public void GivenIHaveTheLengthOfABigArray_WhenICreateABigArrayTest_AnInstanceIsCreated(int xLength, int yLength, int zLength,
int filledIndex)
{
var random = new Random();
var filledValues = new Dictionary <string, GeneratedValues>();
for (int i = 0; i < filledIndex; i++)
{
var x = random.Next(xLength - 1);
var y = random.Next(yLength - 1);
var z = random.Next(zLength - 1);
filledValues[$"{x},{y},{z}"] = new GeneratedValues(x, y, z, random.NextDouble());
}
using (var array = new NoLohArray3D <double>(xLength, yLength, zLength, true))
{
foreach (var item in filledValues)
{
array[item.Value.X, item.Value.Y, item.Value.Z] = item.Value.Value;
}
foreach (var item in filledValues)
{
array[item.Value.X, item.Value.Y, item.Value.Z].Should().Be(item.Value.Value);
}
}
}
public void GivenIHaveABigArray_WhenISetAnIndexGreaterThanLength_AnExceptionIsThrow(int xLength, int yLength, int zLength,
int xIndex, int yIndex, int zIndex)
{
Action action = () =>
{
using (var noLohArray = new NoLohArray3D <double>(xLength, yLength, zLength))
{
noLohArray[xIndex, yIndex, zIndex] = 10;
}
};
action.ShouldThrow <ArgumentException>();
}
public void GivenIHaveABigArray_WhenIGetANegativeIndex_AnExceptionIsThrow(int xLength, int yLength, int zLength,
int xIndex, int yIndex, int zIndex)
{
Action action = () =>
{
using (var noLohArray = new NoLohArray3D <double>(xLength, yLength, zLength))
{
var value = noLohArray[xIndex, yIndex, zIndex];
}
};
action.ShouldThrow <ArgumentException>();
}
public static IEnumerable <Box> CreateFromMtcnnHeatMap(NoLohArray3D <float> probabilities, NoLohArray4D <float> heatmap, float scale, float threshold)
{
const float stride = 2f;
const float cellSize = 12f;
const int zIndex = 1;
var positions = new ConcurrentBag <(int X, int Y, float Score)>();
Parallel.For(0, probabilities.XLength, x =>
{
for (int y = 0; y < probabilities.YLength; y++)
{
if (probabilities[x, y, zIndex] > threshold)
{
positions.Add((x, y, probabilities[x, y, zIndex]));
}
public static float[,,] NormalizeBatch(this NoLohArray3D <float> image)
{
float[,,] normalizedBatch = new float[image.XLength, image.YLength, image.ZLength];
Parallel.For(0, image.XLength, Bootstrapper.Instance.MaxDegreeOfParalelism, row =>
{
for (int column = 0; column < image.YLength; column++)
{
for (int channel = 0; channel < image.ZLength; channel++)
{
normalizedBatch[row, column, channel] = (image[row, column, channel] - 127.5f) * 0.0078125f;
}
}
});
return(normalizedBatch);
}
public void ReturnBoundingBoxes_WhenAHeatmapProbabilityIsSupplied()
{
const float threshold = 0.7f;
const float scale = 0.5f;
using (var probabilities = new NoLohArray3D <float>(50, 50, 2))
using (var heatmap = new NoLohArray4D <float>(1, 50, 50, 4))
{
probabilities[2, 4, 1] = 0.8f;
probabilities[4, 8, 1] = 0.9f;
var boxes = Box.CreateFromMtcnnHeatMap(probabilities, heatmap, scale, threshold);
boxes.Should().NotBeEmpty();
boxes.Should().HaveCount(2);
boxes.Should().Contain(item =>
item.MinX == 8 && item.MaxX == 32 && item.MinY == 16 && item.MaxY == 40 && Math.Abs(item.Score - 0.8f) < Bootstrapper.FloatTolerance);
boxes.Should().Contain(item =>
item.MinX == 16 && item.MaxX == 40 && item.MinY == 32 && item.MaxY == 56 && Math.Abs(item.Score - 0.9f) < Bootstrapper.FloatTolerance);
}
}