private void CreateBitMapFromDepthFrame(DepthImageFrame frame)
{
if (frame != null)
{
// get image from frame
short[] depthPixels = new short[frame.PixelDataLength];
short[] secondDepthPixels = new short[frame.PixelDataLength];
frame.CopyPixelDataTo(depthPixels);
Array.Copy(depthPixels, secondDepthPixels, frame.PixelDataLength);
// find closest point in depth frame (in millimeters)
this.rawDepthFrame = new DepthFrame() { Pixels = depthPixels, Height = frame.Height, Width = frame.Width};
this.croppedFrame = this.floodFill.Process(depthPixels, frame.Height, frame.Width);
this.sensor.DepthStream.Range = this.floodFill.ClosestDistance < 1000 ? DepthRange.Near : DepthRange.Default;
if (this.FrameReady != null)
{
this.FrameReady(this, new DepthFrameEventArgs()
{
Frame = this.croppedFrame
});
}
switch (this.mode)
{
case ProgramMode.Classifying:
this.Classify();
break;
case ProgramMode.Learning:
this.Train();
break;
}
}
}
public void ClassifyImage(DepthFrame croppedFrame)
{
double ratio = ((double)croppedFrame.Width) / (croppedFrame.Width + croppedFrame.Height);
// Ignore too big/small cropped images and broken case.
if (croppedFrame.Width < 200 && croppedFrame.Height < 200 && croppedFrame.Width >= 10 && croppedFrame.Height >= 10 && ratio > 0.2 && ratio < 0.8)
{
short[,] imageData = MatrixUtil.RawFrameTo2D(croppedFrame.Pixels, croppedFrame.Height, croppedFrame.Width);
// queue classifer
if (!this.classifying)
{
this.classifying = true;
ThreadPool.QueueUserWorkItem(new WaitCallback(Classify), imageData);
}
}
else
{
// too big
this.category = 0;
if (this.CategoryDetected != null)
{
this.CategoryDetected(this, new CategoryEventArgs() { CategoryLabel = this.category });
}
}
}
public void LearnGesture(DepthFrame croppedFrame)
{
if (croppedFrame.Width < 200 && croppedFrame.Height < 200 && croppedFrame.Width > 50 && croppedFrame.Height > 50)
{
short[,] imageData = MatrixUtil.RawFrameTo2D(croppedFrame.Pixels, croppedFrame.Height, croppedFrame.Width);
// queue trainer
if (!this.learning && !this.GestureDataReady)
{
this.learning = true;
ThreadPool.QueueUserWorkItem((state) =>
{
this.Learn(imageData);
});
}
}
}