删除不必要的包

fhKeeper/formulahousekeeper/management-crm/src/main/java/com/management/platform/util/ImageCompare.java

@@ -1,297 +0,0 @@
-package com.management.platform.util;
-
-import java.awt.HeadlessException;
-import java.awt.image.BufferedImage;
-import java.io.ByteArrayInputStream;
-import java.io.File;
-import java.io.FileInputStream;
-import java.io.IOException;
-import java.io.InputStream;
-import java.io.UnsupportedEncodingException;
-import java.util.ArrayList;
-import java.util.List;
-
-import javax.imageio.ImageIO;
-
-import org.opencv.core.*;
-import org.opencv.imgcodecs.Imgcodecs;
-import org.opencv.imgproc.Imgproc;
-import org.opencv.utils.Converters;
-
-public class ImageCompare {
-    static {
-        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
-        //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
-        //-Djava.library.path=$PROJECT_DIR$\opencv\x64
-    }
-    private boolean compareResult = false;
-    private String mark = "_compareResult";
-    /**
-     * 通过两张图对比，判断是否是游戏电影类型
-     * @param imagePath1 图片1的路径
-     * @param imagePath2 图片2的路径
-     */
-    public boolean isMoviePlay(String imagePath1, String imagePath2)
-    {
-        Mat mat1 = readMat(imagePath1);
-        Mat mat2 = readMat(imagePath2);
-        mat1 = Imgcodecs.imdecode(mat1, Imgcodecs.IMREAD_UNCHANGED);
-        mat2 = Imgcodecs.imdecode(mat2, Imgcodecs.IMREAD_UNCHANGED);
-        if(mat1.cols() == 0 || mat2.cols() == 0 || mat1.rows() == 0 || mat2.rows() == 0)
-        {
-            System.out.println("图片文件路径异常，获取的图片大小为0，无法读取");
-            return false;
-        }
-        if(mat1.cols() != mat2.cols() || mat1.rows() != mat2.rows())
-        {
-            System.out.println("两张图片大小不同，无法比较");
-            return false;
-        }
-        mat1.convertTo(mat1, CvType.CV_8UC1);
-        mat2.convertTo(mat2, CvType.CV_8UC1);
-        Mat mat1_gray = new Mat();
-        Imgproc.cvtColor(mat1, mat1_gray, Imgproc.COLOR_BGR2GRAY);
-        Mat mat2_gray = new Mat();
-        Imgproc.cvtColor(mat2, mat2_gray, Imgproc.COLOR_BGR2GRAY);
-        mat1_gray.convertTo(mat1_gray, CvType.CV_32F);
-        mat2_gray.convertTo(mat2_gray, CvType.CV_32F);
-        double result = Imgproc.compareHist(mat1_gray, mat2_gray, Imgproc.CV_COMP_CORREL);
-        if(result == 1)
-        {
-            return false;
-        }
-//        System.out.println("相似度数值为:"+result);
-        Mat mat_result = new Mat();
-        //计算两个灰度图的绝对差值，并输出到一个Mat对象中
-        Core.absdiff(mat1_gray, mat2_gray, mat_result);
-        //将灰度图按照阈值进行绝对值化
-        mat_result.convertTo(mat_result, CvType.CV_8UC1);
-        List<MatOfPoint> mat2_list = new ArrayList<MatOfPoint>();
-        Mat mat2_hi = new Mat();
-        //寻找轮廓图
-        Imgproc.findContours(mat_result, mat2_list, mat2_hi, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
-        Mat mat_result1 = mat1;
-        Mat mat_result2 = mat2;
-        //使用红色标记不同点
-        System.out.println(mat2_list.size());
-        List<Point> allPoints = new ArrayList<Point>();
-        //按照目标区域的面积大小， 长宽不低于480*480
-        Point leftTop = null;
-        Point rightTop = null;
-        Point leftBottom = null;
-        Point rightBottom = null;
-        for (MatOfPoint matOfPoint : mat2_list)
-        {
-            Rect rect = Imgproc.boundingRect(matOfPoint);
-            if ((rect.width >= 640 && rect.height >= 480) || (rect.width >= 480 && rect.height >= 640)) {
-//                System.out.println("位置==["+rect.x +","+ rect.y+"]， 大小=" +rect.width+"x"+rect.height+", 包含点=" + matOfPoint.toList().size());
-                Imgproc.rectangle(mat_result1, rect.tl(), rect.br(), new Scalar(0, 0, 255),2);
-                Imgproc.rectangle(mat_result2, rect.tl(), rect.br(), new Scalar(0, 0, 255),2);
-                allPoints = matOfPoint.toList();
-                leftTop = new Point(rect.x, rect.y);
-                rightTop = new Point(rect.x + rect.width -1, rect.y);
-                leftBottom = new Point(rect.x, rect.y + rect.height -1);
-                rightBottom = new Point(rect.x + rect.width -1, rect.y + rect.height -1);
-                break;
-            }
-        }
-        for (Point p : allPoints) {
-            Imgproc.drawMarker(mat_result1, p, new Scalar(0, 255, 0),2);
-        }
-        //找到四个顶点
-        System.out.println("allPoints size=="+allPoints.size());
-        if (allPoints.size() == 0) {
-            return false;
-        }
-        System.out.println(leftTop);
-        System.out.println(rightTop);
-        System.out.println(leftBottom);
-        System.out.println(rightBottom);
-        //统计在矩形边上的点数量
-        int hitCount = 0;
-        for (Point p : allPoints) {
-            if ((Math.abs(p.x - leftTop.x) <= 6 || Math.abs(p.y - leftTop.y) <= 6)
-                    || (Math.abs(p.x - rightBottom.x) <= 6 || Math.abs(p.y - rightBottom.y) <= 6)) {
-                hitCount++;
-            }
-        }
-        System.out.println("hitCount="+hitCount+", percent="+(100*hitCount/allPoints.size())+"%");
-        int percent = (100*hitCount/allPoints.size());
-        //分析占比
-        if (percent > 80) {
-            return true;//
-        } else {
-            return false;
-        }
-    }
-
-    private void writeImage(Mat mat, String outPutFile)
-    {
-        MatOfByte matOfByte = new MatOfByte();
-        Imgcodecs.imencode(".png", mat, matOfByte);
-        byte[] byteArray = matOfByte.toArray();
-        BufferedImage bufImage = null;
-        try {
-            InputStream in = new ByteArrayInputStream(byteArray);
-            bufImage = ImageIO.read(in);
-            ImageIO.write(bufImage, "png", new File(outPutFile));
-        } catch (IOException | HeadlessException e)
-        {
-            e.printStackTrace();
-        }
-    }
-
-    private String getFileName(String filePath)
-    {
-        File f = new File(filePath);
-        return f.getName();
-    }
-
-    private String getParentDir(String filePath)
-    {
-        File f = new File(filePath);
-        return f.getParent();
-    }
-
-    private Mat readMat(String filePath)
-    {
-        try {
-            File file = new File(filePath);
-            FileInputStream inputStream = new FileInputStream(filePath);
-            byte[] byt = new byte[(int) file.length()];
-            int read = inputStream.read(byt);
-            List<Byte> bs = convert(byt);
-            Mat mat1 = Converters.vector_char_to_Mat(bs);
-            return mat1;
-        } catch (UnsupportedEncodingException e) {
-            e.printStackTrace();
-        } catch (IOException e) {
-            e.printStackTrace();
-        }
-        return new Mat();
-    }
-
-    private List<Byte> convert(byte[] byt)
-    {
-        List<Byte> bs = new ArrayList<Byte>();
-        for (int i = 0; i < byt.length; i++)
-        {
-            bs.add(i, byt[i]);
-        }
-        return bs;
-    }
-
-    public boolean test(String imagePath1, String imagePath2)
-    {
-        Mat mat1 = readMat(imagePath1);
-        Mat mat2 = readMat(imagePath2);
-        mat1 = Imgcodecs.imdecode(mat1, Imgcodecs.IMREAD_UNCHANGED);
-        mat2 = Imgcodecs.imdecode(mat2, Imgcodecs.IMREAD_UNCHANGED);
-        /*Mat mat1 = Imgcodecs.imread(imagePath1, Imgcodecs.IMREAD_UNCHANGED);
-        Mat mat2 = Imgcodecs.imread(imagePath2, Imgcodecs.IMREAD_UNCHANGED);*/
-        if(mat1.cols() == 0 || mat2.cols() == 0 || mat1.rows() == 0 || mat2.rows() == 0)
-        {
-            System.out.println("图片文件路径异常，获取的图片大小为0，无法读取");
-            return false;
-        }
-        if(mat1.cols() != mat2.cols() || mat1.rows() != mat2.rows())
-        {
-            System.out.println("两张图片大小不同，无法比较");
-            return false;
-        }
-        mat1.convertTo(mat1, CvType.CV_8UC1);
-        mat2.convertTo(mat2, CvType.CV_8UC1);
-        Mat mat1_gray = new Mat();
-        Imgproc.cvtColor(mat1, mat1_gray, Imgproc.COLOR_BGR2GRAY);
-        Mat mat2_gray = new Mat();
-        Imgproc.cvtColor(mat2, mat2_gray, Imgproc.COLOR_BGR2GRAY);
-        mat1_gray.convertTo(mat1_gray, CvType.CV_32F);
-        mat2_gray.convertTo(mat2_gray, CvType.CV_32F);
-        double result = Imgproc.compareHist(mat1_gray, mat2_gray, Imgproc.CV_COMP_CORREL);
-        if(result == 1)
-        {
-            compareResult = true;//此处结果为1则为完全相同
-            return false;
-        }
-        System.out.println("相似度数值为:"+result);
-        Mat mat_result = new Mat();
-        //计算两个灰度图的绝对差值，并输出到一个Mat对象中
-        Core.absdiff(mat1_gray, mat2_gray, mat_result);
-        //将灰度图按照阈值进行绝对值化
-        mat_result.convertTo(mat_result, CvType.CV_8UC1);
-        List<MatOfPoint> mat2_list = new ArrayList<MatOfPoint>();
-        Mat mat2_hi = new Mat();
-        //寻找轮廓图
-        Imgproc.findContours(mat_result, mat2_list, mat2_hi, Imgproc.RETR_EXTERNAL, Imgproc.CHAIN_APPROX_SIMPLE);
-        Mat mat_result1 = mat1;
-        Mat mat_result2 = mat2;
-        //使用红色标记不同点
-        System.out.println(mat2_list.size());
-        List<Point> allPoints = new ArrayList<Point>();
-        //按照目标区域的面积大小， 长宽不低于480*480
-        Point leftTop = null;
-        Point rightTop = null;
-        Point leftBottom = null;
-        Point rightBottom = null;
-        for (MatOfPoint matOfPoint : mat2_list)
-        {
-            Rect rect = Imgproc.boundingRect(matOfPoint);
-            if (rect.width >= 280 && rect.height >= 280) {
-                System.out.println("位置==["+rect.x +","+ rect.y+"]， 大小=" +rect.width+"x"+rect.height+", 包含点=" + matOfPoint.toList().size());
-                Imgproc.rectangle(mat_result1, rect.tl(), rect.br(), new Scalar(0, 0, 255),2);
-                Imgproc.rectangle(mat_result2, rect.tl(), rect.br(), new Scalar(0, 0, 255),2);
-                allPoints = matOfPoint.toList();
-                leftTop = new Point(rect.x, rect.y);
-                rightTop = new Point(rect.x + rect.width -1, rect.y);
-                leftBottom = new Point(rect.x, rect.y + rect.height -1);
-                rightBottom = new Point(rect.x + rect.width -1, rect.y + rect.height -1);
-                break;
-            }
-        }
-        for (Point p : allPoints) {
-            Imgproc.drawMarker(mat_result1, p, new Scalar(0, 255, 0),2);
-        }
-        String fileName1 = getFileName(imagePath1);
-        String targetPath1 = getParentDir(imagePath2)+File.separator+fileName1.replace(".", mark+".");
-        String fileName2 = getFileName(imagePath2);
-        String targetPath2 = getParentDir(imagePath2)+File.separator+fileName2.replace(".", mark+".");
-        System.out.println(targetPath1);
-        System.out.println(targetPath2);
-        writeImage(mat_result1, targetPath1);
-        writeImage(mat_result2, targetPath2);
-        //找到四个顶点
-        System.out.println("allPoints size=="+allPoints.size());
-        System.out.println(leftTop);
-        System.out.println(rightTop);
-        System.out.println(leftBottom);
-        System.out.println(rightBottom);
-        //检测其他点，是否都在矩形边上
-        int hitCount = 0;
-        for (Point p : allPoints) {
-            if ((Math.abs(p.x - leftTop.x) <= 6 || Math.abs(p.y - leftTop.y) <= 6)
-                    || (Math.abs(p.x - rightBottom.x) <= 6 || Math.abs(p.y - rightBottom.y) <= 6)) {
-                hitCount++;
-            } else {
-//                System.out.println("失效点："+p.x + "," + p.y);
-            }
-        }
-        System.out.println("hitCount="+hitCount+", percent="+(100*hitCount/allPoints.size())+"%");
-        int percent = (100*hitCount/allPoints.size());
-
-        if (percent > 80) {
-            return true;//
-        } else {
-            return false;
-        }
-    }
-
-    public static void main(String[] args) {
-        String img1 = "C:\\Users\\seya\\Desktop\\e.jpg";
-        String img2 = "C:\\Users\\seya\\Desktop\\d.jpg";
-        ImageCompare ip = new ImageCompare();
-        System.out.println("是电影娱乐吗？"+ip.test(img1, img2));
-    }
-
-
-}
-

fhKeeper/formulahousekeeper/management-crm/src/main/java/com/management/platform/util/ImageReconizeUtil.java

@@ -1,129 +0,0 @@
-package com.management.platform.util;
-
-import org.opencv.core.*;
-import org.opencv.features2d.ORB;
-import org.opencv.highgui.HighGui;
-import org.opencv.imgcodecs.Imgcodecs;
-import org.opencv.imgproc.Imgproc;
-
-import javax.imageio.ImageIO;
-import java.awt.image.BufferedImage;
-import java.io.File;
-import java.io.IOException;
-
-import static java.lang.Math.E;
-import static org.opencv.imgproc.Imgproc.*;
-
-public class ImageReconizeUtil {
-//    public static final double YUZHI_HIGH = 2*Math.pow(0.1, 11);
-//    public static final double YUZHI_NORMAL = 1*Math.pow(0.1, 10);
-    public static final double YUZHI = 0.89;
-    static {
-        System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
-        //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
-        //-Djava.library.path=$PROJECT_DIR$\opencv\x64
-    }
-    public static void main(String[] args) {
-        boolean match = isWholeTemplateMatch("C:\\Users\\seya\\Desktop\\wjw.jpg",
-                "C:\\picrecongnize\\im\\wechat.jpg");
-
-    }
-
-    public static boolean isTemplateMatch(String sourcePic, String targetPic) {
-        double matchVal = templete(TM_CCOEFF_NORMED, sourcePic, targetPic,true);
-        if (matchVal >= YUZHI) {
-            System.out.println("找到啦");
-            return true;
-        } else {
-            System.out.println("没匹配上");
-            return false;
-        }
-    }
-
-    public static boolean isWholeTemplateMatch(String sourcePic, String targetPic) {
-        double matchVal = templete(Imgproc.TM_CCOEFF_NORMED, sourcePic, targetPic, false);
-        if (matchVal >= YUZHI) {
-            System.out.println("找到啦"+targetPic);
-            return true;
-        } else {
-            System.out.println("没匹配上");
-            return false;
-        }
-    }
-
-    /**
-     * OpenCV-4.1.0 模板匹配
-     * <table border="1" cellpadding="8">
-     * <tr><th>输入参数</th><th>参数解释</th></tr>
-     * <tr><td align="left">TM_SQDIFF是平方差匹配、TM_SQDIFF_NORMED是标准平方差匹配</td><td>利用平方差来进行匹配,最好匹配为0.匹配越差,匹配值越大。</td></tr>
-     * <tr><td align="left">TM_CCORR是相关性匹配、TM_CCORR_NORMED是标准相关性匹配</td><td>采用模板和图像间的乘法操作,数越大表示匹配程度较高, 0表示最坏的匹配效果。</td></tr>
-     * <tr><td align="left">TM_CCOEFF是相关性系数匹配、TM_CCOEFF_NORMED是标准相关性系数匹配</td><td>将模版对其均值的相对值与图像对其均值的相关值进行匹配,1表示完美匹配,-1表示糟糕的匹配,0表示没有任何相关性(随机序列)。</td></tr>
-     * <tr><td colspan="2">随着从简单的测量(平方差)到更复杂的测量(相关系数),我们可获得越来越准确的匹配(同时也意味着越来越大的计算代价)。</td></tr>
-     * <tr><td colspan="2">相关性是越接近1越大越好，平方差是越小越好，所以TM_SQDIFF在使用时和其他的是有所区别的。</td></tr>
-     * <tr><td colspan="2">模板匹配结果Mat要是32位的。</td></tr>
-     * </table>
-     * @return: void
-     * @date: 2019年5月7日12:16:55
-     */
-    public static double templete(int method, String inFile, String templateFile, boolean cutMatch) {
-        // 1 获取待匹配图片
-//        System.out.println("sourcePic="+sourcePic+", targetPic="+targetPic);
-        Mat srcMat = Imgcodecs.imread(inFile);
-        if (cutMatch) {
-            //先裁减，左上角1/4的截图，提高比对速度。
-            Rect rect = new Rect(0,0,srcMat.width()/4, srcMat.height()/4);
-            Mat subMat = new Mat(srcMat, rect);
-            subMat.copyTo(srcMat);
-        }
-
-        //将rgb灰化处理
-//        Imgproc.cvtColor(templete, templete,Imgproc.COLOR_BGR2GRAY);
-//
-        // 2 获取匹配模板
-        Mat demo = Imgcodecs.imread(templateFile);
-//        Imgproc.cvtColor(demo, demo,Imgproc.COLOR_BGR2GRAY);
-
-        Core.MinMaxLocResult mmr = getLocResult(method, srcMat, demo);
-        // 7 绘制匹配到的结果
-        double x,y;
-        double matchVal = 0;
-        if (method==Imgproc.TM_SQDIFF_NORMED || method==Imgproc.TM_SQDIFF) {
-            x = mmr.minLoc.x;
-            y = mmr.minLoc.y;
-            matchVal = mmr.minVal;
-        } else {
-            x = mmr.maxLoc.x;
-            y = mmr.maxLoc.y;
-            matchVal = mmr.maxVal;
-        }
-
-        System.out.println("匹配度=="+matchVal+", target="+templateFile.substring(templateFile.lastIndexOf(File.separator)-10)+", inFile="+inFile.substring(inFile.lastIndexOf(File.separator)));
-        System.out.println("x="+x+", y=" + y);
-        //我们匹配的图像在左上角，考虑到用户可能拖动窗口，但是不应该偏差很大。 这里增加判断标准：坐标处在左上方。
-
-//        if (matchVal >= YUZHI) {
-//            Imgproc.rectangle(srcMat,new Point(x,y),new Point(x+demo.cols(),y+demo.rows()),new Scalar( 0, 0, 255),2,Imgproc.LINE_AA);
-//            Imgproc.putText(srcMat,"Match Success",new Point(x,y),Imgproc.FONT_HERSHEY_SCRIPT_COMPLEX, 1.0, new Scalar(0, 255, 0),1,Imgproc.LINE_AA);
-//            // 8 显示结果
-//            HighGui.imshow("模板匹配", srcMat);
-//            HighGui.waitKey(0);
-//        }
-
-        return matchVal;
-    }
-
-    private static Core.MinMaxLocResult getLocResult(int method, Mat templete, Mat demo) {
-        int width=templete.cols()-demo.cols()+1;
-        int height=templete.rows()-demo.rows()+1;
-        // 3 创建32位模板匹配结果Mat
-        Mat result=new Mat(width,height,CvType.CV_32FC1);
-        // 4 调用 模板匹配函数
-        Imgproc.matchTemplate(templete, demo, result, method);
-        // 5 归一化
-//        Core.normalize(result, result,0, 1, Core.NORM_MINMAX, -1, new Mat());
-        // 6 获取模板匹配结果
-        Core.MinMaxLocResult mmr = Core.minMaxLoc(result);
-        return mmr;
-    }
-
-}