基于python脚本的疲劳检测，ocv图片转换，dlib库定位五官位置

import cv2 import dlib import numpy as np from scipy.spatial import distance as dist import pyttsx3 import time import webbrowser import subprocess from flask import Flask, render_template, Response, jsonify # 初始化语音引擎 engine = pyttsx3.init() # 加载Dlib的面部关键点检测器 detector = dlib.get_frontal_face_detector() predictor = dlib.shape_predictor("shape_predictor_68_face_landmarks.dat") # 定义函数来计算眼睛的纵横比 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 # 定义常量 EYE_AR_THRESHOLD = 0.3 EYE_AR_CONSEC_FRAMES = 48 # 初始化帧计数器和眼睛纵横比历史列表 COUNTER = 0 EAR_HISTORY = [] # 打开摄像头 cap = cv2.VideoCapture(0) # 设置程序运行的最大时间，单位为秒 MAX_RUN_TIME = 300 # 例如，设置为运行5分钟 # 记录程序的启动时间 start_time = time.time() app = Flask(__name__) @app.route('/get_ear_value') def get_ear_value(): global EAR_HISTORY if EAR_HISTORY: avg_ear = np.mean(EAR_HISTORY) return jsonify({'ear': avg_ear}) else: return jsonify({'ear': 0.0}) @app.route('/') def index(): return render_template('index.html') def gen(): global COUNTER # 声明COUNTER为全局变量 while True: ret, frame = cap.read() if not ret: break # 将图像转换为灰度图 gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # 检测面部 faces = detector(gray) for face in faces: shape = predictor(gray, face) # 提取左眼和右眼的坐标 left_eye = [(shape.part(i).x, shape.part(i).y) for i in range(42, 48)] right_eye = [(shape.part(i).x, shape.part(i).y) for i in range(36, 42)] # 计算左眼和右眼的纵横比 left_ear = eye_aspect_ratio(left_eye) right_ear = eye_aspect_ratio(right_eye) # 平均左右眼的纵横比 ear = (left_ear + right_ear) / 2.0 # 将纵横比添加到历史列表 EAR_HISTORY.append(ear) # 如果历史列表超过指定帧数，则进行判断 if len(EAR_HISTORY) >= EYE_AR_CONSEC_FRAMES: # 计算历史纵横比的平均值 avg_ear = np.mean(EAR_HISTORY) # 如果平均纵横比低于阈值，则认为面部疲劳 if avg_ear < EYE_AR_THRESHOLD: COUNTER += 1 if COUNTER == EYE_AR_CONSEC_FRAMES: engine.say("面部疲劳检测") engine.runAndWait() else: COUNTER = 0 EAR_HISTORY.clear() # 绘制面部区域和纵横比 cv2.putText(frame, "EAR: {:.2f}".format(ear), (300, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2) current_time = time.time() elapsed_time = current_time - start_time # 如果运行时间超过设定的时间，自动停止程序 if elapsed_time >= MAX_RUN_TIME: break # 将图像数据转换为JPEG格式 ret, jpeg = cv2.imencode('.jpg', frame) if not ret: break # 使用生成器发送JPEG数据 yield (b'--frame\r\n' b'Content-Type: image/jpeg\r\n\r\n' + jpeg.tobytes() + b'\r\n') @app.route('/video_feed') def video_feed(): return Response(gen(), mimetype='multipart/x-mixed-replace; boundary=frame') if __name__ == '__main__': app.run(debug=True) # Flask应用程序的URL url = 'http://127.0.0.1:5000/' subprocess.Popen(['start', 'edge', url])