private void Classify_btn_Click(object sender, EventArgs e)
{
using (Bitmap ResizedInput = new Bitmap(InputPictureBox.Image, 28, 28))
{
RawImage28x28 NewInput = new RawImage28x28(ResizedInput, null);
NewInput.Print();
Knn?.Classify(Convert.ToInt32(Knn_KValue_Textbox.Text), NewInput);
Kmeans?.Classify(NewInput);
}
}
//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();
}
private void Knn_OnClassify(RawImage28x28 NewNode, IEnumerable <RawImage28x28> ClosestKPoints, string MostTag, IEnumerable <RawImage28x28> ClassifiedNodes)
{
Image OldBitmap = KnnResultPictureBox.Image;
KnnResultPictureBox.Image = ClosestKPoints.First().ToBitmap();
KnnResultNum_Label.Text = MostTag;
StringBuilder sb = new StringBuilder();
var OrderTags = ClosestKPoints.GroupBy(x => x.Tag).OrderByDescending(group => group.Count());
foreach (var OrderedTag in OrderTags)
{
sb.Append("Tag:");
sb.Append(OrderedTag.Key);
sb.Append("\tCount:");
sb.AppendLine(OrderedTag.Count().ToString());
}
ClosestKCount_RichTextbox.Text = sb.ToString();
OldBitmap?.Dispose();
}
public static RawImage28x28[] LoadData(string pixelFilePath, string labelFilePath)
{
int numImages = 60000;
RawImage28x28[] result = new RawImage28x28[numImages];
FileStream ifsPixels = new FileStream(pixelFilePath, FileMode.Open);
FileStream ifsLabels = new FileStream(labelFilePath, FileMode.Open);
BinaryReader brImages = new BinaryReader(ifsPixels);
BinaryReader brLabels = new BinaryReader(ifsLabels);
int magic1 = brImages.ReadInt32(); // stored as Big Endian
magic1 = ReverseBytes(magic1); // convert to Intel format
int imageCount = brImages.ReadInt32();
imageCount = ReverseBytes(imageCount);
int numRows = brImages.ReadInt32();
numRows = ReverseBytes(numRows);
int numCols = brImages.ReadInt32();
numCols = ReverseBytes(numCols);
int magic2 = brLabels.ReadInt32();
magic2 = ReverseBytes(magic2);
int numLabels = brLabels.ReadInt32();
numLabels = ReverseBytes(numLabels);
byte[] pixels = new byte[RawImage28x28.Height * RawImage28x28.Width];
// each image
for (int di = 0; di < numImages; ++di)
{
int cnt = 0;
for (int i = 0; i < 28; ++i) // get 28x28 pixel values
{
for (int j = 0; j < 28; ++j)
{
int b = brImages.ReadByte();
pixels[cnt++] = Convert.ToByte((b > 0 ? 255 : 0));
}
}
byte lbl = brLabels.ReadByte(); // get the label
RawImage28x28 dImage = new RawImage28x28(pixels, lbl.ToString());
result[di] = dImage;
} // each image
ifsPixels.Close(); brImages.Close();
ifsLabels.Close(); brLabels.Close();
return(result);
} // LoadData
