コード例 #1
0
ファイル: NeuroWork.cs プロジェクト: RedForest347/NeuroNet
        public void StartWriteText()
        {
            string   NeuroNetFile = "";
            NeuroNet neuroNet;

            OpenFileDialog NeuroNetDialog = new OpenFileDialog
            {
                Title = "Выбор нейросети",

                Filter = "Neuronet files|*.NN|All files|*.*"
            };

            if (NeuroNetDialog.ShowDialog() == DialogResult.OK)
            {
                NeuroNetFile = NeuroNetDialog.FileName;
            }
            else
            {
                return;
            }

            neuroNet = NeuroNet.LoadNeuronet(NeuroNetFile);

            NormalizePhoto();
            FindAllLines();
            DebugLines();
            FindAllLetters();
            PreparationWriteTextPass();

            int k = 0;

            while (WriteTextPass(neuroNet) && k < 200000)
            {
                k++;
            }
            Debug.Log("Расшифровка изображения завершена");
            SaveFileDialog SaveTextDialog = new SaveFileDialog
            {
                Title  = "SaveTextDialog",
                Filter = "Text|*.txt|All files|*.*"
            };

            if (SaveTextDialog.ShowDialog() == DialogResult.OK)
            {
                FileWork.SaveText(final_massage, SaveTextDialog.FileName);
            }
            //FileWork.SaveText(final_massage, @"C:\Users\Admin\Desktop\Letter\ForComplete\text.txt");

            Debug.Log("Текст скопирован в буфер обмена");
            Clipboard.SetText(final_massage);
        }
コード例 #2
0
ファイル: NeuroWork.cs プロジェクト: RedForest347/NeuroNet
        void StartLearningThread()
        {
            Debug.Log("начало обучения");
            Bitmap LetterImage;
            char   letter;
            int    count = 100000;

            float[] start_signals;
            float[] ideal_signals;

            //neuroNet = NeuroNet.CreateNeuroNet(new int[] {offset * offset, 42, 255 }, new NeuroData(1, 0.0002f));
            int load_neuroNet = 10800;//34500;

            neuroNet = NeuroNet.LoadNeuronet(@"C:\Users\Admin\Desktop\Letter\forNeuronet\NN" + load_neuroNet + ".NN");

            Debug.SetMaxValueProgressBar(count);
            for (int j = load_neuroNet + 1; j < count; j++)
            {
                neuroNet.ZeroingErrorOfEra();
                for (int i = 0; i < 1030; i++)
                {
                    StreamReader TextReader = new StreamReader(@"C:\Users\Admin\Desktop\ForText\" + i + ".txt");
                    LetterImage   = new Bitmap(@"C:\Users\Admin\Desktop\ForText\" + i + ".jpg");
                    letter        = TextReader.ReadLine()[0];
                    start_signals = GetNormalisedStartSignalsFromImage(LetterImage);
                    ideal_signals = GetNormalisedIdealSignals(letter);

                    neuroNet.Pass(start_signals, ideal_signals);
                }


                if (j % 50 == 0)
                {
                    if (j != 0)
                    {
                        neuroNet.SaveNeuronet(@"C:\Users\Admin\Desktop\Letter\forNeuronet\NN" + j + ".NN");
                        Debug.Log("завершено на " + (j * 100f / count) + "%");
                    }
                    else
                    {
                        neuroNet.SaveNeuronet(@"C:\Users\Admin\Desktop\Letter\forNeuronet\NN" + 0 + ".NN");
                    }
                    Debug.Log("error of era = " + neuroNet.ShowErrorOfEra());
                    //neuroNet.edukationK *= 0.99f;
                }
                //Debug.Log("error of era = " + neuroNet.ShowErrorOfEra());
                Debug.SetCurrentValueProgressBar(j);
            }
            neuroNet.SaveNeuronet(@"C:\Users\Admin\Desktop\Letter\forNeuronet\NN" + count + ".NN");
            Debug.Log("обучение завершено");
        }