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generatepatches.m
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generatepatches.m
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function [imdb] = generatepatches
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
addpath('utilities');
batchSize = 128; % batch size
folder_train = 'Train2'; %
folder_test = 'Test2';
nchannel = 1; % number of channels
patchsize = 40;
stride = 9;
step1 = 2;
step2 = 4;
count = 0;
ext = {'*.tif' };
filepaths = [];
for i = 1 : length(ext)
filepath_train = cat(1,filepaths, dir(fullfile(folder_train, ext{i})));
filepath_test = cat(1,filepaths, dir(fullfile(folder_test, ext{i})));
end
% count the number of extracted patches
scales = [1 0.9 0.8 0.7]; % scale the image to augment the training data
for i = 1 : length(filepath_train)
image_train = imread(fullfile(folder_train,filepath_train(i).name)); % read train
image_test = imread(fullfile(folder_test,filepath_test(i).name)); % read label
if size(image_train,3)==3
image_train = rgb2gray(image_train);
image_test = rgb2gray(image_test);
end
%[~, name, exte] = fileparts(filepaths(i).name);
if mod(i,100)==0
disp([i,length(filepath_train)]);
disp([i,length(filepath_test)]);
end
for s = 1:4
image_train = imresize(image_train,scales(s),'bicubic');
image_test = imresize(image_test,scales(s),'bicubic');
[hei,wid,~] = size(image_train);
for x = 1+step1 : stride : (hei-patchsize+1)
for y = 1+step2 :stride : (wid-patchsize+1)
count = count+1;
end
end
end
end
numPatches = ceil(count/batchSize)*batchSize;
diffPatches = numPatches - count;
disp([int2str(numPatches),' = ',int2str(numPatches/batchSize),' X ', int2str(batchSize)]);
count = 0;
imdb.inputs = zeros(patchsize, patchsize, nchannel, numPatches,'single');
imdb.labels = zeros(patchsize, patchsize, nchannel, numPatches,'single');
for i = 1 : length(filepath_train)
image_train = imread(fullfile(folder_train,filepath_train(i).name)); % read train
image_test = imread(fullfile(folder_test,filepath_test(i).name)); % read label
%[~, name, exte] = fileparts(filepaths(i).name);
if size(image_train,3)==3
image_train = rgb2gray(image_train);
image_test = rgb2gray(image_test);
end
if mod(i,100)==0
disp([i,length(filepath_train)]);
disp([i,length(filepath_test)]);
end
for s = 1:4
image_train = imresize(image_train,scales(s),'bicubic');
image_test = imresize(image_test,scales(s),'bicubic');
for j = 1:1
%image_aug = data_augmentation(image, j); % augment data
% im_label = im2single(image_aug); % single
im_input = im2single(image_train); % single
im_label = im2single(image_test);
[hei,wid,~] = size(im_input);
for x = 1+step1 : stride : (hei-patchsize+1)
for y = 1+step2 :stride : (wid-patchsize+1)
count = count+1;
imdb.inputs(:, :, :, count) = im_input(x : x+patchsize-1, y : y+patchsize-1,:);
imdb.labels(:, :, :, count) = im_label(x : x+patchsize-1, y : y+patchsize-1,:);
if count<=diffPatches
imdb.inputs(:, :, :, end-count+1) = im_input(x : x+patchsize-1, y : y+patchsize-1,:);
imdb.labels(:, :, :, end-count+1) = im_label(x : x+patchsize-1, y : y+patchsize-1,:);
end
end
end
end
end
end
imdb.set = uint8(ones(1,size(imdb.inputs,4)));