//
// 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
}
