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@@ -0,0 +1,296 @@
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+package com.management.platform.util;
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+
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+import java.awt.HeadlessException;
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+import java.awt.image.BufferedImage;
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+import java.io.ByteArrayInputStream;
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+import java.io.File;
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+import java.io.FileInputStream;
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+import java.io.IOException;
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+import java.io.InputStream;
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+import java.io.UnsupportedEncodingException;
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+import java.util.ArrayList;
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+import java.util.List;
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+
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+import javax.imageio.ImageIO;
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+
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+import org.opencv.core.*;
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+import org.opencv.imgcodecs.Imgcodecs;
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+import org.opencv.imgproc.Imgproc;
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+import org.opencv.utils.Converters;
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+
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+public class ImageCompare {
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+ static {
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+ System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
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+ //注意程序运行的时候需要在VM option添加该行 指明opencv的dll文件所在路径
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+ //-Djava.library.path=$PROJECT_DIR$\opencv\x64
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+ }
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+ private boolean compareResult = false;
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+ private String mark = "_compareResult";
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+ /**
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+ * 通过两张图对比，判断是否是游戏电影类型
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+ * @param imagePath1 图片1的路径
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+ * @param imagePath2 图片2的路径
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+ */
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+ public boolean isMoviePlay(String imagePath1, String imagePath2)
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+ {
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+ Mat mat1 = readMat(imagePath1);
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+ Mat mat2 = readMat(imagePath2);
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+ mat1 = Imgcodecs.imdecode(mat1, Imgcodecs.IMREAD_UNCHANGED);
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+ mat2 = Imgcodecs.imdecode(mat2, Imgcodecs.IMREAD_UNCHANGED);
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+ if(mat1.cols() == 0 || mat2.cols() == 0 || mat1.rows() == 0 || mat2.rows() == 0)
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+ {
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+ System.out.println("图片文件路径异常，获取的图片大小为0，无法读取");
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+ return false;
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+ }
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+ if(mat1.cols() != mat2.cols() || mat1.rows() != mat2.rows())
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+ {
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+ System.out.println("两张图片大小不同，无法比较");
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+ return false;
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+ }
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+ mat1.convertTo(mat1, CvType.CV_8UC1);
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+ mat2.convertTo(mat2, CvType.CV_8UC1);
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+ Mat mat1_gray = new Mat();
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+ Imgproc.cvtColor(mat1, mat1_gray, Imgproc.COLOR_BGR2GRAY);
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+ Mat mat2_gray = new Mat();
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+ Imgproc.cvtColor(mat2, mat2_gray, Imgproc.COLOR_BGR2GRAY);
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+ mat1_gray.convertTo(mat1_gray, CvType.CV_32F);
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+ mat2_gray.convertTo(mat2_gray, CvType.CV_32F);
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+ double result = Imgproc.compareHist(mat1_gray, mat2_gray, Imgproc.CV_COMP_CORREL);
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+ if(result == 1)
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+ {
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+ return false;
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+ }
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+// System.out.println("相似度数值为:"+result);
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+ Mat mat_result = new Mat();
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+ //计算两个灰度图的绝对差值，并输出到一个Mat对象中
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+ Core.absdiff(mat1_gray, mat2_gray, mat_result);
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+ //将灰度图按照阈值进行绝对值化
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+ mat_result.convertTo(mat_result, CvType.CV_8UC1);
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+ List<MatOfPoint> mat2_list = new ArrayList<MatOfPoint>();
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+ Mat mat2_hi = new Mat();
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+ //寻找轮廓图
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+ Imgproc.findContours(mat_result, mat2_list, mat2_hi, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
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+ Mat mat_result1 = mat1;
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+ Mat mat_result2 = mat2;
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+ //使用红色标记不同点
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+ System.out.println(mat2_list.size());
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+ List<Point> allPoints = new ArrayList<Point>();
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+ //按照目标区域的面积大小， 长宽不低于480*480
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+ Point leftTop = null;
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+ Point rightTop = null;
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+ Point leftBottom = null;
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+ Point rightBottom = null;
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+ for (MatOfPoint matOfPoint : mat2_list)
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+ {
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+ Rect rect = Imgproc.boundingRect(matOfPoint);
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+ if (rect.width >= 280 && rect.height >= 280) {
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+// System.out.println("位置==["+rect.x +","+ rect.y+"]， 大小=" +rect.width+"x"+rect.height+", 包含点=" + matOfPoint.toList().size());
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+ Imgproc.rectangle(mat_result1, rect.tl(), rect.br(), new Scalar(0, 0, 255),2);
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+ Imgproc.rectangle(mat_result2, rect.tl(), rect.br(), new Scalar(0, 0, 255),2);
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+ allPoints = matOfPoint.toList();
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+ leftTop = new Point(rect.x, rect.y);
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+ rightTop = new Point(rect.x + rect.width -1, rect.y);
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+ leftBottom = new Point(rect.x, rect.y + rect.height -1);
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+ rightBottom = new Point(rect.x + rect.width -1, rect.y + rect.height -1);
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+ break;
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+ }
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+ }
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+ for (Point p : allPoints) {
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+ Imgproc.drawMarker(mat_result1, p, new Scalar(0, 255, 0),2);
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+ }
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+ //找到四个顶点
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+ System.out.println("allPoints size=="+allPoints.size());
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+ if (allPoints.size() == 0) {
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+ return false;
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+ }
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+ System.out.println(leftTop);
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+ System.out.println(rightTop);
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+ System.out.println(leftBottom);
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+ System.out.println(rightBottom);
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+ //统计在矩形边上的点数量
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+ int hitCount = 0;
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+ for (Point p : allPoints) {
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+ if ((Math.abs(p.x - leftTop.x) <= 6 || Math.abs(p.y - leftTop.y) <= 6)
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+ || (Math.abs(p.x - rightBottom.x) <= 6 || Math.abs(p.y - rightBottom.y) <= 6)) {
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+ hitCount++;
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+ }
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+ }
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+ System.out.println("hitCount="+hitCount+", percent="+(100*hitCount/allPoints.size())+"%");
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+ int percent = (100*hitCount/allPoints.size());
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+ //分析占比
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+ if (percent > 80) {
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+ return true;//
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+ } else {
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+ return false;
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+ }
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+ }
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+
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+ private void writeImage(Mat mat, String outPutFile)
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+ {
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+ MatOfByte matOfByte = new MatOfByte();
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+ Imgcodecs.imencode(".png", mat, matOfByte);
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+ byte[] byteArray = matOfByte.toArray();
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+ BufferedImage bufImage = null;
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+ try {
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+ InputStream in = new ByteArrayInputStream(byteArray);
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+ bufImage = ImageIO.read(in);
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+ ImageIO.write(bufImage, "png", new File(outPutFile));
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+ } catch (IOException | HeadlessException e)
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+ {
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+ e.printStackTrace();
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+ }
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+ }
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+
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+ private String getFileName(String filePath)
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+ {
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+ File f = new File(filePath);
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+ return f.getName();
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+ }
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+
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+ private String getParentDir(String filePath)
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+ {
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+ File f = new File(filePath);
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+ return f.getParent();
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+ }
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+
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+ private Mat readMat(String filePath)
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+ {
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+ try {
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+ File file = new File(filePath);
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+ FileInputStream inputStream = new FileInputStream(filePath);
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+ byte[] byt = new byte[(int) file.length()];
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+ int read = inputStream.read(byt);
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+ List<Byte> bs = convert(byt);
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+ Mat mat1 = Converters.vector_char_to_Mat(bs);
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+ return mat1;
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+ } catch (UnsupportedEncodingException e) {
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+ e.printStackTrace();
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+ } catch (IOException e) {
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+ e.printStackTrace();
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+ }
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+ return new Mat();
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+ }
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+
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+ private List<Byte> convert(byte[] byt)
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+ {
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+ List<Byte> bs = new ArrayList<Byte>();
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+ for (int i = 0; i < byt.length; i++)
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+ {
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+ bs.add(i, byt[i]);
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+ }
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+ return bs;
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+ }
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+
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+ public boolean test(String imagePath1, String imagePath2)
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+ {
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+ Mat mat1 = readMat(imagePath1);
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+ Mat mat2 = readMat(imagePath2);
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+ mat1 = Imgcodecs.imdecode(mat1, Imgcodecs.IMREAD_UNCHANGED);
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+ mat2 = Imgcodecs.imdecode(mat2, Imgcodecs.IMREAD_UNCHANGED);
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+ /*Mat mat1 = Imgcodecs.imread(imagePath1, Imgcodecs.IMREAD_UNCHANGED);
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+ Mat mat2 = Imgcodecs.imread(imagePath2, Imgcodecs.IMREAD_UNCHANGED);*/
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+ if(mat1.cols() == 0 || mat2.cols() == 0 || mat1.rows() == 0 || mat2.rows() == 0)
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+ {
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+ System.out.println("图片文件路径异常，获取的图片大小为0，无法读取");
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+ return false;
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+ }
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+ if(mat1.cols() != mat2.cols() || mat1.rows() != mat2.rows())
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+ {
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+ System.out.println("两张图片大小不同，无法比较");
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+ return false;
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+ }
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+ mat1.convertTo(mat1, CvType.CV_8UC1);
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+ mat2.convertTo(mat2, CvType.CV_8UC1);
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+ Mat mat1_gray = new Mat();
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+ Imgproc.cvtColor(mat1, mat1_gray, Imgproc.COLOR_BGR2GRAY);
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+ Mat mat2_gray = new Mat();
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+ Imgproc.cvtColor(mat2, mat2_gray, Imgproc.COLOR_BGR2GRAY);
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+ mat1_gray.convertTo(mat1_gray, CvType.CV_32F);
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+ mat2_gray.convertTo(mat2_gray, CvType.CV_32F);
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+ double result = Imgproc.compareHist(mat1_gray, mat2_gray, Imgproc.CV_COMP_CORREL);
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+ if(result == 1)
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+ {
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+ compareResult = true;//此处结果为1则为完全相同
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+ return false;
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+ }
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+ System.out.println("相似度数值为:"+result);
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+ Mat mat_result = new Mat();
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+ //计算两个灰度图的绝对差值，并输出到一个Mat对象中
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+ Core.absdiff(mat1_gray, mat2_gray, mat_result);
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+ //将灰度图按照阈值进行绝对值化
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+ mat_result.convertTo(mat_result, CvType.CV_8UC1);
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+ List<MatOfPoint> mat2_list = new ArrayList<MatOfPoint>();
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+ Mat mat2_hi = new Mat();
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+ //寻找轮廓图
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+ Imgproc.findContours(mat_result, mat2_list, mat2_hi, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
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+ Mat mat_result1 = mat1;
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+ Mat mat_result2 = mat2;
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+ //使用红色标记不同点
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+ System.out.println(mat2_list.size());
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+ List<Point> allPoints = new ArrayList<Point>();
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+ //按照目标区域的面积大小， 长宽不低于480*480
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+ Point leftTop = null;
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+ Point rightTop = null;
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+ Point leftBottom = null;
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+ Point rightBottom = null;
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+ for (MatOfPoint matOfPoint : mat2_list)
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+ {
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+ Rect rect = Imgproc.boundingRect(matOfPoint);
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+ if (rect.width >= 280 && rect.height >= 280) {
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+ System.out.println("位置==["+rect.x +","+ rect.y+"]， 大小=" +rect.width+"x"+rect.height+", 包含点=" + matOfPoint.toList().size());
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+ Imgproc.rectangle(mat_result1, rect.tl(), rect.br(), new Scalar(0, 0, 255),2);
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+ Imgproc.rectangle(mat_result2, rect.tl(), rect.br(), new Scalar(0, 0, 255),2);
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+ allPoints = matOfPoint.toList();
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+ leftTop = new Point(rect.x, rect.y);
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+ rightTop = new Point(rect.x + rect.width -1, rect.y);
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+ leftBottom = new Point(rect.x, rect.y + rect.height -1);
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+ rightBottom = new Point(rect.x + rect.width -1, rect.y + rect.height -1);
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+ break;
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+ }
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+ }
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+ for (Point p : allPoints) {
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+ Imgproc.drawMarker(mat_result1, p, new Scalar(0, 255, 0),2);
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+ }
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+ String fileName1 = getFileName(imagePath1);
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+ String targetPath1 = getParentDir(imagePath2)+File.separator+fileName1.replace(".", mark+".");
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+ String fileName2 = getFileName(imagePath2);
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+ String targetPath2 = getParentDir(imagePath2)+File.separator+fileName2.replace(".", mark+".");
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+ System.out.println(targetPath1);
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+ System.out.println(targetPath2);
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+ writeImage(mat_result1, targetPath1);
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+ writeImage(mat_result2, targetPath2);
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+ //找到四个顶点
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+ System.out.println("allPoints size=="+allPoints.size());
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+ System.out.println(leftTop);
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+ System.out.println(rightTop);
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+ System.out.println(leftBottom);
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+ System.out.println(rightBottom);
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+ //检测其他点，是否都在矩形边上
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+ int hitCount = 0;
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+ for (Point p : allPoints) {
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+ if ((Math.abs(p.x - leftTop.x) <= 6 || Math.abs(p.y - leftTop.y) <= 6)
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+ || (Math.abs(p.x - rightBottom.x) <= 6 || Math.abs(p.y - rightBottom.y) <= 6)) {
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+ hitCount++;
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+ } else {
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+// System.out.println("失效点："+p.x + "," + p.y);
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+ }
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+ }
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+ System.out.println("hitCount="+hitCount+", percent="+(100*hitCount/allPoints.size())+"%");
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+ int percent = (100*hitCount/allPoints.size());
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+
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+
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+ if (percent > 80) {
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+ return true;//
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+ } else {
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+ return false;
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+ }
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+ }
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+
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+ public static void main(String[] args) {
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+ String img1 = "C:\\Users\\seya\\Desktop\\m1.jpg";
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+ String img2 = "C:\\Users\\seya\\Desktop\\m2.jpg";
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+ ImageCompare ip = new ImageCompare();
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+ System.out.println("是电影娱乐吗？"+ip.test(img1, img2));
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+ }
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+}
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+
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