public static StringBuilder GetCurrentPythonVersion()
{
var parentKey = Registry.LocalMachine.OpenSubKey(_windowsRegistryInstall);
var nameList = parentKey.GetSubKeyNames();
var pythonInstallations = new StringBuilder();
for (int i = 0; i < nameList.Length; i++)
{
var regKey = parentKey.OpenSubKey(nameList[i]);
try
{
var registryDisplayName = (string)regKey.GetValue("DisplayName");
var installationPath = (string)regKey.GetValue("InstallSource");
var version = (string)regKey.GetValue("DisplayVersion");
if (!string.IsNullOrEmpty(registryDisplayName) && registryDisplayName.Contains(_python))
{
pythonInstallations.AppendLine(registryDisplayName);
}
}
catch (Exception ex)
{
_exceptionLogging.LogException(ex.ToString());
}
}
return(pythonInstallations);
}
public void Recognise(string fileName)
{
FileSource = BitmapFrame.Create(new Uri(fileName));
ImageFileName = fileName;
try
{
using (_inceptionGraph = new Inception())
{
_fileName = fileName;
_inceptionGraph.OnDownloadCompleted += OnDownloadComplete;
if (!string.IsNullOrEmpty(DownloadURL) &&
!string.IsNullOrEmpty(InceptionGraphFileName) &&
!string.IsNullOrEmpty(OutputLabelsFileName))
{
_inceptionGraph.Init(new string[] { InceptionGraphFileName, OutputLabelsFileName }, DownloadURL);
}
else
{
_inceptionGraph.Init();
}
}
}
catch (Exception ex)
{
_exceptionLogDataAccess.LogException(ex.ToString());
IsModalVisible = false;
}
}
public static void SerialiseAndWriteObject(string filePath, object parameter, Type type)
{
try
{
using (var writer = new StreamWriter(filePath))
{
var serialiser = new XmlSerializer(type);
serialiser.Serialize(writer, parameter);
}
}
catch (Exception ex)
{
_exceptionLogging.LogException(ex.ToString());
}
}
private void OnVisualiseColumnn()
{
if (SelectedVisualisationColumnIndex >= 0 && ColumnsDictionary.Any())
{
try
{
SelectedColumnItemsCount = new ObservableCollection <KeyValuePair <string, int> >();
var selectedColumnKey = ColumnsDictionary.ElementAt(SelectedVisualisationColumnIndex).Key;
var visualiseColumnData = CleanDataItems.SelectMany(x => x.Data).Where(c => c.Key == selectedColumnKey);
foreach (var visualColumnData in visualiseColumnData.Select(x => x.Value).Distinct())
{
Application.Current.Dispatcher.Invoke(() => SelectedColumnItemsCount.Add(new KeyValuePair <string, int>(visualColumnData,
visualiseColumnData.Select(x => x).Where(c => string.Equals(c.Value, visualColumnData, StringComparison.OrdinalIgnoreCase)).Count())));
}
}
catch (Exception ex)
{
_exceptionLogDataAccess.LogException(ex.ToString());
}
}
}
public static void Main()
{
try
{
var application = new App();
application.InitializeComponent();
application.Run();
}
catch (Exception ex)
{
_exceptionLogging.LogException(ex.ToString());
}
}
public void GetPredictions()
{
try
{
var predictions = new ObservableCollection <CensusBaseEntity>();
using (var reader = new StreamReader(CurrentDirectory.GetPythonAssetsDirectory(@"WideDeep\Prediction.csv")))
{
var line = reader.ReadLine();
while (!reader.EndOfStream)
{
line = reader.ReadLine();
var values = line.Split(',');
predictions.Add(new CensusBaseEntity()
{
Age = Convert.ToInt32(values[0]),
WorkClass = values[1],
Fnlwgt = Convert.ToInt32(values[2]),
Education = values[3],
EducationNumber = Convert.ToInt32(values[4]),
MartialStatus = values[5],
Occupation = values[6],
Relationship = values[7],
Race = values[8],
Gender = values[9],
CapitalGain = Convert.ToInt32(values[10]),
CapticalLoss = Convert.ToInt32(values[11]),
HoursPerWeek = Convert.ToInt32(values[12]),
Country = values[13]
});
}
}
PredictionInputValues = predictions;
}
catch (Exception ex)
{
_exceptionLogging.LogException(ex.ToString());
}
}
private void ReadMNISTDataset()
{
try
{
var directories = GetDirectories();
var ifsLabels = new FileStream(directories.LabelsFileDir, FileMode.Open);
var ifsImages = new FileStream(directories.ImagesFileDir, FileMode.Open);
ifsLabels.Seek(_labelPosition, SeekOrigin.Begin);
ifsImages.Seek(_datasetPosition, SeekOrigin.Begin);
var brLabels = new BinaryReader(ifsLabels);
var brImages = new BinaryReader(ifsImages);
int magic1 = brImages.ReadInt32();
int numImages = brImages.ReadInt32();
int numRows = brImages.ReadInt32();
int numCols = brImages.ReadInt32();
int magic2 = brLabels.ReadInt32();
int numLabels = brLabels.ReadInt32();
var pixels = new byte[28][];
for (int i = 0; i < pixels.Length; ++i)
{
pixels[i] = new byte[28];
}
for (int i = 0; i < 28; ++i)
{
for (int j = 0; j < 28; ++j)
{
byte b = brImages.ReadByte();
pixels[i][j] = b;
}
}
byte lbl = brLabels.ReadByte();
var dImage = new DigitImage(pixels, lbl);
CorrespondingLabel = lbl;
PixelArray = dImage.GetImageArray();
var formatEmptyLines = Regex.Replace(dImage.ToString(), @"^\s+$[\r\n]*", string.Empty, RegexOptions.Multiline);
DatasetInformation += string.Format("{0}\n\r", formatEmptyLines);
ifsImages.Close();
brImages.Close();
ifsLabels.Close();
brLabels.Close();
}
catch (Exception ex)
{
_exceptionLogging.LogException(ex.ToString());
}
}
private void OnDownloadComplete(object sender, AsyncCompletedEventArgs e)
{
try
{
using (var imageTensor = ImageIO.ReadTensorFromImageFile <float>(_fileName, 224, 224, 128.0f, 1.0f / 128.0f))
{
var detectionResult = _graph.Detect(imageTensor);
var detectionAnnotations = MultiboxGraph.FilterResults(detectionResult, 0.1f);
var detectionImage = NativeImageIO.ImageFileToJpeg(_fileName, detectionAnnotations);
var typeConverter = TypeDescriptor.GetConverter(typeof(Bitmap));
var detectionBmpImage = (Bitmap)typeConverter.ConvertFrom(detectionImage.Raw);
ImageSource = BitmapConverter.ConvertBitmap(detectionBmpImage);
}
IsModalVisible = false;
}
catch (Exception ex)
{
_exceptionLogDataAccess.LogException(ex.ToString());
IsModalVisible = false;
}
}
public object InvokeDynamicFunction(string function)
{
try
{
if (function.StartsWith("="))
{
var methodStart = function.IndexOf('=');
var startIndex = function.IndexOf('(');
var endIndex = function.IndexOf(')');
var methodName = function.Substring(++methodStart, startIndex - methodStart);
var parameters = function.Substring(++startIndex, endIndex - startIndex).Split(',');
return(InvokeFunction(methodName, parameters));
}
}
catch (Exception ex)
{
_exceptionLogDataAccess.LogException(ex.ToString());
return(ex);
}
return(string.Empty);
}
private void GetSavedExperimentResults()
{
ExperimentResults = new ObservableCollection <PerformanceIndicatorEntity>();
try
{
using (var reader = new StreamReader(CurrentDirectory.GetAssetsDirectoryFolder(@"CSVFiles\ExperimentResults.csv")))
{
do
{
var line = reader.ReadLine();
if (line != null)
{
var values = line.Split(',');
var experimentResult = new PerformanceIndicatorEntity()
{
PreprocessingTechnique = values[0],
Process = values[1],
Accuracy = int.Parse(values[2]),
AccuracyBaseline = int.Parse(values[3]),
AUC = int.Parse(values[4]),
AUCPrecisionRecall = int.Parse(values[5]),
AverageLoss = int.Parse(values[6]),
LabelMean = int.Parse(values[7]),
Loss = int.Parse(values[8]),
Precision = int.Parse(values[9]),
PredictionMean = int.Parse(values[10]),
Recall = int.Parse(values[11]),
TrainTime = int.Parse(values[12]),
};
ExperimentResults.Add(experimentResult);
}
}while (!reader.EndOfStream);
}
}
catch (Exception ex)
{
_exceptionLogDataAccess.LogException(ex.ToString());
}
}