Update app.py

app.py

@@ -144,11 +144,12 @@ def predict(images, resolution, weights_file):
     
         torch.cuda.empty_cache()
         
-        save_file_path = os.path.join(save_dir, "{}.png".format(os.path.splitext(os.path.basename(image_src))[0]))
-        cv2.imwrite(save_file_path)
-        save_paths.append(save_file_path)
+        if isinstance(images, list):
+            save_file_path = os.path.join(save_dir, "{}.png".format(os.path.splitext(os.path.basename(image_src))[0]))
+            cv2.imwrite(save_file_path)
+            save_paths.append(save_file_path)
 
-    if len(images) > 1:
+    if len(save_paths) > 1:
         zip_file_path = os.path.join(save_dir, "{}.zip".format(save_dir))
         with zipfile.ZipFile(zip_file_path, 'w') as zipf:
             for file in save_paths: