protected void m_btnDelete_Click(object sender, EventArgs e)
{
try
{
WebTestingDataSet.PersonRow person;
if (m_labelId.Text == "-1")
{
return;
}
else
{
person = DatasetUtility.GetPerson(MiscUtility.ParseInt32(m_labelId.Text, -1));
if (person == null)
{
throw new InvalidOperationException("Invalid id.");
}
}
person.Delete();
DatasetUtility.Save(person);
ReturnToList();
}
catch (Exception ex)
{
AddMessage(ex);
}
}
// Loop
private async void Loop()
{
for (; ;)
{
//if(requestImageDraw) {
requestImageDraw = false;
float[] noise;
if (FixNoiseCheckBox.IsChecked.Value)
{
noise = constantNoise;
}
else
{
noise = DatasetUtility.GetNoiseArray(ImageData.NoiseCount);
}
WriteableBitmap bitmap = brain.PredictImage(noise.Concat(new float[] {
NumberEditor_input0.Value,
NumberEditor_input1.Value,
NumberEditor_input2.Value,
}).ToArray());
GeneratedImageView.Source = bitmap;
GeneratedImageView.InvalidateVisual();
//Console.WriteLine("Image updated");
//}
await Task.Delay(Mathf.Clamp(NumberEditor_refreshRate.IntValue, 10, 100000));
}
}
protected void m_btnSave_Click(object sender, EventArgs e)
{
try
{
WebTestingDataSet.PersonRow person;
WebTestingDataSet ds = null;
if (m_labelId.Text == "-1")
{
// create new
ds = new WebTestingDataSet();
person = ds.Person.NewPersonRow();
}
else
{
person = DatasetUtility.GetPerson(MiscUtility.ParseInt32(m_labelId.Text, -1));
if (person == null)
{
throw new InvalidOperationException("Invalid id.");
}
}
person.EmailAddress = m_textEmailAddress.Text;
person.FirstName = m_textFirstName.Text;
person.LastName = m_textLastName.Text;
person.PhoneNumber = m_textPhone.Text;
if (m_chkIsActive.Checked == true)
{
person.Status = "ACTIVE";
}
else
{
person.Status = "INACTIVE";
}
if (m_labelId.Text == "-1")
{
ds.Person.AddPersonRow(person);
}
DatasetUtility.Save(person);
m_labelId.Text = person.Id.ToString();
}
catch (Exception ex)
{
AddMessage(ex);
}
}
// Event - Window
private void OnLoaded(object sender, RoutedEventArgs e)
{
constantNoise = DatasetUtility.GetNoiseArray(ImageData.NoiseCount);
brain = new PantheonBrain("ImageDrawer");
brain.CreateModels();
brain.TrainImageData(1000000);
// RegisterEvents
NumberEditor_input0.ValueChanged += OnInputChanged;
NumberEditor_input1.ValueChanged += OnInputChanged;
NumberEditor_input2.ValueChanged += OnInputChanged;
// Start loop
Loop();
}
protected void Page_Load(object sender, EventArgs e)
{
if (this.IsPostBack == false)
{
int id = -1;
id = MiscUtility.ParseInt32(Request["id"], -1);
if (id == -1)
{
m_labelId.Text = id.ToString();
m_textEmailAddress.Text = "";
m_textFirstName.Text = "";
m_textLastName.Text = "";
m_textPhone.Text = "";
m_chkIsActive.Checked = true;
}
else
{
WebTestingDataSet.PersonRow person = DatasetUtility.GetPerson(id);
m_labelId.Text = person.Id.ToString();
m_textEmailAddress.Text = person.EmailAddress;
m_textFirstName.Text = person.FirstName;
m_textLastName.Text = person.LastName;
m_textPhone.Text = person.PhoneNumber;
if (person.Status == "ACTIVE")
{
m_chkIsActive.Checked = true;
}
else
{
m_chkIsActive.Checked = false;
}
}
}
}
public static ImageData[] GetSampleDatas()
{
List <ImageData> datasetList = new List <ImageData>();
string[] imageFilenames = Directory.GetFiles(DataImageDir, "*.png");
//int i = 0;
//foreach (string imageFile in imageFilenames) {
// ImageData imageData = ImageData.FromFile(imageFile, new float[] { (float)i / (imageFilenames.Length - 1) });
// datasetList.Add(imageData);
// ++i;
//}
// Stick
// 1. 앉음 - 서있음
// 2. 왼쪽 - 오른쪽
// 3. 주먹 - 손으로 V
//AddWithNoise("01.png", new float[] { 1f, 0f, 0f });
//AddWithNoise("02.png", new float[] { 1f, 1f, 0f });
//AddWithNoise("03.png", new float[] { 1f, 0f, 1f });
//AddWithNoise("04.png", new float[] { 1f, 1f, 1f });
//AddWithNoise("05.png", new float[] { 0f, 0f, 0f });
//AddWithNoise("06.png", new float[] { 0f, 1f, 0f });
//AddWithNoise("07.png", new float[] { 0f, 0f, 1f });
//AddWithNoise("08.png", new float[] { 0f, 1f, 1f });
//AddWithNoise("09.png", new float[] { 0.5f, 0.5f, 0.5f });
//AddWithNoise("10.png", new float[] { 0.5f, 0f, 0.5f });
//AddWithNoise("11.png", new float[] { 0.5f, 1f, 0.5f });
// Character
// 1. 여캐 - 남캐
// 2. 모자안씀 - 모자씀
// 3. 단발 - 포니테일 - 장발
AddWithNoise("00.png", new float[] { 0f, 1f, 0.5f });
AddWithNoise("01.png", new float[] { 0f, 0f, 1f });
AddWithNoise("02.png", new float[] { 0f, 0f, 0f });
AddWithNoise("03.png", new float[] { 0f, 1f, 0f });
AddWithNoise("04.png", new float[] { 0f, 0f, 1f });
AddWithNoise("05.png", new float[] { 0f, 0f, 0.5f });
AddWithNoise("06.png", new float[] { 0f, 0f, 0.5f });
AddWithNoise("07.png", new float[] { 0f, 0f, 1f });
AddWithNoise("08.png", new float[] { 0f, 1f, 0f });
AddWithNoise("09.png", new float[] { 0f, 1f, 0f });
AddWithNoise("10.png", new float[] { 0f, 1f, 1f });
AddWithNoise("11.png", new float[] { 1f, 1f, 0f });
AddWithNoise("12.png", new float[] { 1f, 1f, 0f });
AddWithNoise("13.png", new float[] { 1f, 1f, 0f });
AddWithNoise("14.png", new float[] { 1f, 0f, 0f });
AddWithNoise("15.png", new float[] { 1f, 0f, 1f });
AddWithNoise("16.png", new float[] { 1f, 0f, 1f });
AddWithNoise("17.png", new float[] { 1f, 1f, 1f });
return(datasetList.ToArray());
void AddWithNoise(string filename, float[] input)
{
for (int i = 0; i < 3; ++i)
{
datasetList.Add(FromFile(filename, DatasetUtility.GetNoiseArray(NoiseCount).Concat(input).ToArray(), input));
}
}
}
public async void TrainImageData(int epochs, int GanBatchSize = 1, int localEpochs = 1)
{
// Make Discriminator dataset
ImageData[] sampleDatas = ImageData.GetSampleDatas();
for (int epochI = 0; epochI < epochs; ++epochI)
{
await Task.Delay(50);
if (MainWindow.Instance.PauseTrainCheckBox.IsChecked.Value)
{
continue;
}
Console.WriteLine($"Epoch {epochI} / {epochs}.");
if (epochI % 10 == 0)
{
WriteableBitmap checkpointBitmap = PredictImage(MainWindow.Instance.constantNoise.Concat(new float[] {
0f, 0f, 0f,
}).ToArray());
try {
string filename = $"PredictImage/Predict_{epochI}.png";
Directory.CreateDirectory(Path.GetDirectoryName(filename));
using (FileStream stream = new FileStream(filename, FileMode.Create)) {
PngBitmapEncoder encoder = new PngBitmapEncoder();
encoder.Frames.Add(BitmapFrame.Create(checkpointBitmap));
encoder.Save(stream);
}
} catch (Exception ex) {
Console.WriteLine($"Failed to save predict bitmap. {ex}");
}
}
// Add real data
List <float[]> inputList = new List <float[]>();
List <float[]> outputList = new List <float[]>();
for (int i = 0; i < sampleDatas.Length; ++i)
{
ImageData sampleData = sampleDatas[i];
inputList.Add(sampleData.output.Concat(sampleData.manualInput).ToArray());
outputList.Add(new float[] { 1f });
}
// Add fake data
for (int i = 0; i < 20; ++i)
{
float[] fakePixels = PredictPixels(DatasetUtility.GetNoiseArray(ImageData.TotalInputShape), false);
inputList.Add(fakePixels);
outputList.Add(new float[] { 0f });
}
float[,] inputs = inputList.GetMultiDim();
float[,] outputs = outputList.GetMultiDim();
// Train Discriminator
discriminatorModel.SetTrainable(true);
discriminatorModel.Fit(inputs, outputs, batch_size: inputs.GetLength(0), epochs: localEpochs, verbose: 1);
// Make GAN dataset
inputList.Clear();
outputList.Clear();
for (int batchI = 0; batchI < GanBatchSize; ++batchI)
{
inputList.Add(DatasetUtility.GetNoiseArray(ImageData.TotalInputShape));
outputList.Add(new float[] { 1f });
}
inputs = inputList.GetMultiDim();
outputs = outputList.GetMultiDim();
// Train GAN
discriminatorModel.SetTrainable(false);
ganModel.Fit(inputs, outputs, batch_size: inputs.GetLength(0), epochs: localEpochs, verbose: 1);
//SaveModel();
}
Console.WriteLine($"Complete Train.");
//float[] predicts = model.Predict(x).GetData<float>();
//Stopwatch watch = new Stopwatch();
//watch.Start();
//for (int i = 0; i < 1; ++i) {
// predicts = model.Predict(x, verbose: 0).GetData<float>();
// //Debug.WriteLine($"Result: ({string.Join(",", predicts)})");
//}
//watch.Stop();
//MainWindow.Instance.Dispatcher.BeginInvoke(new Action(() => {
// MainWindow.Instance.DebugTextBox.Text = watch.GetElapsedMilliseconds().ToString();
//}));
}
