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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