PERCLOS的python代码

PERCLOS，即眼睑闭合程度百分比（Percentage of Eye Closure over Time），是一种用于评估疲劳程度和注意力水平的指标。以下是使用Python计算PERCLOS的示例代码：

import cv2
import dlib
import numpy as np

# 加载dlib的面部检测器
detector = dlib.get_frontal_face_detector()
# 加载dlib的眼睛检测器
predictor = dlib.shape_predictor('path/to/shape_predictor_68_face_landmarks.dat')

# 定义常量
EAR_THRESH = 0.2  # EAR阈值
FRAME_THRESH = 2  # 连续帧数阈值

# 初始化变量
frame_count = 0  # 连续帧数
ear_list = []  # EAR值列表

# 读取视频
cap = cv2.VideoCapture('path/to/video.mp4')
while cap.isOpened():
    # 读取一帧图像
    ret, frame = cap.read()
    if not ret:
        break

    # 转换为灰度图像
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # 检测面部区域
    faces = detector(gray, 0)

    # 遍历面部区域
    for face in faces:
        # 检测眼睛区域
        landmarks = predictor(gray, face)
        left_eye = np.array([(landmarks.part(i).x, landmarks.part(i).y) for i in range(36, 42)])
        right_eye = np.array([(landmarks.part(i).x, landmarks.part(i).y) for i in range(42, 48)])

        # 计算EAR值
        left_ear = eye_aspect_ratio(left_eye)
        right_ear = eye_aspect_ratio(right_eye)
        ear = (left_ear + right_ear) / 2.0

        # 绘制眼睛区域
        cv2.polylines(frame, [left_eye], True, (0, 255, 0), 1)
        cv2.polylines(frame, [right_eye], True, (0, 255, 0), 1)

        # 判断EAR值是否小于阈值
        if ear < EAR_THRESH:
            frame_count += 1
        else:
            # EAR值大于阈值，重置连续帧数
            if frame_count >= FRAME_THRESH:
                ear_list.append(frame_count)
            frame_count = 0

    # 显示图像
    cv2.imshow('frame', frame)
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# 释放资源
cap.release()
cv2.destroyAllWindows()

# 计算PERCLOS值
perclos = sum(ear_list) / len(ear_list) / FRAME_THRESH
print('PERCLOS:', perclos)

# 计算EAR值
def eye_aspect_ratio(eye):
    # 计算距离
    A = np.linalg.norm(eye[1] - eye[5])
    B = np.linalg.norm(eye[2] - eye[4])
    C = np.linalg.norm(eye[0] - eye[3])
    # 计算EAR值
    ear = (A + B) / (2.0 * C)
    return ear

需要注意的是，上述代码中需要使用dlib库进行面部和眼睛检测，因此需要预先安装该库并下载面部检测器和眼睛检测器的数据文件。