driver_safety_system.py

# Importing OpenCV Library for basic image processing functions
import cv2
# Numpy for array related functions
import numpy as np
# Dlib for deep learning based Modules and face landmark detection
import dlib
# face_utils for basic operations of conversion
from imutils import face_utils
import serial
import time

# Establish serial connection
s = serial.Serial('COM3', 9600)

# Initializing the camera and taking the instance
cap = cv2.VideoCapture(0)

# Initializing the face detector and landmark detector
hog_face_detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

# Status marking for current state
sleep = 0
drowsy = 0
active = 0
status = ""
color = (0, 0, 0)

def compute(ptA, ptB):
    """Computes the Euclidean distance between two points."""
    dist = np.linalg.norm(ptA - ptB)
    return dist

def blinked(a, b, c, d, e, f):
    """Calculates the eye aspect ratio to determine blink state."""
    up = compute(b, d) + compute(c, e)
    down = compute(a, f)
    ratio = up / (2.0 * down)
    
    # Checking if the eye is blinked, drowsy, or open
    if ratio > 0.25:
        return 2  # Active/Open
    elif 0.21 < ratio <= 0.25:
        return 1  # Drowsy
    else:
        return 0  # Sleeping/Closed

while True:
    _, frame = cap.read()
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    faces = hog_face_detector(gray)
    # Detected face in faces array
    for face in faces:
        x1 = face.left()
        y1 = face.top()
        x2 = face.right()
        y2 = face.bottom()

        face_frame = frame.copy()
        cv2.rectangle(face_frame, (x1, y1), (x2, y2), (0, 255, 0), 2)

        landmarks = predictor(gray, face)
        landmarks = face_utils.shape_to_np(landmarks)

        # The numbers are the landmarks which define the eyes
        left_blink = blinked(landmarks[36], landmarks[37], 
                             landmarks[38], landmarks[41], landmarks[40], landmarks[39])
        right_blink = blinked(landmarks[42], landmarks[43], 
                              landmarks[44], landmarks[47], landmarks[46], landmarks[45])

        # Now judge what to do based on the eye blinks
        if left_blink == 0 or right_blink == 0:
            sleep += 1
            drowsy = 0
            active = 0
            if sleep > 6:
                s.write(b'a')
                time.sleep(2)
                status = "SLEEPING !!!"
                color = (0, 0, 255)

        elif left_blink == 1 or right_blink == 1:
            sleep = 0
            active = 0
            drowsy += 1
            if drowsy > 6:
                s.write(b'a')
                time.sleep(2)
                status = "Drowsy !"
                color = (0, 0, 255)
        
        else:
            drowsy = 0
            sleep = 0
            active += 1
            if active > 6:
                s.write(b'b')
                time.sleep(2)
                status = "Active :)"
                color = (0, 255, 0)
        
        cv2.putText(frame, status, (100, 100), cv2.FONT_HERSHEY_SIMPLEX, 1.2, color, 3)

        for n in range(0, 68):
            (x, y) = landmarks[n]
            cv2.circle(face_frame, (x, y), 1, (255, 255, 255), -1)

    cv2.imshow("Frame", frame)
    # cv2.imshow("Result of detector", face_frame)
    
    key = cv2.waitKey(1)
    if key == 27:  # 27 is the ASCII for the Esc key
        break