org.opencv.ml.EM.predict_1()方法的使用及代码示例

x33g5p2x  于2022-01-19 转载在 其他  
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本文整理了Java中org.opencv.ml.EM.predict_1()方法的一些代码示例,展示了EM.predict_1()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台,是从一些精选项目中提取出来的代码,具有较强的参考意义,能在一定程度帮忙到你。EM.predict_1()方法的具体详情如下:
包路径:org.opencv.ml.EM
类名称:EM
方法名:predict_1

EM.predict_1介绍

暂无

代码示例

代码示例来源:origin: DuckDeck/AndroidDemo

public  float predict(Mat samples, Mat results)
{
  
  float retVal = predict_1(nativeObj, samples.nativeObj, results.nativeObj);
  
  return retVal;
}

代码示例来源:origin: farkam135/GoIV

public  float predict(Mat samples)
{
  
  float retVal = predict_1(nativeObj, samples.nativeObj);
  
  return retVal;
}

代码示例来源:origin: tz28/Chinese-number-gestures-recognition

public  float predict(Mat samples)
{
  
  float retVal = predict_1(nativeObj, samples.nativeObj);
  
  return retVal;
}

代码示例来源:origin: leadrien/opencv_native_androidstudio

public  float predict(Mat samples)
{
  
  float retVal = predict_1(nativeObj, samples.nativeObj);
  
  return retVal;
}

代码示例来源:origin: abhn/marvel

/**
 * <p>Returns a likelihood logarithm value and an index of the most probable
 * mixture component for the given sample.</p>
 *
 * <p>The method returns a two-element <code>double</code> vector. Zero element is
 * a likelihood logarithm value for the sample. First element is an index of the
 * most probable mixture component for the given sample.</p>
 *
 * @param sample A sample for classification. It should be a one-channel matrix
 * of <em>1 x dims</em> or <em>dims x 1</em> size.
 *
 * @see <a href="http://docs.opencv.org/modules/ml/doc/expectation_maximization.html#em-predict">org.opencv.ml.EM.predict</a>
 */
  public  double[] predict(Mat sample)
  {

    double[] retVal = predict_1(nativeObj, sample.nativeObj);

    return retVal;
  }

代码示例来源:origin: jtsky/EasyPR_Android

/**
 * <p>Returns a likelihood logarithm value and an index of the most probable
 * mixture component for the given sample.</p>
 *
 * <p>The method returns a two-element <code>double</code> vector. Zero element is
 * a likelihood logarithm value for the sample. First element is an index of the
 * most probable mixture component for the given sample.</p>
 *
 * @param sample A sample for classification. It should be a one-channel matrix
 * of <em>1 x dims</em> or <em>dims x 1</em> size.
 *
 * @see <a href="http://docs.opencv.org/modules/ml/doc/expectation_maximization.html#em-predict">org.opencv.ml.EM.predict</a>
 */
  public  double[] predict(Mat sample)
  {

    double[] retVal = predict_1(nativeObj, sample.nativeObj);

    return retVal;
  }

代码示例来源:origin: nu.pattern/opencv

/**
 * <p>Returns a likelihood logarithm value and an index of the most probable
 * mixture component for the given sample.</p>
 *
 * <p>The method returns a two-element <code>double</code> vector. Zero element is
 * a likelihood logarithm value for the sample. First element is an index of the
 * most probable mixture component for the given sample.</p>
 *
 * @param sample A sample for classification. It should be a one-channel matrix
 * of <em>1 x dims</em> or <em>dims x 1</em> size.
 *
 * @see <a href="http://docs.opencv.org/modules/ml/doc/expectation_maximization.html#em-predict">org.opencv.ml.EM.predict</a>
 */
  public  double[] predict(Mat sample)
  {

    double[] retVal = predict_1(nativeObj, sample.nativeObj);

    return retVal;
  }

代码示例来源:origin: ytai/IOIOPlotter

/**
 * <p>Returns a likelihood logarithm value and an index of the most probable
 * mixture component for the given sample.</p>
 *
 * <p>The method returns a two-element <code>double</code> vector. Zero element is
 * a likelihood logarithm value for the sample. First element is an index of the
 * most probable mixture component for the given sample.</p>
 *
 * @param sample A sample for classification. It should be a one-channel matrix
 * of <em>1 x dims</em> or <em>dims x 1</em> size.
 *
 * @see <a href="http://docs.opencv.org/modules/ml/doc/expectation_maximization.html#em-predict">org.opencv.ml.EM.predict</a>
 */
  public  double[] predict(Mat sample)
  {

    double[] retVal = predict_1(nativeObj, sample.nativeObj);

    return retVal;
  }

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