%LABELIM Construct image of object (pixel) labels %%		IM = LABELIM(A)%		IM = A*LABELIM%% INPUT% 	A 	Dataset containing images stored as features%% OUTPUT%		IM	Image containing the labels of the objects%% DESCRIPTION  % For a dataset A containing images stored as features, where each pixel% corresponds to an object, the routine creates an image presenting the% labels of the objects. Note that if the number of classes is small, e.g.% 2, an appropriate colormap will have to be loaded for displaying the% result using IMAGE(LABELS). More appropriate, LABELS should be multiplied% such that the minimum and maximum of LABELS are well spread in the [1,64]% interval of the standard colormaps. % The resulting image may also directly	be displayed by:%%		LABELIM(A) or %		A*LABELIM% for which a suitable colormap is loaded automatically.% %	SEE ALSO%	DATASETS, CLASSIM% Copyright: R.P.W. Duin, duin@ph.tn.tudelft.nl% Faculty of Applied Sciences, Delft University of Technology% P.O. Box 5046, 2600 GA Delft, The Netherlands% $Id: labelim.m,v 1.4 2004/05/13 14:04:20 duin Exp $function labels = labelim(a)	prtrace(mfilename);	% No arguments given: return an untrained mapping.	if (nargin == 0)		labels = mapping('labelim','fixed');		return	end	isfeatim(a);									% Assert that A is a feature image dataset.	[n,m] = getobjsize(a);				% Get image size and reshape labels to image.	J = getnlab(a); labels = reshape(J,n,m);	if (nargout == 0)		n = 61/(size(a,2)+0.5);			% If no output is requested, display the		imagesc(labels*n);						%    image with a suitably scaled colormap.		colormap colorcube;		clear labels;	endreturn