src/drowsiness_detection.py

# PREP DEPENDENCIES
from scipy.spatial import distance as dist
from imutils import face_utils
from threading import Thread
import numpy as np
import cv2 as cv
import imutils
import dlib
import pygame  # Used for playing alarm sounds cross-platform
import argparse
import os

# --- INITIALIZE MODELS AND CONSTANTS ---

# Haar cascade classifier for face detection
haar_cascade_face_detector = "dependencies/haarcascade_frontalface_default.xml"
face_detector = cv.CascadeClassifier(haar_cascade_face_detector)

# Dlib facial landmark detector
dlib_facial_landmark_predictor = "dependencies/shape_predictor_68_face_landmarks.dat"
landmark_predictor = dlib.shape_predictor(dlib_facial_landmark_predictor)

# Important Variables
font = cv.FONT_HERSHEY_SIMPLEX
# --- INITIALIZE MODELS AND CONSTANTS ---
# Eye Drowsiness Detection
EYE_ASPECT_RATIO_THRESHOLD = 0.25
EYE_CLOSED_THRESHOLD = 20
EYE_THRESH_COUNTER = 0
DROWSY_COUNTER = 0
drowsy_alert = False

# Mouth Yawn Detection
MOUTH_ASPECT_RATIO_THRESHOLD = 0.5
MOUTH_OPEN_THRESHOLD = 15
YAWN_THRESH_COUNTER = 0
YAWN_COUNTER = 0
yawn_alert = False

# NEW: Head Not Visible Detection
FACE_LOST_THRESHOLD = 25  # Conseq. frames face must be lost to trigger alert
FACE_LOST_COUNTER = 0
HEAD_DOWN_COUNTER = 0 # Renaming for clarity
head_down_alert = False

# --- AUDIO SETUP (using Pygame) ---
pygame.mixer.init()
drowsiness_sound = pygame.mixer.Sound("dependencies/audio/drowsiness-detected.mp3")
yawn_sound = pygame.mixer.Sound("dependencies/audio/yawning-detected.mp3")
# head_down_sound = pygame.mixer.Sound("dependencies/audio/head-down-detected.mp3")

# --- CORE FUNCTIONS ---
def play_alarm(sound_to_play):
    if not pygame.mixer.get_busy():
        sound_to_play.play()

def generate_alert(final_eye_ratio, final_mouth_ratio):
    global EYE_THRESH_COUNTER, YAWN_THRESH_COUNTER
    global drowsy_alert, yawn_alert
    global DROWSY_COUNTER, YAWN_COUNTER

    # Drowsiness check
    if final_eye_ratio < EYE_ASPECT_RATIO_THRESHOLD:
        EYE_THRESH_COUNTER += 1
        if EYE_THRESH_COUNTER >= EYE_CLOSED_THRESHOLD:
            if not drowsy_alert:
                DROWSY_COUNTER += 1
                drowsy_alert = True
                Thread(target=play_alarm, args=(drowsiness_sound,)).start()
    else:
        EYE_THRESH_COUNTER = 0
        drowsy_alert = False

    # Yawn check
    if final_mouth_ratio > MOUTH_ASPECT_RATIO_THRESHOLD:
        YAWN_THRESH_COUNTER += 1
        if YAWN_THRESH_COUNTER >= MOUTH_OPEN_THRESHOLD:
            if not yawn_alert:
                YAWN_COUNTER += 1
                yawn_alert = True
                Thread(target=play_alarm, args=(yawn_sound,)).start()
    else:
        YAWN_THRESH_COUNTER = 0
        yawn_alert = False

def detect_facial_landmarks(x, y, w, h, gray_frame):
    face = dlib.rectangle(int(x), int(y), int(x + w), int(y + h))
    face_landmarks = landmark_predictor(gray_frame, face)
    face_landmarks = face_utils.shape_to_np(face_landmarks)
    return face_landmarks

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])
    ear = (A + B) / (2.0 * C)
    return ear

def final_eye_aspect_ratio(shape):
    (lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
    (rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
    left_eye = shape[lStart:lEnd]
    right_eye = shape[rStart:rEnd]
    left_ear = eye_aspect_ratio(left_eye)
    right_ear = eye_aspect_ratio(right_eye)
    final_ear = (left_ear + right_ear) / 2.0
    return final_ear, left_eye, right_eye

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])
    mar = (A + B) / (2.0 * C)
    return mar

def final_mouth_aspect_ratio(shape):
    (mStart, mEnd) = face_utils.FACIAL_LANDMARKS_IDXS["mouth"]
    mouth = shape[mStart:mEnd]
    return mouth_aspect_ratio(mouth), mouth

def head_pose_ratio(shape):
    nose_tip = shape[30]
    chin_tip = shape[8]
    left_face_corner = shape[0]
    right_face_corner = shape[16]
    nose_to_chin_dist = dist.euclidean(nose_tip, chin_tip)
    face_width = dist.euclidean(left_face_corner, right_face_corner)
    if face_width == 0:
        return 0.0
    hpr = nose_to_chin_dist / face_width
    return hpr

def reset_counters():
    global EYE_THRESH_COUNTER, YAWN_THRESH_COUNTER, FACE_LOST_COUNTER
    global DROWSY_COUNTER, YAWN_COUNTER, HEAD_DOWN_COUNTER
    global drowsy_alert, yawn_alert, head_down_alert
    EYE_THRESH_COUNTER, YAWN_THRESH_COUNTER, FACE_LOST_COUNTER = 0, 0, 0
    DROWSY_COUNTER, YAWN_COUNTER, HEAD_DOWN_COUNTER = 0, 0, 0
    drowsy_alert, yawn_alert, head_down_alert = False, False, False

def process_frame(frame):
    global FACE_LOST_COUNTER, head_down_alert, HEAD_DOWN_COUNTER
    frame = imutils.resize(frame, width=640)
    gray_frame = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
    faces = face_detector.detectMultiScale(gray_frame, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30), flags=cv.CASCADE_SCALE_IMAGE)
    if len(faces) > 0:
        FACE_LOST_COUNTER = 0
        head_down_alert = False
        (x, y, w, h) = faces[0]
        face_landmarks = detect_facial_landmarks(x, y, w, h, gray_frame)
        final_ear, left_eye, right_eye = final_eye_aspect_ratio(face_landmarks)
        final_mar, mouth = final_mouth_aspect_ratio(face_landmarks)
        # left_eye_hull, right_eye_hull, mouth_hull = cv.convexHull(left_eye), cv.convexHull(right_eye), cv.convexHull(mouth)
        # cv.drawContours(frame, [left_eye_hull], -1, (0, 255, 0), 1)
        # cv.drawContours(frame, [right_eye_hull], -1, (0, 255, 0), 1)
        # cv.drawContours(frame, [mouth_hull], -1, (0, 255, 0), 1)
        generate_alert(final_ear, final_mar)
        cv.putText(frame, f"EAR: {final_ear:.2f}", (10, 30), font, 0.7, (0, 0, 255), 2)
        cv.putText(frame, f"MAR: {final_mar:.2f}", (10, 60), font, 0.7, (0, 0, 255), 2)
    else:
        FACE_LOST_COUNTER += 1
        if FACE_LOST_COUNTER >= FACE_LOST_THRESHOLD and not head_down_alert:
            HEAD_DOWN_COUNTER += 1
            head_down_alert = True
    cv.putText(frame, f"Drowsy: {DROWSY_COUNTER}", (480, 30), font, 0.7, (255, 255, 0), 2)
    cv.putText(frame, f"Yawn: {YAWN_COUNTER}", (480, 60), font, 0.7, (255, 255, 0), 2)
    cv.putText(frame, f"Head Down: {HEAD_DOWN_COUNTER}", (480, 90), font, 0.7, (255, 255, 0), 2)
    if drowsy_alert: cv.putText(frame, "DROWSINESS ALERT!", (150, 30), font, 0.9, (0, 0, 255), 2)
    if yawn_alert: cv.putText(frame, "YAWN ALERT!", (200, 60), font, 0.9, (0, 0, 255), 2)
    if head_down_alert: cv.putText(frame, "HEAD NOT VISIBLE!", (180, 90), font, 0.9, (0, 0, 255), 2)
    return frame

def process_video(input_path, output_path=None):
    reset_counters()
    video_stream = cv.VideoCapture(input_path)
    if not video_stream.isOpened():
        print(f"Error: Could not open video file {input_path}")
        return False
    
    fps = int(video_stream.get(cv.CAP_PROP_FPS))
    width = int(video_stream.get(cv.CAP_PROP_FRAME_WIDTH))
    height = int(video_stream.get(cv.CAP_PROP_FRAME_HEIGHT))
    
    print(f"Processing video: {input_path}")
    print(f"Original Res: {width}x{height}, FPS: {fps}")
    
    video_writer = None
    if output_path:
        fourcc = cv.VideoWriter_fourcc(*'mp4v')
        # --- FIX: Calculate correct output dimensions to prevent corruption ---
        # The process_frame function resizes frames to a fixed width of 640.
        output_width = 640
        # Maintain aspect ratio
        output_height = int(height * (output_width / float(width)))
        output_dims = (output_width, output_height)
        video_writer = cv.VideoWriter(output_path, fourcc, fps, output_dims)
        print(f"Outputting video with Res: {output_dims[0]}x{output_dims[1]}")

    while True:
        ret, frame = video_stream.read()
        if not ret: break
        
        processed_frame = process_frame(frame)
        if video_writer: video_writer.write(processed_frame)
    
    video_stream.release()
    if video_writer: video_writer.release()
    
    print("Video processing complete!")
    print(f"Final Stats - Drowsy: {DROWSY_COUNTER}, Yawn: {YAWN_COUNTER}, Head Down: {HEAD_DOWN_COUNTER}")
    return True

def run_webcam():
    reset_counters()
    video_stream = cv.VideoCapture(0)
    if not video_stream.isOpened():
        print("Error: Could not open webcam")
        return False
    while True:
        ret, frame = video_stream.read()
        if not ret:
            print("Failed to grab frame")
            break
        processed_frame = process_frame(frame)
        cv.imshow("Live Drowsiness and Yawn Detection", processed_frame)
        if cv.waitKey(1) & 0xFF == ord('q'): break
    video_stream.release()
    cv.destroyAllWindows()
    return True

# --- MAIN EXECUTION LOOP ---
if __name__ == "__main__":
    parser = argparse.ArgumentParser(description='Drowsiness Detection System')
    parser.add_argument('--mode', choices=['webcam', 'video'], default='webcam', help='Mode of operation')
    parser.add_argument('--input', type=str, help='Input video file path for video mode')
    parser.add_argument('--output', type=str, help='Output video file path for video mode')
    args = parser.parse_args()
    
    if args.mode == 'webcam':
        print("Starting webcam detection...")
        run_webcam()
    elif args.mode == 'video':
        if not args.input:
            print("Error: --input argument is required for video mode.")
        elif not os.path.exists(args.input):
            print(f"Error: Input file not found at {args.input}")
        else:
            process_video(args.input, args.output)