void DoProcess()
{
if (!(owner.Value is OpenCVForUnityPlayMakerActions.LogisticRegression))
{
LogError("owner is not initialized. Add Action \"newLogisticRegression\".");
return;
}
OpenCVForUnity.MlModule.LogisticRegression wrapped_owner = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.LogisticRegression, OpenCVForUnity.MlModule.LogisticRegression>(owner);
if (!(samples.Value is OpenCVForUnityPlayMakerActions.Mat))
{
LogError("samples is not initialized. Add Action \"newMat\".");
return;
}
OpenCVForUnity.CoreModule.Mat wrapped_samples = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.Mat, OpenCVForUnity.CoreModule.Mat>(samples);
if (!(results.Value is OpenCVForUnityPlayMakerActions.Mat))
{
LogError("results is not initialized. Add Action \"newMat\".");
return;
}
OpenCVForUnity.CoreModule.Mat wrapped_results = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.Mat, OpenCVForUnity.CoreModule.Mat>(results);
storeResult.Value = wrapped_owner.predict(wrapped_samples, wrapped_results);
}
void DoProcess()
{
if (!(owner.Value is OpenCVForUnityPlayMakerActions.LogisticRegression))
{
LogError("owner is not initialized. Add Action \"newLogisticRegression\".");
return;
}
OpenCVForUnity.MlModule.LogisticRegression wrapped_owner = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.LogisticRegression, OpenCVForUnity.MlModule.LogisticRegression>(owner);
wrapped_owner.setTrainMethod(val.Value);
}
void DoProcess()
{
if (!(owner.Value is OpenCVForUnityPlayMakerActions.LogisticRegression))
{
LogError("owner is not initialized. Add Action \"newLogisticRegression\".");
return;
}
OpenCVForUnity.MlModule.LogisticRegression wrapped_owner = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.LogisticRegression, OpenCVForUnity.MlModule.LogisticRegression>(owner);
storeResult.Value = (float)wrapped_owner.getLearningRate();
}
void DoProcess()
{
if (!(owner.Value is OpenCVForUnityPlayMakerActions.LogisticRegression))
{
LogError("owner is not initialized. Add Action \"newLogisticRegression\".");
return;
}
OpenCVForUnity.MlModule.LogisticRegression wrapped_owner = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.LogisticRegression, OpenCVForUnity.MlModule.LogisticRegression>(owner);
wrapped_owner.setTermCriteria(new OpenCVForUnity.CoreModule.TermCriteria((int)val_type.Value, (int)val_maxCount.Value, (double)val_epsilon.Value));
}
void DoProcess()
{
if (!(owner.Value is OpenCVForUnityPlayMakerActions.LogisticRegression))
{
LogError("owner is not initialized. Add Action \"newLogisticRegression\".");
return;
}
OpenCVForUnity.MlModule.LogisticRegression wrapped_owner = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.LogisticRegression, OpenCVForUnity.MlModule.LogisticRegression>(owner);
if (!(storeResult.Value is OpenCVForUnityPlayMakerActions.TermCriteria))
{
storeResult.Value = new OpenCVForUnityPlayMakerActions.TermCriteria();
}
((OpenCVForUnityPlayMakerActions.TermCriteria)storeResult.Value).wrappedObject = wrapped_owner.getTermCriteria();
}
void DoProcess()
{
if (!(owner.Value is OpenCVForUnityPlayMakerActions.LogisticRegression))
{
LogError("owner is not initialized. Add Action \"newLogisticRegression\".");
return;
}
OpenCVForUnity.MlModule.LogisticRegression wrapped_owner = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.LogisticRegression, OpenCVForUnity.MlModule.LogisticRegression>(owner);
if (!(val.Value is OpenCVForUnityPlayMakerActions.Double))
{
LogError("val is not initialized. Add Action \"newDouble\".");
return;
}
System.Double wrapped_val = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.Double, System.Double>(val);
wrapped_owner.setLearningRate(wrapped_val);
}
void DoProcess()
{
if (!(owner.Value is OpenCVForUnityPlayMakerActions.LogisticRegression))
{
LogError("owner is not initialized. Add Action \"newLogisticRegression\".");
return;
}
OpenCVForUnity.MlModule.LogisticRegression wrapped_owner = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.LogisticRegression, OpenCVForUnity.MlModule.LogisticRegression>(owner);
if (!(val.Value is OpenCVForUnityPlayMakerActions.TermCriteria))
{
LogError("val is not initialized. Add Action \"newTermCriteria\".");
return;
}
OpenCVForUnity.CoreModule.TermCriteria wrapped_val = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.TermCriteria, OpenCVForUnity.CoreModule.TermCriteria>(val);
wrapped_owner.setTermCriteria(wrapped_val);
}
public LogisticRegression(OpenCVForUnity.MlModule.LogisticRegression nativeObj) : base(nativeObj)
{
}
//
// C++: static Ptr_LogisticRegression cv::ml::LogisticRegression::create()
//
/**
* Creates empty model.
*
* Creates Logistic Regression model with parameters given.
* return automatically generated
*/
public static LogisticRegression create()
{
return(LogisticRegression.__fromPtr__(ml_LogisticRegression_create_10()));
}
/**
* Loads and creates a serialized LogisticRegression from a file
*
* Use LogisticRegression::save to serialize and store an LogisticRegression to disk.
* Load the LogisticRegression 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 LogisticRegression
* return automatically generated
*/
public static LogisticRegression load(string filepath)
{
return(LogisticRegression.__fromPtr__(ml_LogisticRegression_load_11(filepath)));
}
//
// C++: static Ptr_LogisticRegression cv::ml::LogisticRegression::load(String filepath, String nodeName = String())
//
/**
* Loads and creates a serialized LogisticRegression from a file
*
* Use LogisticRegression::save to serialize and store an LogisticRegression to disk.
* Load the LogisticRegression 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 LogisticRegression
* param nodeName name of node containing the classifier
* return automatically generated
*/
public static LogisticRegression load(string filepath, string nodeName)
{
return(LogisticRegression.__fromPtr__(ml_LogisticRegression_load_10(filepath, nodeName)));
}