script_use_scribbles.m

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% FUNCTION_NAME - script_use_scribbles
%
% Syntax: script_use_scribbles
%
% Inputs:
%    NONE
%
% Outputs:
%    Exchanges information with java to parse scribbles and suitably use
%    them
%
% Author: Adarsh Kowdle
% email: [e-mail]
% Last revision: 02-June-2009
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

% Set type of experiment - this is what controls the mode of operation and
% options like the number of columns in the GUI
% This variable gives the user flexibity to have multiple gui options
squiggle_handle.setExperiment(0);

flag = 1;
% Fix to make sure mode button works from the start
warning off;
display_fname = fullfile(java_tmp_dir,'no_segs.jpg');
seg_maps = mat2cell(display_fname);
seg_maps = repmat(seg_maps, [1 length(im_list)]);
squiggle_handle.setSegmentations(seg_maps);
warning on;

% different scribble / segment now iterations
while 1
    % Wait for the done/segment now! button to be pressed - if next group is pressed
    % get next group
    while squiggle_handle.getDone() == 0
        if(squiggle_handle.getNextGroup() == 1)
            break
        end
    end
    
    % Status bar to display messages
    status = {'Please wait...'};
    squiggle_handle.setStatus(status);
    
    if(squiggle_handle.getNextGroup() == 1)
        break
    end
    
    % Figuring out the image which was scribbled on
    % Java returns path to image which was scribbled on (but lower case)
    im_path = squiggle_handle.getImagen();
    [pathstr, name, ext, versn] = fileparts(char(im_path));
    image_name = sprintf('%s%s', name, ext);
    % sc_file_id will have the id (in the im_list) of the image which was scribbled on
    sc_file_id = find((strcmp(cellstr(char(im_list(:).name)), repmat(cellstr(image_name), size(im_list))))==1);
    im = imread(fullfile(im_dir, im_list(sc_file_id).name));
    [im_rows, im_cols, im_depth] = size(im);
    
    % Get the vector of squiggles from java
    if flag==1
        squiggle_vect = squiggle_handle.getAllSquiggles();
        squiggle_handle.getSquiggle();
    else
        squiggle_vect = squiggle_handle.getSquiggle();
    end
    
    % Figure out the number of squiggles made
    num_squiggles = squiggle_vect.size();
    
    % Check if there is atleast 1 scribble
    if (num_squiggles==0)
        status = {'Need atleast one (new) scribble!'};
        squiggle_handle.setStatus(status);
        squiggle_handle.setDone(0)
        continue;
    end
    
    % Check if there is both foreground and background on first image
    % Specifically made for a segmentation framework
    bg_fg_flag = zeros(num_squiggles,1);
    if flag == 1 % less than 2 classes have been seen
        for squig_id = 0:num_squiggles-1
            num_pts = squiggle_vect.get(squig_id).size();
            % Check if the current scribble is foreground or background
            tmp_flag = squiggle_vect.get(squig_id).get(num_pts-1);
            bg_fg_flag(squig_id+1) = double(tmp_flag(1));
        end
        if (length(unique(bg_fg_flag))<2)
            squiggle_handle.setDone(0);
            status = {'First image needs both fg and bg scribbles!'};
            squiggle_handle.setStatus(status);
            continue
        else
            flag = 0;
        end
    end
    
    % Figure out the size the image (on screen)
    new_size = squiggle_handle.getImageSize();
    im_rows_blow = new_size(2);
    im_cols_blow = new_size(1);
    
    % Form the vector of squiggle positions with labels (and scribble mask)
    % 0=Background, 1=Foreground
    scribble_mask = zeros([size(im,1) size(im,2)],'uint8');
    for squig_id = 0:num_squiggles-1
        % Check the number of points in the scribble
        num_pts = squiggle_vect.get(squig_id).size();
        
        % Check if the current scribble is foreground or background
        bg_fg_flag = squiggle_vect.get(squig_id).get(num_pts-1);
        bg_fg_flag = double(bg_fg_flag(1));
        
        % mark scribbles in scribble_mask
        for pt_id = 0:num_pts-2
            pt = squiggle_vect.get(squig_id).get(pt_id); % Java/0-based indexing
            pt = [pt(1)*im_cols/im_cols_blow; pt(2)*im_rows/im_rows_blow]; % scaling scribbles to actual image size
            pt = floor(pt) + 1; % Matlab/1-based indexing
            scribble_mask(pt(2),pt(1)) = bg_fg_flag + 1; %0/1 to 1/2 back/fore
        end
    end
    
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
	% YOUR CODE GOES HERE
	% scribble_mask at this point is a 2D matrix the same size as the image
    % where the background points and forground points scribbled on would be
    % labeled 1 and 2 respectively.
    % Also, note that sc_file_id will have the id of the image which was 
    % scribbled on.
	%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

    % Cell arrays which have the paths to the images used in the java gui
    seg_maps = {};
    im_names = {};
    
    %keyboard
    alpha = 0.7;
    for p_im = 1:length(im_list)
        warning off;
        filename_seg = fullfile(java_tmp_dir, sprintf('seg_%d.jpg',p_im));
        im = imread(fullfile(im_dir, im_list(p_im).name));
        im_gray = double(rgb2gray(im));
        seg_mask = zeros(size(im_gray));
        image_gray = cat(3, im_gray, im_gray, im_gray);
        
        % Once you have a segmentation (0 and 1 indicating the two classes)
        % the folloing will display one of the classes in cyan
        seg_image_patch = cat(3, zeros(size(seg_mask)), 255*seg_mask, 255*seg_mask);
        seg_image = uint8(alpha*seg_image_patch + (1-alpha)*image_gray);
        
        % Write the resulting segmented images into files saved in the java
        % tmp directory
        imwrite(seg_image, filename_seg);
        seg_maps = [seg_maps  filename_seg];
        im_file_name = fullfile(im_dir,im_list(p_im).name);
        im_names = [im_names im_file_name];
        
        % This association makes sure that irrespective of whether you
        % click on the image or segmentation matlab can infer which image
        % was clicked on
        squiggle_handle.associate(im_file_name, filename_seg);
        warning on;
    end
    
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    % NOTE: This GUI is capable of handling more than just segmentations,
    % there are provisions to have as much as 4 columns of images in the
    % different modes which can be seen in the api.doc
    %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
    
    % Setup images for displaying in the gui
    display_fname = fullfile(java_tmp_dir, 'pick_an_image.jpg');
    squiggle_handle.setActualImages(im_names);
    squiggle_handle.setSegmentations(seg_maps);
    squiggle_handle.setActualLabel(sprintf('Images'));
    squiggle_handle.setSegmentationLabel(sprintf('Segmentations'));
    squiggle_handle.setImageSize(500, 500);
    squiggle_handle.setImage(seg_maps(sc_file_id));
    
    squiggle_handle.setDone(0);
    frame_handle.setMode(1);
    
    status = {'Done!'};
    squiggle_handle.setStatus(status);
    squiggle_handle.setIterNum(1);
    
end % End loop on multiple scribbles
warning on;