# 疲劳检测，检测眼睛和嘴巴的开合程度

from scipy.spatial import distance as dist
from imutils.video import FileVideoStream
from imutils.video import VideoStream
from imutils import face_utils
import numpy as np  # 数据处理的库 numpy
import argparse
import imutils
import time
import dlib
import cv2
import math
import time
from threading import Thread

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

def mouth_aspect_ratio(mouth):  # 嘴部
    A = np.linalg.norm(mouth[2] - mouth[10])  # 51, 59
    B = np.linalg.norm(mouth[4] - mouth[8])  # 53, 57
    C = np.linalg.norm(mouth[0] - mouth[6])  # 49, 55
    mar = (A + B) / (2.0 * C)
    return mar

# 初始化DLIB的人脸检测器（HOG），然后创建面部标志物预测
print("[INFO] loading facial landmark predictor...")
# 使用dlib.get_frontal_face_detector() 获得脸部位置检测器
detector = dlib.get_frontal_face_detector()
# 使用dlib.shape_predictor获得脸部特征位置检测器
predictor = dlib.shape_predictor('weights/shape_predictor_68_face_landmarks.dat')
# 分别获取左右眼面部标志的索引
(lStart, lEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eye"]
(rStart, rEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eye"]
(mStart, mEnd) = face_utils.FACIAL_LANDMARKS_IDXS["mouth"]

# 从视频流循环帧
def detfatigue(frame):
    #frame = imutils.resize(frame, width=720)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    # 使用detector(gray, 0) 进行脸部位置检测
    rects = detector(gray, 0)
    eyear = 0.0
    mouthar = 0.0
    # 循环脸部位置信息，使用predictor(gray, rect)获得脸部特征位置的信息
    for rect in rects:
        shape = predictor(gray, rect)

        # 将脸部特征信息转换为数组array的格式
        shape = face_utils.shape_to_np(shape)

        # 提取左眼和右眼坐标
        leftEye = shape[lStart:lEnd]
        rightEye = shape[rStart:rEnd]
        # 嘴巴坐标
        mouth = shape[mStart:mEnd]

        # 构造函数计算左右眼的EAR值，使用平均值作为最终的EAR
        leftEAR = eye_aspect_ratio(leftEye)
        rightEAR = eye_aspect_ratio(rightEye)
        eyear = (leftEAR + rightEAR) / 2.0
        # 打哈欠
        mouthar = mouth_aspect_ratio(mouth)

        # 标注识别结果
        # 使用cv2.convexHull获得凸包位置，使用drawContours画出轮廓位置进行画图操作
        leftEyeHull = cv2.convexHull(leftEye)
        rightEyeHull = cv2.convexHull(rightEye)
        cv2.drawContours(frame, [leftEyeHull], -1, (0, 255, 0), 1)
        cv2.drawContours(frame, [rightEyeHull], -1, (0, 255, 0), 1)
        mouthHull = cv2.convexHull(mouth)
        cv2.drawContours(frame, [mouthHull], -1, (0, 255, 0), 1)

        # 画出眼睛、嘴巴竖直线
        cv2.line(frame,tuple(shape[38]),tuple(shape[40]),(0, 255, 0), 1)
        cv2.line(frame,tuple(shape[43]),tuple(shape[47]),(0, 255, 0), 1)
        cv2.line(frame,tuple(shape[51]),tuple(shape[57]),(0, 255, 0), 1)
        cv2.line(frame,tuple(shape[48]),tuple(shape[54]),(0, 255, 0), 1)

    # 返回信息
    # frame已经标注出眼睛和嘴巴的框线
    # eyeae为眼睛的长宽比
    # mouthar为嘴巴的长宽比
    return(frame,eyear,mouthar)