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detector.py
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detector.py
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import cv2
import sys
import time
import dlib
import imutils
import playsound
import numpy as np
from threading import Thread
from imutils import face_utils
from scipy.spatial import distance as dist
from imutils.video import VideoStream, FileVideoStream
SHAPE_PREDICTOR = "shape_predictor_68_face_landmarks.dat"
class Detector:
# define two constants, one for the eye aspect ratio to indicate
# blink and then a second constant for the number of consecutive
# frames the eye must be below the threshold for to set off the
# alarm
EYE_AR_THRESH = 0.17 if sys.platform == 'darwin' else 0.25
EYE_AR_CONSEC_FRAMES = 60
# initialize the frame counter as well as a boolean used to
# indicate if the alarm is going off
COUNTER = 0
ALARM_ON = False
def __init__(self, kwargs):
self.args = kwargs
# initialize dlib's face detector (HOG-based) and then create
# the facial landmark predictor
print("[INFO] loading facial landmark predictor...")
self.detector = dlib.get_frontal_face_detector()
self.predictor = dlib.shape_predictor(SHAPE_PREDICTOR)
# grab the indexes of the facial landmarks for the left and
# right eye, respectively
(self.l_start, self.l_end) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(self.r_start, self.r_end) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
# start the video stream thread
print("[INFO] starting video stream thread...")
try:
video_src = int(self.args["webcam"])
print('[INFO] Using webcam...')
self.vs = VideoStream(src=video_src).start()
except:
print('[INFO] Using video file...')
self.vs = FileVideoStream(path=self.args["webcam"]).start()
time.sleep(1.0)
def __del__(self):
# do a bit of cleanup
cv2.destroyAllWindows()
self.vs.stop()
print('Cleaned up!')
@staticmethod
def sound_alarm(path):
# play an alarm sound
# Linux
playsound.playsound(path)
# MacOS
# playsound.playsound(path, False)
@staticmethod
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
def run(self):
# loop over frames from the video stream
while True:
# grab the frame from the threaded video file stream, resize
# it, and convert it to grayscale
# channels)
frame = self.vs.read()
frame = imutils.resize(frame, width=450)
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
# detect faces in the grayscale frame
rects = self.detector(gray, 0)
# 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 = self.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
left_eye = shape[self.l_start:self.l_end]
right_eye = shape[self.r_start:self.r_end]
left_ear = self.eye_aspect_ratio(left_eye)
right_ear = self.eye_aspect_ratio(right_eye)
# average the eye aspect ratio together for both eyes
ear = (left_ear + right_ear) / 2.0
# compute the convex hull for the left and right eye, then
# visualize each of the eyes
# left_eyeHull = cv2.convexHull(left_eye)
# right_eyeHull = cv2.convexHull(right_eye)
# cv2.drawContours(frame, [left_eyeHull], -1, (0, 255, 0), 1)
# cv2.drawContours(frame, [right_eyeHull], -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
if ear < self.EYE_AR_THRESH:
self.COUNTER += 1
# if the eyes were closed for a sufficient number of
# then sound the alarm
if self.COUNTER >= self.EYE_AR_CONSEC_FRAMES:
# if the alarm is not on, turn it on
if not self.ALARM_ON:
self.ALARM_ON = True
# check to see if an alarm file was supplied,
# and if so, start a thread to have the alarm
# sound played in the background
if self.args["alarm"] != "no":
t = Thread(target=self.sound_alarm,
args=(self.args["alarm"],))
t.daemon = True
t.start()
# draw an alarm on the frame
cv2.putText(frame, "DROWSINESS ALERT!", (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
# otherwise, the eye aspect ratio is not below the blink
# threshold, so reset the counter and alarm
else:
self.COUNTER = 0
self.ALARM_ON = False
# draw the computed eye aspect ratio on the frame to help
# with debugging and setting the correct eye aspect ratio
# thresholds and frame counters
cv2.putText(frame, "EAR: {:.2f}".format(ear), (300, 30),
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