private void initalizeHistograms()
{
int[] binSizes = new int[] { 32, 32 }; //X bins per channel
IntRange[] ranges = new IntRange[]
{
new IntRange(0, 180), //Hue (for 8bpp image hue>> range is (0-180) otherwise (0-360)
new IntRange(0, 255)
};
originalObjHist = new DenseHistogram(binSizes, ranges);
backgroundHist = originalObjHist.CopyBlank();
}
private static unsafe void calculateHistByte(DenseHistogram hist, IImage[] channels, Image<Gray<byte>> mask)
{
/******************************* prepare data *****************************/
float* bins = (float*)hist.HistogramData;
float[][] valueToIndexMultipliers = hist.ValueToIndexMultipliers;
int[] strides = hist.Strides;
int width = channels[0].Width;
int height = channels[0].Height;
int channelStride = channels[0].Stride;
int numDimensions = channels.Length;
byte*[] channelPtrs = new byte*[channels.Length];
for (int i = 0; i < channelPtrs.Length; i++)
{
channelPtrs[i] = (byte*)channels[i].ImageData;
}
byte* maskPtr = (byte*)mask.ImageData;
int maskStride = mask.Stride;
/******************************* prepare data *****************************/
for (int row = 0; row < height; row++)
{
for (int col = 0; col < width; col++)
{
if (maskPtr[col] == 0)
continue;
float* binsTemp = bins;
for (int d = 0; d < numDimensions; d++)
{
var idxDecimal = channelPtrs[d][col] * valueToIndexMultipliers[d][0] + valueToIndexMultipliers[d][1];
int idx = (int)(idxDecimal);
binsTemp += idx * strides[d];
//index checking
Debug.Assert(idx >= 0 && idx < hist.binSizes[d], string.Format("Calculated index does not match specified bin size. Dimension = {0}", d));
}
binsTemp[0]++;
}
for (int d = 0; d < numDimensions; d++)
channelPtrs[d] += channelStride;
maskPtr += maskStride;
}
}
private static void backProjectByte(DenseHistogram hist, IImage[] channels, IImage projImg)
{
/******************************* prepare data *****************************/
float* bins = (float*)hist.HistogramData;
float[][] valueToIndexMultipliers = hist.ValueToIndexMultipliers;
int[] strides = hist.Strides;
int width = channels[0].Width;
int height = channels[0].Height;
int channelStride = channels[0].Stride;
int numDimensions = channels.Length;
byte*[] channelPtrs = new byte*[channels.Length];
for (int i = 0; i < channelPtrs.Length; i++)
{
channelPtrs[i] = (byte*)channels[i].ImageData;
}
byte* projImgPtr = (byte*)projImg.ImageData;
int projImgStride = projImg.Stride;
/******************************* prepare data *****************************/
for (int row = 0; row < height; row++)
{
for (int col = 0; col < width; col++)
{
float* binsTemp = bins;
for (int d = 0; d < numDimensions; d++)
{
var idxDecimal = channelPtrs[d][col] * valueToIndexMultipliers[d][0] + valueToIndexMultipliers[d][1];
int idx = (int)(idxDecimal);
binsTemp += idx * strides[d];
}
projImgPtr[col] = (byte)binsTemp[0];
}
for (int d = 0; d < numDimensions; d++)
channelPtrs[d] += channelStride;
projImgPtr += projImgStride;
}
}
private void initTracking(Image<Bgr, byte> frame)
{
//get hue channel from search area
var hsvImg = frame.Convert<Hsv, byte>(); //<<parallel operation>>
//user constraints...
Image<Gray, byte> mask = hsvImg.InRange(new Hsv(0, 0, minV), new Hsv(0, 0, maxV), Byte.MaxValue, 2);
originalObjHist.Calculate(hsvImg.GetSubRect(roi).SplitChannels(0, 1), !false, mask.GetSubRect(roi));
originalObjHist.Scale((float)1 / roi.Area());
//originalObjHist.Normalize(Byte.MaxValue);
var backgroundArea = roi.Inflate(1.5, 1.5, frame.Size);
backgroundHist.Calculate(hsvImg.GetSubRect(backgroundArea).SplitChannels(0, 1), !false, mask.GetSubRect(backgroundArea));
backgroundHist.Scale((float)1 / backgroundArea.Area());
//backgroundHist.Normalize(Byte.MaxValue);
//how good originalObjHist and objHist match (suppresses possible selected background)
ratioHist = originalObjHist.CreateRatioHistogram(backgroundHist, Byte.MaxValue, 10);
searchArea = roi;
roi = Rectangle.Empty;
}
private void initTracking(Bgr<byte>[,] frame)
{
//get hue channel from search area
var hsvImg = frame.ToHsv();
//user constraints...
Gray<byte>[,] mask = hsvImg.InRange(new Hsv<byte>(0, 0, (byte)minV), new Hsv<byte>(0, 0, (byte)maxV), Byte.MaxValue, 2);
originalObjHist.Calculate(hsvImg.SplitChannels<Hsv<byte>, byte>(roi, 0, 1), !false, mask, roi.Location);
originalObjHist.Scale((float)1 / roi.Area());
//originalObjHist.Normalize(Byte.MaxValue);
var backgroundArea = roi.Inflate(1.5, 1.5, frame.Size());
backgroundHist.Calculate(hsvImg.SplitChannels<Hsv<byte>, byte>(backgroundArea, 0, 1), !false, mask, backgroundArea.Location);
backgroundHist.Scale((float)1 / backgroundArea.Area());
//backgroundHist.Normalize(Byte.MaxValue);
//how good originalObjHist and objHist match (suppresses possible selected background)
ratioHist = originalObjHist.CreateRatioHistogram(backgroundHist, Byte.MaxValue, 10);
searchArea = roi;
roi = Rectangle.Empty;
}
private static void initalize(DenseHistogram hist, int[] binSizes, IntRange[] ranges)
{
hist.binSizes = binSizes;
hist.ranges = ranges;
var valueToIndexMultipliers = new float[binSizes.Length][];
/***********************************************************************************/
// binSizes[i]
//idx = (val - range[i].Min) * -----------------------------------
// range[i].Max - range[i].Min + 1
for (int bin = 0; bin < binSizes.Length; bin++)
{
valueToIndexMultipliers[bin] = new float[2];
valueToIndexMultipliers[bin][0] = (float)binSizes[bin] / (ranges[bin].Max - ranges[bin].Min + 1);
valueToIndexMultipliers[bin][1] = -ranges[bin].Min * valueToIndexMultipliers[bin][0];
}
hist.valueToIndexMultipliers = valueToIndexMultipliers;
/***********************************************************************************/
/***********************************************************************************/
var strides = new int[binSizes.Length];
strides[binSizes.Length - 1] = 1;
for (int bin = (binSizes.Length - 1) - 1; bin >= 0; bin--)
{
strides[bin] = strides[bin + 1] * (binSizes[bin + 1]);
}
hist.strides = strides;
/***********************************************************************************/
hist.NumberOfElements = binSizes.Aggregate((a, b) => a * b);
hist.histogram = new float[hist.NumberOfElements];
hist.histogramHandle = GCHandle.Alloc(hist.histogram, GCHandleType.Pinned);
hist.histPtr = (float*)hist.histogramHandle.AddrOfPinnedObject();
}
/// <summary>
/// Creates ratio histogram [0.. <paramref name="histogramsNormalizationFactor"/>].
/// </summary>
/// <param name="hist2">Second histogram. This histogram will be element-wise dived with it. Both histograms must be normalized to the same value!</param>
/// <param name="histogramsNormalizationFactor">Histogram normalization factor. The maximum value in the ratio histogram will be the provided value.</param>
/// <param name="hist2Gain">Second histogram gain.</param>
/// <returns>Normalized ratio histogram</returns>
public unsafe DenseHistogram CreateRatioHistogram(DenseHistogram hist2, float histogramsNormalizationFactor = 1, float hist2Gain = 1)
{
//histograms must be normalized!
DenseHistogram ratioHist = this.CopyBlank();
float* hist1Ptr = (float*)this.HistogramData;
float* hist2Ptr = (float*)hist2.HistogramData;
float* ratioHistPtr = (float*)ratioHist.HistogramData;
int numOfElems = this.NumberOfElements;
for (int i = 0; i < numOfElems; i++)
{
if (hist2Ptr[i] != 0)
ratioHistPtr[i] = (hist1Ptr[i] / (hist2Gain * hist2Ptr[i])) * histogramsNormalizationFactor;
else
ratioHistPtr[i] = 0; //in original Accord's implementation. Why ?
//ratioHistPtr[i] = hist1Ptr[i];
ratioHistPtr[i] = System.Math.Min(histogramsNormalizationFactor, ratioHistPtr[i]);
}
return ratioHist;
}
/// <summary>
/// Gets the same histogram representation but without data. (data is default = zero)
/// </summary>
/// <returns></returns>
public DenseHistogram CopyBlank()
{
DenseHistogram hist = new DenseHistogram();
initalize(hist, (int[])this.binSizes.Clone(), (IntRange[])this.ranges.Clone());
return hist;
}