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java+opencv實(shí)現(xiàn)人臉識(shí)別功能

更新時(shí)間：2021年05月11日 10:31:40 作者：Litluecat

這篇文章主要介紹了java+opencv實(shí)現(xiàn)人臉識(shí)別功能,本文給大家介紹的非常詳細(xì)，對(duì)大家的學(xué)習(xí)或工作具有一定的參考借鑒價(jià)值，需要的朋友可以參考下

背景：最近需要用到人臉識(shí)別，但又不花錢使用現(xiàn)有的第三方人臉識(shí)別接口，為此使用opencv結(jié)合java進(jìn)行人臉識(shí)別（ps:opencv是開源的，使用它來做人臉識(shí)別存在一定的誤差，效果一般）。

1.安裝opencv
官網(wǎng)地址：https://opencv.org/ , 由于官網(wǎng)下載速度是真的慢

百度網(wǎng)盤：

鏈接: https://pan.baidu.com/s/1RpsP-I7v8pP2dkqALDw7FQ

提取碼: pq7v

如果是官網(wǎng)下載，就無腦安裝就行了，安裝完畢后。

將圖一的兩個(gè)文件復(fù)制到圖二中。

在這里插入圖片描述

從我網(wǎng)盤下載的，忽略這些。

2.在項(xiàng)目中引入pom依賴

<!-- opencv + javacv + ffmpeg-->
        <dependency>
            <groupId>org.bytedeco.javacpp-presets</groupId>
            <artifactId>ffmpeg</artifactId>
            <version>4.1-1.4.4</version>
        </dependency>
        <dependency>
            <groupId>org.bytedeco</groupId>
            <artifactId>javacv</artifactId>
            <version>1.4.4</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.bytedeco.javacpp-presets/ffmpeg-platform -->
        <dependency>
            <groupId>org.bytedeco.javacpp-presets</groupId>
            <artifactId>ffmpeg-platform</artifactId>
            <version>4.1-1.4.4</version>
        </dependency>

        <!-- 視頻攝像頭 -->
        <!-- https://mvnrepository.com/artifact/org.bytedeco/javacv-platform -->
        <dependency>
            <groupId>org.bytedeco</groupId>
            <artifactId>javacv-platform</artifactId>
            <version>1.4.4</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.bytedeco.javacpp-presets/opencv-platform -->
        <dependency>
            <groupId>org.bytedeco.javacpp-presets</groupId>
            <artifactId>opencv-platform</artifactId>
            <version>4.0.1-1.4.4</version>
        </dependency>

1.導(dǎo)入庫依賴
File --> Project Structure，點(diǎn)擊Modules，選擇需要使用opencv.jar的項(xiàng)目。

dWVyQ2F0,size_16,color_FFFFFF,t_70#pic_center)
在這里插入圖片描述

選擇直接opencv安裝路徑

在這里插入圖片描述

2.java代碼demo

package org.Litluecat.utils;

import org.apache.commons.lang.StringUtils;
import org.opencv.core.*;
import org.opencv.highgui.HighGui;
import org.opencv.highgui.ImageWindow;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.videoio.VideoCapture;
import org.opencv.videoio.VideoWriter;
import org.opencv.videoio.Videoio;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.util.Arrays;

/**
 * 人臉比對(duì)工具類
 * @author Litluecat
 * @Title: Opencv 圖片人臉識(shí)別、實(shí)時(shí)攝像頭人臉識(shí)別
**/
public class FaceVideo {

    private static final Logger log = LoggerFactory.getLogger(FaceVideo.class);

    private static final String endImgUrl = "C:\\Users\\lenovo\\Desktop\\";
    /**
     * opencv的人臉識(shí)別xml文件路徑
     */
    private static final String faceDetectorXML2URL = "D:\\Sofeware\\opencv\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml";
    /**
     * opencv的人眼識(shí)別xml文件路徑
     */
    private static final String eyeDetectorXML2URL = "D:\\Sofeware\\opencv\\sources\\data\\haarcascades\\haarcascade_eye.xml";
    /**
     * 直方圖大小，越大精度越高，運(yùn)行越慢
     */
    private static int Matching_Accuracy = 100000;
    /**
     * 初始化人臉探測器
     */
    private static CascadeClassifier faceDetector;
    /**
     * 初始化人眼探測器
     */
    private static CascadeClassifier eyeDetector;

    private static int i=0;

    static {
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
        faceDetector = new CascadeClassifier(faceDetectorXML2URL);
        eyeDetector = new CascadeClassifier(eyeDetectorXML2URL);
    }

    public static void main(String[] args) {
        log.info("開始人臉匹配");
        long begin = System.currentTimeMillis();
        // 1- 從攝像頭實(shí)時(shí)人臉識(shí)別，識(shí)別成功保存圖片到本地
        try{
            getVideoFromCamera(endImgUrl + "2.jpg");
            //僅用于強(qiáng)制拋異常，從而關(guān)閉GUI界面
            Thread.sleep(1000);
            int err = 1/0;
     
            // 2- 比對(duì)本地2張圖的人臉相似度 （越接近1越相似）
//            double compareHist = FaceVideo.compare_image(endImgUrl + "test1.jpg" , endImgUrl + "face.jpg");
//            log.info("匹配度：{}",compareHist);
//            if (compareHist > 0.72) {
//                log.info("人臉匹配");
//            } else {
//                log.info("人臉不匹配");
//            }

        }catch (Exception e){
            log.info("開始強(qiáng)制關(guān)閉");
            log.info("人臉匹配結(jié)束，總耗時(shí)：{}ms",(System.currentTimeMillis()-begin));
            System.exit(0);
        }
    }


    /**
     * OpenCV-4.1.1 從攝像頭實(shí)時(shí)讀取
     * @param targetImgUrl 比對(duì)身份證圖片
     * @return: void
     * @date: 2019年8月19日 17:20:13
     */
    public static void getVideoFromCamera(String targetImgUrl) {
        //1 如果要從攝像頭獲取視頻 則要在 VideoCapture 的構(gòu)造方法寫 0
        VideoCapture capture = new VideoCapture(0);
        Mat video = new Mat();
        int index = 0;
        if (capture.isOpened()) {
            while(i<3) {
                // 匹配成功3次退出
                capture.read(video);
                HighGui.imshow("實(shí)時(shí)人臉識(shí)別", getFace(video, targetImgUrl));
                //窗口延遲等待100ms，返回退出按鍵
                index = HighGui.waitKey(100);
                //當(dāng)退出按鍵為Esc時(shí)，退出窗口
                if (index == 27) {
                    break;
                }
            }
        }else{
            log.info("攝像頭未開啟");
        }
        //該窗口銷毀不生效，該方法存在問題
        HighGui.destroyAllWindows();
        capture.release();
        return;
    }

    /**
     * OpenCV-4.1.0 人臉識(shí)別
     * @param image 待處理Mat圖片(視頻中的某一幀)
     * @param targetImgUrl 匹配身份證照片地址
     * @return 處理后的圖片
     */
    public static Mat getFace(Mat image, String targetImgUrl) {
        MatOfRect face = new MatOfRect();
        faceDetector.detectMultiScale(image, face);
        Rect[] rects=face.toArray();
        log.info("匹配到 "+rects.length+" 個(gè)人臉");
        if(rects != null && rects.length >= 1) {
            i++;
            if(i==3) {
                // 獲取匹配成功第3次的照片
                Imgcodecs.imwrite(endImgUrl + "face.jpg", image);
                FaceVideoThread faceVideoThread = new FaceVideoThread(targetImgUrl , endImgUrl + "face.jpg");
                new Thread(faceVideoThread,"人臉比對(duì)線程").start();
            }
        }
        return image;
    }

    /**
     * 人臉截圖
     * @param img
     * @return
     */
    public static String face2Img(String img) {
        String faceImg = null;
        Mat image0 = Imgcodecs.imread(img);
        Mat image1 = new Mat();
        // 灰度化
        Imgproc.cvtColor(image0, image1, Imgproc.COLOR_BGR2GRAY);
        // 探測人臉
        MatOfRect faceDetections = new MatOfRect();
        faceDetector.detectMultiScale(image1, faceDetections);
        // rect中人臉圖片的范圍
        for (Rect rect : faceDetections.toArray()) {
            faceImg = img+"_.jpg";
            // 進(jìn)行圖片裁剪
            imageCut(img, faceImg, rect.x, rect.y, rect.width, rect.height);
        }
        if(null == faceImg){
            log.info("face2Img未識(shí)別出該圖像中的人臉，img={}",img);
        }
        return faceImg;
    }

    /**
     * 人臉比對(duì)
     * @param img_1
     * @param img_2
     * @return
     */
    public static double compare_image(String img_1, String img_2) {
        Mat mat_1 = conv_Mat(img_1);
        Mat mat_2 = conv_Mat(img_2);
        Mat hist_1 = new Mat();
        Mat hist_2 = new Mat();

        //顏色范圍
        MatOfFloat ranges = new MatOfFloat(0f, 256f);
        //直方圖大小， 越大匹配越精確 (越慢)
        MatOfInt histSize = new MatOfInt(Matching_Accuracy);

        Imgproc.calcHist(Arrays.asList(mat_1), new MatOfInt(0), new Mat(), hist_1, histSize, ranges);
        Imgproc.calcHist(Arrays.asList(mat_2), new MatOfInt(0), new Mat(), hist_2, histSize, ranges);

        // CORREL 相關(guān)系數(shù)
        double res = Imgproc.compareHist(hist_1, hist_2, Imgproc.CV_COMP_CORREL);
        return res;
    }

    /**
     * 灰度化人臉
     * @param img
     * @return
     */
    public static Mat conv_Mat(String img) {
        if(StringUtils.isBlank(img)){
            return null;
        }
        Mat image0 = Imgcodecs.imread(img);
        Mat image1 = new Mat();
        //Mat image2 = new Mat();
        // 灰度化
        Imgproc.cvtColor(image0, image1, Imgproc.COLOR_BGR2GRAY);
        //直方均勻
        //Imgproc.equalizeHist(image1, image2);

        // 探測人臉
        MatOfRect faceDetections = new MatOfRect();
        faceDetector.detectMultiScale(image1, faceDetections);

        //探測人眼
//        MatOfRect eyeDetections = new MatOfRect();
//        eyeDetector.detectMultiScale(image1, eyeDetections);

        // rect中人臉圖片的范圍
        Mat face = null;
        for (Rect rect : faceDetections.toArray()) {

            //給圖片上畫框框 參數(shù)1是圖片 參數(shù)2是矩形 參數(shù)3是顏色 參數(shù)四是畫出來的線條大小
            //Imgproc.rectangle(image0,rect,new Scalar(0,0,255),2);
            //輸出圖片
            //Imgcodecs.imwrite(img+"_.jpg",image0);

            face = new Mat(image1, rect);
        }
        if(null == face){
            log.info("conv_Mat未識(shí)別出該圖像中的人臉，img={}",img);
        }
        return face;
    }

}

這邊的人臉識(shí)別是另外其線程進(jìn)行比對(duì)，代碼如下。

package org.Litluecat.utils;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;


public class FaceVideoThread implements Runnable{
    private static final Logger log = LoggerFactory.getLogger(FaceVideoThread.class);

    private String oneImgUrl = null;
    private String otherImgUrl = null;
    public FaceVideoThread(String oneImgUrl, String otherImgUrl){
        this.oneImgUrl = oneImgUrl;
        this.otherImgUrl = otherImgUrl;
    }
    @Override
    public void run() {
        try {
            double compareHist = FaceVideo.compare_image(oneImgUrl , otherImgUrl);
            log.info("匹配度：{}",compareHist);
            if (compareHist > 0.72) {
                log.info("人臉匹配");
            } else {
                log.info("人臉不匹配");
            }
        } catch (Exception e) {
            e.printStackTrace();
        }
    }
}

提醒：如果運(yùn)行異常，請(qǐng)?zhí)砑幽鉶pencv的安裝地址-Djava.library.path=D:\Sofeware\opencv\build\java\x64;

在這里插入圖片描述