, cv::Mat b)

{

	cv::Mat c;

	c = c_mul(a,conj(b));

	vector<cv::Mat> c_ri(2);

	cv::split(c,c_ri);

	vector<cv::Mat> mag_b_ri(2);

	cv::Mat mag_b = c_mul(b,conj(b));

	cv::split(mag_b,mag_b_ri);

	c_ri[0] = c_ri[0]/mag_b_ri[0];

	c_ri[1] = c_ri[1]/mag_b_ri[0];

	merge(c_ri,c);

	return c;

}

cv::Mat CSK_Tracker::fft2d(cv::Mat a)

{

	cv::Mat padded_a;

	//int m_a = getOptimalDFTSize(a.rows);

	//int n_a = getOptimalDFTSize(a.cols);

	int m_a = a.rows;

	int n_a = a.cols;

	copyMakeBorder(a, padded_a, 0, m_a - a.rows, 0, n_a - a.cols, cv::BORDER_CONSTANT, cv::Scalar::all(0));

	cv::Mat planes_a[] = { cv::Mat_<float>(padded_a), cv::Mat::zeros(padded_a.size(),CV_32F)};

	cv::Mat af;

	merge(planes_a, 2, af);

	dft(af,af);

	return af;

}

//Mat CSK_Tracker::fft2d(IplImage *src)

//{   //实部、虚部

//    IplImage *image_Re = 0, *image_Im = 0, *Fourier = 0;

//	IplImage *D;

//    //   int i, j;

//    image_Re = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 1);  //实部

//    //Imaginary part

//    image_Im = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 1);  //虚部

//    //2 channels (image_Re, image_Im)

//    Fourier = cvCreateImage(cvGetSize(src), IPL_DEPTH_64F, 2);

//    // Real part conversion from u8 to 64f (double)

//    cvConvertScale(src, image_Re);

//    // Imaginary part (zeros)

//    cvZero(image_Im);

//    // Join real and imaginary parts and stock them in Fourier image

//    cvMerge(image_Re, image_Im, 0, 0, Fourier);

//

//    // Application of the forward Fourier transform

//    cvDFT(Fourier, D, CV_DXT_FORWARD);

//    cvReleaseImage(&image_Re);

//    cvReleaseImage(&image_Im);

//    cvReleaseImage(&Fourier);

//	Mat dst = Mat(D);

//	return dst;

//} 

void CSK_Tracker::print_mat(cv::Mat a, string file_name)

{

	ofstream fout(file_name);

	int col = a.cols;

	int row = a.rows;

	for(int i = 0; i< row; i++){

		for(int j = 0; j < col; j++){

			fout << a.at<float>(i,j) << " ";

		}

		fout << '\n';

	}

	fout.close();

}

void CSK_Tracker::print_img(cv::Mat a, string file_name)

{

	ofstream fout(file_name);

	int col = a.cols;

	int row = a.rows;

	for(int i = 0; i< row; i++){

		for(int j = 0; j < col; j++){

			fout << float(a.at<uchar>(i,j)) << " ";

		}

		fout << endl;

	}

	fout.close();

}

　　

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