Code Phyton · Engineer Team

import cv2 import dlib import time import numpy as np from scipy.spatial import distance as dist import pygame import sys import math

# ================= CONFIG ================= FACE_DOWNSAMPLE_RATIO = 1.5 RESIZE_HEIGHT = 460

blinkTime = 0.15 drowsyTime = 1.5 yawnTime = 1.0

modelPath = "models/shape_predictor_68_face_landmarks.dat" sound_path = "alarm.wav" # ==========================================

# ================= AUDIO =================== pygame.mixer.init() pygame.mixer.music.load(sound_path) # ==========================================

# ================= DLIB ==================== detector = dlib.get_frontal_face_detector() predictor = dlib.shape_predictor(modelPath) # ==========================================

# ================= LANDMARK INDEX ========== leftEyeIndex = [36, 37, 38, 39, 40, 41] rightEyeIndex = [42, 43, 44, 45, 46, 47] mouthIndex = [48,49,50,51,52,53,54,55,56,57,58,59] # ==========================================

# ================= VARIABLES =============== blinkCount = 0 yawnCount = 0

eyeState = 0 mouthState = 0

drowsy = False alarm_on = False

adaptiveEAR = 0 adaptiveMAR = 0 # ==========================================

# ================= FUNCTIONS ===============

def get_head_pose(landmarks, frame_size):

image_points = np.array([ landmarks[30], # Nose tip landmarks[8], # Chin landmarks[36], # Left eye left corner landmarks[45], # Right eye right corner landmarks[48], # Left mouth corner landmarks[54] # Right mouth corner ], dtype="double")

model_points = np.array([ (0.0, 0.0, 0.0), # Nose tip (0.0, -330.0, -65.0), # Chin (-225.0, 170.0, -135.0), # Left eye (225.0, 170.0, -135.0), # Right eye (-150.0, -150.0, -125.0), # Left mouth (150.0, -150.0, -125.0) # Right mouth ])

size = frame_size focal_length = size[1] center = (size[1] / 2, size[0] / 2)

camera_matrix = np.array([ [focal_length, 0, center[0]], [0, focal_length, center[1]], [0, 0, 1] ], dtype="double")

dist_coeffs = np.zeros((4,1))

success, rotation_vector, translation_vector = cv2.solvePnP( model_points, image_points, camera_matrix, dist_coeffs, flags=cv2.SOLVEPNP_ITERATIVE )

rmat, _ = cv2.Rodrigues(rotation_vector) angles, _, _, _, _, _ = cv2.RQDecomp3x3(rmat)

pitch = angles[0] yaw = angles[1] roll = angles[2]

return pitch, yaw, roll

def eye_aspect_ratio(eye): A = dist.euclidean(eye[1], eye[5]) B = dist.euclidean(eye[2], eye[4]) C = dist.euclidean(eye[0], eye[3]) return (A + B) / (2.0 * C)

def mouth_aspect_ratio(mouth): A = dist.euclidean(mouth[2], mouth[10]) B = dist.euclidean(mouth[4], mouth[8]) C = dist.euclidean(mouth[0], mouth[6]) return (A + B) / (2.0 * C)

def get_landmarks(frame): gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

small = cv2.resize( gray, None, fx=1.0/FACE_DOWNSAMPLE_RATIO, fy=1.0/FACE_DOWNSAMPLE_RATIO )

rects = detector(small, 0) if len(rects) == 0: return None

rect = rects[0] rect = dlib.rectangle( int(rect.left()*FACE_DOWNSAMPLE_RATIO), int(rect.top()*FACE_DOWNSAMPLE_RATIO), int(rect.right()*FACE_DOWNSAMPLE_RATIO), int(rect.bottom()*FACE_DOWNSAMPLE_RATIO) )

shape = predictor(gray, rect) return [(p.x, p.y) for p in shape.parts()] # ==========================================

# ================= CAMERA ================== cap = cv2.VideoCapture(0) if not cap.isOpened(): print("Camera error") sys.exit() # ==========================================

# ================= CALIBRATION (ADAPTIVE) == print("Calibration... Keep eyes open & mouth closed")

ear_samples = [] mar_samples = [] calib_frames = 60

while len(ear_samples) < calib_frames: ret, frame = cap.read() if not ret: continue

h = frame.shape[0] scale = h / RESIZE_HEIGHT frame = cv2.resize(frame, None, fx=1/scale, fy=1/scale)

landmarks = get_landmarks(frame) if landmarks is None: continue

leftEye = [landmarks[i] for i in leftEyeIndex] rightEye = [landmarks[i] for i in rightEyeIndex] mouth = [landmarks[i] for i in mouthIndex]

ear = (eye_aspect_ratio(leftEye) + eye_aspect_ratio(rightEye)) / 2.0 mar = mouth_aspect_ratio(mouth)

ear_samples.append(ear) mar_samples.append(mar)

print("Calibration Done")

adaptiveEAR = np.mean(ear_samples) * 0.75 adaptiveMAR = np.mean(mar_samples) + 0.15

# ==========================================

# ================= MAIN LOOP =============== while True: ret, frame = cap.read() if not ret: break

h = frame.shape[0] scale = h / RESIZE_HEIGHT frame = cv2.resize(frame, None, fx=1/scale, fy=1/scale)

landmarks = get_landmarks(frame) if landmarks is None: cv2.imshow("Driver Monitoring", frame) if cv2.waitKey(1) & 0xFF == 27: break continue

# ===== EAR ===== leftEye = [landmarks[i] for i in leftEyeIndex] rightEye = [landmarks[i] for i in rightEyeIndex] ear = (eye_aspect_ratio(leftEye) + eye_aspect_ratio(rightEye)) / 2.0

# ===== MAR ===== mouth = [landmarks[i] for i in mouthIndex] mar = mouth_aspect_ratio(mouth)

# ===== BLINK & DROWSY ===== if ear < adaptiveEAR: eyeState += 1 else: if eyeState > 2: blinkCount += 1 eyeState = 0

if eyeState > 15: drowsy = True else: drowsy = False

# ===== YAWN ===== if mar > adaptiveMAR: mouthState += 1 else: if mouthState > 10: yawnCount += 1 mouthState = 0

pitch, yaw, roll = get_head_pose(landmarks, frame.shape) pitch = -pitch # Membalik agar positif = menengadah, negatif = menunduk

# ===== DRAW LANDMARKS ===== for i in leftEyeIndex + rightEyeIndex + mouthIndex: cv2.circle(frame, landmarks[i], 1, (0, 0, 255), -1)

# ===== DISPLAY ===== cv2.putText(frame, f"EAR: {round(ear,2)}", (20, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255,255,0), 2)

cv2.putText(frame, f"MAR: {round(mar,2)}", (20, 70), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255,255,0), 2)

cv2.putText(frame, f"Blinks: {blinkCount}", (350, 40), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0,255,0), 2)

cv2.putText(frame, f"Yawns: {yawnCount}", (350, 70), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (0,255,255), 2)

cv2.putText(frame, f"Yaw: {round(yaw, 1)}", (20, 110), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 0), 2)

cv2.putText(frame, f"Pitch: {round(pitch, 1)}", (20, 140), cv2.FONT_HERSHEY_SIMPLEX, 0.6, (255, 255, 0), 2)

# ===== DISTRACTION DETECTION ===== if abs(yaw) > 20: cv2.putText(frame, "LOOKING SIDEWAYS!", (60, 170), cv2.FONT_HERSHEY_COMPLEX, 0.7, (0, 165, 255), 2)

# ===== HEAD DOWN ALERT ===== if pitch > -20: # sekarang negatif = menunduk cv2.putText(frame, "HEAD DOWN!", (60, 200), cv2.FONT_HERSHEY_COMPLEX, 0.7, (0, 0, 255), 2)

# ===== ALERT ===== if drowsy or mouthState > 10: cv2.putText(frame, "!!! ALERT !!!", (60, 120), cv2.FONT_HERSHEY_COMPLEX, 0.8, (0,0,255), 2)

if not alarm_on: pygame.mixer.music.play(-1) alarm_on = True else: if alarm_on: pygame.mixer.music.stop() alarm_on = False

cv2.imshow("Driver Monitoring", frame)

key = cv2.waitKey(1) if key == ord('r'): blinkCount = 0 yawnCount = 0 elif key == 27: break

pygame.mixer.music.stop() pygame.quit() cap.release() cv2.destroyAllWindows()