本文整理了Java中org.opencv.ml.EM.predict_0()
方法的一些代码示例,展示了EM.predict_0()
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_0()
方法的具体详情如下:
包路径:org.opencv.ml.EM
类名称:EM
方法名:predict_0
暂无
代码示例来源:origin: farkam135/GoIV
public float predict(Mat samples, Mat results, int flags)
{
float retVal = predict_0(nativeObj, samples.nativeObj, results.nativeObj, flags);
return retVal;
}
代码示例来源:origin: tz28/Chinese-number-gestures-recognition
public float predict(Mat samples, Mat results, int flags)
{
float retVal = predict_0(nativeObj, samples.nativeObj, results.nativeObj, flags);
return retVal;
}
代码示例来源:origin: DuckDeck/AndroidDemo
public float predict(Mat samples, Mat results, int flags)
{
float retVal = predict_0(nativeObj, samples.nativeObj, results.nativeObj, flags);
return retVal;
}
代码示例来源:origin: leadrien/opencv_native_androidstudio
public float predict(Mat samples, Mat results, int flags)
{
float retVal = predict_0(nativeObj, samples.nativeObj, results.nativeObj, flags);
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.
* @param probs Optional output matrix that contains posterior probabilities of
* each component given the sample. It has <em>1 x nclusters</em> size and
* <code>CV_64FC1</code> type.
*
* @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, Mat probs)
{
double[] retVal = predict_0(nativeObj, sample.nativeObj, probs.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.
* @param probs Optional output matrix that contains posterior probabilities of
* each component given the sample. It has <em>1 x nclusters</em> size and
* <code>CV_64FC1</code> type.
*
* @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, Mat probs)
{
double[] retVal = predict_0(nativeObj, sample.nativeObj, probs.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.
* @param probs Optional output matrix that contains posterior probabilities of
* each component given the sample. It has <em>1 x nclusters</em> size and
* <code>CV_64FC1</code> type.
*
* @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, Mat probs)
{
double[] retVal = predict_0(nativeObj, sample.nativeObj, probs.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.
* @param probs Optional output matrix that contains posterior probabilities of
* each component given the sample. It has <em>1 x nclusters</em> size and
* <code>CV_64FC1</code> type.
*
* @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, Mat probs)
{
double[] retVal = predict_0(nativeObj, sample.nativeObj, probs.nativeObj);
return retVal;
}
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