function [masks] = convertStardist(mask, gsize)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Converts to an MxNxT matrix of neuron masks to an MxN image of masks used by
%stardist. Meant to make training data, so it assumes that there's a
%desired, square image size for the output. 
% Inputs:
%     - mask: MxNxT matrix of the neuron masks
%     - gsize: desired size for the square output image
% Output:
%     - masks: MxN image of the masks where the value of the pixel
%     corresponds to the neuron number
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
masks = [];
[d1 d2 d3] = size(mask);
cd1 = gsize - d1;
cd2 = gsize - d2;
uniqval = unique(mask(:));
uniqval(uniqval ==0) = [];
for fn = 1:length(uniqval)
    blank = zeros(size(mask));
    ind = find(mask == uniqval(fn));
    blank(ind) = 1;

    blank = padarray(blank, [floor(cd1/2) floor(cd2/2)], 0,'post');
    blank = padarray(blank, [ceil(cd1/2) ceil(cd2/2)], 0,'pre');
    if sum(blank(:)) ~= 0
        masks = cat(3, masks, blank);
    end
end
end