public List <List <TrainingSampleCharacter> > TrainOnImage(string imagePath, List <char[]> referenceLines, int xOffset = 4)
{
var cleaner = new ImageCleaner();
//cleaner.SaveChatColors(imagePath, "debug.png");
var results = new List <List <TrainingSampleCharacter> >();
using (Image <Rgba32> rgbImage = Image.Load(imagePath))
{
var cache = new ImageCache(rgbImage);
var chatRect = new Rectangle(4, 763, 3236, 1350);
var offsets = OCRHelpers.LineOffsets;
var lineHeight = 36;
var refLineIndex = 0;
for (int i = 0; i < offsets.Length; i++)
{
var line = TrainOnLine(referenceLines[refLineIndex], xOffset, chatRect, cache, lineHeight, offsets[i]);
if (line.Count > 0 && line.Count == referenceLines[i].Length)
{
results.Add(line);
refLineIndex++;
}
else if (line.Count == referenceLines[i].Length)
{
throw new Exception("Reference lines do not match up with found characters");
}
}
}
return(results);
}
public void TrainOnImages(string trainingDir, string outputDir, int xOffset = 253)
{
var trainingImagePaths = Directory.GetFiles(trainingDir).Where(f => f.EndsWith(".png")).ToArray();
var trainingTextPaths = Directory.GetFiles(trainingDir).Where(f => f.EndsWith(".txt")).ToArray();
var characters = new List <TrainingSampleCharacter>();
Console.WriteLine("Looking at training images");
for (int i = 0; i < trainingImagePaths.Length; i++)
{
Console.Write("\r" + trainingImagePaths[i]);
var correctText = File.ReadAllLines(trainingTextPaths[i]).Select(line => line.Replace(" ", "").ToArray()).ToList();
var results = TrainOnImage(trainingImagePaths[i], correctText, xOffset);
results.SelectMany(list => list).ToList().ForEach(t => characters.Add(t));
}
var groupedChars = characters.GroupBy(t => t.Character);
//Get max widths
Console.WriteLine("\nFinding max widths");
var maxWidths = new Dictionary <char, int>();
groupedChars.ToList().ForEach(g => maxWidths[g.Key] = g.Max(t => t.Width));
//Turn all pixel lists into arrays of max width
Console.WriteLine("Converting lists to padded arrays");
var groupedCharArrays = groupedChars.Select(g =>
{
Console.Write("\rLooking at: " + g.Key);
return(g.Select(t =>
{
var arr = new float[maxWidths[t.Character], 36];
for (int x = 0; x < maxWidths[t.Character] && x < t.Width; x++)
{
for (int y = 0; y < 36; y++)
{
arr[x, y] = t.Mask[x, y];
}
}
return new { t.Character, Mask = arr };
}));
}).Select(i => i).SelectMany(i => i).GroupBy(t => t.Character).ToList();
//Get pixel counts
Console.WriteLine("\nDeterming pixel counts");
var pixelCounts = groupedCharArrays.Select(g =>
{
Console.Write("\rLooking at: " + g.Key);
var arr = new float[maxWidths[g.Key], 36];
g.ToList().ForEach(t =>
{
for (int x = 0; x < maxWidths[g.Key]; x++)
{
for (int y = 0; y < 36; y++)
{
arr[x, y] += t.Mask[x, y];
}
}
});
return(new { Character = g.Key, PixelCounts = arr, SampleCount = g.Count() });
}).ToList();
Console.WriteLine("\nConverting pixels into visualization");
var grayscalePixels = pixelCounts.Select(i =>
{
var arr = new byte[i.PixelCounts.GetLength(0), i.PixelCounts.GetLength(1)];
for (int x = 0; x < arr.GetLength(0); x++)
{
for (int y = 0; y < arr.GetLength(1); y++)
{
arr[x, y] = (byte)(((float)i.PixelCounts[x, y] / (float)i.SampleCount) * byte.MaxValue);
}
}
return(new { i.Character, Pixels = arr });
}).ToList();
var c = new ImageCleaner();
grayscalePixels.ForEach(i => c.MakeGreyscaleImageFromArray(outputDir, i.Character, i.Pixels));
}
