eye_detect.py

from imutils.video import VideoStream
from imutils import face_utils
import argparse
import imutils
import time
import dlib
import cv2


ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=True,
	help="path to facial landmark predictor")
ap.add_argument("-r", "--picamera", type=int, default=-1,
	help="whether or not the Raspberry Pi camera should be used")
args = vars(ap.parse_args())

print("[INFO] loading facial landmark predictor...")
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(args["shape_predictor"])

print("[INFO] camera sensor warming up...")
vs = VideoStream(usePiCamera=args["picamera"] > 0).start()
time.sleep(2.0)

while True:

	frame = vs.read()
	frame = imutils.resize(frame, width=600)
	gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)


	rects = detector(gray, 0)
	for (i,rect) in enumerate(rects):

		shape = predictor(gray, rect)
		shape = face_utils.shape_to_np(shape)
		for (name, (i,j)) in face_utils.FACIAL_LANDMARKS_IDXS.items():
			for (x, y) in shape[36:48]:
				cv2.circle(frame, (x, y), 1, (0, 0, 255), 0)
			for (x, y) in shape[48:68]:
				cv2.circle(frame, (x, y), 1, (0, 0, 255), 0)
	cv2.imshow("Frame", frame)
	key = cv2.waitKey(1) & 0xFF

	if key == ord("q"):
		break

cv2.destroyAllWindows()
vs.stop()