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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);
			
		}
		
	}
}

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//#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

  技术分享图片

#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.cols - 1),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();
}

  

图像跟踪

标签:共享   algorithm   miss   type   als   ios   event   run   ica   

原文地址:https://www.cnblogs.com/kekeoutlook/p/8353357.html

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