语义分割数据集转物体检测

来源：互联网发布：python求最大公约数包编辑：程序博客网时间：2024/06/07 02:11

最近遇到如题的问题，语义分割数据集格式是原始图像、标注图像、色号与类别对应的标签。
java实现思路就是读入标注图像，将像素转为类别的二维矩阵，然后对二维矩阵进行同类别的连通域检测，将检测结果保存为ArrayList格式：label,point1(x1,y1),point2(x2,y2)
首先得到文件夹下所有的文件

File file=new File("data/img/");File[] tempList = file.listFiles();for (int filei = 0; filei < tempList.length; filei++) {    if (tempList[filei].isFile()) {    }}

读取文件，获取类别对应标签的hashmap，其中类别与色号用#隔开，由于opencv中无法显示中文，这里用数字代替。之后会有一个数字与类别的hashmap与此类似，不一一列出。

public Map Readtxt(String filename) throws Exception{    //读入标签文件，保存成hashmap的格式    Map labelmap = new HashMap();    File file = new File(filename);    FileReader fr = new FileReader(file);    BufferedReader bf = new BufferedReader(fr);    String line = " ";    int i = 1;    while ((line = bf.readLine()) !=null){        String label[] = line.split(" #");        //labelmap.put(label[1], label[0]);        labelmap.put(label[1], i);        i++;        }    bf.close();    return labelmap;    }

然后将图像像素保存为像素矩阵，有像素值的就用类别代替，没有的置零。

//获取图片的像素矩阵GetImagePixel gip = new GetImagePixel( );String colormap [][] = gip.getImagePixel("imgname");int[][] colorintmap = new int[colormap.length][colormap[0].length];for(int i=0;i<colormap.length;i++){    for(int j=0;j<colormap[i].length;j++){        if(labelmap.get(colormap[i][j])!=null){            colorintmap[i][j] = (int) ( labelmap.get(colormap[i][j]));}else{            colorintmap[i][j] = 0;        }    }}

//获取图像中所有像素点的值，返回String的二维数组public String[][] getImagePixel(String image)  throws Exception {    // TODO Auto-generated constructor stub    int[] rgb = new int[3];      File file = new File(image);      System.out.println(file.getName());    BufferedImage bi = null;      try {          bi = ImageIO.read(file);      } catch (Exception e) {          e.printStackTrace();      }      int width = bi.getWidth();      int height = bi.getHeight();      int minx = bi.getMinX();      int miny = bi.getMinY();      //System.out.println("width=" + width + ",height=" + height + ".");    //System.out.println("minx=" + minx + ",miniy=" + miny + ".");    String colormap[][] = new String[width][height];    for (int i = minx; i < width; i++) {        for (int j = miny; j < height; j++) {            int pixel = bi.getRGB(i, j); // 下面三行代码将一个数字转换为RGB数字            rgb[0] = (pixel & 0xff0000) >> 16;            rgb[1] = (pixel & 0xff00) >> 8;            rgb[2] = (pixel & 0xff);            Color pixelcolor = new Color( rgb[0],rgb[1],rgb[2]);            ToHexFromColor thfc = new ToHexFromColor();            String pixelcolorstring = thfc.toHexFromColor(pixelcolor);            colormap[i][j] = pixelcolorstring;            //System.out.println("i=" + i + ",j=" + j + ":(" + pixelcolorstring + ")");          }    }    return colormap;}

public class ToHexFromColor {    //将RGB转化为String的颜色格式    public String toHexFromColor(Color color){          String r,g,b;          StringBuilder su = new StringBuilder();          r = Integer.toHexString(color.getRed());          g = Integer.toHexString(color.getGreen());          b = Integer.toHexString(color.getBlue());          r = r.length() == 1 ? "0" + r : r;          g = g.length() ==1 ? "0" +g : g;          b = b.length() == 1 ? "0" + b : b;          r = r.toUpperCase();          g = g.toUpperCase();          b = b.toUpperCase();          //su.append("0xFF");          su.append(r);          su.append(g);          su.append(b);          //0xFF0000FF          return su.toString();      }

获取二维数组后，获取二维数组连通域

    public ArrayList getCount(int[][] A) {        int result = 0;        ArrayList arraylist = new ArrayList();        for (int i = 0; i < A.length; i++) {            for (int j = 0; j < A[0].length; j++) {                if (A[i][j] != 0) {                    int[] tmp = new int[5];                    result++;                    tmp = Search.bfs(A, i, j,A[i][j]);                    arraylist.add(tmp);                }            }        }        return arraylist;    }

public class Search {    static int dx[] = {0,0,1,-1};    static int dy[] = {1,-1,0,0};    public static void dfs(int[][] A,int i,int j, int tmp){        if(A.length<=0||A[0].length<=0){            return;        }        if(i<0||i>=A.length||j<0||j>=A[0].length||A[i][j]!=tmp){            return;        }        A[i][j]=0;        for(int t=0;t<4;t++){            dfs(A,i+dx[t],j+dy[t],tmp);        }    }    public static int[] bfs(int[][] A,int i,int j, int tmp){        int[] result = {0,0,0,0,0};        if(A.length<=0||A[0].length<=0){            return result;        }        Queue<Integer> queue = new LinkedList<Integer>();        result[0] = tmp;        result[1] = i;        result[2] = j;        result[3] = i;        result[4] = j;        int tp = i*A[0].length+j;        queue.add(tp);        while(!queue.isEmpty()){            tp = queue.poll();            //System.out.println(queue.size());            int nowx = tp/A[0].length;            int nowy = tp%A[0].length;            if(nowx<0||nowx>=A.length||nowy<0||nowy>=A[0].length||A[nowx][nowy]!=tmp){                continue;            }            if(nowx<result[1]){result[1]=nowx;}            if(nowy<result[2]){result[2]=nowy;}            if(nowx>result[3]){result[3]=nowx;}            if(nowy>result[4]){result[4]=nowy;}            A[nowx][nowy] = 0;            for(int t=0;t<4;t++){                int tx = nowx + dx[t];                int ty = nowy + dy[t];                if(tx<0||tx>=A.length||ty<0||ty>=A[0].length||A[tx][ty]!=tmp){                    continue;                }                queue.add(tx*A[0].length+ty);               }        }        return result;    }}

这里用两种方法，第一种是DFS，深度优先遍历，使用堆栈的方式，出现问题栈溢出，所以用第二种方式，BFS，广度优先遍历，使用队列的方式，完美解决问题。
显示图像：

Mat matresult = Highgui.imread("data/img/"+imgname+".jpg");for(int i = 0;i < result.size(); i ++){    int [] tmp = (int[]) result.get(i);    System.out.println(tmp[0]+" "+tmp[1]+" "+tmp[2]+" "+tmp[3]+" "+tmp[4]);    Core.rectangle(matresult, new Point(tmp[1], tmp[2]), new Point(tmp[3],tmp[4]), new Scalar(0, 0, 255));    Core.putText(matresult, String.valueOf(tmp[0]), new Point(tmp[1], tmp[2]), Core.FONT_HERSHEY_COMPLEX, 1, new Scalar(255, 0, 0));}Highgui.imwrite("data/result/"+imgname+".jpg", matresult);

使用opencv时要将opencv的动态链接库引入

static{     System.loadLibrary(Core.NATIVE_LIBRARY_NAME);}

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