1、加载一张图片
main函数:
cv::Mat img = cv::imread("5.jpg");vector<Point2f> points_vec = dectectFace68(img);
2、人脸68特征识别函数
在这里vector<Point2f> dectectFace68(Mat src)
{vector<Point2f> points_vec;int* pResults = NULL;//在检测函数中使用了pBuffer。 //如果你调用多个线程中的函数,请为每个线程创建一个缓冲区! unsigned char* pBuffer = (unsigned char*)malloc(DETECT_BUFFER_SIZE);if (!pBuffer){fprintf(stderr, "Can not alloc buffer.\n");//return 100;}Mat gray;cvtColor(src, gray, CV_BGR2GRAY);int doLandmark = 1;// do landmark detection pResults = facedetect_multiview_reinforce(pBuffer, (unsigned char*)(gray.ptr(0)), gray.cols, gray.rows, (int)gray.step,1.2f, 2, 48, 0, doLandmark);int cxa = *pResults;ofstream file("facedata.txt", ios::out);//打印检测结果 if (0 == cxa){}else{for (int i = 0; i < (pResults ? *pResults : 0); i++){short* p = ((short*)(pResults + 1)) + 142 * i;//rectangle(src, Rect(p[0], p[1], p[2], p[3]), Scalar(0, 255, 0), 2);if (doLandmark){for (int j = 0; j < 68; j++){char c[8];_itoa(j, c, 10);Point2f ff(p[6 + 2 * j], p[6 + 2 * j + 1]);points_vec.push_back(ff);file << ff.x << "\t" << ff.y << endl;/* circle(src, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), 3, Scalar(0, 0, 255), 3);CvPoint font;putText(src, c, Point((int)p[6 + 2 * j], (int)p[6 + 2 * j + 1]), FONT_HERSHEY_SIMPLEX, 0.5, Scalar(255, 23, 0), 1);*/}}}}return points_vec;
}插入代码片
3、结果