开源人脸库调用尝试
基于卷积神经网络的人脸检测库，实现了硬件指令加速，纯C SDK接口，不依赖第三方库与接口，可以独立使用，同时也提供了模型文件下载，之前的版本是caffe模型，最新版本支持pytorch。现已开源！支持最小检测人脸10x10大小
OpenCV DNN可以直接调用训练好的caffe模型文件，实现实时人脸检测，演示代码如下：
代码语言：javascript复制 1#include <opencv2/opencv.hpp>
2#include <opencv2/dnn.hpp>
3#include <iostream>
4
5using namespace cv;
6using namespace cv::dnn;
7using namespace std;
8
9const size_t inWidth = 300;
10const size_t inHeight = 300;
11const double inScaleFactor = 0.007843;
12const Scalar meanVal(104.0, 117, 123.0);
13const float confidence = 0.5;
14
15int main(int argc, char** argv) {
16 string model = "D:/projects/models/yufacedetectnet-open-v2.caffemodel";
17 string config = "D:/projects/models/yufacedetectnet-open-v2.prototxt";
18 // read network
19 Net net = readNetFromCaffe(config, model);
20 VideoCapture cap(0);
21 Mat frame;
22 while (true) {
23 bool ret = cap.read(frame);
24 if (!ret) {
25 break;
26 }
27 int64 start = getTickCount();
28 Mat input_data = blobFromImage(frame, inScaleFactor, Size(320, 240), meanVal, false, false);
29 net.setInput(input_data);
30
31 // 人脸检测
32 Mat detection = net.forward();
33 Mat detectionMat(detection.size[2], detection.size[3], CV_32F, detection.ptr<float>());
34
35 // 推断时间
36 vector<double> layersTimings;
37 double freq = getTickFrequency() / 1000;
38 double time = net.getPerfProfile(layersTimings) / freq;
39
40 ostringstream ss;
41 for (int i = 0; i < detectionMat.rows; i )
42 {
43 // 置信度 0～1之间
44 float score = detectionMat.at<float>(i, 2);
45 if (score > confidence)
46 {
47 int xLeftBottom = static_cast<int>(detectionMat.at<float>(i, 3) * frame.cols);
48 int yLeftBottom = static_cast<int>(detectionMat.at<float>(i, 4) * frame.rows);
49 int xRightTop = static_cast<int>(detectionMat.at<float>(i, 5) * frame.cols);
50 int yRightTop = static_cast<int>(detectionMat.at<float>(i, 6) * frame.rows);
51
52 Rect object((int)xLeftBottom, (int)yLeftBottom,
53 (int)(xRightTop - xLeftBottom),
54 (int)(yRightTop - yLeftBottom));
55
56 rectangle(frame, object, Scalar(0, 255, 0));
57
58 ss << score;
59 String conf(ss.str());
60 String label = "Face: " conf;
61 int baseLine = 0;
62 Size labelSize = getTextSize(label, FONT_HERSHEY_SIMPLEX, 0.5, 1, &baseLine);
63 rectangle(frame, Rect(Point(xLeftBottom, yLeftBottom - labelSize.height),
64 Size(labelSize.width, labelSize.height baseLine)),
65 Scalar(255, 255, 255), FILLED);
66 putText(frame, label, Point(xLeftBottom, yLeftBottom),
67 FONT_HERSHEY_SIMPLEX, 0.5, Scalar(0, 0, 0));
68 }
69 }
70 float fps = getTickFrequency() / (getTickCount() - start);
71 ss.str("");
72 ss << "FPS: " << fps << " ; inference time: " << time << " ms";
73 putText(frame, ss.str(), Point(20, 20), 0, 0.75, Scalar(0, 0, 255), 2, 8);
74 imshow("dnn_face_detection", frame);
75 if (waitKey(1) >= 0) break;
76 }
77 waitKey(0);
78 return 0;
79}运行效果如下：
Github地址
https://github.com/ShiqiYu/libfacedetection
