public RecognizerResult RecognizeSingleGesture(InputGesture g)
{
var features = mValidFeatures.Take(mValidFeatures.Count - 1).Select(x => Features.AllFeatures.GestureFeatures[x]).ToList();
//Console.WriteLine("{0} features to be checked", features.Count);
var results = new List <GestureWeight>();
foreach (var kvp in mWeights)
{
GestureWeight gw = new GestureWeight()
{
name = kvp.Key
};
for (int i = 0; i < features.Count; i++)
{
float fres = features[i].QueryGesture(g);
gw.weight += kvp.Value[i] * fres;
}
gw.weight += kvp.Value[mValidFeatures.Count - 1];
gw.weight = Utility.Sigmoid(gw.weight);
results.Add(gw);
}
results.Sort();
return(new RecognizerResult()
{
Gesture1 = results[0].name, Confidence1 = (float)results[0].weight,
Gesture2 = results[1].name, Confidence2 = (float)results[1].weight,
Gesture3 = results[2].name, Confidence3 = (float)results[2].weight
});
}
void _CheckIfSegmented()
{
if (mCurrSegmentSize >= _minSegmentSize)
{
Console.WriteLine("Segmented gesture");
LastGesture = InputGesture.FromJointStates(mCurrGesture);
GestureSegmented(this, null);
}
}
static public InputGesture FromJointStates(IEnumerable <JointState> states)
{
InputGesture ig = new InputGesture(null);
ig.States = new List <JointState>(states);
if (ig.States.Count > 0)
{
ig.StartTime = ig.States[0].Timestamp;
}
return(ig);
}
public RecognizerResult RecognizeSingleGesture(InputGesture g)
{
foreach (var js in g.States)
{
if (mFeatures[0].QueryFrame(js) > 0.0f)
{
var res = RecognizerResult.Empty();
res.Gesture1 = "high_kick";
res.Confidence1 = 100.0f;
return(res);
}
}
return(RecognizerResult.Empty());
}
static public void BenchmarkRecognize()
{
var sw = new Stopwatch();
var gest = new InputGesture(new LogFileLoader("gestures/track_high_kick_01.log"));
var numiters = 1000;
sw.Start();
for (int i = 0; i < numiters; i++)
{
foreach (var f in Features.AllFeatures.GestureFeatures)
{
f.QueryGesture(gest);
}
}
sw.Stop();
Console.WriteLine("Elapsed time ({0} iters): {1}", numiters, sw.Elapsed);
Console.WriteLine("Gestures per second: {0}", 1000.0f / (sw.ElapsedMilliseconds / (float)numiters));
}
public RecognizerResult RecognizeSingleGesture(InputGesture g)
{
List <Features.IGestureFeature> features = Features.AllFeatures.GestureFeatures;
var results = new List <GestureWeight>();
foreach (var kvp in mWeights)
{
GestureWeight gw = new GestureWeight()
{
name = kvp.Key
};
gw.weight = kvp.Value[features.Count];
for (int i = 0; i < features.Count; i++)
{
float fres = features[i].QueryGesture(g);
gw.weight += kvp.Value[i] * fres;
}
gw.weight = Math.Exp(gw.weight);
results.Add(gw);
}
double total_weight = 0;
for (int i = 0; i < results.Count; i++)
{
total_weight += results[i].weight;
}
for (int i = 0; i < results.Count; i++)
{
results[i].weight = 1.0 * results[i].weight / total_weight;
}
results.Sort();
return(new RecognizerResult()
{
Gesture1 = results[0].name, Confidence1 = (float)results[0].weight,
Gesture2 = results[1].name, Confidence2 = (float)results[1].weight,
Gesture3 = results[2].name, Confidence3 = (float)results[2].weight
});
}
public RecognizerResult RecognizeSingleGesture(InputGesture g)
{
var results = new List <GestureWeight>();
foreach (var kvp in mWeights)
{
GestureWeight gw = new GestureWeight()
{
name = kvp.Key
};
for (int i = 0; i < mFeatures.Count; i++)
{
bool fp = mFeatures[i].QueryGesture(g);
if (fp)
{
gw.weight += kvp.Value[i * 2];
}
else
{
gw.weight += kvp.Value[i * 2 + 1];
}
}
results.Add(gw);
}
results.Sort();
results.Reverse();
float norm = (float)mFeatures.Count;
return(new RecognizerResult()
{
Gesture1 = results[0].name, Confidence1 = results[0].weight / norm,
Gesture2 = results[1].name, Confidence2 = results[1].weight / norm,
Gesture3 = results[2].name, Confidence3 = results[2].weight / norm
});
}
public bool QueryGesture(InputGesture ig)
{
float result = mFeature.QueryGesture(ig);
return(result >= mMin && result < mMax);
}
public void Run(string[] args)
{
Command c = Recognizer.Command.Help;
if (args.Length > 0)
{
c = (Command)Enum.Parse(typeof(Recognizer.Command), args[0]);
}
if (c == Recognizer.Command.Help)
{
Console.WriteLine("Usage:\n\tFinalProject.exe command [filename]\n\nCommands:");
foreach (var cm in Enum.GetNames(typeof(Recognizer.Command)))
{
Console.WriteLine(cm);
}
return;
}
// For CV
mCV = new CrossValidation("cvindex.txt");
////////////////////
// CHANGE THESE LINES TO SWAP MODELS
////////////////////
mRec = new LogisticRegressionRecognizer();
mSeg = new DumbSegmenter();
Console.WriteLine("Using recognizer {0}", mRec.GetType().ToString());
Console.WriteLine("Using segmenter {0}", mSeg.GetType().ToString());
mRecFilename = "models/" + mRec.GetType().ToString() + ".rec.model";
mSegFilename = "models/" + mSeg.GetType().ToString() + ".seg.model";
mSeg.GestureSegmented += delegate(object sender, EventArgs e) {
var segm = ((ISegmenter)sender).LastGesture;
var recres = mRec.RecognizeSingleGesture(segm);
if (recres.Confidence1 > 0.5f)
{
Console.WriteLine("Recognized gesture: {0}", recres.Gesture1);
}
else
{
Console.WriteLine("Inconclusive");
}
};
string filename = "gestures/track_high_kick_01.log";
if (args.Length > 1)
{
filename = args[1];
}
InputGesture gest;
Thread visthread;
switch (c)
{
case Command.Train:
Train();
break;
case Command.TestSingle:
LoadModels();
var result = mRec.RecognizeSingleGesture(new InputGesture(new LogFileLoader(filename)));
Console.WriteLine(result.ToString());
break;
case Command.TestRecognize:
LoadModels();
var test_gestures = LoadData(mGestureNames, false);
int[] total = Enumerable.Range(0, test_gestures.Count).Select(x => 0).ToArray(),
correct = Enumerable.Range(0, test_gestures.Count).Select(x => 0).ToArray();
int i = 0;
Console.WriteLine();
foreach (var gn in test_gestures)
{
foreach (var tg in gn.Value)
{
total[i]++;
var result2 = mRec.RecognizeSingleGesture(tg);
if (result2.Gesture1 == gn.Key)
{
correct[i]++;
}
}
Console.WriteLine("{0}: {1} correct / {2} total = {3}% correct",
gn.Key,
correct[i], total[i], (float)correct[i] / (float)total[i] * 100.0f);
i++;
}
Console.WriteLine("TEST RESULTS:\n\t{0} correct / {1} total = {2}% correct",
correct.Sum(), total.Sum(), (float)correct.Sum() / (float)total.Sum() * 100.0f);
Utility.PrintMemoryUsage();
break;
case Command.TestRealtime:
LoadModels();
gest = new InputGesture(new LogFileLoader(filename));
visthread = new Thread(new ThreadStart(this.StartVisualize));
visthread.Start();
while (true) // Wait for window to get created
{
lock (this) {
if (mVisWindow != null)
{
break;
}
}
}
float lastTime = gest.States[0].Timestamp;
foreach (var frame in gest.States)
{
mSeg.AddState(frame);
mVisWindow.CurrState = frame;
Thread.Sleep((int)((frame.Timestamp - lastTime) * 750.0f));
lastTime = frame.Timestamp;
}
mSeg.Finish();
visthread.Abort();
break;
case Command.RunRealtime:
LoadModels();
visthread = new Thread(new ThreadStart(this.StartVisualize));
visthread.Start();
while (true) // Wait for window to get created
{
lock (this) {
if (mVisWindow != null)
{
break;
}
}
}
var nfl = new NetworkFrameListener(4711);
nfl.Start();
Console.WriteLine("Press the 'x' key to quit");
while (true)
{
var frame = nfl.GetState();
if (frame != null)
{
var js = JointState.FromRawJointState(frame);
mSeg.AddState(js);
mVisWindow.CurrState = js;
}
if (Console.KeyAvailable)
{
var cki = Console.ReadKey(true);
if (cki.Key == ConsoleKey.X)
{
break;
}
}
if (!nfl.Running)
{
break;
}
Thread.Sleep(0);
}
mSeg.Finish();
nfl.Stop();
visthread.Abort();
break;
case Command.PrintFeatures:
gest = new InputGesture(new LogFileLoader(filename));
/*foreach ( var f in Features.AllFeatures.SingleGestureFeatures ) {
* Console.WriteLine("{0}: {1}", f.ToString(), f.QueryGesture(gest));
* }*/
foreach (var f in Features.AllFeatures.GestureFeatures)
{
Console.WriteLine("{0}: {1}", f.ToString(), f.QueryGesture(gest));
}
break;
case Command.BenchmarkRecognize:
Benchmarks.BenchmarkRecognize();
break;
case Command.CycleCV:
mCV.Incr();
mCV.Save();
break;
}
}
public LateralPositionEnumerable(InputGesture g, int j)
{
parent = g;
joint = j;
System.Diagnostics.Debug.Assert(j >= 0 && j < parent.States[0].RelativeJoints.Length);
}
