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
9 const size_t width = 300;//模型尺寸为300*300
10 const size_t height = 300;
11 //label文件
12 String labelFile = "D:/opencv3.3/opencv/sources/samples/data/dnn/labelmap_det.txt";
13 //模型文件
14 String modelFile = "D:/opencv3.3/opencv/sources/samples/data/dnn/VGG_ILSVRC2016_SSD_300x300_iter_440000.caffemodel";
15 //模型描述文件
16 String model_text_file = "D:/opencv3.3/opencv/sources/samples/data/dnn/deploy.prototxt";
17
18 vector<String> readLabels();
19 const int meanValues[3] = { 104, 117, 123 };
20 static Mat getMean(const size_t &w, const size_t &h) {
21 Mat mean;
22 vector<Mat> channels;
23 for (int i = 0; i < 3; i++) {
24 Mat channel(h, w, CV_32F, Scalar(meanValues[i]));
25 channels.push_back(channel);
26 }
27 merge(channels, mean);
28 return mean;
29 }
30
31 static Mat preprocess(const Mat &frame) {
32 Mat preprocessed;
33 frame.convertTo(preprocessed, CV_32F);
34 resize(preprocessed, preprocessed, Size(width, height)); // 300x300 image
35 Mat mean = getMean(width, height);
36 subtract(preprocessed, mean, preprocessed);
37 return preprocessed;
38 }
39
40 int main(int argc, char** argv) {
41 Mat frame = imread("persons.png");
42 if (frame.empty()) {
43 printf("could not load image...\n");
44 return -1;
45 }
46 namedWindow("input image", CV_WINDOW_AUTOSIZE);
47 imshow("input image", frame);
48
49 vector<String> objNames = readLabels();
50 // import Caffe SSD model
51 Ptr<dnn::Importer> importer;
52 try {
53 importer = createCaffeImporter(model_text_file, modelFile);
54 }
55 catch (const cv::Exception &err) {
56 cerr << err.msg << endl;
57 }
58 //初始化网络
59 Net net;
60 importer->populateNet(net);
61 importer.release();
62
63 Mat input_image = preprocess(frame);//获取输入图像
64 Mat blobImage = blobFromImage(input_image);//将图像转换为blob
65
66 net.setInput(blobImage, "data");//将图像转换的blob数据输入到网络的第一层“data”层，见deploy.protxt文件
67 Mat detection = net.forward("detection_out");//结果输出（最后一层“detection_out”层）输出给detection
68 Mat detectionMat(detection.size[2], detection.size[3], CV_32F, detection.ptr<float>());
69 float confidence_threshold = 0.2;//自信区间，可以修改，越低检测到的物体越多
70 for (int i = 0; i < detectionMat.rows; i++) {
71 float confidence = detectionMat.at<float>(i, 2);
72 if (confidence > confidence_threshold) {
73 size_t objIndex = (size_t)(detectionMat.at<float>(i, 1));
74 float tl_x = detectionMat.at<float>(i, 3) * frame.cols;
75 float tl_y = detectionMat.at<float>(i, 4) * frame.rows;
76 float br_x = detectionMat.at<float>(i, 5) * frame.cols;
77 float br_y = detectionMat.at<float>(i, 6) * frame.rows;
78
79 Rect object_box((int)tl_x, (int)tl_y, (int)(br_x - tl_x), (int)(br_y - tl_y));
80 //标记框
81 rectangle(frame, object_box, Scalar(0, 0, 255), 2, 8, 0);
82 //设置颜色
83 putText(frame, format("%s", objNames[objIndex].c_str()), Point(tl_x, tl_y), FONT_HERSHEY_SIMPLEX, 1.0, Scalar(255, 0, 0), 2);
84 }
85 }
86 imshow("ssd-demo", frame);
87
88 waitKey(0);
89 return 0;
90 }
91
92 vector<String> readLabels() {
93 vector<String> objNames;
94 ifstream fp(labelFile);
95 if (!fp.is_open()) {
96 printf("could not open the file...\n");
97 exit(-1);
98 }
99 string name;
100 while (!fp.eof()) {
101 getline(fp, name);
102 if (name.length() && (name.find("display_name:") == 0)) {
103 string temp = name.substr(15);
104 temp.replace(temp.end() - 1, temp.end(), "");
105 objNames.push_back(temp);
106 }
107 }
108 return objNames;
109 }
