【视频】口罩识别

一、实现思路

• 打开本地摄像头
• 遍历每一个图像帧检查出人脸
• 对人脸进行灰度化
• 戴白色面具的人，大多数时候Opencv 无法正确识别人脸，为克服这个困难，使用“阈值”函数转换黑白图像
• 检测出每一个人脸上是否有嘴，或者鼻子
• 如果检测出嘴，则没有带口罩，如果没有检测出嘴，则带了口罩或者面具，面纱遮挡等

二、完整代码

package com.biubiu.example;
import org.opencv.core.Point;
import org.opencv.core.*;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
import org.opencv.videoio.VideoCapture;
import javax.imageio.ImageIO;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.ByteArrayInputStream;
import java.io.InputStream;
import static org.opencv.imgproc.Imgproc.threshold;
/**
 * @author ：张音乐
 * @date ：Created in 2021/10/23 下午2:41
 * @description：口罩检测
 * @email: zhangyule1993@sina.com
 * @version:
 */
public class MasksDetect {
    static {
        // 加载 动态链接库
        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
    }
    public static void main(String[] args) {
        VideoCapture camera = new VideoCapture();
        // 参数0表示，获取第一个摄像头。
        camera.open(0);
        // 图像帧
        Mat frame = new Mat();
        for(;;) {
            camera.read(frame);
            draw(frame);
            // 等待用户按esc停止检测
            if(HighGui.waitKey(100) == 100) {
                break;
            }
        }
        // 释放摄像头
        camera.release();
        // 释放窗口资源
        HighGui.destroyAllWindows();
    }
    /**
     * 逐帧处理
     * @param frame
     */
    private static void draw(Mat frame) {
        Mat grayFrame = new Mat();
        Imgproc.cvtColor(frame, grayFrame, Imgproc.COLOR_BGR2GRAY);
        Mat thresh = new Mat();
        // 戴白色面具的人，大多数时候 OpenCV 无法正确识别人脸。为了克服这个困难，使用“阈值”函数转换黑白图像
        // 根据相机和周围光线在80 到 105 “阈值”范围内调整阈值 (bw_threshold) 值很重要。
        threshold(grayFrame, thresh, 80, 255,  Imgproc.THRESH_BINARY | Imgproc.THRESH_OTSU);
        // OpenCv人脸识别分类器
        CascadeClassifier faceClassifier = new CascadeClassifier("/usr/local/share/OpenCV/haarcascades/haarcascade_frontalface_default.xml");
        // 图像缩放比例,可以理解为相机的X倍镜
        double scaleFactor = 1.1;
        // 对特征检测点周边多少有效检测点同时检测,这样可以避免选取的特征检测点大小而导致遗漏
        int minNeighbors = 4;
        // 用来存放人脸矩形
        MatOfRect faceRect = new MatOfRect();
        // 执行人脸检测 “灰色”图像
        faceClassifier.detectMultiScale(grayFrame, faceRect, scaleFactor, minNeighbors);
        // 用来存放人脸矩形
        MatOfRect faceRect1 = new MatOfRect();
        // 执行人脸检测 “黑白”图像
        faceClassifier.detectMultiScale(thresh, faceRect1, scaleFactor, minNeighbors);
        // OpenCv人脸识别分类器
        CascadeClassifier mouthClassifier = new CascadeClassifier("/usr/local/share/OpenCV/haarcascades/haarcascade_mcs_mouth.xml");
        Scalar color = new Scalar(0, 0, 255);
        // 遍历每一个图像帧上的每一张人脸
        for(Rect rect: faceRect.toArray()) {
            int x = rect.x;
            int y = rect.y;
            int w = rect.width;
            int h = rect.height;
            // 框出人脸
            Imgproc.rectangle(frame, new Point(x, y), new Point(x + h, y + w), color, 2);
            // 用来存放嘴矩形
            MatOfRect mouseRects = new MatOfRect();
            mouthClassifier.detectMultiScale(grayFrame, mouseRects, 1.5, 5);
            if(mouseRects.toArray().length == 0) {
                frame = putChineseTxt(frame, "有口罩/遮挡面具", x + w / 2 - 5, y - 10);
            }
        }
        HighGui.imshow("预览", frame);
    }
    /**
     * Mat二维矩阵转Image
     * @param matrix
     * @param fileExtension
     * @return
     */
    public static BufferedImage matToImg(Mat matrix, String fileExtension) {
        // convert the matrix into a matrix of bytes appropriate for
        // this file extension
        MatOfByte mob = new MatOfByte();
        Imgcodecs.imencode(fileExtension, matrix, mob);
        // convert the "matrix of bytes" into a byte array
        byte[] byteArray = mob.toArray();
        BufferedImage bufImage = null;
        try {
            InputStream in = new ByteArrayInputStream(byteArray);
            bufImage = ImageIO.read(in);
        } catch (Exception e) {
            e.printStackTrace();
        }
        return bufImage;
    }
    /**
     * BufferedImage转换成 Mat
     * @param original
     * @param imgType
     * @param matType
     * @return
     */
    public static Mat imgToMat(BufferedImage original, int imgType, int matType) {
        if (original == null) {
            throw new IllegalArgumentException("original == null");
        }
        if (original.getType() != imgType){
            // Create a buffered image
            BufferedImage image = new BufferedImage(original.getWidth(), original.getHeight(), imgType);
            // Draw the image onto the new buffer
            Graphics2D g = image.createGraphics();
            try {
                g.setComposite(AlphaComposite.Src);
                g.drawImage(original, 0, 0, null);
            } finally {
                g.dispose();
            }
        }
        byte[] pixels = ((DataBufferByte) original.getRaster().getDataBuffer()).getData();
        Mat mat = Mat.eye(original.getHeight(), original.getWidth(), matType);
        mat.put(0, 0, pixels);
        return mat;
    }
    /**
     * 在图片上显示中文
     * @param img
     * @param text
     * @param x
     * @param y
     * @return
     */
    private static Mat putChineseTxt(Mat img, String text, int x, int y) {
        Font font = new Font("微软雅黑", Font.PLAIN, 20);
        BufferedImage bufImg = matToImg(img,".png");
        Graphics2D g = bufImg.createGraphics();
        g.drawImage(bufImg, 0, 0, bufImg.getWidth(), bufImg.getHeight(), null);
        // 设置字体
        g.setColor(new Color(255, 10, 52));
        g.setFont(font);
        // 设置水印的坐标
        g.drawString(text, x, y);
        g.dispose();
        // 加完水印再转换回来
        return imgToMat(bufImg, BufferedImage.TYPE_3BYTE_BGR, CvType.CV_8UC3);
    }
}