c – 将opencv库与g链接起来

您好我正在尝试编译从该网站获取的c文件： http://opencv-code.com/tutorials/eye-detection-and-tracking/用于眼睛跟踪.
但我对此有点新鲜,我并不真正了解库是如何链接的.
我知道include头的绝对路径位于/ user / include / opencv2中.
如何在gcc命令行(ubuntu)中链接它？
我试过这个命令：

$g++ -Wall eye-tracking.cpp -o eyeTracking

看来我还需要链接其他库.我尝试将使用此命令找到的链接：

$pkg-config --libs opencv

但在这里我再也不知道如何将输出链接到我的命令.
我通过输入以下命令尝试了我的逻辑：

$g++ -Wall eye-tracking.cpp -I `pkg-config --libs opencv` -o eyeTracking

当然它不起作用,我真的不明白我在做什么：P

有人可以向我解释一下怎么样？

在这里您可以找到整个文件代码：

/**
* eye-tracking.cpp:
* Eye detection and tracking with OpenCV
*
* This program tries to detect and tracking the user's eye with webcam.
* At startup,the program performs face detection followed by eye detection
* using OpenCV's built-in Haar cascade classifier. If the user's eye detected
* successfully,an eye template is extracted. This template will be used in
* the subsequent template matching for tracking the eye.
*/
#include <opencv2/imgproc/imgproc.hpp>
#include <opencv2/highgui/highgui.hpp>
#include <opencv2/objdetect/objdetect.hpp>

cv::CascadeClassifier face_cascade;
cv::CascadeClassifier eye_cascade;

/**
* Function to detect human face and the eyes from an image.
*
* @param im The source image
* @param tpl Will be filled with the eye template,if Detection success.
* @param rect Will be filled with the bounding Box of the eye
* @return zero=Failed,nonzero=success
*/
int detectEye(cv::Mat& im,cv::Mat& tpl,cv::rect& rect)
{
std::vector<cv::rect> faces,eyes;
face_cascade.detectMultiScale(im,faces,1.1,2,0|CV_HAAR_SCALE_IMAGE,cv::Size(30,30));

for (int i = 0; i < faces.size(); i++)
{
cv::Mat face = im(faces[i]);
eye_cascade.detectMultiScale(face,eyes,cv::Size(20,20));

if (eyes.size())
{
rect = eyes[0] + cv::Point(faces[i].x,faces[i].y);
tpl = im(rect);
}
}

return eyes.size();
}

/**
* Perform template matching to search the user's eye in the given image.
*
* @param im The source image
* @param tpl The eye template
* @param rect The eye bounding Box,will be updated with the new LOCATIOn of the eye
*/
void trackEye(cv::Mat& im,cv::rect& rect)
{
cv::Size size(rect.width * 2,rect.height * 2);
cv::rect window(rect + size - cv::Point(size.width/2,size.height/2));

window &= cv::rect(0,im.cols,im.rows);

cv::Mat dst(window.width - tpl.rows + 1,window.height - tpl.cols + 1,CV_32FC1);
cv::matchTemplate(im(window),tpl,dst,CV_TM_SQDIFF_NORMED);

double minval,maxval;
cv::Point minloc,maxloc;
cv::minMaxLoc(dst,&minval,&maxval,&minloc,&maxloc);

if (minval <= 0.2)
{
rect.x = window.x + minloc.x;
rect.y = window.y + minloc.y;
}
else
rect.x = rect.y = rect.width = rect.height = 0;
}

int main(int argc,char** argv)
{
// Load the cascade classifiers
// Make sure you point the XML files to the right path,or
// just copy the files from [OPENCV_DIR]/data/haarcascades directory
face_cascade.load("haarcascade_frontalface_alt2.xml");
eye_cascade.load("haarcascade_eye.xml");

// Open webcam
cv::VideoCapture cap(0);

// check if everything is ok
if (face_cascade.empty() || eye_cascade.empty() || !cap.isOpened())
return 1;

// Set video to 320x240
cap.set(CV_CAP_PROP_FRAME_WIDTH,320);
cap.set(CV_CAP_PROP_FRAME_HEIGHT,240);

cv::Mat frame,eye_tpl;
cv::rect eye_bb;

while (cv::waitKey(15) != 'q')
{
cap >> frame;
if (frame.empty())
break;

// Flip the frame horizontally,Windows users might need this
cv::flip(frame,frame,1);

// Convert to grayscale and
// adjust the image contrast using histogram equalization
cv::Mat gray;
cv::cvtColor(frame,gray,Cv_bGR2GRAY);

if (eye_bb.width == 0 && eye_bb.height == 0)
{
// Detection stage
// Try to detect the face and the eye of the user
detectEye(gray,eye_tpl,eye_bb);
}
else
{
// Tracking stage with template matching
trackEye(gray,eye_bb);

// Draw bounding rectangle for the eye
cv::rectangle(frame,eye_bb,CV_RGB(0,255,0));
}

// Display video
cv::imshow("video",framE);
}

return 0;
}