Java基于虹软实现人脸识别、人脸比对、活性检测等

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

Java基于虹软实现人脸识别、人脸比对、活性检测等_第1张图片

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

Java基于虹软实现人脸识别、人脸比对、活性检测等_第2张图片

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


    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(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)

Java基于虹软实现人脸识别、人脸比对、活性检测等_第3张图片

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

 到此这篇关于Java基于虹软实现人脸识别、人脸比对、活性检测等的文章就介绍到这了,更多相关Java 人脸识别、人脸比对、活性检测内容请搜索脚本之家以前的文章或继续浏览下面的相关文章希望大家以后多多支持脚本之家!

你可能感兴趣的:(Java基于虹软实现人脸识别、人脸比对、活性检测等)