Fix to image_folder_dataset to accomodate images with mismatched dimensions

codes/data/image_folder_dataset.py

@@ -52,9 +52,7 @@ class ImageFolderDataset:
                     imgs = torch.load(cache_path)
                 else:
                     print("Building image folder cache, this can take some time for large datasets..")
-                    imgs = []
-                    for ext in supported_types:
-                        imgs.extend(glob.glob(os.path.join(path, "*." + ext)))
+                    imgs = util.get_image_paths('img', path)[0]
                     torch.save(imgs, cache_path)
                 for w in range(weight):
                     self.image_paths.extend(imgs)
@@ -67,6 +65,7 @@ class ImageFolderDataset:
     def resize_hq(self, imgs_hq):
         # Enforce size constraints
         h, w, _ = imgs_hq[0].shape
+
         if self.target_hq_size is not None and self.target_hq_size != h:
             hqs_adjusted = []
             for hq in imgs_hq:
@@ -114,6 +113,11 @@ class ImageFolderDataset:
         if not self.disable_flip and random.random() < .5:
             hq = hq[:, ::-1, :]
 
+        # We must convert the image into a square.
+        h, w, _ = hq.shape
+        dim = min(h, w)
+        hq = hq[(h - dim) // 2:dim + (h - dim) // 2, (w - dim) // 2:dim + (w - dim) // 2, :]
+
         if self.labeler:
             assert hq.shape[0] == hq.shape[1]  # This just has not been accomodated yet.
             dim = hq.shape[0]