🛠 Fix visualization (#417)

* Fix scaling of gt_masks in ImageResult

Scaling of `gt_mask` checked `pred_mask` and thus never triggered

* Convert images from RGB to BGR only for `cv2` ops

Tensorboard and wandb expect images in RGB format, and therefore would
display "faulty" images otherwise

* Revert unintended change of default value in .show

anomalib/post_processing/visualizer.py

@@ -52,7 +52,7 @@ def __post_init__(self):
         if self.pred_mask is not None and np.max(self.pred_mask) <= 1.0:
             self.pred_mask *= 255
             self.segmentations = mark_boundaries(self.image, self.pred_mask, color=(1, 0, 0), mode="thick")
-        if self.gt_mask is not None and np.max(self.pred_mask) <= 1.0:
+        if self.gt_mask is not None and np.max(self.gt_mask) <= 1.0:
             self.gt_mask *= 255
 
 
@@ -154,13 +154,13 @@ def _visualize_simple(self, image_result):
             visualization = mark_boundaries(
                 image_result.heat_map, image_result.pred_mask, color=(1, 0, 0), mode="thick"
             )
-            return cv2.cvtColor((visualization * 255).astype(np.uint8), cv2.COLOR_RGB2BGR)
+            return (visualization * 255).astype(np.uint8)
         if self.task == "classification":
             if image_result.pred_label:
                 image_classified = add_anomalous_label(image_result.heat_map, image_result.pred_score)
             else:
                 image_classified = add_normal_label(image_result.heat_map, 1 - image_result.pred_score)
-            return cv2.cvtColor(image_classified, cv2.COLOR_RGB2BGR)
+            return image_classified
         raise ValueError(f"Unknown task type: {self.task}")
 
     @staticmethod
@@ -172,6 +172,7 @@ def show(title: str, image: np.ndarray, delay: int = 0):
             image (np.ndarray): Image that will be shown in the window.
             delay (int): Delay in milliseconds to wait for keystroke. 0 for infinite.
         """
+        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
         cv2.imshow(title, image)
         cv2.waitKey(delay)
         cv2.destroyAllWindows()
@@ -185,6 +186,7 @@ def save(file_path: Path, image: np.ndarray):
             image (np.ndarray): Image that will be saved to the file system.
         """
         file_path.parent.mkdir(parents=True, exist_ok=True)
+        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
         cv2.imwrite(str(file_path), image)
 
 
@@ -233,5 +235,4 @@ def generate(self) -> np.ndarray:
         # convert canvas to numpy array to prepare for visualization with opencv
         img = np.frombuffer(self.figure.canvas.tostring_rgb(), dtype=np.uint8)
         img = img.reshape(self.figure.canvas.get_width_height()[::-1] + (3,))
-        img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
         return img