Dlib's 68 point face detection

68-point-face-detection.py

import cv2
import imutils
import dlib
import sys
from renderface2 import renderFace2

# Capture the webcam feed
cap = cv2.VideoCapture(0)

# 68 point face model
PREDICTOR_PATH = "./models/shape_predictor_68_face_landmarks.dat"
# face detector
detector = dlib.get_frontal_face_detector()
# 68 points predictor
predictor = dlib.shape_predictor(PREDICTOR_PATH)

while(True):
    # Read the frame
    ret, frame = cap.read()
    
    if ret == True:
        pass
    else:
        print("Unable to read frame")
        sys.exit()
    
    #Resize the frame
    frame = imutils.resize(frame, width = 640)
    frame = imutils.resize(frame, height = 480)
    
    #Convert to RGB 
    framecvt = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)

    # Detect faces in the frame
    faces = detector(framecvt,0)

    # Iterate over faces in the frame
    for face in faces:
        newRect = dlib.rectangle(int(face.left()), int(face.top()),int(face.right()), int(face.bottom()))
        # Find face landmarks by providing reactangle for each face
        shape = predictor(framecvt, newRect)
        # Draw facial landmarks
        renderFace2(frame, shape)

    # Display the resulting frame
    winname = '68 Point detection'
    cv2.imshow(winname,frame)
    
    #Waits for a user input to quit the application
    key = cv2.waitKey(10)
    mouse = cv2.getWindowProperty(winname,cv2.WND_PROP_VISIBLE)
    if key == 27  or  mouse < 1:
        break

# When everything done, release the capture
cap.release()
cv2.destroyAllWindows()