try.py

from tracker import Tracker
import cv2
import dlib
from imutils import face_utils
from scipy.spatial import distance as dist
import sys

drowsy_detector = dlib.get_frontal_face_detector()
drowsy_predictor = dlib.shape_predictor(
    'shape_predictor_68_face_landmarks.dat')


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


EYE_AR_THRESH = 0.35
EYE_AR_CONSEC_FRAMES = 48
COUNTER = 0
ALARM_ON = False


def drowsiness(frame):
    global COUNTER, ALARM_ON, EYE_AR_THRESH, EYE_AR_CONSEC_FRAMES

    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # detect faces in the grayscale frame
    rects = drowsy_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 = drowsy_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
        (lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
        (rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]

        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
        if ear < EYE_AR_THRESH:
            COUNTER += 1

            # if the eyes were closed for a sufficient number of
            # then sound the alarm
            if COUNTER >= EYE_AR_CONSEC_FRAMES:
                # if the alarm is not on, turn it on
                if not ALARM_ON:
                    ALARM_ON = True

                # 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:
            COUNTER = 0
            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), (270, 30),
                    cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)

    return frame


try:
    tracker = Tracker(
        detector=("./deploy.prototxt.txt",
                  "./res10_300x300_ssd_iter_140000.caffemodel"),
        confidence=0.4,
        tracker='kcf',
        refresh_interval=5,
        video=None,
        width=400,
        window=None,
        func=drowsiness
        )

except FileNotFoundError:  # If the files are not found
    print("The following files were not found in the current directory,"
          "exiting...\n"
          "\t1. deploy.prototxt.txt, "
          "\t2. res10_300x300_ssd_iter_140000.caffemodel")
    sys.exit(0)

tracker.start()