Added the data gen script for shCNN (super-res)

data/Shepard_CNN/Shepard_super_res/gen_training_data.m

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+clear;
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+% indicate the super-resolution factor
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+down_factor = 3;    % 2, 3 or 4
+image_path = 'data/deepeaf/BSDS500/';
+data_chs = 1;   % 1 or 3
+training_mat_path = 'data/Shepard_CNN/Shepard_super_res/x3/train_1ch/';
+val_mat_path = 'data/Shepard_CNN/Shepard_super_res/x3/val_1ch/';
+
+patch_dim = 48;
+num_patches = 20000;
+listing = dir(strcat(image_path, '*.jpg'));
+mat_num = 51;
+for m = 1 : mat_num
+    fprintf('Extracting patch batch: %d / %d\n', m, mat_num);
+    % extract random patches
+    images = zeros(patch_dim, patch_dim, data_chs, num_patches);
+    labels = zeros(size(images));
+    for i = 1 : num_patches
+        if (mod(i,100) == 0)
+            fprintf('Extracting patch: %d / %d\n', i, num_patches);
+        end
+
+        r_idx = random('unid', size(listing, 1));
+        I = im2double(imread(strcat(image_path, listing(r_idx).name)));
+        orig_img_size = size(I);
+        r = random('unid', orig_img_size(1) - patch_dim + 1);
+        c = random('unid', orig_img_size(2) - patch_dim + 1);
+
+        patch = I(r:r+patch_dim-1, c:c+patch_dim-1, :);
+
+        if(data_chs == 1)
+            patch = rgb2ycbcr(patch);
+            patch = patch(:,:,1);
+        end        
+
+        patch_down = imresize(patch, [patch_dim/down_factor, patch_dim/down_factor], 'bicubic');
+        patch_up = imresize(patch_down, [patch_dim, patch_dim], 'nearest');
+        images(:,:,:,i) = patch_up;
+        labels(:,:,:,i) = patch;
+        %imshow([patch_up patch]); pause;
+    end
+    % save it
+    images = single(images);
+    labels = single(labels);
+
+    if(m >= mat_num)
+        % save validation data
+        filename = strcat(val_mat_path, 'val_1');
+        images_t = images;
+        labels_t = labels;
+        save(filename, '-v7.3', 'images_t', 'labels_t');
+    else
+        % save training data
+        filename = strcat(training_mat_path, 'patches_', num2str(m));
+        save(filename, '-v7.3', 'images', 'labels');
+    end
+end
+
+
+

data/Shepard_CNN/Shepard_super_res/x2/train_1ch/readme.txt

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+data here.

data/Shepard_CNN/Shepard_super_res/x2/val_1ch/readme.txt

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+data here.

data/Shepard_CNN/Shepard_super_res/x3/train_1ch/readme.txt

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+data here.

data/Shepard_CNN/Shepard_super_res/x3/val_1ch/readme.txt

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+data here.

data/Shepard_CNN/Shepard_super_res/x4/train_1ch/readme.txt

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+data here.

data/Shepard_CNN/Shepard_super_res/x4/val_1ch/readme.txt

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+data here.