public async Task HandleData(SensorOrientation expected, byte[] response)
{
SensorOrientation?actual = null;
await accelerometer.Orientation.AddRouteAsync(source => source.Stream(data => actual = data.Value <SensorOrientation>()));
platform.sendMockResponse(response);
Assert.That(actual, Is.EqualTo(expected));
}
/// <summary>
/// Main entry point.
/// </summary>
public static void Main()
{
// camera resolution settings
const ColorResolution resolution = ColorResolution.R720p;
const int widthSource = 1280;
const int heightSource = 720;
// down sampled resolution
const int widthOutput = 80;
const int heightOutput = 45;
const double scaleFactorWidth = (double)widthOutput / widthSource;
const double scaleFactorHeight = (double)heightOutput / heightSource;
// background subtraction beyond this depth
const double maxDepth = 1.0; // meters
const SensorOrientation initialOrientation = SensorOrientation.Default;
using (var pipeline = Pipeline.Create("AzureKinectSample", DeliveryPolicy.LatestMessage))
{
var azureKinect = new AzureKinectSensor(
pipeline,
new AzureKinectSensorConfiguration()
{
OutputImu = true,
ColorResolution = resolution,
DepthMode = DepthMode.WFOV_Unbinned,
CameraFPS = FPS.FPS15,
BodyTrackerConfiguration = new AzureKinectBodyTrackerConfiguration()
{
CpuOnlyMode = true, // false if CUDA supported GPU available
SensorOrientation = initialOrientation,
},
});
StringBuilder sb = new StringBuilder();
SensorOrientation lastOrientation = (SensorOrientation)(-1); // detect orientation changes
// consuming color, depth, IMU, body tracking, calibration
azureKinect.ColorImage.Resize(widthOutput, heightOutput)
.Join(azureKinect.DepthImage)
.Join(azureKinect.Imu, TimeSpan.FromMilliseconds(10))
.Pair(azureKinect.Bodies)
.Pair(azureKinect.DepthDeviceCalibrationInfo)
.Do(message =>
{
var(color, depth, imu, bodies, calib) = message;
public BackgroundTrackingLoop(ref Calibration calibration, SensorOrientation sensorOrientation, float smoothingFactor)
{
var config = new TrackerConfiguration {
SensorOrientation = sensorOrientation
};
tracker = new Tracker(ref calibration, config)
{
TemporalSmoothingFactor = smoothingFactor
};
isRunning = true;
backgroundThread = new Thread(BackgroundLoop)
{
IsBackground = true
};
backgroundThread.Start();
}
public TrackerModel(IApp app, BackgroundReadingLoop readingLoop,
TrackerProcessingMode processingMode, DnnModel dnnModel, SensorOrientation sensorOrientation, float smoothingFactor)
: base(app)
{
// try to create tracking loop first
readingLoop.GetCalibration(out calibration);
trackingLoop = new BackgroundTrackingLoop(in calibration, processingMode, dnnModel, sensorOrientation, smoothingFactor);
trackingLoop.BodyFrameReady += TrackingLoop_BodyFrameReady;
trackingLoop.Failed += BackgroundLoop_Failed;
this.readingLoop = readingLoop;
readingLoop.CaptureReady += ReadingLoop_CaptureReady;
readingLoop.Failed += BackgroundLoop_Failed;
Title = readingLoop.ToString();
// Image and skeleton visualizers for depth
var depthMode = readingLoop.DepthMode;
depthImageVisualizer = ImageVisualizer.CreateForDepth(dispatcher, depthMode.WidthPixels(), depthMode.HeightPixels());
depthSkeletonVisualizer = new SkeletonVisualizer(dispatcher, depthMode.WidthPixels(), depthMode.HeightPixels(), ProjectJointToDepthMap);
// Image and skeleton visualizers for color
var colorRes = readingLoop.ColorResolution;
if (colorRes != ColorResolution.Off)
{
colorImageVisualizer = ImageVisualizer.CreateForColorBgra(dispatcher, colorRes.WidthPixels(), colorRes.HeightPixels());
colorSkeletonVisualizer = new SkeletonVisualizer(dispatcher, colorRes.WidthPixels(), colorRes.HeightPixels(), ProjectJointToColorImage);
bodyIndexMapTransformation = new BodyIndexMapTransformation(in calibration);
}
// Proportions between columns
if (colorRes != ColorResolution.Off)
{
DepthColumnWidth = new GridLength(depthImageVisualizer.WidthPixels, GridUnitType.Star);
ColorColumnWidth = new GridLength(
depthImageVisualizer.HeightPixels * colorImageVisualizer.WidthPixels / colorImageVisualizer.HeightPixels,
GridUnitType.Star);
}
else
{
DepthColumnWidth = new GridLength(1, GridUnitType.Star);
ColorColumnWidth = new GridLength(0, GridUnitType.Pixel);
}
}
public BackgroundTrackingLoop(ref Calibration calibration, bool cpuOnlyMode, SensorOrientation sensorOrientation, float smoothingFactor)
{
var config = new TrackerConfiguration
{
SensorOrientation = sensorOrientation,
ProcessingMode = cpuOnlyMode
? TrackerProcessingMode.Cpu
: TrackerProcessingMode.Gpu
};
tracker = new Tracker(ref calibration, config)
{
TemporalSmoothingFactor = smoothingFactor
};
isRunning = true;
backgroundThread = new Thread(BackgroundLoop)
{
IsBackground = true
};
backgroundThread.Start();
}
// enumerate image coordinates while correcting for orientation
static (IEnumerable <int>, IEnumerable <int>, bool)EnumerateCoordinates(SensorOrientation orientation)
{
var w = Enumerable.Range(0, widthOutput);
var h = Enumerable.Range(0, heightOutput);
return(orientation switch
{
SensorOrientation.Clockwise90 => (h.Reverse(), w, true),
SensorOrientation.Flip180 => (w.Reverse(), h.Reverse(), false),
SensorOrientation.CounterClockwise90 => (h, w.Reverse(), true),
_ => (w, h, false), // normal
});
public LeapTransform(SensorOrientation orientation)
{
Orientation = orientation;
}
