diff --git a/library/train_util.py b/library/train_util.py
index bd2ff6ef..18d3cf6c 100644
--- a/library/train_util.py
+++ b/library/train_util.py
@@ -1082,6 +1082,10 @@ class BaseDataset(torch.utils.data.Dataset):
                     info.image = info.image.result()  # future to image
             caching_strategy.cache_batch_latents(model, batch, cond.flip_aug, cond.alpha_mask, cond.random_crop)
 
+            # remove image from memory
+            for info in batch:
+                info.image = None
+
         # define ThreadPoolExecutor to load images in parallel
         max_workers = min(os.cpu_count(), len(image_infos))
         max_workers = max(1, max_workers // num_processes)  # consider multi-gpu
@@ -1397,7 +1401,17 @@ class BaseDataset(torch.utils.data.Dataset):
                 )
 
     def get_image_size(self, image_path):
-        return imagesize.get(image_path)
+        # return imagesize.get(image_path)
+        image_size = imagesize.get(image_path)
+        if image_size[0] <= 0:
+            # imagesize doesn't work for some images, so use cv2
+            img = cv2.imread(image_path)
+            if img is not None:
+                image_size = (img.shape[1], img.shape[0])
+            else:
+                logger.warning(f"failed to get image size: {image_path}")
+                image_size = (0, 0)
+        return image_size
 
     def load_image_with_face_info(self, subset: BaseSubset, image_path: str, alpha_mask=False):
         img = load_image(image_path, alpha_mask)