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



detector = dlib.get_frontal_face_detector()
predictor = shape_predictor_68_face_landmarks.dat
#data set for facial landmark detection
image = example.jpg
#provide an example image here
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_SIMPLEX, 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)
