Hi
I'm using facial landmark detector (dlib) to detect eye blinks . How the eye landmarks can be imported to a file ?
I need to use eye landmarks to calculate the ration between height and width of eye and to use SVM to classify blinks
Update : when I try to write landmark point to a file , different valuses are saved than the displayed landmarks in terminal windows , how to fix ?
Thanks
#include
#include
#include
#include
#include
#include
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;
frontal_face_detector detector = get_frontal_face_detector();
shape_predictor pose_model;
deserialize("shape_predictor_68_face_landmarks.dat") >> pose_model;
while(!win.is_closed())
{
cv::Mat temp;
cap >> temp;
cv_image cimg(temp);
// Detect faces
std::vector faces = detector(cimg);
// Find the pose of each face.
std::vector shapes;
ofstream outputfile;
outputfile.open("data1.csv");
for (unsigned long i = 0; i < faces.size(); ++i)
{
full_object_detection shape = pose_model(cimg, faces[i]);
cout << "number of parts: "<< shape.num_parts() << endl;
cout << "Eye Landmark points for right eye : "<< endl;
cout << "pixel position of 36 part: " << shape.part(36) << endl;
cout << "pixel position of 37 part: " << shape.part(37) << endl;
cout << "pixel position of 38 part: " << shape.part(38) << endl;
cout << "pixel position of 39 part: " << shape.part(39) << endl;
cout << "pixel position of 40 part: " << shape.part(40) << endl;
cout << "pixel position of 41 part: " << shape.part(41) << endl;
cout << endl;
cout << "Eye Landmark points for left eye : "<< endl;
cout << "pixel position of 42 part: " << shape.part(42) << endl;
cout << "pixel position of 43 part: " << shape.part(43) << endl;
cout << "pixel position of 44 part: " << shape.part(44) << endl;
cout << "pixel position of 45 part: " << shape.part(45) << endl;
cout << "pixel position of 46 part: " << shape.part(46) << endl;
cout << "pixel position of 47 part: " << shape.part(47) << endl;
double P37_41_x = shape.part(37).x() - shape.part(41).x();
double P37_41_y= shape.part(37).y() -shape.part(41).y() ;
double p37_41_sqrt=sqrt((P37_41_x * P37_41_x) + (P37_41_y * P37_41_y));
double P38_40_x = shape.part(38).x() - shape.part(40).x();
double P38_40_y = shape.part(38).y() - shape.part(40).y();
double p38_40_sqrt=sqrt((P38_40_x * P38_40_x) + (P38_40_y * P38_40_y));
double P36_39_x = shape.part(36).x() - shape.part(39).x();
double P36_39_y = shape.part(36).y() - shape.part(39).y();
double p36_39_sqrt=sqrt((P36_39_x * P36_39_x) + (P36_39_y * P36_39_y));
double EAR= p37_41_sqrt + p38_40_sqrt/2* p36_39_sqrt;
cout << "EAR value = " << EAR << endl;
shapes.push_back(pose_model(cimg, faces[i]));
const full_object_detection& d = shapes[0];
}
win.clear_overlay();
win.set_image(cimg);
win.add_overlay(render_face_detections(shapes));
}
}
catch(serialization_error& e)
{
cout << "You need dlib's default face landmarking model file to run this example." << endl;
cout << "You can get it from the following URL: " << endl;
cout << " http://dlib.net/files/shape_predictor_68_face_landmarks.dat.bz2" << endl;
cout << endl << e.what() << endl;
}
catch(exception& e)
{
cout << e.what() << endl;
}
}
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