Java使用OpenCV人脸检测

最新推荐文章于 2025-05-12 15:38:05 发布

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#Java #使用 #OpenCV #人脸检测

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本文介绍了一个使用OpenCV库进行人脸检测的Java程序示例。该程序加载预训练的人脸检测模型，从图像中检测人脸，并在检测到的人脸周围绘制边界框。最后，将带有边界框的图像保存为“faceDetection.png”。程序使用了LBP级联分类器来检测图像中的正面人脸。

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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.highgui.Highgui;
import org.opencv.objdetect.CascadeClassifier;

/*
 * Detects faces in an image, draws boxes around them, and writes the results
 * to "faceDetection.png".
 */
public class DetectFaceDemo {
    public void run() {
        System.out.println("\nRunning DetectFaceDemo");

        // Create a face detector from the cascade file in the resources
        // directory.
        CascadeClassifier faceDetector = new CascadeClassifier(getClass()
                .getResource("/lbpcascade_frontalface.xml").getPath());
        Mat image = Highgui.imread(getClass().getResource(
                "/AverageMaleFace.jpg").getPath());

        // Detect faces in the image.
        // MatOfRect is a special container class for Rect.
        MatOfRect faceDetections = new MatOfRect();
        faceDetector.detectMultiScale(image, faceDetections);

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

        // Draw a bounding box around each face.
        for (Rect rect : faceDetections.toArray()) {
            Core.rectangle(image, new Point(rect.x, rect.y), new Point(rect.x
                    + rect.width, rect.y + rect.height), new Scalar(0, 255, 0));
        }

        // Save the visualized detection.
        String filename = "faceDetection.png";
        System.out.println(String.format("Writing %s", filename));
        Highgui.imwrite(filename, image);
    }
}