void DoProcess()
{
if (!(owner.Value is OpenCVForUnityPlayMakerActions.NormalBayesClassifier))
{
LogError("owner is not initialized. Add Action \"newNormalBayesClassifier\".");
return;
}
OpenCVForUnity.MlModule.NormalBayesClassifier wrapped_owner = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.NormalBayesClassifier, OpenCVForUnity.MlModule.NormalBayesClassifier>(owner);
if (!(inputs.Value is OpenCVForUnityPlayMakerActions.Mat))
{
LogError("inputs is not initialized. Add Action \"newMat\".");
return;
}
OpenCVForUnity.CoreModule.Mat wrapped_inputs = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.Mat, OpenCVForUnity.CoreModule.Mat>(inputs);
if (!(outputs.Value is OpenCVForUnityPlayMakerActions.Mat))
{
LogError("outputs is not initialized. Add Action \"newMat\".");
return;
}
OpenCVForUnity.CoreModule.Mat wrapped_outputs = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.Mat, OpenCVForUnity.CoreModule.Mat>(outputs);
if (!(outputProbs.Value is OpenCVForUnityPlayMakerActions.Mat))
{
LogError("outputProbs is not initialized. Add Action \"newMat\".");
return;
}
OpenCVForUnity.CoreModule.Mat wrapped_outputProbs = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.Mat, OpenCVForUnity.CoreModule.Mat>(outputProbs);
storeResult.Value = wrapped_owner.predictProb(wrapped_inputs, wrapped_outputs, wrapped_outputProbs, flags.Value);
}
//javadoc: NormalBayesClassifier::load(filepath)
public static NormalBayesClassifier load(string filepath)
{
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
NormalBayesClassifier retVal = NormalBayesClassifier.__fromPtr__(ml_NormalBayesClassifier_load_11(filepath));
return(retVal);
#else
return(null);
#endif
}
//
// C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::create()
//
//javadoc: NormalBayesClassifier::create()
public static NormalBayesClassifier create()
{
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
NormalBayesClassifier retVal = NormalBayesClassifier.__fromPtr__(ml_NormalBayesClassifier_create_10());
return(retVal);
#else
return(null);
#endif
}
/**
* Loads and creates a serialized NormalBayesClassifier from a file
*
* Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.
* Load the NormalBayesClassifier from this file again, by calling this function with the path to the file.
* Optionally specify the node for the file containing the classifier
*
* param filepath path to serialized NormalBayesClassifier
* return automatically generated
*/
public static NormalBayesClassifier load(string filepath)
{
return(NormalBayesClassifier.__fromPtr__(ml_NormalBayesClassifier_load_11(filepath)));
}
//
// C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::load(String filepath, String nodeName = String())
//
/**
* Loads and creates a serialized NormalBayesClassifier from a file
*
* Use NormalBayesClassifier::save to serialize and store an NormalBayesClassifier to disk.
* Load the NormalBayesClassifier from this file again, by calling this function with the path to the file.
* Optionally specify the node for the file containing the classifier
*
* param filepath path to serialized NormalBayesClassifier
* param nodeName name of node containing the classifier
* return automatically generated
*/
public static NormalBayesClassifier load(string filepath, string nodeName)
{
return(NormalBayesClassifier.__fromPtr__(ml_NormalBayesClassifier_load_10(filepath, nodeName)));
}
//
// C++: static Ptr_NormalBayesClassifier cv::ml::NormalBayesClassifier::create()
//
/**
* Creates empty model
* Use StatModel::train to train the model after creation.
* return automatically generated
*/
public static NormalBayesClassifier create()
{
return(NormalBayesClassifier.__fromPtr__(ml_NormalBayesClassifier_create_10()));
}
public NormalBayesClassifier(OpenCVForUnity.MlModule.NormalBayesClassifier nativeObj) : base(nativeObj)
{
}