// Get Recipes
public Data[] GetRecipes(ModelChoice model_choice, DataPurpose data_purpose)
{
MLContext mlContext = new MLContext();
IDataView testData = GetDataView(model_choice, mlContext, data_purpose);
IDataView features = GetDataView(model_choice, mlContext, DataPurpose.FEATURES);
return(GetData(testData, features));
}
protected FeatureSet ExtractFeatures(Sample sample, DataPurpose purpose)
{
var extractor = new FeatureExtraction();
var feedback = CaptureFeedback.None;
var features = new FeatureSet();
extractor.CreateFeatureSet(sample, purpose, ref feedback, ref features);
return((feedback == CaptureFeedback.Good) ? features : null);
}
protected FeatureSet ExtractFeatures(Sample Sample, DataPurpose Purpose)
{
FeatureExtraction Extractor = new FeatureExtraction();
CaptureFeedback feedback = CaptureFeedback.None;
FeatureSet features = new FeatureSet();
Extractor.CreateFeatureSet(Sample, Purpose, ref feedback, ref features);
if (feedback == CaptureFeedback.Good)
{
return(features);
}
return(null);
}
private string GetPrefix(DataPurpose dataPurpose)
{
switch (dataPurpose)
{
case DataPurpose.Test:
return(testDataPrefix);
case DataPurpose.Training:
return(trainingDataPrefix);
default:
return(null);
}
}
public IEnumerable <InputOutputPairModel> GetData(DataPurpose dataPurpose)
{
var prefix = GetPrefix(dataPurpose);
var imageData = ReadImageData($@"{mnistDataFolder}\{prefix}-images.dat");
var labelData = ReadLabelData($@"{mnistDataFolder}\{prefix}-labels.dat");
for (var i = 0; i < imageData.Length; i++)
{
yield return(new InputOutputPairModel
{
Inputs = imageData[i].Select(NormalizeImageActivation).ToArray(),
Outputs = NormalizeLabelActivation(labelData[i])
});
}
}
public static FeatureSet ExtractFeatures(Sample sample, DataPurpose datapurpose)
{
FeatureExtraction extractor = new FeatureExtraction();
CaptureFeedback feedback = CaptureFeedback.None;
FeatureSet feature = new FeatureSet();
extractor.CreateFeatureSet(sample, datapurpose, ref feedback, ref feature);
if (feedback == CaptureFeedback.Good)
{
return(feature);
}
else
{
return(null);
}
}
public DPFP.Template ConvertRawBmpAsTemplate(Bitmap RawBmp, DataPurpose ProcessPurpose = DataPurpose.Enrollment, short VertDpi = 700, short HorDpi = 700)
{
VariantConverter VConverter;
Enroller = new DPFP.Processing.Enrollment();
RawBmp = EncodeBitmap(RawBmp, VertDpi, HorDpi);
try
{
// converts raw image to dpSample using DFC 2.0---------------------------------------
// encode the bmp variable using the bitmap Loader
BitmapLoader BmpLoader = new BitmapLoader(RawBmp, (int)RawBmp.HorizontalResolution, (int)RawBmp.VerticalResolution);
BmpLoader.ProcessBitmap();
// return the required result
inputData = BmpLoader.RawData;
inpRaw = BmpLoader.DPInputParam;
// dispose the object
BmpLoader.Dispose();
// start the conversion process
VConverter = new VariantConverter(VariantConverter.OutputType.dp_sample, DataType.RawSample, inpRaw, inputData, false);
MemoryStream DStream = new MemoryStream(VConverter.Convert());
DPsample = new DPFP.Sample(DStream);
// DPsample = DirectCast(VConverter.Convert(), DPFP.Sample)
// converts dpSample to DPFeatures using the OTW'''''''''''''''''''''''''''''''''''''''
DPFeatures = ExtractFeatures(DPsample, ProcessPurpose);
// convert DPfeatures to ISO FMD using the DFC 2.0'''''''''''''''''''''''''''''''''''''''
byte[] SerializedFeatures = null;
DPFeatures.Serialize(ref SerializedFeatures); // serialized features into the array of bytes
ISOFMD = DigitalPersona.Standards.Converter.Convert(SerializedFeatures, DigitalPersona.Standards.DataType.DPFeatureSet, DataType.ISOFeatureSet);
// convert ISO FMD to DPTemplate using DFC 2.0'''''''''''''''''''''''''''''''''''''''
byte[] DPTemplateData = DigitalPersona.Standards.Converter.Convert(ISOFMD, DigitalPersona.Standards.DataType.ISOTemplate, DataType.DPTemplate);
// deserialize data to Template
DPTemplate = new DPFP.Template();
DPTemplate.DeSerialize(DPTemplateData); // required for database purpose
// ============================================================================
DStream.Close();
return(DPTemplate);
}
catch (Exception ex)
{
return(null /* TODO Change to default(_) if this is not a reference type */);
}
}
// Get DataView
public IDataView GetDataView(ModelChoice choice, MLContext ml, DataPurpose purpose)
{
// get features
if (purpose.Equals(DataPurpose.FEATURES))
{
return(LoadFeatures(Path.Combine(Environment.CurrentDirectory, "Data", FEATURES_DATA), ml));
}
// get NMF data (entries set aside for testing)
else if (choice.Equals(ModelChoice.NMF))
{
// test data
if (purpose.Equals(DataPurpose.TEST))
{
return(LoadData(Path.Combine(Environment.CurrentDirectory, "Data", NMF_TEST_DATA), ml));
}
// training data
else
{
return(LoadData(Path.Combine(Environment.CurrentDirectory, "Data", NMF_TRAIN_DATA), ml));
}
}
// get data (recipes set aside for testing)
else
{
// test data
if (purpose.Equals(DataPurpose.TEST))
{
return(LoadData(Path.Combine(Environment.CurrentDirectory, "Data", TEST_DATA), ml));
}
// training data
else
{
return(LoadData(Path.Combine(Environment.CurrentDirectory, "Data", TRAIN_DATA), ml));
}
}
}
