正方体空白页

Question

我使用 tesseract 来检测图像上的字符。

        try
        {
            using (var engine = new TesseractEngine(@"C:\Users\ea\Documents\Visual Studio 2015\Projects\ocrtTest", "eng", EngineMode.Default))
            {
                using (var img = Pix.LoadFromFile(testImagePath))
                {
                    Bitmap src = (Bitmap)Image.FromFile(testImagePath);
                    using (var page = engine.Process(img))
                    {
                        var text = page.GetHOCRText(1);
                        File.WriteAllText("test.html", text);
                        //Console.WriteLine("Text: {0}", text);
                        //Console.WriteLine("Mean confidence: {0}", page.GetMeanConfidence());

                        int p = 0;
                        int l = 0;
                        int w = 0;
                        int s = 0;
                        int counter = 0;
                        using (var iter = page.GetIterator())
                        {
                            iter.Begin();
                            do
                            {
                                do
                                {
                                    do
                                    {
                                        do
                                        {
                                            do
                                            {
                                                //if (iter.IsAtBeginningOf(PageIteratorLevel.Block))
                                                //{
                                                //    logger.Log("New block");
                                                //}
                                                if (iter.IsAtBeginningOf(PageIteratorLevel.Para))
                                                {
                                                    p++;//counts paragraph
                                                    //logger.Log("New paragraph");
                                                }
                                                if (iter.IsAtBeginningOf(PageIteratorLevel.TextLine))
                                                {
                                                    l++;//count lines
                                                    //logger.Log("New line");
                                                }
                                                if (iter.IsAtBeginningOf(PageIteratorLevel.Word))
                                                {
                                                    w++;//count words
                                                    //logger.Log("New word");
                                                }
                                                s++;//count symbols
                                                //logger.Log(iter.GetText(PageIteratorLevel.Symbol));
                                                // get bounding box for symbol
                                                Rect symbolBounds;
                                                if (iter.TryGetBoundingBox(PageIteratorLevel.Symbol, out symbolBounds))
                                                {
                                                    Rectangle dueDateRectangle = new Rectangle(symbolBounds.X1, symbolBounds.Y1, symbolBounds.X2 - symbolBounds.X1, symbolBounds.Y2 - symbolBounds.Y1);
                                                    rect = dueDateRectangle;
                                                    PixelFormat format = src.PixelFormat;
                                                    Bitmap cloneBitmap = src.Clone(dueDateRectangle, format);
                                                    MemoryStream ms = new MemoryStream();
                                                    cloneBitmap.Save(ms, ImageFormat.Png);
                                                    ms.Position = 0;
                                                    Image i = Image.FromStream(ms);
                                                    //i.Save(ms,System.Drawing.Imaging.ImageFormat.Png);
                                                    i.Save("character" + counter + ".bmp", ImageFormat.Png);
                                                    counter++;
                                                }
                                            } while (iter.Next(PageIteratorLevel.Word, PageIteratorLevel.Symbol));
                                            // DO any word post processing here (e.g. group symbols by word)
                                        } while (iter.Next(PageIteratorLevel.TextLine, PageIteratorLevel.Word));
                                    } while (iter.Next(PageIteratorLevel.Para, PageIteratorLevel.TextLine));
                                } while (iter.Next(PageIteratorLevel.Block, PageIteratorLevel.Para));
                            } while (iter.Next(PageIteratorLevel.Block));
                        }
                        Console.WriteLine("Pragraphs = " + p);
                        Console.WriteLine("Lines = " + l);
                        Console.WriteLine("Words = " + w);
                        Console.WriteLine("Symbols = " + s);
                    }

当我有一个包含大量文本的图像时它可以工作，但是当我有一个只有一个字母的图像时它不会。

它找到了一个符号，我在输入中看到它。 Symbols = 1。但它不能得到BoundingBox。为什么？ 与我使用字母图像相同的地方

Answer 1

您可能需要使用不同的page segmentation mode 和OCR Engine mode 测试OCR 以获得最佳结果。以下是Tesseract 4.0 中提供的使用信息。

Page segmentation modes:
  0    Orientation and script detection (OSD) only.
  1    Automatic page segmentation with OSD.
  2    Automatic page segmentation, but no OSD, or OCR.
  3    Fully automatic page segmentation, but no OSD. (Default)
  4    Assume a single column of text of variable sizes.
  5    Assume a single uniform block of vertically aligned text.
  6    Assume a single uniform block of text.
  7    Treat the image as a single text line.
  8    Treat the image as a single word.
  9    Treat the image as a single word in a circle.
 10    Treat the image as a single character.
 11    Sparse text. Find as much text as possible in no particular order.
 12    Sparse text with OSD.
 13    Raw line. Treat the image as a single text line,
                        bypassing hacks that are Tesseract-specific.<br>

OCR Engine modes:
  0    Original Tesseract only.
  1    Neural nets LSTM only.
  2    Tesseract + LSTM.
  3    Default, based on what is available.

例如，

• psm 8 会给 OCR 一个单词的最佳结果
• psm 6 可能会给出一段文本的最佳结果

在您的代码中，它表明您使用了默认 engine mode，而不是指定segmentation mode。你可以做更多的测试来找出哪些模式给出了正确的结果。

Answer 2

对于如下图，在你的 tesseract 命令中使用 --psm 9