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

以上就是本文的全部内容，希望对大家的学习有所帮助，也希望大家多多支持脚本之家。