static void Main(string[] args)
{
string CifarDataBatch = null;
int how_many = 1;
RANDTYPE randomness = RANDTYPE.UNIFORM;
var p = new OptionSet();
p.Add <string>("dataset=", "CIFAR dataset file name", (x => CifarDataBatch = x));
p.Add <int>("how-many=", "Number of new images per image", (x => how_many = x));
p.Add <string>("randomness=", "Gaussian|Uniform", (x => randomness = (x.Equals("Gaussian") ? RANDTYPE.GAUSSIAN : RANDTYPE.UNIFORM)));
int xoffset = 0;
int yoffset = 0;
bool geometric = false;
p.Add("geometric", "Use geometric transform", (x => geometric = (x != null)));
p.Add <int>("xoffset=", "x-offset for geometric transform", (x => xoffset = x));
p.Add <int>("yoffset=", "y-offset for geometric transform", (x => yoffset = x));
bool random = false;
double epsilon = 0.0;
p.Add("random", "Use random perturbation", (x => random = (x != null)));
p.Add <double>("epsilon=", "Distance (for uniform) or standard deviation (for gaussian) random perturbation", (x => epsilon = x));
bool brightness = false;
double brightness_offset = 0.0;
p.Add("brightness", "Use brightness perturbation", (x => brightness = (x != null)));
p.Add <double>("brightness-offset=", "Brightness offset (<= RobustnessOptions.MaxValue - RobustnessOptions.MinValue)", (x => brightness_offset = x));
bool contrast = false;
double contrast_min_factor = 1.0;
double contrast_max_factor = 1.0;
p.Add("contrast", "Use contrast perturbation", (x => contrast = (x != null)));
p.Add <double>("contrast-min-factor=", "Contrast min factor (0.0-1.0)", (x => contrast_min_factor = x));
p.Add <double>("contrast-max-factor=", "Contrast max factor (0.0-1.0)", (x => contrast_max_factor = x));
bool lossy_jpeg = false;
int photoquality = 90;
p.Add("lossy-jpeg", "Use lossy jpeg perturbation (default photoquality = 90)", (x => lossy_jpeg = (x != null)));
p.Add <int>("jpeg-photoquality=", "Lossy jpeg photoquality", (x => photoquality = x));
bool rotate = false;
float angle = 45.0F;
p.Add("rotation", "Rotation transformation (default angle = 45.0)", (x => rotate = (x != null)));
p.Add <double>("rotation-angle=", (x => angle = (float)x));
bool perturbe_only = false;
p.Add("perturbe-only", "Only perturbe (not augment)", (x => perturbe_only = (x != null)));
Cmd.RunOptionSet(p, args);
if (CifarDataBatch == null)
{
Console.WriteLine("Invalid arguments, use --help");
Environment.Exit(1);
}
/* Initialize parameters */
Options.InitializeNNAnalysis();
// Plain old CIFAR binary format
ImageDataset data = CIFAR.ReadData(CifarDataBatch, CIFAR.ALL_IMAGES, 0);
IAugmentor augmentor = null; // TODO
if (geometric)
{
augmentor = new AugmentGeometric(CIFAR.InputCoordinates, randomness, how_many, xoffset, yoffset);
goto KONT;
}
if (random)
{
augmentor = new AugmentRandom(CIFAR.InputCoordinates, randomness, how_many, epsilon);
goto KONT;
}
if (brightness)
{
augmentor = new AugmentBrightness(CIFAR.InputCoordinates, randomness, how_many, brightness_offset);
goto KONT;
}
if (contrast)
{
augmentor = new AugmentContrast(CIFAR.InputCoordinates, how_many, contrast_min_factor, contrast_max_factor);
goto KONT;
}
if (lossy_jpeg)
{
augmentor = new AugmentLossyJpeg(CIFAR.InputCoordinates, how_many, photoquality);
goto KONT;
}
if (rotate)
{
augmentor = new AugmentRotation(CIFAR.InputCoordinates, how_many, angle);
goto KONT;
}
KONT:
int count = data.Dataset.Count();
ImageDataset initial = null;
if (perturbe_only)
{
initial = new ImageDataset(new Dataset(10), CIFAR.InputCoordinates.ChannelCount,
CIFAR.InputCoordinates.RowCount,
CIFAR.InputCoordinates.ColumnCount, true);
}
else
{
initial = data;
}
for (int i = 0; i < count; i++)
{
double[] datum = data.Dataset.GetDatum(i);
int label = data.Dataset.GetLabel(i);
var augmented = augmentor.Augment(datum);
initial.Update(augmented, label);
}
if (perturbe_only)
{
CIFAR.WriteData(CifarDataBatch + ".perturbed", initial);
}
else
{
CIFAR.WriteData(CifarDataBatch + ".augmented", initial);
}
}
static void Main(string[] args)
{
string MNISTData = null;
string MNISTLabels = null;
int how_many = 1;
RANDTYPE randomness = RANDTYPE.UNIFORM;
var p = new OptionSet();
p.Add("datafile=", "MNIST data file name", x => MNISTData = x);
p.Add("labelfile=", "MNIST label file name", x => MNISTLabels = x);
p.Add <int>("how-many=", "Number of new images per image", (x => how_many = x));
p.Add <string>("randomness=", "Gaussian|Uniform", (x => randomness = (x.Equals("Gaussian") ? RANDTYPE.GAUSSIAN : RANDTYPE.UNIFORM)));
int xoffset = 0;
int yoffset = 0;
bool geometric = false;
p.Add("geometric", "Use geometric transform", (x => geometric = (x != null)));
p.Add <int>("xoffset=", "x-offset for geometric transform", (x => xoffset = x));
p.Add <int>("yoffset=", "y-offset for geometric transform", (x => yoffset = x));
bool random = false;
double epsilon = 0.0;
p.Add("random", "Use random perturbation", (x => random = (x != null)));
p.Add <double>("epsilon=", "Distance (for uniform) or standard deviation (for gaussian) random perturbation", (x => epsilon = x));
bool brightness = false;
double brightness_offset = 0.0;
p.Add("brightness", "Use brightness perturbation", (x => brightness = (x != null)));
p.Add <double>("brightness-offset=", "Brightness offset (<= RobustnessOptions.MaxValue - RobustnessOptions.MinValue)", (x => brightness_offset = x));
bool contrast = false;
double contrast_min_factor = 1.0;
double contrast_max_factor = 1.0;
p.Add("contrast", "Use contrast perturbation", (x => contrast = (x != null)));
p.Add <double>("contrast-min-factor=", "Contrast min factor (0.0-1.0)", (x => contrast_min_factor = x));
p.Add <double>("contrast-max-factor=", "Contrast max factor (0.0-1.0)", (x => contrast_max_factor = x));
Cmd.RunOptionSet(p, args);
if (MNISTData == null || MNISTLabels == null)
{
Console.WriteLine("Invalid arguments, use --help");
Environment.Exit(1);
}
/* Initialize parameters */
Options.InitializeNNAnalysis();
ImageDataset data = MNIST.ReadData(MNISTLabels, MNISTData, MNIST.ALL_IMAGES, 0);
IAugmentor augmentor = null; // TODO
if (geometric)
{
augmentor = new AugmentGeometric(MNIST.InputCoordinates, randomness, how_many, xoffset, yoffset);
goto KONT;
}
if (random)
{
augmentor = new AugmentRandom(MNIST.InputCoordinates, randomness, how_many, epsilon);
goto KONT;
}
if (brightness)
{
augmentor = new AugmentBrightness(MNIST.InputCoordinates, randomness, how_many, brightness_offset);
goto KONT;
}
if (contrast)
{
augmentor = new AugmentContrast(MNIST.InputCoordinates, how_many, contrast_min_factor, contrast_max_factor);
goto KONT;
}
KONT:
int count = data.Dataset.Count();
for (int i = 0; i < count; i++)
{
double[] datum = data.Dataset.GetDatum(i);
int label = data.Dataset.GetLabel(i);
var augmented = augmentor.Augment(datum);
data.Update(augmented, label);
}
MNIST.WriteData(MNISTLabels + ".augmented", MNISTData + ".augmented", data);
}
