public static YDataFloat GenerateEdgeDetectionAverageAccel(AcceleratorTarget acceleratorTarget, IEnumerable <YDataFloat> edgeMapList)
{
var target = GetAcceleratorTarget(acceleratorTarget);
var firstEdgeMap = edgeMapList.First();
var width = firstEdgeMap.Width;
var height = firstEdgeMap.Height;
var maximum = firstEdgeMap.MaximumValue;
FloatParallelArray fpTotals = null;
var edgeMapCount = 0;
foreach (var edgeMap in edgeMapList)
{
var fpInput = new FloatParallelArray(edgeMap.Data);
if (fpTotals == null)
{
fpTotals = fpInput;
}
else
{
fpTotals = ParallelArrays.Add(fpTotals, fpInput);
}
edgeMapCount++;
}
var fpOutput = ParallelArrays.Divide(fpTotals, edgeMapCount);
var output = target.ToArray2D(fpOutput);
return(new YDataFloat(output, maximum));
}
public static YDataFloat GenerateEdgeDetectedImageAccel(AcceleratorTarget acceleratorTarget, YDataFloat imageData)
{
var target = GetAcceleratorTarget(acceleratorTarget);
var width = imageData.Width;
var height = imageData.Height;
var fpInput = new FloatParallelArray(imageData.Data);
var fpInputX = ParallelArrays.Shift(fpInput, new int[] { 1, 0 });
var fpInputY = ParallelArrays.Shift(fpInput, new int[] { 0, 1 });
var fpDX = ParallelArrays.Subtract(fpInputX, fpInput);
var fpDY = ParallelArrays.Subtract(fpInputY, fpInput);
var fpTotals = ParallelArrays.Add(fpDX, fpDY);
var fpOutput = ParallelArrays.Divide(fpTotals, 2.0f);
fpOutput = ParallelArrays.Add(fpOutput, imageData.MaximumValue / 2.0f);
fpOutput = ParallelArrays.Max(fpOutput, 0.0f);
fpOutput = ParallelArrays.Min(fpOutput, imageData.MaximumValue);
var output = target.ToArray2D(fpOutput);
return(new YDataFloat(output, imageData.MaximumValue));
}
public static void CalculateAverageAndMaximumAccel(AcceleratorTarget acceleratorTarget, float[,] imageData, out float average, out float maximum)
{
var target = GetAcceleratorTarget(acceleratorTarget);
int width = imageData.GetLength(0);
int height = imageData.GetLength(1);
var fpInput = new FloatParallelArray(imageData);
var fpAverage = ParallelArrays.Sum(fpInput);
fpAverage = ParallelArrays.Divide(fpAverage, (float)(width * height));
fpAverage = ParallelArrays.Pad(fpAverage, new int[] { 0 }, new int[] { 1 }, 0.0f);
var fpMaximum = ParallelArrays.MaxVal(fpInput);
fpMaximum = ParallelArrays.Pad(fpMaximum, new int[] { 1 }, new int[] { 0 }, 0.0f);
var fpOutput = ParallelArrays.Add(fpAverage, fpMaximum);
var output = target.ToArray1D(fpOutput);
average = output[0];
maximum = output[1];
}
public static Target GetAcceleratorTarget(AcceleratorTarget acceleratorTarget)
{
if (acceleratorTarget == AcceleratorTarget.DX9)
{
return(_dx9Target);
}
else
{
return(_multicoreTarget);
}
}
public static void AdvanceEdgeDetectionAverageAccel(AcceleratorTarget acceleratorTarget, ref YDataFloat edgeMapAverage, YDataFloat edgeDataNew, YDataFloat edgeDataOld, int edgeMapAverageCount)
{
var target = GetAcceleratorTarget(acceleratorTarget);
var width = edgeMapAverage.Width;
var height = edgeMapAverage.Height;
float edgeMapAverageCountFloat = edgeMapAverageCount;
var fpAverage = new FloatParallelArray(edgeMapAverage.Data);
var fpNew = new FloatParallelArray(edgeDataNew.Data);
var fpOld = new FloatParallelArray(edgeDataOld.Data);
var fpAdjust = ParallelArrays.Subtract(fpNew, fpOld);
fpAdjust = ParallelArrays.Divide(fpAdjust, edgeMapAverageCountFloat);
var fpOutput = ParallelArrays.Subtract(fpAverage, fpAdjust);
var output = target.ToArray2D(fpOutput);
edgeMapAverage = new YDataFloat(output, edgeMapAverage.MaximumValue);
}
