疲劳检测代码python

疲劳检测通常涉及到生物特征识别或数据分析，Python作为一门强大的数据处理语言，可以用于编写此类应用程序。以下是一个简单的例子，展示如何使用Python进行眼睛疲劳监测，通常是基于摄像头捕捉图像并分析眼睛状态：

import cv2
import dlib
from collections import deque

# 使用dlib库进行面部检测
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat")

# 创建一个滑动窗口（deque）来跟踪眼睛的活动
eye_tracker = deque(maxlen=5)

def detect.eye_tiredness(frame):
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    faces = detector(gray)
    
    for face in faces:
        landmarks = predictor(gray, face)
        
        # 提取眼睛区域坐标
        left_eye = (landmarks.part(36).x, landmarks.part(36).y)
        right_eye = (landmarks.part(45).x, landmarks.part(45).y)
        
        # 添加眼睛位置到滑动窗口
        eye_tracker.append((left_eye, right_eye))
        
        # 计算眼睛之间的平均距离作为疲劳指标
        avg_distance = sum(e_dist for e1, e2 in zip(eye_tracker, eye_tracker[1:])) / len(eye_tracker)
        
        if avg_distance > threshold:  # 设置阈值判断是否疲劳
            return True

# 主循环读取视频帧并检测疲劳
cap = cv2.VideoCapture('webcam.mp4')
while True:
    ret, frame = cap.read()
    if not ret:
        break
    
    is_tired = detect.eye_tiredness(frame)
    cv2.imshow("Eye Fatigue Detection", frame)
    key = cv2.waitKey(1) & 0xFF
    if key == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()