internal AnimationSequenceTemplate(
SequenceJsonRepresentation json,
Dictionary <string, Keyframe <TBoneParameters, TKeyframeParameters, TBoneAttributes> > keyframes
)
{
if (string.IsNullOrEmpty(json.Name))
{
throw new InvalidDataException("Keyframe must have name.");
}
this.name = json.Name;
if (json.Transitions == null)
{
this.transitions = new List <FrameTransition <TBoneParameters, TKeyframeParameters, TBoneAttributes> >().AsReadOnly();
return;
}
var transitions = new List <FrameTransition <TBoneParameters, TKeyframeParameters, TBoneAttributes> >();
FrameTransition <TBoneParameters, TKeyframeParameters, TBoneAttributes> lastTransition = null;
foreach (var t in json.Transitions)
{
lastTransition = new FrameTransition <TBoneParameters, TKeyframeParameters, TBoneAttributes>(t, keyframes, lastTransition);
transitions.Add(lastTransition);
this.duration = lastTransition.EndTime;
}
this.transitions = transitions.AsReadOnly();
}
protected override void DoCompareFrames(FrameTransition transition)
{
RGBData frame1 = transition.Frame1;
RGBData frame2 = transition.Frame2;
int index = transition.Index;
if (outputImageData == null)
{
outputImageData = new ImageData(new Bitmap(frames, frame1.Rows * 3));
outputImageData.Lock();
}
for (int i = 0; i < frame1.Rows; i++)
{
outputImageData.Data.SetR(counter, i, frame1.GetR(frame1.Columns / 4, i));
outputImageData.Data.SetG(counter, i, frame1.GetG(frame1.Columns / 4, i));
outputImageData.Data.SetB(counter, i, frame1.GetB(frame1.Columns / 4, i));
outputImageData.Data.SetR(counter, i + frame1.Rows, frame1.GetR(frame1.Columns / 2, i));
outputImageData.Data.SetG(counter, i + frame1.Rows, frame1.GetG(frame1.Columns / 2, i));
outputImageData.Data.SetB(counter, i + frame1.Rows, frame1.GetB(frame1.Columns / 2, i));
outputImageData.Data.SetR(counter, i + frame1.Rows * 2, frame1.GetR(frame1.Columns * 3 / 4, i));
outputImageData.Data.SetG(counter, i + frame1.Rows * 2, frame1.GetG(frame1.Columns * 3 / 4, i));
outputImageData.Data.SetB(counter, i + frame1.Rows * 2, frame1.GetB(frame1.Columns * 3 / 4, i));
}
}
protected override void DoCompareFrames(FrameTransition frameTransition)
{
RGBData frame1 = frameTransition.Frame1;
RGBData frame2 = frameTransition.Frame2;
int index = frameTransition.Index;
double sum = 0;
for (int row = 0; row < frame1.Rows; row++)
{
for (int col = 0; col < frame1.Columns; col++)
{
double i1 = rFactor * frame1.GetR(col, row) +
gFactor * frame1.GetG(col, row) +
bFactor * frame1.GetB(col, row);
sum += i1;
}
}
result[index] = sum / (frame1.Columns * frame1.Rows);
}
protected abstract void DoCompareFrames(FrameTransition frameTransition);
public Task <double[]> Calculate(IVideoData data)
{
Func <double[]> func = () =>
{
frameCount = data.FrameCount;
DoInitialize(frameCount);
completed = 0;
maxFrameLock = new Semaphore(maxOpenFrames, maxOpenFrames);
completeLock = new Semaphore(1, 1);
completeLock.WaitOne();
data.CurrentFrame = 0;
RGBData frame1 = null;
ImageData data1 = data.GetNextFrame();
if (data1 != null)
{
data1.Lock();
frame1 = data1.Data;
}
RGBData frame2 = null;
ImageData data2 = data.GetNextFrame();
if (data2 != null)
{
data2.Lock();
frame2 = data2.Data;
}
int counter = 0;
while (data2 != null)
{
maxFrameLock.WaitOne();
FrameTransition frameTransition = new FrameTransition(frame1, frame2, counter++);
ThreadPool.QueueUserWorkItem(new WaitCallback((state) =>
{
DoCompareFrames(frameTransition);
maxFrameLock.Release();
Interlocked.Increment(ref completed);
if (completed >= frameCount - 1)
{
completeLock.Release();
}
}));
frame1 = frame2;
data2 = data.GetNextFrame();
if (data2 != null)
{
data2.Lock();
frame2 = data2.Data;
}
}
completeLock.WaitOne();
double[] results = DoComputeData();
completeLock.Release();
return(results);
};
return(Task <double[]> .Run(func));
}
protected override void DoCompareFrames(FrameTransition transition)
{
RGBData frame1 = transition.Frame1;
RGBData frame2 = transition.Frame2;
int index = transition.Index;
int[,,,,] histogram1 = new int[areas, areas, buckets, buckets, buckets];
int[,,,,] histogram2 = new int[areas, areas, buckets, buckets, buckets];
int factor = 256 / buckets;
double colSize = frame1.Columns / (double)areas;
double rowSize = frame2.Rows / (double)areas;
for (int row = 0; row < frame1.Rows; row++)
{
for (int col = 0; col < frame1.Columns; col++)
{
int r1 = frame1.GetR(col, row);
int g1 = frame1.GetG(col, row);
int b1 = frame1.GetB(col, row);
histogram1[(int)(col / colSize), (int)(row / rowSize), r1 / factor, g1 / factor, b1 / factor]++;
int r2 = frame2.GetR(col, row);
int g2 = frame2.GetG(col, row);
int b2 = frame2.GetB(col, row);
histogram2[(int)(col / colSize), (int)(row / rowSize), r2 / factor, g2 / factor, b2 / factor]++;
}
}
List <int> sums = new List <int>();
for (int row = 0; row < areas; row++)
{
for (int col = 0; col < areas; col++)
{
int sum = 0;
for (int k = 0; k < buckets; k++)
{
for (int j = 0; j < buckets; j++)
{
for (int i = 0; i < buckets; i++)
{
sum += Math.Abs(histogram1[col, row, i, j, k] - histogram2[col, row, i, j, k]);
}
}
}
sums.Add(sum);
}
}
int removeCount = (int)(sums.Count * percentRemove);
if (removeCount > 0)
{
sums = sums.OrderBy(s => s).ToList();
for (int i = 0; i < removeCount; i++)
{
sums.RemoveAt(sums.Count - 1);
}
}
double max = frame1.Columns * frame1.Rows * 2 - (colSize * rowSize * removeCount);
result[index] = sums.Sum() / max;
}
