Michael-BJ / Face-Landmark-Detection

The program can put 68 points on the face, especially on the mouth, nose and eyes. The points can be used to determine whether the person is smiling, sleepy or yawning

How it's works

1. First download the library that we need

pip install opencv-python
pip install numpy 
pip install dlib
pip install imutils

2. Connect the webcam to the program

cap = cv2.VideoCapture(0)
while True:
    _, frame = cap.read()
    cv2.imshow('Facial Landmark', frame)
        if cv2.waitKey(1) & 0xFF == ord('q'):
            break

cap.release()
cv2.destroyAllWindows()

3. Make the program to target or detect the face

detector = dlib.get_frontal_face_detector() 

4. Insert the libary that we need

predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat") 

5. Change the BGR to the grayscale

gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

6. Detect the face in the grayscale image

faces = detector(gray)

7. Convert the coordinates of facial landmark to a numpy

point = predictor(gray, face)
	    points = face_utils.shape_to_np(point)

8. Draw a point in a face

 for (x, y) in points :
		    cv2.circle(frame, (x, y), 1, (0, 0, 255), 3)

Demo

Clik the picture to see the Video