// // 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())); }