Java基于虹软实现人脸识别、人脸比对、活性检测等
作者:lytao123 时间:2023-02-18 15:29:09
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
|—demo
| |—ArcFaceDemo Demo工程
|—doc
| |—ARCSOFT_ARC_FACE_DEVELOPER’S_GUIDE.PDF 开发说明文档
|—inc
| |—amcomdef.h 平台文件
| |—asvloffscreen.h 平台文件
| |—arcsoft_face_sdk.h 接口文件
| |—merror.h 错误码文件
|—lib
|—|---Win32/x64
| |—|---libarcsoft_face.dll 算法库
| |—|---libarcsoft_face_engine.dll 引擎库
| |—|---libarcsoft_face_engine.lib 引擎库
|—samplecode
| |—samplecode.cpp 示例代码
|—releasenotes.txt 说明文件
在项目中引入 SDK 包
<dependency>
<groupId>arcsoft</groupId>
<artifactId>arcsoft-sdk-face</artifactId>
<version>3.0.0.0</version>
<scope>system</scope>
<systemPath>${project.basedir}/lib/arcsoft-sdk-face-3.0.0.0.jar</systemPath>
</dependency>
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<FaceDetailInfo> faceDetailInfoList1 = faceEngineMain.detectFaces(faceEngine, imageInfo);
// 人脸检测&特征提取2
List<FaceDetailInfo> 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<FaceDetailInfo> faceDetailInfoList3 = faceEngineMain.detectFacesEx(faceEngine, imageInfo3, DetectModel.ASF_DETECT_MODEL_RGB);
// 人脸检测&特征提取4
List<FaceDetailInfo> 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"));
// * 检测 RGB & IR
faceEngineMain.getLiveness(faceEngine, imageInfo, imageInfoGray);
// 卸载
faceEngineMain.unInit(faceEngine);
}
/**
* * 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<FaceInfo> faceInfoList = new ArrayList<>();
faceEngine.detectFaces(imageInfoRGB.getImageData(),
imageInfoRGB.getWidth(), imageInfoRGB.getHeight(), imageInfoRGB.getImageFormat(), faceInfoList);
// 设置 * 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 * 检测
List<LivenessInfo> livenessInfoList = new ArrayList<>();
faceEngine.getLiveness(livenessInfoList);
LOGGER.info("RGB * :{}", livenessInfoList.get(0).getLiveness());
// IR属性处理
List<FaceInfo> 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 * 检测
List<IrLivenessInfo> irLivenessInfo = new ArrayList<>();
faceEngine.getLivenessIr(irLivenessInfo);
LOGGER.info("IR * :{}", 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<FaceInfo> 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<GenderInfo> genderInfoList = new ArrayList<>();
faceEngine.getGender(genderInfoList);
LOGGER.info("性别:{}", genderInfoList.get(0).getGender());
//年龄检测
List<AgeInfo> ageInfoList = new ArrayList<>();
faceEngine.getAge(ageInfoList);
LOGGER.info("年龄:{}", ageInfoList.get(0).getAge());
//3D信息检测
List<Face3DAngle> 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<FaceInfo> 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<GenderInfo> genderInfoList = new ArrayList<>();
faceEngine.getGender(genderInfoList);
LOGGER.info("性别:{}", genderInfoList.get(0).getGender());
//年龄检测
List<AgeInfo> ageInfoList = new ArrayList<>();
faceEngine.getAge(ageInfoList);
LOGGER.info("年龄:{}", ageInfoList.get(0).getAge());
//3D信息检测
List<Face3DAngle> 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<FaceDetailInfo> 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<FaceInfo> faceInfoList = new ArrayList<>();
faceEngine.detectFaces(imageInfoEx, detectModel, faceInfoList);
List<FaceDetailInfo> 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<FaceDetailInfo> detectFaces(FaceEngine faceEngine, ImageInfo imageInfo) {
// 人脸检测
List<FaceInfo> faceInfoList = new ArrayList<>();
faceEngine.detectFaces(imageInfo.getImageData(),
imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList);
List<FaceDetailInfo> 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(APP_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. * 取值范围为[0~1],推荐阈值如下,高于此阈值的即可判断为 * 。
- RGB * :0.5
- IR * :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
来源:https://blog.csdn.net/qq_24598601/article/details/123038394
![](/images/zang.png)
![](/images/jiucuo.png)
猜你喜欢
深入学习C语言中的函数指针和左右法则
Android Activity View加载与绘制流程深入刨析源码
Spring Boot Admin实践详解
Android 开发之Dialog,Toast,Snackbar提醒
![](https://img.aspxhome.com/file/2023/9/103889_0s.png)
JavaGUI常用三种布局使用介绍
![](https://img.aspxhome.com/file/2023/6/73036_0s.png)
Spring实战之使用ClassPathResource加载xml资源示例
Java中不可或缺的关键字volatile详析
C#微信开发第一章
![](https://img.aspxhome.com/file/2023/8/102238_0s.jpg)
Android短信接收监听、自动回复短信操作例子
ImageView 实现Android colorPikcer 选择器的示例代码
![](https://img.aspxhome.com/file/2023/7/92627_0s.gif)
深度理解Java访问修饰符
![](https://img.aspxhome.com/file/2023/8/76598_0s.png)
Java枚举类使用Lombok方式
SpringBoot整合腾讯云COS对象存储实现文件上传的示例代码
![](https://img.aspxhome.com/file/2023/0/113520_0s.jpg)
详解Kotlin中的面向对象(一)
DoytoQuery中关于N+1查询问题解决方案详解
Android自定义ListView实现下拉刷新上拉加载更多
![](https://img.aspxhome.com/file/2023/0/125550_0s.gif)
实例讲解Android应用开发中TabHost的使用要点
![](https://img.aspxhome.com/file/2023/1/139251_0s.png)
Java中多线程下载图片并压缩能提高效率吗
![](https://img.aspxhome.com/file/2023/6/77076_0s.png)
使用idea解决maven依赖冲突的问题
![](https://img.aspxhome.com/file/2023/0/71160_0s.png)
Android源码 在Ubuntu上下载,编译和安装
![](https://img.aspxhome.com/file/2023/7/139057_0s.jpg)