I was working on a Face Recognition project. After training the database and calling EigenObjectRecognizer, the result is a black image with an unrecognized label. When the code runs, it looks like this http://www.mediafire.com/view/?ewns4iqvd51adsc . As shown in the figure, the detected and suspected face recognition and extraction in the image window is completely black. And the input image for recognition is exactly the same as the one with which the database is trained. Therefore, he continued to produce an Unknown or Unrecognized result. Part of the code looks
Images from a workout set uploaded as
public FaceRecognizer() { InitializeComponent(); //Load faces from the dataset try { ContTrain = ContTrain + 1; //Load previous trained and labels for each image from the database Here string NameLabelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces/TrainedNameLables.txt"); string[] NameLabels = NameLabelsinfo.Split('%'); NumNameLabels = Convert.ToInt16(NameLabels[0]); string IDLabelsinfo = File.ReadAllText(Application.StartupPath + "/TrainedFaces/TrainedNameLables.txt"); string[] IDLables = IDLabelsinfo.Split('%'); NumIDLabels = Convert.ToInt16(IDLables[0]); if (NumNameLabels == NumIDLabels) { ContTrain = NumNameLabels; string LoadFaces; // Converting the master image to a bitmap for (int tf = 1; tf < NumNameLabels + 1; tf++) { LoadFaces = String.Format("face{0}.bmp", tf); trainingImages.Add(new Image<Gray, byte>(String.Format(" {0}/TrainedFaces/{1}", Application.StartupPath, LoadFaces))); IDLabless.Add(IDLables[tf]); NameLabless.Add(NameLabels[tf]); } } } catch (Exception e) { //Returns the following message if nothing saved in the training set MessageBox.Show("Nothing in binary database, please add at least a face(Simply train the prototype with the Add Face Button).", "Triained faces load",MessageBoxButtons.OK, MessageBoxIcon.Exclamation); } }
Face recognition method looks like
private void RecognizeFaces() { //detect faces from the gray-scale image and store into an array of type // 'var',ie 'MCvAvgComp[]' Image<Gray, byte> grayframe = GetGrayframe(); stringOutput.Add(""); //Assign user-defined Values to parameter variables: MinNeighbors = int.Parse(comboBoxMinNeigh.Text); // the 3rd parameter WindowsSize = int.Parse(textBoxWinSiz.Text); // the 5th parameter ScaleIncreaseRate = Double.Parse(comboBoxScIncRte.Text); //the 2nd //parameter //Detect faces from an image and save it to var it MCvAcgComp[][] var faces = grayframe.DetectHaarCascade(haar, ScaleIncreaseRate, MinNeighbors, HAAR_DETECTION_TYPE.DO_CANNY_PRUNING, new Size(WindowsSize, WindowsSize))[0]; if (faces.Length > 0 && trainingImages.ToArray().Length != 0) { Bitmap ExtractedFace; //empty ExtFaces = new Image<Gray, byte>[faces.Length]; faceNo = 0; foreach (var face in faces) { // ImageFrame.Draw(face.rect, new Bgr(Color.Green), 3); //set the size of the empty box(ExtractedFace) which will later //contain the detected face ExtractedFace = new Bitmap(face.rect.Width, face.rect.Height); ExtFaces[faceNo] = new Image<Gray, byte>(ExtractedFace); ExtFaces[faceNo] = ExtFaces[faceNo].Resize(100, 100, Emgu.CV.CvEnum.INTER.CV_INTER_CUBIC); //TermCriteria for face recognition with numbers of trained images // like maxIteration MCvTermCriteria termCrit = new MCvTermCriteria(ContTrain, 0.001); //Eigen face recognizer EigenObjectRecognizer recognizer = new EigenObjectRecognizer( trainingImages.ToArray(), NameLabless.ToArray(), 700, ref termCrit); stringOutput[faceNo] = recognizer.Recognize(ExtFaces[faceNo]); stringOutput.Add(""); faceNo++; } pbExtractedFaces.Image = ExtFaces[0].ToBitmap(); //draw the face detected // in the 0th (gray) channel with blue color if (stringOutput[0] == "") { label1.Text = "Unknown"; label9.Text = ""; } //Draw the label for each face detected and recognized else { //string[] label = stringOutput[faceNo].Split(','); label1.Text = "Known"; // for (int i = 0; i < 2; i++) //{ label9.Text = stringOutput[0]; //label7.Text = label[1]; //} } } if (faceNo == 0) { MessageBox.Show("No face detected"); } else { btnNextRec.Enabled = true; btnPreviousRec.Enabled = true; } }
The training kit trains with detected faces as follows
private void saveFaceToDB_Click(object sender, EventArgs e) { abd = (Bitmap) pbExtractedFaces.Image; TrainedFaces = new Image<Gray, byte>(abd); trainingImages.Add(TrainedFaces); NameLabless.Add(StudentName.Text); IDLabless.Add(StudentID.Text); //Write the number of trained faces in a file text for further load File.WriteAllText(Application.StartupPath + "/TrainedFaces /TrainedNameLables.txt", trainingImages.ToArray().Length + "%"); File.WriteAllText(Application.StartupPath + "/TrainedFaces /TrainedIDLables.txt", trainingImages.ToArray().Length + "%"); //Write the labels of trained faces in a file text for further load for (int i = 1; i < trainingImages.ToArray().Length + 1; i++) { trainingImages.ToArray()[i - 1].Save(String.Format("{0}/TrainedFaces /face{1}.bmp", Application.StartupPath, i)); File.AppendAllText(Application.StartupPath + "/TrainedFaces /TrainedIDLables.txt", NameLabless.ToArray()[i - 1] + "%"); File.AppendAllText(Application.StartupPath + "/TrainedFaces /TrainedNameLables.txt", IDLabless.ToArray()[i - 1] + "%"); } MessageBox.Show(StudentName.Text + "´s face detected and added :)", "Training OK", MessageBoxButtons.OK, MessageBoxIcon.Information); }
thanks