Qt编写百度离线版人脸识别+比对+活体检测

在AI技术发展迅猛的今天，很多设备都希望加上人脸识别功能，好像不加上点人脸识别功能感觉不够高大上，都往人脸识别这边靠，手机刷脸解锁，刷脸支付，刷脸开门，刷脸金融，刷脸安防，是不是以后还可以刷脸匹配男女交友？

很多人认为人脸识别直接用opencv做，其实那只是极其基础的识别个人脸，然并卵，好比学C++写了个hello类似。拿到人脸区域图片只是万里长征的第一步，真正能够起作用的是人脸特征值的提取，然后用于搜索和查找人脸，比如两张图片比较相似度，从一堆人脸库中找到最相似的人脸，对当前人脸识别是否是活体等。

对于可以接入外网的设备，可以直接通过在线api的http请求方式获得结果，但是有很多应用场景是离线的，或者说不通外网，只能局域网使用，为了安全性考虑，这个时候就要求所有的人脸处理在本地完成，本篇文章采用的百度离线SDK作为解决方案。可以去官网申请，默认有6个免费的密钥使用三个月，需要与本地设备的指纹信息匹配，感兴趣的同学可以自行去官网下载SDK。

百度离线人脸识别SDK文件比较大，光模型文件就645MB，估计这也许是识别率比较高的一方面原因吧，不断训练得出的模型库，本篇文章只放出Qt封装部分源码。官网对应的使用说明还是非常详细的，只要是学过编程的人就可以看懂。

第一步：初始化SDK

第二步：执行动作，比如查找人脸、图片比对、特征值比对等

头文件完整代码：

#ifndef FACEBAIDULOCAL_H

#define FACEBAIDULOCAL_H

/**

* 百度离线版人脸识别+人脸比对等功能类作者:feiyangqingyun(QQ:517216493) 2018-8-30

* 1:支持活体检测

* 2:可设置最大队列中的图片数量

* 3:多线程处理,通过type控制当前处理类型

* 4:支持单张图片检索相似度最高的图片

* 5:支持指定目录图片生成特征文件

* 6:支持两张图片比对方式

* 7:可设置是否快速查找

* 8:可设置是否统计用时

#include

#if (QT_VERSION > QT_VERSION_CHECK(5,0,0))

#include

#endif

#include "baidu_face_api.h"

class FaceBaiDuLocal : public QThread

{

Q_OBJECT

public:

static FaceBaiDuLocal *Instance();

explicit FaceBaiDuLocal(QObject *parent = 0);

~FaceBaiDuLocal();

protected:

void run();

private:

static QScopedPointer self;

BaiduFaceApi *api;

std::vector *faces;

QMutex mutex; //锁对象

bool stopped; //线程停止标志位

int maxCount; //最大图片张数

int type; //当前处理类型

int percent; //最小人脸百分比

int delayms; //减去毫秒数,用于造假

bool findFast; //是否快速模式

bool countTime; //统计用时

bool busy; //是否正忙

QList flags; //等待处理的图像队列的名称

QList imgs; //等待处理的图像队列

QList imgs2; //等待处理的比对图像队列

QString sdkPath; //SDK目录

QString imgDir; //图片目录

QImage oneImg; //单张图片比对找出最大特征图像

QList imgNames; //图像队列

QList > features; //特征队列

signals:

//人脸区域坐标返回

void receiveFaceRect(const QString &flag, const QRect &rect, int msec);

//获取人脸区域坐标失败

void receiveFaceRectFail(const QString &flag);

//人脸特征返回

void receiveFaceFeature(const QString &flag, const QList &feature, int msec);

//获取人脸特征失败

void receiveFaceFeatureFail(const QString &flag);

//人脸比对结果返回

void receiveFaceCompare(const QString &flag, float result, int msec);

//人脸比对失败

void receiveFaceCompareFail(const QString &flag);

//单张图片检索最大相似度结果返回

void receiveFaceCompareOne(const QString &flag, const QImage &srcImg, const QString &targetName, float result);

//所有人脸特征提取完毕

void receiveFaceFeatureFinsh();

//活体检测返回

void receiveFaceLive(const QString &flag, float result, int msec);

//活体检测失败

void receiveFaceLiveFail(const QString &flag);

public slots:

//初始化SDK

void init();

//停止处理线程

void stop();

//获取当前是否忙

bool getBusy();

//设置图片队列最大张数

void setMaxCount(int maxCount);

//设置当前处理类型

void setType(int type);

//设置最小人脸百分比

void setPercent(int percent);

//设置减去毫秒数

void setDelayms(int delayms);

//设置是否快速模式

void setFindFast(bool findFast);

//设置是否统计用时

void setCountTime(bool countTime);

//设置是否忙

void setBusy(bool busy);

//设置SDK目录

void setSDKPath(const QString &sdkPath);

//设置要将图片提取出特征的目录

void setImgDir(const QString &imgDir);

//设置单张需要检索的图片

void setOneImg(const QString &flag, const QImage &oneImg);

//往队列中追加单张图片等待处理

void append(const QString &flag, const QImage &img);

//往队列中追加两张图片等待比对

void append(const QString &flag, const QImage &img, const QImage &img2);

//自动加载目录下的所有图片的特征

void getFaceFeatures(const QString &imgDir);

//获取人脸区域

bool getFaceRect(const QString &flag, const QImage &img, QRect &rect, int &msec);

//活体检测

bool getFaceLive(const QString &flag, const QImage &img, float &result, int &msec);

//获取人脸特征

bool getFaceFeature(const QString &flag, const QImage &img, QList &feature, int &msec);

//人脸比对,传入两张照片特征

float getFaceCompare(const QString &flag, const QList &feature1, const QList &feature2);

//人脸比对,传入两张照片

bool getFaceCompare(const QString &flag, const QImage &img1, const QImage &img2, float &result, int &msec);

//从一堆图片中找到最像的一张图片

void getFaceOne(const QString &flag, const QImage &img, QString &targetName, float &result);

//指定特征找到照片

void getFaceOne(const QString &flag, const QList &feature, QString &targetName, float &result);

//添加人脸

void appendFace(const QString &flag, const QImage &img, const QString &txtFile);

//删除人脸

void deleteFace(const QString &flag);

};

#endif // FACEBAIDULOCAL_H

实现文件完整代码：

#include "facebaidulocal.h"

#define TIMEMS qPrintable(QTime::currentTime().toString("HH:mm:ss zzz"))

QByteArray getImageData(const QImage &image)

{

QByteArray imageData;

QBuffer buffer(&imageData);

image.save(&buffer, "JPG");

imageData = imageData.toBase64();

return imageData;

}

QScopedPointer FaceBaiDuLocal::self;

FaceBaiDuLocal *FaceBaiDuLocal::Instance()

{

if (self.isNull()) {

QMutex mutex;

QMutexLocker locker(&mutex);

if (self.isNull()) {

self.reset(new FaceBaiDuLocal);

}

return self.data();

}

FaceBaiDuLocal::FaceBaiDuLocal(QObject *parent) : QThread(parent)

{

//注册信号中未知的数据类型

qRegisterMetaType >("QList");

stopped = false;

maxCount = 100;

type = 1;

percent = 8;

delayms = 0;

findFast = false;

countTime = true;

busy = false;

sdkPath = qApp->applicationDirPath() + "/facesdk";

imgDir = "";

oneImg = QImage();

api = new BaiduFaceApi;

faces = new std::vector();

}

FaceBaiDuLocal::~FaceBaiDuLocal()

{

delete api;

this->stop();

this->wait(1000);

}

void FaceBaiDuLocal::run()

{

this->init();

while(!stopped) {

int count = flags.count();

if (count > 0) {

QMutexLocker lock(&mutex);

busy = true;

if (type == 0) {

QString flag = flags.takeFirst();

QImage img = imgs.takeFirst();

QRect rect;

int msec;

if (getFaceRect(flag, img, rect, msec)) {

emit receiveFaceRect(flag, rect, msec);

} else {

emit receiveFaceRectFail(flag);

}

} else if (type == 1) {

QString flag = flags.takeFirst();

QImage img = imgs.takeFirst();

QList feature;

int msec;

if (getFaceFeature(flag, img, feature, msec)) {

emit receiveFaceFeature(flag, feature, msec);

} else {

emit receiveFaceFeatureFail(flag);

}

} else if (type == 2) {

QString flag = flags.takeFirst();

QImage img1 = imgs.takeFirst();

QImage img2 = imgs2.takeFirst();

float result;

int msec;

if (getFaceCompare(flag, img1, img2, result, msec)) {

emit receiveFaceCompare(flag, result, msec);

} else {

emit receiveFaceCompareFail(flag);

}

} else if (type == 3) {

flags.takeFirst();

getFaceFeatures(imgDir);

} else if (type == 4) {

QString flag = flags.takeFirst();

QString targetName;

float result;

getFaceOne(flag, oneImg, targetName, result);

if (!targetName.isEmpty()) {

emit receiveFaceCompareOne(flag, oneImg, targetName, result);

}

} else if (type == 5) {

QString flag = flags.takeFirst();

QImage img = imgs.takeFirst();

float result;

int msec;

if (getFaceLive(flag, img, result, msec)) {

emit receiveFaceLive(flag, result, msec);

} else {

emit receiveFaceLiveFail(flag);

}

msleep(100);

busy = false;

}

stopped = false;

}

void FaceBaiDuLocal::init()

{

int res = api->sdk_init();

res = api->is_auth();

if(res != 1) {

qDebug() << TIMEMS << QString("init sdk error: %1").arg(res);

return;

} else {

//设置最小人脸,默认30

api->set_min_face_size(percent);

//设置光照阈值,默认40

api->set_illum_thr(20);

//设置角度阈值,默认15

//api->set_eulur_angle_thr(30, 30, 30);

qDebug() << TIMEMS << "init sdk ok";

}

void FaceBaiDuLocal::stop()

{

stopped = true;

}

bool FaceBaiDuLocal::getBusy()

{

return this->busy;

}

void FaceBaiDuLocal::setMaxCount(int maxCount)

{

if (maxCount <= 1000) {

this->maxCount = maxCount;

}

void FaceBaiDuLocal::setType(int type)

{

if (this->type != type) {

this->type = type;

this->flags.clear();

this->imgs.clear();

this->imgs2.clear();

}

void FaceBaiDuLocal::setPercent(int percent)

{

this->percent = percent;

}

void FaceBaiDuLocal::setDelayms(int delayms)

{

this->delayms = delayms;

}

void FaceBaiDuLocal::setFindFast(bool findFast)

{

this->findFast = findFast;

}

void FaceBaiDuLocal::setCountTime(bool countTime)

{

this->countTime = countTime;

}

void FaceBaiDuLocal::setBusy(bool busy)

{

this->busy = busy;

}

void FaceBaiDuLocal::setSDKPath(const QString &sdkPath)

{

this->sdkPath = sdkPath;

}

void FaceBaiDuLocal::setImgDir(const QString &imgDir)

{

this->imgDir = imgDir;

this->flags.clear();

this->flags.append("imgDir");

this->type = 3;

}

void FaceBaiDuLocal::setOneImg(const QString &flag, const QImage &oneImg)

{

setType(4);

//需要将图片重新拷贝一个,否则当原图像改变之后也会改变

this->oneImg = oneImg.copy();

this->flags.append(flag);

}

void FaceBaiDuLocal::append(const QString &flag, const QImage &img)

{

QMutexLocker lock(&mutex);

int count = flags.count();

if (count < maxCount) {

flags.append(flag);

imgs.append(img);

}

void FaceBaiDuLocal::append(const QString &flag, const QImage &img, const QImage &img2)

{

QMutexLocker lock(&mutex);

int count = flags.count();

if (count < maxCount) {

flags.append(flag);

imgs.append(img);

imgs2.append(img2);

}

void FaceBaiDuLocal::getFaceFeatures(const QString &imgDir)

{

imgNames.clear();

features.clear();

//载入指定目录图像处理特征

QDir imagePath(imgDir);

QStringList filter;

filter << "*.jpg" << "*.bmp" << "*.png" << "*.jpeg" << "*.gif";

imgNames.append(imagePath.entryList(filter));

qDebug() << TIMEMS << "getFaceFeatures" << imgNames;

//从目录下读取同名的txt文件(存储的特征)

//如果存在则从文件读取特征,如果不存在则转码解析出特征

//转码完成后将得到的特征存储到同名txt文件

int count = imgNames.count();

for (int i = 0; i < count; i++) {

QList feature;

int msec;

QString imgName = imgNames.at(i);

QStringList list = imgName.split(".");

QString txtName = imgDir + "/" + list.at(0) + ".txt";

QFile file(txtName);

if (file.exists()) {

if (file.open(QFile::ReadOnly)) {

QString data = file.readAll();

file.close();

qDebug() << TIMEMS << "readFaceFeature" << txtName;

QStringList list = data.split(",");

foreach (QString str, list) {

if (!str.isEmpty()) {

feature.append(str.toFloat());

}

} else {

QImage img(imgDir + "/" + imgName);

bool ok = getFaceFeature(imgName, img, feature, msec);

if (ok) {

emit receiveFaceFeature(imgName, feature, msec);

if (file.open(QFile::WriteOnly)) {

QStringList list;

foreach (float fea, feature) {

list.append(QString::number(fea));

}

qDebug() << TIMEMS << "writeFaceFeature" << txtName;

file.write(list.join(",").toLatin1());

file.close();

}

features.append(feature);

msleep(1);

}

qDebug() << TIMEMS << "getFaceFeatures finsh";

emit receiveFaceFeatureFinsh();

}

bool FaceBaiDuLocal::getFaceRect(const QString &flag, const QImage &img, QRect &rect, int &msec)

{

//qDebug() << TIMEMS << flag << "getFaceRect";

QTime time;

if (countTime) {

time.start();

}

faces->clear();

QByteArray imageData = getImageData(img);

int result = api->track_max_face(faces, imageData.constData(), 1);

if (result == 1) {

TrackFaceInfo info = faces->at(0);

FaceInfo ibox = info.box;

float width = ibox.mWidth;

float x = ibox.mCenter_x;

float y = ibox.mCenter_y;

rect = QRect(x - width / 2, y - width / 2, width, width);

if (countTime) {

msec = time.elapsed() - delayms;

} else {

msec = delayms;

}

msec = msec < 0 ? 0 : msec;

return true;

} else {

return false;

}

return false;

}

bool FaceBaiDuLocal::getFaceLive(const QString &flag, const QImage &img, float &result, int &msec)

{

//qDebug() << TIMEMS << flag << "getFaceLive";

QTime time;

if (countTime) {

time.start();

}

result = 0;

QByteArray imageData = getImageData(img);

std::string value = api->rgb_liveness_check(imageData.constData(), 1);

QString data = value.c_str();

data = data.replace("\t", "");

data = data.replace("\"", "");

data = data.replace(" ", "");

int index = -1;

QStringList list = data.split("\n");

foreach (QString str, list) {

index = str.indexOf("score:");

if (index >= 0) {

result = str.mid(6, 4).toFloat();

break;

}

if (index >= 0) {

if (countTime) {

msec = time.elapsed() - delayms;

} else {

msec = delayms;

}

msec = msec < 0 ? 0 : msec;

return true;

} else {

return false;

}

return false;

}

bool FaceBaiDuLocal::getFaceFeature(const QString &flag, const QImage &img, QList &feature, int &msec)

{

//qDebug() << TIMEMS << flag << "getFaceFeature" << img.width() << img.height() << img.size();

QTime time;

if (countTime) {

time.start();

}

const float *fea = nullptr;

QByteArray imageData = getImageData(img);

int result = api->get_face_feature(imageData.constData(), 1, fea);

if (result == 512) {

feature.clear();

for (int i = 0; i < 512; i++) {

feature.append(fea[i]);

}

if (countTime) {

msec = time.elapsed() - delayms;

} else {

msec = delayms;

}

msec = msec < 0 ? 0 : msec;

return true;

} else {

return false;

}

return false;

}

float FaceBaiDuLocal::getFaceCompare(const QString &flag, const QList &feature1, const QList &feature2)

{

//qDebug() << TIMEMS << flag << "getFaceCompareXXX";

std::vector fea1, fea2;

for (int i = 0; i < 512; i++) {

fea1.push_back(feature1.at(i));

fea2.push_back(feature2.at(i));

}

float result = api->compare_feature(fea1, fea2);

//过滤非法的值

result = result > 100 ? 0 : result;

return result;

}

bool FaceBaiDuLocal::getFaceCompare(const QString &flag, const QImage &img1, const QImage &img2, float &result, int &msec)

{

//qDebug() << TIMEMS << flag << "getFaceCompare";

result = 0;

bool ok1, ok2;

QList feature1, feature2;

int msec1, msec2;

QString flag1, flag2;

if (flag.contains("|")) {

QStringList list = flag.split("|");

flag1 = list.at(0);

flag2 = list.at(1);

} else {

flag1 = flag;

flag2 = flag;

}

QTime time;

if (countTime) {

time.start();

}

ok1 = getFaceFeature(flag1, img1, feature1, msec1);

if (ok1) {

emit receiveFaceFeature(flag1, feature1, msec1);

}

ok2 = getFaceFeature(flag2, img2, feature2, msec2);

if (ok2) {

emit receiveFaceFeature(flag2, feature2, msec2);

}

if (ok1 && ok2) {

result = getFaceCompare(flag, feature1, feature2);

if (countTime) {

msec = time.elapsed() - delayms;

} else {

msec = delayms;

}

msec = msec < 0 ? 0 : msec;

return true;

} else {

return false;

}

return false;

}

void FaceBaiDuLocal::getFaceOne(const QString &flag, const QImage &img, QString &targetName, float &result)

{

QList feature;

int msec;

bool ok = getFaceFeature(flag, img, feature, msec);

if (ok) {

emit receiveFaceFeature(flag, feature, msec);

getFaceOne(flag, feature, targetName, result);

}

void FaceBaiDuLocal::getFaceOne(const QString &flag, const QList &feature, QString &targetName, float &result)

{

//用当前图片的特征与特征数据库比对

result = 0;

int count = imgNames.count();

for (int i = 0; i < count; i++) {

QString imgName = imgNames.at(i);

float currentResult = getFaceCompare(flag, feature, features.at(i));

//qDebug() << TIMEMS << "getFaceOne" << imgName << currentResult;

if (currentResult > result) {

result = currentResult;

targetName = imgName;

}

qDebug() << TIMEMS << "getFaceOne result" << targetName << result;

}

void FaceBaiDuLocal::appendFace(const QString &flag, const QImage &img, const QString &txtFile)

{

QList feature;

int msec;

QImage image = img;

bool ok = getFaceFeature(flag, image, feature, msec);

msleep(100);

qDebug() << TIMEMS << "getFaceFeature result" << ok << "appendFace" << txtFile;

if (ok) {

emit receiveFaceFeature(flag, feature, msec);

//保存txt文件

QFile file(txtFile);

if (file.open(QFile::WriteOnly)) {

QStringList list;

foreach (float fea, feature) {

list.append(QString::number(fea));

}

file.write(list.join(",").toLatin1());

file.close();

}

//保存图片文件

QString imgName = txtFile;

imgName = imgName.replace("txt", "jpg");

image.save(imgName, "jpg");

imgNames.append(QFileInfo(imgName).fileName());

features.append(feature);

}

void FaceBaiDuLocal::deleteFace(const QString &flag)

{

//从图片名称中找到标识符

int index = imgNames.indexOf(flag);

if (index >= 0) {

imgNames.removeAt(index);

features.removeAt(index);

//删除图片文件

QString imgFileName = QString("%1/face/%2.jpg").arg(qApp->applicationDirPath()).arg(flag);

QFile imgFile(imgFileName);

imgFile.remove();

qDebug() << TIMEMS << "delete faceImage" << imgFileName;

//删除特征文件

QString txtFileName = QString("%1/face/%2.txt").arg(qApp->applicationDirPath()).arg(flag);

QFile txtFile(txtFileName);

txtFile.remove();

qDebug() << TIMEMS << "delete faceTxt" << txtFileName;

}

Qt编写百度离线版人脸识别+比对+活体检测

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