diff --git a/codes/data/image_folder_dataset.py b/codes/data/image_folder_dataset.py
index db51c383..fddced48 100644
--- a/codes/data/image_folder_dataset.py
+++ b/codes/data/image_folder_dataset.py
@@ -32,6 +32,9 @@ class ImageFolderDataset:
         self.corrupt_before_downsize = opt['corrupt_before_downsize'] if 'corrupt_before_downsize' in opt.keys() else False
         self.fetch_alt_image = opt['fetch_alt_image']  # If specified, this dataset will attempt to find a second image
                                                        # from the same video source. Search for 'fetch_alt_image' for more info.
+        self.fetch_alt_tiled_image = opt['fetch_alt_tiled_image']  # If specified, this dataset will attempt to find anoter tile from the same source image
+                                                                   #  Search for 'fetch_alt_tiled_image' for more info.
+        assert not (self.fetch_alt_image and self.fetch_alt_tiled_image)  # These are mutually exclusive.
         self.skip_lq = opt_get(opt, ['skip_lq'], False)
         self.disable_flip = opt_get(opt, ['disable_flip'], False)
         self.rgb_n1_to_1 = opt_get(opt, ['rgb_n1_to_1'], False)
@@ -188,6 +191,25 @@ class ImageFolderDataset:
                 if not self.skip_lq:
                     for_lq.append(hs[0])
             out_dict['alt_hq'] = alt_hq
+            
+        if self.fetch_alt_tiled_image:
+            # This assumes the output format generated by the tiled image generation scripts included with DLAS. Specifically,
+            # all image read by this dataset are assumed to be in subfolders with other tiles from the same source image. When
+            # this option is set, another random image from the same folder is selected and returned as the alt image.
+            sel_path = self.image_paths[item]
+            other_images = random.shuffle(os.listdir(sel_path))
+            # Assume that the directory contains at least <image>, <ref.jpg>, <centers.pt>
+            if len(other_images) <= 3:
+                alt_hq = hq  # This is a fallback in case an alt image can't be found.
+            else:
+                for oi in other_images:
+                    if oi == sel_path or 'ref.' in oi or 'centers.pt' in oi:
+                        continue
+                    alt_hq = util.read_img(None, oi, rgb=True)
+                    alt_hs = self.resize_hq([alt_hq])
+                    alt_hq = torch.from_numpy(np.ascontiguousarray(np.transpose(alt_hs[0], (2, 0, 1)))).float()
+                    out_dict['has_alt'] = True
+            out_dict['alt_hq'] = alt_hq
 
         if not self.skip_lq:
             lqs, ent = self.synthesize_lq(for_lq)
@@ -244,4 +266,4 @@ if __name__ == '__main__':
         lq = d['lq']
         #torchvision.utils.save_image(lq[:,:,16:-16,:], f'{output_path}\\{i+500000}.png')
         if i >= 200000:
-            break
\ No newline at end of file
+            break