fix error

Author: Jiaqi-Lv

tiatoolbox/models/architecture/grandqc.py

@@ -64,9 +64,10 @@ def preproc(image: np.ndarray) -> np.ndarray:
 
     @staticmethod
     def postproc(image: np.ndarray) -> np.ndarray:
-        """Define post-processing of this class of model.
+        """Define post-processing for this model.
 
-        This simply applies argmin along last axis of the input.
+        This returns the class index with the minimum probability.
+        In this model, this means selecting tissue class.
 
         """
         return image.argmin(axis=-1)
@@ -91,15 +92,6 @@ def infer_batch(
 
         This contains logic for forward operation as well as i/o
 
-        Args:
-            model (nn.Module):
-                PyTorch defined model.
-            batch_data (:class:`torch.Tensor`):
-                A batch of data generated by
-                `torch.utils.data.DataLoader`.
-            device (str):
-                Transfers model to the specified device. Default is "cpu".
-
         Args:
             model (nn.Module):
                 PyTorch defined model.

tiatoolbox/wsicore/wsireader.py

@@ -1572,11 +1572,7 @@ def tissue_mask(
             )
         elif method == "otsu":
             masker = tissuemask.OtsuTissueMasker(**masker_kwargs)
-        else:  # grandqc
-            masker = tissuemask.GrandQCMasker(**masker_kwargs)
-            # GrandQC model is trained on 10mpp images
-            thumbnail = self.slide_thumbnail(resolution=10, units="mpp")
-        mask_img = masker.fit_transform(np.array([thumbnail]))[0]
+        mask_img = masker.fit_transform([thumbnail])[0]
         return VirtualWSIReader(mask_img.astype(np.uint8), info=self.info, mode="bool")
 
     def save_tiles(