facial_landmarks.py

from imutils import face_utils
import numpy as np
import argparse
import imutils
import dlib
import cv2

ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required = True,
    help = "path to facial landmark predictor")
ap.add_argument("-i", "--image", required = True,
    help = "path to input image")
args = vars(ap.parse_args())

detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(args["shape_predictor"])

image = cv2.imread(args["image"])
image = imutils.resize(image, width = 500)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

rects = detector(gray, 1)

for (i, rect) in enumerate(rects):
    shape = predictor(gray, rect)
    shape = face_utils.shape_to_np(shape)

    (x, y, w, h) = face_utils.rect_to_bb(rect)
    cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)

    cv2.putText(image, "Face #{}".format(i+1), (x-10, y-10), 
        cv2.FONT_HERSHEY_COMPLEX, 0.5, (0, 255, 0), 2)
    for (x, y) in shape:
        cv2.circle(image, (x, y), 1, (0, 0, 255), -1)
    
cv2.imshow("Output", image)
cv2.waitKey(0)