JAVA实现人脸识别，活体检测之百度API
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GitHub：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，挖井人二；
然后是官方的使用说明文档：地址；
以上，感谢。
首先引入jar：
maven:
com.baidu.aip
java-sdk
4.3.2
然后获取所需的AppID、APIKey、SecretKey：
进入百度云，创建应用：
创建完成之后可看见如下：
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 options = new HashMap();
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 requests = new ArrayList();
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 options = new HashMap();
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 options = new HashMap();
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 options = new HashMap();
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 options = new HashMap();
// 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 options = new HashMap();
// 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 options = new HashMap();
// 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 options = new HashMap();
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 options = new HashMap();
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 options = new HashMap();
// 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 options = new HashMap();
// 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 options = new HashMap();
// 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 options = new HashMap();
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 list = new ArrayList();
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：
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 queryService(@RequestParam("the_file") MultipartFile file) {
Map modelMap = new HashMap();
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 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"%>
人脸检测
人脸检测实时数据
年龄：
颜值：
性别：
是否戴眼镜:
表情：
活体分数：
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！