1 #include <opencv2/opencv.hpp>
2 #include <opencv2/dnn.hpp>
3 #include <iostream>
4
5 using namespace cv;
6 using namespace cv::dnn;
7 using namespace std;
8 //人脸检测文件
9 String haar_file = "D:/opencv3.3/opencv/build/etc/haarcascades/haarcascade_frontalface_alt_tree.xml";
10 //年龄预测模型
11 String age_model = "D:/opencv3.3/opencv/sources/samples/data/dnn/age_net.caffemodel";
12 //年龄描述文件
13 String age_text = "D:/opencv3.3/opencv/sources/samples/data/dnn/deploy_age.prototxt";
14
15 //性别预测模型
16 String gender_model = "D:/opencv3.3/opencv/sources/samples/data/dnn/gender_net.caffemodel";
17 //年龄描述文件
18 String gender_text = "D:/opencv3.3/opencv/sources/samples/data/dnn/deploy_gender.prototxt";
19
20 void predict_age(Net &net, Mat &image);//预测年龄
21 void predict_gender(Net &net, Mat &image);//预测性别
22 int main(int argc, char** argv) {
23 Mat src = imread("star_lady.png");
24 if (src.empty()) {
25 printf("could not load image...\n");
26 return -1;
27 }
28 namedWindow("input", CV_WINDOW_AUTOSIZE);
29 imshow("input", src);
30 CascadeClassifier detector;
31 detector.load(haar_file);//人脸检测
32 vector<Rect> faces;
33 Mat gray;
34 cvtColor(src, gray, COLOR_BGR2GRAY);
35 detector.detectMultiScale(gray, faces, 1.02, 1, 0, Size(40, 40), Size(200, 200));
36 //加载网络
37 Net age_net = readNetFromCaffe(age_text, age_model);
38 Net gender_net = readNetFromCaffe(gender_text, gender_model);
39
40 for (size_t t= 0; t < faces.size(); t++) {
41 rectangle(src, faces[t], Scalar(30, 255, 30), 2, 8, 0);
42 //年龄、性别预测
43 Mat face = src(faces[t]);//自己加的，不加会报错，提示类型错误
44 predict_age(age_net, face);
45 predict_gender(age_net, face);
46 }
47 imshow("age-gender-prediction-demo", src);
48
49 waitKey(0);
50 return 0;
51 }
52
53 vector<String> ageLabels() {
54 vector<String> ages;
55 ages.push_back("0-2");
56 ages.push_back("4 - 6");
57 ages.push_back("8 - 13");
58 ages.push_back("15 - 20");
59 ages.push_back("25 - 32");
60 ages.push_back("38 - 43");
61 ages.push_back("48 - 53");
62 ages.push_back("60-");
63 return ages;
64 }
65
66 void predict_age(Net &net, Mat &image) {
67 // 输入
68 Mat blob = blobFromImage(image, 1.0, Size(227, 227));
69 net.setInput(blob, "data");
70 // 预测分类
71 Mat prob = net.forward("prob");
72 Mat probMat = prob.reshape(1, 1);//变为一行
73 Point classNum;
74 double classProb;
75
76 vector<String> ages = ageLabels();
77 minMaxLoc(probMat, NULL, &classProb, NULL, &classNum);//提取最大概率的编号和概率值
78 int classidx = classNum.x;
79 putText(image, format("age:%s", ages.at(classidx).c_str()), Point(2, 10), FONT_HERSHEY_PLAIN, 0.8, Scalar(0, 0, 255), 1);
80 }
81
82 void predict_gender(Net &net, Mat &image) {
83 // 输入
84 Mat blob = blobFromImage(image, 1.0, Size(227, 227));
85 net.setInput(blob, "data");
86 // 预测分类
87 Mat prob = net.forward("prob");
88 Mat probMat = prob.reshape(1, 1);
89 putText(image, format("gender:%s", (probMat.at<float>(0, 0) > probMat.at<float>(0, 1) ? "M" : "F")),
90 Point(2, 20), FONT_HERSHEY_PLAIN, 0.8, Scalar(0, 0, 255), 1);
91 }
