OctGridText/runTest.m at master · eddy85br/OctGridText · GitHub

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function [Ys img populations fitValues] = runTest(level)
	Ys = 'error!';
	switch level
		case 1
			picture = imread('./sampleData/easyDNA.png');
		case 2
			picture = imread('./sampleData/fasta_dna.png');
		case 3
			picture = imread('./sampleData/letras.jpg');
		case 4
			picture = imread('./sampleData/DNA.jpg');
		case 5
			picture = imread('./sampleData/fasta_dna90.png');
		case 6
			picture = imread('./sampleData/fasta_dna20.png');
		case 7
			picture = imread('./sampleData/fasta_dna20.jpg');
		otherwise
			picture = level;
	end
	original = picture;

	[numRows, numCols, numZ] = size(picture);	# Get the image size
	## Transform various types of images in Black & White boolean (logical) images:
	if numZ > 1
		picture = sum(picture, 3);				# Fusion of the 3 color channels
		picture = picture ./ max(max(picture));
		if ~ isbool(picture)
			m = median(median(picture));
			picture(find(picture >  m * 0.8)) = 1;
			picture(find(picture <= m * 0.8)) = 0;
			picture = logical(picture);
		endif
	else
		if ~ isbool(picture)
			m = median(median(picture));
			picture(find(picture >  m * 0.8)) = max(max(picture));
			picture(find(picture <= m * 0.8)) = min(min(picture));
			picture = logical(picture);
		endif
	endif
	## All boolean images. Converted to 8-bit integer B&W images:
	picture = uint8(picture);
	picture = picture .* 255;

	xPos      = [];
	yFiltered = [];

	sliceNumber = 0;
	# Process 255 rows at a time, because we are passing only a pair of 8 bits per point (yPosition, 0 to 255)
	for rowNumber = 1:255:numRows
		sliceNumber++;
		sliceSize = rowNumber + 254;
		if sliceSize > numRows
			sliceSize = numRows;
		endif
		slice = picture(rowNumber:sliceSize, :);
		%# disp(['rowNumber: ' num2str(rowNumber) "\t\tsliceSize: " num2str(sliceSize)]);

		## Setting variables "GA Options" to gaGnuOct
		gaOptions.InitialPopulation = [];
		gaOptions.MutationRate      = 0.25;
		gaOptions.PopulationSize    = 5000;
		gaOptions.EliteCount        = 3000;
		gaOptions.Generations       = 20;

		[topIndividual pop popFitVals] = gaGnuOct(@(bits)fitGrid(slice, bits), 16, gaOptions);
		populations(:, :, sliceNumber) = pop;
		fitValues(:, sliceNumber)      = popFitVals;

		%[rowSize, colSize] = size(slice);
		%yPos = bits2bytes(topLines(pop, popFitVals));

		%yPos(find(yPos <= 0)) = 1;
		%yPos(find(yPos > rowSize)) = rowSize;

		%diff = abs(yPos(:,1) - yPos(:,2));
		%mediana = median(diff);
		%yFiltered = yPos(find(diff <= mediana * 1.25), :);

		%xPos = [ones(size(yFiltered)(1),1), repmat(colSize, size(yFiltered)(1),1)];
		%drawLine(slice, yFiltered, xPos);
		%figure;
	end

	#figure; imshow(picture);

	for sliceI = 1:sliceNumber
		pop        = populations(:, :, sliceI);
		popFitVals = fitValues(:, sliceI);

		yPos = bits2bytes(topLines(pop, popFitVals));

		slicePos = (sliceI - 1) * 254;
		yPos = yPos .+ slicePos;

		yPos(find(yPos <= 0)) = 1;
		yPos(find(yPos > numRows)) = numRows;

		diff = abs(yPos(:,1) - yPos(:,2));
		mediana = median(diff);
		#media = mean(diff);
		#diffMetric = mediana + media;

		#yFiltered = yPos(find(diff) <= diffMetric, :);
		yFiltered = [ yFiltered; yPos(find(diff <= mediana * 1.10), :) ];
		#yFiltered = [yFiltered; yPos];

		xPos = [ xPos; [ones(size(yFiltered)(1), 1), repmat(numCols, size(yFiltered)(1), 1)] ];
	end

	Ys = yFiltered;

	#figure;
	#img = drawLine(picture, yFiltered, xPos);
	figure;
	img = drawLine(original, yFiltered, xPos);