人臉識別java,人臉識別java連接數據庫

本文目錄一覽：

• 1、使用百度Ai進行人臉身份識別(公安驗證)
• 2、用OpenCV開發人臉識別軟件，用Java好還是用C/C++好
• 3、如何開發Java動態人臉識別
• 4、人臉識別系統使用java的開發
• 5、java 人臉識別sdk推薦個好用的？
• 6、java怎麼實現人臉識別？

使用百度Ai進行人臉身份識別(公安驗證)

import com.baidu.aip.util.Base64Util;

import com.enation.app.base.core.service.Exception.CreditAuthFaceException;

import com.enation.app.base.core.service.ICreditAuthManager;

import com.enation.app.base.core.util.AuthTokenService;

import com.enation.app.base.core.util.HttpClientUtils;

import org.apache.http.client.methods.CloseableHttpResponse;

import java.io.*;

import javax.imageio.stream.FileImageInputStream;

import javax.imageio.stream.FileImageInputStream;

import java.net.HttpURLConnection;

import java.net.URLEncoder;

import java.util.HashMap;

import java.util.Map;

/**

* 人臉識別service

* @param name

* @param id_card

* @param faceUrl

*/

@Override

public void face(String name, String id_card, String faceUrl) {

//調用接口獲取tocken(有效期一個月)

    String token = AuthTokenService.getAuth();

System.out.println(“1:token:” + token);

//調用身份驗證api地址

    String url =”” + token;

File face=new File(faceUrl);

FileImageInputStream input =null;

byte[] data =null;

String base64Image =null;

try {

input =new FileImageInputStream(face);

ByteArrayOutputStream output =new ByteArrayOutputStream();

byte[] buf =new byte[1024];

int numBytesRead =0;

while ((numBytesRead = input.read(buf)) != -1) {

output.write(buf,0, numBytesRead);

}

data = output.toByteArray();

base64Image = Base64Util.encode(data);

System.out.println(“4base64轉碼:”+base64Image);

}catch (IOException e) {

e.printStackTrace();

}finally {

try {

if (input !=null) {

input.close();

}

}catch (IOException e) {

e.printStackTrace();

}

}

Map headers =new HashMap();

headers.put(“Content-Type”,”application/x-www-form-urlencoded”);

Map bodys =new HashMap();

bodys.put(“image”, base64Image);

bodys.put(“id_card_number”, id_card);

bodys.put(“name”, name);

try {

CloseableHttpResponse response = HttpClientUtils.doHttpsPost(url, headers, bodys);

String result= HttpClientUtils.toString(response);

System.out.println(“5返回json數據:” + result);

org.json.JSONObject jsonObject=new org.json.JSONObject(result);

System.out.println(“jsonObject:”+jsonObject);

Object jsonResult = jsonObject.get(“result”);

Float floatResult = Float.parseFloat(jsonResult.toString());

if (floatResult =0.80) {

System.out.println(“floatResult:”+floatResult+”人臉身份驗證成功”);

}else {

System.out.println(“floatResult:”+floatResult+”人臉身份驗證失敗”);

throw new CreditAuthFaceException(“人臉身份驗證失敗”);

}

}catch (Exception e) {

e.printStackTrace();

System.out.println(“異常輸出”);

throw new CreditAuthFaceException(“人臉認證失敗”);

}

}

用OpenCV開發人臉識別軟件，用Java好還是用C/C++好

我去年就用opencv開發的android手機端的關於人臉識別的增強現實應用。我可以很明確的告訴你，java的opencv頂多調用攝像頭用，圖像處理都用c++的opencv。對於opencv的開發，不管從開發效率還是執行效率，絕對是c++。java版的opencv想都不要想。

如何開發Java動態人臉識別

1.環境搭建

整個項目的結構圖

2.編寫DetectFaceDemo.java,代碼如下：

[java] view plaincopy

package com.njupt.zhb.test;

import org.opencv.core.Core;

import org.opencv.core.Mat;

import org.opencv.core.MatOfRect;

import org.opencv.core.Point;

import org.opencv.core.Rect;

import org.opencv.core.Scalar;

import org.opencv.highgui.Highgui;

import org.opencv.objdetect.CascadeClassifier;

//

// Detects faces in an image, draws boxes around them, and writes the results

// to “faceDetection.png”.

//

public class DetectFaceDemo {

public void run() {

System.out.println(“\nRunning DetectFaceDemo”);

System.out.println(getClass().getResource(“lbpcascade_frontalface.xml”).getPath());

// Create a face detector from the cascade file in the resources

// directory.

//CascadeClassifier faceDetector = new CascadeClassifier(getClass().getResource(“lbpcascade_frontalface.xml”).getPath());

//Mat image = Highgui.imread(getClass().getResource(“lena.png”).getPath());

//注意：源程序的路徑會多打印一個『/』，因此總是出現如下錯誤

/*

* Detected 0 faces Writing faceDetection.png libpng warning: Image

* width is zero in IHDR libpng warning: Image height is zero in IHDR

* libpng error: Invalid IHDR data

*/

//因此，我們將第一個字符去掉

String xmlfilePath=getClass().getResource(“lbpcascade_frontalface.xml”).getPath().substring(1);

CascadeClassifier faceDetector = new CascadeClassifier(xmlfilePath);

Mat image = Highgui.imread(getClass().getResource(“we.jpg”).getPath().substring(1));

// Detect faces in the image.

// MatOfRect is a special container class for Rect.

MatOfRect faceDetections = new MatOfRect();

faceDetector.detectMultiScale(image, faceDetections);

System.out.println(String.format(“Detected %s faces”, faceDetections.toArray().length));

// Draw a bounding box around each face.

for (Rect rect : faceDetections.toArray()) {

Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height), new Scalar(0, 255, 0));

}

// Save the visualized detection.

String filename = “faceDetection.png”;

System.out.println(String.format(“Writing %s”, filename));

Highgui.imwrite(filename, image);

}

}

3.編寫測試類：

[java] view plaincopy

package com.njupt.zhb.test;

public class TestMain {

public static void main(String[] args) {

System.out.println(“Hello, OpenCV”);

// Load the native library.

System.loadLibrary(“opencv_java246”);

new DetectFaceDemo().run();

}

}

//運行結果:

//Hello, OpenCV

//

//Running DetectFaceDemo

///E:/eclipse_Jee/workspace/JavaOpenCV246/bin/com/njupt/zhb/test/lbpcascade_frontalface.xml

//Detected 8 faces

//Writing faceDetection.png

人臉識別系統使用java的開發

現在主流的還是用的百度，千搜等公司的在線API，就是傳圖片過去，等接收結果就行，seetaface這個東西太複雜了。

java 人臉識別sdk推薦個好用的？

推薦虹軟的，他們的是免費下載的，支持Java，也支持多種平台的開發，接入也比較簡單，重點是功能還比較強大。

java怎麼實現人臉識別？

應該可以通過java調用別人的人臉識別的接口,主要是利用圖像處理的技術,識別關鍵點