Springboot+OpenCV+Linux（libopencv

与SpringmvcSpring+OpenCV+Linux（libopencv_java460.so、opencv-460.jar）人脸识别、人脸对比实现_殷长庆的博客-CSDN博客

方式区别在于springboot是jar包方式启动的，

jarsoxml文件下载OpenCV+Linux（libopencv_java460.so、opencv-460.jar）-Java文档类资源-CSDN下载

opencv load无法读取jar包中的so文件，

1、在Linux某文件夹下提前预置so和xml这俩文件

2、springboot启动时候从jar包读取这两个文件生成到某文件夹下，在用load读取

在项目根目录下创建lib文件夹，把jar放进去

    com.opencv
    opencv_java460
    1
    system
    ${basedir}/lib/opencv-460.jar

    
        org.springframework.boot
        spring-boot-maven-plugin
        
            true
            com.opencv.MainApplication
        
        
            
                
                    repackage
                
            
        
    

在src/main/resources下创建opencv文件夹，把so、xml文件放进去

启动时会在Linux中创建/opencv文件夹，并把so、xml文件创建到文件夹下，再次启动时会先检查文件是否存在，存在则直接load

import java.io.BufferedInputStream;
import java.io.BufferedOutputStream;
import java.io.File;
import java.io.FileOutputStream;
import java.io.InputStream;
import java.util.Arrays;

import javax.annotation.PostConstruct;

import org.opencv.core.Mat;
import org.opencv.core.MatOfFloat;
import org.opencv.core.MatOfInt;
import org.opencv.core.MatOfRect;
import org.opencv.core.Rect;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;
import org.opencv.objdetect.CascadeClassifier;
import org.springframework.core.io.ClassPathResource;
import org.springframework.stereotype.Controller;
import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.ResponseBody;


@Controller
public class FaceDetectorController {

	private CascadeClassifier faceDetector;

	@PostConstruct
	private void init() {
		try {
			String openCVDiv = "/opencv/";
			String openCVSo = openCVDiv + "libopencv_java460.so";
			String openCVXml = openCVDiv + "lbpcascade_frontalface.xml";
			File fileso = new File(openCVSo);
			if (null == fileso || !fileso.exists()) {
				File fileDiv = new File(openCVDiv);
				fileDiv.mkdirs();
				ClassPathResource cpr = new ClassPathResource(openCVSo);
				InputStream cprIn = cpr.getInputStream();
				copyFile(cprIn, fileso);
				ClassPathResource cprxml = new ClassPathResource(openCVXml);
				InputStream xmlIn = cprxml.getInputStream();
				File filexml = new File(openCVXml);
				copyFile(xmlIn, filexml);
			}
			System.load(openCVSo);
			faceDetector = new CascadeClassifier(openCVXml);
		} catch (Exception e) {
			e.printStackTrace();
		}
	}

	
	private void copyFile(InputStream input, File targetFile) throws Exception {
		BufferedInputStream inBuff = new BufferedInputStream(input);
		FileOutputStream output = new FileOutputStream(targetFile);
		BufferedOutputStream outBuff = new BufferedOutputStream(output);
		byte[] b = new byte[1024 * 5];
		int len;
		while ((len = inBuff.read(b)) != -1) {
			outBuff.write(b, 0, len);
		}
		outBuff.flush();
		inBuff.close();
		outBuff.close();
		output.close();
		input.close();
	}

	// 灰度化人脸
	private Mat conv_Mat(String img) {
		Mat image0 = Imgcodecs.imread(img);
		Mat image1 = new Mat();
		// 灰度化
		Imgproc.cvtColor(image0, image1, Imgproc.COLOR_BGR2GRAY);
		// 探测人脸
		MatOfRect faceDetections = new MatOfRect();
		faceDetector.detectMultiScale(image1, faceDetections);
		// rect中人脸图片的范围
		for (Rect rect : faceDetections.toArray()) {
			Mat face = new Mat(image1, rect);
			return face;
		}
		return null;
	}

	private double compare_image(String img_1, String img_2) {
		Mat mat_1 = conv_Mat(img_1);
		Mat mat_2 = conv_Mat(img_2);
		Mat hist_1 = new Mat();
		Mat hist_2 = new Mat();

		//颜色范围
		MatOfFloat ranges = new MatOfFloat(0f, 256f);
		//直方图大小， 越大匹配越精确 (越慢)
		MatOfInt histSize = new MatOfInt(10000000);

		Imgproc.calcHist(Arrays.asList(mat_1), new MatOfInt(0), new Mat(), hist_1, histSize, ranges);
		Imgproc.calcHist(Arrays.asList(mat_2), new MatOfInt(0), new Mat(), hist_2, histSize, ranges);

		// CORREL 相关系数
		return Imgproc.compareHist(hist_1, hist_2, Imgproc.CV_COMP_CORREL);
	}

	
	@RequestMapping("faceDetector")
	@ResponseBody
	public String faceDetector() {
		try {
			//图片路径不能包含中文
			double compareHist = compare_image("/home/opencv/1.jpg", "/home/opencv/2.jpg");
			if (compareHist > 0.6) {
				return "人脸对比成功";
			} else {
				return "人脸不匹配";
			}
		} catch (Exception e) {
			return "人脸对比失败";
		}
	}
}