private bool LoadTrainingData()
 {
     mydb           = new DBConn();
     allname        = mydb.getLabelList();
     trainingImages = mydb.getTrainedImageList();
     int[] temp = Enumerable.Range(0, (allname.Count)).ToArray();
     if (mydb.getImageCount() > 0)
     {
         if (trainingImages.Length != 0)
         {
             //set round and ...
             //termCrit = new MCvTermCriteria(mydb.getImageCount(), 0.001);
             //Eigen face recognizer
             recognizer = new FisherFaceRecognizer(0, 3200);//4000
             recognizer.Train(trainingImages, temp);
             return(true);
         }
         else
         {
             return(false);
         }
     }
     else
     {
         return(false);
     }
 }
Ejemplo n.º 2
0
 private bool LoadTrainingData()
 {
     mydb             = new DBConn();
     imagelabel       = mydb.getLabelNumList().ToArray();
     imageStringlabel = mydb.getLabelList().ToArray();
     trainingImages   = mydb.getTrainedImageList();
     Itrainingimage   = trainingImages;
     if (mydb.getImageCount() > 0)
     {
         if (trainingImages.Length != 0)
         {
             f_recognize = new FisherFaceRecognizer(0, 123.0);
             f_recognize.Train(Itrainingimage, imagelabel);
             return(true);
         }
         else
         {
             return(false);
         }
     }
     else
     {
         return(false);
     }
 }
        private bool LoadTrainingData()
        {
            mydb = new DBConn();
            imagelabel = mydb.getLabelNumList().ToArray();
            imageStringlabel = mydb.getLabelList().ToArray();
            trainingImages = mydb.getTrainedImageList();
            Itrainingimage = trainingImages;
            if (mydb.getImageCount() > 0)
            {

                if (trainingImages.Length != 0)
                {
                    f_recognize = new FisherFaceRecognizer(0, 123.0);
                    f_recognize.Train(Itrainingimage, imagelabel);
                    return true;
                }
                else
                {
                    return false;
                }
            }
            else
            {
                return false;
            }      
            
            
        }
        private bool LoadTrainingData()
        {
            mydb = new DBConn();
            allname = mydb.getLabelList();           
            trainingImages = mydb.getTrainedImageList();
            int[] temp = Enumerable.Range(0,(allname.Count)).ToArray();
            if (mydb.getImageCount() > 0)
            {

                if (trainingImages.Length != 0)
                {
                    //set round and ...
                    //termCrit = new MCvTermCriteria(mydb.getImageCount(), 0.001);
                    //Eigen face recognizer
                    recognizer = new FisherFaceRecognizer(0,3200);//4000
                    recognizer.Train(trainingImages, temp);
                    return true;
                }
                else
                {
                    return false;
                }
            }
            else
            {
                return false;
            }
        }