opencv人臉識別

1.官網下載opencv:https://opencv.org/releases/

2.雙擊打開生成檔案夾opencv，

3.創建專案
4.將opencv-454.jar和opencv_java454.dll復制到專案中



5.專案中引入jar

6.將人臉識別的類別庫映入專案


7.測驗代碼

package liu.com.dome;


import org.opencv.core.*;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;

import java.util.Arrays;

public class FaceAi {

    // 初始化人臉探測器
    static CascadeClassifier faceDetector;

    static int i = 0;

    static {
        String path=System.getProperty("user.dir")+"/opencv/opencv_java454.dll";
        System.load(path);
        faceDetector = new CascadeClassifier(System.getProperty("user.dir")+"/opencv/haarcascade_frontalface_alt.xml");
    }

    public static void main(String[] args) {
    //人臉識別后摳圖
    //   getFace("F:/123.png","123_1.jpeg");
    //人臉識別后摳圖
    //    getFace("F:/1234.jpg","1234_1.jpeg");
    
    //相似度對比
        double v = compare_image("F:/0123_1.jpeg", "F:/01234_1.jpeg");
    }


    /**
     * 人臉識別
     * @param imagePath  圖片路徑
     * @param outFile    處理后的圖片路徑
     */
    public static void getFace(String imagePath,String outFile) {
        // 原始影像
        Mat image = Imgcodecs.imread(imagePath);
        System.out.println("圖片長-寬:"+image.rows()+"-"+image.cols());
        //創建一個矩形框住人臉
        MatOfRect matOfRect = new MatOfRect();
        //執行人臉檢測
        faceDetector.detectMultiScale(image,matOfRect);
        //識別出人臉
        Rect[] rects = matOfRect.toArray();
        System.out.println("識別出人臉的數量"+rects.length);

        for (int i=0;i<rects.length;i++){
            Imgproc.rectangle(image,
                    new Point(rects[i].x,rects[i].y),//框的起點
                    new Point(rects[i].x+rects[i].width,rects[i].y+rects[i].height),//框的寬，框的高
                    new Scalar(255,255,255)//框的顏色
            );
            //保存識別后的圖片
            Imgcodecs.imwrite("F:/"+outFile, image);
            //把檢測到的人臉摳出保存
            imageCut(imagePath,"F:/"+i+outFile,rects[i].x,rects[i].y,rects[i].width,rects[i].height);
        }

        System.out.println("成功檢測到人臉在"+"F:/"+outFile+"路徑上");
    }

    /**
     * 裁剪人臉
     *
     * @param imagePath   圖片路徑
     * @param outFile   摳圖后的圖片路徑
     * @param posX    摳圖坐標
     * @param posY
     * @param width   摳圖的寬
     * @param height  摳圖的高
     */
    public static void imageCut(String imagePath, String outFile, int posX, int posY, int width, int height) {
        // 原始影像
        Mat image = Imgcodecs.imread(imagePath);

        // 截取的區域：引數,坐標X,坐標Y,截圖寬度,截圖長度
        Rect rect = new Rect(posX, posY, width, height);
        Mat sub = image.submat(rect);
        Mat mat = new Mat();
        Size size = new Size(300, 300); //指定摳出來的圖示尺寸
        Imgproc.resize(sub, mat, size); // 將人臉進行截圖并保存
        Imgcodecs.imwrite(outFile, mat);
        System.out.println(String.format("圖片裁切成功，裁切后圖片檔案為", outFile));
    }

    /**
     * 人臉比對
     *
     * @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(1000);

        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 相關系數
        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) {
        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()) {
            Mat face = new Mat(image1, rect);
            return face;
        }
        return null;
    }
}