private HeuristicReturnValues ExtractHeursitics(int midpoint)
{
HeuristicReturnValues heuristics = new HeuristicReturnValues();
int idx = midpoint - 6;
int width = Boards.First().Matrix[0].Length;
heuristics.GoThroughBoards(Boards, new Rectangle(idx, 0, Segmentation.WidthOfCanvas, width));
return heuristics;
}
public static IEnumerable<HeuristicReturnValues> Segment(this IteratedBoards boards)
{
HeuristicReturnValues heuristics = new HeuristicReturnValues();
int width = boards.Boards.First().Matrix.Length;
int height = boards.Boards.First().Matrix[0].Length;
for (int idx = 0; idx < width - WidthOfCanvas; idx++) {
heuristics.GoThroughBoards(boards.Boards, new Rectangle(idx, 0, Segmentation.WidthOfCanvas, height));
yield return heuristics;
}
}
public TrainingData Train(CharacterBounds charBounds)
{
int midpoint;
int boardWidth = Boards.First().Matrix.Length;
TrainingData trainingData = new TrainingData();
for (int idx = 0; idx < charBounds.items.Count(); idx++ ){
LetterAndBounds character = charBounds.items[idx];
midpoint = character.Bounds.X + (int)Math.Round(character.Bounds.Width / 2d);
Rectangle rect = new Rectangle(midpoint - 6, 0, character.Bounds.Width, character.Bounds.Height);
HeuristicReturnValues heursitics = new HeuristicReturnValues();
heursitics.GoThroughBoards(Boards, rect);
string label = character.Letter;
if (idx < charBounds.Word.Count()) {
char newChar = UnicodeConversion.convertUnicodeChar(charBounds.Word, ref idx);
heursitics.Label = newChar.ToString();
trainingData.AddHeuristics(heursitics);
}
}
return trainingData;
}