人脸识别尝试

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人脸识别尝试

参考材料

[(181条消息) Java实现人脸识别(各项目结构都有案例说明)_高冷小伙的博客-CSDN博客_java实现人脸识别](https://blog.csdn.net/alpha_xia/article/details/121755220?ops_request_misc=&request_id=&biz_id=102&utm_term=java 人脸识别&utm_medium=distribute.pc_search_result.none-task-blog-2allsobaiduweb~default-0-121755220.nonecase&spm=1018.2226.3001.4187)

下次SDK

人脸识别核心部分是蚕蛹蓝虹公司免费的SDK

下载地址：

开发者中心 (arcsoft.com.cn)

测试阶段

官方给的程序

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package samplecode;

import com.arcsoft.face.*;
import com.arcsoft.face.enums.*;
import com.arcsoft.face.toolkit.ImageInfo;

import java.io.File;
import java.util.ArrayList;
import java.util.List;

import com.arcsoft.face.toolkit.ImageInfoEx;

import static com.arcsoft.face.toolkit.ImageFactory.getGrayData;
import static com.arcsoft.face.toolkit.ImageFactory.getRGBData;


public class FaceEngineTest {


    public static void main(String[] args) {

        String appId = "7K7KG9zfBVrtyhgdfdfg";
        String sdkKey = "AuyJsdgsdfhsf"


        FaceEngine faceEngine = new FaceEngine("D:\\AreFace\\libs\\WIN64");
        //激活引擎，只需要一次
        int errorCode = faceEngine.activeOnline(appId, sdkKey);

        if (errorCode != ErrorInfo.MOK.getValue() && errorCode != ErrorInfo.MERR_ASF_ALREADY_ACTIVATED.getValue()) {
            System.out.println("引擎激活失败");
        }


        ActiveFileInfo activeFileInfo=new ActiveFileInfo();
        errorCode = faceEngine.getActiveFileInfo(activeFileInfo);
        if (errorCode != ErrorInfo.MOK.getValue() && errorCode != ErrorInfo.MERR_ASF_ALREADY_ACTIVATED.getValue()) {
            System.out.println("获取激活文件信息失败");
        }

        //引擎配置，保存默认即可
        EngineConfiguration engineConfiguration = new EngineConfiguration();
        engineConfiguration.setDetectMode(DetectMode.ASF_DETECT_MODE_IMAGE);
        engineConfiguration.setDetectFaceOrientPriority(DetectOrient.ASF_OP_ALL_OUT);
        engineConfiguration.setDetectFaceMaxNum(10);
        engineConfiguration.setDetectFaceScaleVal(16);
        //功能配置，可以设置面容识别时是否分析年龄、性别、3d等。
        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);
        engineConfiguration.setFunctionConfiguration(functionConfiguration);


        //初始化引擎
        errorCode = faceEngine.init(engineConfiguration);

        if (errorCode != ErrorInfo.MOK.getValue()) {
            System.out.println("初始化引擎失败");
        }


        //人脸检测
        ImageInfo imageInfo = getRGBData(new File("d:\\aaa.jpg"));
        List<FaceInfo> faceInfoList = new ArrayList<FaceInfo>();
        errorCode = faceEngine.detectFaces(imageInfo.getImageData(), imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList);
        System.out.println(faceInfoList);

        //特征提取
        FaceFeature faceFeature = new FaceFeature();
        errorCode = faceEngine.extractFaceFeature(imageInfo.getImageData(), imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList.get(0), faceFeature);
        System.out.println("特征值大小：" + faceFeature.getFeatureData().length);

        //人脸检测2
        ImageInfo imageInfo2 = getRGBData(new File("d:\\ccc.jpg"));
        List<FaceInfo> faceInfoList2 = new ArrayList<FaceInfo>();
        errorCode = faceEngine.detectFaces(imageInfo2.getImageData(), imageInfo2.getWidth(), imageInfo2.getHeight(),imageInfo.getImageFormat(), faceInfoList2);
        System.out.println(faceInfoList);

        //特征提取2
        FaceFeature faceFeature2 = new FaceFeature();
        errorCode = faceEngine.extractFaceFeature(imageInfo2.getImageData(), imageInfo2.getWidth(), imageInfo2.getHeight(), imageInfo.getImageFormat(), faceInfoList2.get(0), faceFeature2);
        System.out.println("特征值大小：" + faceFeature.getFeatureData().length);

        //特征比对
        FaceFeature targetFaceFeature = new FaceFeature();
        targetFaceFeature.setFeatureData(faceFeature.getFeatureData());
        FaceFeature sourceFaceFeature = new FaceFeature();
        sourceFaceFeature.setFeatureData(faceFeature2.getFeatureData());
        FaceSimilar faceSimilar = new FaceSimilar();

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

        System.out.println("相似度：" + faceSimilar.getScore());

        //设置活体测试
        errorCode = faceEngine.setLivenessParam(0.5f, 0.7f);
        //人脸属性检测，如果上面功能配置没有的话，这里就不可用
        FunctionConfiguration configuration = new FunctionConfiguration();
        configuration.setSupportAge(true);
        configuration.setSupportFace3dAngle(true);
        configuration.setSupportGender(true);
        configuration.setSupportLiveness(true);
        errorCode = faceEngine.process(imageInfo.getImageData(), imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList, configuration);


        //性别检测，如果上面功能配置没有的话，这里就不可用
        List<GenderInfo> genderInfoList = new ArrayList<GenderInfo>();
        errorCode = faceEngine.getGender(genderInfoList);
        System.out.println("性别：" + genderInfoList.get(0).getGender());

        //年龄检测，如果上面功能配置没有的话，这里就不可用
        List<AgeInfo> ageInfoList = new ArrayList<AgeInfo>();
        errorCode = faceEngine.getAge(ageInfoList);
        System.out.println("年龄：" + ageInfoList.get(0).getAge());

        //3D信息检测，如果上面功能配置没有的话，这里就不可用
        List<Face3DAngle> face3DAngleList = new ArrayList<Face3DAngle>();
        errorCode = faceEngine.getFace3DAngle(face3DAngleList);
        System.out.println("3D角度：" + face3DAngleList.get(0).getPitch() + "," + face3DAngleList.get(0).getRoll() + "," + face3DAngleList.get(0).getYaw());

        //活体检测，如果上面功能配置没有的话，这里就不可用
        List<LivenessInfo> livenessInfoList = new ArrayList<LivenessInfo>();
        errorCode = faceEngine.getLiveness(livenessInfoList);
        System.out.println("活体：" + livenessInfoList.get(0).getLiveness());


        //IR属性处理，如果上面功能配置没有的话，这里就不可用
        ImageInfo imageInfoGray = getGrayData(new File("d:\\IR_480p.jpg"));
        List<FaceInfo> faceInfoListGray = new ArrayList<FaceInfo>();
        errorCode = faceEngine.detectFaces(imageInfoGray.getImageData(), imageInfoGray.getWidth(), imageInfoGray.getHeight(), imageInfoGray.getImageFormat(), faceInfoListGray);

        FunctionConfiguration configuration2 = new FunctionConfiguration();
        configuration2.setSupportIRLiveness(true);
        errorCode = faceEngine.processIr(imageInfoGray.getImageData(), imageInfoGray.getWidth(), imageInfoGray.getHeight(), imageInfoGray.getImageFormat(), faceInfoListGray, configuration2);
        //IR活体检测，如果上面功能配置没有的话，这里就不可用
        List<IrLivenessInfo> irLivenessInfo = new ArrayList<IrLivenessInfo>();
        errorCode = faceEngine.getLivenessIr(irLivenessInfo);
        System.out.println("IR活体：" + irLivenessInfo.get(0).getLiveness());

        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> faceInfoList1 = new ArrayList<FaceInfo>();
        errorCode = faceEngine.detectFaces(imageInfoEx, DetectModel.ASF_DETECT_MODEL_RGB, faceInfoList1);

        FunctionConfiguration fun = new FunctionConfiguration();
        fun.setSupportAge(true);
        errorCode = faceEngine.process(imageInfoEx, faceInfoList1, functionConfiguration);
        List<AgeInfo> ageInfoList1 = new ArrayList<AgeInfo>();
        int age = faceEngine.getAge(ageInfoList1);
        System.out.println("年龄：" + ageInfoList1.get(0).getAge());

        FaceFeature feature = new FaceFeature();
        errorCode = faceEngine.extractFaceFeature(imageInfoEx, faceInfoList1.get(0), feature);


        //引擎卸载
        errorCode = faceEngine.unInit();

    }
}

注意 这里需要导包 吧需要的包导到maven里边

学习阶段

分析官方给的pdf，来分析又什么用法，学会阅读官方文档也是一种能力

使用步奏第一阶段 配置引擎

获得引擎

==代码中出现的数组都是乱码，具体值需要自己到官网拷贝==

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String appId = "7asdasfG3cxqKmpF1DwijXxJ73s75v7uZqxoT";
String sdkKey = "AuyJJasdqwafgadgBnD5wXzSEPtXs5C";


      FaceEngine faceEngine = new FaceEngine("D:\\AreFace\\libs\\WIN64");
      //激活引擎，只需要一次
      int errorCode = faceEngine.activeOnline(appId, sdkKey);

      if (errorCode != ErrorInfo.MOK.getValue() && errorCode != ErrorInfo.MERR_ASF_ALREADY_ACTIVATED.getValue()) {
          System.out.println("引擎激活失败");
      }

C:\Users\Lenovo\Desktop\人脸识别尝试\libs\WIN64该文件名是从官网拷贝下来的压缩包解压后 xx.dll文件所在的位置

image-20221025162958075

第二步 获得激活文件

激活文件是可以直接new 生成 没有对其的配置

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//创建激活文件
ActiveFileInfo activeFileInfo = new ActiveFileInfo();
errorCode = faceEngine.getActiveFileInfo(activeFileInfo);

//判断激活文件是否获取成功
if (errorCode != ErrorInfo.MOK.getValue() && errorCode != ErrorInfo.MERR_ASF_ALREADY_ACTIVATED.getValue()) {
    System.out.println("获取激活文件信息失败");
}

第三步 配置引擎

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//设置配置引擎对象
EngineConfiguration engineConfiguration = new EngineConfiguration();

//几个比较重要的配置设置

//检测模式设置
//这里因为我们是对图片进行人脸识别，因此这里我们使用一个IMAGE模式
engineConfiguration.setDetectMode(DetectMode.ASF_DETECT_MODE_IMAGE);

//可检测图片人脸方向设置
engineConfiguration.setDetectFaceOrientPriority(DetectOrient.ASF_OP_ALL_OUT);//这里我设置的是全方位角设置

具体功能 请参考文档 文档在下载下来的压缩包里有

第四步 配置引擎功能

引擎功能 即引擎能够干什么；

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//功能配置，可以设置面容识别时是否分析年龄、性别、3d等。
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);
       
engineConfiguration.setFunctionConfiguration(functionConfiguration);

第五步 初始化引擎

将配置好的引擎和引擎功能的对象都放到引擎里

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//初始化引擎 (将配置设置到引擎中)
     errorCode = faceEngine.init(engineConfiguration);

     if (errorCode!=ErrorInfo.MOK.getValue()){
         System.out.println("引擎初始化失败");
     }

引擎准备阶段就到此结束，下边就是引擎能进行的操作了

再次强调

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EngineConfiguration engineConfiguration = new EngineConfiguration();
engineConfiguration.setDetectMode(DetectMode.ASF_DETECT_MODE_IMAGE);
engineConfiguration.setDetectFaceOrientPriority(DetectOrient.ASF_OP_ALL_OUT);
engineConfiguration.setDetectFaceMaxNum(10);
engineConfiguration.setDetectFaceScaleVal(16);

配置引擎时，这里个配置比较重要

从上到下分别是

  • 引擎识别模式，是识别静态图片还是视频流
  • 引擎可以识别的头像角度，这里设置的是都可以识别
  • 引擎识别来拿的最大数量
  • 以及引擎识别等级

使用步奏第二部分 使用引擎

准备图像

人脸特征获取

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//准备文件
      File file = new File("D:\\aaa.jpg");

      //这里使用detectFaces方法来对图片进行分析 detectFaces需要很多参数 这里使用getRGBData方法来获得这些参数
      ImageInfo imageInfo = getRGBData(file);
      //分析得到的数据保存在faceInfoList列表中
      List<FaceInfo> faceInfoList = new ArrayList<FaceInfo>();
      faceEngine.detectFaces(imageInfo.getImageData(), imageInfo.getWidth(), imageInfo.getHeight(), imageInfo.getImageFormat(), faceInfoList);


      System.out.println(faceInfoList);

结果：

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[com.arcsoft.face.Rect(245, 397 - 937, 1089),1]

如果一个图中有多个人脸也是能够识别的

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com.arcsoft.face.Rect(1974, 213 - 2749, 987),1
com.arcsoft.face.Rect(1352, 769 - 1839, 1256),1
com.arcsoft.face.Rect(1112, 550 - 1417, 854),1
com.arcsoft.face.Rect(327, 692 - 571, 936),1
com.arcsoft.face.Rect(950, 249 - 1200, 498),1
com.arcsoft.face.Rect(961, 708 - 1186, 933),1

人脸特征提取

extractFaceFeature方法

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//人脸特征提取

       //在输入一个图片
       File file1 = new File("D:\\aaa.jpg");


       ImageInfo imageInfo1 = getRGBData(file1);
       //分析得到的数据保存在faceInfoList列表中
       List<FaceInfo> faceInfoList1 = new ArrayList<FaceInfo>();
       faceEngine.detectFaces(imageInfo1.getImageData(), imageInfo1.getWidth(), imageInfo1.getHeight(), imageInfo1.getImageFormat(), faceInfoList1);


       for (FaceInfo faceInfo : faceInfoList1) {
           System.out.println(faceInfo);
       }


       //人脸信息都存放在这个对象里
       FaceFeature faceFeature = new FaceFeature();
       faceEngine.extractFaceFeature(imageInfo1.getImageData(),imageInfo1.getWidth(), imageInfo1.getHeight(), imageInfo1.getImageFormat(),faceInfoList1.get(0),faceFeature);

       System.out.println("图片AAA.jpg的特征是大小为:"+faceFeature.getFeatureData().length);

人脸相似度对比

准备两张图片，按照上述的方法，获得两个feature 来进行比较

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//在输入一个图片
File file1 = new File("D:\\fff.jpg");


ImageInfo imageInfo1 = getRGBData(file1);
//分析得到的数据保存在faceInfoList列表中
List<FaceInfo> faceInfoList1 = new ArrayList<FaceInfo>();
faceEngine.detectFaces(imageInfo1.getImageData(), imageInfo1.getWidth(), imageInfo1.getHeight(), imageInfo1.getImageFormat(), faceInfoList1);


for (FaceInfo faceInfo : faceInfoList1) {
    System.out.print("第一张图片获得的数据:");
    System.out.println(faceInfo);
}


//人脸信息都存放在这个对象里
FaceFeature faceFeature = new FaceFeature();
faceEngine.extractFaceFeature(imageInfo1.getImageData(),imageInfo1.getWidth(), imageInfo1.getHeight(), imageInfo1.getImageFormat(),faceInfoList1.get(0),faceFeature);

System.out.println("图片fff.jpg的特征值大小为:"+faceFeature.getFeatureData().length);

//第二个图片
File file2 = new File("D:\\eee.jpg");
ImageInfo imageInfo2 = getRGBData(file2);
ArrayList<FaceInfo> faceInfoList2 = new ArrayList<>();
faceEngine.detectFaces(imageInfo2.getImageData(),imageInfo2.getWidth(),imageInfo2.getHeight(),imageInfo2.getImageFormat(),faceInfoList2);

for (FaceInfo faceInfo : faceInfoList2) {
    System.out.print("第二张图片获得的数据:");
    System.out.println(faceInfo);
}
//获得脸部信息
FaceFeature faceFeature1 = new FaceFeature();
faceEngine.extractFaceFeature(imageInfo2.getImageData(),imageInfo2.getWidth(),imageInfo2.getHeight(),imageInfo2.getImageFormat(),faceInfoList2.get(0),faceFeature1);
System.out.println("图片eee.jpg的特征值大小为:"+faceFeature1.getFeatureData().length);

/*
* @Param faceFeature
* @Param faceFeature1
* */
FaceSimilar faceSimilar = new FaceSimilar();
//进行图片对比
faceEngine.compareFaceFeature(faceFeature,faceFeature1, CompareModel.ID_PHOTO,faceSimilar);
System.out.println("两张图片的相似度为:"+faceSimilar.getScore());

通过两个面部特征对象 调用方法进行比较 最后获得值

获得可以获得的数据

可以获得的数据包括

  • 年龄 getAge
  • 性别 getGender
  • 人脸三维角度信息 getFace#DAngle
  • 是否为活物 getLiveness
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//获得 年龄 性别

        faceEngine.process(imageInfo2.getImageData(),imageInfo2.getWidth(),imageInfo2.getHeight(),imageInfo2.getImageFormat(),faceInfoList2,functionConfiguration);


        ImageInfoEx infoEx = new ImageInfoEx();
        infoEx.setHeight(imageInfo2.getHeight());
        infoEx.setWidth(imageInfo2.getWidth());
        infoEx.setImageFormat(imageInfo2.getImageFormat());
        infoEx.setImageDataPlanes(new byte[][]{imageInfo2.getImageData()});
        infoEx.setImageStrides(new int[]{imageInfo2.getWidth() * 3});
        List<FaceInfo> faceInfoList3 = new ArrayList<>();
        faceEngine.detectFaces(infoEx, DetectModel.ASF_DETECT_MODEL_RGB,faceInfoList3);

        //这里又设置了一个引擎功能 不知道为何
        FunctionConfiguration configuration = new FunctionConfiguration();
        configuration.setSupportAge(true);
        configuration.setSupportFace3dAngle(true);
        configuration.setSupportGender(true);
        configuration.setSupportLiveness(true);

        faceEngine.process(infoEx,faceInfoList3,configuration);


        ArrayList<AgeInfo> ageInfos = new ArrayList<>();
        int age = faceEngine.getAge(ageInfos);
        System.out.println("图片eee.jpg中人物的大致年龄为:"+ageInfos.get(0).getAge());

        ArrayList<GenderInfo> genderInfos = new ArrayList<>();
        faceEngine.getGender(genderInfos);
        System.out.println("图片eee.jpg中的人物的性别为:"+genderInfos.get(0).getGender());

中间有一个新建立的FunctionConfiguration()的对象configure，但是我不明白为什么要新建一个 因为之前的程序中已经存在这个对象了，而且设置的配置也是相同的，日后继续学习

总结

使用别人的包，固然是一个快速入门的方法，但是具象性太多，只能获得面部数据，年龄，性别，是否为活物，等等等。

做一个人脸识别功能，是能够实现的，但是无法生成标志着红框框的图片，生产那种高大上的好像在追踪分析的图片。（或许是我自己不会）

学完这个包的使用，增加了自己阅读各种依赖官方文档的能力，人工智能涉足，后续会继续向更深处学习，争取能够手搓出一个程序

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