clear;close all;

folder = 'Train';

savepath = 'train.h5';

size_input = 41;

size_label = 41;

scale = 2;

stride = 14;

data = zeros(size_input, size_input, 1, 1);

label = zeros(size_label, size_label, 1, 1);

padding = abs(size_input - size_label)/2;

count = 0;

filepaths = dir(fullfile(folder,'*.bmp'));

for i = 1 : length(filepaths)

image = imread(fullfile(folder,filepaths(i).name));

image = rgb2ycbcr(image);

image = im2double(image(:, :, 1));

im_label = modcrop(image, scale);

[hei,wid] = size(im_label);

im_input = imresize(imresize(im_label,1/scale,'bicubic'),[hei,wid],'bicubic');

for x = 1 : stride : hei-size_input+1

for y = 1 :stride : wid-size_input+1

subim_input = im_input(x : x+size_input-1, y : y+size_input-1);

subim_label = im_label(x+padding : x+padding+size_label-1, y+padding : y+padding+size_label-1);

count=count+1;

data(:, :, 1, count) = subim_input;

label(:, :, 1, count) = subim_label;

end

end

order = randperm(count);

data = data(:, :, 1, order);

label = label(:, :, 1, order);

chunksz = 64;

created_flag = false;

totalct = 0;

for batchno = 1:floor(count/chunksz)

last_read=(batchno-1)*chunksz;

batchdata = data(:,:,1,last_read+1:last_read+chunksz);

batchlabs = label(:,:,1,last_read+1:last_read+chunksz);

startloc = struct('dat',[1,1,1,totalct+1], 'lab', [1,1,1,totalct+1]);

curr_dat_sz = store2hdf5(savepath, batchdata, batchlabs, ~created_flag, startloc, chunksz);

created_flag = true;

totalct = curr_dat_sz(end);

h5disp(savepath);