//
// C++: static Ptr_SVM cv::ml::SVM::load(String filepath)
//
//javadoc: SVM::load(filepath)
public static SVM load(string filepath)
{
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
SVM retVal = SVM.__fromPtr__(ml_SVM_load_10(filepath));
return(retVal);
#else
return(null);
#endif
}
//
// C++: static Ptr_SVM cv::ml::SVM::create()
//
//javadoc: SVM::create()
public static SVM create()
{
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
SVM retVal = SVM.__fromPtr__(ml_SVM_create_10());
return(retVal);
#else
return(null);
#endif
}
//
// C++: static Ptr_SVM cv::ml::SVM::load(String filepath)
//
/**
* Loads and creates a serialized svm from a file
*
* Use SVM::save to serialize and store an SVM to disk.
* Load the SVM from this file again, by calling this function with the path to the file.
*
* param filepath path to serialized svm
* return automatically generated
*/
public static SVM load(string filepath)
{
return(SVM.__fromPtr__(ml_SVM_load_10(filepath)));
}
//
// C++: static Ptr_SVM cv::ml::SVM::create()
//
/**
* Creates empty model.
* Use StatModel::train to train the model. Since %SVM has several parameters, you may want to
* find the best parameters for your problem, it can be done with SVM::trainAuto.
* return automatically generated
*/
public static SVM create()
{
return(SVM.__fromPtr__(ml_SVM_create_10()));
}
