使用dlib库从摄像头中取人脸进行人眼检测的c++示例代码
时间: 2023-02-12 18:57:59 浏览: 165
使用摄像头的人脸识别算法c++程序
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这是一段使用 dlib 库从摄像头中检测人脸并进行人眼检测的 C++ 示例代码:
```
#include <dlib/opencv.h>
#include <opencv2/highgui/highgui.hpp>
#include <dlib/image_processing/frontal_face_detector.h>
#include <dlib/image_processing/render_face_detections.h>
#include <dlib/image_processing.h>
using namespace dlib;
using namespace std;
int main()
{
try
{
cv::VideoCapture cap(0);
if (!cap.isOpened())
{
cerr << "Unable to connect to camera" << endl;
return 1;
}
image_window win;
// Load face detection and pose estimation models.
frontal_face_detector detector = get_frontal_face_detector();
shape_predictor pose_model;
deserialize("shape_predictor_68_face_landmarks.dat") >> pose_model;
// Grab and process frames until the main window is closed by the user.
while(!win.is_closed())
{
// Grab a frame
cv::Mat temp;
if (!cap.read(temp))
{
break;
}
// Turn OpenCV's Mat into something dlib can deal with. Note that this just
// wraps the Mat object, it doesn't copy anything. So cimg is only valid as
// long as temp is valid. Also don't do anything to temp that would cause it
// to reallocate the memory which stores the image as that will make cimg
// contain dangling pointers. This basically means you shouldn't modify temp
// while using cimg.
cv_image<bgr_pixel> cimg(temp);
// Detect faces
std::vector<rectangle> faces = detector(cimg);
// Find the pose of each face.
std::vector<full_object_detection> shapes;
for (unsigned long i = 0; i < faces.size(); ++i)
shapes.push_back(pose_model(cimg, faces[i]));
// Display it all on the screen
win.clear_overlay();
win.set_image(cimg);
win.add_overlay(render_face_detections(shapes));
}
}
catch(exception& e)
{
cout << "\nexception thrown!" << endl;
cout << e.what() << endl;
}
}
```
注意:需要先下载dlib的shape_predictor_68_face_landmarks.dat模型文件,并将其路径替换到代码中 deserialize("shape_predictor_68_face_landmarks.dat") >> pose
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