Fix datasets

codes/data/base_unsupervised_image_dataset.py

@@ -84,6 +84,7 @@ class BaseUnsupervisedImageDataset(data.Dataset):
             h, w = self.target_hq_size, self.target_hq_size
         else:
             hqs_adjusted, hq_refs_adjusted, hq_masks_adjusted, hq_centers_adjusted = imgs_hq, refs_hq, masks_hq, centers_hq
+            hq_masks_adjusted = [m.squeeze(-1) for m in hq_masks_adjusted]  # This is done implicitly above..
         hq_multiple = self.multiple * self.scale   # Multiple must apply to LQ image.
         if h % hq_multiple != 0 or w % hq_multiple != 0:
             hqs_conformed, hq_refs_conformed, hq_masks_conformed, hq_centers_conformed = [], [], [], []

codes/scripts/extract_subimages_with_ref.py

@@ -150,6 +150,9 @@ class TiledDataset(data.Dataset):
         thres_sz = self.opt['thres_sz']
         h, w, c = img.shape
 
+        if crop_sz > h:
+            return []
+
         h_space = np.arange(0, h - crop_sz + 1, step)
         if h - (h_space[-1] + crop_sz) > thres_sz:
             h_space = np.append(h_space, h - crop_sz)

codes/train.py

@@ -291,7 +291,7 @@ class Trainer:
 
 if __name__ == '__main__':
     parser = argparse.ArgumentParser()
-    parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_teco_vix_using_rrdb_features.yml')
+    parser.add_argument('-opt', type=str, help='Path to option YAML file.', default='../options/train_exd_adrianna_srflow8x.yml')
     parser.add_argument('--launcher', choices=['none', 'pytorch'], default='none', help='job launcher')
     parser.add_argument('--local_rank', type=int, default=0)
     args = parser.parse_args()