diff --git a/src/anomalib/utils/visualization/image.py b/src/anomalib/utils/visualization/image.py
index 54ff976900..0ef0a29975 100644
--- a/src/anomalib/utils/visualization/image.py
+++ b/src/anomalib/utils/visualization/image.py
@@ -170,10 +170,7 @@ def _visualize_batch(self, batch: dict) -> Iterator[GeneratorResult]:
                 box_labels=batch["box_labels"][i].cpu().numpy() if "box_labels" in batch else None,
                 normalize=self.normalize,
             )
-            yield GeneratorResult(
-                image=self.visualize_image(image_result),
-                file_name=file_name,
-            )
+            yield GeneratorResult(image=self.visualize_image(image_result), file_name=file_name)
 
     def visualize_image(self, image_result: ImageResult) -> np.ndarray:
         """Generate the visualization for an image.
@@ -212,11 +209,8 @@ def _visualize_full(self, image_result: ImageResult) -> np.ndarray:
 
             image_grid.add_image(image_result.image, "Image")
             if image_result.gt_boxes is not None:
-                gt_image = draw_boxes(
-                    np.copy(image_result.image),
-                    image_result.gt_boxes,
-                    color=(255, 0, 0),
-                )
+                gt_image = draw_boxes(np.copy(image_result.image), image_result.gt_boxes, color=(255, 0, 0))
+                image_grid.add_image(image=gt_image, color_map="gray", title="Ground Truth")
                 image_grid.add_image(
                     image=gt_image,
                     color_map="gray",
@@ -224,16 +218,8 @@ def _visualize_full(self, image_result: ImageResult) -> np.ndarray:
                 )
             else:
                 image_grid.add_image(image_result.image, "Image")
-            pred_image = draw_boxes(
-                np.copy(image_result.image),
-                image_result.normal_boxes,
-                color=(0, 255, 0),
-            )
-            pred_image = draw_boxes(
-                pred_image,
-                image_result.anomalous_boxes,
-                color=(255, 0, 0),
-            )
+            pred_image = draw_boxes(np.copy(image_result.image), image_result.normal_boxes, color=(0, 255, 0))
+            pred_image = draw_boxes(pred_image, image_result.anomalous_boxes, color=(255, 0, 0))
             image_grid.add_image(pred_image, "Predictions")
         if self.task == TaskType.SEGMENTATION:
             if image_result.pred_mask is None:
@@ -248,11 +234,7 @@ def _visualize_full(self, image_result: ImageResult) -> np.ndarray:
                     title="Ground Truth",
                 )
             image_grid.add_image(image_result.heat_map, "Predicted Heat Map")
-            image_grid.add_image(
-                image=image_result.pred_mask,
-                color_map="gray",
-                title="Predicted Mask",
-            )
+            image_grid.add_image(image=image_result.gt_mask, color_map="gray", title="Ground Truth")
             image_grid.add_image(
                 image=image_result.segmentations,
                 title="Segmentation Result",
@@ -262,15 +244,9 @@ def _visualize_full(self, image_result: ImageResult) -> np.ndarray:
             if image_result.heat_map is not None:
                 image_grid.add_image(image_result.heat_map, "Predicted Heat Map")
             if image_result.pred_label:
-                image_classified = add_anomalous_label(
-                    image_result.image,
-                    image_result.pred_score,
-                )
+                image_classified = add_anomalous_label(image_result.image, image_result.pred_score)
             else:
-                image_classified = add_normal_label(
-                    image_result.image,
-                    1 - image_result.pred_score,
-                )
+                image_classified = add_normal_label(image_result.image, 1 - image_result.pred_score)
             image_grid.add_image(image=image_classified, title="Prediction")
         elif self.task == TaskType.EXPLANATION:
             image_classified = add_normal_label(
@@ -303,11 +279,7 @@ def _visualize_simple(self, image_result: ImageResult) -> np.ndarray:
                 color=(0, 0, 255),
             )
             if image_result.gt_boxes is not None:
-                image_with_boxes = draw_boxes(
-                    image=image_with_boxes,
-                    boxes=image_result.gt_boxes,
-                    color=(255, 0, 0),
-                )
+                image_with_boxes = draw_boxes(image=image_with_boxes, boxes=image_result.gt_boxes, color=(255, 0, 0))
             return image_with_boxes
         if self.task == TaskType.SEGMENTATION:
             visualization = mark_boundaries(
@@ -319,15 +291,9 @@ def _visualize_simple(self, image_result: ImageResult) -> np.ndarray:
             return (visualization * 255).astype(np.uint8)
         if self.task == TaskType.CLASSIFICATION:
             if image_result.pred_label:
-                image_classified = add_anomalous_label(
-                    image_result.image,
-                    image_result.pred_score,
-                )
+                image_classified = add_anomalous_label(image_result.image, image_result.pred_score)
             else:
-                image_classified = add_normal_label(
-                    image_result.image,
-                    1 - image_result.pred_score,
-                )
+                image_classified = add_normal_label(image_result.image, 1 - image_result.pred_score)
             return image_classified
         msg = f"Unknown task type: {self.task}"
         raise ValueError(msg)
@@ -345,12 +311,7 @@ def __init__(self) -> None:
         self.figure: matplotlib.figure.Figure | None = None
         self.axis: Axes | np.ndarray | None = None
 
-    def add_image(
-        self,
-        image: np.ndarray,
-        title: str | None = None,
-        color_map: str | None = None,
-    ) -> None:
+    def add_image(self, image: np.ndarray, title: str | None = None, color_map: str | None = None) -> None:
         """Add an image to the grid.
 
         Args:
@@ -358,11 +319,7 @@ def add_image(
           title (str): Image title shown on the plot.
           color_map (str | None): Name of matplotlib color map used to map scalar data to colours. Defaults to None.
         """
-        image_data = {
-            "image": image,
-            "title": title,
-            "color_map": color_map,
-        }
+        image_data = {"image": image, "title": title, "color_map": color_map}
         self.images.append(image_data)
 
     def generate(self) -> np.ndarray:
@@ -379,6 +336,7 @@ def generate(self) -> np.ndarray:
         matplotlib.use("Agg")
 
         self.figure, self.axis = plt.subplots(1, num_cols, figsize=figure_size)
+        self.figure.subplots_adjust(right=0.9)
 
         axes = self.axis if isinstance(self.axis, np.ndarray) else np.array([self.axis])
         for axis, image_dict in zip(axes, self.images, strict=True):