/// <summary>
/// Des the serialise.
/// </summary>
/// <param name="text">The text.</param>
/// <returns></returns>
public static HistogramLetter DeSerialise(string text)
{
HistogramLetter ret = null;
try
{
var t1 = text.Split(new[] { b }, StringSplitOptions.RemoveEmptyEntries);
var let = t1[0][0];
//get values
var xarr = t1[1];
var xval = xarr.Split(new[] { f }, StringSplitOptions.RemoveEmptyEntries).Select(int.Parse).ToArray();
var yarr = t1[2];
var yval = yarr.Split(new[] { f }, StringSplitOptions.RemoveEmptyEntries).Select(int.Parse).ToArray();
//set values
ret = new HistogramLetter {
XValues = xval, YValues = yval, Letter = let
};
}
catch (ArgumentException)
{
}
return(ret);
}
/// <summary>
/// Des the serialise.
/// </summary>
/// <param name="filename">The filename.</param>
/// <returns></returns>
public static SymbolIdentity DeSerialise(string filename)
{
var ret = new SymbolIdentity();
try
{
var text = FileExtras.LoadFile(filename);
var t1 = text.Split(new[] { v }, StringSplitOptions.RemoveEmptyEntries);
var w = int.Parse(t1[0]);
var h = int.Parse(t1[1]);
var letters = new List <HistogramLetter>();
for (var a = 2; a < t1.Count(); a++)
{
var ltext = t1[a];
var l = HistogramLetter.DeSerialise(ltext);
if (letters.Any(s => s.Letter.Equals(l.Letter)) == false)
{
letters.Add(l);
}
}
ret.HistogramHeight = h;
ret.HistogramWidth = w;
ret.Letters = letters;
}
catch (ArgumentException)
{
}
return(ret);
}
/// <summary>
/// get score. score of 0 is perfect
/// </summary>
/// <param name="b">The b.</param>
/// <param name="l">The l.</param>
/// <returns></returns>
private int GetOffScore(Bitmap b, HistogramLetter l)
{
var bba = BitmapBoolArray.GetBitmapBoolArray(b);
var h = HistogramLetter.GetHistogram(bba, b);
var score = l.GetHistogramOffsetScore(h.Item1, h.Item2);
return(score);
}
/// <summary>
/// take an image of a letter and a character of what it is, and train the ocr
/// </summary>
/// <param name="b">The b.</param>
/// <param name="letterChar">The letter character.</param>
/// <returns></returns>
public bool Train(Bitmap b, char letterChar)
{
try
{
var l = new HistogramLetter(b, letterChar);
Letters.Add(l);
return(true);
}
catch (ArgumentNullException)
{
}
return(false);
}
/// <summary>
/// Des the serialise.
/// </summary>
/// <param name="text">The text.</param>
/// <returns></returns>
public static HistogramLetter DeSerialise(string text)
{
HistogramLetter ret = null;
try
{
var t1 = text.Split(new[] { b }, StringSplitOptions.RemoveEmptyEntries);
var let = t1[0][0];
//get values
var xarr = t1[1];
var xval = xarr.Split(new[] { f }, StringSplitOptions.RemoveEmptyEntries).Select(int.Parse).ToArray();
var yarr = t1[2];
var yval = yarr.Split(new[] { f }, StringSplitOptions.RemoveEmptyEntries).Select(int.Parse).ToArray();
//set values
ret = new HistogramLetter { XValues = xval, YValues = yval, Letter = let };
}
catch (ArgumentException)
{
}
return ret;
}
/// <summary>
/// get score. score of 0 is perfect
/// </summary>
/// <param name="b">The b.</param>
/// <param name="l">The l.</param>
/// <returns></returns>
private int GetOffScore(Bitmap b, HistogramLetter l)
{
var bba = BitmapBoolArray.GetBitmapBoolArray(b);
var h = HistogramLetter.GetHistogram(bba, b);
var score = l.GetHistogramOffsetScore(h.Item1, h.Item2);
return score;
}
/// <summary>
/// take an image of a letter and a character of what it is, and train the ocr
/// </summary>
/// <param name="b">The b.</param>
/// <param name="letterChar">The letter character.</param>
/// <returns></returns>
public bool Train(Bitmap b, char letterChar)
{
try
{
var l = new HistogramLetter(b, letterChar);
Letters.Add(l);
return true;
}
catch (ArgumentNullException)
{
}
return false;
}
