附源码 | SeetaFace6Open开源人脸识别引擎库 人脸识别演示

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来源：公众号 小MoMing工作室 授权

 

SeetaFace6提供了人脸的11个模型，本体验用到了其中7个。

已用到：人脸检测，关键点检测，人脸识别，性别，年龄，眼睛，活体检测；

未用到：带口罩识别，人脸追踪，人脸姿态，质量评估。

SeetaFace6：https://github.com/SeetaFace6Open/index

SeetaFace文档完善，开发方便。支持戴口罩与不带口罩的人脸识别：

支持端侧与云部署，当前开源版本的三个不同模型输的特征向量维度与推理速度：

 

代码演示部分，废话太多了，直接上代码：

#include <iostream>#include <opencv2/opencv.hpp>//用到seetaface的7个模块#include <seeta/FaceDetector.h>#include <seeta/FaceLandmarker.h>#include <seeta/FaceRecognizer.h>#include <seeta/GenderPredictor.h>#include <seeta/AgePredictor.h>#include <seeta/EyeStateDetector.h>#include <seeta/FaceAntiSpoofing.h>#include "draw_box.hpp"

#ifdef _DEBUG

//debug 库,11个#pragma comment(lib,"SeetaFaceDetector600d.lib") #pragma comment(lib,"SeetaFaceLandmarker600d.lib")

#pragma comment(lib,"SeetaFaceRecognizer610d.lib")#pragma comment(lib,"SeetaGenderPredictor600d.lib") #pragma comment(lib,"SeetaAgePredictor600d.lib") #pragma comment(lib,"SeetaFaceAntiSpoofingX600d.lib") #pragma comment(lib,"SeetaEyeStateDetector200d.lib")

//这四个没用到#pragma comment(lib,"SeetaMaskDetector200d.lib")#pragma comment(lib,"SeetaFaceTracking600d.lib") #pragma comment(lib,"SeetaPoseEstimation600d.lib")#pragma comment(lib,"SeetaQualityAssessor300d.lib")

#else//release 库,11个#pragma comment(lib,"SeetaFaceDetector600.lib") #pragma comment(lib,"SeetaFaceLandmarker600.lib")

#pragma comment(lib,"SeetaFaceRecognizer610.lib")#pragma comment(lib,"SeetaGenderPredictor600.lib") #pragma comment(lib,"SeetaAgePredictor600.lib") #pragma comment(lib,"SeetaFaceAntiSpoofingX600.lib") #pragma comment(lib,"SeetaEyeStateDetector200.lib")

//这四个没用到#pragma comment(lib,"SeetaMaskDetector200.lib")#pragma comment(lib,"SeetaFaceTracking600.lib") #pragma comment(lib,"SeetaPoseEstimation600.lib")#pragma comment(lib,"SeetaQualityAssessor300.lib")#endif

using namespace seeta;using namespace std;using namespace cv;

//提取特征bool extract_feature(Mat img,const FaceDetector& FD,const FaceLandmarker& FL,const FaceRecognizer& FR,float* feature){  SeetaImageData simg;  simg.height = img.rows;  simg.width = img.cols;  simg.channels = img.channels();  simg.data = img.data;

  auto faces = FD.detect(simg);

  if (faces.size <= 0){    cout << "no face detected" << endl;    return false;  }

  SeetaPointF points[5];  FL.mark(simg, faces.data[0].pos, points);

  FR.Extract(simg, points, feature);  return true;}

string get_eye_status(seeta::EyeStateDetector::EYE_STATE state){  if (state == seeta::EyeStateDetector::EYE_CLOSE)    return "闭合";  else if (state == seeta::EyeStateDetector::EYE_OPEN)    return "张开";  else if (state == seeta::EyeStateDetector::EYE_RANDOM)    return "无法判断";  else    return "无法判断";}

string get_fas_status(seeta::FaceAntiSpoofing::Status status) {  switch (status) {  case seeta::FaceAntiSpoofing::REAL:    return "真实人脸";  case seeta::FaceAntiSpoofing::SPOOF:    return "照片人脸";  case seeta::FaceAntiSpoofing::FUZZY:    return "无法判断";  case seeta::FaceAntiSpoofing::DETECTING:    return "正在检测";  }  return "无法判断";}



int main(){  string ModelPath = "E:/workspace/03-research/03-cv/face/SeeTaFaceDemo/sf3.0_models/";

  //1.人脸检测模型初始化  ModelSetting FD_setting;  FD_setting.append(ModelPath + "face_detector.csta");  FD_setting.set_device(ModelSetting::CPU);  FD_setting.set_id(0);  FaceDetector FD(FD_setting);

  //2.人脸关键点模型初始化  ModelSetting PD_setting;  PD_setting.append(ModelPath + "face_landmarker_pts5.csta");  FaceLandmarker FL(PD_setting);

  //3.人脸识别模型初始化  ModelSetting fr_setting;  fr_setting.append(ModelPath + "face_recognizer.csta");  FaceRecognizer FR(fr_setting);

  //4.性别检测模型初始化  ModelSetting gb_setting(ModelPath + "gender_predictor.csta");  GenderPredictor GP(gb_setting);

  //5.年龄检测模型初始化  ModelSetting ap_setting(ModelPath + "age_predictor.csta");  AgePredictor AP(ap_setting);

  //6.眼睛状态模型初始化  ModelSetting setting;  setting.append(ModelPath + "eye_state.csta");  EyeStateDetector EBD(setting);

  //7.活体检测模型初始化  ModelSetting anti_setting;  anti_setting.append(ModelPath + "fas_first.csta");  anti_setting.append(ModelPath + "fas_second.csta");  FaceAntiSpoofing FAS(anti_setting);  FAS.SetThreshold(0.3, 0.90);//设置默认阈值，另外一组阈值为(0.7, 0.55)  FAS.SetBoxThresh(0.9);



  //建立人脸数据库的人脸特征向量：这里只有两张人脸1.jpg(刘德华)，2.jpg(薇娅)  vector<pair<string, shared_ptr<float> > > feature_db;  shared_ptr<float> feature1(new float[FR.GetExtractFeatureSize()]);  Mat ldh = imread("1.jpg");  extract_feature(ldh,FD, FL, FR,feature1.get());  feature_db.emplace_back(pair<string, shared_ptr<float>>("刘德华", feature1));

  shared_ptr<float> feature2(new float[FR.GetExtractFeatureSize()]);  Mat wy = imread("2.jpg");  extract_feature(wy,FD, FL, FR, feature2.get());  feature_db.emplace_back(pair<string, shared_ptr<float>>("薇娅", feature2));



  namedWindow("SeetaFaceAntiSpoofing", 0);

  Mat frame;  VideoCapture capture("F:/20201204-WY-LDH-cut.mp4");// ");  VideoWriter writer;  cv::resize(ldh, ldh, cv::Size(120, 160));  cv::resize(wy, wy, cv::Size(120, 160));

  if (!capture.isOpened())  {    cout << "fail to open!" << endl;    return -1;  }

  while (true)  {    if (!capture.read(frame)){      cout << "can not read any frame" << endl;      break;    }    //ImageData image = frame;    SeetaImageData image;    image.height = frame.rows;    image.width = frame.cols;    image.channels = frame.channels();    image.data = frame.data;

    auto faces = FD.detect(image);    cout << "faces.size:" << faces.size << endl;

    for (int i = 0; i < faces.size; i++)    {      vector<string> labels;      Scalar color(0x00, 0xA0, 0x00);      //----人脸----      auto face = faces.data[i].pos;

      //----关键点检测----      vector<SeetaPointF> points(FL.number());      FL.mark(image, face, points.data());

      //----人脸识别----      unique_ptr<float[]> feature(new float[FR.GetExtractFeatureSize()]);      FR.Extract(image, points.data(), feature.get());

      //人脸识别      float threshold = 0.60;      int64_t target_index = -1;      float max_sim = 0;      for (size_t index = 0; index < feature_db.size(); ++index){        auto& pair_name_feat = feature_db[index];        float current_sim = FR.CalculateSimilarity(feature.get(), pair_name_feat.second.get());        if (current_sim > max_sim){          max_sim = current_sim;          target_index = index;        }      }      if (max_sim > threshold)         labels.push_back(feature_db[target_index].first+"（相似度:"+ to_string(max_sim *100).substr(0,5) +"）");      else         labels.push_back("查无此人");      //----性别----      GenderPredictor::GENDER gender;      GP.PredictGenderWithCrop(image, points.data(), gender);      string gender_str = (string("性别：") + (gender == GenderPredictor::GENDER::MALE ? "男" : "女"));

      //----年龄----      int age;      AP.PredictAgeWithCrop(image, points.data(), age);      labels.push_back(gender_str + string("，年龄：") + to_string(age));

      //----眼睛状态----      EyeStateDetector::EYE_STATE leftstate, rightstate;      EBD.Detect(image, points.data(), leftstate, rightstate);      labels.push_back(string("左眼：") + get_eye_status(leftstate)+ string("，右眼：") + get_eye_status(rightstate));

      //活体检测      auto status = FAS.Predict(image, face, points.data());//PredictVideo      float clarity;      float reality;

      FAS.GetPreFrameScore(&clarity, &reality);      labels.push_back(string("活体检测：") + get_fas_status(status));      if (status == FaceAntiSpoofing::SPOOF)        color = Scalar(0x00, 0x00, 0xB0);      drawResult(color, labels, 0, 0.0f, face.x, face.y, face.x + face.width, face.y + face.height, frame);    }    Scalar title_color(0x00, 0x8C, 0xFF);    //绘制人脸库    int space = 6;    frame(cv::Rect(frame.cols / 2 - ldh.cols - space / 2 - space, frame.rows - ldh.rows - space -space, ldh.cols * 2+space+ 2*space, ldh.rows + 2 * space)) = title_color;    ldh.copyTo(frame(cv::Rect(frame.cols / 2 - ldh.cols - space/2,   frame.rows -ldh.rows - space, ldh.cols, ldh.rows)));    wy.copyTo(frame(cv::Rect(frame.cols / 2 + space / 2,             frame.rows - wy.rows - space, wy.cols, wy.rows)));    static cv::Ptr<cv::freetype::FreeType2> ft2;    if (!ft2) {     ft2 = cv::freetype::createFreeType2();     ft2->loadFontData("c:/windows/fonts/msyh.ttc", 0);    }    int baseline = 0;    int fontHeight = 45;    cv::Size text_size;    if (ft2) text_size = ft2->getTextSize("人脸库(2张)", fontHeight, -1, &baseline);    if (ft2)ft2->putText(frame, "人脸库(2张)", cv::Point(frame.cols/2 - text_size.width/2, frame.rows  - ldh.rows/2), fontHeight, title_color, -1, 16, true);    fontHeight = 60;    //绘制最上面的title    string title = "SeetaFace人脸库体验";    text_size = ft2->getTextSize(title, fontHeight, -1, &baseline);    ft2->putText(frame, title, cv::Point(frame.cols / 2 - text_size.width / 2, 60), fontHeight, title_color, -1, 16, true);

    fontHeight = 30;    title = "用到：人脸,关键点,识别,性别,年龄,眼睛,活体；未用到：口罩,追踪,姿态,质量评估";    text_size = ft2->getTextSize(title, fontHeight, -1, &baseline);    ft2->putText(frame, title, cv::Point(frame.cols / 2 - text_size.width / 2, 60+50), fontHeight, title_color, -1, 16, true);





    //写入文件    if (!writer.isOpened()) {      writer.open("F:/setaface.avi", VideoWriter::fourcc('M', 'J', 'P', 'G'), 30, cv::Size(frame.cols, frame.rows), true);    }    if (writer.isOpened()) {      writer.write(frame);    }

    //窗口显示    imshow("SeetaFaceAntiSpoofing", frame);

    //Esc键退出    if (waitKey(1) == 27)      break;  }

  writer.release();  capture.release();

  return 0;}#pragma once#include <string>#include <iostream>

#include <opencv2/opencv.hpp>#include <opencv2/freetype.hpp>

using namespace cv;using namespace std;

//float colors[6][3] = { {1,0,1}, {0,0,1},{0,1,1},{0,1,0},{1,1,0},{1,0,0} };////float get_color(int c, int x, int max)//{//    float ratio = ((float)x / max) * 5;//    int i = floor(ratio);//    int j = ceil(ratio);//    ratio -= i;//    float r = (1 - ratio) * colors[i][c] + ratio * colors[j][c];//    return r;//}



void drawResult(Scalar color,std::vector<string> labels,int classId, float conf, int left, int top, int right, int bottom, Mat& frame){    /*    static std::vector<string> labels = {        "船名: GOLDEN MONTERREY",        "呼号：V7MG6",        "MMSI: 538006355",        "航首向: 110度",        "航迹向: 108度",        "航速度: 11.9",        "经纬度：120.35889, 36.017105",        "更新时间: 2020-11-06 10:38:48"    };    */    //std::string label = /*classes[classId]*/ +"(" + std::to_string(int(conf * 100)) + "%)";

    //classId = 0;//选颜色    //static int classes = 80;    //static int offset = (classId + 2) * 123457 % classes;    //static float red = get_color(2, offset, classes);    //static float green = get_color(1, offset, classes);    //static float blue = get_color(0, offset, classes);    //static cv::Scalar color(int(red * 256), int(green * 256), int(blue * 256));



    static cv::Ptr<cv::freetype::FreeType2> ft2;    if (!ft2) {        ft2 = cv::freetype::createFreeType2();        ft2->loadFontData("c:/windows/fonts/msyh.ttc", 0);    }

    int fontHeight = 25;    int fontTotalHeight = fontHeight * labels.size();    int thickness = -1;    int linestyle = LineTypes::LINE_AA;    int baseline = 0;

    int max_label_index = 0;    int padding = 5;    for (int i = 1; i < labels.size(); i++) {        if (labels[i].length() > labels[max_label_index].length())            max_label_index = i;    }    cv::Size text_size;    if (ft2) text_size = ft2->getTextSize(labels[max_label_index], fontHeight, thickness, &baseline);    else text_size = cv::getTextSize(labels[max_label_index], fontHeight, 1.0f, thickness = 0, &baseline);

    fontTotalHeight += 2 * padding + 2* labels.size();    text_size.width += 2 * padding;

    cv::Point pt1, pt2;    cv::Point pt_text_bg1, pt_text_bg2;    cv::Point pt_text;

    //物体框    pt1.x = left;    pt1.y = top;    pt2.x = right;    pt2.y = bottom;

    //文本背景框    pt_text_bg1.x = left;    pt_text_bg1.y = top - fontTotalHeight;    pt_text_bg2.x = std::max(left + text_size.width, right);    pt_text_bg2.y = top;



    //文本原点(左下角)    pt_text.x = left + padding;    pt_text.y = top - padding;

    static int rect_line_width = 2;//std::max(1.0f, show_img->rows * .002f);    cv::rectangle(frame, pt1, pt2, color, rect_line_width, linestyle, 0);

    cv::rectangle(frame, pt_text_bg1, pt_text_bg2, color, rect_line_width, linestyle, 0);    cv::rectangle(frame, pt_text_bg1, pt_text_bg2, color, cv::FILLED, linestyle, 0);

    static cv::Scalar text_color = CV_RGB(255, 255, 255);

    for (int i = labels.size() - 1; i >= 0; i--) {        if (ft2)ft2->putText(frame, labels[i], pt_text, fontHeight+(i==0?5:0), text_color, thickness, linestyle, true);        else putText(frame, labels[i], pt_text, fontHeight, 1.0f, text_color, thickness = 0, linestyle, true);        pt_text.y -= (fontHeight + 2);//((labels.size()-1 -i) * fontHeight);    }}

 

视频B站观看地址 ：

https://www.bilibili.com/video/BV1qK411u7TF/

 

运行效果视频截图：

 

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