// 工具栏 “识别” 按钮单击事件
private void Button_Click(object sender, RoutedEventArgs e)
{
TesseractEngine ocr;
string path = AppDomain.CurrentDomain.BaseDirectory;
string rootPath = path.Substring(0, path.LastIndexOf("bin"));
string tessdataPath = string.Concat(rootPath, "tessdata"); // TODO: 修改为资源->打包后可用
ocr = new TesseractEngine(tessdataPath, "eng", EngineMode.Default); //设置语言 英文
var img = Pix.LoadFromFile(imgPath);
//bit = PreprocesImage(bit);//进行图像处理,如果识别率低可试试
Tesseract.Page page = ocr.Process(img);
string str = "识别结果：\n\n";
str += page.GetText();//识别后的内容
page.Dispose();
//string str = ImageToText(imgPath);
tessTextBlock.Text = str; // 识别结果显示到界面
// TODO: 识别失败的处理
}
public Boolean Classification(int[,] AddedAreaPoints, string ImageID)
{
// Bitmap DestinationImage = new Bitmap(28, 28); /// To see Result of Scaling
Bitmap DestinationImage = new Bitmap(AddedAreaPoints.Rows(), AddedAreaPoints.Columns());
int[,] DestinationPoints = new int[28, 28]; /// To see Result of Scaling
double XConvertor = (double)(AddedAreaPoints.Rows()) / (double)(28);
double YConvertor = (double)(AddedAreaPoints.Columns()) / (double)(28);
double[] input = new double[784];
for (int i = 0; i < 28; i++)
{
for (int j = 0; j < 28; j++)
{
double XInSourceImage = (double)(XConvertor * i);
double YInSourceImage = (double)(YConvertor * j);
int X = (int)(Math.Floor(XInSourceImage));
int Y = (int)(Math.Floor(YInSourceImage));
input[i * 28 + j] = AddedAreaPoints[X, Y];
DestinationPoints[i, j] = AddedAreaPoints[X, Y];
}
}
// for (int i = 0; i < 28; i++)
for (int i = 0; i < AddedAreaPoints.Rows(); i++)
{
// for (int j = 0; j < 28; j++)
for (int j = 0; j < AddedAreaPoints.Columns(); j++)
{
// if (DestinationPoints[i, j] == 1)
if (AddedAreaPoints[i, j] == 1)
DestinationImage.SetPixel(i, j, Color.Black);
else
DestinationImage.SetPixel(i, j, Color.White);
}
}
DestinationImage.Save(@"C:\Users\nhonarva\Documents\ResultsOfScaling\scaling" + ImageID + ".png");
var image = Pix.LoadFromFile(@"C:\Users\nhonarva\Documents\ResultsOfScaling\scaling" + ImageID + ".png");
// Page page;
page=_engine.Process(image, PageSegMode.SingleBlock);
string text = page.GetText();
double confidence = page.GetMeanConfidence();
page.Dispose();
int actual = (int)ksvm.Compute(input);
if (actual == 1)
return true;
else
return false;
}
public void Dispose()
{
page.Dispose();
}