diff --git a/mmdeploy/apis/visualize.py b/mmdeploy/apis/visualize.py
index a201131c5c..a8524cc25d 100644
--- a/mmdeploy/apis/visualize.py
+++ b/mmdeploy/apis/visualize.py
@@ -71,27 +71,26 @@ def visualize_model(model_cfg: Union[str, mmengine.Config],
     with torch.no_grad():
         result = model.test_step(model_inputs)[0]
 
-    visualize = True
-    try:
-        # check headless
-        import tkinter
-        tkinter.Tk()
-    except Exception as e:
-        from mmdeploy.utils import get_root_logger
-        logger = get_root_logger()
-        logger.warning(
-            f'render and display result skipped for headless device, exception {e}'  # noqa: E501
-        )
-        visualize = False
+    if show_result:
+        try:
+            # check headless
+            import tkinter
+            tkinter.Tk()
+        except Exception as e:
+            from mmdeploy.utils import get_root_logger
+            logger = get_root_logger()
+            logger.warning(
+                f'render and display result skipped for headless device, exception {e}'  # noqa: E501
+            )
+            show_result = False
 
-    if visualize is True:
-        if not isinstance(img, list):
-            img = [img]
-        for single_img in img:
-            task_processor.visualize(
-                image=single_img,
-                model=model,
-                result=result,
-                output_file=output_file,
-                window_name=backend.value,
-                show_result=show_result)
+    if isinstance(img, str) or not isinstance(img, Sequence):
+        img = [img]
+    for single_img in img:
+        task_processor.visualize(
+            image=single_img,
+            model=model,
+            result=result,
+            output_file=output_file,
+            window_name=backend.value,
+            show_result=show_result)
diff --git a/mmdeploy/codebase/base/task.py b/mmdeploy/codebase/base/task.py
index 2e97b96933..df876a83d7 100644
--- a/mmdeploy/codebase/base/task.py
+++ b/mmdeploy/codebase/base/task.py
@@ -112,6 +112,7 @@ def build_pytorch_model(self,
         from mmengine.registry import MODELS
 
         model = deepcopy(self.model_cfg.model)
+        model.pop('pretrained', None)
         preprocess_cfg = deepcopy(self.model_cfg.get('preprocess_cfg', {}))
         preprocess_cfg.update(
             deepcopy(self.model_cfg.get('data_preprocessor', {})))