Java基于虹软实现人脸识别、人脸比对、活性检测等
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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;
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);
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);
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);
}
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<LivenessInfo> livenessInfoList = new ArrayList<>();
faceEngine.getLiveness(livenessInfoList);
LOGGER.info("RGB活体：{}", 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活体检测
List<IrLivenessInfo> irLivenessInfo = new ArrayList<>();
faceEngine.getLivenessIr(irLivenessInfo);
LOGGER.info("IR活体：{}", irLivenessInfo.get(0).getLiveness());
}
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());
}
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());
}
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;
}
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;
}
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;
}
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;
}
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");
}
}
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;
}
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;
}
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
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