【无标题】

import cv2
import mediapipe as mp
import time
import math
from scipy.spatial import distance as dist
import numpy as np
from mediaPose import poseDetector
from mediaFace import FaceMeshDetector
from euler_angle import get_head_pose

#创建面部检测和姿态检测对象
faceDetector = FaceMeshDetector()
poseDetector = poseDetector()


def eye_aspect_ratio(facelist, eye):
    # 垂直眼标志（X, Y）坐标
    A = dist.euclidean(facelist[eye[2]], facelist[eye[3]])  # 计算两个集合之间的欧式距离
    B = dist.euclidean(facelist[eye[4]], facelist[eye[5]])
    # 计算水平之间的欧几里得距离
    # 水平眼标志（X, Y）坐标
    D = dist.euclidean(facelist[eye[0]], facelist[eye[1]])
    # 眼睛长宽比的计算
    ear = (A + B) / (2.0 * D)
    if len(eye) == 8:
        C = dist.euclidean(facelist[eye[6]], facelist[eye[7]])
        ear = (A + B + C) / (3.0 * D)
    # 返回眼睛的长宽比
    return ear


def mouth_aspect_ratio(facelist, mouth):  # 嘴部
    A = dist.euclidean(facelist[mouth[2]], facelist[mouth[3]])  # 计算两个集合之间的欧式距离
    B = dist.euclidean(facelist[mouth[4]], facelist[mouth[5]])
    C = dist.euclidean(facelist[mouth[6]], facelist[mouth[7]])
    D = dist.euclidean(facelist[mouth[0]], facelist[mouth[1]])
    # 眼睛长宽比的计算
    mar = (A + B + C) / (3.0 * D)
    # 返回眼睛的长宽比
    return mar


def headdownOrPhone_detection(lmList, poseKeypoint, headTime, phoneTime, r1, r2):

    '''取出需要的关键点 然后计算距离'''
    nose = lmList[poseKeypoint[0]]
    shoulder1 = lmList[poseKeypoint[1]]
    shoulder2 = lmList[poseKeypoint[2]]
    finger1 = lmList[poseKeypoint[3]]
    finger2 = lmList[poseKeypoint[4]]
    x1, y1, x2, y2 = shoulder1[1], shoulder1[2], shoulder2[1], shoulder2[2]
    x3, y3 = (x1 + x2) / 2, (y1 + y2) / 2
    d1 = dist.euclidean((nose[1],nose[2]),(x3,y3))
    #d2是双肩距离
    d2 = dist.euclidean((shoulder1[1],shoulder1[2]),(shoulder2[1],shoulder2[2]))
    d3 = dist.euclidean((finger1[1],finger1[2]),(nose[1],nose[2]))
    d4 = dist.euclidean((finger2[1],finger2[2]),(nose[1],nose[2]))

    # print('肩宽：', int(d2))

    '''判断低头'''
    headdwon = False
    if d1 < (d2 / r1):
        headTime += 1
    else:
        headTime = 0
    if headTime > 60:
        headdwon = True

    '''判断玩手机'''
    phone = False
    if d3 < (d2 / r2) or d4 < (d2 / r2):
        phoneTime += 1
    else:
        phoneTime = 0
    if phoneTime > 60:
        phone = True
    return headdwon, phone, headTime, phoneTime



def get_facelist(img, option):
    if option == 'mediapipe':
        img, facelist = faceDetector.FindFaceMesh(img)
    return facelist

def get_fatigue_parameter(feature_queue,close_time,open_time,EAR_THRESH,MAR_THRESH,T):
    #删除队首元素
    if len(feature_queue) > T:
        feature_queue.pop(0)

    '''计算连续闭眼时间'''
    #队列中最后一个数据是当前帧的数据 current的格式为[mar, ear_l, ear_r, pitch, yaw, roll]
    current = feature_queue[-1]
    if 0 < (current[1] + current[2])/2 < EAR_THRESH :
        close_time += 1
    else:
        close_time = 0
    '''计算连续张嘴时间'''
    if current[0] >MAR_THRESH :
        open_time += 1
    else:
        open_time = 0

    '''计算perclos'''
    if len(feature_queue) == T:
        wink = 0
        for i in range(T):
            if (feature_queue[i][1] + feature_queue[i][2]) / 2 < EAR_THRESH:
                wink += 1
        perclos = wink / T
    else:
        perclos = -1
    return close_time, perclos, open_time


def fatigue_datection(close_time,  open_time, alert1, alert2,yawnTime1,P,yawn_time):

    '''通过眼睛判断疲劳'''
    if close_time > 40 or perclos > P:
        alert1 = True
    else:
        alert1 = False

    '''通过嘴部判断疲劳'''
    # 打过哈欠了吗  yawntime是上一次打哈欠的时间
    if yawnTime1 > 0:
        #又打哈欠了吗
        if open_time == 40:
            t = time.time() - yawnTime1
            #两次哈欠时间差很短吗
            if t < yawn_time:
                print('两次打哈欠时间间隔为：', t)
                alert2 = True
                yawnTime1 = time.time()
            else:
                alert2 = False
                yawnTime1 = time.time()
        elif open_time >40 :
            yawnTime1 = time.time()
        else:
            alert2 = False
    else:
        alert2 = False
        if open_time == 40:
            yawnTime1 = time.time()
    return alert1,alert2,yawnTime1


#画点函数
def drawCircle_face(img, facelist, list1, list2, list3):
    for i in range(len(list1)):
        p = facelist[list1[i]]
        cv2.circle(img, (p[0], p[1]), 2, (0, 0, 255), 1)
    for j in range(len(list2)):
        p = facelist[list2[j]]
        cv2.circle(img, (p[0], p[1]), 2, (0, 0, 255), 1)
    for k in range(len(list3)):
        p = facelist[list3[k]]
        cv2.circle(img, (p[0], p[1]), 2, (0, 0, 255), 1)
    return img


def drawCircle_pose(img, lmlist):
    list=[lmlist[0],lmlist[11],lmlist[12],lmlist[19],lmlist[20]]
    for p in range(len(list)):
        cv2.circle(img, (list[p][1], list[p][2]), 7, (0, 0, 255), cv2.FILLED)
    return img



EAR_THRESH = 0.15
MAR_THRESH = 0.6
T = 50
Yawn_time = 60
PERCLOS = 0.4
DRAW = True

left_eye = [33, 133, 160, 144, 158, 153, 159, 145]
right_eye = [362, 263, 385, 380, 387, 373, 386, 374]
mouth = [78, 308, 82, 87, 312, 317, 13, 14]
poseKeypoint = [0,11,12,19,20]

if __name__ == "__main__":
    cap = cv2.VideoCapture(1)

    #初始化相关变量
    fps = 0
    feature_queue = []
    close_time, open_time, alert1, alert2, yawnTime1 = 0,0,0,0,-1000
    head_down, phone_call, headTime, phoneTime = False, False, 0, 0

    while cap.isOpened():
        success, img = cap.read()
        t1 = time.time()
        img1 = img.copy()

        # 检测姿态
        t1 = time.time()
        lmList = poseDetector.findPosition(img, draw=False)
        if len(lmList) != 0:
            #判断异常姿态
            head_down, phone_call, headTime, phoneTime = headdownOrPhone_detection(lmList,poseKeypoint, headTime=headTime,phoneTime=phoneTime,r1=3,r2=2)
        else:
            print("请调整坐姿")
            lmList = []
            head_down = False

        # 检测面部特征
        facelist = get_facelist(img1, option='mediapipe')
        mar, ear_l, ear_r, pitch, yaw, roll = 0, 0, 0, 0, 0, 0
        # 如果检测到人脸的话 计算相关疲劳特征参数
        if len(facelist) != 0:
            # 左眼纵横比
            ear_l = eye_aspect_ratio(facelist, left_eye)
            # 右眼
            ear_r = eye_aspect_ratio(facelist, right_eye)
            # 嘴
            mar = mouth_aspect_ratio(facelist, mouth)
            # 姿态角
            pitch, yaw, roll = get_head_pose(facelist)
            #脸部特征参数放队列里去
            feature_queue.append([mar, ear_l, ear_r, pitch, yaw, roll])
        #如果突然没检测到脸 说明乱动了 并不疲劳
        else:
            print("请调整坐姿")
            feature_queue = [[0,0,0,0,0,0]]

        #计算疲劳参数
        close_time, perclos, open_time = get_fatigue_parameter(feature_queue,close_time,open_time,EAR_THRESH=EAR_THRESH,MAR_THRESH=MAR_THRESH,T=50)
        #判断疲劳 alert1是关于眼部的 alert2是关于嘴部的
        alert1, alert2, yawnTime1 = fatigue_datection(close_time, open_time,alert1=alert1,alert2=alert2,yawnTime1=yawnTime1,P=PERCLOS,yawn_time=Yawn_time)

        # 是否画点
        if DRAW and len(facelist) != 0:
            img = drawCircle_face(img, facelist, left_eye, right_eye, mouth)
        if DRAW and len(lmList) != 0:
            img = drawCircle_pose(img, lmList)


        t2 = time.time()
        fps = 1 / (t2 - t1)


        '''显示部分'''
        if alert1:
            cv2.putText(img, "EYE_Fatigue", (200, 180), cv2.FONT_HERSHEY_PLAIN, 3,
                        (255, 0, 0), 3)
        if alert2:
            cv2.putText(img, "YWAN_Fatigue", (200, 280), cv2.FONT_HERSHEY_PLAIN, 3,
                        (255, 0, 0), 3)
        if head_down:
            cv2.putText(img, "Head Down !!!", (100, 80), cv2.FONT_HERSHEY_PLAIN, 3,
                        (255, 0, 0), 3)
        if phone_call:
            cv2.putText(img, "Calling !!!", (100, 120), cv2.FONT_HERSHEY_PLAIN, 3,
                        (255, 0, 0), 3)

        cv2.putText(img, f'FPS:{int(fps)}', (10, 60), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
        cv2.putText(img, "MAR: {:.2f}".format(mar), (300, 60), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
        cv2.putText(img, "EAR_L: {:.2f}".format(ear_l), (300, 90), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
        cv2.putText(img, "EAR_R: {:.2f}".format(ear_r), (500, 90), cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 0, 255), 2)
        cv2.putText(img, "X: " + "{:5.2f}".format(pitch), (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.75,
                    (0, 0, 255), thickness=2)  # GREEN
        cv2.putText(img, "Y: " + "{:5.2f}".format(yaw), (150, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.75,
                    (0, 0, 255), thickness=2)  # BLUE
        cv2.putText(img, "Z: " + "{:5.2f}".format(roll), (300, 30), cv2.FONT_HERSHEY_SIMPLEX, 0.75,
                    (0, 0, 255), thickness=2)  # RED
        cv2.imshow('DETECTION', img)


        if cv2.waitKey(1) & 0xFF == 27:
            cv2.destroyAllWindows()
            cap.release()
            break