Java OpenCV实现人脸识别过程详解

准备 :

下载openCV安装包 :  https://opencv.org/

安装包安装之后支持多种语言环境,此处使用Java,在Eclipse中引入 openCV目录下的java/opencv-320.jar,同时配置openCV库路径。

Eclipse配置openCV

代码实现 :

package 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.objdetect.CascadeClassifier;

import org.opencv.imgcodecs.Imgcodecs;

import org.opencv.imgproc.Imgproc;

public class Test {

//引入训练好的人脸识别XML文件

static String PAHT = "E:/GOF/OpenCV/bin/test/haarcascade_frontalface_alt.xml";

static String IMAGE_PATH = "E:/GOF/OpenCV/src/test/a.jpg";

static String productPath = "E:/GOF/OpenCV";

public static void main(String[] args) {

System.loadLibrary(Core.NATIVE_LIBRARY_NAME);

String Path = Test.class.getResource("haarcascade_frontalface_alt.xml").getPath();

System.out.println(Path);

CascadeClassifier faceDetector = new CascadeClassifier(PAHT);

Mat image = Imgcodecs.imread(IMAGE_PATH);

MatOfRect faceDetections = new MatOfRect();

faceDetector.detectMultiScale(image, faceDetections);

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

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

Imgproc.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x + rect.width, rect.y + rect.height),

new Scalar(0, 255, 0));

}

String filename = "ouput.png";

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

boolean flag = Imgcodecs.imwrite(filename, image);

}

}

实现效果 :

对人脸区域写入边框

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