Java基于虹软实现人脸识别、人脸比对、活性检测等-APISpace

Java基于虹软实现人脸识别、人脸比对、活性检测等

目录虹软一、注册虹软开发者平台二、开始使用SDK

虹软

免费，高级版本试用支持在线、离线有 java SDK，C++ SDK

一、注册虹软开发者平台

点击注册

注册完成后可在“我的应用”中新建应用，获得 APP_ID 和 SDK_Key，请记住这两个信息，后续 SDK 中会用到。

接下来下载SDK就行了。

二、开始使用SDK

SDK包结构在下载的sdk包中，包结构大概是这样

在项目中引入 SDK 包

arcsoft

arcsoft-sdk-face

3.0.0.0

system

${project.basedir}/lib/arcsoft-sdk-face-3.0.0.0.jar

简单的集成

package com.study;

import com.arcsoft.face.*;

import com.arcsoft.face.enums.*;

import com.arcsoft.face.toolkit.ImageFactory;

import com.arcsoft.face.toolkit.ImageInfo;

import com.arcsoft.face.toolkit.ImageInfoEx;

import com.study.exception.CustomException;

import com.study.vo.FaceDetailInfo;

import org.slf4j.Logger;

import org.slf4j.LoggerFactory;

import java.io.File;

import java.net.URL;

import java.util.ArrayList;

import java.util.List;

/**

* 集成虹软-人脸识别测试

* @author ouyangrongtao

* @since 2022-02-20 19:12

public class FaceEngineMain {

// 从上述的开发者平台-“我的应用” 获取

private static final String APP_ID = "";

private static final String SDK_KEY = "";

// sdk安装路径

private static final String ARC_FACE_PATH = "arcsoft";

private static final Logger LOGGER = LoggerFactory.getLogger(FaceEngineMain.class);

public static void main(String[] args) {

FaceEngineMain faceEngineMain = new FaceEngineMain();

// 激活

FaceEngine faceEngine = faceEngineMain.active();

// 识别功能配置

FunctionConfiguration functionConfiguration = faceEngineMain.getFunctionConfiguration();

// 初始化识别引擎

faceEngineMain.initEngine(faceEngine, functionConfiguration);

ImageInfo imageInfo = ImageFactory.getRGBData(new File("d:\\aaa.jpeg"));

ImageInfo imageInfo2 = ImageFactory.getRGBData(new File("d:\\bbb.jpeg"));

// 人脸检测&特征提取1

List faceDetailInfoList1 = faceEngineMain.detectFaces(faceEngine, imageInfo);

// 人脸检测&特征提取2

List faceDetailInfoList2 = faceEngineMain.detectFaces(faceEngine, imageInfo2);

* 特征比对

* 用于证件照或生活照与证件照之间的特征比对，推荐阈值0.82

* 用于生活照之间的特征比对，推荐阈值0.80

FaceSimilar faceSimilar = faceEngineMain.compareFaceFeature(faceEngine,

faceDetailInfoList1.get(0).getFaceFeature(), faceDetailInfoList2.get(0).getFaceFeature());

LOGGER.info("相似度：{}", faceSimilar.getScore());

// 获取人脸属性

faceEngineMain.getFaceAttributes(faceEngine, imageInfo);

ImageInfo imageInfo3 = ImageFactory.getRGBData(new File("d:\\ccc.jpg"));

ImageInfo imageInfo4 = ImageFactory.getRGBData(new File("d:\\ddd.jpg"));

// 人脸检测&特征提取3

List faceDetailInfoList3 = faceEngineMain.detectFacesEx(faceEngine, imageInfo3, DetectModel.ASF_DETECT_MODEL_RGB);

// 人脸检测&特征提取4

List faceDetailInfoList4 = faceEngineMain.detectFacesEx(faceEngine, imageInfo4, DetectModel.ASF_DETECT_MODEL_RGB);

// 特征比对

FaceSimilar faceSimilar2 = faceEngineMain.compareFaceFeature(faceEngine,

faceDetailInfoList3.get(0).getFaceFeature(), faceDetailInfoList4.get(0).getFaceFeature(), CompareModel.LIFE_PHOTO);

* 特征比对

* 用于证件照或生活照与证件照之间的特征比对，推荐阈值0.82

* 用于生活照之间的特征比对，推荐阈值0.80

LOGGER.info("相似度：{}", faceSimilar2.getScore());

// 获取人脸属性

faceEngineMain.getFaceAttributesEx(faceEngine, imageInfo);

ImageInfo imageInfoGray = ImageFactory.getGrayData(new File("d:\\ddd.jpg"));

// 活体检测 RGB & IR

faceEngineMain.getLiveness(faceEngine, imageInfo, imageInfoGray);

// 卸载

faceEngineMain.unInit(faceEngine);

}

/**

* 活体检测

* @param faceEngine 引擎

* @param imageInfoRGB RGB图片信息

* @param imageInfoGray Gray图片信息

private void getLiveness(FaceEngine faceEngine, ImageInfo imageInfoRGB, ImageInfo imageInfoGray) {

// 人脸检测

List faceInfoList = new ArrayList<>();

faceEngine.detectFaces(imageInfoRGB.getImageData(),

imageInfoRGB.getWidth(), imageInfoRGB.getHeight(), imageInfoRGB.getImageFormat(), faceInfoList);

// 设置活体测试阀值

faceEngine.setLivenessParam(0.5f, 0.7f);

// RGB人脸检测

FunctionConfiguration configuration = new FunctionConfiguration();

configuration.setSupportLiveness(true);

faceEngine.process(imageInfoRGB.getImageData(),

imageInfoRGB.getWidth(), imageInfoRGB.getHeight(), imageInfoRGB.getImageFormat(), faceInfoList, configuration);

// RGB活体检测

List livenessInfoList = new ArrayList<>();

faceEngine.getLiveness(livenessInfoList);

LOGGER.info("RGB活体：{}", livenessInfoList.get(0).getLiveness());

// IR属性处理

List faceInfoListGray = new ArrayList<>();

// IR人脸检查

faceEngine.detectFaces(imageInfoGray.getImageData(),

imageInfoGray.getWidth(), imageInfoGray.getHeight(), imageInfoGray.getImageFormat(), faceInfoListGray);

configuration = new FunctionConfiguration();

configuration.setSupportIRLiveness(true);

faceEngine.processIr(imageInfoGray.getImageData(),

imageInfoGray.getWidth(), imageInfoGray.getHeight(), imageInfoGray.getImageFormat(), faceInfoListGray, configuration);

//IR活体检测

List irLivenessInfo = new ArrayList<>();

faceEngine.getLivenessIr(irLivenessInfo);

LOGGER.info("IR活体：{}", irLivenessInfo.get(0).getLiveness());

}

/**

* 人脸属性检测

* @param faceEngine 引擎

* @param imageInfo 图片信息

private void getFaceAttributesEx(FaceEngine faceEngine, ImageInfo imageInfo) {

// 人脸检测

List faceInfoList = new ArrayList<>();

faceEngine.detectFaces(imageInfo.getImageData(),

imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList);

ImageInfoEx imageInfoEx = new ImageInfoEx();

imageInfoEx.setHeight(imageInfo.getHeight());

imageInfoEx.setWidth(imageInfo.getWidth());

imageInfoEx.setImageFormat(imageInfo.getImageFormat());

imageInfoEx.setImageDataPlanes(new byte[][]{imageInfo.getImageData()});

imageInfoEx.setImageStrides(new int[]{imageInfo.getWidth() * 3});

//人脸属性检测

FunctionConfiguration configuration = new FunctionConfiguration();

configuration.setSupportGender(true);

configuration.setSupportAge(true);

configuration.setSupportFace3dAngle(true);

faceEngine.process(imageInfoEx, faceInfoList, configuration);

//性别检测

List genderInfoList = new ArrayList<>();

faceEngine.getGender(genderInfoList);

LOGGER.info("性别：{}", genderInfoList.get(0).getGender());

//年龄检测

List ageInfoList = new ArrayList<>();

faceEngine.getAge(ageInfoList);

LOGGER.info("年龄：{}", ageInfoList.get(0).getAge());

//3D信息检测

List face3DAngleList = new ArrayList<>();

faceEngine.getFace3DAngle(face3DAngleList);

Face3DAngle face3DAngle = face3DAngleList.get(0);

LOGGER.info("3D角度：{}", face3DAngle.getPitch() + "," + face3DAngle.getRoll() + "," + face3DAngle.getYaw());

}

/**

* 人脸属性检测

* @param faceEngine 引擎

* @param imageInfo 图片信息

private void getFaceAttributes(FaceEngine faceEngine, ImageInfo imageInfo) {

//人脸属性检测

FunctionConfiguration configuration = new FunctionConfiguration();

configuration.setSupportGender(true);

configuration.setSupportAge(true);

configuration.setSupportFace3dAngle(true);

// 人脸检测

List faceInfoList = new ArrayList<>();

faceEngine.detectFaces(imageInfo.getImageData(),

imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList);

faceEngine.process(imageInfo.getImageData(),

imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList, configuration);

//性别检测

List genderInfoList = new ArrayList<>();

faceEngine.getGender(genderInfoList);

LOGGER.info("性别：{}", genderInfoList.get(0).getGender());

//年龄检测

List ageInfoList = new ArrayList<>();

faceEngine.getAge(ageInfoList);

LOGGER.info("年龄：{}", ageInfoList.get(0).getAge());

//3D信息检测

List face3DAngleList = new ArrayList<>();

faceEngine.getFace3DAngle(face3DAngleList);

Face3DAngle face3DAngle = face3DAngleList.get(0);

LOGGER.info("3D角度：{}", face3DAngle.getPitch() + "," + face3DAngle.getRoll() + "," + face3DAngle.getYaw());

}

/**

* 特征比对-可设置比对模型

* @param faceEngine 引擎

* @param sourceFaceFeature 原特征值

* @param targetFaceFeature 比对的特征值

* @param compareModel 比对模型

* @return 比对结果

private FaceSimilar compareFaceFeature(FaceEngine faceEngine, FaceFeature sourceFaceFeature, FaceFeature targetFaceFeature, CompareModel compareModel) {

// 特征比对

FaceSimilar faceSimilar = new FaceSimilar();

int errorCode = faceEngine.compareFaceFeature(targetFaceFeature, sourceFaceFeature, compareModel, faceSimilar);

if (ErrorInfo.MOK.getValue() != errorCode) {

LOGGER.error("人脸特征比对失败");

}

return faceSimilar;

}

/**

* 特征比对

* @param faceEngine 引擎

* @param sourceFaceFeature 原特征值

* @param targetFaceFeature 比对的特征值

* @return 比对结果

private FaceSimilar compareFaceFeature(FaceEngine faceEngine, FaceFeature sourceFaceFeature, FaceFeature targetFaceFeature) {

// 特征比对

FaceSimilar faceSimilar = new FaceSimilar();

int errorCode = faceEngine.compareFaceFeature(targetFaceFeature, sourceFaceFeature, faceSimilar);

if (ErrorInfo.MOK.getValue() != errorCode) {

LOGGER.error("人脸特征比对失败");

}

return faceSimilar;

}

/**

* 人脸检测&特征提取--可设置检测模式

* @param faceEngine 引擎

* @param imageInfo 图片信息

* @param detectModel 检测模式

* @return 人脸信息

private List detectFacesEx(FaceEngine faceEngine, ImageInfo imageInfo, DetectModel detectModel) {

ImageInfoEx imageInfoEx = new ImageInfoEx();

imageInfoEx.setHeight(imageInfo.getHeight());

imageInfoEx.setWidth(imageInfo.getWidth());

imageInfoEx.setImageFormat(imageInfo.getImageFormat());

imageInfoEx.setImageDataPlanes(new byte[][]{imageInfo.getImageData()});

imageInfoEx.setImageStrides(new int[]{imageInfo.getWidth() * 3});

List faceInfoList = new ArrayList<>();

faceEngine.detectFaces(imageInfoEx, detectModel, faceInfoList);

List faceDetailInfoList = new ArrayList<>(faceInfoList.size());

for (FaceInfo faceInfo : faceInfoList) {

LOGGER.info("imageInfoEx 人脸检测结果: {}", faceInfo);

FaceFeature faceFeature = new FaceFeature();

faceEngine.extractFaceFeature(imageInfoEx, faceInfo, faceFeature);

LOGGER.info("imageInfoEx 特征值大小：{}", faceFeature.getFeatureData().length);

FaceDetailInfo faceDetailInfo = new FaceDetailInfo(faceInfo, faceFeature);

faceDetailInfoList.add(faceDetailInfo);

}

return faceDetailInfoList;

}

/**

* 人脸检测&特征提取

* @param faceEngine 引擎

* @param imageInfo 图片信息

* @return 人脸信息

private List detectFaces(FaceEngine faceEngine, ImageInfo imageInfo) {

// 人脸检测

List faceInfoList = new ArrayList<>();

faceEngine.detectFaces(imageInfo.getImageData(),

imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList);

List faceDetailInfoList = new ArrayList<>(faceInfoList.size());

// 特征提取

for (FaceInfo faceInfo : faceInfoList) {

LOGGER.info("人脸检测结果: {}", faceInfo);

FaceFeature faceFeature = new FaceFeature();

faceEngine.extractFaceFeature(imageInfo.getImageData(),

imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfo, faceFeature);

LOGGER.info("特征值大小：{}", faceFeature.getFeatureData().length);

FaceDetailInfo faceDetailInfo = new FaceDetailInfo(faceInfo, faceFeature);

faceDetailInfoList.add(faceDetailInfo);

}

return faceDetailInfoList;

}

/**

* 初始化识别引擎

* @param faceEngine 人脸识别引擎

* @param functionConfiguration 功能配置

private void initEngine(FaceEngine faceEngine, FunctionConfiguration functionConfiguration) {

// 引擎配置

EngineConfiguration engineConfiguration = new EngineConfiguration();

engineConfiguration.setDetectMode(DetectMode.ASF_DETECT_MODE_IMAGE);

engineConfiguration.setDetectFaceOrientPriority(DetectOrient.ASF_OP_ALL_OUT);

engineConfiguration.setDetectFaceMaxNum(10);

engineConfiguration.setDetectFaceScaleVal(16);

engineConfiguration.setFunctionConfiguration(functionConfiguration);

// 初始化引擎

int errorCode = faceEngine.init(engineConfiguration);

if (errorCode != ErrorInfo.MOK.getValue()) {

throw new CustomException("初始化引擎失败");

}

/**

* 识别功能配置

private FunctionConfiguration getFunctionConfiguration() {

// 功能配置

FunctionConfiguration functionConfiguration = new FunctionConfiguration();

functionConfiguration.setSupportAge(true);

functionConfiguration.setSupportFace3dAngle(true);

functionConfiguration.setSupportFaceDetect(true);

functionConfiguration.setSupportFaceRecognition(true);

functionConfiguration.setSupportGender(true);

functionConfiguration.setSupportLiveness(true);

functionConfiguration.setSupportIRLiveness(true);

return functionConfiguration;

}

/**

* 激活初次使用SDK时需要对SDK先进行激活，激活后无需重复调用；调用此接口时必须为联网状态，激活成功后即可离线使用；

* @return FaceEngine 对象

private FaceEngine active() {

URL resource = ClassLoader.getSystemResource(ARC_FACE_PATH);

LOGGER.info("软件安装目录：{}", resource);

FaceEngine faceEngine = new FaceEngine(resource.getPath());

ActiveFileInfo activeFileInfo = new ActiveFileInfo();

int errorCode = faceEngine.getActiveFileInfo(activeFileInfo);

if (errorCode != ErrorInfo.MOK.getValue()

&& errorCode != ErrorInfo.MERR_ASF_ALREADY_ACTIVATED.getValue()) {

LOGGER.info("获取激活文件信息失败");

}

// 首次激活

errorCode = faceEngine.activeOnline(APPhttp://_ID, SDK_KEY);

if (errorCode != ErrorInfo.MOK.getValue()

&& errorCode != ErrorInfo.MERR_ASF_ALREADY_ACTIVATED.getValue()) {

throw new CustomException("引擎激活失败");

}

LOGGER.info("激活信息：{}", activeFileInfo);

return faceEngine;

}

/**

* 卸载引擎

* @param faceEngine 人脸识别引擎

private void unInit(FaceEngine faceEngine) {

faceEngine.unInit();

}

性能信息（参考官方文档）

阀值设置推荐（参考官方文档）

1. 活体取值范围为[0~1]，推荐阈值如下，高于此阈值的即可判断为活体。

- RGB 活体：0.5

- IR 活体：0.7

2. 人脸比对取值范围为[0~1]，推荐阈值如下，高于此阈值的即可判断为同一人。

- 用于生活照之间的特征比对，推荐阈值0.80

- 用于证件照或生活照与证件照之间的特征比对，推荐阈值0.82

产品文档 https://ai.arcsoft.com.cn/manual/docs#/89

活体检测技术：防止身份盗用，提升认证系统的安全性

501 2022-10-29

Java基于虹软实现人脸识别、人脸比对、活性检测等

开发者常用的热门免费 API 分享

活体检测技术：防止身份盗用，提升认证系统的安全性

动态活体检测有什么作用？

推荐文章

api接口有哪几种分类及功能

什么是API接口?API接口简单介绍

短信API接口概述，短信API接口的优势

7款快递物流的物流查询API工具，物流快递查询API接口怎么对接？

企业四要素: 了解企业经营成功的关键

什么是语音验证码?,语音验证码平台有哪些

全国工商查询系统怎么查企业名录

哪些平台提供实名认证的接口？

PHP如何调用API接口?

如何使用百度天气预报API接口?

最近发表

热评文章

数据接口api（数据接口API开发平台）

数据开放接口api（数据服务api开发）

Python爬虫教程：爬取酷狗音乐（python爬取

hbuilder怎么更改字体大小和颜色

直播平台api接口 - 构建卓越的直播平台

实时股票数据api接口（股票实时行情api接口）