public void CreateAndCompileModel3()
{
Console.WriteLine("Creating model");
GlobalRandom.InitializeRandom();
int imgSize = 75;
ReluActivation reluActivation = new ReluActivation();
SoftmaxActivation softmaxActivation = new SoftmaxActivation();
model = new ConvolutionalNeuralNetwork(imgSize, "rgb");
model.Add(new ConvolutionalLayer(5, 5, reluActivation, "valid"));
model.Add(new MaxPoolingLayer());
model.Add(new ConvolutionalLayer(5, 3, reluActivation, "valid"));
model.Add(new MaxPoolingLayer());
model.Add(new DropoutLayer(0.2));
model.Add(new FlattenLayer());
model.Add(new DropoutLayer(0.5));
model.Add(new DenseLayer(26, softmaxActivation));
Console.WriteLine("Model created");
model.Compile();
Console.WriteLine("Model compiled");
}
public void CreateAndCompileModel(string jsonPath, string weightsDirectory)
{
Console.WriteLine("Creating model");
GlobalRandom.InitializeRandom();
model = new ConvolutionalNeuralNetwork(jsonPath);
Console.WriteLine("Model created");
model.Compile();
Console.WriteLine("Model compiled");
Console.WriteLine("Reading weights");
//ReadWeightsFromDirectory(weightsDirectory);
ReadWeightsFromDirectory(weightsDirectory);
}
public void CreateAndCompileModelMnist()
{
Console.WriteLine("Creating model");
GlobalRandom.InitializeRandom();
int imgSize = 28;
NoActivation noActivation = new NoActivation();
SoftmaxActivation softmaxActivation = new SoftmaxActivation();
model = new ConvolutionalNeuralNetwork(imgSize, "grayscale");
model.Add(new ConvolutionalLayer(8, 3, noActivation, "valid"));
model.Add(new MaxPoolingLayer());
model.Add(new FlattenLayer());
model.Add(new DenseLayer(10, softmaxActivation));
Console.WriteLine("Model created");
model.Compile();
Console.WriteLine("Model compiled");
}
