%DATA2IM Convert PRTools dataset or datafile to image
%
% IM = DATA2IM(A,J)
% IM = DATA2IM(A(J,:))
%
% INPUT
% A Dataset or datafile containing images
% J Desired images
%
% OUTPUT
% IM If A is dataset, IM is a X*Y*N*K matrix with K images.
% - K is the number of images (length(J))
% - N is the number of bands per image.
% - N = 3 for RGB images, N = 1 for gray value images.
% If A is a datafile, IM is a cell array of K images.
%
% DESCRIPTION
% An image, or a set of images stored in the objects or features of the
% dataset A are retrieved and returned as a 3D matrix IM. In case A is a
% datafile the images are stored in a cell array, except when a single
% image is requested.
%
% SEE ALSO (<a href="http://37steps.com/prtools">PRTools Guide</a>)
% DATASETS, IM2OBJ, IM2FEAT
% Copyright: R.P.W. Duin, r.p.w.duin@37steps.com
% Faculty EWI, Delft University of Technology
% P.O. Box 5031, 2600 GA Delft, The Netherlands
% $Id: data2im.m,v 1.13 2010/02/03 13:17:17 duin Exp $
function im = data2im(a,J)
if nargin > 1, a = a(J,:); end
if isdatafile(a)
m = size(a,1);
im = cell(1,m);
s = sprintf('Unpacking %i images: ',m);
prwaitbar(m,s);
for j=1:m
prwaitbar(m,j,[s int2str(j)]);
%im{j} = readdatafile(a,1,0);
im{j} = feval(mfilename,prdataset(a(j,:)));
end
prwaitbar(0);
if m==1
im = im{1};
end
return
end
%a = testdatasize(a); % Oeps, datafiles are first converted to datasets
% and then to images. This can be done better!
%isdataim(a); % Assert that A contains image(s).
data = +a; % Extract data from dataset, for computational advantage.
[m,k] = size(a); [objsize,featsize] = get(a,'objsize','featsize');
% Reshape data into output array.
if (isfeatim(a))
% A contains K images stored as features (each object is a pixel).
if length(objsize) == 1
im = zeros(1,objsize(1),k);
for j = 1:k
im(1,:,j) = reshape(data(:,j),1,objsize(1));
end
elseif length(objsize) == 2
im = zeros(objsize(1),objsize(2),k);
for j = 1:k
im(:,:,j) = reshape(data(:,j),objsize(1),objsize(2));
end
elseif length(objsize) == 3
im = zeros(objsize(1),objsize(2),k,objsize(3));
for j = 1:k
im(:,:,j,:) = reshape(data(:,j),objsize(1),objsize(2),objsize(3));
end
else
error('Unable to handle these images')
end
else
% A contains M images stored as objects (each feature is a pixel).
if length(featsize) == 1
im = zeros(1,featsize(1),1,m);
for j = 1:m
im(1,:,1,j) = reshape(data(j,:),1,featsize(1));
end
elseif length(featsize) == 2
im = zeros(featsize(1),featsize(2),1,m);
for j = 1:m
im(:,:,1,j) = reshape(data(j,:),featsize(1),featsize(2));
end
elseif length(featsize) == 3
im = zeros(featsize(1),featsize(2),featsize(3),m);
for j = 1:m
im(:,:,:,j) = reshape(data(j,:),featsize(1),featsize(2),featsize(3));
end
% elseif length(featsize) == 4
% if featsize(3) == 1
% im = zeros(featsize(1),featsize(2),featsize(4),m);
% for j = 1:m
% im(:,:,1,j) = reshape(data(j,:),featsize(1),featsize(2),featsize(4));
% end
% elseif featsize(3) == 3
else
error('Unable to handle these images')
end
%im = squeeze(im); % some routines, like filtim, fail by squeezing
end
return