public static void Enter(PostureRecognition <Skeleton, string> postureRecognition, List <Skeleton> lista, string output)
{
foreach (Skeleton skel in lista)
{
postureRecognition.enterPosture(skel, output);
}
}
public void PostureDataReady(Posture posture)
{
if (!training.isFinish())
{
if (PostureRecognition.matches(posture, training.getPosture()))
{
LogUtil.log("匹配成功。");
nextPosture(true);
}
}
}
public static void Main(string[] args)
{
PostureRecognition <Skeleton, string> postureRecognition = new PostureRecognition <Skeleton, string>(PatternType.AnglePatternElbowKnee, DataTrainingType.DataTrainingFile, 1000000);
FileStream fs = new FileStream("Test2.txt", FileMode.Create);
// First, save the standard output.
TextWriter tmp = Console.Out;
StreamWriter sw = new StreamWriter(fs);
Console.SetOut(sw);
Console.WriteLine("ITERACION : " + postureRecognition.training() + "-------------------------------------------------------\n");
Console.WriteLine("VIDEO1 " + "-------------------------------------------------------");
File.WriteAllBytes("save.dat", ToByteArray(postureRecognition));
var lista = FromByteArray <List <Skeleton> >(File.ReadAllBytes("TRAINING_DATA2/video"));
foreach (Skeleton skel in lista)
{
var x = postureRecognition.Predict(skel);
if (x != null && x.Length > 0)
{
Console.WriteLine(x);
}
}
//Console.WriteLine("VIDEO2 " + "-------------------------------------------------------");
//lista = FromByteArray<List<Skeleton>>(File.ReadAllBytes("TRAINING_DATA2/video2"));
//foreach (Skeleton skel in lista)
//{
// var x = postureRecognition.Predict(skel);
// if (x != null && x.Length > 0)
// Console.WriteLine(x);
// else
// {
// Console.WriteLine("NO RECONOCIDO");
// }
//}
Console.SetOut(tmp);
sw.Close();
}
static void Main(string[] args)
{
PostureRecognition <Skeleton, string> postureRecognition = new PostureRecognition <Skeleton, string>(PatternType.AnglePatternElbowKnee, DataTrainingType.DataTrainingFile, 100000);
//1000000
//Console.WriteLine("MOSTRANDO DATOS BRUTOS" + "---------------------------------------------------");
//List<Pose> poselist = LoadData("TRAINING_DATA3");
//printPoses(poselist);
//Console.WriteLine("ITERACION : " + postureRecognition.training() + "-------------------------------------------------------\n");
Console.WriteLine("TESTING" + "-------------------------------------------------------");
postureRecognition = ReadWriteObjectFile.FromByteArray <PostureRecognition <Skeleton, string> >(Convert.FromBase64String(DbServices.GetTrainingRed("octavo", "posture")));
String folderPath = "TESTING";
int counter;
foreach (string file in Directory.EnumerateFiles(folderPath, "*.TD"))
{
var readFile = File.ReadAllBytes(file);
var skeletonList = ReadWriteObjectFile.FromByteArray <List <Skeleton> >(readFile);
counter = 0;
foreach (Skeleton skel in skeletonList)
{
if (counter == 7)
{
break;
}
var x = postureRecognition.Predict(skel);
if (x != null && x.Length > 0)
{
Console.Write(x + "\n");
}
counter++;
}
}
}
public static MyPostureTraining create1()
{
MyPostureTraining training = new MyPostureTraining();
using (StreamReader sr = new StreamReader(Constant.BASE_PATH + "/data/data1/data.txt"))
{
for (int i = 1; i <= 9; i++)
{
Posture pos = new Posture(PostureType.Both);
List <VectorType> vectorTypeList = PostureRecognition.getVectorTypeList(PostureType.Both);
pos.setPic(Constant.BASE_PATH + "/data/data1/" + i + "_color.jpg");
foreach (VectorType type in vectorTypeList)
{
string[] lineData = sr.ReadLine().Split(',');
pos.setVector(type, new Vector(double.Parse(lineData[0]), double.Parse(lineData[1]), double.Parse(lineData[2])));
}
sr.ReadLine();
training.PostureList.Add(pos);
}
}
return(training);
}
private void WindowLoaded(object sender, RoutedEventArgs e)
{
// Create the drawing group we'll use for drawing
this.drawingGroup = new DrawingGroup();
// Create an image source that we can use in our image control
this.imageSource = new DrawingImage(this.drawingGroup);
// Display the drawing using our image control
Image.Source = this.imageSource;
// Look through all sensors and start the first connected one.
// This requires that a Kinect is connected at the time of app startup.
// To make your app robust against plug/unplug,
// it is recommended to use KinectSensorChooser provided in Microsoft.Kinect.Toolkit (See components in Toolkit Browser).
foreach (var potentialSensor in KinectSensor.KinectSensors)
{
if (potentialSensor.Status == KinectStatus.Connected)
{
this.sensor = potentialSensor;
break;
}
}
if (null != this.sensor)
{
TransformSmoothParameters smoothingParam = new TransformSmoothParameters();
smoothingParam.Smoothing = 0.7f;
smoothingParam.Correction = 0.3f;
smoothingParam.Prediction = 1.0f;
smoothingParam.JitterRadius = 1.0f;
smoothingParam.MaxDeviationRadius = 1.0f;
// Turn on the skeleton stream to receive skeleton frames
this.sensor.SkeletonStream.Enable(smoothingParam);
// Add an event handler to be called whenever there is new color frame data
this.sensor.SkeletonFrameReady += this.SensorSkeletonFrameReady;
//------------------------------------------------ CREATE AND SAVE TRAINING RED----------------------------------------
postureRecognition = new PostureRecognition <Skeleton, string>(PatternType.AnglePatternElbowKnee, DataTrainingType.DataTrainingFile, 100000);
postureRecognition.training();
string code = Convert.ToBase64String(ReadWriteObjectFile.ObjectToByteArray(postureRecognition));
DbServices.AddTrainingRed("noveno", code, "posture");
//---------------------------------------------------------------------------------------------------------------------
//------------------------------------------------ LOAD TRAINIG RED FROM DATABASE -------------------------------------
//postureRecognition = ReadWriteObjectFile.FromByteArray<PostureRecognition<Skeleton, string>>(Convert.FromBase64String(DbServices.GetTrainingRed("seven", "posture")));
//---------------------------------------------------------------------------------------------------------------------
//ipAdress = System.Net.IPAddress.Parse("192.168.0.6");
//ipEndpoint = new IPEndPoint(ipAdress, 19834);
//client = new Socket(ipAdress.AddressFamily, SocketType.Stream, ProtocolType.Tcp);
//client.Connect(ipEndpoint);
//ExecuteThreadServiceAsync();
//StartSocketListenner();
// Start the sensor!
try
{
this.sensor.Start();
}
catch (IOException)
{
this.sensor = null;
}
}
/*
* // Turn on the skeleton stream to receive skeleton frames
* this.sensor.SkeletonStream.Enable();
*
* // Add an event handler to be called whenever there is new color frame data
* this.sensor.SkeletonFrameReady += this.SensorSkeletonFrameReady;
*
* // Start the sensor!
* try
* {
* this.sensor.Start();
* }
* catch (IOException)
* {
* this.sensor = null;
* }
* }
*/
if (null == this.sensor)
{
this.statusBarText.Text = Properties.Resources.NoKinectReady;
}
}
private void kinectSensor_SkeletonFrameReady(object sender, SkeletonFrameReadyEventArgs e)
{
if (pause)
{
return;
}
Skeleton[] skeletons = new Skeleton[0];
using (SkeletonFrame skeletonFrame = e.OpenSkeletonFrame())
{
if (skeletonFrame != null)
{
skeletons = new Skeleton[skeletonFrame.SkeletonArrayLength];
skeletonFrame.CopySkeletonDataTo(skeletons);
}
}
using (DrawingContext dc = this.drawingGroup.Open())
{
// Draw a transparent background to set the render size
dc.DrawRectangle(Brushes.Black, null, new Rect(0.0, 0.0, RenderWidth, RenderHeight));
if (skeletons.Length != 0)
{
foreach (Skeleton skel in skeletons)
{
RenderClippedEdges(skel, dc);
if (skel.TrackingState == SkeletonTrackingState.Tracked)
{
this.DrawBonesAndJoints(skel, dc);
index++;
if (actionState)
{
BitmapSource colorFrame = (BitmapSource)this.colorImageElement.Source;
//BitmapSource skeletonFrame = (BitmapSource)this.skeletonImageElement.Source;
actionData.add(colorFrame, null, skel);
}
if (index == 30)
{
index = 0;
Posture posture = PostureRecognition.computePosture(skel, PostureType.Both);
Text_PostureData.Text = posture.toJsonString();
}
}
else if (skel.TrackingState == SkeletonTrackingState.PositionOnly)
{
dc.DrawEllipse(
this.centerPointBrush,
null,
this.SkeletonPointToScreen(skel.Position),
BodyCenterThickness,
BodyCenterThickness);
}
}
}
// prevent drawing outside of our render area
this.drawingGroup.ClipGeometry = new RectangleGeometry(new Rect(0.0, 0.0, RenderWidth, RenderHeight));
}
}
