FaceRecTest1.rar_opencv 训练_opencv人脸识别_人脸_人脸识别_人脸识别opencv

#define _CRT_SECURE_NO_DEPRECATE #include <iostream> #include <stdio.h> #include <ocl\ocl.hpp> #include <opencv2\opencv.hpp> using namespace cv; using namespace std; CascadeClassifier cas("haarcascade_frontalface_default.xml"); //加载人脸分类器 Ptr<FaceRecognizer> fc = createFisherFaceRecognizer(); //vector<Mat> images; //vector<int>labels; VideoCapture cap; vector<Rect> recs; int x = 0, y = 0; int main() { Mat a1 = imread("m01.jpg", CV_LOAD_IMAGE_GRAYSCALE); //加载用于训练的人脸照片 Mat a2 = imread("m02.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat a3 = imread("m03.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat a4 = imread("m04.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat a5 = imread("m05.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat b1 = imread("k01.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat b2 = imread("k02.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat b3 = imread("k03.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat b4 = imread("k04.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat b5 = imread("k05.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat c1 = imread("d01.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat c2 = imread("d02.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat c3 = imread("d03.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat c4 = imread("d04.jpg", CV_LOAD_IMAGE_GRAYSCALE); Mat c5 = imread("d05.jpg", CV_LOAD_IMAGE_GRAYSCALE); vector<Mat> images; vector<int>labels; images.push_back(a1); //照片和标签存入向量里，我了三个人的 labels.push_back(0); images.push_back(a2); labels.push_back(0); images.push_back(a3); labels.push_back(0); images.push_back(a4); labels.push_back(0); images.push_back(a5); labels.push_back(0); images.push_back(b1); labels.push_back(1); images.push_back(b2); labels.push_back(1); images.push_back(b3); labels.push_back(1); images.push_back(b4); labels.push_back(1); images.push_back(b5); labels.push_back(1); images.push_back(c1); labels.push_back(2); images.push_back(c2); labels.push_back(2); images.push_back(c3); labels.push_back(2); images.push_back(c4); labels.push_back(2); images.push_back(c5); labels.push_back(2); fc->train(images, labels); //训练 VideoCapture cap; cap.open(0); Mat image; vector<Rect> recs; Mat test(400, 500, CV_8UC1); Mat gray; int x = 0, y = 0; for (;;) { cap >> image; if (image.empty()) break; cas.detectMultiScale(image, recs,1.2,6,0,Size(50,50)); //先检测人脸 for (int i = 0; i < recs.size();i++) { rectangle(image, recs[i], Scalar(0, 0, 255)); x = recs[i].x + recs[i].width / 2; y = recs[i].y + recs[i].height / 2; Mat roi = image(recs[i]); //因为我训练的样本是400*500大小，所以需要把摄像头中的人脸区域改为400*500大小 cvtColor(roi, gray, CV_BGR2GRAY); resize(gray, test, Size(400, 500)); int result = fc->predict(test); switch (result) { case 0: putText(image, "a", Point(recs[i].x, recs[i].y), FONT_HERSHEY_SIMPLEX, 1.5, Scalar(0, 0, 255), 2); break; case 1: putText(image, "b", Point(recs[i].x, recs[i].y), FONT_HERSHEY_SIMPLEX, 1.5, Scalar(0, 0, 255), 2); break; case 2: putText(image, "c", Point(recs[i].x, recs[i].y), FONT_HERSHEY_SIMPLEX, 1.5, Scalar(0, 0, 255), 2); break; } } imshow("Sample", image); if (waitKey(30) >= 0) break; } }