// // C++: Mat cv::text::createOCRHMMTransitionsTable(String vocabulary, vector_String lexicon) // //javadoc: createOCRHMMTransitionsTable(vocabulary, lexicon) public static Mat createOCRHMMTransitionsTable(string vocabulary, List <string> lexicon) { #if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER Mat lexicon_mat = Converters.vector_String_to_Mat(lexicon); Mat retVal = new Mat(text_Text_createOCRHMMTransitionsTable_10(vocabulary, lexicon_mat.nativeObj)); return(retVal); #else return(null); #endif }
// // C++: void cv::dnn::shrinkCaffeModel(String src, String dst, vector_String layersTypes = std::vector<String>()) // //javadoc: shrinkCaffeModel(src, dst, layersTypes) public static void shrinkCaffeModel(string src, string dst, List <string> layersTypes) { #if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER Mat layersTypes_mat = Converters.vector_String_to_Mat(layersTypes); dnn_Dnn_shrinkCaffeModel_10(src, dst, layersTypes_mat.nativeObj); return; #else return; #endif }
// // C++: void cv::dnn::Net::setInputsNames(vector_String inputBlobNames) // //javadoc: Net::setInputsNames(inputBlobNames) public void setInputsNames(List <string> inputBlobNames) { ThrowIfDisposed(); #if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER Mat inputBlobNames_mat = Converters.vector_String_to_Mat(inputBlobNames); dnn_Net_setInputsNames_10(nativeObj, inputBlobNames_mat.nativeObj); return; #else return; #endif }
// // C++: bool loadDatasetList(String imageList, String annotationList, vector_String images, vector_String annotations) // //javadoc: loadDatasetList(imageList, annotationList, images, annotations) public static bool loadDatasetList(string imageList, string annotationList, List <string> images, List <string> annotations) { #if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER Mat images_mat = Converters.vector_String_to_Mat(images); Mat annotations_mat = Converters.vector_String_to_Mat(annotations); bool retVal = face_Face_loadDatasetList_10(imageList, annotationList, images_mat.nativeObj, annotations_mat.nativeObj); return(retVal); #else return(false); #endif }
// // C++: void cv::ml::TrainData::getNames(vector_String names) // //javadoc: TrainData::getNames(names) public void getNames(List <string> names) { ThrowIfDisposed(); #if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER Mat names_mat = Converters.vector_String_to_Mat(names); ml_TrainData_getNames_10(nativeObj, names_mat.nativeObj); return; #else return; #endif }
// // C++: void cv::dnn::Net::forward(vector_Mat& outputBlobs, vector_String outBlobNames) // //javadoc: Net::forward(outputBlobs, outBlobNames) public void forward(List <Mat> outputBlobs, List <string> outBlobNames) { ThrowIfDisposed(); #if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER Mat outputBlobs_mat = new Mat(); Mat outBlobNames_mat = Converters.vector_String_to_Mat(outBlobNames); dnn_Net_forward_14(nativeObj, outputBlobs_mat.nativeObj, outBlobNames_mat.nativeObj); Converters.Mat_to_vector_Mat(outputBlobs_mat, outputBlobs); outputBlobs_mat.release(); return; #else return; #endif }
// // C++: bool loadTrainingData(vector_String filename, vector_vector_Point2f trainlandmarks, vector_String trainimages) // //javadoc: loadTrainingData(filename, trainlandmarks, trainimages) public static bool loadTrainingData(List <string> filename, List <MatOfPoint2f> trainlandmarks, List <string> trainimages) { #if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER Mat filename_mat = Converters.vector_String_to_Mat(filename); List <Mat> trainlandmarks_tmplm = new List <Mat>((trainlandmarks != null) ? trainlandmarks.Count : 0); Mat trainlandmarks_mat = Converters.vector_vector_Point2f_to_Mat(trainlandmarks, trainlandmarks_tmplm); Mat trainimages_mat = Converters.vector_String_to_Mat(trainimages); bool retVal = face_Face_loadTrainingData_14(filename_mat.nativeObj, trainlandmarks_mat.nativeObj, trainimages_mat.nativeObj); return(retVal); #else return(false); #endif }
// // C++: bool loadTrainingData(String filename, vector_String images, Mat& facePoints, char delim = ' ', float offset = 0.0f) // //javadoc: loadTrainingData(filename, images, facePoints, delim, offset) public static bool loadTrainingData(string filename, List <string> images, Mat facePoints, char delim, float offset) { if (facePoints != null) { facePoints.ThrowIfDisposed(); } #if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER Mat images_mat = Converters.vector_String_to_Mat(images); bool retVal = face_Face_loadTrainingData_10(filename, images_mat.nativeObj, facePoints.nativeObj, delim, offset); return(retVal); #else return(false); #endif }
//javadoc: loadTrainingData(imageList, groundTruth, images, facePoints) public static bool loadTrainingData(string imageList, string groundTruth, List <string> images, Mat facePoints) { if (facePoints != null) { facePoints.ThrowIfDisposed(); } #if UNITY_PRO_LICENSE || ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER Mat images_mat = Converters.vector_String_to_Mat(images); bool retVal = face_Face_loadTrainingData_13(imageList, groundTruth, images_mat.nativeObj, facePoints.nativeObj); return(retVal); #else return(false); #endif }