基于opencv的疲劳驾驶检测 c++代码

以下是基于OpenCV实现疲劳驾驶检测的C++代码：

#include <iostream>
#include <opencv2/opencv.hpp>

using namespace std;
using namespace cv;

int main(int argc, char** argv)
{
    VideoCapture cap(0);
    if (!cap.isOpened())
    {
        cout << "Failed to open camera." << endl;
        return -1;
    }

    int frameCount = 0;
    int eyeCloseCount = 0;
    int eyeOpenCount = 0;
    int yawnCount = 0;

    while (true)
    {
        Mat frame;
        cap >> frame;

        if (frame.empty())
        {
            cout << "Failed to capture frame." << endl;
            break;
        }

        // 人脸检测
        CascadeClassifier faceDetector("haarcascade_frontalface_alt.xml");
        vector<Rect> faces;
        faceDetector.detectMultiScale(frame, faces, 1.1, 2, 0 | CASCADE_SCALE_IMAGE, Size(30, 30));

        if (faces.size() == 0)
        {
            cout << "Failed to detect face." << endl;
            continue;
        }

        // 眼睛检测
        CascadeClassifier eyeDetector("haarcascade_eye.xml");
        vector<Rect> eyes;
        eyeDetector.detectMultiScale(frame(faces[0]), eyes, 1.1, 2, 0 | CASCADE_SCALE_IMAGE, Size(20, 20));

        bool isEyeOpen = false;
        for (int i = 0; i < eyes.size(); i++)
        {
            rectangle(frame(faces[0]), eyes[i], Scalar(255, 0, 0), 2);
            if (eyes[i].y + eyes[i].height / 2 < faces[0].y + faces[0].height / 2)
            {
                isEyeOpen = true;
            }
        }

        // 嘴巴检测
        CascadeClassifier mouthDetector("haarcascade_mcs_mouth.xml");
        vector<Rect> mouths;
        mouthDetector.detectMultiScale(frame(faces[0]), mouths, 1.1, 2, 0 | CASCADE_SCALE_IMAGE, Size(30, 30));

        bool isMouthOpen = false;
        for (int i = 0; i < mouths.size(); i++)
        {
            rectangle(frame(faces[0]), mouths[i], Scalar(0, 255, 0), 2);
            if (mouths[i].y + mouths[i].height / 2 > faces[0].y + faces[0].height / 2)
            {
                isMouthOpen = true;
            }
        }

        // 统计疲劳情况
        frameCount++;
        if (isEyeOpen)
        {
            eyeOpenCount++;
            eyeCloseCount = 0;
        }
        else
        {
            eyeCloseCount++;
            eyeOpenCount = 0;
        }

        if (isMouthOpen)
        {
            yawnCount++;
        }

        if (eyeCloseCount > 30 || yawnCount > 5)
        {
            cout << "Driver is fatigued!" << endl;
            break;
        }

        imshow("Fatigue Detection", frame);
        if (waitKey(30) == 'q')
        {
            break;
        }
    }

    cout << "Frame Count: " << frameCount << endl;
    cout << "Eye Open Count: " << eyeOpenCount << endl;
    cout << "Eye Close Count: " << eyeCloseCount << endl;
    cout << "Yawn Count: " << yawnCount << endl;

    return 0;
}

这段代码基于OpenCV实现了疲劳驾驶检测，其中包括人脸检测、眼睛检测、嘴巴检测和疲劳情况统计。具体流程如下：

1. 打开摄像头，获取一帧图像。
2. 使用Haar级联分类器检测人脸。
3. 在人脸区域中使用Haar级联分类器检测眼睛和嘴巴。
4. 判断眼睛是否闭合，统计连续闭合的帧数。
5. 判断嘴巴是否张开，统计连续张开的帧数。
6. 如果眼睛连续闭合的帧数超过阈值或嘴巴连续张开的帧数超过阈值，则判定驾驶员疲劳。
7. 显示检测结果并等待用户按下“q”键退出程序。

注：上述代码中，使用了三个级联分类器文件：haarcascade_frontalface_alt.xml、haarcascade_eye.xml、haarcascade_mcs_mouth.xml。这些文件可以在OpenCV的安装目录下的data目录中找到。