private void CreateTestData(FaceData faceData, int idx)
{
AuTestData = new svm_node[MaxAuFeatures];
FppTestData = new svm_node[MaxFppFeatures];
for (int i = 0; i < faceData.au_data.Count; i++)
{
AuTestData[i] = new svm_node();
AuTestData[i].index = i;
AuTestData[i].value = faceData.au_data[i];
}
int index = 0;
int j = 0;
while (index < faceData.point_3D.Count)
{
if (FeaturePoint.ContainsValue(index / 3))
{
FppTestData[j] = new svm_node();
FppTestData[j].index = j;
FppTestData[j].value = faceData.point_3D[index];
j++;
}
index++;
}
ScalingData(AuTestData, AuScaleMin, AuScaleMax, MaxAuFeatures, idx);
ScalingData(FppTestData, FppScaleMin, FppScaleMax, MaxFppFeatures, idx);
}
private void TestSVM(FaceData newData)
{
for (int i = 0; i < 7; i++)
{
//Create test data
CreateTestData(newData, i);
//Get the result of estimation
AuClassLabel[i] = (int)svm.svm_predict(AuModel[i], AuTestData);
FppClassLabel[i] = (int)svm.svm_predict(FppModel[i], FppTestData);
}
}
public void showFace3D(FaceData newData)
{
txtPitch.Content = Math.Round(newData.head3D[0], 0) + "°";
txtYaw.Content = Math.Round(newData.head3D[1], 0) + "°";
txtRoll.Content = Math.Round(newData.head3D[2], 0) + "°";
}
public void process(FaceData newData)
{
try
{
int time_change = (int)mainForm.thisTime.Subtract(fps_lastCheck).TotalSeconds;
if (time_change >= 1)
{
txtFps.Content = "fps " + fps_counter;
fps_lastCheck = mainForm.thisTime;
fps_counter = 0;
}
fps_counter++;
//=====================================================
if (checkRun.IsChecked.Value)
{
//------ Test (Show Data) 以下に自分のコード記述--------------
//initialize class labels of each data
InitializeSVM();
//do classfication using SVM
TestSVM(newData);
for (int i = 0; i < 7; i++)
{
//Remove first element if dictionary size is more than equal 30.
if (AuDictionary[i].Count >= MaxRecordFrame)
{
AuDictionary[i].RemoveAt(0);
}
if (FppDictionary[i].Count >= MaxRecordFrame)
{
FppDictionary[i].RemoveAt(0);
}
//Add the result of classfication
AuDictionary[i].Add(AuClassLabel[i]);
FppDictionary[i].Add(FppClassLabel[i]);
}
//Sum labels
for (int i = 0; i < 7; i++)
{
AuC[i] = AuDictionary[i].Sum();
FppC[i] = FppDictionary[i].Sum();
}
//Get index which sum of labels is the highest
int[] AuMaxEmotionIndex = AuC.Select((item, index) => new { Index = index, Value = item })
.Where(item => item.Value == AuC.Max())
.Select(item => item.Index).ToArray();
int[] FppMaxEmotionIndex = FppC.Select((item, index) => new { Index = index, Value = item })
.Where(item => item.Value == FppC.Max())
.Select(item => item.Index).ToArray();
Random rnd = new Random();
AuMaxEmotionIndex[0] = AuMaxEmotionIndex[rnd.Next(AuMaxEmotionIndex.Count())];
FppMaxEmotionIndex[0] = FppMaxEmotionIndex[rnd.Next(FppMaxEmotionIndex.Count())];
FinalEstimation = (AuC.Max() > FppC.Max()) ? AuMaxEmotionIndex[0] : FppMaxEmotionIndex[0];
//output on Window
currentEmotion = FinalEstimation;
txtOutput.Content = "" + EmotionIndex[FinalEstimation];
showFace3D(newData);
}
}
catch (Exception ex) { TheSys.showError(ex); }
}