Esempio n. 1
0
  /** 使用示例 读取模型,识别CT局部病变 */
  public void test2() {
    try {

      // 实例化ObjectInputStream对象
      /*ObjectInputStream ois = new ObjectInputStream(App.class.getResourceAsStream("RandomForest"));*/
      ObjectInputStream ois = new ObjectInputStream(new FileInputStream("conf/RandomForest"));

      try {
        // 读取对象people,反序列化
        RandomForest randomForest = (RandomForest) ois.readObject();
        ImageFeature imageFeature = new ImageFeature();
        /** 图像局部特征提取,参数:图象文件路径,划取区域坐标(x1,y1),(x2,y2) 返回:图像特征向量 */
        double[] data =
            imageFeature.getFeature(
                App.class.getClassLoader().getResource("IMG-0002-00011.jpg").getFile(),
                0,
                0,
                125,
                125);
        /** 识别算法调用 参数:图像特征向量 返回:病变类型(int型),1:正常;2:肝癌;3:肝血管瘤;4:肝囊肿;5:其他 */
        int type = randomForest.predictType(data);
        System.out.println("RandomForest predict:" + type);
      } catch (ClassNotFoundException e) {
        e.printStackTrace();
      }
    } catch (FileNotFoundException e) {
      e.printStackTrace();
    } catch (IOException e) {
      e.printStackTrace();
    }
  }
Esempio n. 2
0
  /** 识别模型生成 */
  public void testGenerateModel() {
    Connection c = null;
    Statement stmt = null;
    List<Double[]> samples = null;
    RandomForest randomforest = null;
    try {
      Class.forName("org.sqlite.JDBC");
      c =
          DriverManager.getConnection(
              "jdbc:sqlite:/Users/macbook/Documents/IdeaProject/BlackHole/db/cad");
      stmt = c.createStatement();
      ResultSet rs = stmt.executeQuery("select * from feature");
      samples = new ArrayList<Double[]>(rs.getRow());
      while (rs.next()) {
        Double[] d = new Double[27];
        d[0] = rs.getDouble("f1");
        d[1] = rs.getDouble("f2");
        d[2] = rs.getDouble("f1");
        d[3] = rs.getDouble("f1");
        d[4] = rs.getDouble("f1");
        d[5] = rs.getDouble("f1");
        d[6] = rs.getDouble("f1");
        d[7] = rs.getDouble("f1");
        d[8] = rs.getDouble("f1");
        d[9] = rs.getDouble("f1");
        d[10] = rs.getDouble("f1");
        d[11] = rs.getDouble("f1");
        d[12] = rs.getDouble("f1");
        d[13] = rs.getDouble("f1");
        d[14] = rs.getDouble("f1");
        d[15] = rs.getDouble("f1");
        d[16] = rs.getDouble("f1");
        d[17] = rs.getDouble("f1");
        d[18] = rs.getDouble("f1");
        d[19] = rs.getDouble("f1");
        d[20] = rs.getDouble("f1");
        d[21] = rs.getDouble("f1");
        d[22] = rs.getDouble("f1");
        d[23] = rs.getDouble("f1");
        d[24] = rs.getDouble("f1");
        d[25] = rs.getDouble("f1");
        d[26] = (double) rs.getInt("label");
        samples.add(d);
      }
      rs.close();
      stmt.close();
      c.close();
      randomforest = new RandomForest(50, 4);
      randomforest.createForest(samples);
    } catch (Exception e) {
      e.printStackTrace();
      System.exit(0);
    }
    System.out.println("-----------------");
    try {
      // 实例化ObjectOutputStream对象
      /*ObjectOutputStream oos = new ObjectOutputStream(new FileOutputStream(App.class.getClassLoader().getResource("RandomForest").getFile()));*/
      ObjectOutputStream oos = new ObjectOutputStream(new FileOutputStream("conf/RandomForest"));
      // 将对象写入文件
      oos.writeObject(randomforest);
      oos.flush();
      oos.close();

      // 实例化ObjectInputStream对象
      /*ObjectInputStream ois = new ObjectInputStream(App.class.getResourceAsStream("RandomForest"));*/
      ObjectInputStream ois = new ObjectInputStream(new FileInputStream("conf/RandomForest"));

      try {
        // 读取对象people,反序列化
        RandomForest randomForest = (RandomForest) ois.readObject();
        double[] data = new double[samples.get(0).length];
        int sum = samples.size();
        int right = 0;
        for (Double[] sample : samples) {
          for (int i = 0; i < sample.length; i++) {
            data[i] = sample[i];
          }
          if (randomForest.predictType(data) == (int) data[26]) {
            right++;
          }
        }
        double accurancy = right * 1.0 / sum;
        System.out.println("RandomForest Accurancy:" + accurancy);
      } catch (ClassNotFoundException e) {
        e.printStackTrace();
      }
    } catch (FileNotFoundException e) {
      e.printStackTrace();
    } catch (IOException e) {
      e.printStackTrace();
    }
  }