Cleaned the code a little and the character recognition is now even better
This commit is contained in:
@@ -18,108 +18,25 @@ namespace OCR_Decode
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public override object DecodePng(List<string> DriverList)
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{
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string result = "";
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int[] recommendedTresholds = new int[] { 100, 125, 150, 175, 200 };
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result = GetStringFromPng();
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int index = 0;
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while (!IsADriver(DriverList, result))
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if (!IsADriver(DriverList, result))
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{
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if(index >= recommendedTresholds.Length -1)
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{
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//150 is usually the safest bet
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result = GetStringFromPng(150);
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//I put everything in uppercase to try to lower the chances of bad answers
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result = FindClosestMatch(DriverList.ConvertAll(d => d.ToUpper()), result.ToUpper());
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break;
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}
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result = GetStringFromPng(recommendedTresholds[index]);
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index++;
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}
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//rawData.Save(Reader.DEBUG_DUMP_FOLDER + result + "_Before" + ".png");
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return result;
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}
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private string GetStringFromPng(int BlackAndWhiteTresholh)
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{
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string result = "";
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Bitmap rawData = WindowImage;
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rawData = Window.ConvertToBlackAndWhite(rawData, 150);
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TesseractEngine engine = new TesseractEngine(TESS_DATA_FOLDER.FullName, "eng", EngineMode.Default);
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var tessImage = Pix.LoadFromMemory(ImageToByte(WindowImage));
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Page page = engine.Process(tessImage);
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Graphics g = Graphics.FromImage(rawData);
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// Get the iterator for the page layout
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using (var iter = page.GetIterator())
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{
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// Loop over the elements of the page layout
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iter.Begin();
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do
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{
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Rect boundingBox;
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// Get the bounding box for the current element
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if (iter.TryGetBoundingBox(PageIteratorLevel.Word, out boundingBox))
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{
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g.DrawRectangle(Pens.Red, new Rectangle(boundingBox.X1, boundingBox.Y1, boundingBox.Width, boundingBox.Height));
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}
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// Get the text for the current element
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result += iter.GetText(PageIteratorLevel.Word);
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} while (iter.Next(PageIteratorLevel.Word));
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}
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return result;
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}
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//This method has been gnerated using ChatGPT
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public static string FindClosestMatch(List<string> array, string target)
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private static bool IsADriver(List<string> drivers, string potentialDriver)
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{
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var closestMatch = "";
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var closestDistance = int.MaxValue;
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foreach (var item in array)
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bool result = false;
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//I cant use drivers.Contains because it has missmatched cases and all
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foreach (string name in drivers)
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{
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var distance = LevenshteinDistance(item, target);
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if (distance < closestDistance)
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{
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closestMatch = item;
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closestDistance = distance;
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if (name.ToUpper() == potentialDriver.ToUpper())
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result = true;
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}
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}
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return closestMatch;
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}
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public static int LevenshteinDistance(string s1, string s2)
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{
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if (string.IsNullOrEmpty(s1))
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{
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return string.IsNullOrEmpty(s2) ? 0 : s2.Length;
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}
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if (string.IsNullOrEmpty(s2))
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{
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return string.IsNullOrEmpty(s1) ? 0 : s1.Length;
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}
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var d = new int[s1.Length + 1, s2.Length + 1];
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for (var i = 0; i <= s1.Length; i++)
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{
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d[i, 0] = i;
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}
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for (var j = 0; j <= s2.Length; j++)
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{
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d[0, j] = j;
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}
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for (var i = 1; i <= s1.Length; i++)
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{
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for (var j = 1; j <= s2.Length; j++)
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{
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var cost = (s1[i - 1] == s2[j - 1]) ? 0 : 1;
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d[i, j] = Math.Min(Math.Min(d[i - 1, j] + 1, d[i, j - 1] + 1), d[i - 1, j - 1] + cost);
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}
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}
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return d[s1.Length, s2.Length];
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return result;
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}
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}
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}
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@@ -22,12 +22,10 @@ namespace OCR_Decode
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{
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Bitmap result = (Bitmap)InputImage.Clone();
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result = Grayscale(result);
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result = Tresholding(result, 200);
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result = InvertColors(result);
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result = Tresholding(result, 100);
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result = Resize(result);
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//result = Resize(result);
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//result = Dilatation(result, 5);
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//result = Erode(result,3);
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result = Dilatation(result, 1);
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return result;
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}
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public static Bitmap Grayscale(Bitmap input)
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+81
-52
@@ -16,6 +16,7 @@ namespace OCR_Decode
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private Rectangle _bounds;
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private Bitmap _image;
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private string _name;
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protected static TesseractEngine Engine;
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public Rectangle Bounds { get => _bounds; private set => _bounds = value; }
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public Bitmap Image { get => _image; set => _image = value; }
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public string Name { get => _name; protected set => _name = value; }
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@@ -36,14 +37,17 @@ namespace OCR_Decode
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{
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Image = image;
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Bounds = bounds;
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Engine = new TesseractEngine(TESS_DATA_FOLDER.FullName, "eng", EngineMode.Default);
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Engine.DefaultPageSegMode = PageSegMode.SingleLine;
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}
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public virtual Object DecodePng()
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{
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return " ";
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return "NaN";
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}
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public virtual Object DecodePng(List<string> drivers)
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{
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return " ";
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return "NaN";
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}
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public static byte[] ImageToByte(Image img)
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{
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@@ -53,58 +57,17 @@ namespace OCR_Decode
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return stream.ToArray();
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}
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}
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public static bool IsADriver(List<string> drivers,string potentialDriver)
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{
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bool result = false;
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//I cant use drivers.Contains because it has missmatched cases and all
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foreach (string name in drivers)
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{
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if (name.ToUpper() == potentialDriver.ToUpper())
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result = true;
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}
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return result;
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}
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public static Bitmap ConvertToBlackAndWhite(Bitmap inputBmp, int Treshold = 165)
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{
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Bitmap result = new Bitmap(inputBmp.Width, inputBmp.Height);
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for (int y = 0; y < inputBmp.Height; y++)
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{
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for (int x = 0; x < inputBmp.Width; x++)
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{
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Color pixelColor = inputBmp.GetPixel(x, y);
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if (pixelColor.R <= Treshold && pixelColor.G <= Treshold && pixelColor.B <= Treshold)
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{
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pixelColor = Color.FromArgb(0, 0, 0);
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}
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else
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{
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pixelColor = Color.FromArgb(255, 255, 255);
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}
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result.SetPixel(x, y, pixelColor);
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}
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}
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return result;
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}
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public static int GetTimeFromPng(Bitmap wImage)
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{
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//returns milliseconds
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string rawResult = "";
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int treshold = 100;
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int result = 0;
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//Bitmap rawData = wImage;
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OcrImage rawData = new OcrImage(wImage);
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Bitmap enhancedImage = rawData.Enhance();
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TesseractEngine engine = new TesseractEngine(TESS_DATA_FOLDER.FullName, "eng", EngineMode.Default);
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engine.DefaultPageSegMode = PageSegMode.SingleLine;
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engine.SetVariable("tessedit_char_whitelist", "0123456789.:+-LEADRPleadrp");
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Bitmap enhancedImage = new OcrImage(wImage).Enhance();
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var tessImage = Pix.LoadFromMemory(ImageToByte(enhancedImage));
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Page page = engine.Process(tessImage);
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Page page = Engine.Process(tessImage);
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Graphics g = Graphics.FromImage(enhancedImage);
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// Get the iterator for the page layout
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using (var iter = page.GetIterator())
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@@ -113,12 +76,6 @@ namespace OCR_Decode
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iter.Begin();
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do
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{
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Rect boundingBox;
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// Get the bounding box for the current element
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if (iter.TryGetBoundingBox(PageIteratorLevel.Word, out boundingBox))
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{
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//g.DrawRectangle(Pens.Red, new Rectangle(boundingBox.X1, boundingBox.Y1, boundingBox.Width, boundingBox.Height));
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}
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// Get the text for the current element
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try
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{
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@@ -136,6 +93,7 @@ namespace OCR_Decode
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List<string> rawNumbers;
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//Removes all non digit chars except for the important ones
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//We will need to change this when trying to see the Leader and Lap texts
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string cleanedResult = Regex.Replace(rawResult, "[^0-9.:]", "");
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//Splits into minuts seconds miliseconds
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@@ -176,8 +134,79 @@ namespace OCR_Decode
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}
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}
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}
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page.Dispose();
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return result;
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}
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protected string GetStringFromPng()
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{
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string result = "";
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Bitmap rawData = WindowImage;
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Bitmap enhancedImage = new OcrImage(rawData).Enhance();
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Page page = Engine.Process(enhancedImage);
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using (var iter = page.GetIterator())
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{
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iter.Begin();
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do
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{
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result += iter.GetText(PageIteratorLevel.Word);
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} while (iter.Next(PageIteratorLevel.Word));
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}
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page.Dispose();
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return result;
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}
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//This method has been gnerated using ChatGPT
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protected static string FindClosestMatch(List<string> array, string target)
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{
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var closestMatch = "";
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var closestDistance = int.MaxValue;
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foreach (var item in array)
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{
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var distance = LevenshteinDistance(item, target);
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if (distance < closestDistance)
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{
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closestMatch = item;
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closestDistance = distance;
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}
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}
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return closestMatch;
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}
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//This is a tool to be able to compare strings
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protected static int LevenshteinDistance(string s1, string s2)
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{
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if (string.IsNullOrEmpty(s1))
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{
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return string.IsNullOrEmpty(s2) ? 0 : s2.Length;
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}
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if (string.IsNullOrEmpty(s2))
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{
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return string.IsNullOrEmpty(s1) ? 0 : s1.Length;
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}
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var d = new int[s1.Length + 1, s2.Length + 1];
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for (var i = 0; i <= s1.Length; i++)
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{
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d[i, 0] = i;
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}
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for (var j = 0; j <= s2.Length; j++)
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{
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d[0, j] = j;
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}
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for (var i = 1; i <= s1.Length; i++)
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{
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for (var j = 1; j <= s2.Length; j++)
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{
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var cost = (s1[i - 1] == s2[j - 1]) ? 0 : 1;
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d[i, j] = Math.Min(Math.Min(d[i - 1, j] + 1, d[i, j - 1] + 1), d[i - 1, j - 1] + cost);
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}
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}
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return d[s1.Length, s2.Length];
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}
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}
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}
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