### 基于Python和OpenCV的人脸检测与睡意检测代码 以下是一个使用Python和OpenCV实现人脸检测、闭眼和张嘴检测的代码示例。此代码利用了Haar Cascade分类器来检测人脸和眼睛，并通过计算眼部纵横比（EAR）来判断是否闭眼，同时通过检测嘴巴区域的高度变化来判断是否张嘴。 ```python import cv2 import numpy as np # 定义眼部纵横比阈值和连续帧数阈值 EYE_AR_THRESH = 0.3 # 眼部纵横比阈值 EYE_AR_CONSEC_FRAMES = 3 # 连续帧数阈值 MOUTH_AR_THRESH = 0.6 # 嘴巴纵横比阈值 # 初始化计数器和标志 COUNTER = 0 ALARM_ON = False # 加载Haar级联分类器 face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml') mouth_cascade = cv2.CascadeClassifier('haarcascade_mcs_mouth.xml') # 计算眼部纵横比 def eye_aspect_ratio(eye): A = np.linalg.norm(eye[1] - eye[5]) B = np.linalg.norm(eye[2] - eye[4]) C = np.linalg.norm(eye[0] - eye[3]) ear = (A + B) / (2.0 * C) return ear # 打开摄像头 cap = cv2.VideoCapture(0) while True: ret, frame = cap.read() if not ret: break gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # 检测脸部 faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30)) for (x, y, w, h) in faces: cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2) # 检测眼睛 roi_gray = gray[y:y+h, x:x+w] eyes = eye_cascade.detectMultiScale(roi_gray) eye_points = [] for (ex, ey, ew, eh) in eyes: cv2.rectangle(frame, (x+ex, y+ey), (x+ex+ew, y+ey+eh), (0, 255, 0), 2) eye_center = (x + ex + ew//2, y + ey + eh//2) eye_points.append(eye_center) if len(eye_points) == 2: ear = eye_aspect_ratio(eye_points) if ear < EYE_AR_THRESH: COUNTER += 1 if COUNTER >= EYE_AR_CONSEC_FRAMES: if not ALARM_ON: ALARM_ON = True cv2.putText(frame, "DROWSINESS ALERT!", (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2) else: COUNTER = 0 ALARM_ON = False # 检测嘴巴 mouth_rects = mouth_cascade.detectMultiScale(gray, scaleFactor=1.5, minNeighbors=11) for (mx, my, mw, mh) in mouth_rects: mouth_center_y = my + mh // 2 if y < mouth_center_y < y + h: cv2.rectangle(frame, (mx, my), (mx + mw, my + mh), (0, 0, 255), 2) mouth_height = mh / h if mouth_height > MOUTH_AR_THRESH: cv2.putText(frame, "MOUTH OPEN!", (10, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2) cv2.imshow('Drowsiness Detection', frame) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows() ``` #### 注意事项 - Haar级联分类器文件（如`haarcascade_frontalface_default.xml`等）需要从OpenCV的GitHub仓库下载并放置在代码运行目录下[^1]。 - 眼部纵横比（EAR）是通过计算眼睛宽度和高度的比例得出的，当EAR低于设定的阈值时，认为眼睛闭合[^2]。 - 嘴巴检测通过计算嘴巴区域的高度占脸部高度的比例，超过设定阈值时认为嘴巴张开[^3]。