private void SetupKmeans()
{
Kmeans.OnClassify += Kmeans_OnClassify;
//Initial view if null
if (KmeansTrainedDataViews == null)
{
KmeansTrainedDataViews = new List <KmeansTrainedDataView>();
for (int i = 0; i < Kmeans.GetTrainResult().Count; i++)
{
var view = new KmeansTrainedDataView();
KmeansTrainedDataViews.Add(view);
KmeansTrainedData_flowPanel.Controls.Add(view);
}
}
//Refresh view
var DataViewsEnum = KmeansTrainedDataViews.GetEnumerator();
foreach (RawImage28x28 TrainResult in Kmeans.GetTrainResult())
{
if (DataViewsEnum.MoveNext())
{
var CurrentView = DataViewsEnum.Current;
CurrentView.SetValue(TrainResult.ToBitmap(), TrainResult.Tag, 0);
}
}
}
//Refresh results
private void Kmeans_OnClassify(RawImage28x28 NewNode, IEnumerable <RawImage28x28> OrderedCenter, string MostTag)
{
Image OldBitmap = KmeansResultPictureBox.Image;
KmeansResultPictureBox.Image = OrderedCenter.First().ToBitmap();
KmeansResultNum_Label.Text = MostTag;
var TrainResultsEnumerator = OrderedCenter.GetEnumerator();
foreach (var KmeansTrainedDataView in KmeansTrainedDataViews)
{
if (TrainResultsEnumerator.MoveNext())
{
var TrainResult = TrainResultsEnumerator.Current;
KmeansTrainedDataView.SetValue(TrainResult.ToBitmap(), TrainResult.Tag, TrainResult.GetEuclideanDistance(NewNode));
}
}
OldBitmap?.Dispose();
}
