diff --git a/seg/utils/dataloaders.py b/seg/utils/dataloaders.py
index 1c11fdeedc..967e728165 100644
--- a/seg/utils/dataloaders.py
+++ b/seg/utils/dataloaders.py
@@ -485,7 +485,7 @@ def __init__(self,
         self.im_files = list(cache.keys())  # update
         self.label_files = img2label_paths(cache.keys())  # update
         n = len(shapes)  # number of images
-        bi = np.floor(np.arange(n) / batch_size).astype(np.int)  # batch index
+        bi = np.floor(np.arange(n) / batch_size).astype(int)  # batch index
         nb = bi[-1] + 1  # number of batches
         self.batch = bi  # batch index of image
         self.n = n
@@ -528,7 +528,7 @@ def __init__(self,
                 elif mini > 1:
                     shapes[i] = [1, 1 / mini]
 
-            self.batch_shapes = np.ceil(np.array(shapes) * img_size / stride + pad).astype(np.int) * stride
+            self.batch_shapes = np.ceil(np.array(shapes) * img_size / stride + pad).astype(int) * stride
 
         # Cache images into RAM/disk for faster training (WARNING: large datasets may exceed system resources)
         self.ims = [None] * n
diff --git a/seg/utils/segment/plots.py b/seg/utils/segment/plots.py
index eac46d9853..9b0ac6068f 100644
--- a/seg/utils/segment/plots.py
+++ b/seg/utils/segment/plots.py
@@ -137,7 +137,7 @@ def plot_images_and_masks(images, targets, masks, paths=None, fname='images.jpg'
                         if mh != h or mw != w:
                             mask = image_masks[j].astype(np.uint8)
                             mask = cv2.resize(mask, (w, h))
-                            mask = mask.astype(np.bool)
+                            mask = mask.astype(bool)
                         else:
                             mask = image_masks[j].astype(np.bool)
                         with contextlib.suppress(Exception):