//开始手势识别
private bool StartMatch()
{
if (Smooth())
{
ShowSmoothPoint();
CreateVectors();
//识别
if (Mode == RUN_MODE.ACTIVE)
{
if (!TestForMatch())
{
MessageBox.Show("An internal error accured when matching!", "GestureStudy", MessageBoxButtons.OK, MessageBoxIcon.Error);
return(false);
}
else
{
ShowResult();
}
}
//学习
else if (Mode == RUN_MODE.LEARNING)
{
//保存新的手势并重新训练网络
if (MessageBox.Show("Do you want to save this gesture?", "GestureStudy", MessageBoxButtons.YesNo, MessageBoxIcon.Question) == DialogResult.Yes)
{
string name = Microsoft.VisualBasic.Interaction.InputBox("Name for this gesture?", "GestureStudy", "", this.Left + 100, this.Top + 100);
data.AddPattern(Vectors, name);
NumValidPatterns++;
net = new NeuralNet(Useful.NUM_VECTORS * 2, NumValidPatterns, Useful.NUM_HIDDEN_NEURONS, Useful.LEARNING_RATE);
net.SendMessage += new NeuralNet.DelegateOfSendMessage(ShowMessage);
txtState.BackColor = Color.FromKnownColor(KnownColor.Control);
RenewNetwork();
Mode = RUN_MODE.ACTIVE;
}
}
}
else
{
MessageBox.Show("Too few points captured, please draw line slowly!", "GestureStudy", MessageBoxButtons.OK, MessageBoxIcon.Information);
Clear();
ClearDraw();
}
return(true);
}
//初始化数据
private void InitData()
{
Mode = RUN_MODE.UNREADY;
NumValidPatterns = Useful.NUM_PATTERNS;
NumSmoothPoints = Useful.NUM_VECTORS + 1;
HighestOutput = 0.0;
BestMatch = -1;
Match = -1;
RawPath = new List <Point>();
SmoothPath = new List <Point>();
Vectors = new List <double>();
data = new GestureData(NumValidPatterns, Useful.NUM_VECTORS);
net = new NeuralNet(Useful.NUM_VECTORS * 2, NumValidPatterns, Useful.NUM_HIDDEN_NEURONS, Useful.LEARNING_RATE);
net.SendMessage += new NeuralNet.DelegateOfSendMessage(ShowMessage);
}
//使用新的参数重建神经网络
private void RenewNetwork()
{
Useful.LEARNING_RATE = (double)(txtLearning.Value);
Useful.ERROR_THRESHOLD = (double)(txtThreshold.Value);
Useful.NUM_HIDDEN_NEURONS = (int)(txtHidden.Value);
Useful.WITH_MOMENTUM = chkMomentum.Checked;
Useful.MOMENTUM = (double)(txtMomentum.Value);
Useful.WITH_NOISE = chkNoise.Checked;
Useful.MAX_NOISE_TO_ADD = (double)(txtNoise.Value);
net = new NeuralNet(Useful.NUM_VECTORS * 2, NumValidPatterns, Useful.NUM_HIDDEN_NEURONS, Useful.LEARNING_RATE);
net.SendMessage += new NeuralNet.DelegateOfSendMessage(ShowMessage);
txtState.Text = "Training";
TrainNetwork();
txtState.Text = "Ready";
}