private void btnTestImage_Click(object sender, EventArgs e)
{
if (LDAClassifier == null)
{
MessageBox.Show("Classifier not trained. Please press Train!");
}
else
{
OpenFileDialog Dialog = new OpenFileDialog();
Dialog.Filter = "jpeg files (*.jpg)|*.jpg|(*.gif)|gif||";
if (DialogResult.OK == Dialog.ShowDialog())
{
ATTFace face = DataUnit.GetATTFace(Dialog.FileName);
double[] projectedPCA = PCAClassifier.ComputeProjection(face.ImageVector); // Do not forget to project in PCA Space
face.ImageVectorTransformed = projectedPCA;
Bitmap TestBitmap = face.getImagesAsBmp();
ShowImage(TestBitmap, picTestImage);
FileInfo fileInfo = new FileInfo(Dialog.FileName);
lblTestImage.Text = fileInfo.Name;
int guessID = LDAClassifier.PredictClassInProjectedSpace(face);
MessageBox.Show("Guessed Class: " + guessID);
List <ATTFace> BestFaces = LDAClassifier.FacesByClass[guessID].FacesInClass; //By default, we print the images in the class
DisplayBestMatches(BestFaces);
}
}
}
private void button3_Click(object sender, EventArgs e)
{
if (PCAClassifier == null)
{
MessageBox.Show("Classifiers have not been trained. Please press Train first!");
}
else
{
String folderName = "C:\\Users\\chris\\Documents\\UNIVERSITY OF BRIDGEPORT\\2020SP Semester\\CPEG 585 - Computer Vision\\ATTFaceDataSet\\Testing";
List <ATTFace> TrainingFaces = DataUnit.GetTestingData(folderName);
PCAClassifier.CalculateProjectedImages(TrainingFaces);
double accuracy = LDAClassifier.ComputeAccuracy(TrainingFaces);
MessageBox.Show("Current accuracy: " + accuracy * 100 + "%");
}
}
