JAVA实现人脸识别，活体检测之百度API

偏执的太偏执、 2022-05-23 11:42 310阅读 0赞

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GitHub：[https://github.com/reamZMX/led-][https_github.com_reamZMX_led-]

\-----------------------8/16更新---------------------------

有人问源码:

链接：https://pan.baidu.com/s/1WP37IBacu6VZwtNOUDbSYg 密码：vdzm

在这

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吃水不忘挖井人，挖井人博客在此：[挖井人一][Link 1]，[挖井人二][Link 2]；

然后是官方的使用说明文档：[地址][Link 3]；

以上，感谢。

首先引入jar：

maven:

<dependency>
            <groupId>com.baidu.aip</groupId>
            <artifactId>java-sdk</artifactId>
            <version>4.3.2</version>
        </dependency>

然后获取所需的AppID、APIKey、SecretKey：

进入百度云，创建应用：

![70][]

创建完成之后可看见如下：

![70 1][]

获取AppID、APIKey、SecretKey后，导入一下代码：

public class FaceSpot {
    	private static final String AppID = "";
    	private static final String APIKey = "";
    	private static final String SecretKey = "";
    
    	static AipFace client = null;
    	static {
    		client = new AipFace(AppID, APIKey, SecretKey);
    		// 可选：设置网络连接参数
    		client.setConnectionTimeoutInMillis(2000);
    		client.setSocketTimeoutInMillis(60000);
    	}
    
    	public static void main(String[] args) throws IOException {
    		 String filePath = "F:/3.jpg";
    		 byte[] imgData = FileToByte(new File(filePath));
    		 
    		 System.out.println(detectFace(imgData,"1"));
    //		String filePath1 = "F:/3.jpg";
    //		String filePath2 = "F:/7.jpg";
    //		byte[] imgData1 = FileUtil.readFileByBytes(filePath1);
    //		byte[] imgData2 = FileUtil.readFileByBytes(filePath2);
    //		System.out.println(faceverify(imgData1));
    	}
    
    	/**
    	 * 人脸检测
    	 * 
    	 * @return
    	 * @throws IOException
    	 */
    	public static String detectFace(File file, String max_face_num) {
    		try {
    			return detectFace(FileToByte(file), max_face_num);
    		} catch (IOException e) {
    			// TODO Auto-generated catch block
    			e.printStackTrace();
    		}
    		return null;
    	}
    
    	/**
    	 * 人脸检测
    	 * 
    	 * @return
    	 * @throws IOException
    	 */
    	public static String detectFace(byte[] arg0, String max_face_num) {
    		try {
    
    			HashMap<String, String> options = new HashMap<String, String>();
    			options.put("face_field", "age,beauty,expression,faceshape,gender,glasses,race,qualities");
    			options.put("max_face_num", "2");
    			options.put("face_type", "LIVE");
    
    			// 图片数据
    			String imgStr = Base64Util.encode(arg0);
    			String imageType = "BASE64";
    			JSONObject res = client.detect(imgStr, imageType, options);
    			System.out.println(res.toString(2));
    			return res.toString();
    		} catch (Exception e) {
    			e.printStackTrace();
    		}
    		return null;
    	}
        /**
         * 人脸比对
         * @param file1
         * @param file2
         * @return
         */
    	public static String matchFace(File file1, File file2) {
    		try {
    			return matchFace(FileToByte(file1), FileToByte(file2));
    		} catch (IOException e) {
    			// TODO Auto-generated catch block
    			e.printStackTrace();
    		}
    		return null;
    	}
    
    	/**
    	 * 人脸比对
    	 * 
    	 * @param arg0
    	 *            人脸1
    	 * @param arg1
    	 *            人脸2
    	 * @return
    	 */
    	public static String matchFace(byte[] arg0, byte[] arg1) {
    		String imgStr1 = Base64Util.encode(arg0);
    		String imgStr2 = Base64Util.encode(arg1);
    		MatchRequest req1 = new MatchRequest(imgStr1, "BASE64");
    		MatchRequest req2 = new MatchRequest(imgStr2, "BASE64");
    		ArrayList<MatchRequest> requests = new ArrayList<MatchRequest>();
    		requests.add(req1);
    		requests.add(req2);
    		JSONObject res = client.match(requests);
    		return res.toString();
    	}
        
    	/**
    	 * 人脸搜索
    	 * @param file
    	 * @param groupIdList
    	 * @param userId
    	 * @return
    	 */
    	public static String searchFace(File file, String groupIdList, String userId) {
    		try {
    			return searchFace(FileToByte(file), groupIdList, userId);
    		} catch (IOException e) {
    			// TODO Auto-generated catch block
    			e.printStackTrace();
    		}
    		return null;
    	}
    
    	/**
    	 * 人脸搜索
    	 * 
    	 * @param arg0
    	 * @param groupIdList
    	 * @return
    	 */
    	public static String searchFace(byte[] arg0, String groupIdList, String userId) {
    		String imgStr = Base64Util.encode(arg0);
    		String imageType = "BASE64";
    		HashMap<String, String> options = new HashMap<String, String>();
    		options.put("quality_control", "NORMAL");
    		options.put("liveness_control", "LOW");
    		if (userId != null) {
    			options.put("user_id", userId);
    		}
    		options.put("max_user_num", "1");
    		JSONObject res = client.search(imgStr, imageType, groupIdList, options);
    		return res.toString(2);
    	}
        /**
         * 增加用户
         * @param file
         * @param userInfo
         * @param userId
         * @param groupId
         * @return
         */
    	public static String addUser(File file, String userInfo, String userId, String groupId) {
    		try {
    			return addUser(FileToByte(file), userInfo, userId, groupId);
    		} catch (IOException e) {
    			// TODO Auto-generated catch block
    			e.printStackTrace();
    		}
    		return null;
    	}
    
    	/**
    	 * 增加用户
    	 * 
    	 * @param arg0
    	 * @param userInfo
    	 * @param userId
    	 * @param groupId
    	 * @return
    	 */
    	public static String addUser(byte[] arg0, String userInfo, String userId, String groupId) {
    		String imgStr = Base64Util.encode(arg0);
    		String imageType = "BASE64";
    		HashMap<String, String> options = new HashMap<String, String>();
    		options.put("user_info", userInfo);
    		options.put("quality_control", "NORMAL");
    		options.put("liveness_control", "LOW");
    
    		JSONObject res = client.addUser(imgStr, imageType, groupId, userId, options);
    		return res.toString(2);
    	}
    
    	public static String updateUser(File file, String userInfo, String userId, String groupId) {
    		try {
    			return updateUser(FileToByte(file), userInfo, userId, groupId);
    		} catch (IOException e) {
    			// TODO Auto-generated catch block
    			e.printStackTrace();
    		}
    		return null;
    	}
    
    	/**
    	 * 更新用户
    	 * 
    	 * @param arg0
    	 * @param userInfo
    	 * @param userId
    	 * @param groupId
    	 * @return
    	 */
    	public static String updateUser(byte[] arg0, String userInfo, String userId, String groupId) {
    		String imgStr = Base64Util.encode(arg0);
    		String imageType = "BASE64";
    		HashMap<String, String> options = new HashMap<String, String>();
    		if (userInfo != null) {
    			options.put("user_info", userInfo);
    		}
    		options.put("quality_control", "NORMAL");
    		options.put("liveness_control", "LOW");
    
    		JSONObject res = client.updateUser(imgStr, imageType, groupId, userId, options);
    		return res.toString(2);
    	}
        /**
         * 删除用户人脸信息
         * @param userId
         * @param groupId
         * @param faceToken
         * @return
         */
    	public static String deleteUserFace(String userId, String groupId, String faceToken) {
    		HashMap<String, String> options = new HashMap<String, String>();
    		// 人脸删除
    		JSONObject res = client.faceDelete(userId, groupId, faceToken, options);
    		return res.toString();
    	}
        /**
         * 查询用户信息
         * @param userId
         * @param groupId
         * @return
         */
    	public static String searchUserInfo(String userId, String groupId) {
    		HashMap<String, String> options = new HashMap<String, String>();
    		// 用户信息查询
    		JSONObject res = client.getUser(userId, groupId, options);
    		return res.toString(2);
    	}
        /**
         * 获取用户人脸列表
         * @param userId
         * @param groupId
         * @return
         */
    	public static String getUserFaceList(String userId, String groupId) {
    		HashMap<String, String> options = new HashMap<String, String>();
    		// 获取用户人脸列表
    		JSONObject res = client.faceGetlist(userId, groupId, options);
    		return res.toString(2);
    	}
        /**
         * 获取一组用户
         * @param groupId
         * @param returnNum
         * @return
         */
    	public static String getGroupUsers(String groupId, String returnNum) {
    		HashMap<String, String> options = new HashMap<String, String>();
    		options.put("start", "0");
    		if (returnNum != null) {
    			options.put("length", returnNum);
    		}
    		// 获取用户列表
    		JSONObject res = client.getGroupUsers(groupId, options);
    		return res.toString(2);
    	}
        /**
         * 组用户复制
         * @param userId
         * @param srcGroupId
         * @param dstGroupId
         * @return
         */
    	public static String userCopy(String userId, String srcGroupId, String dstGroupId) {
    		HashMap<String, String> options = new HashMap<String, String>();
    		options.put("src_group_id", srcGroupId);
    		options.put("dst_group_id", dstGroupId);
    		// 复制用户
    		JSONObject res = client.userCopy(userId, options);
    		return res.toString(2);
    	}
        /**
         * 删除用户
         * @param userId
         * @param groupId
         * @return
         */
    	public static String deleteUser(String userId, String groupId) {
    		HashMap<String, String> options = new HashMap<String, String>();
    		// 人脸删除
    		JSONObject res = client.deleteUser(groupId, userId, options);
    		return res.toString();
    	}
        /**
         * 增加组信息
         * @param groupId
         * @return
         */
    	public static String addGroup(String groupId) {
    		HashMap<String, String> options = new HashMap<String, String>();
    		// 创建用户组
    		JSONObject res = client.groupAdd(groupId, options);
    		return res.toString();
    	}
        /**
         * 删除
         * @param groupId
         * @return
         */
    	public static String deleteGroup(String groupId) {
    		HashMap<String, String> options = new HashMap<String, String>();
    		// 创建用户组
    		JSONObject res = client.groupDelete(groupId, options);
    		return res.toString();
    	}
        /**
         * 获取组列表
         * @param length
         * @return
         */
    	public static String getGroupList(String length) {
    		HashMap<String, String> options = new HashMap<String, String>();
    		options.put("start", "0");
    		options.put("length", length);
    		// 组列表查询
    		JSONObject res = client.getGroupList(options);
    		return res.toString();
    	}
    	/**
    	 * 活体检测
    	 * @param arg0
    	 * @return
    	 */
    	public static String faceverify(byte[] arg0){
    		String imgStr = Base64Util.encode(arg0);
            String imageType = "BASE64";
            FaceVerifyRequest req = new FaceVerifyRequest(imgStr, imageType);
            ArrayList<FaceVerifyRequest> list = new ArrayList<FaceVerifyRequest>();
            list.add(req);
            JSONObject res = client.faceverify(list);
            return res.toString();
    	}
    
    	private static byte[] FileToByte(File file) throws IOException {
    		// 将数据转为流
    		InputStream content = new FileInputStream(file);
    		ByteArrayOutputStream swapStream = new ByteArrayOutputStream();
    		byte[] buff = new byte[100];
    		int rc = 0;
    		while ((rc = content.read(buff, 0, 100)) > 0) {
    			swapStream.write(buff, 0, rc);
    		}
    		// 获得二进制数组
    		return swapStream.toByteArray();
    	}
    
    }

填入自己的AppID, APIKey, SecretKey；

函数的参数可自行根据官方文档自己改一改，文件读取那边提供一下小帅的FileUtil并且处理好了异常：

public class FileUtil {
    
        /**
         * 根据文件路径读取byte[] 数组
         */
        public static byte[] readFileByBytes(String filePath) throws IOException {
            File file = new File(filePath);
            if (!file.exists()) {
                throw new FileNotFoundException(filePath);
            } else {
                ByteArrayOutputStream bos = new ByteArrayOutputStream((int) file.length());
                BufferedInputStream in = null;
    
                try {
                    in = new BufferedInputStream(new FileInputStream(file));
                    short bufSize = 1024;
                    byte[] buffer = new byte[bufSize];
                    int len1;
                    while (-1 != (len1 = in.read(buffer, 0, bufSize))) {
                        bos.write(buffer, 0, len1);
                    }
    
                    byte[] var7 = bos.toByteArray();
                    return var7;
                } finally {
                    try {
                        if (in != null) {
                            in.close();
                        }
                    } catch (IOException var14) {
                        var14.printStackTrace();
                    }
    
                    bos.close();
                }
            }
        }
    }

然后就是测试啦，测试的话，随便百度了一张美女的照片，然后看返回：

{
      "timestamp": 1528422299,
      "result": {
        "face_list": [{
          "expression": {
            "probability": 0.9997190833,
            "type": "smile"
          },
          "face_probability": 1,
          "glasses": {
            "probability": 0.9999995232,
            "type": "none"
          },
          "location": {
            "height": 102,
            "rotation": -2,
            "width": 109,
            "left": 102.9398575,
            "top": 56.39219284
          },
          "age": 19,
          "gender": {
            "probability": 0.9999992847,
            "type": "female"
          },
          "face_shape": {
            "probability": 0.7517765164,
            "type": "heart"
          },
          "face_token": "706eaee3240ef0cc679ab209b1b71e0d",
          "beauty": 69.47167206,
          "race": {
            "probability": 0.9999864101,
            "type": "yellow"
          },
          "angle": {
            "yaw": -2.858289719,
            "roll": -2.302281618,
            "pitch": 9.867022514
          }
        }],
        "face_num": 1
      },
      "cached": 0,
      "error_code": 0,
      "log_id": 3671200838,
      "error_msg": "SUCCESS"
    }

嗯，确实是美女，

"beauty": 69.47167206

好，然后通过浏览器开启摄像头来实时的试下，先上效果图：

![20180608095840893][]

好，大家不用在意这些细节，比如颜值啥的。。

我觉得颜值这项可能是假的，因为我做搞怪的表情时分数反而高一些？？？？？？？？？？

上代码吧。。

首先是Controller：

@Controller
    @RequestMapping(value = "/faceRecognition")
    public class faceRecognitionController {
    
    	 /**
    	 * 人脸检测测试页面
    	 * @return
    	 * @throws Exception  
    	 */
        @RequestMapping(value = "/test.do")
        public ModelAndView queryVoi() throws Exception {
            ModelAndView modelAndView = new ModelAndView();
            modelAndView.setViewName("/artificialIntelligence/faceRecognition/test");
            return modelAndView;
        }
    	
        /**
       	 * 请求人脸检测
       	 * @return
       	 * @throws Exception  
       	 */
    	@RequestMapping(value = "/save.do")
    	@ResponseBody
    	public Map<String, Object> queryService(@RequestParam("the_file") MultipartFile file) {
    		Map<String, Object> modelMap = new HashMap<String, Object>();
    		try {
    			//将数据转为流
    			InputStream content = file.getInputStream();
    			ByteArrayOutputStream swapStream = new ByteArrayOutputStream();  
    	        byte[] buff = new byte[100];  
    	        int rc = 0;  
    	        while ((rc = content.read(buff, 0, 100)) > 0) {  
    	            swapStream.write(buff, 0, rc);  
    	        }  
    	        //获得二进制数组
    	        byte[] in2b = swapStream.toByteArray(); 
    	        //调用人脸检测的方法
    	        String  str = FaceSpot.detectFace(in2b,""+1);
    	        JSONObject job = new JSONObject(FaceSpot.faceverify(in2b));
    			 System.out.println(job.toString());
    			 JSONObject testData = job.getJSONObject("result");
    			 //System.out.println(testData.get("face_liveness"));
    	        
    	        JSON json = JSON.parseObject(str);
                FaceV3DetectBean bean = JSON.toJavaObject(json, FaceV3DetectBean.class);
                JSONArray arr = new JSONArray();
                
    	     	 for(int i=0;i<bean.getResult().getFace_list().size();i++){
    			        JSONObject jsonObject = new JSONObject();
    			    	//获取年龄
    			        int ageOne = bean.getResult().getFace_list().get(i).getAge();
    			     	//处理年龄
    			        String age =String.valueOf(new BigDecimal(ageOne).setScale(0, BigDecimal.ROUND_HALF_UP));
    			        jsonObject.put("age", age);
    					
    					//获取美丑打分
    			        Double beautyOne = (Double) bean.getResult().getFace_list().get(i).getBeauty();
    					//处理美丑打分
    			     	String beauty =String.valueOf(new BigDecimal(beautyOne).setScale(0, BigDecimal.ROUND_HALF_UP));
    			     	jsonObject.put("beauty", beauty);
    					
    					//获取性别  male(男)、female(女)
    					String gender = (String) bean.getResult().getFace_list().get(i).getGender().getType();
    					jsonObject.put("gender", gender);
    					
    					//获取是否带眼睛 0-无眼镜，1-普通眼镜，2-墨镜
    					String glasses =  bean.getResult().getFace_list().get(i).getGlasses().getType();
    					jsonObject.put("glasses", String.valueOf(glasses));
    					
    					//获取是否微笑，0，不笑；1，微笑；2，大笑
    					String expression =  bean.getResult().getFace_list().get(i).getExpression().getType();
    					jsonObject.put("expression", String.valueOf(expression));
    					arr.put(jsonObject);
    			 }
    			modelMap.put("strjson", arr.toString());
    			modelMap.put("face_liveness", testData.get("face_liveness"));
    			modelMap.put("success", true);
    		} catch (Exception e) {
    			e.printStackTrace();
    			modelMap.put("success", false);
    			modelMap.put("data", e.getMessage());
    		}
    		return modelMap;
    	}
    	
    	
    }

用的是fastjson，自行加jar包。

然后是jsp：

<%@ page language="java" contentType="text/html; charset=UTF-8" pageEncoding="UTF-8"%>
    <%@ taglib prefix="c" uri="http://java.sun.com/jsp/jstl/core"%>
    <!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
    <html>
    <head>
    <meta http-equiv="Content-Type" content="text/html; charset=UTF-8">
    <meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1">	
    <title>人脸检测</title>
    <script src="js/jquery-2.1.1.js" type="text/javascript" charset="utf-8"></script>
    <script>
    
    	//判断浏览器是否支持HTML5 Canvas
    	window.onload = function () {
    		try {
    		//动态创建一个canvas元 ，并获取他2Dcontext。如果出现异常则表示不支持 document.createElement("canvas").getContext("2d");
    		 document.getElementById("support").innerHTML = "浏览器支持HTML5 CANVAS";
    		}
    		catch (e) {
    		 document.getElementByIdx("support").innerHTML = "浏览器不支持HTML5 CANVAS";
    		}
    	};
    	
    	//这段代 主要是获取摄像头的视频流并显示在Video 签中
    	window.addEventListener("DOMContentLoaded", function () {
    		var canvas = document.getElementById("canvas"),
    		context = canvas.getContext("2d"),
    		video = document.getElementById("video"),
    		videoObj = { "video": true },
    		errBack = function (error) {
    			console.log("Video capture error: ", error.code);
    		};
    		//拍照按钮
    // 		$("#snap").click(function () {
    // 			context.drawImage(video, 0, 0, 330, 250);
    // 			})
    		//拍照每秒一次
    		setInterval(function(){
    			context.drawImage(video, 0, 0, 330, 250)
    			CatchCode();
    		},1000);
    		//navigator.getUserMedia这个写法在Opera中好像是navigator.getUserMedianow
    		//更新兼容火狐浏览器
    		if (navigator.getUserMedia || navigator.webkitGetUserMedia || navigator.mozGetUserMedia) {
    			    navigator.getUserMedia=navigator.getUserMedia || navigator.webkitGetUserMedia || navigator.mozGetUserMedia;
    			    navigator.getUserMedia(videoObj, function (stream) {
    				video.srcObject  = stream;
    				video.play();
    				}, errBack);
    		}
    	
    	}, false);
    	
    	function dataURItoBlob(base64Data) {
    		var byteString;
    		if (base64Data.split(',')[0].indexOf('base64') >= 0)
    		byteString = atob(base64Data.split(',')[1]);
    		else
    		byteString = unescape(base64Data.split(',')[1]);
    		var mimeString = base64Data.split(',')[0].split(':')[1].split(';')[0];
    		var ia = new Uint8Array(byteString.length);
    		for (var i = 0; i < byteString.length; i++) {
    		ia[i] = byteString.charCodeAt(i);
    		}
    		return new Blob([ia], {type:mimeString});
    	}
    	
    	//上传服务器
    	function CatchCode() {
    		var canvans = document.getElementById("canvas");
    		//获取浏览器页面的画布对象
    		//以下开始编 数据
    		var imageBase64 = canvans.toDataURL();
    		var blob = dataURItoBlob(imageBase64);  // 上一步中的函数
    		var fd = new FormData(document.forms[0]);
    		fd.append("the_file", blob, 'image.png');
    		//将图像转换为base64数据
    		$.ajax({
    	   		type:"POST",
    	   		url:"faceRecognition/save.do",
    	   		processData: false,     // 必须
    	      	contentType: false,     // 必须
    	      	data:fd,
    	    	datatype: "json",
    	   		success:function(data){
    		   		var mes = eval(data);
    		   		//alert(mes.success);
    		   		//var jsonObj =   $.parseJSON(mes.strjson); 
    		   		//alert(jsonObj[0].age);
    		   		if (mes.success) {
     		   			//alert(mes.strjson);
    		   			var jsonObj =  $.parseJSON(mes.strjson); 
    		   			//alert(jsonObj);
    		   			var age = jsonObj[0].age;
     		   			
    		   			var beauty = jsonObj[0].beauty;
    		   			var gendergender = jsonObj[0].gender;
    		   			var glasses = jsonObj[0].glasses;
    		   			var expression = jsonObj[0].expression
    		   			
    		   			$("#age").html(age);
    		   			$("#beauty").html(beauty);
    		   			$("#faceverify").html(mes.face_liveness);
    		   			
    		   			if(gendergender == 'male'){
    		   				$("#gendergender").html("男");
    		   			}else{
    		   				$("#gendergender").html("女");
    		   			}
    		   			
    		   			if(glasses == 'none'){
    		   				$("#glasses").html("未戴眼镜");
    		   			}else if(glasses == 'common'){
    		   				$("#glasses").html("戴了普通眼镜");
    		   			}else{
    		   				$("#glasses").html("戴了墨镜");
    		   			}
    					
    		   			if(expression == 'none'){
    		   				$("#expression").html("不笑");
    		   			}else if(expression == 'smile'){
    		   				$("#expression").html("微笑");
    		   			}else{
    		   				$("#expression").html("大笑");
    		   			}
    		   		}
    	   		},
    	   		error: function(){
    	    		//请求出错处理
    	    		alert("出情况了");
    	    		}         
    	  		});
    	}
    </script>
    <style> 
    .div-a{ float:left;width:60%;height:60%;border:1px solid #F00} 
    .div-b{ float:left;width:39%;height:60%;border:1px solid #000} 
    span{ font-size:25px }
    </style> 
    </head> 
    <body> 
    	
    	<div class="div-a" id="contentHolder">
    			<video id="video" width="100%" height="60%" autoplay></video>
    			<canvas style="" hidden="hidden"  id="canvas" width="520" height="250"></canvas>
    	</div> 
    	
    	<div class="div-b" >
    			
    
    
    		
    		<h1>人脸检测实时数据</h1>
    		<span>年龄：</span><span id="age"></span><br/>
    		<span>颜值：</span><span id="beauty" ></span><br/>
    		<span>性别：</span><span id="gendergender"></span><br/>
    		<span>是否戴眼镜:</span><span id="glasses"></span><br/>
    		<span>表情：</span><span id="expression"></span><br/>
    		<span>活体分数：</span><span id="faceverify"></span><br/>
    	</div> 
    		
    	</body>
    </html>

这个貌似只支持火狐？？我用其他浏览器摄像头并未开启，有哪位大神知道代码还请告诉在下，谢谢指教。

这边有个活体指数，我测试了下，貌似还挺准，我首先百度了一张胡歌的照片放在摄像头上，emmmm.....颜值80，但是活体指数就很低，然后本人上，活体指数一直在0.95之上浮动，还是可靠的。

好，告辞！

[https_github.com_reamZMX_led-]: https://github.com/reamZMX/led-
[Link 1]: https://blog.csdn.net/u010651369/article/details/64439090
[Link 2]: https://ai.baidu.com/forum/topic/show/496738
[Link 3]: http://ai.baidu.com/docs#/Face-Java-SDK/ab5e2cb4
[70]: /images/20220523/6e409da841e14fa69001cf2f43e482fa.png
[70 1]: /images/20220523/e5d8195de4f44d1bacd74c0631af3ed2.png
[20180608095840893]: /images/20220523/0d8294ec247340d3a5d5c3232b44eed9.png