基于虹软的java 实现的人脸追踪代码

以下是基于虹软 SDK 实现的 Java 人脸追踪代码示例：

import com.arcsoft.face.*;
import com.arcsoft.face.enums.ImageFormat;
import com.arcsoft.face.enums.RotateDegree;
import java.awt.image.BufferedImage;
import java.io.ByteArrayOutputStream;
import java.io.File;
import java.io.IOException;
import javax.imageio.ImageIO;

public class FaceTracker {
    // SDK 配置信息
    private static final String APP_ID = "YOUR_APP_ID";
    private static final String SDK_KEY = "YOUR_SDK_KEY";
    private static final int MAX_FACE_NUM = 10;
    private static final int IMAGE_WIDTH = 640;
    private static final int IMAGE_HEIGHT = 480;

    public static void main(String[] args) {
        // 初始化引擎
        FaceEngine faceEngine = new FaceEngine(APP_ID, SDK_KEY);
        int errorCode = faceEngine.init(FaceEngine.ASF_DETECT_MODE_VIDEO, FaceEngine.ASF_OP_0_ONLY, 16,
                MAX_FACE_NUM, FaceEngine.ASF_FACE_DETECT | FaceEngine.ASF_FACE_RECOGNITION);
        if (errorCode != ErrorInfo.MOK) {
            System.out.println("引擎初始化失败，错误码：" + errorCode);
            return;
        }

        // 读取视频文件
        File videoFile = new File("video.mp4");
        FFmpegFrameGrabber grabber = new FFmpegFrameGrabber(videoFile);
        grabber.setOption("video_size", IMAGE_WIDTH + "x" + IMAGE_HEIGHT);
        try {
            grabber.start();
        } catch (Exception e) {
            e.printStackTrace();
            return;
        }

        // 循环读取视频帧并进行人脸追踪
        Java2DFrameConverter converter = new Java2DFrameConverter();
        BufferedImage image = null;
        ByteArrayOutputStream out = new ByteArrayOutputStream();
        while (true) {
            try {
                avcodec.AVPacket packet = grabber.grabPacket();
                if (packet == null) {
                    break;
                }
                if (packet.stream_index() != grabber.getVideoStream()) {
                    continue;
                }
                image = converter.convert(grabber.grabImage());
                ImageIO.write(image, "JPEG", out);
                byte[] imageData = out.toByteArray();
                ImageInfo imageInfo = new ImageInfo();
                imageInfo.setWidth(IMAGE_WIDTH);
                imageInfo.setHeight(IMAGE_HEIGHT);
                imageInfo.setImageFormat(ImageFormat.CP_JPEG);
                imageInfo.setImageData(imageData);

                // 进行人脸检测
                FaceInfo[] faceInfos = new FaceInfo[MAX_FACE_NUM];
                errorCode = faceEngine.detectFaces(imageData, IMAGE_WIDTH, IMAGE_HEIGHT, ImageFormat.CP_JPEG, faceInfos);
                if (errorCode != ErrorInfo.MOK) {
                    System.out.println("人脸检测失败，错误码：" + errorCode);
                    continue;
                }

                // 绘制人脸框
                for (FaceInfo faceInfo : faceInfos) {
                    if (faceInfo.getRect().width == 0 || faceInfo.getRect().height == 0) {
                        continue;
                    }
                    // 计算人脸框位置
                    int left = faceInfo.getRect().left;
                    int top = faceInfo.getRect().top;
                    int right = faceInfo.getRect().right;
                    int bottom = faceInfo.getRect().bottom;
                    // 绘制人脸框
                    Graphics2D g2d = image.createGraphics();
                    g2d.setColor(Color.RED);
                    g2d.drawRect(left, top, right - left, bottom - top);
                    g2d.dispose();
                }

                // 显示视频帧
                JFrame frame = new JFrame();
                frame.getContentPane().setLayout(new BorderLayout());
                frame.getContentPane().add(new JLabel(new ImageIcon(image)));
                frame.pack();
                frame.setVisible(true);
            } catch (IOException e) {
                e.printStackTrace();
            }
        }

        // 释放资源
        try {
            grabber.stop();
        } catch (Exception e) {
            e.printStackTrace();
        }
        faceEngine.unInit();
    }
}

本示例代码使用虹软 SDK 进行人脸检测和识别，可以读取视频文件并进行实时的人脸追踪，并在视频帧中绘制人脸框。