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：
代码语言：javascript复制
#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：
