基于python opencv检测疲劳驾驶源代码

Python和OpenCV结合使用非常方便，可以轻松处理和分析图像。使用Python和OpenCV检测疲劳驾驶需要两个核心部分：面部检测和眼睛检测。以下是基于Python和OpenCV检测疲劳驾驶的源代码：

import cv2
import dlib
from scipy.spatial import distance

def calculate_eye_ratio(eye_points):
    A = distance.euclidean(eye_points[1], eye_points[5])
    B = distance.euclidean(eye_points[2], eye_points[4])
    C = distance.euclidean(eye_points[0], eye_points[3])

    eye_ratio = (A + B) / (2.0 * C)
    return eye_ratio

cap = cv2.VideoCapture(0)
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor('shape_predictor_68_face_landmarks.dat')

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

    faces = detector(gray)

    for face in faces:
        landmarks = predictor(gray, face)

        left_eye_ratio = calculate_eye_ratio([(landmarks.part(36).x, landmarks.part(36).y),
                                               (landmarks.part(37).x, landmarks.part(37).y),
                                               (landmarks.part(38).x, landmarks.part(38).y),
                                               (landmarks.part(39).x, landmarks.part(39).y),
                                               (landmarks.part(40).x, landmarks.part(40).y),
                                               (landmarks.part(41).x, landmarks.part(41).y)])

        right_eye_ratio = calculate_eye_ratio([(landmarks.part(42).x, landmarks.part(42).y),
                                                (landmarks.part(43).x, landmarks.part(43).y),
                                                (landmarks.part(44).x, landmarks.part(44).y),
                                                (landmarks.part(45).x, landmarks.part(45).y),
                                                (landmarks.part(46).x, landmarks.part(46).y),
                                                (landmarks.part(47).x, landmarks.part(47).y)])

        eye_ratio = (left_eye_ratio + right_eye_ratio) / 2.0

        if eye_ratio < 0.3:
            cv2.putText(frame, "Sleepy Alert!!!", (10, 80), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 255),2)

    cv2.imshow("Driver_Drowsiness_Detection", frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

这个代码片段使用了OpenCV和dlib库，它首先利用dlib库进行面部检测，然后使用预测器从面部形状中获取眼睛位置，最后利用算法计算眼睛的宽高比来判断是否疲劳驾驶。如果宽高比小于指定值，代码就会在视频流上显示 "Sleepy Alert !!!"。您需要将 "shape_predictor_68_face_landmarks.dat" 替换为自己的预测器文件。