diff --git a/kraken/lib/dataset/recognition.py b/kraken/lib/dataset/recognition.py
index 5f8744724..5a13d2f00 100644
--- a/kraken/lib/dataset/recognition.py
+++ b/kraken/lib/dataset/recognition.py
@@ -15,21 +15,24 @@
 """
 Utility functions for data loading and training of VGSL networks.
 """
-import dataclasses
 import io
 import json
+import torch
+import numpy as np
+import pyarrow as pa
 import traceback
+import dataclasses
+import multiprocessing as mp
+
 from collections import Counter
 from functools import partial
 from typing import (TYPE_CHECKING, Any, Callable, List, Literal, Optional,
                     Tuple, Union)
 
-import numpy as np
-import pyarrow as pa
-import torch
 from PIL import Image
-from torch.utils.data import Dataset
+from ctypes import c_char
 from torchvision import transforms
+from torch.utils.data import Dataset
 
 from kraken.containers import BaselineLine, BBoxLine, Segmentation
 from kraken.lib import functional_im_transforms as F_t
@@ -331,7 +334,7 @@ def __init__(self,
         if augmentation:
             self.aug = DefaultAugmenter()
 
-        self.im_mode = '1'
+        self._im_mode = mp.Value(c_char, b'1')
 
     def add(self,
             line: Optional[BaselineLine] = None,
@@ -437,15 +440,16 @@ def __getitem__(self, index: int) -> Tuple[torch.Tensor, torch.Tensor]:
                                           legacy=self.legacy_polygons))
             im = self.transforms(im)
             if im.shape[0] == 3:
-                im_mode = 'RGB'
+                im_mode = b'R'
             elif im.shape[0] == 1:
-                im_mode = 'L'
+                im_mode = b'L'
             if is_bitonal(im):
-                im_mode = '1'
+                im_mode = b'1'
 
-            if im_mode > self.im_mode:
-                logger.info(f'Upgrading "im_mode" from {self.im_mode} to {im_mode}')
-                self.im_mode = im_mode
+            with self._im_mode.get_lock():
+                if im_mode > self._im_mode.value:
+                    logger.info(f'Upgrading "im_mode" from {self._im_mode.value} to {im_mode}')
+                    self._im_mode.value = im_mode
             if self.aug:
                 im = im.permute((1, 2, 0)).numpy()
                 o = self.aug(image=im)
@@ -461,6 +465,12 @@ def __getitem__(self, index: int) -> Tuple[torch.Tensor, torch.Tensor]:
     def __len__(self) -> int:
         return len(self._images)
 
+    @property
+    def im_mode(self):
+        return {b'1': '1',
+                b'L': 'L',
+                b'R': 'RGB'}[self._im_mode.value]
+
 
 class GroundTruthDataset(Dataset):
     """
@@ -520,7 +530,7 @@ def __init__(self,
         if augmentation:
             self.aug = DefaultAugmenter()
 
-        self.im_mode = '1'
+        self._im_mode = mp.Value(c_char, b'1')
 
     def add(self,
             line: Optional[BBoxLine] = None,
@@ -616,14 +626,15 @@ def __getitem__(self, index: int) -> Tuple[torch.Tensor, torch.Tensor]:
             im = im.crop((xmin, ymin, xmax, ymax))
             im = self.transforms(im)
             if im.shape[0] == 3:
-                im_mode = 'RGB'
+                im_mode = b'R'
             elif im.shape[0] == 1:
-                im_mode = 'L'
+                im_mode = b'L'
             if is_bitonal(im):
-                im_mode = '1'
-            if im_mode > self.im_mode:
-                logger.info(f'Upgrading "im_mode" from {self.im_mode} to {im_mode}')
-                self.im_mode = im_mode
+                im_mode = b'1'
+            with self._im_mode.get_lock():
+                if im_mode > self._im_mode.value:
+                    logger.info(f'Upgrading "im_mode" from {self._im_mode.value} to {im_mode}')
+                    self._im_mode.value = im_mode
             if self.aug:
                 im = im.permute((1, 2, 0)).numpy()
                 o = self.aug(image=im)
@@ -639,3 +650,11 @@ def __getitem__(self, index: int) -> Tuple[torch.Tensor, torch.Tensor]:
 
     def __len__(self) -> int:
         return len(self._images)
+
+    @property
+    def im_mode(self):
+        return {b'1': '1',
+                b'L': 'L',
+                b'R': 'RGB'}[self._im_mode.value]
+
+
diff --git a/kraken/lib/util.py b/kraken/lib/util.py
index 609e924fe..267b4545b 100644
--- a/kraken/lib/util.py
+++ b/kraken/lib/util.py
@@ -56,7 +56,7 @@ def is_bitonal(im: Union[Image.Image, torch.Tensor]) -> bool:
     if isinstance(im, Image.Image):
         return im.getcolors(2) is not None and len(im.getcolors(2)) == 2
     elif isinstance(im, torch.Tensor):
-        return len(im.int().unique()) == 2
+        return len(im.unique()) == 2
 
 
 def get_im_str(im: Image.Image) -> str: