1功能
- 鼠标选取目标 S按键取消重新选择
- 共享内存目标框 中心 X Y 边框W H
/////////////////////////////////////////////////////////////////////////
// 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.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();
}
