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gwanryo/sleep_n_smash.py

Last active Feb 5, 2020
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# https://github.com/mans-men/eye-blink-detection-demo
# import the necessary packages
from scipy.spatial import distance as dist
from imutils.video import FileVideoStream
from imutils.video import VideoStream
from imutils import face_utils
import argparse
import imutils
import time
import dlib
import cv2
import serial
def eye_aspect_ratio(eye):
# compute the euclidean distances between the two sets of
# vertical eye landmarks (x, y)-coordinates
A = dist.euclidean(eye[1], eye[5])
B = dist.euclidean(eye[2], eye[4])
# compute the euclidean distance between the horizontal
# eye landmark (x, y)-coordinates
C = dist.euclidean(eye[0], eye[3])
# compute the eye aspect ratio
ear = (A + B) / (2.0 * C)
# return the eye aspect ratio
return ear
# construct the argument parse and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor",default="shape_predictor_68_face_landmarks.dat",
help="path to facial landmark predictor")
ap.add_argument("-v", "--video", type=str, default="camera",
help="path to input video file")
ap.add_argument("-t", "--threshold", type = float, default=0.20,
help="threshold to determine closed eyes")
ap.add_argument("-f", "--frames", type = int, default=2,
help="the number of consecutive frames the eye must be below the threshold")
ap.add_argument("-s", "--serial", type=str, default="COM3",
help="serial port path")
ap.add_argument("-e", "--speed", type=int, default=9600,
help="serial connection speed")
def main() :
args = vars(ap.parse_args())
EYE_AR_THRESH = args['threshold']
EYE_AR_CONSEC_FRAMES = args['frames']
# initialize the frame counters and the total number of blinks
COUNTER = 0
TOTAL = 0
SLEEP = 0
SLEEP_TIME = 0
# initialize serial port
print("[INFO] connect to serial port...")
ser = serial.Serial()
ser.port = args['serial']
ser.baudrate = args['speed']
try:
ser.open()
except:
print("[WARN] serial connection failed")
exit()
print("[INFO] verify serial is ready")
while not ser.is_open:
pass
# initialize dlib's face detector (HOG-based) and then create
# the facial landmark predictor
print("[INFO] loading facial landmark predictor...")
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(args["shape_predictor"])
# grab the indexes of the facial landmarks for the left and
# right eye, respectively
(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
# start the video stream thread
print("[INFO] starting video stream thread...")
print("[INFO] print q to quit...")
if args['video'] == "camera":
vs = VideoStream(src=0).start()
fileStream = False
else:
vs = FileVideoStream(args["video"]).start()
fileStream = True
time.sleep(1.0)
# verify crane is okay
ser.write(b'Hello, this is sleep & smash')
print("[INFO] crane is ready!")
# loop over frames from the video stream
while True:
# if this is a file video stream, then we need to check if
# there any more frames left in the buffer to process
if fileStream and not vs.more():
break
# grab the frame from the threaded video file stream, resize
# it, and convert it to grayscale
# channels)
frame = vs.read()
frame = imutils.resize(frame, width=450)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# detect faces in the grayscale frame
rects = detector(gray, 0)
# student is sleeping if camera cannot detect eyes
if not rects:
SLEEP = 1
# loop over the face detections
for rect in rects:
# determine the facial landmarks for the face region, then
# convert the facial landmark (x, y)-coordinates to a NumPy
# array
shape = predictor(gray, rect)
shape = face_utils.shape_to_np(shape)
# extract the left and right eye coordinates, then use the
# coordinates to compute the eye aspect ratio for both eyes
leftEye = shape[lStart:lEnd]
rightEye = shape[rStart:rEnd]
leftEAR = eye_aspect_ratio(leftEye)
rightEAR = eye_aspect_ratio(rightEye)
# average the eye aspect ratio together for both eyes
ear = (leftEAR + rightEAR) / 2.0
# compute the convex hull for the left and right eye, then
# visualize each of the eyes
leftEyeHull = cv2.convexHull(leftEye)
rightEyeHull = cv2.convexHull(rightEye)
cv2.drawContours(frame, [leftEyeHull], -1, (0, 255, 0), 1)
cv2.drawContours(frame, [rightEyeHull], -1, (0, 255, 0), 1)
# check to see if the eye aspect ratio is below the blink
# threshold, and if so, increment the blink frame counter
# student is sleeping if ear value under threshold
if ear < EYE_AR_THRESH:
COUNTER += 1
SLEEP = 1
# otherwise, the eye aspect ratio is not below the blink
# threshold
else:
# if the eyes were closed for a sufficient number of
# then increment the total number of blinks
if COUNTER >= EYE_AR_CONSEC_FRAMES:
TOTAL += 1
# reset the eye frame counter
COUNTER = 0
# draw the total number of blinks on the frame along with
# the computed eye aspect ratio for the frame
cv2.putText(frame, "Blinks: {}".format(TOTAL), (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
cv2.putText(frame, "EAR: {:.2f}".format(ear), (300, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
# if student is not SLEEP, initialize timer
if not SLEEP:
SLEEP_TIME = time.time()
else:
SLEEP = 0
# if sleep time is over 3s, detect as sleeping student
if time.time() - SLEEP_TIME > 3.0:
cv2.putText(frame, "DO NOT SLEEP!", (10, 90),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
ser.write(b'W')
SLEEP_TIME = time.time()
cv2.putText(frame, "SLEEP: {0:.1f}s".format(time.time() - SLEEP_TIME), (10, 60),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
# show the frame
cv2.imshow("Frame", frame)
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
# do a bit of cleanup
ser.close()
cv2.destroyAllWindows()
vs.stop()
if __name__ == '__main__' :
main()
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