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))); }